Genetic Stock Structure of the Sailfish, Istiophorus Platypterus, Based on Nuclear and Mitochondrial DNA

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2002

Genetic stock structure of the sailfish, Istiophorus platypterus, based on nuclear and mitochondrial DNA

Jan Renee McDowell College of William and Mary - Virginia Institute of Marine Science

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Recommended Citation McDowell, Jan Renee, "Genetic stock structure of the sailfish, Istiophorus platypterus, based on nuclear and mitochondrial DNA" (2002). Dissertations, Theses, and Masters Projects. Paper 1539616769. https://dx.doi.org/doi:10.25773/v5-2wv9-6970

This Dissertation is brought to you for free and open access by the Theses, Dissertations, & Master Projects at W&M ScholarWorks. It has been accepted for inclusion in Dissertations, Theses, and Masters Projects by an authorized administrator of W&M ScholarWorks. For more information, please contact [email protected]. Reproduced with with permission permission of of the the copyright copyright owner.owner. Further Further reproduction reproduction prohibited prohibited without without permission. permission. GENETIC STOCK STRUCTURE OF THE SAILFISH. ISTIOPHORUS PLATY'PTERUS, BASED ON NUCLEAR AND MITOCHONDRIAL DNA.

A Dissertation

Presented to

The Faculty of the School of Marine Science

The College of William and Mary in Virginia

In Partial Fulfilment

Of the Requirements for the Degree of

Doctor of Philospophy

Jan Renee McDowell

2002

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. This dissertation is submitted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Jan Ri McDowell

Approved November, 2002

( a A (Job* E. Graves, Ph.D. Committee Chair/Advisor

ft t< Eugene M. Burreson, Ph.D.

Bruce B. Collette, Ph.D.

f j l . Emmett Duffy, Ph.D^> J7

David

/I ilian Pepperell, Ph.D.

KimberlydfS.t S. Reece, Pn.D

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. TABLE OF CONTENTS

Page

LIST OF TABLES...... iv

LIST OF FIGURES...... viii

ABSTRACT...... x

GENERAL INTRODUCTION...... 2

CHAPTER 1. REVIEW OF SAILFISH BIOLOGY...... 6

LITERATURE CITED...... 21

CHAPTER 2. MODERN AND HISTORICAL POPULATION STRUCTURE

OF THE SAILFISH, ISTIOPHRUSPLATYPTERUS, INFERRED

FROM ANALYSIS OF MITOCHONDRIAL DNA...... 33

INTRODUCTION...... 34

MATERIALS AND METHODS...... 41

RESULTS...... 47

DISCUSSION...... 58

LITERATURE CITED...... 68

APPENDIX 1...... 106

CHAPTER 3. GENETIC STOCK STRUCTURE OF THE SAILFISH,

ISTIOPHORUSPLATYPTERUS, BASED ON

MICROSATELLITE DNA MARKERS...... 149

INTRODUCTION...... 150

MATERIALS AND METHODS...... 154

RESULTS...... 157

iii

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. DISCUSSION...... 163

LITERATURE CITED...... 169

CHAPTER 4. NUCLEAR AND MITOCHONDRIAL DNA MARKERS

FOR SPECIFIC IDENTIFICATION OF ISTIOPHORID

AND XIPHIID BILLFISHES...... 195

INTRODUCTION...... 196

MATERIALS AND METHODS...... 199

RESULTS...... 202

DISCUSSION...... 205

LITERATURE CITED...... 209

VITA...... 231

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. LIST OF TABLES

Table Page

1. Distribution of composite haplotypes based on RFLP analysis of the

mitochondrial control region ...... 77

2. Haplotypic diversity (/z) and nucleotide diversity (^) within samples

of sailfish ...... 79

3. Analysis of geographic heterogeneity in frequency distributions

using a Monte Carlo Simulation with 10,000 replicates ...... 80

4. Probability of significance for exact tests using pairwise comparisons

based on mtDNA RFLP analysis ...... 81

5. Hierarchical analysis of molecular variance (AMOVA) of sailfish

mtDNA RFLP data...... 82

6. Frequency distribution of major clades identified by RFLP analysis ...... 83

7. Diversity of within and between major clades based on mtDNA

RFLP data...... 84

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 8. Nucleotide sequence diversity estimates based on sequencing of 1636

base pairs of sailfish mitochondrial DNA including the control region ...... 85

9. Divergence estimates based on DNA sequence analysis of 1636 base

pairs of sailfish mitochondrial DNA including the control region ...... 86

10. Average nucleotide usage for the six amplified mitochondrial regions ...... 87

11. Position in sequence, state in respective clade (A,G,C,or T),

type of change (Tr for transition. Tv for transversion), for the 19

fixed differences between Atlantic and ubiquitous clade sequences ...... 88

12. Diversity within and Divergence between Atlantic and Ubiquitous

sailfish clades and White (Atlantic) and Striped (Pacific) marlin based

on control region sequences ...... 89

13. Haplotype frequencies across all collections ...... 90

14. Descriptive statistics for microsatellite data ...... 175

15. Hardy Weinburg Equilibrium-test of association at the locus level using

the methods of Guo and Thompson (1993) ...... 176

16. Tests of Hardy-Weinburg equillibrium at the level of genotype ...... 178

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 17. Hierarchical analysis of molecular variance (AMOVA) of sailfish

microsatellite data based on sum of squared size difference (RST) ...... 179

18. Hierarchical analysis of molecular variance (AMOVA) of sailfish

microsatellite data based on number of alleles (FST) ...... 181

19. Locus by locus AMOVA of sailfish microsatellite data based on

number of different alleles (FST) ...... 183

20. Population pairwise FST and RST values calculated for the MN01

locus ...... 187

21. Population pairwise FST and RST values calculated for the MN08

locus ...... 188

22. Population pairwise FST and RST values calculated for the MN10

locus ...... 189

23. Population pairwise FST and RST values calculated over all loci ...... 190

24. Collection information for billfish samples surveyed ...... 213

vii

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 25. Primer pairs used to amplify regions evaluated in species id study 214

26. Restriction fragment patterns of the mitochondrial ND4 region of istiophorid and

xiphiid billfishes ...... 215

27. Restriction fragment patterns of the nuclear gene region BM32-2 of istiophorid

billfishes and their frequency of occurrences ...... 216

viii

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. LIST OF FIGURES

Figure Page

1. Geographic distribution of sailfish ...... 29

2. Map of known spawning activity for sailfish ...... 31

3. Distribution of haplotvpic diversity, nucleotide sequence diversity within

collections ...... 92

4. L'PGMA tree based on corrected nucleotide sequence divergence between

RFLP haplotvpes ...... 94

5. L'PGMA tree based on the control region sequence of 58 sailfish using a

Tamura-\ei distance ...... 96

6. Minimum spanning network and nesting scheme of Indo-Pacific data

based on RFLP haplotvpes ...... 98

7. Minimum Spanning Tree of the 54 haplotypes found in the RFLP analysis

of the mitochondrial D-loop region ...... 100

8. Nesting scheme for all RFLP haplotypes ...... 102

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 9. UPGMA tree based on corrected mean nucleotide sequence divergence

between sailfish collections calculated from RFLP data ...... 104

10. Allele frequency distributions for the three micorsatellite loci ...... 191

11. Allele frequency distributions for Atlantic, Eastern Pacific and Indo-west

Pacific sailfish using three microsatellite loci ...... 193

12. Most common restriction fragment patterns of the ND4 mitochondrial gene

region of istiophorid billfishes ...... 217

13. Key to distinguish species of billfishes based on the mitochondrial

locus ND4 ...... 221

14. Most common restriction fragment patterns of the nuclear gene region

BM32-2 of istiophorid billfishes ...... 223

15. Key to distinguish species of billfishes based on the single copy nuclear

locus BM32-2 ...... 227

16. Larval billfish and its corresponding specific identification as sailfish

based on the BM32-2 locus ...... 229

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ABSTRACT

The results of life history studies involving the sailfish, Istiophorus platyptenis. from

the Atlantic. Pacific, and Indian oceans were renewed. Results of studies agree on

several aspects of sailfish biology: sailfish exhibit opportunistic feeding behavior, follow

the 2S"C isotherm, spawn in summer mature at approximately age 3. and are the least

migratory of the billfishes. However, results are in conflict concerning sex ratio and

whether sailfish are single or multiple spawners. Although many researchers have

reported that sailfish are sexually dimorphic, their fragile otoliths make them difficult to

age. aging studies have not been validated, and sexual dimorphism has not been

adequately separated from differences in age at first maturity. Life history studies are

further compromised because identification of early life history stages is difficult and

effect of genetically distinct stocks on these studies is unknown.

Molecular markers representing a range of genetic resolution were used to

investigate the genetic stock structure of the sailfish both within and between oceans and

to discriminate sailfish from other istiophorid billfishes. To investigate the genetic basis

of stock structure, a 1700 bp region of mitochondrial DNA which included the control

region, was surveyed with five restriction endonucleases and representative individuals

were sequenced. In addition, five nuclear microsatellite loci were assayed.

Approximately 647 sailfish were collected from throughout the species’ range over a six-

year period from the Atlantic, Pacific, and Indian Oceans. Both mitochondrial and

nuclear markers found that Atlantic, eastern Pacific, and Indo-west Pacific sailfish

represent distinct genetic stocks. In addition, mitochondrial data revealed the presence of

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. div erse clades, which were probably formed during Pleistocene glaciation.

Independent molecular markers based on mitochondrial and nuclear DNA were

developed to provide positive identification of istiophorid and xiphiid billfishes. Both

classes of markers are based on amplification of short segments (< 1.7 kb) of DNA and

subsequent digestion with informative restriction endonucleases. ND4 and MN32-2. the

selected markers, allow unambiguous specific identification, although it was not possible

to differentiate white marlin and striped marlin. The resulting keys provide two

independent means for the forensic identification of fillets and for specific identification

of early life history stages.

xii

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. GENETIC STOCK STRUCTURE OF THE SAILFISH. ISTIOPHORUS PLAT)'PTERi'S. BASED ON NUCLEAR AND MITOCHONDRIAL DNA

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. INTRODUCTION

Sailfish. Istiophonisplatxpterus (Shaw. 1792). are globally distributed throughout

the world’s tropical and subtropical marine waters and support significant directed

recreational and artisanal fisheries across their range. In addition, sailfish constitute a

significant portion of the incidental catch of longline fleets targeting swordfish and tunas.

Despite their economic importance, few resources have been directed at understanding

the sail fish's life history and consequently, relatively little is know about the biology of

the sailfish. This understanding is further limited because they are highly migratory and

therefore the sailfish resource is managed by four separate organizations (The Inter-

American Tropical Tuna Commission. IATTC: The International Commission for the

Conservation of Atlantic Tunas. ICCAT; Secretariat of the Pacific Communities Ocean

Fisheries Programme, SPC OFP: and the Indian Ocean Tuna Commission; IOTC)

comprised of at least 81 member nations responsible for the conservation of tunas and

tuna-like species in a particular area.

One problem associated with the study of sailfish has been the inability to reliably

discriminate the larvae of istiophorid billfishes based on morphological characters. Until

recently, larval sailfish have not been routinely captured and they are not easily

discriminated from other billfish species. Larvae cannot be successfully reared to allow

evaluation of morphological characters. This has meant that the timing and location of

spawning and other early life history parameters of sailfish are difficult to assess

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accurately. In addition, aging has been difficult due to the sailfish's small fragile otolith

and tagging studies have return rates among the lowest for any species of marine fish,

limiting the inferences that can be drawn from these results. Thus, sailfish remain an

enigma.

This lack of understanding of sailfish biology extends to the specific status of the

sailfish. While some researchers (Morrow and Harbo. 1969) consider the sailfish to be a

single circumtropical species, others recognize separate species of Atlantic sailfish

(Istiophoms albicans: Latrielle. 1804) and Indo-Pacific sailfish (/. planptem s)

(Nakamura. 1985). This division is based on the Atlantic sailfish having relatively longer

pectoral and caudal fins when the fish are less than 90 cm in length, a distinction that

disappears as the fish surpass 90 cm (Beardsley et al.. 1972).

Recently, molecular genetic techniques have been successfully applied to the

question of the specific status of sailfish. A comparison of mitochondrial DNA (mtDNA)

restriction fragment length polymorphism (RFLP) patterns between sailfish taken from

the Atlantic and Indo-Pacific indicate that, although there is significant inter-ocean

divergence, separate taxonomic status is not warranted (Graves and McDowell. 1995).

This conclusion is based on the fact that no restriction sites were found to discriminate

between Atlantic and Indo-Pacific samples, and in many cases, haplotypes that were

unique to a particular ocean were closely related to haplotypes common to samples from

both oceans.

Little is known about the within-ocean stock structure of the sailfish or about the

relationship of sailfish between the three oceans. Researchers have postulated the

presence of distinct stocks in the Pacific based on dissimilarities in catch rates and

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spawning locations (Shomura. 1980; Skillman, 1989) and Williams (1970) concluded that

Indian Ocean sailfish were closely related to those in the western Pacific based on

maximum size. However these theories have never been tested.

This dissertation provides a summary of the available biological information on

sailfish and an analysis of the stock structure of sailfish both within and between oceans

based on mitochondrial and nuclear DNA markers. In addition, it provides two

independent molecular keys for the forensic identification of fillets and for the specific

identification of early life history’ stages.

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LITERATURE CITED

Beardsley. G.L. Jr.. N.R. Merrett, and W.J. Richards. 1972. Synopsis of the biology of

the sailfish. Istiophonis platy-ptcms (Shaw and Nodder, 1971 . Proceedings of the

International Billfish Symposium. Richard S. Shomura and Francis Williams

(ed). pp 95-120 NOAA Technical Report NMFS SSRF-675.

Graves. J.E. and J.R. McDowell. 1995. Inter-ocean genetic divergence of Istiophorid

billfishes. Mar. Biol. 122:193-203.

Morrow. J.E.. and S.J. Harbo S.J. 1969. A revision of the sailfish genus Istiophonis.

Copeia. 1969: 34-44.

Nakamura. I.. 1985 FAO Species Catalogue: Billfishes of the world: An annotated and

illustrated catalogue of marlins, sailfishes. spearfishes, and swordfishes known to

date. FAO Fish. Synop. no. 125, vol. 5, 65pp.

Shomura, R.S.(ed.) 1980. Summary report of the billfish stock assessment workshop.

Pacific resources, Honolulu Laboratory, Southwest Fisheries Center, Honolulu

Hawaii, 5-14 December, 1977. NOAA Tech. Memo. SWFC-5 58 p.

Skillman, R.A., 1989. Status of Pacific Billfish Stocks. Proceedings of the Second

Annual Billfish Symposium. Richard H. Stroud (ed). Pp 179-195.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 1. REVIEW OF SAILFISH BIOLOGY

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INTRODUCTION

Sailfish, Istiophorus platypterus, a member of the family Istiophoridae, are large

charismatic fish capable of swimming at speeds up to 68 mph (Johnson et al.. 1994). The

record size for an Atlantic sailfish is 141 lb. while the record for an Indo-Pacific sailfish

is 221 lb (IGFA, 2001). Sailfish are globally distributed in tropical and sub-tropical

marine waters ranging from 40°N to 40°S in the western Atlantic Ocean and from 50°N to

32°S in the eastern Atlantic (Nakamura, 1985; Figure 1). In the Pacific Ocean, sailfish

range from 50°N to 40°S in the west and from 35°N to 35°S in the east, and in the Indian

Ocean they range to 45°S in the west and 35°S in the east. Sailfish are considered to be

the most coastal and least migratory of all the billfish species based on tag return data;

but while sailfish are most abundant close to continental coasts, islands, and reefs, they

are also found in open ocean waters (Nakamura, 1985; Uozumi, 1997). A number of

researchers (Ovichinnikov, 1966; Williams, 1970; Mather et al.. 1974; Bayley and Prince,

1994; Vidairri-Sotelo et al., 1998) have noted that movements of sailfish coincide with

the 28°C isotherm, and although sailfish are year-round residents over most of their

range, these latitudinal shifts cause marked seasonal variations in abundance. It has also

been noted that, in general, sailfish have a wider range and are more abundant on the

western sides o f oceans (Beardsley et al., 1972).

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Sailfish are known to form feeding aggregations and are largely piscivorous,

although they are also reported to eat squid and crustaceans. Studies of stomach contents

from Atlantic sailfish taken off Brazil indicate a preference for spiny boxfish

(Chilomycterus sp.), flying fish ( Exocoetus sp.), blue runner ( Caranx sp.). sardine

(Sardinella sp.) and conger (Gcnyptcnis sp.) (Pimenta et al.. 2001). In the Pacific,

Nakamura (1985) found that sailfish taken in the eastern North Pacific primarily

contained fishes and squids. Examination of 118 stomachs from Indian Ocean sailfish off

Natal (Van der Elst. 1990) found cuttlefish (Sepia) (24%). squid (Loligo sp.). octopus

(Argonauta sp.). needlefish (Strongylura sp.). sardines (Sardinops and Etcnimens sp.).

scad (Decaptents sp). and smaller sailfish. along with a variety of other teleost fishes. In

general, the diet of sailfish has been found to be broader than that of other billfish studied

and they are categorized as opportunistic feeders (Nakamura. 1985). The differences in

composition of the sailfish's diet reflected in these regional studies underscore their

opportunistic feeding behavior.

The timing of spawning and age at first maturity of sailfish have been investigated

throughout their range; however, the majority of studies have focused on western Atlantic

samples. Beardsley (1975). concluded that female sailfish in the western Atlantic reach

sexual maturity at roughly 158 cm, or 13.6 kg. These conclusions were supported by a

recent study by de Sylva and Breder (1997) which analyzed gonads from 266 sailfish in

the western North Atlantic, including 131 adult females which found that size at first

maturity for female sailfish is 13-18kg. Males in this study were found to reach maturity

by 10 kg (122 cm) and at a slightly earlier age than females; however, size at first

maturity was consistent with both males and females being approximately age 3.

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Reproduction in the western Atlantic is known to occur off Florida in the Florida

Straits from April-October (Jolley. 1972; deSylva and Breder. 1997; Fig. 2) and ripe

(stage 4) ovaries are present from mid-July to mid-October. Based on the incidence of

post-ovulatory follicles and/or the presence of large residual ova. it has been surmised

that sailfish are either multiple or fractional spawners. spawning up to 4 times during the

season (deSylva and Breder. 1997). Post et al. (1997) found that sailfish larvae were

present from Mav-October off Miami, peaking during May and July. Although sailfish

are considered to be coastal spawners. larvae assumed to be sailfish were found off the

Straits of Florida at least 30 km from land.

In Venezuelan waters, sailfish reproduce from February to May and again from

August to November (Garcia de los Salmones et al.. 1989) but are most abundant from

March-April and June-November (Fig 2). A comparison of 922 sailfish from the

Venezuelan artisanal fishery showed that animals captured between September and

October are significantly smaller than those captured from November through June,

suggesting that recruitment occurs during September and October (Alio et al. 1994).

Western South Atlantic females with ripe ovaries are found off the coast of Brazil

from November-February (Fig. 2). which corresponds with the southern summer.

Sailfish have been found to migrate south to southeast of Brazil to spawn between

latitudes 20° and 27° S and longitudes 39° and 48° W. where they appear from October-

March (Hazin et al., 1994). Arfelli and Amorin (1981) concluded that the difference in

the timing of spawning between North and South Atlantic sailfish was indicative of

separate northern and southern stocks. However, the timing of spawning may simply

coincide with northern and southern summers and sailfish in this area may be a single

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stock.

In the eastern North Atlantic. Limouzy and Cavyre (1981) noted the presence of

ripe sailfish in Senegalese waters in July through the end of their study in August, and

Diouf (! 994) noted the presence of ripe adults in Senegalese waters from July to

September. Although male and female sailfish in spawning condition have been found

off Senegal, no juveniles have been reported (Limouzv-Paris and McGowan. 1994)

Pacific sailfish spawn throughout the year in warm tropical waters (Nakamura.

19S5) and as with western Atlantic sailfish. western Pacific fish have spawning seasons at

opposite times of the year in the northern and southern hemispheres (Uevanagi. 1959). In

the western North Pacific, sailfish are closely associated with the Kuroshio Current where

they are known to spawn throughout the year with peaks occurring during the summer

months (Uevanagi. 1959). In the western South Pacific Ocean, larvae are present from

January-March (late summer, early autumn) in the Coral Sea between Lizard Island and

the Great Barrier Reef (Leis et al.. 1997; Fig. 2).

In the eastern Pacific, sailfish larvae and juveniles have been captured from

September-April (Howard and Ueyanagi. 1965) and in the Pacific off Mexico, sailfish are

known to reproduce at least from the Gulf of California to the Gulf of Tehuantepec

(Vidairri-Sotelo et al., 1998). Kume and Joseph (1969) found sailfish from Costa Rican

waters in spawning condition from February-March. and larval collections by Eldridge

and Wares (1972) suggest that sailfish spawn off Costa Rica from December-March

(Fig.2). Based on these collections, they also surmised that sailfish spawn off Guatemala

from January-April and off Mexico from April-November, indicating a general

northward migration of spawning activity (Fig 2). This northward progression in

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spawning activity was found to correspond with the movement of the 28°C isotherm

along the coast of the Mexico. Examination of 821 sailfish taken in sport fisheries off

Mazatlan and Buena Vista, Mexico showed no indication of multiple spawning in the

eastern Pacific Ocean: mature ova in the lumen were never observed coincidentally with

developing ova in the follicles. Developing gonads suggest that first maturity for sailfish

in the eastern Pacific occurs at sizes between 160-165 cm eye-fork length (Eldridge and

Wares. 1972). Studies in both the Atlantic and Pacific oceans indicate that sailfish larvae

concentrate in surface waters during daylight and are dispersed through the upper 50

meters during the night (Uvenagi. 1964: Post 1977).

As in other areas examined, western Indian Ocean sailfish have spawning seasons

at opposite times of the year in opposite hemispheres (Williams, 1970: Merrett, 1971). In

the northwest Indian Ocean, sailfish were found to spawn off Kenyan coastal waters from

December-February with an increase in abundance coinciding with the seasonal

development of the Somali current when water temperatures reach a maximum of 29-

30(’C (Williams. 1970: Fig. 2). In the southwest Indian Ocean, sailfish are present

throughout the year off Natal (South Africa) but they most are most abundant from

November-February which corresponds to the southern summer (van der Elst, 1990).

Surprisingly, a 1990 study of 333 sailfish off Natal found no evidence of spawning, and it

was therefore suggested that sailfish come to this area for the localized and periodic

abundance of food. However, despite the lack of sailfish in spawning condition, juvenile

sailfish less than 15 cm are present in the area and are commonly found in the stomachs

of other gamefishes such as dolphin fish, Coryphaena hippurus, and yellowfin tuna,

Thunnus albacares, (van der Elst, 1990). Examination of 501 sailfish off the coast of

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India in the eastern Indian Ocean found that individuals were in spawning condition from

March-September with peaks of occurrence in March-April and again in August-

September (Somvanshi and Varghese 2001; Fig. 2),

Although some istiophorid billfish species such as the blue marlin. Makaira

nigricans, and the black marlin. Makaira indica. exhibit obvious sexual size dimorphism,

the presence of sexual dimorphism in sailfish is unresolved. Likewise, the results of

studies examining the sex ratio of sailfish differ depending on where and when the study

took place. In the western North Atlantic, female sailfish are found to be consistently

larger than males and females are more prevalent than males in winter; 65% of the

sailfish examined from December-May wrere female (1:1.8) (Jolley Jr.. 1972). Females

were also found to be larger than males taken off Cozumel (Martinez and Gonzalas,

1994). Lenarz and Nakamura (1972) found no significant differences in the length-

weight relationship for male:female sailfish from the western Atlantic; however, their

sample size consisted of only 6 fish.

In the eastern North Atlantic off Senegal, female sailfish wrere found to be slightly

larger and heavier than males and weight increased faster with increasing length for

females (Limouzy-Paris and McGowan, 1994). These differences were found to be

statistically significant. In addition, length-weight regressions had steeper slopes for

females than for males, another indication of sexual dimorphism (Limouzy-Paris and

McGowan, 1994). However, unlike the western Atlantic, males were found to be more

abundant than females in the two years of this study; the male: female sex ratios were

1.26:1 in 1980 and 1.37:1 in 1982 (Limouzy-Paris and McGouran, 1994). Conversely,

Mensah (1994) found an overall sex ratio of 1:1.01 male/female for 1616 sailfish taken in

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the artisanal fishery off Ghana from 1989-1991, but noted significant variation in the sex

ratios from month to month.

In the Indian Ocean, no sexual dimorphism was found in the length-weight

relationship of 120 sailfish taken off Kenya. However, it was noted that the fish were

generally larger than those off Florida (Merrett, 1968). and Van der Elst (1990) found

that sailfish taken off the Natal coast of South Africa tend to be larger on average than

those caught off' Kenya and Mozambique. In addition. Van der Elst (1990) found a

skewed sex ratio in 333 sailfish taken throughout the year: females were consistently

much more prevalent than males (1:4.3 males: females). Although there were no

statistically significant size differences noted between the sexes, males were found to be

slightly larger than females (226.9 cm vs. 224.9 cm). This is in contrast to studies in

other areas, which suggest that either females tend to be slightly larger or there is no size

difference.

Studies in the eastern Pacific off Mazatlan, Mexico found that the sex ratio

remained close to 50%. but more females were present until early June after which the

ratio tended toward males (Eldridge and Wares. 1972). It is clear that the results of sex

ratio and sexual dimorphism studies are heavily dependent on the size of fish caught and

the timing of sampling. In addition, the possibility of sampling bias caused by

differences in gear type used in the different studies has not been examined. Sexual

dimorphism, if it exists, is much subtler in sailfish than in the black and blue marlin and

needs to be separated from the effects of differences in age at first maturity.

Unfortunately, it is difficult to separate these factors because the sailfish's fragile otoliths

make them notoriously difficult to age accurately (Radtke and Sheperd, 1991).

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Relatively little is known about the basic life history of sailfish. Tagging

programs in operation around the world have provided information about sailfish

movements and stock structure. In the Atlantic, participants in the Cooperative Gamefish

Tagging Program (CGFTP) and The Billfish Foundation (TBF) have tagged more sailfish

than any other istiophorid species, with a total of 102.690 sailfish tagged and released to

date, mostly in the western Atlantic (Ortiz et al., unpublished data). Thus far there have

been no documented trans-Atlantic or trans-equatorial movements, suggesting a lack of

mixing between eastern and western Atlantic sailfish. However, the tag recovery rate for

sailfish is 1.7% which is extremely low relative to other recreational species (Prince et

al., 2001). and while the vast majority of Atlantic sailfish are recaptured in the vicinity of

their release, there have been several movements in excess of 1,000 nautical miles. The

longest movement reported for an Atlantic sailfish was 1895 nautical miles, from North

Carolina to Guyana (Scott et. al., 1990), demonstrating that sailfish are capable of

undertaking extensive movements. The longest time at liberty for a sailfish in this

program was 6568 days (17.99 years) indicating that sailfish are relatively long lived.

Tagging effort in the Pacific has been less intense than in the Atlantic; 4,821

sailfish were tagged and released in the years 1954-1971 by the Cooperative Marine

Gamefish Tagging Program with a return rate of 0.24%, which translates into recovery of

10 fish (Squire, 1974). The National Marine Fisheries Service's Southwest Fisheries

Science Center has tagged a total of 7749 sailfish between 1963-2000 and 45 have been

recovered (0.58%). As in the Atlantic, most were recaptured close to the site of their

release. The longest movement reported for a Pacific sailfish was 250 nautical miles

from Mazatlan to the northwest tip of Baja California after 457 days at liberty (Squire

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 15

1974). In Australia, the Fisheries Institute of New South Wales has tagged 16,370

sailfish, mostly off Queensland waters (Ortiz et al, in prep). Thus far, 182 sailfish have

been recaptured (1.11%) and as in other tagging programs, few have moved from the site

of release. As of 1990, the longest time at liberty for a tagged sailfish in the Australian

program was 1717 days (4.7 yrs) (Williams 1990), and until recently there was little

evidence for movement between northern and southern fishing grounds (Julian Pepperell,

pers. com.).

Tag return data for Pacific and Indian Ocean sailfish have been insufficient to

infer migration patterns (Squire, 1974). No trans-equatorial or trans-oceanic movements

have been documented in the Pacific. There are, however, three records of trans-

equatorial movement in the Indian Ocean, all from fish moving from south of the equator,

off the coast of Kenya to Northeast Africa, off Somalia (M. Ortiz pers. comm). Overall,

tagging has provided sparse but suggestive insights into the movements of sailfish

throughout the world’s oceans. The 2002 summary by Ortiz et al.(in press), calculated

that the modal time at large for recaptured and reported sailfish in all tagging programs

was 0.5 years. However, they noted that there were several hundred records of sailfish

remaining at large for 1-4 years suggesting the possibility that sailfish either make

circular annual movements, exhibit some degree of site fidelity, or that they manifest a

combination of both behaviors. This cycle of circular annual movement is consistent

with the observation that sailfish tend to follow the 28°C isotherm. In addition, tagging

studies support the hypothesis that sailfish are the least migratory of the billfish species

studied.

Sailfish are an incidental catch of pelagic longline fisheries and are a target

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species of artisanal fisheries throughout the world. In addition, many countries have

economically lucrative recreational fisheries that target sailfish. However, their highly

migratory nature, worldwide distribution, and the lack of information about stock

structure, has made management difficult. Traditionally, sailfish have been managed by

a number of organizations. In the Atlantic Ocean and adjacent seas, sailfish fall under the

purview of the International Commission for the Conservation of Atlantic Tunas

(ICCAT), whose members are responsible for the conservation of tunas and tuna-like

species. Currently ICCAT has 31 member nations. In the eastern Pacific, the Inter-

American Tuna Commission (IATTC) manages sailfish. IATTC has 12 member nations

and is responsible for the area bounded by the coastline of North, Central, and South

America, and 40(>N. 150°W, and 40°S. The Secretariat of the Pacific Community (SPC)

Oceanic Fisheries Programme (OFP), formerly known as the Tuna and Billfish

Assessment Programme (TBAP), is responsible for the sailfish resource in the western

and central Pacific, defined as the area west of 150° W and includes 26 member nations.

Finally, the Indian Ocean Tuna Commission (IOTC). which includes 18 member nations,

is responsible for the management of sailfish in the Indian Ocean.

In the Atlantic, the sailfish resource is utilized in a variety ways. In the western

Atlantic the majority of sailfish are taken as an incidental catch in longline fisheries

targeting tuna and swordfish, but there are also important recreational and artisanal

components of the fishery (ICCAT, 2001). In the eastern Atlantic the artisanal fisheries

of West Africa land the majority of sailfish, but the recreational fishery is also significant.

Currently ICCAT manages sailfish as separate eastern and western stocks with an

arbitrary line drawn at 30° W between the two management units. This model is based on

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 17

both morphological differences and tag and recapture data. Specifically, eastern Atlantic

sailfish tend to be larger than western Atlantic sailfish, and spots occurring on the inter-

radial area of the dorsal fin of sailfish from Brazil, west Africa and the Indian Ocean are

absent on western north Atlantic sailfish (ICAAT, 1994). In addition no trans-Atlantic

tag return has been reported to date, however there is no compelling evidence to support a

discontinuity at 30° W.

Although seasonal and spatial distribution data are commonly used to infer stock

structure in other species, commercial pelagic longline catch data has been of limited use

in the definition of Atlantic sailfish stocks. This is because sailfish and spearfish have

historically been reported together in ICCAT landing statistics with the assumption that

fish caught within a few hundred miles of shore are sailfish, and those taken pelagically

are spearfish. This has made it impossible to estimate the distribution of sailfish across

the Atlantic. However, beginning in 1994, Japan began reporting catches of these two

species separately. Although the Japanese effort during these years was predominantly

concentrated in the eastern Atlantic, preliminary analysis based on the 1994-1996

Japanese database show's that while the catch rate of sailfish was higher in coastal waters,

sailfish comprised 10-25% of the total spearfish-sailfish catch across the 30°W line

(Uozumi, 1997). These results may challenge the validity of the two-stock hypothesis in

the Atlantic as well as change estimates of the stocks' status.

The last stock assessments for Atlantic sailfish were performed in 1992 for the

western Atlantic and in 1995 for the eastern Atlantic. While the western Atlantic catch

has remained fairly steady for the past two decades, there has recently been an increasing

trend in the catch from the eastern Atlantic. Estimates of sailfish abundance in the

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western Atlantic indicate that the biomass is currently 62% of the biomass needed to

produce maximum sustainable yield (MSY) and sailfish are therefore considered an

overexploited resource (ICAAT. 1995). A more recent assessment of western Atlantic

sailfish was attempted in 2001 utilizing the new' sailfish only catch statistics.

Unfortunately, none of the assessment models fit the data, and no formal assessment was

made. However, it was suggested that western Atlantic stocks of sailfish are stable

because annual catches have remained steady (about 700 metric tons) over the past two

decades, as has catch per unit effort (CPUE). In the eastern Atlantic, abundance indices

and estimates of catches from coastal fisheries suggest that the eastern stock may be in

decline (ICCAT. 2001b).

In the Pacific Ocean, as in the western Atlantic, longline and purse seine fisheries

targeting tuna take the majority of sailfish. although recreational and artisanal fisheries

are also important (Ueyanagi et al.. 1989). The longline fishery, which is composed

primarily of boats from Japan. Taiwan and Korea, extends throughout the tropical and

subtropical waters of the Pacific, effectively covering the sailfish's entire range.

Unfortunately, as in the Atlantic, catches of eastern Pacific sailfish have historically been

grouped w'ith spearfish, making stock assessment difficult. However, sailfish are

considered an under-exploited resource in this area and are estimated to be at pre-

exploitation levels inside the Mexican exclusive economic zone (Macias-Zamora et al..

1994).

Stock assessment of sailfish in the western Pacific is problematic for several

reasons. Sailfish are generally not reported on logbooks with the exception of Japanese

distant water and New Caledonian fleets (Williams et al., 2000). Even w'hen sailfish are

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reported, as in Japan, they have historically been combined with spearfish catch, although

Japan began separating the two species in 1995 (Williams et al.. 1999). Also, discard

rates are unpredictable and not recorded in logbooks (Bailey, 1996). It has been noted in

observer data that sailfish discard rates tend to be high, presumably due their low

commercial value (Sharpies et al., 2000). In addition, sailfish tend to have the highest

hooking mortalities of the istiophorid billfish species based on observer data which shows

a 73% mortality upon haulback in the western South Pacific and a 64% mortality in the

western tropical Pacific based on longline observer data (Sharpies et al., 2000). For a

valid assessment of billfish stocks in the western Pacific, these data must first be

standardized (Uozumi, 1999).

Production models using sailfish-shortbill spearfish data from the entire Pacific

estimate that the biomass of the combined species stocks is at or near the biomass needed

for maximum sustainable yield (B m sy)- However, analyses which attempt to estimate the

proportion of sailfish in the catch, suggest that sailfish stocks are over-exploited since

over-harv esting of spearfish is improbable due to their relative scarcity (Skillman, 1989).

Production models based on the entire Pacific may not be accurate since Pacific sailfish

are thought to comprise eastern and western stocks based on their abundance along the

American and Asian rims and the distribution of spawning sites (Shomura. 1980).

Skillman (1989) suggested that the western Pacific may be further divided into northern

and southern stocks based on dissimilar trends in catch rates, assuming that catch rates

are reflective of abundance. In addition, Whitlaw (2001) has suggested that there may be

resident populations around many central and western Pacific Islands since there is little

seasonal variation in catch rates. This lack of seasonality is probably due to the fact that

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water temperatures remain fairly constant all year. There are currently no assessments

available for the putative western and central Pacific stocks (Whitlaw, 2001). The

unknown stock structure of sailfish adds another level of uncertainty to abundance

estimates and further complicates management of the fishery.

In the Indian Ocean, sailfish are an incidental catch of almost all fisheries and

efforts to estimate stock status have not been possible because sailfish have historically

been reported as an aggregate under the category "billfishes" by many nations. In

addition, even when sailfish are reported separately, they are often discarded and are

therefore not recorded in longline logbooks. However, it is clear that there has been an

increasing trend in the catch of sailfish since the 1980s. even allowing for statistical

uncertainty due to the catch reported as "billfishes" (IOTC 2000). There has been no

effort to delineate the stock structure of Indian Ocean sailfish but some researchers

(Williams, 1970; Merrett, 1971) have suggested that Indian Ocean sailfish are closely

related to western Pacific sailfish.

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LITERATURE CITED

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the artisanal fishery of billfish in the central coast of Venezuela. Report of the

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the sailfish, Istiophonis platyptems (Shaw and Nodder, 1792). Proceedings of

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(ed). pp 95-120 NOAA Tech. Rep. NMFS SSRF-675.

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U.S. recreational fishery for billfishes (Istiophoridae) in the western North

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Garcia de los Salmones. R., O. Infante, and J.J. Alio. 1989. Reproduction and feeding of

Istiophonis albicans, Tetraptums albidus and Makaira nigricans, on the central

coast of Venezuela. ICCAT. Coll. Vol. Sci. Pap. 30: 436-439.

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leased longliners (1971-91). ICCAT. Coll. Vol. Sci. Pap. 41: 199-207.

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(Istiophoridae) of the Pacific Ocean. Univ. Miami. Inst. Mar. Sci. Stud. Trop.

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1 to 7,2001.

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Ocean Tuna Commission working party on billfish. Victoria, Seychelles October

2-3, 2000.

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Encyclopedia of Fishes. Sydney: New South Wales University Press; San

Diego:Academic Press [1995]. Pp. 240.

Jolley, J.W. Jr. 1972. On the biology of the Florida east coast Atlantic sailfish

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NMFS SSRF-675.

Kume, S., and J. Joseph. 1969. Size composition and sexual maturity of billfish caught

by the Japanese longline fishery in the Pacific Ocean east of 130° W. Bull. Far

Seas Fish. Res. Lab. 2:115-162.

Lenarz, W„ and E.L. Nakamura. 1972. Analysis of length and weight data on three

species of billfish from the western Atlantic Ocean. Proceedings of the

International Billfish Symposium. Richard S. Shomura and Francis Williams

(ed). Pp. 121-125 NOAA Tech. Rep. NMFS SSRF-675.

Leis, J.M., B. Goldman, and S.Ueyanagi. 1987. Distribution and abundance of billfish

larvae (Pisces: Istiophoridae) in the Great Barrier Reef Lagoon and Coral Sea near

Lizard Island, Australia. Fish. Bull. 85: 757-765.

Limouzy-Paris, C., and M.F. McGowan. 1994. Sailfish lengths, weights and sex data

from the Senegalese sport fishery in 1980 and 1982. ICCAT Coll.Vol. Sci. Pap.

41:354-362.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Macias-Zamora, R., A.L.Viduarri-Sotelo, and H. Santana-Hemandez. 1994. Analysis

of the tendency of catch per unit effort in the Mexican Pacific sailfish fishery.

Ciencias Marina 20:393-408.

Martinez, M.A. and M.E. Gonzales. 1994. A review of the recreational fishery for the

Atlantic sailfish Istiophonis albicans in Cozumel Island, Quintana Roo. Mexico.

ICCAT Coll. Vol. Sci. Pap. 41:199-207.

Mather. F.J., D.C. Tabb, J.M. Mason. J.R. Clark, and H.L. Clark. 1974. Results of sailfish

tagging in the western North Atlantic Ocean. In R.S. Shomura and F. Williams

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Hawaii, 9-12 August 1972 ppl94-210 NOAA Tech Rep. NMFS SSRF-675.

Matsumoto, W.M., and T.S. Kazama. 1972. Occurrence of young billfishes in the central

Pacific Ocean. Proceedings of the International Billfish Symposium. Richard S.

Shomura and Francis Williams (ed). Pp. 238-245 NOAA Tech. Rep. NMFS

SSRF-675.

Morrow, J.E., and S.J. Harbo S.J. 1969. A revision of the sailfish genus Istiophonis.

Copeia: 34-44.

Mensah, M.A. 1994. The catch statistics of the billfish fishery in Ghana. ICCAT Coll.

Vol. Sci. Pap. 41:287-305.

Merrett, N.R. 1968. Weight-length relationships for certain scombrid fishes from the

equatorial western Indian Ocean. East. Aff. Agric. For. J. 34:165-169.

Merrett, N.R., Aspects of the biology of billfish (Istiophoridae) from the equatorial

western Indian Ocean. J. Zool. (Lond.) 163:351-395.

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of marlins, sailfishes, spearfishes, and swordfishes known to date. FAO Fish.

Synop.

Ovichinnikov, V. V. 1966. The effect of oceanographic conditions on the distribution of

the sailfish, Istiophonis americanus, off the west African coast. Oceanology 6:

566-567.

Penrith, M.J. and D.L. Cram. 1972. The Cape of Good Hope: a hidden barrier to

billfishes. Proceedings of the International Billfish Symposium. Richard S.

Shomura and Francis Williams (ed). Pp. 175-187 NOAA Tech. Rep. NMFS

SSRF-675.

Pimenta. E.G., F.R. Marques, G.S.Limas, and A.F.Amorin. 2001. Marlin Project: tag-

and-release, biometrics, and stomach content of billfish in Cabo Frio city, Rio de

Janeiro, Brazil ICCAT 53:371-375.

Post. J.T, J.E. Serafy, J.S Ault, T.R. Capo, and D.P. de Sylva. 1997. Field and laboratory

observations on larval Atlantic sailfish ( Istiophonisplatyptems) and swordfish

(Xiphias gladiiis). Bull. Mar. Sci. 60:1026-1034.

Prince, E.D, M.A. Ortiz, D.Rosenthal, A. Venizelso, and K. Davy. 2001. An update of

the tag and release and recapture files for Atlantic Istiophoridae. ICCAT Coll.

Vol. Sci. Pap. 53:198-204.

Radtke, R.L., and B.S. Sheperd. 1991. Current methodological refinements for the

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gamefish tagging program in the Atlantic Ocean, Gulf of Mexico, and Caribbean

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Sharpies, P.B.. D. Brogan, and P.G. Williams. 2000. A preliminary summary of (i)

species identification problems, (ii) discarding practices and (iii) life status of

billfish taken in longline fisheries of the western and central Pacific Ocean,

according to information collected by observers and logbook data. 13th meeting

of the standing committee on tuna and billfish. Oceanic Fisheries Programme

BBRG -i5.

Shomura. R.S.(ed.) 1980. Summary report of the billfish stock assessment workshop.

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Hawaii, 5-14 December. 1977. NOAA Tech. Memo. SWFC-5 58 p.

Skillman. R.A.. 1989. Status of Pacific Billfish Stocks. Proceedings of the Second

Annual Billfish Symposium. Richard H. Stroud (ed). Pp. 179-195.

Somvanshi, V.S.. S. Varghese. 2001. Distribution, abundance indices and some

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and Nodder, 1792) in the north western Indian EEZ. Report to the Indian Ocean

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Speare, P. 1995. Parasites as biological tags for sailfish Istiophorus platypterus from East

Coast Australian waters. Marine Ecology Progress Series, vol. 118: 43-50.

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determined by cooperative tagging programs. In R.S. Shomura and F. Williams

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Hawaii 9-12 August 1972. Part 2. Review and contributed papers, pp. 188-193..

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Ueyanagi, S.. 1964. Description and distribution of larvae of five istiophorid species in

the Indo-Pacific. Proc. Symp. Scombroid fishes. Part 1, 499-528 Mar. Biol.

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during 1994-1996 based on the logbook database of the Japanese longline fishery.

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southwest Indian Ocean. Proceedings of the Second Annual Billfish Symposium.

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juv eniles de pez vela. Istiophonis platyptenis (Shaw y Nodder. 1791). capturados

en el Pacifico Mexican. Ciencas Marinas 24:499-505.

Wares. P.G. and G.T. Sakagawa. 1972. Some morphometries of billfishes from the

eastern Pacific Ocean. Proceedings of the International Billfish Symposium.

Richard S. Shomura and Francis Williams (ed). Pp. 107-120 NOAA Tech. Rep.

NMFS SSRF-675.

Whitlaw. W. 2000. Interactive session on billfish: An update for the year 2000: Present

knowledge, current and future research. 13th meeting of the standing committee

on tuna and billfish. Oceanic Fisheries Programme BBRG-1, 22 pgs.

Williams. F.. 1970. The sport fishery for sailfish at Malindi. Kenya. 1958-1968. with

some biological notes. Bull. Mar. Sci. 20: 830-852.

Williams. P.G.. K.A. Bigelow, and A.W. Whitlaw. 1999. Estimates o f longline billfish

catch (1980-1997) in the western and central Pacific Ocean. Report of the 12th

Standing Committee on Tuna and Billfish Research. Oceanic Fisheries

Programme BBRG-2 25pgs.

Yabe H., 1953. On the larvae of sailfish, Istiophonis orientalis. collected in the south

western Sea of Japan. Contrib. Nankai Reg. Fish. Res. Lab. 1(6): 1-10

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 29

Figure 1. Geographic distribution of sailfish

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. -----.._ ... ·-:·:-: . ...~ .:.' '·_ ·-' __../

ReproducedReproduced with with permission permission of of the the copyright copyright owner. owner. Further Further reproduction reproduction prohibited prohibited without without permission. permission. 31

Figure 2. Map of known spawning activity for sailfish

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. %

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 2.

MODERN AND HISTORICAL POPULATION STRUCTURE OF THE SAILFISH. ISTIOPHORUSPLAD'PTERL’S. INFERRED FROM ANALYSIS OF MITOCHONDRIAL DNA

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 34

INTRODUCTION

Analyses of mitochondrial DNA (mtDNA) have been used extensively to answer

questions about population structure, forensic identity, and evolutionary history (Avise.

1994). MtDNA is a closed circular molecule located in the mitochondrion. In most

vertebrate species including all teleosts examined to date, mtDNA encodes 37 functional

gene regions including 22 tRNAs. 13 mRNAs and two ribosomal RNAs (Lee et al., 1995;

Saitoh et al.. 2000). Because it is haploid, maternally inherited and does not undergo

recombination. mtDNA is functionally a single locus and haplotypes record the

evolutionary history of an organism.

The mitochondrial control region (D-loop) is the origin of replication of the

mtDNA molecule. The control region consists of two hypervariable regions (HVRs) on

either side of a conserved central domain, 2-3 conserved sequence blocks (CSBs), and an

extended termination sequence (ETAS) (Saccone et al., 1987; Sbisa et al.. 1997). It has

been suggested that the central domain functions as the origin of replication, the CSBs

prime H-strand replication, and the ETAS signal the termination of replication (Sbisa et

al., 1997).

The control region has been used extensively in studies of population structure in

marine species due to its rapid rate of sequence evolution (McMillan and Palumbi, 1997;

Bowen and Grant, 1997; Nesbo et al., 2000). Sequence divergence rates for the entire

mtDNA molecule have been estimated to be approximately 2% per million years in

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 35

vertebrate mitochondrial genomes based primarily on mammalian data (Brown et al.,

1979); however, estimates of divergence rates in the control region are much higher for

most species examined. Recent estimates based on divergence of geminate species of

snook across the Isthmus of Panama suggest that the control region diverges at rate of

3.6% per million years (Donaldson and Wilson, 1999). However, the divergence rate has

been reported to be 11.5-20% per million years in other vertebrates (Saccone et al., 1987;

Saccone et al.. 1991; Brown et al.. 1993) and the tRNApro end of the control region has

been reported to diverge at rates of 30-108% per million years in some species (Irwin et

al.. 1991).

The timing of known geological events has often been used to calibrate rates of

molecular divergence under the premise of the "molecular clock", which assumes that

evolutionary (mutation) rates, once calibrated, are both steady within a species and

comparable among species for a particular gene. Levels of genetic divergence for that

gene region can then be used to estimate the time since divergence of other lineages,

providing insight into the forces or events responsible for the present day population

structure of a particular species or groups of species (A vise, 1994).

The association of particular groups of mtDNA haplotypes with geographic

regions has become known as the study of phylogeography (Avise, 1994). However,

separating current day population structure, which is the result of ongoing but potentially

restricted gene flow, from the effects of historical events has been problematic (Avise et

al., 1987, 1998; Hewitt, 2000; Nesbo et al., 2000; Colburn et al., 2001). Until recently,

phylogeographic studies have relied primarily on visual inspection of genealogies

overlaid onto maps; there have been few statistical tests available to test to resolve

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conflicting hypotheses, and not all methods take full advantage of the information

implicit in the data (Templeton, 1998).

Several methods of phylogeographic analysis are now available that use

information from genealogical relationships among haplotypes. This information,

combined with knowledge about the behavior of alleles under different evolutionary

constraints, provides a powerful tool for population genetic analyses. The analysis of

molecular variance. AMOVA (Excoffier et al., 1992). is one test that allows for the

incorporation of haplotvpic relationships. This method uses a matrix of squared

differences between all pairs of haplotypes and can be built from the mean number of

restriction site differences between haplotypes. from the nucleotide diversity between

haplotypes (neither of which take into account the evolutionary relationships between

haplotypes). or from the evolutionary distance between haplotypes as calculated from a

haplotvpe network and weighted by the nucleotide divergence between haplotypes.

When more than one connection between haplotypes is possible, the network algorithm

chooses between connections based on two assumptions: 1) a link between two rare

(<5%) haplotypes is less likely than a link between a rare and a frequent haplotype, and

2) links between haplotypes from the same population/geographic region are more likely

than links between haplotypes from different regions (Excoffier et al, 1992). Samples

can then be grouped into different hierarchical levels based on a priori hypotheses about

population structure and tested to determine whether the variance between groups is

greater than would be expected by random chance.

Another statistical test, nested clade analysis, has been developed to separate the

effects of contemporaneous gene flow from historical events. This test, originally

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developed by Templeton et al. (1989) for mapping phenotypic traits onto haplotypes, has

been adapted to questions of phylogeography and has been used extensively in studies of

human populations (Templeton. 1992; Hammer et al., 1998) and more recently, to other

organisms including freshwater mussels (Turner et al.. 2000). brown trout (Bematchez.

2001). northern clingfish (Hickerson and Ross. 2001). leatherside chub (Johnson and

Jordan. 2000). and even saltwater rotifers (Gomez et al.. 2000). Nested clade analysis

can give insight not only into the timing of evolutionary events but. in some cases, it can

discriminate among range expansion. long distance colonization and population

fragmentation by considering the different factors that lead to population subdivision

(Templeton. 1998). For example, haplotypes should theoretically be more frequent near

their geographic location of origin under an isolation by distance model; therefore, in a

nested analysis interior clades must be as old or older than all the less interior clades

nested within them. In addition, when a mutation arises resulting in a new haplotype. the

new haplotype originates within the range of its ancestral haplotype and should therefore

have a more restricted range than the ancestral haplotype under an isolation by distance

model; so tip clades should have a more restricted geographic range than those interior to

them under an isolation by distance model.

In the case of range fragmentation, the nested clade distance should increase

markedly as compared to the clade distance due to geographic constraints on the clade

distance resulting from geographic constraints on the mutations that differentiated the

fragmented populations. Alternately, in the case of range expansion, the haplotypes that

were involved in the range expansion will become geographically widespread. Thus, the

slow spread over geographic space expected under an isolation by distance/restricted

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gene flow scenario, including the correlation between the age/abundance of haplotypes

and range (i.e. the assumption that older more abundant haplotypes should have the

largest geographic range) will be absent. In fact, simulations show that when long

distance colonization has taken place, haplotypes found in expanding populations can

become genetically distant from older haplotypes that are confined to pre-expansion

ranges (Templeton, 1998).

The factors leading to population structure in large pelagic species, such as

istiophorid billfishes. have been subject to much speculation. Unlike less mobile

organisms, pelagic species have a vast potential for dispersal and a lack of apparent

physical barriers (Graves, 1998). In addition, information that has traditionally been

used to appraise the presence of distinct stocks in other marine fishes, such as where and

when they spawn, preferred migratory routes, and what comprises suitable habitat, is

lacking for istiophorid billfishes. The fossil record, which gives insight into the

evolutionary history of other organisms, is also largely absent for billfish; although it is

postulated that the common ancestor of modem billfishes and swordfish w as extant

during the Miocene 5-23 MYA and probably originated in the Tethys Sea (Firenstein,

1990). Since they are the most coastal of all the billfish species, sailfish are the most

likely candidate among the istiophorids to exhibit some degree of stock structure.

Delineation of the partitioning of genetic variation in sailfish is a first step towards

understanding not only the factors that promote divergence in large pelagic species, but

also towards understanding the evolutionary history of istiophorids.

Recently mitochondrial DNA analyses have been used to characterize the stock

structure of several billfishes including striped marlin (Graves and McDowell, 1994),

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white marlin (Graves and McDowell, 1998), swordfish (Reeb et al., 2000; Alvarado et

al., 1996; Rosel and Block, 1996; Alvarado et al., 1995), blue marlin (Graves and

McDowell 1998; Buonacccorsi et al., 2001), and sailfish (Graves and McDowell, 1995).

Although the striped marlin was found to exhibit stock structure within the Pacific Ocean,

a similar study of the closely related white marlin showed no evidence of stock structure

within the Atlantic. Sailfish appeared to exhibit intra-ocean stock structure based on

whole molecule mtDNA analysis; however sample sizes and sampling locations were

limited (Graves and McDowell, 1995). Interestingly, all billfishes examined with a

worldwide distribution, including swordfish, blue marlin, and sailfish show evidence of

inter-ocean divergence, which is primarily driven by the existence of two distinct clades,

one of which occurs in the Atlantic and the other which is distributed across the species'

range. The existence of these two clades has been attributed to isolation during

Pleistocene glaciation and subsequent gene flow that has been largely unidirectional from

Pacific to Atlantic (Graves and McDowell, 1995).

Molecular genetic techniques have also been applied to investigate the specific

status of sailfish. A comparison of mitochondrial DNA (mtDNA) restriction fragment

length polymorphism (RFLP) patterns between sailfish taken from the Atlantic and Indo-

Pacific indicates that, although there is significant inter-ocean divergence between ocean

populations, separate taxonomic status is not warranted (Graves and McDowell, 1995).

This conclusion is based on the fact that no restriction sites were found to discriminate

between Atlantic and Indo-Pacific samples and in many cases, haplotypes that were

unique to a particular ocean were closely related to haplotypes common to samples from

both oceans. The corrected mean nucleotide sequence divergence between samples from

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different oceans in this study was 0.27%, a value that is lower than values reported for

many geographically isolated populations of marine fish including bluefish (Pomatomus

saltatrix) and mackerels of the genus Scomber (Graves. 1998).

In this study, genetic analyses are used to elucidate the global stock structure of

sailfish taken from throughout their range. RFLP analysis of the mitochondrial control

region as well as sequence analysis of the most common haplotypes revealed in the RFLP

analysis are used to infer the relative contribution of historical processes and current

associations.

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MATERIALS AND METHODS

Altogether. 647 sailfish were collected and analyzed from throughout the species'

range over a six year period (Table 1). In the western Atlantic, 164 individuals were

analyzed from Florida (FLA. 42). Brazil (BRA, 93). Venezuela (VEN. 15). and

TrinidadTobago (CAR. 14): and in the eastern Atlantic. 130 individuals were analyzed

from Senegal (SEN. 37) and Ghana (GHA. 130). In the eastern Pacific. 149 individuals

were analyzed from Mazatlan (MAZ, 51) and Cabo San Lucas (CAB, 27) Mexico,

Ecuador (ECU. 60). and Panama (PAN, 11); and in the western Pacific, 113 individuals

were analyzed from Vietnam (VNM, 12). Papua New Guinea (PNG. 36). and Taiwan

(TAW, 65). In the Indian Ocean. 91 individuals were analyzed from Australia (AUS.

21). Kenya (KEN; 47) and the Persian Gulf (PER, 23).

Sailfish were collected by commercial, artisanal, and recreational fishermen and

samples consisted of either heart tissue removed after capture and stored at -80°C until

isolation, or white muscle preserved in 0.25mM EDTA pH 8.0, 20% DMSO, and

saturated NaCl (Seutin, 1991) at room temperature until isolation. DNA was isolated

according to the methods of Sambrook et al. (1989). Briefly, a small (1 cm3) amount of

tissue was diced and placed into 500 ul of buffer consisting of 10 mM Tris, 2 mM EDTA,

1% SDS, 10 ul of 10 mg/ml RNAse and 10 ul of 25 mg/ml Proteinase K and incubated

overnight in a water bath at 37°C. After incubation, the solution was centrifuged at

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16.000 g for 30 min. to pellet cellular debris and the supernatant was transferred to a

clean tube. DNA was isolated using a standard phenol:chloroform:isoamyl alcohol

extraction and precipitated in 0.4X volumes of 5M NaCl, 2X volumes of 100% ethanol.

DNA was reconstituted in 50 ul of 0. IX TE (pH 8.0) and stored at -20°C.

Following DNA isolation, the mitochondrial cytochrome b. ATPase. cytochrome

oxidase I. ND4 and control gene regions were amplified using universal primers. After

amplification conditions had been optimized, amplicons were screened with up to 25

restriction enzymes at each locus using a single sailfish sample. Gene region/enzyme

combinations that produced easily interpretable profiles were screened for intra-specific

variation using a subset of 12 Atlantic and 12 Pacific sailfish. Of the regions screened,

the control region exhibited the highest level of variation and was therefore chosen for

further analysis.

The CB3R-5' (CATATTAAACCCGAATGATATTT) and 12SAR5’

(ATAGTGGGGTATCTAATCCCAGTT) polymerase chain reaction (PCR) primers of

Martin et al. (1993) were used for all control region amplifications. Amplification

products were approximately 1700 bp and spanned the entire control region as well as the

flanking tRNAs and portions of the cytochrome b and 12S RNA gene regions. All

amplifications were done using the BRL PCR Reagent System (Life Technologies Inc.,

Bethesda, MD). Reactions consisted of a 20 mM Tris-HCL (pH 8.4). 50 mM K.C1, 1.5

mM MgCh, 0.2 mM dNTP mix, luM each of the forward and reverse primer, 1.125 units

o f Taq polymerase and approximately 50 ng template DNA in a total volume of 50 ul.

Cycling conditions included an initial denaturation of 5 min. at 95°C followed by 39

cycles of 94°C for 30 sec., 46°C for 1 min., and 72°C for 1 min., followed by a 5 min.

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final extension at 72°C. Amplified fragments were initially digested with six variable

restriction enzymes. Dde I. Hinc II, H inf I, Nci I, Sri-1, and Mbo I. The enzyme Mbo I

was subsequently dropped from the analysis due to the presence of a large number of

enzyme profiles that were difficult to distinguish reliably. Fragments were resolved on

2.5% agarose gels consisting of 1.25% ultraPure agarose (Life Technologies Inc..

Bethesda. MD) and 1.25% NuSeive GTG agarose (FMC BioProducts, Rockland. ME)

electrophoresed at 100 volts for approximately four hours on a horizonal gel apparatus

and visualized using ethidium bromide staining and UV illumination.

Fragment sizes were estimated by comparison to a lkb DNA ladder (Life

Technologies. Bethesda. MD) and each distinct restriction pattern was given a unique

letter designation. Relationships among restriction fragment patterns (gains and losses of

restriction sites) for a particular enzyme were inferred from their fragment sizes.

Composite haplotypes were assembled from the unique letter designation for each

enzyme and the number of each haplotype in each location was tabulated (Table 1).

Haplotypic diversity ( h ), nucleotide sequence diversity (ji). and a matrix of

nucleotide sequence divergences between haplotypes were calculated using the program

REAP (McElroy et al., 1991). The matrix of nucleotide sequence divergence values

between populations was generated using the algorithm of Nei and Miller (1990). In

addition, REAP was used to generate a list of haplotype definitions in the form of a

binary character state matrix from the presence/absence data for each restriction site such

that " 1" represented the presence of a site and "O' represented the absence of a site.

Geographic heterogeneity in haplotype frequency distributions was assessed for

all collection locations simultaneously using Markov chain Monte Carlo simulations with

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10,000 replicates to estimate the probability that the distribution of different haplotypes

among populations was non-random using REAP (McElroy et al., 1991). Haplotype

distributions were then compared among collection locations within each ocean and with

oceans divided into eastern and western collections. Finally, pairwise comparisons were

made between all collection locations within each ocean. Probabilities were calculated

using 10,000 replicates. These calculations were done without the Panama. Caribbean,

Venezuelan and Vietnam collections due to their small sizes (n< 12) and accompanying

lack of statistical power

The number of pairwise differences between haplotypes was calculated as the

number of restriction sites separating two haplotypes and significance of these

differences was assessed via randomization in the program ARLEQUIN (Schneider et al.,

2000). The level of population differentiation was estimated using the AMOVA

algorithm (Excoffier et al., 1992) as implemented in ARLEQUIN ver. 2.1 (Schneider et

al., 2000). This algorithm was performed both by taking into account the number of

mutations between molecular haplotypes (

which use only relative allele frequencies and include no information on haplotype

relatedness.

Minimum spanning networks between haplotypes were constructed from the

matrix of squared distances between haplotypes according to the algorithms of Rohlf

(1973) and Excoffier and Smouse (1974) as implemented in Arlequin ver 2.1 (Schneider

et al., 2000). In addition, phenetic trees were constructed from the matrix of nucleotide

sequence divergence estimates between haplotypes using the program PHYLIP version

3.6a2 (Felsenstein, 2001)

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Geographic distances between collection locations were calculated using the

program ArcView GIS ver. 3.2a (ESRI Software. Redlands, CA). Distances were used

in conjunction with the matrix of mean nucleotide sequence divergences between

collections to assess geographic/genetic associations. Geographic distances were also

used in a nested clade analysis (Templeton, 1995; 1998) to assess geographic correlation

using the program GeoDis (Posada et al., 2000).

Representatives of the major control region haplotypes found in the RFLP

analysis were amplified by PCR as described above and sequenced. After amplification,

reactions were purified using the Wizard PCR Preps DNA Purification System (Promega.

Madison, WI) and the amount of DNA present in each sample was quantified using a

DyNAQuant fluorometer (Hoefer Pharmacia Biotechnology, San Francisco, CA). After

quantification, the Thermo Sequencase DYEnamic Direct cycle sequencing kit with 7-

deaza dGTP (Amersham, Piscataway, NJ) was used to direct sequence amplified products

using IRD-700 labeled forward primer and IRD-800 labeled reverse primer (LiCor,

Lincoln, NE) on a LI-COR global IR2 system. Primer sequences were identical to those

used for the initial amplification. Standard chromatographic curves (SCF curves) of

forward and reverse sequences were imported into the program Sequencher 3.0 (Gene

Codes Corp., Ann Arbor, MI), aligned and edited. The consensus of the forward and

reverse sequence was exported to the program MacVector 6.5 (Oxford Molecular Ltd.,

Madison, WI) and aligned to other sequences using the CLUSTALW algorithm

(Thompson et al., 1994) and adjusted by eye.

Restriction sites for the five enzymes used in the study were located in the

alignment and used to assess the accuracy of previously inferred fragment patterns and to

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ascertain the relative order of those fragments along the molecule (Appendix 1). The

different gene regions amplified by the primers were located by using the CLUSTALW

algorithm of MacVector to align a representative sequence to the complete mitochondrial

sequence of the Japanese flounder, Paralichthys olivaceus (Saitoh et al., 2000; Genbank

accession no. AB028664). The number of polymorphic sites, the total number of

mutations, the average number of nucleotide differences (Dxy), the number of fixed

differences between populations, and estimates of Fst were calculated in the program

DNAsp (Rozas and Rozas, 1999). The nucleotide diversity (n), and the net nucleotide

divergence between clades (Dxy) were calculated using the Tamura-Nei algorithm

(1993), which corrects for multiple mutations at a single site by taking into account

substitutional rate differences between nucleotides and unequal nucleotide frequencies. It

distinguishes between transitional substitution rates between purines and pyrimidines and

transversional substitution rates. Unweighted pair group method with arithmetic mean

(UPGMA) trees were drawn based on the pairwise distance matrix using the program

MEGA 2.1 (Kumar et al., 2001). Calculations were done both for the entire sequence

generated and for the isolated control region.

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RESULTS

Intcr-Occan RFLP analysis

Data were initially analyzed with samples collected in multiple years at a location

held separately, but because there was no evidence of temporal heterogeneity between

years at any location, temporal samples were combined for subsequent analyses. As with

other istiophorid billfishes. sailfish have a considerable amount of genetic variation:

mtDNA analysis resulted in a total of 54 composite haplotypes (Table 1). Haplotvpic

diversities ranged from 0.94 (Venezuela) to 0.11 (Papua. New Guinea) and nucleotide

diversities ranged from 0.024 (Senegal) to 0.0019 (Australia, Table 2). A cursory

examination of the levels of haplotvpic and nucleotide sequence diversities by area

reveals that haplotvpic diversity is consistently higher (0.81-0.94) in the Atlantic Ocean

than in other areas sampled, while diversity indices were consistently lower (0.22-0.32)

in the eastern Pacific. In the western Pacific and Indian oceans, no consistent pattern was

evident; haplotypic diversity ranged from 0.18-0.60 in the western Pacific Ocean and

from 0.11-0.49 in the Indian Ocean (Table 2). In addition, nucleotide sequence

diversities between haplotypes were consistently higher in Atlantic samples (0.017-

0.026) while Indian and Pacific samples had mean nucleotide diversities that were

generally an order of magnitude smaller (0.0018-0.010, Table 2. Figure I).

A UPGMA tree based on the corrected mean nucleotide sequence divergences

between haplotypes revealed the presence of two distinct haplotype clades within the

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sailfish (Fig 2). One clade, designated the "ubiquitous" clade, was present in all

collections examined while a second "Atlantic" clade was noted only in Atlantic

collections. The coexistence of these two distinct mitochondrial clades in the Atlantic

contributes to the higher levels of diversity seen within Atlantic samples.

Comparison of the overall distribution of haplotypes found in the Atlantic, Pacific

and Indian oceans resulted in a calculated probability of homogeneity of <0.0001,

indicating a highly significant non-random distribution of haplotypes among collections

from the three oceans. Haplotype distributions were then tested within each ocean, with

oceans divided into eastern and western populations (Table 3), and finally, pairwise

comparisons were done between samples in a given ocean (Table 4). These analyses

were done without the Panama. Caribbean. Venezuelan and Vietnam samples due to their

small sizes.

Within the Atlantic Ocean, the distribution of haplotypes was not significantly

heterogeneous within collections from Brazil, Florida, Senegal and Ghana after

correction for multiple tests (p=0.0476 +/-0.0021). However, since the probability was

near significance, collections were also tested within the eastern Atlantic (Ghana vs.

Senegal) and within the western Atlantic (Florida vs. Brazil), resulting in non-significant

probabilities of 0.1900+/-0.0039 and 0.3578 +/- 0.0048, respectively. In addition, Ghana

and Senegal were pooled into an “eastern Atlantic” collection and Florida and Brazil

were pooled into a “western Atlantic” collection and compared, resulting in a non

significant value of p=0.0589 +/- 0.0024. Using these analyses there is no discemable

population structure in the Atlantic based on the control region. However, these analyses

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used only the frequencies of particular haplotypes in each collection and did not

incorporate information about the relationships among haplotypes.

In the Pacific Ocean, there was a significant difference (p=0.0I67 +/- 0.0013) in

the distribution of haplotypes among locations. Pairwise comparisons between

collections from Cabo San Lucas, Mexico. Mazatlan, Mexico and Ecuador in the eastern

Pacific were all non-significant, ranging from 0.2157 +/- 0.0041 to 0.7323 +/- 0.0044.

The distribution of haplotypes between the Taiwan and New Guinea collections in the

western Pacific was also non-significant (p=0.0796 +/-0.0027). However, when eastern

Pacific collections were compared to western Pacific collections, the distribution of

haplotypes was significantly heterogeneous (p=0.0005 +/- 0.0002).

As in the Pacific, the distribution of haplotypes among collection locations in the

Indian Ocean was significantly different from random (p<0.0001). Pairwise comparisons

indicated that the distribution of haplotypes was not significantly different between

collections taken from Australia and those taken from Kenya (p=0.2048 +/- 0.0040).

However pairwise comparisons of Australia and Kenya with the Persian Gulf each

resulted in a probability of <0.0001, suggesting that the Persian Gulf collection is distinct

from the other Indian Ocean collections.

Finally, the distribution of haplotypes between Indian Ocean collections and those

from the western Pacific was found to be significantly non- random (p<0.0001); however,

when the Persian Gulf collection was removed from the analysis, collections from the

two regions did not differ significantly (p=0.2312; Table 3). Pairwise comparisons of

haplotype distribution between collections from Australia and Kenya in the Indian and

Taiwan and New Guinea in the western Pacific were not significant.

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An analysis of molecular variance (AMOVA) was performed using RFLP data

which incorporated information about the distance between pairs of haplotypes (Ost.

Table 5). When collections were grouped by ocean of origin, 32.53% (p<0.0001) of the

variance was attributable to variation among the three oceans, and 1.85% of the variance

(p=0.0002), a small but highly significant amount, was due to variation among

collections within the oceans. The remaining 66.53 % (p=0.0001) was ascribed to

variation harbored within the collections.

An AMOVA which considered the entire Atlantic as a single group found that

99.95% of the variance was attributable to variation within the individual collections and

0.05% (p=0.400) was attributable to variation between collections. When collections

were partitioned into eastern and western Atlantic groups, 100% of the variance was due

to variation within populations; as with the exact tests of population differentiation, no

population structure was detected within Atlantic sailfish even when the relationship

among haplotypes was considered (Table 5).

Within the Pacific Ocean, 97.65% of the variance was attributable to variation

within the collections and 2.33% (p=0.0015) was attributable to variation between

collections. When collections were further subdivided into eastern and western Pacific

groups, 1.39% of the variation (p=0.10050) was due to variation among collections

within the eastern and western groups, and 1.47% (p=0.04198, Table 5) was due to

differences among the groups.

In the Indian Ocean, 34.34% of the variance was due to variation among the three

collections (p<0.0001). Because the Australian and Kenyan collections were not found to

be significantly different using exact tests, (differences in the distribution of haplotypes

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in the Indian Ocean were driven by the Persian Gulf collection) the Persian Gulf

collection was removed from the analysis and structure was tested again. In this case,

1.18% of the variance was attributable to variation among the two populations

(p=0.12198. Table 5).

Clades

Tw o major clades of haplotypes were revealed using both RFLP and sequence

analysis, an "Atlantic" clade present solely in the Atlantic and an "ubiquitous" clade

distributed throughout all three oceans (Figure 2). At the RFLP level, the frequency of

the two major clades was found to be similar in all Atlantic locations (Table 6). An

AMOVA analysis with Atlantic and ubiquitous clade individuals grouped as separate

populations found that 66.02% (p<0.0001) of the variance was due to the variation

among the two clades and 33.98 % (p<0.0001) of the variance was due to variation

within the clades. The Fst analog, Ost. between the two clades was 0.6603 and the net

(corrected) nucleotide sequence divergence between clades wras estimated to be 2.5%

based on RFLP data.

Closer examination of the UPGMA tree based on the corrected mean nucleotide

sequence divergence between the 54 haplotypes (Figure 2) suggests that the "ubiquitous"

clade is actually made up of two closely related subclades, one of which is composed of

haplotypes present in the Atlantic, Indian and Pacific Ocean collections (designated "2"

in Figure 2) and the second (designated "1" in Figure 2) which is present almost

exclusively in Atlantic collections (60.54%, Table 6), although it does occur in 15 Indo-

Pacific individuals (4.9% Pacific, 2.2% Indian; Table 6). The distribution of these three

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clades was compared between oceans and between pooled eastern and western Atlantic

collections (Table 6). The frequency of the Atlantic clade was similar in eastern and

western Atlantic collections and therefore the geographic origin of this clade could not be

determined. However, ubiquitous subclade 1 appears to be more frequent in the eastern

Atlantic (64.3%) as compared to the western Atlantic (55.38%). Conversely, ubiquitous

sub-clade 2 appears to be more frequent in the western Atlantic (27.69%) as compared to

the eastern Atlantic (19.51 %).

Overall, pooled ubiquitous clade individuals had a haplotypic diversity of 0.6713

and a nucleotide sequence diversity of 0.0125 and Atlantic clade individuals had a

haplotypic diversity of 0.8475 and a nucleotide diversity of 0.04244. When the

ubiquitous clade was partitioned into sub-clades 1 and 2, the haplotypic diversity of

pooled sub-clade 1 individuals (the clade containing predominantly Atlantic fish) had a

haplotypic diversity of 0.5541 and a nucleotide diversity of 0.00956 and pooled sub-clade

2 individuals had a haplotypic diversity of 0.4920 and a nucleotide diversity of 0.00653

(Table 7).

Sequencing

In sum, 58 sequences were generated from Atlantic, Pacific, and Indian Ocean

collections. Individuals were chosen to be representative of both clades and all major

haplotypes. In all, 20 individuals were sequenced from the Indo-Pacific and 38

individuals were sequenced from the Atlantic including 31 “Atlantic clade" individuals

and 7 “ubiquitous” clade individuals, for a total of 27 "ubiquitous clade" and 31 "Atlantic

clade" individuals. For major haplotypes occurring in more than one ocean, at least one

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representative individual was sequenced from each ocean. In addition, for the most

common haplotype individuals from each collection were sequenced No two sequences

were identical; haplotypic diversity was 1. On average, sequences had 36.56 nucleotide

differences (k) between them and the average number of nucleotide differences per site

between any two sequences (re) was 0.033. Diversity estimates based solely on Atlantic

individuals yielded similar results (k=30.46, re=0.027), while estimates based on Indo-

Pacific individuals were much lower (k= 10.43. re=0.009) due to the presence of a single

clade. Grouping individuals both by clade without regard to ocean of origin as well as by

clade within an ocean led to diversity estimates that were similar to those derived from

the Pacific. Atlantic clade sailfish had an average of 17.91 nucleotide differences

between pairs of sequences and a nucleotide diversity of 0.016 while ubiquitous clade

fish had an average of 11.20 nucleotide differences and a nucleotide diversity of 0.010.

The seven ubiquitous clade sailfish examined from the Atlantic had an average of 14.23

nucleotide differences and a nucleotide diversity of 0.009 (Table 8).

Several divergence estimates were calculated between sequences from Atlantic

and Indo-Pacific individuals, between Indo-Pacific and “ubiquitous clade” Atlantic

individuals, between “Atlantic clade” and “ubiquitous” individuals in the Atlantic and

between all “Atlantic clade” and all ‘ubiquitous clade” individuals (Table 9). No fixed

differences were found in comparisons between Atlantic and Indo-Pacific sequences, nor

were consistent differences found between Atlantic and Indo-Pacific “ubiquitous”

sequences. However, there were 19 fixed nucleotide differences between sequences from

“Atlantic clade” and “ubiquitous clade” sailfish (localized on sequences in Appendix 1)

and 25 fixed differences between “Atlantic clade” and “ubiquitous clade” sailfish taken

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from the Atlantic. Comparison of other divergence statistics confirms that “ubiquitous

clade” sequences are very closely related regardless of ocean of origin.

As with the RFLP data, a UPGMA tree of the 58 sequences also suggests the

presence of a third clade (Fig 3). However, while this subclade was part of the ubiquitous

clade based on RFLP analysis, it appears to be closer to the Atlantic clade based on

control region sequences (see Atlantic clade samples marked RFLP ubiqu 1 in Fig. 3).

There are three fixed differences between these two subsets of sequences and the

corrected mean nucleotide sequence divergence is estimated at 0.033 while the nucleotide

sequence diversity within the subclades is 0.13 and 0.14 respectively. The estimated Fst

between these subclades is 0.58 using the Hudson. Slatkin and Maddison algorithm

(1982) and Fst is very similar between the ubiquitous clade and each of the two Atlantic

subclades: both are estimated to be approximately 0.80. The corrected nucleotide

sequence divergence between the two subclades was estimated to be 0.0202.

Fst between Atlantic and Indo-Pacific “ubiquitous clade” sequences was 0.0018

and the average number of nucleotide differences was 12.37 while “Atlantic clade” vs

“ubiquitous clade” sequences from within the Atlantic Ocean had and Fst of 0.726 and

an average of 59.48 nucleotide differences between sequences (Table 9).

Since the primers used in this study amplify a portion of the cytochrome b gene

region, the complete tRNA1^, tRNApro, and tRNAphe. as well as a portion of the 12SRNA

gene region, these genes were localized in the sequence (Appendix I) and sequences

were re-analyzed using only the control region nucleotides. The control region of the

sailfish was found to be between 839 and 855 base pairs in length. As in other

vertebrates, the control region in sailfish is A-T rich and nucleotide usage was very

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similar between individuals. Nucleotide usage ratios in the control region were (T) 28.7-

29.6%: x=29.2%. (C) 22.1-23.3%: x=22.7%. (A) 31.5-33%: x=32.2% and (G) 15.1-

16.5%: x=15.9% (Table 10). Overall, there were 35 transitional pairs comprised of 19

T<->C and 16 A<->G and only 1 transversional pair. Divergence estimates using only the

control region yielded a net mean nucleotide sequence divergence of 0.0556 + - 0.0082

between clades using the Tamura-Nei model and the coefficient of differentiation, an

estimate of the proportion of interpopulational diversity, was 0.6175- - 0.0360. An

AMOVA analysis indicates that 75.15% of the variance is due to variation among clades

while 24.S5°o of the variance is due to variation between sequences within clades.

Interestingly. 18 19 fixed differences between clades were located in the control region

and the other difference was located in the tRNAlhr. Of the 19 fixed differences. 18 were

transitions and the remaining fixed difference consisted of a lbp indel that is present in

the Atlantic clade and missing in the ubiquitous clade. Of the transitions. 11 were A«-*G

and 7 were T<->C (Appendix 1. Table 11).

The recognition sequences of the five restriction enzymes used in the RFLP

analysis were located on the DNA sequences to see which gene regions were surveyed

and if any of the enzyme sites encompassed the fixed differences between clades

(Appendix 1). Two enzyme sites were in the cytochrome 6. one in the tRNAmr, one in

the tRNApro, 4 in the 12SRNA. and 19 were in the control region. Of the 19 recognition

sites in the control region, 18 were variable among sequences while 3 of 8 recognition

sites in all other regions combined were variable. Two of the restriction enzymes were

found to be diagnostic of the two major clades based on the 58 individuals sequenced.

The first was an Nci I restriction site spanning position 891 which, when present.

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indicates that the sample belongs to the ubiquitous clade and the second was a Dde I

restriction site spanning position 1003, which indicates that the sample belongs to the

Atlantic clade (Table 10).

For comparative purposes. 8 striped marlin (Tctraptums audax) and 9 white

marlin (Tctraptums albidus) sequences which included the control region (Reece and

Graves, unpublished data) were aligned, and the control region was localized within the

sequences as above. Sinee striped and white marlin are closely related sister species with

w hite marlin occurring in the Atlantic Ocean and striped marlin occurring in the Indian

and Pacific oceans, divergence estimates were calculated for comparison to the sailfish

Atlantic and ubiquitous clades (Table 12). Overall, diversity was slightly higher in the

white striped marlin than in sailfish (0.0560 vs. 0.0461). however: the standard errors are

overlapping indicating that the two estimates are essentially equivalent. These estimates

were also essentially equiv alent for the two species using whole molecule mtDNA RFLP

analysis: sequence diversity for sailfish was estimated to be 0.0023 and diversity was

estimated to be 0.0029 for white striped marlin (Graves and McDowell. 1995). Within

oceans/groups, striped marlin (Pacific) were more diverse than white marlin (Atlantic)

(0.0503 vs. 0.0213) while in sailfish. the Atlantic clade was more diverse than the

ubiquitous clade (0.0217 vs. 0.00135). It is interesting to note that diversity estimates for

the Atlantic clade sailfish were nearly identical to diversity estimates for white marlin,

while Pacific sailfish sequences were more closely related (less diverse) than striped

marlin sequences. Although the uncorrected divergence between sailfish clades and

striped/white marlin was very similar, 0.0732 and 0.0756 respectively, the corrected

divergences were different, 0.0556 for sailfish and 0.0399 for white and striped marlin

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due to the high diversity present in striped marlin as compared to ubiquitous clade sailfish

(Table 12). In addition, there were 14 fixed differences between white and striped marlin

sequences while there were 19 between the sailfish clades.

S'ested clade analysis

In order to distinguish the effects of evolutionary history from those of population

structure resulting from contemporary processes and to attempt to pinpoint the potential

factors contributing to stock structure, a nested clade analysis was carried out among

samples following the methods of Templeton et al.. (1995, Figures 5.6). Results indicate

that there was a significant association between haplotypes and geographic location in

clades 1-3. 1-7. 1-11. 2-1, 2-3. 2-1. 3-2. and the total cladogram (Fig. 5. 6). The causes of

geographic association assessed following the inference key of Templeton et al. (1998)

indicate that the patterns seen for all clades except 3-1 are consistent with restricted gene

flow dispersal with some long distance dispersal over intermediate areas not occupied by

the species. The overall pattern of clade 3-1 is consistent with past fragmentation.

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DISCUSSION

Population structure

MtDNA failed to reveal the presence of stock structure among sailfish within the

Atlantic Ocean. Population genetic studies of other Atlantic istiophorid billfishes.

including white marlin (Graves and McDowell. 1998) and blue marlin (Buonacorssi et

al.. 2001) have given similar results. In RFLP analyses of the whole mtDNA molecule of

both white marlin and blue marlin, the distribution of genetic variation was

homogeneously distributed among geographic locations although there was sufficient

variation to detect stock structure. Likewise, studies involving other large pelagic fishes

sampled throughout the Atlantic and analyzed using mtDNA. including yellowfin tuna

(Scoles and Graves. 1993) and swordfish (Alvarado et al.. 1995; Rosel and Block. 1996)

have not discerned any appreciable stock structure. This is probably due to the relatively

small size of the Atlantic basin: the distance from Brazil to Senegal is approximately

2575 km while in the Pacific, the distance from Indonesia to Columbia is 19.800 km and

in the Indian Ocean, the distance from South Africa to Australia is 10,000 km. The

relatively short distance across the Atlantic basin combined with the dispersal ability of

highly migratory pelagic fishes is likely to ensure enough gene flow to inhibit the

accumulation of genetic differences in the Atlantic basin.

In contrast to the Atlantic, sailfish collections from the Indian and Pacific basins

reveal significant heterogeneity. In the Pacific, analyses of geographic heterogeneity

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indicates that haplotypes are not randomly distributed and AMOVA estimates that 2.33%

of the variation was due to variance among collections, a small but significant value

(p=0.00149). In the eastern Pacific, all of the descriptive statistics such as haplotypic

diversity and nucleotide diversity are very similar among collections and on average,

values for the eastern Pacific are lower than values obtained in any other area. The most

common haplotype was evenly distributed among all eastern Pacific sampling locations

and was present in 82-88% of all samples (Table 13). In addition, the probability of

significance for mtDNA exact tests in pairwise comparisons were all non- significant,

and no variation was attributable to variance among the three largest collections;

Mazatlan. Ecuador, and Mexico. When the Panama sample was included in the AMOVA

analysis, a significant amount of the variance was attributable to variation among

samples, probably due to sampling error caused by the small sample size (12 individuals).

Regardless, analysis of a larger sample from this area in the future is warranted. Overall,

the results obtained in the eastern Pacific are consistent with what is known of the life

history of sailfish in this area, namely that they tend to move up and down the coast

seasonally in a predictable pattern with the 28 isotherm (Eldridge and Wares. 1972).

In the western Pacific, the Vietnam sample was excluded from analyses because

of its small size (12 individuals). Unlike the eastern Pacific, the Taiwan and Papua. New

Guinea samples did not have similar descriptive statistics; haplotype and nucleotide

diversity were much higher in the Taiwan samples (/;=0.489 vs. 0.1095 and tt=0.0063 vs.

0.0019). Although exact tests of population differentiation revealed no differences in the

distribution of haplotypes between samples, an AMOVA indicated that 3.73% of the

variance (p=0.01881) was due to variation between the samples, suggesting that the

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populations are somewhat differentiated and gene flow may be partially restricted

between these areas. The most common haplotype occurred in 70.1% of the individuals

collected in Taiwan but was present in 94.4% of the individuals collected in New Guinea

(Table 13). This was the highest frequency of the most common haplotype for any

location sampled. In addition the haplotype diversity (0.11) was the lowest of any

location sampled: not only are there very few haplotypes. all haplotypes are very closely

related suggesting that New Guinea sailfish may have been founded by relatively few

individuals. If the population were truly a founder population (as opposed to an artifact

of sampling error) as the low diversity and prevalence of a single haplotype suggest, one

might expect to detect a signal in microsatellite DNA in the form of heterozygosity that is

higher than expected (Comuet and Luikart. 1997; Garza and Williamson 2001).

In the Indian Ocean, significant geographic heterogeneity was detected between

the Kenya, Persian Gulf, and Australia collections. However, pairwise comparisons

indicate that the Australia and Kenya collections are not significantly different

(p=0.2048) while the Persian Gulf collection is distinct from each of the other collections

(p=0.0000), and although 34.55% of the variance (p=0.0000) was due to among-

collection variation, only 1.81% of the variance (p=0.12198) was due to variation among

collections when the Persian Gulf was excluded. The most common haplotype was

present in 90.5% of the Australia collection and 78.7% of the Kenya collection, but only

8.7% of the Persian Gulf collection. In addition, haplotype 4 was present in 21.7% of the

Persian Gulf collection, but was present in only 10.6% of the Kenya collection and was

absent in the Australia collection (Table 13) suggesting the possibility that the Persian

Gulf is an isolated population that has little contact with other Indian Ocean sailfish. In

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addition, Persian Gulf sailfish had the highest nucleotide diversity of any collection in the

Indo-Pacific. Nucleotide diversity was 0.00999 in Persian Gulf collection as compared

to 0.0018 for Australia and 0.0038 for Kenya due to the elevated frequency of haplotype

4 in the Persian Gulf and the fact that the Persian Gulf contained haplotypes that are not

closely related (Table 3: Fig 3. 7). A UPGMA tree of all sailfish locations based on

corrected mean nucleotide sequence divergence illustrates the tangential relationship of

the Persian Gulf sample to the remainder of the Indo- Pacific (Fig. 9). Thus far. tag

return data agree with the results of the genetic analysis. Tag return data show a seasonal

pattern of movement within the Gulf and to date, no sailfish tagged inside the Persian

Gulf have been recaptured outside the Gulf (John Hoolihan. Pers comm). For the

remaining Indian Ocean samples (KEN and AUS), no variance was attributable to

variation between samples, although both haplotypic and nucleotide sequence diversity

were much higher for the Kenyan samples. Unfortunately the Australian collection

consisted of only 21 individuals, so no firm conclusions could be drawn from the reduced

diversity as compared to the Kenyan sample without an examination of more samples

from this area.

When western Pacific collections were compared to both eastern Pacific and

Indian Ocean samples, western Pacific sailfish samples were found to be more closely

related to Indian Ocean samples than to east Pacific samples. In comparisons of Indian

and west Pacific populations, none (-7.28%) of the variance was due to variation between

groups (p=0.69772) while 0.86% of the variance was due to variation between eastern

and western Pacific samples (p=0.08584). Although the probabilities were not significant

in either case, they were much closer to significance in the east/west comparison. In

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addition, the minimum spanning network based on the RFLP data of Indo-Pacific

samples (Fig.6) as well as visual inspection of Table 2 indicated that some haplotypes

present in the Indo-west Pacific were absent in the eastern Pacific. In particular,

haplotype 5 occured in 7 west Pacific samples and 10 Indian samples, haplotvpe 11

occured in 4 west Pacific samples and 2 Indian samples, and haplotype 14 occured in 3

west Pacific samples and 1 Indian sample. Only haplotype 35 occured in the eastern

(n=l) and western (n=l) Pacific but was absent in the Indian. This inter-relationship

makes sense in light of the proximity of the Indian and western Pacific basins.

Overall, it is clear from the mtDNA data that sailfish do exhibit stock structure

both within and between Ocean basins. The next question then becomes, how much

variation is due to historical barriers to gene flow followed by present day contact, and

how much is attributable to a lack of contemporary gene flow and can these mechanisms

be discriminated? Nested clade analyses seem to suggest that sailfish have been affected

by periods of range fragmentation but there is also evidence of restricted gene flow with

some component of long distance dispersal. However, many of the clades in the nested

clade analysis did not show significant correlations. This may be due to the high level of

homoplasy (decreased resolution) generally present in RFLP data sets. An expanded

DNA sequence analysis would probably help to clarify results and further resolve the

forces driving the phylogeographic distribution of sailfish haplotypes.

Sequencing

The control region of the sailfish was found to be between 839 and 855 base pairs

in length, somewhat shorter than the lkb average seen in other vertebrates including the

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reported range for percids (908-1208; Faber and Stepian, 1997) rainbow trout (1003 bp;

Zaroyda et al., 1995), and Japanese flounder (1400bp; Saitoh et al., 2000). Although

length variation is common in other teleost fishes due to the insertion of tandem repeats

adjacent to the termination association sequence, these repeats appear to be missing in the

majority of sailfish. One exception appears to be a fish collected in Taiwan which had an

insertion of a second AATATAAGCATATA sequence from bases 58-71 (Appendix 1).

However because the sample was amplified and sequenced only once. Taq error cannot

be ruled out.

Although the genetic variation present in the Atlantic is distributed

homogeneously among samples, it is clear there are two distinct clades, one of which is

comprised of two major subclades. The estimated corrected mean nucleotide sequence

divergence of between clades based on the control region sequences is 5.56% and the

uncorrected estimate is 7.3%. However, correlating these divergence estimates with time

is precarious; several divergence rates have been suggested for teleost control regions and

it is clear that there is a fair amount of variation in mutation rates. For example, in

salmon and charr (Bematchez and Danzman, 1993; Zhu et al., 1994) the rate of evolution

of the tRNApro end of the control region is similar to the rate of 2%/million years

generally observed across the mitochondrial genome as a whole. In contrast, Donaldson

and Wilson (1999) calculated an average divergence rate for teleost control regions of

3.6% per million years based on amphi-Panamic geminates of snook and the tRNApro end

of the control region in butterflyfishes was estimated to evolve at rates of 15% to 38% per

million years (McMillian and Palumbi, 1997).

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A strong correlation has been noted in the control region between

transition/transversion ratios and the rate of control region evolution.

Transition/transversion ratios were found to be between 10:1 and 28:1 in the control

region of fishes with a high rate of control region evolution (defined as a rate of evolution

1 OX the rate observed in either mitochondrial protein coding genes or the whole

mitochondrial molecule, McMillian and Palumbi, 1997). The transition/transversion rate

of sailfish control regions in this study was found to be 35:1. which is extremely high.

Based on the high transition/transversion ratio of sailfish. it seems reasonable to assume

that the control region is evolving relatively rapidly and the 3.6% per million year

estimate seems tenable only as an extremely conservative low-end estimate. Using this

rate of divergence, it is estimated that the two sailfish clades diverged 1.3-1.75 million

years ago based on the corrected sequence divergence (Table 13). The two clades

contained within the Atlantic clade based on sequencing data had a corrected divergence

of 0.0201 +/-0.0042 and the estimated divergence times based on the 3.6%/million year

rate are 440,000-660,0000 million years.

Alternately, Alvarado estimated that the 5' end of the control region in swordfish

was evolving 6.45 times faster than the rest of the mitochondrial molecule, which was

assumed to be evolving at 2% per million years. Based on this 12.9% rate, divergence

times for the Atlantic and ubiquitous sailfish clades would be estimated at 370,000-

490,000 years ago and the separation between the two Atlantic clades would be estimated

at 124,000-186,000 years ago based on sequence data.

The presence of two major clades, one of which is unique to the Atlantic and the

other which is spread throughout the oceans has been noted in other large pelagic species

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including blue marlin, Makaira nigricans (Finnerty and Block, 1992; Graves and

McDowell, 1995; Buonaccorrsi et al., 2001), bigeye tuna, Thunnus obesus. (Alvarado-

Bremmer et al., 1998), and swordfish, Xiphias gladius, (Alvarado et al., 1995; Rosel and

Block, 1996) and has been attributed to Pleistocence glaciation which began around 0.8-

1 million years before present and reached the last glacial maximum approximately

18.000-22.000 years ago. RFLP studies of the entire mtDNA molecule in blue marlin

based on 356 individuals gave a 1.2% nucleotide sequence divergence between clades

(Graves and McDowell, 1995) suggesting that the separation of the two clades dates to

0.6 million years ago assuming that the 2%/million year divergence rate estimated by

Brown (1979) for mammalian mtDNA is valid for blue marlin.

Using a 6 i 2 bp portion of the cytochrome b gene Finnerty and Block (1992)

estimated that the sequence divergence between the two blue marlin clades was 1.6%.

Assuming a divergence rate of 0.5-1.0% /million years, they estimated that the two clades

seen in blue marlin diverged 1.5-3 million years ago. However, the rate of cytochrone b

sequence divergence has been estimated to be between 1% and 2.5% per million years in

vertebrates (Irwin et al., 1991). Using this range yields divergence estimates of 0.64-1.5

million years which agrees much more closely with the estimate of 0.6 million years

derived from whole molecule RFLP analysis.

For swordfish, the divergence between mtDNA clades was estimated to be 7.1%

on average for 280 bp of the hypervariable left domain of the control region and 1.1%

divergent for the whole mitochondrial molecule based of RFLP analysis. By assuming

that the control region was evolving 7.1/1.1 =6.45 X faster than the rest of the molecule,

which was assumed to be evolving at 2% per million years, Alvarado et al. (1995)

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estimated that the two clades diverged 500,000 ybp. which is in general agreement with

the 0.6 million years estimated from blue marlin RFLP haplotypes. This further suggests

that the 0.5-1% per million years rate used for swordfish cytochrome b is an

underestimate of the true divergence rate assuming that the presence of these clades was

caused by a common event, namely Pleistocene glaciation.

In the case of bigeve tuna, divergent clades were found to be approximately 5%

different based on combined RFLP and sequence analysis of the control region, however

no estimates of divergence time was attempted (Avarrado-Bremmer, et al., 1998).

Assuming a 7.1% rate of divergence implies that populations were separated 0.7 million

years ago. which also falls within the range of previous estimates. It has been

hypothesized that the presence of two clades in the Atlantic is the result of unidirectional

gene flow from the Indo-Pacific to the Atlantic mediated by the warm Agulhas current

flowing from the Indian Ocean along west coast of Africa to the Southeast Atlantic

(Alvarado Bremmer. 1995: Graves and McDowell, 1995: Buonaccorsi et al., 2000).

Although both RFLP analysis and sequencing reveal the presence of a third

clade, its placement is enigmatic. In the case of RFLP analysis, this clade appears to be

more closely related to and part of the ubiquitous clade while in the case of control region

sequences it seems to be a component of and more closely related to the Atlantic clade.

However, since the resolution of RFLP analysis is much lower than sequence analysis, it

seems more likely that the sequence analysis is correct. It seems plausible that sequential

rounds of isolation during Pleistocene glacial/interglacial cycles could have caused the

presence of this clade, which is closely related to the original Atlantic clade. In fact,

closer examination of the neighbor joining tree presented in Buonaccorsi et al., (2001)

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shows a similar distinct subclade in blue marlin. An analysis of several large pelagic

species using identical markers would help to obtain more accurate estimates of

divergence and clarify the evolutionary history of these species.

It is clear that sailfish exhibit stock structure based on mtDNA RFLP and

sequence data. In addition, these analyses indicate that the divergence between the

Atlantic and ubiquitous clade sequences is at least as great, if not greater than the

divergence between white and striped marlin. These results agree with results of studies

of other large pelagic fishes which carry a genetic imprint of Pleistocene glaciation

events. Although nested clade analyses have been useful for honing in on the

mechanisms responsible for population structure in other species, the relatively low

resolution of the RFLP data limited the conclusions that could be drawn from these

analyses. However, the limited conclusions suggest that contemporary sailfish stock

structure is a result of isolation by distance. Thus, while no appreciable stock structure

could be detected in the relatively small Atlantic basin, significant structure was detected

in the Indo-Pacific basin.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. I. I. Sty I, and Nei 1 I 0 0 0 0 0 0 0 0 0 0 0 r> 0 0 0 0 0 2 0 0 0 0 0 14 EER II, ///« / I, I 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 KEN ,1line 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 S 0 0 0 0 1 77 i 0 0 0 0 0 0 0 0 4 1 0 0 0 0 0 (> 0 0 0 0 z.0 00 0 0 0 2 0 0 0 0 0 WE r 0 D ili- 4 f> 4 9 1 17 TAW AUS 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 WE 14 ENC. > 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 t) 0 0 0 0 VNM 1 0 3 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 EE WE 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 12 8 CAB 1 1 1 0 0 ') 0 0 0 0 0 0 0 0 0 0 ECU 1 0 0 0 0 0 0 0 2 0 0 0 0 0 EE EE Z. 0 0 2 0 4 2 4 S3 MAZ 1 1 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 1 00 0 0 0 0 0 0 (J 0 0 1 0 1 1 0 (, 0 0 0 00 0 2 0 0 0 0 0 0 0 EA El’ 0 0 0 0 0 2 0 6 0 0 2 u 0 2 2 12 2 3 2 7 2 6 2 0 0 0 CI1A FAN

1 1 0 3 3 1 0 0 0 ') 0 0 EA 6 0 0 0 0 0 0 1 0 1 1 0 0 1 0 0 0 0 0 00 0 0 0 2 10 2 2 0 WA 1 0 1 0 0 1 1 0 1 0 3 1 9 5 0 0 2 0 0 0 0 0 0 0 0 0 0 0 4 1 2 0 02 0 2 0 0 WA 0 0 0 14 32 3 9 BRA VEN SEN 1 1 0 2 0 1 4 0 0 0 0 2 0 2 7 0 0 0 0 2 7 FLA 1 0 0 0 2 0 4 5 14 0 0 0 0 2 0 0 0 0 0 0 0 0 WA WA 2 0 2 5 4 0 0 2 2 0 Sum CAR 20 0 27 BAABA 2 0 0 DAABA 6 0 EABAA 3 BABAA 13 0 AACAA 3 0 ABDAB 2 ABAAA 2 AAEBA 2 AABBB ABDAA ABCAA 2 0 ABAAC CBAAC 8 AABAE 6 AABAC 3 ABBAA AACBC ADBAA 5 AAA DA 2AAA 0 AAABA 334 AABAA 91 ABABA 2 CBDAC 18 AC BAA AC AAAAA 44 1 AAABC AACBA AABBA 12 0 ID Hap Each letter in the haplotype represents a restriction enzyme in the following order: SAIL24 5 SAIL2 FLA; Brazil, BRA; Venezuela, VEN; Senegal, SEN; Ghana, CJHA; Panama, PAN; Ma/.atlan, Mexico, MAZ; Ecuador, ECU; SAIL23 SAIL22 SAIL26 SAIL27 SAIL21 SAIL28 SAIL19 SAIL20 SAIL18 SAIL10 SAIL16 SAIL17 SAIL14 SAIL15 5AIL13 SAIL01 SAIL02 SAIL03 SA1L09 SAIL11 SAIL12 Cabo San Lucas, Mexico, CAB; Vietnam, VNM; New Guinea, PNG; Taiwan, TAW; Australia, AUS; Kenya, KEN; Persian SAIL08 Table 1. Distribution ofcomposite haplotypesWestern based Atlantic,on RFLP WA;analysis eastern of theAtlantic, mitochondrial EA; eastern control Pacific, region. EP; western Pacific, WP; Indian, I; Caribbean, CAR; Florida, SAIL05 SAIL04 SAIL06 SAIL07 Gulf, PER.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. without prohibited reproduction Further owner. copyright the of permission with Reproduced < < < < < < < < < < < < < < < < < < < < < < < < < M < WQ W C Q W W W W Q C n M C aW K O T Q M W C n W M Q W W W W W Hap Sum CAR FLA BRA VEN SEN GHA RAN MAZ ECU CAB VNM RNG TAW AUS KEN RER ÔrttMn’TLO^â:ÔH(\n^rin^M35J'OHM(riv C M C N C S iC N C N JC N l* — * OOOOOOOOOOOOOOOOOCOOOOOOOrH , , , , , C U < U < Q < o < < c < u < o U a U U c U a U u U u < < < <

Table 2. Haplotypic diversity (A) and nucleotide diversity (7t) within samples of sailfish. Western Atlantic. WA: eastern Atlantic. EA: eastern Pacific. EP; western Pacific, WP: Indian, I: Caribbean. CAR: Florida. FLA: Brazil, BRA; Venezuela, VEN: Senegal. SEN; Ghana, GHA; Panama. PAN: Mazatlan. Mexico. MAZ: Ecuador. ECU; Cabo San Lucas, Mexico. CAB; Vietnam. \ rNM; New Guinea. PNG: Taiwan, TAW; Australia. AUS: Kenya. KEN: Persian Gulf. PER.

Coll. - Samp =Hap Haplotvpe Diversity (h) Nucleotide Diversity (rc) CAR (WA) 14 6 0.8132+/- 0.07374 0.017278 FLA (WA) 42 15 0.8571 +'- 0.04114 0.020909 BRA (WA) 93 22 0.8441 + -0.02868 0.020155 VEN (WA) 15 10 0.9429 +•'- 0.04027 0.025931 SEN (WA) 37 14 0.8664 +'- 0.03682 0.024051 GHA (WA) 93 20 0.S413 t '- 0.02292 0.020088 PAN (EP) 11 4 0.6000 ^ - 0.15391 0.010069 MAZ (EP) 51 7 0.3224 * - 0.08460 0.003517 ECU (EP) 60 6 0.2203 - - 0.07112 0.002436 CAB (EP) 27 j 0.2707 0.10457 0.003214 AUS (I) 21 j“S 0.1857 - - 0.11022 0.001864 KEN (I) 47 5 0.3728 - - 0.08581 0.003844 PER (I) 23 5 0.5968 - - 0.09839 0.009993 VNM (WP) 12 4 0.5606 - - 0.15401 0.007057 PNG (WP) 36 j-» 0.1095 - -0.07007 0.001949 TAW (WP) 65 8 0.4899 -r/- 0.07369 0.006299

Average 0.5559 0.00497 0.01 166 +/- 0.0000048

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Table 3. Analysis of geographic heterogeneity in frequency distributions of sailfsih samples using a Monte Carlo simulation with 10,000 replicates. P indicates the probability, based on repeated randomization, of encountering an X ' value as large as the one calculated for the original matrix. S.E. is the standard error. All populations were kept separate within geographic regions tested.

Overall Sample ______Calculated X2 p S.E. ______All populations 1508.90 0.0000 +/- 0.0000 Atlantic 138.79 0.0476 +/- 0.0021 Pacific 68.55 0.0167+/- 0.0013 Indian 64.88 0.0000 +/- 0.0000 Eastern Atlantic 29.70 0.1900 +/- 0.0039 Western Atlantic 26.76 0.3578 +/- 0.0048 Western Pacific 12.50 0.0796 +/- 0.0027 Eastern Pacific 13.47 0.5064 ^/- 0.0050

Indian Ocean Sample Calculated X2 p S.E. AUS KEN 6.85 0.2048 +/- 0.0040 AUS PER 36.75 0.0000 +/- 0.0000 KEN PER 42.13 0.0000 +/- 0.0000

Atlantic Ocean Sample Calculated X2 p S.E Atlantic 138.79 0.0476 +/- 0.0021 Eastern Atlantic 29.70 0.1900 +/- 0.0039 Western Atlantic 26.76 0.3578 +/- 0.0048 FLA/BRA 26.76 0.3578 +./- 0.0048 SEN/GHA 29.70 0.1900 +./- 0.0039 EAST/WEST 48.05 0.0589 +/- 0.0024

Pacific Ocean Sample Calculated X2 p S.E. ECU/CAB 4.12 0.6467 +/- 0.0048 ECU/MAZ 5.25 0.7323 +/- 0.0044 MAZ/CAB 9.02 0.2157+/- 0.0041 TAW/PNG 12.50 0.0796 +/- 0.0027 East/West 27.22 0.0005 +/- 0.0002

Indo west Pacific Sample Calculated X2 p S.E. IWP (Gulf) 0.0000+/-0.0000 IWP (no Gulf) 0.2312+/-0.0042

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. si FLA FLA BRA SEN G1IA MAZ ECU CAB AUS KIN P1R PNG KEN KEN 0.00000PER 0.00000 0.00000 0.00000 0.02545 PNG 0.00000 0.00000 0.03455 0.17875 0.00000 0.25345 0.00000 0.00000 0.00000 0.00000 0.000000.00000 0.00000 0.00000 0.00000 0.34225 0.49780 0.06795 0.46355 0.00000 0.06805 0.00000 AUS 0.00000 0.00000 0.00020 0.00005 0.85450 0.78675 0 .15055 TAW 0.00000 0.00000 0.00000 0.00000 0.02670 0.01060 0.16100 0.50070 0.88720 0.00000 0.09480 MAZ MAZ 0.00000 ECU 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.75110 BRA BRA SEN 0.36535 0.23010 0.12110 CAB 0.00000 0.00000 0.00000 0.00000 0.32470 0.60345 GHA GHA 0.18405 0.34300 0.19080 analysis ofsailfish. Probabilities are based on 10,000 permutations ofthe data. Table 4. Probability ofsignificance for exact tests ofpopulation differentiation using pairwise comparisons based on mtDNA RFLP

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Table 5. Hierarchical analysis of molecular variance (AMOVA) of sailfish mtDNA RFLP data. Distance method used was pairwise differences with 10,000 permutations. 'Oceans' refers to ocean of origin of collections. 'Regions' refers to thr geographic region of origin: western Atlantic, WA; eastern Atlantic, EA; eastern Pacific. EP: western Pacific, WP; Indian. I. 'Collections' refers to all the samples taken from a specific geographic location within a region.

Structure Tested Variance Component F-statistic Percent Variation p - value Collections grouped by Ocean Among oceans 0.30484 Va FCT: 0.32527 32.53 0.00000 Among colls within oceans 0.01738 Vb FSC: 0.02749 1.85 0.00020 Within collections 0.61496 Vc FST: 0.33799 66.52 0.00010

Indian Among collections 0.13202 Va FST: 0.3429 34.33 0.00000 Within collections 0.25255 Vb 65.67

Pacific Ocean Among collections 0.00476 Va FST: 0.02331 -i.jj 0.00149 Within collections 0.19938 Vb 97.67

Atlantic Ocean Among collections 0.00054 Va FST: 0.00049 0.05 0.40050 Within collections 1.10973 Vb 99.95

East/West Atlantic Among regions 0.0274 Va FCT: 0.00246 0.25 0.33724 Among colls within regions -0.00557 Vb FSC:-0.00501 -0.50 0.66764 Within collections 1.11648 Vc FST:-0.00246 100.25 0.67840

East/West Pacific .Among regions 0.00258 Va FCT: 0.01387 1.39 0.10050 .Among colls within regions 0.00298 Vb FSC: 0.01474 1.47 0.04198 Within collections 0.19938 Vc FST: 0.02841 97.16 0.00178

Indian minus PER Among collections 0.00311 Va FST 0.01805 1.81 0.12198 Within collections 0.16941 Vb 98.19

Indian/West Pacific Among regions -0.02208 Va FCT -0.07284 -7.28 0.69772 Among colls within regions 0.06853 Vb FSC 0.21070 22.61 0.00000 Within collections 0.25672 Vc FST 0.15321 84.68 0.00000

Indo-West Pacific/East Pacific Among regions -0.00136 Va FCT-0.00537 -0.54 0.22505 Among colls within regions 0.03557 Vb FSC 0.13995 14.07 0.00000 Within collections 0.21861 Vc FST 0.13533 86.47 0.00000

*note that FSTis much lower in the Atlantic even though there are 2 clades that are distantly related suggesting even distribution of clades across the Atlantic.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 2.2% 97.8% 0% Pacific5.98% Indian 93.62% 0% 5.31% 94.69% 0% 6.52% 0% 92.75% 16.33% Atlantic E Pacific W Pacific 60.54% 23.13% 16.92% 55.38% 27.69% 15.85% 19.51% E. Atlantic W. Atlantic 64.63% Clade 1 (Ubiqu1 1) 3 3 (Atl) 2 (Ubiqu 2) Tabic 6. Frequency distribution ofthe major clades identified by RFLP analysis ol'sailfsih mtDNA.

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Table 7. (a) Diversity of within and between major clades based on mtDNA RFLP data. Above diagonal: Mean nucleotide sequence divergence between collections. Below diagonal, corrected mean nucleotide sequence divergence between collections. Diagonal: Nucleotide diversity within collections, (b) Haplotypic diversity ( h ) of clades

(a) Ubiqu 1 Ubiqu 2 Atlantic Ubiqu. 1 0.00956 0.02350 0.04350 Ubiqu 2 0.01546 0.00652 0.04214 Atlantic 0.02811 0.02826 0.02122

Ubiqu (all) Atlantic Ubiqu (all) 0.01246 0.04244 Atlantic 0.02555 0.02122

(b)

Haplotypic diversity ( h) of clades Ubiqu 0.6713+/-0.0196 Atlantic 0.8476 +/- 0.0426

Ubiqu.(l) 0.5541 +/- 0.0503 Ubiqu (2) 0.4920 +/- 0.0275 Atlantic 0.8476 +/-0.0426

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Table 8. Nucleotide sequence diversity estimates based on sequencing of 1636 base pairs of sailfish mitochondrial DNA including the control region. K. refers to the average number of nucleotide differences between sequences and (th ) indicates thehe average number of nucleotide differences per site between two sequences. Numbers in parentheses indicate the number of sequences used in the calculation.

SAMPLE k (*) Overall 36.56 0.033 (58) Atlantic 30.46 0.027 (38) Indo-Pacific 10.43 0.009 (20) Atlantic Clade 17.91 0.016 (31) Ubiqu Clade 11.20 0.010 (27) Ubiqu in Atl 14.23 0.009 (7)

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Table 9. Sequence divergence estimates based on DNA sequence analysis of 1636 base pairs of sailfish mitochondrial DNA including the control region. K is the average number of nucleotide differences between sequences. Dxy the average number of nucleotide substitutions per site between clades, and FD is the number of fixed differences between groups of sequences.

Fst______k______Dxv ______FD Atlantic/Indo-Pacific 0.580 48.75 0.033 0 Indo-Pacific/ Atl. Ubiq 0.0018 12.375 0.010 0 Atlantic Clade/ Atl Ubiqu 0.726 59.484 0.038 25 Atlantic Clade/ Indo-Pacific 0.752 57.023 0.051 19

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Table 10. Average nucleotide usage for the mitochondrial regions amplified and sequenced in sailfish. Values for the individual nucleotides are in percent. Total refers to the average number of base pairs examined for each region.

Reeion T C A G Total Cytb 28.0 31.6 23.0 17.4 239.1 tRNA1^ prt> 28.2 25.4 28.6 17.9 141.8 Dloop 29.2 22.7 32.2 15.9 840.4 tRNAphc 19.2 22.0 32.4 26.4 67.7 12sRNA 21.8 25.2 29.3 23.7 300.7 Overall 27.1 24.7 29.9 18.3 1589.7

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Table 11. Position in sequence, state in respective clade (A, G, C, or T), type of change (Tr for transition. Tv for transversion), location of change, and whether or not change was assayed by the RJFLP analysis for the 19 fixed differences between Atlantic and ubiquitous clade sequences.

C l a d e Su r v e y e d NO Pos. UBIO. A t l .T ype L o c a t io n WITH 1 284 G A Tr tRNAThr N 2 463 C T Tr D-loop N 3 471 C T Tr D-loop N 4 503 A G Tr D-Ioop N 5 556 T C Tr D-loop N 6 562 G A Tr D-loop N 7 635 G A Tr D-loop N 8 655 G A Tr D-loop N 9 659 C T Tr D-loop N 10 767 A G Tr D-loop N 11 768 G A Tr D-loop N 12 809 G A Tr D-loop N 13 821 C T Tr D-loop N 14 891 G A Tr D-loop Y * 1 15 895 G A Tr D-loop N 16 943 T C Tr D-loop N 17 1003 A G Tr D-loop Y * 2 18 1214 C T Tr D-loop N 19 1027 GAP NO Gap D-loop N

*' If Neil restriction site is present, sample belongs to the ubiquitous clade *“ If Ddel restriction site is present, sample belongs to the Atlantic clade

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Table 12. Diversity within and Divergence between Atlantic and ubiquitous sailfish clades and White (Atlantic) and Striped (Pacific) marlin based on control region sequences using Tamura-Nei distances with no gamma correction. Standard errors were estimated using 1000 bootstrap resamplings and are indicated in parentheses.

Overall Diversity Sailfish 0.0461 (0.0047) White/Striped 0.0560 (0.0053)

Within group diversity Atlantic Ubiquitous (Pacific) Sailfish 0.0217(0.0027) 0.0135(0.0015) White/Striped 0.0213 (0.0030) 0.0503 (0.0051)

Between Group Divergence (uncorrected) Sailfish 0.0732 (0.0085) White/Striped 0.0756 (0.0081)

Net Divergence (corrected) Sailfish 0.0556 (0.0077) White/Striped 0.0399 (0.0062)

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 16 0.0(88) O.OOOO 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 O.OOOO 0.0000 0.0000 0.(888) 0.0000 0.0870 0.04.15 0.2174 0.6087 0.0000 O.OOOO 0.0000 1 1 15 0.(888) 0.0000 0.(888) 0.0000 0.(888) 0.0000 O.OOOO O.OOOO 0.0000 0.0000 0.0000 0.0426 .OO0.0000O.OOOO 0.0000 0.0000 .OOO.OOOO O.OOOO 0.00(8) 0.0213 0.0000 0.0000 0.(888) 0.0000 0.0000 0.0000 0.0000 0.0000 0.7872 0.(888) 0.0000 0.0000 14 1 0.0000 0.0000 0.0000 0.(888) 0.0000 0.0000 0.0000 0.01)00 0.0476 0.0000 0.0000 0.1064 0.0000 0.0000 1.1 0.0000 0.0000 0.0000 0.(888) 0.0154 0.(888) 0.0000 0.0000 0.0000 0.0000 0.0462 0.0000 WP 0.0615 0.7077 0.9048 0.0000 0.0(88) 0.0000 0.0000 0.0923 0.0308 0.0000 0.0426 0.0000 0.0000 0.0000 12 0.0000 0.0000 0.0278 0.0000 0.0000 0.0000 0.0(88) >N(i >N(i TAW A lls KEN PER II 0.0000 0.0000 0.(888) 0.0000 0.0000 0.0000 0.0000 0.0000 0.(888) 0.0000 .OO0.0(88)O.OOOO O.OOOO O.OOOO 0.(888) 0.0000 0.0000 0.0000 0.00(8) 0.0000 WP WP 0.0000 0.0000 0 (888) 0.(888) 0.0000 0.0000 0.6667 0.9444 0.0000 0.0000 O.OOOO 0.0000 0.0833 0.0000 0.0000 0.00000.0000 0.0000 0.0000 NAM EP EP EP 0.0000 0.0167 0.0000 0.0000 0.(888) O.OOOO 0.18)00 0.18)00 0.0000 0.0000 0.0(88) 0.0000 0.(888) 0.0000 O.OOOO 0.0000 O.OOOO 0.0000 0.0000 0.0(88) 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.(888) 0.0392 0.0000 0.0392 0.033.1 0.0392 0.0167 0.0000 0.0000 O.OOOO O.OOOO O.OOOO 0.0196 0.0.1.13 0.1667 0.0000 0.0000 El* 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.(888) 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.(888) 0.0(88) 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.00(8) 0.0000 0.0000 0.00000.0000 0.0000 0.0000 0.0000 0.0000 O.OOOO 0.0000 0.0000 0.0000 O.OOOO 0.0000 0.6364 0.8235 0.88.13 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 E.A 0.0000 0.1818 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0108 0.0000 0.0000 0.0000 0.0000 0.0000 tillA PAN MAZ ECU C 0.0000 0.0215 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0278 0.1290 0.0909 0.0000 0.0000 O.OOOO O.OOOO 0.0000 O.OOOO 0.0000 0.0108 0.0645 0.0215 0.0215 0.2796 0.0000 0.0000 0.0000 0.0000 0.0000 0.2473 0.0000 0.0000 0.0000 0.0000 0.0000 0.00(8) 0.(888) 0.0000 0.08.1.1 0.0000 0.0.108 0.0000 0.0215 0.0000 0.0000 0.0645 0.0215 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0541 0.0000 0.0000 0.0000 0.0811 0.0270 0.0270 0.2432 0.2703 0.0000 0.0000 0.0000 0.0000 4 5 6 7 8 9 WA EA VEN SEN 0.0000 0.0000 0.0000 0.0270 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0667 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0667 0.0270 0.0108 0.0000 0.0000 0.133.1 0.0000 0.0000 0.0000 0.0000 0.00(H) 0.0000 0.0000 0.0667 0.0000 0.0000 0.0000 0.0909 3 BRA 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0108 0.0108 0.0108 0.0000 0.0000 0.0215 0.0000 0.0000 0.0000 0.01MM) 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.(888) 0.0000 0.0215 0.0968 0.0108 0.0215 0.0000 0.00000.0000 0.0270 0.0000 0.0108 0.(H)00 0.0000 0.0000 0,0188) 0.0000 0.0)96 0.0000 0.0167 0.0000 0.(888) 0.0000 0.0000 0.0000 0.0000 O.OOOO 0.0000 0.1505 0.1333 0.0215 0.0538 0.0000 0.0541 0.04.10 0.0667 0.0270 0.0000 0.0000 0.0.123 0.0667 0.0753 0.1333 WA WA 0.0000 0.0000 0.0000 0.0000 0.0238 0.0000 0.0000 0.0000 0.0000 0.0000 0.0238 0.0238 0.0000 0.0476 0.0108 0.0000 0.0000 0.3333 0.3441 0.2000 0.0000 0.0000 0.0476 0.0108 0.0000 0.0811 0.0000 1 2 WA 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0,0000 0.0000 0.0000 0.0000 0.0476 0.0000 0.0476 0.0000 0.0000 0.0000 0.0000 0.0000 0.0238 0.0108 0.0000 0.0000 0.0108 0.0000 0.0000 0.0000 0.0000 0.0000 0,0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.3571 0.2857 0.1667 0.0000 0.0000 0.0238 0.0000 0.0000 0,1429 AACAC CBDAA C'BCAA ABC’AA BAABA CABAA A BA A A A BA A ABAAC 0.0000 DA A BA A DA ABDAA ABABA 0.0000 AABAC 0.0000 ACBAA ABBA A ABBA A DBA A DBA A 0.0000 AABBA AABAE Hup CAR FLA CBAAC AAAHA C'BDAC 0.0000 0.0476 AADAA Table 13. Haplotype frequencies across all sailfish collections. SAIL34 AABBC SAIL35 AADBA SAIL36 SA1L33 SAIL32 CBCAC SA 11.30 SA CACAC 11.31 SA SAIL29 SAIL26 AABBBSAIL27 AAADA 0.0000 SAIL2H SAIL23 ABDABSAIL24 AAEBA SAIL25 AAC'AA 0.0714 SAIL22 SAILI9 SAIL20 SAIL2I SAILI5 EABAA SAIL17 SAILI8 SAILI6 SAILI4 AACBC 0.0000 0.0000 0.0000 0.0000 SAIL08 BABAASAIL12 0.0000SAILI3 0.0000 SAIL 11 SAIL ID SAIL06 SAIL07 SAIL09 SAIL04 AACBASAIL05 AAABC 0.0000 0.0000 SAILIO SA 11.02 SA SAILOI SAIL03 AAAAA 0.0714 0.0952

SAIL37 AABAB 0.0015 0.0000 0.0000 s 0.0000 3 5 3 s = 3 = 5 = =’ = = 5 3 = 3 = 5 5 = 3 = S ■ = = 3 = = 3 = ;=. s ; i i i = i O l O i O l O i l SAIL38 AADAA 0.0015 0.0000 0.0000 0.0108 o * -= = — = = = = -* -■ — O SAIL39 AAACA 0.0015 0.0000 0.0000 0.0000

SAIL40 CAAAA 0.0015 0.0000 0.0000 0.0108 SAIL'D GABAA 0.0015 0.0000 0.0000 0,0000 s s s VIVI VI QUC < < < 2 2 2 2 < 2 < 3 < 3 3 3 3 3 3 3 — (Ni^iTrirtsr-oess < UU < s 3 5 s 3 5 s s s 3 3 s' 3 s' s' s' s' s' s' s' 3 5 5 5 5 O5 5 O o' o' O o o'o = = = = = 3 ! 1 ;3 5 = = 5 5 = = 5

U U < Q < O u o < < < < s s' s s © O 12 = = = n = = — = = — = = — = = — s » s ; s s s 2 : VIVI L-< < Q < a a U U 5 3 «/i in < < s s s s . „ S 2 s S s = s S s 2 S „ . < < == 3 3 5 = — i v: vi a a < ca < < < < ea < s s 11 m s s =’ = =’ = : = = sc = = =: 2 =: — = = s = sg = =: ^ = •/% < <

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Figure 1. Geographic distribution of haplotypic diversity within sailfsih collections.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. %

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Figure 2. UPGMA tree based on corrected nucleotide sequence divergence between sailfish RFLP haplotypes. 1 indicates the "ubiquitous 1" clade, 2 indicates the "ubiquitous 2" clade and 3 indicates the "Atlantic" clade. Numbers on the tips of trees correspond to the haplotype numbers in table 1. WA, Western Atlantic; EA, eastern Atlantic; EP eastern Pacific; WP, western Pacific; I, Indian.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Ocean inol ------sail2 A (09) J ------sail42 EA (1) ------sai!37 EA(1) r '------sail41 EA(1) ------sail 13 A (5) ------sail 12 A (5) !_ ------saillO WA (6) ______sailS A (13) ______sail 15 A (3) ______sail7 EA (12) , ------sail26 EP (2) |______sail 16 A (3) ------sail34 P (2) ------sail3 A (31) P (9) I (2) ,------sail38 WA (1) j ------sail25 WA (3) j | |------sail29 WA (2) ------saiWO WA (1) '------sail46 EA(1) ------sail50 WA (1) ------sail27 EP (2) I------sail5 A (3) WP (7) 1(10) (5PER) . j 1------sail47 I (1XPER) J '------sail48 WP(1) !______i------sail4 P (11) I (16) (14PER) 1------sail 14 WP (3) I (1) (1PER) |------sail24 WA(2) 1------sail52 WA (1) ^ _ j ------sail35 1(1) 1------sail51 WA (1) '------sail 18 EP (2) ------sail39 1(1) — ------saiH 1 WP (4) I (2) j ------sail49 EA(1) \ i------saiH A (60) P (213) I (50) 1------sail20 EP (2) i ______sail28 WA (2) ______sail31 WA (2) ______sail32 A (2) ------sail53 WA (1) ______sail30 EA (2) ------sail36 EA (1) ------sail43 EA (1) ^ _ l ------sail6 A (18) ------,------sail9 A (8) 1 ------sail 19 WA (2) ' sail44 EA(1) ______------sa«22 WA(2) ------sail54 WA (1) ______sail 17 EA (2) ------sail23 WA (2) |_ _ j ------sail21 EA (2) ------sail33 EA(2) ------sai!45 EA (1) 0.02 0.01 0.01 0.00 0.00

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Figure 3. UPGMA tree based on the control region sequence of 58 sailfish using a Tamura-Nei distance. WA. Western Atlantic: EA. eastern Atlantic; EP eastern Pacific; WP. western Pacific; I. Indian.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. j < s l-w a

A (RFLP Atiantic clade)

"WA

-EA j WA ri -EA

A (RFLP Ubiquitous clade 1) -EA

"WP

"WA

WA WA

EP P (RFLP Ubiquitous rEP TEP clade 2)

0.03 0.03 0.02 0.02 0.01 0.01 0.00 0.00

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Figure 4. Minimum spanning network and nesting scheme of Indo-Pacific data based on RFLP haplotvpes. WA, Western Atlantic: EA. eastern Atlantic: EP eastern Pacific; WP. western Pacific; I. Indian. MZ. Mexico; EC. Ecuador; PG. Persian Gulf: PN. Papua New Guinea; TW. Taiwan; KN, Kenya; PA. Panama; AU. Australia. NM. Vietnam.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. •©

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Figure 5. Minimum spanning tree of the 54 haplotypes found in the RFLP analysis of the mitochondrial D-loop region of sailfish. Caribbean, CAR: Florida, FLA; Brazil. BRA: Venezuela. VEN: Senegal. SEN: Ghana, GHA: Panama, PAN; Mazatlan, Mexico. MAZ; Ecuador. ECU: Cabo San Lucas, Mexico. CAB: Vietnam. VNM; New Guinea. PNG; Taiwan, TAW; Australia. AUS: Kenya. KEN: Persian Gulf. PER.

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Figure 6. Nesting scheme used for sailfish RFLP haplotypes in the nested clade analysis. Numbers coincide with the the haplotype numbers in table 1.

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r r

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 7. UPGMA tree based on corrected mean nucleotide sequence divergence betw een sailfish collections calculated from RFLP data.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. AUS PNG ECU MAZ MEX PAN NAM KEN TAW PER FLA SEN BRA CAR VEN GHA —I------1------1------1 0.003 0.002 0.001 0.000

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 106 | | 7 9 | 6 3 ) 7 9 ] 7 9 ] 7 8 1 7 8 | 7 9 1 7 9 ) 4 6 ] 7 9 ) 7 9 | 7 9 ] 7 9 ) 7 9 ) T9) 7 8 ] 7 9 1 7 9 1 7 9 ) 7 9 ) 7 9 | 7 9 ] 7 9 1 7 9 1 7 9 ) 7 9 ] 7 9 1 7 8 ] 0 7 9 | 7 9 1 7 9 ) 8 0 1 7 0 6 0 AACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG 3 0 4 0 9 0 CCTTCATACCTCTAAACAGCGAGGCCTAACCTTMCGACCCCTAACCCAGTTCCTATTCTG CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAAOCCAGTTCCTATTCTG CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTADCCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCDTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCOGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCC'I’AACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTGCCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG ------•CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGArcCCTAACCCAGTTCCTATTCTG■CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG•CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCtTAACCCAGTTCCTATTCTG■CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG■CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG•CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCGTAACCCAGTTCCTATTCTG•CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG ■CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG■CCTTCATACCTCTAAACAGCGAGGCCTAACCTTCCGACCCCTAACCCAGTTCCTATTCTG 20

10 - ► b C y t C A T . TACTAATAGTGGTCCC-TACTAATAGTGGT AT•TACTAATAGTGGTCCCCAT- CCC- AT - TACTAATAGTGGTCCCCAT■ TACTAATAGTGGTCCCCAT-TACTAATAGTGGTCCCCAT - TACTAATAGTGGTCCCCAT-TACTAATAGTGGTCCCCAT- TACTAATAGTGGTCCCCAT- TACTAATAGTGGTCCCCAT-TACTAATAGTGGTCCCCAT• TACTAATAGTGGTCCCCAT TACTAATAGTGGTCCCCAT- - TAHTAATAGTGGTCCC-AT- TACTAATAGTGGTCCCCAT-TACTAATAGTGGTCBCCAT- TACTAATAGTGGTCCCCAT-TACTAATAGTGGTCCCCAT- TACTAATAGTGGTCCCCAT TACTAATAGTGGTCCCCAT- - TACTAATAGTGGTCCCCAT-TACTAATAGTGGTCCCCAT TACTAATAGTGGTCCCCAT- - TACTAATAGTGGTCCCCAT - TACTAATAGTGGTCCC-AT- TACTAATAGTGGTCCCCAT-TACTAATAGTGGTCCCCAT- TACTAATAGTGGTCCCCAT- TACTAATAGTGGTCCCCAT- Appendix I. Sequences of58 sailfish samples. Regions, restriction sites surveyed with RFLP, and fixed differences (fd) between cladcs are indicated. Different gene regions surveyed are delimited. 1 DAMPIER93#1O a m 9 3 # 2 Dam pier93tt4 BRAZIL93D29B raz iB 193H razi193042 37 B R A 9 5B 1 R A 9 9 0 3 B R A 9 5 31 P N G 9 9P 1 N G 9 9 _ 0 3 B R O 9 2 _ 0BRAZIL93D20 8 ERAZIL93#25B r a 9 3 _ 2 8 B raz iB R ]93 A Z 4 I6 LK 9B 3 # r a4 9 9 3 3 1 E C U 9 7 2 2 E C U 9 7 2 5 E C U 9 7 4 7 M a z 9 7 # 8 T A I 1 9 8T A I 7 1 9 8Tai2_98f(22 2 4 T a i 2 _ 9 8 K 4 1 C A B 9 4 2 3 E C U 9 7 0 2 E C U 9 7 3 7 M A Z 9 7 H 1 M a z 9 7 # 2 C A B 9 2 0 2

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E- C E- < C C E- E- < 0 < C 0 C 0 E- - C C < < 0 C 0 0> - r 0 0 C e-1 0 0 E-* - c < 0 0 0 0 0 0 0 m m m m m m m m 112 [315] [315] [317] [316| [316] [317] [317] [317] 1316) (316) [317] [315] [317] [317| [316| |317| [3171 [3171 [176] 1317] [317] 1317] [317] [317] [316] [317] [316] [314] [317] [317] 1318) I . 3 2 0 | H l R N A P ro g 3 1 0 3 0 0 2 9 0 FL> 2 8 0 2 7 0 2 6 0 I Ihjo 2 5 0 3CACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCCTCCCTACTGC GCACTAGTAGCTCAGTA'l’CAGAGCGCCGGTCT'rGTAAACCGGATGCCGGAG-TTAAAT'l'CGTCGGTACTGCl GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCGGGATGCCGGAGGTTAAATTGCTCCCTACTGC GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCCTCCCTACTGtiGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAACCGGATGCCGGAGGTTAAATTCCTCCCTACTGrIGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCC’GGAG-TTAAATTCGTCGCTACTGC'IGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAACGGGATGCCGGAGGTTAAATTCCTCCr'TACTGrl GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAACCGGATGCCGGAGGTTAAATTCCTCCCTACTGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAACCGGATGCrr;t;AGGTTAAAT"l'CrTCCCTACTG(GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAACCGGATGCCGGAGGTTAAATTOCTC<’(TACTG(..lGCACTAOTAGCTCAGTATCAGAGCGCCGGTCTTGTAAACCGGATGCCOOAGOTTAAATTCCTCCCTACTGCl GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCrGGATGCCGGAGGTTAAATTCGTCCCTACTGclGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAG-TTAAATTCCTGCCTACTGdGCACTAGTAGCTCAGTATCAGAGrGCCGGTCTTGTAAGCGGGATGCCGGAGGTTAAATTrGTCCCTACTGC GCACTAGTAGCTCAGTATCAGAGCGOCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCCTCCCTACTGCl GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCCTCCCTACTGClGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGGCGGATGrCGGAGGTTAAATTGCTCCCTACTGCl GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCC'l’CCCTACTGCiGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAOGTTAAATTCCTrcCTACTGrJGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCCTCCCTACTGCGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCCTCCCTACTGCl GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCCTCCCTACTGtlGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCCTCCCTACTGrGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCCTCCCTACTGCJGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAG-TTAAATTCCTCCCTACTGC GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAG-TTAAATTCCTCCCTACTGCI GCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTOTAAGCCGGATGCCGCAGGTTAAATTCCTCCCTACTGdGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGCCGGATGCCGGAGGTTAAATTCOTCCCTACTGd TGCACTAGTAGCTCAGTATCAGAGCGCCGGTCTTGTAAGOCGGATGCCGGAG-TTAAATTCCTCCCTACTGCl t.RN AThr GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT GAGCCT DAMPIER93R1 Dam93j)2Dam pier93tt4 GAGCC'l BRAZIL93D29B r a z i 1 9 3 3 ft 7 BRAZIL93M4B 9 r a 9 3 3 1 BRAZ1L93II25B r a 9 3 2 8 Braz i 193B 4 2 ft razil93t)46 GAGCCT B R 0 9 2 BRAZIL93H20 0 8 P N G 9 9 1 P N G 9 9 0 3 Tai2 981141 GAGCCT T A I 1 9 8 2Tai2 4 981122 E c u 4 7 F T A I 1 9 8 7 E C U 9 7 2E 2 C U 9 7 2E 5 c 9 7 tt 3 7 M A Z 97H 1 M a z 9 7 i)8 M a z 9 7 # 2 C a b o 9 2 #C 2 A B 0 9 4 H 2 3 E c u 9 7 # 2

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 3. GENETIC STOCK STRUCTURE OF THE SAILFISH. ISTIOPHORUS PLATYPTERUS , BASED ON MICROSATELLITE DNA MARKERS

~~149~~

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~~INTRODUCTION~~

~~The large number of alleles and highly polymorphic nature of microsatellites have~~

~~made them useful for the study of population genetic structure in marine fishes (Shaklee~~

~~and Bentzen, 1998). Recently microsatellites have been used to investigate the stock~~

~~structure in other highly migratory species including bluefin tuna (Thunmis thynnus:~~

~~Broughton and Gold. 1997; Tagaki et al., 1999; McDowell et al., 2002). and yellowfin~~

~~tuna (Thunmis albacares) (Appleyard et al.. 2001). In addition microsatellite analysis has~~

~~been useful in examining the population genetic structure of istiophorid and xiphiid~~

~~billfishes including the blue marlin, Makaira nigricans, (Buonacccorsi et al., 2001), and~~

~~swordfish, Xiphias gladius (Reeb et al., 2000).~~

~~Microsatellites, also known as VNTRs (variable number of tandem repeats) or~~

~~SSRs (simple sequence repeats) are short stretches of DNA containing tandem repeats of~~

~~1 -6 base pairs in length. These repeats have been found to recur up to 100 times in a~~

~~single uninterrupted stretch, although alleles rarely exceed 60 repeat units (Goldstein and~~

~~Pollock, 1997). Microsatellites are codominant markers that are inherited in Mendelian~~

~~fashion and they are generally considered to be selectively neutral (Weber and Wong,~~

~~1993). They are distributed throughout the eukaryotic genome and the most commonly~~

~~studied microsatellites are either di-, tri-, or tetranucleotide repeats. In general, repeats~~

~~fall into one of three repeat classes; perfect, compound, or interrupted. Perfect repeats~~

~~are composed of stretches of a single uninterrupted repeat while interrupted repeats have~~

~~one or more short sections of intervening sequence inserted within the stretch of repeats.~~

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~~Compound microsatellites are composed of two or more repeat motifs strung~~

~~together end to end (Jame and Lagoda, 1996). In general, interrupted microsatellites tend~~

~~to be less polymorphic than perfect repeats and longer stretches of repeats seem to be~~

~~more polymorphic than shorter stretches. Point mutations and insertions/deletions of less~~

~~than one repeat unit, while they do occur, are generally infrequent and are often~~

~~impossible to detect without sequencing (DiReinzo et al., 1994; Estoup, et al., 1995;~~

~~Garza and Fremmer. 1996).~~

~~Sev eral studies have attempted to estimate the relative mutation rates of~~

~~microsatellite repeat classes. Weber and Wong (1993) estimated that the mutation rate of~~

~~tetranucleotide repeats was four times faster than the rate for di-nucleotide repeats based~~

~~on direct observation. However, Chakraborty et al. (1997) estimated that di-nucleotide~~

~~repeats have mutation rates 1.5-2 times higher than tetranucleotide repeats while the~~

~~mutation rates of tri-nucleotide repeats are intermediate. This conclusion was based on~~

~~evaluation of published data sets under the assumption that within-population variance in~~

~~repeat size is proportional to the product of the mutation rate and effective population~~

~~size.~~

~~Because they are distributed throughout the genome and have a high mutation rate~~

~~(1 O'5-lO0 mutations per locus per generation, Weber and Wong, 1993) microsatellites~~

~~have been used extensively as genetic markers in mapping studies, population genetic~~

~~analyses, forensics, and assignment testing (Jame 1996, Goldstein. 1997). Microsatellites~~

~~do, however, have several drawbacks. One shortcoming of microsatellites is the presence~~

~~of null alleles, defined as an allele that fails to amplify, usually due to a mutation(s) in the~~

~~primer binding site. The occurrence of null alleles is generally assessed by the presence~~

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~~of heterozygote deficiencies such that allele frequencies are inconsistent with the~~

~~expectations of Hardy-Weinburg equilibrium. It has been estimated that null alleles~~

~~occur in approximately 15-25% of microsatellite loci (Jorde, 2000). A second, more~~

~~pervasive problem with microsatellites is homoplasy: the presence of alleles that are~~

~~identical in state rather than identical by descent. Homoplasy is especially problematic in~~

~~microsatellites because they have a rapid mutation rate and because they most often~~

~~mutate by one repeat unit. Since homoplasy can lead to an underestimate of divergence,~~

~~understanding the most appropriate mutational model is critical to developing accurate~~

~~statistics for use with microsatellites.~~

~~To this end. the mechanisms responsible for the genesis and evolution of~~

~~microsatellites have been investigated extensively. Slipped-strand mispairing (SSM) is~~

~~the most widely accepted model (Levinson and Gutman, 1987). Under the SSM model~~

~~of microsatellite formation, chance mutations are required to produce an initial tandem~~

~~repeat which subsequently leads to strand slippage, a concept which has been supported~~

~~by studies in primates (Messier et al., 1996). However, Taylor and Breden (2000)~~

~~recently proposed an alternate mechanism for microsatellite formation w hereby SSM at~~

~~noncontiguous repeats leads to the formation of novel microsatellites. Conversely, it is~~

~~hypothesized that a two-step process causes microsatellite "death"; the microsatellite~~

~~repeat first becomes imperfect via a point mutation which prevents slipped-strand~~

~~mispairing, followed by the deletion of a major portion of the repeat (Taylor et al., 1999).~~

~~Studies of microsatellite genesis have led to important insights into the mode of~~

~~microsatellite evolution, allowing the development of appropriate statistical models. For~~

~~example, microsatellites generally follow a stepwise mutational model (SMM) more~~

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~~closely than the infinite alleles model (IAM) of evolution assumed by traditional F~~

~~statistics. Under SMM alleles that are similar in size are more closely related than alleles~~

~~that are very different in size. This is because, as mentioned above, microsatellites~~

~~generally change by the addition or loss of one repeat unit. This finding led to the~~

~~development of Rst. an Fst analogue that assumes an SMM of evolution (Slatkin, 1995).~~

~~Alternately. DiRienzo (1994) introduced a two-phase model of microsatellite mutation.~~

~~Under the two-phase model, mutation changes the repeat length of the microsatellite by 1~~

~~unit with some probability. P. and by more than one unit with a probability of 1-P. None~~

~~of these models take into account constraints on allele size. The high mutation rates of~~

~~microsatellites are expected to produce the most serious underestimation of genetic~~

~~structure using conventional F statistics when mutation is higher or of the same order of~~

~~magnitude as migration (Hedrick, 1999: Balloux et al., 2000)~~

~~In the current study, microsatellite DNA markers were used to examine samples~~

~~of sailfish taken from the eastern and western Atlantic, eastern and western Pacific, and~~

~~Indian oceans to investigate stock structure both with and between oceans.~~

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~~MATERIALS AND METHODS~~

~~In total, 647 sailfish were analyzed from samples collected throughout the species'~~

~~range over a period of six years. In the western Atlantic, 164 individuals were analyzed~~

~~from Florida (42), Brazil (93), Venezuela (15), and Trinidad/Tobago (14); and in the~~

~~eastern Atlantic, 130 individuals were analyzed from Senegal (37) and Ghana (130). In~~

~~the eastern Pacific, 149 individuals were analyzed from Mazatlan (51) and Cabo San~~

~~Lucas (27), Mexico, Ecuador (60), and Panama (11); and in the western Pacific. 113~~

~~individuals were analyzed from Vietnam (12), Papua New Guinea (36), and Taiwan (65).~~

~~In the Indian Ocean, 91 individuals were analyzed from Australia (21), Kenya (47) and~~

~~the Persian Gulf (23).~~

~~Sailfish were collected by commercial, artisanal, and recreational fishermen and~~

~~samples consisted of either heart tissue removed after capture and stored at -80°C until~~

~~isolation, or white muscle preserved in 0.25mM EDTA pH 8.0, 20% DMSO, and~~

~~saturated NaCl (Seutin, 1991) at room temperature until isolation. DNA was isolated~~

~~according to the methods of Sambrook et al. (1989). Briefly, a small (1cm3) amount of~~

~~tissue was diced and placed into 500 ul of buffer consisting of 10 mM Tris, 2mM EDTA,~~

~~1% SDS, 10 ul of 10 mg/ml RNAse and 10 ul of 25 mg/ml proteinase K and incubated~~

~~overnight in a water bath at 37°C. After incubation, the solution was centrifuged at~~

~~16,000 g for 30 min. to pellet cellular debris and the supernatant was transferred to a~~

~~clean tube. DNA was isolated using a standard phenol :chloroform:isoamyl alcohol~~

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~~extraction and precipitated in 0.4X volumes of 5M NaCl and 2X volumes of 100%~~

~~ethanol. DNA was reconstituted in 50 ul of 0.1X TE (pH 8.0) and stored at -20°C.~~

~~Following isolation, DNA was amplified using primers specific for five~~

~~microsatellite loci: MN01, MN08. and MN10. MN60 and MN90 originally developed for~~

~~use in the blue marlin (Buonaccorsi et al., 2001). PCR was performed using the~~

~~Gibco/BRL PCR Reagent System (Gibco BRL. Bethesda, MD) with a final concentration~~

~~of 20 Mm Tris-HCl (pH 8.4), 50 mM KC1. 1.5 mM MgCh, 0.2 mM dNTP mix. 0.05 uM~~

~~of each primer. 0.1125 units of Taq polymerase and approximately 5 ng of template DNA~~

~~in a total volume of 5 ul. Cycling conditions consisted of an initial denaturation of 5 min~~

~~at 95 (’C followed by 32 cycles of 94 °C for 1 min.. 55 °C for 1 min.. and 72 °C for 1 min.~~

~~followed by a 7 min. final extension at 72°C, with the exception of MN-90 which used a~~

~~50 °C annealing temperature. One primer from each primer pair was labeled with either~~

~~IRD-700 or IRD-800 fluorescent dye (LiCor, Lincoln. NE) for visualization. PCR~~

~~products were separated on 25 cm, 7% polyacrylamide gels run on a LiCor 4000 or 4200~~

~~sequencer. A size standard was run at each end and in the middle of the gel to determine~~

~~allele size. The resulting products were scored using RFLPSCAN 3.0 software~~

~~(Scanalytics, CSP, Inc.).~~

~~Data were analyzed with individuals collected in multiple years at a location held~~

~~separately and, since there was no evidence of temporal heterogeneity between years at a~~

~~location, combined. Conformance of genotypic distributions to Hardy-Weinburg~~

~~equilibrium was assessed using the exact test of Guo and Thompson (1992) as~~

~~implemented in ARLEQUIN 2.0. Pairwise genetic distances were calculated and~~

~~significance was assessed via randomization (Schneider et al., 2000) using both~~

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~~conventional F statistics and Slatkin's Rst which is essentially the sum of the squared~~

~~number of repeat differences between haplotypes and was developed to approximate the~~

~~SMM. Exact tests of population differentiation were carried out using the methods of~~

~~Raymond and Rousset (1995) and the level of population differentiation was estimated~~

~~using the AMOVA algorithm (Excoffier et al., 1992) as implemented in ARLEQUIN ver.~~

~~2.0 using both heirarchical F statistics and heirarchical R statistics (Schneider et al.,~~

~~2000).~~

~~Throughout this chapter, consistent terminology will be used when discussing~~

~~sample hierarchy. 'Individuals' will be used to refer to single sailfish. Samples' will be~~

~~used to refer to sailfish taken from a specific geographic area in a particular year, while~~

~~'collections' will be used to refer to all the sailfish taken from a specific geographic area~~

~~over all years. 'Regions' will be used to refer to all sailfish taken from a particular~~

~~geographic region defined as; eastern Atlantic, western Atlantic, eastern Pacific, western~~

~~Pacific, or Indian, and in some cases, Indo-west Pacifc. 'Oceans' will be used to refer to~~

~~ocean of origin of sampled sailfish as; Atlantic, Pacific, Indian, or in some cases, Indo-~~

~~west Pacific. F-statistics were given subscripts corresponding the level tested. O, oceans;~~

~~R, regions; C, collections, S, samples and I, individuals such that Fot refers to the~~

~~comparisions of oceans tested in a particular test to all individuals included in that~~

~~particular test and etc.~~

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~~RESULTS~~

~~Three microsatellite loci, MN01. MN08 and MN10 were surveyed in all~~

~~collections. Two additional loci. MN60 and MN90, were analyzed for a subset of the~~

~~available collections and were subsequently abandoned because the number of alleles (52~~

~~and 49. respectively) rendered the available collection sizes statistically inadequate for~~

~~meaningful analysis. Overall. MN01 had 23 alleles ranging from 2-31 repeats with the~~

~~majority between 7 and 16 repeat units. MN08 had 13 alleles ranging from 5-28 repeats~~

~~with the majority between 5 and 11 repeat units, and MN10 had 20 alleles ranging~~

~~between 10 and 35 repeats with the majority between 15 and 24 repeat units (Figure 1).~~

~~Heterozygosity was high for all collections in all oceans (Table 1). MN01 had~~

~~heterozygosities ranging from 0.8021 +/- 0.0269 in Cabo San Lucas, Mexico to 0.8904~~

~~0.0134 in Papua. New Guinea. MN08 had heterozygosities ranging from 0.4553 +/-~~

~~0.0508 in Cabo San Lucas. Mexico to 0.7494 +/- 0.0525 in the Caribbean. MN10 had~~

~~heterozygosities ranging from 0.7527 +/- 0.0542 in the Persian Gulf to 0.9048 +/- 0.0281~~

~~in the Caribbean (Table 1).~~

~~Tests for conformance of genotypic distributions to the expectations of Hardy-~~

~~Weinburg equilibrium at each individual locus and over all loci revealed one significant~~

~~departure out of 22 comparisons for the MN01 locus, none for the MN08 Locus and three~~

~~for the MN 10 locus. Only the PNG99 sample at the MN 10 locus was significant after~~

~~using a Bonferroni correction for multiple tests (0.05/23=0.002; Rice, 1989; Table 2).~~

~~This sample was subsequently re-amplified and re-scored, but the results did not change.~~

~~Over all loci, no samples exhibited significant departures of genotypes from the~~

~~expectations of Hardy-Weinburg equilibrium after correction for multiple tests (Table 3).~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 158~~

~~Global tests of non-differentiation among samples at all loci resulted in an exact P~~

~~value of <0.00001 (6000 Markov steps done). An AMOVA using Fst which grouped~~

~~collections into Atlantic, Pacific, and Indian Oceans indicated that 1.67 percent~~

~~(p=0.00129) of variance was due to variation among the different oceans while 0.77~~

~~percent (p<0.00001) was due to variation among collections within the oceans, the~~

~~remaining variance was attributable to variation among individuals within the oceans.~~

~~Slatkin's RsTwith collections classified into Atlantic. Pacific, and Indian Oceans~~

~~indicated that a larger amount of variance, 4.45%. was due to variation among the oceans~~

~~(p=0.00050) but attributed none of the variance (-0.37%) to variation among samples~~

~~within oceans (Tables 5 and 6). Thus, while both estimators detected significant~~

~~differences between oceans, only F s t detected differences among samples within oceans.~~

~~To save space, values based on F statistics will henceforth be reported followed by~~

~~valued based on Rst statistics (F s t 'R s t )-~~

~~AMOVAS were carried out between oceans in pairwise fashion to assess which~~

~~were most closely related. A comparison between Atlantic and Pacific Oceans indicated~~

~~that 2.41% (p=0.00802)/6.75% (p=0.00880) of variance was due to variation between~~

~~oceans and Fot/Rot, a hierarchical F statistic analogue denoting the amount of variation~~

~~attributable to variance between user defined classes as compared to the amount in the~~

~~overall sample, in this case oceans/total, was estimated at 0.02406/0.06738. Between~~

~~Atlantic and Indian Ocean samples, 1.77% (p<0.00001)/3.93% (p<0.00001) of variance~~

~~was due to variation between oceans and Fot/Rot was estimated at 0.01768/0.03927. In~~

~~comparisons between Indian and Pacific Ocean collections, no significant variance~~

~~(0.12% (p=0.27960/0.13% p=0.33138) was due to variation between oceans and F o t /R o t~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 159~~

~~was estimated to be an order of magnitude lower than the comparison between Atlantic~~

~~and Pacific samples: 0.00123/0.00126.~~

~~Since it has been suggested that western Pacific sailfish are more closely related~~

~~to Indian Ocean sailfish than to eastern Pacific sailfish based on morphological data~~

~~(Williams. 1970). an AMOVA was constructed to assess the differences between Indian~~

~~and western Pacific regions. Results indicated that no variation could be attributed to~~

~~variance between these regions (-0.49% p=0.59792/-0.30% p=0.80352) and F r t R r t was~~

~~estimated -0.00491-0.00302. When the Indian and western Pacific regions were~~

~~subsequently grouped together and compared to eastern Pacific region. 1.93%~~

~~(p=0.00000) '1.93% (p=0.00000) of the variance was due to variation between regions~~

~~and the Frt'Rrt was 0.01933/0.01933.~~

~~Finally, the Indo-west Pacific region and the eastern Pacific region were~~

~~compared to the Atlantic ocean in pairwise fashion. In the Indo-west Pacific/Atlantic~~

~~comparison, 1.78% (p=0.00000)/3.85% (p=0.00000) of variance was attributable to~~

~~variation among groups and F r t /R r t was estimated at 0.01784/0.03854. In the~~

~~Atlantic/eastern Pacific comparison, 4.14% (p=0.00000)/10.40% (p=0.00000) of the~~

~~variance was due to variation between samples and Fst/Rst was estimated to be~~

~~0.04143/0.10403.~~

~~After comparisons between oceans/ocean regions, collections taken within each~~

~~ocean/region were compared. Each locus had several alleles present at high frequency as~~

~~well as several low frequency alleles (Figure 2). In the Atlantic, MN01 had a total of 16~~

~~alleles ranging from 6-31 repeats with the most common alleles, 9 and 12 repeats, present~~

~~in 21.7% and 21.3% of samples respectively. MN08 had 13 alleles ranging from 5-28~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 160~~

~~repeats with allele 7 present at a frequency of 60.5%. MN10 had 17 alleles ranging from~~

~~12-35 repeats with allele 16 present at a frequency of 27%. An AMOVA considering the~~

~~Atlantic as a single group found that 100% of the variance could be attributed to variation~~

~~within collections both when using the distribution of alleles ( F s t ) and the distribution~~

~~and allelic relationships ( R s t ) as estimators. Dividing samples into eastern and western~~

~~Atlantic regions produced similar estimates of the percent of the variance due to variation~~

~~among groups for both estimators (0.50/0.58. Tables 5.6). However in the case of F r t ,~~

~~which was estimated to be 0.00495, this was highly significant (p=0.00000) while R r t~~

~~was estimated at -0.00829, a non-significant value (p=0.10119. Tables 5 and 6). There~~

~~were no significant differences between the SEN, GHA, FLA, and BRA collections with~~

~~either estimator over all loci (Table 10). however the SEN-FLA comparison was~~

~~significant using F s t as an estimator at the MNOI locus ( F s t = 0.0214 p=0.0238. Table 7)~~

~~and the BRA-GHA comparison was significant using Rst at the MN10 locus~~

~~( F s t = 0.01579 p = 0.04188).~~

~~In the Pacific, MN01 had a total of 17 alleles ranging from 3-23 repeats. Allele 9,~~

~~which was present at a frequency of 21.7% in Atlantic collections, was at a much lower~~

~~frequency (4.4%) in Pacific collections (Figure 2). However allele 16, which was present~~

~~at 23.7% in Atlantic collections was also present at 23.7% in Pacific collections. MN08~~

~~had 7 alleles ranging from 5-11 repeats and 60.5% of alleles were 8 repeats in length.~~

~~MN10 had 16 alleles ranging from 10-27 repeats with the most common allele present in~~

~~27% of alleles sampled. An AMOVA considering the Pacific as a single group using R st~~

~~as an estimator found that 0.53% of the variance was due to variation between loci~~

~~(p=0.14089) with an estimated Rst of 0.00526. Using Fst as an estimator indicated that~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 161~~

~~1.64% of variance is due to variation among collections (p<0.00001) and yielded a Fst~~

~~estimate of 0.01737. When collections were grouped into eastern Pacific (CAB, MAZ,~~

~~ECU) and western Pacific (TAW, PNG) regions. 1.83% (p<0.00001 F r t = 0 .01825 )~~

~~/1.53% (p<0.00001 R Rr = 0 .0 1531) of the variance was due to variation among the groups~~

~~of populations. Using F Cr , 0.47% ( F sc =0.00482. p=0.02505) of the variance was due to~~

~~variation among collections within the regions, while none of the variance (-0.44%) was~~

~~attributable to variance among the collections within the regions using R c r ( R c r~~

~~=0.00452 p=0.62659; Tables 5 and 6). Using either estimator reveals significant~~

~~structuring between eastern and western Pacific regions while traditional F statistics also~~

~~indicate the presence of population structure among collections within regions.~~

~~Pairwise comparisons of all eastern Pacific and all western Pacific Ocean~~

~~collections were calculated based on both Fst and Rst estimators at each locus~~

~~individually and over all loci to evaluate the presence of stock structure within ocean~~

~~regions. In the western Pacific, comparisons between the PNG and TAW populations~~

~~were not significant with either estimator when calculated over all loci, nor were there~~

~~any significant pairwise comparisons at any individual locus (Tables 7-10). In the eastern~~

~~Pacific (CAB, ECU, and MAZ). comparisons w'ere non-significant over all loci and~~

~~across loci using both estimators. Interestingly, measures of Hardy-Weinburg~~

~~equilibrium were bordering on significance for two of the three loci in the PNG collection~~

~~and observed heterozygosity was greater than expected at all loci in this collection~~

~~(MN01: obs=0.92683 exp=0.89130; MN08 obs=0.81081 exp= 0.62903 MN10,~~

~~obs=0.92683 exp= 0.84974; Tables 2 and 3) despite re-amplification and re-scoring of~~

~~samples.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 162~~

~~In the Indian Ocean, MN01 had a total of 13 alleles ranging from 2-16 repeats.~~

~~As in the Pacific, the 9 repeat allele, which was prevalent in the Atlantic, was present at~~

~~low frequency (5.2%) while the 12 repeat allele was present at a similar frequency to both~~

~~the Atlantic and Pacific collections (26.6%; Figure 2). MN08 had 6 alleles ranging from~~

~~5-11 repeats and 49.9% of alleles were 8 repeats in length. MN10 had 12 alleles ranging~~

~~from 14-25 repeats with the 12 repeat allele present in 28.6% of alleles sampled (Figure~~

~~2). No significant differences were found between the AUS. KEN, and PER collections~~

~~using an AMOVA based on R c t - However, using F c t . 1.21 % of the variance was due to~~

~~variation among collections and F c t was estimated at 0.01206 (p<0.00001; Table 5 and~~

~~6). In pairwise comparisons between the three collections, there were no significant~~

~~comparisons using Rst as an estimator (Tables 7-10). Using Fst, the PER collection was~~

~~significantly different from the AUS and KEN collections over all loci. In a locus by~~

~~locus analysis, both the MN01 and MN10 loci yielded significant pairwise comparisons~~

~~for AUS-PER and for KEN-PER. There were no significant pairwise comparisons~~

~~between the AUS and KEN collections. Interestingly, in pairwise comparisons between~~

~~Indian and western Pacific samples, the TAW-PER and PNG-PER comparisons using F st~~

~~also gave significant values at both the MN01 and MN10 loci as well as over all loci.~~

~~There were no significant pairwise comparisons between any other Indian and western~~

~~Pacific coollections.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 163~~

~~DISCUSSION~~

~~In general, divergence estimates based on R-statistics were larger than those based~~

~~on F-statistics. but use of F-statistics yielded more significant pairwise comparisons~~

~~(Tables 5-10). However, both Fst and Rst differentiated Atlantic, eastern Pacific and~~

~~Indo-west Pacific groups (regions). RSt generally did not differentiate collections within~~

~~these regions. However, simulation studies of R s t indicate that when sample sizes are~~

~~not equal, populations (collections) with larger sample sizes contribute more to the~~

~~variance than populations (collections) with smaller sample sizes (Goodman, 1997). It~~

~~has therefore been suggested that R s t is most appropriate when samples are all equal but~~

~~in the absence of equality, all sample sizes should be relatively large (n>50: Ruzzante,~~

~~1998). In addition, simulations have shown that the variance of Rst increases with an~~

~~increasing number of alleles (Ruzaante, 1998).~~

~~Slatkin (1995) found that Fst underestimates genetic divergence (samples appear~~

~~too similar) for microsatellites when the time since the populations diverged was long~~

~~relative to the ancestral populations size, whereas R s t did not show this bias in~~

~~simulations. He also noted that Fst becomes more accurate when the time since the~~

~~splitting of ancestral populations is short relative to population size. This was attributed~~

~~to the fact that over short time periods, drift is the predominant process responsible for~~

~~differentiation and mutation plays minor role. Thus, when mutation is higher, or of the~~

~~same magnitude as migration, conventional F statistics will underestimate genetic~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 164~~

~~structure (Hedrick, 1999; Balloux, 2000). In light of these findings, it seems reasonable~~

~~that Rst is probably a more accurate estimator of divergence between sailfish populations~~

~~taken from different ocean regions (i.e.. Atlantic, eastern Pacific and Indo-west Pacific)~~

~~since samples sizes at this level are all relatively large, and there is presumably very little~~

~~migration. Alternately. Fst is more likely to accurately reflect stock structure within~~

~~ocean regions since in these instances, sample sizes are smaller and drift is probably more~~

~~important than mutation.~~

~~Unlike the mtDNA analyses in Chapter 2. microsatellite data suggest the~~

~~possibility of stock structure between eastern and western Atlantic sailfish collections~~

~~based on Fst- However, it is important to note that no significant differences were~~

~~observed in pairwise comparisons of eastern and western collections when all loci were~~

~~combined (Table 10). the percent of variance attributable to variation among Atlantic~~

~~regions in the AMOVA was extremely small (0.50o/o), and only one of four possible~~

~~pairwise comparisons was significant between Atlantic regions for both the MN01 and~~

~~MN10 loci (none were noted at the Mn08 locus. Tables 7-9). Furthermore, if a~~

~~Bonferroni correction is applied, resulting in a significance threshold of 0.01, neither of~~

~~these comparisons are significant. Larger collections need to be examined across an~~

~~increased number of loci between Atlantic regions before any conclusions can be~~

~~confidently drawn from these data.~~

~~Failure to find stock structure using genetic techniques does not necessarily mean~~

~~that there is not structure, just that the method used failed to detect structure. However,~~

~~based on these same types of analyses, population genetic studies of other Atlantic~~

~~istiophorid billfishes have also reported a lack of significant structuring within the~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 165~~

~~Atlantic basin. Analysis of four microsatellite loci in the white marlin showed that~~

~~although there was sufficient variation to detect stock structure, the genetic variation was~~

~~homogeneously distributed among Atlantic collections (McDowell and Graves,~~

~~unpublished data). In addition, analysis of Atlantic and Pacific collections of blue marlin~~

~~with five microsatellite loci showed that although there were significant differences~~

~~between collections from different oceans, there was no evidence of within ocean stock~~

~~structure (Buonacorrsi et aL 2001).~~

~~Results based on Indo-Pacific collections of sailfish contrast with results ased on~~

~~Atlantic collections. Comparisons between eastern and western Pacific collections using~~

~~an AMOVA based on RSt revealed that, as with mtDNA. a small but significant amount~~

~~of variance (1.53%) was due to the variation between eastern and western Pacific~~

~~collections while the estimate was 1.83% based on F s t - However, unlike mtDNA~~

~~analyses, eastern Pacific collections did not have consistently lower diversity estimates~~

~~relative to other areas sampled (Table 1). However, the three eastern Pacific collections~~

~~did have lower diversity estimates than other collections at the MN08 Locus (Table 1).~~

~~This difference between mtDNA and microsatellite results is likely due to the fourfold~~

~~greater effective population size of nuclear loci which makes them less suceptible loss if~~

~~diversity and other effects of genetic drift.~~

~~Within the eastern Pacific, there were no significant pairwise comparisons~~

~~between CAB, MAZ and ECU for any locus or over all loci combined, and Fst estimates~~

~~between samples ranged from -0184 to 0.0074 (Tables 7-10). Microsatellite analysis~~

~~was unable to detect the presence of stock structure within the eastern Pacific collections.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 166~~

~~In the western Pacific, Fst between TAW and PNG over all loci was estimated at~~

~~0.00244 (p=0.14642: Table 10) and there were no significant pairwise comparisons at any~~

~~locus: no genetic structure was detected between collections. This contrasts with the~~

~~results of mtDNA analyses, which suggest that these samples were not drawn from a~~

~~common gene pool. The fact that measures of Hardy-Weinburg equilibrium were~~

~~bordering on significance for two of the three loci in PNG and observed heterozygosity~~

~~was greate than expected at all loci in this sample is consistent with the observ ation that~~

~~in recently bottlenecked populations, the allele number is reduced faster than the gene~~

~~diversity, and therefore the observ ed heterozygosity is higher than the expected. This is~~

~~because rare alleles are lost from the population at a faster rate. It would be necessary to~~

~~examine several more loci before tests of statistical significance could be carried out~~

~~(Comuet and Luikart. 1996).~~

~~In the Indian Ocean. mtDNA analyses suggested that the Persian Gulf collection~~

~~was distinct from collections taken near both Kenya and Australia. Results based on~~

~~microsatellite analysis using F s t a s an estimator agree with the mtDNA data; samples~~

~~taken from the western Pacific are more closely related to Indian Ocean samples than to~~

~~eastern Pacific samples. None of the variation between Indian and western Pacific~~

~~samples was due to variance among groups but 1.93 percent of variance (p<0.000l) was~~

~~attributable to variance betw een Indo-west Pacific and eastern Pacific regions in close~~

~~agreement with mtDNA analysis.~~

~~Population genetic studies of both the striped marlin (Graves and McDowell,~~

~~1994) and the Indo-Pacific sailfish (McDowell and Graves unpublished data) were found~~

~~to have levels of genetic variation similar to their Atlantic counterparts. However~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 167~~

~~whereas stock structure was absent in the Atlantic for both white marlin and sailfish. both~~

~~striped marlin and Indo-Pacific sailfish were found to comprise distinct genetic stocks.~~

~~Since there is no obvious biological reason why stock structure should exist m the Pacific~~

~~but not in the Atlantic for these species, the most likely explanation appears to be the~~

~~relative size of the Atlantic Ocean as compared to the Indian and Pacific Oceans. The~~

~~Atlantic is sufficiently small that isolation by distance is probably not tenable. In fact,~~

~~the 1994-1996 Japanese landing statistics demonstrate a continuous distribution of~~

~~sailfish across the Atlantic Ocean. Likewise, the Indian and western Pacific are separated~~

~~by a relatively short distance as compared to the distance across the Pacific basin. Since~~

~~the tropical Indo-west Pacific has temperatures that are relatively stable compared to~~

~~other provinces, sailfish are year-round residents throughout much of their range in this~~

~~area (Whitlaw. 2001). The presence of stable year round populations is likely another~~

~~factor promoting stock structure (limiting gene flow) in this region.~~

~~The term stock has generally been used to refer to a group of organisms whose~~

~~genetic/demographic (or evolutionary) trajectory is largely independent from the~~

~~trajectory of other such groups (Waples, 1998). Under this definition it is clear that at a~~

~~minimum, sailfish comprise distinct Atlantic, eastern Pacific, and Indo-west Pacific~~

~~stocks based on microsatellite DNA analysis. It is also clear that the Persian Gulf~~

~~comprises a distinct stock; population pairwise Fsts over all micorsatellite loci were~~

~~significant for ten of eleven pairwise comparisons between the Persian Gulf collection~~

~~and other collections (Table 10). If additional stocks of sailfish exist, larger numbers of~~

~~individuals, more sampling locations, and an increased number of loci would be~~

~~necessary to delineate their existence based on microsatellite data. The results of both~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 168~~

~~mtDNA and microsatellite analyses suggest that sailfish may well consist of more than~~

~~the four stocks clearly delineated by the current microsatellite analyses.~~

~~Unlike mtDNA analysis, microsatellite analysis showed no evidence of the~~

~~existence of distinct clades in either ocean in the form of disjunct modes of alleles. It is~~

~~probable that the high mutation rate of microsatellite loci combined with constraints on~~

~~allele size have had a homogenizing effect on micorsatellite alleles over time. This is in~~

~~contrast to the results from blue marlin in which the MN08 locus had two modes of~~

~~alleles in the Altantic but only a single mode in the Pacific, however this phenomenon~~

~~was not seen in the other four loci examined in that study (Buonaccorsi et al.. 2001). The~~

~~two modes present at the MN08 locus in blue marlin may have originated much later than~~

~~the mtDNA split, or the less frequent (and larger) mode may have been lost in the~~

~~sailfish.~~

~~Sailfish clearly exhibit stock structure based on the analysis of microsatellite loci~~

~~and these results generally agree with conclusions based on mtDNA analyses, which~~

~~indicate that sailfish are minimally comprised of Atlantic, eastern Pacific. Indo-west~~

~~Pacific, and Persian Gulf stocks. Whether or not additional stocks of sailfish exist could~~

~~not be determined within the bounds of this study due to sampling limitations. However,~~

~~if additional stocks exist, they are most probably located with the Indo-west Pacific since~~

~~stock structure was not found within the Atlantic or eatem Pacific. Additionally, using~~

~~mtDNA as a benchmark, results of analyses based on F s t appear to more accurately~~

~~estimate stock structure when drift is the predominant factor leading to stock structure~~

~~while R s t appears to be more accurate when samples sizes are large.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 169~~

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~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 175~~

~~Table 1. Descriptive statistics for microsatellite data.~~

MN01 Region Collection Gene Copies Allelic Diversity Repeat Range Gene Diversity EA SEN 74 9 7-15 0.8193 ^ - 0.0210 EA GHA 182 11 6-16 0.8245 — 0.0127 WA FLA 66 10 6-15 0.8406 0.0189 WA BRA 232 U 7-17 0.8652 0.0077 WA VEN 34 10 7-18 0.8431 0.0314 WA C.AR 30 10 7-30 0.8782 0.0353 EP CAB 50 8 7-16 0.8204 +/- 0.0268 EP MAZ 84 10 8-17 0.8021 -/- 0.0269 EP ECU 114 11 8-19 0.8297 - - 0.0177 W? TAW 122 14 3-23 0.8598 - - 0.0185 WP PNG 82 12 3-16 0.8904 *'- 0.0134 \\T NAM 20 7 9-20 0.8053 - - 0.0564 IAUS 54 12 2-16 0.8539 0.0297 I PER 42 8 7-15 0.8664 0.0213 IKEN 134 11 5-16 0.8519 - - 0.0167

MN08 Region Collection Gene Copies Allelic Diversity ______Repeat Range Gene Diversity EA SEN 68 6 5-10 0.6765 - - 0.0429 EA GHA 166 10 5-19 0.7352 +- 0.0242 WA FLA 70 4 5-10 0.6791 -/- 0.0309 WA BRA 232 6 5-11 0.5832 * - 0.0283 WA VEN 28 4 5-10 0.6402 -/- 0.0526 WA CAR 30 7 5-28 0.7494 - - 0.0525 EP CAB 42 2 7-8 0.4553 +.'- 0.0508 EP MAZ 86 4 5-10 0.4752 +/- 0.0377 EP ECU 108 7 5-11 0.5665 - - 0.0412 \\T TAW 108 6 5-10 0.6071 +/- 0.0360 WP PNG 74 4 5-10 0.6290-/- 0.0397 WP NAM 20 3 7-10 0.2789*/- 0.1235 IAUS 46 4 5-10 0.5729 +/- 0.0348 I PER 46 5 5-11 0.6444 +/- 0.0407 I KEN 130 6 5-11 0.6258 */- 0.0310

MN10 Region Collection Gene Copies Allelic Diversity Repeat Range Gene Diversity EA SEN 56 8 15-24 0.8104+/- 0.0308 EA GHA 174 12 15-26 0.7853 +/- 0.0171 WA FLA 72 11 15-26 0.8103 +/- 0.0258 WA BRA 234 15 15-35 0.8259+/- 0.0127 WA VEN 36 7 15-25 0.7810+/- 0.0455 WA CAR 28 11 13-28 0.9048+/- 0.0281 EP CAB 44 7 15-26 0.8266+/- 0.0271 EP MAZ 82 9 15-24 0.8326+/- 0.0176 EP ECU 116 10 15-25 0.7967+/- 0.0217 WP TAW 124 13 11-34 0.8505+/- 0.0158 WP PNG 82 11 10-23 0.8497+/- 0.0203 WP NAM 20 7 15-22 0.8263 +/- 0.0546 I AUS 42 11 14-24 0.8769 +/- 0.0277 IPER 46 9 15-25 0.7527+/- 0.0542 I KEN 132 12 14-25 0.8238+/- 0.0217

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 176~~

Table 2. Hardy Weinburg Equilibrium-test of association at the locus level using the methods of Guo and Thompson (1993). Significance values are based on 100,000 randomizations. Values significant at 0.05 level after Bonferroni correction are bolded. No. Genot.. number of observed genotypes: Obs. Heter., observed heterozygosity: Exp. Heter., expected heterozygosity: P. probability of significance: s.d., standard deviation.

~~Sample Locus =Genot Obs. Heter. . Exp.Heter. P. s.d. Sen97 MN01 37 0.78378 0.81933 0.85136 0.00084 MN08 34 0.70588 0.67647 0.46621 0.00121 MN10 28 0.64286 0.81688 0.02083 0.00037~~

~~Gha98 MN01 44 0.90909 0.85005 0.93810 0.00063 MN08 41 0.68293 0.55706 0.44332 0.00139 MN10 40 0.82500 0.75570 0.52255 0.00109~~

~~Gha99 MN01 47 0.87234 0.81126 0.86015 0.00060 MN08 42 0.76190 0.82846 0.23380 0.00084 MN10 47 0.93617 0.79936 0.26383 0.00092~~

~~Isl92 MN01 15 0.73333 0.87356 0.08835 0.00079 MN08 16 0.87500 0.67944 0.57785 0.00175 MN10 18 0.72222 0.78730 0.20428 0.00143~~

~~Fla98 MN01 24 0.95833 0.84574 0.16188 0.00083 \1N08 25 0.80000 0.68327 0.41274 0.00142 MN10 23 0.78261 0.84348 0.08701 0.00028~~

~~Bra93 MN01 48 0.81250 0.86009 0.03270 0.00055 MN08 47 0.55319 0.52528 0.32494 0.00094 MN10 47 0.80851 0.84512 0.09719 0.00043~~

~~Bra95 MN01 36 0.80556 0.86463 0.50324 0.00149 MN08 37 0.54054 0.61829 0.38994 0.00112 MN10 37 0.81081 0.83080 0.56287 0.00099~~

~~Bra98 MN01 32 0.81250 0.78522 0.50456 0.00104 MN08 32 0.65625 0.64137 0.75197 0.00140 MN10 33 0.87879 0.79394 0.09262 0.00045~~

~~Ven98 MN01 17 0.88235 0.84314 0.10048 0.00034 MN08 14 0.71429 0.69841 0.71380 0.00144 M NI0 18 0.77778 0.78413 0.53425 0.00159~~

~~Cab92 MN01 25 0.80000 0.82041 0.23839 0.00137 MN08 21 0.38095 0.50174 0.62364 0.00158 MN10 22 0.81818 0.83087 0.36676 0.00178~~

~~Maz92 MN0I 13 0.69231 0.83385 0.34839 0.00116 MN08 12 0.33333 0.35870 0.17688 0.00134 MN10 9 0.88889 0.84967 0.03079 0.00055~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 177~~

~~Table 2. cont.~~

~~Sample Locus -Genot Obs. Heter. Exp.Heter. P. s.d. Maz97 MN01 29 0.82759 0.80883 0.76109 0.00105 MN08 31 0.61290 0.52089 0.34163 0.00154 MNIO 32 0.78125 0.83780 0.10096 0.00069~~

~~Ecu95 MN01 15 0.86667 0.86207 0.90220 0.00073 MN08 14 0.50000 0.62963 0.34344 0.00110 MNIO 13 0.84615 0.84308 0.52443 0.00098~~

~~Ecu97 MN01 42 0.78571 0.79346 0.48416 0.00150 MN08 40 0.70000 0.53861 0.07130 0.00085 MNIO 45 0.91111 0.77503 0.33428 0.00082~~

~~Ta\v298 MN01 34 0.91176 0.86874 0.06467 0.00047 MN08 33 0.69697 0.62378 0.58110 0.00112 MNIO 34 0.82353 0.79763 0.78209 0.00127~~

~~Tail 98 MNO1 29 0.79310 0.86449 0.37962 0.00058 MN08 21 0.71429 0.61789 1.00000 0.00000 MNIO 28 0.92857 0.90325 0.59140 0.00089~~

~~Pny99 MNO 1 41 0.92683 0.89130 0.04655 0.00041 MN08 37 0.81081 0.62903 0.16155 0.00113 MNIO 41 0.92683 0.84974 0.00177 0.00013~~

~~\'nm9S MNO 1 10 0.80000 0.80526 0.54231 0.00104 MN'08 10 0.30000 0.27895 1.00000 0.00000 MNIO 10 0.80000 0.82632 0.51454 0.00085~~

~~Aus92 MNO I 27 0.77778 0.86303 0.09878 0.00043 MN’08 23 0.73913 0.57295 0.26015 0.00119 MNIO 21 0.85714 0.87805 0.31093 0.00096~~

~~Per99 MN01 21 1.00000 0.86643 0.04907 0.00083 MN08 23 0.82609 0.64444 0.12576 0.00110 MNIO 23 0.69565 0.75556 0.17742 0.00060~~

~~Ken94 MN01 21 0.85714 0.82927 0.60488 0.00100 MN08 19 0.57895 0.53912 1.00000 0.00000 MNIO 19 0.73684 0.79659 0.58029 0.00077~~

~~Ken99 MN01 46 0.93478 0.85475 0.79766 0.00070 MN08 46 0.65217 0.66030 0.60959 0.00138 MNIO 47 0.70213 0.84260 0.12855 0.00076~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 178~~

Table 3. Tests of Hardy-Weinburg equilibrium over all loci combined. Significance values are based on 100.000 randomizations. Values significant at 0.05 level after Bonferroni correction are bolded. P. probability of significance: s.d.. standard deviation.

Sam ple P. s.d. Sen97 0.13619 0.00007 Gha98 1.00000 0.00000 Gha99 0.13424 0.00009 Isl92 0.07422 0.00009 Fla 98 1.00000 0.00000 Bra93 0.35837 0.00009 Bra95 1.00000 0.00000 Bra98 1.00000 0.00000 Ven98 0.41928 0.00015 Cab92 0.31370 0.00012 Nlaz92 0.02856 0.00004 Maz97 0.36337 0.00016 Ecu95 1.00000 0.00000 Ecu97 0.118"1 0.00009 Taw298 0.32089 0.00008 Taw 198 0.10039 0.00007 Pni:99 0.06484 0.00009 \'nm9S 1.00000 0.00000 Aus92 0.13092 0.00009 Per99 0.42857 0.00006 Ken94 0.48582 0.00011 Ken99 0.61898 0.00007

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 179~~

Table 4. Hierarchical analysis of molecular variance (AMOVA) of sailfish microsatellite data. Distance method used was sum of squared size difference (Rst) with 10,000 permutations. Underlined values were estimated to be significant using Fst (see table 6).

~~Structure Tested Variance C umnonents Fstatistic Percent Variation n-value Atlantic Ocean Among ocean -0.0(1455 Va FST: -0.00429 -0.43 0.97099 Within collections 1.00441 Vb 100.43~~

~~EaslAV est Atlantic Amonf regions 0.00015 Va FCT -0.00829 0.58 0.10119 Among colls within regions -0.00875 Vb FSC: 0.00579 -0.82 0.90891 Within collections 1.00441 Vc FST: 4) 00245 100.24 0.97356~~

~~Oceans (API) Among groups 0.06571 Va FCT : 0.04448 4.45 0 00050 Among colls within groups 41.05596 \T> FSC 4100391 4),37 0.81020 Wilhin collections 14.35522 Vc FST. 0.04074 95.93 0.00000~~

~~A s s lW P s s E P Among regions O.’ SOIIVa FCT 0.05203 5.20 0.00000 Among colls within regions -0 14053 Vb FSC 41.00989 41.94 0.99921 U ithin collections 14 55522 Vc FST 0.04265 95.73 0.00000~~

~~Indian Pacific Among oceans 0 01809 Va FCT 0.00126 0.13 0 33138 Among colls within oceans 0.00524 Vb FSC 0.00(137 0.04 0.37928 \\ ithin collections 14.32977 Vc FST 0.00163 99 84 0.30987~~

~~Atlantic Pacific Among groups 1.0501’ Va FCT 006738 6.74 0.00880 Among colls within groups 4) 03037 Vb FSC 41 00209 4) . 19 0.63245 Within collections 14.56481 Vc FST 0.06544 93 46 0.00000~~

~~Atlantic/Indian Among oceans 0.5'013 Va FCT 0.03927 3.93 0.00000 Among colls within oceans 4i 15807 Vb FSC 4)01133 -1.09 0 99804 Within collections 14.10564 Vc FST 0.02838 97.16 0.01760~~

~~EPAVP Among regions 0 22811 Va FCT 0 01531 1-53 0.00000 Among colls within regions 41.06627 Vb FSC 4) 00452 4)44 0.62659 Within collections 14.73941 Vc FST 0 01086 48.91 0.13978~~

~~EP/IWP Among regions 0.27983 Va FCT: 0.01933 1.93 0.00000 Among colls within regions 4). 13561 Vb FSC : 4100955 -0.94 0 98827 Within collections 14.32977 Vc FST. 0.00996 99.00 0.31476~~

~~India n/W P Among regions 4) .04444 Va FCT: -0.00302 -0.30 0.80352 Among colls within regions 4). 15483 Vb FSC : 4) 01048 -1.05 0.94037 Within collections 14.92406 Vc FST: -0.01353 101.35 0.99902~~

~~Atlantic/IWP Among regions 0.86648 Va FCT: 0.05709 5.71 0.00000 Among colls within regions -0.04340 Vb FSC : 41.00303 -0.29 0.74976 Within collections 14.35522 Vc FST: 0.05423 94.58 0.00000~~

~~Pacific Among collections 0.07798 Va FST: 0.00526 0.53 0.14089 Within collections 14.73991 Vb 99.47~~

~~Indian Among collections 41.18032 Va FST: -0.01349 -1.35 0.92574 Within collections 13.54294 Vb 101.35~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 180~~

~~Table 4 cont.~~

~~Atlantic vs EP Among regions 1.61283 Va FCT: 0.10403 10.40 0.00000 Among colls within regions -011150 Vb FSC :-0.00803 -0.72 0.06515 Within collections 14.00223 Vc FST 0.00684 00.32 0.00000~~

~~Atlantic vs IWP Among regions 0.58077 Va FCT 0.03854 3JJ5 0.00000 Among colls within regions -0.lt>55l Vb FSC 4) 01142 -1.10 090000 Within collections 14.65236 Vc FST: 0.02756 07.24 0.00455~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 181~~

~~Table 5. Hierarchical analysis of molecular variance (AMOVA) of sailfish microsatellite data. Distance method used was number of alleles (FST) with 10.000 permutations.~~

~~Structure Tested Variance Comp. Fsiatistic Percent Variation rvvalue Atlantic Ocean Among collections -0.00293 Va FST: A).00277 -0.28 0.84066 Within collections 1.116293 Vb 100.28~~

~~East/West Atlantic Among regions 0.00526 Va FC T . 0.00495 0.50 0.00000 Among colls within regions -0.00659 Vb FSC -0.00624 -0.62 0 98861 Within collections 1 06293 Vc FST: -0.00126 100.13 0.84218~~

~~Oceans (API) Among iHtcans O.OITOVa FCT : 0.01673 1.67 0 00129 Among colls within oceans 0 00814 Vb FSC 0.00783 0.77 0.00000 Within collections 1.03214 Vc FST 0.02443 97.56 0.00000~~

~~A vs IWP vs EP Among regions 0.02608 Va FCT: 0.02459 2.46 0.00000 Among colls within regions 0.00208 Vb FSC: 0 00201 0.20 0.03396 W uhin collections 1.03214 Vc FST: 0.02656 97.34 0 (10000~~

~~Indian. Pacific Among oceans 0.00126 Va FCT 0 00123 0.12 0.27960 Among colls within oceans 0.ol557 Vb FSC 0.01516 1.51 0.00000 Within collections 1.01149 Vc FST: 0 01637 98.36 0.00000~~

~~Atlantic. Pacific Among oceans 0.025’,5 Va FCT: 0.02406 2.41 0 00802 Among colls within oceans 0.00729 Vh FSC: 0.00698 0.68 0 00010 Within collections I (l3'35 Vc FST: 0.03087 96.91 0.00000~~

~~Atlantic/Indian Among oceans (I 01885 Va FCT: 0 01768 1.77 0.00000 Among colls w ithin oceans 0.00158 Vb FSC : 0.00151 0.15 0 12683 Within collections I 04569 Vc FST 0 01917 98.08 0 00000~~

~~EP/WP Among regions 0.01889 Va FCT 0.01825 1.83 0.00000 Among colls within regions 0.00489 Vb FSC 0.00482 0.47 0.02505 Within collections 1.01126 Vc FST 0.02298 97.70 0.00000~~

~~EP/IWP Among regions 0.02005 Va FCT 0.01933 1.93 0.00000 Among colls within regions 0.00547 Vb FSC 0.00537 0.53 0.00098 W'ithin collections 1.01149 Vc FST 0.02460 97.54 0.00000~~

~~Indian/W P Among regions -0.00515 Va F C T :-0.00491 -0.49 0.59792 Among colls within regions 0.00822 Vb FSC: 0.00780 0.78 0.00485 Within collections 1.04589 Vc FST: 0.00293 99.71 0.00970~~

~~Indian/WP (no PER) Among regions -0.00091 Va FCT: -0.00086 -0.09 0.33545 Among colls within regions -0.00485 Vb FSC: -0.00457 -0.46 0.89663 Within collections 1.06466 Vc FST: -0.00543 100.54 0.98158~~

~~Atlantic/IWP Among regions 0.01918 Va FCT: 0.01784 1.78 0.00000 Among colls within regions 0.00103 Vb FSC: 0.00098 0.10 0.12059 Within collections 1.05461 Vc FST: 0.01880 98.12 0.00000~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 182~~

~~Pacific Among collections 0.01684 Va FST: 0.01638 1.64 0.00000 Within collections I 01 lift \T) 08.36~~

~~Indian Among collections O.OI235 Va FST 0.01206 I. 0.00624 Within collections I 01 I'M Vb 08.~~

~~Atlantic vs EPAC Among regions 0 04425 Va FCT 0,04143 4.14 0.00000 Among colls within regions 0 00000 Vb FSC 0 00008 0.01 0.30337 Within collections I.023M Vc FST 0 04151 05.85 0.00000~~

~~Atlantic vs IWP Among regions o o 1018 Va FCT 0 01784 1.78 0.00000 Among colls within regions 0 00103 Vb FSC 000008 0 10 0.12188 W ithin collections I 05461 Vc FST 001880 08.12 0.00000~~

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. P-valuc 10,000 19 FCT FCT P-value 0.00746 0.00746 0.01955 0.02926 0.02926 0.00489 0 03856 03856 0 O.OI27I

~~FST FST P-value FCT 0.00000 0.00000 0.02348 002639 0.00196 001905 02737 0 0.00000 0.00414 007722 00000~~

183 0 000000 0 00000 00000 0 ’-value ’-value P-value P-value 002819 0.02381 01702 0 ISC Fixation indices: Fixation 0.06061 0.10459 0.00098 Fixulion indices: indices: Fixulion Fixation indices. Fixation P-value P-value FST f 0 15054 0 15054 003125 001369 001362 0.00000 0.00000 005564 I SC SC I P-vnlue SI I P-valuc ( I I P-value 0.00010 0.00010 000000 0.01639 0.06663 0.00357 006337 002511 0.00000 0.00059 002121 0.00000 0.00000 004129 00(1000 002529000762 0.00486 0.01294 FSC 0.00620 0.01776 0.00205 0.01287 000398 5<> variation variation 5<> °o variation variation °o 98.63797 94.43632 9687452 97.18074 97.18074 97.61859 00482 0 98.29760 97.48803 97.48803 98.36115 95 87136 87136 95 0.01641 Vc Vc Vc 0.40691 0 41758 41758 0 0.31178 0.41907 0.41907 0 33077 0.40275 Within Collections: Within Vc Vc variation % 0.41977 0.41977 0.31138 0.31138 0.40758 Within Collections: Collections: Within Within Collections: Collections: Within 1.28205 1.59985 1.59985 0.39003 0.39003 1.70794 1.70794 0.61560 0 19930 0 19930 1.28877 0.47106 0.47644 Vb Vb variation % Vb Vb variation % Among C ollcctions. ollcctions. C Among Vb Vb variation % 0.00700 0.00700 0.00125 0.00531 Among C olteelion: olteelion: C Among 0.00254 000755 0.00064 Among Collection: Collection: Among 0.00203 0.00161 0.00528 Among Oceans: Oceans: Among Among Groups: Groups: Among Among Groups: Groups: Among 1 1 0.01013 2.34820 FST : : FST 0.00000 p= 0.02306 : FSC p-0.00098 0.00768 FCT: p=0.00000 0.01549 2 2 3 0.00645 0.00169 1.90497 0.41363 1 1 0.01705 3.85575 FCT: p=0.00000 0.02511 FST : : FST p=0.00000 0.02807 FSC: FCT: p=0.00000 0.01177 p=O.OOOIO 0.01650 FST : : FST 0.00000 : FSC p= 0.03424 p=0.00000 0.00936 2 2 3 0.00942 0.00308 2.92618 0.74644 Locus Locus . Va variation % MNO I I MNO MN08 MNIO 0.01107 0.00678 2.52879 0.00148 2.12134 0.35680 locus Va variation “o Locus Locus Va variation % Atlantic vs Pacific Average F-Statistics over all loci loci all over F-Statistics Average Atlantic vi Indian Average F-Slatistics over all loci loci all over F-Slatistics Average permutations. Atlantic vi Pacific vs Indian loci all over F-Slatistics Average Tabic 6. Locus by locus AMOVA ofsailfish microsatellite data based on number ofdifferent alleles (Fs^

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 3<>4 io~~

o Ft I P-salue 0 00099 0 .12942 -0 00517 0 8X954 •OIIIIXX 0 71554 ooinni 1st I’value 1(1 P-value iihim Fixation indices indices Fixation I isationI indices value S I I P-valuc P-valuc I S I P-value 0 137X3 0 00566 (107918 0 01955 1100147 0 041111 0 000110 0 01619 0II09X II nxniso oooxoi IS t I St I Fixation indices 99 43419 (100467 99 65252 0 00X61 9X 161.17 0 02794 variation variation Vc °o satiation 0 42142 0 20040 os 5.1952 0 47.150 0 0 OK 1 2 6 li|2 000226 2 IO0 16422 llllllllllll 111)44611 OOIS26 IKI4I4X001466 IIOIOSS 001.101 (102346 041.127 25X73 OK 0022220 00000 OOI74I 0 00000 -0 00402 0 52100 .10957 (I 0 4311.1 0.41691 0.420X6 OS 27995 11(1104 tl 0 34711 0(147311 000000 004515 0 004K3 Ve “o 04I47S 99514 9X (1017IX 1100301 no|f|i|S 0 011000-0 0074(1 OOIIOX Ve °u satiation FSC P value SI I P-value t I I P-value 0.2K0IX 00 10X66 -000731 Within Collections: Collections: Within Within Collections 223322 0 32.132 0 32.132 0.46696 2 2 82707 “o variation variation “o Vb Among Collection: Collection: Among Vb Vb variation % Vh Vh variation % 0.00030 000130 000066 0 31373 OOOI45 OOOI45 Among Collection. Among 000.174 000.174 0 X6496 (11198 0 0.000X2 0.000X2 0.IX50X 0.00733 .75075 -0.00200 -0.00200 -0.70010 Among Collection:Among Collections Within Among Groups: Groups: Among Vn Vn variation % Among Groups: Groups: Among 0.02003 0.02003 0.00452 4.534% 60053 1 -0.00313 -0.00313 -0.74600

1 1 -000224 -0.5I74X FST : : FST 000874: FSC p (1.00000 : 001462 FC'T pMI.00000 65494 -000597 pM) 1 1 0.0IX3X 4 14776 2 2 .1 0.000.31 -0.00504 09X66 0 -I IKK44 1 FCT : : FCT p-0.006X4 0.01740 3 3 -0.00207 49195 -0 FSC: p=OOI9XO FCT: 0.0054X p-0.0IXI2 0.01874 FST: : FSC p-0.00000 0.02727 p-0.00000 0.01004 FST: p=0.00000 0.02412 2 3 2 2 0.00384 1.30328 Uicus Uicus Va variation % Locus Average F'-Slatislics rivet all Inci Inci all rivet F'-Slatislics Average Indian vs WP E P v t IW P Locus Va variation % Average F-Stalistics over all loci loci all over F-Stalistics Average Among Groups: Among E P v» W P Average F-Statistics overall loci overall loci F-Statistics Average

~~Average F-Slalislics over nil loci~~

~~iVUHtl) LSHftCZ HSOOO0 0 OMiil 0 It I Hf L<< Z\r I IS FXIOOO II iftHI HiiiOO (I 0~~

dt r HilI 'il SFOO 'O 0 £?IOOO 0 X'UOl SlFSOOO l i'lill HSillKI Hr. idit U (,11100 0 OOOOO tfdldd (» 0(1000 HdldOd IVliOd 1X0 11. 11. OOODIIO 0 03097 0(1(17X2 I S I I S I I’-value C l I P-Vulue 0 01012 0 000000 0I7XX 0 000000 02420 0.00343 0 0009X ((03572 (HUH (HUH 0 01504 '-value ISC ISC 1' l ivution indues l ivution 0 001)01 0 01774 0 00000 1.71909 0 41977 95 1X429 vnrialion Vc vuiiuhon “n Among Collection:Among Colleiliims Within O.OOI88 0 58667 0.31 138 90 9X775 0.00758 0.02014 0.00000 0.02014 0.0I26K 0.00000 0.0I26K 0.03256 0.00000 0.00000 0.03256 0.01366 3.09662 Among Groups: Among 1 FCT 2 0.00779 2.42558 FST FSC 3 0.00226 0.54526 0.00516 1.24317 0.40758 9X 2II5X 0 01250 0 00000 Locus Va variation % Vb % Average F-Statistics over all loci all over F-Statistics Average A ll v> IW P

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 187 Table 7a. Population pairwise FSTs for MN01 locus. Values significant at the 0.01 level are bolded and underlined. Values significant between 0.01 and 0.05 are bolded. Exact P values after 10,000 simulations.

SEN GHA BRA FLA AUS CAB MAZ ECU TAW PNG PER KEN SEN 0.00000 GHA 0.01123 0.00000 BRA 0.01037 ■0.00472 0.00000 FLA 0.02142 0.00074 -0.00258 0.00000 ALS 0.05452 0.03608 0.03112 0.04206 0.00000 CAB 0.07091 0.06103 0.05575 0.05807 0.03603 0.00000 MAZ 0.09584 0.09199 0.08934 0.08669 0.08308 0.01682 0.00000 ECU 0.06539 0.06250 0.05879 0.06048 0.04880 -0.00492 0.00074 0.00000 TAW 0.04083 0.02220 0.01761 0.01688 0.00049 0.01654 0.06355 0.03198 0.00000 PNG 0.04103 0.03869 0.03167 0.03840 0.00373 0.02228 0.06369 0.03586 0.00471 0.00000 PERI 0.03779 0.04932 0.04065 0.03536 0.02655 0.00339 0.01995 0.00540 0.01401 0.00986 0.00000 KEN 0.03690 0.01884 0.01571 0.01545 0.00088 0.02123 0.06246 0.03142 -0.00596 0.00823 0.01622 0.00000

Table 7b. Population pairwise RSTs for MN01 locus. Values significant at the 0.01 level are bolded and underlined. Values significant between 0.01 and 0.05 are bolded. Exact P values after 10.000 permutations.

SEN GHA BRA FLA ALS CAB MAZ ECU TAW PNG PER KEN SEN 0.00000 GHA 0.00678 0.00000 BRA 0.00625 -0.00647 0.00000 FLA -O.OI43S 0 00318 0.00268 0.00000 ALS 0.14546 0.09988 0.09740 0.13964 0.00000 CAB 0.21110 0.14952 0.15029 0.20782 41.01694 0.00000 MAZ 0.26097 0.21135 0.20870 0.25570 0.00548 41.00587 0.00000 ECU 0.20193 0.14821 0.14589 0.19593 4)00971 -0.01442 -0 00294 0.00000 TAW 0.08370 0.04241 0.04056 0.07786 -0.00357 0.01015 0.04951 0.01926 0.00000 PNG 0.05572 0.02349 0.02154 0.05033 0.00011 0.01605 0.05713 0.02664 -0.00915 0.00000 PER 0.09353 0.04713 0.04604 0.08846 41.01409 4)00047 0.03699 0.00816 -0.01612 4)01638 0.00000 KEN 0.09552 0.04486 0.04400 0.08979 0.00064 0.01871 0.06354 0.02669 41.00782 -0.00913 4)01540 0.00000

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 188 Table 8a. Population pairwise FSTs for MN08 locus. Values significant at the 0.01 level are bolded and underlined. Values significant between 0.01 and 0.05 are bolded. Exact P values after 10000 permutations.

MAZ ECL CAB PNG TAW AL'S PER KEN FLA BRA SEN GHA MAZ 0.00000 ECU -0.00 239 0.00000 CAB -0.01741 -0.00455 0.00000 PNG 0 01840 0.00251 0.01904 0.00000 TAW 0 01292 (1.00101 001277 -0.01014 0.00000 AL'S 0.02971 002920 0.02774 0.01918 0.02585 0.00000 PER 0.05151 0.03890 0.05077 0.01807 0.02952 -0 01577 0.00000 KEN 0.01557 0.00178 0.01579 -0 01029 -0 00722 0.01867 0.01896 0 00000 FLA 0.06346 0.03269 0.06478 0.01801 0.03132 0.03975 0.02222 0.01982 0 00000 BRA 0.03308 001202 0.03383 0.02149 0.02495 0.06844 0.06652 0.02090 0.01346 0.00000 SEN 0.03348 0.00714 It.03477 -0.00814 -0.00140 0 03158 0.02248 -0 00518 -0.00069 0.00776 0.00000 GHA 0.03247 0.01134 0.03281 0.02271 0.02711 0.06115 0.05806 0.02137 0.00807 -0.00544 0.00779 0.00000

Table 8b. Population pairwise RSTs for MN08 locus. Values significant at the 0.01 level are bolded and underlined. Values significant between 0.01 and 0.05 are bolded. Exact P values after 10.000 permutations.

MAZ ECU CAB PNG T a W ALS PER KEN FLA BRA SEN GHA MAZ 0.00000 ECU -0.01039 0.00000 CAB -0.01801 -0.01657 0.00000 PNG 0.00378 0.00305 -000507 0.00000 TAW 0.02853 0.02412 0.01817 -0.00847 0.00000 ALS 0.02811 0.00626 0.02556 0.04459 0.08503 0.00000 PER 0.01364 0 00215 0.00482 0.03303 0.06897 -0.02222 0.00000 KEN 0.00299 0.00400 -0 00503 -0.01068 •0.00491 0.04099 0.03389 0.00000 FLA 0.09288 0.07039 0.07219 0.10779 0.15567 0 01094 0.00641 0.11342 0.00000 BRA 0.01823 0 01457 0.01074 0.04700 0.07629 -0.01225 -0.01231 0.04871 0.00724 0.00000 SEN -0.01285 -0 01202 -0.01911 -0.00186 0.01650 -0.00634 -0.00841 0.00047 0.04241 0.00648 0.00000 GHA 0.00946 0.00719 0.00075 0.02940 0.05486 -0.01472 -0.01477 0.03421 0.00042 -0.00643 -0.(10050 0.00000

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 189 Table 9a. Population pairwise FSTs for MN10 locus. Values significant at the 0.01 level are bolded and underlined. Values significant between 0.01 and 0.05 are bolded. Exact P values after 10,000 permutations.

AUS CAB MAZ ECU TAW PNG 1PER KEN FLA BRA SEN AUS 0.00000 CAB 0.00882 0.00000 MAZ 0.00143 0.04696 0.00000 ECU -0.00425 0.03*24 0.00679 0.00000 TAW -0.01157 0.01408 0.00715 -0.00008 0.00000 PNG -0.00432 0.0465* 0.00842 0.01135 0.00482 0.00000 PER 0.05774 0.00735 0.10*6* 0.10072 0.07257 0. 1166* 0.00000 KEN -0.00696 0.03469 0.01*49 0.00143 -0.00131 0.00157 0.1006* 0.00000 FLA -0.00077 0.02*69 0.01567 -0.00125 0.00191 0.02744 0.0*617 0.01034 0.00000 BRA -0.00017 0.02622 0.0144* 0.00618 0.00556 0.03166 0.07177 0.01847 -0.00624 0.00000 SEN -0.01116 0.01721 0.02462 -0.00259 -0.00224 0.01*91 0.06588 -0.00160 -0.00252 0.00322 0.00000 GHA 0.00108 0.03435 0.02427 0.0002S 0.00687 0.03300 0.0*352 0.01079 -0.00307 0.00384 -0.00402 0.00000

Table 9b. Population pairwise RSTs for MN10 locus. Values significant at the 0.01 level are bolded and underlined. Values significant between 0.01 and 0.05 are bolded. Exact P values after 10,000 permutations.

AUS CAB MAZ ECU TAW PNG PER KEN FLA BRA SEN GHA AUS 0.00000 CAB -0.02360 0.00000 MAZ -0.01652 -0.01421 0.00000 ECU -0.00224 -0.00367 0.01520 0.00000 TAW -0.01597 -0.01563 -0.00726 0.00039 0.00000 PNG •0.01128 -0.01220 0.00344 -0.00938 -0.00642 0.00000 PER -0.01893 •0.01460 -0.01693 0.02067 -0.00988 0.00647 0.00000 KEN -0.01421 -0.01457 -0.00278 -0.00183 -0.00738 -0.00795 -0.00293 0.00000 FLA -0.01334 -0.01407 0.00060 -0.01029 -0.00771 -0.01321 0.00178 -0.00909 0.00000 BRA -0.01395 -0.01285 -0.00797 0.00693 -0.00527 -0.00079 -0.01211 -0.00322 -0.00217 0.00000 SEN -0.01678 -0.01740 -0.00336 -0.01076 -0.01104 -0.01496-0.00088 -0.01211 -0.01590 -0.00602 0.00000 GHA 0.00821 0.00612 0.02*15 -0.00628 0.00856 -0.00483 0.03543 0.00565 -0.00588 0.01579 -0.00499 0.00000

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 190~~

~~Table 10a. Population pairwise FSTs over all loci. Values significant at the 0.01 level are bolded and underlined. Values significant between 0.01 and 0.05 are bolded. Exact P values are below.~~

SEN GHA BRA FLA CAB ECU AUS MAZ TAW PNG PER KEN SEN 0.00000 GHA -0.00508 0.00000 BRA -0.00556 0.00157 0.00000 FLA -0.00026 -0.00400 -0.00750 0.00000 CAB 0.0365* 0.04485 0.04043 0.04969 0.00000 ECU 0.02243 0.03318 0.02832 0.03548 0.00824 0.00000 AUS 0.02912 0.01374 0.01294 0.01818 0.02504 0.01769 0.00000 MAZ 0.05949 0.06136 0.04938 0.06235 0.01764 0.00182 0.04223 0.00000 TAW 0.00520 0.01353 0.01421 0.00957 0.01626 0.01477 -0.01047 0.03263 0.00000 PNG 0.00808 0.02796 0.02578 0.02335 0.02579 0.01852 -0.00929 0.03127 0.00244 0.00000 PER 0.0377* 0.04395 0.05390 0.04948 0.01349 0.04686 0.02233 0.06482 0.03071 0.04098 0.00000 KEN 0.00081 0.01444 0.01582 0.01231 0.01753 0.01240 -0.01379 0.03131 -0.00647 -0.00006 0.03634 0.00000

~~Table 10b. Population pairwise RSTs over all loci. Values significant at the 0.01 level are bolded and underlined. Values significant between 0.01 and 0.05 are bolded. Exact P values are below.~~

SEN GHA BRA FLA CAB ECU AUS MAZ TAW PNG PER KEN SEN 0.00000 GHA -0.00771 0.00000 BRA -0.04846 -0.00053 0.00000 FLA -0.03205 0.00790 -0.01196 0.00000 CAB 0.13325 0.06563 0.03889 0.11230 0.00000 ECU 0.11242 0.07301 0.06462 0.10955 -0.01848 0.00000 AUS 0.08802 0.03754 -0.01084 0.04637 -0,01261 -0 01574 0.00000 MAZ 0.17368 0.12963 0.09004 0.15879 -0.00709 0.00740 -0.00068 0.00000 TAW 0.05304 0.03012 0.03308 0.06621 -0.01474 0.00111 -0.02025 0.02125 0.00000 PNG 0.01330 0.00385 0.00699 0.01525 -0.00916 0.00905 -0.01393 0.04075 -0.00651 0.00000 PER 0.06687 0.02810 -0.00916 0.04349 -0.00206 0.00231 -0.01518 0.02576 -0.01739 -0.03010 0.00000 KEN 0.03507 0.02356 0.02050 0.05201 -0.00405 0.01485 -0.01225 0.04143 -0.00647 -0.01086 -0.01415 0.00000

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 191~~

~~Figure 1. Allele frequency distributions for the three microsatellite loci.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Distribution of MN01 Alleles~~

~~0.25~~

~~0.2~~

~~0.15 ■ Frequency~~

~~0.1~~

~~0.05 0 III li.. n-KOcocMtoa>«- v - e - CM CM CM CO Number of Repeats~~

~~Distribution of MN08 Alleles~~

~~0.6 0.5 > g 0.4 5 0.3 ■ Frequency 9 • 0.2 Ik 0.1 0 CO (O 0 ) CM t o eo ** ^ ^ CM <>4 CM Number of Repeats~~

~~Distribution of MN10 Alleles~~

~~0.35 0.3 u 0.25 3 0.2 ■ Frequency cr 0.15 0.1 0.05 0 ^KOCOCOO>CMIOflO«-*^■e-e-^CMCMCMCO Number of Repeats~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 193~~

~~Figure 2. Allele frequency distributions for Atlantic. Eastern Pacific and Indo-west Pacific sailfish based on three microsatellite loci.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. MN 01~~

~~1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24~~

~~Repeat No.~~

~~MN 08~~

~~0.7 0.6 0 5 ; - : r. 04 O e p ! I ... 0 3 H B i w p ; 0.2 1 d A TIJ 0.1 fl I 0 ...... d l — 9 m m 10 II 12 13 14 15 16 17 18 19~~

~~Repeat No.~~

~~MN 10~~

~~§BEP § BIWP 1 DATL~~

~~Repeat No.~~

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 4. NUCLEAR AND MITOCHONDRIAL DNA MARKERS FOR SPECIFIC IDENTIFICATION OF ISTIOPHORID AND XIPHIID BILLFISHES

~~195~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 196~~

~~INTRODUCTION~~

~~Specific identifications of most marine fishes are typically based on adult~~

~~characters. However, distinguishing characters may be removed from adults as they are~~

~~processed for market or personal consumption, making specific identification~~

~~problematic. Furthermore, specific identification of early life history stages of many~~

~~marine fishes is not possible, as diagnostic morphological characters are not known.~~

~~Consequently, alternative means of identification are needed.~~

~~A variety of molecular genetic characters have been used to provide~~

~~identifications of marine fishes. Marine fish eggs and larvae have been identified using~~

~~allozymes (Mork, et al., 1983; Graves et al., 1988), restriction analysis of whole~~

~~mitochondrial (mt) DNA (Daniel and Graves, 1994), restriction analysis of specific~~

~~mtDNA gene regions (Luczkovich et al., 1999), and specific amplification of mtDNA~~

~~gene regions (Rocha-Olivares, 1998). A similar suite of molecular markers has been~~

~~used to provide positive identification of adult marine fish tissues, with recent emphasis~~

~~on restriction analysis of amplified regions of the mitochondrial genome (Chow et al.,~~

~~1993; Chow 1994, Chow and Kishino, 1995; Heist and Gold, 1997; Innes et al., 1998;~~

~~Cordes and Graves, 2001).~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 197 To be effective, a diagnostic molecular marker must demonstrate consistent~~

~~differences among closely related species and exhibit very limited intraspecific variation.~~

~~Restriction analyses of regions of the mitochondrial genome have met these criteria for~~

~~several marine fishes. However, reliance on a single, maternally inherited character~~

~~(mtDNA) can provide misleading results in situations where there is a possibility of~~

~~hybridization or introgression. and analyses of both nuclear and mitochondrial markers~~

~~are desirable.~~

~~The istiophorid and xiphiid billfishes (marlins, spearfishes. sailfish and swordfish)~~

~~represent an important commercial and recreational fisheries resource. Due to depleted~~

~~stock levels, current regulations within the United States prohibit the sale of istiophorid~~

~~billfish taken in the Atlantic Ocean. While adult billfishes are easily discriminated on the~~

~~basis of morphological characters, these characters are typically removed during~~

~~processing, preventing morphological identification. In addition, the early life history~~

~~stages of istiophorid billfishes are not well known, and specific identification is~~

~~problematic (Nakamura, 1985).~~

~~Chow (1994) used 13 restriction enzymes in a restriction fragment length~~

~~polymorphism (RFLP) analysis of a 350 bp region of the mtDNA cytochrome b gene to~~

~~discriminate among ten nominal species of billfishes; however samples sizes were small~~

~~for several species and banding patterns differed by as little as 15 base pairs, making~~

~~alternate patterns difficult to distinguish. Innes et al. (1998) were able to discriminate~~

~~among seven species of billfish found in Australian waters with RFLP analysis of a 1400~~

~~bp region of the mtDNA control region (D-Ioop). Their analysis, which employed four~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 198 restriction enzymes, revealed relatively high levels of intraspecific variation of the~~

~~diagnostic characters within some species, and there was some overlap of banding~~

~~patterns betw een species. In neither study was an independent nuclear marker developed~~

~~to corroborate specific identifications based on analyses of mtDNA.~~

~~In this paper we present a molecular key to the identification of istiophorid and~~

~~xiphiid billfishes using RFLP analyses of independent mitochondrial and nuclear DNA~~

~~regions. We demonstrate low intraspecific variation of the characters within large~~

~~collections of individuals sampled from throughout each species’ range, and show' the~~

~~utility of the markers for the identification of fillets and early life history' stages.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 199~~

~~MATERIALS AND METHODS~~

~~Collections of striped marlin Tetrapturus audax, white marlin Tctrapturus albidus,~~

~~blue marlin Makaira nigricans, and sailfish Istiophorus platypterus were available from~~

~~previous analyses of stock structure (Graves and McDowell 1994. 1995: Graves. 1998).~~

~~and individuals from locations throughout each species’ range were selected for the~~

~~present study (Table 1). These DNA samples consisted of the nuclear and mitochondrial~~

~~bands resulting from mtDNA purifications using the equilibrium density gradient~~

~~centrifugation protocols of Lansman et al. (1981). Samples of black marlin Makaira~~

~~indica, longbill spearfish Tctrapturus pfluergcri. shortbill spearfish Tctrapturus~~

~~angustirostris and swordfish Xiphias gladius, were obtained from recreational and~~

~~commercial fishers (Table 1) and consisted of either frozen heart tissue or white muscle~~

~~tissue preserved in DMSO storage buffer (Seutin et al., 1991). DNA was extracted from~~

~~these tissues following the protocols of Winnepenninckx et al. (1993).~~

~~Evaluation of candidate mitochondrial and nuclear loci involved a two-step process.~~

~~The first was to ensure consistent amplification by the polymerase chain reaction (PCR)~~

~~of a similar sized product across all taxa. The second step was to screen those loci that~~

~~successfully amplified across all billfish species with a panel of restriction endonucleases~~

~~to identify enzymes that discriminated among species and revealed limited intraspecific~~

~~variation.~~

~~Several candidate mitochondrial and nuclear gene regions were amplified by PCR~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 200 (Table 2). The 25ul PCR reactions consisted of 0.25 pi template DNA, 2.5pl 10X PCR~~

~~buffer plus magnesium, 0.5pl dNTP mix. 0.25jil forward primer, 0.25gl reverse primer.~~

~~0.125|il Taq DNA polymerase. and 21.125pl PCR grade water. Primers were ordered~~

~~from either Life Technologies (Gaithersburg. MD) or Genosvs Biotechnologies Inc (The~~

~~Woodlands. TX). and PCR reactions were carried out in an MJ Research Corporation~~

~~PTC-200 Peltier Thermal Cycler (Watertown, MA) using the Life Technologies PCR~~

~~Reagent System (Gaithersburg. MD). Initial screening demonstrated that the~~

~~mitochondrial ND4 gene region and the nuclear BM32-2 locus produced the most reliable~~

~~amplifications across taxa and PCR conditions were optimized for these loci. The~~

~~cycling parameters for the ND4 gene region were an initial denaturation at 95°C for 5~~

~~min.. followed by 35 cycles of 94°C for 1 min.. 47°C for 1 min. 65l’C for 3 min.. and a~~

~~final extension at 65"C for 7 min. Amplification of BM32-2 proceeded with an initial~~

~~denaturation at 95' C for 5 min.. 40 cycles of 94°C for 1 min.. 57°C for 1 min.. 65°C for 3~~

~~min., and a final extension at 72°C for 7 min. Amplified products were held at 4°C until~~

~~use. The size of each amplification product was determined on a 1 % agarose gel run in~~

~~TBE at 100 volts for 1 hour. ND4 amplification resulted in a product of approximately~~

~~1.7 kb and BM32-2 amplification resulted in a product of approximately 1.2 kb.~~

~~Amplified products were screened with a panel of restriction endonucleases to~~

~~identify those that discriminated among species, and revealed a minimum level of~~

~~variation within species. All enzymes were purchased from Gibco/BRL Life~~

~~Technologies Inc. (Bethesda, MD) with the exception of Banl. which was purchased~~

~~from Promega (Madison, WI). All were used according to the manufacturers’~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 201 instructions.~~

~~Restriction fragments were separated on 2.5% horizontal agarose gels made from~~

~~1.25% UltraPure agarose (Life Technologies Inc., Bethesda. MD) and 1.25% NuSeive~~

~~GTG agarose (FMC BioProducts, Rockland, ME), and visualized under UV light after~~

~~staining with ethidium bromide. Fragment sizes were estimated by comparison with a 1~~

~~kb size standard (Life Technologies Inc.. Bethesda. MD) using RFLPScan Plus 3.0~~

~~(Scanalytics, Billerica. MA).~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. RESULTS~~

~~Mitochondrial marker.~~

~~Four mtDNA regions, cytochrome b. D-loop, ND4, and ATPase. were included in the~~

~~initial screening (Table 2). The ATPase region was tested with eight potentially useful~~

~~enzymes based on published sequences and was found to have an extremely low level of~~

~~inter-specific variation with many species exhibiting identical banding patterns. The~~

~~cytochrome b region was screened with four enzymes based on published sequences, but~~

~~because of the small size of the amplification product (350bp), differences in banding~~

~~patterns were small and difficult to distinguish. The D-loop region was screened with a~~

~~total of 40 enzymes. O f these, Bel I, Alu I, Rsa I and H in f I were tested with up to 50~~

~~individuals from each species. Banding patterns that were initially thought to be~~

~~diagnostic for blue marlin based on Rsa 1 were found to occur at low frequency in~~

~~sailfish. This overlap combined with the large amount of intra-specific variation in some~~

~~species made this region unsuitable for use as a forensic marker. Finally, the ND4~~

~~region was screened with a total of 47 restriction enzymes. Of these, 17 were tested more~~

~~extensively, and the combination of Banl and HaelII was found to be diagnostic and to~~

~~reveal a low level of intra-specific variation.~~

~~After finding diagnostic enzymes for use with the ND4 region, a total of 540~~

~~billfish samples was screened (Table 1) to evaluate the accuracy of the marker. Samples~~

~~from a broad geographic range including both the Atlantic and Indo-Pacific were used for~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 203 each species whenever possible. Of these, the white marlin, spearfishes and sailfish each~~

~~exhibited one alternative restriction pattern for Hae III at low frequency (3.6, 20.0 and~~

~~7.4% respectively) but in no case was the alternate pattern the same as a pattern seen in~~

~~another species (Table 3). In addition, spearfishes exhibited an alternate pattern for the~~

~~enzyme Ban I at a frequency of 40%; however, since Ban I was only used to discriminate~~

~~white/striped marlin from sailfish in the ND4 identification key, this did not affect the~~

~~results (Figs. 1. 2).~~

~~A'uclcar marker.~~

~~Six nuclear markers were screened in the preliminary analysis (Table 2). These~~

~~included the short actin intron, the internal transcribed spacer (ITS) region (Goggin,~~

~~1994). and four anonymous single copy nuclear (scnDNA) markers. The scnDNA~~

~~markers. BM32-2, BM47, BM81, and WM08 were originally developed for analyses of~~

~~population structure in blue marlin (Buonaccorsi et al., 1999). The short actin intron~~

~~primers were modified from "universal" actin gene primers "480"and "483" (Siddall et~~

~~al., 2001).~~

~~Both the short actin and the ITS marker were rejected because neither marker~~

~~amplified reliably across species. For the scnDNA markers, the program GeneJockey~~

~~(Taylor, 1996) was used to search for the presence of restriction sites in sequences~~

~~previously generated for blue marlin. The WM08 marker was screened with a total of ten~~

~~enzymes, each of which produced identical patterns across species. BM47 and BM81~~

~~were also screened with ten enzymes each. For BM47 the combination of enzymes Bel I~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 204 and Dde I appeared to be diagnostic in a preliminary screening. However, upon further~~

~~analysis, it was discovered that this combination of locus and enzymes produced~~

~~confounding patterns for blue marlin and sailfish; the most common pattern for blue~~

~~marlin was seen as a rare pattern for sailfish. Likewise, the BM81 locus did not~~

~~distinguish between blue marlin and sailfish or between white/striped marlin and~~

~~spearfish with any of the enzymes used. The BM32-3 locus was screened with a total of~~

~~nine restriction endonucleases. The combination of Dra I and Dde I was found to allow~~

~~for unambiguous identification of billfish species (Figs.3. 4).~~

~~As with the ND4 locus, after determining a diagnostic enzyme-marker~~

~~combination, a total of 540 billfish samples from a broad geographic range was screened~~

~~to evaluate the accuracy of the marker (Table 1). The enzyme Dra I was found have two~~

~~alternate alleles. “D” and "E" for blue marlin at a frequency of 19% and 5.5%~~

~~respectively. All other species appeared to be fixed for different (homozygous) alleles~~

~~with respect to this enzyme. For Dde I. spearfishes had an alternate allele, “E”. at a~~

~~frequency of 36%. In addition, blue marlin had two alternate alleles “H” and ‘T* at~~

~~frequencies of 16% and 50%. respectively (Table 4). Although the “H" allele in blue~~

~~marlin was the only allele seen in black marlin, use of Dde I was not necessary to~~

~~distinguish the two species since they are easily differentiated by Dra I (Figs. 3. 4).~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 205~~

~~DISCUSSION~~

~~The purpose of this study was to develop a key to the identification of billfish~~

~~species based on independent mitochondrial and nuclear markers. Our goal was to make~~

~~the process streamlined and capable of being performed in a modestly equipped genetics~~

~~laboratory. Specific identification can be accomplished with a single PCR amplification~~

~~of either the mitochondrial ND4 locus or nuclear BM32-2 locus and two restriction~~

~~digestions. Previous methodologies using other mitochondrial gene regions required the~~

~~use of either four or 13 restriction digestions (Innes et al., 1998 and Chow 1994,~~

~~respectively).~~

~~To facilitate specific identification, an objective of this study was to develop~~

~~diagnostic markers that exhibited limited intraspecific variation. Analysis of large~~

~~sample sizes (60 - 100 or more) of sailfish, white marlin, striped marlin, blue marlin, and~~

~~black marlin from throughout each species’ range revealed minimal variation of the~~

~~species-specific characters. Most species displayed a single genotype for digestions with~~

~~the two enzymes used to cleave either the mitochondrial or nuclear amplification~~

~~products, and no species exhibited more than three genotypes for any locus/restriction~~

~~enzyme combination. In contrast, Innes et al. (1998) reported ten composite haplotypes~~

~~among 47 black marlin, six composite haplotypes among 26 blue marlin, six composite~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 206 haplotypes among 46 striped marlin, and six haplotypes among 21 swordfish, all from the~~

~~southwest Pacific. Based on the level of intraspecific variation relative to the sample~~

~~sizes and the regional nature of their collections, it is reasonable to assume that Innes et~~

~~al. (1998) may have missed several composite genotypes characteristic of the different~~

~~species. In fact, based on the level of variation exhibited by black marlin, striped marlin~~

~~and swordfish. Innes et al. (1998) suggested their diagnostic species markers could be of~~

~~potential use in population structure analyses. It occurs to us that if a genetic character~~

~~exhibits sufficient intraspecific variation to be useful for analyses of stock structure, it is~~

~~probably not a good candidate for specific identification.~~

~~A high degree of genetic similarity was noted among white marlin and striped~~

~~marlin in the present study. None of the molecular markers evaluated in this study was~~

~~able to unambiguously distinguish between the two species. Chow (1994) was also~~

~~unable to distinguish between the two species based on RFLP analysis of the cytochrome~~

~~b gene, and Innes et al. (1998) did not consider white marlin in their investigation as it~~

~~does not occur in Australian waters. RFLP analysis of the whole mtDNA molecule~~

~~indicated that white and striped marlin share composite haplotypes, although there are~~

~~highly significant frequency differences between the species (Graves and McDowell,~~

~~1995; Graves, 1998). Sequence analysis o f the mtDNA cytochrome b gene also~~

~~demonstrated a lack of genetic divergence among white and striped marlin (Finnerty and~~

~~Block, 1995), and a further genetic analysis of the species’ relationships is warranted.~~

~~To evaluate the utility o f the methods outlined in this study to other investigators,~~

~~detailed protocols and six unknown billfish samples were sent to the Southeast Fisheries~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 207 Science Center’s (now National Ocean Survey’s) Charleston. SC laboratory. Scientists~~

~~at the Charleston Laboratory analyzed both mitochondrial and nuclear DNA markers for~~

~~each sample, and arrived at consistent, correct identifications for each of the unknowns.~~

~~In addition, samples of juvenile billfish collected by investigators at the University of~~

~~Miami were analyzed in our laboratory using these molecular markers. Samples~~

~~consisting of one eye taken from 3 mm juvenile billfish provided sufficient DNA to~~

~~amplify the mtDNA and nuclear markers, allowing specific identification (Fig. 5). The~~

~~technique is currently being used to determine the temporal occurrence of istiophorid~~

~~larvae in the Florida Straits (Luthy and McDowell. 2001).~~

~~While the methods presented in this study allow the specific identification of~~

~~billfish species, more sensitive molecular markers are required to distinguish among~~

~~ocean populations of some istiophorid species. Amendment I to the Fishery~~

~~Management Plan for Atlantic Billfishes prohibits the sale of blue marlin, white marlin~~

~~and sailfish taken in the Atlantic Ocean, although it is legal to market blue marlin, striped~~

~~marlin, and sailfish from the Indian or Pacific oceans. Enforcement of this regulation~~

~~requires the ability to discriminate between Atlantic and Indo-Pacific individuals of blue~~

~~marlin, sailfish, and white/striped marlin. Examination of our results suggests that there~~

~~are several other molecular markers, which while not used in this study, occur at~~

~~relatively high frequencies in Atlantic blue marlin, sailfish, and white marlin, but do not~~

~~occur, in their Pacific conspecifics. These molecular markers could potentially be used~~

~~to identify some Atlantic individuals without misclassifying a Pacific fish, thereby~~

~~allowing the enforcement of the management plan. Additional work will be required to~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. develop a database that would support such analyses.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 209~~

~~LITERATURE CITED~~

~~Bielavvski. J.P and J.R. Gold. 1996. Unequal synonymous substitution rates within and~~

~~between two protein-coding mitochondrial genes. Mol. Biol Evol. 13:889-892~~

~~Buonaccorsi. V.P.. K.S.. Reece. L.W. Morgan, and J.E. Graves. 1999. Geographic~~

~~distribution of molecular variance within the blue marlin (Makaira nigricans): A~~

~~hierarchical analysis of allozyme. single-copy nuclear DNA, and mitochondrial~~

~~DNA markers. Evolution 53: 568-579.~~

~~Chow, S. 1994. Identification of billfish species using mitochondrial cytochrome b gene~~

~~fragment amplified by polymerase chain reaction. Intematl. Comm. Conserv. Atl.~~

~~Tunas. Report of the 2nd ICCAT billfish workshop. ICCAT XLI, 549-56.~~

~~Chow. S., M.E. Clarke, and P. J. Walsh. 1993. PCR-RFLP analysis on thirteen western~~

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~~identification. Fish. Bull. 91: 619-627.~~

~~Chow, S and H. K.ishino.1995. Phylogenetic relationships between tuna species of the~~

~~genus Thunnus (Scombridae: Teleostei): Inconsistent implications from~~

~~morphology, nuclear and mitochondrial genomes. J. Mol. Evol. 41: 741-748.~~

~~Chow, S. and K. Hazama.1998. Universal PCR primers for S7 ribosomal protein gene~~

~~introns in fish. Mol. Ecol. 7: 1247-1263.~~

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~~Chesapeake Bay sportfishes using mitochondrial DNA restriction fragment -~~

~~length polymorphism (RFLP) analysis. Estuaries. 24: 49-58.~~

~~Daniel. L.B. Ill and J.E. Graves. 1994. Morphometric and genetic identification o f~~

~~eggs of spring-spawning sciaenids in lower Chesapeake Bay. Fish. Bull. 92:254-~~

~~261.~~

~~Finnerty. J.R. and B.A. Block. 1995. Evolution of cytochrome b in the Scombroidei~~

~~(Teleostei): Molecular insights into billfish (Istiophoridae and Xiphiidae)~~

~~relationships. Fish. Bull. 9:78-96.~~

~~Goggin. C.L. 1994. Variation in the two internal transcribed spacers and 5.8S ribosomal~~

~~RNA from five isolates o f the marine parasite Perkinsits (Protista. Apicomplexa).~~

~~Mol.and Biochem. Parasitology. 65 (1994)179-182.~~

~~Graves. J.E. 1998. Molecular insights into the population structures o f cosmopolitan~~

~~marine fishes. J. Heredity 89:427-437.~~

~~Graves. J.E.. and J.R. McDowell. 1994. Genetic analysis of striped marlin Tctrapturus~~

~~audax population structure in the Pacific Ocean. Can. J. Fish. Aquat. Sci.,~~

~~51:1762-1768.~~

~~Graves, J.E.. and J.R. McDowell. 1995. Inter-ocean genetic divergence o f istiophorid~~

~~billfishes. Mar. Biol. 122:193-204.~~

~~Graves, J.E., M.A. Simovich and K..M. Schaefer. 1988. Electrophoretic identification~~

~~o f early juvenile yellowfin tuna. Fish. Bull., 86: 835-838~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Heist, E.J.. and J.R. Gold. 1997. Genetic identification o f sharks in the US Atlantic~~

~~large-coastal fishery. Fish. Bull. 97:53-61.~~

~~Innes, B. H ., P. M. Grewe, and R. D. Ward. 1998. PCR-based genetic identification~~

~~o f marlin and other billfish. Mar. Freshwater Res. 49: 383-388.~~

~~Lansman, R. A., R. O. Shade, J. F. Shapira and J. C. Avise. 1981. The use o f restriction~~

~~endonucleases to measure mitochondrial DNA sequence relatedness in natural~~

~~populations. J. Mol. Evol. 17: 214-226.~~

~~Luczkovich, J. J.. H. J. Daniel, M. W. Sprague, S. E. Johnson, R. C. Pullinger, T.~~

~~Jenkins, and M.Hutchinson. 1999. Characterization o f critical spawning habitats~~

~~o f weakfish, spotted seatrout and red drum in Pamlico Sound using hydrophone~~

~~surveys. Final report to the North Carolina Division of Marine Fisheries under~~

~~grant numbers F-62-1 and F-62-2. North Carolina Department of Environment~~

~~and Natural Resources, Division o f Marine Fisheries. Morehead City. NC 28557.~~

~~Luthy, S. and McDowell, J. 2001. A Molecular approach to the identification o f larval~~

~~billfishes. Submitted to the Australian Journal o f Marine and Freshwater Research~~

~~as part of the 3rd International Billfish Symposium. CSIRO Publishing, 150~~

~~Oxford St. Collingwood, Vic. 3066, Australia.~~

~~Mork, J., P. Solemdal, and G. Sundnes. 1983. Identification o f marine fish eggs: a~~

~~biochemical genetics approach. Can. J. Fish. Aquat. Sci. 40: 361-369.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Nakamura, I. 1985. FAO species catalogue. Vol. 5: Billfishes of the world: an~~

~~annotated and illustrated catalogue o f marlins, sailfishes, spearfishes and~~

~~swordfishes known to date. FAO Fish Synop 125.~~

~~Palumbi, S., A. Martin, S. Romano, W.O. McMillan, L. Stice, et al., 1991. The~~

~~Simple Fool’s Guide to PCR, 47 p. Department o f Zoology and Kewalo Marine~~

~~Laboratory. University o f Hawaii, Honolulu, H.I.~~

~~Rocha-Olivares. A. 1998. Multiplex haplotype-specific PCR: a new approach for~~

~~species identification o f the early life stages o f rockfishes o f the species-rich~~

~~genus Scbastcs Cuvier. J. Exp. Mar. Biol. Ecol. 231: 279-290.~~

~~Scutin. G., B.N. White, and P.T. Boag. 1991. Preservation o f avian blood and tissue~~

~~samples for DNA analysis. Can. J. Zool. 69:82-90.~~

~~Siddall. M.E.. K.S. Reece, T.A. Nerad, and E.M. Burreson. 2001. Molecular~~

~~determiniation of the phylogenetic position o f a species in the genusColpodella~~

~~(Alveolata). American Museum Novitiates 3314: 1-10.~~

~~Taylor. P.L. 1996. GeneJockey-II Sequence processor. Software distributed by~~

~~BIOSOFT, Cambridge, UK.~~

~~Winnepenninckx, B., T. Backeljau, and R. De Wachter. 1993. Extraction o f high~~

~~molecular weight DNA from mollusks. Trends Genet. 9:407.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 1. Collection information for billfish samples surveyed.~~

Species______Location Number______Total Sailfish Brazil 34 99 Mexico 24 Ecuador 17 Australia 24 White Marlin Brazil 38 99 Morocco 36 Venezuela 25 Striped Marlin Mexico 28 96 Ecuador 38 Australia 30 Black Marlin Ecuador 12 60 Australia 48 Spearfish Venezuela 12 16 Hawaii 4 Blue Marlin Mexico 24 150 Australia 4 Ecuador 20 Hawaii 63 Jamaica 39 Swordfish Hawaii 20 20

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 214~~

~~Table 2. Primer pairs used to amplify regions evaluated in this study.~~

~~Locus Primer Sequence Source Cvtochrome b: CYTB-F TGGGSNCARATGTCNTWYTG Joseph Quattro. personal C iT B -R GCRAANAGRAARTACCAYTC communication~~

~~ATPase 6: ATPasc L833I T.AAGCRNYAGCCTTTT AAG Joseph Quattro. personal ATPase H8969 GGGGNCGRATRAANAGRCT communication~~

~~D-Loop: CB3R-L CATATTAAACCCGAATGATATTT Palumbi ct al.. 1991 12SAR-H ATAGTGGGGTATCTAATCCCAGTT~~

~~ND4: ND4 ARG-BL CAAGACCCTTGATTTCGGCTCA Bielawski and Gold. 1996 ND4 LEU CCAGAGTTTCAGGCTCCTAAGACCA~~

~~ITS: ITS-3 TATGCTTAAATTCAGCGGGT Goggin. C.L, 1994 ITS-5 CGTAGGTGAACCTGCGG.AAGG~~

~~SACTIN SACSMSF-F CGGACGCCCCCGTCACCAGGTAC This Study SACIN-R CCAGAGGCATACAGGGACAGCACAGC~~

~~BM32-2: BM32-2F GTAGCAAGGGGCTGTTGCATAG Buonaccorsi et al.. 1999 Bm32-2R GAGTCAGTGGTTCGGGATTTTATC~~

~~BM47: BM47-F GCTGTTGACCCAAACAATCCGG Buonaccorsi et al.. 1999 BM47-R GGGCATAAATGCTCAGGACACTT~~

~~BM81: BM81-F CACTCAAACAGGTGAATCCTGGC Buonaccorsi et al.. 1999 BM81-R C.AAAACAACAGATGCCGCTAAGG~~

~~WM08: WM08F AGCAGCTAGGGACACACGATTCC Buonaccorsi ct al., 1999 WM08R GGCAAACCTTACACTGAGGGGATG~~

~~5 Quattrro, J 1995. Department of Biological Sciences. University of South Carolina College of Science and Mathematics, Columbia, SC, 29208. Pers. Comm.~~

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 215 Table 3. Restriction fragment patterns o f the mitochondrial ND4 region o f istiophorid and xiphiid billfishes. Only diagnostic bands are shown.

~~(A) Digestions with Hae III. A=blue marlin; B=striped marlin, white marlin; C=white marlin, sailfish; D=black marlin; E=spearfish; F=white marlin; G=spearfish; H=swordfish.~~

~~A BC D EFG H 800 570 800 570 405 570 405 950 320 405 405 530 380 405 320 300 270 320 320 320 320 380 270 290~~

~~(B) Digestions with Ban I. A=blue marlin, black marlin, sailfish. spearfish; B=stiped marlin, white marlin, spearfish; C=swordfish~~

~~A BC 850 1500 700 650 400 650 400 400~~

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 216 Table 4. Restriction fragment patterns of the nuclear gene region BM32-2 o f istiophorid billfishes and their frequency o f occurrences. This locus did not amplify in the swordfish.

(A) Digestions with Dra I. A=blue marlin; B=striped marlin, white marlin, black marlin, sailfish; C=spearfish; D=blue marlin; E=blue marlin. AT) and A/E heterozygotes were seen in blue marlin cut with Dra 1. Individuals o f all other species were fixed homozygous.

~~ABCD 750 670 670 750 450 280 280 400 260 220 50~~

(B) Digestions with Dde I. A=blue marlin; B= striped marlin, white marlin; C=spearfish; D=sailfish; E=spearfish; H=bluc marlin; I=blue marlin. A 7I A H and H/I heterozygotes were seen in blue marlin cut withDdc I. C/E heterozygotes were seen in spearfish cut with Ddc I. Individuals o f all other species were fixed homozygous.

~~ABCD E H I 700 850 700 475 475 775 700 300 425 475 370 370 425 425 125 125 280 205 125 130 125~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 217~~

~~Figure 1 A. ND4 gel photograph. Most common restriction fragment patterns o f the ND4~~

~~mitochondrial gene region o f istiophorid billfishes. (A) Digestion withHae III. From~~

~~left to right. 1 kb DNA ladder, black marlin pattern D, blue marlin pattern A.~~

~~white/striped marlin pattern B. sailfish pattern B, shortbill spearfish pattern E, and~~

~~longbill spearfish pattern E. (B) Digestion with Ban I. From left to right, 1 kb DNA~~

~~ladder, black marlin pattern A, blue marlin pattern A, white/striped marlin pattern B,~~

~~sailfish pattern A, shortbill spearfish pattern B, and longbill spearfish pattern B.~~

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. .... ~ ...... ~ Ill ~"' :g" "=' ::; "=' ~ ~ j ...c.. "' §- .e •t: < ~ "' ..:: "' < ., ~ ;;; ~ :r. .... :::;: .. :r. ~ .Jf. "' z ~ -s; 'E ::: ... c .Jf. ..:: " " ~ ~ "'c.. ..c u .. ~ .Jf. ~ ·;; .."'c. ~ J. " ~ (/) = "' ~ = s =~

~~ND4 cut with Hae Ill ND4 cut \\ith Ban I~~

~~Figure 1B. ND4 gel line drawing. Most common restriction fragment patterns o f the~~

~~ND4 mitochondrial gene region o f istiophorid billfishes. (A) Digestion withHae III.~~

~~From left to right. 1 kb DNA ladder, black marlin pattern D. blue marlin pattern A,~~

~~white striped marlin pattern B. sailfish pattern B. shortbill spearfish pattern E. and~~

~~longbill spearfish pattern E. (B) Digestion with Ban I. From left to right, 1 kb DNA~~

~~ladder, black marlin pattern A. blue marlin pattern A. white/striped marlin pattern B.~~

~~sailfish pattern A. shortbill spearfish pattern B. and longbill spearfish pattern B.~~

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. e <3 S3 2 “3 2 - 3 “3 ■o *3 S3 e 3J ^ _ c .£• u *w £ < S3 < •xx Z X X. z . 3 2 cu i \r . o o c ; 3 -C n 3 **^ i . a . SQ a t S ailfish £ 7 5

~~2,036 1,636~~

~~1.018 1.018~~

~~506.517 506,517 396 344 a 298 298 220.201 154.134 154.134~~

~~ND4 cut with Hae III ND4 cut with Ban I~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 221~~

~~Figure 2. Key to distinguish species o f billfishes based on the mitochondrial locus ND4.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Swordfish HaelU Blue Marlin ND4 Black Marlin~~

~~Spearfish Striped Marlin B a n l Striped Marlin White Marlin White Marlin Sailfish Sailfish~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 223~~

~~Figure 3A. BM32-2 gel photograph. Most common restriction fragment patterns of the~~

~~nuclear gene region BM32-2 o f istiophorid billfishes. This locus did not amplify in the~~

~~swordfish. (A) Digestions withDra I. From left to right. 1 kb DNA ladder, blue marlin~~

~~pattern A. white/striped marlin pattern B, sailfish pattern B, black marlin pattern B,~~

~~shortbill spearfish pattern C. and longbill spearfish pattern C. (B) Digestions with Dde I.~~

~~From left to right. 1 kb DNA ladder, blue marlin pattern A, white/striped marlin pattern~~

~~B, sailfish pattern D, black marlin pattern H. shortbill spearfish pattern C. and longbill~~

~~spearfish pattern C.~~

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. I kb DNA Ladder ? m t m 11 Blue Marlin White/Striped Marlin H t - n ■ i Saillish i * i Black Marlin H t j Shonbill Spearfish t! I Longbill Spearfish

~~m i i m I kb DNA bidder i i s Blue Marlin f ta u i. While'Siriped Marlin Saillish t i t s : ; ' i i U K ) . Black Marlin it Shortbill Spearfish I t Longbill Speurfish 225~~

~~Figure 3B. BM32-2 gel line drawing. Most common restriction fragment patterns o f~~

~~the nuclear gene region BM32-2 o f istiophorid billfishes. This locus did not amplify in~~

~~the swordfish. (A) Digestions withDra I. From left to right, 1 kb DNA ladder, blue~~

~~marlin pattern A, white/striped marlin pattern B, sailfish pattern B. black marlin pattern~~

~~B, shortbill spearfish pattern C, and longbill spearfish pattern C. (B) Digestions with~~

~~Dde I. From left to right, 1 kb DNA ladder, blue marlin pattern A, white/striped marlin~~

~~pattern B, sailfish pattern D, black marlin pattern H, shortbill spearfish pattern C, and~~

~~longbill spearfish pattern C.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. - 3 u * 3 S3 3 72 E 2 . SL < cz: C/3 2 Q 2 o I JD 3 I — E £ CO 22 sz; —•~~

~~1.018 1 ,0 1 8 -►~~

~~506.517 506,517 — 396 396 — 344 344 — 298 298 -► 220.201 220.201 — 154,134 — 154,134~~

~~Bm32-2cut with Dra I Bm32-2 cut with Dde I~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 227~~

~~Figure 4. Key to distinguish species o f billfishes based on the single copy nuclear locus~~

~~BM32-2~~

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Spearfish Dral BM32-2 Blue Marlin Striped Marlin Striped Marlin ~ . White Marlin White Marlin g Black Marlin Black Marlin Sailfish Sailfish

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 229~~

~~Figure 5. Larval billfish and its corresponding specific identification as sailfish based on~~

~~the BM32-2 locus. Lane 1 Dra I . lane 2, lkb plus DNA ladder (Gibco/BRL Life~~

~~Technologies Inc., Bethesda MD) lane 3 , DdeI~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. l 2 3~~

~~Reproduced with with permission permission of of the the copyright copyright owner.owner. Further Further reproduction reproduction prohibited prohibited without without permission. permission. VITA~~

~~Jan Renee McDowell~~

~~Bom in Des Moines Iowa on September 4, 1964. Graduated from Ottumwa High School,~~

~~Ottumwa, Iowa in 1982. Earned a B.S. in Zoology from the University o f Iowa. Earned a~~

~~doctoral degree in August o f 2002 from the College o f William and Mary, School o f~~

~~Marine Science.~~

~~Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.~~