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Dissertations, Theses, and Masters Projects Theses, Dissertations, & Master Projects
2003
Genetic Variation Within and among the Suminoe Oyster (Crassostrea ariakensis) Populations and Stocks as Assessed by Molecular Markers
Qian Zhang College of William and Mary - Virginia Institute of Marine Science
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Recommended Citation Zhang, Qian, "Genetic Variation Within and among the Suminoe Oyster (Crassostrea ariakensis) Populations and Stocks as Assessed by Molecular Markers" (2003). Dissertations, Theses, and Masters Projects. Paper 1539617806. https://dx.doi.org/doi:10.25773/v5-nngz-rg29
This Thesis 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]. GENETIC VARIATION WITHIN AND AMONG THE SUMINOE OYSTER (iCRASSOSTREA ARIAKENSIS) POPULATIONS AND STOCKS AS ASSESSED BY MOLECULAR MARKERS
A Thesis Presented to The Faculty of the School of Marine Science The College of William and Mary in Virginia
In Partial Fulfillment Of the Requirements for the Degree of Master of Science
By Qian Zhang 2003 APPROVAL SHEET
This thesis is submitted in partial fulfillment of
The requirements for the degree of
Master of Science
Qian Zhang
Approved, July 2003
Kimberly S. Reece, Ph.D. Co-Advisor
Sj^ndish K. A llel Jr., Ph.D. Co-Advisor
A a O—/ s / \ RogepL. Mann, Ph.D.
John M. Brubaker, Ph.D. TABLE OF CONTENTS
Page
ACKNOWLEDGEMENTS...... v
LIST OF TABLES...... vi
LIST OF FIGURES...... ix
ABSTRACT...... x
CHAPTER 1. GENERAL INTRODUCTION TO THE SUMINOE OYSTER
CRASSOSTRIA ARIAKENSIS ...... 1
INTRODUCTION...... 2
OBJECTIVES...... 7
LITERATURE CITED...... 8
CHAPTER 2. GENETIC VARIATION WITHIN AND AMONG CRASSOSTREA
ARIAKENSIS WILD AND HATCHERY SAMPLES, AS REVEALED
BY RFLP ANALYSIS OF MITOCHONDRIAL AND NUCLEAR
LOCI...... 13
INTRODUCTION...... 14
MATERIAL AND METHODS...... 17
RESULTS...... 25
DISCUSSION...... 34
LITERATURE CITED...... 43
CHAPTER 3. GENETIC VARIATION WITHIN AND AMONG CRASSOSTREA
ARIAKENSIS WILD AND HATCHERY SAMPLES, AS REVEALED
BY MICROSATELLITE MARKERS...... 91 INTRODUCTION...... 92
MATERIALS AND METHODS...... 94
RESULTS...... 97
DISCUSSION...... 105
LITERATURE CITED...... 113
APPENDIX A ...... 148
APPENDIX B...... 158
VITA...... 174
iv ACKNOWLEDGEMENTS
I sincerely appreciate the time, guidance, patience, and encouragement my advisors Drs. Kimberly Reece and Standish Allen Jr. provided during my time at VIMS.
They gave me much helpful advice over the years and their critical review of this thesis contributed countless suggestions for improvement. I would also like to thank my other committee members, Dr. Roger Mann and Dr. John Brubaker, for their constant support and assistance in the completion of this thesis.
Special thanks to everyone in, or associated with, the VIMS Oyster Genetics
Laboratory for providing me support and encouragement through all stages of this study.
I owe a special thanks to Karen Hudson, who taught me the essentials of laboratory protocols, answered many of my questions and walked me through several procedures during the initial stages of this project. Without her help this work would not have been possible.
I am very grateful to Dr. Jan McDowell for her advice and assistance in using
ARLEQUIN, RFLPSCAN and GENEPOP software and introducing me to the joys of handling genetic data.
Finally, I would like to thank the following individuals and companies for their assistance in collecting specimens: Elizabeth Francis collected Crassostrea ariakensis samples from Japan, Dr. Standish Allen collected C. ariakensis from coastal areas of
China, the Taylor United Industry Co. sent samples from Washington states, USA, and
Liz Walker facilitated collection of C. ariakensis hemolymph from VIMS hatchery samples. LIST OF TABLES
Table Page
1. Sample groups of the Suminoe oyster, used in PCR-RFLP and
microsatellite genotyping ...... 58
2. Primer pairs used for amplification of Crassostrea ariakensis DNA 60
3. Composite haplotypes based on RFLP analysis of the mitochondrial COI
gene ...... 61
4. Percent mean nucleotide sequence divergence based on the mtDNA RFLP
analysis ...... 63
5. Tajima’s D and Fu’s F tests to access the deviation from the mutation-drift
equilibrium ...... 64
6. Analysis of molecular variance (AMOVA) between the northern (YR and I)
and southern (B, C, D) groups based on the mtDNA RFLP analysis ...... 65
7. Hierarchical AMOVA tests based on the mtDNA RFLP analysis ...... 66
8. Analysis of molecular variance (AMOVA) between the northern (YR and I)
and southern (C and D) groups based on the mtDNA RFLP analysis ...... 67
9. Population pairwise Fst and significance P-values calculated based on the
mitochondrial COI RFLP analysis ...... 68
10. Composite genotypes based on RFLP analysis of the nuclear ITS-1
region ...... 70
vi Hardy-Weinberg equilibrium (HWE) tests based on the nuclear ITS-1 RFLP
analysis ...... 72
Percent mean nucleotide sequence divergence based on the nuclear DNA
ITS-1 RFLP analysis ...... 74
Analysis of molecular variance (AMOVA) between the northern (YR and I)
and southern (B, C, D) groups based on the nuclear DNA RFLP analysis ..... 75
Hierarchical AMOVA tests based on the nuclear DNA RFLP analysis ...... 76
Analysis of molecular variance (AMOVA) between the northern (YR and I)
and southern (C and D) groups based on the nuclear DNA RFLP analysis.... 77
Population pairwise Fst and significance P- values calculated based on the
nuclear ITS-1 RFLP analysis ...... 78
P-values for pairwise comparisons of allelic and genotypic frequencies
based on nuclear the ITS-1 RFLP analysis ...... 79
Microsatellite primers, optimal annealing temperatures (Tm) and product
size for locus ucdCg-120, 172 and 199 ...... 122
Number of samples used, number of alleles and genotypes, allele size range,
size and frequency at the three microsatellite loci ...... 123
Expected and observed heterozygosity, inbreeding coefficient, probability
of deviation from Hardy-Weinberg equilibrium ...... 125
Number of alleles and genotypes, allele size range, expected and observed
heterozygosity, inbreeding coefficient, probability of deviation from Hardy-
Weinberg equilibrium in the wild and hatchery samples ...... 127
Microsatellite allele frequencies in the wild and hatchery samples ...... 129
vii 23. Genotypic linkage-equilibrium and probability tests ...... 131
24. Results of microsatellite assignment test ...... 132
25. Results of RFLP genotyping and microsatellite assignment tests in the
Beihai sample ...... 133
26. Results of RFLP genotyping and microsatellite assignment tests in the
SCA 00 sample ...... 135
27. P- values for pairwise comparison of allelic and genotypic frequencies at the
microsatellite locus ucdCg 199, ucdCg 172 and ucdCg 120 ...... 137
28. Two sample t-test showing the difference between wild and hatchery
samples in number of alleles and genotypes ...... 139
viii LIST OF FIGURES
Figure Page
1. Crassostrea ariakensis sample collection locations for RFLP and
microsatellite analysis ...... 81
2. RFLP analysis of the nuclear ITS-1 region digested with BamH I and Sst II.... 83
3. RFLP analysis of the mitochondrial COI gene digested with Alu I, Hae III and
Taq 1...... 85
4. UPGMA tree calculated from net nucleotide sequence divergence based on
the mitochondrial COI RFLP analysis ...... 87
5. UPGMA tree calculated from net nucleotide sequence divergence based on
the nuclear ITS-1 RFLP analysis ...... 89
6. Allele frequency distribution histogram at ucdCg 199 ...... 140
7. Allele frequency distribution histogram at ucdCg 172 ...... 142
8. Allele frequency distribution histogram at ucdCg 120 ...... 144
9. Allele frequency distribution between the northern and southern samples 146
10. Allele frequency distribution in the Beihai sample ...... 147
ix ABSTRACT
Genetic variability and population structure were examined by means of restriction fragment length polymorphism (RFLP) and microsatellite analyses in five
Suminoe oyster (Crassostrea ariakensis) samples collected from coastal sea areas of
China and Japan. Population bottlenecks and inbreeding were examined in five hatchery- propagated stocks in the United States.
RFLP analysis of the mitochondrial cytochrome c oxidase subunit 1 (COI) gene and the nuclear first internal transcribed spacer (ITS -1) region showed low intra-sample variation (haplotypic diversity, 0.1184; nucleotide diversity, 0.6016; gene diversity,
0.1094) in the Suminoe oyster populations. Marked reduction of genetic variation in hatchery-propagated stocks (haplotyic diversity, 0.0237; nucleotide diversity, 0.0086; gene diversity, 0.0237) was observed, suggesting population bottlenecks. Heterozygote deficiencies {Ho = 0.0000) were observed in all wild samples, and were attributed to non- random assortative mating. AMOVA and pairwise comparison analyses revealed large genetic subdivision between the samples from the northern area of China (Yellow River) and Japan (Itoki River) and from the southern China (Zhuhai and Yangjiang) (P < 0.05).
The northern and southern types of the Suminoe oyster both appeared in the Beihai
sample, however no heterozygotes were observed, suggesting the possibility of reproductive isolation of the two types. UPGMA analysis based on the distance matrix of net nucleotide sequence divergence clustered all hatchery samples into the northern phenetic group.
x All three microsatellite loci examined were variable in all samples. The average number of alleles per locus was 3.7 to 7.3 and the average observed heterozygosity per locus ranged from 0.080 to 0.487. Hatchery stocks showed a significant reduction in allelic and genotypic diversity (P < 0.05) over that seen in their source populations. Most observed genotype frequencies (70%) at each locus were not in agreement with Hardy-
Weinberg expectations (HWE) (P < 0.017). A consistent excess of homozygotes occurred with departures from HWE probably mainly due to null (non-amplifying) alleles. Alleles in the northern (Yellow River and Itoki River) and southern groups (Zhuhai and
Yangjiang) showed different distribution allele size patterns. Assignment tests assigned
97.6% and 99.0% of oysters from either the northern (Yellow River and Itoki River) or southern (Zhuhai and Yangjiang) areas to their putative groups. The assignments of
Beihai sample were largely (96%) consistent with the results of the RFLP tests. GENERAL INTRODUCTION
TO
THE SUMINOE OYSTER CRASSOSTREA ARIAKENSIS 2
INTRODUCTION
Range and Industry History
The Suminoe oyster ( Crassostrea ariakensis) is a warm-water estuarine bivalve species. It is common on intertidal hard grounds below the low water mark and in muddy creeks in warm habitats (Rao, 1987; Barkati and Khan, 1987). The natural geographic range of C. ariakensis has been reported to extend from southern Japan (Cagbn, A.R.,
1950; Torigoe, 1981; Quayle and Newkirk, 1989), along the west coast of Korea (Kuroda and Tadashige, 1952; Harry, 1981), the whole coastal area of China (Tchang and Lou,
1956; Cai and Li, 1990; Zhuang, 1992), southward to the coast of India (Ahmed,
1971;Durve, 1986; Mahadevan, 1987; Rao, 1987) and Pakistan (Tchang and Lou, 1956;
Rao, 1987), the Arabian Gulf and into western Africa (Durve, 1986). It also has been reported in the Philippines and North Borneo (Durve, 1986). However, some of these distribution reports need to be viewed with caution since this putative range of distribution could be due to the misclassification or incorrect usage of the species name
(Carriker and Gaffney, 1996).
Crassostrea ariakensis was known as “Jinjiang” in China and “Suminoegaki” or
“Suminoe” in Japan, referring to the Suminoe River in the Saga Prefecture of Ariake Bay,
Japan (Galstoff, 1964). It is an important aquaculture species in Southern China particularly in Zhejiang, Fujian and Guangdong Provinces (Cai and Li, 1990; Zhuang,
1992). Aquaculture growers from the Pacific Northwest in the United States imported this species from Japan with the seeds of the Pacific oyster, C. gigas and the Kumanoto oyster, C. sikamea (Galstoff, 1964; Breese and Malouf, 1977). The Suminoe oyster survived, grew well, and became the basis of a brood stock for further hatchery propagation on the west coast. Galstoff (1964) and Breese and Malouf (1977) reported a limited culture of the Suminoe oyster in Yaquina Bay, Oregon; however, the production of C. ariakensis on the west coast is presently very limited, largely because the region’s higher salinities make hatchery culture inconvenient and more costly (Hallerman et al.,
2001).
Morphology and Biology
Compared to another non-native species Crassostrea gigas, the Pacific oyster, the
Suminoe oyster is distinguished by its large, roughly round, flat and thick shell valves, a shallow shell cavity and white or smoky white adductor muscle scar (Mahadevan, 1987;
Rao, 1987). It tolerates a wide range of salinity (range 1 to 32 ppt), but prefers low salinity (10 to 28 ppt) estuaries and riverbeds (Nei, 1982; Cai et ah, 1992; Guo et ah,
1999. The optimum salinity for C. ariakensis to proliferate is 10-25%o (Tchang and Lou,
1956). The spawning of C. ariakensis may depend on water temperature and salinity. In
Southern China, the spatfall of C. ariakensis usually occurs from June to August (Nei,
1982), and from late May to early September in Japan (Tanaka, 1954). C. ariakensis larvae presented an optimum growth and survival at a temperature of 28 °C and a salinity of 20 ppt (Breese and Malouf, 1977). In Yaquina Bay, Oregon, female Suminoe oysters were reported to become sexually mature in late summer with peak gonad maturation occurring in October (Langdon and Robinson, 1991; Langdon and Robinson, 1993).
Langdon and Robinson (1993) studied the aquaculture potential of Suminoe oysters and developed successful guides for the culture of the Suminoe oyster (Langdon and Robinson, 1993). Their results of a series of breeding and growth experiments with C. ariakensis showed that larvae could be reared to setting and metamorphosis on a mixed 4 diet of the flagellate Pseudoisochrysis paradoxa and the diatom Chaetoceros calcitrans at 25 °C in 15-20%o seawater. The larvae or juveniles were found to grow fastest at a salinity of 25%o. Sexual maturation of the adult oysters can be accelerated by holding broodstocks in flowing seawater at 20°C for 4 to 6 weeks (Robinson and Langdon, 1993;
Robinson and Langdon, 1995).
Taxonomy
Crassostrea ariakensis (Phylum: Mollusca, Class: Bivalvia, Subclass:
Pteriomorphia, Order: Ostreoida, Family: Ostreidae, Subfamily: Ostreinae, Genus:
Crassostrea) was first placed in the genus Ostrea as Ostrea rivularis by Gould (1861)
(Cagbn, 1950) and reported as Ostrea ariakensis by Fujita (1913) and Wakiya (1929)
(Harry, 1981). Two reports by Shun-ichi Takatsuki (1949) and Ken-ichi Numachi (1971) written in Japanese described some early taxonomic history of this species
(http://www.lib.noaa.gov/docaqua/oyster.html). Lischke (1869) and Amemiya (1928) regarded O. rivularis as a young stage of O. ariakensis. Fujimori (1949) suggested that O. ariakensis is the synonym of O. laperousei. Whereas Taki (1933) disagreed with this view, and Wakiya (1915) regarded both as different species due to the difference in tentacle rows on the mantle edge. Dunker (1882) reported O. rivularis of Lischke (1869) as the synonym of O. arborea Dillwyn. Hirase (1930) supported this view. Kuroda (1931) disagreed. Since that time C. rivularis (Gould) has been noted as follows in the text:
Crassostrea rivularis (Gould)
Ostrea rivularis (Gould 1861), (Lischke 1869), (Wakiya 1915) and (Amemiya 1928)
Ostrea ariakensis (Fujita 1913), (Wakiya 1929) and (Lischke 1871) 5
Some authors even considered this species as conspecific with C. gigas (Cagbn,
1950). However, that conclusion was later denied by phylogenetic studies based on protein electrophoresis and DNA sequence analysis (Buroker et al., 1979; Littlewood,
1994). Torigoe (1981) reached the conclusion that Ostrea rivularis and Crassostrea ariakensis should be considered a single species (Coan et al. 1995). Crassotrea rivularis and C. ariakensis are now considered as identical and the name C. ariakensis Fujita 1913 is generally accepted as the proper species name (Carriker and Gaffney, 1996).
C. ariakensis Project and Population Genetics
In the mid-Atlantic region of the United States, the native Eastern oyster,
Crassostrea virginica, which was for three centuries the object of a major fishery, has decreased greatly in numbers due to diseases, pollution, habitat-destruction and overfishing in recent decades (Mann, et al., 1991). To reconstruct the local commercial oyster industry and to help improve water quality, some non-native oyster species are being considered for aquaculture use in the Chesapeake Bay region. From 1998, the researchers at the Virginia Institute of Marine Science (VIMS) have been investigating the non-indigenous Suminoe oyster C. ariakensis for survival, growth and disease susceptibility as compared with the Bay’s native oyster C. virginica. Field trails of C. ariakensis showed that C. ariakensis was faster growing and has better tolerance to disease infections compared to C. virginica (Calvo et al., 2000). In addition, since C. ariakensis is a warm-habitat species, it shows relatively limited sexual maturation on the west coast of the United States in the summer. The storage of energy-rich glycogen in productive tissues makes C. ariakensis taste good and a superior summer product for market (Breese and Malouf, 1977; Purdue and Erickson, 1984; Langdon and Robinson, 6
1996). These findings suggest that hatchery-reared C. ariakensis hold promise for rebuilding the commercial oyster industry in the mid-Atlantic region of the United States through aquaculture production. Introduction of C. ariakensis to Chesapeake Bay have been seriously proposed in Maryland, USA.
In an attempt to establish selective breeding programs for C. ariakensis and prepare hatchery-tamed C. ariakensis for the Chesapeake Bay, the VIMS hatchery brought several C. ariakensis brood stocks from Asia and the Pacific west of the United
States from 1998 to 2002. However, little is known about genetic variation among these artificially reared hatchery strains or how that variation compares to that of natural populations.
In addition, all published reports concerning C. ariakensis focus on its interrelationship with other species and few data have attempted to reveal C. ariakensis population genetics. For instance, molecular phylogenetic studies of cupped oysters demonstrated that C. ariakesnis is more closely related to C. gigas and C. belcheri, while
C. virginica, C. rhizophorae and C. commericalis belong to another lineage (Littlewood,
1994). The genetic relatedness of C. ariakensis and C. gigas is also supported by hybridization trials: C. ariakensis and the native Eastern oyster C. virginica could not hybridize (Allen et al., 1993); however, the crossing of C. ariakensis and C. gigas produces some viable hybrids, although production had limited success (Zhou et al.,
1982; Allen and Gaffney, 1993). 7
OBJECTIVES
This study was aimed to access the genetic variability of C. ariakensis wild populations and hatchery brood stocks using both polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis and highly polymorphic microsatellite markers; and the latter generally improves the efficiency of monitoring intra-population genetic variability. Two null hypotheses were proposed. Hol\ A single panmictic population of the Suminoe oyster occurs along the coastal areas of Japan,
Northern and Southern China owing to large-scale gene flow by migration of oyster pelagic larvae. Ho2 : Genetic variability was not reduced in the first generation of the hatchery-produced stocks. In this case, we assumed that the pattern of genetic differentiation and variation of the derived stocks does not significantly differ from those of the wild source populations. The understanding of C. ariakensis population history and levels of genetic variability would help to provide information on the range of the genetic resource and perhaps allow selection of a specific genetic entity with an ecotype that would compliment the ecological features of the Chesapeake Bay. In addition, the RFLP and microsatellite markers identified could be used as potential genetic tools to discriminate genetic units of C. ariakensis to carry out genetic-based stock enhancement and breeding design. LITERATURE CITED
Allen, S. K. Jr. and P. M. Gaffney. 1993. Genetic confirmation of hybridization between
Crassostrea gigas (Thunberg) and Crassostrea rivularis (Gould). Aquaculture
113:291-300.
Allen, S. K. Jr., P. M. Gaffney, J. Scarpa and D. Bushek. 1993. Inviable hybrids of
Crassostrea virginica (Gmelin) with C. rivularis (Gould) and C. gigas (Thunbrg).
Aquaculture 113: 269-289.
Ahme, M. 1971. Oyster species of West Pakistan. Pakistan Journal of Zoology 3(2): 229-
236.
Avise, J. C. 1994. Molecular Markers, Natural History, and Evolution. Chapman and Hall,
Inc. One Penn Plaza, New York, NY 10119.
Barkati, S. and R. M. Khan. 1987. Relative Growth in three species of oysters. Pakistan
Journal of Scientific and Industrial Research 30(8): 624-627.
Breese W. P. and R. E. Malouf. 1977. Hatchery rearing techniques for the oyster
Crassostrea rivularis Could. Aquaculture 12: 123-126.
Buroker, N. E., W. K. Hershberger and K. K. Chew. 1979. Population Genetics of the
Family Ostreidae. II. Interspecific Studies of the Genera Crassostrea and
Saccostrea. Marine Biology 54: 171 -184.
Cagbn, A. R. 1950. Oyster culture in Japan. Fish. Leafl. Fish. Wildl. Serv. 383: 1-80.
Cai, Y, C. Deng and Z. Liu. 1992. Studies on the ecology of Crassostrea rivularis (Gould)
in Zhangjiang Bay. Tropic Oceanology 11(3): 37-44. (In Chinese). Cai, Y. and X, Li. 1990. Oyster culture in the People’s Republic of China. World
Aquaculture 21(4): 67-72.
Calvo, G. W., M. W. Luckenbach, S. K. Allen, Jr. and E. M. Burrenson. 2000. A
comparative field study of Crassostrea ariakensis and Crassostrea virginica in
relation to salinity in Virginia. Special report in applied marine science and ocean
engineering No. 360.
Carriker, M. R. and P. M. Gaffney. 1996. A catalogue of selected species of living
oysters (Ostrea) of the world. In The Eastern Oyster. Kennedy, V.S., R. E. I.
Newell and A. F. Eble, eds. Maryland Sea Grant College Publication UM-SG-TS-
96-01. pp 1-18.
Coan, E. V., P. H. Scott and F. R. Bernard. 1995. Bivalve seashells of western North
American. Marine bivalve mollusks from Arctic Alaska to Baja California. Santa
Barbara Museum of Natural History, Santa Barbra, California.
Durve, V. S. 1986. On the ancestry and distribution pathways of three species of Indian
oysters. Indian Journal of Marine Sciences 15: 56-58.
Galstoff, P. S. 1964. Taxonomy. In The American Oyster Crassostrea virginica Gmelin.
Galtsoff, P. S., eds. U.S. Fish and Wildlife Service. Fisheries Bulletin 64: 1-15.
Hallerman, E. M., S. Mills, and S. Allen, Jr. 2000. Aquaculture of triploid C. ariakensis
in Chesapeake Bay: A symposium report. Maryland Publication UM-SG-TS-
2002-01, Virginia Publication VSG-02-03.
Harry, H. W. 1981. Nominal species of living oysters proposed during the last fifty years.
The Veliger 24: 39-45. 10
Kuroda, T. and H. Tadashige. 1952. Check list and bibliography of the recent marine
mollusca of Japan. Leo W. Stach, Publ. Tokyo, Japan, pp 210.
Langdon, C. J. and A. M. Robinson. 1991. Development of the commercial aquaculture
of the Suminoe Oyster ( Crassostrea rivularis). Journal of Shellfish Research
10(1): 238.
Langdon, C. J. and A. M. Robinson. 1993. Guide for the culture of the Suminoe oyster
{Crassostrea rivularis). Hatfield Marine Science Center, Oregon State University,
Newport, Oregon 97365.
Langdon, C. J. and A. M. Robinson. 1996. Aquaculture potential of the Suminoe oyster
{Crassostrea ariakensis Fugita 1913). Aquaculture 144: 321-338.
Littewood, D. T. J. 1994. Molecular phygenetics of cupped oysters based on partial 28S
rRNA gene sequence. Molecular Phylogenetic and Evolution 3(3): 221-229.
Mahadevan, S. 1987. Oyster resources in India. In Central Marine Fisheries Research
Institute Bulletin 38, K. N. Nayar and S. Mahadevan, eds. Indian Council of
Agricultural Research, Cochin, India, pp 14-17.
Mann, R., E. M. Burreson, and P. K. Baker. 1991. The decline of the Virginia oyster
fishery in Chesapeake Bay: considerations for introduction of non-endemic
species, Crassostrea gigas (Thunberg, 1973). Journal of Shellfish Research 10(2):
379-388.
Nei, M. 1987. Molecular Evolutionary Genetics. Columbia University Press, New York,
NY, USA. pp 512. 11
Purdue, J. A. and G. Erickson. 1984. A comparison of the gametogenic cycle between the
Pacific oyster Crassostrea gigas and the Suminoe oyster Crassostrea rivularis in
Washington State. Aquaculture 37: 231-237.
Quayle, D.B. and G. F. Newkirk. 1989. Farming bivalve mollusks: methods for study and
development. Adv. World Aquaculture 1: 1-294.
Rao, 1987. Taxonomy of Indian Oysters. In Oyster Culture-Status and Prospects.
Nagappan, K. and S. Mahadevan, eds. Central Marine Fisheries Research Institute.
Indian Council of Agricultural Research. P. B. No.2704. Cochin 682031. India, pp
1-6.
Robinson, A. M. and C. J. Langdon. 1993. The Suminoe Oyster-candidate for the half
shell trade? Journal of Shellfish Research 12 (1): 152.
Robinson, A. M. and C. J. Langdon. 1995. The Suminoe oyster: Ready for commercial
production. Triennial meeting of fish culture section of American Fisheries
Society World Aquaculture Society Nation Shellfisheries Association. Journal of
Shellfish Research 14(1): 276-277.
Tanaka, Y. 1954. Spawning season of important bivalves in Ariake bay II. Ostrea
rivularis Gould and O. gigas Thunberg. Bulletin of the Japanese Society of
Scientific Fisheries 19(12): 1161-116. (In Japanese).
Tchang, S. and Tse-kong, Lou. 1956. A study on Chinese Oysters. Acta Zoologica Sinica
8: 65-93.
Torigoe, K. 1981. Oysters in Japan. J. Sci. Hiroshima University. Ser. B., Div I (Zool.) 29:
291-319. Zhou, M., Y. Kao, and Y. Wu. 1982. Preliminary studies on hybridizaion of Crassostrea
gigas with Ostrea rivularis and Ostrea plicatula. Journal of Fishery Sciences of
China 6: 235-241.
Zhuang, Qiquan. 1992. Research on marine bivalves in the People’s Republic of China.
American Malacologica Bulletin 9(2): 207-215. GENETIC VARIATION WITHIN AND AMONG CRASSOSTREA
ARIAKENSIS WILD AND HATCHERY SAMPLES, AS REVEALED
BY RFLP ANALYSIS OF MITOCHONDRIAL AND NUCLEAR
LOCI 14
INTRODUCTION
Among many molecular markers for population genetic studies, mitochondrial
DNA (mtDNA) markers have proven to be very powerful (Avise et al., 1987; Moritz et ah, 1987). The mitochondrial genome in animals generally consists of a closed circular
DNA molecule, 14-42 kilobases (kb) in length, containing 13 protein-coding genes plus 2 ribosomal RNA and 22 transfer RNA genes, as well as a non-coding region involved in controlling transcription and replication (Moritz et ah, 1987; Wilstenholme, 1992).
Special features of mtDNA have made it a good tool in estimating phylogenies between both closely and distantly related taxa. First, the animal mitochondrial genome has a relatively rapid rate of base substitution (Brown et ah, 1982). Second, effective haploid and maternal inheritance of mitochondrial DNA reduces the effective population size and thus increases the sensitivity to genetic drift (Birky et ah, 1989; Ovenden, 1990).
However, mtDNA must be used in conjunction with nuclear markers to identify evolutionary distinct populations (Cronin, 1993). Alleles of nuclear genes are expected to take substantially longer to show phylogenetic sorting between populations because of their typically larger effective population size and slower neutral mutation rate (Nei,
1987). In one study, mtDNA was reported to diverge while nuclear genes did not given a lower effective number of genes (Birky et ah, 1989) or greater dispersal by males than females. So it is reasonable to seek correlative evidence from both mitochondrial and nuclear loci.
Cytochrome c oxidase subunit 1 (COI) gene has been found to be one of the most conservative protein-coding genes in the mitochondrial genome of Metazoans (Brown, 15
1985). To date COI has proven to be a robust evolutionary marker for determining intra- and inter-specific relationships in many marine mollusks. Van Syoc (1994) used COI sequence to determine the genetic relationships among the subpopulations of the edible goose barnacle, Pollicipes elegans. Mokay et al. (2000) used COI to discriminate the conical and bent populations of a rock-inhabiting barnacle, Chthamalus anisopama.
O Foighil et al., (1998) used COI sequences to compare the Portuguese oyster,
Crassostrea angulata to its their Asian congeners, while Boudry et al., (1998) used COI to examine genetic differentiation in the Portuguese oyster, C. angulata and the Pacific
Oyster, C. gigas.
Cytochrome c oxidase subunit III (COIII) gene codes for a functionally conserved protein and is relatively well conserved in both vertebrates (Amason and Gullberg, 1993;
Desjardin and Morais, 1990) and invertebrates (Cantatore et al., 1989; Simon et al.,
1994). COIII is phylogenetically informative on both interspecific and intraspecific studies, but is probably best suited for closely related taxa. Vitic and Strobeck (1996) used the COIII gene to study the population genetic structure of the lake trout, Salvelinus namaycush and Versteegen and Lawler (1997) used COIII sequences to study genetic variation among the populations of crayfish, Euastacus armatus. O Foighil and Smith
(1995) used the COIII gene to reveal phylogenies between the sexual versus asexual forms of the cosmopolitan marine clam Lasaea australis. Chow et al., (2000) used COIII genes to study the geographically stocks of the bigye tuna, Thunnus obesus and Machado et al., (2001) investigated the genetic diversity among populations of the shrimp
Farfantepenaesu notialis. 16
Of mtDNA coding-regions, the large subunit (16S) of mitochondrial ribosomal
DNA gene is reasonably well conserved. Ribosomal DNA has been used to infer phylogenies from a number of vertebrate species (e.g., lizards, Fu, 1999 and warblers,
Cibios et al., 1999). Numerous studies have used 16S DNA sequences to resolve evolutionary interspecific relationships in Mollusks. For example, Banks et al. (1993) employed RFLP analysis of the 16S rRNA gene to discriminate C. gigas and C. sikamea.
C. sikamea. O Foighil et al. (1995) developed a simple PCR-RFLP protocol based on 16S rRNA gene to differentiate among C. ariakensis, C. gigas and C. virginica. Hedgecock et al. (1999) discriminated among the species C. ariakensis, C. gigas and C. sikamea using thel6S rRNA gene. The 16S rRNA gene was also used to study the population genetic variation in the bay scallop, Argopecten irradians (Wilbur and Gaffney, 1997).
In addition to rapidly evolving mtDNA, some gene arrays in the nuclear genome contain a diversity of transcribed spacers that evolve at intermediate rates, and these have been useful for phylogeny studies (Hillis, 1987). As a part of the multi-copy nuclear ribosomal RNA gene complex in eukaryotic organisms (Palumbi, 1996), the first internal transcribed spacer (ITS-1) region is a non-coding region that is located between the large
(18S) and small subunit (5.8S) of the nuclear ribosomal RNA gene complex (Hillis and
Dixon, 1991). Variation in ITS-1 accumulates presumably because it is less constrained by selection, making these regions useful for intraspecific and interspecific genetic studies between closely related taxa. Wilbur and Gaffney (1997) distinguished C. gigas,
C. sikamea and the native Pacific Northwest oyster, Ostrea conchaphila using ITS-1 region. Sequences of the ITS-1 region were compared among the populations of the soft- shell clams, My a arenaria to determine genetic heterogeneity (Caporale, 1997). King 17
(1996) used ITS-1 region to reveal a latitudinal discontinuity in the population structure of the green floater, Lasmigona subviridis (King, 1996).
The polymerase chain reaction-restriction fragment length polymorphism (PCR-
RFLP) analysis is a standard technique to investigate the genetic differentiation within and among populations (Avise et al., 1987). Genetic variability caused by a site gain or site loss at mitochondrial or nuclear DNA among individuals can be identified by fragment presence or absence by cutting DNA with one or more endonucleases and separating the resulting fragments by electrophoresis on an agarose gel (Avise, 1994).
The RFLP technique is also a cost- and time-efficient approach for population genetics studies of a large sample size.
Currently, there is no data on the population genetic structure of Crassostrea ariakensis. Preliminary phylogenetic analyses based on the DNA sequencing data of mitochondrial COI and nuclear ITS-1 regions suggested that there might be genetic differentiation between C. ariakensis samples from Japan and northern China, and those from southern China, or that they may even represent different subspecies or sister species (Reece et al., unpublished).
In this study, polymorphic mitochondrial and nuclear DNA markers were employed to assess genetic variation within, and genetic divergence among five wild
Suminoe oyster samples from different geographic locations at Japan and China. In addition, five hatchery strains were examined for possible bottleneck effects. 18
MATERIALS AND METHODS
Sampling Collection and Storage
Table 1 summarizes the code, collecting date, location and sample size of each oyster sample. Adductor muscle, mantle or gill tissues were collected from Crassostrea ariakensis individuals along the coastal areas of northern China (Yellow River (YR)) and southern China (Beihai (B), Zhuhai (C) and Yangjiang (D)) and from Japan (Itoki River
(I)) from May to June 1999 (Figure 1). Oyster hemolymph (10-20 pi) was collected using sterile syringes from the adductor muscle of hatchery-propagated C. ariakensis at VIMS.
VIMS stocks comprise four first-generation offsprings of wild C. ariakensis: (1) northern
China ariakensis (NCA), spawned from the Yellow River collection in 1999; (2) southern
China ariakensis 99 (SCA 99) spawned from the Beihai collection in 1999; (3) southern
China ariakensis 00 (SCA 00) spawned from the Beihai (B) colletion but with different parents in 2000; and (4) west coast ariakensis (WCA) spawned from C. ariakensis brood stock imported from Washington State, USA in 1999. In addition, fifty tissue samples obtained from oysters sent to VA from the Taylor United Industry (TUI) Co. of
Washington State, USA, in March of 2002 were also examined. These samples were i hatchery-reared potentially over several generations.
Oyster tissue samples were preserved either in DMSO storage buffer (25 mM
EDTA, 20% DMSO, and saturated NaCl) or 95% ethanol for later DNA extraction.
Hemolyph samples from each hatchery stock were centrifuged at 14,000 rpm for 5 minutes and the precipitated floccules were directly subjective to DNA extraction. 19
DNA Extraction
Genomic DNA was extracted using the DNeasy Tissue Kit (Qiagen Inc., Santa
Clara, CA, USA). The DNA extraction procedure was done according to the manufacturers’ protocol with some modifications. Macerated tissues or hemolyph floccules were incubated in 180 pi of ATL lysis buffer and 20 pi of Proteinase K (25 mg m l_1, stored at - 4°C) at 55°C overnight until the tissue was completely lysed. Residual
RNA was removed by the addition of 4 pi of RNase A (lOOmg ml'1, stored at - 20°C) and followed by vortexing and incubation at room temperature for 2 min. After vortexing for
15 sec, 200 pi of AL buffer was added to the sample for incubation at 70°C for 10 min.
After adding 200 pi of ice-cold ethanol (96-100%) and vortexing thoroughly, all the mixture was transferred to a DNeasy mini column and centrifuge at 8,000 rpm for 1 min.
The flow-through was discarded. Then the mini column was washed with 500 pi of wash buffer AWi, centrifuge for lmin at 8,000 rpm, and 500 pi of AW 2 , centrifuge for 3 min at
14,000 rpm. Genomic DNA was finally eluted by adding 50 or 100 pi of elution buffer
AE, incubating for 1 min at room temperatue and centrifuging for 1 min at 8,000 rpm.
PCR Reactions
Polymerase Chain Reaction (PCR) was performed either in a PTC-100 DNA thermal cycler (MJ Research Inc., Watertown, MA, USA) or TGradient thermal cycler
200 (Biometra, Gottingen, Germany). PCR was set up in a 25 pi mix composed of 15.357 pi of PCR water, 2.5 pi of 10 X PCR buffer, 5 pi of 1 mg ml'1 Bovine Serum Albumin
(BSA), 0.75 pi of 50 mM MgCb, 0.5 pi of 10 mM dNTP, 0.25 pi of each primer, 0.125 pi of 5 unit pi'1 Taq polyerase. As a template, 0.25 pi of extracted genomic DNA was added for each reaction. The cycling parameters varied slightly with each primer pair 20
according to Table 2. After the reaction was complete, 2 j L t l of 6 X loading dye (40% sterile glycerol, 0.2% xylene cyanol, 0.2% bromophenol blue) was added and PCR products were examined by running 4 pi of the reaction mixture on 1% agarose gels with a 1 kilobase molecular weight ladder (Life Technologies, Gaithersburg, MD, USA).
Species Identification by DNA Sequencing
One or two individuals of each sample were sequenced for species identification.
Oyster samples, which were indicated as other species based on DNA sequences, were not included in this study. The sequencing procedure could be summarized as follows:
PCR products were cloned into the pCR 2.1 plasmid vector using the Invitrogen TA
Cloning Kit (Invitrogen Life Technologies, Carlsbad, CA, USA) following the manufacturer’s protocol. Plasmid vectors were cloned into competent Eschrichia coli cells and grew overnight on LB-agar plates in the presence of ampicillin and 5-bromo-4- chloro-3-indolyl-/?-D-galactoside (Xgal). White clones, which were supposed to contain inserts, were picked and grown in 3 ml 2XYT medium overnight at 37°C. Plasmids were purified by the Qiagen Plasmid Prep Kit (Invitrogen Life Technologies, Carlsbad, CA,
USA) following the manufacturer’s protocol. The clean plasmids were checked for inserts by EcoR I digestions before sequencing. Digestion reactions were performed in a mixture of 3.0 pi of plasmid DNA, 10. 5 pi of d H 2 O, with 0.3 pi of EcoR I restriction enzyme and 1.5 pi of corresponded reaction buffer (Takara Technologies, Shiga, Japan) at
37 °C for 2 hours. Digested fragments were screened on 1% agarose gels. Plasmids that contained the PCR inserts of interest were selected for sequencing.
Sequencing reactions were performed using the dideoxynucleotide chain termination method (Sanger et al., 1977). Reaction cocktail for each sample included 7 21
pi plasmid, 5 pi H 2 O and 1.5 pi of each infrared-labeled M13 FWD/IRD 700 or Ml 3
REV/IRD 800 primer (LICOR, Lincoln, NE, USA). 3.5 pi of the plasmid and primer mixture was added to a strip tube with 2 pi dNTP (N stands for A, G, C or T).
Amplification consisted of an initial denaturation for 5 minutes at 95 °C, followed by 29 cycles of 92°C denaturation for 0.3 minute, 54°C annealing for 0.3 minute and extension at
54°C for 0.3 min. Sequencing reactions were electrophoresed on 6% polyacrylamide 66 cm 0.25 mm gels (25.2 g urea, 4.8 ml Long RangeIR acrylamide, 400 pi of 10% ammonium persulfate and 40 pi of TEMED) with 0.1 X TBE (Tris-Boric acid-EDTA) buffer on a LICOR automated sequencer (model 4200L, LICOR Inc., Lincoln, NE, USA) with e-Seq version 2.0 (LICOR Inc., Lincoln, NE, USA).
Multiple alignments were performed using the ClustalW algorithm (Thompson,
1994) by Mac Vector version 7.0 (Kaufinann, 1994; Oxford Molecular, Madison, WI,
USA). Phylogenetic analysis of aligned sequences was conducted using PAUP version
4.0 (Sworfford 2000; Sinauer Associates Inc., Sunderland, MA, USA). A DNA sequence from Crass os trea plicatula was used as an out-group.
RFLP Analysis
Consensus sequence profiles of the COI gene and ITS-1 region were constructed and virtually digested using Mac Vector. Restriction endonucleases, which revealed genetic polymorphism among consensus sequences, were selected after the inspection of the digestion profiles. PCR products were subjected to digestion with selected restriction endonucleases (Hae III, Alu I and Taq I (four cutters) for the COI gene; BamH I, Sst II and Rsr II (six cutters) for the ITS-1 region). 22
The amplified segments of 16S gene were screened for restriction site polymorphism by using a panel of twelve restriction enzymes as follows: Alu I, Msp I,
Taq I (four cutters), and BamH I, Dm I, EcoR I, Hind III, Hpa I, Kpn I, Sst I, Sst II, Xho I
(six cutters).
Each restriction digest reaction was carried out in a 15 pi mixture containing 5 pi of amplified products, 8.2 pi of distilled water and 0.3 pi of restriction enzyme in 1.5 pi of different reaction buffer solutions recommended by the manufacturers (New England
Biolabs, Beverly, MA, USA; Invitrogen Life Technologies, Carlsbad, CA, USA; Fisher
Scientific, Fair Lawn, NJ, USA; Promega, Madison, WI, USA; Takara Technologies,
Shiga, Japan) at 37°C for 2 hours except digests with Taql, which were performed in a
PTC-100DNA thermal cycler (MJ Research Inc., Watertown, MA, USA) at 65°C for 2 hours.
Resulting fragments were separated by electrophoresis in a 2.5% (1% agarose and
1.5% Low Melt DNA agarose (Fisher Scientific, Fair Lawn, NJ, USA)) gel with 1 X
TBE buffer (Tris, boric acid and EDTA), followed by staining with ethidium bromide
(EtBr) for visualization by UV light. The lengths of the digestion fragments were estimated by comparison with 100 bp or lkb plus DNA ladder (Invitrogen Life
Technologies, Carlsbad, CA, USA). Composite haplotypes (genotypes) were designated by capital letters, representing the different profiles for each of the restriction enzymes.
Individuals with rare and unique composite haplotypes (genotypes) were subjected to species denotation by DNA sequencing. 23
Statistical Analysis
MtDNA
The haplotypic diversity (h) in each sample was calculated using ARLEQUIN, ver. 2.000 software (Schneider et al., 2000; available at http://lgb.unige.ch/arlequin/) according to Nei’s formula (Nei, 1987): h = n (1- YX\ )/ (n-1), where n is the sample size, and X \ is the frequency of each haplotype in each sample. Nucleotide diversity or the average percentage nucleotide differences (p), which assesses polymorphisms at the nucleotide level, was estimated following Nei (1987) and Tajima (1983), as implemented in ARLEQUIN.
The percent nucleotide sequence diversities (7r) and divergences (6) (Nei’s average number of pairwise differences), which estimate intra-sample genetic variations and genetic distances between samples, were calculated following Nei and Li (1979), as implemented in ARLEQUIN. Net nucleotide sequence divergence (5 a ) was calculated using the following formula: 8 a ( x , y ) = 8 xy - (8 x + 8 y) /2 .
The Tajima’s D and Fu’s Fs tests were performed based on the infinite-site model as a means to access selective neutrality (Tajima, 1989a; Fu, 1997). The significance levels were assessed by generating random samples under the hypothesis of selective neutrality and population equilibrium, using a coalescent simulation algorithm (Hudson,
1990) by ARLEQUIN.
Hierarchical genetic differentiations among populations were quantified by analysis of molecular variance (AMOVA) (Exoffier et al., 1992) with ARLEQUIN.
Significance levels of pairwise Fst (within sample), Fsc (among samples within groups) and Fct (among groups) were tested under the hypothesis of no differentiation among 24 samples, through a non-parametric random permutation approach described in Exocoffier et al. (1992) with 10,000 permutations. If the significance P- value associated with the fixation index among samples within a group (Fsc) is out of the rejection zone (P < 0.05), then the group was considered to be further subdivided.
Genetic structure was also assessed by estimation of pariwise Fst values
(Reynolds et al., 1983) for all possible sample combinations. The probability associated with Fst values was evaluated by a test analogous to Fisher’s exact test using the
Markov-chain procedure with 10,000 permutations for Mantel test and significance test, as implemented in ARLEQUIN.
UPGMA (unweighted pair-group method of arithmetic averages) tree was generated from a distance matrix of net nucleotide sequence divergence estimated among samples (Nei and Miller, 1990) with MEGA ver. 2.1 (Kumar et al., 2001; available at http://www.megasoftware.net/).
Nuclear DNA
Genetic variation in each sample was quantified using measures of gene diversity following Nei (1973) with ARLEQUIN. The percent nucleotide sequence diversities (7r) and divergences (5), and net nucleotide sequence divergence (6 a ) were calculated as mtDNA data.
The departure from Hardy-Weinberg equilibrium (HWE) for each sample at each locus was examined by both ARLEQUIN and GENEPOP web version 3.1 (Raymond and
Rosset, 1995; available at http://wbiomed.curtin.edu.au/genepop/). Probability tests were performed with Markov-chain parameters (1,000 dememorizations, 100 batches, and
1,000 iteration). Values of the inbreeding coefficient ( Fis; Weir and Cockerham 1984) 25 were also estimated to measure the HWE departures with significant criteria using
GENEPOP.
Statistical analyses of nuclear DNA data for AMOVA, pairwise Fst and significant tests for population differentiations were performed as with the mitochondrial
RFLP data using ARLEQUIN. GENEPOP was also used to test the pairwise allelic and genotype dissimilarity and a random permutation procedure by the Markov-chain method
(Guo and Thompson, 1992) was employed to produce significant values with the parameters: 1,000 dememorizations, 100 batches, and 1,000 iterations.
UPGMA analysis was performed by MEGA.
RESULTS
MtDNA
Gene Amplification
Each pair of primers successfully amplified approximately 650 and 525 bp fragments of the cytochrome c oxidase I and 16S ribosomal RNA genes, respectively, from five wild and five hatchery samples. There were no apparent differences in the fragment size among samples. Primer pair COIII A and B successfully amplified cytochrome oxydase III region from Japan and Northern China samples, but not from
Zhuhai and Yangjiang samples. The other three COIII primer pairs (COIIICLAM,
COIIICEPHA and COIIIMUSSEL) failed to produce PCR products from any samples.
Digestion Polymorphism
No variability was revealed on digestion profiles of the 16S rRNA fragment.
However, restriction fragment polymorphism of the COI gene was observed for three 26 endonucleases Hae III, Alu I and Taq I (Figure 2) and allowed three haplotypes to be distinguished in a total sample of 477 individuals. Table 3 lists the haplotype frequencies for five wild samples and five hatchery stocks. In the wild samples, haplotype AAA was widespread through the samples of Yellow River (YR) from Northern China and Itoki
River (I) from Japan, while haplotype BBB was dominant in two samples from Southern
China (Zhuhai (C) and Yangjiang (D)). Both haplotypes were encountered in the Beihai
(B) sample. Haplotype ACA was rare and only found in two samples ((B) and (D)) at very low frequencies. Hatchery strains were a roughly dominated by the haplotype AAA.
Two other haplotypes (BBB and ACA) were only detected in one individual from SCA
99 and two from SCA 00 from the hatchery, respectively.
Among these individuals, a total of three individuals from Itoki River (I) showed very distinct RFLP haplotypes (Individuals 110,117 and 139) and phylogenetic analysis studies based on sequences suggested that 117 and 139 were C. gigas, while 110 was C. sikamea. These individuals were excluded from the population genetics studies.
Haplotype Diversity and Nucleotide Diversity
Estimates of average haplotype diversity ( h ) and nucleotide diversity (p) among the geographical samples were 0.1184 and 0.0547, respectively. Samples from Yellow
River (YR), Itoki River (I) and Zhuhai (C) were haplotype monomorphic {h = 0.0000).
The Beihai sample showed the largest intra-sample genetic variation (h - 0.5486; p =
0.2458) (Table 3).
Within-sample diversity averaged over five hatchery stocks was even lower (h =
0.0237 and p = 0.0086) compared with wild samples (Table 3). Hatchery produced strains SCA 99 and SCA 00 derived from the Beihai population contained two rare 27 haplotypes and showed the highest genetic variability of the hatchery stocks (h = 0.0400 and p = 0.0037; h = 0.0400 and p = 0.0356 respectively). Extremely low diversity (h =
0.0000; p < 0.0001) was revealed in the hatchery stocks NCA and WCA, and the hatchery stocks collected from the Pacific coast of the United States (TUI).
Nucleotide Sequence Diversities and Divergences
The average within-sample nucleotide sequence diversity (7r) of the wild C. ariakensis samples was 0.6016 (Table 4). The Beihai (B) sample showed a significantly higher sequence difference of 2.704, while the other four samples showed an average nucleotide sequence difference of 0.0761. The value of the within-sample nucleotide sequence difference was as low as 0.0000 in the samples of YR, C and I. The mean nucleotide sequence divergence among the wild samples (6) was 3.073, ranging from
0.0000 (between YR and I) to 5.180 (between C and I). The greatest net nucleotide sequence divergence (6a ) was found between the YR and C samples (5.000) and between the C and I samples (5.000) with an average of 2.363 overall.
For hatchery samples, within-sample nucleotide diversity varied from 0 (TUI,
NCA and WCA) to 0.3919 (SCA 00) with an average of 0.0944, while among-sample nucleotide sequence divergence (6) ranged from 0 to 0.24 with an average of 0.132. The greatest net nucleotide sequence divergence was found between SCA 00 and many of the other samples including TUI, NCA, SCA or WCA (0.004) with an average of 0.0016
(Table 4).
Selective Neutrality and Population Equilibrium
The result of mutation-drift equilibrium tests is shown in Table 5. Using the
Tajima’s D test, D values of -2.176, -1.464, -1.573 were obtained for samples D, SCA 99 28 and SCA 00, respectively, which were significantly different from 0 (P < 0.05). However, the result of Fu’s Fs, which was devised specifically to detect population expansion and is more sensitive to the presence of singletons in a sample, showed a non- significant value (Fs = 0.9429, P = 0.480; Fs = -0.8585, P = 0.097; Fs =1.4362, P = 0.652) in these three samples.
AMOVA
Tables 6, 7 and 8 summarize the results of several hierarchical AMOVA analyses and associated significant tests. When the putative groups were defined as the northern
(YR and I) and southern (B, C and D) groups according to their geographic locations, the observed mitochondrial variance could be attributed to inter-group variance (71%) with a significant fixation index (Fct = 0.7086, P < 0.0001). Only 14% of variance was attributed to inter-sample divergence. Furthermore, an estimated Fsc value (among samples within each group) of 0.4439 (P < 0.0001) suggested that samples were still substructured within at least one group (Table 6). So the second AMOVA test was performed between samples in each northern (YR and I) and southern group (B, C and
D). YR and I in the northern group were not significantly different (Fsc - 0.0000), whereas the southern group was structured due to the significant differentiation among the samples of B, C and D at inter-sample level (Fsc = 0.4568, P - 0.000). A further
AMOVA test between each pair of the samples of B, C, and D revealed that sample B was significantly different from either C (Fsc = 0.4956, P < 0.0001) or D (Fsc = 0.4375,
P < 0.0001). However, there was no significant genetic differentiation between C and D
(Fsc = 0.0018, P = 0.4830) (Table 7). 29
When the putative groups were defined as the northern (YR and I) and southern
(C and D) groups and B sample was not included, the difference between the northern and southern groups was more significant (Fct — 0.9843; P < 0.0001). Most of within- group variation resulted from within-sample (Fst = 0.9843; P < 0.0001), rather than among-sample (Fsc = 0.0003; P = 0.4467) variation (Table 8).
Pairwise Genetic Differentiation
In pairwise population comparisons, highly significant genetic differentiation existed (P < 0.05) between the northern (YR and I) and southern (B, C and D) groups based on Fst values calculated from pairwise differences, suggesting that these samples were structured according to geographic localities (Table 9). Furthermore, B significantly differed from either C or D (P < 0.0001), while C and D were not significantly different at P < 0.05 level (P = 0.487).
UPGMA Analysis
UPGMA analysis clustered the five wild and five hatchery samples into three distinct groups based on the distance matrix of net nucleotide sequence divergences of mtDNA haplotypes (Figure 4). All assayed samples from the hatchery stocks clustered with YR and I in one phenetic group. B was a close sister group to the “northern” samples (YR and I) and hatchery stocks. Samples C and D fell into another highly divergent group.
Nuclear DNA
Gene Amplification
PCR reactions successfully amplified roughly 520 or 535 bp of the first internal transcribed spacer (ITS-1) gene from all five geographic and five hatchery samples. It is 30 noteworthy that the fragment size of PCR products amplified from some samples in the southern group (B, C and D) was about 15 bp larger than those obtained from the YR and
I samples.
Digestion Polymorphism
PCR-RFLP analysis with the restriction enzymes BamH I and Sst II revealed polymorphisms in the ITS-1 region (Figure 3 and Table 10) among a total of 277 oyster individuals. However, restriction digests with Rsr II at the ITS-1 region showed invariable patterns between samples, although the virtual digests revealed a cutting site between 463 bp and 464 bp in two individuals of ITS-1 sequences from Itoki River but not in those of the YR, B, C and D samples.
ITS-1 revealed two distinct composite genotypes. The absence of the BamH I restriction site was always observed together with the presence of a Sst II restriction site, while the absence of the Sst II site was always associated with the presence of a BamH I site. The composite genotype AAAA was assigned to individuals with the Sst II site, but lacking the BamH I site and BBBB was assigned to those with the BamH I site, but lacking the Sst II site. Both genotypes were detected in the Beihai (B) sample. YR and I were fixed for the composite genotype AAAA, while genotype BBBB was found at a frequency of 100% in the Zhuhai (C) and 98% in the Yangjiang (D) samples, respectively.
Gene Diversity
The average gene diversity at the ITS-1 gene for the two loci among the five wild samples was 0.1094, ranging from 0.0000 (YR, C and I) to 0.5042 (B). Similar to the 31 results obtained from the mitochondrial RFLP data, hatchery stocks showed a lower gene diversity of 0.0237 at ITS-1 compared with the wild samples (Table 10).
Hardy-Weinberg Equilibrium (HWE)
Observed and expected heterozygosities for both sets of RFLP nuclear markers
(ITS-l-BamH I and ITS-l-Slst II) and associated significance levels of Hardy-Weinberg equilibrium tests by ARLEQUIN and GENEPOP are presented in Table 11. The distributions of genotypes in the samples B, D and SCA 00 did not conform to Hardy-
Weinberg expectations (HWE) (P < 0.05).
Nucleotide Sequence Divergence
Nucleotide sequence diversity within C. ariakensis wild samples ranged from
0.0000 (YR, I and C) to 1.0085 (B) with the average value of 0.2189. The average nucleotide sequence divergence (5) among samples was 1.492. Sequence homogeneity was found between YR and I (0.0000), whereas the greatest divergence values between samples were observed between C and YR or I (2.000). Net nucleotide divergence (5a ) between samples varied from 0.0000 (between YR and I) to 2.000 (between YR and C or b etween C and I) with a mean value of 1.252, suggesting the presence of population structuring among these samples (Table 12).
Among hatchery-produced stocks, the greatest within-sample nucleotide sequence diversity was found in SCA 00 (1.5515), while the other four hatchery samples (TUI,
NCA, SCA 99 and WCA) were genotypically homogeneous. The mean nucleotide sequence divergence among hatchery samples (5) was 0.0176, ranging from 0.0000
(between TUI and NCA, SCA 99, or WCA; between NCA and SCA 99 or WCA; between WCA and SCA 99) to 0.08 (between TUI and SCA 00). The greatest net 32 nucleotide sequence divergence was found between the SCA 00 and other four hatchery samples (0.0024) with an average of 0.00096.
AMOVA
The samples were hierarchically subdivided into the northern (YR and I) and southern (B, C and D) groups and the analysis of molecular variance (AMOVA) was conducted to reveal C. ariakensis population structure. Overall Fct between geographic groups was determined to be 0.7172 (P < 0.0001) with 71% of variance, indicating that inter-specific genetic differentiation did exist in the East Asian C. ariakensis (Table 13).
Further hierachical AMOVA were performed between each pair of samples within the northern or southern geographical group (Table 14). In the northern group, YR and I were haplotypic homogenous, while a significant fixation index value of 0.4828 (P
< 0.0001) was detected at the inter-population level with in the southern group, revealing the existence of substructure among the samples B, C and D. A further division of the southern group suggested that B, C and D were all significantly different (B and C: Fsc =
0.5152, P < 0.0001; B and D: Fsc = 0.4640, P < 0.0001; C and D: Fsc = 0.0127, P <
0.0001). It should be noted, however, that the significant difference between samples C and D is due to a single individual that had a northern-type genotypic profile that was different from the other individuals in both samples C (N = 50) and D (N = 45), which were identical.
Furthermore, AMOVA between the northern group (YR and I) and the southern group (C and D) suggested that the largest component of variance was between groups
(Fct = 0.9887; P < 0.0001), while only 1% of variance was due to the differences within groups (Table 15). 33
Pairwise Genetic Differentiation
Table 16 compares population pairwise Fst values for the five geographic samples. Both samples in the northern group (YR and I) were significantly distinct from the samples in the southern group (B, C and D) (P < 0.0001). In the southern group, B significantly differed from both C and D (P < 0.001). However C and D were not significantly different from each other at the P < 0.05 level (P = 0.228).
Both AMOVA and the pairwise comparisons done with ARLEQUIN gave equivalent results, indicating a tendency for genetic isolation by distance between the northern (YR and I) and southern group (B, C and D). However, AMOVA showed that the C and D samples could be viewed as from a single continuous C. ariakensis population (P < 0.0001), while C and D did not differ by pairwise comparisons (P =
0.228).
Pairwise comparisons of allelic and genotypic frequencies by GENEPOP indicated distinct genetic differentiation between (YR and I) and each of South samples
(B, C and D) (P < 0.001) (Table 17).
UPGMA Analysis
UPGMA analysis based on the net nucleotide sequence divergence from the nuclear ITS-1 RFLP analysis revealed significant genetic differences between the northern and southern groups, showing the same three clusters that were formed based on the mtDNA data (Figure 5). 34
DISCUSSION
Genetic Variability
One striking feature of this data set was the frequency distribution of the observed genotypes. Most (98.7%) of the Crassostrea ariakensis sampled had one of the two most common composite genotypes, and only 1.3% of individuals carried rare alleles.
Frequency distributions similar to those found here have been reported for the Pacific oyster Crassostrea gigas (Boom, 1994) and the American oyster C. viginica (Reeb and
Avise, 1990; Brown and Paynter, 1991). Most individuals of these two oyster species shared the two common haplotypes in roughly the same frequencies and each haplotype was representative of one geographically separated group. Very rare unique alleles were detected in our study. However, more samples would be needed to determine whether these rare alleles are geographically restricted or whether they also occur at a low frequency in other samples.
Intra-population variation in the mtDNA of C. ariakensis (haplotype diversity:
0.1184 and nucleotide diversity: 0.0547) in this study was lower than what has been reported in the literature for other bivalve species. For instance, the studies of genetic diversity of the wild British Columbian populations of C. gigas using restriction analysis of the mitochondrial genome showed a haplotype diversity range of 0.78-0.82 and an average nucleotide diversity of 0.159 (Boom et al., 1994). In that study, a total number of forty-four mtDNA haplotypes were identified among 141 individuals. Reeb and Avise
(1990) reported haplotypic diversities of 0.57 and 0.80 in the Atlantic and Gulf Coast populations of the Eastern oyster C. virginica, respectively, based on RFLP analysis of 35 the whole mitochondrial genome. Similar values were also found in the pearl oyster
Pinctada mazatlanica with haplotypic diversity ranging from 0 to 0.8500 (Amaud et al.,
2000) and in the Hokkaido and Aomori samples of the Japanese scallop Patinopecten yessoensis with haplotypic diversities of 0.66 and 0.79 (Boulding et al., 1993). Lower genetic diversity revealed in this study could result from the application of very limited number of genetic markers compared with other studies.
Decrease in genetic variation can result in a reducted in the effective population size, leading to a limited local carrying capacity and variance in reproductive success, as has been reported for other marine invertebrates (e.g., sea urchins Strongylocentrotus purpuratus and S. droebrachiensis (Palumbi and Wilson, 1990) and the pearl oyster,
Pinctada mazatlanica (Amaud, et al., 2000). However, there is no simple relationship between mtDNA diversity and diversity in the nuclear genome or between mtDNA diversity and fitness (Moritz, 1994).
Population Subdivision
This study indicated population genetic structure in C. ariakensis with both mtDNA-RFLP and nuclear DNA-RFLP data (P < 0.05). These results are in agreement with previous phylogenetic analysis based on the ITS-1 and COI DNA sequences of 5-10 individuals from each sample (Reece, unpublished). However, this study defined a third genetically distinct group from Beihai (B) in the Gulf of Tonkin. The individuals in the B group were genetically similar to either the “northern” or the “southern” genetic-types of
C. ariakensis.
For many marine species, some studies supported the hypothesis that the existence of a pelagic larval stage in the life cycle possibly facilitates large-scale 36 dispersal, depresses variances in allele frequencies, and results in genetic homogeneity among populations (Scheltma, 1971, 1978; Berger, 1973, 1983; Crisp, 1978; Grassle and
Grassle, 1978; Levinton and Suchanek, 1978; Johnson and Black, 1982, 1984a,b;
Palumbi and Wilson, 1990; Palumbi, 1992). However, several studies have revealed significant differentiation between populations of marine invertebrates, such as in bryozoans (e.g., Schopf, 1974; Gooch, 1975), gastropods (e.g., Berger, 1973; Gooch et al., 1972), bivalves and crustaceans (reviewed by Hedgecock, 1986).
Genetic differentiation has been observed among widely separated populations of several oyster species, even considering their strong dispersal ability and high fecundity.
RFLP analysis of the mitochondrial 12S rRNA and the subunit one of cytochrome oxidase genes defined three significantly distinct groups from the Calafia Pearl oyster
Pinctada mazatlanica. These groups corresponded to samples from Northern Mexico,
Southern Mexico and Panama (Amaud et al., 2000). RFLP analysis, based on the whole mitochondrial genome and single-copy nuclear DNA, of the Eastern oyster Crassostrea virginica indicated a pronounced population subdivision between the Atlantic coast and
Gulf of Mexico populations (Reeb and Avise, 1990; Karl and Avise, 1992). A pronounced genetic transition zone was found near Cape Canavera, FL, within which free interbreeding occurred between Gulf and Atlantic populations of oysters (Hare and
Avise, 1996).
Along the eastern coastline of the United States, several marine and salt-marsh species, including marine toadfish (Avise, Reeb and Saunder, 1987), horseshoe crab
(Saunder, et al., 1986), stone crab (Bert, 1986; Bert and Harrision, 1988), southern oyster drill (Liu et al., 1991), ribbed mussel (Sarver et al., 1992) displayed pronounced genetic 37 differences between Atlantic versus Gulf of Mexico locales, with the differences sometimes localizing to the east-Florida coastline, which has long been recognized as the transitional zone between temperate and subtropical maritime faunas (Briggs, 1974).
The finding here of the highly significant difference (P < 0.001) between the northern and southern groups of C. ariakensis was also consistent with the reported population divergence in the wild stocks of the Red Sea bream Pagrus major in China.
The genetic distances based on AFLP analysis indicated that the Yellow Sea stocks
(Weihai) was separated from the East China Sea stocks (Xiamen) and the South China
Sea stocks (Beibuwan), belonging to a different subpopulation (Wang et al., 2001).
Although further information of population subdivision from other species is not available to support that this biogeographic divergence is a multiple-species pattern as that in the southeastern United States, this congruence of geographical divergence accumulated in both mitochondrial and nuclear DNA genetic markers of a phylogeographic pattern in bivalve and fish species may indicate similar biogeographic influences.
The large geographical divergence observed between the northern and southern groups of C. ariakensis may reflect a considerable period of genetic separation due to restricted gene flow. The northern (YR: Yellow River and I: Itoki River) and southern (C:
Zhuhai and D: Yangjiang) localities are separated by more than 6,000 km of temperate and subtropical coastline. Ability of larval dispersal could be limited by spatial (e.g., geographic and hydrographic barriers) or temporal restrictions (e.g. different spawning times). Genetic profiles of each group might shift after genetic segregation because of continuously genetic drift. 38
Another hypothesis might account for this genetic difference is that the mtDNA and nuclear DNA genotype frequencies have responded to different selection pressures between northern China and southern China. For example, with water temperature differences to which mtDNA or nuclear DNA genotypes might be differentially adapted.
However, the environmental selection hypothesis cannot explain for similar genetic breaks among fish and bivalve species.
Within each C. ariakensis geographic group (YR and I, or C and D), no structure was observed among samples separated by up to hundreds of kilometers. Thus, either these groups are still exchanging individuals with sufficient regularity to prevent divergence of genetic patterns, or these groups have not been separated for sufficient time for genetic drift and consequent divergence to occur.
Departures from Hardy-Weinberg Equilibrium
C. ariakensis revealed significant deviations for expected Hardy-Weinberg equilibrium frequencies of genotypes. Heterozygosity estimated from the studied C. ariakensis samples was found to be even lower {Ho = 0.0000) than those in other species of oysters surveyed by low resolution allozyme markers (e.g., the Portuguese oyster C. angulata (0.229 to 0.357), Rebordinos, 1999), the Pacific oyster C. gigas (0.256 to 0.268)
(Hedgecock and Sly, 1990), and the Edible oyster Ostrea edulis from Norway and
Sweden (0.023 to 0.066) (Johannesson et al., 1989)), although there might be substantial differences between populations from different geographic areas.
A deficiency of heterozygotes compared to Hardy-Weinberg expectations appears to be a general characteristic of marine mollusk species as surveyed by allozyme electrophoresis (Berger, 1983; Skibinski et al., 1983; Singh and Green, 1984; Zouros and 39
Foltz, 1984; Gaffney et al., 1990; Gardner, 1992). Zouros and Foltz (1984) listed 27 bivalve species from studies by various authors in which this phenomenon had been reported including Brachidontes , Crassostrea, Macoma, Modiolus and Mytilus. The basis for heterozygote deficiency revealed has been theoretically and experimentally explored by many authors and possible explanations for heterozygosity deficits fall in five categories: inbreeding (Homback et al., 1980), Wahlund effect (Tracey et al., 1975;
Koehn et al., 1976; Kartavtsev, 1978), selection against heterozygotes (Koenh and
Mitton, 1972; Koenh et al., 1973; Boyer, 1974; Beaumont et al., 1980; Gartner-Kepkay et al., 1980; Colgan, 1981), presence of null alleles (Milkman and Beaty, 1970), and scoring bias (Ayala et al., 1973; Buroker et al., 1975).
The absence of heterozygosity as well as co-existence of two genotypes at Beihai sample indicated the possibility of reproductive isolation between the two groups of C. ariakensis. Reproductive isolation could be attributed by: 1) ecological or habitat isolation. Populations occupy different habitats in the same general region, and most matings take place within these microhabitat types. 2) temporal spawning segregation.
Genotype-dependent spawning times or spawning zones may lead to excess production of homozygotes through assortative mating (Zouros and Foltz, 1984; Smith, 1987). 3)
Gametic mortality or incompatibility. Transfer of male gametes occurs but eggs are not fertilized. The northern and southern groups of C. ariakensis might even be considered as different sub-species or sibling species, between which hybridization could not occur.
Further hybridization trials between these two groups of C. ariakensis may allow demonstrating whether two types of the Suminoe oyster should be regrouped into two different species. 40
Analysis of Hatchery Stocks
Hatchery stocks of C. ariakensis held at VIMS hatchery showed reduction in genetic variation and diversity, compared to the wild samples, consistent with population bottlenecks.
It is a common practice for hatcheries to produce large numbers of offsprings from a limited number of parents. To ensure that an adequate number of larvae are produced, broodstock are typically spawned in groups, often with an unequal number of males and females (e.g., Bourne et al., 1989). Group spawning can result in tremendous variation in the number of larvae produced per female; a single female bivalve can spawn millions of eggs, but if the eggs are unripe or if rearing conditions are poor, no viable larvae will be produced. The combination of using few broodstock, greatly unequal family size, and unequal sex rations greatly increases the amount of inbreeding.
Smith et al. (1986) made similar observations when comparing introduced New
Zealand wild stocks with cultured oysters from Mangokuura, Japan. Reduction of genetic variation in wild and hatchery stocks of oysters inferred from allozyme analyses were also reported in Japanese pearl oyster, Pinctada fucata martensii (Wada, 1986), the black pearl oyster, Pinctada margaritifera (Durand et al., 1993), and the Pacific oyster,
Crassostrea gigas (English et al., 2000). One previous study has used mtDNA to assess inbreeding in bivalve populations. Brown and Paynter (1991) used RFLP analysis of the mitochondrial genome to compare the distribution of haplotypes of a hatchery population of the Eastern oyster ( Crassostrea virginica) with that of some wild source populations.
They concluded that the hatchery population was severely inbred. 41
There is no simple relationship between single locus molecular markers such as restriction site changes and most ecological traits (Lande and Barrowclough, 1987), because genetic variation in many quantitative traits often involves many loci that each has a small effect on a trait (Falconer, 1989). Experimental studies where housefly populations were put through various population bottlenecks have demonstrated that a single locus marker may lose genetic variation at a higher rate than quantitative traits
(Bryant et al., 1990; McCommas and Bryant, 1990). Populations maintained at a small effective population size, however, for several generations can lose a substantial amount of genetic variation for quantitative traits such as growth rate and disease resistance
(Lande and Barrowclough, 1987; Hartl and Clark, 1989). Thus a population’s response to either deliberate selection or selection resulting from the invasion of parasites or pathogens can be severely limited (Beattie et al., 1980; Lannan, 1980; Newkirk, 1980;
Hershberger et al., 1984; Beattie et al., 1987). Significant reductions of fish species
(Allendorf and Phelps, 1980; Ryman and Stahl, 1980), and losses of allozyme variation have even been correlated with declines in performance (e. g. Sbordoni et al, 1987). To maintained genetic variability in C. ariakensis stocks prepared for Chesapeake Bay, re- introduction of the southern type of C. ariakensis might be necessary in the near future.
More Sampling
With only five RFLP markers in this study, genotypes characteristic of regions and highly characteristic of populations were identified. This result indicates that it might be possible, with improved of samplings from more geographic localities, to identify the range of geographic distribution and population structure for the Suminoe oyster.
Especially, genetic surveys of geographically intermediate samples (e. g., samples from sites between the northern and southern groups) may allow identification of a genetic transition or hybridization zone between two lineages of genetic types. In addition, it would be interesting to see if these region-specific, as well as the unique markers, can still be productive when more samples from the same or other geographic locations in each north and south group could be tested.
RFLP Analysis of More Nuclear and Mitochondrial Loci
Since each region within the mitochondrial and nuclear genome have different functional and structural constraints and a unique substitution rate, digestion of more nuclear and mitochondrial regions using more enzymes would produce restriction fragment haplotypes (genotypes) that could allow more accurate estimation of genetic variation and heterozygosity. Furthermore, more RFLP markers could help breeding programs to remain genetic diversity in the Suminoe oyster hatchery stocks and protect genetic resources. 43
LITERATURE CITED
Allendorf, F. W. and S. R. Phelps. 1980. Loss of genetic variation in a hatchery stock of
cutthroat trout. Transaction of the American Fisheries Society 109: 537-543.
Angeles Barriga Sosa, I. D. L., K. Beckenbach, B. Hartwick and M. J. Smith. 1995. The
Molecular Phylogeny of Five Eastern North Pacific Octopus Species. Molecular
Phylogenetics and Evolution 4(2): 163-174.
Amason, U. and A. Gullberg. 1993. Comparison between the complete mtDNA
sequences of the blue and the fin whale, two species that can hybridize in nature.
Journal of Molecular Evolution 37: 312-322.
Amaud, S., M. Monteforte, N. Galtier, F. Bonhomme and F. Banc. 2000. Population
structure and genetic variability of pearl oyster Pinctada mazatlanica along
Pacific coasts from Mexico to Panama. Conservation Genetics 1(4): 299-307.
Avise, J. C. 1994. Molecular Markers, Natural History, and Evolution. Chapman and
Hall, Inc. One Penn Plaza, New York, NY 10119.
Avise, J. C., J. Arnold, R. M. Ball, E. Bermingham, T. Lamb, J. E. Neigel, C, A. Reeb,
andN. Saunders. 1987. Intraspecific Phylogeography: The mitochondrial bridge
between population genetics and systematcis. Annual Review of Ecology and
Systematics 18: 489-522.
Avise, J. C., C. A. Reeb and N. C. Saunders. 1987. Geographic population structure and
species differences in mitochondrial DNA of mouthbrooding maring catfishes
(Ariidae) and demersal spawning toadfishes (Batrachoididae). Evolution 41: 991-
1002. 44
Ayala, F. J., D. Hedgecock, G. S. Zumwalt and J. W. Valentine. 1973. Genetic variation
in Tridacna maxima, an ecological analog of some unsuccessful evolutionary
lineages. Evolution 27: 177-191.
Banks, M. A., D. Hedgecock and C. Waters. 1993. Discrimination between closely
related Pacific oyster species ( Crossostrea) via mitochondrial DNA sequences
coding for large subunit rRNA. Molecular Marine Biology and Biotechnology
2(3): 129-136.
Banks, M. A., D. J. McGoldrick, W. Borgeson and D. Hedgecock. 1994. Gametic
incompatibility and genetic divergence of Pacific and Kumanoto oysters,
Crassostrea gigas and C. sikamea. Marine Biology 121: 127-135.
Beattie, J. H., K. K. Chew and W. H. Hershberger. 1980. Differential survival of selected
strains of Pacific oysters ( Crassostrea gigas) during summer mortality.
Proceedings of the National Shellfisheries Association 70: 184-189.
Beattie, J. H., J. Perdue, W. Hershberger and K. Chew. 1987. Effects of inbreeding on
growth in the Pacific oyster ( Crassostrea gigas). Journal of Shellfish Research
6(1): 25-28.
Beaumont, A. R., T. R. Day and G. Gaede. 1980. Genetic variation at the octopine
dehydrogenase locus in the adductor muscle of Cerastoderma edule (L.) and six
other bivalve species. Marine Biology letters 1: 137-148.
Berger, E. M. 1973. Gene-enzyme variation in three sympatric species of Littorina.
Biological Bulletin 145: 83-90. 45
Berger, E. M. 1983. Population Genetics of marine gastropods and bivalves. In The
Mollusca, Vol. 6, Ecology. Russell-Hunter, W. D., eds. Acedemic Press, New
York, pp 563-596.
Bert, T. M. 1986. Speciation in western Atlantic stone crabs (genus Menippe): the role of
geological patterns and climatic events in the formation and distribution of
species. Marine Biology 93: 157-170.
Bert, T. M. and R. G. Harrison. 1988. Hybridization in western Atlantic stone crabs
(genus Menippe): evolutionary history and ecological context influence species
interactions. Evolution 42: 528-544.
Birky, C. W. Jr., P. Fuerst and T. Maruyamal. 1989. Organelle gene diversity under
migration, mutation, and drift: Equilibrium expectations, approach to equilibrium,
effects of heteroplasmic cells, and comparison to nuclear genes. Genetics 121 (3):
613-627,
Bonnaud, L., R. Boucher-Rodoni and M. Monnerot. 1997. Phylogeny of cephalopods
inferred from mitochondrial DNA sequences. Molecular Phylogenetics and
Evolution. 7(1): 44-54.
Boom, J. D. G., E. G. Boulding and A. T. Beckenbach. 1994. Mitochondrial DNA
variation in introduced populations of Pacific oyster, Crassostrea gigas, in British
Columbia. Canadian Journal of Fisheries and Aquatic Sciences 51(7): 1608-1614.
Boudry, P., S. Heurtebise, B. Collet, F. Comette and A. Gerard. 1998. Differentiation
between populations of the Portuguese oyster, Crassostrea angulata (Lamark)
and the Pacific oyster, Crassostrea gigas (Thunberg), revealed by mtDNA RFLP
analysis. Journal of Experimental Marine Biology and Ecology 226: 279-291. 46
Boulding, E. G., J. D. G. Boom and A. T. Beckenbach. 1993. Genetic variation in one
bottlenecked and two wild populations of the Japanese scallop ( Patinopecten
yessoensis ): Empirical parameter estimates from coding regions of mitochondrial
DNA. Canadian Journal of Fisheries and Aquatic Sciences 50 (6): 1147-1157.
Bourne, N., C. A. Hodgson and J. N. C. Whyte. 1989. A manual for scallop culture in
British Columbia. Department of Fisheries and Oceans, Nanaimo, B.C. (Canada).
Pacific Biological Stn. Can. Tech. Pep. Fish. Aquat. Sci., no. 1694, 1989, 230pp.
Boyer, J. F. 1974. Clinal and size-dependent variation at the Lap locus in Mytilus edulis.
Biological Bulletin 147: 535-549.
Briggs, J. C. 1974. Marine Zoogeograhy. McGraw-Hill, New York.
Brown, W. M. 1985. The mitochondrial genome of animals. In Molecular Evolutionary
Genetics. Macintre, R. J., eds. Plenum Press, New York, pp 95-130.
Brown, B.L. and K. T. Paynter. 1991. Mitochondrial DNA analysis of native and
selectively inbred Chesapeake Bay oysters, Crassostrea virginica. Marine
Biology 110: 343-352.
Brown, W. M., E. M. Prager, A. Wang and A. C. Wilson. 1982. Mitochondrial DNA
sequences of primates: tempo and mode of evolution. Journal of Molecular
Evolution 18: 225-239.
Bryant, E. H. and L. M. Meffert. 1990. Multivariate phenotypic differentiation among
bottleneck lines of the housefly. Evolution 44(3): 660-668.
Buroker, N. E., W. K. Hershberger and K. K. Chew. 1975. Genetic variationin the Pacific
oyster, Crassostrea gigas. Journal of the Fisheries Research Board of Canada, 32:
2471-2477. 47
Carlini, D. B. and J. E. Graves. 1999. Phylogenetic analysis of cytochrome C oxidase I
sequences to determine higher-level relationships within the coleoid cephalopods.
Bulletin of Marine Science 64(1): 57-76.
Cantatore, P., M. Roberti., G. Rainaldi, M. N. Gadaleta and C. Saccone. 1989. The
complete nucleotide sequence, gene organization, and genetic code of the
mitochondrial genome of Paracentrotus lividus. Journal of Biological Chemistry
264(19): 10965-10975.
Caporale, D.A., B. F. Beal, R. Roxby and R. J. Van Beneden. 1997. Population structure
of Mya arenaria along the New England coastline. Molecular Marine Biology and
Biotechnology 6(1): 33-39.
Chaisson, R. E., L. A. Serunian and T. J. M. Schopf. 1976. Allozyme variation between
two marshes and possible heterozygote superiority within a marsh in the bivalve
Modiolus demissus. Biological Bulletin 151: 404.
Colgan, D. J. 1981. Spatial and temporal variation in the genotypic frequencies of the
mussle Brachidontes rostratus. Heredity 46: 197-208.
Crisp, D. J. 1978. Genetic consequences of different reproductive strategies in marine
invertebrates. In Marine Organisms: Genetics, Ecology and Evolution. Battaglia,
B and J. A. Beardmore, eds. Plenum Press, New York, pp 257-273.
Cronin, M. A. 1993. Mitochondrial DNA in wild life taxonomy and conservation
biology: cautionary notes. Wildlife Society Bulletin 21: 339-348. 48
Desjardin, P. and R. Morais.1990. Sequence and gene organization of the chicken
mitochondrial genome. A novel gene order in higher vertebrates. Journal of
Molecular Biology 212: 599-634.
Durand, P., K. T. Wada and F. Banc. 1993. Genetic variation in wild and hatchery stocks
of the black pearl oyster, Pinctada margaritifera, from Japan. Aquaculture
110(1): 27-40.
English, L. J., G. B. Maguire and R. D. Ward. 2000. Genetic variation of wild and
hatchery populations of the Pacific oyster, Crassostrea gigas (Thunberg).
Australia. Aquaculture 187(3-4): 283-298.
Excoffier, L., P. Smouse and J. Quattro. 1992. Analysis of molecular variance inferred
from metric distances among DNA haplotypes: Application to human
mitochondrial DNA restriction data. Genetics 131: 479-491.
Falconer, D. S. 1989. Introduction to quantitative genetics. 3rd ed. Longman, New York,
NY. 438pp.
Folmer, O., M. Black, W. Hoeh, R. Lutz and R. Vrijenhoek. 1994. DNA primers for
amplification of mitochondrial cytochrome c oxidase subunit I from diverse
metazoan invertebrates. Molecular Marine Biology and Biotechnology 3(5): 294-
299.
Fu, Y.-X. 1997. Statistical tests of neutrality of mutations against population growth,
hitchhiking and background selection. Genetics 147: 915-925.
Gaffney, P. M., T. M. Scott, R. K. Koehn and W. J. Eiehl. 1990. Interrelationships of
heterozyogosity, growth rate and heterozygote deficiencies in the coot clam,
Mulinia lateralis. Genetics 124: 687-699. 49
Gardner, J. P. A. 1992. Null alleles and heterozygote deficiencies among mussels
(Mytilus edulis and M. galloprovincialis) of two sympatric populations.
Malacologia 34(1-2): 99-102.
Gartner-Kepkay, K. E., L. M. Dickie, K. R. Freeman and E. Zouros. 1980. Genetic
differences and environments of mussel populations in the Marinetime provinces.
Canadian Journal of Fisheries and Aquatic Sciences 37: 755-782.
Gooch, J. L. 1975. Mechanisms of evolution and population genetics. In Marine Ecology,
Vol. II, Part 1. Kinne, O., eds. Wiley, Chichester, pp 349-409.
Gooch, J. L, B. S. Smith, and D. Knupp. 1972. Regional survey of gene frequencies in
the mud snail Nassarius obsoletus. Biological Bulletin 142: 36-48.
Grassle, J. F. and J. P. Grassle. 1978. Life histories and genetic variation in marine
invertebrates. In Marine Organisms: Genetics, Ecology and Evolution. Battaglia,
B and J. A. Beardmore, eds. Plenum Press, New York, pp 347-364.
Groue, K. J. and L. J. Leste. 1982. A morphological and genetic analysis of geographic
variation among oysters in the Gulf of Mexico. Veliger 24: 331-335.
Guo, S. W. and E. A. Thompson. 1992. Performing the exact test of Hardy-Weinberg
proportions for multiple alleles. Biometrics 48: 361-372.
Hartl, D. L. and A. G. Clark. 1989. Principles of population genetics. 2nded. Sinauer,
Sunderland, MA. 683pp.
Hedgecock, D. 1986. Is gene flow from pelagic larval dispersal important in the
adaptation and evolution of marine invertebrates? Bulletin of Marine Science 39:
550-564. 50
Hedgecock, D., G. Li, M. A. Banks and Z. Kain. 1999. Occurrence of the Kumamoto
oyster Crassostrea sikamea in the Arianke Sea, Japan. Marine Biology 133:65-68.
Hedgecock, D. and F. Sly. 1990. Genetic drift and effective population sizes of hatchery-
propagated stocks of the Pacific oyster Crassostrea gigas. Aquaculture 88: 21-38.
Hershberger, W. K., J. A. Perdue and J. H. Beattie. 1984 Genetic selection and systematic
breeding in Pacific oyster culture. Aquaculture 39(1-4): 237-245.
Hillis, D. M. 1987. Molecular versus morphological aproaches to systematics. Annual
Review of Ecology Systematics 18: 23-42.
Hillis, D. M. and M. T. Dixon. 1991. Ribosomal DNA: Molecular evolution and
phylogenetic inference. The Quarterly Review of Biology 66(4): 411-433.
Hombach, D. J., M. J. McLeod, S. I. Guttman and S. K. Seilkop. 1980. Genetic and
morphological variation in the freshwater clam, Sphaerium (Bivalvia:
Sphaeriidea). Journal of Molluscan studies 46: 158-170.
Hudson, R. R. 1990. Gene genealogies and the coalescent process. In Oxford Surveys in
Evolutionary Biology. Futuyama and J. D. Antonovice, eds. Oxford University
Press, New York, pp 1-44.
Johannesson, K., E. M. Roedstroem and H. Aase. 1989. Low genetic variability in
Scandinavian populations of Ostrea edulis L. -- possible causes and implications.
Journal of Experimental Marine Biology and Ecology 128(2): 177-190.
Karl, S. A. and J. C. Avise. 1992. Balancing selection at allozyme loci in oysters:
Implications from nuclear RFLPs. Science 256: 100-102.
Kartavtsev, Y. F. 1978. Genetic variability of bivalve mollusk, the mussel Crenomytilus
gray anus (Mytilidae). Soviet Genetics 14: 186-191. 51
Kauffnann, J., S. Olson and J. Panagrossi. 1994. “MacVector,” Version 7.0. Kodak
Scientific Imaging System, New Haven.
Kemmerer, E. C., M. Lei and R. Wu. 1991. Isolation and molecular evolutionary analysis
of a cytochrome c gene from Oryza sativa (rice). Molecular Biology and
Evolution 8(2): 212-226.
King, T. L., R. F. Villella, M. E. Smith, and M. S. Eackles. 1996. Discontinuity in the
genetic population structure of the green floater Lasmigona subviridis. Journal of
Shellfish Research 15(2): 527-528.
Koehn, R. K., R. Milkman and J. B. Mitton. 1976. Population genetics of marine
pelecypods. IV. Selection, migration and genetic differentiation in the blue mussel
Mytilus edulis. Evolution 30: 2-32.
Koehn, R. K. and J. B. Mitton. 1972. Population genetics of marine pelecypods. I.
Ecological heterogeneity and evolutionary strategy at an enzyme locus. American
Natrualist 106: 47-56.
Kumar, S., K. Tamura, I. B. Jakobsen and M. Nei. 2001. MEGA2: Molecular
Evolutionary Genetics Analysis software. Bioinformatics 17 (12): 1244-1245.
Ladoukakis, E. D. and E. Zouros. 2001. Recombination in animal mitochondrial DNA:
Evidence from Published sequences. Molecular Biology and Evolution 18(11):
2127-2131.
Lande, R. and G. F. Barrowclough. 1987. Effective population size, genetic variation, and
their use in population management. In Viable Populations for Conservation.
Soule, M. E., eds. Cambridge University Press, Cambridge, New York, pp 87-
123. 52
Lannan, J. E. 1980. Broodstock management of Crassostrea gigas. III. Selective breeding
for improved larval survival. Aquaculture 21: 347-351.
Levinton, J. S. and T. H. Suchanek. 1978. Geographic variation, niche breadth and
genetic differentiation at different geographic scales in the mussels Mytilus
californianus and Mytilus edulis. Marine Biology 49: 363-375.
Liu, L. L., D. W. Foltz and W. B. Stickle. 1991. Genetic population structure of the
southern oyster drill Stamonita ( = Thais) haemostoma. Marine Biology 111:71-
79.
McCommas, S. A. and E. H. Bryant. 1990. Loss of electrophoretic variation in serially
bottlenecked populations. Heredity 64: 315-321.
Milkman, R. and L. D. Beaty. 1970. Large-scale electrophoretic studies of allelic
variation in Mytilus edulis. Biological Bulletin 139: 430.
Moritz, C. 1994. Applications of mitochondrial DNA analysis in conservation: A critical
review. Molecular Ecology 3(4): 401-411.
Moritz, C., T. E. Dowling and W. M. Brown. 1987. Evolution of animal mitochondrial
DNA: relevance for population biology and systematics. Annual Review of
Ecology and Systematcis 18: 269-292.
Nei, M. 1987. Molecular Evolutionary Genetics. Columbia University Press, New York,
NY, USA. pp 512.
Nei, M. and J. C. Miller. 1990. A simple method for estimating average number of
nucleotide substitutions within and between populations from restriction dada.
Genetics 125: 873-879. 53
Newkirk, G. F. 1980. Review of the genetics and the potential for selective breeding of
commercially important bivalves. Aquaculture 19: 209-228.
O Foighil, D. and M. J. Smith. 1994. Evolution of asexuality in the cosmopolitan marine
clam Lasaea. Evolution 49(1): 140-150.
Ovenden, J. R. 1990. Mitochondrial DNA and marine stock assessment: A review.
Australian Journal of Marine Freshwater Research 41: 835-853.
Palumbi, S. R. 1992. Marine speciation on a small planet. Tree 7: 114-118.
Palumbi, S. R. 1996. What can molecular genetics contribute to marine biogeography?
An urchin’s tale. Journal of Experimental Marine Biology and Ecology 203: 75-
92.
Palumbi, S. R and A. C. Wilson, 1990. Mitochondrial DNA diversity in the sea urchins
Strongylocentrotuspurpuratus and S. droebachiensis. Evolution 44: 403-415.
Raymond, M. and F. Rousset. 1995. GENEPOP (version 1.2): population genetics
software for exact test and ecumenicism. Journal of Heredity 86: 248-249.
Rebordinos, L., P. Garcia and J. M. Cantoral. 1999. Founder effect, genetic variability,
and weight in the cultivated Portuguese oyster Crassostrea angulata. Journal of
Shellfish Research 18(1): 147-153.
Reeb, C. A. and J. C. Avise. 1990. A genetic discontinuity in a continuously distributed
species: mtDNA in American oyster. Genetics 124: 397-406.
Reece, K.S., K.A. Hudson, Q. Zhang, P. M. Gaffney and S. K. Allen Jr. (unpublished).
Molecular phylogenetic analyses of Crassostrea based on nuclear and
mitochondrial sequences. 54
Reynolds, J., B. S. Weir and C. C. Cockerham. 1983. Estimation for the coancestry
coefficient: basis for a short-term genetic distance. Genetics 105: 767-779.
Ryman, N. and G. Stahl. 1980. Genetic changes in hatchery stocks of brown trout (Salmo
trutta). Canadian Journal of Fisheries and Aquatic Sciences 37: 82-87.
Sambrook, J., E. F. Fritsch and T. Maniatis. 1989. Molecular cloning: a laboratory
manual, 2nd edn. Cold Spring Harbor Laboratory Press, Cold Spring Harbor,
N.Y.
Sanger, F., S. Nicklen and A. R. Coulson. 1977. DNA Sequencing with chain-terminating
inhibitors. Proceedings of the National Academy Sciences, USA 74(12): 5463-
5467.
Sarver, S. K., M. C. Landrum and D. W. Foltz. 1992. Genetics and taxonomy of ribbed
mussles (Geukensia spp.). Marine Biology 113: 385-390.
Saunders, N. C., L. G. Kessler and J. C. Avise. 1986. Genetic variation and geographic
differentiation in mitochondrial DNA of the horseshoe crab, Limulus polyphemus.
Genetics 112: 613-627.
Sbordoni, V., G. La Rosa, M. Mattoccia, M. Cobolli Sbordoni and E. De Matthaeis.
1987. Genetic changes in seven generations of hatchery stocks of the kuruma
prawn, Penaeus japonicus (Crustacea, Decapoda). In Selection, Hybridization
and Genetic Engineering in Aquaculture. Vol. 1, Schriften der
Bundesforschungsanstalt fur Fischerei Hamburg, Hamburg, vol. 18-19, pp 143-
155. 55
Scheltema, R. S. 1971. Larval dispersal as a means of genetic exchange between
geographically separated populations of shallow-water benthic marine gastropoda.
Biological Bulletin 140: 284-322.
Scheltema, R. S. 1977. Dispersal of marine invertebrate organisms. Paleobiogeographic
and biostratigraphic implications. In Concepts and Method of Biostratigraphys.
Kauffman, E.G. and J. E. Hazel, eds. Dowden, Hutchinson and Ross, Inc.
Stroudsbury, Pennsylvania, pp 73-122.
Schopf, T. J. M. 1974. Survey of genetic differentiation in a coastal zone invertebrate: the
ectoproct Schizoporella errata. Biological Bulletin 146: 78-87.
Schneider, S., D. Roessli and L. Excoffer. 2000. Arlequin: A software for population
genetic data analysis, version 2.000. Genetic and Biometry Lab., Department of
Anthropology, University of Geneva, Geneva.
Simon, C., F. Frati, A. Beckenbach, B. Crespi, H. Liu and P. Flook. 1994. Evolution,
weighting, and phylogenetic utility of mitochondrial gene sequences and a
compilation of conserved polymerase chain reaction primers. Ann. Entomol. Soc.
Am. 87(6): 651-701.
Skibinski, D. O. F., J. A. Beardmore and T. F. Cross. 1983. Aspects of the population
genetics of Mytilus (Mytilidae; Mollusca) in the British Isles. Biological Journal
of the Linnean Society 19: 137-183.
Smith, P. J., H. Ozaki and Y. Fujio. 1986. No evidence for reduced genetic variation in
the accidentally introduced oyster Crassostrea gigas in New Zealand. New
Zealand Journal of Marine and Freshwater Research 20 (4): 569-574. 56
Smith, P. J., H. Ozaki and Y. Fujio. 1986. No evidence for reduced genetic variation in
the accidentally introduced oyster Crassostrea gigas in New Zealand. New
Zealand Journal of Marine Research 20: 569-574.
Smith, P. J. 1987. Homozygous excess in sand flounder, Rhombosolea plebeia, produced
by assortative mating. Marine Biology 95(4): 489-492.
Swofford, D. L. 2000. PAUP: Phylogenetic Analysis Using Parsimony (and Other
Methods. Version 4. Sinauer Associates. Sunderland, Massachusetts.
Tajima, F. 1983. Evolutionary relationship of DNA sequences in finite populations.
Genetics 105: 437-460.
Tajima, F. 1989a. Statistical method for testing the neutral mutation hypotheise by DNA
polymorphism. Genetics 123: 585-595.
Thompson, J. D., D. G. Higgins and T. J. Gibson. 1994. Improving the sensitivity of
progressive multiple sequence alignment through sequence weighting, positions-
specific gap penalties and matrix choice. Nucleic Acids Research 22: 4673-4680.
Wada, K. T. 1986. Genetic variability at four polymorphic loci in Japanese pearl oysters,
Pinctada fucata martensii, selected for six generations. Aquaculture 59(2): 139-
146.
Wang, Zhi-yong, Yi-lei Wang, Li-min Lin, Hui-xin Hong, Ya-zhi Zhang, S. K. Khoo
and N. Okamoto. 2001. Genetic variation and divergence of Pagrus major from
China seas using AFLP fingerprinting. Journal of Fisheries of China. 25(4): 289-
293. (In Chinese).
Weir, B. S. and C. C. Cockerham. 1984. Estimating F-statistics for the analysis of
population structure. Evolution 38: 1358-1370. 57
Wolstenholme, D. R. 1992. Animal mitochondrial DNA: structure and evolution. Int.
Rev. Cytol. 141: 173-216.
Zardoya, R. and A. Meyer. 1996. Phylogenetic performance of mitochondrial protein-
coding genes in resolving relationships among vertebrates. Mol. Biol. Evol. 13(7):
933-942.
Zouros, E. and D. W. Foltz. 1984. Possible explanations of heterozygote deficiency in
bivalve mollusks. Malacologia 25(2): 583-591. 58
Table 1 Sample groups of the Suminoe oyster, Crassostrea ariakensis, used in PCR-
RFLP and microsatellite genotyping. 1: Derived from the Yellow River (YR) collection;
2: derived from the Beihai (B) collection in 1999; derived from the Beihai (B) collection in 2000; 4: derived from a C. ariakensis stock in Washington state, USA. N/A: data not available. 59
Locality Abbreviation Date Sampled Sample Species Size Typed by DNA sequencing Yellow River, Bohai Bay, China YR June 1999 36 C. ariakensis
Dafen River, Beihai, Guangxi Province, China B May 1999 50 C. ariakensis
Yamen River, Zhuhai, Guangdong Province, China C May 1999 50 C. ariakensis
Shouchang River, Yangjiang, Guangdong Province, D May 1999 46 C. ariakensis China
Itoki River, I May 1999 50 C. ariakensis Saga Prefecture, Kyushu, Ariake Bay, Japan
VIMS Hatchery NCA1 July and Dec. 50 C. ariakensis 2002 VIMS Hatchery SCA992 July and Dec. 50 C. ariakensis 2002 VIMS Hatchery SCAOO3 July and Dec. 50 C. ariakensis 2002 VIMS Hatchery WCA4 Dec. 2002 and 50 C. ariakensis January 2003
Taylor United Industry Co., Washington State, USA TUI March 2002 50 N/A Table 2 Primer pairs used for amplification of Crassostrea ariakensis DNA, temperatures and durations used for the annealing and "w #o 43 ! ea u CL ClJ u 'o P p in 2 ~ ~ 2 b a>N- ClJ h S3 2 c % NO a NO u u u o u o H O S R H U s a o H S § ’S 2 ^ .2^ T3 o o o 00 0 0 CO w w 1-Q O O O < 3 fa o 2 « S o « ° 00 h pp 3 Q 44 ffi CN O C/3 H 2 P CN in CN CN CN .fi r-' Sample N Composite Haplotype Haplotypic Nucleotide Diversity Diversity ° 2 ^ 2 ^ o o o o r" o o m or- vo < n o o o o o o U o o in j 0.0237 0.0086 o o o oo O o © o o o C/5 <3 < o o o d O o o o o o Table 5 Tajima’s D and Fu’s F tests to assess the deviation from the mutation-drift equilibrium of five wild and five hatchery samples of Crassostrea ariakensis using the infinite site model based on the mitochondrial COIRFLP analysis. Fu’s test is not valid for samples with one allele. Data were obtained by ARLEQUIN ver. 2. 000 (Schneider et al., 2000). Significant P-values (P < 0.05) are shown in bold. Population D P (Tijima) Fs P (Fu’s) Wild YR 0.0000 1.0000 -- B 1.9315 0.9670 6.6152 0.9990 C 0.0000 1.0000 -- D -2.1759 0.0002 0.9429 0.4800 I 0.0000 1.0000 - - Hatchery TUI 0.0000 1.0000 - - NCA 0.0000 1.0000 -- SCA 99 -1.4644 0.0170 -0.8585 0.0970 SCA 00 -1.5727 0.0380 1.4362 0.6520 WCA 0.0000 1.0000 -- T3 I 42 O i > Table 7 Hierarchical AMOVA tests showing the fixation indices and associated significant P- values from pairwise comparisons within each geographical group of Crassostrea ariakensis based on the mitochondrial COIRFLP analysis. Data were obtained by ARLEQUIN ver. 2.000 (Schneider et al., 2000). Significant J°-values (P < 0.05) are shown in bold. Among Samples Fixation Indices Significant Test (Fsc) (P) Northern YR and I 0.0000 - Southern B, C and D 0.4568 < 0.0001 B and C 0.4956 < 0.0001 B and D 0.4375 < 0.0001 C and D 0.0018 0.4830 o £> TO (D G ¥CD • cdH £ +-» G 43 o O C / 3 < p oo 1 cx « o w H■s ■a 3 < 3 O 3 o •2 S3 R •2 53£! Q 2i >«»so O to03 c§ tHO & T3 d> £ O O' W o VJ &0 % #G xn 3 a G CJ? 3 CXC3 § G HH _o O '+-* U 3 3 p . *C o T3 PU G O n 43O J- O 3 o C3 H ^ r-T o s 8 0 0 0 0 o 2 00 9 2o o • IS V o ® o ^ o § § ® S t § 9 © w © S © S ^ QQ ^^ /<1-*s /-—s g o o o ^ m ^ o SO ^ o o o ^ o s g o d S 9 S d S o S 1 ^ 0 0 ® i 1 ® w in Os ® o ® n 'Co^o'fiSO o s ^O s os V ■ d v .2 ,v.2 .v o V OS r \ o ® o ® 1—I ® © o o O r, © OM s O2 0 © O2 O ? © o o © OS © 1/} o © © © \ © So5 Vj v2 v 2 s 2 ;v - ^ IT) © © © O sO © °O s © O s ® m m ® .r- o ^ o ^ o ^ o ? : 9 3 ® o s o tf^O^O^lO^O^ n © »£ © v■ © 3 v 2 v 2 v ^ ”^v Z- v3 v 0 0 © © © ^§00°0N0^S§0 2 f^2 o ^ • ^ • • ^ © S o S oot -i^ OO O o 5020S©n°n00-t. . S -t 8 s ©^ \/ ^ w\/ °^ © m S o9 J S o9 ‘ 9 ■S d S o c C3 #© O s *-C os 13J3 «< U a U U U £ o ca U Q H £ C/3 C/3 P- m Tf m SO © OS Sample N Composite Genotypes Gene Diversity 0 0 0 0 0 - O tN r-H o O O *0 s S O o O 10 O 0 0 0 0 r-" o' —1 ,— _ un o 10 u ^ u (N ^ H o (0.99) (0.01) Mean 0.0237 hH i"H o o CO Tf o o o o 1 © © o o § © © © © 0.0116 0.0106 © © V V o o o o o o o o o o o o ^3 o o o o o o Ph © © © © © © o l-H hH hH i-H hH D- W o o o o o o £S o o o o o o o o o o o o «! o o o o o o o o o © o © hH o o lO vo Tf Tf a o o rs o o o o o 1-H tH o o fif © © © © © © o © © o VV HH£ P o o o o o o £S o o o o o o hS o o o o o o *3 o o o o o o © o o © © © a P 4 WA H+.t5 o o VO VO o o fl vo VO VO VO 0> o HHHH HH 1—1 HH HH 3 H-1 H-1 HH Cd Q 03 *73 s §• PLh O h-1 kb 2 2 s '42 o 03 R § O *»-*Q f-. § 'I 0 Table 14 Hierarchical AMOVA tests showing the fixation indices and associated significant P- values from pairwise comparisons within each geographical group of Crassostrea ariakensis based on the nuclear ITS-1 RFLP analysis. Data were obtained by ARLEQUIN ver. 2.000 (Exoffier et al., 1992). Significant P-values (P < 0.05) are shown in bold. denotes the absence of data due to presence of a single common genotype. Among Samples Fixation Indices Significant Test (Fsc) (P) North YR and I 0 . 0 0 0 0 - South B, C and D 0.4828 < 0 . 0 0 0 1 B and C 0.5152 < 0 . 0 0 0 1 B and D 0.4640 < 0 . 0 0 0 1 C and D 0.0127 < 0 . 0 0 0 1 Td § nd cd § Q C/D §■ § &H 2 I) H-I 'o § s c o GO £ sd H o CD I—i dd C / 3 £ cd CD 03 O K <■** § .<3 o ’I £ yd CN a © nd a © -m CO ) ( CO to d> p O M o 60 _o p 8 ' 8 o© w _ o ^ 0 0 0 to d> "-M . H o_ O O o CN ^cd 1 O O 0.0000 0.0000 0.0000 0.0303 3 a § P h © (0.117) (0.114) (0.125) 3 ) ( co 1 hP i n © O n © O n © a> C/5 © © © 00 00 00 m 0 0 1 B r- © r- © r- © m . CO ON ON ON O n 0 t-" d) 8 OV © © © © cd On 3 Ph O & Ml 1“H ) (< cd hP d- oo ® 2 O 2 O o « d) 0 0 0 0 (N?o ® ® ® i 0 0 1 S-H 3 hm^j O o O o OO'P . d) O ^ © ..© ..© .. On 0 T3 dJ O H VwH W s«^ O 3 TO | d> Mo o in > 2 ® 2 2 00 ® 00 § © s d> PQ ® d ® o \ 9 ^ ® Tf 0 o i-H © NO O O £ ° ^ ©• £®N p o p ) (< p _o V ^ V Tf- v Tr- - V • © w © w © © w © ^ 2 (<0.001) (< 0.001) (< 0.001) CN m a 0 0 1 1 . m s4 d> d) 0 H3 > S in a\ ® O - ® fOo S'©— o ' o o ' 0 0 0.4748 1.0000 0.9789 o NO ® © © O 00o — ^ © oo © © © ©i t"8 8 a2 ®O ® g O- ^CN b? P o © Os o ° ® o CX V v d> ) (< M V 2 ^ 2 O o Cd © d) 0 0 0 £ . cd < 3 1 ) ( ) Ph &0 Q< oo^S^S^SSoSoSo®^ P P 3 © © m ^ © ^ i n ^ © o <~>©<~,© fSl ,o co © O fr5©®©^"'©<^,© c—>©(~>©CN 0 0 0 d> ©•^w©\/9\„0-0.0.0 . p ,-C T-1.- ! V • V V._: -h.mC r*.^< 1 0.0000 0.0000 0.0000 0.0000 3 (0.142) (0.127) cd 3 CO P h > o d> Ph Id o NO § § MS o O n © p 3 O n © -m eL 3 3 E «3 ^h C/5 C/5 C/5 WCA H hP C/5 PQ £ ( /_v r-~ f" © CO © © r~- o 00 < (N © U 1—1 © cn © © „__ s © t-~ © © © •cf © 00 00 (N © r- © © ■'3’ © 0 © 0 /—»s s ©T—« r- v ^ y *—1 ■ 1 O O /—s<--"v /<~S © © OO © © O © © o © © O © © © © © © © © © © © V, V 'w'V s—✓V V^v^ v . v © © ©"o' ©"©" 5 © © © © © 0 © © © © © © © © © 0 © 0 © © 0 0 © 0 © © /”“S i-H1-H/■~\ --I o o o © © 0 © © © vo ^ o o © o © © © © t"- oo © O © © © © © © © © © © © © O © © © © © V V V, v^ V. V. V ^ CO © © © 0 © © © © © 0 © © © © © 0 © 0 © © © © © © 0 © © © © © © © © © © © o o © © © © © © © © o © © © © o © © o o © © o o © © © © o © © © © © © © o o o o © © © © © © © © V V V. y. V V V. .V V, V, © © o © © © © © © o © © o © © © © © © © © © © © © © » © © © © © © © © © © © © o © VO CO © © © © © OV © © © © © © .V. V. V.V V V o ©, © © © © © © © © © © © © © hH NH HH l-H ^ OS ^ © M M tq h &; B St; H tq B e tq a < Bq B 5 Sq B 5 St; B < St; B 03 eq 81 Figure 1 Map of East China and Japan showing locations where samples of Crassostrea ariakensis were collected for population genetic analysis. YR: Yellow River, Bohai Bay, China; B: Dafen River, Beihai, Guangxi Province, China; C: Yamen River, Zhuhai, Guangdong Province, China; D: Shouchang River, Yangjiang, Guangdong Province, China; I: Itoki River, Saga Prefecture, Kyushu, Ariake Bay, Japan. 82 Khabarovsk } ! Irkutsk' Harbin Ulaanbaatar * Changchun MONGOLIA ~ Vladivostok Shenyang Sea or Japan Beijing VokShama r,W ’7 3% VR ^ Lanzhou X\ Zhengzhou ~'i I Naniing^-V-^Shanghai w ac?u s9 AKHns SAR- ---- f - — PhWppine Sea Hasrutn O,io 83 Figure 2 RFLP analysis of the COI gene in the Crassostrea ariakensis. PCR-amplified DNA fragments from C. ariakensis genomic DNA were digested individually with Alu I, Hae III or Taq I. Lane 1, Yellow River (YR); lane 2, Itoki River (I); lane 3, Zhuhai (C); lane 4, Yangjiang (D); lane 5 and 6 , Beihai (B); lane 8 , NCA; lane 9, SCA 99; lane 10, SCA 00; lane 11, TUI; lane 12, WCA. Lane 7 and 13, ladder-molecular weight marker. 84 1 2 3 4 5 6 7 8 9 10 11 12 13 85 Figure 3 RFLP analysis of the ITS-1 region in the Crassostrea ariakensis. PCR- amplified DNA fragments from C. ariakensis genomic DNA were digested individually with BamHl or Sst II. Lane 1, Yellow River (YR); lane 2, Itoki River (I); lane 3, Zhuhai (C); lane 4, Yangjiang (D); lane 5 and 6 , Beihai (B); lane 8 , NCA; lane 9, SCA 99; lane 10, SCA 00; lane 11, TUI; lane 12, WCA. 86 87 Figure 4 UPGMA tree calculated from net nucleotide sequence divergence based on the mitochondrial COI RFLP analysis. YR: Yellow River; I: Itoki River; C: Zhuhai; D: Yangjiang; B: Beihai; NCA: northern China ariakensis, derived from the Yellow River collection; SCA 99: southern China ariakensis, derived from the Beihai collection in 1999; SCA 00: southern China ariakensis, derived from the Beihai collection in 2000; WCA: west coast ariakensis, derived from a C. ariakensis stock in Washington state, USA; TUI: the Taylor United Industry Co. of Washington State, USA. 88 TUI NCA YR WCA 0.546 SCA99 1.642 I SCA00 B C 2.190 D 2,0 1.5 1.0 0.5 0.0 89 Figure 5 UPGMA tree calculated from net nucleotide sequence divergence based on the nuclear ITS-1 RFLP analysis. YR: Yellow River; I: Itoki River; C: Zhuhai; D: Yangjiang; B: Beihai; NCA: northern China ariakensis, derived from the Yellow River collection; SCA 99: southern China ariakensis, derived from the Beihai collection in 1999; SCA 00: southern China ariakensis, derived from the Beihai collection in 2000; WCA: west coast ariakensis, derived from a C. ariakensis stock in Washington state, USA; TUI: the Taylor United Industry Co. of Washington State, USA. 90 YR I WCA 0.222 SCA00 TUI 0.562 NCA SCA99 B 0.784 C D H- H— H- H 0.6 0.4 0.2 0.0 GENETIC VARIATION WITHIN AND AMONG CRASSOSTREA ARIAKENSIS WILD AND HATCHERY SAMPLES, AS REVEALED BY MICROSATELLITE MARKERS 92 INTRODUCTION Microsatellites are tandem arrays of short nucleotide motifs whose unit of repetition is between one and five base pairs (Tautz and Renz, 1984; Tautz, 1989). They are generally found broadly dispersed throughout the nuclear genome of eukaryotes and also in the chloroplast genome of plants (Taultz and Renze, 1984; Wright and Bentzen, 1994). They once were regarded as sequences of no particular interest, however, with the development of the PCR (polymerase chain reaction) technologies, microsatellites are now widely studied and are used in genome mapping programs, and by population biologists for parentage and kinship assignments and for more classical studies of population genetic structure (Jame and Lagoda, 1996). Microsatellites have many advantages over alternative polymorphic marker systems and are very powerful for population studies in many taxa. The rapid mutation rate of microsatellite markers, estimated at 1 0 " 3 to 1 0 " 4 events per locus per generation, make them ideal tools for elucidating finer population genetic structure (Avise, 1994; Jame and Lagoda, 1996; Estoup and Angers, 1998). Although microsatellites have been found within expressed regions of the genome (Brook et al., 1992; Slatkin, 1995), most microsatelllites are located in non-coding regions and are therefore, not likely to be under selective pressure, and are usually considered neutral markers (Avise, 1994; Jame and Lagoda, 1996; Estoup and Angers, 1998). Moreover, they can be detected in very small amounts of DNA. It is therefore advantageous to use these markers for addressing biological questions where one wishes to detect slight departures from panmixia. 93 In population studies, microsatellites have generally been studied by radioactively or fluorescently labeling one of the two PCR primers, which are complementary to the flanking sequence on either side of the repeat unit array. Then the repeat unit array is amplified by PCR. The size of different repeat units at a given locus is identified by their relative electrophoretic migration by comparison with standards (e.g., M13 sequence) or an allelic ladder. Microsatellites can be analyzed further through sequencing, although this is not always possible due to lack of time and money. The use of microsatellites to resolve closely related marine fish populations has increased rapidly over the last few years. For example, population structure was assessed by microsatellite markers in Atlantic cod (Ruzzante et al., 1996), Atlantic salmon (McConnell et al., 1995a and b; Fontaine et al., 1997), brook char (Angers et al., 1995), broad white fish (Patton et al., 1997), whiting (Rico et al., 1997), European sea bass (Garcia de Leon et al., 1997), catfish (Na-Nakom et al., 1999), gag grouper (Chapman et al., 1999), vermilion snapper (Bagly et al., 1999), wreckfish (Ball et al., 2000), rockfish (Sekino et al., 2001), and Japanese flounder (Sekino and Hara, 2001). In studies where both nuclear and mitochondrial genetic markers were used, microsatellite markers have frequently provided additional information about population structure, e.g., in landlocked Atlantic salmon (Tessier et al., 1995) and Atlantic cod (Amason et al., 1992; Brook et al., 1994; Bentzen et al., 1996). Many highly variable microsatellite markers have been developed from mollusks (e.g., the Japanese oyster, Crassostrea gigas, McGoldrick and Fledgecock, 1996; McGoldrick et al., 2000; Magoulas et al., 1998; the European flat oyster Ostrea edulis; Naciri et al., 1995; the Eastern oyster, Crassostrea virginica\ Reece et al., submitted). 94 However, these markers were developed primarily for genome mapping, localization of quantitative trait loci and the implementation of marker-assisted selection regimes (e.g., the Pacific oyster, Boudry et al., 1998; Boudry et al., 2000). The application of microsatellite markers to population genetics studies in mollusks has been very limited. In studies of genetic diversity and differentiation in the European and Asian populations of the Pacific oyster, C. gigas, and the Portuguese oyster, C. angulata, by highly variable microsatellite markers, the introduced C. angulata populations did not show any significant reduction in genetic variability compared to the Taiwanese source populations (Huvet et al., 1999). The objective of this Chapter is to describe the levels of genetic variation and divergence at three microsatellite loci developed for C. gigas and used for Suminoe oyster C. ariakensis individuals collected from four sites along the China coast and one site in Japan. The levels of genetic polymorphism of wild populations of C. ariakensis was also compared with that of five cultured stocks in the United States in an attempt to evaluate the possible inbreeding effect within the hatchery stocks. MATERIALS AND METHODS Microsatellite Amplification and Scoring Three highly polymorphic microsatellite loci, ucdCg 120, ucdCg 172, ucdCg 199, were amplified by flanking primers developed for the Pacific oyster, Crassostrea gigas (Li et al., 2002). Polymerase chain reaction (PCR) amplification of the array was done in 5 u 1 reaction mixtures that included 0.15 u 1 of template DNA, 2.975 u 1 of PCR H 2 O, 1 U 1 of 1 mg/ml Bovine Serum Albumin (BSA), 0.5 u 1 of 10 X PCR buffer, 0.15 u 1 of 50 95 mM MgCl2 , 0.1 u 1 of 10 mM dNTP, 0.05 u 1 of each primer, 0.025 U 1 of 5 unit/ u 1 Taq polymerase. One primer in each primer pair was 5’ end-IR labeled (LICOR Inc., Lincoln, NE). Cycling conditions included an initial denaturation of 2 min at 92 °C, followed by 30 cycles of 30 sec at denaturation at 92°C, 30 sec at the optimal annealing temperature of each primer pair (Table 18), and 45 sec at 72 °C. Final extension was carried out for 5 min at 72 °C. At the termination of the cycling reaction 4 u 1 of formamide stop dye (95% deionized formamide, 0.08% bromophenol blue, 20 mM EDTA [pH 8.0]) were added to each reaction. PCR products were separated on 25 cm, 7% long-range polyacrylamide gels (12.6 g urea, 4.2 ml LongRangIR acrylamide, and 2.4 ml 5 X TBE [pH 8.0] with 220 u 1 10% ammonium persulfate and 22 u 1 TEMED) using an automated sequencer (model 4200L, LICOR Inc., Lincoln, NE) with e-Seq version 2.0 (LICOR Inc., Lincoln, NE). Alleles were designated according to the PCR product size relative to a molecular size marker (LICOR Inc., Lincoln, NE) with RFLPSCAN version 1.00 software (Scanalytics, Fairfax, VA). To score bands with stutters, the strongest band was chosen for allele size determination (Tautz, 1989). Statistical Analysis Standard measures of genetic variation within the samples including the allele frequencies, genotype frequencies, observed heterozygosity (Ho) and expected heterozygosity (He) of each sample at each locus were estimated using GENEPOP program web version 3.1 (Raymond and Rosset, 1995; available at http://wbiomed.curtin.edu.au/genepop/). The difference associated with the average number of alleles per locus (A) and the average number of genotypes (G) between 96 hatchery strains and wild samples was tested by two sample t-tests with MINITAB version 12.1 (Minitab Inc., State College, PA, USA). To assess conformity of genotype distributions to Hardy-Weinberg expectations (HWE), probability tests were performed by the Markov-chain random method (Guo and Thompson, 1992) on all samples using GENEPOP. The permutation parameters used in probability tests were: 1,000 dememorization, 1,000 batches, and 1,000 iterations. Global (table-wide) departures from Hardy-Weinberg were assessed by means of Fisher’s method for combining independent test results (Manly, 1985). Values of the inbreeding coefficient ( Fis; Weir and Cockerham 1984) were also estimated to measure the HWE departures. In addition, all wild and hatchery samples were grouped and a test of Hardy- Weinberg proportions with these groups was performed. Allele-frequency distributions were tested for non-homogeneity across samples using an approximation of an exact test implemented in GENEPOP. A Bonferroni correction (Rice, 1989) was used to calculate the level of significance for multiple comparisons of Hardy-Weinberg equilibrium and linkage equilibrium tests. For three microsatellite loci, the significant criteria after adjustment by Bonferroni methods were 0.05/3 = 0.017. Assessment of genotypic linkage-equilibrium was also calculated using GENEPOP. Probability tests were performed using a Markov-chain method with the following parameters: 1000 dememorizations, 1500 batches and 1000 iterations. Pairwise Fst differences in allelic and genotypic frequencies between wild and cultured stocks (Reynolds et al., 1983; Slatkin, 1995) were estimated using GENEPOP. Unbiased estimators of exact significance probabilities was performed to estimate the probability of whether or not the value of the Fst for each pair of samples was not 97 different from zero by a log-likelihood G test (Goudet et al., 1996), which is analogous to Fisher’s procedure (Sokal and Rohlf, 1995). The difference in the number of alleles and genotypes at three loci among wild samples and hatchery strains was examined by the sequential Bonferroni technique (Rice, 1989). To determine how indicative an individual’s genotype was of the population and from which geographic location each individual was most like to have come, assignment tests (Paetkau et al., 1995) were performed using the Doh assignment test calculator (Brzustowski, 2002; available at http://www2.biology.ualberta.ca/jbrzusto/Doh.php). Wild samples were pooled into two putative groups: the north (YR and I) and south (C and D), and labeled as known groups. All samples were labeled as unknown populations. Assignment test calculated the expected frequency of each individual’s genotype and subsequently assigned each C. ariakensis individual of each sample to one of two genetic types where its expected genotype frequency was higher (Paetkau et al., 1995). By using the microsatellite assignment tests, each individual was assigned to either the northern or southern group from which it was most likely to have come. RESULTS Description and Analysis of the Variability All three microsatellite loci were polymorphic and showed different levels of genetic variability and heterozygosity (Table 19, 20 and Figure 6-8). Microsatellite variation was present with, on average, 12.3 alleles per locus and average heterozygosities close to 32% per locus for ten samples. Overall, average observed heterozygosity (Ho) was low, ranging from 0.080 to 0.4867. 98 Allele frequency distributions typically showed one or two major modes, and exhibited a few rare alleles that typically occurred at the extremes of the size distribution (Figure 6-8). The total number of alleles per locus (A) for each sample, as shown in Table 19, ranged from 3 to 11 with the average number ranging from 3.7 (in the hatchery sample TUI) to 7.3 (in the wild sample B and C). The total number of genotypes per locus ( G) for each sample ranged from 4 to 20 with the average number from 5 (in WCA) to 13.7 (in B). The ranges of allele size at the three loci, ucdCg 199, ucdCg 172 and ucdCg 120, were 198 to 240, 189 to 219, and 94 to 120, respectively. Sample C at ucdCg 199,1 and NCA at ucdCg 172 and I at ucdCg 120 had the largest allele size range compared to other samples. The most common allele (the allele with the highest frequency) of each sample at each locus presented with a frequency ranging from 33% to 95%. At ucdCg 172, particularly, the most common allele occurred at a frequency of more than 50% in seven samples. At one locus, ucdCg 199, the most frequent allele (225 bp) was common to all ten samples, whereas the most common allele varied among samples at the loci ucdCg 172 (201/204 bp) and ucdCg 120 (102/104/116/118 bp). Some differences existed between the microsatellite loci. Indeed, the loci with larger allele size ranges (ucdCg 199 and ucdCg 172) were found to have more alleles per locus, 4 to 11 and 3 to 11 per locus, than the relatively smaller locus, ucdCg 120, which had 3 to 7 alleles per locus. The smaller number of repetitions observed for these two loci is in rough agreement with the observation that the number of alleles usually increases with the mean number of repetitions (Weber, 1990). 99 Departures from Hardy-Weinberg Equilibrium The results, shown in Table 20, clearly indicated a large discrepancy between the observed heterozygosity {Ho) and expected heterozygosity {He) values in each sample at each locus, except for the ucdCg 172 loci in the YR sample {He = 0.6480; Ho = 0.6286). Ho tended to be smaller than He and consequently the mean Ho/He ranged from 14.6% to 82.7%. At the sample level, a consistent and unexpected excess of homozygotes was apparent across the three microsatellite loci (P < 0.017). When a significance test using Markov-chain method was performed for each sample, there was a significant departure from Hardy-Weinberg Equilibrium (HWE) in the wild sample B and in all five hatchery strains (TUI, NCA, SCA 99, SCA00 and WCA) across all three microsatellite loci after correction of significance criteria for K = 3 simultaneous tests {P < 0.017). In addition, sample I deviated from HWE at locus ucdCg 199 and ucdCg 120, while YR and D were out of HWE at locus ucdCg 120. Two of the five hatchery strains (TUI and WCA) and sample B showed significant heterozygote deficiency {P < 0.017) at all three microsatellite loci. Nineteen out of 21 tests (90.5%) showed departures from HWE with an excess of homozygous genotypes {P < 0.017). Only in two cases the lack of HWE equilibrium could not be attributed to a heterozygote deficiency, which occurred in the hatchery stocks NCA and SCA99 at locus ucdCg 172. Departures from HWE remained {P < 0.001) when samples were pooled into the wild or hatchery group, increasing sample sizes to 227 or 228 for the wild group and 249 or 250 for the hatchery group (Table 22). Mutilocus tests of heterozygote deficiencies for grouped wild samples or hatchery strains were also significant {P < 0.001). 100 Linkage Disequilibrium Permutation tests indicated that there was no significant linkage disequilibrium (P > 0.05) for 25 out of 30 (83.3%) pairwise comparisons made for each pair of loci within each of the ten samples. Only sample B, which has two types of C. ariakensis, was significantly out of linkage equilibrium (P < 0.001) at two pairs of loci comparisons (ucdCg 199 and ucdCg 120, and ucdCg 172 and ucdCg 120) (Table 23). Population Subdivision The total number of alleles (A) and genotypes ( G) per locus for each sample ranged from 4 in sample YR at ucdCg 199 to 11 in C at ucdCg 199, and from 5 in I at ucdCg 120, to 20 in C at ucdCg 199, respectively (Table 19). Among five wild samples, the average number of alleles per locus (A) was observed in the order, B (7.3) = C (7.3) > D (6.3) > 1(6) > YR (5.7), and the number of average genotypes per locus ( G) was described as: B (13.7) > C (13.0) > D (10.3)> I (9) >YR (8.3). Allele distribution patterns differed between the northern (YR and I) and southern (C and D) groups (Figure 9 A-C). Allele frequency distributions at the locus ucdCg 120 (Figure 9 C) indicated two separate peaks representing the northern and southern groups. The allele frequency distribution of the northern and southern types of individuals in the sample B assigned by RFLP data also showed two distinct peaks, which is consistent with the allele frequency distributions observed in the northern (YR and I) and southern (C and D) groups (Figure 10 A-C). The results of the assignment tests, shown in Table 24 and Appendix B, were that 81 of 83 individuals (97.6%) from North China and Japan, and 95 of 96 individuals (99.0%) from South China were correctly assigned to their putative groups. The 101 individuals from sample B were assigned to either the northern or southern type. The assignments of the B individuals were largely, 48 of 50 (96%), consistent with the results of the RFLP tests on the mitochondrial and nuclear DNA regions described in the previous Chapter. Only two individuals, B5 and B7 (4.0%), were assigned to a different group based on microsatellites data as compared to the RFLP profile (Table 25 and Appendix B). Population differentiation among wild oysters was also observed when pairwise comparisons of allelic and genotypic frequencies were performed (Table 27). B is the most differentiated wild sample. It was significantly different from the other four wild samples in allelic and genotypic frequencies at the three microsatellite loci. The sample YR was significantly different in both allelic and genotypic frequencies from B, C, and D at all three loci. C and D were different at both ucdCg 199 and ucdCg 120. Analysis of Hatchery Stocks The microsatellite data, presents in Table 19, demonstrated significant reductions in genetic diversity in hatchery strains, which might be caused by hatchery selective breeding together with the occurrence of bottleneck events when these stocks were founded. Two sample t-tests showed that the average number of alleles (A) and genotypes (G) per locus across all five hatchery-held oysters (4.94 and 7.48, respectively) was significantly lower (P = 0.0096 and 0.022, respectively) than the values observed in the wild samples (6.52 and 10.86, respectively), despite the fact that the sample size of each hatchery strain examined (50 individuals) was roughly the same as that of each wild sample (Table 28). The five wild Suminoe oyster samples surveyed showed mean expected heterozygosities of approximately 70.3% while the value for hatchery stocks 102 from the United States was 61.4%. Hatchery stocks also showed a reduced average observed heterozygosity {Ho = 26.8%) and higher inbreeding coefficients {Fis = 60.8%) per locus compared with those from wild samples {Ho = 37.8%; Fis = 46.1%)(Table 21). The large discrepancy between the Ho and He values in each strain revealed a considerable deviation from HWE {P < 0.017) (Table 20). Overall expected heterozygosity {He) associated with the microsatellite loci did not show a pronounced difference between the hatchery strains (mean, 0.2627) and the wild samples (mean, 0.3792), only a substantial reduction of the He value was observed in the SCA 00 strain (0.6820) compared with B (0.7747). Table 22 and Figure 6-8 illustrate the allele frequency distribution of the five wild and five hatchery-produced C. ariakensis samples at the three microsatellite loci. The most common allele at each microsatellite locus was different for wild and hatchery samples. However, the average frequency of the most common allele in the wild samples (0.38-0.68) was not significantly different from that of the cultured samples (0.43-0.73). At the locus ucdCg 120, in particular, an allele with the repeat number of 58 (116bp) appeared with the extremely high frequency (70.3%) among hatchery stocks. Some low- frequency alleles were lost in hatchery-reared stocks. Alleles with the sizes of 198, 201, 231, 234, 237 and 240 bp at locus ucdCg 199 in wild samples were not observed in the samples of hatchery stocks. At ucdCg 172, the allele with the size of 198 in wild oysters was lost in hatchery stains. At the locus 120, alleles in range of 94-108 bp were absent in cultivated stocks except four alleles with the size of 104 were found in the sample of SCA 99. 103 The cultivated stocks SCA 99 and SCA 00, which are composed of first- generation individuals spawned at VIMS hatchery, have fewer alleles per locus (A = 5.7) and genotypes (G = 9) than their progenitor wild sample B (A = 7.3; G = 13.7) (Table 19). Loss of rare alleles was also observed in SCA 99 and SCA 00 (Figure 6-8). For example, five low frequency alleles (201, 210, 213, 234 and 240 bp) at locus ucdCg 199 and four (98, 102, 106, and 108 bp) at ucdCg 120 in B were absent. On the other hand, the most common alleles in the sample B (size 225 bp at ucdCg 199 and 201 bp at ucdCg 172) were different from those in SCA 99 and SCA 00 (size 216 bp at ucdCg 199 and 204 bp at ucdCg 172). Higher frequencies of the most common alleles (mean, 42.7% and 57.0%) were observed in SCA 99 and SCA 00 than those in B (mean, 37.7%). Consistent with the above data, assignment tests showed all individuals from SCA 99 (100%) and most of SCA 00 (94%) were assigned to the northern group with the wild samples from North China (YR) and Japan (I) (Table 24). Two individuals (SCA 00 25 and SCA 00 31) were grouped with the wild samples from southern China by RFLP analysis and were assigned to the southern group by microsatellite assignment tests. However, SCA 00 7 was assigned to the southern group by the microsatellite-based assignment tests instead of the northern one as observed with the RFLP pattern (Table 26). On the other hand, it appeared that only a few alleles (size 213 bp at ucdCg 199; 192 bp at ucdCg 172; 104 and 112 bp at ucdCg 120) were lost in another hatchery- produced stock, NCA, resulting in similar microsatellite variability (A = 5.3; G = 8.7) to its contributing wild sample YR (A = 5.7; G= 8.3). Although the mean observed heterozygosity decreased and the inbreeding coefficient increased in NCA (Ho = 36.0%; Fis = 39.1%) compared with YR {Ho = 42.0%; Fis — 30.6%), NCA and YR shared the 104 most common alleles at all three loci (216 bp at ucdCg 199; 204 bp at ucdCg 172; 116 bp at ucdCg 120) with roughly the same frequency (mean, 66.0% in NCA; mean, 61.3% in YR). All 150 individuals from hatchery strains of NCA, WCA and TUI, as shown by microsatellite assignment tests in Table 24, were assigned to the northern group with oysters from North China (YR) and Japan (I). Moreover, NCA, SCA 99 and SCA 00 strains were founded by directly using wild C. ariakensis and homozygote excess values estimated for these strains were not evident {Ho/He ranging from 0.5299 to 0.7707) compared with values in the strains TUI (Ho/He = 0.2412) and WCA {Ho/He = 0.1460), which were potentially held in hatcheries for generations. In addition, the Fis values of NCA, SCA 99 and SCA 00 strains (0.391, 0.474 and 0.417) were indeed lower compared with those of the stocks that had been held in the hatchery for generations (TUI = 0.763; WCA = 0.853). The microsatellite data presented here also revealed a number of alleles that were not observed in the wild samples, but that were found in reared stocks due to sampling error (Figure 6-8). Two alleles with the sizes of 225 and 228 bp at ucdCg 199, and two alleles with the size of 216 and 219 bp at ucdCg 172 were present in NCA, however, did not appear in the wild sample YR. At ucdCg 172, a new allele with the size of 192 bp appeared in SCA 99 and allele of 195 bp appeared in both SCA 99 and SCA 00. SCA 00 also had new four alleles at microsatellite locus ucdCg 120 (104 bp, 110 bp, 118 bp and 120 bp), among which three alleles (110 bp, 118 bp and 120 bp) also presented in another hatchery strains from B (SCA 99). 105 DISCUSSION Departures from Hardy-Weinberg Equilibrium All analyses consistently revealed a significant excess of homozygotes and most samples showed significant deviation from Hardy-Weinberg expectations (HWE). Similar deviations from HWE have been noted for other marine invertebrate species, such as the blacklip abalone (Haliotis rubra) (Huang et al., 2000). Heterozygote deficiencies detected at three microsatellite loci of the blacklip abalone were attributed to inbreeding caused by restricted larval recruitment, instead of technical or statistical artifacts. However, sometimes it is difficult to determine whether the extensive heterozygote deficiency represents a real biological phenomenon or if it is an artifact of the amplification process. Microsatellite loci may be particularly sensitive to inbreeding effects in small and isolated populations. In a study of eight (CA)n microsatellite loci in isolated human populations, average heterozygosity was significantly lower than expected heterozygosity at some of the loci (Deka et al., 1995). Such variability could also occur due to genetic structure on a microgeographic scale but is unlikely given the very weak macrogeographic structure observed in oysters (Hedgecock, 1994). Variability in allelic frequencies among oysters spawned at different times can also produce an apparent increased in homozygosity. As mentioned by many authors (Na-Nakorn et al. 1999), some inherent technical difficulties associated with scoring of microsatellite alleles can also cause some heterozygotes to be misclassified as homozygotes. 106 Null alleles appear to be a most likely explanation for heterozygote deficiency in this study. Null (non-amplifying) alleles may exist because of polymorphisms between the PCR primer binding sites in C. ariakensis and C. gigas, affecting the efficiency of PCR priming or extension. The presence of null alleles and selection near genetic markers has been documented for bivalve mollusks where pedigree analysis was feasible (e.g., in the Pacific oyster C. gigas, McGoldrick et al., 2000). Although point mutations within the primer-binding site are thought to be generally responsible for the null allele observations, large insertion or deletion events between the repeat array and the primer binding site, poor DNA preparation or mutation within the array, can lead to large changes in product size, which may go undetected (O Connell and Wright, 1997). Null alleles are sometimes difficult to detect in the heterozygous condition and can cause an apparent excess of homozygosity by scoring. In this study, null alleles are most likely to exist at the loci ucdCg 199 and ucdCg 120, where a few possible intermediate size alleles (repeat number 68, 69 at ucdCg 199 and 48 at ucdCg 120) were not detected. In addition, the overall number of heterozygotes was also significantly less than expected from the parental genotypes at ucdCg 199 and ucdCg 120 in most samples. On the other hand, null alleles are less possible at locus ucdCg 172, since all possible alleles respective to ucdCg 172 covering the size range of the microsatellite loci were observed and only 40% of samples showed a significantly excess of homozygotes. Null allele problem may be resolved by lowering priming stringency to accommodate sequence mismatches such as decrease annealing primer-annealing temperature and add more primers for each reaction. Redesigning PCR primers directly from C. ariakensis microsatellite library could avoid most mutation sites. For example, 107 redesigned primers revealed previously invisible alleles at all three human loci investigated (Callen et al., 1993; Phillips et al., 1993; Koorey et al., 1993). However, this is not a final solution, because however exhaustive the search, one can never know whether all non-amplifying alleles at all loci are detected. McGoldrick et al.(2000) also reported that some “borderline” null alleles might amplify more intensely under less stringent PCR conditions (e.g., addition of more primer and lowering of annealing temperatures). The second artifact, which might attribute to heterozygote deficiency in this study, is the appearance of “stutter” bands, particularly for the analysis of dinucleotide- repeat locus ucdCg 120. Stutter bands are ladders of bands typically smaller than the band of interest. They can result in the appearance of thick bands, complicate scoring and lead to the misclassification of heterozygotes for closely sized alleles as homozygotes (O Reilly and Wright, 1995). “Smiling” in a gel is another problem, which may cause scoring error. To reduce the level of variability detected, three sets of size standards were included with two flanked on both sides and one in the middle of each gel. Another possible approach to avoid this problem is to select tetranucleotide repeat loci. These loci are easier to score because of the greater distance between alleles and reduced stutter (O Reilly and Wright, 1995). However, since the very limited number of microsatellite primers of C. gigas could be used in amplifying C. ariakensis microsatellites, tetranucleotide repeat loci were not included in this study. In addition, excess homozygosity may also be observed if sample size is small or sampling ignores genetic structure within sample sites. Given the very high numbers of 108 alleles at most microsatellite loci in the majority of organisms investigated to date, some increase in the sample size is required from that used to investigate genetic variability using less variable markers. Although it is impossible to provide a single optimum sample size for microsatellites, a minimum sample size of 50 individuals per population should be considered for loci showing between five and ten alleles (O Connell and Wright, 1997). So sample size is not a problem in this study. Furthermore, the number of samples that departed from HWE in this study increased accordingly to number of alleles at a locus. More samples deviated from HWE at ucdCg 199 and ucdCg 120, which have 13 alleles per locus, than at ucdCg 172 with 11 alleles. A problem related to that of sample size is the number of loci required to investigate microsatellite variability. The number of loci required depends very much on the biological questions being addressed and the variability of the loci being used (O Connell and Wright, 1997). Since this study aimed to examine population differentiation, three loci may suffice in demonstrating a significant level of structuring among populations. Population Differentiation Distribution of microsatellite allele frequency among C. ariakensis wild samples by microsatellite assignment tests revealed a homogenous genetic structure in geographically relatively close samples. Assignment tests, however, provided insight on genetic structure between the northern (YR and I) and southern group (C and D), which was consistent with the population differentiation indicated by the RFLP results based on mitochondrial and nuclear loci as discussed in Chapter 2. Similarly, it is noteworthy that the two microsatellite allele frequency distribution patterns also existed in Beihai sample 109 as suggested by RFLP data. There is likely to be very limited gene flow, as a result of genetic isolation between the Northern China and Japanese samples and the Southern China samples, which could be attributed to distance, geographic or hydrographic constraints. Alternatively, these two groups of C. ariakensis could be reproductively isolated either physically or temporally. Analysis of Hatchery Strains For stocks of aquaculture species that have been isolated recently from natural populations, the existence of source populations allows analysis of genetic changes (Hedgcock and Sly, 1990). Isolation of commercially cultivated stocks from wild samples opens possibilities for genetic deterioration through reduced effective population sizes. Genetic divergence of isolated hatchery-propagated stocks from their parent groups is expected to accrue over time. Microsatellite variability of the Suminoe oyster hatchery strains in this study could be characterized by reduction in allelic diversity in terms of the number of alleles and genotypes per locus subsequent to their isolation from natural populations. For stocks of aquaculture species that have been isolated recently from extant natural populations, loss of genetic variability might occur even in the first hatchery generation (Verspoor, 1988). This would be caused by loss of low-frequency alleles most likely due to the small number of effective parents when strains were founded, particularly two SCA stocks lost typical alleles representing northern type of C. ariakensis. The large discrepancy between the Ho and He values in most strains revealed a considerable deviation from HWE (P < 0.017). Overall, expected heterozygosity (He) associated with the microsatellite loci did not show a pronounced difference between the 110 hatchery strains (mean, 0.2627) and the wild samples (mean, 0.3792), only a substantial reduction of the He value was observed in the SCA 00 strain (0.6820) compared with the source population B (0.7747). This result agrees with several previous studies for other fish species (reviewed in O Connell and Wright, 1997; Norris et al., 1999; Coughlan et al., 1998), demonstrating that allelic diversity was substantially reduced in hatchery strains without significant differences in the He values between hatchery and wild samples. These results are hardly surprising since loss of low-frequency alleles seems to have little effect on heterozygosity, if a strain was founded using heterozygous parents (Allendorf, 1986). It is thus plausible to consider that a population bottleneck may initially reduce the number of alleles followed by significant loss of heterozygous individuals during subsequent generations (Sekino et al., 2002). Microsatellite Markers Previous studies using allozyme electrophoresis to investigate inbreeding in bivalve populations have failed to detect a decline in the average proportion of allozyme loci that are heterozygous per individual (Dillon and Manzi, 1987; Hedgecock and Sly, 1990; Rebordinos, 1999), probably due to low heterozygosity in both the wild and hatchery groups. This has lead some to conclude that current broodstock management practices were sufficient to prevent loss of genetic variation and eventual inbreeding depression. Such conclusions, however, may be premature since allozymes may be less sensitive and can only detect extreme bottlenecks (Watterson 1984). Genetic variability estimates for microsatellite markers usually provides more genetic information than allozymic loci (Fujio et al., 1989). For the loci analyzed for C. ariakensis, diversity and divergence measures were both higher for the microsatellite loci than for the RFLP I ll analysis of the mtDNA COI and nuclear DNA ITS-1 region. Increased population structure was revealed by analysis of microsatellites because of the different mutation rate of these two markers (Avise, 1994). The microsatellite study not only enabled us to detect large variation in heterozygosity (Ho) (ranged from 0.080 to 0.4867), but also allowed us to detect unique alleles to discriminate among the wild samples. These unique and rare alleles could be used as population or stock-specific markers and are a potential indicator of gene flow (Slatkin, 1985). The results described here also have broader implications for genetic studies in other species, such as many marine invertebrates, characterized by low genetic variation. High variation at microsatellite markers has been described in species with little genetic diversity (Hughes and Queller, 1993), and microsatellite markers have been suggested as a tool for monitoring the loss of genetic variation in isolated or remnant populations (Paetkau and Strobeck, 1994). The work described here on Suminoe oysters indicated that microsatellite analysis could be highly informative for studying genetic structure in populations possessing insufficient diversity to be amenable to study using other genetic markers. Development of ariakensis-specific Microsatellite Markers Using C. gigas primers for amplification of homologous loci in C. ariakensis may not be ideal. These primers may always be prone to numerous null allele problems due to substantial differences in flanking region sequences. Constructing a C. ariakensis microsatellite library will allow for selection of some new primer pairs to produce microsatellite products with ideal size and the number of tandem repeats. The new microsatellite markers would be helpful for two reasons. First, C. ariakensis-specific 112 primers could provide consistently strong microsatellite amplifications for individual samples, saving costly selection attempts from C. gigas primers. Second, the ability to amplify microsatellites in C. ariakensis would strengthen the analysis of genetic variability and population structure of C. ariakensis. Information from more microsatellite markers would provide additional evidence that could be used to evaluate the genetic structure of C. ariakensis. 113 LITERATURE CITED Allendorf, F. W. 1986. Genetic drift and the loss of alleles versus heterozygosity. Proceedings of the workshop on genetic management of captive populations. Zoo Biology 5(2): 181-190. Angers, B., L. Bematchez, A. Angers and L Desgroseillers. 1995. Specific microsatellite loci for Brook charr reveal strong population subdivision on a microgeographic scale. Journal of Fish Biology 47: 177-185. Amason, E., S. Palsson and S. Arason. 1992. Gene flow and lack of population differentiation in Atlantic cod, Gadus morhus L., from Iceland and a comparison of cod from Norway and Newfoundland. Journal of Fish Biology 40: 751-770. Avise, J. C. 1994. Molecular Markers, Natural History, and Evolution. Chapman and Hall, Inc. One Penn Plaza, New York, NY 10119. Bagly, M. J., D. G., Lindquist and J. B. Geller. 1999. Microsatellite variation, effective population size, and population genetic structure of Vermilion snapper, Rhomboplites aurorubens, off the southeastern USA. Marine Biology 134: 609- 620. Ball, A. O., G. R. Sedberry, M. S. Zatcoff, R. W. Chapman and J. L. Carlin. 2000. Population structure of the wreckfish Polyprion americanus determined with microsatellite genetic markers. Marine Biology 137: 1077-1099. Bentzen, P., C. T. Taggart, D. E. Ruzzante and D. Cook. 1996. Microsatellite polymorphism and the population structure of Atlantic cod (Gadus morhud) in the Northwest Atlantic. Canadian Journal of Fisheries and Aquatic Sciences 53: 114 2706-2721. Boudry, P., B. Collet, G. Kotoulas, A. Magoulas, V. Hervouet, F. Bonhomme and A. Gerard. The use of microsatellite markers for parentage analysis in the Pacific cupped oyster, Crassostrea gigas (Thunberg). In International Counc. for the Exploration of the Sea Copenhagen (Denmark) Theme Sess. on the Use of Genetics in Aquaculture. ICES, Copenhagen (Denmark), pp 9. Boudry, P., B. Collet, F. Comette, V. Hervouet and F. Bonhomme. 2000. Microsatellite markers as a tool to study reproductive success in the Pacific oyster, Crassostra gigas (Thunberg), crossed under controlled hatchery condition. Journal of Shellfish Research 19(1): 612. Brzustowski, J. 2002. Doh assignment test calculator. (Available: http://www2.biology.ualberta.ca/ibrzusto/Doh.php) Callen, D. F., A. D. Thompson, Y. Shen, H. A. Phillips, R. I. Richards, J. C. Mulley and G. R. Sutherland. 1993. Incidence and origin o f ‘null’ alleles in the (AC)n microsatellite markers. American Journal of Human Genetics 52: 922-927. Chapman, R. W., G. R. Sedberry, C. C. Koenig and B. M. Eleby. 1999. Stock identification of gag, Mycteroperca microlepis, along the southeast coast of the United States. Marine Biotechnology 1: 137-146. Coughlan, J. P., A. K. Imsland, P. T. Galvin, R. D. Fitzgerald, G. Naevdal and T. F. Cross. 1998. Microsatellite DNA variation in wild populations and farmed strains of turbot from Ireland and Norway: a preliminary study. Journal of Fish Biology 52 (5): 916-922. Deka, R., M. D. Shriver, L. M. Yu, R. E. Ferrell and R. Chakraborty. 1995. Intra- and 115 inter-population diversity at short tandem repeat loci in diverse populations of the world. Electrophoresis 16(9): 1659-1664. Dillion, R. T. and J. J. Manzi. 1987. Hard clam, Mercenaria mercenaria, brookstocks: Genetic drift and loss of rare alleles without reduction in heterozygosity. Aquaculture 60(2): 99-105. Estoup, A. and B. Angers. 1998. Microsatellites and minisatellites for molecular ecology: theoretical and empirical considerations. In Advances in molcecular ecology, Carvalho, G. R.eds. IOS Press, Amsterdam, pp 55-86 (NATO Adv. Sci. Inst. Ser. A: Life Sciences). Estoup, A., F. Rousset, Y. Michalakis, J.-M. Comuet, M. Adriamanga, and R. Guyomard. 1998. Comparative analysis of microsatellite and allozyme markers: a case study investigating microgeographical differentiation in brown trout ( Salmo trutta L.). Molecular Ecology 7: 339-340. Foltz, D. W. 1986. Null alleles as possible causes of heterozygote deficiencies in the oyster Crassostrea virginica and other bivalves. Evolution 40: 869-870. Fontaine, P-M., J. J. Dodson, L. Bematchez and A. Slettan. 1997. A genetic test of metapopulation structure in Atlantic salmon {Salmo salar) using microsatellites. Canadian Journal of Fisheries and Aquatic Sciences 54: 2434-2442. Fujio et al. 1989. Detection of a null allele for MDH isozymes in the guppy ( Poecilia reticulata), with special reference to sex-linked inheritance. Japanese Journal of Genetics 64(5): 347-354. Garcia de Leon, F. J., L. Chikhi and F. Bonhomme. 1997. Microsatellite polymorphisam and population subdivision in natural populations of European sea bass 116 Dicentrarchus labrax (Linnaeus, 1758). Molecular Ecology 6(1): 51-62. Goudet, J., M. Raymond, T. De Meeiis and F. Rousset. 1996. Testing differentiation in diploid populations. Genetics 144: 1933-1940. Guo S. W. and E. A. Thompson. 1992. Performing the exact test of Hardy-Weinberg proportions for multiple alleles. Biometrics 48: 361-372. Hedgecock, D. and F. Sly. 1990. Genetic drift and effective population sizes of hatchery- propagated stocks of the Pacific oyster Crassostrea gigas. Aquaculture 88: 21-38. Hedgecock, D. 1994. Temporal and spatial genetic structure of marine animal populations in the California Current. Reports of California Cooperative Oceanic Fisheries Investigations 35: 73-81. Huang, B. X., P. Peakall, and P. J. Hanna. 2000. Analysis of genetic structure of blacklip abalone ( Haliotis rubra) populations using RAPD, minisatellite and microsatellite markers. Marine Biology 136: 207-216. Hughes, C. R. and D. C. Queller. 1993. Detection of highly polymorphic microsatellite loci in a species with little allozyme polymorphism. Molecular Ecology 2(3): 131- 137. Huvet. A., P. Boudry, M. Ohresser, C. Delsert and F. Bonhomme. 1999. Variable microsatellites in the Pacific oyster Crassostrea gigas and other cupped oyster species. Animal Genetics 31: 68-79. Jame, P. and P. J. L. Lagoda. 1996. Microsatellites, from molecules to populations and back. Tree 11(10): 424-429. Koorey, D. J., G. A. Bishop, and G. W. McCaughan.1993. Allele non-amplification: a source of confusion in linkage studies employing microsatellite polymorphisms Human Molecular Genetics 2: 289-291. Li, G., S. Hubert, K. Bucklin, V. Ribes and D. Hedgecock. (unpublished).Characterization of 79 microsatellite DNA loci in the Pacific oyster Crassostrea gigas: Widespread PCR null-alleles and rapid decay in amplification across congeneric oyster species. Magoulas, A., B. Gjetvaj, V. Terzoglou and E. Zouros. 1998. Three ploymorphic microsatellites in the Japanese oyster, Crassostrea gigas (Thunberg). Animal Genetics 29: 63-72. Manly, B. F. J. 1985. Tests of the theory of natural selection: An overview. Journal of the Royal Society of New Zealand 15(4): 411-432. McConnell, S. K., L. Hamilton, J. Wright and P. Bentzen. 1995a. Isolation of microsatellite loci in Atlantic salmon and their application to the population genetics of Canadian East coast stocks. Aquaculture. McConnell, S. K., P. O Reilly, L. Hamilton, J. M. Wright and P. Bentzen. 1995b. Polymorphic microsatellite loci from Atlantic salmon {Salmo salar): genetic differentiation of North American and European populations. Canadian Journal of Fisheries and Aquatic Sciences 52: 1863-1872. McGoldrick, D. J. and D. Hedgecock. 1996. Microsatellite marker development in the Pacific oyster {Crassostrea gigas): Variability transmission, linkage and QTL mapping. Journal of Shellfish Research 15(2): 512. McGodrick, D. J., D. Hedgecock, L. J. English, P. Baoprasertul and R. D. Ward. 2000. The transmission of microsatellite alleles in Australian and North American stocks of the Pacific oyster {Crassostrea gigas): selection and null alleles. Journal of Shellfish Research 19(2): 779-788. Na-Nakom, U., N. Taniguchi, E. Nugroh, S. Seki and W. Kamonrat. 1999. Isolation and characterization of microsatellite loci of Clarias macrocephalus and their application to genetic diversity study. Fisheries Science 65(4): 520-526. Naciri, Y., Y. Vigouroux, J. Dallas, E. Desmarais, C. Delsert and F. Bonhomme. 1995. Identification and inheritance of (GA/TC)n and (AC/GT)n repeats in the European flat oyster Ostrea edulis (L.). Molecular Marine Biology and Biotechnology 4(1): 83-89. Norris, A. T., D. G. Bradley and E. P. Cunningham. 1999. Microsatellite genetic variation between and within farmed and wild Atlantic salmon {Salmo salar) populations. Aquaculture 180 (3-4): 247-264. O Connell, M. and J. M. Wright. 1997. Microsatellite DNA in fishes. Reviews in Fish Biology and Fisheries 7: 331-363. O Reilly, P. and J. M. Wright. 1995. The evolving technology of DNA fingerprinting and its application to fisheries and aquaculture. Journal of Fish Biology 47 (Supplement A): 29-55. Paetkau, D., W. Calvert, I. Sterling and C. Strobeck. 1995. Microsatellite analysis of population structure in Canadian polar bears. Molecular Ecology 4:347-354. Paetkau, D. and C. Strobeck. 1994. Microsatellite analysis of genetic variation in black bear populations. Molecular Ecology 3(5): 489-495. Patton, J. C., B. J. Gallaway, R. G. Fechhelm and M. A. Cronin. 1997. Genetic variation of microsatellite and mitochondrial DNA markers in broad whitefish {Coregonus nasus) in the Colville and Sagavanirktok rivers in northern Alaska. Canadian 119 Journal of Fisheries and Aquatic Sciences 54: 1548-1556. Phillips, H. A., A. D. Thompson, H. M. Kozman, G. R. Sutherland and J. C. Mulley. 1993. A microsatellite marker within the duplicated D16S79 locus has a null allele: significance for linkage mapping. Cytogenetics and Cell Genetics 64: 131- 132. Raymond, M. and F. Rousset. 1995. GENEPOP (version 1.2): Population genetics software for exact test and ecumenicism. Journal of Fleredity 86: 248-249. Rebordinos, L., P. Garcia and J. M. Cantoral. 1999. Founder effect, genetic variability, and weight in the cultivated Portuguese oyster Crassostrea angulata. Journal of Shellfish Research 18(1): 147-153. Reece, K. S., W. L. Ribeiro, P. M. Gaffney, R. B. Carnegie and S. K. Allen Jr. submitted. Microsatellite marker development and analysis in the eastern oyster, Crassostrea virginica: Confirmation of null alleles and non-Mendelian segregation ratios. J. Fleredity. Reynolds, J., B. S. Weir and C. C. Cockerham. 1983. Estimation for the coancestry coefficient: basis for a short-term genetic distance. Genetic 105: 767-779. Rice, W. R. 1989. Analyzing tables of statistical tests. Evolution 43: 223-225. Rico, C., K. M. Ibrahim, I. Rico and G. M. Hewitt. 1997. Stock composition in North Atlantic populations of whiting using microsatellite markers. Journal of Fish Biology 51: 462-475. Ruzzante, D. E., C. T. Taggart, D. Cook and S. Goddard. 1996. Genetic differentiation between inshore and offshore Atlantic cod (Gadus morhua) off Newfoundland: Microsatellite DNA variation and antifreeze level. Canadian Journal of Fisheries and Aquatic Sciences 53(3): 634-645. Sekino, M. and M. Hara. 2001. Application of microsatellite markers to population genetic studies of Japanese flounder Paralichthys olivaceus. Marine Biotechnology 3: 572-589. Sekino, M., N. Takagi, M. Hara and H. Takahashi. 2001. Analysis of Microsatellite DNA polymorphisms in rockfish Sebastes thompsoni and application to population genetics studies. Marine Biotechnology 3: 45-52. Sekino, M., M. Harab and N. Taniguchi. 2002. Loss of microsatellite and mitochondrial DNA variation in hatchery strains of Japanese flounder Paralichthys olivaceus. Aquaculture 213 (1-4): 101-122. Slatkin, M. 1985. Rare alleles as indicators of gene flow. Evolution 39(1): 53-65. Slatkin, M. 1995. A measure of population subdividion based on microsatellite allele frequencies. Genetics 139: 457-462. Tautz, D.1989. Hypervariability of simple sequences as a general source for polymorphic DNA markers. Nucleic Acids Research 17: 6463-6471. Tautz, D. and M. Renz. 1984. Simple sequences are ubiquitous repetitive components of eukaryotic genomes. Nucleic Acids Research 12: 4127-4138. Tessier, N., L. Bernatchez, P. Presa and B. Angers. 1995. Gene diversity analysis of mitochondrial DNA, microsatellites and allozymes in landlocked Atlantic salmon. Journal of Fish Biology 47 (Supplement A): 156-163. Watterson, G. A. 1984. Lines of descent and the coalescent. Theoretical Population Biology 26(1): 77-92. Weber, J. L. 1990. Informativeness of human (dC-dA)n (dG-dT)n polymorphisms. 121 Genomics 7: 524-530. Weir, B. S. and C. C. Cockerham. 1984. Estimating F-statistics for the analysis of population structure. Evolution 38: 1358-1370. Vespoor, E. 1988. Reduced genetic variability in first-generation hatchery population of Atlantic salmon (Salmon salar). 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N" " N - r © d d d ^ © © © Ov - r ,—v vo —I .— CO © - N i * © i \ — i.—1 —i i 1 1 I3 g 3 - d d d CN d o c CN CN " N v O d o v o o CN N C OV N C © vo © © n i n c © v o o c t v © © - r d CN OV p r~ d © d CN vo d OV - r n i © - r N" OC v O CN CO © - r - r " t © NCO CN d © © © © © OO © © © n i VO © © © VO OO " N N C © © n i © © oo CO oo CN of © © N© CN © o o © v O o o © CN © © d N d ( CN n i vo d OO CN " N d Q © o £ - t- r CO CO © d d t v CN © d OO vo CN N" v O o © n i n i CN © - r - r - r OV OV © VO © CN d d © o c OV N~ n i d OV © in CN © CN ; " t © © © © © © o © o o * © * * d d * * © © © CN © * * d d © © © © © © © © © CO * o ©d o o o o o n i ©vo t"~ © V V V V V V © d CO * n c © '—V © © HJHe 0.7812 0.4990 0.8273 0.6469 0.4058 0.2412 0.7707 0.5299 0.6632 0.1460 Fis 0.306 0.507 0.178 0.338 0.508 0.763 0.391 0.474 0.417 0.852 127 Table 21 Crassostrea ariakensis. Number of samples analyzed (TV), number of alleles per locus (A) and genotypes ( G), allele size range (R), expected heterogosity ( He), observed heterozygosity (H0), inbreeding coefficient (Fis; Weir and Cockerham, 1984), probability of significant deviation from Hardy-Weinberg equilibrium (P) and heterozygote deficiency (P in parenthesis) at the three microsatellite loci when ten samples were pooled into wild and hatchery groups. Calculations were achieved by GENEPOP version 3.3 on web. Significant values which indicates that genotypic frequencies were out of Hardy-Weinberg equilibrium based on exact test with significant level P < 0.017 by initial K of sequential Bonferroni correction (Rice, 1989; K = 3) are shown in bold. 128 Locus Wild______Hatchery ______Mean ucdCg 199 N 228 250 A 13 7 G 31 14 R 198-240 210-228 He 0.7443 0.7064 0.7254 Ho 0.5132 0.3480 0.4306 Ho/He 0.6895 0.4926 0.5936 Fis 0.3111 0.5079 0.4095 P <0.0001 < 0.0001 (< 0.0001) (< 0.0001) ucdCg 172 N 228 250 A 9 10 G 21 21 R 189-213 192-219 He 0.6211 0.6607 0.6409 Ho 0.3728 0.4080 0.3904 Ho/He 0.6002 0.6175 0.6091 Fis 0.4022 0.3829 0.2667 P < 0.0001 <0.0001 (< 0.0001) (< 0.0001) ucdCg 120 N 227 249 A 11 7 G 20 10 R 94-118 110-120 He 0.7423 0.4738 0.6081 Ho 0.2467 0.0321 0.1394 Ho/He 0.3323 0.0678 0.2001 Fis 0.6682 0.9323 0.6471 P <0.0001 <0.0001 (< 0.0001) (< 0.0001) Mean He 0.7026 0.6136 Ho 0.3776 0.2627 Fis 0.4605 0.6077 129 Table 22 Craossostrea ariakensis. Distribution of microsatellite allele frequencies when ten samples were pooled into either wild populations or hatchery strains. 130 Loci Repeat Number Allele Frequency WILDHATCHERY ucdCg 199 66 0.002 0 67 0.004 0 68 0 0 69 0 0 70 0.015 0.002 71 0.039 0.004 72 0.409 0.280 73 0.184 0.188 74 0.182 0.414 75 0.136 0.098 76 0.013 0.014 77 0.002 0 78 0.004 0 79 0.004 0 80 0.004 0 ucdCg 172 63 0.002 0 64 0.007 0.006 65 0.026 0.008 66 0.058 0.018 67 0.554 0.238 68 0.234 0.506 69 0.080 0.156 70 0.033 0.056 71 0.007 0.002 72 0 0.002 73 0 0.008 ucdCg 120 63 0.002 0 64 0.007 0.006 65 0.026 0.008 66 0.058 0.018 67 0.554 0.238 68 0.234 0.506 69 0.080 0.156 70 0.033 0.056 71 0.007 0.002 72 0 0.002 73 0 0.008 Table 23 Crassostrea ariakensis. Pairwise genotypic linkage-equilibrium tests by GENEPOP web version 3.E Probability tests were performed using a Markov chain method with parameters: 1000 dememorization, 1500 batches and 1000 iterations. Significant values are shown in bold. Sample Locus# 1 Locus#2 P - value S. E. YR ucdCg-199 ucdCg-172 0.05824 0.00297 YR ucdCg-199 ucdCg-120 0.19673 0.00405 YR ucdCg-172 ucdCg-120 0.55972 0.00831 B ucdCg-199 ucdCg-172 0.06336 0.00450 B ucdCg-199 ucdCg-120 0.00355 0.00103 B ucdCg-172 ucdCg-120 0.00210 0.00067 C ucdCg-199 ucdCg-172 0.49952 0.00943 C ucdCg-199 ucdCg-120 0.54717 0.00991 C ucdCg-172 ucdCg-120 0.66363 0.00726 D ucdCg-199 ucdCg-172 0.83244 0.00656 D ucdCg-199 ucdCg-120 0.45049 0.00998 D ucdCg-172 ucdCg-120 0.50209 0.00904 I ucdCg-199 ucdCg-172 0.76288 0.00741 I ucdCg-199 ucdCg-120 0.82948 0.00513 I ucdCg-172 ucdCg-120 0.86029 0.00482 TUI ucdCg-199 ucdCg-172 0.20372 0.00471 TUI ucdCg-199 ucdCg-120 0.93640 0.00254 TUI ucdCg-172 ucdCg-120 0.04674 0.00128 NCA ucdCg-199 ucdCg-172 0.94523 0.00325 NCA ucdCg-199 ucdCg-120 0.08489 0.00264 NCA ucdCg-172 ucdCg-120 0.20512 0.00529 SCA 99 ucdCg-199 ucdCg-172 0.03346 0.00214 SCA 99 ucdCg-199 ucdCg-120 0.07370 0.00221 SCA 99 ucdCg-172 ucdCg-120 0.78407 0.00459 SCA 00 ucdCg-199 ucdCg-172 0.53770 0.00705 SCA 00 ucdCg-199 ucdCg-120 0.76135 0.00456 SCA 00 ucdCg-172 ucdCg-120 0.18750 0.00557 WCA ucdCg-199 ucdCg-172 0.39294 0.00402 WCA ucdCg-199 ucdCg-120 0.74338 0.00293 WCA ucdCg-172 ucdCg-120 0.03067 0.00112 132 Table 24 Crassostrea ariakensis. Results of an assignment test by Doh assignment test calculator (Brzustowskii, 2002). The expected frequency of each individual’s genotype was calculated and oysters were assigned into to either of two putative groups: northern (YR and I) or southern (C and D), in which their genotype was most likely to occur. Values are the number of animals from each sample assigned to each of the two geographic groups in the study. Assigned Population Source Population North (YR and I) South (C and D) YR (36) 35 1 1(47) 46 1 C (50) 0 50 D (46) 1 45 B (50) 26 24 NCA (50) 50 0 SCA 99 (50) 50 0 SCA 00 (50) 47 3 WCA (50) 50 0 TUI (50) 50 0 133 Table 25 Crassostrea ariakensis. Results of RFLP genotyping and microsatellite assignment tests in sample Beihai (B). N: genotype of C. ariakensis in Northern China and Japan; S: genotype of C. ariakensis in Southern China. indicates the two cases of inconsistencies between RFLP genotyping and microsatellite assignment tests. RFLP Microsatellite B1 S S B2 N N B3 N N B4 S S B5 S N* B6 s S B7 N S* B8 s s B9 s s BIO s s B ll s s B12 s s B13 N N B14 N N B15 s s B16 N N B17 S S B18 N N B19 N N B20 S S B21 S S B22 N N B23 N N B24 S S B25 S S B26 s s B27 N N B28 N N B29 N N B30 N N B31 N N B32 N N B33 N N B34 N N B35 N N B36 N N B37 S S B38 N N B39 N N B40 N N B41 S S B42 S s B43 s s B44 N N B45 s s B46 N N B47 N N B48 S S B49 s s B50 s s 135 Table 26 Crassostrea ariakensis. Results of RFLP genotyping and micro satellite assignment tests in sample SCA 00. N: genotype of C. ariakensis in Northern China and Japan; S: genotype of C. ariakensis in Southern China. indicates one case of inconsistency between RFLP genotyping and microsatellite assignment tests. RFLP Microsatellite SCA 00 1 N N SCA 00 2 N N SCA 00 3 N N SCA 00 4 NN SCA 00 5 NN SCA 00 6 N N SCA 00 7 N S* SCA 00 8 NN SCA 00 9 NN SCA 00 10 N N SCA 00 11 N N SCA 00 12 N N SCA 00 13 NN SCA 00 14 N N SCA 00 15 N N SCA 00 16 NN SCA 00 17 N N SCA 00 18 N N SCA 00 19 N N SCA 00 20 NN SCA 00 21 N N SCA 00 22 N N SCA 00 23 N N SCA 00 24 N N SCA 00 25 SS SCA 00 26 NN SCA 00 27 N N SCA 00 28 NN SCA 00 29 NN SCA 00 30 N N SCA 00 31 S S SCA 00 32 NN SCA 00 33 N N SCA 00 34 N N SCA 00 35 N N SCA 00 36 N N SCA 00 37 N N SCA 00 38 N N SCA 00 39 NN SCA 00 40 N N SCA 00 41 N N SCA 00 42 NN SCA 00 43 N N SCA 00 44 N N SCA 00 45 NN SCA 00 46 NN SCA 00 47 N N SCA 00 48 NN SCA 00 49 NN SCA 00 50 NN Population YR I B C D TUI NCA SCA99 SCAOO q NO ® q ® S ® O NO ® co© q ® ©» q © © © T* v ® © q - V o V V 0 0 S r~cspQ©t'CMU©t^-cMQ©r^ © © ^ o ~ 22 cv° < CHU 00 © o o i < s ® NO © © ® ® O ® q ® ® ® q q - t ® ®o CO ® ® o q CO © ® ® © © © © © © o o o © q © cO O n 0 0 o ® 23 V ' u < 199 0.2305(0.6524) 0.0016(0.0344) <0.0001(<0.0001) <0.0001 (<0.0001) 0.1256(0.2981) <0.0001 (<0.0001) 0.2275(0.4613) <0.0001(<0.0001) <0.0001(<0.0001) 61878537 ^12^2389 172 <0.0001(0.0001) 0.0108(0.0286) <0.0001(0.0001) o .oooko.oooi) Table 28 Two sample t-test showing the difference between wild and hatchery samples in number of alleles (A) and genotypes (G) per locus by MINITAB. Significant values (P < 0.05) are shown in bold. N Mean StDev SE Mean P A Wild 5 6.520 0.743 0.33 0.0082 Hatchery 5 4.940 0.899 0.40 G Wild 5 10.86 2.40 1.1 0.022 Hatchery 5 7.48 1.96 0.88 Yellow River (YR) Itoki River (I) Figure 6 Crassostrea ariakensis. Allele frequency distribution histogram (bp: base pairs) at ucdCg 199. /fouanbajj CM Yellow River (YR) Itoki Rvier (I) :53 cS a S3 00 c3 o" 00 o o o o' o o Figure 7 Crassostrea ariakensis. Allele frequency distribution histogram (bp: base pairs) at ucdCg 172. Yellow River (YR) Itoki River (I) Figure 8 Crassostrea ariakensis. Allele frequency distribution histogram (bp: base pairs) at ucdCg 120. NCA Xouanbajj Allele Size (bp) 146 A: ucdCg 199 0,6 YR and I 0,5 C and D 0,4 0,3 0,2 0, 1 0 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 B:ucdCg 172 1 YR and I 0, 8 C and D 0, 6 0 ,4 0,2 0 63 64 65 66 67 68 69 70 71 72 73 C: ucdCg 120 1 YR and I 0,8 C and D 0,6 0 ,4 0,2 0 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Figure 9 A-C Crassostra ariakensis. Microsatellite allele frequency distribution between the northern (YR and I) and southern (C and D) wild samples. 147 A: ucdCg 199 0 ,7 (North) 0,6 (South) 0 ,5 0 ,4 0 ,3 0,2 0,1 0 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 B:ucdCg 172 0,7 -♦— B (North) 0,6 -■— B (South) 0, 5 0 ,4 0, 3 0 , 2 0, 1 0 63 64 65 66 67 68 69 70 71 72 73 C:ucdCgl20 0,8 —♦— B (North) 0 ,7 t —■— B (South) 0 , 6 0, 5 0 ,4 0, 3 A 0,2 0, 1 0 ■ i 1Nh i—i■ 1 1 ■ 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Figure 10 A-C Crassostra ariakensis. Microsatellite allele frequency distribution between the northern and southern types of individuals from B (Beihai) sample. B (North): the northern-type the northern type designed based on RFLP results. B (South): the southern-type designed based on RFLP results. 148 Appendix A. Results of Restriction Fragment Length Polymorphism (RFLP) analyses. YR: N = 36 COl-HaelH COl-AluI COl-TaqI ITS-l-BamHI ITS-1-SstII YR1 A A AAAAA YR2 A A AAA AA YR3 A AA AAAA YR4 A A A AAAA YR5 A A A AAAA YR7 A A A AAAA YR8 A A A AAAA YR9 A A A AAAA YR10 A A A AAAA YR11 AA A AAAA YR19 AA A AAAA YR20 AA A AAAA YR21 AA A AA AA YR22 A A A AA AA YR23 A A A AAAA YR24 AA A AAAA YR25 AA A AAAA YR26 AA A AAAA YR27 A A A AA AA YR28 A A A AAAA YR29 A A A AAAA YR30 AA A AAAA YR31 AA A AAAA YR32 A A A AAAA YR33 AA A AAAA YR34 A A A AAAA YR35 A A A AAAA YR36 AA A AAAA YR37 AA A AAAA YR38 AA A AAAA YR39 A A A AAAA YR40 A A A AAAA YR41 A A A AAAA YR42 A A A AAAA YR43 A A A AAAA YR44 A A A AAAA 149 I: N = 47 COl-Haelll COl-AluI 1-TaqI ITS-l-BamHI ITS-1-SstII 11 AA AAA AA 12 A A AAAAA 13 A A AAAAA 14 A A AAAAA 15 AA AAA AA 16 A A AAA AA 17 AA AAAAA 18 AA AAAAA 19 AA AAAAA 111 A A AAAAA 112 A A AAAAA 113 A A AAAAA 114 A A AAAAA 115 A A A AAAA 116 A A AAAAA 118 A A AAAAA 119 A A AAAAA 120 A A AAAAA 121 A A AAA AA 122 AA A AAAA 123 A A A AAAA 124 AA A AAAA 125 A A AAA AA 126 A A AAA AA 127 A A A AAAA 128 A A A AAAA 129 AA AAA AA 130 A A AAA AA 131 A A A AAAA 132 AA A AAAA 133 A A A AA AA 134 A A AAA AA 135 A A A AAAA 136 AA AAA AA 137 A A A AAAA 138 A A A AA AA 140 AA AAA AA 141 AA A AAAA 142 AA A AA AA 143 AA AAA AA 144 AA AAA AA 145 AA A AA AA 146 A A AAA AA 147 A A AAA AA 148 AA A AA AA 149 A A A AA AA 150 A A AAA AA 150 B: N = 50 COl-Haelll COl-AluI COl-TaqI ITS-l-BamHI ITS-1-SstII B1 BBBBBBB B2 AA A AAAA B3 AAAAAAA B4 B BB BB BB B5 B B B BB BB B6 B BBBBBB B7 A AA AA AA B8 B BBBBBB B9 B BBBBBB BIO B BB BB BB B ll B BB BB BB B12 B BB BB BB B13 A AA AA AA B14 A AA AA AA B15 B B B BBBB B16 A A A AAAA B17 B B B BBBB B18 A AAAAAA B19 A AAAAAA B20 B BB BBBB B21 B B B BBBB B22 A A A AAAA B23 A AAAAAA B24 B BBBBBB B25 B B B BBBB B26 BBB BBBB B27 A A A AAAA B28 A C AAAAA B29 A A A AAAA B30 A AA AAAA B31 A AA AA AA B32 A C A AAAA B33 A A A AAAA B34 AAA AAAA B35 AAA AAAA B36 A A A AA AA B37 B BB BBBB B38 A AA AAAA B39 A AA AAAA B40 A A A AAAA B41 B B B BBBB B42 BB B BBBB B43 B B B BBBB B44 A AAAAAA B45 B BB BB BB B46 A A A AAAA B47 A AAAAAA B48 B BB BBBB B49 B BB BBBB B50 B BB BB BB 151 C: N -50 COl-Haelll COl-AluI COl-TaqI ITS-l-BamHI ITS-1-SstII Cl B B B BB BB C2 B B B BB BB C3 B B B BB BB C4 B B B BB BB C5 B B B BB BB C6 B B B BB BB C7 B B B BB BB C8 B B B BB BB C9 B B B BB BB CIO B B B BB BB C ll B B B BB BB C12 B B B BB BB C13 B B B BB BB C14 B B B BB BB C15 B B B BB BB C16 B B B BB BB C17 B B B BB BB C18 B B B BB BB C19 B B B BB BB C20 B B B BB BB C21 B B B BB BB C22 B B B BB BB C23 B B B BB BB C24 B B B BB BB C25 B B B BB BB C26 B B B BB BB C ll B B B BB BB C28 B B B BB BB C29 B B B BB BB C30 B B B BB BB C31 B B B BB BB C32 B B B BB BB C33 B B B BB BB C34 B B B BB BB C35 B B B BB BB C36 B B B BB BB C37 B B B BB BB C38 B B B BB BB C39 B B B BB BB C40 B B B BB BB C41 B B B BB BB C42 B B B BB BB C43 B B B BB BB C44 B B B BB BB C45 B B B BB BB C46 B B B BB BB C47 B B B BB BB C48 B B B BB BB C49 B B B BB BB C50 B B B BB BB 152 D: N = 46 COl-Haelll COl-AluI 1-TaqI ITS-l-BamHI ITS-1-SstII D1 B B B BB BB D2 B B B BB BB D3 B B B BB BB D4 B B B BB BB D9 B B BBB BB DIO BB BBB BB D ll BB B BB BB D12 BB B BB BB D13 B B B BBBB D14 B B B BBBB D15 BB B BBBB D16 B B BBBBB D17 BB BBBBB D18 B B BBBBB D19 BB BBBBB D20 BB BBB BB D21 B B BBB BB D22 B B BBB BB D23 B B B BBBB D24 BB B BB BB D25 BB BBB BB D26 BB BBB BB D27 A C A AAAA D28 BB B BB BB D29 BB BBB BB D30 BB BBB BB D31 BB B BBBB D32 B B BBB BB D33 BB BBB BB D34 B B BBB BB D35 BB BBB BB D36 B B B BBBB D37 BB B BB BB D38 BB B BB BB D39 BB B BB BB D40 BB BBB BB D41 B B BBB BB D42 B B B BB BB D43 B B BBB BB D44 BB BBB BB D45 B B BBB BB D46 B B B BB BB D47 B B BBB BB D48 B B BBB BB D49 B B BBB BB D50 B B BBB BB 153 NCA: N = 50 COl-Haelll COl-AluI 1-TaqI ITS-l-BamHI ITS-1-SstII NCA1 A A A AA AA NCA2 A A A AAAA NCA3 A A A AAAA NCA4 A A A AAAA NCA5 A A A AA AA NCA6 A A A AAAA NCA7 A A A AAAA NCA8 A A A AAAA NCA9 A A AAAAA NCA 10 A A A AA AA NCA11 A A AAAAA NCA 12 A A A AAAA NCA 13 A A A AAAA NCA 14 A A A AAAA NCA 15 A A A AAAA NCA 16 A A A AAAA NCA 17 A A A AAAA NCA 18 A A A AAAA NCA 19 A A A AAAA NCA20 A A AAAAA NCA21 A A A AAAA NCA22 A A A AAAA NCA23 A A A AAAA NCA24 A A A AAAA NCA25 A A A AAAA NCA26 A A A AAAA NCA27 A A A AAAA NCA28 A A A AAAA NCA29 A A A AA AA NCA30 A A A AAAA NCA31 A A A AAAA NCA32 A A A AAAA NCA33 A A A AAAA NCA34 A A A AAAA NCA35 A A A AAAA NCA36 A A A AA AA NCA37 A A A AAAA NCA38 A A A AAAA NCA39 A A A AAAA NCA40 A A A AAAA NCA41 A A A AAAA NCA42 A A A AAAA NCA43 A A A AA AA NCA44 A A A AAAA NCA45 A A A AAAA NCA46 A A AAA AA NCA47 A A A AAAA NCA48 A A A AAAA NCA49 A A A AAAA NCA50 A A A AA AA 154 SCA 99: N = 50 COl-Haelll COl-AluI 1-TaqI ITS-l-BamHI ITS-1-SstII SCA99-1 AA A AAAA SCA99-2 AA A AAAA SCA99-3 A A A AAAA SCA99-4 A A A AAAA SCA99-5 A A A AA AA SCA99-6 A A A AAAA SCA99-7 A A A AAAA SCA99-8 A A A AA AA SCA99-9 A A A AAAA SCA99-10 A A A AAAA SCA99-11 A A A AAAA SCA99-12 A A A AA AA SCA99-13 A A A AA AA SCA99-14 A A A AA AA SCA99-15 A A A AA AA SCA99-16 A A A AA AA SCA99-17 A A A AAAA SCA99-18 A A A AAAA SCA99-19 A A A AAAA SCA99-20 A A A AA AA SCA99-21 A A A AAAA SCA99-22 A A A AAAA SCA99-23 A A A AAAA SCA99-24 A A A AA AA SCA99-25 A A A AAAA SCA99-26 A A A AAAA SCA99-27 A A A AAAA SCA99-28 A A A AA AA SCA99-29 A A A AA AA SCA99-30 A A A AAAA SCA99-31 A A A AAAA SCA99-32 A A A AAAA SCA99-33 A A A AA AA SCA99-34 A C A AA AA SCA99-35 A A A AAAA SCA99-36 A A A AA AA SCA99-37 A A A AAAA SCA99-38 A A A AAAA SCA99-39 A A A AAAA SCA99-40 A A A AA AA SCA99-41 A A A AA AA SCA99-42 A A A AAAA SCA99-43 A A A AA AA SCA99-44 A A A AA AA SCA99-45 A A A AA AA SCA99-46 A A A AA AA SCA99-47 A A A AA AA SCA99-48 A A A AA AA SCA99-49 A A A AAAA SCA99-50 A A A AA AA 155 SCA 00: N = 50 COl-Haelll COl-AluI 1-TaqI ITS-l-BamHI ITS-1-SstII SCA00-1 AA A AA AA SCA00-2 AA AAA AA SCA00-3 AA AAA AA SCA00-4 AA AAA AA SCA00-5 AA A AAAA SCAOO-6 A A AAA AA SCA00-7 A A AAA AA SCAOO-8 A A A AA AA SCA00-9 AA AAA AA SCA00-10 A A A AAAA SCA00-11 A A AAA AA SCA00-12 A A A AA AA SCAOO-13 A A A AA AA SCA00-14 AA A AA AA SCA00-15 AA A AA AA SCA00-16 AA A AA AA SCA00-17 A A AAA AA SCA00-18 AA AAA AA SCA00-19 A A AAA AA SCA00-20 AA AAA AA SCA00-21 A A A AA AA SCA00-22 A A AAA AA SCA00-23 A A A AA AA SCA00-24 A A AAA AA SCAOO-25 B B B BB BB SCA00-26 A A A AA AA SCA00-27 A A A AA AA SCAOO-28 AA A AA AA SCA00-29 AA A AA AA SCA00-30 A A A AA AA SCA00-31 B B B BB BB SCA00-32 A A AAA AA SCAOO-33 AA A AA AA SCA00-34 A A A AA AA SCAOO-35 AA A AA AA SCAOO-36 AA A AA AA SCAOO-37 A A A AA AA SCAOO-38 A A A AA AA SCA00-39 A A AAA AA SCA00-40 A A A AA AA SCA00-41 A A A AA AA SCA00-42 A A A AA AA SCA00-43 A A A AA AA SCA00-44 AA AAA AA SCA00-45 A A A AA AA SCA00-46 AA A AA AA SCA00-47 AA AAA AA SCA00-48 AA A AAAA SCA00-49 AA A AA AA SCA00-50 AA A AAAA 156 WCA: N = 50 COl-Haelll COl-AluI 1-TaqI ITS-l-BamHI ITS-1-SstII WCA1 A A A AAAA WCA2 A A AAAAA WCA3 A A AAAAA WCA4 A A AAAAA WCA5 A A AAAAA WCA6 A A A AAAA WCA7 A A AAAAA WCA8 A A AAAAA WCA9 A A AAAAA WCA10 A A A AAAA WCA11 A A AAA AA WCA12 A A A AAAA WCA13 A A A AAAA WCA14 A A AAAAA WCA15 A A AAAAA WCA16 A A A AA AA WCA17 A A AAA AA WCA18 A A A AAAA WCA19 A A A AAAA WCA20 A A A AAAA WCA21 A A AAA AA WCA22 A A AAA AA WCA23 A A A AAAA WCA24 A A A AAAA WCA25 A A AAA AA WCA26 A A AAA AA WCA27 A A AAA AA WCA28 A A AAA AA WCA29 A A A AAAA WCA30 A A AAA AA WCA31 A A AAA AA WCA32 A A AAA AA WCA33 A A A AAAA WCA34 A A A AA AA WCA35 A A AAA AA WCA36 A A A AAAA WCA37 A A A AA AA WCA38 A A A AA AA WCA39 A A A AA AA WCA40 A A A AA AA WCA41 A A A AA AA WCA42 A A A AA AA WCA43 A A A AA AA WCA44 A A AAA AA WCA45 A A AAA AA WCA46 A A A AA AA WCA47 A A A AA AA WCA48 A A AAA AA WCA49 A A A AA AA WCA50 A A A AA AA 157 TUI: N = 48 COl-Haelll COl-AluI 1-TaqI ITS-l-BamHI ITS-1-SstII TUI1 A A A AA AA TUI2 A A AAAAA TUB A A A AA AA TUI4 A A A AAAA TUI6 A A AAAAA TUI7 A A A AAAA TUI8 A A AAAAA TUI9 A A A AAAA TUI 10 A A AAAAA TUI 11 A A AAAAA TUI 12 A A AAAAA TUI 13 A A AAAAA TUI 14 A A A AAAA TUI 15 A A A AA AA TUI 16 A A A AAAA TUI 17 A A A AAAA TUI 19 A A A AA AA TUI20 A A A AAAA TUI21 A A A AAAA TUI22 A A A AAAA TUI23 A A A AAAA TUI24 A A A AAAA TUI25 A A A AAAA TUI26 A A A AAAA TUI27 A A A AAAA TUI28 A A A AAAA TUI29 A A A AAAA TUI30 A A A AAAA TUI31 A A A AAAA TUI32 A A A AAAA T U B 3 A A A AAAA TUI34 A A A AAAA T U B 5 A A A AAAA TU B 6 A A A AAAA TU B 7 A A A AAAA T U B 8 A A A AAAA TU B 9 A A A AAAA TUI40 A A A AAAA TUI41 A A A AAAA TUI42 A A A AAAA TUI43 A A A AA AA TUI44 A A A AAAA TUI45 A A A AA AA TUI46 A A A AA AA TUI47 A A A AAAA TUI48 A A A AA AA TUI49 A A A AA AA TUI50 A A A AA AA a -Ca ~a ■S s o 3 Q 2 a 3 3 N o i- T f ON I- 3 ) 0 1 OS 1 NO1 NO1 1 r -1 r -1 O1n 0 NO1 ON1 OX) t^5 NO1 OO1 r -1 C"1 001 OO1 OO1 r -1 ON OO ON 3 W W H W w WW w 1 1 W 1 w 3 O w W w NOw NO W OS OS c o c o W W W NO W 00 W W W w O' W GO J- On OS 1—1 T f C O T f GO ON 00 o s NO GO r - 00 l- H r H GO GO l- H T i T t- ON o s NO «u T f 1—1 0 OO ON OS i- H ON GO 1— 1 O t-H 0 l- H ON O ON l- H r - er, OO 0 NO A l- H 1— 1 T f t C l- H O' Sh O GO c o c o GO OO OS OS O OO NO GO OO 0 o s GO CO OS a> rl- r - r - ON i- H T f OO OS » i c o OO c o O T t r - l- H OO r - 0 NO 0 c o 0 3 1—i l- H l- H o £ rn c o r - c o r - O O O ' 0 0 ON O 0 r - GO c o O CO 0 GO c o O' t/5 On 0 0 0 OS OS 00 O' NO 0 0 ON (N r - l- H o s GO 0 0 OS r - NO o ~ T t- OS O' l- H "3 H GO 0 0 c o NO O t"~ ON OS o s c o OS ON NO l- H COCO c o ON ON 0 0 OO ON NO 0 0 . O i—H OX) GO GO c o ON 00 r - c o OO ON ON GO OO OS CO r - ON 0 OO r - OO 00 0 NO OS o OS T f GO r - t j - NO OO OS c o 0 0 ON OO ON r - ~ t J- GO OS OO ON OS GO OS 0 0 GO T f 1—1 r - O ' NO O T f OS OS 0 c o T f ON c o ON r - c o T f ON c o OO T f OS 0 © i—i i— ( c o o s O NO c o ON T f NO T f CO c o NO NO f x f x NO o T f NO NO NO NO NO NO NO ON NO T f NO NO f x 1 NO o T f NO NO ON w i OO 1 1 NO f x NO T f OO o 1 NO 1 OO ON f x 1 f x OO f x W OO 1 NO 1 f x T f CN NO W OO W w ON OO 1 f x OO T f W ON W T f f x OO w o NO OO l-H NO o o W CN w NO o CN r x x T f NO CN f x NO ON w o NO NO f x NO f x T f T f o c o o OO NO ON c o OO o c o c o f x OO f x f x t-H NO OO ON oo CN o CO o OO o ON CN 1— 1 o NO f x f x o T f OO OO T f o CN f x ON l-H T f o T f NO c o NO CO NO OO NO CO l-H NO o CN OO c o OO CN CO l-H o OO NO NO l-H f x l-H OO ON T f OO CO OO o NO NO f x CO OO NO O n NO NO o c o OO CN T f T f o o f x NO NO OO f x ON o T f NO NO NO c o CN f x ON c o l-H T f NO T f O CN c o l-H f x NO l-H T f CN NO l-H i-H ON CO c o c o NO NO o T f CO ON CN OO o l-H IN- o CN (X o O OO (X o c o f x ON NO ON f x NO T f ON f x f x o NO o T f l-H T f ON o o i-H CN CO o l-H i-H T f f x ( x c o f x NO l-H c o NO NO NO ON CN 0 0 CO l-H o c o f x f x T f NO OO c o f x CN CN T f ON l-H ON c o CO c o T f o NO ON i—i OO OO T f OO o NO T f o NO NO NO f x NO CO NO CO ON f x O l-H CN ON ON NO iH NO t-H NO CN <^> NO f x CO T f f x l-H CN l-H T f NO ON OO CN o O CN l-H OO c o o T f NO NO CN o o CN T f l-H OO CN T f CN ON ON o o NO T f f x 0 0 CN NO OO T f T f NO l-H NO CN ON CN OO 1—H NO CN o T f CN OO T f NO i-H NO ON NO o T f NO CN ON f x o f x NO OO OO NO l-H T f c o l- H ON OO CN CO c o l-H NO o o T f c o i-H o f x OO i-H NO f x ON O OO o i-H T f f x l-H f x OO f x T f o T f T f f x c o cN NO f x T f CN T f c o i-H o l-H CN T f T f NO T f NO o c o CN ON NO o NO OO CN NO OO NO T f CN o O NO o NO r- H l-H o NO CN o o NO o CN NO o NO t-H O o l-H f x CN l-H O OO q o NO q o O f x o o o q O NO O o o OO o o o o OO o o CN o CN O o o CN Tf* o f x CN o o o o o i-J o ON o o o T f o o o o CN o o NO o | X O o NO c o ON T f NO T f CO c o i NO NO f x (X NO o T f NO NO NO NO NO NO NO ON NO T f NO NO f x NO o T f NO NO ON w 1 OO 1 1 NO f x NO T f OO ON 1 NO 1 OO ON f x 1 f x OO f x W OO 1 NO 1 f x T f CN NO w OO w W ON OO 1 f x OO T f W ON H T f f x OO w o NO OO i- H • o o o w CN H NO o CN f x T f NO CN f x NO ON w o NO NO f x NO f x T f T f o c o o OO NO ON CO OO o c o c o f x OO f x f x l- H NO OO ON OO CN o CO ON OO ON ON CN l - H o NO f x f x o T f OO OO T f o CN f x ON i- H T f o T f NO c o NO c o NO OO NO CO l- H NO ON CN OO c o OO CN c o i- H o OO NO NO l- H f x « HOO ON T f OO c o OO o NO NO ( x CO OO NO ON NO NO ON c o OO CN T f T f o o f x NO NO OO f x ON O T f NO NO NO c o CN f x ON c o l- H T f NO T f O n CN c o » H f x NO l- H T f CN NO i- H i - H ON c o c o CO NO NO o T f CO O n CN OO o l- H f x o CN f x o O OO f x ON c o f x ON NO ON f x NO T f ON f x f x o NO o T f l- H T f O n o o i- H CN c o o l- H l- H T f f x f x c o f x NO 1—1 CO NO NO NO ON CN 0 0 CO t-H o c o f x f x T f NO OO c o f x CN CN T f ON l- H ON c o CO CO T f ON NO ON l- H OO OO T f OO o NO T f O NO NO NO f x NO CO NO c o ON f x O i- H CN ON ON NO i- H NO l- H NO CN ON NO f x c o T f f x l- H CN l- H T f NO O n 0 0 CN o O CN l- H 0 0 CO o T f NO NO CN o o CN T f l- H OO CN T f CN ON ON o o NO T f f x OO CN NO OO T f T f NO l- H NO CN ON CN OO l- H NO CN ON T f CN 0 0 T f NO l- H NO ON NO o T f NO CN ON f x O f x NO OO OO NO i- H T f c o l- H ON OO CN CO CO l- H NO ON o T f c o l- H o f x OO i- H NO f x ON o OO O l- H T f f x i- H f x OO f x T f o T f T f f x c o CN NO f x T f CN T f c o l- H O l - H CN T f T f NO T f NO o c o CN o NO o NO OO CN NO OO NO T f CN o O NO O NO f H l- H o NO CN o o NO o CN NO o NO l- H O o i- H f x CN i- H O OO q o NO q o o fx- o o O q o NO O o o OO o o o o OO o O CN o CN o o O CN T f o fx* CN* o* o i i o*o* o* 1—H o* ON* o o* o T f o* O o*o* CN o o cococococococoTfTfTfrj-T^-m't^'OhooO\OHOifni- H(Nni-in^M)00\ (N w tl0'0000\0^ p4 P4 04 C^p4 p4 p4 pch P4p4 p4 p4 o o o o o o o o o r-" VO I/O o o m vo i n vo in i n OO i n n v o v o v o in i r - i o v i Ov r - i i o v i OO i v o n r - 1 1 v o 00 in W i W i W 1 i i 1 W W 1 W W 1 W W W i i i W W w W W W i CN i v o W CN W OO w W W OO T f W OO r - w OO n r - W W W OO OO CN VO c o n W W vo o v T f I/O CN s ov c o i n CN T f i n CO CN m c o T f ov in i n •n VO CN r - n T f ov OV Ov 1 I—I i—i I—I i—i i—i i—i i—i l-H T f c o r - CN OV c o ov CN ov o Ov CO i n CN c o i n cn OO v o c o o m in o v i—i T f CN i n o c o T f c o 1—1 o O CN o 1—1 OO o CN o o v OO OO o CN OO l-H c o o o v T f c o 1—1 T f T f 1—1 i—i 0 0 t-H n OO o v r - CN o o OO t-" in T f o CN o o o OO o OV i n CN CN m m c o o v VO i n OV i n O ov n o v ov O in VO o o o v T f N N OO T f VO N vo c o vo o ov v o c o T f O OO VO o v o r - OO o i n v o n r - v o c o i—i vo OO OO Ov n VO v o 1-H 1-H CN OV o v m OV ON OO CN OO o v m OO Ov i—i ov r - OO o v i n o ov 1—1 T f OV Ov ov OV CO VO VO o v cN ov vo OO o- CN o v t-" CN I/O T f ov OV o v m OO CO i n T f OO i n i n VO o v -f-H 1-H i n o v i—Hc o i n CN ov o v m 1-H v o r-- T f i n OV CO CN T f T f r - c o o v o CO 0 0 c o CO i n v o T f v o v o c o o v OV i-H c o OO T f o o v i- h r - o v r - v o r - r - c o i—i vo o v o v o T f 1—1 v o v o T f T f OO OO v o ov t"- r - T f ov T f vo OO l-H r - OO OO CN c o OO T f oo OO OO OO v o CN OO r - i n 00 T f OV OO OO OO OO CN OO r - i o ov OO OO o vo m CN c o o n in T f r - o CN c o O o o v o CN 1—1 T f T f T f o CN c o v o c o o T f c o m OO OO OO i n o v o v i/O OO OO T f o v c o f " OV o v o OV O T f «N i n in o v i n o OO CN OO r - CN i n o VO o CN i—i CN o o f - VO CN v o CO CN CN T f CN v o OO T f i—i 1-H CN CN CN 1-H CN T f T f 1-H i n o vq i n T f CN c o o wo o o c o o cq cq vq OV cq t q iq rq Ov o v cq OO in cq o v i n r - o r - m N vo CN VO VO t-" CN i n T f i VO i n i n T f i n v o c o m v o CO m v o OO vo CO c o v o OO CN OO i n o v o v W n T f ov 1 i t'- v o OO t-'- T f N i 1 o ov o v N c o CN T f o v T f o W 1 w CN T f I— I r-~ v o o T f w W VO v o 1-H VO CN c o vo W w T f i n r^- i n vo CN VO CN m T f VO i n i n T f i n VO c o i n vo c o i n v o i vo c o c o VO OO CN CN CN CN CN c o CN CO T f i n vo N OO OV o 1-H CN CO T f i n VO OO o 1-H CN c o T f m VO N OO ov o o o o CN CN CN CN CN CN CN CN c o c o co CO co CO co co c o Tf Tf Tf Tf Tf Tf T f T f T f T f i n l - H l- H l- H l- H l-H l-H l-H l-H l - H l- H l-H l-H l-H HH hH M l- H l- H l- H HH HH HHHH HHHH HHHHHH OO U T f v o CN T f T f CN VO T f v o T f VO CN c o OO c o T f OV OO I/O 1 OO T f v o CO VO CN T f T f i i n i OO 00 N OV i n o c o T f OO I/O VO CN OO w o 1 VO m T f OV 1 1 W OO w w w CN o T f c o OO T f o o W l- H r - v o r-~W CN CN c o VO v o OO N N v o N o v o O v o o v o v IN o v o v r - v o i i N N i o 1 OO o v OO N i i i N 1 i w W W r-' w i t — w i W w 1 w W i W N W N 1 W i i i W W WWi W CO vo OO i N w 1 i n W OO CN W vo 1 T f W c o i T f 1 W T f W W w CN CN CN W O n CN c o vo o v W VO T f w i n i n CN T f N voW OV VO CO w o w i n m o m r - i n T f o i n T f T f N o N o v l- H OO i n CN N- OO CN OO o c o o v i n IN OV T f IN c o c o T f c o o T f CN o v t-H CO i n O i n I IN l - H 1-H l- H c o T f T f l- H o v i n l- H c o OO o N OO CN i n N CO i n i n CO i n v o o 1— 1 i n VO CN T f i- H N N o i n OV T f OO VO CN Ov o i n v o l- H T f OO OO N- T f OO m c o i n VO N o vo v o c o CO c o CN N N N OO T f o v CO c o i n T f c o VO c o v o o t — v o CN r-~ m T f VO OO i n 1 -H o VO o OO l- H O N m N C-~ CN ov 1-H o CN N- OO VO l- H v o OO c o l- H i- H c o v o N- v o T f o v 1 -H m o o OO i n CN O Ov v o N - OO in v o o v CN CN i n ov i n VO v o N N- T f N OV T f c o Ov N c o l- H i n c o IN ov l - H o N i- H N i n l- H o c o ov CN OO in o v o CO l- H v o T f i- H CO i n N O N v o CN ov c o c o OO OO ov N T f OO VO OO l- H c o c o c o T f ov OO 1-H m c o m in CO o v CO o v IN o v O T f o T f i n O n o o o v T f T f VO i n OO T f CN v o Ov o v o v Ov T f T f m T f T f o v c o CN VO T f i n CN o 1-H T f l- H c o T f T f c o CN r~- CN o l- H CO v o O Ov l- H v o 1-H i n OV OV i n o v i n OO o N v o T f v o o v ov v o o CO N i n N c o c o N o v O r - N- VO vo r - l- H vo v o o v o c o CO o N i n CN T f OO o o O l - H T f i n CN OO N T f OO o O i n ov OO o VO CN o T f l- H O o T f T f OO t-H i n i n c o r - m T f N- o v l - H o N VO OO 1-H N CN c o v o c o T f CN CN o v i n l- H o o OV Ov OO CN CO OO T f vq » i N O 1—1 CN 1—J i n i—N i n o vq ov ON oq T f IN T f i n CN Ov cq CN vq T f N OV CN i— 3 CN . - 3 r- 3 CN CO i- 3 OO CN c o ^h” i- 3 OO i— 3 CN CN Ov 1— 3 c o T f OO i- 3 1— 3 — 3 i— 3 c o T f v o CN T f T f CN v o T f v o f - T f VO CN CO 1 OO CO T f o v OO i n OO T f vo CO VO CN T f T f i i n 1 00 OO N o v i n O CO T f w OO i n 1 v o CN OO W o 1 v o i n T f o v 1 W OO w W w CN O T f c o OO T f O o N - v o N w CN CN CO CN w T f N r - i—i w w i n CN ov i n l-H CN 1 o l-HW 1 T f VO o o c o v o v o VO ov 00 VO N OO CO v o CN Ov CN CN o OO i n c o l-H o v N- H T f N l-H w o v VO CN o v o N o m T f c o CO m v o CN I o v l-H ov O T f c o VO o l-H T f m OO N i n i n T f o r— 0 0 l-H CN o m r—H T f v o 1—I l-H i n O o m o v o v CN o v o v o o CN T f l-H t-H l-H N T f o T f T f OO o r - o CN CN n o v o T f CO l-H o o CN VO OO o v o v i—* o i n in T f OV o T f CN c o o o CO o CN v o o T f r-~ N vo T f CO r-~ VO l-H l-H i n cN 1-H r - T f OO N T f VO T f in i n v o 1-H o l-H i n c o CN T f VO i n T f CN o r - t-H CN i n v o o CN o T f OV o IN i n OV 0 0 VO l-H o v O o v l-H N OO c o OV N OV v o CN OO o CN O o v o CN CN CO v o CN i n VO CN v o o i n T f i n 1-H VO CN c o i n o o v CN VO m o v Ov i n VO c o CN CN CN o v 1-H o v OO CO IN o v v o l-H OV l-H m 1-H l-H i n IN T f v o c o OO l-H o O OO v o o v i n c o o v VO T f r" l-H o v r - c o O o VO T f CN ov o CN c o N v o OV CN OO o Ov vo O o c o l-H vo OO i n v o CN Ov i n o T f T f v o vo c o Ov OO c o T f OV OO m T f c o c o N r - OO 1-H o v vo l-H o t-H r - r - OO CN T f T f o v CN vo l-H t-H 1-H CN CN 0 0 l-H OO CN o c o c o N v o VO CN c o l-H CN v o 1-H c o v o T f o i n r^- o v 1-H v o o OO CO v o VO l-H OO N T f o OV v o c o CN CN o v CN CN OO CO c o c o r - CN v o 1-H OO CN c o OO r - v o i-H CN c o OO OV CN c o i n I—1 v o 1-H o o O l-H O l-H o CN o l-H o O o o l-H ov o o OO o v c o l-H o N o o c o c o o o o i n o o T f o o o OO o T f o O o o T f i n vq o i—j o v CO O o i—i o ON ov o o o Tf" o o’ T f o o o’ i— 3 o’ T f o’ o’ o o’ CN r -‘ T f o’ - — 3 co’ 1— 3 o’ o’ OV o’ o’ oo’ o’ o’ CN CN CN CN CN CN CN CN CN CN CN CN cN cN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN T f i n VO t-- OO OV o T—H CN c o T f i n vo C" OO ov o T—H CN c o T f i n vo r - OO ov o 1—H CN c o T f O o o o o o T— < l- H i—H i- H l- H l- H l- H CN CN CN CN CN CN CN CN CN CN CO c o c o CO c o U U OOO O 5 o u o o o o o U u u u o u U U o U U O U U U u O i n VO T f CN VO VO c o 1 1 c o 1 OO CN T f c o v o T f r-- T f CN O f VO vo r - OO t"- c o o f vo - T f t"- w VO W o o Ov t-- 1 1 T f i o o f o v w o vo CN o CN CN 1 i v o CN ov CN VO s I-H OO CN OV l- H ov w w OW Ov O f VO OO 1-H VO l- H CN Ov l- H OV WW CN OO l- H l- H OO r - i—i o VO 1-H r - OO CN o T f CN VO r-- VO CO o v t-- l- H OO o f o f OO CN CN CN o f CO r - OO o v m OV VO c o OO vo o OV OO Ov VO vo VO CO O f r -H v o CO o OO o v o c o l- H O CO ov c o o r - ov CO i- h r - CN l- H c o OO o OO v o o o f VO o f c o v o OO 1-H t - - CN VO r - o f r - v o CN vo r - r-" CN l- H c o VO r " OO T f o r - r - o v i— i VO r - vo o 1-H vo vo OO co co co c o CO c o CN c o OO m c o CO o i n o t ' - vo T f vo l- H CN o v o CO vo O CO o OO o f l- H o f OO 1-H 1-H l- H OV o f r - r - l- H T f f " T f r — l T f r - OV OV OO v o t-H 1-H l- H o f o v OV c o vo OO r - o OV r - o o v v o o v OV o f o v o T f f - r-~ CO T f o vo v o o T f r-- l- H vo vo o f o v OO OV r - v o OO o v v o o f O r - OO o OO VO O OO r - VO o OO v o o r - VO OO o v T f r - o v VO OO OV r-~ c o CN 1-H o v CN o f CO o f 1-H l- H CN i n ov c o VO T f o VO T f o 00 T f T f o f o o o o f o f vo o r - c o o f r - r - OO l- H c o v o c o (-" o l- H T f OV OO c o CO o v o v c o r - VO CO 00 o r-~ v o VO CN VO o v o f m o f o CN ov i- H OO i/O CN o v o o vo OO l- H i H CN v o T f CN VO o 00 o v t-H o f 1-H o v r - OV O r - OV c o i n o v r - vo r - ~ CN c o o Ov 1— 1 v o v o CN VO v o c o O o v o OO CN o v OV o f c o o r - c o c o o v l- H o OO ov c o c o CN v o VO 1— 1 v o c o VO l- H r - T f v o l - H VO i H CN 1-H v o r-- CN CN o v CN CN vo CN r - o v CN CN CN l- H vo OO o CN o o o o o v o CN o O l- H vo CN l- H CN i—H o CN O CO VO l- H o o CN O o *—< o o VO o o o o o v CN o o o O o r-; O o O o o O o CO o v o o o O o o c o i—I o i— 3 o o o o vo vd o CN cd cd cd cd cd cd cd cd cd cd cd vd CN cd cd cd cd cd o o o OO N o VO vo VO OO OO CN VO vo vo i i OO 1 r- OO vo i VO OO 1 N i vo N VO i i VO 1 1 i vo i OO WW 1 Wr- i 1 1 OO W 1 i 1 W i W i i 1 WW i H w i WW i W i T f W ICO i WWW 1 CO WWw N w m Ww w T f W T f vo W T f r- r- Wov W CO CN l- H W ICO in WVO CO vo c o i n ov l- H OO OO vo N r -H vo c o 1-H ov r-~ CN vo T f OO vo T f ICO l- H Ov CN o vo o CN c o vo N o T f CN OO l- H 1-H OV vo i- H CN r - i n OV VO W l- H N OO OO r - CN VO r- Ov •n m T f CN m vo c o c o OO CN T f c o vo T f IN T f CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN m vo r- OO OVo r -H CN c o T f in vo r- OO ov o l- H CN CO T f ov o H CN m T f in vo r- OO ov r-H c o c o CO CO c o T f T f T f T f T f T f T f T f T f T f m o O o o o i- H i- H i- H i- H r -H i- H r-H OOOO O o o u u O o O u u U QQQQ Q QQQ QQ5 Q QQQ T f T f VO CN OO TV T f TV O' TV OO 1 OO OO CN o> o VO T f CN T f T f CN TV T f T f CN O' i OO c o o - c o c o T f 1 vo W VO W OO co o - CN c o i i—H TV TV OO ov TV CN W o W vo T f vo T f 1-H CN CO i—i co vo tv OO W o W CN W O' W w O' CN w vo 1-H vo o TV O' 1-H O' 1-H W CN i—i CO r - co c o VO OO TV OO O' CN T f ov o c o c o O OO c o c o 1-H OO ov o TV 1-H 1-H 1-H o CO T f o 1-H CO i—i o OO c o o - o vo vo OO TV o c o CO o c o T f T f o o TV CN T f c o T f CO CN CN OO CN T f o~ T f CN vo CN CO r - o T f CN o vo ov ov vo vo c o c o Ov O ' VO o~ OO OO T f OO OO vo CN OO VO tv VO r - ov CN c o c o 1-H T f c o VO TV c o c o TV OV l- H i-H o - CO o T f CN O ' OO o - OO OV c o in o - o - CN tv TV TV 1-H Ov o T f CN OO o o OO O' TV c o CN 1-H vo TV OV 1" ( TV t-H c o ov T f CN T f ov T f co T f Ov O' o 0 0 o OV VO c o vo vo c o T f O- c o i i o ov T f CN co TV CO l- H ov OV ov o - OO o - CO vo 1—1 oo VO CO TV OO o OV 1—1 l- H ov CN CN Ov o VO CN CN T f CN o CN O' vo OO i—i o o ~ o ov m vo CO CN O' 1-H 1-H T f o - ov ov O' OV o - OO ov CN c o vo r - O l- H O TV 1—1 r-H o co CO co vo o - TV c o O- o T f c o T f o> ov OV o~ ov OO T f vo O' T f CN CN O ' TV o- r - CN CO c o T f OO T f CN oo vo CN TV OO ov OV o OO CN CN OO o vo O' TV TV CO r - TV o CN o VO 1-H ov tv T f VO T f co CN o TV o- Ov ov ov r -H 0 0 c o c o OO OV T f 1-H o O ' o~ VO CO OV OO ov T f T f OV tv o ov o o- OO OO 1-H c o CN T f o CO 1-H c o c o T < 1-H CO CN OO c o l - H c o VO o- CO r - c o OV o c o 1—1 CN 1-H CN TV 1-H OO CN i—i r-~ o- vo TV l- H 1-H TV OO VO 1-H 1-H CN 1-H o vo c o 1-H c o vo VO o- o tv O tv o o o OO CN O T f 1-H o o o o o o vo 1-H 1-H CN TV 1-H CN o o o 1-H T f 1-H o vq o vo o o o T f O o OO o CN o I—1 ’—I o o o-o o O 0 0 o CN o o o o TV o o ON o ON o o o T f o o OO o CN o TV TV o o oo o o o CO o CN C5 o o o TV o o o v o T f O' v o TV TV v o O' v o o v v o OO v o r - VO v o o v O' i 1 VO i OO 1 o 1 1 1 1 1 o v O' 1 vo ov O' 1 1 1 O' 1 1 i i i i 1 W w i W i w 1 w w w w w 1 1 w 1 1 1 w w w ffl 1 w w W W o - W WW o v TV W v o W T f w TV T f T f TV v o w w o - w H w TV OO v o OO w T f T f TV TV TV CN CN o vo v o v o CN O' TV CN TV TV CN v o 1-H o v c o VO TV O' T f TV CN TV CN o v O' OV oW o O TV T f H i—H O c o o v o c o T f T f c o o o T f VO 1-H TV o ov 00 1-H OO TV o v o v CO OO OO OO ov T f o OO OO TV OO c o T f O' c o c o o - TV c o TV OO OO OO TV O' 1-H Ov 1-H T f T f c o TV v o c o v o vo c o T f O' 1-H TV T f CN CN CN OO OO CN CN T f o o 1-H TV TV T f OO c o OO c o OO CN v o TV CN TV v o c o VO CN Ov TV O' OO o O' Ov ov O ' c o O' O ' CN OV 1-H TV TV O' CN O' c o o v OO VO T f v o T f OO T f TV 00 CN v o TV CN o o v o v o o v o OO O' vo CN 00 v o T f TV c o TV T f O' CN T f c o C c o T f O' TV ov T f ov O ' TV CN 1-H 1-H 1-H i - H ov o v CN 00 T f TV ov CN r -H o 1-H O ' CN TV T f T f C' T f o v T f OV TV c o c o o v o 1-H o c o c o o c o c o v o VO c o 00 CO T f OO OV OO T f TV v o T f o TV o o TV VO c o Ov Ov VO o TV v o o v o v v o c o c o CO ov Ov TV o v CN T f T f T f TV v o Ov O' O' OV O ' r-~ c o T f TV vo O c o CN o TV OO OO TV T f c o O ' O' v o c o o v c o T f o T f c o o CN c o T f O' T f VO c o CN H l- H o TV v o o TV T f T f TV 1-H CN O' o 1-H o o v OO T f T f T f c o VO v o v o c o T f c o O TV VO OV T f c o l - H OO O' o 1-H 1-H o o v c o OO CN T f o c o T f o o o TV T f OO o c~ OO O' o - c o c o vo o v o 1--1 OO TV TV o o TV o o Ov CN OV CN o O' o o o c o O ' OO O' r-' CO o~ oo T f TV OO c - o vo o 00 O' o v o v o - O' i- H 1-H o - O ' c o o o CN TV CN T f v o o v TV TV OO TV OO Ov TV O; 1—1 vq O o^ T f CN 1—1 1— ; CN vq O'; TV oo 1 O'; vq ON cq vq cq o v ON O; CN vd TV vd ov T f H 1—H vd cd vd cd ON 1— 3 T f T f i—3 i—3 CN OO vd T f cd cd y i cd 1—3 T f i—3 cd T f T f vo T f OO TV T f TV O ' TV OO 1 OO OO CN O' o vo T f CN T f T f CN TV T f T f CN O' OO co o - co co T f vo vo w OO CO O' w CN c o 1 1-H 1 TV TV OO ov TV CN w ow vo T f vo T f l- H CN co r -H c o vo TV OO TV o PQ CNw O 'w w O ' CN w vo i ■H 1-H vo o TV O' l- H O' 1-H w CN l- H co O' c o c o vo OO vo OO O ' CN T f OV o c o CO o OO c o co r-H OO o o TV 1-H 1-H 1-H o c o T f o 1-H CO l- H o OO CO 1-H o VO vo OO TV o CO co o CO T f T f o o TV CN T f CO T f c o CN CN OO CN T f O' T f CN vo CN 00 O ' o T f CN o VO ov ov VO vo c o co o O' VO O' OO OO T f OO OO vo CN OO vo TV vo O' ov CN O' CO 1 -H T f c o VO TV c o co TV ov 1-H 1-H O' co o T f CN O ' OO O' 00 ov CO TV O'O' O ' CN TV TV CN 1-H ov o T f CN OO o o OO O' TV co CN 1-H vo TV ov r-H TV 1-H co ov T f CN T f ov T f CO T f ov OO o 00 o ov vo co vo vo CO T f O' co 1-H o o T f CN CO TV co 1-H ov ov ov O' OO O' co VO 1-H ov vo CO TV OO o OV i- H 1-H OV CN CN O n o vo CN CN T f CN o CN O' vo OO 1-H o O' o ov co vo TV CN O' 1-H 1-H T f O' ov Ov O' ov O' OO o CN CO vo O' o o TV 1-H 1-H o c o CO co vo O' TV c o O' o T f co T f O' ov OV O' ov OO T f VO O' T f CN CN O ' TV O ' O ' CN co c o T f OO T f CN OO vo TV TV OO ov ov o OO CN CN OO o VO O' TV TV co O' TV o CN o vo 1-H ov TV T f vo T f c o CN o 1-H O' OV ov ov r-H OO co c o OO ov T f 1-H o o - O' vo co OV OO Ov T f T f OV TV o ov o O ' OO OO Ov co CN T f o CO 1-H co CO 1-H 1— 1 CO CN OO co 1-H co vo O' co O' co OV o co r -H CN 1-H CN TV 1 -H vo CN l- H O' O' vo TV 1-H 1-H TV OO vo 1-H 1-H CN i- H ov vo co 1-H c o vo vo o - o TV o TV o o o OO CN o T f 1 -H o o o o o o vo 1-H 1-H CN TV 1-H CN o o o 1-H T f 1-H o vq o vq o o o O'; o o OO o ON o 1— 1 1—1o o O; o o o OO o CN o o o o TV o cd ON o ON cd cd cd H cd cd OO cd o i cd TV TV cd cd OO c> cd cd cd cd ON cd cd cd cd TV cd CN CN CN CN CN CN CN hh CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN CN O CN c o T f TV vo O' OO OV o 1— 1 CN c o T f TV vo O' OO o v o 1— 1 CN CO T f TV VO O' OO OV o CN CN CN CN CN CN CN CN CN CN c o CO C O c o c o CO c o c o c o c o T f T f T f T f T f T f T f T f T f T f TV Q Q Q QQ Q QQQ Q Q Q QQ QQ QQQ Q Q QQ QQQQQQ Q Q o on NO on 7 ~| cn cn OO o o NO on NO o 1 ON ON i oo i NO on o o NO i i—i n r o o r—H o o nT nT 1—H i ON 1 oo i-H r-H H 1 i W i W i i n r nT NO w i i W nT 1 HQ HQ on HQ HQ i HQ i 1 CN W W NO W e-- W W NO 1 ON nT ON W W cn NO WWW W NO NO NO oo r - 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CN o cn ON cn N" r - 1—H o o e' o cn i—i cn CN r-~ ON o nf- t-' cn cn on o e' cn cn CN O (-- cn CN i—H cn o o o o o ON en r - r - i—i ON cn l-H i-H on ON i—i o ON o o en oo N" ^|- i—i i—H cn O CN N" ON i—i on 1—( cn i—i o o r - o t-~ on N- OO on cn NO c n t—- on ON n - on e-- o o o o O cn o CN CN on o N" on cn i—i cn o NO O NO CN o o r-~ NO n - o o NO 1— 1 CN on o cn cn o OO ON oo OO i—i cn N" r - i—i NO NO r - o o o o o CN N" on o o o NO CN 1—H CN n - o r-~ e~- o o ON NO IN o o CN O NO OO NO o OO on on cn CN N" O O) NO r-; cn OO o o n - o o p NO o o NO OO ON ON o N NO on o o on CN ON OO NO i—I cn N" CN N- on o o NO K CN n -’ o o CN OO * - 5 o i—< NO on NO on NO on NO CN e-~ i on I N" i NO on oo NO e-~ ON nT oo oo ON NO n r n r on on NO oo CN on W i t}" W i W I i Tf- NO i i i 1 nj- 1 1 1 1 cn cn i/n W w I 1 on W i CN W NO w e-- W W NO 1 ON n r W W W W NO w W w w CN CN NO oo r - W w cn oo W N- cn W CN N- e— NO CN o W cn oo i—i CN oo CN o n r i—i e ' oo e ' t '' i—I n r CN e ' cn n r on NO on cn on N" O i—i ON NO e-- CN o CN e-~ O on OO r - On oo CN cn NO NO OO CN on en NO CN oo OO t-' on '^1' O o o o o CN on e - cn i—i o o on on on on n r CN cn o ON ON 0 0 ON o o o n r NO o nT on N- CN i—i ON i—i o n f cn l—i n f CN on o o CN cn CN CN NO 1—1 cn on on 1—1 CN t'- i—i o CN nr cn O cn on N" OO o oo ON on e-- O OO n r cn on o on ON n r c n i—i o o 0 0 f ' ON CN oo OO o cn NO oo N" I-- ON NO on CN o n r on r-- oo i—i nT cn o on on CN o cn cn NO C ' cn NO e ' o CN oo N" ON i—i oo cn on i—i i—i NO e-- nT NO NO oo e ' e-~ NO oo on nT nT ON ON CN e ' NO NO on n r nT n r ON CN oo CN ON on ("- NO O o cn O CN ON e n on o oo n r NO OO e' e' O CN 00 cn o on > H on o NO on ON cn NO ON NO OO on on ON on cn n r NO oo o NO on CN en en NO o n r CN o cn ON cn cn i—i OO e' i—i cn i—i on CN i—i OO o nT n r cn on on o e-> cn nT nT NO NO ON t-- cn CN i—i cn ON o o o o en ON o o f - e-~ CN ON ON on ON ON o t ' o o NO o nT nT cn 1—1 on O CN nT ON i—i 1—1 cn CN oo e - ON NO i—i e-- i—i ON cn NO cn e ' i—i ON n r ON ON o o ON on r - o CN CN on o o on cn i—i cn oo o on ON NO CN cn r-~ NO on oo ON 1—1 CN n r r - c n cn i—i ON r—i oo OO r—i cn n r oo i—i NO N- C" CN OO N- CN o CN cn o NO on i—i CN n r o o CN o o O nr On oo CN O NO oo cn o ip p on CN ’—1 oo O ON O o e-- cn i-- oo O o o cn nT o o o oo e ' ON ON O e-- NO oo on cn CN CN NO o e-^ o o CN n f CN oo o e ' CN ON ON o o o 1-H en oo o i—< NO CN 1 CN ^ CN CN CN CN CN CN CN l-H 1— 1 CN ,—1 CN '—1 1-H CN CN 1 — 1 — 1 (M CN CN r~l i—* i—1 i-1 i—1 C-1 C-- C-- O - C-- C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 C-1 ^ _ l CN cn n r on NO e ' oo ON o I-H CN cn nr on NO C ' o o ON o i— i CN cn n r on NO C ' o o ON o i— i o o o o o o o o o r-H t—H 1-H i- H r -H i - H T— < i- H i- H i— H CN CN CN CN CN CN CN CN CN CN cn cn CQ CQ PQ m PQ PQ PP PP PP PQ PQ PP PQ PQ PQ PQ PQ PQ PQ PQ PQ PQ PP PQ PQ PQ PQ PQ PQ PQ PQ B32 ? 1 1.393141121676385E-4 1.3931411216763 85E-4 1.2342324886700936E-8 B33 ? 1 5.400328670792618E-5 5.400328670792618E-5 3.8745983926786E-9 B34 ? 1 1.4901418008717008E-4 1.4901418008717008E-4 3.3490403572085077E-10 B35 ? 1 1.7869153598278165E-4 1.7869153598278165E-4 6.0920638878745246E-9 PQ VO CN co oo r- o r- o N" CNN" in oo CNCNCNo oo oo VOvo PQ vo CN VO r- OV COin o oo N- r-~ t-" C"in N" vo oo o CN o oo oo in ov q p CN ov co o vo o o o o oN" COco vo oo N" CN o i-H 1—1co VOvo 1/0 "Cj- ov COvo PQ i 1 1 - o o' QP PQ PQ PQ COCOCO C-" o vo i—i O vo OV N- oo l-H r- O N" -N"r- ov 00 oo co o o O in i— r- vo CN r- O PQ r- o i—ir- ov ov i—i CN ■"Cf I—H in H n n n i o cq o H l- oo cn o OV Ov n - d oo - d oo oo vo ov Ov cn o cn cd o i-H -H i- n i o oo l-H m d oo m o cn .-Q n i d in d cn in O O VO CN vo r" in - r i U O VOV OV v o vOv Ov O CN n i VO n i o v cn o v - e vo cn cn vO vov o o v Ov Ov Ov o o cn C/Q < - d PQ i-H —H i— i-Q - d - d o CN - d 1—H - e - e m in d 1 d vo vo cn d d PQ PQ ov eQ d ov O H l- in - e PQ —H i i v o O CN - d v o O cn H l- -e'O-e' e O'- ' e O- CN oo CN oo o - d o vr- r Ov cn GO < ov PQ PQ H h rq cn CN vo - d n i oo i— in CN vo CN CN no cn o o oo d ov vvq ov ov oo 1 1— O o ov CN cn d in o v cn rq d 1— in W Q i i i 1 v o o vovovov o v o v o Ov v o vOv Ov o o en cn o v in cn o cn CN o cn CN m - r CN OV vo cn CN CN oCNCN vo PQ d m o O o oo CN GO < < i"- m 1— h o cn m - e in QC rQ CN rQ OV .—i in o PQVOPQ H i Q H i i en d o v n i o v oo cn o n i o v o cn o vo ov vo Ov d VO d CN OG CO GO GO U QPQ PQ n i i-Q in CN ov Ov d" m - r H l- cn in in - r l-H oo Ocn VO o o cn PQ in >—< n i H i- oo oo v o o Ov oo d o OO d - d CN cn - d CN CN cn ' ' C'- C'- C'- o v OO Ov n i o - d o cn vo ov d- o - d PQ h d o v m NV r^ VO CN d o oo - r - r - r PQ d U ov PQ PQ - d — -Hl H l- H l- 1—H - r d - d r^ - e d- - r in - e < Q i 1 CN oo ov CN vo - d d o ov oo o v cn CN Ov v o OO CN oo VO OO o v NCN CN cn d v CNo CN d - r n i VO CN in CN oo in ncn cn - e PQ rQ Ovo v VO 1 O - r in PQ GO U ov A eQ m - r - r < —H i i cn OV o o OO oo CN o o o n i OO CN - r o o CN vo o Oo VO CN PQ in in n i -ct- N- m i n m i n r - in VO i n o o v o vo o N i n OV o o N" vo vo N" VO i w i n i n v o W i i cn cn i W ■ 1 W i W v o i i w o i i i i W N- W W v o o i 1 vo WW ov N" i n CN w m W W v o W r - i W w N- o W W W H CN r - N" m o v i n W w o 00 cn t-H OVi N o v vo CN vo N CN cn W o r - v o o cn r^ N - r"- VO OO o v cn o N- N" N ov oo Ov cn W i n N" CN cn N N c n t-H o o v o o VO CN o vo o i n ov Ov v o o o IN o r — I i n OO T H ov N OV cn i n ov OV o o N CN N" i n N- v o N" OO VO 00 CN o CN i n v o OV i n o o CN t-H v o OO v o OO N in t-H oo N cn N OV t-H OO o i n N" cn N" v o O N" i n r - CN cn i n cn i n OV in t-H v o N t-H i n N" N- CN v o CN CN CN N" r-~ t-H O m o o i n i n t-H o CN i n OV m OV v o o CN CN i n OV N" N VO cn O N" VO o VO o CN CN v o N- CN vo r - OV vo o O cn t-H N N" N ' CN t-H t— o o v VO o v N i n OO o v m VO VO N- 00 N" m OO vo vo r - cn CN r-" o v o Ov O cn N" N" ov cn m t-H VO O o VO cn N" c n i n t-H ----- 1 cn i n t-H cn t-H t-H oo v o N- o o t-H cn OV cn t-H N" N CN N o N CN N" t-H t-H o v N" o o t-H m cn in in t-H t-H r - oo v o r - t-H v o N" N OV N N- C— OO CN o v v o t-H N N CN Ov v o t-H o o t-H o v o t-H OO t-H N" m cn i n OO N N" N N- CN OO OO N" i n N vo N" N" m OV O Ov v o t-H o o t " - o vo N" vo t-H o v o cn cn O cn CN ov o o N VO t-H T—H o o N" Ov OO o o v Ov t-H m o t-H cn o cn r - cn o o CN r - o o cn cn OV CN cn cn T-H cn N- VO CN CN v o cn Ov r - m r - m T-H m m t-H r-~ CN N" vo t-H O m o o N in m cn m o o cn O O "it o v cn O cn t-H v o ----- 1 t-H o o T-H o cn t-H o cn N" i n o v o N"N; m CN o o CN O N i n o o o rq N; t q cn t q o cn CN o CN OO o o o T—J CN o vd Ov t— 3vd vd o cd cn cd cn cn t-H* N T—3c n N- o o CN t- 3 CN o T-H* t-H OV N" CN o' vd N" in in in in r - N- in VO in i o o i v o v o o r - N- i in o v o o i N VO VO VO i w m in v o W i 1 cn cn i W i i W 1 WVO i i w ov i 1 1 ■ WN- WW v o o i i v o WWov N" in CN w m WWv o WIN i w w N" o w Ww WCN N in Ov in WWo o o cn Ho v i r- OV vo CN v o r- CN cn Wo v N VO o N cn N N" N v o o o o v cn o N*N" r- o v o o o v cn Win N" CN cn r- r- c n t—H o o v o O VO CN COVO CO in o v ov v o o o r- o t-H m o o t-H OV r- o v cn in Ov OV o o r- CN N" in N- v o N" oo v o oo CN o CN in v o o v m oo CN t-H v o OO v o oo r- in t-H OO r- c n ov t-H OO o in cn N~ v o o N" in r- CN cn in cn m OV m HVO r- t-H in N- N- CN v o CN CN CN N" r- N t-H O m t-H oo m m t-H o CN m Ov m o v VO o CN CN m o v N" r- vo cn o N" VO O VO o CN CN VO N" CN VO N OV VO o O cn t-H r" N" N- CN t-H r-~o Ov v o OV r - in o o o v i n N - VO v o N" OO N" in o o VO VO r - cn CN N o v o o v O cn N" N" o v cn in r -H VO o o VO cn N- c n in t-H t-H cn m t-H cn t-H t-H oo v o N" OO t—H cn o v c n t-H N" t-H CN r-" o r - CN N" t-H t-H o v o o t-H in cn m m t-H t-H C"~ oo VO r- t-H v o N"r- OV r- N- r- OO CN OV v o r-H r- r-~ CN o v v o t-H oo N t-H o v o r -H 00 t-H N- in cn m OO r-- N" r- N" CN oo 00 N" m r^ v o N" in OV o r- OV v o t-H o o r- o v o N" VO t-H o v o cn cn O cn CN o v O o VO t-H t-H OO N" Ov oo o o v Ov t-H in o t-H cn o cn NN cn oo CN t— oo cn c n o v CN cn cn t-H c n N" vo CN CN v o cn OV r- in N cn t-H m in T-H r- CN N" v o t-H o in o o r- in m cn in o o cn o O N- OV cn o c n t-H VO t-H t-H o o t-H NO cn t-H o cn N" in o v o N" in CN o o CN o tq in cq o o tq N; tq t-H cn rq o cn CN O CN OO o o o T—J CN cd vd OV T— I vo vd cd cd cn cd cn cn t— 3 T-H* c n N" o o CN t-H CN c> r-i t-H o v N" CN cd vd (>• n- (>• o m NO CN N" i n i n N NO N" ON cn N" i n t-H N" NO CN i n CN O i H CN N" NO OO r - O w W i n NO i w ON cn o o ON W NO N" NOi W w ON W i ON NO w N" i cn i ON oo oo CN i OO N- W NO O NO NO t-Hoo NO r - cn W oo m N" cn W N ON CN o o w W ON cn NO NO W t-Hi—Hcn in O ON N- r-~ N- t-HN" NO o 00 cn t-HO cn CN OO ON N~ t-HON ON cn ON N - NO o N- 00 N i n N- CN cn NO NO NO OO ON ON oo ON o cn ON O n t-H o NO OO o ON o o t-H oo i n t-HI-H m N- OO ON OO OO o CN i n i n cn I"- NO in CN cn o o N ON NO l-Ho ON CN NO ON o CN CN O o i n cn N CN CN in NO 1—H t-HNO cn ON CN m i n NO OO CN i n NO CN r - o i n N" i n N" t-HN t-Hi n t—HNO NO t-HON NO o r-~ CN ON CN cn CN NO ON CN N" o o l-Hcn cn ON ON I ■ ON N ON CN CN N- ON N" N" ON O OO o O n cn cn ON CN "Cf o NO t-Hr - OO ON t-H OO o i n N" N- ON in O in ON N" N" N" cn r~- CN i n CN NO CN CN cn t-HON OO CN N" 00 OO cn NO m o O NO m m N- t-Hi n NO NO oo f" t-H NO N" ON N" ON o o CN cn CN NO i n r - ON oo cn cn N cn OO t-HI-Hi n N ON O n CN o o i n NO ON NO t-HO cn i n t-HNO t-HO OO o o r-HCN r - o ON m IN OO N- o cn o CN OO o o N" cn cn N" cn i n o t-HNO ON o cn OO 00 cn i n t-- CN N CN ON N cn CN CN NO IN i n NO NO NO CN r f o N" 00 CN oo N" o cn I-HCN NO cn NO o o r - NO N O cn cn ON N t-Hl-Hcn NO cn cn t-H CN oo O CN O CN oo in t N - O i n ON NO CN t-Ht-H CN cn r-Hcn N - CN NO o i n cn o o o o l-Hm t—i t-HN" CN m CN IN o t-HCN OO NO NO t-HOO t-H O NO IN r - cn t-H00 CN o O o o o ON o o O m NO cn O oo cn O t 1H m cn ON o NO o O OO IN NO o o CN cn o O o o o cn o o O cn NO o t-Hcn OO r - o NO o CN o d r-3 I—i NO d d d r'Hd d o o o t-H* o o o ON t—Hcn o CN ON o O cn o O n o NO d o i n NO CN i n in NO r" N" ON cn i n r-HN" N - N" t—HNO CN in CN NO t-HCN NO N" NO oo r~~ o Wi n N - NO i w ON cn O O ON WNO N" NO i WWOW I o NO CN N" i cn i ON o o WCN i OO N" WNO O N- NO NO t-Ho o NO r - cn Woo NO N" cn Wr - o cn oo w r - WON cn CN NO Wl-Ht-Hcn i n O ON r - r - t"- t-HN- NO o 00 cn O NO cn CN oo o l-Ht-HON ON cn ON N" OO o N" oo r - m N" CN cn NO NO NO o o ON ON oo ON o o o o * ■ 4 n - o NO oo o ON o o t-H OO ON i n t—i i-HN" m OO ON OO OO o CN i n m cn f" NO N" CN cn oo o I-Ht-Ho ON N" CN NO N" o CN CN o o i n cn r - CN CN i n NO r-H l-HNO cn in o CN in i n NO o CN m NO CN r - O CN n - i n N - t-H t-Hi n t-HNO NO t-HON NO o r^ CN ON o cn CN NO o CN i n N" o o cn cn ON ON ON IN ON CN CN r f ON N" N" ON O OO o r- ON cn in o CN N" o NO NO r - r - o o ON t-H OO OO i n N" N" ON i n O i n ON N" N" cn r-~ CN m CN NO CN CN cn r-Ho OO 00 N' o o OO cn NO N" o O NO i n i n N" r-Hm NO NO OO t-HN" NO O n CN O NO o CN cn o NO i n r - ON oo cn N" r - cn OO "vf t-Ht-Hi n r - ON ON CN oo m NO ON NO t-HNO cn in l-HNO t-HOO OO o o t-HCN r - o O i n r^- OO N" o cn o CN o o OO cn cn CN o - C - C^t NO r - OO ON o CN cn N" i n NO r - oo ON o CN cn N" m NO N oo ON o CN cn N" m NO o o O o t-HT-H t-HI-Ht-Hr-H1—1t-Ht-Ht-HCN CN CN CN CN CN CN CN CN CN cn cn cn cn cn cn cn o o o o o o o o o o o o o o o O OO o o O o o o o o o o O o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o O o o < < < < < < < < < < < < < < < < < c < < < < < < < C < < < < < U U (J o u u u u u U u U U U U U U U U U U U u u u U U U U U U 00 00 00 00 00 00 00 oo C/D oo C/D CO C/D CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO SCA0037 ? 1 5.76870037176018 IE-4 5.768700371760181E-4 8.043392907125937E-9 SCA0038 ? 1 0.018023138626909962 0.018023138626909962 1.4407080008468922E-7 SCA0039 ? 1 5.1917819759592E-4 5.1917819759592E-4 3.1558687186233033E-9 SCA0040 ? 1 0.0012851788169997364 0.0012851788169997364 6.024840281008122E-9 C- <• O' O' O' O' O' O' O' O' O' - o - o ' O ' O ' O ' O ' O ' O ' O ' O ' O ' O ' O ' O ' O ' O ' O ' O ' O ' O <>• - C ' O CN HMm^in\0 OO o O Ov cn CN o oo nc Oo VO cn o cn vo ov o oo o o cn i o oo vo vo N- o CN pq VO CN vvo OO l-H ov -v 'o O' vo N- o o oo o cn vvo vo Ov o vo cn VO o -vo N- CN h PQ Ov in 1—1 ov ov OV vo CN in ov t N- o 'O' O' PQ — —H 1 - i CN vo O oo-o - o vo o O' O N" OV N" cn cn CN 1 PQ ov N" o CN ov nN’ cn cn cn o Ov "N" N" m O' oVO vo PQ 'vo O' ov m OV N- ov CN o in ov m T-H ov pq -Q i 1 CN 00 vo ov o oo o o oo VO in O' nc O- cn cn vo N" o cn o O; o o nc -N" O- o cn oo cn OV OO' VO vo CN N" vo OV oo O' o cn oo o oo o OO oo I ov o O' o O' O' oo PQ —1 1 oo o ov o O' N" cn N" O' O' oo CN h 0 pq oo cn N" ovo oo o oo N" o vd 'CN O' O' nO' in PQ CN pq N- O CN N" omoo m oo o CN CN I o OV CN VO o OO CN W —1 Q - 1 O CN Ov o O in CN CN O' i-H i-H i-H VO PQ VO Ov O N" I-H l-H vo OV VO m o NCN CN o vo i o oOI oo CN oO' oo nO vov ov O' cn r-H vq -OO noO' o cn O' O N- in ov in in w oo OV O' N" m i i 1 vV VO VO ov in CN in N" oo oo cn ov vo OO i-H cn N" o CN cn N- -CN N- O' cn i—i PQ N" OV in in oo O' cn Oo OO Vov OV OO OO ov OO i-H oo N" nCN cn o cn pq CN m N" - - l-H i-H l-H nov in vo T—< PQ t —H i 1 i-H h00(j\O cn O; vo o o OO i-H ov N" noN nN- cn N" o o N" cn vo din cd in o l-H CN N" i-H o- i-H oo l-H in c> N" cn OO ov O' i-H in vo l-H m vq m oo vo O' CN oo oo vo PQ i oo vo O cn O' r-H oo VO in OO CN o ''cl- O' O' i-H pq - o vcn ov 'N Nocn o CN N* O' cn O' o l-H O' vo o in l-H l-H PQ N" OO CD -CN N- cn CN ov o ov cn O' CN m o- W i o ov in N" CN oo oo ov Oo ov (N ov OO l-H nO' O' cn cn o O o O cn cn h PQ N" ov oo O' ov vo CN l-H oo N" oo o cn pq Nv N; vq CN in "VO N" - i-H l-H 'CNin O' PQ oo O' vo i-H Q i 1 VO i-H cn o O o o o oo l-H N" ni Vmov CN m OV in in vo O' vo vo CD in O i—i N- l-H oo vo l-H t in CD CNN" O' vo vo cn ocn oo CN vo ov oin oo vmov m Ov m m 'CNl-H O' m l-H in nN" in oo O' Ov OO vc -N" N- cn ov N" vo PQ —H 1 oo voo oo ov oo no-in - o cn o (N vo CN CN CD l-H O' in oo O' in CN N- Ovo VO DC CD CD CD oo m l-H O' oo oo ov ooo oo VO l-H m oVOcn vo t 'ov O' PQ O' N" —H vo CN CN CD CN l-H O' l-H l-H CN in VO l-H CN nVO cn CN l-H p l-H vo O' l-H i-H vo nvo cn i o CN 00 oo nCN cn l-H 00 OO i-H i-H N- N- N- W W OO O' oO ocn vo O- vo H lvo Ol Oo oo oo OO l-H O- oo VO o o CD vo o N" o in vo vo o CN o O' oo O' OO OV oo oo oin oo vo i o CN O' O' 1—1 - o N- o oo N- N" CN CN nin O' cn CN N- oov oo O; m N" in oo VO CN N" ov H in vo i—i N" l-H OO l-H* in vo CN CN i o vo m i-H O' in oo W in vq CN - i-H l-H oO oo m O- vo -vo N- oc vo cn vo VO oc O' cn vo l-H OV ov l-H W i i i o OO VO oi o o O in vo O' oo OI O' o l-H o in oo W oo OV ov oo ov OO l-H in VO l-H OO i-H oo oo o OO o- OV cn i o ov CN W vq i-H O' N" in W o N" in in 1 i 00 i-H cn l-H "O' N" cn i-H o l-H cn m i-H O' N" W N- m cn oo cn -N" N- oo O N" m l-H 'vo O' oo i—i i—i PQ t o- in 'O in m OO O' Ov CN vo VO ov ov oov l-H oo o o O' W H i i CN "O O' O' N" OO VO ni in m in oo cn CD o l-H in VOo in N" oo 'O' O' o VO l-H N’ N" o o i-H m in cn O' ■"sf no ^0 no no no 1 tn O' NO no 1 NO oo NO C' NO NO C' NO NO NO NO NO NO NO NO i i O' W o W OO o OO NO O ' CO w OO 1 OO oo o f o o oo NO oo oo o o o o 00 o o w w WW o no CN no ON O CN no o no CN O' no o w o o ON o o no o o o o o o no CN l-H l-H o|- o\ OO O n c o NO OO ON NO oO no c o ON NO no NO NO c o NO NO Of- NO NO NO NO NO NO CN c o v o o o o ON O ' ON 0^ OO O' ON OO CN ON ON ON OO ON OO o o C ' o o o o CN o o o o o o o o o o oo CN NO l-H o o o o CO r^0 O' OO CN ^0 l-H c o C' ^t" NO Of- o o o CN OO CN o o O ' no ON O o o 0^ i-H r-' C ' C ' C' no C'C' C' C' C' C' i-H o\ c o i-H ON NO ON CN t—H NO ON l-H O OO ON ON l-H l-H l-H 1—1CN l-H i—H o l-H i-H l-H i-H i-H l-H no C' CN CN CN OO Of- OO o o OO OO NO O ' o ^0 OO ON OO o o OO o o o o NO oo oo o o o o oo o o CN CN o o ON o o ON O' ON OO O' O' CN ^0 o o C ' ON C ' r-' ON C' C'C' C' C'C'C'C' r-' no o c o O ' l-H CO o c o CO o o O CO o o 1—1NO o c o o o O o o oo c o oo oo l-H oo o o o o oo oo o o o Of- o o c o O ' c o CN c o ON no CN c o no no no ^0 c o no NO no no ON no no no no no no no no no NO c o CN o i-H ON O' ON o o O' ON o no ^0 ^0 ON O r f o O o o o no o o o o o o NO CN o o O' oo o O' o O' O'O'O O' l-H CN NO o C' no C' o- C' C'C' l-H C' I'- C' C' C' l-H NO o f c o l-H NO no NO c o O' no NO O ' c o o no NO c~ r f c^- C' c o 1^ C ' c o C ' C' C'C' C'C' o NO CN o o c o o l-H o no CN i-H o CN ON o o NO o CN no CN CN no CN CN ON CN CN CN CN CN CN ON rH o c o l-H ON o ON o o o ON o CN l-H o ON o CN o o o o o CN o o o o o o c o c o c o CN o o o o o o f o O o o ^0 o o o o o o o o o o o o oo o no CO oi NO o 1—i o i—H o o o i—! o o o o 1—I o o o o o o o o o o o o o CN o f no o f O f no o f no no no C' NO no 1 NO o f o o NO t '' NO NO C' NO NO o f NO NO NO NO NO NO i 1 1 O' w o w O f o o o o o NO C' c o w OO 1 OO OO o f o o OO NO o o OO OO o o OO oo W W w w o no CN no o o CN no o no CN C' no o W o O ON o o no o O o o o o no CN l- H l- H On o o o CO NO o o ON NO o f no c o ON NO no NO NO c o NO NO o f NO NO NO NO NO NO CN c o NO o oo ON O' o C ' o o f ' ON o o CN ON ON ON OO ON OO OO C' o o OO CN oo o o OO o o oo OO CN NO l- H o o o o o f c o o f O f O f O f C' o o CN O f o f l- H o f O f c o O f o f C' Of of Of of of of o f NO o o o CN o o O f f ' CN o o I-' no ON o o o r-' l- H C-' C' o f C' C' no C ' C ' C ' C' t'- C ' O f l- H ON c o i- H O n NO o CN l- H NO ON l- H o o o ON ON i-H l-H i-H i-H CN i- H i- H o i—H l- H i—H l- H i—i l- H no C' CN CN CN o o o o o o oo o f o o NO C' o O f OO ON o o oo OO oo OO NO o o OO OO o o o o OO CN C ' CN l- H o f o o o 00 On C' ON o o f ' C' CN O f o o f ' ON r-' f ' ON C' f-' C' I'' f " C ' C' C' no o c o l- H c o o c o CO o o o cn o o l - H NO o c o o o o o o o o c o o o o o i—H o o o o 0 0 o o o o oo O o f oo c o O ' c o CN CO ON no CN c o no no no o f c o no NO no no ON no no no no no no no no no NO c o CN o i- H ON O' o o o f ' ON o no o f O f O n o O f o o O o o no o o o o o O NO CN oo C' o o o O' o f ' C ' C' o C' l - H CN NO o I-' no C' f ' C ' o C ' i- H C ' f ' f ' f ' C' f ' l- H NO c o i- H NO no NO c o C' no NO f ' CO o no NO C' o f C' C' CO C' C' CO C' C' r-' C' C'C' o NO CN o o c o o l- H o no CN l- H o CN ON o o NO o CN no CN CN no CN CN ON CN CN CN CN CN CN ON l- H o CO l- H o o o o o o ON o CN l- H o ON o CN o o o o o CN o o o o o o CO c o c o ON o o o f o o o o f o o o o o f o o o o o o o o O o o o o o o no c o CN NO o H o i- H o o o i— ! o o o o o o o o o o o o o o o o o <—<* CN o - o - o - O'- O'- o * o * o * o - o - O'* O n o CN CO O f no NO C' oo o o CN CO O f no NO c - oo o o CN CO o f no NO c - CN CN CN CN CN CN CN CN CN CN c o CO CO c o c o c o c o c o CO c o o f o f o f O f o f o f o f 5 D D D P 5 PD P3 p PD D PD P PD PD PDP3 PD p 5 p3 p P3 D HHH HH H H H HH H H H H H H H HHHHHH HH HHHH TUI49 ? 1 9.462599913529373E-5 9.462599913529373E-5 1.9867779845491828E-10 TUI50 ? 1 E366514991858625E-5 1.366514991858625E-5 2.621661466561996E-9 WCA01 ? 1 0.029318220057162905 0.029318220057162905 1.9157548354229868E-7 WCA02 ? 1 2.638898308729874E-4 2.638898308729874E-4 2.9020430075979364E-10 U o o o cn - o (>• o o o CN o CN o CN Ooinm n i o OO NO n c CN CN & < - o o c o " N o n o n n c NO o o o o o o O NC CN CN CN o c o c o OO o " N o n OOoinm n i o O NO OO o CN in N- N" in in in m i in m N" in in in i ne vo in m in vo i ov OV o i o o PQ o o OV i PQ ov i i PQ oo in ov PQ ov o vo Ov ov m PQPQ PQ in PQ PQ PQ PQ PQ vo CN in CN vo CN CN N" CN CN in cn cn t-H OO in r - ov vo CN e ' ov o CN VO cn vo vo f" vo VO CN oo oo OO in CN cn o c n VO e n m e-- l-H l-H CN 1—Hi-H 'ce i-H l-H l-H CN CN oo VO y < CN CN O CN e - CN i-H r - ov e - e-~ CN e' e - i-H r— r-~ r - cn t—H e - in OV vo r" e - OO t-H in oo in m Ov en m t-H o o t-H vo r* i oo e ' OO CN oo oo c n o o N- o o m o o o vo vo vo e - o r - en N- OO e ' t-H c n m o e - o o CN o o in N" N - cn oo in m l-H e-~ oo en e - i-H VO CN m CN CN oo CN CN VO o o o l-H VO m in m ov m vo o '3 - CN oo CN CN Ov CN CN "3- CN CN i—i CN "3- vo cn oo l-H vo OV in N" OO vo OO OO OO OO N" CN CN VO ov N" VO oo vo o vo o cn N" i-H c n l-H i-H m i-H i-H N" OO i-H m N- oo ov cn ov oo ov oo in cn o c n c n i-H cn cn m OV OV OO e-- in CN N" o CN CN cn vo e'- ov c n ov o ov ov r-- cn cn vo ov e - ov cn cn vo OV l-H in CN CN o CN CN c n CN CN CN o o r— i-H CN in t-H o m c n o o O ov o O vq o O o cn cn r— ov o cn cn ov in c n CN d d d Ov d O N -’ d d d Ov Ov vd ^Q cd ov i-Q ov CN Ov t-Q N- i n N" i n «n i n i n i i n i n i n i n i n i N" v o i n i n m VO i O n o v oi o o PQ o o OV i i PQ OV i i PQ o o i n o v PQ o v ov v o OV o v m PQ PQ PQ N - n PQ PQ PQ PQ PQ v o CN m CN v o CN CN N - CN CN i n cn cn t-H oo i n e ' ov v o CN e^ OV O cn v o cn VO VO e-' vo VO CN o o 00 OO i n CN cn o cn v o cn i n e - i- H i—i CN i- H t -H ne i- H i- H l- H CN CN o o v o l- H CN N- CN o CN e" CN t-H e- OV e- e ' CN e' e-' l - H r-' e ' cn i- H r'- in o v VO C" r" o o t-H i n o o m i n O n i n i n l- H o o l- H v o i—H o o e ' o o CN OO o o cn o o N- o o i n o o o v o VO vo e ' o e ' cn n e OO e ' i- H cn i n o e ' o o CN o o i n N" cn o o i n i n l- H e' o o i n e ' l- H VO CN en CN CN o o CN CN v o o O o i- H v o i n m m OV i n VO o CN o o CN CN o v CN CN CN CN i- H CN N- v o c n o o i- H v o o v i n ^e OO v o OO OO o o OO CN CN VO ov VO o o v o o VO o c n N" t-H cn i- H i- H i n 1—1 l - H OO i- H i n '3 - o o OV cn o v OO o v o o i n cn o cn cn i- H cn cn m OV o v OO r-' in CN "sf o CN CN cn VO e- OV cn o v OV e ' o v o v e ' cn cn vo OV e ' o v cn cn v o o v l- H i n CN CN o CN CN cn CN CN CN o o e'- l- H CN i n l- H o N- i n cn o o O o v o O vq O O o cn cn f" Ov o cn cn o v i n cn CN c d c d o’ Ov d d n f - c d < N »• o- e' n - e' C'- C'- o- C'- C'- C'- C'- e' C'- e' C'- C'- C'- o - C'- o CN e n ^ e e n vo e' OO ov o CN e n N" e n vo C' oo VITA Qian Zhang Bom in Fushun, Liaoning Province, China, on November 11st, 1975. Received a Bachelor of Science degree in Marine Biology from the School of Oceanography and Environmental Science at Xiamen University, China. Entered the master’s program the College of William and Mary, School of Marine Science, in 2000.