Fisheries Research 175 (2016) 1–9

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Fisheries Research

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Population genetics of the jumbo Dosidicus gigas (Cephalopoda:

Ommastrephidae) in the northern Humboldt Current system based on

mitochondrial and microsatellite DNA markers

a a b c

Gustavo Sanchez , Satoshi Tomano , Carmen Yamashiro , Ricardo Fujita ,

d e a,∗

Toshie Wakabayashi , Mitsuo Sakai , Tetsuya Umino

a

Graduate School of Biosphere Science, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8528, Japan

b

Unidad de Investigación en Invertebrados Marinos, Instituto del Mar del Perú, Esquina Gamarra y General Valle s/n, Chucuito, Callao, Peru

c

Centro de Genética y Biología Molecular, Facultad de Medicina Humana de la Universidad de San Martín de Porres, Lima, Peru

d

Department of Fisheries Science and Technology, National Fisheries University, Shimonoseki, Yamaguchi 759-6595, Japan

e

Tohoku National Fisheries Research Institute, Hachinohe, Aomori 031-0841, Japan

a r t i c l e i n f o a b s t r a c t

Article history: Jumbo squid, Dosidicus gigas, is commercially important in the Eastern Pacific Ocean, principally

Received 15 June 2015

in the Northern Humboldt Current System where is notably abundant. In this area, jumbo squid display

Received in revised form 24 October 2015

difference in density at geographical level, in size of mature individuals and inter-annual demographic

Accepted 4 November 2015

fluctuation. Thereby, a population genetics study of jumbo squid in this location is needed especially for

Available online 21 November 2015

fisheries management. This study evaluated the population genetic of this squid (n = 120) based on novel

microsatellite loci and 675 bp of the mtDNA ND2 divided into two groups according to the Geographical

Keywords:

density and Size at maturity. Our results at nuclear loci showed an overall low genetic diversity and no

Population genetics

signatures of genetic differentiation of any group. At mtDNA loci level, low but significant genetic differ-

Jumbo squid

Microsatellite entiation were detected between Small (n = 33) and Large (n = 39) populations. The low genetic diversity

mtDNA ND2 is more likely explained by a historical demographic expansion whereas the contradictory results of

Northern Humboldt Current system population structure may be due to the low number of microsatellite loci in HWE, different maternal

history of this species or the different influence of genetic drift on mitochondrial and nuclear genes. Fur-

thermore, demographic history analysis suggested that jumbo squid population went through a period

of pure demographic expansion over the last 50,000 years ago. This study provides results of combined

nuclear and mtDNA molecular markers that was never reported before and may represent a valuable

information for the monitoring of the population genetic of this species.

© 2015 Elsevier B.V. All rights reserved.

◦

1. Introduction 2001). In addition, a recent extension to 60 N during unusual warm

surface waters in 2004 has been reported (Cosgrove, 2005; Wing,

The ommastrephid squid Dosidicus gigas (d’Orbigny, 1835) also 2006). Sub-populations of this species throughout its geographical

known as the jumbo or is one of the largest and distribution have been previously identified based on the mature

most abundant nektonic squid in the epipelagic zone of the world’s individual sizes determined as dorsal length (Nigmatullin

oceans (Roper et al., 1984). Jumbo squid is endemic to the East- et al., 2001). Small individual-size population is found predomi-

ern Pacific Ocean and its distribution commonly stretches from nantly in equatorial waters, the Medium individual-size population

◦ ◦ ◦ ◦

30 N to 25 S and occasionally from 40 N to 47 S (Nigmatullin et al., along the species distribution, and the Large individual-size popula-

tion in the northern and southern peripheries of the total range. This

size variations is explained by two different hypotheses; the first

suggests the presence of genetically distinct populations (Nesis,

∗

Corresponding author. Fax: +81 824 24 7944. 1983), whereas the second and more plausible suggests the pres-

E-mail addresses: [email protected]

ence of these populations as a response to environmental variation

(G. Sanchez), [email protected] (S. Tomano),

and food availability (Keyl et al., 2008; Sandoval-Castellanos et al.,

[email protected] (C. Yamashiro), [email protected]

2009; Staaf et al., 2010; Tafur et al., 2010).

(R. Fujita), twakaba@fish-u.ac.jp (T. Wakabayashi), [email protected] (M. Sakai), [email protected] (T. Umino).

http://dx.doi.org/10.1016/j.fishres.2015.11.005

0165-7836/© 2015 Elsevier B.V. All rights reserved.

2 G. Sanchez et al. / Fisheries Research 175 (2016) 1–9

Landing of jumbo squid occurs mainly within the exclusive catch density at geographical level and size of mature individuals

economic zones (EEZs) of Peru, Chile, and Mexico with a com- (DML). Additionally, an evaluation of jumbo squid in an extensive

bined annual production of approximately 0.66–0.75 million tons area of the Humboldt Current System was analyzed with sequences

between the years 2008 and 2012 (FAO, 2014). Particularly, the from the Chilean waters.

marine ecosystem off Peru, i.e., the northern Humboldt Current

System (HCS), is one of the most productive areas with remark-

2. Materials and methods

able fisheries production compared to currents of the Pacific and

Atlantic Oceans (Bakun and Weeks, 2008). Here, jumbo squid is

2.1. Sample collection and DNA extraction

highly abundant and supports one of the world’s most impor-

tant invertebrate fisheries (Roper et al., 1984; Taipe et al., 2001;

A total of 120 individuals of jumbo squid were collected in

Yamashiro et al, 1998). During 2012, overall global production of ◦

Peruvian waters at 4–16 S by the research vessel R/V Kaiyo Maru

jumbo squid in Peru was estimated at >0.49 million tons, which

from December 16th 2011 to January 19th 2012 (Fig. 1). The dorsal

represents more than 50% of its global production in all of the fish-

mantle length (DML) of each individual was measured and histolog-

eries areas within the EEZ and international offshore waters(FAO,

ical techniques were performed to determine the maturity stage.

2014). The main fishing grounds for this squid in the Peruvian

◦ Immediately after measure, approximately 2 cm of muscular tissue

EEZ are situated between 2 and 10 S, whereas fishing in interna-

◦ from arm was isolated from each individual and stored in 99.5%

tional waters off Peru are situated between 3 and 18 S (Waluda

ethanol for molecular analysis. Genomic DNA was extracted from

and Rodhouse, 2005). The international fleet mainly consists of

a small piece of tissue using TNES-urea buffer (Asahida et al., 1996)

vessels with Asian flag (Korea, China, and Japan), which landed

followed by the standard phenol-chloroform isolation.

0.28 million tons combined in the Pacific South East in 2012

The analysis was performed on the basis of two different groups,

(FAO, 2014). However, production of this species may be sub-

herein named as Geographical density (catch density at geographi-

jected to high inter-annual variability. In fact, high variability in

cal level) and Size at maturity group. For the first group, individuals

catch density of jumbo squid was reported during 1991–1999 at

were pooled according to the geographical origin of the sam-

geographical level along Peruvian coast, with high concentrations ◦ ◦

◦  ◦ ples and named as North (4–10 S) and Central–South (11–16 S)

from 3 24 –9 S to low-medium densities observed in the south

populations. For the second group, individuals were pooled into

(Taipe et al., 2001). Additionally, year to year fluctuations in catches

Small, Medium, and Large population according to the DML at

occurred in Peruvian waters (Rodhouse, 2001; Waluda et al., 2006)

maturity data following Nigmatullin et al. (2001) with a slight

with a remarkable high abundance after a strong El Nino˜ event in

modification to exclude overlapping between populations. Consid-

1997–1998. Therefore, this fluctuation is possibly influenced by cli-

ering males and females, the modification was as follows: Small

matic variations such as the variable El Nino˜ Southern Oscillation

population (13–26 cm and 14–34 cm, respectively), medium popu-

(ENSO) events in the upwelling system off Peru (Rodhouse, 2001)

lation (27–42 cm and 35–60 cm, respectively), and large population

and by of the overexploitation (Xavier et al., 2014).

(43–50 cm and 61–120 cm, respectively).

Squid have natural ability to recover from low biomass—level

that may occur during unfavorable conditions, nonetheless a strong

2.2. Microsatellite development

fishing pressure during such periods could negatively affect the

recovery process and, consequently, their fishing stocks (Arkhipkin

Pooled Genomic DNA from the arm tissue of seven individ-

et al., 2015). Thus, considering the importance that jumbo squid

uals of jumbo squid was digested with Sau3AI. DNA fragments

represents for global catch, it is essential to under-

between 500 and 1000 bp were selected from agarose gel using a

stand the drivers affecting the spatial and temporal variations,

QIA-quick Gel Extraction Kit (Qiagen, Germany). Around 300 ng of

density and further how these yearly fluctuations affect the popu-

the fragments was ligated into a pUC19 vector according to manu-

lation of this species. Most commonly used methods in the recent

facterıs´ protocol (Takara Bio Inc., Japan), transferred into competent

times, besides well-established biometrics to identify and distin-

Echerichia coli bacteria JM109 (Takara) and grown on agar media

guish squid populations, are population genetic studies.

containing ampicillin, IPTG and X-gal for blue-white screening. Pos-

One of the primary goals of population genetics studies is

itive clones containing microsatellites were identified by colony

to understand the population structure, intraspecific variability

PCR with universal M13 primer and chemiluminescence using Dig-

and gene flow of the species by the identification of discrete

(GT) hybridization probes and Digoxigenin nucleic acid detection

sub-populations or the so called “stocks” using nuclear and/or mito- 15

kit (Boehringer Mannheim, Germany). A total of 122 positive clones

chondrial DNA markers (Palsbøll et al., 2007). The identification of

from 2112 colonies were sequenced using the ABI 3130x1 Genetic

these stocks represent an important component for effective fish-

Analyzer with BigDye Terminator v3.1 (Applied Biosystem). The

eries management (Begg et al., 1999). Unidentified genetic stocks

online software Primer3 v.0.4.0 (http://bioinfo.ut.ee/primer3-0.4.

may be heavily impacted by natural and/or anthropogenic stresses

0) was then used to design primer set for candidate microsatellites.

that may lead to loss of genetic diversity.



Either the forward or reverse primer was labelled at the 5 end

To date, population genetics assessment of jumbo squid have

with FAM, NED, VIC or PET. The PCR amplification was performed

only been carried out through allozyme polymorphisms (Yokawa,

in a total volume of 5 ␮L containing 2.5 ␮L KOD buffer,1 ␮L dNTP,

1995), random amplified polymorphic DNA PCR (RAPD-PCR)

0.1 ␮L KOD polymerase (Toyobo Co., Ltd., Osaka, Japan), 0.2 mM

with single strand confirmation polymorphism (SSCP) (Sandoval-

each primer and approximately 25 ng template DNA. PCR was per-

Castellanos et al., 2009), and sequencing of mtDNA (Ibanez˜ et al.,

formed in a Mastercycler Gradient 96-Well system (Eppendorf,

2011; Sandoval-Castellanos et al., 2010; Staaf et al., 2010) but no

◦

Hamburg, Germany) with initial denaturation at 94 C for 4 min

studies with fast-mutation DNA markers such as microsatellites;

◦

followed by 30 cycles of 94 C for 1 min, locus-specific annealing

one of the most powerful molecular marker to assess the population

◦

temperatures (Table S1) for 1 min and 72 C for 1 min; and a final

genetic of species, have been performed yet.

◦

extension at 72 C for 10 min. Then, 1 ␮L of diluted PCR products

The goal of this study was to evaluate the genetic diversity, sig-

was mixed with a solution of 8.6 ␮L of formamide and 0.4 ␮L of

natures of past demographic events, and population structure of

TM ®

GeneScan -600 LIZ size standard (Applied Biosystem). This mix-

jumbo squid in Peruvian waters based on novel microsatellite loci

◦

ture was denatured at 95 C for 3 min and then ran through an ABI

and mitochondrial DNA NADH dehydrogenase 2 (ND2). We evalu-

3130x1 Genetic Analyzer (Applied Biosystem).

ated our samples pooled in two different groups according to the

G. Sanchez et al. / Fisheries Research 175 (2016) 1–9 3

Fig. 1. Dosidicus gigas study area and the number of individuals sampled in each location. A dashed line indicates the Exclusive Economic Zone (EEZ) of Peru.

2.3. Sequencing of mtDNA ND2 tests. At this point of the study, only loci in HWE with the initial

24 individuals amplified were selected for further analysis to avoid

A fragment of 675 base pair was obtained with the primers SqSF- the impact of non-genotyped individuals.

 

forward 5 -GCTGCTAACTTTATTTTGAGC-3 and DCOR2-reverse The above-mentioned softwares were also used to assess poly-

 

5 -ATTAGTCTTAGAGAAGTTCC-3 designed by Staaf et al. (2010). morphism in the 120 individuals. Further, Micro-Checker software

For each individual, PCR reaction was carried out in a total vol- (Van Oosterhout et al., 2004) was used to asses null alleles and

ume of 5 ␮L containing 2.5 ␮L KOD buffer,1 ␮L dNTP, 0.1 ␮L KOD scoring errors for loci with departure from HWE.

polymerase (Toyobo Co., Ltd., Osaka, Japan), 0.2 mM each primer To estimate genetic structure, global AMOVA and estimation

and approximately 25 ng template DNA. PCR was performed in of pairwise F-statistics (FST) based on 10,000 permutations were

a Mastercycler Gradient 96-Well system (Eppendorf, Hamburg, performed in Arlequin v3.5.1.2. To overcome a possible bias when

◦

Germany) with initial denaturation at 94 C for 2 min followed by individuals were pooled, Bayesian clustering analysis was also per-

◦ ◦ ◦

40 cycles of 94 C for 10 s, 46 C for 30 s and 72 C for 1 min; and a formed using Structure v.2.3.4 (Pritchard et al., 2000) based on

◦

final extension at 72 C for 7 min. PCR products were treated with admixture and correlated allele frequencies model with 10 inde-

ExoSAP-IT (Affymetrix/USB Corporation, Cleveland, OH) and then pendent run and genetic clustering K ranged from 1 to 4 without

sequenced using BigDye v3.1 Terminator Sequencing Kit (Applied prior information on the origin of individuals. Each run consisted

Biosystems) with the forward primer on a Genetic Analyzer (ABI of 1,000,000 Markov Chain Monte Carlo (MCMC) repetitions and a

3130x1, Applied Biosystems). burn-in period of 100,000. Structure output was visualized with the

web-based program Structure Harvester (http://taylor0.biology.

ucla.edu/structureHarvester) (Earl and vonHoldt, 2012).

2.4. Data analysis

For mitochondrial ND2, chromatograms were manually checked

using Chromas lite 2.1.1 (Technelysium Pty. Ltd.) and sequences

2.4.1. Genetic diversity and population structure

alignment were performed with Clustal W (Thompson et al., 1994)

For microsatellite loci, length variants were visualized and

◦ implemented in MEGA 6.0 (Tamura et al., 2013). Number of haplo-

genotyped in 24 individuals belonging to the North (∼4 S)

types (h), number of polymorphic sites (S), haplotype diversity (HD)

group using Peak Scanner Software v1.0 (Applied Biosystems).

(Nei, 1987) and nucleotide diversity () (Nei, 1987) were estimated

Observed (HO) and expected (HE) heterozygosity, departure from

with DnaSP v. 5.10 (Librado and Rozas, 2009).

the Hardy–Weinberg equilibrium (HWE), and genotypic linkage

The genetic differentiation within both groups was evaluated

disequilibrium (LD) were tested using Arlequin v3.5.1.2 (Excoffier

with the same software and procedures as microsatellite data

and Lischer, 2010); whereas the number of alleles (A) were esti-

(global AMOVA and pairwise FST mentioned above). The relation-

mated with FSTAT 2.9.3.2 (Goudet, 1995). Additionally, we used

ship among the haplotypes generated were visualized by a 95%

Bonferroni corrected p-values to assess the significance of multiple

4 G. Sanchez et al. / Fisheries Research 175 (2016) 1–9

statistical parsimony network using the program TSC 1.21 (Clement LC017894–LC017911). The number of alleles ranged from 2 to 27.

et al., 2000). For these analyses, 59 additional sequences represent- HO and HE ranged from 0.042 to 0.958 and from 0.042 to 0.963

ing samples from Chile in 2005 and 2006 (Staaf et al., 2010) were respectively. After Bonferroni correction, no significant LD was

retrieved from GenBank (HQ612278.1–HQ612336.1) to include detected between any pairs of locus and significant departure from

missing haplotypes. HWE was found at eight loci (p < 0.0027). From the ten loci in HWE,

one amplified only in 20 individuals (Dgigas-8) and another had low

polymorphism with only 2 alleles (Dgigas-10). Thus, the remaining

2.4.2. Demographic analysis

eight loci in HWE were used for the total individuals (n = 120).

From the total individuals, inference of pattern on historical

demographic were based on neutrality tests, mismatch distribu-

tion, and Bayesian skyline plots from the mtDNA ND2 region. For

3.2. Genetic diversity

the neutrality tests, Tajima’s D test based on the frequency of segre-

gating sites (Tajima, 1989) and Fu’s Fs test based on the distribution

Estimation of genetic diversity across eight microsatellite DNA

of haplotypes (Fu, 1997) were performed using Arlequin v3.5.1.2

loci is summarized in Table 1. The mean number of alleles (NA)

with 10,000 permutations.

was 21.5 and 18.75 for the North and Central–South populations,

For mismatch distribution, the observed distribution of pair-

respectively. The mean observed and expected heterozygosity

wise differences between sequences (Rogers and Harpending,

(HO/HE) at eight loci was 0.712/0.828 and 0.658/0.825 for the North

1992) were compared with expected distribution under sudden

and Central–South populations, respectively. None of the LD tests

population expansion in Arlequin v3.5.1.2. The unimodal distri-

were significant for any pair of loci. After sequential Bonferroni

bution indicated that the population had passed through a either

correction, departures from HWE were found at loci Dgigas-2,

bottleneck or demographic expansion; whereas the bimodal or

Dgigas-6, and Dgigas-7 in the North population and at loci Dgigas-

multimodal distributions indicated that the population has been

1, Dgigas-2, Dgigas-3, Dgigas-6, and Dgigas-7 in the Central–South

stable over long time. The validation of our result to the demo-

population. Micro-checker tests confirmed the presence of null

graphic expansion model was evaluated by a goodness of fit test

alleles at these loci. Scoring errors were found in locus Dgigas-1.

using a parametric bootstrap based on the sum of square devia-

Finally, only the HWE loci Dgigas-4, Dgigas-5, and Dgigas-9 were

tions (SSD) and Harpending’s raggedness index (Hri) (Harpending,

considered for further analysis. The average HO/HE in the HWE loci

1994) as implemented in Arlequin v3.5.1.2.

was 0.667/0.772 and 0.622/0.747 for the North and Central–South

Furthermore, the demographic expansion parameter tau () was

populations, respectively and 0.644/0.759 as a mean of loci in the

calculated in Arlequin v3.5.1.2. and the expansion time was esti-

total population.

mated from the equation ␶ = 2 ut (Rogers and Harpending, 1992)

For mitochondrial DNA diversity, a product of 675 base pairs was

where t is the number of generation and u is the mutation rate

successfully obtained from the total individuals (n = 120). Thirty-

of the sequence analyzed. The parameter u which was calculated

seven haplotypes were found in the entire dataset. The most

according to the equation u = 2 k, where is the mutation rate per

common haplotype H1 was found in 53 individuals followed by H2

nucleotide per site and k is the length of the sequence, in this study

with 22 individuals (Table S2, Supplemental material). All of the 37

675 bp. The expansion time in years was calculated by multiplying t

haplotypes were deposited in GenBank with the accession numbers

by the generation time (∼1 year, general assumption). Considering

−1 LC060315–LC060434. For each population, genetic diversity indices

a divergence time twice the mutation rate, the value of 1.2/Myr

are shown in Table 2. Overall, 37 different haplotypes and 41 vari-

was used for as proposed by Hellberg and Vacquier (1999) (2.4%

able sites; including 30 singleton variable sites and 11 parsimony

for gastropod Tegula).

informative sites were found. Additionally, values of haplotype

To reconstruct the demographic history of jumbo squid, we

and nucleotide diversity were moderate in the overall dataset

used the Bayesian skyline plot (BSP) approach implemented in

(HD = 0.772 ± 0.036, = 0.00233 ± 0.00025). Furthermore, HD was

Beast v1.8.1 (Drummond et al., 2012). BSP is a useful method for

0.798 ± 0.051 and 0.746 ± 0.048, whereas was 0.00217 ± 0.00027

tracking the past population dynamics with all the parameter of

and 0.00244 ± 0.00038 for the North and Central–South popula-

demographic history pooled into a single analysis. The best model

tions, respectively.

that fit our data set was TrN (TN93 in Beast software) as inferred

The TCS parsimony network showed two main clusters (H1 and

with BIC (Bayesian information criterion) using jModeltest 2.1.6

H2) with a small genetic distance of 1–3 mutation steps. Within

(Posada, 2008) (-ln(likelihood) = 1185.18, BIC = 3953.44). The anal-

7 each cluster, most of the haplotypes were differentiated by one

ysis was performed with three independent runs of 7 × 10 MCMC

mutation step. Furthermore, the most dominant haplotypes (H1

in every 7000 steps obtaining an effective sample size (ESS) of >400.

and H2) in Peruvian waters were also the dominant haplotypes in

The number of grouped intervals (m) was set at 10. The mutation

−8 an extensive area of the Humboldt Current system (Fig. 2).

rate per year was set at 1.2 × 10 assuming the generation time

mentioned above; whereas the uncorrelated exponential model

distribution was used as the best model that fitted our data, selected

3.3. Demographic history

by Bayes factor comparison (log10Bayes Factor = 3.367). Each inde-

pendent log file and tree file was pooled using LogCombiner v.1.8.1

Significant negatives values of Fu’s Fs and Tajima’s D tests indi-

(implemented in Beast package) with a burn-in of 10%. The sky-

cate the presence of a recent demographic expansion of jumbo

line plot generated was visualized with Tracer v.1.5. (Drummond

squid (Table 3). Additionally, the unimodal distribution of the total

and Rambaut, 2007). BSP is shown as population size (Ne) vs years

dataset fitted the curve of demographic expansion model (Fig. 3).

before present (Ho and Shapiro, 2011).

These results were also supported by the non-significant SSD and

Hri tests (Table 3).

The time of population expansion based on the parameter

3. Results

tau ( = 1.412) was estimated to be approximately 43,500 years

ago. Furthermore, Bayesian skyline analysis revealed a population

3.1. Microsatellite development

growth with an increase in the effective population size of females

to a median of 22 million individuals (95% HPD = 0.49–60.9 million)

A summary of the eighteen polymorphic microsatellite loci

over the last 50,000 years (Fig. 4).

isolated is shown in the Table S1. (Genbank accession numbers

G. Sanchez et al. / Fisheries Research 175 (2016) 1–9 5

Table 1

Genetic diversity at eight microsatellite loci for the Geographical density group. n, Number of individuals; A, number of alleles; S (bp), allelic size range; HO, observed

heterozygosity; HE, expected heterozygosity; p-value, probability of departure from HWE. Value in bold refers to loci with significant departures from HWE after Bonferroni

corrections (p < 0.00625).

Population Locus

Dgigas-1 Dgigas-2 Dgigas-3 Dgigas-4 Dgigas-5 Dgigas-6 Dgigas-7 Dgigas-9 Mean

Geographical density

North (n = 60)

A 15 30 22 9 24 41 18 11 21.25

S (bp) 121–179 138–216 144–244 125–153 165–219 200–324 153–237 145–185 –

HO 0.533 0.783 0.883 0.433 0.867 0.717 0.783 0.700 0.712

HE 0.618 0.954 0.919 0.521 0.930 0.890 0.925 0.863 0.828

p-Value 0.0159 0.0000 0.1239 0.2407 0.6439 0.0031 0.0015 0.0494 –

Central–South (n = 60)

A 12 28 15 9 20 39 15 12 18.75

S (bp) 121–171 142–216 160–228 125–153 169–213 212–330 177–233 145–189 –

HO 0.467 0.783 0.800 0.367 0.717 0.633 0.717 0.783 0.658

HE 0.665 0.949 0.907 0.456 0.898 0.912 0.930 0.885 0.825

p-Value 0.0018 0.0019 0.0036 0.0481 0.0073 0.0002 0.0000 0.0219 –

Mean of loci

A 13.5 29 18.5 9 22 40 16.5 11.5 20

HO 0.500 0.783 0.842 0.400 0.792 0.675 0.750 0.742 0.685

HE 0.641 0.952 0.913 0.489 0.914 0.901 0.927 0.874 0.827

Table 2

Molecular diversity indices for Dosidicus gigas in the northern Humboldt Current based on ND2 sequences.

Population n S h HD ± SD ␲ ± SD

North 60 27 24 0.798 ± 0.051 0.00217 ± 0.00027

Central–South 60 18 16 0.746 ± 0.048 0.00244 ± 0.00038

All 120 41 37 0.772 ± 0.036 0.00233 ± 0.00025

Fig. 2. Haplotype parsimony network for Dosidicus gigas in an extensive area of the Humboldt Current System. Each circle represents the haplotypes and the area is

proportional to the frequencies of individuals. Each dash represents one mutation step and small black dots indicate absent haplotypes. The circles at the bottom of the figure

are the scale of the respective number of individuals in the network.

Table 3

Demographic parameters estimated for Dosidicus gigas in the northern Humboldt Current. *Statistically significant values (p < 0.05).

Population Fuıs´ Fs (P) Tajimaıs´ D (P) SSD (P) Hri (P)

North −26.074 (0.000)* −2.399 (0.000)* 0.001 (0.620) 0.060 (0.270)

Central–South −1.756 (0.021)* −9.403 (0.000)* 0.011 (0.110) 0.060 (0.400)

Overall −2.440 (0.001)* −27.998 (0.000)* 0.002 (0.190) 0.050 (0.370)

6 G. Sanchez et al. / Fisheries Research 175 (2016) 1–9

Table 4

Global AMOVA for both Geographical density and Size at maturity groups based on mtDNA ND2 and HWE microsatellite loci. *Statistically significant values (p < 0.05).

Source of variation mtDNA ND2 HWE microsatellite loci

d.f Sum of squares Variance components Percentage variation d.f Sum of squares Variance components Percentage variation

Geographical density

Among populations 1 1.8 0.01706 Va 2.15 1 1.754 0.00513 Va 0.45

Within population 118 91.633 0.77655 Vb 97.85 238 271 1.13866 Vb 99.55

Fixation index FST = 0.02149* FST = 0.00448

Size at maturity

Among populations 2 2.615 0.01344 Va 1.7 2 1.353 −0.00033 Va −0.05

Within population 117 90.819 0.77623 Vb 98.3 237 166.468 0.70239 Vb 100.05

Fixation index FST = 0.01701* FST = − 0.00046

Table 5

Analysis of pairwise FST for both Geographical density and Size at maturity groups.

For each group, upper triangular matrix: values based on mtDNA sequence data and

lower triangular matrix: values based on microsatellite data. *Statistically significant

values (p < 0.05).

Geographical density

North Central–South

North – 0.02149*

Central–South 0.00448 –

Size at maturity

Small Medium Large

Small – 0.01998 0.02608*

Medium 0.00062 – 0.0097

−

Large 0.0083 0.0038 –

Fig. 3. Mismatch distribution of mitochondrial DNA ND2 haplotypes for the total

tion between the Small and Large populations. When analysis was

Dosidicus gigas dataset (n = 120) in the northern Humboldt Current system under

made between males from the Small (n = 15) and Large (n = 12)

the sudden population expansion model.

populations, the pairwise FST analysis showed a non-significant

(p > 0.05) and negative FST value (FST = −0.015). However, the anal-

ysis between females from the Small (n = 18) and Large (n = 27)

3.4. Population structure

populations, resulted in significant (p < 0.05) FST value (FST = 0.050)

(data not shown).

At microsatellite loci in HWE (Dgigas-4, Dgigas-5, and Dgigas-

Global AMOVA and pairwise FST comparison analysis in both

9 for Geographical density and Dgigas-3 and Dgigas-4 for Size at

groups are shown in Tables 4 and 5, respectively. Besides, analysis

maturity), neither global AMOVA nor pairwise FST analysis showed

based on HWE loci from the Size at maturity group is shown in

significant value of genetic differentiation at any groups.

Table S3 (Supplemental material).

At mtDNA loci, global AMOVA showed low but significant fix-

In addition, Bayesian clustering analysis for both the Geograph-

ation indexes in the Geographical density and Size at maturity

ical density and Size at maturity groups failed to detect any genetic

groups (FST = 0.02149 and 0.01701, respectively). In addition, pair-

structure, with the highest posterior probability value for K = 1 (ln

wise FST analysis supported the results obtained by global AMOVA,

P[K/X] = −1469.37 and −902.23, respectively).

indicating a low but significant (FST = 0.02608) genetic differentia-

Fig. 4. Bayesian skyline plot for Dosidicus gigas with mitochondrial DNA ND2. Curve represents changes in the effective population size. Thick solid line represents the median

estimate of the population size and the gray area denotes the 95% HPD intervals.

G. Sanchez et al. / Fisheries Research 175 (2016) 1–9 7

4. Discussion 1988; Rodhouse et al., 1995). Thefore, the wide distribution of

jumbo squid could lessen the impact of fisheries.

4.1. Genetic diversity and demographic history Historical events could better explain the low genetic diversity

observed. The star-like shape of the haplotype network, unimodal

In this study, we found high percentage of microsatellite loci mismatch distribution, significantly negative neutrality tests and

with departures from HWE in jumbo squid (62.5% and 75% for the Bayesian skyline suggest a primary hypothesis of pure demographic

Geographical density and Size at maturity groups, respectively). For expansion. Although a historical bottleneck event can produce

oegopsid , the highest number of loci with HWE departures similar result in the haplotype network, BSP does not showed

previously reported was in pacificus (54.4%) (Iwata et al., any signatures of a strong reduction of populations followed by

2008). a population expansion. Similar influence of demographic events

One possible explanation for the HWE departures is the poten- in the Humboldt current was also observed in the myopsid squid

tial high fecundity of females of this species, reported as the Doryteuthis gahi, showing less genetic diversity in Peruvian pop-

highest for all with 0.3–13 million oocytes per indi- ulation in contrast with the Chilean population, with evidence of

vidual (Nigmatullin et al., 2001). Marine invertebrates have many demographic expansion for the first population (Ibánez˜ and Poulin,

variations in life history traits that are correlated with the HWE 2014).

departures (Addison and Hart, 2005). High genetic load is expected In to avoid a bias in the past demographic history analy-

in organism with highly fecundity (Williams, 1975) and the increas- sis of jumbo squid, two different approaches were evaluated, the

ing of mutational events that could eventually lead the HWE least-square ( -value) and coalescence-based (BSP) methods. The

departures, may be explained by the high number of cell divi- differences in the time of expansion calculated by both approach

sions necessary to produce millions of eggs (Launey and Hedgecock, is the effectiveness of Bayesian skyline plot to describe signatures

2001). A second and more plausible explanation for the HWE of demographic signatures that are not readily described by other

departures came from the demographic inter-annual fluctuations basic demographic models (Drummond et al., 2005). The time of

of jumbo squid; acting as temporal and little bottleneck, affect- expansion of this species into Peruvian waters was calculated at

∼

ing the allele frequencies. HWE is characterized by the equilibrium 43,500 years ago with the generalized least-square approach.

between alleles and the genotype frequencies after one generation Even though this value is close to the 45,000 years calculated from

and thereafter. As mentioned, environmental variability affects the mtDNA COI by Ibanez˜ et al. (2011), our Bayesian approach indi-

biomass of jumbo squid which is observed in the annual variation of cates that the time of expansion for this species was before 50,000

the catch per effort unit (CPUE) possibly creating a large variance in years. In fact, the Bayesian skyline plot indicates that during this

the reproductive success with direct influence in the genetic diver- period, the squid population was already in a process of expansion.

sity by differences in allele frequencies of the next offspring. The Nonetheless, these results should be carefully considered because

variation in the reproductive success is a common characteristic of factors such as the time dependency of mutation rate (Ho et al.,

in most of marine with high fecundity and pelagic eggs or 2005) and the diversity of assumptions in our demographic history

larvae (Ruzzante et al., 1996). This variation and the short life span analysis such as the constant generation time (1 year) and diver-

may considerably affect jumbo squid. gence rate value taken from gastropods that may overestimate the

Levels of genetic diversity inferred from ND2 in other oegopsid real time of historical events.

squid are not available for an appropriate comparison. Never-

theless, the analysis of Chilean mtDNA ND2 data used for the 4.2. Population structure

haplotype network showed values of haplotype diversity (HD = 0.80

and HD = 0.72 for Chile 2005 and 2006, respectively), close to the Microsatellite loci indicated a single genetic structure in jumbo

overall dataset in this study (HD = 0.77). However, analysis inferred squid population (∼1500 km) in both the Geographical density and

from mtDNA COI and Cytb suggest that the Chilean population Size at maturity groups. Unique genetic stock was expected due

has lower genetic diversity than the Peruvian population and low to the species characteristics, e.g., one of the highest metabolic

haplotype diversity for the HCS (Ibanez˜ et al., 2011; Sandoval- rates in the marine animals (Rosa and Seibel, 2010; Seibel and

Castellanos et al., 2010). The differences found in this study can Drazen, 2007), the potential of dispersion of its eggs and paralar-

be explained by the rapid recovery of genetic diversity as a result vae (Ibánez˜ and Poulin, 2014), and its long distance migrations

of potentially high fecundity (Nigmatullin and Markaida, 2009) and (Nesis, 1970; Nigmatullin et al., 2001). Furthermore, this results are

multiple spawner characteristics of this species (Rocha et al., 2001) related to the lack of cryptic differentiation within this suborder,

with temporal environmental factors. Nevertheless, the different with only three species reported based on molecular data: Martialia

mutation rates of mtDNA genes could also influence this compari- hyadesi (Brierley et al., 1993), Berryteuthis magister (Katugin, 2000),

son. (Sandoval-Castellanos et al., 2009) and oualaniensis

From microsatellite DNA loci, levels of genetic diversity in our (Staaf et al., 2010)

study were low (HO = 0.64) compared with other commercially In contrast, the mtDNA indicated a low but significant genetic

important oegopsid squid, such as argentinus (HO = 0.84) and differentiation between the Small and Large populations, which

Todaropsis eblanae (HO = 0.82–0.91)(Adcock et al., 1999; Dillane also explained the significant FST value in the Global AMOVA of

et al., 2005). Additionally, the North population exhibited higher the Geographical density group.

genetic diversity than the Central–South population with both DNA The difference found between nuclear and mitochondrial

markers. marker analyses can be explained by three factors: (1) the low

Highly mobile characteristic and the high number of offspring, number of microsatellite loci used for the genetic differentiation

estimated at ∼0.6–2 million eggs from a natural egg mass with a (Dgigas-3 and Dgigas-4); (2) the difference in the dispersal poten-

reproductive output likely between 3 and 20 egg masses from a sin- tial of the sexes (different maternal history of the Small and Large

gle female (Staaf et al., 2008), mean that fishing pressure likely does population) and (3) different influence of genetic drift on mito-

not explain the low genetic diversity. In addition, spatial distribu- chondrial and nuclear genes. Maternal (uniparental) inheritance

tion is an important factor for cephalopod survival (Llpinski,´ 1998). has important consequences in a population, because only a frac-

I. argentinus, a commercially important cephalopod in the south- tion (depending on sex ratio) of the total population will pass their

west Atlantic with high genetic diversity (Adcock et al., 1999), is mtDNA to the offspring, thus creating a 4-fold smaller effective pop-

◦ ◦

distributed along the Patagonia shelf from 22 S to 54 S (Hatanaka, ulation size comparing with to that calculated from nuclear DNA

8 G. Sanchez et al. / Fisheries Research 175 (2016) 1–9

(Esa et al., 2013; Harrison, 1989). Thereby, stochastic processes Appendix A. Supplementary data

such as genetic drift are easier to affect the mitochondrial than the

nuclear alleles and thus likely to show patterns of demographic Supplementary data associated with this article can be found,

structure. in the online version, at http://dx.doi.org/10.1016/j.fishres.2015.11.

Eventhough the small number of individuals used in this study, 005.

only female’s sub-population provides a significant differentiation

between the Small and Large population based on a sex specific References

genetic comparison. Thus, increasing the number of individuals

Adcock, G.J., Shaw, P.W., Rodhouse, P.G., Carvalho, G.R., 1999. Microsatellite

from both sexes is an interesting route for the exploration of

analysis of genetic diversity in the squid during a period of

our current result. However, it is important to mention that sex

intensive fishing. Mar. Ecol. Prog. Ser. 187, 171–178, http://dx.doi.org/10.3354/

segregated migration in oegopsid squid was previously reported meps187171.

in other members of the same , Sthenoteuthis oualaniensis Addison, J., Hart, M., 2005. Spawning, copulation and inbreeding coefficients in

marine invertebrates. Biol. Lett. 1, 450–453, http://dx.doi.org/10.1098/rsbl.

(Nesis, 1977) and Ommastrephes bartramii, associated with favor-

2005.0353.

able oceanographic environments (Ichii et al., 2009).

Arkhipkin, A.I., Rodhouse, P.G.K., Pierce, G.J., Sauer, W., Sakai, M., Allcock, L.,

In addition, the Small individual-size population is predominant Arguelles, J., Bower, J.R., Castillo, G., Ceriola, L., Chen, C.-S., Chen, X.,

Diaz-Santana, M., Downey, N., González, A.F., Amores, J.G., Green, C.P., Guerra,

in the sub-equatorial area likely because of the warmer waters and

A., Hendrickson, L.C., Ibánez,˜ C., Ito, K., Jereb, P., Kato, Y., Katugin, O.N., Kawano,

low food availability (Friedemann Keyl et al., 2008; Nigmatullin

M., Kidokoro, H., Kulik, V.V., Laptikhovsky, V.V., Lipinski, M.R., Liu, B.,

et al., 2001). Thereby, an migration/invasion of individuals from Mariátegui, L., Marin, W., Medina, A., Miki, K., Miyahara, K., Moltschaniwskyj,

N., Moustahfid, H., Nabhitabhata, J., Nanjo, N., Nigmatullin, C.M., Ohtani, T.,

warmer waters into the Peruvian waters as it was reported in 1992

Pecl, G., Perez, J.A.A., Piatkowski, U., Saikliang, P., Salinas-Zavala, C.A., Steer, M.,

and early 1993 (Tafur and Rabí, 1997) could also explain the genetic

Tian, Y., Ueta, Y., Vijai, D., Wakabayashi, T., Yamaguchi, T., Yamashiro, C.,

differentiation between the Small and Large population. In fact, a Yamashita, N., Zeidberg, L.D., 2015. World squid fisheries. Rev. Fish. Sci. Aquac.

23, 92–252, http://dx.doi.org/10.1080/23308249.2015.1026226.

very similar significant pairwise FST value (FST = 0.023) between

Asahida, T., Kobayashi, T., Saitoh, K., Nakayama, I., 1996. Tissue preservation and

samples from Peru (2007) and the Eastern Tropical Pacific (ETP)

total DNA extraction form fish stored at ambient temperature using buffers

were reported by Staaf et al. (2010) using the same mitochon- containing high concentration of urea. Fish. Sci. 62, 727–730.

Bakun, A., Weeks, S.J., 2008. The marine ecosystem off Peru: what are the secrets of

drial marker. This migration/invasion is probably induced by food

its fishery productivity and what might its future hold? Prog. Oceanogr. 79,

availability and suitable spawning area in Peruvian waters. Fur-

290–299, http://dx.doi.org/10.1016/j.pocean.2008.10.027.

ther genetic structure comparison between Humboldt Current and Begg, G.A., Friedland, K.D., Pearce, J.B., 1999. Stock identification and its role in

Eastern Tropical Pacific population will help to clarify the difference stock assessment and fisheries management: an overview. Fish. Res. 43, 1–8,

http://dx.doi.org/10.1016/S0165-7836(99)00062-4.

within Size at maturity group.

Brierley, A.S., Rodhouse, P.G., Thorpe, J.P., Clarke, M.R., 1993. Genetic evidence of

population heterogeneity and cryptic speciation in the ommastrephid squid

Martialia hyadesi from the Patagonian Shelf and Antarctic Polar Frontal Zone.

Mar. Biol. 116, 593–602, http://dx.doi.org/10.1007/BF00355478.

5. Conclusion

Clement, M., Posada, D., Crandall, K.A., 2000. TCS: a computer program to estimate

gene genealogies. Mol. Ecol. 9, 1657–1659, http://dx.doi.org/10.1046/j.1365-

The results of our study provide very important information 294x.2000.01020x.

Cosgrove, J.A., 2005. The First Specimens of Humboldt Squid in British Columbia,

to be implemented in the ongoing monitoring of jumbo squid,

13. PICES Press, pp. 30–31.

especially due to the combined nuclear and mitochondrial DNA

Dillane, E., Galvin, P., Coughlan, J., Lipinski, M., Cross, T.F., 2005. Genetic variation

information that contribute for the first time for this species. The in the lesser flying squid (Cephalopoda, )

in east Atlantic and Mediterranean waters. Mar. Ecol. Prog Ser. 292, 225–232,

major findings of this study have important implications in the fish-

http://dx.doi.org/10.3354/meps292225.

eries management of this species, especially considering the low

Drummond, A.J., Rambaut, A., 2007. BEAST: Bayesian evolutionary analysis by

level of genetic diversity that may be caused by historical demo- sampling trees. BMC Evol. Biol. 7, 214, http://dx.doi.org/10.1186/1471-2148-7-

214.

graphic expansion but also the inter-annual fluctuations, acting as

Drummond, A.J., Rambaut, A., Shapiro, B., Pybus, O.G., 2005. Bayesian coalescent

temporal and little bottleneck that can produce the allele loss. Nev-

inference of past population dynamics from molecular sequences. Mol. Biol.

ertheless, there was a limitation at microsatellite loci due to the Evol. 22, 1185–1192, http://dx.doi.org/10.1093/molbev/msi103.

high number of loci with HWE departures that could decrease the Drummond, A.J., Suchard, M.A., Xie, D., Rambaut, A., 2012. Bayesian phylogenetics

with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29, 1969–1973, http://dx.doi.

performance of these loci to accurately detect a population genetic

org/10.1093/molbev/mss075.

structure. Thus, whether the northern Humboldt Current contains

Earl, D.A., vonHoldt, B.M., 2012. STRUCTURE HARVESTER: a website and program

a unique genetic population stock or not, remains uncertain and it for visualizing STRUCTURE output and implementing the Evanno method.

Conserv. Genet. Resour. 4, 359–361, http://dx.doi.org/10.1007/s12686-011-

will require additional comparison between the Humboldt Current

9548-7.

population and population(s) from the Eastern Tropical Pacific with

Esa, Y., Abdul Rahim, K.A., Esa, Y., Abdul Rahim, K.A., 2013. Genetic structure and

nuclear and mtDNA loci. Additionally, the integration of the genetic preliminary findings of cryptic diversity of the Malaysian mahseer (Tor

tambroides Valenciennes: Cyprinidae) inferred from mitochondrial DNA and

data from this study with biological and environmental information

microsatellite analyses. BioMed Res. Int., http://dx.doi.org/10.1155/2013/

would facilitate an effective management plan for jumbo squid in

170980, e170980.

the intensive fisheries area of the Peruvian waters. Excoffier, L., Lischer, H.E.L., 2010. Arlequin suite ver 3.5: a new series of programs

to perform population genetics analyses under Linux and Windows. Mol. Ecol.

Resour., 564–567, http://dx.doi.org/10.1111/j1755-0998.2010.02847. x.

FAO, 2014. FishStatJ, Ssoftware for fishery statistical time series. FAO Fisheries and

Acknowledgments Aquaculture department [online], Rome (2014). Available at http://www.fao.

org/fishery/statistics/software/fishstatj/en (accessed December 2014.).

Fu, Y.-X., 1997. Statistical tests of neutrality of mutations against population

This research was supported by the Japanese Government

growth, hitchhiking and background selection. Genetics 147, 915–925.

through the Ministry of Education, Culture, Sport, Science and Goudet, J., 1995. FSTAT (Version 1.2): a computer program to calculate F-statistics.

Technology in Japan (Monbukagakusho: MEXT) and partly by the J. Hered. 86, 485–486.

Harpending, H.C., 1994. Signature of ancient population growth in a low-resolution

Peruvian Government FINCyT Perú (Contrato 060 PIN 115). We

mitochondrial DNA mismatch distribution. Hum. Biol. 66, 591–600.

would like to thank to Tjasaˇ Kogovsekˇ (Hiroshima University) for

Harrison, R.G., 1989. mitochondrial DNA as a genetic marker in population

their constructive advice about the writing of the manuscript. and evolutionary biology. Trends Ecol. Evol. 4, 6–11, http://dx.doi.org/10.1016/

0169-5347(89)90006-2.

The authors also wish to thank to the editor and two anonymous

Hatanaka, H., 1988. Feeding migration of short-finned squid Illex argentinus in the

reviewers who greatly improved the manuscript through their crit-

waters off Argentina. Nippon Suisan Gakkaishi 54, 1343–1349, http://dx.doi. icism. org/10.2331/suisan.54.1343.

G. Sanchez et al. / Fisheries Research 175 (2016) 1–9 9

Hellberg, M.E., Vacquier, V.D., 1999. Rapid evolution of fertilization selectivity and Ruzzante, D.E., Taggart, C.T., Cook, D., 1996. Spatial and temporal variation in the

lysin cDNA sequences in teguline gastropods. Mol. Biol. Evol. 16, 839–848. genetic composition of a larval cod (Gadus morhua) aggregation: cohort

Ho, S.Y.W., Phillips, M.J., Cooper, A., Drummond, A.J., 2005. Time dependency of contribution and genetic stability. Can. J. Fish. Aquat. Sci. 53, 2695–2705,

molecular rate estimates and systematic overestimation of recent divergence http://dx.doi.org/10.1139/f96-235.

times. Mol. Biol. Evol. 22, 1561–1568, http://dx.doi.org/10.1093/molbev/ Sandoval-Castellanos, E., Uribe-Alcocer, M., Díaz-Jaimes, P., 1835. Population

msi145. genetic structure of the Humboldt squid (Dosidicus gigas d’Orbigny, inferred by

Ho, S.Y.W., Shapiro, B., 2011. Skyline-plot methods for estimating demographic mitochondrial DNA analysis. J. Exp. Mar. Biol. Ecol. 385, 73–78, http://dx.doi.

history from nucleotide sequences. Mol. Ecol. Resour. 11, 423–434, http://dx. org/10.1016/j.jembe.2009.12.015.

doi.org/10.1111/j1755-0998.2011.02988. x. Sandoval-Castellanos, E., Uribe-Alcocer, M., Díaz-Jaimes, P., 2009. Lack of genetic

Ibanez,˜ C.M., Cubillos, L.A., Tafur, R., Argelles, J., Yamashiro, C., Poulin, E., 2011. differentiation among size groups of jumbo squid (Dosidicus gigas). Cienc. Mar.

Genetic diversity and demographic history of Dosidicus gigas (Cephalopoda: 35, 419–428.

Ommastrephidae) in the Humboldt Current System. Mar. Ecol. Prog. Ser. 431, Seibel, B.A., Drazen, J.C., 2007. The rate of metabolism in marine animals:

163–171, http://dx.doi.org/10.3354/meps09133. environmental constraints, ecological demands and energetic opportunities.

Ibánez,˜ C.M., Poulin, E., 2014. Genetic structure and diversity of squids with Philos. Trans. R. Soc. B Biol. Sci. 362, 2061–2078, http://dx.doi.org/10.1098/

contrasting life histories in the Humboldt Current System. Hidrobiológica 24 rstb.2007.2101.

(1), 1–10. Staaf, D.J., Camarillo-Coop, S., Haddock, S.H.D., Nyack, A.C., Payne, J., Salinas-Zavala,

Ichii, T., Mahapatra, K., Sakai, M., Okada, Y., 2009. Life history of the neon flying C.A., Seibel, B.A., Trueblood, L., Widmer, C., Gilly, W.F., 2008. Natural egg mass

squid: effect of the oceanographic regime in the North Pacific Ocean. Mar. Ecol. deposition by the Humboldt squid (Dosidicus gigas) in the Gulf of California and

Prog Ser. 378, 1–11, http://dx.doi.org/10.3354/meps07873. characteristics of hatchlings and paralarvae. J. Mar. Biol. Assoc. U. K 88,

Iwata, Y., Lian, C.L., Sakurai, Y., 2008. Permanent genetic resources: development of 759–770, http://dx.doi.org/10.1017/S0025315408001422.

microsatellite markers in the Japanese common squid Todarodes pacificus Staaf, D.J., RuizCooley, R.I., Elliger, C., Lebaric, Z., Campos, B., Markaida, U., Gilly,

(Ommastrephidae). Mol. Ecol. Resour. 8, 466–468, http://dx.doi.org/10.1111/ W.F., 2010. Ommastrephid squids Sthenoteuthis oualaniensis and Dosidicus

j1471-8286. 2007.0.x. gigas in the eastern Pacific show convergent biogeographic breaks but

Katugin, 2000. A new subspecies of the schoolmaster gonate squid, Berryteuthis contrasting population structures. Mar. Ecol. Prog. Ser. 418, 165–178, http://

magister (Cephalopoda: Gonatidae), from the Japan Sea. Veliger 43, 82–97. dx.doi.org/10.3354/meps08829.

Keyl, F., Arguelles, J., Mariátegui, L., Tafur, R., Wolff, M., Yamashiro, C., 2008. A Tafur, R., Keyl, F., Argelles, J., 2010. Reproductive biology of jumbo squid Dosidicus

hypothesis on range expansion and spatio temporal shift in size-at-maturity of gigas in relation to environmental variability of the northern Humboldt

jumbo squid (Dosidicus gigas) in the Eastern Pacific Ocean. CCOFI Rep., Current System. Mar. Ecol. Prog. Ser. 400, 127–141, http://dx.doi.org/10.3354/

119–128. meps08386.

Launey, S., Hedgecock, D., 2001. High genetic load in the Pacific Oyster Crassostrea Tafur, R., Rabí, M., 1997. Reproduction of the jumbo flying squid, Dosidicus gigas

gigas. Genetics 159, 255–265. (Orbigny, (Cephalopoda: Ommastrephidae) off Peruvian coasts. Sci. Mar. 61,

Librado, P., Rozas, J., 2009. DnaSP v5: a software for comprehensive analysis of 33–37.

DNA polymorphism data. Bioinformatics 25, 1451–1452, http://dx.doi.org/10. Taipe, A., Yamashiro, C., Mariategui, L., Rojas, P., Roque, C., 2001. Distribution and

1093/bioinformatics/btp187. concentrations of jumbo flying squid (Dosidicus gigas) off the Peruvian coast

Llpinski,´ M.R., 1998. Cephalopod life cycles: patterns and exceptions. S. Afr. J. Mar. between 1991 and 1999. Fish. Res. 54, 21–32, http://dx.doi.org/10.1016/

Sci. 20, 439–447, http://dx.doi.org/10.2989/025776198784126205. S0165-7836(01)377-0, Squid Fishery Biology in the Eastern Pacific Coastal

Nei, M., 1987. Molecular Evolutionary Genetics. Columbia University Press. Upwelling System.

Nesis, K.N., 1983. Dosidicus gigas. In: Boyle, P.R. (Ed.), Cephalopod Life Cycles. Tajima, F., 1989. Statistical method for testing the neutral mutation hypothesis by

Accounts Academic Press, London (1983) I, pp. 216–231. DNA polymorphism. Genetics 123, 585–595.

Nesis, K.N., 1977. Population structure of the squid Sthenoteuthis oualaniensis Tamura, K., Stecher, G., Peterson, D., Filipski, A., Kumar, S., 2013. MEGA6: molecular

(Lesson, 1830) in the tropical West Pacific. Trudy IO AN SSSR 107, 15–29. evolutionary genetics analysis version 6. 0. Mol. Biol. Evol. 30, 2725–2729,

Nesis, K.N., 1970. The biology of the giant squid of Peru and Chile, Dosidicus gigas. http://dx.doi.org/10.1093/molbev/mst197.

Oceanology 10, 140–152. Thompson, J.D., Higgins, D.G., Gibson, T.J., 1994. CLUSTAL W: improving the

Nigmatullin, C.M., Markaida, U., 2009. Oocyte development, fecundity and sensitivity of progressive multiple sequence alignment through sequence

spawning strategy of large sized jumbo squid Dosidicus gigas (: weighting, position-specific gap penalties and weight matrix choice. Nucleic

Ommastrephinae). J. Mar. Biol. Assoc. U. K. 89, 789–801, http://dx.doi.org/10. Acids Res. 22, 4673–4680.

1017/S0025315408002853. Van Oosterhout, C., Hutchinson, W.F., Wills, D.P.M., Shipley, P., 2004.

Nigmatullin, C.M., Nesis, K.N., Arkhipkin, A.I., 2001. A review of the biology of the Micro-checker: software for identifying and correcting genotyping errors in

jumbo squid Dosidicus gigas (Cephalopoda: Ommastrephidae). Fish. Res. 54, microsatellite data. Mol. Ecol. 4, 535–538, http://dx.doi.org/10.1111/j. 1471-

9–19, http://dx.doi.org/10.1016/S0165-7836(01)00371-X. 8286.2004.00684. x.

Palsbøll, P.J., Bérubé, M., Allendorf, F.W., 2007. Identification of management units Waluda, C.M., Rodhouse, P.G.K., 2005. Dosidicus gigas fishing grounds in the

using population genetic data. Trends Ecol. Evol. 22, 11–16, http://dx.doi.org/ Eastern Pacific as revealed by satellite imagery of the light-fishing fleet. Phuket

10.1016/j.tree.2006.09.003. Mar. Biol. Cent. Res. Bull., 321–328.

Posada, D.J., 2008. ModelTest: phylogenetic model averaging. Mol. Biol. Evol. 25, Waluda, C.M., Yamashiro, C., Rodhouse, P.G., 2006. Influence of the ENSO cycle on

1253–1256, http://dx.doi.org/10.1093/molbev/msn083. the light-fishery for Dosidicus gigas in the Peru Current: an analysis of remotely

Pritchard, J.K., Stephens, M., Donnelly, P., 2000. Inference of population structure sensed data. Fish. Res. 79, 56–63, http://dx.doi.org/10.1016/j.fishres.2006.02.

using multilocus genotype data. Genetics 155, 945–959. 017.

Rocha, F., Guerra, Á., González, Á.F., 2001. A review of reproductive strategies in Williams, G.C., 1975. Sex and Evolution. Princeton University Press, Princeton, N.J.

cephalopods. Biol. Rev. 76, 291–304, http://dx.doi.org/10.1017/ Wing, B.L., 2006. Unsual Invertebrates and Fish Observed in the Gulf of Alaska,

S1464793101005681. 2004–2005. PICES Press 14, 26–28.

Rodhouse, P., Barton, J., Hatfield, E.M., 1995. Illex argentinus: life cycle population Xavier, J.C., Allcock, A.L., Cherel, Y., Lipinski, M.R., Pierce, G.J., Rodhouse, P.G.K.,

structure and fishery. ICES MSS Mar. Sci. Symp. 199, 425–432. Rosa, R., Shea, E.K., Strugnell, J.M., Vidal, E.A.G., Villanueva, R., Ziegler, A., 2014.

Rodhouse, P.G., 2001. Managing and forecasting squid fisheries in variable Future challenges in cephalopod research. J. Mar. Biol. Assoc. U. K. FirstView,

environments. Fish. Res. 54, 3–8, http://dx.doi.org/10.1016/S0165- 1–17, http://dx.doi.org/10.1017/S00253154140 00782.

7836(01) 370-8, Squid Fishery Biology in the Eastern Pacific Coastal Upwelling Yamashiro, C., Mariátegui, L., Rubio, J., Arguelles, J., Tafur, R., Taipe, A., RabI, M.,

System. 1998. Jumbo flying squid fishery in Peru. In: Okutani, T. (Ed.), Large Pelagic

Rogers, A.R., Harpending, H., 1992. Population growth makes waves in the Squid. Japan Marine Fishery Resources Center, Tokyo, pp. 119–125.

distribution of pairwise genetic differences. Mol. Biol. Evol. 9, 552–569. Yokawa, K., 1995. Isozyme comparison of large, medium and small size specimens

Roper, C.F.E., Sweeney, M.J., Nauen, C.E.,1984. Cephalopods of the world. An of Dosidicus gigas. Proc. Res. Conf. Squid Resourc. Fish. Cond. Hachinohe f. y.

annotated and illustrated catalogue of species of interest to fisheries, 43, 277. 1993, 48–52 (in Japanese).

Rosa, R., Seibel, B.A., 2010. Metabolic physiology of the Humboldt squid, Dosidicus

gigas: implications for vertical migration in a pronounced oxygen minimum

zone. Prog. Oceanogr. 86 (1), 72–80, http://dx.doi.org/10.1016/j.pocean.2010. 04.004.