Genetic diversity of mitochondrial DNA from Litopenaeus vannamei broodstock used in northwestern Mexico

 

Diversidad genética del ADN mitocondrial en reproductores de Litopenaeus vannamei utilizados en el noroeste de México

 

Fernando Mendoza-Cano^1,2, José Manuel Grijalva-Chon¹*, Ricardo Pérez-Enríquez³, Josefina Ramos-Paredes^1,4, Alejandro Varela-Romero¹

 

¹ Departamento de Investigaciones Científicas y Tecnológicas, Universidad de Sonora, Av. Colosio s/n, entre Sahuaripa y Reforma, Hermosillo 83000, Sonora, México. *Corresponding author. E-mail: mgrijal@guayacan.uson.mx.

² Laboratorio de Referencia, Análisis y Diagnóstico en Sanidad Acuícola, Centro de Investigaciones Biológicas del Noroeste, Calle Hermosa 101, Col. Los Ángeles, Hermosillo 83106, Sonora, México (permanent address).

³ Centro de Investigaciones Biológicas del Noroeste, Instituto Politécnico Nacional 195, Col. Playa Palo de Santa Rita Sur, La Paz 23096, Baja California Sur, México.

⁴ Laboratorio Especializado de Biología Molecular, Servicio Nacional de Sanidad, Calle Esteban Sarmiento 35, Col. Matanza, Hermosillo 83080, Sonora, México (current address).

 

Received January 2013,
received in revised form June 2013,
accepted July 2013.

 

ABSTRACT

Shrimp cultivation in Mexico is based on the whiteleg shrimp, Litopenaeus vannamei, with a production of about 100,320 t in 2012. Postlarvae are produced in hatcheries, where the selection process is geared towards producing lineages with better productive parameters and resistance to some diseases; however, the crossing of related organisms may reduce genetic variability, resulting in inbreeding depression. In this study we analyzed the sequences of the mitochondrial DNA control region of 425 shrimp from five hatcheries and of 29 wild whiteleg shrimp. The results suggest the presence of two dominant haplotypes in a monophyletic group of organisms used as broodstock and in wild whiteleg shrimp; this finding suggests a common origin. Low levels of genetic variability in some hatcheries highlight the importance of monitoring genetic diversity and supervising breeding programs to prevent loss of haplotypes.

Key words: broodstock, genetic diversity, mitochondrial DNA, Litopenaeus vannamei, sequence analysis.

 

RESUMEN

El cultivo de camarón en México se basa en el camarón blanco, Litopenaeus vannamei, con una producción de aproximadamente 100,320 t en 2012. El suministro de postlarvas proviene de laboratorios de producción cuyo proceso de selección está dirigido a producir linajes con parámetros más productivos y resistencia a ciertas enfermedades; sin embargo, la cruza de organismos emparentados puede reducir la variabilidad genética, dando como resultado una depresión endogámica. En este estudio se analizaron las secuencias de la región control del ADN mitocondrial de 425 camarones procedentes de cinco laboratorios de producción de postlarvas y 29 camarones silvestres. Los resultados evidencian la presencia de dos haplotipos dominantes en un grupo monofilético de los organismos utilizados como reproductores y en los organismos silvestres; este hallazgo sugiere la hipótesis de un origen común. Debido a los bajos valores de variabilidad genética en algunos laboratorios, se resalta la importancia de vigilar la diversidad genética y supervisar los programas de reproducción para evitar la pérdida continua de haplotipos.

Palabras clave: reproductores, diversidad genética, ADN mitocondrial, Litopenaeus vannamei, análisis de secuencias.

 

INTRODUCTION

Penaeid shrimp cultivation contributes 9% of the world's aquaculture production, with a mean annual growth of 18% since the 1970s (Benzie 2009). Its expansion has generated a large demand for hatchery postlarvae produced under controlled conditions. Usually, broodstock selection is based on phenotypic traits to obtain lineages with better production parameters and disease resistance. Artificial selection usually increases mating of closely related organisms, leading to reduced genetic variability and ability to produce viable offspring. Inbreeding can affect survival, growth, and reproductive quality (Sbordoni et al. 1986, 1987; De Donato et al. 2005; Moss et al. 2007). Surveillance of the genetic structure in hatchery facilities is thus very important (Álvarez-Jurado 1987, Benzie and Williams 1996). Breeding programs and management of fishery resources require detailed information of the genetic structure of shrimp populations and its associated diversity (Chu et al. 2003). Benzie (2009) reviewed the most relevant information on genetic resources of penaeid shrimp.

In Mexico, production of cultivated shrimp, mainly Litopenaeus vannamei, during 2012 was 100,320 t, exceeding wild shrimp catches (CONAPESCA 2012). Shrimp farming is mainly concentrated along the coast of the Gulf of California. In this region, commercial hatcheries produce up to 10 billion postlarvae each year to supply shrimp farmers. Mexican producers of shrimp larvae need to understand the genetic variability of their broodstock. Several genetic markers have been used, including allozymes (Ramos-Paredes and Grijalva-Chon 2003, Soto-Hernández and Grijalva-Chon 2004, Rivera-García and Grijalva-Chon 2006) and random amplified polymorphic DNA (RAPD) (Valerio-García and Grijalva-Chon 2008). Perez-Enriquez et al. (2009) analyzed the genetic diversity of broodstock from six commercial hatcheries using microsatellites, and the results showed moderate diversity, major inbreeding, and evidence of a common origin of the broodstock. This study aims to complement that of Perez-Enriquez et al. (2009) by using sequence analysis of the mitochondrial DNA control region of broodstock from five hatcheries to estimate genetic variability and strengthen the hypothesis of a common origin.

 

MATERIALS AND METHODS

Amplifying and sequencing of the mitochondrial DNA control region

Broodstock of 425 shrimp from five hatcheries (A, B, C, E, and F) located in northwestern Mexico were analyzed. Details of their origin and DNA isolation procedures are given in Perez-Enriquez et al. (2009). Additionally, 29 wild whiteleg shrimp reported by Valerio-García and Grijalva-Chon (2008) were analyzed.

DNA primers RV1 (5'-TATAACCGCGGCTGCTGGCAC-3') and FW1 (5'-GGTATGAGCCCACGAGCTTGC-3') were designed from the NC 009626 sequence in GenBank to amplify a 1452 bp segment. The segment partly includes a segment of the 12S rRNA gene, the entire mitochondrial control region, and a portion of the tRNA^met gene. This region extends from base number 14,766 to base number 228 of the NC 009626 sequence. Polymerase chain reactions (PCR) were performed using PuRe Taq Ready-to-Go PCR beads (GE Healthcare Life Sciences, Uppsala, Sweden) with 1 of each primer, 2 (oL DNA extract, and 21 (oL PCR grade water. PCR conditions were an initial denaturation step at 95 °C for 5 min, 35 cycles of 95 °C for 50 s, 60 °C for 50 s, 72 °C for 90 s, and a final extension step at 72 °C for 7 min. The PCR products were visualized on 2% agarose gel (Sigma-Aldrich) prepared with TAE buffer 1* and stained with ethidium bromide (Sigma-Aldrich). A molecular weight marker of 100 bp (Invitrogen10488-058) was used to estimate the size of the obtained products. PCR products were sent to Macrogen in Seoul (Korea) for purification and sequencing in both directions. The sequences were assembled, corrected for ambiguities, and adjusted only to the mitochondrial control region, using ChromasPro v1.41 software (Technelysium, Brisbane, Australia).

Broodstock genetic diversity by sequence analysis

The analysis considered each base position as a locus to record polymorphic sites. Similar to Perez-Enriquez et al. (2009), all individuals within a hatchery were pooled to represent the hatchery's genetic composition and gene diversity. Haplotypes in all samples were identified and their frequencies calculated. Data analysis was performed with Arlequin v3.5 software (Excoffier et al. 2005). Gene and nucleotide diversities were calculated with the same software, and an analysis of molecular variance (AMOVA) was performed. To determine the degree of difference between hatcheries, the FST value between paired samples was calculated, and the exact test, analogous to Fisher's test, was performed using 100,000 Markovchain steps and 10,000 dememorization steps.

Origin of broodstock in Mexico

To determine the origin of L. vannamei broodstock in Mexico and the phylogenetic relationship with wild shrimp populations, PAUP* 4.0b software (Swofford 2002) was used with the complete mitochondrial control region sequences for each haplotype in our samples and those reported in GenBank for this species and other species of the genus.

All sequences were aligned using Clustal X v2.1 (Larkin et al. 2007). For the construction of the phylogenetic relationship between the populations and sequences deposited in GenBank of the same species and other genera of the family, maximum parsimony and maximum likelihood methods were used. We used complete nucleotide sequences for both approaches to obtain the most parsimonious trees that showed the groups or clades within each species, using tree bisection-reconnection (TBR) as the branch swapping search with PAUP*. All characters were equally weighted. Insertions and deletions (indels) were treated as missing and starting trees were obtained by 1000 random stepwise additions. Nodal support was estimated by nonparametric bootstrap (1000 pseudo-replicates, 10 random additions) proportions (Felsenstein 1985) and decay indices (Bremer 1994) using PAUP*. The consensus tree was constructed using PAUP*. We calculated the hierarchical likelihood rate (HLRT; Posada and Buckley 2004) with ModelTest v3.06 (Posada and Crandall 1998) to estimate the optimal model of nucleotide substitution in our maximum likelihood analysis. With this model, we conducted a maximum likelihood search with a branch-swapping algorithm to find the tree topology and greater likelihood values using PAUP*. This tree was used as the initial topology for calculating the nonparametric re-sampling of the data (1000 pseudo-replicates) to estimate the support of the nodes in the maximum likelihood tree. The cladogram was constructed using the FigTree v1.4 software (http://tree.bio.ed.ac.uk/software/figtree/).

 

RESULTS

Thirty-six haplotypes were obtained from the sequence analysis of the samples from five hatcheries and they were registered in GenBank (accession numbers GQ857079 to GQ857122). All sequences were compared with the mitochondrial control region of NC 009626 and comparisons provided 94-99% homology. The length of the sequences fluctuated between 996 and 998 nucleotides because of indels; polymorphic sites ranged between 78 and 114. The wild sample showed the lowest number of polymorphic sites (table 1).

Two haplotypes (H1 and H2) showed high frequency in all samples, with 76% in those from hatchery B and up to 96% in those from hatchery C (table 2). Other haplotypes had very low frequencies and, with the exception of haplotype 29, were distinct to individual hatcheries. Hatchery E samples and the wild sample had the fewest haplotypes (5), and hatchery A samples had the most (15). Hatchery B samples had the highest diversity and hatchery C samples the lowest. Diversity of the wild sample was lower than in the samples from three hatcheries (table 1).

Genetic differentiation analysis, based on the AMOVA, showed that 86% of molecular variance occurs within hatcheries; global F_ST was 0.14, which was significantly different from zero (P < 0.001). Of the 15 paired comparisons, the F_ST analysis showed that 66% were significant, agreeing in general with the exact test. Both tests showed that the wild sample was not different from hatcheries A, E, and F (table 3).

We generated 1109 nucleotide sites in the alignment due to indels, of which 607 were parsimoniously informative, 174 were not informative, and 328 were constant in the analysis. The nucleotide maximum parsimony tree (length = 1683 steps, consistence index = 0.708, retention index = 0.880) and maximum likelihood analysis (length = 8669 steps, evolution model TVM + G) produced trees with highly similar topology. Thus, only the maximum likelihood tree is shown in figure 1. The phylogenetic tree of maximum parsimony and maximum likelihood shows that sequences of cultivated shrimp and the wild shrimp form two groups (one for haplotype H1 and another for haplotype H2), which constitute a distinct clade of our sequences, suggesting a single common ancestor for all broodstock used in northwestern Mexico. The other GenBank sequences of wild L. vannamei (AY845710-AY845715) form a sister clade of the studied group of broodstock, and all result from a single common ancestor and show strong statistical support (100%) for the monophyletic condition. In addition, the clade that includes all penaeids shows a close relationship between the species of the family (fig. 1).

 

DISCUSSION

According to shrimp growers and hatchery managers, the origin of current shrimp strains in Mexico is a batch imported from Venezuela in 1997 that survived a Taura syndrome outbreak (Perez-Enriquez et al. 2009). The analysis carried out by Perez-Enriquez et al. (2009) based on microsatellite allelic composition indicated the recent common origin of the Mexican broodstock. Our study agrees and strengthens the hypothesis of a common ancestor, based on the abundance of two genetically distant haplotypes present in shrimp from all five hatcheries and the high percentage of paired comparisons with no significant differences (F_ST and exact test). The two haplotypes may have increased their frequencies by domestication and selection in Venezuela or even in the founding group in Texas (Sunden and Davis 1991, Perez-Enriquez et al. 2009). The genetic structure of cultivated shrimp and differentiation from wild populations is depicted in the phylogenetic tree, where none of the previously reported sequences in GenBank of wild whiteleg shrimp were included in the cultivated shrimp clade.

In shrimp cultivation, as in livestock programs, breeding individuals that are related or the mismanagement of brood-stock usually causes inbreeding and loss of genetic variability. The detrimental effects of inbreeding on domesticated animals have been widely reported (Goyard et al. 2003, De Donato et al. 2005, Moss et al. 2007). For cultivated shrimp, high inbreeding with respect to wild populations in northwestern Mexico is well known (Ramos-Paredes and Grijalva-Chon 2003, Soto-Hernández and Grijalva-Chon 2004, Perez-Enriquez et al. 2009). Perez-Enriquez et al. (2009) report high inbreeding coefficients at the same hatcheries involved in our study. Their results agree with our findings: low genetic variability, high genetic identity, and low genetic differentiation among the hatcheries. Even though inbreeding cannot be estimated using mtDNA markers, they provide information about genetic diversity. The low diversity of broodstock analyzed in our study, compared with the diversity analyzed by Valles-Jiménez et al. (2006) for wild populations, and the high frequency of two haplotypes indicate that cultivated shrimp from these hatcheries show a combination of founder effect, genetic drift, and selection.

Despite the common origin of the sample lots, diversity varies among hatcheries. Significant differences in F_ST values were found between some paired tests, which may be the result of genetic drift; however, since all samples have the same two very frequent haplotypes, genetic drift would have occurred in a very similar way in all of them, and that can only happen if the original genetic composition of each hatchery was very similar. If the genetic composition had been different, the process of genetic drift would have generated a different haplotype composition among hatcheries. Furthermore, the diversity pattern among hatcheries (those with the maximum and minimum levels) does not coincide with the pattern reported by Perez-Enriquez et al. (2009), possibly because there are differences in the mtDNA and microsatellite evolution rates. The population bottleneck after the outbreak of the Taura syndrome virus in the late 1990s (Perez-Enriquez et al. 2009) could have generated a different population genetic structure in mitochondrial and nuclear genomes because the mitochondrial genome is more prone to be structured than the nuclear genome (Ferris and Berg 1987, Birky et al. 1989). The Hardy-Weinberg disequilibrium could be caused by that bottleneck (Perez-Enriquez et al. 2009). Additionally, the phylogenetic analysis that depicted the cultivated shrimp in a separate clade supports the bottleneck hypothesis.

Contrary to reports on wild populations (Klinbunga et al. 1998, 1999, 2001; McMillen-Jackson and Bert 2003; Valles-Jiménez et al. 2006; Khamnamtong et al. 2009), the wild sample in our study had less diversity than shrimp from some of the hatcheries. This suggests a closer relationship with cultivated shrimp because shrimp escape from farms. Several genetic tools have been used to assess the population genetic structure and diversity of wild and cultivated populations of penaeid shrimp (table 4). The diversity values obtained in our study are not comparable with studies using other analytical tools, as seen by comparing our results with those of Perez-Enriquez et al. (2009). The lack of population studies that consider the complete sequencing of the mitochondrial control region of L. vannamei and other penaeids makes it difficult to assess genetic diversity values of whiteleg shrimp. McMillen-Jackson and Bert (2003) obtained data on nucleotide diversity from wild populations of Farfantepenaeus aztecus and Litopenaeus setiferus, but only from a fraction of the mitochondrial control region (541 and 499 bp, respectively), resulting in average values of 2.8% and 2.1%, respectively, which are close to the average values of 2.6% obtained in our study. Kumar et al. (2007) reported an average of 3.4% for a fraction of 577 bp of the mitochondrial control region of wild Penaeus monodon, with values as high as 5.4% for one of the populations in India. The values reported by Kumar et al. (2007) are high, considering that we analyzed the entire control region and the maximum value obtained was 3.2%. Since the whiteleg shrimp come from a long, artificial selection process, this inevitably leads to declining diversity.

In spite of our estimates of reduced genetic diversity and the high inbreeding reported by Soto-Hernández and Grijalva-Chon (2004) and Perez-Enriquez et al. (2009), there is no evidence of inbreeding depression in shrimp cultivated in Mexico, given the sustained growth of the industry, from 45,000 t in 2000 to 133,282 t in 2009 (CONAPESCA 2010, 2011). However, this dynamic growth has declined in recent years (109,815 t in 2011 and 100,320 t in 2012), caused mainly by viral outbreaks (white spot syndrome), particularly in the state of Sonora (Aquaculture Health Committee of the State of Sonora, pers. comm.; CONAPESCA 2012). Among the farming practices that need to be improved is the management of genetic diversity in hatcheries. The recommendation for this is to enrich the gene pool of broodstock through the exchange of pathogen-free shrimp from hatcheries that maintain lineages other than those reported herein, at a rate that does not affect overall performance and following strict reproduction control to avoid inbreeding in future generations.

 

ACKNOWLEDGMENTS

This research was funded by Consejo Nacional de Ciencia y Tecnología (CONACYT, Mexico, research project 2006-60030 to RPE). FMC was a recipient of a graduate fellowship from CONACYT (No. 208901). Thanks are due to the commercial hatcheries that provided the samples, and to Jorge Hernández-López, Daniel Coronado-Molina, Trinidad Encinas-García, and Arturo Sánchez-Paz at CIBNOR (Hermosillo) for technical support. Ira Fogel (CIBNOR, La Paz) provided English editing services.

 

REFERENCES

Álvarez-Jurado A. 1987. Genética y acuacultura. In: Espinosa J, Labarta U (eds.), Genética en Acuacultura. Industrias Gráficas España, Madrid, pp. 1-31.         [ Links ]

Benzie JAH. 2009. Use and exchange of genetic resources of penaeid shrimps for food and aquaculture. Rev. Aquaculture 1: 232-250. http://dx.doi.org/10.1111/j.1753-5131.2009.01018.x        [ Links ]

Benzie JAH, Williams ST. 1996. Limitations in the genetic variation of hatchery produced batches of the giant clam, Tridacna gigas. Aquaculture 139: 225-241. http://dx.doi.org/10.1016/0044-8486(95)01171-4        [ Links ]

Benzie JAH, Ballment E, Frusher S. 1993. Genetic structure of Penaeus monodon in Australia: Concordant results from mtDNA and allozymes. Aquaculture 111: 89-93. http://dx.doi.org/10.1016/0044-8486(93)90027-V        [ Links ]

Benzie JAH, Ballment E, Forbes AT, Demetriades NT, Sugama K, Haryanti, Moria S. 2002. Mitochondrial DNA variation in Indo-Pacific populations of the giant tiger prawn, Penaeus monodon. Mol. Ecol. 11: 2553-2559. http://dx.doi.org/10.1046/j.1365-294X.2002.01638.x        [ Links ]

Birky CW Jr, Fuerst P, Maruyama T. 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: 613-627.         [ Links ]

Bremer K. 1994. Branch support and tree stability. Cladistics 10: 295-304. http://dx.doi.org/10.1006/clad.1994.1019        [ Links ]

Chu KH, Li CP, Tam YK, Lavery S. 2003. Application of mitochondrial control region in population genetic studies of the shrimp Penaeus. Mol. Ecol. Notes 3: 120-122. http://dx.doi.org/10.1046/j.1471-8286.2003.00376.x        [ Links ]

CONAPESCA 2010. Anuario Estadístico de Acuacultura y Pesca. Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación. Comisión Nacional de Pesca y Acuacultura, Mexico City, http://www.conapesca.sagarpa.gob.mx/wb/cona/cona_anuario_estadistico_de_pesca.         [ Links ]

CONAPESCA 2011. Anuario Estadístico de Acuacultura y Pesca. Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación. Comisión Nacional de Pesca y Acuacultura, Mexico City, http://www.conapesca.sagarpa.gob.mx/wb/cona/cona_anuario_estadistico_de_pesca.         [ Links ]

CONAPESCA 2012. Anuario Estadístico de Acuacultura y Pesca. Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación. Comisión Nacional de Pesca y Acuacultura, Mexico City, http://www.conapesca.sagarpa.gob.mx/wb/cona/cona_anuario_estadistico_de_pesca.         [ Links ]

De Donato M, Manrique R, Ramirez R, Mayer L, Howell C. 2005. Mass selection and inbreeding effects on a cultivated strain of Penaeus (Litopenaeus) vannamei in Venezuela. Aquaculture 247: 159-167. http://dx.doi.org/10.1016/j.aquaculture.2005.02.005        [ Links ]

Dixon TJ, Coman GJ, Arnold SJ, Sellars MJ, Lyons RE, Dierens L, Preston NP, Li Y. 2008. Shifts in genetic diversity during domestication of black tiger shrimp, Penaeus monodon, monitored using two multiplexed microsatellite systems. Aquaculture 283: 1-6. http://dx.doi.org/10.1016/j.aquaculture.2008.07.009        [ Links ]

Excoffier L, Laval G, Schneider S. 2005. Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evol. Bioinformatics 1: 47-50.         [ Links ]

Felsenstein J. 1985. Confidence limits on phylogenies: An approach using the bootstrap. Evolution 39: 783-791. http://dx.doi.org/10.2307/2408678        [ Links ]

Ferris SD, Berg WJ. 1987. The utility of mitochondrial DNA in fish genetics and fishery management. In: Ryman N, Utter F (eds.), Population Genetics and Fishery Management. University of Washington Press, Seattle, pp. 277-299.         [ Links ]

Francisco AK, Galetti PM Jr. 2005. Genetic distance between broodstocks of the marine shrimp Litopenaeus vannamei (Decapoda, Penaeidae) by mtDNA analysis. Genet. Mol. Biol. 28: 258-261. http://dx.doi.org/10.1590/S1415-47572005000200014        [ Links ]

Freitas PD, Galetti PM Jr. 2002. PCR-based VNTR core sequence analysis for inferring genetic diversity in the shrimp Litopenaeus vannamei. Genet. Mol. Biol. 4: 431-434. http://dx.doi.org/10.1590/S1415-47572002000400012        [ Links ]

Freitas P, Galetti PM Jr. 2005. Assessment of the genetic diversity in five generations of a commercial broodstock line of Litopenaeus vannamei shrimp. Afr. J. Biotechnol. 12: 1362-1367.         [ Links ]

García DK, Faggart MA, Rhoades L, Alcivar-Warren A. 1994. Genetic diversity of cultured Penaeus vannamei shrimp using three molecular genetic techniques. Mol. Mar. Biol. Res. 5: 270-280.         [ Links ]

Goyard E, Arnaud S, Vonau V, Bishoff V, Mouchel O, Pham D. 2003. Residual genetic variability in domesticated populations of the Pacific blue shrimp (Litopenaeus stylirostris) of New Caledonia, French Polynesia and Hawaii and some management recommendations. Aquat. Living Resour. 16: 501-508. http://dx.doi.org/10.1016/j.aquliv.2003.07.001        [ Links ]

Hidalgo-de la Toba JA. 2007. Evaluación de la diversidad genética en el camarón blanco (Litopenaeus vannamei) en granjas de cultivo de Nayarit, México, mediante análisis de RFLP de la región control del ADNmt. BSc thesis, Universidad Autónoma de Baja California Sur, La Paz, BCS, México. 60 pp.         [ Links ]

Khamnamtong B, Klinbunga S, Menasveta P. 2009. Genetic diversity and geographic differentiation of the giant tiger shrimp (Penaeus monodon) in Thailand analyzed by mitochondrial COI sequences. Biochem. Genet. 47: 42-55. http://dx.doi.org/10.1007/s10528-008-9205-3        [ Links ]

Klinbunga S, Penman DJ, McAndrew BJ. 1998. A preliminary study of ribosomal DNA polymorphism in the tiger shrimp Penaeus monodon. J. Mar. Biotechnol. 6: 186-188.         [ Links ]

Klinbunga S, Penman DJ, McAndrew BJ, Tassanakajon A. 1999. Mitochondrial DNA diversity in three populations of the giant tiger shrimp Penaeus monodon. Mar. Biotechnol. 1 : 113-121. http://dx.doi.org/10.1007/PL00011758        [ Links ]

Klinbunga S, Siludjai D, Wudthijinda W, Tassanakajon A, Jarayabhand P, Menasveta P. 2001. Genetic heterogeneity of the giant tiger shrimp (Penaeus monodon) in Thailand revealed by RAPD and mitochondrial DNA RFLP analyses. Mar. Biotechnol. 3: 428-438. http://dx.doi.org/10.1007/s10126-001-0055-9        [ Links ]

Klinbunga S, Preechaphol R, Thumrungtanakit S, Leelatanawit R, Aoki T, Jarayabhand P, Menasveta P. 2006. Genetic diversity of the giant tiger shrimp (Penaeus monodon) in Thailand revealed by PCR-SSCP of polymorphic EST-derived markers. Biochem. Genet. 44: 222-236. http://dx.doi.org/10.1007/s10528-006-9027-0        [ Links ]

Kumar N, Lakra WS, Majumdar KC, Goswami M, Kondadhasula R. 2007. Genetic diversity in the Indian population of Penaeus monodon (Fabricius 1798) as revealed by mtDNA sequence analysis. Aquacult. Res. 38: 862-869. http://dx.doi.org/10.1111/j.1365-2109.2007.01740.x        [ Links ]

Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG. 2007. Clustal W and Clustal X version 2.0. Bioinformatics 23: 2947-2948. http://dx.doi.org/10.1093/bioinformatics/btm404        [ Links ]

Lavery S, Chan TY, Tam YK, Chu KH. 2004. Phylogenetic relationships and evolutionary history of the shrimp genus Penaeus s.I. derived from mitochondrial DNA. Mol. Phylogenet. Evol. 31: 39-49. http://dx.doi.org/10.10167j.ympev.2003.07.015        [ Links ]

Lima APS, Lira dos Santos AC, Dantas HL, Gomes-Filho MA, Maggioni R, Moura-Coimbra MR. 2008. Genetic monitoring of broodstock of the marine shrimp Litopenaeus vannamei in a closed rearing system in Pernambuco, Brazil. Aquacult. Res. 39: 1461-1466. http://dx.doi.org/10.1111/j.1365-2109.2008.02022.x        [ Links ]

Luvesuto E, Freitas PD, Galetti Jr PM. 2007. Genetic variation in a closed line of the white shrimp Litopenaeus vannamei (Penaeidae). Genet. Mol. Biol. 30: 1156-1160. http://dx.doi.org/10.1590/S1415-47572007000600021        [ Links ]

Machado-Tamayo RJ. 2006. Assessment of genetic variability in two lots of white shrimp, Litopenaeus vannamei (Boone 1931) introduced to Cuba. MSc thesis, Norwegian College of Fishery Science, University of Troms0, Norway, 42 pp.         [ Links ]

McMillen-Jackson AL, Bert TM. 2003. Disparate patterns of population genetic structure and population history in two sympatric penaeid shrimp species (Farfantepenaeus aztecus and Litopenaeus setiferus) in the eastern United States. Mol. Ecol. 12: 2895-2905. http://dx.doi.org/10.1046/j.1365-294X.2003.01955.x        [ Links ]

Moss DR, Arce SM, Otoshi CA, Doyle RW, Moss SM. 2007. Effects of inbreeding on survival and growth of Pacific white shrimp Penaeus (Litopenaeus) vannamei. Aquaculture 272: 30-37. http://dx.doi.org/10.1016/j.aquaculture.2007.08.014        [ Links ]

Perez-Enriquez R, Hernández-Martínez F, Cruz P. 2009. Genetic diversity status of white shrimp Penaeus (Litopenaeus) vannamei broodstock in Mexico. Aquaculture 297: 44-50. http://dx.doi.org/10.1016/j.aquaculture.2009.08.038        [ Links ]

Posada D, Buckley TR. 2004. Model selection and model averaging in phylogenetics: Advantages of the AIC and Bayesian approaches over likelihood ratio tests. Syst. Biol. 53: 793-808. http://dx.doi.org/10.1080/10635150490522304        [ Links ]

Posada D, Crandall KA. 1998. Modeltest: Testing the model of DNA substitution. Bioinformatics 14: 817-818. http://dx.doi.org/10.1093/bioinformatics/14.9.817        [ Links ]

Ramos-Paredes J, Grijalva-Chon JM. 2003. Allozyme genetic analysis in hatchery strains and wild blue shrimp, Penaeus (Litopenaeus) stylirostris (Stimpson), from the Gulf of California. Aquacult. Res. 34: 221-234. http://dx.doi.org/10.1046/j.1365-2109.2003.00807.x        [ Links ]

Rivera-García M, Grijalva-Chon JM. 2006. Genetic variability and differentiation in cultured white shrimp Penaeus (Litopenaeus) vannamei with low and high growth. Cienc. Mar. 32: 1-11.         [ Links ]

Sbordoni V, de Matthaeis E, Cobolli-Sbordoni M, La Rosa G, Mattocia M. 1986. Bottleneck effects and the depression of genetic variability in hatchery stocks of Penaeus japonicus (Crustacea, Decapoda). Aquaculture 57: 239-251. http://dx.doi.org/10.1016/0044-8486(86)90202-4        [ Links ]

Sbordoni V, La Rosa G, Mattocia M, Cobolli-Sbordoni M, de Matthaeis E. 1987. Genetic changes in seven hatchery stocks of the kuruma prawn, Penaeus japonicus (Crustacea, Decapoda). Proc. World Symp. on Selection, Hybridization and Genetic Engineering in Aquaculture, Bordeaux, 27-30 May 1986.         [ Links ]

Soto-Hernández J, Grijalva-Chon JM. 2004. Genetic differentiation in hatchery strains and wild white shrimp Penaeus (Litopenaeus) vannamei (Boone 1931) from northwest Mexico. Aquacult. Int. 12: 593-601. http://dx.doi.org/10.1007/s10499-004-5750-x        [ Links ]

Sunden SLF, Davis SK. 1991. Evaluation of genetic variation in a domestic population of Penaeus vannamei (Boone): A comparison with three natural populations. Aquaculture 97: 131-142. http://dx.doi.org/10.1016/0044-8486(91)90260-E        [ Links ]

Swofford DL. 2002. PAUP* 4.0: Phylogenetic Analysis Using Parsimony (and other methods) 4.0 Beta. Sinauer Associates, Sunderland, Massachussets, http://www.sinauer.com/paupphylogenetic-analysis-using-parsimony-and-other-methods-4-0-beta.html.         [ Links ]

Tsoi KH, Chan TY, Chu KH. 2007. Molecular population structure of kuruma shrimp Penaeus japonicus species complex in western Pacific. Mar. Biol. 150: 1345-1364 http://dx.doi.org/10.1007/s00227-006-0426-x        [ Links ]

Valerio-García RC, Grijalva-Chon JM. 2008. Random-amplified polymorphic DNA analysis in hatchery populations and wild Pacific white shrimp Penaeus vannamei from the Gulf of California. Aquacult. Res. 39: 666-669. http://dx.doi.org/10.1111/j.1365-2109.2008.01909.x        [ Links ]

Valles-Jiménez R, Gaffney PM, Perez-Enriquez R. 2006. RFLP analysis of the mtDNA control region in white shrimp (Litopenaeus vannamei) populations from the eastern Pacific. Mar. Biol. 148: 867-873. http://dx.doi.org/10.1007/s00227-005-0122-2        [ Links ]