AMOVA design and results in 11 locations of
The mud crab (Scylla paramamosain) is a commercially important species for aquaculture and fisheries in China. In this study, a total of 302 polymorphic microsatellite markers have been isolated and characterized. The observed and expected heterozygosity ranged from 0.04 to 1.00 and from 0.04 to 0.96 per locus. The wild populations distributed along South-eastern China coasts showed high genetic diversity (HO ranged from 0.62 to 0.77) and low genetic differentiation (FST = 0.018). Meanwhile, a significant association (r2 = 0.11) was identified between genetic and geographic distance of 11 locations. Furthermore, a PCR-based parentage assignment method was successfully developed using seven polymorphic microsatellite loci that could correctly assign 95% of the progeny to their parents. Moreover, three polymorphic microsatellite loci were identified to be significantly associated with 12 growth traits of S. paramamosain, and four genotypes were considered to be great potential for marker-assisted selection. Finally, a first preliminary genetic linkage map with 65 linkage groups and 212 molecular markers was constructed using microsatellite and AFLP markers for S. paramamosain. This map was 2746 cM in length, and covered approximately 50% of the estimated genome. This study provides novel insights into genome biology and molecular marker-assisted selection for S. paramamosain.
- genetic linkage map
- growth traits linked loci
- microsatellite marker
- parentage assignment
- population genetic diversity
The mud crab (
Microsatellites, normally known as simple sequence repeats (SSR), are widely used for population structure analysis [3, 4], parentage assignment , genetic map construction [6, 7], and marker-assisted selection [8, 9] because they are abundantly distributed throughout genome, codominant, and hyper-variable in most eukaryotic organism genomes. Before this study, there were only 15 polymorphic microsatellite loci available for
The purpose of this study is to massively develop polymorphic microsatellite markers, uncover the population genetic diversity, create molecular parentage assignment technique, identify growth performance-associated markers, and construct a genetic linkage map, so as to provide novel insights into population genetic diversity and genetic improvement of economic traits for
2. Microsatellites and their application in population genetics and MAS
2.1. Material and methods
For microsatellite loci isolation, a total of six different strategies based on PIMA , FIASCO , GenBank-derived genes , 5’ anchored PCR , cDNA library , and 454 sequencing transcriptome [17, 18] have been employed to isolate microsatellite markers. The polymorphisms of microsatellite loci were evaluated by using a wild population with approximately 30 individuals.
For population genetics analysis, a total of 397 wild individuals were sampled from 11 locations (Sanmen, Ningde, Zhangzhou, Shantou, Shenzhen, Zhanjiang, Haikou, Wenchang, Wanning, Dongfang, and Danzhou) of South-eastern coasts of China. Nine polymorphic microsatellite markers were genotyped in these specimens .
For development of parentage assignment technique, four G1 families were collected, with 46 progenies in each family. Family 1 lost both parents information, and families 2, 3, and 4 only had maternal information. Ten polymorphic microsatellite loci were selected for genotyping the above crabs .
For trait-marker association analysis, a total of 96 three-month-old full-sib specimens were randomly sampled from a G1 family. Sixteen growth traits including carapace length (CL), internal carapace width (ICW), carapace width (CW), body height (BH), carapace frontal width (CFW), carapace width at spine 8 (CWS8), abdomen width (AW), fixed finger length of the claw (FFLC), fixed finger width of the claw (FFWC), fixed finger height of the claw (FFHC), distance between lateral spine 1 (DLS1), distance between lateral spine 2 (DLS2), meropodite length of pereiopod 1 (MLP1), meropodite length of pereiopod 2 (MLP2), meropodite length of pereiopod 3 (MLP3), and body weight (BW) were measured. Moreover, 129 transcriptome-derived polymorphic microsatellite loci were genotyped in these animals .
For genetic linkage map construction, a G1 family with 95 individuals was selected as mapping population. Microsatellite and AFLP markers were employed for linkage analysis. A total of 337 polymorphic microsatellite markers and 64 AFLP selective primer combinations were used in this study .
For data analysis, the observed (
2.2. Results and discussion
2.2.1. Isolation and characterization of microsatellite loci
In this study, a total of 302 polymorphic microsatellite markers were successfully developed by using six different strategies. For methods based on PIMA, FIASCO, GenBank-derived genes, 5’ anchored PCR, cDNA library, and 454 sequencing transcriptome, a total of 12, 54, 18, 18, 36, and 164 polymorphic microsatellite loci were identified, respectively. A total of 1858 alleles were detected with an average of 6.15 alleles per locus from these microsatellite markers. The observed and expected heterozygosity ranged from 0.04 to 1.00, and from 0.04 to 0.96 per locus, respectively. The genotype proportions at 45 microsatellite loci significantly deviated from Hardy-Weinberg equilibrium expectations after Bonferroni correction; this could be due to the small sample size or the presence of null alleles, but cannot be attributed to technical or statistical artifacts. No significant linkage disequilibrium was detected between these loci pairs. According to the utilities for comparative mapping, molecular markers are classified into two types: type I markers are linked with genes of known functions, while type II markers are linked with anonymous genomic fragments. Among these 302 microsatellite loci, 218 may be associated with functional genes, which were classified as type I markers that are usually considered to have lower polymorphic level than type II markers. In this study, the genetic diversity level of type I loci was slightly lower than that of genome-derived loci too. Moreover, the polymorphisms of type II loci isolated in this study were lower than those described in previous references [10, 11].
2.2.2. Population genetic diversity and differentiation
The population genetic diversity of
Approximately 98.2% of variance was within locations and 1.8% of that was among locations, which indicated that the population genetic variation mainly existed within locations, and the genetic differentiation level was very low among locations (Table 1).
|Source of variation||Sum of squares||Variance components||Percentage of variation|
|Among individuals within
The mtDNA data also indicated that the population genetic structure of this crab was genetically homogeneous . Therefore, we concluded that
2.2.3. Parentage assignment technique based on PCR
In this study, 10 polymorphic microsatellite loci produced 1870 genotypes in 184 offspring and three parents. The genetic diversity indexes showed a relative high variation of these individuals, with
Furthermore, the exclusion probability was used to distinguish the pedigree relationship of
2.2.4. Identification of growth performance related microsatellite markers
In aquatic animals, a set of microsatellite markers were identified to link to growth traits [40, 41]. In this study, of 129 polymorphic microsatellite loci, 30 showed polymorphisms in the experimental G1 family. Statistical analysis indicated that three markers (Scpa36, Scpa75, and Spm30) were significantly linked to 12 growth traits (CL, BH, ICW, AW, FFWC, FFLC, FFHC, CWS8, MLP2, MLP3, DLS2, and BW) in
|Locus||Genotype||Number||Growth trait (Means ± SD, mm)|
|Scpa36||AB||19||47.87 ± 7.88a||23.85 ± 3.62a||28.37 ± 3.96a||43.98 ± 7.34a||11.80 ±
|17.10 ± 3.37a||26.58 ± 3.72a||21.88 ± 2.88a|
|BB||21||49.80 ± 7.85ab||24.48 ± 4.08ab||28.97 ± 4.68a||46.90 ± 9.20ab||13.01 ± 3.14ab||18.65 ± 4.39ab||27.29 ± 4.71ab||22.98 ± 4.33ab|
|AC||23||52.50 ± 8.83ab||26.20 ± 4.86ab||30.73 ± 5.36ab||49.79 ± 9.72ab||14.07 ±
|19.99 ± 4.86ab||28.70 ± 5.30ab||24.73 ± 3.98bc|
|BC||21||54.46 ± 5.012_1||27.08 ± 2.75b||32.21 ± 3.10b||52.37 ± 7.57b||14.39 ±
|21.01 ± 4.29b||30.45 ± 3.36b||25.75 ± 2.64c|
|Locus||Genotype||Number||Growth trait (Means ± SD, mm)|
|Scpa75||AD||32||69.79 ± 11.83a||24.10 ± 4.20a||71.90 ± 12.50a||43.45 ± 7.18a||22.45 ± 4.20a|
|AC||17||74.70 ± 11.75a||24.98 ± 3.75a||77.03 ± 12.06a||46.65 ± 6.50ab||24.63 ± 3.83a|
|BD||24||76.82 ± 9.99a||26.85 ± 4.32a||79.15 ± 10.16a||47.21 ± 5.28ab||24.54 ± 3.52a|
|BC||14||77.59 ± 7.34a||26.45 ± 2.65a||80.00 ± 7.74a||48.69 ± 4.30b||25.51 ± 2.83a|
Among 16 growth traits tested in this study, traits AW and MLP3 were associated with two loci Scpa36 and Scpa75, and traits BH and DLS2 were associated with two loci Scpa75 and Spm30. Meanwhile, traits CL, FFWC, FFLC, ICW, MLP2, BW, and CWS8 were associated with only one microsatellite locus. It is considered to be a common event that one locus contributes to several quantitative traits and/or several different loci influence a same quantitative trait [41, 42]. In the next artificial breeding program, these three microsatellite markers should be first considered for marker-assisted selection of
|Locus||Genotype||Number||Growth trait (Means ± SD, mm)|
|Spm30||CD||18||27.34 ± 4.47a||42.13 ± 7.28a||57.72 ± 31.66a|
|AB||24||29.52 ± 5.24ab||44.78 ± 7.07ab||79.68 ± 38.73b|
|BD||33||30.88 ± 4.22b||47.28 ± 5.30b||89.53 ± 32.98b|
|AC||21||31.08 ± 3.58b||47.54 ± 4.25b||92.99 ± 31.06b|
2.2.5. Construction of genetic linkage map
Of 337 microsatellite markers, 118 segregated from parents to offspring of
A first preliminary genetic linkage map was developed for
This study isolated and characterized 302 polymorphic microsatellite markers for the mud crab (
This work was supported by the Top-Notch Young Talents Program of China, the National Natural Science Foundation of China (Grant No. 31001106), and the Fund of Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture, China (Grant No. 2013-SDMFMA-KF-5).
Shen Y, Lai Q. Present status of mangrove crab ( Scylla serrata(Forskål)) culture in China. The ICLARM Quarterly. 1994; 17: 28–29.
Fishery Bureau of Ministry of Agriculture of China. China Fisheries Yearbook (2014). Beijing: Chinese Agricultural Press. 2015; 219 p.
Ma HY, Bi JZ, Shao CW, Chen Y, Miao GD, Chen SL. Development of 40 microsatellite markers in spotted halibut ( Verasper variegatus) and the cross-species amplification in barfin flounder ( Verasper moseri). Animal Genetics. 2009; 40: 576–578. DOI: 10.111/j.1365-2052.2009.01869.x
Hughes JM, Schmidt DJ, Huey JA, Real KM, Espinoza T, McDougall A, Kind PK, Brooks S, Roberts DT. Extremely low microsatellite diversity but distinct population structure in a long-lived threatened species, the Australian lungfish Neoceratodus forsteri(Dipnoi). Plos One. 2015; 10: e0121858. DOI: 10.1371/journal.pone.0121858
Bai X, Huang S, Tian X, Cao X, Chen G, Wang W. Genetic diversity and parentage assignment in Dojo loach, Misgurnus anguillicaudatusbased on microsatellite markers. Biochemical Systematics and Ecology. 2015; 61: 12–18. DOI: 10.1016/j.bse.2015.05.005
Ma HY, Chen SL, Yang JF, Chen SQ, Liu WH. Genetic linkage maps of barfin flounder ( Verasper moseri) and spotted halibut ( Verasper variegatus) based on AFLP and microsatellite markers. Molecular Biology Reports. 2011; 38: 4749–4764. DOI: 10.1007/s11033-010-0612-2
Nietlisbach P, Camenisch G, Bucher T, Slate J, Keller LF, Postma E. A microsatellite-based linkage map for song sparrows ( Melospiza melodia). Molecular Ecology Resources. 2015; 15: 1486–1496. DOI: 10.1111/1755-0998.12414
Ibitoye DO, Akin-Idowu PE. Marker-assisted-selection (MAS): A fast track to increase genetic gain in horticultural crop breeding. African Journal of Biotechnology. 2010; 9: 8889–8895. DOI: 10.5897/AJB2010.000-3318
Chen SL, Ji XS, Shao CW, Li WL, Yang JF, Liang Z, Liao XL, Xu GB, Xu Y, Song WT. Induction of mitogynogenetic diploids and identification of WW super-female using sex-specific SSR markers in half-smooth tongue sole ( Cynoglossus semilaevis). Marine Biotechnology. 2012; 14: 120–128. DOI: 10.1007/s10126-011-9395-2
Takano M, Barinova A, Sugaya T, Obata Y, Watanabe T, Ikeda M, Taniguchi N. Isolation and characterization of microsatellite DNA markers from mangrove crab, Scylla paramamosain. Molecular Ecology Notes. 2005; 5: 794–795. DOI: 10.1111/j.1471-8286.2005.01065.x
Xu XJ, Wang GZ, Wang KJ, Li SJ. Isolation and characterization of ten new polymorphic microsatellite loci in the mud crab, Scylla paramamosain. Conservation Genetics. 2009; 10: 1877–1878. DOI: 10.1007/s10592-009-9843-y
Ma HY, Ma CY, Ma LB, Cui HY. Novel polymorphic microsatellite markers in Scylla paramamosainand cross-species amplification in related crab species. Journal of Crustacean Biology. 2010; 30: 441–444. DOI: 10.1651/09-3263.1
Ma HY, Ma CY, Ma LB, Zhang FY, Qiao ZG. Isolation and characterization of 54 polymorphic microsatellite markers in Scylla paramamosainby FIASCO approach. Journal of the World Aquaculture Society. 2011; 42: 591–597. DOI: 10.1111/j.1749-7345.2011.00503.x
Ma HY, Ma CY, Ma LB. Identification of type I microsatellite markers associated with genes and ESTs in Scylla paramamosain. Biochemical Systematics and Ecology. 2011; 39: 371–376. DOI: 10.1016/j.bse.2011.05.007
Cui HY, Ma HY, Ma LB. Development of eighteen polymorphic microsatellite markers in Scylla paramamosainby 5’ anchored PCR technique. Molecular Biology Reports. 2011; 38: 4999–5002. DOI: 10.1007/s11033-010-0645-6
Ma CY, Ma HY, Ma LB, Jiang KJ, Zhang FY, Song W. Isolation and characterization of polymorphic microsatellite loci from cDNA library of Scylla paramamosain. African Journal of Biotechnology. 2011; 10: 11142–11148. DOI: 10.5897/AJB11.973
Ma HY, Jiang W, Liu P, Feng NN, Ma QQ, Ma CY, Li SJ, Liu YX, Qiao ZG, Ma LB. Identification of transcriptome-derived microsatellite markers and their association with the growth performance of the mud crab ( Scylla paramamosain). Plos One. 2014; 9: e89134. DOI:10.1371/journal.pone.0089134
Ma HY, Ma CY, Li SJ, Jiang W, Li XC, Liu YX, Ma LB. Transcriptome analysis of the mud crab ( Scylla paramamosain) by 454 deep sequencing: assembly, annotation, and marker discovery. Plos One. 2014; 9: e102668. DOI: 10.1371/journal.pone.0102668
Ma HY, Cui HY, Ma CY, Ma LB. High genetic diversity and low differentiation in mud crab ( Scylla paramamosain) along the southeastern coast of China revealed by microsatellite markers. The Journal of Experimental Biology. 2012; 215: 3120–3125. DOI: 10.1242/jeb.071654
Ma QQ, Ma HY, Chen JH, Ma CY, Feng NN, Xu Z, Li SJ, Jiang W, Qiao ZG, Ma LB. Parentage assignment of the mud crab ( Scylla paramamosain) based on microsatellite markers. Biochemical Systematics and Ecology. 2013; 49: 62–68. DOI: 10.1016/j.bse.2013.03.013
Ma HY, Li SJ, Feng NN, Ma CY, Wang W, Chen W, Ma LB. First genetic linkage map for the mud crab ( Scylla paramamosain) constructed using microsatellite and AFLP markers. Genetics and Molecular Research. 2016; 15: gmr.15026929. DOI: http://dx.doi.org/10.4238/gmr.15026929
Yeh FC, Yang RC, Boyle T. POPGENE version 1.31. Microsoft window-based freeware for population genetic analysis. 1999. Available from: http://www.ualberta.ca/~fyeh/.
Excoffier L, Laval G, Schneider S. ARLEQUIN (version 3.0): an integrated software package for population genetics data analysis. Evolutionary Bioinformatics. 2005; 1: 47–50.
Rice WR. Analyzing tables of statistical tests. Evolution. 1989; 43: 223–225. DOI: 10.2307/2409177
Van OCW, Hutchinson WF, Wills DPM, Shipley P. MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes. 2004; 4: 535–538. DOI: 10.1111/j.1471-8286.2004.00684.x
Peakall R, Smouse PE. GENALEX 6: genetic analysis in excel. Population genetic software for teaching and research. Molecular Ecology Notes. 2006; 6: 288–295. DOI: 10.1111/j.1471-8286.2005.01155.x
Tamura K, Dudley J, Nei M, Kumar S. MEGA 4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Molecular Biology and Evolution. 2007; 24: 1596–1599. DOI: 10.1093/molbev/msm092
Mantel N. The detection of disease clustering and a generalized regression approach. Cancer Research. 1967; 27: 209–220.
Kalinowski ST, Taper ML, Marshall TC. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology. 2007; 16: 1099–1106. DOI: 10.1111/j.1365-294X.2007.03089.x
Van OJW. JoinMap 3.0: software for the calculation of genetic linkage maps. Plant Research International. 2001. Wageningen, the Netherlands.
Voorrips RE. MapChart: software for the graphical presentation of linkage maps and QTLs. Journal of Heredity. 2002; 93: 77–78. DOI: 10.1093/jhered/93.1.77
Fishman L, Kelly AJ, Morgan E, Willis JH. A genetic map in the Mimulus guttatusspecies complex reveals transmission ratio distortion due to heterospecific interactions. Genetics. 2001; 159: 1701–1716.
Chakravarti A, Lasher LK, Reefer JE. A maximum likelihood method for estimating genome length using genetic linkage data. Genetics. 1991; 128: 175–182.
Lu XP, Ma LB, Qiao ZG, Zhang FY, Ma CY. Population genetic structure of Scylla paramamosainfrom the coast of the Southeastern China based on mtDNA COI sequence. Journal of Fisheries of China. 2009; 33: 15–23. DOI: 10.3724/SP.J.00001 (In Chinese with English abstract)
Nei M. Melecular Evolutionary Genetics. New York, Columbia University. 1987.
Avise J. Phylogeography. Cambridge, MA: Harvard University Press. 1998.
He L, Zhang A, Weese D, Zhu C, Jiang C, Qiao Z. Late Pleistocene population expansion of Scylla paramamosainalong the coast of China: a population dynamic response to the last interglacial sea level highstand. Journal of Experimental Marine Biology and Ecology. 2010; 385: 20–28. DOI: 10.1016/j.jembe.2010.01.019
Zhang YG, Li DQ, Rao LQ, Xiao QM, Liu D. Identification of polymorphic microsatellite DNA loci and paternity testing of Amur tigers. Acta Zoologica Sinica. 2003; 49: 118–123. (In Chinese with English Abstract)
Zhang ZH, Sen FJ, Sun S, David VA, Zhang AJ, O’Brien SJ. Paternity assignment of giant panda by microsatellite genotyping. Hereditas. 2003; 25: 504–510. DOI: 10.3321/j.issn:0253-9772.2003.05.002 (In Chinese with English Abstract)
Yang J, Zhang XF, Chu ZY, Sun XW. Correlation analysis of microsatellite markers with body weight, length, height and upper jaw length wensize of common carp ( Cyprinus carpioL.). Journal of Fishery Sciences of China. 2010; 17: 721–730. (In Chinese with English Abstract)
Liu L, Li J, Liu P, Zhao FZ, Gao BQ, Du Y, Ma CY. Correlation analysis of microsatellite DNA markers with growth related traits of swimming crab ( Portunus trituberculatus). Journal of Fisheries of China. 2012; 36: 1034–1041. DOI: 10.3724/SP.J.1231.2012.27872 (In Chinese with English abstract)
Li XH, Bai JJ, Ye X, Hu YC, Li SJ, Yu LY. Polymorphisms in the 5’ flanking region of the insulin-like growth factor I gene are associated with growth traits in largemouth bass Micropterus salmoides. Fisheries Science. 2009; 75: 351–358. DOI: 10.1007/s12562-008-0051-3
Liebhard R, Koller B, Gianfranceschi L, Gessler C. Creating a saturated reference map for the apple (Malus × domesticaBorkh.) genome. Theoretical and Applied Genetics. 2003; 106: 1497–1508. DOI: 10.1007/s00122-003-1209-0
Chen XL, Wang GZ, Chen LH, Li SJ. Methodological improvement and its application effect in chromosome study of mud crab, Scylla serrata. Journal of Oceanography in Taiwan Strait. 2004; 23: 347–353. (In Chinese with English Abstract)