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Mining and identification of SNP markers associated with growth traits in the clam Meretrix meretrix

文献类型： 外文期刊

作者： Dai, Ping 1 ; Wang, Hongxia 2 ; Liu, Baozhong 2 ;

作者机构： 1.Chinese Acad Fishery Sci, Key Lab Sustainable Utilizat Marine Fisheries Res, Minist Agr, Yellow Sea Fisheries Res Inst, Qingdao 266071, Peoples R China

2.Chinese Acad Sci, Key Lab Expt Marine Biol, Inst Oceanol, Qingdao 266071, Peoples R China

3.Qingdao Natl Lab Marine Sci & Technol, Lab Marine Biol & Biotechnol, Qingdao, Peoples R China

关键词： GMD;Growth;Marker-trait association;Meretrix meretrix;SNPs

期刊名称：AQUACULTURE INTERNATIONAL （ 影响因子：2.235； 五年影响因子：2.616 ）

ISSN：

年卷期：

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收录情况： SCI

摘要： Selecting fast-growing strains is the most common objective of genetic breeding programs. In this study, we sought to mine the growth-associated single nucleotide polymorphisms (SNPs) in the commercially cultured clam Meretrix meretrix by candidate gene association analysis. Fifty potentially growth-associated contigs based on their functional annotation were chosen as candidates from our EST database, and 240 SNPs were predicted from these contigs. Seventy-one predicted SNPs and five novel SNPs were identified by pooled DNA sequencing in both a fast-growing population (09SPSB) and a control population (09G(3)SB). Among these SNPs, 24 were also identified in an independent population (CP). Through multiplex SNaPshot genotyping, 16 of the 24 SNPs were used in the marker-trait association analysis between 09SPSB and 09G(3)SB. The results showed that seven SNPs in five contigs were significantly associated with clam shell length (P < 0.05). With bidirectional selective genotyping in the CP, three of the seven growth-associated SNPs were further confirmed. Annotations of these SNP-containing contigs provided some clues of these genes functioning in growth. After a haplotype association analysis, we found four haplotypes with significantly different frequencies between 09SPSB and 09G(3)SB (P < 0.001). Through a generalized multifactor dimensionality reduction (GMDR) analysis, we found several gene-gene interaction models, of which the two-factor model (SNPg5/SNPg16) was the best one. These obtained markers will be useful in further quantitative trait loci identification and marker-assisted selection in M. meretrix.

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