Literature DB >> 31273567

Mapping and Validating QTL for Fatty Acid Compositions and Growth Traits in Asian Seabass.

Le Wang1, Elaine Chua1, Fei Sun1, Zi Yi Wan1,2, Baoqing Ye1, Hongyan Pang1, Yanfei Wen1, Gen Hua Yue3,4,5.   

Abstract

Asian seabass is an important food fish species. While improving growth, increasing the nutritional value is important, omega-3 fatty acids are indispensable to human health. Identifying and validating DNA markers associated with traits is the first step towards marker-assisted selection (MAS). We quantified 13 different fatty acids and three growth traits in 213 F2 Asian seabass from a family at the age 270 days post hatch, and screened QTL for these traits. The content of total fatty acids in 100 g flesh was 2.57 ± 0.80 g, while the proportions of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) were 16.96 ± 2.20% and 5.42 ± 0.90%, respectively. A linkage map with 2424 SNPs was constructed and used for QTL mapping. For fatty acid compositions, 14 significant QTL were identified on three linkage groups (LG5, LG11 and LG14), with phenotypic variance explained (PVE) from 12.8 to 24.6%. Thirty-nine suggestive QTL were detected on 16 LGs. Two significant QTL for EPA were identified on LG5 and LG14, with PVE of 15.2% and 15.1%, respectively. No significant QTL was identified for DHA. For growth traits, six significant and 13 suggestive QTL were identified on two and seven LGs, respectively. Only a few significant QTL for fatty acids overlapped with previously mapped QTL for these traits, suggesting that most QTL detected in a family are family-specific and could only be used in MAS in the family per se. To facilitate population-wide molecular breeding, more powerful methods (e.g. GWAS) should be used to identify SNPs for genomic selection.

Entities:  

Keywords:  Asian seabass; Fatty acid; Genetic map; Growth; QTL; Selective breeding

Mesh:

Substances:

Year:  2019        PMID: 31273567     DOI: 10.1007/s10126-019-09909-7

Source DB:  PubMed          Journal:  Mar Biotechnol (NY)        ISSN: 1436-2228            Impact factor:   3.619


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