Joint genome-wide association study of body mass and morphological traits in turbot (Scophthalmus maximus)
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    Abstract:

    To reveal the molecular genetic mechanisms of body mass and morphological traits in turbot (Scophthalmus maximus) and scan molecular markers and candidate genes, which can be used to improve the target traits, a genome-wide association study (GWAS) was carried out using specific-locus amplified fragment technology (restriction site-associated DNA, 2b-RAD). First, body mass (BM), body length (BL), body width (BW), and caudal peduncle width (CPW) of 441 individuals were measured at about 473 days of growth period in a turbot breeding population. Second, all individuals were genotyped using 2b-RAD, and 23,988 SNPs were obtained after strict quality control. Using a multivariate linear mixed model (mvLMM) for GWAS of traits of BM-BL and BL-BW-CPW, 9 and 2 pleiotropic QTNs were detected for each phenotypic combination, respectively. However, a single-trait linear mixed model (LMM) based on the FaST-LMM algorithm was used for the association analysis of each trait, and the results showed that 4 QTNs were detected in the BM trait, 1 QTN was associated with BL and BW traits, respectively, and no significant locus was found in the CPW trait. A comparison between results of mvLMM and LMM found that mvLMM could detect more QTNs than LMM in GWAS, and the pleiotropic QTNs detected by mvLMM were more biologically meaningful. This study applied mvLMM and LMM to the joint GWAS of body mass and morphological traits in turbot, 17 significant QTNs were detected both using mvLMM and LMM, and 4 of them were detected repeatedly. Furthermore, 12 candidate genes were found by searching the nearest gene of each detected QTN on the whole turbot genome. All of them might be important candidate markers and functional genes, which could influence turbot body mass and morphology. Our study also provided the theory and a reference for marker-assisted selection of body mass and morphological traits in turbot.

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高进,杨润清.大菱鲆体重和体尺性状联合GWAS分析.渔业科学进展,2021,42(2):63-70

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History
  • Received:February 02,2020
  • Revised:February 19,2020
  • Adopted:
  • Online: January 26,2021
  • Published: April 30,2021
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