Genomics and transcriptomics identify quantitative trait loci affecting growth-related traits in silver pomfret (Pampus argenteus).

Comp Biochem Physiol Part D Genomics Proteomics

National Engineering Research Laboratory of marine biotechnology and Engineering, Ningbo University, Zhejiang, Ningbo 315211, China; Key Laboratory of Marine Biotechnology of Zhejiang Province, Ningbo University, Zhejiang, Ningbo 315211, China; Key Laboratory of Green Mariculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural, Ningbo University, Zhejiang, Ningbo 315211, China. Electronic address:

Published: January 2025

Pampus argenteus, a species distributed throughout the Indo-West Pacific, plays a significant role in the yield of aquaculture species. However, cultured P. argenteus has always been characterised by unbalanced growth synchronisation among individuals, slow growth rate, and lack of excellent germplasm resources. Therefore, we conducted mass selection for fast-growing strain P. argenteus for several consecutive years. Various genetic improvement programs have modified its genome sequence through selective pressure, leaving nucleotide signals that can be detected at the genomic level. In the present study, we combined bulked segregant analysis and transcriptome sequencing to identify candidate single nucleotide polymorphisms (SNPs) and key genes for growth-related traits in P. argenteus. A total of 7,280,936 SNPs and 2,212,379 insertions/deletions were identified in the extreme phenotypes of the fast-growing and slow-growing groups. Based on the examination of SNP frequency differences and sliding-window analysis, 42 SNPs were identified as candidate markers. Moreover, 14 of the 42 SNPs linked to growth-related traits were confirmed to be credible SNPs, and eight growth-related genes were screened, namely myb-binding protein 1 A, insulin A/B chains, α-1B adrenoceptor, engulfment and cell motility protein 3, myosin light chain kinase family member 4, insulin receptor located, unconventional myosin-9b, and matrilin-1. An optimal three-factor model (SNP4&SNP12&SNP14) was constructed using the generalized multifactor dimensionality reduction method, and its accuracy was verified as 67.72 %. These results may benefit genetic studies and accelerate genetic improvement of fast-growing strains of P. argenteus.

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http://dx.doi.org/10.1016/j.cbd.2025.101414DOI Listing

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