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Mandarin fish ( S. chuatsi ) is China’s most economically important freshwater aquaculture species, yet selective breeding remains constrained by long generation intervals and limited genomic resources. We performed whole-genome resequencing of 98 Siniperca chuatsi individuals (minimum 10-fold coverage), retaining 1,310,398 quality-controlled bi-allelic SNPs across 24 chromosomes. Population structure analysis (principal component analysis, neighbor-joining, and ADMIXTURE) resolved four primary ancestral lineages that further separated into up to six finer-scale ancestry components, with evidence of admixture among individuals. Four morphometric traits (body length, height, weight, and thickness) were recorded; genome-wide association analyses were performed for body height and body weight, a derived shape index (length-to-thickness ratio), and two multivariate combinations of composite size and shape phenotypes, using single-trait and multivariate linear mixed models in GEMMA that accounted for population structure via a genomic relationship matrix and principal components. At a Bonferroni-corrected threshold (P < 3.82 × 10 −8 ), 32 genome-wide significant SNP associations were detected across the five analyses, including a core set shared across multiple analyses, suggesting cross-trait associations. The two most robust loci were intronic variants in BCL2L1 on chromosome 10, detected in all five analyses, and MRC1 on chromosome 13, the single strongest association overall. A locus spanning PITPNM2 and Zswim6 on chromosome 18 was detected only in the multivariate analysis, illustrating the added power of joint trait modeling over the single-trait GWAS performed here. A nonsynonymous variant in PITPNM2 (p.R1254H) within this locus was prioritized as a computational candidate for its potential role in growth and body-shape variation, pending experimental validation. These findings provide a candidate-marker resource to support marker-assisted and genomic selection for growth traits in S. chuatsi aquaculture breeding programs.
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Yang et al. (2026) studied this question.
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