biostudies-literatureLv TShandong Provincial Postdoctoral Innovative Talents Support ProgramNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China42103https://www.ebi.ac.uk/biostudies/studies/S-EPMC12658181biostudies-literatureUnknown15(1)The genome of Penaeus vannamei is rich in short tandem repeats (STRs), occupying 18.96% of the genome, with 68.6% of loci showing high polymorphic information content, highlighting their potential as molecular markers. Accordingly, we performed an integrative GWAS leveraging STR, SNP, and InDel markers to identify 78 growth-associated loci, including 17 additional STRs compared with single-marker GWAS and six high-linkage regions containing metabolic, molting, and other growth-related genes. Four markers were validated in an independent population. In genomic prediction, STRs outperformed SNPs under the GBLUP model at low marker densities (20-50 loci), with accuracy gains up to 183%. GWAS-informed marker selection improved cross-population prediction performance, with STR-Top sets enhancinScientific reportsMulti-marker GWAS and variant-specific genomic prediction for growth traits in Pacific white shrimp.PMC12658181SDBX202302022ZR2024QC19232273129Xia YFu QLiu JLiu MTan JChen MCao JLuan SKong JChen BMeng XLi XLuo KDai PSui JQiang GLv TZhou HXing QfalseMulti-marker GWAS and variant-specific genomic prediction for growth traits in Pacific white shrimp.The genome of Penaeus vannamei is rich in short tandem repeats (STRs), occupying 18.96% of the genome, with 68.6% of loci showing high polymorphic information content, highlighting their potential as molecular markers. Accordingly, we performed an integrative GWAS leveraging STR, SNP, and InDel markers to identify 78 growth-associated loci, including 17 additional STRs compared with single-marker GWAS and six high-linkage regions containing metabolic, molting, and other growth-related genes. Four markers were validated in an independent population. In genomic prediction, STRs outperformed SNPs under the GBLUP model at low marker densities (20-50 loci), with accuracy gains up to 183%. GWAS-informed marker selection improved cross-population prediction performance, with STR-Top sets enhancin2025-01-01T00:00:00Z2025 Nov2026-06-08T04:49:51.544Z2026-06-08T03:08:51.568ZS-EPMC126581814129859410.1038/s41598-025-26048-3