A parentage identification system and genetic analysis of growth traits in <i>Percocypris pingi</i> (Tchang, 1930) for breeding programs

To effectively evaluate genetic diversity and estimate trait heritability, the establishment of a robust parentage identification system is indispensable. For tetraploid species, the success of such a system critically depends on the development of highly polymorphic loci. In this study, we screened simple sequence repeats (SSRs) for Percocypris pingi , a tetraploid species, by leveraging full-length data. Using SSREnricher software, we further compared these sequences with muscle transcriptome data obtained from four geographically distinct populations to identify highly polymorphic SSR loci. We identified nine highly polymorphic SSR markers with a mean polymorphism information content (PIC) of 0.647 and constructed a high-resolution parentage assignment system with a cumulative exclusion probability of 0.999984. The system was validated using 300 offspring from single-pair families, achieving an assignment accuracy of 96%. Growth traits, including total length (TL), body length (BL), and body weight (BW), were measured in 270 individuals from mixed-rearing groups. We investigated the relationship between parental genetic distance and offspring growth. The average Bruvo distance between parents was relatively low (0.37). A weak positive trend was observed between parental genetic distance and offspring TL (P &gt; 0.05). Given that all pairwise trait correlations exceeded 0.9 (P &lt; 0.05), the multivariate model provided more reliable estimates, and BW (heritability = 0.307) emerged as a priority trait for future breeding programs. Overall, our findings highlight the utility of transcriptome-derived SSR markers for accurate parentage analysis and emphasize the importance of monitoring genetic diversity and estimating trait heritability in stock enhancement efforts.