AUTHOR=Wang Shunzhe , Liang Long , Ziyayiding Dilinigeer , Jiao Wenjing , Kasimu Hailati , He Sangang , Liu Mingjun 

TITLE=Inbreeding patterns and genetic diversity under selection in Teha sheep

JOURNAL=Frontiers in Genetics

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2025.1576125

DOI=10.3389/fgene.2025.1576125

ISSN=1664-8021

ABSTRACT=BackgroundInbreeding and genetic diversity are critical factors influencing the adaptability, productivity, and sustainability of livestock populations. Teha sheep, a crossbred line between Texel and Kazakh sheep, are an important meat-producing breed in China, yet their genetic structure and inbreeding status remain underexplored. In this study, we aim to evaluate inbreeding coefficients, genetic diversity, and selection signatures in Teha sheep by integrating pedigree and genomic data.ResultsAnalysis of pedigree data from 2,652 individuals revealed a low inbreeding coefficient (FPED = 0.001), whereas analysis of genomic data from 1,271 individuals indicated slightly higher inbreeding coefficients, with the FROH averaging 0.044. Genetic diversity metrics, including Ho = 0.347 and PIC = 0.345, confirmed moderate variability within the population. A significant region of runs of homozygosity (ROH) hotspot was identified on chromosome 2 (112.01–119.89 Mb), encompassing genes such as MSTN, TUBGCP5, and NIPA2, which are associated with muscle growth, fat metabolism, and skeletal development. Notably, CYFIP1, SAP130, and UGGT1 were identified as key genes shared across ROH hotspots, QTL regions, and LD blocks, implicating their roles in growth efficiency, carcass quality, and protein regulation under stress. These findings reveal critical genomic regions contributing to the breed’s productivity and adaptability.ConclusionIn this study, we highlight the low inbreeding levels and moderate genetic diversity of Teha sheep, emphasizing the integration of pedigree and genomic analyses for sustainable breeding programs. The identification of key genes provides a foundation for optimizing productivity and maintaining genetic variability in this important livestock population.