Estimates of genomic inbreeding and identification of candidate regions in Beijing-You chicken populations

Runs of homozygosity (ROHs) has become an effective method for analysing inbreeding in livestock populations. Moreover, ROHs is well-suited to detect signatures of selection via ROH islands. This study aimed to investigate the occurrence and distribution of ROHs, compare the genomic inbreeding coefficients and identify the genomic regions with high ROH frequencies in different Beijing-You chicken (BY) populations, including a random conservation population (BY_R), a pedigree conservation population (BY_P), and a commercial population obtained from the market (BY_C). Among them, BY_R in 2010 and 2019 were BY_R1 and BY_R2 respectively. A total of 27 916 ROHs were identified. The average number of ROHs per individual across the three BY populations ranged from 213 (BY_P) to 161 (BY_C), and the average length of ROHs ranged from 0.432 Mb (BY_R2) to 0.451 Mb (BY_P). The highest inbreeding coefficient calculated based on ROHs (F-ROH) was 0.1 in BY_P, whereas the lowest F-ROH was 0.0743 in BY_C. In addition, the inbreeding coefficient of BY_R2 (F-ROH = 0.0798) was higher than that of BY_R1 (F-ROH = 0.0579). Furthermore, the highest proportion of long ROH fragments (> 4 Mb) was observed in BY_P and BY_C. This study showed the top 10 ROH islands of each population, and these ROH islands harboured 53 genes, some of which were related to limb development, body size and immune response. These findings contribute to the understanding of genetic diversity and population demography, and might help improve breeding and conservation strategies for BY populations.

Automated summary

Runs of homozygosity (ROHs) are effective for assessing inbreeding and detecting selection in livestock populations. This study investigated the occurrence and distribution of ROHs, compared genomic inbreeding coefficients, and identified genomic regions with high ROH frequencies in different Beijing-You chicken populations. The findings contribute to understanding genetic diversity and population demography.