Abstract
Chinese local cattle with a high level of genetic diversity mainly originate from two subspecies; the cattle in northern China are primarily Bos Taurus, and the cattle in southern China are primarily Bos indicus. Cattle from southern China are characterized by a specific phenotype and adapted to the local environment. This study explored the genetic diversity, degree of admixture, and selection signature in eight local cattle breeds in southern China. The lowest level of heterozygosity was found in Hainan and Nandan cattle from Hainan and Guangxi province, respectively, whereas the highest level of heterozygosity was detected in Zhaotong cattle from Yunnan province. A neighbor-joining phylogenetic tree analysis clearly separated Lufeng cattle from other breeds, whereas Leiqiong and Hainan cattle have some crossover. Based on linkage disequilibrium-filtered single nucleotide polymorphisms (SNPs), the admixture analysis revealed two clusters corresponding to the taurine and indicine cattle lineages, and the local cattle breeds from southern China showed a certain degree of admixture. When K = 4 and 9, we found a slight separation among Leiqiong, Lufeng, and Hainan cattle. Meanwhile, we performed a selection signature analysis in Hainan, Leiqiong, and Lufeng cattle distributed in the extreme south of China, using the integrated haplotype score (iHS), Rsb statistic, and BayeScan software. Using the iHS approach, we identified 251, 270, and 256 candidate regions in Lufeng, Leiqiong, and Hainan cattle, respectively. Moreover, we identified 184, 174, and 146 candidate regions in pairwise comparisons of Leiqiong vs. Lufeng, Leiqiong vs. Hainan, and Hainan vs. Lufeng cattle using the Rsb approach. In addition, we identified 76 loci with a total of 48 genes under selection, based on the FST approach. Several candidate genes under selection were found to be related to meat quality, immunity, and adaptation to the local environment in southern China. Our results provide significant information about the genetic differences among the cattle breeds from southern China and the possible cause of difference in breed-specific characteristics. Selection signature analysis identified a few candidate SNPs and genes related to certain important traits of these cattle. In general, our results provide valuable insights into the genetic basis of specific traits under selection in certain local cattle breeds.
Highlights
Cattle are important livestock species worldwide as humans obtain meat, milk, and leather from cattle
We found that Lufeng cattle (LFC) and Hainan cattle (HNC) displayed lower heterozygosity and higher inbreeding coefficients
We explored the genomic regions under recent selection in southern Chinese local cattle breeds by estimating an integrated haplotype score (iHS) analysis of three representative cattle breeds (LFC, Leiqiong cattle (LQC), and HNC)
Summary
Cattle are important livestock species worldwide as humans obtain meat, milk, and leather from cattle. Most local cattle in China are classified into two categories based on physical appearance and genomic differences: Bos taurus cattle (humpless) and B. indicus cattle (humped) (Bradley et al, 1996; Lei et al, 2006; Zeder, 2008). In China, numerous cattle breeds are raised in diverse environmental conditions, and they can be divided into three groups based on the morphological characteristics and geographic distributions in China. The southern distributed breeds belong primarily to the subspecies B. indicus, which is resistant to damp heat and mites and exhibits a small but robust and compact constitution (Li et al, 2013). The northern distributed breeds belong primarily to the subspecies B. taurus, which has large body size, broad breast, and thick skin. The cattle breeds distributed centrally between the northern and southern regions are mostly B. taurus and B. indicus hybrids. Previous studies based on Y chromosome polymorphisms and mitochondrial DNA indicate a declining south-to-north gradient of indicine introgression (Cai et al, 2006; Lei et al, 2006; Xia et al, 2019)
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