生物
单核苷酸多态性
增强子
选择(遗传算法)
SNP公司
否定选择
遗传学
适应(眼睛)
人口
局部适应
进化生物学
计算生物学
基因
基因型
基因组
基因表达
人口学
人工智能
神经科学
社会学
计算机科学
作者
Shoulu Dai,Pengju Zhao,Wenhao Li,Lingwei Peng,Enhui Jiang,Yuqin Du,Wengang Zhang,Xuelei Dai,Yang Liu,Zhiqiang Li,Lei Xu,Xianyong Lan,Wenhui Lyu,Liguo Yang,Lingzhao Fang,George E. Liu,Yang Zhou
标识
DOI:10.1093/molbev/msaf205
摘要
Abstract Based on a pangenome graph platform, we simultaneously analyzed the impacts of SNPs and SVs in the population structure and phenotypic formation of global cattle using 2,409 individuals from 82 breeds. We demonstrated that SVs, like SNPs, effectively explain the population structure of global cattle. Genomic regions under strong selection, identified using both SNPs and SVs, consistently revealed footprints associated with human-mediated selection of economic traits in European improved cattle or natural selection of geographical adaptations. Notably, we detected that ∼40.14% of SVs were not tagged (LD, r2 < 0.6) by nearby SNPs. These “orphan” SVs may uncover new genetic signals and represent recent mutations associated with specific selection pressures or local environmental adaptation. Selected SVs tagged by SNPs also play causal or dominant roles in regions under selection. For example, our single-cell RNA sequencing has demonstrated that a notable SNP-tagged SV functions as an enhancer of the IGFBP7 gene, regulating fat deposition through IGFBP7+ cells. In conclusion, these SV-related mechanisms likely have caused some differences in economic traits and local adaptability across global cattle populations. Our integrated approaches highlight the unique and indispensable roles of SVs in shaping genetic diversity, offering novel insights into adaptation, selection, and strategies for improving cattle populations.
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