Division of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK.
Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China.
BMC Genomics. 2024 Oct 19;25(1):981. doi: 10.1186/s12864-024-10852-8.
African cattle represent a unique resource of genetic diversity in response to adaptation to numerous environmental challenges. Characterising the genetic landscape of indigenous African cattle and identifying genomic regions and genes of functional importance can contribute to targeted breeding and tackle the loss of genetic diversity. However, pinpointing the adaptive variant and determining underlying functional mechanisms of adaptation remains challenging.
In this study, we use selection signatures from whole-genome sequence data of eight indigenous African cattle breeds in combination with gene expression and quantitative trait loci (QTL) databases to characterise genomic targets of artificial selection and environmental adaptation and to identify the underlying functional candidate genes. In general, the trait-association analyses of selection signatures suggest the innate and adaptive immune system and production traits as important selection targets. For example, a large genomic region, with selection signatures identified for all breeds except N'Dama, was located on BTA27, including multiple defensin DEFB coding-genes. Out of 22 analysed tissues, genes under putative selection were significantly enriched for those overexpressed in adipose tissue, blood, lung, testis and uterus. Our results further suggest that cis-eQTL are themselves selection targets; for most tissues, we found a positive correlation between allele frequency differences and cis-eQTL effect size, suggesting that positive selection acts directly on regulatory variants.
By combining selection signatures with information on gene expression and QTL, we were able to reveal compelling candidate selection targets that did not stand out from selection signature results alone (e.g. GIMAP8 for tick resistance and NDUFS3 for heat adaptation). Insights from this study will help to inform breeding and maintain diversity of locally adapted, and hence important, breeds.
非洲牛代表了对众多环境挑战适应的遗传多样性的独特资源。描述本地非洲牛的遗传景观，并确定具有功能重要性的基因组区域和基因，可以促进有针对性的育种，并解决遗传多样性的丧失问题。然而，确定适应性变体并确定适应的潜在功能机制仍然具有挑战性。
在这项研究中，我们使用了来自八个本地非洲牛品种的全基因组序列数据中的选择信号，结合基因表达和数量性状基因座（QTL）数据库，来描述人工选择和环境适应的基因组目标，并确定潜在的功能候选基因。一般来说，选择信号的性状关联分析表明先天和适应性免疫系统以及生产性状是重要的选择目标。例如，在 BTA27 上，除了 N'Dama 之外，所有品种都确定了选择信号的一个大基因组区域，其中包括多个防御素 DEFB 编码基因。在分析的 22 个组织中，假定选择的基因在脂肪组织、血液、肺、睾丸和子宫中过度表达的基因显著富集。我们的研究结果还表明，顺式 eQTL 本身就是选择目标；对于大多数组织，我们发现等位基因频率差异与顺式 eQTL 效应大小之间存在正相关，这表明正选择直接作用于调节变体。
通过将选择信号与基因表达和 QTL 的信息相结合，我们能够揭示引人注目的候选选择目标，这些目标不仅从选择信号结果中脱颖而出（例如，用于抗蜱的 GIMAP8 和用于耐热适应的 NDUFS3）。这项研究的结果将有助于为本地适应的、因此非常重要的品种提供信息，以促进选育并保持多样性。
