基于规则和模型的同时检测方法为猪的基因组选择足迹打开了一扇窗户。

Simultaneous testing of rule- and model-based approaches for runs of homozygosity detection opens up a window into genomic footprints of selection in pigs.

机构信息

Research Group Veterinary Functional Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany.

Department of Biology, Chemistry and Pharmacy, Institute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany.

出版信息

BMC Genomics. 2022 Aug 6;23(1):564. doi: 10.1186/s12864-022-08801-4.

Abstract

BACKGROUND

Past selection events left footprints in the genome of domestic animals, which can be traced back by stretches of homozygous genotypes, designated as runs of homozygosity (ROHs). The analysis of common ROH regions within groups or populations displaying potential signatures of selection requires high-quality SNP data as well as carefully adjusted ROH-defining parameters. In this study, we used a simultaneous testing of rule- and model-based approaches to perform strategic ROH calling in genomic data from different pig populations to detect genomic regions under selection for specific phenotypes.

RESULTS

Our ROH analysis using a rule-based approach offered by PLINK, as well as a model-based approach run by RZooRoH demonstrated a high efficiency of both methods. It underlined the importance of providing a high-quality SNP set as input as well as adjusting parameters based on dataset and population for ROH calling. Particularly, ROHs ≤ 20 kb were called in a high frequency by both tools, but to some extent covered different gene sets in subsequent analysis of ROH regions common for investigated pig groups. Phenotype associated ROH analysis resulted in regions under potential selection characterizing heritage pig breeds, known to harbour a long-established breeding history. In particular, the selection focus on fitness-related traits was underlined by various ROHs harbouring disease resistance or tolerance-associated genes. Moreover, we identified potential selection signatures associated with ear morphology, which confirmed known candidate genes as well as uncovered a missense mutation in the ABCA6 gene potentially supporting ear cartilage formation.

CONCLUSIONS

The results of this study highlight the strengths and unique features of rule- and model-based approaches as well as demonstrate their potential for ROH analysis in animal populations. We provide a workflow for ROH detection, evaluating the major steps from filtering for high-quality SNP sets to intersecting ROH regions. Formula-based estimations defining ROHs for rule-based method show its limits, particularly for efficient detection of smaller ROHs. Moreover, we emphasize the role of ROH detection for the identification of potential footprints of selection in pigs, displaying their breed-specific characteristics or favourable phenotypes.

摘要

背景

过去的选择事件在家畜的基因组中留下了痕迹,可以通过纯合基因型的延伸来追溯,这些延伸被称为纯合子区域(ROH)。对表现出潜在选择特征的群体或群体内的常见 ROH 区域进行分析,需要高质量的 SNP 数据以及精心调整的 ROH 定义参数。在这项研究中,我们使用基于规则和基于模型的方法的同时测试,在来自不同猪群的基因组数据中进行战略性 ROH 调用,以检测针对特定表型的选择基因组区域。

结果

我们使用 PLINK 提供的基于规则的方法和 RZooRoH 运行的基于模型的方法进行 ROH 分析,这两种方法都表现出了很高的效率。它强调了提供高质量 SNP 集作为输入以及根据数据集和群体调整 ROH 调用参数的重要性。特别是,这两种工具都以高频率调用了≤20kb 的 ROH,但在对调查猪群共有的 ROH 区域的后续分析中,在一定程度上覆盖了不同的基因集。与表型相关的 ROH 分析导致了潜在选择的区域,这些区域特征是传统品种,已知具有长期的繁殖历史。特别是,与适应性相关的性状的选择焦点是由各种含有疾病抗性或耐受性相关基因的 ROH 强调的。此外,我们确定了与耳朵形态相关的潜在选择特征,这些特征证实了已知的候选基因,并揭示了 ABCA6 基因中的错义突变,该突变可能支持耳朵软骨的形成。

结论

这项研究的结果突出了基于规则和基于模型的方法的优势和独特之处,并展示了它们在动物群体中的 ROH 分析中的潜力。我们提供了一个 ROH 检测工作流程,从过滤高质量 SNP 集到相交 ROH 区域,评估了主要步骤。基于公式的 ROH 定义对基于规则的方法的估计显示出其局限性,特别是对于较小的 ROH 的高效检测。此外,我们强调了 ROH 检测在鉴定猪中的潜在选择痕迹中的作用,这些痕迹显示了它们的品种特异性特征或有利的表型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5fa/9357325/581556052b17/12864_2022_8801_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索