Xu Fuyi, Hu Shixian, Chao Tianzhu, Wang Maochun, Li Kai, Zhou Yuxun, Xu Hongyan, Xiao Junhua
College of Chemistry, Chemical Engineering, and Biotechnology, Donghua University, 2999 North Renmin Road, Shanghai, 201620, China.
Department of Biostatistics and Epidemiology, Medical College of Georgia, Augusta University, 1120 15th Street, Augusta, GA, 30912, USA.
Mol Genet Genomics. 2017 Oct;292(5):1111-1121. doi: 10.1007/s00438-017-1335-z. Epub 2017 Jun 19.
Both natural and artificial selection play a critical role in animals' adaptation to the environment. Detection of the signature of selection in genomic regions can provide insights for understanding the function of specific phenotypes. It is generally assumed that laboratory mice may experience intense artificial selection while wild mice more natural selection. However, the differences of selection signature in the mouse genome and underlying genes between wild and laboratory mice remain unclear. In this study, we used two mouse populations: chromosome 1 (Chr 1) substitution lines (C1SLs) derived from Chinese wild mice and mouse genome project (MGP) sequenced inbred strains and two selection detection statistics: Fst and Tajima's D to identify the signature of selection footprint on Chr 1. For the differentiation between the C1SLs and MGP, 110 candidate selection regions containing 47 protein coding genes were detected. A total of 149 selection regions which encompass 7.215 Mb were identified in the C1SLs by Tajima's D approach. While for the MGP, we identified nearly twice selection regions (243) compared with the C1SLs which accounted for 13.27 Mb Chr 1 sequence. Through functional annotation, we identified several biological processes with significant enrichment including seven genes in the olfactory transduction pathway. In addition, we searched the phenotypes associated with the 47 candidate selection genes identified by Fst. These genes were involved in behavior, growth or body weight, mortality or aging, and immune systems which align well with the phenotypic differences between wild and laboratory mice. Therefore, the findings would be helpful for our understanding of the phenotypic differences between wild and laboratory mice and applications for using this new mouse resource (C1SLs) for further genetics studies.
自然选择和人工选择在动物适应环境的过程中都起着关键作用。检测基因组区域中的选择特征有助于深入了解特定表型的功能。一般认为,实验室小鼠可能经历了强烈的人工选择,而野生小鼠则更多地受到自然选择。然而,野生小鼠和实验室小鼠在基因组及相关基因上的选择特征差异仍不清楚。在本研究中,我们使用了两个小鼠群体:源自中国野生小鼠的1号染色体(Chr 1)代换系(C1SLs)和已进行全基因组测序的小鼠基因组计划(MGP)近交系,以及两种选择检测统计量:Fst和Tajima's D,以识别Chr 1上的选择足迹特征。对于C1SLs和MGP之间的差异,我们检测到了110个包含47个蛋白质编码基因的候选选择区域。通过Tajima's D方法,在C1SLs中总共鉴定出149个选择区域,覆盖7.215 Mb。而对于MGP,我们鉴定出的选择区域数量几乎是C1SLs的两倍(243个),占Chr 1序列的13.27 Mb。通过功能注释,我们确定了几个显著富集的生物学过程,包括嗅觉转导途径中的7个基因。此外,我们搜索了与通过Fst鉴定出的47个候选选择基因相关的表型。这些基因涉及行为、生长或体重、死亡率或衰老以及免疫系统,这与野生小鼠和实验室小鼠之间的表型差异高度吻合。因此,这些发现将有助于我们理解野生小鼠和实验室小鼠之间的表型差异,并有助于利用这种新的小鼠资源(C1SLs)进行进一步的遗传学研究。
Genet Sel Evol. 2018-3-22
G3 (Bethesda). 2016-7-7
Evolution. 1984-11
Nucleic Acids Res. 2015-1
Nat Commun. 2014-8-5
Mol Biol Evol. 2014-7
Nucleic Acids Res. 2013-11-26
Annu Rev Genomics Hum Genet. 2013-7-3