Multiple solutions at the genomic level in response to selective breeding for high locomotor activity
Multiple solutions at the genomic level in response to selective breeding for high locomotor activity
复制标题
基因组水平上的多种解决方案，以响应高运动活性的选择性育种
DOI：
10.1093/genetics/iyac165
复制
发表时间：
2022
期刊：
影响因子：
3.3
通讯作者：
Gleason, ed., J.
中科院分区：
文献类型：
--
作者：
Hillis, David A.;Garland, Jr, Theodore;Gleason, ed., J.
在均匀选择下的复制系往往以不同的方式进化。此前，对来自4个重复高跑系和4个非选择控制系的个体小鼠（小家鼠）的全基因组序列数据进行了分析，结果表明，基因组区域对自愿跑轮行为的选择做出了一致的反应。在这里，我们要问的是，即使在相似的水平上达到了选择极限，“高跑者”系的进化是否彼此不同。我们关注的是1个高跑者系（HR3），它在一个主要影响基因（Myh4Minimsc）上发生突变，在纯合子条件下，导致后肢肌肉质量减少50%和许多多效性效应。我们从SNP分析中排除了HR3，并确定了19个在所有4个品系的分析中未一致确定的区域。重复分析，同时放弃其他High Runner系列，确定了12个、8个和6个这样的区域。（在这45个地区中，有37个是独特的。）这些结果表明，每个“高跑者”品系对选择的反应确实有些独特，但HR3也是最独特的。然后，当仅丢弃HR3时，我们应用了2种额外的分析方法（基于单倍型和涉及固定模式的非统计测试）。所有3种方法都确定了7个新区域（与使用所有4个High Runner品系的分析相比），包括与活动水平、多巴胺信号、海马体形态、心脏大小和体型相关的基因，所有这些在High Runner品系和对照品系之间都不同。我们的结果说明了多重解决方案和“私有”等位基因如何模糊了涉及“公共”等位基因的一般选择签名。
Replicate lines under uniform selection often evolve in different ways. Previously, analyses using whole-genome sequence data for individual mice (Mus musculus) from 4 replicate High Runner lines and 4 nonselected control lines demonstrated genomic regions that have responded consistently to selection for voluntary wheel-running behavior. Here, we ask whether the High Runner lines have evolved differently from each other, even though they reached selection limits at similar levels. We focus on 1 High Runner line (HR3) that became fixed for a mutation at a gene of major effect (Myh4Minimsc) that, in the homozygous condition, causes a 50% reduction in hindlimb muscle mass and many pleiotropic effects. We excluded HR3 from SNP analyses and identified 19 regions not consistently identified in analyses with all 4 lines. Repeating analyses while dropping each of the other High Runner lines identified 12, 8, and 6 such regions. (Of these 45 regions, 37 were unique.) These results suggest that each High Runner line indeed responded to selection somewhat uniquely, but also that HR3 is the most distinct. We then applied 2 additional analytical approaches when dropping HR3 only (based on haplotypes and nonstatistical tests involving fixation patterns). All 3 approaches identified 7 new regions (as compared with analyses using all 4 High Runner lines) that include genes associated with activity levels, dopamine signaling, hippocampus morphology, heart size, and body size, all of which differ between High Runner and control lines. Our results illustrate how multiple solutions and “private” alleles can obscure general signatures of selection involving “public” alleles.