Hughes David A, Kircher Martin, He Zhisong, Guo Song, Fairbrother Genevieve L, Moreno Carlos S, Khaitovich Philipp, Stoneking Mark
Max-Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig, 04103, Germany.
CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai, 200031, P.R. China.
Genome Biol. 2015 Mar 19;16(1):54. doi: 10.1186/s13059-015-0627-z.
Gene expression variation is a phenotypic trait of particular interest as it represents the initial link between genotype and other phenotypes. Analyzing how such variation apportions among and within groups allows for the evaluation of how genetic and environmental factors influence such traits. It also provides opportunities to identify genes and pathways that may have been influenced by non-neutral processes. Here we use a population genetics framework and next generation sequencing to evaluate how gene expression variation is apportioned among four human groups in a natural biological tissue, the placenta.
We estimate that on average, 33.2%, 58.9%, and 7.8% of the placental transcriptome is explained by variation within individuals, among individuals, and among human groups, respectively. Additionally, when technical and biological traits are included in models of gene expression they each account for roughly 2% of total gene expression variation. Notably, the variation that is significantly different among groups is enriched in biological pathways associated with immune response, cell signaling, and metabolism. Many biological traits demonstrate correlated changes in expression in numerous pathways of potential interest to clinicians and evolutionary biologists. Finally, we estimate that the majority of the human placental transcriptome exhibits expression profiles consistent with neutrality; the remainder are consistent with stabilizing selection, directional selection, or diversifying selection.
We apportion placental gene expression variation into individual, population, and biological trait factors and identify how each influence the transcriptome. Additionally, we advance methods to associate expression profiles with different forms of selection.
基因表达变异是一个特别令人感兴趣的表型特征,因为它代表了基因型与其他表型之间的初始联系。分析这种变异在群体间和群体内的分配情况,有助于评估遗传和环境因素如何影响这些特征。这也为识别可能受到非中性过程影响的基因和途径提供了机会。在这里,我们使用群体遗传学框架和下一代测序技术,来评估基因表达变异在胎盘这一自然生物组织中的四个人类群体间是如何分配的。
我们估计,平均而言,胎盘转录组的33.2%、58.9%和7.8%分别由个体内变异、个体间变异和人类群体间变异所解释。此外,当技术和生物学特征被纳入基因表达模型时,它们各自约占基因表达总变异的2%。值得注意的是,群体间显著不同的变异在与免疫反应、细胞信号传导和代谢相关的生物学途径中富集。许多生物学特征在临床医生和进化生物学家可能感兴趣的众多途径中表现出表达的相关变化。最后,我们估计人类胎盘转录组的大部分表现出与中性一致的表达谱;其余的与稳定选择、定向选择或多样化选择一致。
我们将胎盘基因表达变异分配到个体、群体和生物学特征因素中,并确定每种因素如何影响转录组。此外,我们改进了将表达谱与不同形式选择相关联的方法。