Webster Amy K, Willis John H, Johnson Erik, Sarkies Peter, Phillips Patrick C
Institute of Ecology and Evolution, University of Oregon, Eugene, United States.
Department of Biological Science, Florida State University, Tallahassee, United States.
Elife. 2025 Sep 2;14:RP106525. doi: 10.7554/eLife.106525.
In recent decades, genome-wide association studies (GWAS) have been the major approach to understand the biological basis of individual differences in traits and diseases. However, GWAS approaches have limited predictive power to explain individual differences, particularly for complex traits and diseases in which environmental factors play a substantial role in their etiology. Indeed, individual differences persist even in genetically identical individuals, although fully separating genetic and environmental causation is difficult in most organisms. To understand the basis of individual differences in the absence of genetic differences, we measured two quantitative reproductive traits in 180 genetically identical young adult roundworms in a shared environment and performed single-individual transcriptomics on each worm. We identified hundreds of genes for which expression variation was strongly associated with reproductive traits, some of which depended on individuals' historical environments and some of which was random. Multiple small sets of genes together were highly predictive of reproductive traits, explaining on average over half and over a quarter of variation in the two traits. We manipulated mRNA levels of predictive genes to identify a set of causal genes, demonstrating the utility of this approach for both prediction and understanding underlying biology. Finally, we found that the chromatin environment of predictive genes was enriched for H3K27 trimethylation, suggesting that gene expression variation may be driven in part by chromatin structure. Together, this work shows that individual, non-genetic differences in gene expression are both highly predictive and causal in shaping reproductive traits.
近几十年来，全基因组关联研究（GWAS）一直是理解个体在性状和疾病方面差异的生物学基础的主要方法。然而，GWAS方法在解释个体差异方面的预测能力有限，尤其是对于复杂性状和疾病，其中环境因素在其病因中起着重要作用。事实上，即使在基因相同的个体中，个体差异仍然存在，尽管在大多数生物体中完全区分遗传和环境因果关系很困难。为了在没有遗传差异的情况下理解个体差异的基础，我们在共享环境中测量了180条基因相同的年轻成年蛔虫的两个定量生殖性状，并对每条蛔虫进行了单个体转录组学分析。我们鉴定出数百个基因，其表达变异与生殖性状密切相关，其中一些取决于个体的历史环境，一些是随机的。多组少量基因共同对生殖性状具有高度预测性，平均解释了这两个性状中超过一半和超过四分之一的变异。我们操纵预测基因的mRNA水平以鉴定一组因果基因，证明了这种方法在预测和理解潜在生物学方面的实用性。最后，我们发现预测基因的染色质环境富含H3K27三甲基化，表明基因表达变异可能部分由染色质结构驱动。总之，这项工作表明基因表达中的个体非遗传差异在塑造生殖性状方面既具有高度预测性又具有因果性。
