Abstract：
In aging, physiologic networks decline in function at rates that differ between individuals, producing a wide distribution of lifespan. Though 70% of human lifespan variance remains unexplained by heritable factors, little is known about the intrinsic sources of physiologic heterogeneity in aging. To understand how complex physiologic networks generate lifespan variation, new methods are needed. Here, we present Asynch-seq, an approach that uses gene-expression heterogeneity within isogenic populations to study the processes generating lifespan variation. By collecting thousands of single-individual transcriptomes, we capture the Caenorhabditis elegans \"pan-transcriptome\"-a highly resolved atlas of non-genetic variation. We use our atlas to guide a large-scale perturbation screen that identifies the decoupling of total mRNA content between germline and soma as the largest source of physiologic heterogeneity in aging, driven by pleiotropic genes whose knockdown dramatically reduces lifespan variance. Our work demonstrates how systematic mapping of physiologic heterogeneity can be applied to reduce inter-individual disparities in aging.
摘要：
在衰老中，生理网络的功能下降速度在个体之间不同，产生广泛的寿命分布。尽管70％的人类寿命差异仍然无法由遗传因素解释，关于衰老生理异质性的内在来源知之甚少。要了解复杂的生理网络如何产生寿命变化，需要新的方法。这里,我们提出Asynch-seq，一种使用等基因种群内基因表达异质性来研究产生寿命变异的过程的方法。通过收集数千个单个转录组，我们捕获了秀丽隐杆线虫“泛转录组”-非遗传变异的高度分辨图谱。我们使用我们的地图集来指导大规模的扰动筛选，确定种系和体细胞之间的总mRNA含量的解耦是衰老中生理异质性的最大来源。由多效基因驱动，这些基因的敲除大大降低了寿命差异。我们的工作证明了如何应用生理异质性的系统映射来减少衰老中的个体间差异。
