Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA.
Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA.
Cell. 2018 Jan 25;172(3):478-490.e15. doi: 10.1016/j.cell.2017.12.015.
Understanding the sequence determinants that give rise to diversity among individuals and species is the central challenge of genetics. However, despite ever greater numbers of sequenced genomes, most genome-wide association studies cannot distinguish causal variants from linked passenger mutations spanning many genes. We report that this inherent challenge can be overcome in model organisms. By pushing the advantages of inbred crossing to its practical limit in Saccharomyces cerevisiae, we improved the statistical resolution of linkage analysis to single nucleotides. This "super-resolution" approach allowed us to map 370 causal variants across 26 quantitative traits. Missense, synonymous, and cis-regulatory mutations collectively gave rise to phenotypic diversity, providing mechanistic insight into the basis of evolutionary divergence. Our data also systematically unmasked complex genetic architectures, revealing that multiple closely linked driver mutations frequently act on the same quantitative trait. Single-nucleotide mapping thus complements traditional deletion and overexpression screening paradigms and opens new frontiers in quantitative genetics.
理解导致个体和物种多样性的序列决定因素是遗传学的核心挑战。然而，尽管测序的基因组数量不断增加，但大多数全基因组关联研究无法区分因果变体与跨越许多基因的连锁乘客突变。我们报告说，这种内在的挑战可以在模式生物中克服。通过将近交杂交的优势推向其在酿酒酵母中的实际极限，我们将连锁分析的统计分辨率提高到了单个核苷酸。这种“超分辨率”方法使我们能够在 26 个数量性状上定位 370 个因果变体。错义、同义和顺式调控突变共同导致了表型多样性，为进化分歧的基础提供了机制上的见解。我们的数据还系统地揭示了复杂的遗传结构，表明多个紧密连锁的驱动突变经常作用于相同的数量性状。因此，单核苷酸作图补充了传统的缺失和过表达筛选范式，并为数量遗传学开辟了新的前沿。
