Ota Mineto, Spence Jeffrey P, Zeng Tony, Dann Emma, Marson Alexander, Pritchard Jonathan K
Department of Genetics, Stanford University, Stanford CA.
Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA.
bioRxiv. 2025 Jan 24:2025.01.22.634424. doi: 10.1101/2025.01.22.634424.
Genetic association studies provide a unique tool for identifying causal links from genes to human traits and diseases. However, it is challenging to determine the biological mechanisms underlying most associations, and we lack genome-scale approaches for inferring causal mechanistic pathways from genes to cellular functions to traits. Here we propose new approaches to bridge this gap by combining quantitative estimates of gene-trait relationships from loss-of-function burden tests with gene-regulatory connections inferred from Perturb-seq experiments in relevant cell types. By combining these two forms of data, we aim to build causal graphs in which the directional associations of genes with a trait can be explained by their regulatory effects on biological programs or direct effects on the trait. As a proof-of-concept, we constructed a causal graph of the gene regulatory hierarchy that jointly controls three partially co-regulated blood traits. We propose that perturbation studies in trait-relevant cell types, coupled with gene-level effect sizes for traits, can bridge the gap between genetics and biology.
基因关联研究为识别从基因到人类性状和疾病的因果联系提供了一种独特工具。然而，确定大多数关联背后的生物学机制具有挑战性，而且我们缺乏从基因到细胞功能再到性状推断因果机制途径的基因组规模方法。在此，我们提出新方法来弥合这一差距，即将功能丧失负担测试中基因与性状关系的定量估计与从相关细胞类型的Perturb-seq实验推断出的基因调控联系相结合。通过结合这两种形式的数据，我们旨在构建因果图，其中基因与性状的定向关联可以通过它们对生物学程序的调控作用或对性状的直接作用来解释。作为概念验证，我们构建了一个共同控制三种部分共同调控的血液性状的基因调控层次因果图。我们提出，在与性状相关的细胞类型中进行扰动研究，再加上性状的基因水平效应大小，可以弥合遗传学与生物学之间的差距。
