Genetic mapping of developmental trajectories for complex traits and diseases.
Genetic mapping of developmental trajectories for complex traits and diseases.
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DOI：
10.1016/j.csbj.2021.05.055
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发表时间：
2021
影响因子：
6
通讯作者：
Elkon R
中科院分区：
文献类型：
--
作者：
Shulman ED;Elkon R
全基因组关联研究已经确定了与复杂的人类特征和疾病相关的许多常见的遗传变异。然而，将GWAs的发现转化为生物学和临床见解是非常具有挑战性的。在这项研究中，我们提出了一种新的生物信息学方法，基于它们与检查发育过程的单细胞(Sc)RNA-seq数据集的集成，来增强对Gwas信号的功能解释。我们的方法执行三个任务：(1)识别细胞分化轨迹和特征之间的联系；(2)阐明作为这种轨迹-特征联系基础的生物过程和分子途径；以及(3)确定携带轨道、途径和特征之间联系的目标基因的优先顺序。我们将我们的方法应用于一组不同病理特征的11个性状，以及不同发育过程的12个scRNA-seq数据集，它很容易检测到公认的生物学联系，包括皮质抑制中间神经元的成熟与精神分裂症、肝细胞与胆固醇水平以及胰腺β-胰岛细胞与2型糖尿病之间的联系。对于这些关联中的每一个，我们的方法都精确地定位了与分化轨迹的动力学和疾病的遗传风险密切相关的顶级候选基因。通过识别轨迹-疾病链接、基础的分子路径和优先考虑候选风险基因，我们的方法提高了对复杂疾病病因学的理解，从而有望加强合理的药物开发，旨在针对介导疾病遗传易感性的特定生物过程。
Genome-wide association studies (GWAS) have identified numerous common genetic variants associated with complex human traits and diseases. However, the translation of GWAS discoveries into biological and clinical insights is highly challenging. In this study, we present a novel bioinformatics approach for enhancing the functional interpretation of GWAS signals, based on their integration with single-cell (sc)RNA-seq datasets that examine developmental processes. Our approach performs three tasks: (1) Identification of links between cell differentiation trajectories and traits; (2) Elucidation of biological processes and molecular pathways that underlie such trajectory-trait links; and (3) Prioritization of target genes that carry the links between trajectories, pathways and traits. We applied our method to a set of 11 traits of various pathologies, and 12 scRNA-seq datasets of diverse developmental processes, and it readily detected well-established biological connections, including those between the maturation of cortical inhibitory interneurons and schizophrenia, hepatocytes and cholesterol levels, and pancreatic beta-islet cells and type-2 diabetes. For each of these associations, our method pinpointed top candidate genes that are strongly associated with both the kinetics of the differentiation trajectory and the disease’s genetic risk. By the identification of trajectory-disease links, molecular pathways that underlie them and prioritizing candidate risk genes, our method improves the understanding of the etiology of complex diseases, and thus holds promise for enhancing rational drug development that is aimed at targeting specific biological processes that mediate the genetic predisposition to diseases.
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影响因子：
64.8
作者：
Cao, Junyue;Spielmann, Malte;Shendure, Jay
通讯作者：
Shendure, Jay
影响因子：
30.8
作者：
Bulik-Sullivan, Brendan K.;Loh, Po-Ru;Finucane, Hilary K.;Ripke, Stephan;Yang, Jian;Patterson, Nick;Daly, Mark J.;Price, Alkes L.;Neale, Benjamin M.
通讯作者：
Neale, Benjamin M.
影响因子：
30.8
作者：
Finucane HK;Reshef YA;Anttila V;Slowikowski K;Gusev A;Byrnes A;Gazal S;Loh PR;Lareau C;Shoresh N;Genovese G;Saunders A;Macosko E;Pollack S;Brainstorm Consortium;Perry JRB;Buenrostro JD;Bernstein BE;Raychaudhuri S;McCarroll S;Neale BM;Price AL
通讯作者：
Price AL
影响因子：
4.5
作者：
Billingsley KJ;Manca M;Gianfrancesco O;Collier DA;Sharp H;Bubb VJ;Quinn JP
通讯作者：
Quinn JP
影响因子：
64.5
作者：
Boyle EA;Li YI;Pritchard JK
通讯作者：
Pritchard JK