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整合小鼠和人类遗传数据可鉴定胆固醇代谢中的致病基因
作者:小柯机器人 发布时间:2020/3/28 22:24:29

近日,美国威斯康星大学麦迪逊分校Brian W. Parks及其团队通过整合小鼠和人类遗传数据鉴定出胆固醇代谢中的致病基因。相关论文于2020年3月19日在线发表在《细胞—代谢》杂志上。

研究人员开发了一种系统的方法,其将小鼠肝脏共表达网络与人类脂质全基因组关联研究(GWAS)数据整合在一起,以鉴别胆固醇和脂质代谢的调节因子。通过这一方法,研究人员鉴定出48个能够在小鼠中重现,并与人类血浆脂质特征相关的基因,以及X染色体上的6个基因。在这54个基因中,有25个以前在脂质代谢中没有发现作用。

基于功能研究并与其他人类脂质GWAS数据集整合,研究人员确定了Sestrin1是与人类血浆胆固醇水平相关的致病基因。这些验证研究表明Sestrin1在多种小鼠模型中影响血浆胆固醇并调节胆固醇的生物合成。总之,这些结果凸显结合小鼠和人类数据集进行研究的潜力,从而可用于鉴定人类脂质GWAS基因座的优先级以及发现脂质基因。

据悉,在GWAS中鉴定联系遗传变异与表型的致病基因是一个具有挑战性的问题。
 
附:英文原文

Title: Integrating Mouse and Human Genetic Data to Move beyond GWAS and Identify Causal Genes in Cholesterol Metabolism

Author: Zhonggang Li, James A. Votava, Gregory J.M. Zajac, Jenny N. Nguyen, Fernanda B. Leyva Jaimes, Sophia M. Ly, Jacqueline A. Brinkman, Marco De Giorgi, Sushma Kaul, Cara L. Green, Samantha L. St. Clair, Sabrina L. Belisle, Julia M. Rios, David W. Nelson, Mary G. Sorci-Thomas, William R. Lagor, Dudley W. Lamming, Chi-Liang Eric Yen, Brian W. Parks

Issue&Volume: 2020-03-19

Abstract: Identifying the causal gene(s) that connects genetic variation to a phenotype is achallenging problem in genome-wide association studies (GWASs). Here, we develop asystematic approach that integrates mouse liver co-expression networks with humanlipid GWAS data to identify regulators of cholesterol and lipid metabolism. Throughour approach, we identified 48 genes showing replication in mice and associated withplasma lipid traits in humans and six genes on the X chromosome. Among these 54 genes,25 have no previously identified role in lipid metabolism. Based on functional studiesand integration with additional human lipid GWAS datasets, we pinpoint Sestrin1 as a causal gene associated with plasma cholesterol levels in humans. Our validationstudies demonstrate that Sestrin1 influences plasma cholesterol in multiple mouse models and regulates cholesterolbiosynthesis. Our results highlight the power of combining mouse and human datasetsfor prioritization of human lipid GWAS loci and discovery of lipid genes.

DOI: 10.1016/j.cmet.2020.02.015

Source: https://www.cell.com/cell-metabolism/fulltext/S1550-4131(20)30074-7

期刊信息

Cell Metabolism:《细胞—代谢》,创刊于2005年。隶属于细胞出版社,最新IF:22.415
官方网址:https://www.cell.com/cell-metabolism/home
投稿链接:https://www.editorialmanager.com/cell-metabolism/default.aspx