The availability of genome-wide transcriptomic and proteomic datasets is ever-increasing and often not used beyond initial publication. Here, we applied module-based coexpression network analysis to a comprehensive catalog of 35 mouse genome-wide liver expression datasets (encompassing more than 3800 mice) with the goal of identifying and validating unknown genes involved in cholesterol metabolism. From these 35 datasets, we identified a conserved module of genes enriched with cholesterol biosynthetic genes. Using a systematic approach across the 35 datasets, we identified three genes (, , and ) with no known role in cholesterol metabolism. We then performed functional validation studies and show that each gene is capable of regulating cholesterol metabolism. For the glycolytic gene, , we demonstrate that it contributes to de novo cholesterol biosynthesis and regulates cholesterol and triglyceride levels in mice. As is located within a genome-wide significant genome-wide association studies locus for human plasma cholesterol levels, our studies establish as a causal gene within this locus. Through our work, we develop a framework for leveraging mouse genome-wide liver datasets for identifying and validating genes involved in cholesterol metabolism.

中文翻译：

---

从数千只小鼠肝脏中挖掘胆固醇基因，确定醛缩酶 C 是胆固醇生物合成的调节剂

全基因组转录组和蛋白质组数据集的可用性不断增加，并且通常在最初发布后就不再使用。在这里，我们将基于模块的共表达网络分析应用于 35 个小鼠全基因组肝脏表达数据集（包含 3800 多只小鼠）的综合目录，目的是识别和验证参与胆固醇代谢的未知基因。从这 35 个数据集中，我们鉴定了富含胆固醇生物合成基因的保守基因模块。通过对 35 个数据集采用系统方法，我们确定了三个在胆固醇代谢中没有已知作用的基因（、、和）。然后我们进行了功能验证研究，结果表明每个基因都能够调节胆固醇代谢。对于糖酵解基因，我们证明它有助于胆固醇从头生物合成并调节小鼠的胆固醇和甘油三酯水平。由于它位于人类血浆胆固醇水平的全基因组显着全基因组关联研究基因座内，我们的研究确定该基因座内有一个因果基因。通过我们的工作，我们开发了一个框架，利用小鼠全基因组肝脏数据集来识别和验证参与胆固醇代谢的基因。