Sara Schneider, Xue Zhong, Emre E. Turer, Jeffrey A. SoRelle, Sydney Cooper, Miao Tang, Jamie Russell, Stephen Aplin Lyon, Xiaoming Zhan, Zhao Zhang, Priscilla Anderton, Katie Keller, Andrew Sakla, Jennifer Cardin, Bruce Beutler, Lei Sun, Jiexia Quan, Roxana Farokhnia, Sara Mazal, Carol Wise, Duanwu Zhang, Lijing Su, Jin Huk Choi, Qihua Sun, Baifang Qin, Braden Hayse, Hexin Shi, Brandon Nguyen, Xiaohong Li, Hannah Coco, Andrew Wadley, Darui Xu, Meron Tadesse, William McAlpine, Eva Marie Y. Moresco, Tao Yue, Gabrielle Coolbaugh, Ying Wang, Chun Hui Bu, Sara Hildebrand, Evan Nair-Gill, Rochelle Simpson, Elena Mahrt, Aijie Liu, Jonathan J. Rios, Jianhui Wang, Takuma Misawa, Edward Rodriguez, Sara Ludwig, Mihwa Choi, Lindsay Scott, Amanda Press, Dawson Medler, Tiffany Collie, and Kuan Wen Wang
Forward genetic studies use meiotic mapping to adduce evidence that a particular mutation, normally induced by a germline mutagen, is causative of a particular phenotype. Particularly in small pedigrees, cosegregation of multiple mutations, occasional unawareness of mutations, and paucity of homozygotes may lead to erroneous declarations of cause and effect. We sought to improve the identification of mutations causing immune phenotypes in mice by creating Candidate Explorer (CE), a machine-learning software program that integrates 67 features of genetic mapping data into a single numeric score, mathematically convertible to the probability of verification of any putative mutation–phenotype association. At this time, CE has evaluated putative mutation–phenotype associations arising from screening damaging mutations in ∼55% of mouse genes for effects on flow cytometry measurements of immune cells in the blood. CE has therefore identified more than half of genes within which mutations can be causative of flow cytometric phenovariation in Mus musculus. The majority of these genes were not previously known to support immune function or homeostasis. Mouse geneticists will find CE data informative in identifying causative mutations within quantitative trait loci, while clinical geneticists may use CE to help connect causative variants with rare heritable diseases of immunity, even in the absence of linkage information. CE displays integrated mutation, phenotype, and linkage data, and is freely available for query online.