Fairfield Heather, Srivastava Anuj, Ananda Guruprasad, Liu Rangjiao, Kircher Martin, Lakshminarayana Anuradha, Harris Belinda S, Karst Son Yong, Dionne Louise A, Kane Coleen C, Curtain Michelle, Berry Melissa L, Ward-Bailey Patricia F, Greenstein Ian, Byers Candice, Czechanski Anne, Sharp Jocelyn, Palmer Kristina, Gudis Polyxeni, Martin Whitney, Tadenev Abby, Bogdanik Laurent, Pratt C Herbert, Chang Bo, Schroeder David G, Cox Gregory A, Cliften Paul, Milbrandt Jeffrey, Murray Stephen, Burgess Robert, Bergstrom David E, Donahue Leah Rae, Hamamy Hanan, Masri Amira, Santoni Federico A, Makrythanasis Periklis, Antonarakis Stylianos E, Shendure Jay, Reinholdt Laura G
The Jackson Laboratory, Bar Harbor, Maine 04609, USA;
The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA;
Genome Res. 2015 Jul;25(7):948-57. doi: 10.1101/gr.186882.114. Epub 2015 Apr 27.
Spontaneously arising mouse mutations have served as the foundation for understanding gene function for more than 100 years. We have used exome sequencing in an effort to identify the causative mutations for 172 distinct, spontaneously arising mouse models of Mendelian disorders, including a broad range of clinically relevant phenotypes. To analyze the resulting data, we developed an analytics pipeline that is optimized for mouse exome data and a variation database that allows for reproducible, user-defined data mining as well as nomination of mutation candidates through knowledge-based integration of sample and variant data. Using these new tools, putative pathogenic mutations were identified for 91 (53%) of the strains in our study. Despite the increased power offered by potentially unlimited pedigrees and controlled breeding, about half of our exome cases remained unsolved. Using a combination of manual analyses of exome alignments and whole-genome sequencing, we provide evidence that a large fraction of unsolved exome cases have underlying structural mutations. This result directly informs efforts to investigate the similar proportion of apparently Mendelian human phenotypes that are recalcitrant to exome sequencing.
100多年来,自发产生的小鼠突变一直是理解基因功能的基础。我们利用外显子组测序来确定172种不同的孟德尔疾病自发产生的小鼠模型的致病突变,这些模型包括广泛的临床相关表型。为了分析所得数据,我们开发了一个针对小鼠外显子组数据进行优化的分析流程以及一个变异数据库,该数据库允许进行可重复的、用户定义的数据挖掘,并通过基于知识的样本和变异数据整合来提名突变候选者。使用这些新工具,在我们的研究中为91个(53%)品系鉴定出了推定的致病突变。尽管潜在的无限谱系和可控繁殖提供了更强的能力,但我们约一半的外显子组病例仍未得到解决。通过对外显子组比对进行人工分析和全基因组测序相结合,我们提供了证据表明,很大一部分未解决的外显子组病例存在潜在的结构突变。这一结果直接为调查外显子组测序难以解决的类似比例的明显孟德尔人类表型的研究工作提供了信息。