Interpretation, Stratification and Evidence for Sequence Variants Affecting mRNA Splicing in Complete Human Genome Sequences

作     者：Ben C.Shirley Eliseos J.Mucaki Tyson Whitehead Paul I.Costea Pelin Akan Peter K.Rogan 

作者机构：Department of Computer ScienceMiddlesex CollegeThe University of Western Ontario Department of BiochemistrySchulich School of Medicine and DentistryThe University of Western Ontario SHARCNET Royal Institute of TechnologyScience for Life Laboratory Cytognomix Inc. 

出 版 物：《Genomics, Proteomics & Bioinformatics》 (基因组蛋白质组与生物信息学报（英文版）)

年 卷 期：2013年第11卷第2期

页      面：77-85页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 081704[工学-应用化学] 1001[医学-基础医学(可授医学、理学学位)] 07[理学] 08[工学] 0817[工学-化学工程与技术] 071007[理学-遗传学] 0714[理学-统计学（可授理学、经济学学位）] 0703[理学-化学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：support from Natural Sciences and Engineering Research Council (Discovery Grant 371758-2009) (PKR) Canadian Breast Cancer Foundation(PKR) Compute Canada (PKR),Canadian Foundation for Innovation,Canada Research Chairs,MITACS Accelerate(BCS) the Ontario Graduate Scholarship Programs (BCS) and Cytognomix Inc 

主　　题：Mutation mRNA splicing Information theory Next-generation sequencing Genome interpretation 

摘      要：Information theory-based methods have been shown to be sensitive and specific for pre- dicting and quantifying the effects of non-coding mutations in Mendelian diseases. We present the Shannon pipeline software for genome-scale mutation analysis and provide evidence that the soft- ware predicts variants affecting mRNA splicing. Individual information contents （in bits） of refer- ence and variant splice sites are compared and significant differences are annotated and prioritized. The software has been implemented for CLC-Bio Genomics platform. Annotation indicates the context of novel mutations as well as common and rare SNPs with splicing effects. Potential natural and cryptic mRNA splicing variants are identified, and null mutations are distinguished from leaky mutations. Mutations and rare SNPs were predicted in genomes of three cancer cell lines （U2OS, U251 and A431）, which were supported by expression analyses. After filtering, tractable numbers of potentially deleterious variants are predicted by the software, suitable for further laboratory investigation. In these cell lines, novel functional variants comprised 6-17 inactivating mutations, 1 5 leaky mutations and 6-13 cryptic splicing mutations. Predicted effects were validated by RNA-seq analysis of the three aforementioned cancer cell lines, and expression microarray analysis of SNPs in HapMap cell lines.