Direct Testing for Allele-Specific Expression Differences Between Conditions

G3: Genes, Genomes, Genetics

article

Luis León-Novelo¹  Alison R. Gerken²  Rita M. Graze³  Lauren M. McIntyre⁴  Fabio Marroni⁵ 

[1] Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston-School of Public Health, Texas 77030;United States Department of Agriculture, Agricultural Research Service, Center for Grain and Animal Health Research, Manhattan, Kansas 66502;Department of Biological Sciences, Auburn University, Alabama 36849;Genetics Institute and Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, Florida 32603;Dipartimento di Scienze Agroalimentari, Ambientali e Animali, Università di Udine, 33100, Italy;Istituto di Genomica Applicata, 33100 Udine, Italy

关键词: robust regulation;    allelic imbalance;    allele-specific expression;    gene regulatory networks;   

DOI  :  10.1534/g3.117.300139

学科分类：社会科学、人文和艺术（综合）

来源: Genetics Society of America

【 摘 要 】

Allelic imbalance (AI) indicates the presence of functional variation in cis regulatory regions. Detecting cis regulatory differences using AI is widespread, yet there is no formal statistical methodology that tests whether AI differs between conditions. Here, we present a novel model and formally test differences in AI across conditions using Bayesian credible intervals. The approach tests AI by environment (G×E) interactions, and can be used to test AI between environments, genotypes, sex, and any other condition. We incorporate bias into the modeling process. Bias is allowed to vary between conditions, making the formulation of the model general. As gene expression affects power for detection of AI, and, as expression may vary between conditions, the model explicitly takes coverage into account. The proposed model has low type I and II error under several scenarios, and is robust to large differences in coverage between conditions. We reanalyze RNA-seq data from a Drosophila melanogaster population panel, with F1 genotypes, to compare levels of AI between mated and virgin female flies, and we show that AI × genotype interactions can also be tested. To demonstrate the use of the model to test genetic differences and interactions, a formal test between two F1s was performed, showing the expected 20% difference in AI. The proposed model allows a formal test of G×E and G×G, and reaffirms a previous finding that cis regulation is robust between environments.

【 授权许可】

CC BY|CC BY-NC