期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2018
卷号：115
期号：24
页码：E5440-E5449
DOI：10.1073/pnas.1710980115
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Infectious diseases are often affected by specific pairings of hosts and pathogens and therefore by both of their genomes. The integration of a pair of genomes into genome-wide association mapping can provide an exquisitely detailed view of the genetic landscape of complex traits. We present a statistical method, ATOMM (Analysis with a Two-Organism Mixed Model), that maps a trait of interest to a pair of genomes simultaneously; this method makes use of whole-genome sequence data for both host and pathogen organisms. ATOMM uses a two-way mixed-effect model to test for genetic associations and cross-species genetic interactions while accounting for sample structure including interactions between the genetic backgrounds of the two organisms. We demonstrate the applicability of ATOMM to a joint association study of quantitative disease resistance (QDR) in the Arabidopsis thaliana–Xanthomonas arboricola pathosystem. Our method uncovers a clear host–strain specificity in QDR and provides a powerful approach to identify genetic variants on both genomes that contribute to phenotypic variation.
关键词：statistical genetics ; genome-wide association studies ; mixed-effect models ; host–pathogen interaction ; population structure
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