Title |
Two-way mixed-effects methods for joint association analysis using both host and pathogen genomes
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Published in |
Proceedings of the National Academy of Sciences of the United States of America, May 2018
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DOI | 10.1073/pnas.1710980115 |
Pubmed ID | |
Authors |
Miaoyan Wang, Fabrice Roux, Claudia Bartoli, Carine Huard-Chauveau, Christopher Meyer, Hana Lee, Dominique Roby, Mary Sara McPeek, Joy Bergelson |
Abstract |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 11 | 22% |
France | 6 | 12% |
Germany | 4 | 8% |
United Kingdom | 3 | 6% |
Spain | 3 | 6% |
Austria | 1 | 2% |
India | 1 | 2% |
Canada | 1 | 2% |
Netherlands | 1 | 2% |
Other | 2 | 4% |
Unknown | 16 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 28 | 57% |
Scientists | 21 | 43% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 131 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 30 | 23% |
Researcher | 29 | 22% |
Student > Master | 14 | 11% |
Student > Bachelor | 13 | 10% |
Student > Doctoral Student | 9 | 7% |
Other | 17 | 13% |
Unknown | 19 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 63 | 48% |
Biochemistry, Genetics and Molecular Biology | 21 | 16% |
Environmental Science | 5 | 4% |
Engineering | 4 | 3% |
Mathematics | 3 | 2% |
Other | 11 | 8% |
Unknown | 24 | 18% |