Linking traits based on their shared molecular mechanisms
There is growing recognition that co-morbidity and co-occurrence of disease traits are often determined by shared genetic and molecular mechanisms. In most cases, however, the specific mechanisms that lead to such trait–trait relationships are yet unknown. Here we present an analysis of a broad spec...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2015-03-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/04346 |
| _version_ | 1811253381904203776 |
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| author | Yael Oren Aharon Nachshon Amit Frishberg Roni Wilentzik Irit Gat-Viks |
| author_facet | Yael Oren Aharon Nachshon Amit Frishberg Roni Wilentzik Irit Gat-Viks |
| author_sort | Yael Oren |
| collection | DOAJ |
| description | There is growing recognition that co-morbidity and co-occurrence of disease traits are often determined by shared genetic and molecular mechanisms. In most cases, however, the specific mechanisms that lead to such trait–trait relationships are yet unknown. Here we present an analysis of a broad spectrum of behavioral and physiological traits together with gene-expression measurements across genetically diverse mouse strains. We develop an unbiased methodology that constructs potentially overlapping groups of traits and resolves their underlying combination of genetic loci and molecular mechanisms. For example, our method predicts that genetic variation in the Klf7 gene may influence gene transcripts in bone marrow-derived myeloid cells, which in turn affect 17 behavioral traits following morphine injection; this predicted effect of Klf7 is consistent with an in vitro perturbation of Klf7 in bone marrow cells. Our analysis demonstrates the utility of studying hidden causative mechanisms that lead to relationships between complex traits. |
| first_indexed | 2024-04-12T16:50:03Z |
| format | Article |
| id | doaj.art-8deb23f6cd2547d6b46939cb08073f46 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T16:50:03Z |
| publishDate | 2015-03-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-8deb23f6cd2547d6b46939cb08073f462022-12-22T03:24:25ZengeLife Sciences Publications LtdeLife2050-084X2015-03-01410.7554/eLife.04346Linking traits based on their shared molecular mechanismsYael Oren0Aharon Nachshon1Amit Frishberg2Roni Wilentzik3Irit Gat-Viks4Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, IsraelDepartment of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, IsraelDepartment of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, IsraelDepartment of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, IsraelDepartment of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, IsraelThere is growing recognition that co-morbidity and co-occurrence of disease traits are often determined by shared genetic and molecular mechanisms. In most cases, however, the specific mechanisms that lead to such trait–trait relationships are yet unknown. Here we present an analysis of a broad spectrum of behavioral and physiological traits together with gene-expression measurements across genetically diverse mouse strains. We develop an unbiased methodology that constructs potentially overlapping groups of traits and resolves their underlying combination of genetic loci and molecular mechanisms. For example, our method predicts that genetic variation in the Klf7 gene may influence gene transcripts in bone marrow-derived myeloid cells, which in turn affect 17 behavioral traits following morphine injection; this predicted effect of Klf7 is consistent with an in vitro perturbation of Klf7 in bone marrow cells. Our analysis demonstrates the utility of studying hidden causative mechanisms that lead to relationships between complex traits.https://elifesciences.org/articles/04346computational biologyphenome connectioncausative networkrecombinant inbred mouse strain |
| spellingShingle | Yael Oren Aharon Nachshon Amit Frishberg Roni Wilentzik Irit Gat-Viks Linking traits based on their shared molecular mechanisms eLife computational biology phenome connection causative network recombinant inbred mouse strain |
| title | Linking traits based on their shared molecular mechanisms |
| title_full | Linking traits based on their shared molecular mechanisms |
| title_fullStr | Linking traits based on their shared molecular mechanisms |
| title_full_unstemmed | Linking traits based on their shared molecular mechanisms |
| title_short | Linking traits based on their shared molecular mechanisms |
| title_sort | linking traits based on their shared molecular mechanisms |
| topic | computational biology phenome connection causative network recombinant inbred mouse strain |
| url | https://elifesciences.org/articles/04346 |
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