論文 - 詳細
| RRC ID | 35654 |
|---|---|
| 著者 | Wagner A, Zarecki R, Reshef L, Gochev C, Sorek R, Gophna U, Ruppin E. |
| タイトル | Computational evaluation of cellular metabolic costs successfully predicts genes whose expression is deleterious. |
| ジャーナル | Proc Natl Acad Sci U S A |
| Abstract |
Gene suppression and overexpression are both fundamental tools in linking genotype to phenotype in model organisms. Computational methods have proven invaluable in studying and predicting the deleterious effects of gene deletions, and yet parallel computational methods for overexpression are still lacking. Here, we present Expression-Dependent Gene Effects (EDGE), an in silico method that can predict the deleterious effects resulting from overexpression of either native or foreign metabolic genes. We first test and validate EDGE's predictive power in bacteria through a combination of small-scale growth experiments that we performed and analysis of extant large-scale datasets. Second, a broad cross-species analysis, ranging from microorganisms to multiple plant and human tissues, shows that genes that EDGE predicts to be deleterious when overexpressed are indeed typically down-regulated. This reflects a universal selection force keeping the expression of potentially deleterious genes in check. Third, EDGE-based analysis shows that cancer genetic reprogramming specifically suppresses genes whose overexpression impedes proliferation. The magnitude of this suppression is large enough to enable an almost perfect distinction between normal and cancerous tissues based solely on EDGE results. We expect EDGE to advance our understanding of human pathologies associated with up-regulation of particular transcripts and to facilitate the utilization of gene overexpression in metabolic engineering. |
| 巻・号 | 110(47) |
| ページ | 19166-71 |
| 公開日 | 2013-11-19 |
| DOI | 10.1073/pnas.1312361110 |
| PII | 1312361110 |
| PMID | 24198337 |
| PMC | PMC3839766 |
| MeSH | Algorithms* Computational Biology / methods* Gene Expression / genetics* Gene Expression Profiling / methods Gene Expression Regulation, Neoplastic / genetics Humans Metabolic Networks and Pathways / genetics* Models, Genetic* |
| IF | 9.412 |
| 引用数 | 14 |
| WOS 分野 | BIOTECHNOLOGY & APPLIED MICROBIOLOGY |
| オルトメトリクス指標 |
オルトメトリクス指標項目
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| 最多言及媒体 | |
| 各媒体での言及数の合計 | 3 |
| 過去6か月間でのオルトメトリクス指標の変動値 | 0.0 |
| リソース情報 | |
| 原核生物(大腸菌) | ME5305(AG1) ASKA library |