ArticlePLoS genetics2011
Integrated genome-scale prediction of detrimental mutations in transcription networks.
Article in PLoS genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Population genomics and transcriptional consequences of regulatory motif variation in globally diverse Saccharomyces cerevisiae strains.Molecular biology and evolution · 2013Article
- Genotype to phenotype: lessons from model organisms for human genetics.Nature reviews. Genetics · 2013Review
- Analyzing the genomic variation of microbial cell factories in the era of "New Biotechnology".Computational and structural biotechnology journal · 2012Review
- Predicting phenotypic variation in yeast from individual genome sequences.Nature genetics · 2011Article
- Translating Mendelian and complex inheritance of Alzheimer's disease genes for predicting unique personal genome variants.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. The consequences of gene inhibition have been systematically studied and can be predicted reasonably well across a genome. However, many sequence variants important for disease and evolution may alter gene regulation rather than gene function. The consequences of altering a regulatory interaction (or "edge") rather than a gene (or "node") in a network have not been as extensively studied. Here we use an integrative analysis and evolutionary conservation to identify features that predict when the loss of a regulatory interaction is detrimental in the extensively mapped transcription network of budding yeast. Properties such as the strength of an interaction, location and context in a promoter, regulator and target gene importance, and the potential for compensation (redundancy) associate to some extent with interaction importance. Combined, however, these features predict quite well whether the loss of a regulatory interaction is detrimental across many promoters and for many different transcription factors. Thus, despite the potential for regulatory diversity, common principles can be used to understand and predict when changes in regulation are most harmful to an organism.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.