ArticleNature communications2019
Changes in gene expression predictably shift and switch genetic interactions.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 44 citations in OpenAlex.
- Epistatic impacts of cis- and trans-regulatory mutations on the distribution of mutational effects for gene expression in Saccharomyces cerevisiae.Molecular biology and evolution · 2026Article
- SynFit: Synergistic Contrastive Learning for Multi-Objective Protein Fitness Prediction and Optimization.bioRxiv : the preprint server for biology · 2026Article
- HyperdCas12a-based multiplexed genetic regulation in Candida albicans.Nucleic acids research · 2025Article
- Sex-Specific Gene Expression Differences in Varicose Veins.Biomedicines · 2025Article
- Modified pea apyrase has altered nuclear functions and enhances the growth of yeast and Arabidopsis.Frontiers in plant science · 2025Article
- Data-driven discovery of the interplay between genetic and environmental factors in bacterial growth.Communications biology · 2024Article
- MAGICAL: A multi-class classifier to predict synthetic lethal and viable interactions using protein-protein interaction network.PLoS computational biology · 2024Article
- Deep mutational scanning quantifies DNA binding and predicts clinical outcomes of PAX6 variants.Molecular systems biology · 2024Article
- Genotype sampling for deep-learning assisted experimental mapping of a combinatorially complete fitness landscape.Bioinformatics (Oxford, England) · 2024Article
- Arsenic and UVR co-exposure results in unique gene expression profile identifying key co-carcinogenic mechanisms.Toxicology and applied pharmacology · 2024Article
- Design and deep learning of synthetic B-cell-specific promoters.Nucleic acids research · 2023Article
- Dominance vs epistasis: the biophysical origins and plasticity of genetic interactions within and between alleles.Nature communications · 2023Article
- Evolvability-enhancing mutations in the fitness landscapes of an RNA and a protein.Nature communications · 2023Article
- Environment-dependent epistasis increases phenotypic diversity in gene regulatory networks.Science advances · 2023Article
- A global genetic interaction network by single-cell imaging and machine learning.Cell systems · 2023Article
- Epistasis between promoter activity and coding mutations shapes gene evolvability.Science advances · 2023Article
- Deep mutational scanning: A versatile tool in systematically mapping genotypes to phenotypes.Frontiers in genetics · 2023Review
- Binary combinatorial scanning reveals potent poly-alanine-substituted inhibitors of protein-protein interactions.Communications chemistry · 2022Article
- On the incongruence of genotype-phenotype and fitness landscapes.PLoS computational biology · 2022Article
- Identifying significant genes and functionally enriched pathways in familial hypercholesterolemia using integrated gene co-expression network analysis.Saudi journal of biological sciences · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-additive interactions between mutations occur extensively and also change across conditions, making genetic prediction a difficult challenge. To better understand the plasticity of genetic interactions (epistasis), we combine mutations in a single protein performing a single function (a transcriptional repressor inhibiting a target gene). Even in this minimal system, genetic interactions switch from positive (suppressive) to negative (enhancing) as the expression of the gene changes. These seemingly complicated changes can be predicted using a mathematical model that propagates the effects of mutations on protein folding to the cellular phenotype. More generally, changes in gene expression should be expected to alter the effects of mutations and how they interact whenever the relationship between expression and a phenotype is nonlinear, which is the case for most genes. These results have important implications for understanding genotype-phenotype maps and illustrate how changes in genetic interactions can often-but not always-be predicted by hierarchical mechanistic models.
Indexed as
Identifiers
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.