ReviewTrends in genetics : TIG2015
Higher-order genetic interactions and their contribution to complex traits.
Review in Trends in genetics : TIG, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 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.
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.
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Who cites it
86 citing papers in PubMed.
- Deconstruction ofbioRxiv : the preprint server for biology · 2026Article
- Predictive models of the genetic bases underlying budding yeast fitness in multiple environments.NAR genomics and bioinformatics · 2026Article
- Article
- A novel explainable deep-learning approach for network analysis of epistatic interactions.NAR genomics and bioinformatics · 2026Article
- Predictive models of the genetic bases underlying budding yeast fitness in multiple environments.bioRxiv : the preprint server for biology · 2025Article
- Global epistasis in budding yeast driven by many natural variants whose effects scale with fitness.Genetics · 2025Article
- Integrating multi-omics and machine learning for disease resistance prediction in legumes.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Genetic Background and Gene Essentiality.Genes · 2025Article
- Epistasis and cryptic QTL identified using modified bulk segregant analysis of copper resistance in budding yeast.Genetics · 2025Article
- Modeling gene interactions in polygenic prediction via geometric deep learning.Genome research · 2025Article
- Epistasis and cryptic QTL identified using modified bulk segregant analysis of copper resistance in budding yeast.bioRxiv : the preprint server for biology · 2024Article
- Epistasis and pleiotropy-induced variation for plant breeding.Plant biotechnology journal · 2024Review
- A phenotypic drug discovery approach by latent interaction in deep learning.Royal Society open science · 2024Article
- Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations.PLoS biology · 2024Article
- Genome-scale analysis of interactions between genetic perturbations and natural variation.Nature communications · 2024Article
- Genome-scale analysis of interactions between genetic perturbations and natural variation.bioRxiv : the preprint server for biology · 2024Article
- Building synthetic chromosomes from natural DNA.Nature communications · 2023Article
- The use of weighted multiple linear regression to estimate QTL × QTL × QTL interaction effects of winter wheat (Triticum aestivum L.) doubled-haploid lines.Journal of applied genetics · 2023Article
- Higher-order epistasis shapes natural variation in germ stem cell niche activity.Nature communications · 2023Article
- Widespread epistasis among beneficial genetic variants revealed by high-throughput genome editing.Cell genomics · 2023Article
26 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The contribution of genetic interactions involving three or more loci to complex traits is poorly understood. These higher-order genetic interactions (HGIs) are difficult to detect in genetic mapping studies, therefore, few examples of them have been described. However, the lack of data on HGIs should not be misconstrued as proof that this class of genetic effect is unimportant. To the contrary, evidence from model organisms suggests that HGIs frequently influence genetic studies and contribute to many complex traits. Here, we review the growing literature on HGIs and discuss the future of research on this topic.
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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.