ArticleGenetics2010
Mapping environment-specific quantitative trait loci.
Article in Genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- A guide to plant breeding for animal breeders.G3 (Bethesda, Md.) · 2026Review
- Construction of a high-density genetic linkage map and QTL mapping for bioenergy-related traits in sweet sorghum [Frontiers in plant science · 2023Article
- A simulation-based assessment of the efficiency of QTL mapping under environment and genotype x environment interaction effects.PloS one · 2023Article
- Comparing a Mixed Model Approach to Traditional Stability Estimators for Mapping Genotype by Environment Interactions and Yield Stability in Soybean [Frontiers in plant science · 2021Article
- Quantitative Trait Nucleotides Impacting the Technological Performances of IndustrialFrontiers in genetics · 2019Article
- Dissection of the molecular bases of genotype x environment interactions: a study of phenotypic plasticity of Saccharomyces cerevisiae in grape juices.BMC genomics · 2018Article
- Article
- Inclusive Composite Interval Mapping of QTL by Environment Interactions in Biparental Populations.PloS one · 2015Article
- Construction of a SSR-based genetic map and identification of QTLs for catechins content in tea plant (Camellia sinensis).PloS one · 2014Article
- Genotype by environment interaction of quantitative traits: a case study in barley.G3 (Bethesda, Md.) · 2012Article
- An expectation and maximization algorithm for estimating Q X E interaction effects.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012Article
- Bias correction for estimated QTL effects using the penalized maximum likelihood method.Heredity · 2012Article
- A new broccoli × broccoli immortal mapping population and framework genetic map: tools for breeders and complex trait analysis.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Environment-specific quantitative trait loci (QTL) refer to QTL that express differently in different environments, a phenomenon called QTL-by-environment (Q × E) interaction. Q × E interaction is a difficult problem extended from traditional QTL mapping. The mixture model maximum-likelihood method is commonly adopted for interval mapping of QTL, but the method is not optimal in handling QTL interacting with environments. We partitioned QTL effects into main and interaction effects. The main effects are represented by the means of QTL effects in all environments and the interaction effects are represented by the variances of the QTL effects across environments. We used the Markov chain Monte Carlo (MCMC) implemented Bayesian method to estimate both the main and the interaction effects. The residual error covariance matrix was modeled using the factor analytic covariance structure. A simulation study showed that the factor analytic structure is robust and can handle other structures as special cases. The method was also applied to Q × E interaction mapping for the yield trait of barley. Eight markers showed significant main effects and 18 markers showed significant Q × E interaction. The 18 interacting markers were distributed across all seven chromosomes of the entire genome. Only 1 marker had both the main and the Q × E interaction effects. Each of the other markers had either a main effect or a Q × E interaction effect but not both.
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.