Correction: Genotype-by-environment interactions affecting heterosis in maize.
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ABSTRACT:
SUBMITTER: Li Z
PROVIDER: S-EPMC6681948 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The environment can influence heterosis, the phenomena in which the offspring of two inbred parents exhibits phenotypic performance beyond the inbred parents for specific traits. In this study we measured 25 traits in a set of 47 maize hybrids and their inbred parents grown in 16 different environments with varying levels of average productivity. By quantifying 25 vegetative and reproductive traits across the life cycle we were able to analyze interactions between the environment and multiple distinct instances of heterosis. The magnitude and rank among hybrids for better-parent heterosis (BPH) varied for the different traits and environments. Across the traits, a higher within plot variance was observed for inbred lines compared to hybrids. However, for most traits, variance across environments was not significantly different for inbred lines compared to hybrids. Further, for many traits the correlations of BPH to hybrid performance and BPH to better parent performance were of comparable magnitude. These results indicate that inbred lines and hybrids show similar trends in environmental response and both are contributing to observed genotype-by-environment interactions for heterosis. This study highlights the degree of heterosis is not an inherent trait of a specific hybrid, but varies depending on the trait measured and the environment where that trait is measured. Studies that attempt to correlate molecular processes with heterosis are hindered by the fact that heterosis is not a consistent attribute of a specific hybrid.
| S-EPMC5771596 | biostudies-literature
Project description:Background: Cases where genotype-phenotype relationships depend on environmental factors have been quantified for many complex diseases. Such genotype-environment interactions (GEI or GxE) may also affect expression Quantitative Trait Loci (eQTL) present in tissues critical for the manifestation of disease. To assess this hypothesis, we performed an analysis of eQTL-GEI resulting from an individual's smoking environment in the lung small airway epithelium (SAE). While the SAE is challenging to sample, this is the cell population that shows the first signs of smoking related stress and gene expression in the SAE appears to play a role in mediating smoking effects on lung disease. Results: We used expression microarrays to assay the SAE transcriptome for a small sample of African-American individuals and we analyzed SNPs genotyped genome-wide to identify GEI affecting eQTL. While a genome-wide trans- analysis identified few instances of GEI after a multiple test correction, an analysis of cis-genotypes identified a small but significant number of GEI affecting lung SAE gene expression. We determined that significant cases of eQTL-GEI were not driven by outliers and we were also able to find corroborative evidence for a few of these eQTL-GEI in a small, independent sample of individuals of European ancestry. Conclusion: Given that the power of GEI tests is low compared to tests of genotype association and that the total sample size of our study was small, including only 61 African American individuals in our focal population, the identification of significant GEI in our study implies that there may be considerable genotype-specific effects on eQTL due to smoking environment. We discuss individual cases of GEI of interest for lung disease, such as SDC1 and ZAK, as well as the broader implications of our results for the analysis of eQTL and for genome-wide association analysis of complex diseases.
2024-06-05 | GSE23087 | GEO
Project description:[This corrects the article DOI: 10.1371/journal.pgen.1007019.].
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Project description:Plant growth and productivity are greatly affected by drought, which is likely to become more threatening with the predicted global temperature increase. Understanding the genetic architecture of complex quantitative traits and their interaction with water availability may lead to improved crop adaptation to a wide range of environments. Here, the genetic basis of 20 physiological and morphological traits is explored by describing plant performance and growth in a Brassica rapa recombinant inbred line (RIL) population grown on a sandy substrate supplemented with nutrient solution, under control and drought conditions. Altogether, 54 quantitative trait loci (QTL) were identified, of which many colocated in 11 QTL clusters. Seventeen QTL showed significant QTL-environment interaction (Q×E), indicating genetic variation for phenotypic plasticity. Of the measured traits, only hypocotyl length did not show significant genotype-environment interaction (G×E) in both environments in all experiments. Correlation analysis showed that, in the control environment, stomatal conductance was positively correlated with total leaf dry weight (DW) and aboveground DW, whereas in the drought environment, stomatal conductance showed a significant negative correlation with total leaf DW and aboveground DW. This correlation was explained by antagonistic fitness effects in the drought environment, controlled by a QTL cluster on chromosome A7. These results demonstrate that Q×E is an important component of the genetic variance and can play a great role in improving drought tolerance in future breeding programmes.
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Project description:Hybrids account for nearly all commercially planted varieties of maize and many other crop plants because crosses between inbred lines of these species produce first-generation [F1] offspring that greatly outperform their parents. The mechanisms underlying this phenomenon, called heterosis or hybrid vigor, are not well understood despite over a century of intensive research. The leading hypotheses-which focus on quantitative genetic mechanisms (dominance, overdominance, and epistasis) and molecular mechanisms (gene dosage and transcriptional regulation)-have been able to explain some but not all of the observed patterns of heterosis. Abiotic stressors are known to impact the expression of heterosis; however, the potential role of microbes in heterosis has largely been ignored. Here, we show that heterosis of root biomass and other traits in maize is strongly dependent on the belowground microbial environment. We found that, in some cases, inbred lines perform as well by these criteria as their F1 offspring under sterile conditions but that heterosis can be restored by inoculation with a simple community of seven bacterial strains. We observed the same pattern for seedlings inoculated with autoclaved versus live soil slurries in a growth chamber and for plants grown in steamed or fumigated versus untreated soil in the field. In a different field site, however, soil steaming increased rather than decreased heterosis, indicating that the direction of the effect depends on community composition, environment, or both. Together, our results demonstrate an ecological phenomenon whereby soil microbes differentially impact the early growth of inbred and hybrid maize.
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Project description:To assess plasticity in genetic regulation of gene expression in Arabidopsis thaliana, genome wide gene expression variation was analyzed in a Ler/Cvi recombinant inbred line (RIL) population treated with low-light. The variation in expression could be explained for many genes by expression quantitative trait loci (eQTLs), which were compared to a previous genetical genomics study in the same untreated population. Please note Characteristics[StrainOrLine] is the population of 162 recombinant inbred lines between the accessions Ler x Cvi. Ler and Cvi are the names of the parental accessions.
2013-03-01 | E-MTAB-1357 | biostudies-arrayexpress
Project description:Climate-driven reef decline has prompted the development of next-generation coral conservation strategies, many of which hinge on the movement of adaptive variation across genetic and environmental gradients. This process is limited by our understanding of how genetic and genotypic drivers of coral bleaching will manifest in different environmental conditions. We reciprocally transplanted 10 genotypes of Acropora cervicornis across eight sites along a 60 km span of the Florida Reef Tract and documented significant genotype × environment interactions in bleaching response during the severe 2015 bleaching event. Performance relative to site mean was significantly different between genotypes and can be mostly explained by ensemble models of correlations with genetic markers. The high explanatory power was driven by significant enrichment of loci associated DNA repair, cell signalling and apoptosis. No genotypes performed above (or below) bleaching average at all sites, so genomic predictors can provide practitioners with 'confidence intervals' about the chance of success in novel habitats. These data have important implications for assisted gene flow and managed relocation, and their integration with traditional active restoration.
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Project description:High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics.
| S-EPMC8022981 | biostudies-literature
Project description:How combinations of gene-environment interactions collectively give rise to genotype-environment interactions is not fully understood. To shed light on this problem, we genetically dissected an environment-specific poor growth phenotype in a cross of two budding yeast strains. This phenotype is detectable when certain segregants are grown on ethanol at 37°C ('E37'), a condition that differs from the standard culturing environment in both its carbon source (ethanol as opposed to glucose) and temperature (37°C as opposed to 30°C). Using recurrent backcrossing with phenotypic selection, we identified 16 contributing loci. To examine how these loci interact with each other and the environment, we focused on a subset of four loci that together can lead to poor growth in E37. We measured the growth of all 16 haploid combinations of alleles at these loci in all four possible combinations of carbon source (ethanol or glucose) and temperature (30 or 37°C) in a nearly isogenic population. This revealed that the four loci act in an almost entirely additive manner in E37. However, we also found that these loci have weaker effects when only carbon source or temperature is altered, suggesting that their effect magnitudes depend on the severity of environmental perturbation. Consistent with such a possibility, cloning of three causal genes identified factors that have unrelated functions in stress response. Thus, our results indicate that polymorphisms in stress response can show effects that are intensified by environmental stress, thereby resulting in major genotype-environment interactions when multiple of these variants co-occur.
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