scholarly journals A Genome-Wide Association Study Reveals a Novel Regulator of Ovule Number and Fertility in Arabidopsis thaliana

2018 ◽  
Author(s):  
Jing Yuan ◽  
Sharon A. Kessler
Keyword(s):  
Arabidopsis Thaliana ◽  
Flower Development ◽  
Natural Variation ◽  
Pleiotropic Effects ◽  
Genome Wide Association ◽  
Egg Cell ◽  
Dependent Manner ◽  
Genome Wide ◽  
A Genome ◽  
Ovule Number

AbstractOvules contain the female gametophytes which are fertilized during pollination to initiate seed development. Thus, the number of ovules that are produced during flower development is an important determinant of seed crop yield and plant fitness. Mutants with pleiotropic effects on development often alter the number of ovules, but specific regulators of ovule number have been difficult to identify in traditional mutant screens. We used natural variation in Arabidopsis accessions to identify new genes involved in the regulation of ovule number. The ovule numbers per flower of 189 Arabidopsis accessions were determined and found to have broad phenotypic variation that ranged from 39 ovules to 84 ovules per pistil. Genome-Wide Association tests revealed several genomic regions that are associated with ovule number. T-DNA insertion lines in candidate genes from the most significantly associated loci were screened for ovule number phenotypes. The NEW ENHANCER of ROOT DWARFISM (NERD1) gene was found to have pleiotropic effects on plant fertility that include regulation of ovule number and both male and female gametophyte development. Overexpression of NERD1 increased ovule number per fruit in a background-dependent manner and more than doubled the total number of flowers produced in all backgrounds tested, indicating that manipulation of NERD1 levels can be used to increase plant productivity.Author SummaryOvules are the precursors of seeds in flowering plants. Each ovule contains an egg cell and a central cell that fuse with two sperm cells during double fertilization to generate seeds containing an embryo and endosperm. The number of ovules produced during flower development determines the maximum number of seeds that can be produced by a flower. In this paper, we used natural variation in Arabidopsis thaliana accessions to identify regions of the genome that are associated with ovule number. Polymorphisms in the plant-specific NERD1 gene on chromosome 3 were significantly associated with ovule number. Mutant and overexpression analyses revealed that NERD1 is a positive regulator of ovule number, lateral branching, and flower number in Arabidopsis. Manipulation of NERD1 expression levels could potentially be used to increase yield in crop plants.

scholarly journals The maternal environment interacts with genetic variation in regulating seed dormancy in Arabidopsis thaliana

2017 ◽  
Author(s):  
Envel Kerdaffrec ◽  
Magnus Nordborg
Keyword(s):  
Arabidopsis Thaliana ◽  
Association Study ◽  
Seed Dormancy ◽  
Genome Wide Association Study ◽  
Seed Maturation ◽  
Genome Wide Association ◽  
Maternal Environment ◽  
Genome Wide ◽  
A Genome ◽  
Wide Range

AbstractSeed dormancy is a complex adaptive trait that controls the timing of seed germination, one of the major fitness components in many plant species. Despite being highly heritable, seed dormancy is extremely plastic and influenced by a wide range of environmental cues. Here, using a set of 92 Arabidopsis thaliana lines from Sweden, we investigate the effect of seed maturation temperature on dormancy variation at the population level. The response to temperature differs dramatically between lines, demonstrating that genotype and the maternal environment interact in controlling the trait. By performing a genome-wide association study (GWAS), we identified several candidate genes that could account for this plasticity, two of which are involved in the photoinduction of germination. Altogether, our results provide insight into both the molecular mechanisms and the evolution of dormancy plasticity, and can serve to improve our understanding of environmentally dependent life-history transitions.HighlightThe effect of low seed-maturation temperatures on seed dormancy is highly variable in Arabidopsis thaliana accessions from Sweden, denoting strong genotype-environment interactions, and a genome-wide association study identified compelling candidates that could account for this plasticity.

scholarly journals Identifying Pleiotropic Effects: A Two-Stage Approach Using Genome-Wide Association Meta-Analysis Data

2017 ◽  
Author(s):  
Xing Chen ◽  
Yi-Hsiang Hsu
Keyword(s):  
Genetic Variant ◽  
Density Lipoprotein ◽  
Pleiotropic Effects ◽  
Genome Wide Association ◽  
Two Stage ◽  
Individual Level ◽  
Multiple Phenotypes ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale

AbstractPleiotropic effects occur when a single genetic variant independently influences multiple phenotypes. In genetic epidemiological studies, multiple endo-phenotypes or correlated traits are commonly tested separately in a univariate statistical framework to identify associations with genetic determinants. Subsequently, a simple look-up of overlapping univariate results is applied to identify pleiotropic genetic effects. However, this strategy offers limited power to detect pleiotropy. In contrast, combining correlated traits into a composite test provides a powerful approach for detecting pleiotropic genes. Here, we propose a two-stage approach to identify potential pleiotropic effects by utilizing aggregated results from large-scale genome-wide association (GWAS) meta-analyses. In the first stage, we developed two novel approaches (direct linear combining, dLC; and empirical combining, eLC) combining correlated univariate test statistics to screen potential pleiotropic variants on a genome-wide scale, using either individual-level or aggregated data. Our simulations indicated that dLC and eLC outperform other popular multivariate approaches (such as principal component analysis (PCA), multivariate analysis of variance (MANOVA), canonical correlation (CCA), generalized estimation equations (GEE), linear mixed effects models (LME) and O’Brien combining approach). In particular, eLC provides a notable increase in power when the genetic variant exhibits both protective and deleterious effects. In the second stage, we developed a unique approach, conditional pleiotropy testing (cPLT), to examine pleiotropic effects using individual-level data for candidate variants identified in Stage 1. Simulation demonstrated reduced type 1 error for cPLT in identifying pleiotropic genetic variants compared to the typical conditional strategy. We validated our two-stage approach by performing a bivariate GWA study on two correlated quantitative traits, high-density lipoprotein (HDL) and triglycerides (TG), in the Genetic Analysis Workshop 16 (GAW16) simulation dataset. In summary, the proposed two-stage approach allows us to leverage aggregated summary statistics from univariate GWAS and improves the power to identify potential pleiotropy while maintaining valid false-positive rates.Author SummaryPleiotropy, occurring when a single genetic variant contributes to multiple phenotypes, remains difficult to identify in genome-wide association studies (GWAS). To leverage data for multiple phenotypes and incorporate univariate GWAS summary results, we propose a novel two-stage approach for discovering potential pleiotropic variants. In the first stage, two novel combining approaches were developed to screen potential pleiotropic variants on a genome-wide scale. Simulations demonstrated the superior statistical power of these approaches over other multivariate methods. In the second stage, our approach was used to identify potential pleiotropy in the candidate marker sets generated from the first stage. The proposed two-stage approach was applied to the GAW16 simulation dataset to discover pleiotropic variants associated with high-density lipoprotein and triglycerides. In summary, we demonstrate that the proposed two-stage approach can be applied as a viable and robust strategy to accommodate phenotypic and genetic heterogeneity for discovering potential pleiotropy on genome-wide scale.

scholarly journals Temporal dynamics of QTL effects on vegetative growth in Arabidopsis thaliana

2020 ◽  
Author(s):  
Rhonda C. Meyer ◽  
Kathleen Weigelt-Fischer ◽  
Dominic Knoch ◽  
Marc Heuermann ◽  
Yusheng Zhao ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Association Study ◽  
Vegetative Growth ◽  
Molecular Mechanisms ◽  
Genome Wide Association Study ◽  
Temporal Dynamics ◽  
Expression Patterns ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

ABSTRACTWe assessed early vegetative growth in a population of 382 accessions of Arabidopsis thaliana using automated non-invasive high-throughput phenotyping. All accessions were imaged daily from seven to 18 days after sowing in three independent experiments and genotyped using the Affymetrix 250k SNP array. Projected leaf area (PLA) was derived from image analysis and used to calculate relative growth rates (RGR). In addition, initial seed size was determined. The generated data sets were used jointly for a genome-wide association study that identified 238 marker-trait associations (MTAs) individually explaining up to 8 % of the total phenotypic variation. Co-localisation of MTAs occurred at 33 genomic positions. At 21 of these positions, sequential co-localisation of MTAs for two to nine consecutive days was observed. The detected MTAs for PLA and RGR could be grouped according to their temporal expression patterns, emphasising that temporal variation of MTA action can be observed even during the vegetative growth phase, a period of continuous formation and enlargement of seemingly similar rosette leaves. This indicates that causal genes may be differentially expressed in successive periods. Analyses of the temporal dynamics of biological processes are needed to gain important insight into the molecular mechanisms of growth-controlling processes in plants.HighlightA genome-wide association study including the factor time highlighted that early plant growth in Arabidopsis is governed by several medium and many small effect loci, most of which act only during short phases of two to nine days.

scholarly journals Arabidopsis thaliana genes contributing to differences in the outcome of infection with generalist and specialist strains of Turnip mosaic virus identified by genome-wide association studies

2020 ◽  
Author(s):  
Anamarija Butković ◽  
Rubén González ◽  
Mark Paul Selda Rivarez ◽  
Santiago F. Elena
Keyword(s):  
Arabidopsis Thaliana ◽  
Association Study ◽  
Host Range ◽  
Host Species ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Null Mutant ◽  
Genome Wide ◽  
A Genome

AbstractPathogens can be classified as generalists or specialists depending on their host breadth. While generalists are able to successfully infect a wide variety of host species, the host range of specialists is limited to a few related species. Even though generalists seem to gain an advantage due to their wide host range, they usually pay a cost in terms of fitness within each host species (i.e., the jack-of-all trades, master of none). On the contrary, specialists have high fitness within their own host. A highly relevant yet poorly explored question is whether generalist and specialist viruses differ in the way they interact with their host’s gene expression networks. To identify host genetic factors relevant for the infection of specialist or generalist viruses, we undertook a genome-wide association study (GWAS) approach. Four hundred fifty natural accessions of Arabidopsis thaliana were inoculated with turnip mosaic potyvirus strains that were either generalist (TuMV-G) or specialist (TuMV-S). Several disease-related traits have been associated with different sets of host genes for each TuMV strain. While most of the mapped loci were traitor strain-specific, one shared locus was mapped for both strains, a disease resistance TIR-NBS-LRR class protein. Likewise, only one locus was found involved in more than one of the disease-related traits evaluated, a putative cysteine-rich receptor-like protein kinase 20. To validate these results, the corresponding null mutant plants were inoculated with TuMV-G or -S and the outcome of infection was characterized.Author summaryGeneralist and specialist viruses are commonly found in nature, where they have potential for epidemics, and are classified depending on their host breath. In this study we used a genome-wide association study to characterize differences in the genetic basis of both infection strategies from a host perspective. Our experimental setup consisted of 450 accessions of A. thaliana and two strains of TuMV. We found differences in the number of associated genes and their functions in disease-related traits. Results were validated by characterization of viral infections in null mutant plants deficient for a set of the identified genes.

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