Dataset Information

Alleles of the GRF3-2A Gene in Wheat and Their Agronomic Value.

ABSTRACT: The Growth-regulating factors (GRF) are a family of plant-specific transcription factors that have roles in plant growth, development and stress response. In this study the diversity of the TaGRF3-2A (TraesCS2A02G435100) gene was investigated in Russian bread wheat germplasm by means of next generation sequencing and molecular markers, and the results compared with those from multiple wheat genome and exome sequencing projects. The results showed that an allele possessing c.495G>T polymorphism found in Bezostaya 1 and designated as TaGRF3-2Ab, is connected with earlier heading and better grain filling under conditions of the Krasnodar Krai. TaGRF3-2Ab is more frequent among Russian winter wheat cultivars than in other germplasms found in the world, implying that it is adaptive for the Chernozem region. A new rare mutation of the TaGRF3-2A was found in the spring wheat cultivar Novosibirskaya 67. The molecular markers developed will facilitate utilization of TaGRF3-2A mutations in future agronomic studies and wheat improvement. Albeit GRF3-2Ab may be good at maintaining high milling quality of the grain, it should be used with caution in breeding of winter wheat cultivars in the perspective of climate change.

SUBMITTER: Bazhenov MS

PROVIDER: S-EPMC8622619 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Alleles of the GRF3-2A Gene in Wheat and Their Agronomic Value.

Bazhenov Mikhail S MS Chernook Anastasiya G AG Bespalova Ludmila A LA Gritsay Tatiana I TI Polevikova Nadezhda A NA Karlov Gennady I GI Nazarova Lubov A LA Divashuk Mikhail G MG

International journal of molecular sciences 20211116 22

The Growth-regulating factors (GRF) are a family of plant-specific transcription factors that have roles in plant growth, development and stress response. In this study the diversity of the <i>TaGRF3-2A</i> (TraesCS2A02G435100) gene was investigated in Russian bread wheat germplasm by means of next generation sequencing and molecular markers, and the results compared with those from multiple wheat genome and exome sequencing projects. The results showed that an allele possessing c.495G>T polymor ...[more]

PMID: 34830258

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Project description:Principal component analysis (PCA) is widely used in various genetics studies. In this study, the role of classical PCA (cPCA) and robust PCA (rPCA) was evaluated explicitly in genome-wide association studies (GWAS). We evaluated 294 wheat genotypes under well-watered and rain-fed, focusing on spike traits. First, we showed that some phenotypic and genotypic observations could be outliers based on cPCA and different rPCA algorithms (Proj, Grid, Hubert, and Locantore). Hubert's method provided a better approach to identifying outliers, which helped to understand the nature of these samples. These outliers led to the deviation of the heritability of traits from the actual value. Then, we performed GWAS with 36,000 single nucleotide polymorphisms (SNPs) based on the traditional approach and two robust strategies. In the conventional approach and using the first three components of cPCA as population structure, 184 and 139 marker-trait associations (MTAs) were identified for five traits in well-watered and rain-fed environments, respectively. In the first robust strategy and when rPCA was used as population structure in GWAS, we observed that the Hubert and Grid methods identified new MTAs, especially for yield and spike weight on chromosomes 7A and 6B. In the second strategy, we followed the classical and robust principal component-based GWAS, where the first two PCs obtained from phenotypic variables were used instead of traits. In the recent strategy, despite the similarity between the methods, some new MTAs were identified that can be considered pleiotropic. Hubert's method provided a better linear combination of traits because it had the most MTAs in common with the traditional approach. Newly identified SNPs, including rs19833 (5B) and rs48316 (2B), were annotated with important genes with vital biological processes and molecular functions. The approaches presented in this study can reduce the misleading GWAS results caused by the adverse effect of outlier observations.

Project description:BACKGROUND:Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles. RESULTS:GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016-2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (-log10 P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively. CONCLUSIONS:Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.

Project description:BackgroundGossypium hirsutum L. is grown worldwide and is the largest source of natural fiber crop. We focus on exploring the favorable alleles (FAs) for upland cotton varieties improvement, and further understanding the history of accessions selection and acumination of favorable allele during breeding.ResultsThe genetic basis of phenotypic variation has been studied. But the accumulation of favorable alleles in cotton breeding history in unknown, and potential favorable alleles to enhance key agronomic traits in the future cotton varieties have not yet been identified. Therefore, 419 upland cotton accessions were screened, representing a diversity of phenotypic variations of 7362 G. hirsutum, and 15 major traits were investigated in 6 environments. These accessions were categorized into 3 periods (early, medium, and modern) according to breeding history. All accessions were divided into two major groups using 299 polymorphic microsatellite markers: G1 (high fiber yield and quality, late maturity) and G2 (low fiber yield and quality, early maturity). The proportion of G1 genotype gradually increased from early to modern breeding periods. Furthermore, 21 markers (71 alleles) were significantly associated (-log P > 4) with 15 agronomic traits in multiple environments. Seventeen alleles were identified as FAs; these alleles accumulated more in the modern period than in other periods, consistent with their phenotypic variation trends in breeding history. Our results demonstrate that the favorable alleles accumulated through breeding effects, especially for common favorable alleles. However, the potential elite accessions could be rapidly screened by rare favorable alleles.ConclusionIn our study, genetic variation and genome-wide associations for 419 upland cotton accessions were analyzed. Two favorable allele types were identified during three breeding periods, providing important information for yield/quality improvement of upland cotton germplasm.

Dataset Information

Alleles of the GRF3-2A Gene in Wheat and Their Agronomic Value.

Publications

Alleles of the GRF3-2A Gene in Wheat and Their Agronomic Value.

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