Dataset Information

Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS.

ABSTRACT: Wheat genetic improvement by integration of advanced genomic technologies is one way of improving productivity. To facilitate the breeding of economically important traits in wheat, SNP loci and underlying candidate genes associated with the 36 agro-morphological traits were studied in a diverse panel of 404 genotypes. By using Breeders' 35K Axiom array in a comprehensive genome-wide association study covering 4364.79 cM of the wheat genome and applying a compressed mixed linear model, a total of 146 SNPs (-log10 P ? 4) were found associated with 23 traits out of 36 traits studied explaining 3.7-47.0% of phenotypic variance. To reveal this a subset of 260 genotypes was characterized phenotypically for six quantitative traits [days to heading (DTH), days to maturity (DTM), plant height (PH), spike length (SL), awn length (Awn_L), and leaf length (Leaf_L)] under five environments. Gene annotations mined ?38 putative candidate genes which were confirmed using tissue and stage specific gene expression data from RNA Seq. We observed strong co-localized loci for four traits (glume pubescence, SL, PH, and awn color) on chromosome 1B (24.64 cM) annotated five putative candidate genes. This study led to the discovery of hitherto unreported loci for some less explored traits (such as leaf sheath wax, awn attitude, and glume pubescence) besides the refined chromosomal regions of known loci associated with the traits. This study provides valuable information of the genetic loci and their potential genes underlying the traits such as awn characters which are being considered as important contributors toward yield enhancement.

SUBMITTER: Sheoran S

PROVIDER: S-EPMC6511880 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS.

Sheoran Sonia S Jaiswal Sarika S Kumar Deepender D Raghav Nishu N Sharma Ruchika R Pawar Sushma S Paul Surinder S Iquebal M A MA Jaiswar Akanksha A Sharma Pradeep P Singh Rajender R Singh C P CP Gupta Arun A Kumar Neeraj N Angadi U B UB Rai Anil A Singh G P GP Kumar Dinesh D Tiwari Ratan R

Frontiers in plant science 20190425

Wheat genetic improvement by integration of advanced genomic technologies is one way of improving productivity. To facilitate the breeding of economically important traits in wheat, SNP loci and underlying candidate genes associated with the 36 agro-morphological traits were studied in a diverse panel of 404 genotypes. By using Breeders' 35K Axiom array in a comprehensive genome-wide association study covering 4364.79 cM of the wheat genome and applying a compressed mixed linear model, a total o ...[more]

PMID: 31134105

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Project description:BackgroundRapid reductions in emissions from fossil fuel burning are needed to curb global climate change. Biofuel production from crop residues can contribute to reducing the energy crisis and environmental deterioration. Wheat is a renewable source for biofuels owing to the low cost and high availability of its residues. Thus, identifying candidate genes controlling these traits is pivotal for efficient biofuel production. Here, six multi-locus genome-wide association (ML-GWAS) models were applied using 185 tetraploid wheat accessions to detect quantitative trait nucleotides (QTNs) for fifteen traits associated with biomass composition.ResultsAmong the 470 QTNs, only 72 identified by at least two models were considered as reliable. Among these latter, 16 also showed a significant effect on the corresponding trait (p.value < 0.05). Candidate genes survey carried out within 4 Mb flanking the QTNs, revealed putative biological functions associated with lipid transfer and metabolism, cell wall modifications, cell cycle, and photosynthesis. Four genes encoded as Cellulose Synthase (CeSa), Anaphase promoting complex (APC/C), Glucoronoxylan 4-O Methyltransferase (GXM) and HYPONASTIC LEAVES1 (HYL1) might be responsible for an increase in cellulose, and natural and acid detergent fiber (NDF and ADF) content in tetraploid wheat. In addition, the SNP marker RFL_Contig3228_2154 associated with the variation in stem solidness (Q.Scsb-3B) was validated through two molecular methods (High resolution melting; HRM and RNase H2-dependent PCR; rhAMP).ConclusionsThe study provides new insights into the genetic basis of biomass composition traits on tetraploid wheat. The application of six ML-GWAS models on a panel of diverse wheat genotypes represents an efficient approach to dissect complex traits with low heritability such as wheat straw composition. The discovery of genes/genomic regions associated with biomass production and straw quality parameters is expected to accelerate the development of high-yielding wheat varieties useful for biofuel production.

Project description:Spring wheat is the largest agricultural crop grown in Kazakhstan with an annual sowing area of 12 million hectares in 2016. Annually, the country harvests around 15 million tons of high quality grain. Despite environmental stress factors it is predicted that the use of new technologies may lead to increases in productivity from current levels of 1.5 to up to 3 tons per hectare. One way of improving wheat productivity is by the application of new genomic oriented approaches in plant breeding projects. Genome wide association studies (GWAS) are emerging as powerful tools for the understanding of the inheritance of complex traits via utilization of high throughput genotyping technologies and phenotypic assessments of plant collections. In this study, phenotyping and genotyping data on 194 spring wheat accessions from Kazakhstan, Russia, Europe, and CIMMYT were assessed for the identification of marker-trait associations (MTA) of agronomic traits by using GWAS.Field trials in Northern, Central and Southern regions of Kazakhstan using 194 spring wheat accessions revealed strong correlations of yield with booting date, plant height, biomass, number of spikes per plant, and number of kernels per spike. The accessions from Europe and CIMMYT showed high breeding potential for Southern and Central regions of the country in comparison with the performance of the local varieties. The GGE biplot method, using average yield per plant, suggested a clear separation of accessions into their three breeding origins in relationship to the three environments in which they were evaluated. The genetic variation in the three groups of accessions was further studied using 3245 polymorphic SNP (single nucleotide polymorphism) markers. The application of Principal Coordinate analysis clearly grouped the 194 accessions into three clades according to their breeding origins. GWAS on data from nine field trials allowed the identification of 114 MTAs for 12 different agronomic traits.Field evaluation of foreign germplasm revealed its poor yield performance in Northern Kazakhstan, which is the main wheat growing region in the country. However, it was found that EU and CIMMYT germplasm has high breeding potential to improve yield performance in Central and Southern regions. The use of Principal Coordinate analysis clearly separated the panel into three distinct groups according to their breeding origin. GWAS based on use of the TASSEL 5.0 package allowed the identification of 114 MTAs for twelve agronomic traits. The study identifies a network of key genes for improvement of yield productivity in wheat growing regions of Kazakhstan.

Project description:Background and aimsThe development and morphology of crop plants have been profoundly altered by evolution under cultivation, initially through unconscious selection, without deliberate foresight, and later by directed breeding. Wild wheats remain an important potential source of variation for modern breeders; however, the sequence and timing of morphological changes during domestication are not fully resolved.MethodsWe grew and measured 142 wheat accessions representing different stages in wheat evolution, including three independent domestication events, and compared their morphological traits to define the morphospace of each group.Key resultsThe results show that wild and domesticated wheats have overlapping morphospaces, but each also occupies a distinct area of morphospace from one another. Polyploid formation in wheat increased leaf biomass and seed weight but had its largest effects on tiller loss. Domestication continued to increase the sizes of wheat leaves and seeds and made wheat grow taller, with more erect architecture. Associated changes to the biomass of domesticated wheats generated more grains and achieved higher yields. Landrace improvement subsequently decreased the numbers of tillers and spikes, to focus resource allocation to the main stem, accompanied by a thicker main stem and larger flag leaves. During the Green Revolution, wheat height was reduced to increase the harvest index and therefore yield. Modern wheats also have more erect leaves and larger flower biomass proportions than landraces.ConclusionsQuantitative trait history in wheat differs by trait. Some trait values show progressive changes in the same direction (e.g. leaf size, grain weight), whereas others change in a punctuated way at particular stages (e.g. canopy architecture), and other trait values switch directions during wheat evolution (e.g. plant height, flower biomass proportion). Agronomically valued domestication traits arose during different stages of wheat history, such that modern wheats are the product of >10 000 years of morphological evolution.

Dataset Information

Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS.

Publications

Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS.

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