GWAS identifies an ortholog of the rice D11 gene as a candidate gene for grain size in an international collection of hexaploid wheat.
Ontology highlight
ABSTRACT:
SUBMITTER: Tekeu H
PROVIDER: S-EPMC8484655 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundIncreasing wheat (Triticum aestivum L.) production is required to feed a growing human population. In order to accomplish this task a deeper understanding of the genetic structure of cultivated wheats and the detection of genomic regions significantly associated with the regulation of important agronomic traits are necessary steps. To better understand the genetic basis and relationships of adaptation and yield related traits, we used a collection of 102 Argentinean hexaploid wheat cultivars genotyped with the 35k SNPs array, grown from two to six years in three different locations. Based on SNPs data and gene-related molecular markers, we performed a haplotype block characterization of the germplasm and a genome-wide association study (GWAS).ResultsThe genetic structure of the collection revealed four subpopulations, reflecting the origin of the germplasm used by the main breeding programs in Argentina. The haplotype block characterization showed 1268 blocks of different sizes spread along the genome, including highly conserved regions like the 1BS chromosome arm where the 1BL/1RS wheat/rye translocation is located. Based on GWAS we identified ninety-seven chromosome regions associated with heading date, plant height, thousand grain weight, grain number per spike and fruiting efficiency at harvest (FEh). In particular FEh stands out as a promising trait to raise yield potential in Argentinean wheats; we detected fifteen haplotypes/markers associated with increased FEh values, eleven of which showed significant effects in all three evaluated locations. In the case of adaptation, the Ppd-D1 gene is consolidated as the main determinant of the life cycle of Argentinean wheat cultivars.ConclusionThis work reveals the genetic structure of the Argentinean hexaploid wheat germplasm using a wide set of molecular markers anchored to the Ref Seq v1.0. Additionally GWAS detects chromosomal regions (haplotypes) associated with important yield and adaptation components that will allow improvement of these traits through marker-assisted selection.
| S-EPMC6916457 | biostudies-literature
Project description:BackgroundHexaploid wheat is one of the most important cereal crops for human nutrition. Molecular understanding of the biology of the developing grain will assist the improvement of yield and quality traits for different environments. High quality transcriptomics is a powerful method to increase this understanding.ResultsThe transcriptome of developing caryopses from hexaploid wheat (Triticum aestivum, cv. Hereward) was determined using Affymetrix wheat GeneChip oligonucleotide arrays which have probes for 55,052 transcripts. Of these, 14,550 showed significant differential regulation in the period between 6 and 42 days after anthesis (daa). Large changes in transcript abundance were observed which were categorised into distinct phases of differentiation (6-10 daa), grain fill (12-21 daa) and desiccation/maturation (28-42 daa) and were associated with specific tissues and processes. A similar experiment on developing caryopses grown with dry and/or hot environmental treatments was also analysed, using the profiles established in the first experiment to show that most environmental treatment effects on transcription were due to acceleration of development, but that a few transcripts were specifically affected. Transcript abundance profiles in both experiments for nine selected known and putative wheat transcription factors were independently confirmed by real time RT-PCR. These expression profiles confirm or extend our knowledge of the roles of the known transcription factors and suggest roles for the unknown ones.ConclusionThis transcriptome data will provide a valuable resource for molecular studies on wheat grain. It has been demonstrated how it can be used to distinguish general developmental shifts from specific effects of treatments on gene expression and to diagnose the probable tissue specificity and role of transcription factors.
| S-EPMC2292175 | biostudies-literature
Project description:Kernel morphology is one of the major yield traits of wheat, the genetic architecture of which is always important in crop breeding. In this study, we performed a genome-wide association study (GWAS) to appraise the genetic architecture of the kernel traits of 319 wheat accessions using 22,905 single nucleotide polymorphism (SNP) markers from a wheat 90K SNP array. As a result, 111 and 104 significant SNPs for Kernel traits were detected using four multi-locus GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, and pLARmEB) and three single-locus models (FarmCPU, MLM, and MLMM), respectively. Among the 111 SNPs detected by the multi-locus models, 24 SNPs were simultaneously detected across multiple models, including seven for kernel length, six for kernel width, six for kernels per spike, and five for thousand kernel weight. Interestingly, the five most stable SNPs (RAC875_29540_391, Kukri_07961_503, tplb0034e07_1581, BS00074341_51, and BobWhite_049_3064) were simultaneously detected by at least three multi-locus models. Integrating these newly developed multi-locus GWAS models to unravel the genetic architecture of kernel traits, the mrMLM approach detected the maximum number of SNPs. Furthermore, a total of 41 putative candidate genes were predicted to likely be involved in the genetic architecture underlining kernel traits. These findings can facilitate a better understanding of the complex genetic mechanisms of kernel traits and may lead to the genetic improvement of grain yield in wheat.
| S-EPMC7460857 | biostudies-literature
Project description:Wheat is a major food crop and an important component of human diet throughout the world. There are two major types of cultivated wheat; one is tetraploid durum (pasta) wheat and another one is hexaploid bread wheat. Wheat grain is the reservoir of two major dietary components - carbohydrate and protein, which get accumulated during seed maturation and directly affects yield and quality. Hexaploid, having 6 copies of each chromosome differs to a great extent from tetraploid having 4 copies of each chromosome. Studying the gene expression pattern in developing grain would help in understanding the difference in metabolic process as well as involvement of the genes in these two types of wheat. A transcriptional comparison of developing grains was carried out between the two wheat genotypes; tetraploid (AABB:PDW233) and hexaploid (AABBDD:PBW343) using RNA-seq. Approximately 194 million raw reads were obtained from both libraries. After removal of contaminations, a huge proportion (>99%), of high quality reads were obtained, were aligned to reference genome. A total of 2324 up-regulated and 522 down-regulated genes were identified as differentially expressed between PDW233 vs PBW343. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes between durum and bread wheat. This information will help in understanding process grain reserve in tetraploid and hexaploid wheat in relation to their nutritional quality.
| S-EPMC6321973 | biostudies-literature
Project description:The expression of genes involved in starch synthesis in wheat was analyzed together with the accumulation profiles of soluble sugars, starch, protein, and starch granule distribution in developing caryopses obtained from the same biological materials used for profiling of gene expression using DNA microarrays. Multiple expression patterns were detected for the different starch biosynthetic gene isoforms, suggesting their relative importance through caryopsis development. Members of the ADP-glucose pyrophosphorylase, starch synthase, starch branching enzyme, and sucrose synthase gene families showed different expression profiles; expression of some members of these gene families coincided with a period of high accumulation of starch while others did not. A biphasic pattern was observed in the rates of starch and protein accumulation which paralleled changes in global gene expression. Metabolic and regulatory genes that show a pattern of expression similar to starch accumulation and granule size distribution were identified, suggesting their coinvolvement in these biological processes.
| S-EPMC2834961 | biostudies-literature
Project description:Cellular protein abundance results from the relative rates of protein synthesis and protein degradation. Through combining in vivo stable isotope labelling and in-depth quantitative proteomics, we created a protein turnover atlas of wheat grain proteins during grain development. Our data demonstrate that protein turnover rates for 1447 unique wheat grain protein groups have an apparent spatiotemporal pattern that aids explanation of the 60% of variation in protein abundances that are not attributable to gene expression. Protein synthesis rates of individual proteins vary over 100 fold and degradation rates over 20 fold. Storage proteins have both higher synthesis and degradation rates than the overarching average rates of grain proteins in other functional categories, while those proteins involved in photosynthesis, DNA synthesis and glycolysis, by contrast, are house-keeping proteins that show low synthesis and degradation rates at all times. Approximately 20% of total grain ATP production through respiration is used for grain proteome biogenesis and maintenance, and the grain invests nearly half of this budget in storage protein synthesis alone. Degradation of storage proteins as a class of grain proteins also consumed a significant amount of the total ATP allocated to protein degradation processes. This analysis suggests that 20% of newly synthesized storage proteins are turned over rather than stored suggesting that this process is not energetically optimal. This approach to measure protein turnover rates at the proteome scale shows how different functional categories of grain proteins accumulate, calculates the costs of futile cycling of protein turnover during wheat grain development and identifies the most and the least stable wheat grain proteins.
2021-12-21 | PXD022231 | Pride
Project description:Allohexaploid bread wheat (Triticum aestivum, L.) provides ~ 20% of calories consumed by humans. Hitherto lack of genome sequence for the three homoelogous and highly similar bread wheat genomes (A, B and, D) impeded expression analysis of the grain transcriptome. We used novel genome information to analyze the cell type specific expression of homeologous genes in the developing wheat grain.
2014-07-18 | E-MTAB-2137 | biostudies-arrayexpress
Project description:Wheat is a major food crop worldwide. The plant architecture is a complex trait mostly influenced by plant height, tiller number, and leaf morphology. Plant height plays a crucial role in lodging and thus affects yield and grain quality. In this study, a wheat population was genotyped by using Illumina iSelect 90K single nucleotide polymorphism (SNP) assay and finally 22,905 high-quality SNPs were used to perform a genome-wide association study (GWAS) for plant architectural traits employing four multi-locus GWAS (ML-GWAS) and three single-locus GWAS (SL-GWAS) models. As a result, 174 and 97 significant SNPs controlling plant architectural traits were detected by ML-GWAS and SL-GWAS methods, respectively. Among these SNP makers, 43 SNPs were consistently detected, including seven across multiple environments and 36 across multiple methods. Interestingly, five SNPs (Kukri_c34553_89, RAC875_c8121_1490, wsnp_Ex_rep_c66315_64480362, Ku_c5191_340, and tplb0049a09_1302) consistently detected across multiple environments and methods, played a role in modulating both plant height and flag leaf length. Furthermore, candidate SNPs (BS00068592_51, Kukri_c4750_452 and BS00022127_51) constantly repeated in different years and methods associated with flag leaf width and number of tillers. We also detected several SNPs (Jagger_c6772_80, RAC875_c8121_1490, BS00089954_51, Excalibur_01167_1207, and Ku_c5191_340) having common associations with more than one trait across multiple environments. By further appraising these GWAS methods, the pLARmEB and FarmCPU models outperformed in SNP detection compared to the other ML-GWAS and SL-GWAS methods, respectively. Totally, 152 candidate genes were found to be likely involved in plant growth and development. These finding will be helpful for better understanding of the genetic mechanism of architectural traits in wheat.
| S-EPMC7990932 | biostudies-literature
Project description:Tan spot, caused by Pyrenophora tritici-repentis, is a serious foliar disease of wheat in Kazakhstan with reported yield losses as high as 50% during epidemic years. Here, we report the evaluation of a collection of 191 hexaploid spring and winter wheat lines for tan spot resistance and its underlying genetic architecture using genome-wide association study (GWAS). Our wheat collection comprised candidate varieties from Kazakhstan, Russia, and CIMMYT. It was genotyped using the DArTseq technology and phenotyped for resistance to tan spot at seedling and adult plant stages in Kazakhstan. DArTseq SNPs revealed high genetic diversity (average polymorphic information content = 0.33) in the panel and genome-wide linkage disequilibrium decay at 22 Mb (threshold r2 = 0.1). Principal component analysis revealed a clear separation of Eurasian germplasm from CIMMYT and IWWIP lines. GWAS identified 34 marker-trait associations (MTA) for resistance to tan spot and the amount of phenotypic variation explained by these MTA ranged from 4% to 13.7%. Our results suggest the existence of novel valuable resistant alleles on chromosomes 3BS, and 5DL and 6AL for resistance to Race 1 and Race 5, respectively, in addition to known genes tsn1 and tsc2. On chromosome 6AL, a genomic region spanning 3 Mb was identified conferring resistance to both Race 1 and Race 5. Epistatic interaction of associated loci was revealed on chromosomes 1B, 5B, 7B, 5A, and 6A contributing to additional variation of 3.2-11.7%. Twenty-five lines with the best allele combinations of SNPs associated with resistance to both races have been identified as candidates for future variety release and breeding. The results of the present study will be further validated in other independent genetic backgrounds to be able to use markers in breeding.
| S-EPMC7831376 | biostudies-literature
Project description:Lodging is one of the most important limiting environmental factors for achieving the maximum yield and quality of grains in cereals, including wheat. However, little is known about the genetic foundation underlying lodging resistance (LR) in wheat. In this study, 208 landraces and 90 cultivars were phenotyped in two cropping seasons (2018-2019 and 2019-2020) for 19 LR-related traits. A genome-wide association study (GWAS) and genomics prediction were carried out to dissect the genomic regions of LR. The number of significant marker pairs (MPs) was highest for genome B in both landraces (427,017) and cultivars (37,359). The strongest linkage disequilibrium (LD) between marker pairs was found on chromosome 4A (0.318). For stem lodging-related traits, 465, 497, and 478 marker-trait associations (MTAs) and 45 candidate genes were identified in year 1, year 2, and pooled. Gene ontology exhibited genomic region on Chr. 2B, 6B, and 7B control lodging. Most of these genes have key roles in defense response, calcium ion transmembrane transport, carbohydrate metabolic process, nitrogen compound metabolic process, and some genes harbor unknown functions that, all together may respond to lodging as a complex network. The module associated with starch and sucrose biosynthesis was highlighted. Regarding genomic prediction, the GBLUP model performed better than BRR and RRBLUP. This suggests that GBLUP would be a good tool for wheat genome selection. As a result of these findings, it has been possible to identify pivotal QTLs and genes that could be used to improve stem lodging resistance in Triticum aestivum L.
| S-EPMC10761700 | biostudies-literature