Dataset Information

Genome-wide prediction of three important traits in bread wheat.

ABSTRACT: Five genomic prediction models were applied to three wheat agronomic traits-grain yield, heading date and grain test weight-in three breeding populations, each comprising about 350 doubled haploid or recombinant inbred lines evaluated in three locations during a 3-year period. The prediction accuracy, measured as the correlation between genomic estimated breeding value and observed trait, was in the range of previously published values for yield (r = 0.2-0.5), a trait with relatively low heritability. Accuracies for heading date and test weight, with relatively high heritabilities, were about 0.70. There was no improvement of prediction accuracy when two or three breeding populations were merged into one for a larger training set (e.g., for yield r ranged between 0.11 and 0.40 in the respective populations and between 0.18 and 0.35 in the merged populations). Cross-population prediction, when one population was used as the training population set and another population was used as the validation set, resulted in no prediction accuracy. This lack of cross-population prediction accuracy cannot be explained by a lower level of relatedness between populations, as measured by a shared SNP similarity, since it was only slightly lower between than within populations. Simulation studies confirm that cross-prediction accuracy decreases as the proportion of shared QTLs decreases, which can be expected from a higher level of QTL × environment interactions.

SUBMITTER: Charmet G

PROVIDER: S-EPMC4544631 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Genome-wide prediction of three important traits in bread wheat.

Charmet Gilles G Storlie Eric E Oury François Xavier FX Laurent Valérie V Beghin Denis D Chevarin Laetitia L Lapierre Annie A Perretant Marie Reine MR Rolland Bernard B Heumez Emmanuel E Duchalais Laure L Goudemand Ellen E Bordes Jacques J Robert Olivier O

Molecular breeding : new strategies in plant improvement 20140716 4

Five genomic prediction models were applied to three wheat agronomic traits-grain yield, heading date and grain test weight-in three breeding populations, each comprising about 350 doubled haploid or recombinant inbred lines evaluated in three locations during a 3-year period. The prediction accuracy, measured as the correlation between genomic estimated breeding value and observed trait, was in the range of previously published values for yield (<i>r</i> = 0.2-0.5), a trait with relatively low ...[more]

PMID: 26316839

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Project description:BackgroundWheat is a cool seasoned crop requiring low temperature during grain filling duration and therefore increased temperature causes significant yield reduction. A set of 125 spring wheat genotypes from International Maize and Wheat Improvement Centre (CIMMYT-Mexico) was evaluated for phenological and yield related traits at three locations in Pakistan under normal sowing time and late sowing time for expose to prolonged high temperature. With the help of genome-wide association study using genotyping-by-sequencing, marker trait associations (MTAs) were observed separately for the traits under normal and late sown conditions.ResultsSignificant reduction ranging from 9 to 74% was observed in all traits under high temperature. Especially 30, 25, 41 and 66% reduction was observed for days to heading (DH), plant height (PH), spikes per plant (SPP) and yield respectively. We identified 55,954 single nucleotide polymorphisms (SNPs) using genotyping by sequencing of these 125 hexaploid spring wheat genotypes and conducted genome-wide association studies (GWAS) for days to heading (DH), grain filled duration (GFD), plant height (PH), spikes per plant (SPP), grain number per spike (GNS), thousand kernel weight (TKW) and grain yield per plot (GY). Genomic regions identified through GWAS explained up to 13% of the phenotypic variance, on average. A total of 139 marker-trait associations (MTAs) across three wheat genomes (56 on genome A, 55 on B and 28 on D) were identified for all the seven traits studied. For days to heading, 20; grain filled duration, 21; plant height, 23; spikes per plant, 13; grain numbers per spike, 8; thousand kernel weight, 21 and for grain yield, 33 MTAs were detected under normal and late sown conditions.ConclusionsThis study identifies the essential resource of genetics research and underpins the chromosomal regions of seven agronomic traits under normal and high temperature. Significant relationship was observed between the number of favored alleles and trait observations. Fourteen protein coding genes with their respective annotations have been searched with the sequence of seven MTAs which were identified in this study. These findings will be helpful in the development of a breeder friendly platform for the selection of high yielding wheat lines at high temperature areas.

Project description:Depleting water resources and increasing global temperature due to climate change are major challenges to agriculture and food security worldwide. Deciphering the underlying mechanisms of traits contributing to grain development and yield is essential for the development of climate-resilient cultivars. Therefore, this study assessed 105 bread wheat genotypes grown under control, drought, and heat-stress conditions for two crop seasons and performed a genome-wide association study (GWAS) using a 90k SNP array. The genotypes showed significant trait differences under all environmental conditions. Highly significant variation was observed, with moderate (50.09%) to high (76.19%) heritability in the studied germplasms. The studied traits were all also significantly positively correlated. A total of 541 significant associations (p ≤ 10-3) between marker and trait (MTAs) were observed after crossing the FDR <0.05 threshold for all traits. Among these, 195, 179, and 167 significant MTAs were detected under control, drought, and heat-stress conditions, respectively. Under the control and drought conditions, pleiotropic loci BS00010616_51 and BS00010868_51 were observed on chromosomes 7B and 1B situated at 186.24 cM and 35.47 cM, respectively. Pleiotropic loci BS00010868_51, Kukri_c11154_1723, and Ex_c10068_1509 were identified on chromosomes 1B, 5B, and 2A, respectively, under control and heat stress conditions. A stable and consistent locus (Excalibur_c20796_395) on chromosome 7A, located at 372.34 cM, was also linked to grain morphology and yield-related attributes in control, drought, and heat-stress conditions. The results of the current study confirmed several previously reported MTAs for the traits under consideration and identified new MTAs under harsh climatic conditions. These SNPs will aid in the discovery of novel genes in wheat. SNPs showing significant associations may be used in marker-assisted selection and allow the development of drought- and heat-tolerant genotypes with high yields to address global food security concerns.

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.

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Genome-wide prediction of three important traits in bread wheat.

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Genome-wide prediction of three important traits in bread wheat.

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