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A wheat protein kinase gene TaSnRK2.9-5A associated with yield contributing traits.

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Key message

We developed breeder-friendly high-throughput and cost-effective KASP marker for marker-assisted selection for grain yield related traits in wheat. Plant-specific protein kinase, SnRK2s, is a major family of signaling genes associated with metabolic regulations, nutrient utilization and response to external stimuli. In the present study, three copies of TaSnRK2.9 were isolated from chromosomes 5A, 5B and 5D of wheat (Triticum aestivum L.). The coding regions of TaSnRK2.9-5A, TaSnRK2.9-5B and promoter region of TaSnRK2.9-5D were investigated for sequence polymorphism. Single nucleotide polymorphisms (SNPs) were identified for TaSnRK2.9-5A, while no polymorphism was identified in TaSnRK2.9-5B and TaSnRK2.9-5D. The nucleotide sequence of TaSnRK2.9-5A consisted of 2180 bp having eight introns and nine exons. Three SNPs were identified at 308 nt, 698 nt and 1700 nt. For high-throughput genotyping, two kompetitive allele-specific PCR (KASP) markers were developed. Four haplotypes Hap-5A-1, Hap-5A-2, Hap-5A-3 and Hap-5A-4 were detected in wheat populations collected from China, Europe and Pakistan. Association analysis was performed with mixed linear model in TASSEL (v 5.0). The results indicated that Hap-5A-1/2 of TaSnRK2.9-5A were significantly associated with high thousand kernel weight, while Hap-5A-4 with high grains per spike. Overexpressing transgenic rice also showed higher grains per spike which is in accordance with association analysis results. Geographic distribution and allelic frequency indicted that the favored haplotypes were positively selected in Chinese (Hap-5A-1/2), Pakistani (Hap-5A-1), east European (Hap-5A-1) and west European (Hap-5A-4) wheat breeding. The results suggest that the developed KASP markers can be utilized in yield improvement by marker-assisted selection in wheat breeding.

SUBMITTER: Ur Rehman S

PROVIDER: S-EPMC6449320 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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A wheat protein kinase gene TaSnRK2.9-5A associated with yield contributing traits.

Ur Rehman Shoaib S Wang Jingyi J Chang Xiaoping X Zhang Xueyong X Mao Xinguo X Jing Ruilian R

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik 20181205 4

<h4>Key message</h4>We developed breeder-friendly high-throughput and cost-effective KASP marker for marker-assisted selection for grain yield related traits in wheat. Plant-specific protein kinase, SnRK2s, is a major family of signaling genes associated with metabolic regulations, nutrient utilization and response to external stimuli. In the present study, three copies of TaSnRK2.9 were isolated from chromosomes 5A, 5B and 5D of wheat (Triticum aestivum L.). The coding regions of TaSnRK2.9-5A, ...[more]

PMID: 30519711

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Project description:Background and aimsPlant roots growing underground are critical for soil resource acquisition, anchorage and plant-environment interactions. In wheat ( Triticum aestivum ), however, the target root traits to improve yield potential still remain largely unknown. This study aimed to identify traits of seedling root system architecture (RSA) associated with yield and yield components in 226 recombinant inbred lines (RILs) derived from a cross between the bread wheat Triticum aestivum 'Forno' (small, wide root system) and spelt Triticum spelta 'Oberkulmer' (large, narrow root system).MethodsA 'pouch and wick' high-throughput phenotyping pipeline was used to determine the RSA traits of 13-day-old RIL seedlings. Two field experiments and one glasshouse experiment were carried out to investigate the yield, yield components and phenology, followed by identification of quantitative trait loci (QTLs).Key resultsThere was substantial variation in RSA traits between genotypes. Seminal root number and total root length were both positively associated with grains m -2 , grains per spike, above-ground biomass m -2 and grain yield. More seminal roots and longer total root length were also associated with delayed maturity and extended grain filling, likely to be a consequence of more grains being defined before anthesis. Additionally, the maximum width of the root system displayed positive relationships with spikes m -2 , grains m -2 and grain yield. Ten RILs selected for the longest total roots exhibited the same effects on yield and phenology as described above, compared with the ten lines with the shortest total roots. Genetic analysis revealed 38 QTLs for the RSA, and QTL coincidence between the root and yield traits was frequently observed, indicating tightly linked genes or pleiotropy, which concurs with the results of phenotypic correlation analysis.ConclusionsBased on the results from the Forno × Oberkulmer population, it is proposed that vigorous early root growth, particularly more seminal roots and longer total root length, is important to improve yield potential, and should be incorporated into wheat ideotypes in breeding.

Project description:ERECTA encodes a receptor-like kinase and is proposed as a candidate for determining transpiration efficiency of plants. Two genes homologous to ERECTA in Arabidopsis were identified on chromosomes 6 (TaER2) and 7 (TaER1) of bread wheat (Triticum aestivum L.), with copies of each gene on the A, B and D genomes of wheat. Similar expression patterns were observed for TaER1 and TaER2 with relatively higher expression of TaER1 in flag leaves of wheat at heading (Z55) and grain-filling (Z73) stages. Significant variations were found in the expression levels of both TaER1 and TaER2 in the flag leaves at both growth stages among 48 diverse bread wheat varieties. Based on the expression of TaER1 and TaER2, the 48 wheat varieties could be classified into three groups having high (5 varieties), medium (27 varieties) and low (16 varieties) levels of TaER expression. Significant differences were also observed between the three groups varying for TaER expression for several transpiration efficiency (TE)- related traits, including stomatal density (SD), transpiration rate, photosynthetic rate (A), instant water use efficiency (WUEi) and carbon isotope discrimination (CID), and yield traits of biomass production plant-1 (BYPP) and grain yield plant-1 (GYPP). Correlation analysis revealed that the expression of TaER1 and TaER2 at the two growth stages was significantly and negatively associated with SD (P<0.01), transpiration rate (P<0.05) and CID (P<0.01), while significantly and positively correlated with flag leaf area (FLA, P<0.01), A (P<0.05), WUEi (P<0.05), BYPP (P<0.01) and GYPP (P<0.01), with stronger correlations for TaER1 than TaER2 and at grain-filling stage than at heading stage. These combined results suggested that TaER involved in development of transpiration efficiency -related traits and yield in bread wheat, implying a function for TaER in regulating leaf development of bread wheat and contributing to expression of these traits. Moreover, the results indicate that TaER could be exploitable for manipulating important agronomical traits in wheat improvement.

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Project description:Genomic selection (GS) is a strategy to predict the genetic merits of individuals using genome-wide markers. However, GS prediction accuracy is affected by many factors, including missing rate and minor allele frequency (MAF) of genotypic data, GS models, trait features, etc. In this study, we used one wheat population to investigate prediction accuracies of various GS models on yield and yield-related traits from various quality control (QC) scenarios, missing genotype imputation, and genome-wide association studies (GWAS)-derived markers. Missing rate and MAF of single nucleotide polymorphism (SNP) markers were two major factors in QC. Five missing rate levels (0%, 20%, 40%, 60%, and 80%) and three MAF levels (0%, 5%, and 10%) were considered and the five-fold cross validation was used to estimate the prediction accuracy. The results indicated that a moderate missing rate level (20% to 40%) and MAF (5%) threshold provided better prediction accuracy. Under this QC scenario, prediction accuracies were further calculated for imputed and GWAS-derived markers. It was observed that the accuracies of the six traits were related to their heritability and genetic architecture, as well as the GS prediction model. Moore-Penrose generalized inverse (GenInv), ridge regression (RidgeReg), and random forest (RForest) resulted in higher prediction accuracies than other GS models across traits. Imputation of missing genotypic data had marginal effect on prediction accuracy, while GWAS-derived markers improved the prediction accuracy in most cases. These results demonstrate that QC on missing rate and MAF had positive impact on the predictability of GS models. We failed to identify one single combination of QC scenarios that could outperform the others for all traits and GS models. However, the balance between marker number and marker quality is important for the deployment of GS in wheat breeding. GWAS is able to select markers which are mostly related to traits, and therefore can be used to improve the prediction accuracy of GS.

Dataset Information

A wheat protein kinase gene TaSnRK2.9-5A associated with yield contributing traits.

Key message

Publications

A wheat protein kinase gene TaSnRK2.9-5A associated with yield contributing traits.

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