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Using the UK reference population Avalon × Cadenza as a platform to compare breeding strategies in elite Western European bread wheat.

ABSTRACT: Wheat breeders select for qualitative and quantitative traits, the latter often detected as quantitative trait loci (QTL). It is, however, a long procedure from QTL discovery to the successful introduction of favourable alleles into new elite varieties and finally into farmers' crops. As a proof of principle for this process, QTL for grain yield (GY), yield components, plant height (PH), ear emergence (EM), solid stem (SS) and yellow rust resistance (Yr) were identified in segregating UK bread wheat reference population, Avalon × Cadenza. Among the 163 detected QTL were several not reported before: 17 for GY, the major GY QTL on 2D; a major SS QTL on 3B; and Yr6 on 7B. Common QTL were identified on ten chromosomes, most interestingly, grain number (GN) was found to be associated with Rht-D1b; and GY and GN with a potential new allele of Rht8. The interaction of other QTL with GY and yield components was discussed in the context of designing a UK breeding target genotype. Desirable characteristics would be: similar PH and EM to Avalon; Rht-D1b and Vrn-A1b alleles; high TGW and GN; long and wide grains; a large root system, resistance to diseases; and maximum GY. The potential of the identified QTL maximising transgressive segregation to produce a high-yielding and resilient genotype was demonstrated by simulation. Moreover, simulating breeding strategies with F₂ enrichment revealed that the F₂-DH procedure was superior to the RIL and the modified SSD procedure to achieve that genotype. The proposed strategies of parent selection and breeding methodology can be used as guidance for marker-assisted wheat breeding.

SUBMITTER: Ma J

PROVIDER: S-EPMC4317512 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Key messageWe evaluated genomic selection across five breeding cycles of bread wheat breeding. Bias of within-cycle cross-validation and methods for improving the prediction accuracy were assessed. The prospect of genomic selection has been frequently shown by cross-validation studies using the same genetic material across multiple environments, but studies investigating genomic selection across multiple breeding cycles in applied bread wheat breeding are lacking. We estimated the prediction accuracy of grain yield, protein content and protein yield of 659 inbred lines across five independent breeding cycles and assessed the bias of within-cycle cross-validation. We investigated the influence of outliers on the prediction accuracy and predicted protein yield by its components traits. A high average heritability was estimated for protein content, followed by grain yield and protein yield. The bias of the prediction accuracy using populations from individual cycles using fivefold cross-validation was accordingly substantial for protein yield (17-712 %) and less pronounced for protein content (8-86 %). Cross-validation using the cycles as folds aimed to avoid this bias and reached a maximum prediction accuracy of [Formula: see text] = 0.51 for protein content, [Formula: see text] = 0.38 for grain yield and [Formula: see text] = 0.16 for protein yield. Dropping outlier cycles increased the prediction accuracy of grain yield to [Formula: see text] = 0.41 as estimated by cross-validation, while dropping outlier environments did not have a significant effect on the prediction accuracy. Independent validation suggests, on the other hand, that careful consideration is necessary before an outlier correction is undertaken, which removes lines from the training population. Predicting protein yield by multiplying genomic estimated breeding values of grain yield and protein content raised the prediction accuracy to [Formula: see text] = 0.19 for this derived trait.

Project description:BackgroundWheat seed germination directly affects wheat yield and quality. Although transcriptome and proteome analyses during seed germination have been reported in some crop plant species, dynamic transcriptome characterization during wheat seed germination has not been conducted. We performed the first comprehensive dynamic transcriptome analysis during different seed germination stages of elite Chinese bread wheat cultivar Jimai 20 using the Affymetrix Wheat Genome Array.ResultsA total of 61,703 probe sets representing 51,411 transcripts were identified during the five seed germination stages of Jimai 20, of which 2,825 differential expression probe sets corresponding to 2,646 transcripts with different functions were declared by ANOVA and a randomized variance model. The seed germination process included a rapid initial uptake phase (0-12 hours after imbibition [HAI]), a plateau phase (12-24 HAI), and a further water uptake phase (24-48 HAI), corresponding to switches from the degradation of small-molecule sucrose to the metabolism of three major nutrients and to photosynthesis. Hierarchical cluster and MapMan analyses revealed changes in several significant metabolism pathways during seed germination as well as related functional groups. The signal pathway networks constructed with KEGG showed three important genes encoding the phosphofructokinase family protein, with fructose-1, 6-bisphosphatase, and UTP-glucose-1-phosphate uridylyltransferase located at the center, indicating their pivotal roles in the glycolytic pathway, gluconeogenesis, and glycogenesis, respectively. Several significant pathways were selected to establish a metabolic pathway network according to their degree value, which allowed us to find the pathways vital to seed germination. Furthermore, 51 genes involved in transport, signaling pathway, development, lipid metabolism, defense response, nitrogen metabolism, and transcription regulation were analyzed by gene co-expression network with a k-core algorithm to determine which play pivotal roles in germination. Twenty-three meaningful genes were found, and quantitative RT-PCR analysis validated the expression patterns of 12 significant genes.ConclusionsWheat seed germination comprises three distinct phases and includes complicated regulation networks involving a large number of genes. These genes belong to many functional groups, and their co-regulations guarantee regular germination. Our results provide new insight into metabolic changes during seed germination and interactions between some significant genes.

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Using the UK reference population Avalon × Cadenza as a platform to compare breeding strategies in elite Western European bread wheat.

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