Dataset Information

Unlocking wheat genetic resources for the molecular identification of previously undescribed functional alleles at the Pm3 resistance locus.

ABSTRACT: The continuous improvement of crop plants is essential for agriculture in the coming decades and relies on the use of genetic variability through breeding. However, domestication and modern breeding have reduced diversity in the crop germplasm. Global gene banks conserve diversity, but these resources remain underexplored owing to a lack of efficient strategies to isolate important alleles. Here we describe a large-scale allele-mining project at the molecular level. We first selected a set of 1,320 bread wheat landraces from a database of 16,089 accessions, using the focused identification of germplasm strategy. On the basis of a hierarchical selection procedure on this set, we then isolated 7 resistance alleles of the powdery mildew resistance gene Pm3, doubling the known functional allelic diversity at this locus. This targeted approach for molecular utilization of gene bank accessions reveals landraces as a rich resource of new functional alleles. This strategy can be implemented for other studies on the molecular diversity of agriculturally important genes, as well as for molecular breeding.

SUBMITTER: Bhullar NK

PROVIDER: S-EPMC2686639 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature

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Unlocking wheat genetic resources for the molecular identification of previously undescribed functional alleles at the Pm3 resistance locus.

Bhullar Navreet K NK Street Kenneth K Mackay Michael M Yahiaoui Nabila N Keller Beat B

Proceedings of the National Academy of Sciences of the United States of America 20090526 23

The continuous improvement of crop plants is essential for agriculture in the coming decades and relies on the use of genetic variability through breeding. However, domestication and modern breeding have reduced diversity in the crop germplasm. Global gene banks conserve diversity, but these resources remain underexplored owing to a lack of efficient strategies to isolate important alleles. Here we describe a large-scale allele-mining project at the molecular level. We first selected a set of 1, ...[more]

PMID: 19470492

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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.

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Dataset Information

Unlocking wheat genetic resources for the molecular identification of previously undescribed functional alleles at the Pm3 resistance locus.

Publications

Unlocking wheat genetic resources for the molecular identification of previously undescribed functional alleles at the Pm3 resistance locus.

Similar Datasets

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