Dataset Information

Haplotype block analysis of an Argentinean hexaploid wheat collection and GWAS for yield components and adaptation.

ABSTRACT:

Background

Increasing 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).

Results

The 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.

Conclusion

This 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.

SUBMITTER: Lujan Basile SM

PROVIDER: S-EPMC6916457 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Publications

Haplotype block analysis of an Argentinean hexaploid wheat collection and GWAS for yield components and adaptation.

Luján Basile Silvana Marisol SM Ramírez Ignacio Abel IA Crescente Juan Manuel JM Conde Maria Belén MB Demichelis Melina M Abbate Pablo P Rogers William John WJ Pontaroli Ana Clara AC Helguera Marcelo M Vanzetti Leonardo Sebastián LS

BMC plant biology 20191216 1

<h4>Background</h4>Increasing 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 ...[more]

PMID: 31842779

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Project description:Spring wheat is the largest agricultural crop grown in Kazakhstan with an annual sowing area of 12 million hectares in 2016. Annually, the country harvests around 15 million tons of high quality grain. Despite environmental stress factors it is predicted that the use of new technologies may lead to increases in productivity from current levels of 1.5 to up to 3 tons per hectare. One way of improving wheat productivity is by the application of new genomic oriented approaches in plant breeding projects. Genome wide association studies (GWAS) are emerging as powerful tools for the understanding of the inheritance of complex traits via utilization of high throughput genotyping technologies and phenotypic assessments of plant collections. In this study, phenotyping and genotyping data on 194 spring wheat accessions from Kazakhstan, Russia, Europe, and CIMMYT were assessed for the identification of marker-trait associations (MTA) of agronomic traits by using GWAS.Field trials in Northern, Central and Southern regions of Kazakhstan using 194 spring wheat accessions revealed strong correlations of yield with booting date, plant height, biomass, number of spikes per plant, and number of kernels per spike. The accessions from Europe and CIMMYT showed high breeding potential for Southern and Central regions of the country in comparison with the performance of the local varieties. The GGE biplot method, using average yield per plant, suggested a clear separation of accessions into their three breeding origins in relationship to the three environments in which they were evaluated. The genetic variation in the three groups of accessions was further studied using 3245 polymorphic SNP (single nucleotide polymorphism) markers. The application of Principal Coordinate analysis clearly grouped the 194 accessions into three clades according to their breeding origins. GWAS on data from nine field trials allowed the identification of 114 MTAs for 12 different agronomic traits.Field evaluation of foreign germplasm revealed its poor yield performance in Northern Kazakhstan, which is the main wheat growing region in the country. However, it was found that EU and CIMMYT germplasm has high breeding potential to improve yield performance in Central and Southern regions. The use of Principal Coordinate analysis clearly separated the panel into three distinct groups according to their breeding origin. GWAS based on use of the TASSEL 5.0 package allowed the identification of 114 MTAs for twelve agronomic traits. The study identifies a network of key genes for improvement of yield productivity in wheat growing regions of Kazakhstan.

Dataset Information

Haplotype block analysis of an Argentinean hexaploid wheat collection and GWAS for yield components and adaptation.

Background

Results

Conclusion

Publications

Haplotype block analysis of an Argentinean hexaploid wheat collection and GWAS for yield components and adaptation.

Similar Datasets

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