Prioritizing quantitative trait loci for root system architecture in tetraploid wheat

© The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Détails bibliographiques
Publié dans:Journal of experimental botany. - 1985. - 67(2016), 4 vom: 18. Feb., Seite 1161-78
Auteur principal: Maccaferri, Marco (Auteur)
Autres auteurs: El-Feki, Walid, Nazemi, Ghasemali, Salvi, Silvio, Canè, Maria Angela, Colalongo, Maria Chiara, Stefanelli, Sandra, Tuberosa, Roberto
Format: Article en ligne
Langue:English
Publié: 2016
Accès à la collection:Journal of experimental botany
Sujets:Journal Article Research Support, Non-U.S. Gov't Association mapping GWAS drought stress germplasm collection grain yield meta-QTLs root growth angle root system architecture plus... rooting depth seminal root.
Description
Résumé:© The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.
Optimization of root system architecture (RSA) traits is an important objective for modern wheat breeding. Linkage and association mapping for RSA in two recombinant inbred line populations and one association mapping panel of 183 elite durum wheat (Triticum turgidum L. var. durum Desf.) accessions evaluated as seedlings grown on filter paper/polycarbonate screening plates revealed 20 clusters of quantitative trait loci (QTLs) for root length and number, as well as 30 QTLs for root growth angle (RGA). Divergent RGA phenotypes observed by seminal root screening were validated by root phenotyping of field-grown adult plants. QTLs were mapped on a high-density tetraploid consensus map based on transcript-associated Illumina 90K single nucleotide polymorphisms (SNPs) developed for bread and durum wheat, thus allowing for an accurate cross-referencing of RSA QTLs between durum and bread wheat. Among the main QTL clusters for root length and number highlighted in this study, 15 overlapped with QTLs for multiple RSA traits reported in bread wheat, while out of 30 QTLs for RGA, only six showed co-location with previously reported QTLs in wheat. Based on their relative additive effects/significance, allelic distribution in the association mapping panel, and co-location with QTLs for grain weight and grain yield, the RSA QTLs have been prioritized in terms of breeding value. Three major QTL clusters for root length and number (RSA_QTL_cluster_5#, RSA_QTL_cluster_6#, and RSA_QTL_cluster_12#) and nine RGA QTL clusters (QRGA.ubo-2A.1, QRGA.ubo-2A.3, QRGA.ubo-2B.2/2B.3, QRGA.ubo-4B.4, QRGA.ubo-6A.1, QRGA.ubo-6A.2, QRGA.ubo-7A.1, QRGA.ubo-7A.2, and QRGA.ubo-7B) appear particularly valuable for further characterization towards a possible implementation of breeding applications in marker-assisted selection and/or cloning of the causal genes underlying the QTLs
Description:Date Completed 02.11.2016
Date Revised 09.04.2022
published: Print
Citation Status MEDLINE
ISSN:1460-2431
DOI:10.1093/jxb/erw039