Saturation mapping of regions determining resistance to Ascochyta blight and broomrape in faba bean using transcriptome-based SNP genotyping
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Transcriptome-based SNP markers were genotyped in a faba bean map to saturate regions bearing QTL for Ascochyta fabae and broomrape and distinguish positional and functional candidates underlying both resistances.
Faba bean is an important food crop worldwide. Marker-assisted selection for disease resistance is a top priority in current faba bean research programs, with pathogens such as Ascochyta fabae and broomrape (Orobanche crenata) being among the major constraints in global faba bean production. However, progress in genetics and genomics in this species has lagged behind that of other grain legumes. Although genetic maps are available, most markers are not in or are too distant from target genes to enable an accurate prediction of the desired phenotypes. In this study, a set of SNP markers located in gene coding regions was selected using transcriptomic data. Ninety-two new SNP markers were genotyped to obtain the most complete map reported so far in the 29H × Vf136 faba bean population. Most of the QTL regions previously described in this cross were enriched with SNP markers. Two QTLs for O. crenata resistance (Oc7 and Oc8) were confirmed. Oc7 and Oc10 located nearby a QTL for A. fabae resistance suggested that these genomic regions might encode common resistance mechanisms and could be targets for selection strategies against both pathogens. We also confirmed three regions in chromosomes II (Af2), III (Af3) and VI associated with Ascochyta blight resistance. The QTLs ratified in the present study are now flanked by or include reliable SNP markers in their intervals. This new information provides a valuable starting point in the search for relevant positional and functional candidates underlying both types of resistance.
This research was financed by the Spanish MINECO (project RTA2010-00059) co-financed by the EU through the European Regional Development Fund (ERDF) 2014–2020 “Programa Operativo de Crecimiento Inteligente” and the IFAPA project PR.AVA.AVA201601.17 co-financed by ERDF. Partial funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under the Grant agreement no. FP7-613551, LEGATO project is also acknowledged. S. Ocaña-Moral acknowledges the FPI-INIA fellowship and N. Gutiérrez the MINECO financial support through the “Juan de la Cierva” Program. The authors would like to thank Dr. CM Avila and Dr. SG Atienza for their helpful and critical comments.
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Conflict of interest
All authors have read and approved the final manuscript. The authors declare that they have no conflict of interest.
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