QTL-mapping for sunflower Verticillium wilt and leaf mottle resistance

GARCÍA M.; BEN GUERRERO E.; MARINGOLO C.; LIA V.; MERINO G.; AGUILERA P.; TROGLIA C.; HEINZ R.; MONTECCHIA J.F.; FASS M.; GONZÁLEZ S.; QUIROZ F.; PANIEGO N.

Córdoba

Simposio; 1º Simposio internacional de mejoramiento genético vegetal; 2021

Sunflower Verticillium wilt and leaf mottle (SVW), caused by Verticillium dahliae (Kleb.; Vd), is a soil-borne monocyclic disease affecting sunflower worldwide. A single dominant locus, known as V1, was formerly effective in controlling North-American Vd races, whereas races from Argentina, Europe and an emerging race from USA overcome its resistance. Here, we present a QTL-mapping study for SVW resistance using a recombinant inbred line (RIL) population (BMP). A robust phenotypic characterization for SVW-resistance was made across four consecutive field-trials (FTs) growing the BMP in a highly Vd-infested field. Several disease descriptors (DDs), including incidence (DI) and severity (DS), were scored across four phenological stages, from early floral growth to grain filling onset. DI at flowering (DI.Flw) and DS at grain filling (DS.Gf) were selected for QTL-mapping due to their impact on sunflower yield. Genetically, the RIL panel and the parental lines were characterized by a double digest restriction-site associated DNA sequencing technique (ddRADSeq). Objectives: The main goal of this work was to identify the chromosomal regions controlling SVW-resistance on a biparenal population by performing a QTL-mapping analysis on different DDs. Materials and methods: The BMP is composed of 139 RILs derived from the crossing of two public restorer lines, PAC2 and RHA439, susceptible and highly tolerant to Vd Argentinian races, respectively. Four consecutive FTs in two replicates were conducted from 2013/14 to 2016/17 in a V.dahliae inoculum reservoir at the Agricultural Experimental Station of INTA Balcarce, Bs.As. Argentina. The adjusted means for each RIL were obtained from Montecchia et al. 2021. The BMP was genotyped by ddRADSeq methodology. Sequenced reads were processed and mapped to the genome reference. SNP identification was performed using the software Stacks (Catchen et al. 2013) with the sunflower reference genome published by Badouin et al. (2017). A total of 3927 SNP loci were found. An imputation strategy of missing data accounting for linkage disequilibrium and read´s map position in the reference genome was implemented. The R-Package onemap version 2.1.1 (Margarido et al. 2007, R Core Team) was used for linkage map calculation and the Composite Interval Mapping (CIM) procedure of the R-Package qtl version 1.42-8 (Broman et al. 2003) was used for QTL-mapping analyses.Results and Conclusions: After filtering for marker quality and frequency criteria, the missing data imputation strategy implemented rendered a full matrix of 2292 SNPs. These markers were located in 17 linkage groups corresponding to the 17 chromosomes of the sunflower genome. Four SVW-resistance QTL were identified for DI.Gf in four different chromosomes and two QTL for DS.Gf co-localized to the most significant QTL of DI.Flw. Together, these QTLs explained a large proportion of the variation of these DDs. This work provides valuable information about the genomic regions underlying SVW resistance. The results presented enable the search of candidate genes and the identification of genetic variability among sunflower breeding materials. Altogether, these resources will allow the development of new disease resistance breeding strategies for SVW.