Eggplant Resistance to the Ralstonia solanacearum Species Complex Involves Both Broad-Spectrum and Strain-Specific Quantitative Trait Loci

Abstract

Bacterial wilt (BW) is a major disease of solanaceous crops caused by the Ralstonia solanacearum species complex (RSSC). Strains are grouped into five phylotypes (I, IIA, IIB, III, and IV). Varietal resistance is the most sustainable strategy for managing BW. Nevertheless, breeding to improve cultivar resistance has been limited by the pathogen’s extensive genetic diversity. Identifying the genetic bases of specific and non-specific resistance is a prerequisite to breed improvement. A major gene (ERs1) was previously mapped in eggplant (Solanum melongena L.) using an intraspecific population of recombinant inbred lines derived from the cross of susceptible MM738 (S) × resistant AG91-25 (R). ERs1 was originally found to control three strains from phylotype I, while being totally ineffective against a virulent strain from the same phylotype. We tested this population against four additional RSSC strains, representing phylotypes I, IIA, IIB, and III in order to clarify the action spectrum of ERs1. We recorded wilting symptoms and bacterial stem colonization under controlled artificial inoculation. We constructed a high-density genetic map of the population using single nucleotide polymorphisms (SNPs) developed from genotyping-by-sequencing and added 168 molecular markers [amplified fragment length polymorphisms (AFLPs), simple sequence repeats (SSRs), and sequence-related amplified polymorphisms (SRAPs)] developed previously. The new linkage map based on a total of 1,035 markers was anchored on eggplant, tomato, and potato genomes. Quantitative trait locus (QTL) mapping for resistance against a total of eight RSSC strains resulted in the detection of one major phylotype-specific QTL and two broad-spectrum QTLs. The major QTL, which specifically controls three phylotype I strains, was located at the bottom of chromosome 9 and corresponded to the previously identified major gene ERs1. Five candidate R-genes were underlying this QTL, with different alleles between the parents. The two other QTLs detected on chromosomes 2 and 5 were found to be associated with partial resistance to strains of phylotypes I, IIA, III and strains of phylotypes IIA and III, respectively. Markers closely linked to these three QTLs will be crucial for breeding eggplant with broad-spectrum resistance to BW. Furthermore, our study provides an important contribution to the molecular characterization of ERs1, which was initially considered to be a major resistance gene.

Genomic Tools for the Enhancement of Vegetable Crops: A Case in Eggplant

“…The availability of a large array of molecular markers obtained by genomic techniques allows a very efficient marker-assisted selection (MAS), by selecting the genes or quantitative trait loci (QTLs) of interest and facilitating the removal of undesirable traits of wild relatives and saving time and resources compared to the conventional breeding approach (Morrell et al, 2012;Brozynska et al, 2016). Even though the gap between eggplant and the crops with more genomic resources is still wide, a clear turnaround in this trend has occurred in the last few years (Hirakawa et al, 2014;Portis et al, 2015;Kouassi et al, 2016;Plazas et al, 2016;Salgon et al, 2017).…”

“…Although, the map had a low saturation due to extremely low polymorphism rate, with only 119 markers mapped and most of which AFLPs, a major gene was identified (ERs1) in LG2. The low level of polymorphism in the RILs population showed with AFLPs drastically changed when the individuals were sequenced by GBS, identifying 1,779 filtered SNPs and allowing to build a high-density genetic map for screening four new strains of R. solanacearum, apart from the previous ones of Lebeau et al (2013), belonging to phylotypes I, IIA, IIB and III (Salgon et al, 2017). The overall map length and the average marker density had been increased to 1,085 and 4.4 cM, respectively, and the LGs number had been reduced from 18 to 14 (Table 2), which lead to identifying a major QTL at the bottom of LG 9 that controls three phylotype I strains, corresponded to the previously identified major gene ERs1 of Lebeau et al (2013), and two other minor QTLs on LG 2, associated with partial resistance to strains of phylotypes I, IIA, III, and on LG 5, controlling the strains of phylotypes IIA and III.…”

“…Barchi et al (2011) RAD approach identified ~10,000 SNPs and 2,000 putative SSRs from the parents of a mapping population with a reference genome. Similarly, a GBS was performed in a 180 F6 RILs population identifying 1,779 filtered SNPs and improved drastically the quality of an intraspecific genetic map (Salgon et al, 2017). These genotyping through sequencing methods constitute a really powerful tools to increase precision and accelerate al., 2016b).…”

Genetics and Genomics of Cultivated Eggplants and Wild Relatives

“…AFLPs drastically changed when the individuals were sequenced by GBS, identifying 1,779 filtered SNPs and allowing to build a high-density genetic map for screening four new strains of R. solanacearum, apart from the previous ones of Lebeau et al (2013), belonging to phylotypes I, IIA, IIB and III (Salgon et al, 2017). The overall map length and the average marker density had been increased to 1,085 and 4.4 cM, respectively, and the LGs number had been reduced from 18 to 14 (Table 2), which lead to identifying a major QTL at the bottom of LG 9 that controls three phylotype I strains, corresponded to the previously identified major gene ERs1 of Lebeau et al (2013), and two other minor QTLs on LG 2, associated with partial resistance to strains of phylotypes I, IIA, III, and on LG 5, controlling the strains of phylotypes IIA and III.…”

“…The availability of a large array of molecular markers obtained by genomic techniques allows a very efficient marker-assisted selection (MAS), by selecting the genes or quantitative trait loci (QTLs) of interest and facilitating the removal of undesirable traits of wild relatives and saving time and resources compared to the conventional breeding approach (Morrell et al, 2012;Brozynska et al, 2016). Even though the gap between eggplant and the crops with more genomic resources is still wide, a clear turnaround in this trend has occurred in the last few years (Hirakawa et al, 2014;Portis et al, 2015;Kouassi et al, 2016;Salgon et al, 2017).…”