Transcriptome-Assisted SNP Marker Discovery for Phytophthora infestans Resistance in Solanum lycopersicum L.

Late blight, caused by oomycetes Phytophthora infestans is one of the most challenging fungal diseases to manage in tomato plants (Solanum lycopersicum L.). Toward managing the disease, conventional breeding has successfully introgressed genetic loci conferring disease resistance from various wild relatives of tomato into commercial varieties. The cataloging of disease-associated SNP markers and a deeper understanding of disease-resistance mechanisms are needed to keep up with the demand for commercial varieties resistant against emerging pathogen strains. To this end, we performed transcriptome sequencing to evaluate the gene expression dynamics of tomato varieties, resistant and susceptible to Phytophthora infection. Further integrating the transcriptome dataset with large-scale public genomic data of varieties with known disease phenotypes, a panel of single nucleotide polymorphism (SNP) markers correlated with disease resistance was identified. These SNPs were then validated on 31 lines with contrasting phenotypes for late blight. The identified SNPs are located on genes coding for a putative cysteine-rich transmembrane module (CYSTM), Solyc09g098310, and a nucleotide-binding site-leucine-rich repeat protein, Solyc09g098100, close to the well-studied Ph-3 resistance locus known to have a role in plant immunity against fungal infections. The panel of SNPs generated by this study using transcriptome sequencing showing correlation with disease resistance across a broad set of plant material can be used as markers for molecular screening in tomato breeding.

Bacterial endophytes as indicators of susceptibility to Cercospora Leaf Spot (CLS) disease in Beta vulgaris L.

The fungus Cercospora beticola causes Cercospora Leaf Spot (CLS) of sugar beet (Beta vulgaris L.). Despite the global importance of this disease, durable resistance to CLS has still not been obtained. Therefore, the breeding of tolerant hybrids is a major goal for the sugar beet sector. Although recent studies have suggested that the leaf microbiome composition can offer useful predictors to assist plant breeders, this is an untapped resource in sugar beet breeding efforts. Using Ion GeneStudio S5 technology to sequence amplicons from seven 16S rRNA hypervariable regions, the most recurring endophytes discriminating CLS-symptomatic and symptomless sea beets (Beta vulgaris L.ssp. maritima) were identified. This allowed the design of taxon-specific primer pairs to quantify the abundance of the most representative endophytic species in large naturally occurring populations of sea beet and subsequently in sugar beet breeding genotypes under either CLS symptomless or infection stages using qPCR. Among the screened bacterial genera, Methylobacterium and Mucilaginibacter were found to be significantly (p < 0.05) more abundant in symptomatic sea beets with respect to symptomless. In cultivated sugar beet material under CLS infection, the comparison between resistant and susceptible genotypes confirmed that the susceptible genotypes hosted higher contents of the above-mentioned bacterial genera. These results suggest that the abundance of these species can be correlated with increased sensitivity to CLS disease. This evidence can further prompt novel protocols to assist plant breeding of sugar beet in the pursuit of improved pathogen resistance.

Endophytic Microbiome Responses to Sulfur Availability in Beta vulgaris (L.).

Sulfur is an essential plant macronutrient, and its adequate supply allows an efficient root storage and sugar extractability in sugar beets (Beta vulgaris L.). In this study, we investigated the effect of changes in sulfur availability on the endophytic community structure of sugar beets. Plants were hydroponically grown in a complete nutrient solution (S-supplied), a nutrient solution without MgSO4 (S-deprived), and a nutrient solution without MgSO4 for six days and resupplied with 100 µM MgSO4 for 48 h (S-resupplied). The sulfur status was monitored by inductively coupled plasma ICP-OES, and combustion analysis together with the evaluation of microRNA395 as a biomarker for sulfate status. Metabarcoding of the bacterial 16S rRNA gene was carried out in order to determine leaf endophytic community structure. The Shannon diversity index significantly differed (p < 0.05) between sulfate-supplied and sulfate-deprived seedlings. Validation by Real-Time PCR showed a significant increase (p < 0.05) of Burkholderia spp. in sulfate-deprived plants as compared to sulfate-supplied ones. The study sheds new light on the effects of nutrient deficiency on the microbiome of sugar beet plants.

Identification and validation of SNP markers linked to seed toxicity in Jatropha curcas L.

Edible/non-toxic varieties of Jatropha curcas L. are gaining increasing attention, providing both oil as biofuel feedstock or even as edible oil and the seed kernel meal as animal feed ingredient. They are a viable alternative to the limitation posed by the presence of phorbol esters in toxic varieties. Accurate genotyping of toxic/non-toxic accessions is critical to breeding management. The aim of this study was to identify SNP markers linked to seed toxicity in J. curcas. For SNP discovery, NGS technology was used to sequence the whole genomes of a toxic and non-toxic parent along with a bulk of 51 toxic and 30 non-toxic F2 plants. To ascertain the association between SNP markers and seed toxicity trait, candidate SNPs were genotyped on 672 individuals segregating for seed toxicity and two collections of J. curcas composed of 96 individuals each. In silico SNP discovery approaches led to the identification of 64 candidate SNPs discriminating non-toxic and toxic samples. These SNPs were mapped on Chromosome 8 within the Linkage Group 8 previously identified as a genomic region important for phorbol ester biosynthesis. The association study identified two new SNPs, SNP_J22 and SNP_J24 significantly linked to low toxicity with R2 values of 0.75 and 0.54, respectively. Our study released two valuable SNP markers for high-throughput, marker-assisted breeding of seed toxicity in J. curcas.