Single nucleotide polymorphisms reveal genetic diversity in New Mexican chile peppers (Capsicum spp.)

Insights into the genetic architecture of Phytophthora capsici root rot resistance in chile pepper (Capsicum spp.) from multi-locus genome-wide association study

BACKGROUND

Phytophthora root rot, a major constraint in chile pepper production worldwide, is caused by the soil-borne oomycete, Phytophthora capsici. This study aimed to detect significant regions in the Capsicum genome linked to Phytophthora root rot resistance using a panel consisting of 157 Capsicum spp. genotypes. Multi-locus genome wide association study (GWAS) was conducted using single nucleotide polymorphism (SNP) markers derived from genotyping-by-sequencing (GBS). Individual plants were separately inoculated with P. capsici isolates, 'PWB-185', 'PWB-186', and '6347', at the 4-8 leaf stage and were scored for disease symptoms up to 14-days post-inoculation. Disease scores were used to calculate disease parameters including disease severity index percentage, percent of resistant plants, area under disease progress curve, and estimated marginal means for each genotype.

RESULTS

Most of the genotypes displayed root rot symptoms, whereas five accessions were completely resistant to all the isolates and displayed no symptoms of infection. A total of 55,117 SNP markers derived from GBS were used to perform multi-locus GWAS which identified 330 significant SNP markers associated with disease resistance. Of these, 56 SNP markers distributed across all the 12 chromosomes were common across the isolates, indicating association with more durable resistance. Candidate genes including nucleotide-binding site leucine-rich repeat (NBS-LRR), systemic acquired resistance (SAR8.2), and receptor-like kinase (RLKs), were identified within 0.5 Mb of the associated markers.

CONCLUSIONS

Results will be used to improve resistance to Phytophthora root rot in chile pepper by the development of Kompetitive allele-specific markers (KASP®) for marker validation, genomewide selection, and marker-assisted breeding.

Optimized Pepper Target SNP-Seq Applied in Population Structure and Genetic Diversity Analysis of 496 Pepper (Capsicum spp.) Lines

Peppers are a major vegetable crop worldwide. With the completion of additional genome assemblies, a multitude of single-nucleotide polymorphisms (SNPs) can be utilized for population structure and genetic diversity analysis. In this study, we used target SNP-sequencing as a new high-throughput sequencing technology, screening out 425 perfect SNPs for analyzing the genetic diversity and population structure among 496 pepper lines from five pepper species in China and abroad. The perfect SNP panel exhibited commendable discriminative ability, as indicated by the average values of polymorphism information content, observed heterozygosity, minor allele frequency, and genetic diversity, which were 0.346, 0.011, 0.371, and 0.449, respectively. Based on phylogenetic, population structure, and principal component analyses, 484 C. annuum lines were divided into four subpopulations according to the shape of fruit: blocky fruit, wide-horn fruit, narrow-horn fruit, and linear fruit. These subpopulations displayed clear clustering with minimal or no overlap. Moreover, F statistic (Fst) analysis revealed considerable distinctions among these subpopulations. Additionally, we established a set of 47 core SNPs that could effectively differentiate among all pepper lines. This core SNP set could precisely classify the C. annuum lines into four distinct fruit-shape groups. The blocky and narrow-horn fruit subpopulations displayed the lowest and highest genetic diversity, respectively. This study highlights the importance of fruit shape as a crucial trait in pepper breeding. Moreover, this work indicates the immense potential of optimized target SNP technology in the addition of foreground markers of important traits to improve molecular breeding efficiency, and demonstrates its broad application prospects in the genetic analysis and variety identification of peppers.

Ridge regression and deep learning models for genome-wide selection of complex traits in New Mexican Chile peppers

BACKGROUND

Genomewide prediction estimates the genomic breeding values of selection candidates which can be utilized for population improvement and cultivar development. Ridge regression and deep learning-based selection models were implemented for yield and agronomic traits of 204 chile pepper genotypes evaluated in multi-environment trials in New Mexico, USA.

RESULTS

Accuracy of prediction differed across different models under ten-fold cross-validations, where high prediction accuracy was observed for highly heritable traits such as plant height and plant width. No model was superior across traits using 14,922 SNP markers for genomewide selection. Bayesian ridge regression had the highest average accuracy for first pod date (0.77) and total yield per plant (0.33). Multilayer perceptron (MLP) was the most superior for flowering time (0.76) and plant height (0.73), whereas the genomic BLUP model had the highest accuracy for plant width (0.62). Using a subset of 7,690 SNP loci resulting from grouping markers based on linkage disequilibrium coefficients resulted in improved accuracy for first pod date, ten pod weight, and total yield per plant, even under a relatively small training population size for MLP and random forest models. Genomic and ridge regression BLUP models were sufficient for optimal prediction accuracies for small training population size. Combining phenotypic selection and genomewide selection resulted in improved selection response for yield-related traits, indicating that integrated approaches can result in improved gains achieved through selection.

CONCLUSIONS

Accuracy values for ridge regression and deep learning prediction models demonstrate the potential of implementing genomewide selection for genetic improvement in chile pepper breeding programs. Ultimately, a large training data is relevant for improved genomic selection accuracy for the deep learning models.

Characterization of the Key Compounds of Bell Pepper by Spectrophotometry and Gas Chromatography on the Effects of Induced Stress on the Concentration of Secondary Metabolite

Sweet peppers are consumed worldwide, and traditional uses have sparked interest in their applications as dietary antioxidants, which can be enhanced in plants using elicitors. These are endowed with phytochemicals with potential health benefits such as antioxidants, bioavailability, and bioaccessibility. The trend in metabolomics shows us chemical fingerprints linking metabolomics, innovative analytical form, and bioinformatics tools. The objective was to evaluate the impact of multiple stress interactions, elicitor concentrations, and electrical conductivity on the concentration of secondary metabolites to relate their response to metabolic pathways through the foliar application of a cocktail of said elicitors in pepper crops under greenhouse conditions. The extracts were analyzed by spectrophotometry and gas chromatography, and it was shown that the PCA analysis identified phenolic compounds and low molecular weight metabolites, confirming this as a metabolomic fingerprint in the hierarchical analysis. These compounds were also integrated by simultaneous gene and metabolite simulants to obtain effect information on different metabolic pathways. Showing changes in metabolite levels at T6 (36 mM H₂O₂ and 3.6 dS/m) and T7 (0.1 mM SA and 3.6 dS/m) but showing statistically significant changes at T5 (3.6 dS/m) and T8 (0.1 mM SA, 36 mM H₂O₂, and 3.6 dS/m) compared to T1 (32 dS/m) or control. Six pathways changed significantly (p < 0.05) in stress-induced treatments: aminoacyl t-RNA and valine-leucine-isoleucine biosynthesis, and alanine-aspartate-glutamate metabolism, glycoxylate-dicarboxylate cycle, arginine-proline, and citrate. This research provided a complete profile for the characterization of metabolomic fingerprint of bell pepper under multiple stress conditions.

Widely Targeted Metabolomics Reveals Metabolite Diversity in Jalapeño and Serrano Chile Peppers (Capsicum annuum L.)

Chile peppers (Capsicum annuum L.) are good sources of vitamins and minerals that can be included in the diet to mitigate nutritional deficiencies. Metabolomics examines the metabolites involved in biological pathways to understand the genes related to complex phenotypes such as the nutritional quality traits. The current study surveys the different metabolites present in jalapeño ('NuMex Pumpkin Spice') and serrano ('NuMex LotaLutein') type chile peppers grown in New Mexico using a widely targeted metabolomics approach, with the 'NuMex LotaLutein' as control. A total of 1088 different metabolites were detected, where 345 metabolites were differentially expressed; 203 (59%) were downregulated and 142 (41%) were upregulated (i.e., relative metabolite content is higher in 'NuMex Pumpkin Spice'). The upregulated metabolites comprised mostly of phenolic acids (42), flavonoids (22), and organic acids (13). Analyses of principal component (PC) and orthogonal partial least squares demonstrated clustering based on cultivars, where at least 60% of variation was attributed to the first two PCs. Pathway annotation identified 89 metabolites which are involved in metabolic pathways and the biosynthesis of secondary metabolites. Altogether, metabolomics provided insights into the different metabolites present which can be targeted for breeding and selection towards the improvement of nutritional quality traits in Capsicum.

Chile Pepper (Capsicum) Breeding and Improvement in the "Multi-Omics" Era

Chile pepper (Capsicum spp.) is a major culinary, medicinal, and economic crop in most areas of the world. For more than hundreds of years, chile peppers have "defined" the state of New Mexico, USA. The official state question, "Red or Green?" refers to the preference for either red or the green stage of chile pepper, respectively, reflects the value of these important commodities. The presence of major diseases, low yields, decreased acreages, and costs associated with manual labor limit production in all growing regions of the world. The New Mexico State University (NMSU) Chile Pepper Breeding Program continues to serve as a key player in the development of improved chile pepper varieties for growers and in discoveries that assist plant breeders worldwide. Among the traits of interest for genetic improvement include yield, disease resistance, flavor, and mechanical harvestability. While progress has been made, the use of conventional breeding approaches has yet to fully address producer and consumer demand for these traits in available cultivars. Recent developments in "multi-omics," that is, the simultaneous application of multiple omics approaches to study biological systems, have allowed the genetic dissection of important phenotypes. Given the current needs and production constraints, and the availability of multi-omics tools, it would be relevant to examine the application of these approaches in chile pepper breeding and improvement. In this review, we summarize the major developments in chile pepper breeding and present novel tools that can be implemented to facilitate genetic improvement. In the future, chile pepper improvement is anticipated to be more data and multi-omics driven as more advanced genetics, breeding, and phenotyping tools are developed.

Genomic regions and candidate genes linked with Phytophthora capsici root rot resistance in chile pepper (Capsicum annuum L.)

BACKGROUND

Phytophthora root rot, caused by Phytophthora capsici, is a major disease affecting Capsicum production worldwide. A recombinant inbred line (RIL) population derived from the hybridization between 'Criollo de Morellos-334' (CM-334), a resistant landrace from Mexico, and 'Early Jalapeno', a susceptible cultivar was genotyped using genotyping-by-sequencing (GBS)-derived single nucleotide polymorphism (SNP) markers. A GBS-SNP based genetic linkage map for the RIL population was constructed. Quantitative trait loci (QTL) mapping dissected the genetic architecture of P. capsici resistance and candidate genes linked to resistance for this important disease were identified.

RESULTS

Development of a genetic linkage map using 1,973 GBS-derived polymorphic SNP markers identified 12 linkage groups corresponding to the 12 chromosomes of chile pepper, with a total length of 1,277.7 cM and a marker density of 1.5 SNP/cM. The maximum gaps between consecutive SNP markers ranged between 1.9 (LG7) and 13.5 cM (LG5). Collinearity between genetic and physical positions of markers reached a maximum of 0.92 for LG8. QTL mapping identified genomic regions associated with P. capsici resistance in chromosomes P5, P8, and P9 that explained between 19.7 and 30.4% of phenotypic variation for resistance. Additive interactions between QTL in chromosomes P5 and P8 were observed. The role of chromosome P5 as major genomic region containing P. capsici resistance QTL was established. Through candidate gene analysis, biological functions associated with response to pathogen infections, regulation of cyclin-dependent protein serine/threonine kinase activity, and epigenetic mechanisms such as DNA methylation were identified.

CONCLUSIONS

Results support the genetic complexity of the P. capsici-Capsicum pathosystem and the possible role of epigenetics in conferring resistance to Phytophthora root rot. Significant genomic regions and candidate genes associated with disease response and gene regulatory activity were identified which allows for a deeper understanding of the genomic landscape of Phytophthora root rot resistance in chile pepper.