Improving the Health Benefits of Snap Bean: Genome-Wide Association Studies of Total Phenolic Content

Snap beans are a significant source of micronutrients in the human diet. Among the micronutrients present in snap beans are phenolic compounds with known beneficial effects on human health, potentially via their metabolism by the gut-associated microbiome. The genetic pathways leading to the production of phenolics in snap bean pods remain uncertain. In this study, we quantified the level of total phenolic content (TPC) in the Bean Coordinated Agriculture Program (CAP) snap bean diversity panel of 149 accessions. The panel was characterized spectrophotometrically for phenolic content with a Folin-Ciocalteu colorimetric assay. Flower, seed and pod color were also quantified, as red, purple, yellow and brown colors are associated with anthocyanins and flavonols in common bean. Genotyping was performed through an Illumina Infinium Genechip BARCBEAN6K_3 single nucleotide polymorphism (SNP) array. Genome-Wide Association Studies (GWAS) analysis identified 11 quantitative trait nucleotides (QTN) associated with TPC. An SNP was identified for TPC on Pv07 located near the P gene, which is a major switch in the flavonoid biosynthetic pathway. Candidate genes were identified for seven of the 11 TPC QTN. Five regulatory genes were identified and represent novel sources of variation for exploitation in developing snap beans with higher phenolic levels for greater health benefits to the consumer.

Association Mapping for 24 Traits Related to Protein Content, Gluten Strength, Color, Cooking, and Milling Quality Using Balanced and Unbalanced Data in Durum Wheat [Triticum turgidum L. var. durum (Desf).]

Durum wheat [Triticum durum (Desf).] is mostly used to produce pasta, couscous, and bulgur. The quality of the grain and end-use products determine its market value. However, quality tests are highly resource intensive and almost impossible to conduct in the early generations in the breeding program. Modern genomics-based tools provide an excellent opportunity to genetically dissect complex quality traits to expedite cultivar development using molecular breeding approaches. This study used a panel of 243 cultivars and advanced breeding lines developed during the last 20 years to identify SNPs associated with 24 traits related to nutritional value and quality. Genome-wide association study (GWAS) identified a total of 179 marker-trait associations (MTAs), located in 95 genomic regions belonging to all 14 durum wheat chromosomes. Major and stable QTLs were identified for gluten strength on chromosomes 1A and 1B, and for PPO activity on chromosomes 1A, 2B, 3A, and 3B. As a large amount of unbalance phenotypic data are generated every year on advanced lines in all the breeding programs, the applicability of such a dataset for identification of MTAs remains unclear. We observed that ∼84% of the MTAs identified using a historic unbalanced dataset (belonging to a total of 80 environments collected over a period of 16 years) were also identified in a balanced dataset. This suggests the suitability of historic unbalanced phenotypic data to identify beneficial MTAs to facilitate local-knowledge-based breeding. In addition to providing extensive knowledge about the genetics of quality traits, association mapping identified several candidate markers to assist durum wheat quality improvement through molecular breeding. The molecular markers associated with important traits could be extremely useful in the development of improved quality durum wheat cultivars using marker-assisted selection (MAS).

Quantitative Disease Resistance under Elevated Temperature: Genetic Basis of New Resistance Mechanisms to Ralstonia solanacearum

In the context of climate warming, plants will be facing an increased risk of epidemics as well as the emergence of new highly aggressive pathogen species. Although a permanent increase of temperature strongly affects plant immunity, the underlying molecular mechanisms involved are still poorly characterized. In this study, we aimed to uncover the genetic bases of resistance mechanisms that are efficient at elevated temperature to the Ralstonia solanacearum species complex (RSSC), one of the most harmful phytobacteria causing bacterial wilt. To start the identification of quantitative trait loci (QTLs) associated with natural variation of response to R. solanacearum, we adopted a genome wide association (GWA) mapping approach using 176 worldwide natural accessions of Arabidopsis thaliana inoculated with the R. solanacearum GMI1000 strain. Following two different procedures of root-inoculation (root apparatus cut vs. uncut), plants were grown either at 27 or 30°C, with the latter temperature mimicking a permanent increase in temperature. At 27°C, the RPS4/RRS1-R locus was the main QTL of resistance detected regardless of the method of inoculation used. This highlights the power of GWA mapping to identify functionally important loci for resistance to the GMI1000 strain. At 30°C, although most of the accessions developed wilting symptoms, we identified several QTLs that were specific to the inoculation method used. We focused on a QTL region associated with response to the GMI1000 strain in the early stages of infection and, by adopting a reverse genetic approach, we functionally validated the involvement of a strictosidine synthase-like 4 (SSL4) protein that shares structural similarities with animal proteins known to play a role in animal immunity.

Genome-wide association mapping of quantitative resistance to sudden death syndrome in soybean

BACKGROUND

Sudden death syndrome (SDS) is a serious threat to soybean production that can be managed with host plant resistance. To dissect the genetic architecture of quantitative resistance to the disease in soybean, two independent association panels of elite soybean cultivars, consisting of 392 and 300 unique accessions, respectively, were evaluated for SDS resistance in multiple environments and years. The two association panels were genotyped with 52,041 and 5,361 single nucleotide polymorphisms (SNPs), respectively. Genome-wide association mapping was carried out using a mixed linear model that accounted for population structure and cryptic relatedness.

RESULT

A total of 20 loci underlying SDS resistance were identified in the two independent studies, including 7 loci localized in previously mapped QTL intervals and 13 novel loci. One strong peak of association on chromosome 18, associated with all disease assessment criteria across the two panels, spanned a physical region of 1.2 Mb around a previously cloned SDS resistance gene (GmRLK18-1) in locus Rfs2. An additional variant independently associated with SDS resistance was also found in this genomic region. Other peaks were within, or close to, sequences annotated as homologous to genes previously shown to be involved in plant disease resistance. The identified loci explained an average of 54.5% of the phenotypic variance measured by different disease assessment criteria.

CONCLUSIONS

This study identified multiple novel loci and refined the map locations of known loci related to SDS resistance. These insights into the genetic basis of SDS resistance can now be used to further enhance durable resistance to SDS in soybean. Additionally, the associations identified here provide a basis for further efforts to pinpoint causal variants and to clarify how the implicated genes affect SDS resistance in soybean.