Regulatory Mechanisms of the Resistance to Common Bacterial Blight Revealed by Transcriptomic Analysis in Common Bean (Phaseolus vulgaris L.)

GWAS of resistance to three bacterial diseases in the Andean common bean diversity panel

Bacterial brown spot (BBS) caused by Pseudomonas syringae pv. syringae (Pss), common bacterial blight (CBB) caused by Xanthomonas axonopodis pv. phaseoli (Xap) and Xanthomonas fuscans subsp. fuscans (Xff), and halo bacterial blight (HBB), caused by Pseudomonas syringae pv. phaseolicola (Psph), are major bacterial diseases that severely affect common bean yields and global food security. Andean-origin dry beans, representing large-seeded market classes, are particularly susceptible. Using 140,325 SNPs, a multi-locus GWAS was conducted on subsets of the Andean diversity panel (ADP) phenotyped for BBS in South Africa, CBB in Puerto Rico, South Africa, and Zambia, and HBB in South Africa, through natural infection, artificial inoculation, or both. Twenty-four QTL associated with resistance were identified: nine for BBS, eight for CBB, and seven for HBB. Four QTL intervals on Pv01, Pv03, Pv05, and Pv08 overlapped with BBS and HBB resistance. A genomic interval on Pv01, near the fin gene, which determines growth habit, was linked to resistance to all three pathogens. Different QTLs were detected for BBS and CBB resistance when phenotyped under natural infection versus artificial inoculation. These results underscore the importance of combining phenotyping methods in multi-GWAS to capture the full genetic spectrum. Previously recognized CBB resistance QTL SAP6 and SU91 and HBB resistance QTL HB4.2, and HB5.1, were observed. Other common (MAF >0.25) and rare (MAF <0.05) resistance QTL were also detected. Overall, these findings enhance the understanding and utilization of bacterial resistance present in ADP for the development of common beans with improved resistance.

Global transcriptome analysis reveals resistance genes in the early response of common bean (Phaseolus vulgaris L.) to Colletotrichum lindemuthianum

BACKGROUND

Disease can drastically impair common bean (Phaseolus vulgaris L.) production. Anthracnose, caused by the fungal pathogen Colletotrichum lindemuthianum (Sacc. and Magnus) Briosi and Cavara, is one of the diseases that are widespread and cause serious economic loss in common bean.

RESULTS

Transcriptome analysis of the early response of common bean to anthracnose was performed using two resistant genotypes, Hongyundou and Honghuayundou, and one susceptible genotype, Jingdou. A total of 9,825 differentially expressed genes (DEGs) responding to pathogen infection and anthracnose resistance were identified by differential expression analysis. By using weighted gene coexpression network analysis (WGCNA), 2,051 DEGs were found to be associated with two resistance-related modules. Among them, 463 DEGs related to anthracnose resistance were considered resistance-related candidate genes. Nineteen candidate genes were coexpressed with three resistance genes, Phvul.001G243600, Phvul.001G243700 and Phvul.001G243800. To further identify resistance genes, 46 candidate genes were selected for experimental validation using salicylic acid (SA) and methyl jasmonate (MeJA). The results indicated that 38 candidate genes that responded to SA/MeJA treatment may be involved in anthracnose resistance in common bean.

CONCLUSIONS

This study identified 38 resistance-related candidate genes involved in the early response of common bean, and 19 resistance-related candidate genes were coexpressed with anthracnose resistance genes. This study identified putative resistance genes for further resistance genetic investigation and provides an important reference for anthracnose resistance breeding in common bean.

Full-length transcriptome and RNA-Seq analyses reveal the resistance mechanism of sesame in response to Corynespora cassiicola

BACKGROUND

Corynespora leaf spot is a common leaf disease occurring in sesame, and the disease causes leaf yellowing and even shedding, which affects the growth quality of sesame. At present, the mechanism of sesame resistance to this disease is still unclear. Understanding the resistance mechanism of sesame to Corynespora leaf spot is highly important for the control of infection. In this study, the leaves of the sesame resistant variety (R) and the sesame susceptible variety (S) were collected at 0-48 hpi for transcriptome sequencing, and used a combined third-generation long-read and next-generation short-read technology approach to identify some key genes and main pathways related to resistance.

RESULTS

The gene expression levels of the two sesame varieties were significantly different at 0, 6, 12, 24, 36 and 48 hpi, indicating that the up-regulation of differentially expressed genes in the R might enhanced the resistance. Moreover, combined with the phenotypic observations of sesame leaves inoculated at different time points, we found that 12 hpi was the key time point leading to the resistance difference between the two sesame varieties at the molecular level. The WGCNA identified two modules significantly associated with disease resistance, and screened out 10 key genes that were highly expressed in R but low expressed in S, which belonged to transcription factors (WRKY, AP2/ERF-ERF, and NAC types) and protein kinases (RLK-Pelle_DLSV, RLK-Pelle_SD-2b, and RLK-Pelle_WAK types). These genes could be the key response factors in the response of sesame to infection by Corynespora cassiicola. GO and KEGG enrichment analysis showed that specific modules could be enriched, which manifested as enrichment in biologically important pathways, such as plant signalling hormone transduction, plant-pathogen interaction, carbon metabolism, phenylpropanoid biosynthesis, glutathione metabolism, MAPK and other stress-related pathways.

CONCLUSIONS

This study provides an important resource of genes contributing to disease resistance and will deepen our understanding of the regulation of disease resistance, paving the way for further molecular breeding of sesame.

Genetic variation in a tepary bean (Phaseolus acutifolius A. Gray) diversity panel reveals loci associated with biotic stress resistance

Tepary bean (Phaseolus acutifolius A. Gray), indigenous to the arid climates of northern Mexico and the Southwest United States, diverged from common bean (Phaseolus vulgaris L.), approximately 2 million years ago and exhibits a wide range of resistance to biotic stressors. The tepary genome is highly syntenic to the common bean genome providing a foundation for discovery and breeding of agronomic traits between these two crop species. Although a limited number of adaptive traits from tepary bean have been introgressed into common bean, hybridization barriers between these two species required the development of bridging lines to alleviate this barrier. Thus, to fully utilize the extant tepary bean germplasm as both a crop and as a donor of adaptive traits, we developed a diversity panel of 422 cultivated, weedy, and wild tepary bean accessions which were then genotyped and phenotyped to enable population genetic analyses and genome-wide association studies for their response to a range of biotic stressors. Population structure analyses of the panel revealed eight subpopulations and the differentiation of botanical varieties within P. acutifolius. Genome-wide association studies revealed loci and candidate genes underlying biotic stress resistance including quantitative trait loci for resistance to weevils, common bacterial blight, Fusarium wilt, and bean common mosaic necrosis virus that can be harnessed not only for tepary bean but also common bean improvement.

Identification of Candidate Genes for a Major Quantitative Disease Resistance Locus From Soybean PI 427105B for Resistance to Phytophthora sojae

Phytophthora root and stem rot is a yield-limiting soybean disease caused by the soil-borne oomycete Phytophthora sojae. Although multiple quantitative disease resistance loci (QDRL) have been identified, most explain <10% of the phenotypic variation (PV). The major QDRL explaining up to 45% of the PV were previously identified on chromosome 18 and represent a valuable source of resistance for soybean breeding programs. Resistance alleles from plant introductions 427105B and 427106 significantly increase yield in disease-prone fields and result in no significant yield difference in fields with less to no disease pressure. In this study, high-resolution mapping reduced the QDRL interval to 3.1 cm, and RNA-seq analysis of near-isogenic lines (NILs) varying at QDRL-18 pinpointed a single gene of interest which was downregulated in inoculated NILs carrying the resistant allele compared to inoculated NILs with the susceptible allele. This gene of interest putatively encodes a serine-threonine kinase (STK) related to the AtCR4 family and may be acting as a susceptibility factor, based on the specific increase of jasmonic acid concentration in inoculated NILs. This work facilitates further functional analyses and marker-assisted breeding efforts by prioritizing candidate genes and narrowing the targeted region for introgression.

Revealing Genetic Differences in Fiber Elongation between the Offspring of Sea Island Cotton and Upland Cotton Backcross Populations Based on Transcriptome and Weighted Gene Coexpression Networks

Fiber length is an important indicator of cotton fiber quality, and the time and rate of cotton fiber cell elongation are key factors in determining the fiber length of mature cotton. To gain insight into the differences in fiber elongation mechanisms in the offspring of backcross populations of Sea Island cotton Xinhai 16 and land cotton Line 9, we selected two groups with significant differences in fiber length (long-fiber group L and short-fiber group S) at different fiber development stages 0, 5, 10 and 15 days post-anthesis (DPA) for transcriptome comparison. A total of 171.74 Gb of clean data was obtained by RNA-seq, and eight genes were randomly selected for qPCR validation. Data analysis identified 6055 differentially expressed genes (DEGs) between two groups of fibers, L and S, in four developmental periods, and gene ontology (GO) term analysis revealed that these DEGs were associated mainly with microtubule driving, reactive oxygen species, plant cell wall biosynthesis, and glycosyl compound hydrolase activity. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis indicated that plant hormone signaling, mitogen-activated protein kinase (MAPK) signaling, and starch and sucrose metabolism pathways were associated with fiber elongation. Subsequently, a sustained upregulation expression pattern, profile 19, was identified and analyzed using short time-series expression miner (STEM). An analysis of the weighted gene coexpression network module uncovered 21 genes closely related to fiber development, mainly involved in functions such as cell wall relaxation, microtubule formation, and cytoskeletal structure of the cell wall. This study helps to enhance the understanding of the Sea Island–Upland backcross population and identifies key genes for cotton fiber development, and these findings will provide a basis for future research on the molecular mechanisms of fiber length formation in cotton populations.