Transcriptome and metabolome response of eggplant against <i>Ralstonia solanacearum</i> infection

Xiao, Xi; Lin, Wenqiu; Feng, Enyou; Ou, Xiong-chang

doi:10.7717/peerj.14658

Cited by 11 publications

(7 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The bacterial wilt resistance inbreed line NY cross between KY (highly susceptibility to bacterial wilt) [30] in the spring of 2021. The F 2 plants were generated in the fall of 2021.…”

Section: Development Of Mapping Populationmentioning

confidence: 99%

See 1 more Smart Citation

QTL Mapping for Bacterial Wilt Resistance in Eggplant via Bulked Segregant Analysis Using Genotyping by Sequencing

Xiao,

Lin,

Nie

et al. 2024

Agronomy

Self Cite

View full text Add to dashboard Cite

The bacterial wilt disease caused by Ralstonia solanacearum is a significant threat to eggplant production. Breeding and promoting resistant varieties is one of the most effective methods to manage bacterial wilt. Conducting QTL (quantitative trait locus) mapping of resistant genes can substantially enhance the breeding of plant resistance to bacterial wilt. In this study, a population of 2200 F2 individuals derived from resistant and susceptible materials was utilized to establish extreme resistance and susceptibility pools. Following resequencing analysis of the parents and extreme pools, the QTL were examined using the DEEP-BSA software and QTLseqr R package (version 0.7.5.2). The results revealed that the detection of 10 QTL sites on chromosomes 5, 8, 9, and 11 by the five algorithms of the DEEP-BSA software. Additionally, the candidate region of 62 Mb–72 Mb on chromosome 5 was identified in all five algorithms of the DEEP-BSA software, as well as by the QTLseqr R package. Subsequent gene annotation uncovered 276 genes in the candidate region of 62 Mb–72 Mb on chromosome 5. Additionally, RNA-seq results indicated that only 13 genes had altered expression levels following inoculation with R. solanacearum in the resistant materials. Based on the expression levels, SMEL4_05g015980.1 and SMEL4_05g016110.1 were identified as candidate genes. Notably, SNP annotation identified a non-synonymous mutation in the exonic region of SMEL4_05g015980.1 and a variant in the promoter region of SMEL4_05g016110.1. The research findings have practical significance for the isolation of bacterial wilt resistance genes in eggplant and the development of resistance to bacterial wilt varieties in eggplant.

show abstract

“…The bacterial wilt resistance inbreed line NY cross between KY (highly susceptibility to bacterial wilt) [30] in the spring of 2021. The F 2 plants were generated in the fall of 2021.…”

Section: Development Of Mapping Populationmentioning

confidence: 99%

“…The RNA-seq data utilized in this study was obtained from our previous experiment focusing on the transcriptome and metabolome response of eggplant to R. solanacearum infection [30]. During the RNA-seq data, we referenced V3 reference genome [34].…”

Section: Combined Analysis Of Bsa-seq and Rna-seq For Screening Candi...mentioning

confidence: 99%

QTL Mapping for Bacterial Wilt Resistance in Eggplant via Bulked Segregant Analysis Using Genotyping by Sequencing

Xiao,

Lin,

Nie

et al. 2024

Agronomy

Self Cite

View full text Add to dashboard Cite

show abstract

“…Research on the molecular and genetic framework of resistance to R. solanacearum has largely utilized Arabidopsis thaliana and Medicago truncatula model plants (Chen et al., 2019; Kover & Schaal, 2002; Roux et al., 2010; Vailleau et al., 2007), tomato (Prior et al., 1999; Yuliar et al., 2015), eggplant (Lebeau et al., 2013; Liu et al., 2016; Xiao et al., 2023), tobacco (Pan et al., 2021; Qian et al., 2013) and potato (Puigvert et al., 2017; Zuluaga et al., 2015). Various domesticated potato species, including S. phureja and closely associated wild species like S. chacoense , have been found to possess genetic resistance to bacterial wilt (Carputo et al., 2009; Habe et al., 2019; Liu et al., 2016; Puigvert et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

Transcriptional alterations of the resistant potato genotype ‘Cruza 148’ in response to Ralstonia solanacearum infection

Okiro,

Mulwa,

Oyoo

et al. 2024

Journal of Phytopathology

View full text Add to dashboard Cite

Ralstonia solanacearum, a highly destructive phytopathogen causing bacterial wilt disease, poses a substantial risk to the potato value chain, putting global food security at risk and impeding potato production. ‘Cruza 148’, a locally adapted potato genotype, has been reported to exhibit resistance when cultivated in areas with a background of bacterial wilt occurrences. This study aimed to acquire a deeper understanding of the factors influencing resistance and susceptibility in ‘Cruza 148’ and ‘Shangi’ potato genotypes respectively. To achieve this, RNA‐seq was deployed to detect DEGs in ‘Cruza 148’ and ‘Shangi’ potato genotypes at 6 h, 24 h, 48 h, and 72 h post‐inoculation with Ralstonia solanacearum. A total of 54.2% of the DEGs were upregulated and 45.8% were downregulated in the roots of the ‘Cruza 148’ potato genotype, while 45.5% and 54.5% of DEGs were upregulated and downregulated in the roots of the susceptible potato genotype ‘Shangi’ respectively. The gene ontology (GO) enrichment analysis indicated that the ‘Cruza 148’ genotype consistently displayed the ‘defence response’ category throughout every stage of infection. The analysis of enriched GO terms revealed 225 terms, with 132 related to biological processes, 16 linked to cellular components and 12 linked to molecular functions. The ‘Cruza 148’ genotype had the highest gene counts in peptide metabolic processes and cellular component assembly, while the ‘Shangi’ genotype had the greatest number of gene counts that responded to chemicals and cellular component assembly. Defence genes identified, included leucine‐rich repeat protein, MYB transcription factor, glucan endo‐1,3‐beta‐glucosidase, serine/threonine‐protein kinase, ethylene‐responsive transcriptional coactivator and disease resistance protein, which could help explain the mechanisms and pathways of resistance to R. solanacearum. This study presents a fundamental understanding of the transcriptional alterations that occur during pathogen interactions with potato. It will also assist in identifying potential useful genes induced during the resistance and susceptibility processes.

show abstract

“…With regard to tobacco, different studies using different materials and methods have identified the involvement of the same pathway in BW resistance, namely the phenylpropane pathway [27][28][29], but also different pathways, including glutathione metabolism [28] and hormone-related pathways [29]. Phytohormones play a critical role in eggplant (Solanum melongena) resistance to BW as indicated by transcriptome and metabolome analyses [30]. Dual RNA-seq has revealed that inhibition of ethylene synthesis, promotion of photosynthesis, up-regulation of polysaccharide metabolism, and strengthening of cell wall defense can prevent the invasion of R. solanacearum in pepper [31].…”

Section: Introductionmentioning

confidence: 99%

Transcriptome sequencing and expression analysis in peanut reveal the potential mechanism response to Ralstonia solanacearum infection

Wang,

Qi,

Sun

et al. 2024

BMC Plant Biol

View full text Add to dashboard Cite

Background Bacterial wilt caused by Ralstonia solanacearum severely affects peanut (Arachis hypogaea L.) yields. The breeding of resistant cultivars is an efficient means of controlling plant diseases. Therefore, identification of resistance genes effective against bacterial wilt is a matter of urgency. The lack of a reference genome for a resistant genotype severely hinders the process of identification of resistance genes in peanut. In addition, limited information is available on disease resistance-related pathways in peanut. Results Full-length transcriptome data were used to generate wilt-resistant and -susceptible transcript pools. In total, 253,869 transcripts were retained to form a reference transcriptome for RNA-sequencing data analysis. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of differentially expressed genes revealed the plant-pathogen interaction pathway to be the main resistance-related pathway for peanut to prevent bacterial invasion and calcium plays an important role in this pathway. Glutathione metabolism was enriched in wilt-susceptible genotypes, which would promote glutathione synthesis in the early stages of pathogen invasion. Based on our previous quantitative trait locus (QTL) mapping results, the genes arahy.V6I7WA and arahy.MXY2PU, which encode nucleotide-binding site-leucine-rich repeat receptor proteins, were indicated to be associated with resistance to bacterial wilt. Conclusions This study identified several pathways associated with resistance to bacterial wilt and identified candidate genes for bacterial wilt resistance in a major QTL region. These findings lay a foundation for investigation of the mechanism of resistance to bacterial wilt in peanut.

show abstract

Transcriptome and metabolome response of eggplant against Ralstonia solanacearum infection

Cited by 11 publications

References 53 publications

QTL Mapping for Bacterial Wilt Resistance in Eggplant via Bulked Segregant Analysis Using Genotyping by Sequencing

QTL Mapping for Bacterial Wilt Resistance in Eggplant via Bulked Segregant Analysis Using Genotyping by Sequencing

Transcriptional alterations of the resistant potato genotype ‘Cruza 148’ in response to Ralstonia solanacearum infection

Transcriptome sequencing and expression analysis in peanut reveal the potential mechanism response to Ralstonia solanacearum infection

Contact Info

Product

Resources

About