Dataset Information

Transcriptome profiling of Cucumis metuliferus infected by Meloidogyne incognita provides new insights into putative defense regulatory network in Cucurbitaceae.

ABSTRACT: Root-knot nematodes (RKN) represent extensive challenges to Cucurbitaceae crops. However, Cucumis metuliferus (Cm) is known to be resistant to Meloidogyne incognita (Mi) infections. Thus, analysis of differentially expressed genes may lead to a comprehensive gene expression profiling of the incompatible Cm-Mi interaction. In this study, the time-course transcriptome of Cm against Mi infection was monitored using RNA-Seq. More than 170000 transcripts were examined in Cm roots, and 2430 genes were subsequently identified as differentially expressed in response to Mi infection. Based on function annotation and orthologs finding, the potential mechanism of transcriptional factor, cytoskeleton, pathogen-related genes and plant hormone were assessed at the transcription level. A comparison of gene expression levels between Mi-infected Cm and cucumber plants revealed that cytoskeleton-related genes are key regulators of Cm resistance to Mi. We herein discuss the dual nature of cytoskeleton-related genes in the susceptibility and resistance of plant hosts to Mi. Our observations provide novel insights into the responses of Cm to Mi at the transcriptome level. The data generated in this study may be useful for elucidating the mechanism underlying resistance to RKNs in cucurbitaceous crops.

SUBMITTER: Ling J

PROVIDER: S-EPMC5471208 | biostudies-other | 2017 Jun

REPOSITORIES: biostudies-other

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Transcriptome profiling of Cucumis metuliferus infected by Meloidogyne incognita provides new insights into putative defense regulatory network in Cucurbitaceae.

Ling Jian J Mao Zhenchuan Z Zhai Mingjuan M Zeng Feng F Yang Yuhong Y Xie Bingyan B

Scientific reports 20170614 1

Root-knot nematodes (RKN) represent extensive challenges to Cucurbitaceae crops. However, Cucumis metuliferus (Cm) is known to be resistant to Meloidogyne incognita (Mi) infections. Thus, analysis of differentially expressed genes may lead to a comprehensive gene expression profiling of the incompatible Cm-Mi interaction. In this study, the time-course transcriptome of Cm against Mi infection was monitored using RNA-Seq. More than 170000 transcripts were examined in Cm roots, and 2430 genes were ...[more]

PMID: 28615634

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Project description:BackgroundGene regulatory networks (GRNs) are models of molecule-gene interactions instrumental in the coordination of gene expression. Transcription factor (TF)-GRNs are an important subset of GRNs that characterize gene expression as the effect of TFs acting on their target genes. Although such networks can qualitatively summarize TF-gene interactions, it is highly desirable to quantitatively determine the strengths of the interactions in a TF-GRN as well as the magnitudes of TF activities. To our knowledge, such analysis is rare in plant biology. A computational methodology developed for this purpose is network component analysis (NCA), which has been used for studying large-scale microbial TF-GRNs to obtain nontrivial, mechanistic insights. In this work, we employed NCA to quantitatively analyze a plant TF-GRN important in floral development using available regulatory information from AGRIS, by processing previously reported gene expression data from four shoot apical meristem cell types.ResultsThe NCA model satisfactorily accounted for gene expression measurements in a TF-GRN of seven TFs (LFY, AG, SEPALLATA3 [SEP3], AP2, AGL15, HY5 and AP3/PI) and 55 genes. NCA found strong interactions between certain TF-gene pairs including LFY???MYB17, AG???CRC, AP2???RD20, AGL15???RAV2 and HY5???HLH1, and the direction of the interaction (activation or repression) for some AGL15 targets for which this information was not previously available. The activity trends of four TFs?-?LFY, AG, HY5 and AP3/PI as deduced by NCA correlated well with the changes in expression levels of the genes encoding these TFs across all four cell types; such a correlation was not observed for SEP3, AP2 and AGL15.ConclusionsFor the first time, we have reported the use of NCA to quantitatively analyze a plant TF-GRN important in floral development for obtaining nontrivial information about connectivity strengths between TFs and their target genes as well as TF activity. However, since NCA relies on documented connectivity information about the underlying TF-GRN, it is currently limited in its application to larger plant networks because of the lack of documented connectivities. In the future, the identification of interactions between plant TFs and their target genes on a genome scale would allow the use of NCA to provide quantitative regulatory information about plant TF-GRNs, leading to improved insights on cellular regulatory programs.

Project description:Background: Chickpea (Cicer arietinum L.) contributes 75% of total pulse production. Being cheaper than animal protein, makes it important in dietary requirement of developing countries. Weed not only competes with chickpea resulting into drastic yield reduction but also creates problem of harboring fungi, bacterial diseases and insect pests. Chemical approach having new herbicide discovery has constraint of limited lead molecule options, statutory regulations and environmental clearance. Through genetic approach, transgenic herbicide tolerant crop has given successful result but led to serious concern over ecological safety thus non-transgenic approach like marker assisted selection is desirable. Since large variability in tolerance limit of herbicide already exists in chickpea varieties, thus the genes offering herbicide tolerance can be introgressed in variety improvement programme. Transcriptome studies can discover such associated key genes with herbicide tolerance in chickpea. Results: This is first transcriptomic studies of chickpea or even any legume crop using two herbicide susceptible and tolerant genotypes exposed to imidazoline (Imazethapyr). Approximately 90 million paired-end reads generated from four samples were processed and assembled into 30,803 contigs using reference based assembly. We report 6,310 differentially expressed genes (DEGs), of which 3,037 were regulated by 980 miRNAs, 1,528 transcription factors associated with 897 DEGs, 47 Hub proteins, 3,540 putative Simple Sequence Repeat-Functional Domain Marker (SSR-FDM), 13,778 genic Single Nucleotide Polymorphism (SNP) putative markers and 1,174 Indels. Randomly selected 20 DEGs were validated using qPCR. Pathway analysis suggested that xenobiotic degradation related gene, glutathione S-transferase (GST) were only up-regulated in presence of herbicide. Down-regulation of DNA replication genes and up-regulation of abscisic acid pathway genes were observed. Study further reveals the role of cytochrome P450, xyloglucan endotransglucosylase/hydrolase, glutamate dehydrogenase, methyl crotonoyl carboxylase and of thaumatin-like genes in herbicide resistance. Conclusion: Reported DEGs can be used as genomic resource for future discovery of candidate genes associated with herbicide tolerance. Reported markers can be used for future association studies in order to develop marker assisted selection (MAS) for refinement. In endeavor of chickpea variety development programme, these findings can be of immense use in improving productivity of chickpea germplasm.

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Dataset Information

Transcriptome profiling of Cucumis metuliferus infected by Meloidogyne incognita provides new insights into putative defense regulatory network in Cucurbitaceae.

Publications

Transcriptome profiling of Cucumis metuliferus infected by Meloidogyne incognita provides new insights into putative defense regulatory network in Cucurbitaceae.

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