Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Catharanthus Transcriptome and Gene Expression

ABSTRACT: In this study, we aim to present a global transcriptome analysis of medicinal plant, Catharanthus roseus. We generated about 343 million high-quality reads from three tissues (leaf, root and flower) using Illumina platform. We performed an optimized de novo assembly of the reads and estimated transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses among tissue samples. We collected different tissue samples from the mature plants. Total RNA isolated from these tissue samples was subjected to Illumina sequencing. The sequence data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were used for de novo assembly optimization. The reads were further mapped to the Catharanthus transcripts via CLC Genomics Workbench and differential gene expression analysis was performed using DESeq software.

ORGANISM(S): Catharanthus roseus

SUBMITTER: Mukesh Jain

PROVIDER: E-GEOD-57326 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Transcriptome analysis of Catharanthus roseus for gene discovery and expression profiling.

Verma Mohit M Ghangal Rajesh R Sharma Raghvendra R Sinha Alok K AK Jain Mukesh M

PloS one 20140729 7

The medicinal plant, Catharanthus roseus, accumulates wide range of terpenoid indole alkaloids, which are well documented therapeutic agents. In this study, deep transcriptome sequencing of C. roseus was carried out to identify the pathways and enzymes (genes) involved in biosynthesis of these compounds. About 343 million reads were generated from different tissues (leaf, flower and root) of C. roseus using Illumina platform. Optimization of de novo assembly involving a two-step process resulted ...[more]

PMID: 25072156

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Project description:We used next generation sequencing to examine global changes in gene expression in the spleen and splenic macrophages in a hamster model of progressive visceral leishmaniasis. We used RNA sequencing coupled with de novo transcriptome assembly, because the Syrian hamster does not have a fully sequenced and annotated reference genome. Libraries for deep sequencing were constructed from poly-A RNA isolated from the spleens or splenic macrophages of uninfected and 28-day L. donovani-infected hamsters (n=4 per group) using standard Illumina protocols. The library quality was confirmed by Agilent Bioanalyzer. Paired-end 50-base sequencing was performed using TruSeq SBS kit v3 (Illumina) on an Illumina HiSeq 1000.The quality of raw sequencing reads was checked using FastQC (v0.10.1). To avoid the contamination of pathogen sequences, we filtered out reads (using the FASTX Toolkit v0.0.13) that aligned to the Leishmania donovani BPK282A1 genome (NCBI BioProject PRJEA61817) using Bowtie 2 (v2.0.0-beta5) under default options. To reduce the effect of low quality reads, we further filtered out artifacts and reads having a phred score <28 in more than 10% of nucleotides using FASTX Toolkit (v0.0.13). Both forward and reverse reads were removed if any of them failed to pass the filters. To obtain a complete transcriptome, we used two steps. First, the cleaned sequencing reads from different spleen samples were pooled together and de novo assembled using Trinity software. Second, the resulting transcriptome was combined with all cleaned reads from hamster spleen and splenic macrophages and the CHO-K1 RefSeq genome to perform a second de novo assembly using BRANCH. We first created a customized reference library using Rattus norvegicus (Rnor_5.0.73) and Mus musculus (GRCm38.73) genomes. We then used BLAST (v 2.2.28+) to align each transcript generated from BRANCH against the customized library to assign it a gene name based upon sequence similarity. An E-value cutoff of <1e-3 was used. Additionally, we compared the Trinity transcripts with the CHO-K1 Ref Seq genome. All the non-Leishmania-like raw sequencing reads were first mapped to our de novo reference genome using Bowtie2 (v2.1.0) with default options, but allowing one read to map to as many as 500 different transcripts. We then measured the expression abundance, count of reads mapped to each transcript, using the software eXpress. To identify differentially expressed transcripts in each experiment, 3 different approaches were applied: exact tests of Robinson and Smyth and generalized linear models with the likelihood ratio test using the BioConductor R package EdgeR, and the Wald test using DESeq2. Only transcripts with at least 1 count per million in at least 3 out of 4 samples in the control or experimental group were included in the analysis. A transcript was considered differentially expressed only when it was identified by all three different approaches. Analysis of differentially expressed transcripts identified a highly inflammatory spleen environment with abundant expression of type I and type II interferon response genes. However, high IFN-γ expression was ineffective in directing exclusive M1 macrophage polarization, suppressing M2-associated gene expression, and restraining parasite replication and disease. While many IFN-inducible transcripts were upregulated in the infected spleen, fewer were induced in splenic macrophages in VL suggesting suppression of macrophage responsiveness to activating cytokines. The transcription factor STAT3 was predicted and confirmed to be activated, and found to orchestrate an exuberant counter-regulatory response that favors parasite replication.

Dataset Information

Catharanthus Transcriptome and Gene Expression

Publications

Transcriptome analysis of Catharanthus roseus for gene discovery and expression profiling.

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