Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type Vibrio harveyi 345 and hfq mutant 345∆hfq Transcriptomes
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ABSTRACT:
PROVIDER: PRJNA802111 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR17832033_1.fastq.gz | Fastqsanger.gz | |||
| SRR17832033_2.fastq.gz | Fastqsanger.gz | |||
| SRR17832034_1.fastq.gz | Fastqsanger.gz | |||
| SRR17832034_2.fastq.gz | Fastqsanger.gz |
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Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare the gene (including sRNA) expression of the Wild Type Vibrio harveyi 345 and hfq mutant 345∆hfq, thus to figure out the effect of hfq on the gene expression of V. harveyi Methods:The mid-log bacterial cells (OD600 = 3.5) of wild type strain V. harveyi 345 and the hfq mutant strain 345∆hfq were collected to extract the total RNA. TruSeqTM RNA sample preparation Kit (Illumina, San Diego, CA)) was used to prepare RNA-seq transcriptome library using 2μg of total RNA. The Illumina HiSeq×TEN was performed to sequence the paired-end RNA-seq sequencing library (2 × 150bp read length). A Perl program was written to remove low-quality sequences, reads with more than 5% of N bases (unknown bases) and reads containing adaptor sequences, obtaining clean reads. The high quality reads in each sample were mapped to the referent V. harveyi (PRJNA418027) genome by Bowtie2 (Langmead and Salzberg, 2012). Transcript per million (TPM) mapped reads was calculated by RSEM (Dewey and Li, 2011) to assessment the gene expression. The different expressed genes (DEGs) were identified by using the edgeR, DESeq2, or DESeq packages (Anders, 2010; Love et al., 2014; Smyth, 2020). The cluster Profiler software KOBAS 2.0 (Chen et al., 2011) was used to perform KEGG pathway enrichment analysis of DGEs. The adjusted P-value (padj) ≤ 0.05 was the threshold for significant enrichment.The software Rockhopper (Ryan et al., 2013) was used to predict sRNAs basing on base sequencing coverage. Then the sRNAs were annotated by Blast, sRNAMap, sRNATarBase, SIPHT, and Rfam (Hsi-Yuan et al., 2008; Cao et al., 2010). RNAfold (Denman, 1993) was performed to predicted sRNAs second structure. RNAphybrid and RNAplex were used to predicted sRNAs targets (Jan and Marc, 2006; Tafer and Hofacker, 2008). Results: There were total 883 genes significantly differential expressed in 345Δhfq compared with the wild type strain V. harveyi 345, accounting for 16.39% of the total genes on V. harveyi 345 with 538 were up-regulated and 345 were down-regulated. The up-regulated genes were enriched mainly in the pathways those involved into metabolism, including biosynthesis of siderophore group nonribosomal peptides, phosphotransferase system (PTS), starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, fructose and mannose metabolism, naphthalene degradation, chloroalkane and chloroalkene degradation, ascorbate and aldarate metabolism, fatty acid degradation, retinol metabolism, and histidine metabolism. The down-regulated genes were mainly enriched in shigellosis (fliC), NOD-like receptor signaling pathway (fliC), Salmonella infection (gapA, fliC), legionellosis (fliC), plant-pathogen interaction (fliC), apoptosis, flagellar assembly (flgI, fliD, fliS, motY, and fliC), bacterial chemotaxis (malE, cheV, cheW, and mcp), and microRNAs in cancer (dcm) which were involved into bacterial virulence. In addition, a total of 434 sRNAs were obtained in the transcriptome data, and 11 sRNAs were significantly down-regulated (padjust>0.05, fold change >8, and at least one the strains Transcripts Per Million reads tpm >50) without hfq. The RNAfold indicated that all the sRNAs were stem-loop structures. Conclusions: Our study represents the first detailed analysis of the effect of hfq on gene expression of Vibrio harveyi by RNA-seq technology. We conclude that Hfq played variable roles in bacterial metabolism, cell mobility, bacterial chemotaxis, biofilm formation, and secretion which are associated with bacterial virulence.
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Project description:Objectives: determination of transcription start sites in Vibrio harveyi genome and discovery of new transcripts Methods: we performed differential seqencing of total RNA isolated from o.n. control Vibrio harveyi cultures. Sample treatment with Terminator EXonuclease (TEX) allowed differenciation of primary and secondary transcripts, helping in the definition of transcription start sites (TSS) Results: by data-mining RNA-seq data and performing some Northern Blot experiments we were able to detect new putative small-RNAs, along with these results, a more deep analisys of our RNA-seq data will give futher insight into genetic organization of Vibrio harveyi genome to help in its investigation
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Project description:Increasing evidence points to an important functional or regulatory role of long noncoding RNA in cellular processes as well as some cancer diseases result from the aberrant lncRNA expression. LncRNA could participate in the cancer progross and develop a significant role through the interaction with proteins. In the present study, we report a lncRNA termed uc.345 that is up-regulated in tumor tissues, compared to the corresponding noncancerous tissues. We found that a higher uc.345 expression lever was significantly more frequent in tissues with increased depth of invasion and advanced TNM tumor node metastasis T stage. Moreover, uc.345 serves as an independent risk factor for pancreatic cancer patients’ overall survival (OS). Through soft agar assay and tumor xenograft model, our results indicate that uc.345 could stimulate tumor growth in vitro and in vivo. We also found the uc.345 could upregulate the hnRNPL protein level, furthermore, we demonstrate that the inhibition of (hnRNPL) by its association with uc.345 contributes to depress tumorgenesis in vitro. Collectively, these results demonstrate that uc.345 functions as an oncogenic lncRNA that promotes tumor progression and serves as a poor predictor for pancreatic cancer patients' overall survival.
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