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Sample GSM1005459

Query DataSets for GSM1005459

Status

Public on Sep 18, 2013

Title

whiB6Tn rep3

Sample type

SRA

Source name

whiB6Tn

Organism

Mycobacterium tuberculosis CDC1551

Characteristics

genotype: whiB6 disrupted by transposon
strain: CDC1551

Treatment protocol

The two strains were synchronized by adjusting the OD600 to 0.1 in antibiotic-free 7H9 and grown for three days. This was repeated two more times to make sure the two strains were in the same growth phase. WT and whiB6Tn were grown shaking in E-flasks in biological triplicates and harvested three days later at an OD of 1 in the WT cultures and 0.9 in the whiB6Tn cultures.

Growth protocol

Bacteria were grown in 7H9 broth (Becton Dickinson, Sparks, MD) supplemented with 10% OADC (oleic acid, albumin, dextrose, and catalase) (Becton Dickinson, Sparks, MD), 0.5% v/v glycerol and 0.05% v/v Tween 80 (Sigma Aldrich, St. Louis, MO) at 37°C with agitation.

Extracted molecule

total RNA

Extraction protocol

RNA from synchronized cultures in triplicate was extracted using a Trizol - spin column hybrid protocol followed by DNase treatment. RNA integrity was tested using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA), and mRNA was enriched using the MICROBExpress kit according to the manufacturer's instructions (Life technologies, Grand Island, NY). Successful removal of rRNA was verified by another Bioanalyzer assay.
Starting with 200-500ng of rRNA-depleted total RNA, fragmentation of the whole transcriptome RNA was performed by chemically induced method as described in Applied Biosystems SOLiD™ Total RNA-Seq Kit protocol (Applied Biosystems, Carlsbad, CA). Fragmented RNA was purified using the Invitrogen RiboMinus Concentration Module (Life technologies, Grand Island, NY) and the size distribution and yield were assessed by Bioanalyzer using the RNA 6000 pico Chip Kit (Agilent technologies, Santa Clara, CA) and Qubit Fluorometer (Life technologies, Grand Island, NY) respectively. Once concentration was confirmed, construction of the amplified whole transcriptome library was performed as directed in the Applied Biosystems SOLiD™ Total RNA-Seq Kit protocol, which is intrinsically strand-specific.
After reverse transcription was complete, each sample was barcoded with a unique 3’primer during the library amplification step.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

AB 5500xl Genetic Analyzer

Data processing

Libraries were run on DNA1000 chip using the Agilent Bioanalyzer to assess size distribution and quality of the amplified library. Quantification of each library was performed by qPCR and equimolar concentrations of each library were pooled together to proceed with emulsion PCR and sequenced on the AB 5500xl SOLiD sequencer (Applied Biosystems, Carlsbad, CA).
Reads were aligned to CDC1551 using the Bioscope 1.3 Whole Transcriptome Analysis Pipeline using default settings (Applied Biosystems, Carlsbad, CA). CDC1551 transcript annotations were downloaded from TBDB.org (Reddy, Riley et al. 2009). The number of reads mapped to each transcript was calculated using HTSeq-count v0.5.3. The overlap resolution mode was set to “intersection-nonempty” and feature type was set to “exon”. (http://www.huber.embl.de/users/anders/HTSeq/doc/install.html#download) Differential expression between the WT and whiB6Tn sample groups was determined using DESeq v1.4.1 (http://genomebiology.com/2010/11/10/R106), using a test based on the negative binomial distribution, modeling both biological and technical variation. p-values are adjusted for multiple comparisons using the Benjamini - Hochberg method. Transcripts with adjusted p values less than 0.05 were considered significant. Gene Ontology (GO) terms were downloaded from BioMart (Ensembl Bacteria release 13, http://bacteria.ensembl.org/) and enrichment of GO terms in differentially expressed genes was tested with topGO v2.6 (http://bioinformatics.oxfordjournals.org/content/22/13/1600.long). The list of p values generated from DESeq was loaded into topGO along with the list of gene ontology (GO) terms associated with each transcript. The Kolmogorov-Smirnov (KS) test was used to identify GO term enrichment and the weight01 algorithm was used to handle GO graph structure. GO terms with fewer than five genes have low confidence and high variability and thus were not used in the analysis. Reads were aligned to CDC1551 using the Bioscope 1.3 Whole Transcriptome Analysis Pipeline using default settings (Applied Biosystems, Carlsbad, CA). CDC1551 transcript annotations were downloaded from TBDB.org (Reddy, Riley et al. 2009). The number of reads mapped to each transcript was calculated using HTSeq-count v0.5.3. The overlap resolution mode was set to “intersection-nonempty” and feature type was set to “exon”. (http://www.huber.embl.de/users/anders/HTSeq/doc/install.html#download) Differential expression between the WT and whiB6Tn sample groups was determined using DESeq v1.4.1 (http://genomebiology.com/2010/11/10/R106), using a test based on the negative binomial distribution, modeling both biological and technical variation. p-values are adjusted for multiple comparisons using the Benjamini - Hochberg method. Transcripts with adjusted p values less than 0.05 were considered significant. Gene Ontology (GO) terms were downloaded from BioMart (Ensembl Bacteria release 13, http://bacteria.ensembl.org/) and enrichment of GO terms in differentially expressed genes was tested with topGO v2.6 (http://bioinformatics.oxfordjournals.org/content/22/13/1600.long). The list of p values generated from DESeq was loaded into topGO along with the list of gene ontology (GO) terms associated with each transcript. The Kolmogorov-Smirnov (KS) test was used to identify GO term enrichment and the weight01 algorithm was used to handle GO graph structure. GO terms with fewer than five genes have low confidence and high variability and thus were not used in the analysis. Reads were aligned to CDC1551 using the Bioscope 1.3 Whole Transcriptome Analysis Pipeline using default settings (Applied Biosystems, Carlsbad, CA). CDC1551 transcript annotations were downloaded from TBDB.org (Reddy, Riley et al. 2009). The number of reads mapped to each transcript was calculated using HTSeq-count v0.5.3. The overlap resolution mode was set to “intersection-nonempty” and feature type was set to “exon”. (http://www.huber.embl.de/users/anders/HTSeq/doc/install.html#download) Differential expression between the WT and whiB6Tn sample groups was determined using DESeq v1.4.1 (http://genomebiology.com/2010/11/10/R106), using a test based on the negative binomial distribution, modeling both biological and technical variation. p-values are adjusted for multiple comparisons using the Benjamini - Hochberg method. Transcripts with adjusted p values less than 0.05 were considered significant. Gene Ontology (GO) terms were downloaded from BioMart (Ensembl Bacteria release 13, http://bacteria.ensembl.org/) and enrichment of GO terms in differentially expressed genes was tested with topGO v2.6 (http://bioinformatics.oxfordjournals.org/content/22/13/1600.long). The list of p values generated from DESeq was loaded into topGO along with the list of gene ontology (GO) terms associated with each transcript. The Kolmogorov-Smirnov (KS) test was used to identify GO term enrichment and the weight01 algorithm was used to handle GO graph structure. GO terms with fewer than five genes have low confidence and high variability and thus were not used in the analysis.
The number of reads mapped to each transcript was calculated using HTSeq-count v0.5.3.
Genome_build: M. tuberculosis CDC1551
Supplementary_files_format_and_content: tab-delimited text file with one column for each sample

Submission date

Sep 18, 2012

Last update date

May 15, 2019

Contact name

Christer Larsson

E-mail(s)

christer.larsson@molbiol.umu.se

Phone

+46 90 7850811

Organization name

Umeå universitet