GEN220_2019

RNAseq and comparisons

Reanalyze data in this published paper Baker et al 2014 “Slow growth of Mycobacterium tuberculosis at acidic pH is regulated by phoPR and host‐associated carbon sources”

Data are downloaded to /bigdata/gen220/shared/data/M_tuberculosis

The Transcriptome file is also in the folder as M_tuberculosis.cds.fasta - I have renamed the sequences to be the LOCUS names. It was downloaded from https://www.ncbi.nlm.nih.gov/assembly/GCF_000008585.1/ and the specific file is linked here

There is a sra_info.tab file which lists the sample accessions and their metadata so you can see what are the data sets. This is from the BioProject PRJNA226557 and the SRA Project SRP032513

Compare gene expression between two sets of conditions.

• pH5.7
• pH7

And growth carbon source

• Glycerol
• Pyruvate

1. Run Kallisto to get the gene expression calculated from each sample - you will need the file M_tuberculosis.cds.fasta as the database and each of the 8 .fastq.gz files in the folder. You can make links to these files (ln -s /bigdata/gen220/shared/data/M_tuberculosis/*.fastq.gz. You do not need to uncompress the files, Kallisto can read gzip compressed files.
2. Run pfam analysis to get the Protein domains found in each protein - you will need the file M_tuberculosis.pep.fasta
3. Construct a tab delimited file which lists on each line
   • The Gene (LOCUS) name
   • The Protein length
   • An average TPM across replicates for each condition (eg there will be 4 conditions, two replicates per condition)
   • The Pfam Protein domains, separated by comma found in each Protein
   • GO Terms assigned to each domain

FYI - to process the file and move the locus_tags as the sequence names I ran this regular expression (in Perl)

perl -p -e 's/>(\S+).+(\[locus_tag=([^\]]+)\])/>$3 $1 $2/' GCF_000008585.1_ASM858v1_cds_from_genomic.fna  > M_tuberculosis.cds.fasta

I made the protein file of sequences using script from BioPerl. bp_translate_seq.pl M_tuberculosis.cds.fasta > M_tuberculosis.pep.fasta