Truseq sr cluster kit v4

RNA-seq libraries were prepared using 200 ng of total RNA as described in Nikolaeva et al.^{5 (link)}. Illumina TruSeq SR Cluster Kit v4 reagents were used. Sequencing data were processed as described in^{45 (link)} using Mus musculus.GRCm38.86 gene annotation. Statistical analysis was performed in R (version 3.4.0). Genes with low counts were filtered out according to the rule of 1 count per million (cpm) in at least 1 sample. Library sizes were scaled using TMM normalization and log-transformed into counts per million (CPM) using voom^{46 (link)}.
Principal component analysis showed a large variability between replicate samples. Two factors of unwanted variation were removed using the RUVs function (R package RUVSeq v. 1.10.0^{47 (link)}). Differential expression between knock-out and wild-type was computed using limma^{48 (link)}. A linear model with a factor for each combination of time point and genotyope was used. Factors to correct for batch effect and unwanted variation were also added in the design matrix. Differences in gene expression levels between KO and WT animals at each time points were combined into one F-test. Genes with a false discovery rate <5% were considered significant. The limma function ‘classifyTestsF’ was used to classify time point as significant or not for the selected genes.

M. tuberculosis genomic DNA was extracted as previously described [57 (link)]. Libraries were prepared using the Kapa LTP Library Prep kit (Kapa Biosystems) according to the manufacturer’s recommendations. Cluster generation was performed using the Illumina TruSeq SR Cluster Kit v4 reagents and sequenced on the Illumina HiSeq 2500 using TruSeq SBS Kit v4 reagents. Sequencing data were demultiplexed using the bcl2fastq Conversion Software (v. 2.20, Illumina, San Diego, California, USA). Raw reads were adapter- and quality-trimmed with Trimmomatic v0.33 [58 (link)]. The quality settings were “SLIDINGWINDOW:5:15 MINLEN:40”. Preprocessed reads were mapped onto the M. tuberculosis H37Rv reference genome sequence (RefSeq NC_000962.3) with Bowtie2 v2.2.5 [59 (link)]. SNP calling was done using VarScan v2.3.9 [60 (link)]. To avoid false-positive SNP calls the following cutoffs were applied: minimum overall coverage of ten non-duplicated reads, minimum of five non-duplicated reads supporting the SNP, mapping quality score >8, base quality score >15, and a SNP frequency above 80%. All SNPs were manually checked by visualizing the corresponding read alignments. Sequencing data have been deposited to the Sequence Read Archive (SRA) under accession number SRP158673.

RNA was extracted from biological duplicates as described above. RNA-seq libraries were prepared from 1 μg of total RNA. The RNA samples were depleted of r-RNAs with the Illumina Ribo-Zero rRNA Removal Kit (Gram-Positive Bacteria) then used to generate sequencing libraries with the Illumina TruSeq Stranded mRNA reagents, omitting the polyA selection step (Illumina, San Diego, California, USA). Cluster generation was performed with the resulting libraries using the Illumina TruSeq SR Cluster Kit v4 reagents and sequenced on the Illumina HiSeq 2500 using TruSeq SBS Kit v4 reagents. Sequencing data were demultiplexed using the bcl2fastq Conversion Software (v. 2.20, Illumina, San Diego, California, USA).
Reads were processed and mapped to the reference genome sequence as described above. Counting reads over features was done with featureCounts [61 (link)] from the Subread package v1.4.6. Annotation was taken from TubercuList release R27 (https://mycobrowser.epfl.ch/releases). Differential gene expression analysis was done using DESeq2 [62 (link)]. RNA-seq data have been deposited to the Gene Expression Omnibus (GEO) repository under accession number GSE118994.