Similar protocols

Pipeline publication

[…] n of the GSTs was then normalized and quantified in Log2 (experimental/control) as described in Pfaffl et al., []. The 1 x-fold expression level was therefore chosen as the threshold for significance of target genes. In one case (EFA, day 0.5, June experiment), one of the three biological replicates was removed as an outlier because the standard deviation (SD) of the mean relative expression of its technical replicates was >1., During the July experiment, high-throughput sequencing was performed on C. finmarchicus females on days 2 and 5 of the experiment. A total of 18 RNA-Seq libraries (3 replicates × 3 treatments × 2 time points) were sequenced []. RNA-Seq reads were quality filtered (FASTX Toolkit, version 0.013; http://hannonlab.cshl.edu/fastx_toolkit/) by trimming the first nine and the last 29 bases, and followed by the elimination of low quality reads (cutoff “Phred” score = 20) as well as Illumina adapters. This resulted in the removal of an average of 34% of reads []; reads were then mapped to the C. finmarchicus reference transcriptome (96,090 contigs) [] using the software Bowtie (version, 2.0.6) with a 2-nucleotide mismatch tolerance []. Identification of significant differences in expression in GST genes was performed using the BioConductor package edgeR []. As implemented by edgeR, each library was normalized using the Trimmed mean of M values (TMM) to reduce the differences between library size. Libraries were also normalized using the RPKM method (reads per kilobase of the transcript per million mapped reads); briefly for each gene, the summarized counts were divided by the length of the transcript and the total number of mapped reads in each library using a custom script written in Perl (www.perl.org). Differentially expressed GSTs were statistically identified using the Exact test, implemented by edgeR (parallel to Fisher’s Exact test), based on pairwise comparisons between the control and experimental treatments: CONTROL vs LD and CONTROL vs HD for each time point. In addition, controls at 2 and 5 days were compared statistically to determine whether GST expression changed during the experimental incubation. Transcripts were identified as differentially expressed using the Exact test (p<0.05) and a multiple comparison correction with Benjamini-Hochberg method (false discovery rate <5%) implemented by edgeR []. Expression rate was quantified in units of Log2 fold (experimental/control) where a value of 0 represents equal expression between the experimental condition and control., Comparison between the RNA-Seq and RT-qPCR measurement was done for all six genes: three glutathione S-transferases (GSTs; 2 cytosolic and one microsomal) and three candidate reference genes (EFA, 16S, actin) genes at days 2 and 5 for the July experiment. RT-qPCR results were compared with the RNA-Seq data in two ways. First, the normalized Cq-values (RT-qPCR) were compared to the normalized counts from RNA-Seq for each gene-treatment-day combination using linear regression. RNA-Seq reads were normalized to count […]

Pipeline specifications

Software tools FASTX-Toolkit, Bowtie, edgeR