RNA-Seq of Thalassiosira pseudonana
FastQC [65] was used to check GC content and per-base quality scores in each sample. Raw reads were quality trimmed and filtered using Sickle v1.33 [66] with the options -q 33 -l 50. The first option sets the quality score threshold for trimming to 33, while the second option discards all reads that are shorter than 50 base pairs after trimming. Sequencing adapters were not removed, as previous studies have shown that adapters do not significantly affect alignments to reference genomes and that aggressive trimming can lead to bias and poorer results [67,68]. The T. pseudonana reference genome was obtained from NCBI in GFF format (accession number GCA_000149405.2) and converted to GTF using gffread. Reads were aligned to the reference genome using HISAT2 v2.1.0 [69] with the option --dta. HISAT2 is a splice-aware aligner that generates alignments more quickly and using less memory than older alignment software such as BowTie or BWA [70]. The --dta option tells the program to report alignments in a format that is tailored to transcriptome assemblers like StringTie. HISAT2 created sequence alignment/map files for each sample. These files contain the alignments in the order that the sequences occurred in the input FASTQ files. SAMtools v1.3 [71] was used to sort the alignments with respect to their genomic positions and then convert the files to binary alignment/map files, which facilitate more rapid computation. Coverage depth of the genome was calculated using the genomeCoverageBed command with the -ibam option in BEDTools v2.25.0 [72]. StringTie v1.3.3 [73] was used to assemble putative transcripts and generate counts tables for use in DESeq2. First, putative transcripts were assembled using the reference annotation file downloaded from NCBI. Then, data from all samples was merged into a single file using the command stringtie --merge. Finally, stringtie -eB was used to calculate transcript abundances and generate count tables structured for Ballgown (DESeq2 also accepts these counts tables as input). DESeq2 v1.20.0 [74] was used to perform differential expression analysis and create exploratory visualizations