We’re working on a project with ~2.2 million 454 reads from two cDNA libraries and my job is to find and classify the insertion/deletion variants (indels). As you might guess, since these are reads of transcribed sequence, there’s a lot of noise due to mRNA processing. Spliced-out introns look like deletions. Partially-processed transcripts might look like they contain insertions. So, once I made indel predictions based on aligning 454 data to the hg36 reference sequence, the next priority was to remove the noise.
Fortunately, two colleagues in my group, Ken Chen (the developer of PolyScan) and Brian Dunford-Shore (our resident physicist) have built a “transcriptome” based on all of the known transcripts in CCDS, Ensembl, and Vega databases. One of the files generated with the transcriptome is the refseq “footprint” which contains all of the UTRs and exons of all transcripts. It seems to me this file offers the most comprehensive source for annotating the indels from cDNA data.
So, I wrote a script, annotate_with_footprint.pl, which cross-references a set of indels with the footprint file. Insertions are classified as either within-CDS-exon, within-UTR-exon, or noncoding. Deletions are a bit more complicated – they could be within-CDS-exon, within-UTR-exon, or noncoding. They could also span multiple CDS or UTR exons, span intron-exon-junctions, etc.
As it turned out, only about 12% of the insertions and 1% of the deletions were in exons; The vast majority were in UTR/intron regions or intron-exon splice artifacts. Another 4% of the deletions appeared to span one or more CDS exons, but many of these may be exon-skipping events, not true deletions.
Even with strong 454 cDNA support, I won’t be confident that these are real coding mutations until we validate them in genomic DNA.