Dear Michael, I am still checking my data, but your clue seems to be the solution to the problem. Thank you very much for your prompt and helpful response.
Dear all,
I am analyzing RNA sequencing data from ribo-depleted RNA samples generated using 150 bp paired-end, stranded sequencing. Reads were aligned to the human reference genome GRCh38 (Ensembl release 115) using STAR, with more than 95 percent of reads successfully aligned. I then quantified gene expression using featureCounts with the corresponding Ensembl GTF (release 115).
When running featureCounts with -t exon -g gene_id, approximately 20 to 30 percent of the aligned reads are assigned, which is expected given that this setting effectively quantifies mature (exonic) RNA only. In contrast, when using -t gene -g gene_id, the proportion of assigned reads increases to about 70 to 85 percent, consistent with aggregation across the full gene body, including intronic and other non exonic regions present in ribo-depleted libraries.
However, I observe an unexpected behavior: for some genes that have non-zero counts across all samples when using -t exon, the corresponding counts are zero when using -t gene. Intuitively, I would expect these genes to retain at least the same counts (or even higher counts) when switching from exon-level to gene-level features, not to drop to zero.
Is there a plausible explanation for this behavior?
Thanks in advance for your help.
Best regards.
1 answer
That may be due to the regions overlapping in the genome. If you have not specified the option -O, then the reads will only be assigned to one overlapping feature. Extending to gene level might introduce overlaps that aren't there on the exon feature level.
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