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3.3 years ago
heinyxiao
▴
10
Hello! I really appreciate it if anyone can help me with this issue!
Recently we used siRNA to knock down a gene, and did RNA-seq to find the downstream targets of this gene. We performed qRT-PCR and Western blot to make sure the gene was successfully knocked down before submitting it to sequencing. But when we check the RNA-seq results, this weird thing happened... The expression of this gene was not reduced - both the ctrl and treatment group have ~90 counts of this gene.
I used both STAR and HISAT2 for alignment, followed by DESeq2 normalization, but both of them generated similar results.
Thanks so much if you could provide any suggestions!
Hi!
After reading your issue, did you considerate that your siRNA could only have post-translational effects? i.e. only affects the protein expression and not the mRNA/transcript stability. Also, it is important to considerate the number of cells that were successfully transfected.
Best regards!
Thanks for replying!
I feel the siRNA has knockdown effects on both mRNA and protein level, since we also did qRT-PCR and the results showed ~70% knockdown efficiency... After sequencing, we got back the leftover samples and did qRT-PCR again - the knockdown group still having ~50% less expression on the target gene.
Another issue was, after analyzing the differential expressed genes, we found only 4 genes were significantly affected - which is too few for downstream analysis.
So I was wondering maybe there's something that happened with my analysis...
We did the paired-end 3'-tagged RNA-seq and the read length was 38bp. Do you have suggestions on which aligner to use and what special arguments should I set up?
Many thanks!!!
I guess that the length of your reads could affect the alignment. I consider that they are a little bit short, are you interested in a specific population of RNA? Also, I suggest you to check the annotation of aligned/mapped reads by using RSEqC. Follow the read.distribution.py module.
Best regards