RNA-seq doesn't match qPCR and western blot results
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!
• 3,059 views
•
link
updated
by
rodolfo.peacewalker •
•
written
by
heinyxiao •
•
written
by
heinyxiao •
0 answers
No answers yet.
Log in to answer this question.
More posts like this
-
RNA-seq data compared to qRT-PCR
written by SeoG •
-
Microbial transcriptomic analysis
written by imaparna27 •
-
Blog: Using Transcriptome Sequencing to identify DEGs in response to chemical challenges
written by Novogene •
-
SVA on RT-PCR verification of RNA-Seq data
written by henry-keen •
-
Plots for gene expression data
written by jsw940 •
-
Mixed population of cells - Targeted / Amplicon Sequencing?
written by alexille5640 •
-
DNA starting material
written by op263 •
-
confirmation RNA-seq's results
written by parviz Heidari •
-
RNA-seq results do not match qRT-PCR results
written by xiaoyonf •
-
Technical Or Biological Replicate
written by h.mon
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