Validation of RNAseq Experiments by qPCR?
This was originally posted here on 9 November 2014:
As preliminary data for a talk can I graph transcript counts of particular genes (transcriptome data) instead of qPCR (haven't done it yet)? — Sciencegurl (@sciencegurlz0) October 27, 2014
In response to the that I posted a response I made in response to a similar query from a reviewer for a recent manuscript (original available here). Based on the fact that this came up a couple times in two weeks, I thought that I'd try to be more clear on my thoughts (and put them somewhere easier for others to find). This is how we address this issue experimentally, and in response to reviewer requests. Feel free to use any of these arguments yourself but your mileage with your supervisor/manuscript or grant reviewers may vary. Most importantly, if you have some suggestions/data/papers that we should include please comment below and I'll try to keep this post up to date.
The Answer We Gave:
We had considered performing qPCR studies to ‘re-validate’ some of our gene-expression findings but there is little evidence that qPCR analyses from the same samples will add any extra utility to our data so we decided to eschew those experiments. Previous studies have shown extremely close correlations between qPCR and RNAseq data [1-4]. Ideally, we would re-validate our findings (potentially by qPCR) in a separate cohort of samples, but due to the difficulty in accessing these samples, those experiments are not possible at this time.
What Do We Mean By Validation of RNAseq Results?
- Are these transcripts really differentially expressed in these samples (technical reproducibility)?
- Are these transcripts really generally differentially expressed in other samples (biological reproducibility)?
- Do these transcriptional changes represent phenotypic differences (significance)?
Why was qPCR the traditional validation experiment from microarray studies?
How similar are RNAseq and qPCR results?
Under What Conditions Would qPCR Be a Good Validation Method?This isn't to say qPCR isn't useful, we use it all the time in my lab. Its a great tool for looking at a small number of genes in samples for example. But when would it be good to use in the context of validating a RNAseq experiment? I would argue that it is most useful in the case where you have independent samples from those that you did your RNAseq studies on. For example, maybe for economical reasons, you examined 5 control samples and 5 drug-treated samples but you have another 20 samples available. qPCR would be a great way to test whether the differences observed are also true in separate samples, thus answering question #2. I think this is especially important as in my experience a lot of RNAseq studies are underpowered to answer the questions asked (if you want a quick and easy way to check the power of your experimental design I like Scotty).
- Griffith M, Griffith OL, Mwenifumbo J, Goya R, Morrissy a S, et al. (2010) Alternative expression analysis by RNA sequencing. Nat Methods 7: 843–847. doi:10.1038/nmeth.1503.
- Asmann YW, Klee EW, Thompson EA, Perez E a, Middha S, et al. (2009) 3’ tag digital gene expression profiling of human brain and universal reference RNA using Illumina Genome Analyzer. BMC Genomics 10: 531. doi:10.1186/1471-2164-10-531.
- Wu AR, Neff NF, Kalisky T, Dalerba P, Treutlein B, et al. (2014) Quantitative assessment of single-cell RNA-sequencing methods. Nat Methods 11: 41–46. doi:10.1038/nmeth.2694.
- Shi Y, He M (2014) Differential gene expression identified by RNA-Seq and qPCR in two sizes of pearl oyster (Pinctada fucata). Gene 538: 313–322. doi:10.1016/j.gene.2014.01.031.
- Wang Z, Gerstein M, Snyder M (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10: 57–63. doi: 10.1038/nrg2484.
- Hughes TR (2009) “Validation” in genome-scale research. J Biol 8: 3. doi:10.1186/jbiol104.