Next Generation Sequencing for Gene Expression Analysis – Seq It Out #11

Do you perform qPCR as a routine part of your research? Are you interested in gene expression, but haven’t yet looked into how next generation sequencing or NGS can help you out? Let me see if I can help answer some of those questions.

Next generation sequencing, also known as NGS, provides opportunities to profile gene expression in a wide range of settings. Whether you are looking to discover potentially novel genes or transcripts, or study how certain genes respond to stimuli, NGS can offer a great complement to your existing methodology.

Let’s say you’re interested in studying a particular set of genes’ response to a certain stimulus, and currently you’re using a set of TaqMan probes to accomplish this. This works well enough, but you’re relying on a prior knowledge of this particular set of genes’ involvement in the affected pathway. Are there other genes or RNA transcripts that are playing a part in the response?

Let’s think a bit differently and talk about targeted RNA sequencing. Using this approach, you can target a known set of genes or non-coding RNA’s and measure their expression levels, much like a qPCR/Taqman approach. This method can allow you to target a small number of custom-selected genes with custom Ion AmpliSeq RNA panels, or all the way up to over 20,000 genes in a single reaction when using Ion AmpliSeq Transcriptome for instance. These methods also allow for low input starting material and work well with degraded RNA, such as that sourced from Formalin Fixed paraffin embedded tissue also refered to as FFPE. When combined with the ability to multiplex many samples and sequence them together in a single run, this approach provides the ability to economically analyze a large number of targets within a large number of samples.

For targeted RNA sequencing, analysis is much more straightforward. Data is analyzed using a provided software plugin available in Torrent Suite software, and gene expression values are provided as well as clustering of genes that exhibit different patterns of expression. The expression data can be used in a variety of standard software packages for further statistical analysis if desired.

For many, this is the best of both worlds – being able to use low amounts of input material, having a comprehensive set of genes or transcripts to target economically, and have a simple analysis path to allow them to move right into the interpretation and understanding of their data.

I hope this video was helpful regarding Gene Expression applications using next gen sequencing and I am sure you’ll have more questions.

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And remember, when in doubt, just Seq It Out