Did You Know There Are (At Least) 20 Applications of Next-generation DNA Sequencing?

Just a while ago large-scale DNA sequencing meant basically sequencing DNA to assemble a genome. The low cost Next-gen sequencing technology revolution has completely changed the landscape of applications of sequencing. Even then, for most of us the applications of next-gen sequencing that stands out is Exome-sequencing, Whole Genome Sequencing, mRNA sequencing, and ChIP-Seq.

Applications of Next-Gen DNA Sequencing (NGS)

Applications of Next-Gen DNA Sequencing (NGS)

Did you know there are at least 20 different applications for next-generation DNA sequencing. In a review paper titled “The expanding scope of DNA sequencing” (this month’s Nature Biotechnology issue),  Shendure and Aiden lists 20 applications of next-gen sequencing.

Granted that many of the applications are not main stream yet, but it drives the point that next-gen sequencing is just a means to an end and they represent the meaning of “next” in next-gen sequencing.

Here is the 20 different applications of Next-Gen Sequencing with references from the paper.

  1. DNA-Seq
  2. Targeted DNA-Seq
  3. Methyl-Seq
  4. Targeted methyl-Seq
  5. DNase-Seq, Sono-Seq and FAIrE-Seq
  6. MAINE-Seq (MNase-mediated purification of mononucleosomes to extract histone-bound DNA (MAINE))
  7. ChIP-Seq
  9. RNA-Seq
  10. FRT-Seq
  11. NET-Seq (Native Elongating Transcript Sequencing)
  12. Hi-C
  13. ChIA-PET (Chromatin Interaction Analysis by Paired-End Tag sequencing)
  14. Ribo-Seq
  15. TRAP
  16. PARS (Parallel Analysis of RNA Structure)
  17. Synthetic saturation mutagenesis
  18. Immuno-Seq
  19. Deep protein mutagenesis
  20. PhIT-Seq

What is Your Favorite Application of Next-Gen Sequencing That is Missing?

One easy addition to the list is a wishful “tissue-specific targeted” RNA-Seq.  As the name suggests the targeted RNA-Seq is just a regular RNA-Seq but on a subset of transcriptomes.

A common problem in RNA-Seq is that each tissue has a few genes (at least one) that are highly expressed. Often, they can account for over 10-20% of the sequenced reads. Many RNA-Seq applications can afford to miss the “crazily” expressed genes and gain a view on lowly expressed genes. Just like one throws out ribosomal RNA in the standard RNA-Seq library prep, one can possibly exclude these highly expressed genes and then sequence the left-over sample.

Another related application that is not listed here is microRNA-seq. Do you think the list can be expanded? Please feel free to chime in to add any of your favorite applications of next-gen DNA sequencing.

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