Next generation sequencing (NGS) has been a hot research topic and constantly evolving technique to sequence microbial communities in medical and environmental research. Its many pros (namely its quick turnaround time and massively parallel platform) have revolutionized the way we can process DNA, but one of its failures is the inability to detect low-frequency reads or variants in a population. In virology, the ability to detect rare viruses and their variants is extremely important (particularly for infectious disease, where only a few viruses are needed to cause disease, and small mutations can cause different health outcomes).
A new paper this month in the Journal of Virology has suggested a new way to look for low-frequency RNA viral variants, called CirSeq. Essentially, this method decreases the error rate that occurs in NGS, and thereby increases the confidence in detecting rare variants in a sample. Because the error is so low, if rare sequences are detected, we can be confident that the sequence is real (and not an error from the sequencing platform).
Although this may seem like a trivial pursuit to some, this could actually help advance our understanding of viruses associated with infectious disease, develop vaccines, or think about how viruses evolved to present day. The paper points out that it only took a single point mutation in the Chikungunya virus's genome to allow the virus to be carried by a different mosquito, Aedes albopictus. These mosquitos can then carry the virus to new habitats where they previously couldn't be transmitted. From an evolutionary perspective, CirSeq could lead to new analyses of fitness among viral variants.
Some scientists have already used the method with good results. However the authors acknowledge several current shortcomings regarding the CirSeq method, specifically the purity and mass requirements for viral RNA and how to interpret some of the results. Further development of CirSeq to circumvent these issues may have huge benefits, both in public health and in basic research.
Whitfield, Z.W. and Andino, R.. "Characterization of Viral Populations by Using Circular Sequencing." ASM: Journal of Virology (2016). http://jvi.asm.org/content/90/20/8950.full?keytype=ref&siteid=asmjournals&ijkey=Y0U7yeqwLfx%2F.#sec-4.
Acevedo, A., and Andino, R.. "Library preparation for highly accurate population sequencing of RNA viruses." Nature Protocols (2014). http://www.nature.com/nprot/journal/v9/n7/full/nprot.2014.118.html#ref7