QuasiFlow: a bioinformatic tool for genetic variability analysis from next generation sequencing data
Pedro SeoaneiD, Luis Díaz‐MartíneziD, Enrique VigueraiD, Manuel Gonzalo ClarosiD, Ana Grande-PéreziD
Abstract
Populations of RNA and ssDNA viruses within their hosts contain a heterogeneous collection of variant genomes known as quasispecies. Large variability in mitochondrial DNA has also been found within the same organism, drawing an interesting parallel between the two situations. The advent of next-generation sequencing technologies facilitated studying genetic variation, but many open-source bioinformatic tools have to be combined in a non-trivial approach. Here it is presented QuasiFlow, a workflow based on well-stablished software that extracts reliable mutations and recombinations, even at low frequencies (~10-4), provided that at least 250 million nucleotides are analysed. Accurate prediction of mutations and recombinations has been demonstrated with synthetic reads and with in vitro rolling-circle amplification of a plant geminivirus. An in-depth analysis of viral quasispecies was performed and QuasiFlow revealed the coexistence in the plant of three virus genomes and distinct recombinations between some of them. Human mitochondrial variants were also investigated and high level of heteroplasmy (75%) was confirmed, and the relation between low-frequency heteroplasmy (0.1- 0.2%) and some human diseases, regardless of sex, was established. Hence, we propose that QuasiFlow may find use with known and emerging viruses to reveal evolutionary jumps and co-infections, with mitochondrial DNA to detect relevant heteroplasmy would otherwise be elusive, or even in other population studies such as those considering single cell sequencing.
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