Biology subjects

Zarevski, N.

Publications and source records attributed to Zarevski, N..

2 recordsLinked to original sources

bioRxiv2021

Within-Arctic horizontal gene transfer as a driver of convergent evolution in distantly related microalgae

The Arctic Ocean is being impacted by warming temperatures, increasing freshwater and highly variable ice conditions. The microalgal communities underpinning Arctic marine food webs, once thought to be dominated by diatoms, include a phylogenetically diverse range of small algal species, whose biology remains poorly understood. Here, we present genome sequences of a cryptomonad, a haptophyte, a chrysophyte, and a pelagophyte, isolated from the Arctic water column and ice. Comparing protein family distributions and sequence similarity across a densely-sampled set of algal genomes and transcriptomes, we note striking convergences in the biology of distantly related small Arctic algae, compared to non-Arctic relatives; although this convergence is largely exclusive of Arctic diatoms. Using high-throughput phylogenetic approaches, incorporating environmental sequence data from Tara Oceans, we demonstrate that this convergence was partly explained by horizontal gene transfers (HGT) between Arctic species, in over at least 30 other discrete gene families, and most notably in ice-binding domains (IBD). These Arctic-specific genes have been repeatedly transferred between Arctic algae, and are independent of equivalent HGTs in the Antarctic Southern Ocean. Our data provide insights into the specialized Arctic marine microbiome, and underlines the role of geographically-limited HGT as a driver of environmental adaptation in eukaryotic algae.

evolutionary biology↗

bioRxiv2020

Accurate detection of single nucleotide polymorphisms using nanopore sequencing

Nanopore sequencing is a powerful single molecule DNA sequencing technology which offers high throughput and long sequence reads. Nevertheless, its high native error rate limits the direct detection of point mutations in individual reads of amplicon libraries, as these mutations are difficult to distinguish from the sequencing noise. In this work, we developed SINGLe (SNPs In Nanopore reads of Gene Libraries), a computational method to reduce the noise in nanopore reads of amplicons containing point variations. Our approach uses the fact that all reads are very similar to a wild type sequence, for which we experimentally characterize the position-specific systematic sequencing error pattern. We then use this information to reweight the confidence given to nucleotides that do not match the wild type in individual variant reads. We tested this method in a set of variants of KlenTaq, where the true mutation rate was well below the sequencing noise. SINGLe improves between 4 and 9 fold the signal to noise ratio, in comparison to the data returned by the basecaller guppy. Downstream, this approach improves variants clustering and consensus calling. SINGLe is simple to implement and requires only a few thousands reads of the wild type sequence of interest, which can be easily obtained by multiplexing in a single minION run. It does not require any modification in the experimental protocol, it does not imply a large loss of sequencing throughput, and it can be incorporated downstream of standard basecalling.

bioinformatics↗