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Varia: Prediction, analysis and visualisation of variable genes

Authors :
Rasmus Weisel Jensen
Thomas D. Otto
Thomas Lavstsen
Mackenzie G
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

SummaryAssessing the diversity or expression of variable gene families in pathogens can inform about immune escape mechanisms or host interaction phenotypes of clinical relevance. However, obtaining the sequences and quantifying their expression is a challenge. Here, we present a tool, which based on unique sequence tag similarity between members of a gene family, predicts the domains encoded by the queried gene. As an example, we are using the var gene family, encoding the major virulence proteins (PfEMP1) of the human malaria parasite, Plasmodium falciparum. We developed Varia, which predicts the likely var gene sequence and encoded protein domain composition of a gene from short sequence tags. We provide a new extended annotated var genome database, in which Varia identifies genes with identical tag sequences and compares these to return the most probable domain composition of the query gene. Varia’s ability to predict correct PfEMP1 domain compositions from short var sequence tags was tested in two complementary pipelines to (a) return the putative gene sequences and domain compositions of the query gene from any partial sequence provided, thereby enabling detailed assessment of specific genes’ putative function and experimental validation of these (b) to accommodate rapid profiling of var gene expression in complex patient samples, by compiling the overall domain prevalence among var transcripts predicted identified and quantified by next generation sequencing of so-called var DBLα-sequence tags.Availability and implementationVaria is available on GitHub (https://github.com/GCJMacken-zie/Varia) under the MIT license.Contactthomasl@sund.ku.dk, thomasdan.otto@glasgow.ac.uk

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........47bbd1243127e53e604d8fbcc8cbf269
Full Text :
https://doi.org/10.1101/2020.12.15.422815