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Varia: Prediction, analysis and visualisation of variable genes
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Summary
Assessing 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 implementation
Varia is available on GitHub (
https://github.com/GCJMacken-zie/Varia
) under the MIT license.
Contact
thomasl@sund.ku.dk
,
thomasdan.otto@glasgow.ac.uk
Title: Varia: Prediction, analysis and visualisation of variable genes
Description:
Summary
Assessing 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 implementation
Varia is available on GitHub (
https://github.
com/GCJMacken-zie/Varia
) under the MIT license.
Contact
thomasl@sund.
ku.
dk
,
thomasdan.
otto@glasgow.
ac.
uk.
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