Evidence map›Paper›PMID 35073845›Full record

ArticleBMC bioinformatics2022

Varia: a tool for prediction, analysis and visualisation of variable genes.

Gavin Mackenzie, Rasmus W Jensen, Thomas Lavstsen, Thomas D Otto

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. UnravellingFrontiers in parasitology · 2022
    Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

Gavin MackenzieCentre for Immunobiology, Institute of Infection, Immunity and Inflammation, MVLS, University of Glasgow, Glasgow, UK.
Rasmus W JensenDepartment of Immunology and Microbiology, Department of Infectious Diseases, Centre for Medical Parasitology, University of Copenhagen, 1017, Rigshospitalet, Copenhagen, Denmark.
Thomas LavstsenDepartment of Immunology and Microbiology, Department of Infectious Diseases, Centre for Medical Parasitology, University of Copenhagen, 1017, Rigshospitalet, Copenhagen, Denmark. thomasl@sund.ku.dk.
Thomas D OttoCentre for Immunobiology, Institute of Infection, Immunity and Inflammation, MVLS, University of Glasgow, Glasgow, UK. thomasdan.otto@glasgow.ac.uk.ORCID http://orcid.org/0000-0002-1246-7404
University of Copenhagen · DKMRC University of Glasgow Centre for Virus Research · GBUniversity of Glasgow · GB

Funding

Wellcome Trust 104111/Z/14/ZR
6 · The paper itself

Abstract

backgroundParasites use polymorphic gene families to evade the immune system or interact with the host. Assessing the diversity and expression of such gene families in pathogens can inform on the repertoire or host interaction phenotypes of clinical relevance. However, obtaining the sequences and quantifying their expression is a challenge. In Plasmodium falciparum, the highly polymorphic var genes encode the major virulence protein, PfEMP1, which bind a range of human receptors through varying combinations of DBL and CIDR domains. Here we present a tool, Varia, to predict near full-length gene sequences and domain compositions of query genes from database genes sharing short sequence tags. Varia generates output through two complementary pipelines. Varia_VIP returns all putative gene sequences and domain compositions of the query gene from any partial sequence provided, thereby enabling experimental validation of specific genes of interest and detailed assessment of their putative domain structure. Varia_GEM accommodates rapid profiling of var gene expression in complex patient samples from DBLα expression sequence tags (EST), by computing a sample overall transcript profile stratified by PfEMP1 domain types.

resultsVaria_VIP was tested querying sequence tags from all DBL domain types using different search criteria. On average 92% of query tags had one or more 99% identical database hits, resulting in the full-length query gene sequence being identified (> 99% identical DNA > 80% of query gene) among the five most prominent database hits, for ~ 33% of the query genes. Optimized Varia_GEM settings allowed correct prediction of > 90% of domains placed among the four most N-terminal domains, including the DBLα domain, and > 70% of C-terminal domains. With this accuracy, N-terminal domains could be predicted for > 80% of queries, whereas prediction rates of C-terminal domains dropped with the distance from the DBLα from 70 to 40%.

conclusionPrediction of var sequence and domain composition is possible from short sequence tags. Varia can be used to guide experimental validation of PfEMP1 sequences of interest and conduct high-throughput analysis of var type expression in patient samples.

Indexed as

Malaria, FalciparumProtozoan ProteinsHumansPlasmodium falciparumProtozoan Proteins

Identifiers

PMID35073845
PMCPMC8785495
OpenAlexW4206919410

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.