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

Abstract

Background Parasites 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. Results Varia_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%. Conclusion Prediction 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.

Unravelling var complexity: Relationship between DBLα types and var genes in Plasmodium falciparum

“…These factors, in addition to the often uneven sequence coverage of var genes during whole genome sequencing, greatly challenges the sequence assembly process. Until recently ( Dara et al, 2017 ; Otto et al, 2019 ; Mackenzie et al, 2022 ), no large repository of var sequences existed as these genes were routinely excluded from studies using whole genome sequencing datasets (e.g., Pf3k, Pf6). The assembled var dataset made publicly available by Otto et al (2019) therefore represents the largest var repository currently available.…”

A novel computational pipeline forvargene expression augments the discovery of changes in thePlasmodium falciparumtranscriptome during transition fromin vivoto short-termin vitroculture

“…This model showed no significant differences between generations, suggesting that differences observed in the raw data may be a consequence of small changes in developmental stage distribution in culture. Var expression profiling by DBLα-tag sequencing Deep sequencing of RT-PCR-amplified DBLα expressed sequence tags (ESTs) combined with prediction of the associated transcripts and their encoded domains using the Varia tool (Mackenzie et al, 2022) was performed, as in the original analysis, to supplement the RNA-sequencing analysis. The raw Varia output file is given in Supplementary file 2.…”

“…Significant differences in total var gene expression were tested by constructing a linear model with the proportion of gene expression dedicated to var gene expression as the explanatory variable, the generation and life cycle stage as an independent variables and the patient identity included as a random effect. Var expression profiling by DBLα-tag sequencing DBLα-tag sequence analysis was performed as in the original analysis (Wichers et al, 2021), with Varia used to predict domain composition (Mackenzie et al, 2022). The proportion of transcripts encoding NTSA, NTSB, DBLα1, DBLα2 and DBLα0 domains were determined for each sample.…”

“…Validation of var expression profiling by DBLα-tag sequencing Deep sequencing of RT-PCR-amplified DBLα expressed sequence tags (ESTs) combined with prediction of the associated transcripts and their encoded domains using the Varia tool (Mackenzie et al, 2022) was performed to supplement the RNA-sequencing analysis. The raw Varia output file is given in Supplementary file 2.…”

“…Var expression profiling by DBLα-tag sequencing DBLα-tag sequence analysis was performed as in the original analysis (Wichers et al, 2021), with Varia used to predict domain composition (Mackenzie et al, 2022). The proportion of transcripts encoding NTSA, NTSB, DBLα1, DBLα2 and DBLα0 domains were determined for each sample.…”