ToxoCEN: A Co-expression network for Toxoplasma gondii

Elucidating gene function is a major goal in biology, especially among non-model organisms. However, doing so is complicated by the fact that molecular conservation does not always mirror functional conservation, and that complex relationships among genes are responsible for encoding pathways and higher-order biological processes. Co-expression, a promising approach for predicting gene function, relies on the general principal that genes with similar expression patterns across multiple conditions will likely be involved in the same biological process. For Toxoplasma gondii, a prevalent human eukaryotic pathogen greatly diverged from malaria, approximately 47% of the predicted genes in the genome lack functional annotations. Here, we leveraged a large amount of publicly available transcriptomic data to generate a T. gondii Co-Expression Network (ToxoCEN), recapitulating known protein networks, predicting gene function, and enabling insights into the principles influencing co-expression. Overall, co-expression is a powerful tool for uncovering gene function, and decreases the experimental tests needed to identify functions for currently under-annotated genes.

CS Arnold, Y Wang, VB Carruthers, MJ O'Meara
ToxoCEN: A Co-Expression Network for Toxoplasma gondii
Code available at https://github.com/maomlab/CalCEN/tree/master/vignettes/ToxoCEN

TGME49_transcript_annotations.tsv

• Toxoplasma gondii ME49 (NCBI Taxon:508771) annotated protein features collected from ToxoDB Release 64

top_coexp_hits.tsv

• top 50 ToxoCEN associations for each gene

top_coexp_hits_0.15.tsv

• top ToxoCEN associations for each gene filtered by score > 0.85 and at most 50 per gene

Data/estimated_expression_meta.tsv

• Metadata for RNAseq estimated expression runs

Data/estimated_expression.tsv

• gene by RNA-seq run estimated expression

Networks/ToxoCEN_network.tsv

• ToxoCEN Co-expression network

Networks/BlastP_network.tsv

• Protein sequence similarity network