OpenVar: functional annotation of variants in non-canonical open reading frames

Abstract

Background Recent technological advances have revealed thousands of functional open reading frames (ORF) that have eluded reference genome annotations. These overlooked ORFs are found throughout the genome, in any reading frame of transcripts, mature or non-coding, and can overlap annotated ORFs in a different reading frame. The exploration of these novel ORFs in genomic datasets and of their role in genetic traits is hindered by a lack of software. Results Here, we present OpenVar, a genomic variant annotator that mends that gap and fosters meaningful discoveries. To illustrate the potential of OpenVar, we analysed all variants within SynMicDB, a database of cancer-associated synonymous mutations. By including non-canonical ORFs in the analysis, OpenVar yields a 33.6-fold, 13.8-fold and 8.3-fold increase in high impact variants over Annovar, SnpEff and VEP respectively. We highlighted an overlapping non-canonical ORF in the HEY2 gene where variants significantly clustered. Conclusions OpenVar integrates non-canonical ORFs in the analysis of genomic variants, unveiling new research avenues to better understand the genotype–phenotype relationships.

OpenCustomDB: Integration of Unannotated Open Reading Frames and Genetic Variants to Generate More Comprehensive Customized Protein Databases

“…It takes advantage of the OpenProt annotation that includes altProts, predicted novel isoforms of canonical proteins, and canonical proteins . A VCF (Variant Calling File) is generated with the OpenVar genomic variant annotator, which integrates altORFs . A transcript expression file is used as a second input to control database size by either adjusting the number of transcripts according to their level of expression (i.e., threshold value) or by establishing a maximum number of protein entries.…”

“… 12 A VCF (Variant Calling File) is generated with the OpenVar genomic variant annotator, which integrates altORFs. 18 A transcript expression file is used as a second input to control database size by either adjusting the number of transcripts according to their level of expression (i.e., threshold value) or by establishing a maximum number of protein entries. With the default parameters, the maximum number of protein entries is 100,000 and the Transcripts Per Kilobase Million or TPM threshold is adjusted accordingly.…”

“…SNPs and Indels with FreeBayes quality of less than 20 were filtered out with an internal Python script. Then, OpenCustomDB uses OpenVar 18 to predict the impact of variations on the primary structure of the corresponding canonical proteins, novel isoforms, and altProts and inserts the variations at their correct positions in the transcripts.…”