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Blog: Improving annotation, assessment and interpretation of coding variants

Are you happy with the current toolset available for coding variant annotations / interpretations? I think we are at the cusp of the arrival of a new set of tools to annotate, understand and prioritize variants. An obvious direction would be fuelled by the recent progress in proteogenomics.

In a recent review article in Briefings in Bioinformatics, we have outlined 10 challenges that could improve coding variant interpretation.

  • Sequence and structural properties perturbed by coding SNVs
  • Gain and loss of PTMs owing to SNVs
  • Coding SNVs in unassigned regions of proteins
  • Impact of coding SNVs in low-complexity regions
  • Coding SNVs and intrinsically disordered regions in proteins
  • Influence of coding SNVs on protein misfolding, domain swapping, aggregation, macromolecular crowding, and degradation
  • Coding SNVs and metamorphic proteins
  • Impact of coding SNVs on the transcriptomic diversity
  • Functional impact of synonymous variations
  • Impact of coding SNVs on the interactome of a protein

We have more gene-centric studies and understanding of "genes" than non-coding genomic regions, however, we don't have orthogonal experiments as part of genome-analytics to understand the expression, function, and impact of singleton or combined variant impact. Delineating these underplay of genome-transcriptome-proteome is a key aspect of implementing precision medicine.

Thoughts?

Full article: Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation, and assessment (Brief Bioinform (2015) doi: 10.1093/bib/bbv084)

genomics annotation sequencing snp proteogenomics

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