Poster Presentation 44th Lorne Genome Conference 2023

VIVID: a web application for variant interpretation and visualisation in multidimensional analyses (#225)

Swapnil Tichkule 1 2 , Yoochan Myung 3 4 5 , Myo T. Naung 1 2 , Brendan RE. Ansell 1 , Andrew J. Guy 6 , Namrata Srivastava 7 , Somya Mehra 8 , Simone M. Cacciò 9 , Ivo Mueller 1 , Alyssa E. Barry 8 10 , Cock van Oosterhout 11 , Bernard Pope 12 13 14 , David B. Ascher 3 4 5 , Aaron R. Jex 1 15
  1. Population Health & Immunity, Walter Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
  2. Department of Medical Biology, University of Melbourne, Melbourne, VIC, Australia
  3. Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, VIC, Australia
  4. Computational Biology and Clinical Informatics, Baker Heart and Diabetes, Melbourne, Australia
  5. School of Chemistry and Molecular Biosciences, University of Queensland, St Lucia, Queensland, Australia
  6. School of Science, RMIT University, Melbourne, Australia
  7. Department of Data Science and AI, Monash University, Melbourne, Australia
  8. Life Sciences Discipline, Burnet Institute, Melbourne, Australia
  9. Department of Infectious, Parasitic and Immune-mediated Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, Rome, Italy
  10. Institute of Mental and Physical Health and Clinical Translation (IMPACT) and School of Medicine, Deakin University, Geelong, Australia
  11. School of Environmental Sciences, University of East Anglia, Norwich, UK
  12. Melbourne Bioinformatics, University of Melbourne, Melbourne, Australia
  13. Australian BioCommons, University of Melbourne, Melbourne, VIC, Australia
  14. Department of Clinical Pathology, University of Melbourne, Melbourne, VIC, Australia
  15. Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, VIC, Australia

Large-scale comparative genomics and population genetics studies generate enormous amounts of data in the form of DNA variants. Ultimately, many of these studies aim to associate genetic variants with phenotypes or fitness. However, phenotypic association studies are hampered due to a lack of automatic, generalised and data-integrative tools. Here we introduce VIVID, an interactive, user-friendly web application that integrates a wide range of approaches for associating genotypic to phenotypic information in any organism, from an individual or population, in three-dimensional (3D) structure of the encoded protein.

VIVID integrates published algorithms, tools and databases that allow mutation mapping and annotation, calculation of interactions and conservation scores, prediction of deleterious effects, analysis of diversity and selection, and 3D visualisation of genotypic information encoded in Variant Call Format (VCF) on AlphaFold2 protein models.

 VIVID supports improved visualisation, analysis and understanding of how mutations impact protein structure and function in any organism. It can colour any protein model based on localised differences in population genetic metrics, enabling users to visualise protein evolution in 3D and identify genomic regions under selection. It allows the rapid assessment of genes of interest in studying adaptive evolution and the genetic load and helps prioritise targets for experimental validation. We have demonstrated the utility of VIVID by exploring the evolutionary genetics of Plasmodium falciparum and SARS-CoV-2 by revealing spatial and temporal variation in the signature of selection in potential targets of functional antibodies.

VIVID is a valuable resource to the research community working in population genetics, evolutionary genomics and protein structural biology. It allows users to visualise genomic mutations for their impact on protein structure, function, and evolution. VIVID is freely available at http://biosig.unimelb.edu.au/vivid.