Tracing Genome Evolution for COVID-19 Predictive Intelligence

Presenter: Gustavo Caetano-Anollés, Department of Crop Sciences and Carl R. Woese Institute for Genomic Biology, University of Illinois

Tuesday, December 13

8 AM Pacific / 9 AM Mountain / 10 AM Central / 11 AM Eastern for one hour


Predictive intelligence is a forward-looking strategy that uses past events to anticipate the future. I will report on our efforts to generate predictive intelligence for viral pandemics. Our focus is the evolving COVID-19 virus. The virus continues to represent a worldwide threat despite implementation of public-wide vaccination measures. Analysis of over 12 million genome sequences revealed how viral genetic makeup is being structured by emerging mutant constellations. We found that haplotypes – sets of mutations that are inherited together – were linked to virus seasonality and coalesced into constellations delimiting networks of molecular interactions. We also modelled the changing structure of the ~30 proteins of the COVID-19 genome with powerful deep-learning ab initio structural prediction methods, uncovering a central functional role of protein loop and structural domain regions. Our goal is to develop artificial intelligence and machine learning tools that can be utilized for emergency health security programs.


Dr. Caetano-Anollés is Professor of Bioinformatics and University Scholar, working in the Department of Crop Sciences and the Carl R. Woese institute for Genomic Biology of the University of Illinois. His group explores molecular diversity and how molecular structure determines biological function in higher organisms and microbes of significance. One focus is the origin, structure, and evolution of genomes, proteomes, RNomes, and functionomes for applications in bioengineering, biomedicine, and systems biology.