Integration of heterogeneous functional genomics data in gerontology research identifies genes and pathway underlying aging across species

Bubier, J. A.; Sutphin, G. L.; Reynolds, T. J.; Korstanje, R.; Fuksman-Kumpa, A.; Baker, E. J.; Langston, M. A.; Chesler, E. J.

doi:10.1101/451013

bioRxiv · 10.1101/451013

Integration of heterogeneous functional genomics data in gerontology research identifies genes and pathway underlying aging across species

Bubier, J. A.·Sutphin, G. L.·Reynolds, T. J.·Korstanje, R.·Fuksman-Kumpa, A.·Baker, E. J.·Langston, M. A.·Chesler, E. J.

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Abstract

Understanding the biological mechanisms behind aging, lifespan and healthspan is becoming increasingly important as the proportion of the world's population over the age of 65 grows, along with the cost and complexity of their care. BigData oriented approaches and analysis methods for integrative functional genomics enable current and future bio-gerontologists to synthesize, distill and interpret vast, heterogeneous data. GeneWeaver is an analysis system for integration of data that allows investigators to store, search, and analyze immense amounts of data including user-submitted experimental data, data from primary publications, and data in other databases. Aging related genome-wide gene sets from primary publications were curated into this system in concert with data from other model-organism and aging-specific databases, and used in several application using GeneWeavers analysis tools. For example, we identified Cd63 as a frequently represented gene among aging-related genome-wide results. To evaluate the role of Cd63 in aging, we performed RNAi knockdown of the C. elegans ortholog, tsp-7, demonstrating that this manipulation is capable of extending lifespan. The tools in GeneWeaver enable aging researchers to make new discoveries into the associations between the genes, normal biological processes, and diseases that affect aging, healthspan, and lifespan.

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Bubier, J. A., Sutphin, G. L., Reynolds, T. J., Korstanje, R., Fuksman-Kumpa, A., Baker, E. J., Langston, M. A., Chesler, E. J.. 2018-10-24. Integration of heterogeneous functional genomics data in gerontology research identifies genes and pathway underlying aging across species. https://doi.org/10.1101/451013

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