A University of Texas at Austin-led research team announced on May 27 that it has identified genes previously unknown to be connected to three rare disorders by comparing groups of proteins across a wide range of species and using animal models and human patient data. The findings provide new insight into the genetic causes of human diseases.
The discovery was made by reconstructing the most detailed map yet of the molecular machines that carried out essential life functions in an ancient ancestor believed to have given rise to all complex life, including humans. This protein network map, known as the protein interactome and published in Cell Genomics, allowed researchers to identify hundreds of genes not previously associated with human diseases.
Rachael Cox, a former UT doctoral student who led the data analysis in Edward Marcotte’s lab, said, “There was a huge range of diseases that we could predict pretty well, just using ancient protein complexes.” She added that while they found links to three rare diseases so far—osteopetrosis, end-stage kidney disease and short-rib thoracic dysplasia—other diseases likely have similar connections. The research used computational resources from the Texas Advanced Computing Center (TACC), which is supported by the National Science Foundation and offers significant academic supercomputing capabilities.
Scientists refer to this ancient organism as the Last Eukaryotic Common Ancestor (LECA), estimated at 1.5 to 1.8 billion years old. The research team found about half of all human genes can be traced back to LECA, with versions shared broadly across eukaryotic organisms. Marcotte said, “I think it gives you perspective as a human to look around at all the organisms you can see and realize you’re related to them in some deep, fundamental way.”
To build their interactome map for LECA, researchers identified shared genes among 156 eukaryotic species and conducted over 25,000 biochemical experiments on cells from 31 species. Data were analyzed using TACC’s Lonestar and Stampede supercomputers. With this resource in hand, they mapped known gene-disease relationships onto their interactome for further insights into possible disease associations through related proteins.
In follow-up studies, researchers plan further experimental verification using animal models for specific gene-disease associations suggested by their findings.
