Orthologs in Systems Biology

A recent paper by Renaud, et al., (Environmental Pollution, Vol 244, January 2019, pp 926-937) points out the significant hazard posed by endocrine disrupting chemical (EDC) exposure for aquatic organisms.  Renaud, et al., employed iPathwayGuide as part of a systems biology approach because it is a “powerful tool for obtaining a comprehensive picture” of these effects in aquatic organisms. Using iPathwayGuide’s meta-analysis functionality, the authors were able to identify 13 shared pathways related to EDC exposure in sardine and mackerel, as well as a unique signature for each species.

Annotation—a necessary component of systems biology analysis– tends to be very robust for human, mouse, and rat.  To a lesser extent, annotation is available for widely-used model organisms such as C. elegans and Drosophila, but annotation for many organisms is largely incomplete.  This limitation in the data availability requires an adaptation for systems biology applications.

iPathwayGuide is the premiere systems biology platform, and by employing orthologs, Renaud, et al., made great use of it in this analysis.  Since their species of interest (sardine and mackerel) are not well annotated, they mapped their reads to closely-related fish species (zebrafish and fugu), and then appended the gene identifiers for orthologous human genes. This process allowed Renaud, et al., to take maximum advantage of the very sophisticated analysis capabilities available in iPathwayGuide, and understand the affected biological pathways and mechanisms in the species of their interest, even though these species are not currently well-annotated. The resulting analysis provides insights into the effects of EDC exposure on important metabolic and physiologic processes that are both unique to, and in common between, these sentinel fish species.

If you have RNA-Seq, ChIP-Seq, microarray, proteomics, epigenomics, or any other gene-annotated data from an organism that is not well annotated, take a look at this paper. If you are interested in identifying impacted pathways,  underlying mechanism and upstream regulators in  your own experiment, contact us!


Analyze Now

  1. Register to explore demo data
  2. Subscribe to analyze your ‘omics data
  3. Review and interact with pathways impacted in your experiment
  4. Share your results with collaborators for interpretation and analysis iteration
  5. Create publication-ready figures simply and easily

What You Can Expect

  • Better Insights
  • Higher Quality
  • Superior Convenience
  • Unmatched Usability
  • Unparalleled Reproducibility
Register to Explore Advaita’s Platform with Demo Data

Get Started!

Get in touch with Advaita to learn how our software will accelerate the work of your Core Facility or Research Lab.


About the Author: Richard McEachin

Dr. McEachin joins Advaita Bioinformatics in the dual role of Senior Scientist and COO. His efforts are devoted to leadership of the team of Advaita professionals, continued development of Advaita products, customer service, and day-to-day management of operations. He has more than 25 years of data analysis experience, including 15 years in bioinformatics and 10 years in operations research. Prior to joining Advaita, Dr. McEachin served for 4 years as Managing Director of the University of Michigan’s bioinformatics core. His education includes a PhD in Human Genetics and an MS in Biostatistics, both from the University of Michigan. In addition to his work at Advaita, Dr. McEachin serves as an Adjunct Assistant Professor of Biostatistics at the University of Michigan. He also volunteers for the Galactosemia Foundation and Buddy-to-Buddy.