CS Professor Patro’s Genomic Research with Cambridge University Receives NSF Funding


Robert Patro, an Assistant Professor in the Department of Computer Science, has received NSF funding to collaborate on a high-level genomic project with Julian Hibberd and Richard Smith-Unna of Cambridge University. The award, which totals over $300k for Stony Brook University, will be given over two years for the formally titled project, Data-Driven Hierarchical Analysis of De Novo Transcriptomes.

Patro’s research focuses on fundamental issues in functional genomics, the area of molecular biology which studies mechanisms, such as gene expression, which enable essentially fixed genomes to give rise to varied and dynamic biological behavior. Although genome sequencing has simplified the analysis of gene expression in certain cases, much work remains to be done; as Dr. Patro notes in a summary of the project:

"Recent advances in sequencing technology have revolutionized our ability to study how gene expression changes across different conditions, in different developmental stages, and between different tissues (including diseased versus healthy tissues).  However, scientists often wish to measure gene expression in organisms for which a reliable reference genome is not available; this is known as de novo transcriptome analysis.  In fact, we have not assembled the genomes for the overwhelming majority of organisms in which we may be interested in studying gene expression”


For this project, which begins in July 2016, Patro and fellow researchers at Cambridge University will develop novel methods and an integrated set of tools for the analysis of de novo transcriptomes.  These tools will be based on new mathematical models and algorithms, and will be aimed at closing the gap between reference-based and de novo analysis of gene expression. The new methods will be able to identify and correct a host of errors in the predicted (assembled) transcripts, which, in turn, will improve estimates of gene expression.

Crucially, the methods developed in this project will estimate and incorporate measures of statistical uncertainty and biological variability at each stage of transcriptome analysis. The developed tools will be applied to the study of C4 photosynthesis — a highly efficient form of photosynthesis whose underlying genetic mechanisms are still not fully understood.

Portions of the project related to C4-photosynthesis analysis will be led by Cambridge University’s researchers Hibberd and Smith-Unna from the Department of Plant Sciences. Cambridge’s portion of the research totals over $235,000 (U.S.) in funding and their team will focus on understanding the genetic mechanism underlying this trait.  Specifically, using the tools developed in this project, they will design a system for prioritizing candidate regulatory elements for C4 engineering, and will further test the hypothesis that a common mutational event (i.e. a “master switch”) underlies the many independent C4 systems observed in nature.

Committed to sharing the project's scientific outcomes, individuals are encouraged to follow the project’s progress, including the relevant software being developed, by visiting the .

About the Researchers:

earned a PhD from the University of Maryland, College Park. Before joining Stony Brook in 2014, he was a post-doctoral research associate in Carnegie Mellon University's Department of Computational Biology, in the School of Computer Science. Patro’s primary areas of research include computational biology and bioinformatics, with a specific focus on the development of methods for high-throughput genomic analysis.   

Professor Julian Hibberd is the leader of the at Cambridge University. He primarily focuses on the genetic basis of traits that underlie components of crop productivity.

Richard Daniel Smith-Unna is a member of the Hibberd Lab, a Mozilla Fellow for Science and he previously worked as a software developer. With his lab colleagues, he is probing molecular control and evolution of C4 photosynthesis. He is particularly interested in how C4 may be engineered in rice, which is a C3 plant.