The National Science Foundation has awarded a $3.75 million grant to a team of New York research and educational institutions to further develop BigPlant v1.0. This new computational tool enables the analysis of all currently sequenced plant genomes within a phylogenetic framework--that is, according to their evolutionary history. The aim is to further develop and mine the BigPlant v1.0 data matrix to discover the genes that evolved to give rise to important economic traits, such as the development of seeds.
This project combines the expertise of scientists from four New York area research and educational institutions specializing in evolution and genomics, building upon resources developed during a previous round of NSF Plant Genome funding of this project.
The principal investigators on the five-year grant are: Gloria Coruzzi, professor at NYU’s Center for Genomics and Systems Biology; Robert DeSalle, curator at the Sackler Institute for Comparative Genomics at the American Museum Natural History (AMNH); Dennis Stevenson, vice president for laboratory research at the New York Botanical Garden; W. Richard McCombie and Rob Martienssen, professors at Cold Spring Harbor Laboratory; and Dennis Shasha, a professor at NYU’s Courant Institute of Mathematical Sciences.
Using the sequences of all currently sequenced plant genomes, the collaborating scientists generated a computer-based phylogenetic tree called BigPlant v1.0, which was constructed using 22,833 sets of genes from each of 150 plant species covering all the major groups of seed plants. This matrix will now be used in machine-learning approaches, to make trait-to-gene predictions to identify the genes responsible for the evolution of economic seed traits. It is envisioned that the data and software resources generated in BigPlant v1.0 will empower the entire community of Plant Genomic researchers to exploit plant diversity to identify genes associated with any trait of interest or economic value.
The project’s goal is to use the genomic diversity of plants in order to discover new genes involved in the development of seeds.
Under the new NSF Plant Genome grant, the researchers aim to make predictions concerning the genes that caused the evolution of specific traits in plants. To do this, they will generate data, resources, and tools to enable functional trait-to-gene predictions for a variety of plant species.
The project will rely on bioinformatics—the use of algorithms as well as computational and statistical techniques to conduct research in biology—in achieving these aims.
The researchers anticipate that the data and software resources generated under the project will empower other comparative genomic researchers to exploit plant diversity to identify genes associated with any trait of interest or agronomic value.
The public can access data and resources generated from this NSF Plant Genome project through the website of the NY Plant Genome Consortium by clicking here.
Kristin Elise Phillips