Award Abstract #0723510
Collaborative Research: An Arabidopsis Polymorphism Database

NSF Org:	DEB Division of Environmental Biology
Initial Amendment Date:	June 12, 2008
Latest Amendment Date:	July 28, 2008
Award Number:	0723510
Award Instrument:	Standard Grant
Program Manager:	Nancy J. Huntly DEB Division of Environmental Biology BIO Directorate for Biological Sciences
Start Date:	June 15, 2008
Expires:	May 31, 2011 (Estimated)
Awarded Amount to Date:	$770222
Investigator(s):	Doreen Ware ware@cshl.edu (Principal Investigator) Lincoln Stein (Former Principal Investigator) Doreen Ware (Former Co-Principal Investigator)
Sponsor:	Cold Spring Harbor Laboratory 1 BUNGTOWN ROAD COLD SPRING HARBOR, NY 11724 516/367-8307
NSF Program(s):	THE 2010 PROJECT
Field Application(s):
Program Reference Code(s):	EGCH, 9169, 1684, 1174
Program Element Code(s):	1684

ABSTRACT

Abstract

This project will to generate a community resource for Arabidopsis genetics by integrating several new data sets with the existing A. thaliana genome sequence and those of two closely related species, A. lyrata and Capsella rubella. These data will make it possible to answer fundamental questions about the evolution of A. thaliana, and will facilitate the interpretation of the existing genome sequence. It is analogous to similar efforts to understand human variation and evolution by integrating vast amounts of human polymorphism data with genome sequences from closely related primates like chimpanzee and orangutan. This project will provide a tool for making sense of genetic variation. Understanding how genotypic variation translates into phenotypic variation and how it is structured in populations is fundamental to our understanding of evolution, and has enormous practical implications for human health as well as for plant and animal breeding. The project will also provide training opportunities in bioinformatics and computational biology for multiple students at different levels, areas where there is a nationally recognized shortage of biology students with the requisite quantitative skills.

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