GEPR: Genome-Wide Analysis of Root Traits

NSF Award Abstract #0209754

Intellectual merit:

The long-term goal of this project is to use genomic approaches to identify the genes that control the branching patterns of crop roots. How roots branch in soil is known as the plant’s “root system architecture” and it varies dramatically from plant to plant. These differences are known to impact the plant’s ability to acquire water and nutrients. Since many plants have to deal with environments in which nutrients and water are limiting, the root system architecture is a central feature of how plants adapt to their environment. A better understanding of root system architecture addresses two of the major challenges confronting plant biology – how to feed a burgeoning world population in a sustainable manner and how to cope with global climate change. Poor soil fertility and environmental stress suppress crop yields in many parts of the world, and many models predict these stresses will increase in coming decades. Intensive irrigation and fertilization are not environmentally sustainable, nor economically viable in most developing countries. Thus, identifying the genes that underlie root system architecture could have a profound significance for agriculture and world food security. Surprisingly, little is known about the individual traits that comprise root system architecture. There are two principal issues that have restricted the understanding of the genetic basis of root system architecture: 1) the lack of cost-effective methods for non-invasively imaging growing roots and 2) the lack of adequate means of describing the complex spatial structure of root system architecture. Two non-invasive imaging technologies will be used in this project to acquire images of growing rice and maize roots under different environmental conditions. Response of root systems will be compared to responses when grown in soil under similar conditions. Mathematical approaches to describing growing root systems and simulations for comparing different root system architectures will be developed. Quantitative trait loci (QTL) for root architecture traits will be identified using special populations of rice and maize and efforts will be initiated toward isolating genes of significance to plant breeding.

Broader impacts:

Because the nature of this research is inherently interdisciplinary, training at various levels (undergraduate, graduate, post-doctoral) will integrate quantitative approaches with applications to experimental biology. A course will be developed in collaboration with faculty at North Carolina Central University (NCCU) that focuses on understanding complex genetic traits. NCCU is a historically black university (HBCU) located 5 miles from the Duke campus. The course will use examples from plants as well as human disease to inform and educate undergraduates as to the issues involved in analyzing complex genetic traits and the cutting edge technologies and computational approaches now available for identifying the genes responsible for these traits. For qualified students who have taken this course, research internships will be provided. To disseminate the results from this project a website will be developed to describe methods and results of interest to researchers and breeders.

PIs : Philip Benfey (Duke – Biology), John Harer (Duke – Mathematics), Jonathan Lynch (Penn State – Horticulture), Joshua Weitz (Georgia Tech – Biology); Senior Personnel: Herbert Edelsbrunner (Duke – Computer Science), Leon Kochian (Cornell-USDA), Daniel Williams (North Carolina Central University – Biology)

Contact:
philip.benfey@duke.edu

Last updated: February 17, 2009