Features

Chris Topp, Ph.D.

Chris’s current research interests are subterranean phenotyping and characterizing the environmental and genetic factors that condition root growth. As a postdoctoral scholar, he led the development of a high-throughput 3D root imaging and analysis pipeline, and applied it to map regions of the rice genome controlling root architecture. Long-term, he aims to understand of how genotype directs phenotype for agriculturally important traits.

Research Summary

The Topp Lab takes a phenomics approach to study crop root growth dynamics in response to environmental stress such as drought and rhizosphere competition, and as a consequence of artificial selection for agronomically important traits such as Nitrogen uptake. Studying roots requires the development of imaging technologies, computational infrastructure, and statistical methods that can capture and analyze morphologically complex networks over time and at high-throughput. Thus the lab combines expertise in imaging (optical, X-ray CT, PET, etc.), computational analysis, and quantitative genetics with molecular biology to understand root growth and physiology.

What is the genetic basis of root system architecture (RSA)?

automated_OPT_table

‘Root system architecture’ encompasses the spatial and temporal organization of roots in the growth medium, and thus greatly influences the resource capturing abilities of a plant. However, root architecture traits are notoriously difficult to measure due to the opacity of soil and a complex morphology that is environmentally sensitive. The Topp lab uses a semi-automated optical tomography (OPT) system to phenotype crop root systems in 3D as they grow in environmentally controlled conditions. By comparing different genotypes that were bred or naturally selected for different growth traits and combining with molecular analysis, we aim to identify genes that can help generate more stress resistant and sustainable crops. In one project, we are exploring the genetic basis of enhanced Nitrogen uptake. The Illinois High and Low Protein maize lines have been recurrently selected for over 100 years for high or low seed protein content; during this time the IHP lines have evolved enhanced Nitrogen scavenging abilities. We phenotyped the two lines with OPT to reveal major architectural differences, including lateral root density. Work is underway to identify the responsible genes  in a high-resolution mapping population using field and lab based phenotyping tools combined with ionomics.

How do roots communicate and distinguish self from non-self?

Roots exude an array of chemicals into the rhizosphere to modify the chemical composition of the soil, as well as to communicate with microbes and other root systems. The lab is interested in the nature of these exudates in root-root and root-microbe interactions, and their effects on plant health and productivity. In one project, we are comparing the effects of long-term adaptation to high planting density on maize root-root interactions. A primary factor driving the approximately 8-fold increase in US maize production over the past 80 years has been the ability of modern varieties to maintain high grain yields at increasing planting densities. The Topp lab has shown that density selected maize has a dampened inhibition to intraspecific root competition, likely through a change in roPET-OPTot exudations. We are combining transcriptome profiling (RNAseq), and OPT with PET, which can image the dynamics of carbon allocation in real time. In this way, we can identify transcriptional, morphological, and physiological responses to root competition in real time. In another project we have used OPT-PET to study the growth promoting properties of roots infected with different fungal isolates.

Fine scale dynamics: How is the growth of individual roots coordinated with the whole?

A fundamental question arises in the study of any biological network, “Is the network topology purely an emergent property of local patterns, or is there coordination at a higher level?” We ask the same question of root growth dynamics, and are investigating relationships between local root growth patterns, global architecture traits, and gene expression with high spatiotemporal resolution. Using an automated system that images roots 24/7, we are generating several dozen high-density time series data sets during approximately two weeks of maize root growth. With collaborators at the IST, the lab is using these data sets to map the growth rates, angles, curvatures, and branching patterns of each root back to their respective global architectures. They will then extend these analyses to functional studies of root growth response to nitrogen availability in the high and low protein lines, as well as response to neighboring roots in the historical versus modern maize material.

What is perenniality?

The perennial life form offers a number of desirable traits for agriculture, including rapid early season growth for increased biomass, and an established root system for increased stress resistance and growth in marginal soil by providing access to greater water and nutrient resources. Despite the fact that each major crop variety has a close perennial relative, little is known about the mechanisms that confer perenniality outside of a few studies that suggest a handful of major genes condition the trait. The Topp lab is applying subterannean phenomics methods to identifying the genes controlling perenniality in maize x teosinte (wild relative) and Sorghum bicolor x S.propinquum (wild relative) mapping populations.

Contact

Christopher Topp
Assistant Member
Danforth Center
975 N. Warson Rd.
St. Louis, MO 63132
(314) 587-1401
ctopp@danforthcenter.org

LinkedIn

Selected Publications

Topp, C.N., Iyer-Pascuzzi, A.S., Anderson, J.T., Lee, C.-R., Zurek, P.R., Symonova, O., Zheng, Y., Bucksch, A., Mileyko, Y., Galkovskyi, T., Moore, B.T., Harer, J., Edelsbrunner, H., Mitchell-Olds, T., Weitz, J.S., and Benfey, P.N. (2013). 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture. Proc Natl Acad Sci USA 110: E1695–704.

Galkovskyi T., Mileyko Y., Bucksch A., Moore B., Symonova O., Price C.A., Topp C.N., Iyer-Pascuzzi A.S., Zurek P.R., Fang S., Harer J., Benfey P.N., Weitz J.S. (2012) GiA Roots: software for the high throughput analysis of plant root system architecture. BMC Plant Biology, 12:116.

Topp, C.N., Benfey P.N. (2011). Growth Control of Root Architecture. In Plant Biotechnology and Agriculture: Prospects for the 21st Century. Eds. Altman, A. and Hasegawa, P.M.

Position Openings

General:
The Topp Lab is recruiting new team members at the undergraduate, technician, graduate, and postdoctoral levels. Applicants with backgrounds in Engineering, Computer Science, Statistics and an interest in learning Plant Biology, or a deep knowledge of plants and great enthusiasm for computation and building things are especially encouraged. We strive to push the limits of technology enabled science, learn something new each day, and have fun doing it! Contact Chris with a brief statement of background and interests.