Evolution of Plant Secondary Metabolites

Kliebenstein Lab

UC Davis Plant Sciences

Network Analysis of Complex Traits

Numerous important plant traits are controlled by genes that act quantitatively (QTL). We are attempting to develop rapid techniques to allow for the identification of these genes. This involves looking at the relationship between QTL that control gene expression, metabolite accumulation and pathogen resistance.

Project Summary

· Most traits are quantitatively controlled.

· Gene expression can be modeled as networks.

· These gene networks are only partially predictive of the resulting phenotypic variation.

· It is possible to link gene expression to metabolite accumulation to disease resistance using QTL.

Most agriculturally important plant traits, height, yield, shape, resistance, etc., are controlled by genes with quantitative impacts on a given phenotype, Quantitative Trait Loci (QTL). These genes however are considered difficult to identify and little is known about the genes that control them. Using replicated experimental design, we have cloned a large number of QTL controlling glucosinolate biosynthesis and hydrolysis and shown that by-in-large they are controlled be variable gene expression.


Recent work has begun to shift the methodology for QTL analysis towards genome wide association mapping. We have utilized this with a variety of metabolites and shown that there are significant false positive and negative issues with GWA. To solve this problem, we have developed novel network based approaches to increase our level of true positives. This has reached an 80% success rate in identifying and validating causal genes controlling natural variation in plant metabolism.


Interestingly, this work is beginning to identify unexpected connections between plant metabolism and physiology that function at the gene expression regulatory level.

Shape of different Arabidopsis “Wild-types”.

To contact us:

Phone: 530-754-7775
Fax: 530-752-9569

Text Box: Sample Publication:
Chan, E.K.F., Rowe, H.C., Corwin, J.A. Joseph, B. and  D.J. Kliebenstein. (In Press) “Combining genome-wide association mapping and transcriptional networks to identify novel genes controlling glucosinolates in Arabidopsis thaliana”. PLoS Biology v(i)pp-pp.
Chan, E.K.F., Rowe, H.C., Hansen, B.G, and  Kliebenstein, D.J. (2010) “The complex genetic architecture of the metabolome”. PLoS Genetics 6(11)e1001198. (Pubmed link)
Kliebenstein, D.J.  (2009) “Advancing genetic theory and application by metabolic QTL analysis.” Plant Cell v(i)pp-pp. (Direct Link)