New method pinpoints metabolic genes, boosts seed biofortification efforts
March 17, 2017
Seed crops, like rice and corn, are consumed in great amounts worldwide but are poor sources of protein, making them ideal targets for biofortification efforts. Unfortunately, attempts to alter the pool of free amino acids (protein composition) in seeds generally result in either yield and/or growth penalties or no change in the total amino acids of the plant seeds. This dilemma has made identifying the genes that underlie this complex metabolic trait a priority for scientists. In a new study out in Plant Physiology, MU biologist Ruthie Angelovici reports on a new experimental approach that is aiding in the rapid discovery of these genes.
In the study, Angelovici and her colleagues investigated associations between the phenotypic variation of the seed free amino acid (measured as ratios of free amino acids) and the natural variation in DNA across a large population of Arabidopsis plants. The authors used two approaches to derive the free amino acids traits: one based on known metabolic pathways and a second, newer approach based on an analysis of metabolic pathways. They then performed a genome-wide association study, or GWAS, on the traits and compared the results. They found that a GWAS of traits derived from the network analysis identified associations missed in a GWAS of traits derived from known metabolic pathways.
Using the new approach, the authors identified two candidate genes responsible for the natural variation in traits associated with the amino acid histidine. Using a reverse genetic approach, they discovered that one of the genes, CAT4, is responsible for the natural variation of histidine-related traits across the association panel. The authors propose that equivalent genes to CAT4 in crop species may be excellent targets for biofortification efforts.
Angelovici is an assistant professor of biological sciences in the College of Arts and Science. She initiated the research as part of her postdoctoral work with Dean Della Penna at Michigan State University and concluded it in her new lab in the Christopher Bond Life Sciences Center.
Read the study: R. A. Angelovici, A. Batushansky, N. Deason, S Gonzalez-Jorge, M. A. Gore, A. Fait, D DellaPenna. Network-guided GWAS improves identification of genes affecting free amino acids. Plant Physiology 2017, 173(1): 872-886. DOI:10.1104/pp.16.01287
News by research strength
- Cell Biology
- Genetics & Genomics
- Molecular Biology
- Plant Biology
- Quantitative & Computational Biology