ECA-PGR: Regulatory variation controlling architectural diversity in maize

Donald Danforth Plant Science Center, Saint Louis MO

Investigators

Abstract

Plant architecture, the number and arrangement of organs (e.g. branches, leaves, flowers) on a plant, is central to crop productivity and has been a primary target in domestication and improvement of many crops. Maize is a cereal crop with the highest dollar value in the U.S. and abroad. Maize yields have increased eight-fold in the past century due largely to selecting for optimal architecture at increased planting densities. However, yield gains have significantly diminished in recent years. This reduction requires the acquisition of new knowledge about complex gene networks that control plant architecture, which could be applied to breeding and engineering better maize varieties. In maize, genes that control leaf angle also affect panicle architecture. Breeding for upright leaves allows light capture within the lower canopy in dense fields, while optimizing the structure of the grain-bearing panicle improves seed set, grain fill, and harvestability. The major goal of this project is to develop the ability to manipulate target traits without disrupting other aspects of growth and development that may negatively impact yield. This goal will be accomplished through an integrated approach that will define the gene networks that control these traits, and map the location of key regulatory genes on maize chromosomes. This information will be used for genetic manipulation of optimal plant architectures that will lead to increased yields. This project will educate high school and rural community college teachers in concepts of quantitative genetics and genomics, and will also provide an interactive curriculum for their classrooms. Pleiotropy is the effect a gene has on multiple phenotypic characters, and it represents a major force that shapes and constrains biological evolution. A well-established principle of developmental evolution is that genes are reused in different developmental processes leading to pleiotropic effects. The importance of cis-regulatory elements for adaptive evolution is thought to result from their reduced pleiotropy relative to protein-coding variants. Thus, the ability to manipulate cis-regulatory elements at functionally conserved pleiotropic loci would allow greater precision for engineering and/or breeding of optimal crop ideotypes. Several lines of evidence in maize suggest a common gene regulatory network functions at the boundaries of distinct lateral organs and contributes to pleiotropy between leaf angle and tassel branch number, two important agronomic traits. This proposal aims to uncover genetic variation in pleiotropic loci and determine how that variation mediates phenotypic effects in these traits. First, context-specific multi-omics datasets will be integrated to define core regulatory modules that function at lateral organ boundaries, and promote development of morphologically distinct organs in maize. Second, quantitative approaches that leverage maize diversity will be used to explore allelic variation in these modules and how it translates to phenotype. Finally, hypotheses on function of cis-regulatory variants controlling pleiotropic loci will be tested using functional genomics approaches, including genome editing. These integrated analyses will define regulatory loci that control architectural variation across maize diversity, which can be leveraged for targeted crop improvement. New methods for incorporating biological network information in genomic selection models to predict phenotype from genotype will be explored.