TECHNIQUE ALLOWS RESEARCHERS TO IDENTIFY KEY MAIZE GENES FOR INCREASED YIELD
Scientists have identified the genes related to leaf angle in corn (maize) -- a key trait for planting crops closer together, which has led to an eight-fold increase in yield since the early 1900s.

The study, led by researchers from Cornell and the U.S. Department of Agriculture -- Agricultural Research Service (USDA-ARS) at Cornell and North Carolina State University, is the first to relate genetic variation across the entire maize genome to traits in a genomewide association study. The researchers have so far located 1.6 million sites on the maize genome where one individual may vary from another, and they used those sites to identify the genes related to changes in leaf angle that have allowed greater crop density.
Yield increases have mostly resulted from adaptations made by breeders to maize so crops can be planted closer together. Along with changes in roots and nutrient uptake that also play roles in increased crop densities, the leaves of maize crop plants have become more upright to maintain access to sunlight in crowded plots.
The team of researchers found that natural mutations in genes that affect ligules -- the first thick part of the leaf where it wraps around the stalk -- contributed to more upright leaves. Also, the changes in leaf angle result from many small genetic effects added together; while leaf angles may vary from one maize variety to another by up to 80 degrees, the biggest effect from a single gene was only 1.5 degrees.
"Although each gene and variant has a small effect, we can make very accurate predictions," said Ed Buckler, the paper's senior author, a USDA-ARS research geneticist in Cornell's Institute for Genomic Diversity and a Cornell adjunct associate professor of plant breeding and genetics. Lead authors include Feng Tian, a postdoctoral researcher in Buckler's lab, and Peter Bradbury, a computational biologist with the USDA-ARS in Ithaca.
The genomewide association study method allows researchers to examine a corn plant's genome and predict a trait with 80 percent accuracy. This would be analogous to predicting the height of a person by sequencing and analyzing their genes, or genotyping a seed to predict traits of the plant, said Buckler. The methodology may be applied to other traits, crops and species, including animals.
"This method will allow the intelligent design of maize around the world for high-density planting, higher yields and disease resistance," said Buckler.
In this study, the researchers had the advantage of making controlled crosses in maize plants to capture a great deal of genetic variation in the population of maize they studied, something that cannot be done when studying human genetics. The study offers proof that variation in traits is the sum of many small effects in genes, a hypothesis that has also been proposed by some human geneticists.
Also in the Jan. 9 online issue of Nature Genetics, a companion paper by the same research team, but led by those at USDA-ARS and North Carolina State University, used the same technique to identify key genes associated with southern leaf blight in maize. The study was funded by the National Science Foundation and USDA-ARS. James Holland, a researcher at USDA-ARS and North Carolina State University, is also a senior co-author of the study.

Journal Reference:
Feng Tian, Peter J Bradbury, Patrick J Brown, Hsiaoyi Hung, Qi Sun, Sherry Flint-Garcia, Torbert R Rocheford, Michael D McMullen, James B Holland, Edward S Buckler. Genome-wide association study of leaf architecture in the maize nested association mapping population. Nature Genetics, 2011; DOI: 10.1038/ng.746

Cornell University (2011, January 11). Technique allows researchers to identify key maize genes for increased yield. ScienceDaily. Retrieved January 12, 2011, from http://www.sciencedaily.com­ /releases/2011/01/110111171847.htm