2012 Annual Report
1a.Objectives (from AD-416):
Objective 1: Identify and evaluate genes important for agronomic performance (e.g., symbiosis/nitrogen fixation, nutrient uptake and utilization, yield, composition, etc.).
Objective 2: Identify and evaluate genes useful for legume defense against pathogens, e.g., Asian Soybean Rust.
Objective 3: Conduct comparative analyses of legume genes and genomes to place agronomically important genes in evolutionary and genome sequence context.
1b.Approach (from AD-416):
The project will define and characterize the organization and structure of the soybean genome and the genomes of other legumes with special emphasis on genes and gene families that underlie important agronomic and developmental traits. Hydroponics and global gene expression tools will be used to identify genes differentially expressed during iron stress conditions. Affymetrix GeneChips will be used to identify genes involved in yield, seed composition and other important traits in soybean. Bioinformatics will be used to position these genes on the whole genome sequence and the genetic map. Bioinformatic and experimental approaches will be used to identify and map genes differentially expressed during defense response and to identify and map defensin-like genes. A set of comparative molecular-evolutionary protocols will be used to make systematic and integrated use of large amounts of new genomic and functional data. Analyses will include comparison of homeologous regions, phylogenetic comparisons, and annotation of specific genomic regions.
Ames researchers have combined Virus Induced Gene Silencing (VIGS) with microarray technologies to identify genes involved in resistance to Asian Soybean Rust (ASR). We compared gene expression in resistant silenced and mock-silenced plants infected with Phakopsora pachyrhizi (the causal agent of ASR). While these plants were genetically identical, they differed in the expression of the VIGS target gene and other dependent downstream genes. This approach allowed us to identify hundreds of genes in the Rpp2 and Rpp4 signaling pathways. Understanding how these signaling pathways function will help us understand how resistance occurs and how novel resistance specificities may be generated.
Collaborating with Iowa State University (ISU) scientists, we have identified a gene we believe confers tolerance to Iron Deficiency Chlorosis (IDC) in soybean. Our previous microarrays comparing iron efficient and inefficient genotypes suggested the regulation of DNA replication was an important response to iron stress in the iron efficient genotype. In fact, a homolog replication protein A subunit 3 (RPA3), was the most differentially expressed gene found in our microarray experiment. Using VIGS, we silenced RPA3 in the iron inefficient genotype to mirror expression found in the efficient genotype. This resulted in decreased IDC symptoms and greater chlorophyll content. By mining microarray and RNAseq data, we have demonstrated that the regulation of growth is a specific response to iron stress found only in the iron efficient genotype. We are in the process of defining how this response is regulated in order to develop molecular markers that could be used by breeders to select for IDC tolerance.
More than four thousand three hundred distinct homogeneous domains were identified in the soybean genome. Three hundred thirty-one were statistically classified into Large Homogeneous Genome Regions (LHGRs). These were further categorized into four families based upon Guanine-Cytosine (G-C) content. An analysis of the gene ontology terms of genes located in these regions identified an over abundance of genes involved in the Krebs Cycle. Another analysis of the genome sequence of soybean identified 12 evolutionarily related regions derived from three polyploidy events. Genes within these homoeologous regions were examined. It was determined that genes in networks with a high degree of connectivity are more strongly conserved than those with low connectivity. It was proposed that the connectivity of genes in important pathways may explain why they were conserved over more than 100 million years of evolution. Fine mapping of a iron deficiency Quantitative trait loci (QTL) region accompanied by refinement of NILs for the QTL region and RNASeq analysis of the genes within the QTL under iron stressed and non-stressed conditions identified a transcription factor that is known to control the expression of an iron reductase and an iron transporter. This is the first identification of the causative gene for a soybean QTL.
Identification of a gene affecting iron efficiency in soybean. Millions of dollars in lost production in crops is caused each year by iron deficiency. The genetic cause of iron 'efficiency' is complex and is thought to be controlled by many genes. The location of these genes is in regions called Quantitative Trait Locus (QTL). ARS scientists at Ames, Iowa identified one of these QTLs and genetically dissected it to find which genes are differentially activated between iron efficient soybean and iron inefficient soybean. Further analysis narrowed the probable region of the causative gene(s) to a very small region of DNA referred to as a transcription factor, which may convert iron in the soil to a usable form and transport it into the plant root. This finding may make it possible for breeders to make knowledgeable selections for iron efficient breeding lines without the need for expensive and time-consuming field trials. This may allow faster development of more iron efficient cultivars and the subsequent savings of many millions of dollars in lost production for producers.
Analysis of the resistance to Asian Soybean Rust (ASR). The fungus Phakopsora pachyrhizi causes ASR, a serious foliar disease of soybean. Thus far, only six sources of resistance have been identified. ARS researchers in Ames, IA, in collaboration with scientists from Iowa State University, have characterized a promising resistance pathway (the Rpp3 gene-mediated ASR resistance pathway). The researchers compared resistant and susceptible soybean genotypes infected with P. pachyrhizi at six time points covering a 288-hour time course, tracking disease progression and plant defense responses. Using this approach, they were able to identify thousands of differentially activated genes and correlate Rpp3-mediated defense with disease progression. These results identify a gene network of soybean-ASR interactions that will help in finding novel sources of resistance.
Characterization of chromosome landmarks in soybean. As more genomes of higher organisms are completely sequenced and assembled, the next challenge is understanding how genome segments affect biological function. ARS researchers at Ames, IA examined the genome sequence of soybean, an important protein and oilseed crop in the U.S. and identified over 4,000 distinct domains. Three hundred thirty-one of them were identified as Large Homogeneous Genome Regions (LHGRs). Using mathematics and statistics they broke these LHGRs down into four distinctive families. The most common gene classes found in LHGRs were involved in energy processes. This finding identifies a fundamental feature of soybean, and perhaps general plant, genome organization and assigns a possible function. This information is important for targeting regions for genetic improvement to increase energy efficiency and crop production efficiency.
Ha, J., Abernathy, B., Nelson, W., Grant, D.M., Wu, X., Nguyen, H., Stacey, G., Wing, R., Shoemaker, R.C., Jackson, S. 2012. Integration of the draft sequence and physical map as a framework for genomic research in soybean (Glycine max (L.) Merr.) and wild soybean (Glycine soja Sieb. and Zucc.). Genes, Genomes, Genetics. 2(3):321-329.
Jackson, S.A., Lee, S., Schmutz, J., Shoemaker, R.C. 2011. Sequencing crop genomes: approaches and applications. New Phytologist. 191:915-925.
Morales, A., Borem, A., Graham, M.A., Abelnoor, R. 2012. Advances on molecular studies of the interaction soybean - Asian rust. Crop Breeding and Applied Biotechnology. 12:1-7.
Liu, J., Horstman, H.D., Braun, E., Graham, M.A., Zhang, C., Navarre, D., Lee, Y., Nettleton, D., Hill, J.H., Whitham, S.A. 2011. Soybean homologs of MPK4 negatively regulate defense responses and positively regulate growth and development. Journal of Plant Physiology. 157(3):2363-1378.
Severin, A.J., Cannon, S.B., Graham, M.A., Grant, D.M., Shoemaker, R.C. 2011. Changes in twelve conserved soybean genomic regions following three rounds of polyploidy. The Plant Cell. 23(9):3129-3136.
Schneider, K.T., Van De Mortel, M., Bancroft, T.J., Nelson, R., Nettleton, D., Braun, E., Frederick, R.D., Baum, T.J., Graham, M.A., Whitham, S.A. 2011. Biphasic gene expression changes elicited by Phakopsora pachyrhizi in soybean correlates with fungal penetration and haustoria formation. Plant Physiology. 157:355-371.
Peiffer, G.A., King, K.E., Severin, A.J., May, G.D., Cianzio, S.R., Lin, S., Lauter, N.C., Shoemaker, R.C. 2012. Identification of candidate genes underlying an iron efficiency QTL in soybean. Plant Physiology. 158(4):1745-1754.
Woody, J.L., Shoemaker, R.C. 2011. Gene Expression: Sizing it all up. Frontiers in Plant Genetics and Genomics. 2:70.
Woody, J.L., Beavis, W., Shoemaker, R.C. 2012. Large homogeneous genome regions (Isochores) in soybean (Glycine max (L.) Merr.). Frontiers in Plant Genetics and Genomics. 3:98 DOI:10.3389/fgene.2012.00098.
Wiebbecke, C.E., Graham, M.A., Cianzio, S.R., Palmer, R.G. 2012. Day temperature influences the male-sterile locus in soybean. Crop Science. 52(4):1503-1510.
Brace, R.C., Fehr, W.R., Graham, M.A. 2012. Inheritance and molecular mapping of an allele providing resistance to Cowpea mild mottle virus-like symptoms in soybean. Crop Science. 52(5):2109-2114.