2012 Annual Report
1a.Objectives (from AD-416):
Objective 1: Determine if altering expression of genes that exhibit evidence of past selection during maize domestication and improvement, modifies the expression of currently relevant agronomic traits.
Objective 2: Develop strategies and mechanisms for improving drought-stress tolerance of maize.
Objective 3: Conduct an analysis of the role of transcription factors in controlling agronomic traits in maize.
Objective 4: Integrate new maize genetic and genomic data into the database (MaizeGDB).
1b.Approach (from AD-416):
Identify and verify selected genes. Make teosinte NIL and use to characterize phenotypic effect of teosinte alleles of selected genes. Identify genes central to drought-tolerance in plants for maize improvement. Use transgenic maize line to test candidate genes for drought tolerance. Identify transcription factors exhibiting specific transcription responses to drought treatments. Analysis the role of MYB transcription factors in controlling agronomic trait expression.
Progress of this aspect of the research addresses the application of genetics and genomics for the improvement of agronomic traits in maize (NP 301 Component 4, problem statement 4A). We evaluated our teosinte near isogenic lines (NILs) to identify genes underlying agronomic traits and to compare the allelic variation of teosinte to that of inbreds, which relates to Objective 1. We focused on kernel row number (KRN) and kernel weight (KWT). We identified a very large effect quantitative trait loci (QTL) for KRN on chromosome 2, where one of the teosinte alleles is predicted to decrease row number by 4. We used a multiple location trial to validate the allelic effects, and initiated fine mapping populations to identify the underlying gene. A number of KWT QTL were identified for similar future work. We initiated an experiment to fine-map the major QTL for the synthesis of a major introgenous antibiotic compound (DIMBOA) located on the short arm of chromosome 4 to address Objective 3 (NP 301 Component 4, problem statement 4B). We chose the inbred line CI31A for the donor allele because it has very high levels of DIMBOA at mid-whorl stage. We developed a recombinant inbred population (RILs), genotyped them with 779 single nucleotid polymorphisms (SNPs), and confirmed the QTL clearly within the region of the bx gene cluster. We created 25 lines with recombinant chromosomes (RC) near and within the bx region, and selfed these plants in the greenhouse to generate families to identify plants homozygous for the RC. Phenotypic trials are ongoing. To further our ability to isolate genes that are directly involved in dehydration tolerance we completed a transcriptome analysis of root tissues of a desiccation tolerant grass at various stages during a dehydration event, which directly targets Objective 2 (NP 301 Component 4, problem statement 4A). To increase the power of our analysis we also developed a transcriptome profile for the desiccation sensitive sister species. These studies allowed the identification of several candidate genes that may play a role in dehydration tolerance. Ten of these candidate genes have been engineered for overexpression in a drought sensitive plant model. Testing of the transgenic plants under dehydrating conditions is underway. We completed a comprehensive analysis of maize root miRNA profiles in response to specific soil water deficits and identified the putative suppression of phosphate uptake as a possible outcome of drought. We added a new tool suite to decipher metabolic pathways associated with the B73 reference genome sequence. It relied on both predicted and experimentally confirmed pathway information and directly impacts Objective 4 and relates to NP 301 Component 2, problem statement 2A. This is a collaborative effort with researchers at Palo Alto CA, Ames IA, Corvallis OR and ARS. It provides a genome map view of genes for selected pathways that is expected to be highly useful in defining the best candidate genes for QTLs.
The genetic control of the response of maize to imposed drought. Droughts occurring in the U.S. and across the globe threaten food security and contribute to the growing problem of malnutrition and hunger. Understanding how plants respond to soil water deficits at the level of control of gene networks is key to developing strategies for crop improvement for drought tolerance. ARS scientists in Columbia, MO utilized a seedling system to expose maize to precise and quantifiable soil water deficits to elucidate which gene networks and gene control elements are directly induced by drought in specific tissues of the plant. They found that a large number of genetic control elements respond to specific levels of applied soil water deficits and that each tissue (leaves, root tips, main root tissue, etc.) had distinct patterns of gene activation or deactivation. These data also revealed the possibility that drought induced inhibition of phosphate uptake by inhibition of key regulatory genes may play an important role in limiting plant productivity under drought. The ability to focus attention to specific processes and gene regulatory processes will enable breeders to develop novel genetic strategies for improving drought tolerance in maize and will ultimately improve food security and address yield stability in a changing climate.
Phenotype and trait data integration into the MaizeGDB. Providing access to phenotype and trait data in the Maize Genome Database (MaizeGDB) is a critical aspect of the archiving of genetic information for researchers working on crop improvement for maize. The MaizeGDB scientists in Columbia, MO, integrated detailed phenotypic evaluations (descriptions of the plants at all levels from visual to biochemical) for 5000 lines of a mapping population that encompasses much of the variation for improved maize germplasm. These evaluations identify regions of the maize genome associated with over 150 traits of agronomic importance and were performed with other ARS researchers at Ithaca, NY and Raleigh, NC. The integration at MaizeGDB will allow researchers ready access to these data in standard and custom formats to test solutions for relating gene sequence to plant phenotypes and other resources for further investigation of candidate gene function. The informatics tools that are being developed to accommodate this data and relate it to other plant genetic databases will support breeding advances by assisting in identifying genes that would improve crop performance, quality and yield.
Genetic analysis of seed weight in maize. The maize kernel plays an essential role in human and animal nutrition around the world. An understanding of what genetic factors control yield in maize, one component of which is seed weight, is critical for continued maize crop yield increases to meet future food security needs of a growing global population. ARS scientists in Columbia, Missouri used a novel genetic approach that makes use of a newly developed genetic mapping population of maize lines, the Nested Association Mapping (NAM) population, to uncover the main genes that control kernel weight. Genetic analysis revealed 18 chromosomal regions within the genome of maize that control seed weight. Using a different genetic technique called genome-wide association (GWAS) mapping to breakdown seed weight into its components (starch, protein, and oil content) scientists were able to generate a list of candidate genes that contribute to seed weight, including those involved in sugar and starch metabolism. The results of this research point to promising gene targets for germplasm improvement that will benefit producers and consumers.
Cook, J.P., McMullen, M.D., Holland, J.B., Tian, F., Bradbury, P., Ross-Ibarra, J., Buckler IV, E.S., Flint-Garcia, S.A. 2012. Genetic architecture of maize kernel composition in the nested association mapping and inbred association panels. Plant Physiology. 158:824-834.
Santos, A., Oliver, M.J., Sanchez, A., Oliviera, M. 2011. Expression of almond KNOTTED1 homologue (PdKn1) anticipates adventitious shoot initiation. In Vitro Cellular and Developmental Biology - Plants. 48:40-49.
Harnsomburana, J., Green, J., Barb, A., Schaeffer, M.L., Vincent, L., Shyu, C. 2011. Computable visually observed phenotype ontological framework for plants. BMC Bioinformatics. 12:260. Available: http://www.biomedcentral.com/1471-2105/12/260.
Stark, L.R., Brinda, J.C., McLetchie, N.D., Oliver, M.J. 2012. Extended periods of hydration do not elicit dehardening to desiccation tolerance in regeneration trials of the moss Syntrichia caninervis. International Journal of Plant Science. 173(4):333-343.
Hung, H., Shannon, L.M., Tian, F., Bradbury, P., Chen, C., Flint Garcia, S.A., McMullen, M.D., Ware, D., Buckler IV, E.S., Doebley, J.F., Holland, J.B. 2012. ZmCCT and the genetic basis of day-length adaptation underlying the postdomestication spread of maize. Proceedings of the National Academy of Sciences. 109:E1913–E1921.
Hufford, M., Xu, X., Van Heerwaarden, J., Pyhajarvi, T., Chia, J., Cartwright, R., Elshire, R., Glaubitz, J., Guill, K.E., Kaeppler, S., Lai, J., Morrell, P., Shannon, L., Song, C., Springer, N., Swanson-Wagner, R., Tiffin, P., Wang, J., Zhang, G., Doebley, J., McMullen, M.D., Ware, D., Buckler IV, E.S., Yang, S., Ross-Ibarra, J. 2012. Comparative population genomics of maize domestication and improvement. Nature Genetics. 44:808-811. DOI: 10.1038/ng.2309.
Brown, P.J., Upadyayula, N., Mahone, G.S., Tian, F., Bradbury, P., Myles, S., Holland, J.B., Flint Garcia, S.A., McMullen, M.D., Buckler IV, E.S., Rocheford, T.R. 2011. Distinct genetic architectures for male and female inflorescence traits of maize. PLoS Genetics. 7(11):e1002383.
Chia, J., Song, C., Bradbury, P., Costich, D., De Leon, N., Doebley, J., Elshire, R., Gaut, B., Geller, L., Glaubitz, J., Gore, M.A., Guill, K., Holland, J., Hufford, M., Lai, J., Li, M., Liu, X., Lu, Y., McCombie, R., Nelson, R., Poland, J.A., Prasanna, B., Phyajarvi, T., Rong, T., Sekhon, R., Sun, Q., Tenaillon, M., Tian, F., Wang, J., Xu, X., Zhang, Z., Kaeppler, S.M., Ross-Ibarra, J., McMullen, M.D., Buckler IV, E.S., Zhang, G., Xu, Y., Ware, D. 2012. Maize HapMap2 identifies extant variation from a genome in flux. Nature Genetics. 40:803-807. DOI: 10.1038/ng.2313.
Hung, H., Browne, C.J., Guill, K.E., Coles, N., Eller, M., Garcia, A., Lepak, N.K., Melia-Hancock, S., Oropeza-Rosas, M., Salvo, S., Upadyayula, N., Buckler IV, E.S., Flint Garcia, S.A., Mcmullen, M.D., Rocheford, T., Holland, J.B. 2012. The relationship between parental genetic or phenotypic divergence and progeny variation in the maize nested association mapping population. Heredity. 108:490-499.
Cannon, E.K., Birkett, S.M., Braun, B.L., Kodavali, S., Jennewein, D.M., Yilmaz, A., Antonescu, V., Antonescu, C., Harper, E.C., Gardiner, J.M., Schaeffer, M.L., Campbell, D.A., Andorf, C.M., Andorf, D., Lisch, D., Koch, K.K., McCarty, D.R., Quackenbush, J., Grotewold, E., Lushbough, C.M., Sen, T.Z., Lawrence, C.J. 2011. POPcorn: An online resource providing access to distributed and diverse maize project data. International Journal of Plant Genomics. 2011:Article 923035. Available http://www.hindawi.com/journals/ijpg/2011/923035.