Plant Sciences Commons^™

The Pho1;2a'-M1.1 Allele Of Phosphate1 Conditions Misregulation Of The Phosphorus Starvation Response In Maize (Zea Mays Ssp. Mays L.), Ana Laura Alonso-Nieves, M. Nancy Salazar-Vidal, J. Vladimir Torres-Rodríguez, Leonardo M. Pérez-Vázquez, Julio A. Massange-Sánchez, C. Stewart Gillmor, Ruairidh J. H. Sawers

Center for Plant Science Innovation: Faculty and Staff Publications

Plant PHO1 proteins play a central role in the translocation and sensing of inorganic phosphate. The maize (Zea mays ssp. mays) genome encodes two co-orthologs of the Arabidopsis PHO1 gene, designated ZmPho1;2a and ZmPho1;2b. Here, we report the characterization of the transposon footprint allele Zmpho1;2a'-m1.1, which we refer to hereafter as pho1;2a. The pho1;2a allele is a stable derivative formed by excision of an Activator transposable element from the ZmPho1;2a gene. The pho1;2a allele contains an 8-bp insertion at the point of transposon excision that disrupts the reading frame and is predicted to …

Association Mapping Across A Multitude Of Traits Collected In Diverse Environments In Maize, Ravi V. Mural, Guangchao Sun, Marcin Grzybowski, Michael C. Tross, Hongyu Jin, Christine Smith, Linsey Newton, Carson M. Andorf, Margaret R. Woodhouse, Addie M. Thompson, Brandi Sigmon, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 …

Hyperspectral Reflectance-Based Phenotyping For Quantitative Genetics In Crops: Progress And Challenges, Marcin Grzybowski, Kuwan K. Wijewardane, Abbas Atefi, Yufeng Ge, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

Many biochemical and physiological properties of plants that are of interest to breeders and geneticists have extremely low throughput and/or can only be measured destructively. This has limited the use of information on natural variation in nutrient and metabolite abundance, as well as photosynthetic capacity in quantitative genetic contexts where it is necessary to collect data from hundreds or thousands of plants. A number of recent studies have demonstrated the potential to estimate many of these traits from hyperspectral reflectance data, primarily in ecophysiological contexts. Here, we summarize recent advances in the use of hyperspectral reflectance data for plant phenotyping, …

72-H Diurnal Rna-Seq Analysis Of Fully Expanded Third Leaves From Maize, Sorghum, And Foxtail Millet At 3-H Resolution, Xianjun Lai, Claire Bendix, Yan Zhang, James Schnable, Frank G. Harmon

Center for Plant Science Innovation: Faculty and Staff Publications

Objectives: The purpose of this data set is to capture the complete diurnal (i.e., daily) transcriptome of fully expanded third leaves from the C4 panacoid grasses sorghum (Sorghum bicolor), maize (Zea mays), and foxtail millet (Setaria italica) with RNA-seq transcriptome profiling. These data are the cornerstone of a larger project that examined the conservation and divergence of gene expression networks within these crop plants. This data set focuses on tem- poral changes in gene expression to identify the network architecture responsible for daily regulation of plant growth and metabolic activities. The power of this data set is fine temporal resolution …

Leaf Angle Extractor: A High-Throughput Image Processing Framework For Leaf Angle Measurements In Maize And Sorghum, Sunil Kumar Kenchanmane Raju, Miles Adkins, Alex Enersen, Daniel Santana De Carvalho, Anthony J. Studer, Baskar Ganapathysubramanian, Patrick S. Schnable, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

PREMISE: Maize yields have significantly increased over the past half-century owing to advances in breeding and agronomic practices. Plants have been grown in increasingly higher densities due to changes in plant architecture resulting in plants with more upright leaves, which allows more efficient light interception for photosynthesis. Natural variation for leaf angle has been identified in maize and sorghum using multiple mapping populations. However, conventional phenotyping techniques for leaf angle are low throughput and labor intensive, and therefore hinder a mechanistic understanding of how the leaf angle of individual leaves changes over time in response to the environment.

METHODS …

Conventional And Hyperspectral Time-Series Imaging Of Maize Lines Widely Used In Field Trials, Zhikai Liang, Piyush Pandey, Vincent Stoerger, Yuhang Xu, Yumou Qiu, Yufeng Ge, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

Background: Maize (Zea mays ssp. mays) is 1 of 3 crops, along with rice and wheat, responsible for more than one-half of all calories consumed around the world. Increasing the yield and stress tolerance of these crops is essential to meet the growing need for food. The cost and speed of plant phenotyping are currently the largest constraints on plant breeding efforts. Datasets linking new types of high-throughput phenotyping data collected from plants to the performance of the same genotypes under agronomic conditions across a wide range of environments are essential for developing new statistical approaches and computer …