Source: UNIVERSITY OF NEBRASKA submitted to
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
Funding Source
Reporting Frequency
Accession No.
Grant No.
Project No.
Proposal No.
Multistate No.
Program Code
Project Start Date
Dec 15, 2015
Project End Date
Dec 14, 2019
Grant Year
Project Director
Schnable, J. C.
Recipient Organization
Performing Department
Agronomy and Horticulture
Non Technical Summary
Corn and sorghum are both agriculturally and economically significant crop species. Both species are susceptible to cold and freezing damage (sorghum even more so than maize), which restricts the length of the growing season for each species. Shorter growing seasons provide less total opportunity for photosynthesis, which restricts the ability of plant breeders to increase yields. However, many other species can tolerate cold temperatures, and with acclimation can even tolerate short periods of freezing temperatues. This project focus on close relatives of maize and sorghum that much higher tolerance for cold. By identifying the changes in specific genes and metabolites that provide this increased cold tolerance, this project aims to develop the knowledge that will make it possible in the future to develop varieties of corn and sorghum which can be planted earlier, havested later, and have higher upper boundaries on yield than has previously been feasible.
Animal Health Component
Research Effort Categories

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
Goals / Objectives
Changes in membrane lipid composition and gene expression in response to cold and subsequent freezing stress will be profiled for 10 panicoid grasses in objective one. Synteny-based comparative genomic approaches will be employed to enable the comparisons of the transcriptional response of the same genes across multiple species to the same changes in environmental condition.A broader set of 180 grass species will be assayed for cold and freezing tolerance.Patterns of metabolic change in response to cold stress will be assayed in maize, sorghum, and two close relatives in which freeze tolerance has evolved independently
Project Methods
The execution of this project hinges on successful generation and analysis of three types of data:Data on changes in gene expression in response to cold stress. This will be gathered using RNA-seq, converted to meaningful numbers using a suite of widely used software tools (GSNAP, samtools, cufflinks)Data on phenotypic responses to cold

Progress 12/15/15 to 12/14/16

Target Audience: Nothing Reported Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest?The PDs and personell supported by this grant participated in an open house day at the Morrell Hall Museum of Natural History on on campus titled"Why Plants Don't Wear Sweaters" which sought to educate children about the diversity of grass species and careers in molecular and computational biology. A number of different hands on activity stations were run by us and members of our labs. Attendance:61 adults, 45 youth, 4 UNL students What do you plan to do during the next reporting period to accomplish the goals?1. Complete generation of the initial lipid data(wild species grow more slowly than domesticated ones), analyze the data and identify specific target changes in lipid metabolism which are unique to freeze tolerant species and those unique to cold tolerant species. Generate time course RNA-seq for theadditional five species for which we have samples collected, and collect samples for the remaining two species. 2. A postdoc will start on this project in year two who will focus on integrating the kmeans and GLMM based methods for analyzingsyntenic gene expression across multiple species and identifyng specific gene candidates. They will also start work on the integration of gene expression and lipid data types, although we do not anticipate this being completed in year 2. 3. An undergraduate is currently being trained in RNA extraction and controlled cold stress treatments and should begin working on this grant in Year 2. We anticipate havinghave reported cold and freezing test assessments for at least 32species in year 2. 4. Using data from #1 & 2 above, begin growing plants for specific time point tissue collection to enable generating this data in year 3.

What was accomplished under these goals? 1. We have generated lipid composition data for 8 of the 10 target species thus far. While working with a statistician to better control for between growth trial variation across species, our current statistical approaches have already identified a set of lipid head group abundance and fatty acid composition changes induced by prolonged cold stress which areunique to cold tolerant species across the panel of 8 as well as other changes which are shared across all the grasses in our panel. Detailed time course RNA-seq data has been sequenced and analyzed for 3/10 species. Detailed time course RNA samples have been collected for an additional 5 species, with library construction to start in the near future. 2. As described in the grant we have been employing k-means based clustering to identify groups of genes which react in the same way across multiple species. In addition, we have developed a new approach based upon a generalized linear mixed model, which allows us to identify genes where we have strong statistical evidence for changes in gene regulation across species. A manuscript describing this approach and the findings when applied to our existing data (changes in the transcriptional regulation of cold responsive gene regulation are far more common than would have been anticipated, even between closely related species with the same phenotype) is currently in review, with the support from this grant properly acknowledged. 3. Work on this goal is currently starting. 4. We anticipate completing data generation for this goal in years 2 & 3, after we have as much data from the RNA-seq and lipid assays as possible so we can pick the most informative timepoints.