Progress 12/15/15 to 12/14/20
Outputs
Target Audience:The target audience reached during this time period was primarily the scientific community working on maize and sorghum genomics and/or cold tolerance across various crop and wild species. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?In 2018 this project supported a postdoctoral scholar Sunil KK Raju who came from a pure molecular biology background. During his work with Prof. Schnable, Dr. Raju became familiar with and employed a wide range of bioinformatics and genomics tools, allowing him to secure a position at Michigan State University working in comparative epigenomics. One postdoc Yang Zhang, got firsthand experience with the process of writing and submitting a paper for the first time, as well as composing a response to reviewers document. This was also a new experience and training opportunity for Daniel Carvalho, a graduate student partially supported by this project in 2017. In 2018 this project supported a postdoctoral scholar Sunil KK Raju who came from a pure molecular biology background. During his work with Prof. Schnable, Dr. Raju became familiar with and employed a wide range of bioinformatics and genomics tools, allowing him to secure a position at Michigan State University working in comparative epigenomics. In 2019 this project supported Xiaoxi Meng who graduated from Mississippi State with a molecular biology focused PhD. During her time supported by the project she became familiar not only with genomic and bioinformatic tools but ultimately implemented a random forest based machine learning framework for gene expression prediction, ultimately publishing her work on this project in PNAS. Holly Podliska, an internally funded undergraduate, was able to get first hand experience in what it was like to be a part of an academic research lab conducting work as part of major goal #3. How have the results been disseminated to communities of interest?The primary venue through which results were disseminated were peer reviewed publications, and talks at conferences and departmental seminar serieses. However, in addition to these traditional dissemination plans.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?
Nothing Reported
Impacts
What was accomplished under these goals?
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 We generated lipid composition data for 8 of the 10 target species and one additional species not originally planned for inclusion (see below). Working with a statistician we were better able 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 are unique to cold tolerant species across the panel of 8 as well as other changes which are shared across all the grasses in our panel. Cold stress and control RNA-seq data was also generated for eight of the original target species plus one additional unplanned target. We generated syntenic gene lists and employed employed 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. Goal 3 was scaled back significantly in the revised plan of work associated with the cut in funding relative to the original request. Our revised goal at project initiation was to screen 90 total species. In 64 cases we were able to successfully germinate plants or grow from vegetative clones requested from the NPGS and conduct evaluations of cold and freezing sensitivity following cold acclimating in order to assign plants to the phenotypic categories of "cold sensitive" "cold tolerant but freezing sensitive" or "freezing tolerant." Grass synteny data was expanded to incorporate data from the oropetium genome, an outgroup for the purposes of the analyses conducted in 2018. In addition, the declining cost of sequencing since the original experimental design for this grant meant we were able to generate long sequence read mRNA data from Tripsacum dactyloides using PacBio IsoSeq as well as lipid and transcriptomic data from a reduced set of time points. Tripsacum dactyloides is a close relative of maize which is native to temperate lattitudes and exhibits increased cold tolerance. It was originally excluded from out experimental design because the absence of a reference genome or high quality transcriptome assembly made comparative transcriptomics challenging. However, isoseq data was of sufficient quality to allow us to resolve homeologous gene copies between Tripsacum/Zea subgenomes. Combining transcriptomic and lipid profiling with comparative genomic approaches, we identified faster rates of protein sequence evolution in Tripsacum for the genes encoding enzymes in the pathways leading to these membrane lipids. We extended our synteny based comparative framework to include a set of genomic and functional genomic features associated with each gene model and found it was possible to train machine learning networks to predict which genes will transcriptionally respond to cold stress. We validated this model using genomic features and cold stress responsive transcriptomic data from six grasses with distinct degrees of cold tolerance and demonstrated that it was possible to train models in well studied cold sensitive crop species which could successfully predict which genes would transcriptionally respond to cold in cold tolerant wild relatives given only a genome sequence and set of gene model annotations.
Publications
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Progress 12/15/19 to 12/14/20
Outputs
Target Audience:The primary target audience reached in this reporting period where plant biologists working in the areas of stress biology and/or maize and sorghum genetics. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?During this period three postdoctoral scholars who were partially supported with funding from the proposed project gained experience in computational biology, transcriptomic analysis, machine learning,and comparative genomics How have the results been disseminated to communities of interest?Through scientific publications and presentations at remote conferences. It was not possible to present in person during the majority of this reporting period as a result of the coronavirus pandemic and associated travel restrictions. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
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. While we had initially planned to work with a single representative genotype per species, we were able to modestly extend this goal by collecting data on variation in post-acclimation cold tolerance and membrane lipid composition from a set of 10 diverse sorghum accessions selected from the Sorghum Association panel. 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 predictive machine learning model, referenced in last year's report,for predicting which genes will transcriptionally respond to cold stress in one species purely from genomic features based on training data generated in another species was further expanded and validated including the incorporation of data generated by other research groups using different cold stress protocols. A broader set of 180 grass species will be assayed for cold and freezing tolerance. No work was completely under this goal in the final year of this project. 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 No work was conducted on this project goal in the final year of this project.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Jarquin D, Howard R, Liang Z, Gupta SK, Schnable JC, Crossa J (2020) Enhancing hybrid prediction in pearl millet using genomic and/or multi-environment phenotypic information of inbreds. Frontiers in Genetics doi: 10.3389/fgene.2019.01294
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Yan L, Raju SKK, Lai X, Zhang Y, Dai X, Rodriguez O, Mahboub S, Roston RL, Schnable JC (2019) Parallel natural selection in the cold-adapted crop-wild relative Tripsacum dactyloides and artificial selection in temperate adapted maize. The Plant Journal doi: 10.1111/tpj.14376 bioRxiv doi: 10.1101/187575
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Carvalho DS, Nishimwe A, Schnable JC (2020) IsoSeq transcriptome assembly of C3 panicoid grasses provides tools to study evolutionary change in the Panicoideae. Plant Direct doi: 10.1002/pld3.203 bioRxiv doi: 10.1101/689356
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Meng X, Liang Z, Dai X, Zhang Y, Mahboub S, Ngu DW, Roston RL, Schnable JC (2021) Predicting transcriptional responses to cold stress across plant species. Proceedings of the National Academy of Sciences doi: 10.1073/pnas.2026330118 bioRxiv doi: 10.1101/2020.08.25.266635
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Progress 12/15/18 to 12/14/19
Outputs
Target Audience:Scientific and professional community, through publications and conferences. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?In 2019 this project support a postdoc named Xiaoxi Meng who had completed her PhD working on wet-lab proteomics. In her research, supported by this award, she learned and became confident working with python, the linux command line, both genomics and comparative genomics tools, and machine learning algorithms to address functional genomic biological questions. How have the results been disseminated to communities of interest?Results have been disseminated through peer reviewed publications and talks at scientific conferences. What do you plan to do during the next reporting period to accomplish the goals?We plan to wrap up and publish the remaining datasets generated as part of goals #1 and #2. In addition we plan to further validate our ML models for predicting cold responsive gene expression using genomic and functional genomic descriptors and ideally publish or otherwise disseminate that result as well.
Impacts
What was accomplished under these goals?
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. As a result of advances in sequencing technology wewere able to expand beyond the original plan of work for this objective to include work on Tripsacum dactyloides, a species we had originally omitted from our research plan because of its lack of a sequenced reference genome. As I think was described in last year's report were were able to generate a set of full length cDNA sequences using PacBio IsoSeq (released as an "other product" in this year's report). In 2019, we extended this work to include RNA-seq and membrane lipid profiling of Tripsacum and maize in response to cold stress and identified both changes in the lipid metabolism responses of these species to cold stress but also faster rates of protein sequence evolution in Tripsacum for the genes encoding enzymes in the pathways leading to these membrane lipids (as detailed in Yan et al published this year and reported in this report). 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. We extended our synteny based comparative framework to include a set of genomic and functional genomic features associated with each gene model. In early preliminary tests we found that it may be possible to train machine learning networks to predict which genes will transcriptionally respond to cold stress. A broader set of 180 grass species will be assayed for cold and freezing tolerance. Nothing to report under this goal. 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 Nothing to report under this goal.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Yan L, Raju SKK, Lai X, Zhang Y, Dai X, Rodriguez O, Mahboub S, Roston RL, Schnable JC (2019) Parallel natural selection in the cold-adapted crop-wild relative Tripsacum dactyloides and artificial selection in temperate adapted maize. The Plant Journal doi: 10.1111/tpj.14376 bioRxiv doi: 10.1101/187575
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
Roston RL. 2019. How freezing tolerance is regulated at the chloroplast envelope membrane. Annual Meeting of the American Society for Plant Biologists. San Jose, CA. (Selected Oral Presentation)
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
Roston RL. 2019. The Rhythms of Membrane Lipid Dynamics in Monocots. Gordon Research Conference on Plant Lipids: Structure, Metabolism & Function. Galveston, TX. (Invited Oral Presentation)
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Progress 12/15/17 to 12/14/18
Outputs
Target Audience:The target audience reached during this time period was primarily the scientific community working on maize and sorghum genomics and/or cold tolerance across various crop and wild species. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?In 2018 this project supported a postdoctoral scholar Sunil KK Raju who came from a pure molecular biology background. During his work with Prof. Schnable, Dr. Raju became familiar with and employed a wide range of bioinformatics and genomics tools, allowing him to secure a position at Michigan State University working in comparative epigenomics. How have the results been disseminated to communities of interest?Through both peer reviewed papers and presentations at scientific conferences. What do you plan to do during the next reporting period to accomplish the goals?Conduct additional comparative transcriptomic/lipidomic analyses employing the data generated in this reporting period and write up the results. Generate the final bolus of time series transcriptomic and metabolomic data.
Impacts
What was accomplished under these goals?
Goals: 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 In 2018, we completedtime course RNA-seq and lipid profiling under control and cold stress conditions from an additional three of the ten target species for this project. Grass synteny data was expanded to incorporate data from the oropetium genome, an outgroup for the purposes of the analyses conducted in 2018. In addition, the declining cost of sequencing since the original experimental design for this grant meant we were able to generate long sequence read mRNA data from Tripsacum dactyloides using PacBio IsoSeq as well as lipid and transcriptomic data from a reduced set of time points. Tripsacum dactyloides is is a close relative of maize which is native to temperate lattitudes and exhibits increased cold tolerance. It was originally excluded from out experimental design because the absence of a reference genome or high quality transcriptome assembly made comparative transcriptomics challenging. However, isoseq data was of sufficient quality to allow us to resolve homeologous gene copies between Tripsacum/Zea subgenomes.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Kenchanmane Raju SK, Barnes AC, Schnable JC, Roston RL (2018) Low-temperature tolerance in land plants: Are transcript and membrane responses conserved? Plant Science. 276, 73-86. https://doi.org/10.1016/j.plantsci.2018.08.002
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Liang Z, Schnable JC. (2018) Functional Divergence Between Subgenomes and Gene Pairs After Whole Genome Duplications. Molecular Plant doi: 10.1016/j.molp.2017.12.010
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Miao C, Yang J, Schnable JC (2018) Optimizing the identification of causal variants across varying genetic architectures in crops. Plant Biotechnology Journal doi: 10.1111/pbi.13023 bioRxiv doi: 10.1101/310391
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Progress 12/15/16 to 12/14/17
Outputs
Target Audience:In 2017 the primary target audience we reached were other researchers including attendees at conferences (PD Roston's presentation), plant science departments at other land grant universities (PD Schnable's seminars), and readers of the journal The Plant Cell. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?One postdoc Yang Zhang, got firsthand experience with the process of writing and submitting a paper for the first time, as well as composing a response to reviewers document. This was also a new experience and training opportunity for Daniel Carvalho, a graduate student partially supported by this project in 2017. A new short term postdoc, Sunil KK Raju, joined the lab in 2017. His background in his PhD was purely in molecular biology and his work as part of the lab in 2017 allowed him to develop competitency in genomics and bioinformatic analysis. Holly Podliska, an internally funded undergraduate, was able to get first hand experience in what it was like to be a part of an academic research lab conducting work as part of major goal #3 (with the research itself funded by this grant even though her time was not). How have the results been disseminated to communities of interest?In 2017, both PDs gave presentationsdisseminating the results of this research project. These include: These include Rebecca L. Roston's presentation at the 2017Gordon Research Conference on Plant Lipids: Structure, Metabolism & Function. Galveston, TX, and James C. Schnable's invited departmental seminars at Iowa State University and the University of Minnesota, as well as the Universtiy of Missouri Interdisciplinary Plant Group seminar series. What do you plan to do during the next reporting period to accomplish the goals?In 2018 we will expand the number of plant species profiled as part of Objective #1 and analyzed as part of Objective #2, with a particular focus on testing and determining the best ways to integrate the lipid and gene expression data.
Impacts
What was accomplished under these goals?
By2017 we had completedprofiling both gene expression data and membrane lipid composition data from the first two of the ten species we had targetted as part of this proposed project. As part of developingand validating synteny based approaches to compare transcriptional approaches across multiple species we developed new analytical approaches to both test for differential and conserved patterns of gene regulation in response to cold stress across species,as well as new ways to visualize these results of these tests. These approaches and the results of comparing the first two species: maize and sorghum were published in a paper in The Plant Cell. In 2017 a UCARE student (an internal UNL funding program) joined PDSchnable's research group and began screening different grass species for their tolerance of both cold and freezing as part of accomplishing major goal #3.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Zhang Y, Ngu DW, Carvalho D, Liang Z, Qiu Y, Roston RL, Schnable JC (2017) Differentially Regulated Orthologs in Sorghum and the Subgenomes of Maize. The Plant Cell. 29, 1938-1951. doi: 10.1105/tpc.17.00354
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Progress 12/15/15 to 12/14/16
Outputs
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.
Impacts
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.
Publications
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