\item DOE ``Phenotypic and Molecular Characterization of Nitrogen Responsive Genes in Sorghum.'' (co-PI) 2022-2025. \$2.7M
\item DOE ``\href{https://news.unl.edu/newsrooms/today/article/nebraska-team-merges-machine-learning-plant-genetics-to-maximize-sorghum/}{TGCM: (T)rait, (G)ene, and (C)rop Growth (M)odel directed targeted gene characterization in sorghum}.'' (PI) 2019-2023. \$2.7M
\item NSF ``\href{https://www.nsf.gov/awardsearch/showAward?AWD_ID=1838307}{RoL: FELS: EAGER: Genetic constraints on the increase of organismal complexity over time.}'' (PI) 2018-2022. \$300k
\item NSF ``\href{https://www.nsf.gov/awardsearch/showAward?AWD_ID=1844707}{BTT EAGER: A wearable plant sensor for real-time monitoring of sap flow and stem diameter to accelerate breeding for water use efficiency.}'' (PI) 2019-2023. \$300k
\item USDA-NIFA ``\href{https://portal.nifa.usda.gov/web/crisprojectpages/1022298-high-intensity-phenotyping-sites.html}{High Intensity Phenotyping Sites: Transitioning To A Nationwide Plant Phenotyping Network.}'' (co-PI) 2020-2023. \$3M
\item USDA-NIFA ``\href{https://portal.nifa.usda.gov/web/crisprojectpages/1022368-high-intensity-phenotyping-sitesa-multi-scale-multi-modal-sensing-and-sense-making-cyber-ecosystem-for-genomes-to-fields.html}{High Intensity Phenotyping Sites: A multi-scale, multi-modal sensing and sense-making cyber-ecosystem for Genomes to Fields.}'' (co-PI) 2020-2023. \$2.7M
\item USDA-NIFA ``\href{https://portal.nifa.usda.gov/web/crisprojectpages/1022122-cps-medium-collaborative-research-field-scale-single-plant-resolution-agricultural-management-using-coupled-molecular-and-macro-sensing-and-multi-scale-data-fusion-and-modeling.html}{CPS: Medium: Field-scale, single plant-resolution agricultural management using coupled molecular and macro sensing and multi-scale data fusion and modeling}'' (co-PI) (2020-2023) \$1.05M
\item NSF ``\href{https://www.nsf.gov/awardsearch/showAward?AWD_ID=1826781}{RII Track-2 FEC: Functional analysis of nitrogen responsive networks in Sorghum.}'' (co-PI) 2018-2023. \$4M
\item FFAR ``\href{http://www.ncsa.illinois.edu/news/story/crops_in_silico_project_awarded_5_million}{Crops in silico: Increasing crop production by connecting models from the microscale to the macroscale.}'' (co-PI) 2019-2023. \$5M
\item NSF ``AI Institute for Resilient Agriculture'' (Investigator) 2021-2026 \$20M
\item NSF ``\href{https://nsf.gov/awardsearch/showAward?AWD_ID=1557417}{Center for Root and Rhizobiome Innovation.}'' (Investigator \& Management Team Member) 2016-2021. \$20M
%\item DOE-JGI Community Sequencing Program ``Expanding grass genome comparators.''
\end{itemize}
\subsection*{Non-Federal (Current)}
\begin{itemize}
\itemICRISAT ``Identifying Novel Loci Controlling Priority Traits in Pearl Millet and Sorghum using Supervised Classification Algorithms.'' (PI) 2020-2021\$50k
\item Nebraska Corn Board ``Genomes to Fields (G2F) - Predicting Final Yield Performance in Variable Environments.'' (PI) 2016-2022. \$300k \textit{(to date)}
\item Wheat Innovation Foundation ``A Low-Cost, High-Throughput Cold Stress Perception Assay for Sorghum Breeding.'' (co-PI) 2019-2021. \$205k
\itemUniversity of Nebraska ``SPACE2: Space, Policy, Agriculture, Climate, and Extreme Environment.'' (co-PI) 2022-2024\$150k.
\item Nebraska Corn Board ``Genomes to Fields (G2F) - Predicting Final Yield Performance in Variable Environments.'' (PI) 2016-2023. \$300k \textit{(to date)}
\item Wheat Innovation Foundation ``A Low-Cost, High-Throughput Cold Stress Perception Assay for Sorghum Breeding.'' (co-PI) 2019-2023. \$205k
\end{itemize}
\subsection*{Completed Projects}
\begin{itemize}
\item ICRISAT ``Identifying Novel Loci Controlling Priority Traits in Pearl Millet and Sorghum using Supervised Classification Algorithms.'' (PI) 2020-2021 \$50k
\item NSF ``\href{https://nsf.gov/awardsearch/showAward?AWD_ID=1557417}{Center for Root and Rhizobiome Innovation.}'' (Investigator \& Management Team Member) 2016-2021. \$20M
\item NSF ``\href{https://www.nsf.gov/awardsearch/showAward?AWD_ID=1838307}{RoL: FELS: EAGER: Genetic constraints on the increase of organismal complexity over time.}'' (PI) 2018-2022. \$300k
\item USDA-NIFA ``\href{https://portal.nifa.usda.gov/web/crisprojectpages/1008702-identifying-mechanisms-conferring-low-temperature-tolerance-in-maize-sorghum-and-frost-tolerant-relatives.html}{Identifying mechanisms conferring low temperature tolerance in maize, sorghum, and frost tolerant relatives.}'' (PI) 2015-2020. \$455k
\item ARPA-E ``\href{https://arpa-e.energy.gov/?q=slick-sheet-project/soil-sensors-nitrogen-use-efficiency}{In-plant and in-soil microsensors enabled high-throughput phenotyping of root nitrogen uptake and nitrogen use efficiency.}'' (co-PI) 2017-2019. \$1.1M
\item USDA/NSF Joint Program ``PAPM EAGER: Transitioning to the next generation plant phenotyping robots.'' (co-PI) 2016-2018. \$285k
Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$undergraduate author, $^\S$corresponding author
\end{center}
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...
@@ -294,11 +301,7 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
\addtolength{\leftskip}{9mm}
\subsection*{Preprints}
\noindent Kick D, Wallace J, \textbf{Schnable JC}, Kolkman JM, Alaca B, Beissinger TM, Ertl D, Flint-Garcia S, Gage JL, Hirsch CN, Knoll JE, de Leon N, Lima DC, Moreta D, Singh MP, Weldekidan T, Washburn JD$^\S$ Yield prediction through integration of genetic, environment, and management data through deep learning. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2022.07.29.502051}{10.1101/2022.07.29.502051}
\noindent\textbf{Sun G}, Wase N, Shu S, Jenkins J, Zhou B, Chen C, Sandor L, Plott C, Yoshinga Y, Daum C, Qi P, Barry K, Lipzen A, Berry L, Gottilla T, \textbf{Foltz A}, Yu H, O'Malley R, Zhang C, Devos KM, \textbf{Sigmon B}, Yu B, Obata T, Schmutz J$^\S$, \textbf{Schnable JC}$^\S$ Genome sequence of \textit{Paspalum vaginatum} indicates trehalose may act as a conserved trigger for increased nitrogen use efficiency in grasses. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2021.08.18.456832}{10.1101/2021.08.18.456832}\\
\noindent Yang Q, Van Haute M, \textbf{Korth N}, Sattler S, Toy J, Rose D, \textbf{Schnable JC}, Benson A$^\S$ Complex trait analysis of human gut microbiome-active traits in \textit{Sorghum bicolor}: a new category of human health traits in food crops. \textsc{Research Square} doi: \href{https://doi.org/10.21203/rs.3.rs-1490527/v1}{10.21203/rs.3.rs-1490527/v1}
\noindent Kick D, Wallace J, \textbf{Schnable JC}, Kolkman JM, Alaca B, Beissinger TM, Ertl D, Flint-Garcia S, Gage JL, Hirsch CN, Knoll JE, de Leon N, Lima DC, Moreta D, Singh MP, Weldekidan T, Washburn JD$^\S$ Yield prediction through integration of genetic, environment, and management data through deep learning. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2022.07.29.502051}{10.1101/2022.07.29.502051}\\
\noindent Xu G, Lyu J, Obata T, Liu S, Ge Y, \textbf{Schnable JC}, Yang J$^\S$ A historically balanced locus under recent directional selection in responding to changed nitrogen conditions during modern maize breeding. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2022.02.09.479784}{10.1101/2022.02.09.479784}\\
...
...
@@ -323,13 +326,22 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
\begin{etaremune}
\subsection*{Faculty Publications}
\item Li D, Bai D, Tian Y, Li Y, Zhao C, Wang Q, Gou S, Gu Y, Luan X, Wang R, Yang J, Hawkesford MJ, \textbf{Schnable JC}, Jin X, Qiu L (2022) Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean. \textsc{Journal of Integrative Plant Biology}\textit{(Accepted)}
\item Gaillard M, Benes B, \textbf{Tross MC}, \textbf{Schnable JC} (2023) Multi-view triangulation without correspondences. \textsc{Computers and Electronics in Agriculture}\textit{(Accepted)}
\item\textbf{Grzybowski M}$^\S$, \textbf{Mural RV}, Xu G, \textbf{Turkus, J}, Yang Jinliang, \textbf{Schnable JC} (2023) A common resequencing-based genetic marker dataset for global maize diversity. \textsc{The Plant Journal} doi: \href{https://doi.org/10.1111/tpj.16123}{10.1111/tpj.16123}
\item\textbf{Sun G}, Wase N, Shu S, Jenkins J, Zhou B, Chen C, Sandor L, Plott C, Yoshinga Y, Daum C, Qi P, Barry K, Lipzen A, Berry L, Gottilla T, \textbf{Foltz A}, Yu H, O'Malley R, Zhang C, Devos KM, \textbf{Sigmon B}, Yu B, Obata T, Schmutz J$^\S$, \textbf{Schnable JC}$^\S$ (2023) Genome of \textit{Paspalum vaginatum} and the role of trehalose mediated autophagy in increasing maize biomass. \textsc{Nature Communications} doi: \href{https://doi.org/10.1038/s41467-022-35507-8}{10.1038/s41467-022-35507-8}\textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2021.08.18.456832}{10.1101/2021.08.18.456832}\\
\textbf{\textit{"Research Highlight" in Nature Plants}} doi: \href{https://doi.org/10.1038/s41477-023-01343-x}{10.1038/s41477-023-01343-x}
\item\textbf{Grzybowski M}$^\S$, \textbf{Zweiner M}, \textbf{Jin H}, Wijewardane NK, Atefi A, Naldrett MJ, Alverez S, Ge Y, \textbf{Schnable JC} (2022) Variation in morpho-physiological and metabolic responses to low nitrogen stress across the sorghum association panel. \textsc{BMC Plant Biology} doi: \href{https://doi.org/10.1186/s12870-022-03823-2}{10.1186/s12870-022-03823-2}\textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2022.06.08.495271}{10.1101/2022.06.08.495271}
\item Yang Q, Van Haute M, \textbf{Korth N}, Sattler S, Toy J, Rose D, \textbf{Schnable JC}, Benson A (2022) Genetic analysis of seed traits in Sorghum bicolor that affect the human gut microbiome. \textsc{Nature Communications} doi: \href{https://doi.org/10.1038/s41467-022-33419-1}{10.1038/s41467-022-33419-1}
\item\textbf{Grzybowski M}$^\S$, \textbf{Zweiner M}, \textbf{Jin H}, Wijewardane NK, Atefi A, Naldrett MJ, Alverez S, Ge Y, \textbf{Schnable JC} (2022) Variation in morpho-physiological and metabolic responses to low nitrogen stress across the sorghum association panel. \textsc{BMC Plant Biology}\textit{(Accepted)}\textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2022.06.08.495271}{10.1101/2022.06.08.495271}
\itemLi D, Bai D, Tian Y, Li Y, Zhao C, Wang Q, Gou S, Gu Y, Luan X, Wang R, Yang J, Hawkesford MJ, \textbf{Schnable JC}, Jin X, Qiu L (2022) Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean. \textsc{Journal of Integrative Plant Biology} doi: \href{https://doi.org/10.1111/jipb.13380}{10.1111/jipb.13380}
\item Khound R, \textbf{Sun G}, \textbf{Mural RV}, \textbf{Schnable JC}, Santra D$^\S$ (2022) SNP Discovery in Proso millet (\textit{Panicum miliaceum} L.) using low-pass genome sequencing. \textsc{Plant Direct}\textit{(Accepted)}
\item Khound R, \textbf{Sun G}, \textbf{Mural RV}, \textbf{Schnable JC}, Santra D$^\S$ (2022) SNP Discovery in Proso millet (\textit{Panicum miliaceum} L.) using low-pass genome sequencing. \textsc{Plant Direct}doi: \href{https://doi.org/10.1002/pld3.447}{10.1002/pld3.447}
\item Zhang K, Yang Y, Zhang X, Zhang L, Fu Y, Guo Z, Chen S, Wu J, \textbf{Schnable JC}, Yi K, Wang X, Cheng F$^\S$ (2022) The genome of *Orychophragmus violaceus* provides genomic insights into the evolution of Brassicaceae polyploidization and its distinct traits. \textsc{Plant Communications}\textit{(Accepted)}
\item Zhang K, Yang Y, Zhang X, Zhang L, Fu Y, Guo Z, Chen S, Wu J, \textbf{Schnable JC}, Yi K, Wang X, Cheng F$^\S$ (2022) The genome of *Orychophragmus violaceus* provides genomic insights into the evolution of Brassicaceae polyploidization and its distinct traits. \textsc{Plant Communications}doi: \href{https://doi.org/10.1016/j.xplc.2022.100431}{10.1016/j.xplc.2022.100431}
\item\textbf{Mural RV}, \textbf{Sun G}, \textbf{Grzybowski M}, \textbf{Tross MC}, \textbf{Jin H}, \textbf{Smith C}, Newton L, Andorf CM, Woodhouse MR, Thompson AM, \textbf{Sigmon B}, \textbf{Schnable JC}$^\S$ (2022) Association mapping across a multitude of traits collected in diverse environments identifies pleiotropic loci in maize. \textsc{Gigascience} doi: \href{https://doi.org/10.1093/gigascience/giac080}{10.1093/gigascience/giac080}\textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2022.02.25.480753}{10.1101/2022.02.25.480753}
...
...
@@ -696,7 +708,9 @@ Science Advances
% \item University of Massachusetts Amherst, Oxford, OH, USA\textit{\hfill(Sept. 2019)}
%\end{itemize}
\begin{itemize}
\item French Agricultural Research Centre for International Development (CIRAD), Montpellier, France \hfill 2022
\item Carnegie Institution for Science, Stanford, CA, USA\hfill 2022
\item Center for Sorghum Improvement, Manhattan, KS, USA \hfill 2022 \textit{(Remote)}
\item CIRAD, Montpellier, France \hfill 2022
\item California State East Bay, Hayward, CA, USA \hfill 2021 \textit{(Remote, COVID)}
\item University of Missouri, Columbia, MO, USA\hfill2020 \textit{(Remote, COVID)}
\item Rutgers University, New Brunswick, NJ, USA\hfill2020 \textit{(Remote, COVID)}
...
...
@@ -779,6 +793,7 @@ Science Advances
\end{itemize}
\subsection*{Internal}
\begin{itemize}
\item CROPS Entrepreneurship/Industry Career Panel (Student Organized), UNL\hfill2023
