\item USDA-NIFA ``Improving Causal Gene Detection across Crop and Livestock Species.'' (co-PI) 2023. \$1.3M
\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=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
Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$undergraduate author, $^\S$corresponding author
\end{center}
%Figure out how to emphasis italics stuff more.
%\addtolength{\leftskip}{9mm}
%\subsection*{Preprints}
\addtolength{\leftskip}{9mm}
\subsection*{Preprints}
\noindent Sahay S, \textbf{Shrestha N}, \textbf{Moura Dias H}, \textbf{Mural RV}, \textbf{Grzybowski M}, \textbf{Schnable JC}$^\S$, Glowacka K$^\S$ Comparative GWAS identifies a role for Mendel’s green pea gene in the nonphotochemical quenching kinetics of sorghum, maize, and arabidopsis. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2023.08.29.555201}{10.1101/2023.08.29.555201}\\
\noindent Engelhorn J, Snodgrass S, Kok A, Seetharam A, Schneider M, Kiwit T, Singh A, Banf M, Khaipho-Burch M, Runcie D, Camargo V, \textbf{Torres-Rodriguez JV}, \textbf{Sun G}, Stam M, Fiorani F, \textbf{Schnable JC}, Bass H, Hufford M, Stich B, Frommer W, Ross-Ibarra J, Hartwig T$^\S$ Phenotypic variation in maize can be largely explained by genetic variation at transcription factor binding sites. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2023.08.08.551183}{10.1101/2023.08.08.551183}\\
\noindent Li D, Wang Q, Tian Y, Lyu X, Zhang H, Sun Y, Hong H, Gao H, Li Y, Zhao C, Wang J, Wang R, Yang J, Liu B, Schnable PS, \textbf{Schnable JC}$^\S$, Li Y$^\S$, Qiu L$^\S$ Transcriptome brings variations of gene expression, alternative splicing, and structural variations into gene-scale trait dissection in soybean. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2023.07.03.545230}{10.1101/2023.07.03.545230}
%\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}\\
...
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@@ -319,8 +327,6 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
%\noindent Wang M, Shilo S, Levy AA, Zelkowski M, Olson MA, Jiang J, \textbf{Schnable JC}, Sun Q, Pillardy J, Kianian PMA, Kianian SF, Chen C, Pawlowski WP$^\S$ Elucidating features and evolution of recombination sites in plants using machine learning. \textit{(In Review)} \\
%\noindent Yang Q, Van Haute M, \textbf{Korth N}, Sattler S, Toy J, \textbf{Schnable KC}, Benson AK$^\S$ Complex Trait Analysis of Human Gut Microbiome-Active Traits (MATs) in Sorghum bicolor: a new approach for genetic analysis of human health traits in food crops. \textit{(In Review)}\\
%\noindent Kusmec A, Yeh CT, AlKhalifa N ... \textbf{Schnable JC} (26th of 38 authors) ... Willis DM, Wisser RJ, Schnable PS$^\S$ Data-driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates: a case study involving grain yield of hybrid maize. \textit{(In Review)}\\
%\noindent Chen J, Wang Z, Tan K, Huang W, Shi J, Li T, Hu J, Wang K, Xin B, Zhao H, Song W, Hufford MB, \textbf{Schnable JC}, Ware DH, Jin W, Lai J$^\S$ A complete telomere-to-telomere assembly of the genome of maize. \textit{(In Review)}
...
...
@@ -328,9 +334,12 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
\begin{etaremune}
\subsection*{Faculty Publications}
\item DiMario R, Kophs A, Apalla A, \textbf{Schnable JS}, Cousins A (2023) Multiple highly expressed phosphoenolpyruvate carboxylase genes have divergent enzyme kinetic properties in two C4 grasses. \textsc{Annals Of Botany}\textit{(In Press)}
\item Barnes AC, Myers JL, Surber SM, \textbf{Liang Z}, Mower JP, \textbf{Schnable JC}, Roston RL (2023) Oligogalactolipid production during cold challenge is conserved in early diverging lineages. \textsc{Journal of Experimental Botany} doi: \href{https://doi.org/10.1093/jxb/erad241}{10.1093/jxb/erad241}
\item Chen J, Wang Z, Tan K, Huang W, Shi J, Li T, Hu J, Wang K, Xin B, Zhao H, Song W, Hufford MB, \textbf{Schnable JC}, Ware DH, Jin W, Lai J$^\S$ (2023) A complete telomere-to-telomere assembly of the maize genome. \textsc{Nature Genetics} doi: \href{https://doi.org/10.1038/s41588-023-01419-6}{10.1038/s41588-023-01419-6}
\item Chen J, Wang Z, Tan K, Huang W, Shi J, Li T, Hu J, Wang K, Xin B, Zhao H, Song W, Hufford MB, \textbf{Schnable JC}, Ware DH, Jin W, Lai J$^\S$ (2023) A complete telomere-to-telomere assembly of the maize genome. \textsc{Nature Genetics} doi: \href{https://doi.org/10.1038/s41588-023-01419-6}{10.1038/s41588-023-01419-6}\\
\textbf{\textit{ Selected as an Editor's Choice by MaizeGDB Editorial Board}} August 2023
\item 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{G3} doi: \href{https://doi.org/10.1093/g3journal/jkad006}{10.1093/g3journal/jkad006}\textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2022.07.29.502051}{10.1101/2022.07.29.502051}
...
...
@@ -340,7 +349,8 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
\item Wijewardane NK, Zhang H, Yang J, \textbf{Schnable JC}, Schachtman DP, Ge Y$^\S$ (2023) A leaf-level spectral library to support high throughput plant phenotyping: Predictive accuracy and model transfer. \textsc{Journal of Experimental Botany} doi: \href{https://doi.org/10.1093/jxb/erad129}{10.1093/jxb/erad129}
\item\textbf{Sun G}, Yu H, Wang P, Lopez-Guerrero MG, \textbf{Mural RV}, \textbf{Mizero ON}$^\ddagger$, \textbf{Grzybowski M}, Song B, van Dijk K, Schachtman DP, Zhang C, \textbf{Schnable JC}$^\S$ (2023) A role for heritable transcriptomic variation in maize adaptation to temperate environments. \textsc{Genome Biology} doi: \href{https://doi.org/10.1186/s13059-023-02891-3}{10.1186/s13059-023-02891-3}
\item\textbf{Sun G}, Yu H, Wang P, Lopez-Guerrero MG, \textbf{Mural RV}, \textbf{Mizero ON}$^\ddagger$, \textbf{Grzybowski M}, Song B, van Dijk K, Schachtman DP, Zhang C, \textbf{Schnable JC}$^\S$ (2023) A role for heritable transcriptomic variation in maize adaptation to temperate environments. \textsc{Genome Biology} doi: \href{https://doi.org/10.1186/s13059-023-02891-3}{10.1186/s13059-023-02891-3}\\
\textbf{\textit{ Selected as an Editor's Choice by MaizeGDB Editorial Board}} August 2023
\item Gaillard M, Benes B, \textbf{Tross MC}, \textbf{Schnable JC} (2023) Multi-view triangulation without correspondences. \textsc{Computers and Electronics in Agriculture} doi: \href{https://doi.org/10.1016/j.compag.2023.107688}{10.1016/j.compag.2023.107688}
...
...
@@ -407,7 +417,9 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
\item Sankaran S$^\S$, Marzougui A, \textbf{Hurst JP}, Zhang C, \textbf{Schnable JC}, Shi Y (2021) Can high resolution satellite imagery be used in high-throughput field phenotyping? \textsc{Transactions of the ASABE} doi: \href{https://elibrary.asabe.org/abstract.asp?aid=52080&t=3&redir=aid=52080&confalias=t2&redir=[volume=0&issue=0&conf=t&orgconf=]&redirType=toc_journals.asp&redirType=toc_journals.asp}{10.13031/trans.14197}
\item Zhu Y, Chen Y, Ali Md. A, Dong L, Wang X, Archontoulis SV, \textbf{Schnable JC}, Castellano MJ$^\S$ (2021) Continuous in situ soil nitrate sensors: a comparison with conventional measurements and the value of high temporal resolution measurements. \textsc{Soil Science Society of America Journal} doi: \href{https://doi.org/10.1002/saj2.20226}{10.1002/saj2.20226}
\textbf{\textit{Recipient of the Soil Science Society of America Best Paper Award in 2023}}
\item\textbf{Lai X}, Bendix C, \textbf{Zhang Y}, \textbf{Schnable JC}, Harmon FG$^\S$ (2021) 72-hour diurnal RNA-seq analysis of fully expanded third leaves from maize, sorghum, and foxtail millet at 3-hour resolution. \textsc{BMC Research Notes} doi: \href{https://doi.org/10.1186/s13104-020-05431-5}{10.1186/s13104-020-05431-5}
...
...
@@ -629,6 +641,7 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
\subsection*{Peer Reviewed Conference Papers}
\begin{etaremune}
\item Noh M, Sium F, Tope S, Khan S, Karkhanis M, Wang L, Deshpande A, Dalapati R, \textbf{Mural RV}, Mastrangelo C, Zang L, Ji M, \textbf{Schnable JC}, Kim H (2023) Localization of crop damage utilizing a wake up gas sensor network. \textsc{Transducers 2023} Kyoto, Japan
\item Khan SH, Karkhanis M, Hatasaka B, Tope S, Noh S, Bulbul A, Banerjee A, Ji M, Mastrangelo CH, Kim H, Dalapati R, Zang L, \textbf{Mural RV}, \textbf{Schnable JC}, Kim K (2022) Field deployment of a nanogap gas sensor for crop damage detection. \textsc{35th International Conference on Micro Electro Mechanical Systems Conference (MEMS)} Berlin, Germany doi: \href{https://doi.org/10.1109/MEMS51670.2022.9699614}{10.1109/MEMS51670.2022.9699614}
\item Khan SH, Tope S, Dalpati R, Kim KH, Noh M, Bulbul A, \textbf{Mural RV}, Banerjee A, \textbf{Schnable JC}, Ji M, Mastrango C, Zang L, Kim H (2021) Development of a gas sensor for green leaf volatile detection. \textsc{Transducers 2021} doi: \href{https://doi.org/10.1109/Transducers50396.2021.9495597}{10.1109/Transducers50396.2021.9495597}
\item Gaillard M, \textbf{Miao C}, \textbf{Schnable JC}, Benes B (2020) Sorghum Segmentation by Skeleton Extraction. \textsc{Computer Vision Problems in Plant Phenotyping (CVPPP 2020)} Glasgow, UK