@@ -287,10 +287,6 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
...
@@ -287,10 +287,6 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
\noindent Rodene E, Xu G, Delen SP, \textbf{Smith C}, Ge Y, \textbf{Schnable JC}, Yang J$^\S$ A UAV-based high-throughput phenotyping approach to assess time-series nitrogen responses and identify traits associated genetic components in maize. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2021.05.24.445447}{10.1101/2021.05.24.445447}\\
\noindent Rodene E, Xu G, Delen SP, \textbf{Smith C}, Ge Y, \textbf{Schnable JC}, Yang J$^\S$ A UAV-based high-throughput phenotyping approach to assess time-series nitrogen responses and identify traits associated genetic components in maize. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2021.05.24.445447}{10.1101/2021.05.24.445447}\\
\noindent\textbf{Sun G}$^\S$, \textbf{Mural RV}, \textbf{Turkus JD}, \textbf{Schnable JC} Quantitative resistance loci to southern rust mapped in a temperate maize diversity panel. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2021.04.02.438220}{10.1101/2021.04.02.438220}\\
\noindent\textbf{Miao C}, \textbf{Guo A}$^\ddagger$, Yang J, Ge Y, \textbf{Schnable JC}$^\S$ Automation of leaf counting in maize and sorghum using deep learning. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2020.10.27.355495}{10.1101/2020.12.19.423626}\\
\noindent\textbf{Miao C}, \textbf{Hoban TP}$^\ddagger$, \textbf{Pages A}$^\ddagger$, Xu Z, Rodene E, Ubbens J, Stavness I, Yang J, \textbf{Schnable JC}$^\S$ Simulated plant images improve maize leaf counting accuracy. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/706994}{10.1101/706994}\\
\noindent\textbf{Miao C}, \textbf{Hoban TP}$^\ddagger$, \textbf{Pages A}$^\ddagger$, Xu Z, Rodene E, Ubbens J, Stavness I, Yang J, \textbf{Schnable JC}$^\S$ Simulated plant images improve maize leaf counting accuracy. \textsc{bioRxiv} doi: \href{https://doi.org/10.1101/706994}{10.1101/706994}\\
\noindent Zhang Z$^\S$, Chen C, Rutkoski J, \textbf{Schnable JC}, Murray S, Wang L, Jin X, Stich B, Crossa J, Hayes B. Harnessing Agronomics Through Genomics and Phenomics in Plant Breeding: A Review. \textsc{preprints.org} doi: \href{https://www.preprints.org/manuscript/202103.0519/v1}{10.20944/preprints202103.0519.v1}
\noindent Zhang Z$^\S$, Chen C, Rutkoski J, \textbf{Schnable JC}, Murray S, Wang L, Jin X, Stich B, Crossa J, Hayes B. Harnessing Agronomics Through Genomics and Phenomics in Plant Breeding: A Review. \textsc{preprints.org} doi: \href{https://www.preprints.org/manuscript/202103.0519/v1}{10.20944/preprints202103.0519.v1}
...
@@ -301,19 +297,19 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
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@@ -301,19 +297,19 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
\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 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 Serba DD, \textbf{Meng X}, \textbf{Schnable JC}, Bashir E, Michaud JP, Prasad PVV, Perumal R$^\S$ Comparative transcriptome analysis reveals genetic mechanisms of sugarcane aphid resistance in grain sorghum. \textit{(In Review)}\\
\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. \textit{In Review}\\
\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. \textit{In Review}\\
\noindent Hurst JP, \textbf{Schnable JC}, Holding DR$^\S$ Tandem duplicate expression patterns areconserved between maize haplotypes of the $\alpha$-zeingene family. \textit{In Review}\\
\noindent Yu H, Sandhu J, \textbf{Sun G}, Nguyen H, Clemente T, \textbf{Schnable JC}, Walia H, Xie W, Yu B, Mower JP, Zhang C$^\S$ Pervasive misannotation of the smallest microexons that are evolutionarily conserved and crucial for gene function in plants. \textit{In Review}\\
\noindent Yu H, Sandhu J, \textbf{Sun G}, Nguyen H, Clemente T, \textbf{Schnable JC}, Walia H, Xie W, Yu B, Mower JP, Zhang C$^\S$ Pervasive misannotation of the smallest microexons that are evolutionarily conserved and crucial for gene function in plants. \textit{In Review}\\
%\noindent qTeller: A tool for comparative multi-genomic gene expression analysis.
\begin{etaremune}
\begin{etaremune}
\subsection*{Faculty Publications}
\subsection*{Faculty Publications}
\item\textbf{Miao C}, \textbf{Guo A}$^\ddagger$, Yang J, Ge Y, \textbf{Schnable JC}$^\S$ (2021) Automation of leaf counting in maize and sorghum using deep learning. \textsc{The Plant Phenome Journal}\textit{(Accepted)}\textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2020.10.27.355495}{10.1101/2020.12.19.423626}
\item Hurst JP, \textbf{Schnable JC}, Holding DR$^\S$ (2021) Tandem duplicate expression patterns are conserved between maize haplotypes of the $\alpha$-zeingene family. \textsc{Plant Direct}\textit{(Accepted)}
\item\textbf{Sun G}$^\S$, \textbf{Mural RV}, \textbf{Turkus JD}, \textbf{Schnable JC} (2021) Quantitative resistance loci to southern rust mapped in a temperate maize diversity panel. \textsc{Phytopathology} doi: \href{https://doi.org/10.1094/PHYTO-04-21-0160-R}{10.1094/PHYTO-04-21-0160-R}\textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2021.04.02.438220}{10.1101/2021.04.02.438220}
\item\textbf{Mural RV}, \textbf{Grzybowski M}, \textbf{Miao C}, \textbf{Damke A}$^\ddagger$, Sapkota S, Boyles RE, Salas Fernandez MG, Schnable PS, \textbf{Sigmon B}, Kresovich S, \textbf{Schnable JC}$^\S$ (2021) Meta-analysis identifies pleiotropic loci controlling phenotypic trade-offs in sorghum. \textsc{Genetics} doi: \href{https://doi.org/10.1093/genetics/iyab087}{10.1093/genetics/iyab087}\textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2020.10.27.355495}{10.1101/2020.10.27.355495}
\item\textbf{Mural RV}, \textbf{Grzybowski M}, \textbf{Miao C}, \textbf{Damke A}$^\ddagger$, Sapkota S, Boyles RE, Salas Fernandez MG, Schnable PS, \textbf{Sigmon B}, Kresovich S, \textbf{Schnable JC}$^\S$ (2021) Meta-analysis identifies pleiotropic loci controlling phenotypic trade-offs in sorghum. \textsc{Genetics} doi: \href{https://doi.org/10.1093/genetics/iyab087}{10.1093/genetics/iyab087}\textsc{bioRxiv} doi: \href{https://doi.org/10.1101/2020.10.27.355495}{10.1101/2020.10.27.355495}
\item\textbf{Grzybowski M}, Wijewardane NK, Atefi A, Ge Y, \textbf{Schnable JC}$^\S$ (2021) The potential of hyperspectral reflectance as a tool for quantitative genetics in crops. \textsc{Plant Communications} doi: \href{https://doi.org/10.1016/j.xplc.2021.100209}{10.1016/j.xplc.2021.100209}
\item\textbf{Grzybowski M}, Wijewardane NK, Atefi A, Ge Y, \textbf{Schnable JC}$^\S$ (2021) The potential of hyperspectral reflectance as a tool for quantitative genetics in crops. \textsc{Plant Communications} doi: \href{https://doi.org/10.1016/j.xplc.2021.100209}{10.1016/j.xplc.2021.100209}
...
@@ -504,6 +500,8 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
...
@@ -504,6 +500,8 @@ Lab members in \textbf{bold}, $^*$authors contributed equally, $^\ddagger$underg
\subsection*{Graduate Publications}
\subsection*{Graduate Publications}
\item Woodhouse MR, Sen S, Schott D, Portwood JL, Freeling M, Walley JW, Andorf CM, \textbf{Schnable JC} (2021) qTeller: A tool for comparative multi-genomic gene expression analysis. \textsc{Bioinformatics}\textit{(Accepted Pending Minor Revision)}
\item Cheng F, Sun C, Wu J, {\bf Schnable JC}, Woodhouse MR, Liang J, Cai C, Freeling M,$^\S$ Wang X$^\S$ (2016) Epigenetic regulation of subgenome dominance following whole genome triplication in \textit{Brassica rapa}. \textsc{New Phytologist} doi: \href{http://dx.doi.org/10.1111/nph.13884}{10.1111/nph.13884}
\item Cheng F, Sun C, Wu J, {\bf Schnable JC}, Woodhouse MR, Liang J, Cai C, Freeling M,$^\S$ Wang X$^\S$ (2016) Epigenetic regulation of subgenome dominance following whole genome triplication in \textit{Brassica rapa}. \textsc{New Phytologist} doi: \href{http://dx.doi.org/10.1111/nph.13884}{10.1111/nph.13884}
\item Almeida AMR, Yockteng R, {\bf Schnable JC}, Alvarez-Buylla ER, Freeling M, Specht CD$^\S$ (2014) Co-option of the polarity gene network shapes filament morphology in angiosperms. \textsc{Scientific Reports} doi: \href{http://dx.doi.org/10.1038/srep06194}{10.1038/srep06194}
\item Almeida AMR, Yockteng R, {\bf Schnable JC}, Alvarez-Buylla ER, Freeling M, Specht CD$^\S$ (2014) Co-option of the polarity gene network shapes filament morphology in angiosperms. \textsc{Scientific Reports} doi: \href{http://dx.doi.org/10.1038/srep06194}{10.1038/srep06194}