Life Sciences Commons^™

Gene Expression Programs During Shoot, Root, And Callus Development In Arabidopsis Tissue Culture, Ping Che, Sonia Lall, Dan Nettleton, Stephen H. Howell

Dan Nettleton

Shoots can be regenerated from Arabidopsis (Arabidopsis thaliana) root explants in tissue culture through a two-step process requiring preincubation on an auxin-rich callus induction medium. Regenerating tissues can be directed along different developmental pathways leading to the formation of shoots, new roots, or callus by transferring to the appropriate organ induction medium. Using gene-profiling methods, we identified groups of genes that serve as molecular signatures of the different developmental processes, i.e. genes that were specifically up- or down-regulated on one developmental pathway, but not on others. One transcription factor gene that was up-regulated during early shoot development was …

Loss Of Rna–Dependent Rna Polymerase 2 (Rdr2) Function Causes Widespread And Unexpected Changes In The Expression Of Transposons, Genes, And 24-Nt Small Rnas, Yi Jia, Damon R. Lisch, Kazuhiro Ohtsu, Michael J. Scanlon, Dan Nettleton, Patrick S. Schnable

Dan Nettleton

Transposable elements (TEs) comprise a substantial portion of many eukaryotic genomes and are typically transcriptionally silenced. RNA–dependent RNA polymerase 2 (RDR2) is a component of the RNA–directed DNA methylation (RdDM) silencing pathway. In maize, loss of mediator of paramutation1 (mop1) encoded RDR2 function results in reactivation of transcriptionally silenced Mu transposons and a substantial reduction in the accumulation of 24 nt short-interfering RNAs (siRNAs) that recruit RNA silencing components. An RNA–seq experiment conducted on shoot apical meristems (SAMs) revealed that, as expected based on a model in which RDR2 generates 24 nt siRNAs that suppress expression, most differentially …

Comparative Gene Expression Profiles Between Heterotic And Non-Heterotic Hybrids Of Tetraploid Medicago Sativa, Xuehui Li, Yanling Wei, Dan Nettleton, E. Charles Brummer

Dan Nettleton

Background: Heterosis, the superior performance of hybrids relative to parents, has clear agricultural value, but its genetic control is unknown. Our objective was to test the hypotheses that hybrids expressing heterosis for biomass yield would show more gene expression levels that were different from midparental values and outside the range of parental values than hybrids that do not exhibit heterosis.

Results: We tested these hypotheses in three Medicago sativa (alfalfa) genotypes and their three hybrids, two of which expressed heterosis for biomass yield and a third that did not, using Affymetrix M. truncatula GeneChip arrays. Alfalfa hybridized to approximately 47% …

Interchromosomal Transfer Of Immune Regulation During Infection Of Barley With The Powdery Mildew Pathogen, Priyanka Surana, Ruo Xu, Gregory Fuerst, Antony V. E. Chapman, Dan Nettleton, Roger P. Wise

Dan Nettleton

Powdery mildew pathogens colonize over 9500 plant species, causing critical yield loss. The Ascomycete fungus, Blumeria graminis f. sp. hordei (Bgh), causes powdery mildew disease in barley (Hordeum vulgare L.). Successful infection begins with penetration of host epidermal cells, culminating in haustorial feeding structures, facilitating delivery of fungal effectors to the plant and exchange of nutrients from host to pathogen. We used expression Quantitative Trait Locus (eQTL) analysis to dissect the temporal control of immunity-associated gene expression in a doubled haploid barley population challenged with Bgh. Two highly significant regions possessing trans eQTL were identified near …

Crowdsourcing Image Analysis For Plant Phenomics To Generate Ground Truth Data For Machine Learning, Naihui Zhou, Zachary D. Siegel, Scott Zarecor, Nigel Lee, Darwin A. Campbell, Carson M. Andorf, Dan Nettleton, Carolyn J. Lawrence-Dill, Baskar Ganapathysubramanian, Jonathan W. Kelly, Iddo Friedberg

Dan Nettleton

The accuracy of machine learning tasks critically depends on high quality ground truth data. Therefore, in many cases, producing good ground truth data typically involves trained professionals; however, this can be costly in time, effort, and money. Here we explore the use of crowdsourcing to generate a large number of training data of good quality. We explore an image analysis task involving the segmentation of corn tassels from images taken in a field setting. We investigate the accuracy, speed and other quality metrics when this task is performed by students for academic credit, Amazon MTurk workers, and Master Amazon MTurk …