Browsing by Author "Grene, Ruth"

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    Changes in RNA Splicing in Developing Soybean (Glycine max) Embryos
    Aghamirzaie, Delasa; Nabiyouni, Mahdi; Fang, Yihui; Klumas, Curtis; Heath, Lenwood S.; Grene, Ruth; Collakova, Eva (MDPI, 2013-11-21)
    Developing soybean seeds accumulate oils, proteins, and carbohydrates that are used as oxidizable substrates providing metabolic precursors and energy during seed germination. The accumulation of these storage compounds in developing seeds is highly regulated at multiple levels, including at transcriptional and post-transcriptional regulation. RNA sequencing was used to provide comprehensive information about transcriptional and post-transcriptional events that take place in developing soybean embryos. Bioinformatics analyses lead to the identification of different classes of alternatively spliced isoforms and corresponding changes in their levels on a global scale during soybean embryo development. Alternative splicing was associated with transcripts involved in various metabolic and developmental processes, including central carbon and nitrogen metabolism, induction of maturation and dormancy, and splicing itself. Detailed examination of selected RNA isoforms revealed alterations in individual domains that could result in changes in subcellular localization of the resulting proteins, protein-protein and enzyme-substrate interactions, and regulation of protein activities. Different isoforms may play an important role in regulating developmental and metabolic processes occurring at different stages in developing oilseed embryos.
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    Characterization of the amino acid transporter AAP1 in Arabidopsis thaliana
    Boyd, Shelton Roosevelt (Virginia Tech, 2018-01-22)
    Amino acids are essential molecules in plant metabolism. Amino acids carry reduced nitrogen while serving as precursors for protein synthesis and secondary metabolites. Translocation of amino acids in the cell is mediated by amino acid transporters. While about 100 transporters have been identified, only a dozen have been fully characterized. The regulation of amino acid transporters is not fully understood and stands as the basis of this study. Previous toxicity-based screenings of Arabidopsis thaliana mutants led to the isolation of a loss-of-function line and the phenylalanine insensitive growth (pig1) mutant capable of growth on toxic concentrations of phenylalanine (1). The pig1-1 mutants also displayed a deregulated metabolism (1). We followed this work with a similar forward genetic screening of Arabidopsis thaliana that led to the identification of 18 mutants capable of growth in the presence of amino acids at toxic concentrations. From this screen, seven mutations were confirmed to affect the amino acid transporter AAP1. Here I demonstrate that, when expressed in yeast deficient for endogenous amino acid transporters, three variant aap1 proteins restored growth similar to yeast complemented by wild type AAP1. Transport of radiolabeled Pro was abolished by variant aap1 proteins while deletion of an intracellular loop spanning the 8th and 9th transmembrane domains reduced Pro transport in yeast. Site directed mutagenesis of this loop conferred a variant aap1 protein which augmented Pro transport in yeast. Amino acid transport in loss-of-function aap1 plants display decreased uptake and increased efflux. In addition, aap1 mutant plants accumulated between 2 and 8 times more free amino acids in the leaves than the wild type. These observations are not fully compatible with the accepted role of AAP1 in transport by the root. The present work describes how the amino acid transporter AAP1 could play a role in regulating amino acid metabolism. We hypothesize that the amino acid transporter AAP1 functions as a senor that is involved in amino acid homeostasis in addition to its established role as a transporter. Is true, this would make AAP1 the first identified amino acid sensor in plants. Knowledge of the mechanism of amino acid sensing would enable us to engineer crops for improved nutrition in a more efficient way than affecting metabolic enzymes.
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    Characterization of the Arabidopsis glutamine dumper1 mutant reveals connections between amino acid homeostasis and plant stress responses
    Yu, Shi (Virginia Tech, 2015-04-15)
    Amino acids constitute the major organic form of transported nitrogen in plants, elements for protein synthesis, and precursors of many plant secondary metabolites, such as lignin, hormones, and flavonoids. Furthermore, amino acid metabolism lies at the crossroad of carbon and nitrogen metabolism. The Arabidopsis glutamine dumper1 (gdu1) mutant secretes glutamine from hydathodes, a phenotype caused by the overexpression of Glutamine Dumper1 (GDU1). GDU1 is a small transmembrane protein presents only in higher plants. The gdu1-1D mutant shows a pleiotropic phenotype: perturbed amino acid metabolism, tolerance to exogenous toxic concentrations of amino acids, elevated amino acid export, and activated stress/defense responses, lesions, and smaller rosettes. The biochemical function of GDU1 remains elusive. To better elucidate the biological processes leading to the complex Gdu1D phenotype, two approaches were conducted: (1) An ethyl methanesulfonate suppressor screening of the Gdu1D phenotype, which led to the isolation of intragenic mutations in GDU1 and mutations in the ubiquitin ligase LOG2 (Loss Of Gdu1D 2). Study of the intragenic mutations in GDU1 helped to characterize its structure-function relationships. Characterization of LOG2 showed that LOG2 interacts with GDU1 and is necessary for the Gdu1D phenotype. (2) The responses of the plant to the dexamethasone-induced expression of GDU1 were studied over time. This experiment identified major signaling pathways contributing to different components of the Gdu1D phenotype and the early events triggered by the perturbation of amino acid homeostasis. Our results showed that GDU1 overexpression first increases amino acid export, which is followed by amino acid imbalance and stress responses. This study sheds light on how amino acid imbalance interacts with various plant signaling pathways and stress responses, and suggests that LOG2 is involved in this process.
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    The Colonizers and Their Colonized
    Grene, Ruth (Virginia Tech, 2019-01-09)
    This study is concerned with the Self/Other dichotomy, originally formulated by scholars of South Asian history in the context of European imperialistic treatments of the peoples whom they colonized for centuries, as applied to Mexican history. I have chosen some visual, cinematic, and literary representations of indigenous and other dispossessed peoples from both colonial and post-colonial Mexico in order to gain some insights into the vision of the powerless, (the 'Other'), held by the powerful (the colonizers, whether internal or external), especially, but not exclusively, in the context of race. Some public and private works of Mexican art from the 18th , 19th. and the 20th centuries are used to understand the perceptions of the Other in Colonial Mexico City, at the time of Independence, in state-sponsored pre and post-Revolutionary spectacles representing indigenous peoples, cinematic representations of the marginalized and the dispossessed from the Golden Age of Mexican cinema, and in the representation of the marginalized in the literary and photographic works of Juan Rulfo. I conclude that an ambivalent mixture co-existed in Mexican culture through the centuries, on the one hand, honoring the blending that is expressed in the word 'mestizaje', and on the other, adhering to a thoroughly Eurocentric world view. This ambivalence persisted from the 18th century through Independence and the Revolution and its aftermath, albeit in transformed '
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    Comparing time series transcriptome data between plants using a network module finding algorithm
    Lee, Jiyoung; Heath, Lenwood S.; Grene, Ruth; Li, Song (2019-06-01)
    Background Comparative transcriptome analysis is the comparison of expression patterns between homologous genes in different species. Since most molecular mechanistic studies in plants have been performed in model species, including Arabidopsis and rice, comparative transcriptome analysis is particularly important for functional annotation of genes in diverse plant species. Many biological processes, such as embryo development, are highly conserved between different plant species. The challenge is to establish one-to-one mapping of the developmental stages between two species. Results In this manuscript, we solve this problem by converting the gene expression patterns into co-expression networks and then apply network module finding algorithms to the cross-species co-expression network. We describe how such analyses are carried out using bash scripts for preliminary data processing followed by using the R programming language for module finding with a simulated annealing method. We also provide instructions on how to visualize the resulting co-expression networks across species. Conclusions We provide a comprehensive pipeline from installing software and downloading raw transcriptome data to predicting homologous genes and finding orthologous co-expression networks. From the example provided, we demonstrate the application of our method to reveal functional conservation and divergence of genes in two plant species.
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    Computational Analysis of Gene Expression Regulation from Cross Species Comparison to Single Cell Resolution
    Lee, Jiyoung (Virginia Tech, 2020-08-31)
    Gene expression regulation is dynamic and specific to various factors such as developmental stages, environmental conditions, and stimulation of pathogens. Nowadays, a tremendous amount of transcriptome data sets are available from diverse species. This trend enables us to perform comparative transcriptome analysis that identifies conserved or diverged gene expression responses across species using transcriptome data. The goal of this dissertation is to develop and apply approaches of comparative transcriptomics to transfer knowledge from model species to non-model species with the hope that such an approach can contribute to the improvement of crop yield and human health. First, we presented a comprehensive method to identify cross-species modules between two plant species. We adapted the unsupervised network-based module finding method to identify conserved patterns of co-expression and functional conservation between Arabidopsis, a model species, and soybean, a crop species. Second, we compared drought-responsive genes across Arabidopsis, soybean, rice, corn, and Populus in order to explore the genomic characteristics that are conserved under drought stress across species. We identified hundreds of common gene families and conserved regulatory motifs between monocots and dicots. We also presented a BLS-based clustering method which takes into account evolutionary relationships among species to identify conserved co-expression genes. Last, we analyzed single-cell RNA-seq data from monocytes to attempt to understand regulatory mechanism of innate immune system under low-grade inflammation. We identified novel subpopulations of cells treated with lipopolysaccharide (LPS), that show distinct expression patterns from pro-inflammatory genes. The data revealed that a promising therapeutic reagent, sodium 4-phenylbutyrate, masked the effect of LPS. We inferred the existence of specific cellular transitions under different treatments and prioritized important motifs that modulate the transitions using feature selection by a random forest method. There has been a transition in genomics research from bulk RNA-seq to single-cell RNA-seq, and scRNA-seq has become a widely used approach for transcriptome analysis. With the experience we gained by analyzing scRNA-seq data, we plan to conduct comparative single-cell transcriptome analysis across multiple species.
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    CoSpliceNet: a framework for co-splicing network inference from transcriptomics data
    Aghamirzaie, Delasa; Collakova, Eva; Li, Song; Grene, Ruth (BMC, 2016)
    Background: Alternative splicing has been proposed to increase transcript diversity and protein plasticity in eukaryotic organisms, but the extent to which this is the case is currently unclear, especially with regard to the diversification of molecular function. Eukaryotic splicing involves complex interactions of splicing factors and their targets. Inference of co-splicing networks capturing these types of interactions is important for understanding this crucial, highly regulated post-transcriptional process at the systems level. Results: First, several transcript and protein attributes, including coding potential of transcripts and differences in functional domains of proteins, were compared between splice variants and protein isoforms to assess transcript and protein diversity in a biological system. Alternative splicing was shown to increase transcript and functionrelated protein diversity in developing Arabidopsis embryos. Second, CoSpliceNet, which integrates co-expression and motif discovery at splicing regulatory regions to infer co-splicing networks, was developed. CoSpliceNet was applied to temporal RNA sequencing data to identify candidate regulators of splicing events and predict RNAbinding motifs, some of which are supported by prior experimental evidence. Analysis of inferred splicing factor targets revealed an unexpected role for the unfolded protein response in embryo development. Conclusions: The methods presented here can be used in any biological system to assess transcript diversity and protein plasticity and to predict candidate regulators, their targets, and RNA-binding motifs for splicing factors. CoSpliceNet is freely available at http://delasa.github.io/co-spliceNet/.
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    DeTangle: A Framework for Interactive Prediction and Visualization of Gene Regulatory Networks
    Altarawy, Doaa Abdelsalam Ahmed Mohamed (Virginia Tech, 2017-05-02)
    With the abundance of biological data, computational prediction of gene regulatory networks (GRNs) from gene expression data has become more feasible. Although incorporating other prior knowledge (PK), along with gene expression, greatly improves prediction accuracy, the accuracy remains low. PK in GRN inference can be categorized into noisy and curated. Several algorithms were proposed to incorporate noisy PK, but none address curated PK. Another challenge is that much of the PK is not stored in databases or not in a unified structured format to be accessible by inference algorithms. Moreover, no GRN inference method exists that supports post-prediction PK. This thesis addresses those limitations with three solutions: PEAK algorithm for integrating both curated and noisy PK, Online-PEAK for post-prediction interactive feedback, and DeTangle for visualization and navigation of GRNs. PEAK integrates both curated as well as noisy PK in GRN inference. We introduce a novel method for GRN inference, CurInf, to effectively integrate curated PK, and we use the previous method, Modified Elastic Net, for noisy PK, and we call it NoisInf. Using 100% curated PK, CurInf improves the AUPR accuracy score over NoisInf by 27.3% in synthetic data, 86.5% in E. coli data, and 31.1% in S. cerevisiae data. Moreover, we developed an online algorithm, online-PEAK, that enables the biologist to interact with the inference algorithm, PEAK, through a visual interface to add their domain experience about the structure of the GRN as a feedback to the system. We experimentally verified the ability of online-PEAK to achieve incremental accuracy when PK is added by the user, including true and false PK. Even when the noise in PK is 10 times more than true PK, online-PEAK performs better than inference without any PK. Finally, we present DeTangle, a Web server for interactive GRN prediction and visualization. DeTangle provides a seamless analysis of GRN starting from uploading gene expression, GRN inference, post-prediction feedback using online-PEAK, and visualization and navigation of the predicted GRN. More accurate prediction of GRN can facilitate studying complex molecular interactions, understanding diseases, and aiding drug design.
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    Developing machine learning tools to understand transcriptional regulation in plants
    Song, Qi (Virginia Tech, 2019-09-09)
    Abiotic stresses constitute a major category of stresses that negatively impact plant growth and development. It is important to understand how plants cope with environmental stresses and reprogram gene responses which in turn confers stress tolerance. Recent advances of genomic technologies have led to the generation of much genomic data for the model plant, Arabidopsis. To understand gene responses activated by specific external stress signals, these large-scale data sets need to be analyzed to generate new insight of gene functions in stress responses. This poses new computational challenges of mining gene associations and reconstructing regulatory interactions from large-scale data sets. In this dissertation, several computational tools were developed to address the challenges. In Chapter 2, ConSReg was developed to infer condition-specific regulatory interactions and prioritize transcription factors (TFs) that are likely to play condition specific regulatory roles. Comprehensive investigation was performed to optimize the performance of ConSReg and a systematic recovery of nitrogen response TFs was performed to evaluate ConSReg. In Chapter 3, CoReg was developed to infer co-regulation between genes, using only regulatory networks as input. CoReg was compared to other computational methods and the results showed that CoReg outperformed other methods. CoReg was further applied to identified modules in regulatory network generated from DAP-seq (DNA affinity purification sequencing). Using a large expression dataset generated under many abiotic stress treatments, many regulatory modules with common regulatory edges were found to be highly co-expressed, suggesting that target modules are structurally stable modules under abiotic stress conditions. In Chapter 4, exploratory analysis was performed to classify cell types for Arabidopsis root single cell RNA-seq data. This is a first step towards construction of a cell-type-specific regulatory network for Arabidopsis root cells, which is important for improving current understanding of stress response.
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    Dissection of Drought Responses in Arabidopsis
    Harb, Amal Mohammad (Virginia Tech, 2010-07-19)
    Plants as sessile organisms are susceptible to many environmental stresses such as drought, and salinity. They have therefore evolved mechanisms to acclimate and tolerate environmental stresses. Knowledge of the molecular aspects of abiotic stress gleaned from extensive studies in Arabidopsis has provided much information on the complex processes underlying plant response to abiotic stresses. Nevertheless, there is a need for integration of the knowledge gained and a systematic molecular genetic dissection of the complex responses to abiotic stress. In this study in Arabidopsis, comparative expression profiling analysis of progressive (pDr) and moderate (mDr) drought treatments revealed common drought responses, as well as treatment specific signatures responses to drought stress. Under prolonged moderate drought plants develop different mechanisms for acclimation: induction of cell wall loosening at early stage, and a change in hormonal balance (ABA: JA) at late stage of moderate drought. Taking a reverse genetics approach, a MYB transcription factor (MYB109) has been identified as a regulator of growth under drought and salt stress. Global expression profiling showed possible mechanisms of how MYB109 modulates growth under drought conditions: as a regulator of RNA processing and splicing and as a negative regulator of jasmonic acid biosynthesis and signaling. A forward genetics screen for drought and salt tolerance of transposon activation tag (ATag) lines led to the discovery of novel genes, which shed light on unexplored areas of abiotic stress biology. Utilizing this strategy, a potential role for cell wall modification and MATE transporters in response to drought and salt stress has been discovered, which needs further analysis to integrate this information on the role of these biological processes in plant stress biology.
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    Effects of Drought on Gene Expression in Maize Reproductive and Leaf Meristem Tissues as Revealed by Deep Sequencing
    Kakumanu, Akshay (Virginia Tech, 2012-06-28)
    Drought is a major environmental stress factor that poses a serious threat to food security. The effects of drought on early reproductive tissue at 1-2 DAP (days after pollination) is irreversible in nature and leads to embryo abortion, directly affecting the grain yield production. We developed a working RNA-Seq pipeline to study maize (Zea mays) drought transcriptome sequenced by Illumina GSIIx technology to compare drought treated and well- watered fertilized ovary (1-2DAP) and basal leaf meristem tissue. The pipeline also identified novel splice junctions - splice variants of previously known gene models and potential novel transcription units. An attempt was also made to exploit the data to understand the drought mediated transcriptional events (e.g. alternative splicing). Gene Ontology (GO) enrichment analysis revealed massive down-regulation of cell division and cell cycle genes in the drought stressed ovary only. Among GO categories related to carbohydrate metabolism, changes in starch and sucrose metabolism-related genes occurred in the ovary, consistent with a decrease in starch levels, and in sucrose transporter function, with no comparable changes occurring in the leaf meristem. ABA-related processes responded positively, but only in the ovaries. GO enrichment analysis also suggested differential responses to drought between the two tissues in categories such as oxidative stress-related and cell cycle events. The data are discussed in the context of the susceptibility of maize kernel to drought stress leading to embryo abortion, and the relative robustness of actively dividing vegetative tissue taken at the same time from the same plant subjected to the same conditions. A hypothesis is formulated, proposing drought-mediated intersecting effects on the expression of invertase genes, glucose signaling (hexokinase 1-dependent and independent), ABA-dependent and independent signaling, antioxidant responses, PCD, phospholipase C effects, and cell cycle related processes. This work was supported by the National Science Foundation Plant Genome Research Pro- gram (grant no. DBI0922747), iPlant Collaborative (NSF DBI-0735191) and also NSF ABI1062472.
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    Evidence for extensive heterotrophic metabolism, antioxidant action, and associated regulatory events during winter hardening in Sitka spruce
    Collakova, Eva; Klumas, Curtis; Suren, Haktan; Myers, Elijah; Heath, Lenwood S.; Holliday, Jason A.; Grene, Ruth (2013-04-30)
    Background Cold acclimation in woody perennials is a metabolically intensive process, but coincides with environmental conditions that are not conducive to the generation of energy through photosynthesis. While the negative effects of low temperatures on the photosynthetic apparatus during winter have been well studied, less is known about how this is reflected at the level of gene and metabolite expression, nor how the plant generates primary metabolites needed for adaptive processes during autumn. Results The MapMan tool revealed enrichment of the expression of genes related to mitochondrial function, antioxidant and associated regulatory activity, while changes in metabolite levels over the time course were consistent with the gene expression patterns observed. Genes related to thylakoid function were down-regulated as expected, with the exception of plastid targeted specific antioxidant gene products such as thylakoid-bound ascorbate peroxidase, components of the reactive oxygen species scavenging cycle, and the plastid terminal oxidase. In contrast, the conventional and alternative mitochondrial electron transport chains, the tricarboxylic acid cycle, and redox-associated proteins providing reactive oxygen species scavenging generated by electron transport chains functioning at low temperatures were all active. Conclusions A regulatory mechanism linking thylakoid-bound ascorbate peroxidase action with “chloroplast dormancy” is proposed. Most importantly, the energy and substrates required for the substantial metabolic remodeling that is a hallmark of freezing acclimation could be provided by heterotrophic metabolism.
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    Exploration of Physiological and Molecular Responses to Precipitation Extremes in Soybean and Nitrogen Fertility in Wheat
    Gole Tamang, Bishal (Virginia Tech, 2016-09-27)
    Soybean and wheat are important crop species due to their significance for human consumption, animal feed, and industrial use. However, increasing global population and worsening climate change have put a major strain on the production system of these crops. Natural disasters such as flooding and drought can severely impact growth and productivity of these crops. In addition, increased application of synthetic nitrogenous fertilizers to meet the global food demand has led to environment related issues. Therefore, with a goal of understanding mechanisms of flooding and drought tolerance in soybean and nitrogen-use-efficiency in wheat, we explored their physiological and transcriptomic regulation. We characterized the fundamental acclimation responses of soybean to flooding and drought and compared the metabolic and transcriptomic regulation during the stresses in a tissue-specific manner. We demonstrated the dynamic reconfiguration of gene expression and metabolism during flooding, drought, and recovery from these stresses. Our study displayed that flooding triggers more dramatic adjustments than drought at the transcriptional level. We also identified that the soybean genome encodes nine members of group VII ERF genes and characterized their responses in leaves and roots under flooding and drought. Based on the expression patterns, it is estimated that two of the nine genes are promising candidate genes regulating tolerance to submergence and drought. In addition, our genome-scale expression analysis discovered commonly induced ERFs and MAPKs across both stresses (flooding and drought) and tissues (leaves and roots), which might play key roles in soybean survival of flooding and drought. In wheat, we evaluated the effect of three different nitrogen rates on yield and its components across four diverse soft red winter wheat genotypes. The cultivar Sisson displayed superior performance in grain yield and nitrogen use efficiency at low nitrogen levels. Our results suggested that improvement of nitrogen use efficiency in low nitrogen environments can be achieved through the selection of three components: grain number/spike, 1000-seed weight, and harvest index. Overall, this study has advanced our understanding of how plants respond to abiotic stresses such as flooding, drought, and nutrient limitation conditions.
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    Fusion: a Visualization Framework for Interactive Ilp Rule Mining With Applications to Bioinformatics
    Indukuri, Kiran Kumar (Virginia Tech, 2004-12-01)
    Microarrays provide biologists an opportunity to find the expression profiles of thousands of genes simultaneously. Biologists try to understand the mechanisms underlying the life processes by finding out relationships between gene-expression and their functional categories. Fusion is a software system that aids the biologists in performing microarray data analysis by providing them with both visual data exploration and data mining capabilities. Its multiple view visual framework allows the user to choose different views for different types of data. Fusion uses Proteus, an Inductive Logic Programming (ILP) rule finding algorithm to mine relationships in the microarray data. Fusion allows the user to explore the data interactively, choose biases, run the data mining algorithms and visualize the discovered rules. Fusion has the capability to smoothly switch across interactive data exploration and batch data mining modes. This optimizes the knowledge discovery process by facilitating a synergy between the interactivity and usability of visualization process with the pattern-finding abilities of ILP rule mining algorithms. Fusion was successful in helping biologists better understand the mechanisms underlying the acclimatization of certain varieties of Arabidopsis to ozone exposure.
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    GeneSieve: A Probe Selection Strategy for cDNA Microarrays
    Shukla, Maulik (Virginia Tech, 2004-08-24)
    The DNA microarray is a powerful tool to study expression levels of thousands of genes simultaneously. Often, cDNA libraries representing expressed genes of an organism are available, along with expressed sequence tags (ESTs). ESTs are widely used as the probes for microarrays. Designing custom microarrays, rich in genes relevant to the experimental objectives, requires selection of probes based on their sequence. We have designed a probe selection method, called GeneSieve, to select EST probes for custom microarrays. To assign annotations to the ESTs, we cluster them into contigs using PHRAP. The larger contig sequences are then used for similarity search against known proteins in model organism such as Arabidopsis thaliana. We have designed three different methods to assign annotations to the contigs: bidirectional hits (BH), bidirectional best hits (BBH), and unidirectional best hits (UBH). We apply these methods to pine and potato EST sets. Results show that the UBH method assigns unambiguous annotations to a large fraction of contigs in an organism. Hence, we use UBH to assign annotations to ESTs in GeneSieve. To select a single EST from a contig, GeneSieve assigns a quality score to each EST based on its protein homology (PH), cross hybridization (CH), and relative length (RL). We use this quality score to rank ESTs according to seven different measures: length, 3' proximity, 5' proximity, protein homology, cross hybridization, relative length, and overall quality score. Results for pine and potato EST sets indicate that EST probes selected by quality score are relatively long and give better values for protein homology and cross hybridization. Results of the GeneSieve protocol are stored in a database and linked with sequence databases and known functional category schemes such as MIPS and GO. The database is made available via a web interface. A biologist is able to select large number of EST probes based on annotations or functional categories in a quick and easy way.
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    Glutathione Dynamics in Arabidopsis Seed Development and Germination
    Sumugat, Mae Rose S. (Virginia Tech, 2004-12-09)
    Seed desiccation and germination have great potential for oxidative stress. Glutathione, one of the most abundant antioxidants in plant cells, is a crucial to the plant's defense mechanisms. To better understand glutathione's responses during these two stages, we examined its dynamics in wildtype Arabidopsis seeds and in a transgenic line containing an antisense glutathione reductase2 (anGR2) cDNA insert. Seeds from the two genotypes were compared morphologically. Glutathione levels in maturing and germinating seeds were measured by HPLC, and GR activity by native PAGE. Cytosolic glutathione was measured in situ by confocal laser scanning microscopy. Stress in the form of natural and accelerated ageing, and germination at high and low temperature and at low water potential was applied to both WT and anGR2 seeds to test vigor. Results show similar glutathione levels and GR activity (except during late imbibition) in WT and anGR2. In both genotypes, GSH/GSSG ratio increased and GR activity decreased during seed maturation. During imbibition, the glutathione pool becomes very reduced (<1% GSSG) and in WT seeds, GSH levels increase mostly by GSSG recycling. Cytosolic GSH in embryonic epidermal cells was estimated to be 1.1-1.6 mM. AnGR2 seeds aged faster, and were less tolerant of heat and drought stress than WT. Accumulation of glutathione during maturation indicated that glutathione is a major antioxidant in the seed during storage. Changes in GSH levels during imbibition coincided with ROS production during radicle protrusion. Under stress conditions, anGR2 seeds showed lower vigor, indicating perturbations in the ROS scavenging systems particularly GR2.
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    GridWeaver: A Fully-Automatic System for Microarray Image Analysis Using Fast Fourier Transforms
    Vergara, John Paul C.; Heath, Lenwood S.; Grene, Ruth; Ramakrishnan, Naren; Watson, Layne T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2008)
    Experiments using microarray technology generate large amounts of image data that are used in the analysis of genetic function. An important stage in the analysis is the determination of relative intensities of spots on the images generated. This paper presents GridWeaver, a program that reads in images from a microarray experiment, automatically locates subgrids and spots in the images, and then determines the spot intensities needed in the analysis of gene function. Automatic gridding is performed by running Fast Fourier Transforms on pixel intensity sums. Tests on several data sets show that the program responds well even on images that have significant noise, both random and systemic.
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    Identification of Drought-Responsive Genes and Validation for Drought Resistance in Rice
    Batlang, Utlwang (Virginia Tech, 2010-01-05)
    Drought stress was studied in rice (Oryza sativa) and maize (Zea mays) to identify drought-responsive genes and associated biological processes. One experiment with rice examined drought responses in vegetative and reproductive tissues and identified drought-responsive genes in each tissue type. The results showed that brief periods of acute drought stress at or near anthesis reduced photosynthetic efficiency and ultimately lowered grain yield. Yield was reduced as a result both of fewer spikelets developed and of lower spikelet fertility. Affymetrix arrays were used to analyze global gene expression in the transcriptomes of rice vegetative and reproductive tissue. Comparative analysis of the expressed genes indicated that the vegetative and reproductive tissues responded differently to drought stress. An experiment was conducted with maize, using GS-FLX pyrosequencing to identify differentially expressed genes in vegetative and reproductive tissues; and these results were compared with those from the just-described rice transcriptome. Some of the drought-responsive genes in the maize reproductive tissue were validated by quantitative real time polymerase chain reaction (qRT-PCR). The differentially expressed genes common to both maize and rice were further analyzed by gene ontology analysis to reveal core biological processes involved in drought responses. In both species, drought caused a transition from protein synthesis to degradation, and photosynthesis was one of the most severely affected metabolic pathways. In a validating experiment, a drought-responsive transcription factor found in rice and dubbed HIGHER YIELD RICE (HYR) was constitutively expressed in rice, and the transgenic HYR plants were studied. Under well-watered conditions, the HYR plants developed higher rates of photosynthesis, greater levels of soluble sugars (glucose, fructose, and sucrose), more biomass, and higher yield. They also exhibited a drought-resistant phenotype, with higher water use efficiency, photosynthesis, and relative leaf water content under drought stress. Taken together, these studies demonstrate the potential value of newer technologies for identifying genes that might impart drought resistance and for using such genes to make crops more productive either in the presence or in the absence of drought stress.
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    Identification of regulatory modules in genome scale transcription regulatory networks
    Song, Qi; Grene, Ruth; Heath, Lenwood S.; Li, Song (2017-12-15)
    Background In gene regulatory networks, transcription factors often function as co-regulators to synergistically induce or inhibit expression of their target genes. However, most existing module-finding algorithms can only identify densely connected genes but not co-regulators in regulatory networks. Methods We have developed a new computational method, CoReg, to identify transcription co-regulators in large-scale regulatory networks. CoReg calculates gene similarities based on number of common neighbors of any two genes. Using simulated and real networks, we compared the performance of different similarity indices and existing module-finding algorithms and we found CoReg outperforms other published methods in identifying co-regulatory genes. We applied CoReg to a large-scale network of Arabidopsis with more than 2.8 million edges and we analyzed more than 2,300 published gene expression profiles to charaterize co-expression patterns of gene moduled identified by CoReg. Results We identified three types of modules in the Arabidopsis network: regulator modules, target modules and intermediate modules. Regulator modules include genes with more than 90% edges as out-going edges; Target modules include genes with more than 90% edges as incoming edges. Other modules are classified as intermediate modules. We found that genes in target modules tend to be highly co-expressed under abiotic stress conditions, suggesting this network struture is robust against perturbation. Conclusions Our analysis shows that the CoReg is an accurate method in identifying co-regulatory genes in large-scale networks. We provide CoReg as an R package, which can be applied in finding co-regulators in any organisms with genome-scale regulatory network data.