NSF Microarray Grants Awarded July 15 — Sept. 15, 2009
Chemotaxis and the regulation of multiple cellular functions in a bacterium. Start date: July 15, 2009. Expires: June 30, 2012. Awarded amount to date: $587,546. Principal investigator: Gladys Alexandre. Sponsor: University of Tennessee - Knoxville
This project focuses on establishing the molecular basis of the coordinated control of chemotaxis, aggregation, and cell length mediated by the chemotactic pathway in Azospirillum brasilense. The researchers intend to characterize in molecular detail changes in cell surface properties during aggregation. Specifically, the project will characterize the structure of the oligosaccharides produced by aggregating cells and their interaction with outer membrane proteins. Whole-genome microarray and mutagenesis experiments will be used to identify the genes responsible for cell-to-cell interactions. The project will also test the hypothesis that interaction of the response regulator CheY with the polar flagellar motor complex results in cell length changes and aggregation via an effect on other molecular targets.
Nonparametric curve estimation in the presence of nuisance functions. Start date: Aug. 1, 2009. Expires: July 31, 2010. Awarded amount to date: $114,122. Principal investigator: Sam Efromovich. Sponsor: University of Texas at Dallas
The aim of this research project is to create adaptive statistical procedures that can work in the presence of nuisance functions. This research will be tested on: a) ChIP-on-chip microarrays used to find regulatory protein binding sites in a bacterial genome; and b) ultra-fast functional magnet resonance images, which help in understanding aging and brain diseases such as Alzheimer's and Parkinson's diseases.
Novel methods for pharmacogenomic data analysis using gene clusters. Start date: Aug. 15, 2009. Expires: July 31, 2012. Awarded amount to date: $100,000. Principal investigator: Michael Kosorok. Sponsor: University of North Carolina at Chapel Hill
The goal of this study is to develop a systematic framework using principal component analysis-based methods to detect gene clusters differentially expressed and with joint predictive power. Specifically, the investigators plan to: develop methodology to detect gene clusters marginally differentially expressed; develop penalization methodology to detect gene clusters with joint predictive power for the disease clinical outcomes of interest; conduct extensive numerical studies; and develop publicly available software. According to the inventors, the study will use microarray data to arrive at a "deeper understanding" of the genomic mechanisms underlying breast cancer, colon cancer, and lymphoma.
Phylogenomics. Start date: Aug. 15, 2009. Expires: July 31, 2010. Awarded amount to date: $217,159. Principal investigator: David Hillis. Sponsor: University of Texas at Austin
The inventors aim to develop a method for producing large amounts of high-quality DNA sequence data for phylogenomic applications. The project will extend microarray-based genome selection, which is capable of enriching a DNA sample for thousands of genes, to simultaneous enrichment across distantly related species. According to the investigators, this study has the potential to address the remaining obstacles to microarray hybridization across species and result in hugely increased scaling of microarray-based genome selection technology.
Genomic approaches to identify insect resistance genes in poplar trees. Start date: Aug. 15, 2009. Expires: July 31, 2012. Awarded amount to date: $677,356. Principal investigator: Steven Ralph. Sponsor: University of North Dakota
In previous studies undertaken by the investigators, several dozen mutant lines in poplar trees were identified as resistant to feeding by defoliating insects. In this project, the modified gene in at least 10 of these insect-resistant lines will be identified. The roles these genes play in mediating insect resistance will be examined in poplar through both gene knock-down and over-expression studies. Additionally, mutant plants will be subject to thorough phenotypic characterization that includes evaluation of global changes in gene expression and measurement of insect feeding performance and larval development. The investigators expect that these studies will provide insight into the genes and pathways that enhance resistance to feeding insects. Identification of specific insect-resistance genes will enable breeding of improved tree varieties in the future, they claim.
SBIR Phase II: New labeling reagents for genetic analysis. Start date: Aug. 15, 2009. Expires: July 31, 2011. Awarded amount to date: $499,889. Principal investigator: John Naleway. Sponsor: Marker Gene Technologies
Marker Gene Technologies has developed a direct labeling approach for use in microarray analysis. The firm said it has validated its detection methods by preparing ultrasensitive fluorescent-labeling reagents and protocols for directly labeling DNA or RNA samples isolated from live cells. In Phase II of this project, these systems will be validated by further analysis of the fluorescent labeling methods and characterization of their ability to monitor changes in gene expression upon application of drugs or other bioactive compounds or in response to biological changes in cell function or disease, in a cell-specific manner, the investigators state.
A combined biochemical, molecular and computational approach to understanding the regulation of gibberellin biosynthesis in Arabidopsis. Start date: Sept. 1, 2009. Expires: Aug. 31, 2010. Awarded amount to date: $150,000. Principal investigator: Valerie Sponsel. Sponsor: University of Texas at San Antonio.
The investigators in this project will examine the transcriptional regulation of gene-encoding enzymes in the gibberellin biosynthetic pathway in the model plant Arabidopsis thaliana. It focuses on how 2-oxoglutarate-dependent dioxygenase enzymes are regulated by internal factors including gibberellins and other plant hormones, such as auxin. Integrated computational analysis of promoter sequences and of publicly available large-scale microarray data will be performed to determine if particular motifs are shared between 2-oxoglutarate-dependent dioxygenases that have common regulation, and to construct quantitative, predictive models of transcriptional regulation using those motifs. The investigators plan to test whether these motifs define cis-regulatory elements that are responsible for timing, location, and hormonal regulation of transcriptional activity in Arabidopsis seedlings.
Extending the RAST server to support reconstruction and modeling of cellular networks. Start date: Sept. 1, 2009. Expires: Aug. 31, 2011. Awarded amount to date: $1,267,183. Principal investigators: Matthew DeJongh. Sponsor: Hope College
This grant supports the development of software tools to enable three types of analyses that will be integrated into the Rapid Annotation using Subsystem Technology server: a) generation and refinement of genome-scale metabolic reaction networks; b) genome-based prediction of transcriptional regulons; and c) analysis of gene-expression microarray data and regulatory network prediction. The resulting extended RAST server will provide the research community with an integrated suite of tools that enables analyses of genomic and high-throughput transcription data, according to the grant abstract.
Bayesian data mining approaches for biological threat detection. Start date: Sept. 1, 2009. Expires: Aug. 31, 2010. Awarded amount to date: $275,818. Principal investigator: Bani Mallick. Sponsor: Texas A&M Research Foundation
The investigators plan to use Bayesian detection methods combining prior biological information as well as data from different biological platforms to detect pathogens. Gene-expression microarray data as well as massively-parallel signature sequencing will be combined by a data fusion method to perform proper inference about the unknowns. Gene networks models will be developed to identify the dependence and interactions among the genes. The investigators plan to develop hierarchical Bayesian models where the data from different sources will be related to each other by conditional models at different stages of the hierarchy. They will consider nonparametric models to automatically cluster the genes. A Bayesian graph-clustering model will be developed by combining local Gaussian models and the Dirichlet process. Markov chain Monte Carlo-based computation methods will be used to draw samples from the posterior distribution.
Computational infrastructure for the identification of copy number variations from SNP microarrays. Start date: Sept. 1, 2009. Expires: Aug. 31, 2012. Awarded amount to date: $497,603. Principal investigator: Mehmet Koyuturk. Sponsor: Case Western Reserve University.
The objective of this project is to develop optimization-based algorithms and software for the identification and genotyping of copy number variations, and to enable the identification of different types of CNVs, both rare and common, without training data. The investigators plan to use a computational approach by formulating CNV identification as a series of optimization problems that incorporate multiple factors, including sensitivity to noise, rarity and commonality of CNVs, genotypic specificity, and parsimony. They plan to make the developed software available to the research community.
Methods for characterizing small genes in bacteria. Start date: Sept. 1, 2009. Expires: Aug. 31, 2012. Awarded amount to date: $327,007. Principal investigator: Brian Tjaden. Sponsor: Wellesley College
The investigators plan to develop bioinformatics methods for the systematic identification of small, noncoding RNA genes and their regulatory targets. Using a combination of computational and experimental approaches, small-noncoding RNA genes will be investigated in Shewanella oneidensis. Specifically, the role of noncoding RNAs in metal reduction will be studied. Additionally, a bioinformatics tool will be developed for characterizing short open reading frames in bacterial genomes. The tool will be based on a framework that incorporates primary sequence data with comparative genomics information and genome-tiling microarray measurements for the purpose of predicting short genes encoding new small proteins.
Stochastic dynamic network models of gene regulation under environmental stress. Start date: Sept. 1, 2009. Expires: Aug. 31, 2012. Awarded amount to date: $246,123. Principal investigator: Kam Dahlquist. Sponsor: Loyola Marymount University
This project aims to identify the network of transcription factors that regulate the response to cold shock in budding yeast, Saccharomyces cerevisiae, through a combination of mining of publicly available data, the genetic screening of systematic yeast deletion strains and the analysis of in-house microarray data, and a Bayesian approach to network reconstruction based on our model. In addition, the investigators intend to analyze the model by comparing it to deterministic chemical kinetic and dynamic Bayesian network models in development and use in the research community; and to develop models of the additional exogenous perturbations of multiple temperature shifts and the resultant affect on growth rate for integration into the stochastic dynamic network model. They also plan to test the model predictions using qRT-PCR and microarrays on both total RNA and transcriptionally active mRNA, in both wild type and gene-deletion strains; and to develop and analyze a general mathematical modeling framework suitable for studying a wide variety of gene regulatory networks.
Post-transcriptional control of immunoglobulin expression. Start date: Sept. 1, 2009. Expires: Aug. 31, 2012. Awarded amount to date: $525,000. Principal investigator: Martha Peterson. Sponsor: University of Kentucky Research Foundation
This project will explore the mechanistic interconnections between RNA processing events, such as splicing and cleavage-polyadenylation, and transcription elongation and termination in the immunoglobulin M gene. The investigators believe the M gene is an "excellent model system" to study, as its expression is regulated during B lymphocyte maturation at multiple steps, including RNA splicing, cleavage-polyadenylation and transcription termination. The investigators will use a collection of well-characterized modified M genes and multiple reagents to analyze M gene expression and microarray data from B cells before and after being stimulated to differentiate. They aim to identify trans-regulators of M-alternative RNA processing based on microarray data and gene expression experiments, to determine how RNA processing signals affect RNA polymerase II elongation, using a combination of nuclear run-on and high-resolution chromatin-immunoprecipitation-on-chip assays, and to characterize changes in factors associated with elongating pol II over wild-type and modified µ genes in B cells and plasma cells by high-resolution ChIP experiments.
Cereal drought stress response and resistance networks. Start date: Sept. 15, 2009. Expires: Aug. 31, 2010. Awarded amount to date: $839,916. Principal investigator: Andy Pereira. Sponsor: Virginia Polytechnic Institute and State University
The goal of this project is to develop a systems biology-based view of drought responses in cereals to improve drought resistance and water use efficiency. Genome-wide comparative transcriptome analysis of drought responses in rice and maize will be integrated into a cereal drought gene interaction network, using ortholog information to predict conserved functional relationships as a basis for cereals. Conserved orthologous regulatory genes between rice and maize involved in drought responses and resistance will be identified comprising transcription factors, protein kinases and phosphatases, genes in hormone signaling pathways, chromatin-binding proteins, protein degradation and small-RNA pathways. To demonstrate proof of principle, a set of these putative conserved rice and maize genes will be tested by genetic analysis of mutants and natural allelic variant to assess them for altered drought response phenotypes and perturbation in the drought gene interaction network. The investigators believe these analyses will validate and improve the cereal gene interaction network predictions, and provide candidate genes for improvement of drought resistance and tolerance in cereals.