Conlon, Erin

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Associate Professor, Department of Math and Statistics
Last Name
Conlon
First Name
Erin
Discipline
Microarrays
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Bayesian models for the analysis of genomic data and comparative genomics
Microarray and DNA sequence analysis
Introduction
Erin Conlon develops statistical methods for integrating multiple sources of genomic information, including microarray, DNA sequence and functional data. She also develops Bayesian models for genomic data, currently focusing on gene expression meta-analysis. Further research areas involve comparative genomics approaches to identifying genetic regulatory networks in prokaryotic species.
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2007 - 200922010 - 20182
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Now showing 1 - 4 of 4
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    Hierarchical Bayesian meta-analysis models for cross-platform microarray studies
    (2009) Conlon, Erin; Postier, B; Methe, BA; Nevin, KP; Lovley, DR
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    PublicationOpen Access
    A Bayesian Model for Pooling Gene Expression Studies That Incorporates Co-Regulation Information
    (2012) Conlon, Erin; Postier, B; Methe, BA; Nevin, KP; Lovley, DR
    Current Bayesian microarray models that pool multiple studies assume gene expression is independent of other genes. However, in prokaryotic organisms, genes are arranged in units that are co-regulated (called operons). Here, we introduce a new Bayesian model for pooling gene expression studies that incorporates operon information into the model. Our Bayesian model borrows information from other genes within the same operon to improve estimation of gene expression. The model produces the gene-specific posterior probability of differential expression, which is the basis for inference. We found in simulations and in biological studies that incorporating co-regulation information improves upon the independence model. We assume that each study contains two experimental conditions: a treatment and control. We note that there exist environmental conditions for which genes that are supposed to be transcribed together lose their operon structure, and that our model is best carried out for known operon structures.
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    PublicationOpen Access
    Rapid Changes in Gene Expression Dynamics in Response to Superoxide Reveal SoxRS-Dependent and Independent Transcriptional Networks
    (2007) Blanchard, Jeffrey L.; Wholey, Wei-Yun; Conlon, Erin; Pomposiello, Pablo J.
    Background SoxR and SoxS constitute an intracellular signal response system that rapidly detects changes in superoxide levels and modulates gene expression in E. coli. A time series microarray design was used to identify co-regulated SoxRS-dependent and independent genes modulated by superoxide minutes after exposure to stress. Methodology/Principal Findings soxS mRNA levels surged to near maximal levels within the first few minutes of exposure to paraquat, a superoxide-producing compound, followed by a rise in mRNA levels of known SoxS-regulated genes. Based on a new method for determining the biological significance of clustering results, a total of 138 genic regions, including several transcription factors and putative sRNAs were identified as being regulated through the SoxRS signaling pathway within 10 minutes of paraquat treatment. A statistically significant two-block SoxS motif was identified through analysis of the SoxS-regulated genes. The SoxRS-independent response included members of the OxyR, CysB, IscR, BirA and Fur regulons. Finally, the relative sensitivity to superoxide was measured in 94 strains carrying deletions in individual, superoxide-regulated genes. Conclusions/Significance By integrating our microarray time series results with other microarray data, E. coli databases and the primary literature, we propose a model of the primary transcriptional response containing 226 protein-coding and sRNA sequences. From the SoxS dependent network the first statistically significant SoxS-related motif was identified.
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    PublicationOpen Access
    Genome Sequence of Verrucomicrobium sp. Strain GAS474, a Novel Bacterium Isolated from Soil
    (2018) Pold, Grace; Conlon, Erin; Huntemann, Marcel; Pillay, Manoj; Mikhailova, Natalia; Stamatis, Dimitrios; Reddy, T.B.K.; Daum, Chris; Shapiro, Nicole; Kyrpides, Nikos C.; Woyke, Tanja; DeAngelis, Kristen
    Verrucomicrobium sp. strain GAS474 was isolated from the mineral soil of a temperate deciduous forest in central Massachusetts. Here, we present the complete genome sequence of this phylogenetically novel organism, which consists of a total of 3,763,444 bp on a single scaffold, with a 65.8% GC content and 3,273 predicted open reading frames.