Biomedical subjects

Erin M Conlon

Publications and source records attributed to Erin M Conlon.

7 recordsLinked to original sources

PubMed2006

Bayesian models for pooling microarray studies with multiple sources of replications.

BACKGROUND: Biologists often conduct multiple but different cDNA microarray studies that all target the same biological system or pathway. Within each study, replicate slides within repeated identical experiments are often produced. Pooling information across studies can help more accurately identify true target genes. Here, we introduce a method to integrate multiple independent studies efficiently. RESULTS: We introduce a Bayesian hierarchical model to pool cDNA microarray data across multiple independent studies to identify highly expressed genes. Each study has multiple sources of variation, i.e. replicate slides within repeated identical experiments. Our model produces the gene-specific posterior probability of differential expression, which provides a direct method for ranking genes, and provides Bayesian estimates of false discovery rates (FDR). In simulations combining two and five independent studies, with fixed FDR levels, we observed large increases in the number of discovered genes in pooled versus individual analyses. When the number of output genes is fixed (e.g., top 100), the pooled model found appreciably more truly differentially expressed genes than the individual studies. We were also able to identify more differentially expressed genes from pooling two independent studies in Bacillus subtilis than from each individual data set. Finally, we observed that in our simulation studies our Bayesian FDR estimates tracked the true FDRs very well. CONCLUSION: Our method provides a cohesive framework for combining multiple but not identical microarray studies with several sources of replication, with data produced from the same platform. We assume that each study contains only two conditions: an experimental and a control sample. We demonstrated our model's suitability for a small number of studies that have been either pre-scaled or have no outliers.

Bacillus subtilis↗

PubMed2006

The forespore line of gene expression in Bacillus subtilis.

Endospore formation by Bacillus subtilis involves three differentiating cell types, the predivisional cell, the mother cell, and the forespore. Here we report the program of gene expression in the forespore, which is governed by the RNA polymerase sigma factors sigma(F) and sigma(G) and the DNA-binding proteins RsfA and SpoVT. The sigma(F) factor turns on about 48 genes, including the gene for RsfA, which represses a gene in the sigma(F) regulon, and the gene for sigma(G). The sigma(G) factor newly activates 81 genes, including the gene for SpoVT, which turns on (in nine cases) or stimulates (in 11 cases) the expression of 20 genes that had been turned on by sigma(G) and represses the expression of 27 others. The forespore line of gene expression consists of many genes that contribute to morphogenesis and to the resistance and germination properties of the spore but few that have metabolic functions. Comparative genomics reveals a core of genes in the sigma(F) and sigma(G) regulons that are widely conserved among endospore-forming species but are absent from closely related, but non-spore-forming Listeria spp. Two such partially conserved genes (ykoU and ykoV), which are members of the sigma(G) regulon, are shown to confer dry-heat resistance to dormant spores. The ykoV gene product, a homolog of the non-homologous end-joining protein Ku, is shown to associate with the nucleoid during germination. Extending earlier work on gene expression in the predivisional cell and the mother cell, we present an integrated overview of the entire program of sporulation gene expression.

Bacillus subtilis↗

PubMed2004

The program of gene transcription for a single differentiating cell type during sporulation in Bacillus subtilis.

Asymmetric division during sporulation by Bacillus subtilis generates a mother cell that undergoes a 5-h program of differentiation. The program is governed by a hierarchical cascade consisting of the transcription factors: sigma(E), sigma(K), GerE, GerR, and SpoIIID. The program consists of the activation and repression of 383 genes. The sigma(E) factor turns on 262 genes, including those for GerR and SpoIIID. These DNA-binding proteins downregulate almost half of the genes in the sigma(E) regulon. In addition, SpoIIID turns on ten genes, including genes involved in the appearance of sigma(K). Next, sigma(K) activates 75 additional genes, including that for GerE. This DNA-binding protein, in turn, represses half of the genes that had been activated by sigma(K) while switching on a final set of 36 genes. Evidence is presented that repression and activation contribute to proper morphogenesis. The program of gene expression is driven forward by its hierarchical organization and by the repressive effects of the DNA-binding proteins. The logic of the program is that of a linked series of feed-forward loops, which generate successive pulses of gene transcription. Similar regulatory circuits could be a common feature of other systems of cellular differentiation.

Amino Acid Motifs↗

PubMed2004

Evidence for a novel late-onset Alzheimer disease locus on chromosome 19p13.2.

Late-onset familial Alzheimer disease (LOFAD) is a genetically heterogeneous and complex disease for which only one locus, APOE, has been definitively identified. Difficulties in identifying additional loci are likely to stem from inadequate linkage analysis methods. Nonparametric methods suffer from low power because of limited use of the data, and traditional parametric methods suffer from limitations in the complexity of the genetic model that can be feasibly used in analysis. Alternative methods that have recently been developed include Bayesian Markov chain-Monte Carlo methods. These methods allow multipoint linkage analysis under oligogenic trait models in pedigrees of arbitrary size; at the same time, they allow for inclusion of covariates in the analysis. We applied this approach to an analysis of LOFAD on five chromosomes with previous reports of linkage. We identified strong evidence of a second LOFAD gene on chromosome 19p13.2, which is distinct from APOE on 19q. We also obtained weak evidence of linkage to chromosome 10 at the same location as a previous report of linkage but found no evidence for linkage of LOFAD age-at-onset loci to chromosomes 9, 12, or 21.

Adult↗

PubMed2003

Oligogenic segregation analysis of hereditary prostate cancer pedigrees: evidence for multiple loci affecting age at onset.

Previous studies have suggested strong evidence for a hereditary component to prostate cancer (PC) susceptibility. Here, we analyze 3,796 individuals in 263 PC families recruited as part of the ongoing Prostate Cancer Genetic Research Study (PROGRESS). We use Markov chain Monte Carlo (MCMC) oligogenic segregation analysis to estimate the number of quantitative trait loci (QTLs) and their contribution to the variance in age at onset of hereditary PC (HPC). We estimate 2 covariate effects: diagnosis of PC before and after prostate-specific antigen (PSA) test availability, and presence/absence of at least 1 blood relative with primary neuroepithelial brain cancer (BC). We find evidence that 2 to 3 QTLs contribute to the variance in age at onset of HPC. The 2 QTLs with the largest contribution to the total variance are both effectively dominant loci. We find that the covariate for diagnosis before and after PSA test availability is important. Our findings for the number of QTLs contributing to HPC and the variance contribution of these QTLs will be instructive in mapping and identifying these genes.

Adenocarcinoma↗

PubMed2003

The sigmaE regulon and the identification of additional sporulation genes in Bacillus subtilis.

We report the identification and characterization on a genome-wide basis of genes under the control of the developmental transcription factor sigma(E) in Bacillus subtilis. The sigma(E) factor governs gene expression in the larger of the two cellular compartments (the mother cell) created by polar division during the developmental process of sporulation. Using transcriptional profiling and bioinformatics we show that 253 genes (organized in 157 operons) appear to be controlled by sigma(E). Among these, 181 genes (organized in 121 operons) had not been previously described as members of this regulon. Promoters for many of the newly identified genes were located by transcription start site mapping. To assess the role of these genes in sporulation, we created null mutations in 98 of the newly identified genes and operons. Of the resulting mutants, 12 (in prkA, ybaN, yhbH, ykvV, ylbJ, ypjB, yqfC, yqfD, ytrH, ytrI, ytvI and yunB) exhibited defects in spore formation. In addition, subcellular localization studies were carried out using in-frame fusions of several of the genes to the coding sequence for GFP. A majority of the fusion proteins localized either to the membrane surrounding the developing spore or to specific layers of the spore coat, although some fusions showed a uniform distribution in the mother cell cytoplasm. Finally, we used comparative genomics to determine that 46 of the sigma(E)-controlled genes in B.subtilis were present in all of the Gram-positive endospore-forming bacteria whose genome has been sequenced, but absent from the genome of the closely related but not endospore-forming bacterium Listeria monocytogenes, thereby defining a core of conserved sporulation genes of probable common ancestral origin. Our findings set the stage for a comprehensive understanding of the contribution of a cell-specific transcription factor to development and morphogenesis.

Bacillus subtilis↗

PubMed2003

Integrating regulatory motif discovery and genome-wide expression analysis.

We propose motif regressor for discovering sequence motifs upstream of genes that undergo expression changes in a given condition. The method combines the advantages of matrix-based motif finding and oligomer motif-expression regression analysis, resulting in high sensitivity and specificity. motif regressor is particularly effective in discovering expression-mediating motifs of medium to long width with multiple degenerate positions. When applied to Saccharomyces cerevisiae, motif regressor identified the ROX1 and YAP1 motifs from Rox1p and Yap1p overexpression experiments, respectively; predicted that Gcn4p may have increased activity in YAP1 deletion mutants; reported a group of motifs (including GCN4, PHO4, MET4, STRE, USR1, RAP1, M3A, and M3B) that may mediate the transcriptional response to amino acid starvation; and found all of the known cell-cycle regulation motifs from 18 expression microarrays over two cell cycles.

Algorithms↗