19 resultados para Gene expression profiling


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Although many feature selection methods for classification have been developed, there is a need to identify genes in high-dimensional data with censored survival outcomes. Traditional methods for gene selection in classification problems have several drawbacks. First, the majority of the gene selection approaches for classification are single-gene based. Second, many of the gene selection procedures are not embedded within the algorithm itself. The technique of random forests has been found to perform well in high-dimensional data settings with survival outcomes. It also has an embedded feature to identify variables of importance. Therefore, it is an ideal candidate for gene selection in high-dimensional data with survival outcomes. In this paper, we develop a novel method based on the random forests to identify a set of prognostic genes. We compare our method with several machine learning methods and various node split criteria using several real data sets. Our method performed well in both simulations and real data analysis.Additionally, we have shown the advantages of our approach over single-gene-based approaches. Our method incorporates multivariate correlations in microarray data for survival outcomes. The described method allows us to better utilize the information available from microarray data with survival outcomes.

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Nutrient availability profoundly influences gene expression. Many animal genes encode multiple transcript isoforms, yet the effect of nutrient availability on transcript isoform expression has not been studied in genome-wide fashion. When Caenorhabditis elegans larvae hatch without food, they arrest development in the first larval stage (L1 arrest). Starved larvae can survive L1 arrest for weeks, but growth and post-embryonic development are rapidly initiated in response to feeding. We used RNA-seq to characterize the transcriptome during L1 arrest and over time after feeding. Twenty-seven percent of detectable protein-coding genes were differentially expressed during recovery from L1 arrest, with the majority of changes initiating within the first hour, demonstrating widespread, acute effects of nutrient availability on gene expression. We used two independent approaches to track expression of individual exons and mRNA isoforms, and we connected changes in expression to functional consequences by mining a variety of databases. These two approaches identified an overlapping set of genes with alternative isoform expression, and they converged on common functional patterns. Genes affecting mRNA splicing and translation are regulated by alternative isoform expression, revealing post-transcriptional consequences of nutrient availability on gene regulation. We also found that phosphorylation sites are often alternatively expressed, revealing a common mode by which alternative isoform expression modifies protein function and signal transduction. Our results detail rich changes in C. elegans gene expression as larvae initiate growth and post-embryonic development, and they provide an excellent resource for ongoing investigation of transcriptional regulation and developmental physiology.

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During bacterial growth, a cell approximately doubles in size before division, after which it splits into two daughter cells. This process is subjected to the inherent perturbations of cellular noise and thus requires regulation for cell-size homeostasis. The mechanisms underlying the control and dynamics of cell size remain poorly understood owing to the difficulty in sizing individual bacteria over long periods of time in a high-throughput manner. Here we measure and analyse long-term, single-cell growth and division across different Escherichia coli strains and growth conditions. We show that a subset of cells in a population exhibit transient oscillations in cell size with periods that stretch across several (more than ten) generations. Our analysis reveals that a simple law governing cell-size control-a noisy linear map-explains the origins of these cell-size oscillations across all strains. This noisy linear map implements a negative feedback on cell-size control: a cell with a larger initial size tends to divide earlier, whereas one with a smaller initial size tends to divide later. Combining simulations of cell growth and division with experimental data, we demonstrate that this noisy linear map generates transient oscillations, not just in cell size, but also in constitutive gene expression. Our work provides new insights into the dynamics of bacterial cell-size regulation with implications for the physiological processes involved.

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Developmental signals in metazoans play critical roles in inducing cell differentiation from multipotent progenitors. The existing paradigm posits that the signals operate directly through their downstream transcription factors to activate expression of cell type-specific genes, which are the hallmark of cell identity. We have investigated the mechanism through which Wnt signaling induces osteoblast differentiation in an osteoblast-adipocyte bipotent progenitor cell line. Unexpectedly, Wnt3a acutely suppresses the expression of a large number of genes while inducing osteoblast differentiation. The suppressed genes include Pparg and Cebpa, which encode adipocyte-specifying transcription factors and suppression of which is sufficient to induce osteoblast differentiation. The large scale gene suppression induced by Wnt3a corresponds to a global decrease in histone acetylation, an epigenetic modification that is associated with gene activation. Mechanistically, Wnt3a does not alter histone acetyltransferase or deacetylase activities but, rather, decreases the level of acetyl-CoA in the nucleus. The Wnt-induced decrease in histone acetylation is independent of β-catenin signaling but, rather, correlates with suppression of glucose metabolism in the tricarboxylic acid cycle. Functionally, preventing histone deacetylation by increasing nucleocytoplasmic acetyl-CoA levels impairs Wnt3a-induced osteoblast differentiation. Thus, Wnt signaling induces osteoblast differentiation in part through histone deacetylation and epigenetic suppression of an alternative cell fate.