Elucidating mechanisms of gene regulation. Integration of high-throughput sequencing data for studying the epigenome

The recent advent of High-Throughput Sequencing (HTS) methods has triggered a revolution in gene regulation studies. Demand has never been higher to process the immense amount of emerging data to gain insight into the regulatory mechanisms of the cell. We address this issue by describing methods to analyze, integrate and interpret HTS data from different sources. In particular, we developed and benchmarked Pyicos, a powerful toolkit that offers flexibility, versatility and efficient memory usage. We applied it to data from ChIP-Seq on progesterone receptor in breast cancer cells to gain insight into regulatory mechanisms of hormones. Moreover, we embedded Pyicos into a pipeline to integrate HTS data from different sources. In order to do so, we used data sets from ENCODE to systematically calculate signal changes between two cell lines. We thus created a model that accurately predicts the regulatory outcome of gene expression, based on epigenetic changes in a gene locus. Finally, we provide the processed data in a Biomart database to the scientific community.La llegada reciente de nuevos métodos de High-Throughput Sequencing (HTS) ha provocado una revolución en el estudio de la regulación génica. La necesidad de procesar la inmensa cantidad de datos generados, con el objectivo de estudiar los mecanismos regulatorios en la celula, nunca ha sido mayor. En esta tesis abordamos este tema presentando métodos para analizar, integrar e interpretar datos HTS de diferentes fuentes. En particular, hemos desarollado Pyicos, un potente conjunto de herramientas que ofrece flexibilidad, versatilidad y un uso eficiente de la memoria. Lo hemos aplicado a datos de ChIP-Seq del receptor de progesterona en células de cáncer de mama con el fin de investigar los mecanismos de la regulación por hormonas. Además, hemos incorporado Pyicos en una pipeline para integrar los datos HTS de diferentes fuentes. Hemos usado los conjuntos de datos de ENCODE para calcular de forma sistemática los cambios de señal entre dos líneas celulares. De esta manera hemos logrado crear un modelo que predice con bastante precisión los cambios de la expresión génica, basándose en los cambios epigenéticos en el locus de un gen. Por último, hemos puesto los datos procesados a disposición de la comunidad científica en una base de datos Biomart

Predictive models of gene regulation from high-throughput epigenomics data

The epigenetic regulation of gene expression involves multiple factors. The synergistic or antagonistic action of these factors has suggested the existence of an epigenetic code for gene regulation. Highthroughput sequencing (HTS) provides an opportunity to explore this code and to build quantitative models of gene regulation based on epigenetic differences between specific cellular conditions. We describe a new computational framework that facilitates the systematic integration of HTS epigenetic data. Our method relates epigenetic signals to expression by comparing two conditions. We show its effectiveness by building a model that predicts with high accuracy significant expression differences between two cell lines, using epigenetic data from the ENCODE project. Our analyses provide evidence for a degenerate epigenetic code, which involves multiple genic regions. In particular, signal changes at the 1st exon, 1st intron, and downstream of the polyadenylation site are found to associate strongly with expression regulation. Our analyses also show a different epigenetic code for intron-less and intron-containing genes. Our work provides a general methodology to do integrative analysis of epigenetic differences between cellular conditions that can be applied to other studies, like cell differentiation or carcinogenesis.This work was supported by Grants BIO2011-23920 and CSD2009-00080 from the Spanish Ministry of/nScience and by the Sandra Ibarra Foundation. S. Althammer was supported by an FI grant from the Generalitat de Cataluny

Predictive models of gene regulation from high-throughput epigenomics data

The epigenetic regulation of gene expression involves multiple factors. The synergistic or antagonistic action of these factors has suggested the existence of an epigenetic code for gene regulation. Highthroughput sequencing (HTS) provides an opportunity to explore this code and to build quantitative models of gene regulation based on epigenetic differences between specific cellular conditions. We describe a new computational framework that facilitates the systematic integration of HTS epigenetic data. Our method relates epigenetic signals to expression by comparing two conditions. We show its effectiveness by building a model that predicts with high accuracy significant expression differences between two cell lines, using epigenetic data from the ENCODE project. Our analyses provide evidence for a degenerate epigenetic code, which involves multiple genic regions. In particular, signal changes at the 1st exon, 1st intron, and downstream of the polyadenylation site are found to associate strongly with expression regulation. Our analyses also show a different epigenetic code for intron-less and intron-containing genes. Our work provides a general methodology to do integrative analysis of epigenetic differences between cellular conditions that can be applied to other studies, like cell differentiation or carcinogenesis.This work was supported by Grants BIO2011-23920 and CSD2009-00080 from the Spanish Ministry of/nScience and by the Sandra Ibarra Foundation. S. Althammer was supported by an FI grant from the Generalitat de Cataluny

Pyicos: a versatile toolkit for the analysis of high-throughput sequencing data

MOTIVATION: High-throughput sequencing (HTS) has revolutionized gene regulation studies and is now fundamental for the detection of protein-DNA and protein-RNA binding, as well as for measuring RNA expression. With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing. RESULTS: We describe Pyicos, a powerful toolkit for the analysis of mapped reads from diverse HTS experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. We prove the effectiveness of Pyicos to select for significant signals and show that its accuracy is comparable and sometimes superior to that of methods specifically designed for each particular type of experiment. Pyicos facilitates the analysis of a variety of HTS datatypes through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics. AVAILABILITY: Open-source software, with tutorials and protocol files, is available at http://regulatorygenomics.upf.edu/pyicos or as a Galaxy server at http://regulatorygenomics.upf.edu/galaxyGeneralitat de Catalunya by FI grant (to S.A.); Spanish Ministry of Science (MICINN) by FPI grant (to J.G.V.); MICINN grant BIO2008-01091 (to E.E.); European Commission grant EURASNET-(LSHG-CT-2005-518238) (to E.E.)

Pyicos: a versatile toolkit for the analysis of high-throughput sequencing data

MOTIVATION: High-throughput sequencing (HTS) has revolutionized gene regulation studies and is now fundamental for the detection of protein-DNA and protein-RNA binding, as well as for measuring RNA expression. With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing. RESULTS: We describe Pyicos, a powerful toolkit for the analysis of mapped reads from diverse HTS experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. We prove the effectiveness of Pyicos to select for significant signals and show that its accuracy is comparable and sometimes superior to that of methods specifically designed for each particular type of experiment. Pyicos facilitates the analysis of a variety of HTS datatypes through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics. AVAILABILITY: Open-source software, with tutorials and protocol files, is available at http://regulatorygenomics.upf.edu/pyicos or as a Galaxy server at http://regulatorygenomics.upf.edu/galaxyGeneralitat de Catalunya by FI grant (to S.A.); Spanish Ministry of Science (MICINN) by FPI grant (to J.G.V.); MICINN grant BIO2008-01091 (to E.E.); European Commission grant EURASNET-(LSHG-CT-2005-518238) (to E.E.)

Nucleosome-driven transcription factor binding and gene regulation

In fission yeast cells, Cds1 is the effector kinase of the DNA replication checkpoint. We previously showed that when the DNA replication checkpoint is activated, the repressor Yox1 is phosphorylated and inactivated by Cds1, resulting in activation of MluI-binding factor (MBF)-dependent transcription. This is essential to reinitiate DNA synthesis and for correct G1-to-S transition. Here we show that Cdc10, which is an essential part of the MBF core, is the target of the DNA damage checkpoint. When fission yeast cells are treated with DNA-damaging agents, Chk1 is activated and phosphorylates Cdc10 at its carboxy-terminal domain. This modification is responsible for the repression of MBF-dependent transcription through induced release of MBF from chromatin. This inactivation of MBF is important for survival of cells challenged with DNA-damaging agents. Thus Yox1 and Cdc10 couple normal cell cycle regulation in unperturbed conditions and the DNA replication and DNA damage checkpoints into a single transcriptional complex.The experimental work was supported by grants from the Spanish government (BMC 2003-02902 and 2010-15313; CSD2006-00049), the European Union (IP HEROIC), and the Catalan government (AGAUR). L.G. was a recipient of a fellowship from the International PhD program of LaCaixa; G.P.V. was a recipient of a fellowship from the Ramón y Cajal program

Nucleosome-driven transcription factor binding and gene regulation

In fission yeast cells, Cds1 is the effector kinase of the DNA replication checkpoint. We previously showed that when the DNA replication checkpoint is activated, the repressor Yox1 is phosphorylated and inactivated by Cds1, resulting in activation of MluI-binding factor (MBF)-dependent transcription. This is essential to reinitiate DNA synthesis and for correct G1-to-S transition. Here we show that Cdc10, which is an essential part of the MBF core, is the target of the DNA damage checkpoint. When fission yeast cells are treated with DNA-damaging agents, Chk1 is activated and phosphorylates Cdc10 at its carboxy-terminal domain. This modification is responsible for the repression of MBF-dependent transcription through induced release of MBF from chromatin. This inactivation of MBF is important for survival of cells challenged with DNA-damaging agents. Thus Yox1 and Cdc10 couple normal cell cycle regulation in unperturbed conditions and the DNA replication and DNA damage checkpoints into a single transcriptional complex.The experimental work was supported by grants from the Spanish government (BMC 2003-02902 and 2010-15313; CSD2006-00049), the European Union (IP HEROIC), and the Catalan government (AGAUR). L.G. was a recipient of a fellowship from the International PhD program of LaCaixa; G.P.V. was a recipient of a fellowship from the Ramón y Cajal program