ABSTRACT During my PhD tenure, I have been involved in developing a user-friendly cross-platform system capable of analyzing epigenomic data and further use it in understanding the role of the Polycomb Repressive Complex 2 (PRC2) in genome regulation. From current trending in epigenetics research, we can sense increasing ease of high throughput sequencing and greater interest towards genome wide epigenomic studies. As a result of which we experience an exponential flooding of epigenetic related data such as Chromatin immunoprecipitation followed by sequencing (ChIP-seq), and RNA sequencing (RNA-seq) in public domain. This creates an opportunity for crowd sourcing and exploring data outside the boundaries of specific query centered studies. Such data has to undergo standard primary analysis, which with the aid of multiple programs has been stabilized courtesy to the scientific community. Further downstream, out of many, genome wide comparative, correlative and quantitative studies have proven to be critical and helpful in deciphering key biological features. For such studies we lack platforms, which can be capable of handling, analyzing and linking multiple interdisciplinary (ChIP-seq/RNA-seq) datasets with efficient analytical methods. With this aim we developed ChIP_QC, a user-friendly standalone computational program with an ability to support numerous datasets with high/moderate sequencing depth for performing genome wide analysis. First, using ENCODE project (Consortium, 2012) data, we illustrated few applications of the program by posing different biological scenarios and showed the comfort with which some known observations can be verified and also how it can be helpful in deducing some other novel observations. Second, we were interested in understanding the functionality of the products generated through catalytic activity of PRC2. It is known that Lysine 27 of histone H3 (H3K27) undergoes posttranslational modification (PTM) and methylation is one such dominant PTM. Methylation on H3K27 can be either mono/di/tri-methylation form. Out of all three forms, it is very well demonstrated that trimethylation of H3K27 (H3K27me3) is PRC2 dependent and at the same time its role in gene repression is well characterized, but functional roles of other forms of methylation on H3K27 are still poorly characterized. For understanding this, we used mouse embryonic stem cells (mESC) as model system of our study and we were able to provide an extensive characterization of other forms of methylation, highlighting their differential deposition along the genome, their fundamental role in transcriptional regulation, and their indispensability during differentiation program. Using ChIP_QC and with other computational methods along with experimental evidences, our data demonstrated that the monomethylation of Lys27 (H3K27me1) is required for correct transcription of genes and positively correlates with trimethylated Lys36 (H3K36me3); on the other hand dimethylated Lys27 (H3K27me2), that we identified to be the principal activity of PRC2, prevents firing of non cell type specific enhancers.

CHIP_QC, COMPUTATIONAL PLATFORM FOR MULTIVARIATE EPIGENETIC STUDIES AND ITS APPLICATION IN UNCOVERING ROLE OF POLYCOMB DEPENDENT METHYLATIONS STATES / S.g. Jammula ; Dr. Diego Pasini: immediate supervisor ; Dr. Mattia Pelizzola: added supervisor ; Dr. Claudia Angelini: internal adviser ; Dr. Rory Johnson: external adviser ; Dr. Saverio Minucci: tutor. - : . UNIVERSITA' DEGLI STUDI DI MILANO, 2016 Mar 18. ((27. ciclo, Anno Accademico 2015. [10.13130/jammula-sri-ganesh_phd2016-03-18].

CHIP_QC, COMPUTATIONAL PLATFORM FOR MULTIVARIATE EPIGENETIC STUDIES AND ITS APPLICATION IN UNCOVERING ROLE OF POLYCOMB DEPENDENT METHYLATIONS STATES

S.G. Jammula
2016-03-18

Abstract

ABSTRACT During my PhD tenure, I have been involved in developing a user-friendly cross-platform system capable of analyzing epigenomic data and further use it in understanding the role of the Polycomb Repressive Complex 2 (PRC2) in genome regulation. From current trending in epigenetics research, we can sense increasing ease of high throughput sequencing and greater interest towards genome wide epigenomic studies. As a result of which we experience an exponential flooding of epigenetic related data such as Chromatin immunoprecipitation followed by sequencing (ChIP-seq), and RNA sequencing (RNA-seq) in public domain. This creates an opportunity for crowd sourcing and exploring data outside the boundaries of specific query centered studies. Such data has to undergo standard primary analysis, which with the aid of multiple programs has been stabilized courtesy to the scientific community. Further downstream, out of many, genome wide comparative, correlative and quantitative studies have proven to be critical and helpful in deciphering key biological features. For such studies we lack platforms, which can be capable of handling, analyzing and linking multiple interdisciplinary (ChIP-seq/RNA-seq) datasets with efficient analytical methods. With this aim we developed ChIP_QC, a user-friendly standalone computational program with an ability to support numerous datasets with high/moderate sequencing depth for performing genome wide analysis. First, using ENCODE project (Consortium, 2012) data, we illustrated few applications of the program by posing different biological scenarios and showed the comfort with which some known observations can be verified and also how it can be helpful in deducing some other novel observations. Second, we were interested in understanding the functionality of the products generated through catalytic activity of PRC2. It is known that Lysine 27 of histone H3 (H3K27) undergoes posttranslational modification (PTM) and methylation is one such dominant PTM. Methylation on H3K27 can be either mono/di/tri-methylation form. Out of all three forms, it is very well demonstrated that trimethylation of H3K27 (H3K27me3) is PRC2 dependent and at the same time its role in gene repression is well characterized, but functional roles of other forms of methylation on H3K27 are still poorly characterized. For understanding this, we used mouse embryonic stem cells (mESC) as model system of our study and we were able to provide an extensive characterization of other forms of methylation, highlighting their differential deposition along the genome, their fundamental role in transcriptional regulation, and their indispensability during differentiation program. Using ChIP_QC and with other computational methods along with experimental evidences, our data demonstrated that the monomethylation of Lys27 (H3K27me1) is required for correct transcription of genes and positively correlates with trimethylated Lys36 (H3K36me3); on the other hand dimethylated Lys27 (H3K27me2), that we identified to be the principal activity of PRC2, prevents firing of non cell type specific enhancers.
PASINI, DIEGO
Settore BIO/11 - Biologia Molecolare
CHIP_QC, COMPUTATIONAL PLATFORM FOR MULTIVARIATE EPIGENETIC STUDIES AND ITS APPLICATION IN UNCOVERING ROLE OF POLYCOMB DEPENDENT METHYLATIONS STATES / S.g. Jammula ; Dr. Diego Pasini: immediate supervisor ; Dr. Mattia Pelizzola: added supervisor ; Dr. Claudia Angelini: internal adviser ; Dr. Rory Johnson: external adviser ; Dr. Saverio Minucci: tutor. - : . UNIVERSITA' DEGLI STUDI DI MILANO, 2016 Mar 18. ((27. ciclo, Anno Accademico 2015. [10.13130/jammula-sri-ganesh_phd2016-03-18].
Doctoral Thesis
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/366602
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