Identify chromatin state signature and its functional implications in nine cell lines Open Access

Abstract

The study provides a new way for including cis-regulatory elements into gene analysis. The genome is cut into small units and each unit is given a specific chromatin state according to its potential functions. The study analyzes the 15 chromatin states, which is defined by 9 histone marks, across 9 cell lines. The genome was cut into 200bp per unit and each unit was given a state according to their different responds to the histone marks. The study focuses on analyzing the chromatin states combinations and the combinations with length of 6 and length of 8 are emphasized. Among all the combinations, the combinations with repeated elements such as 11,7/7,11, 11,10/10,11 are relatively common. The study also uses GREAT system developed by Stanford University for gene set enrichment analysis aiming at regions of chromatin states combinations. The results show that combinations with repeated elements of 10,11/11,10 tends to have shared functions, while combinations with repeated elements of 11,7/7,11 and 13,8/8,13 tends to have unique functions. On the other hand, the shared functions for unique combinations within all cell lines are also emphasized. The functions related with ligase activity for combinations of repeated element of 10,11/11,10 appear in all cell lines with those combinations.

Table of Contents

Introduction: 7 Methodology: 10 1. Datasets: 10

2. Choose frequent chromatin states combinations. 10

3. Gene Enrichment analysis. 11

3.1 Identify chromatin states combinations with common gene functions across cell lines. 11

3.2 Identify common chromatin state combination functions within each chromatin states combinations across cell lines. 12

Results: 13

1. Choose frequent chromatin states combinations 13

2. Gene Enrichment Analysis. 14

Discussion: 17 Acknowledgement: 20 References: 21 Appendix: 22

About this Master's Thesis

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School	Rollins School of Public Health
Department	Biostatistics and Bioinformatics
Subfield / Discipline	Biostatistics - MPH & MSPH
Degree	MSPH
Submission	Master's Thesis
Language	English
Research Field	Biology, Biostatistics Biology, Bioinformatics
Keyword	histome marks chromatin states combinations gene enrichment
Committee Chair / Thesis Advisor	Qin, Zhaohui, Emory University
Committee Members	Yu, Tianwei, Emory University
Partnering Agencies	Does not apply (no collaborating organization)

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