Computational Approaches in Epigenomics

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Computational Approaches in Epigenomics Guo-Cheng Yuan Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute Harvard School of Public Health BIO506, Jan 11 th , 2010

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Computational Approaches in Epigenomics. Guo-Cheng Yuan Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute Harvard School of Public Health. BIO506, Jan 11 th , 2010. Definition. - PowerPoint PPT Presentation

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Page 1: Computational Approaches in Epigenomics

Computational Approaches in Epigenomics

Guo-Cheng YuanDepartment of Biostatistics and Computational Biology

Dana-Farber Cancer Institute

Harvard School of Public Health

BIO506, Jan 11th, 2010

Page 2: Computational Approaches in Epigenomics

Definition

• Epigenetics refers to changes in phenotype (appearance) or gene expression caused by mechanisms other than changes in the underlying DNA sequence.

wikipedia

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Epigenetic mechanisms

• Nucleosome positions

• Histone modification

• DNA methylation

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Chromatin

• DNA is packaged into chromatin.

• Nucleosome is the fundamental unit of chromatin. It wraps 146 bp DNA.

• The chromatin structure is hierarchical.

Felsenfeld and Groudine 2003

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Nucleosome and histone modification

First layer chromatin structure looks like “beads-on-a-string”.

A nucleosome is made of core histone proteins.

The amino acids on the N-terminus of histones can be covalently modified. Felsenfeld and Groudine 2003

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DNA methylation

Alberts et al. Molecular Biology of the Cell

DNA methylation normally occurs at CpG dinucleotide only and can be inherited during cell-division.

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Why do we care?

• Epigenetics is an extra layer of transcriptional control.

• Epigenetics plays an important role in development.

• Epigenetic mechanisms can cause cancer and other diseases.

• Epigenetic patterns are reversible and can be influenced by environments.

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Our goalsepigenonic

data

microarray

DNA sequence

Computational model

Characterize cell-type specific epigenetic states

Elucidate epigenetic targeting

mechanism

Understand epigenetic

regulation in cell differentiation

Epigenetic signature of

diseases

TF binding

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Chromatin domains

Intrachromosomal interactions

large-scale histone modification patterns

chromatin loops

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A hidden Markov model for prediction of multi-gene chromatin domains

Jessica Larson

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Prediction results

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Targeting mechanism for epigenetic factorsNucleosome positions

Histone modification pattern

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Wavelet Energy

Dinucleotide Frequency

Signal

Wavelet Basis

Signal Decomposition

E1E2

E3

kk EElinP

nucleosomeP

...

ker)(

)(log 11

An N-score model to prediction nucleosome positions

Yuan and Liu

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N-score prediction in two yeast species

Lanterman et al.

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Polycomb targets developmental genes in ES

Boyer et al. 2006

Polycomb

Oct4NanogSox2

expressed

repressed

Kim et al. 2008

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Motif A

Motif B Motif C

AA cS AA cS

NO YES

BB cS BB cS

NO YES NO YES

CC cS CC cS

A computational model: BARTBART is a Bayesian average of regression trees

Chipman et al. 2007

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Overall prediction accuracy

AUC = 0.82

all factors

5 factors

CpG

random

testing data ROC

Number of cell-types in which the gene is

targeted

Pro

pen

sity

sco

re

Spring Liu; Zhen Shao

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TF network

+Polycomb

Hox

Dnmt1Hox

+

cell-type A cell-type B

An integrated network

Jess Mar

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Future directions

• How do genetic and epigenetic factors work together to regulate cell-type specific gene expression?

• How does the integrated regulatory network change across cell-types?

• Are there epigenetic signatures associated with common diseases and if so what role do they have?

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Acknowledgment

• Jessica Larson • Yingchun (Spring) Liu• Zhen Shao

• John Quackenbush Lab– Jess Mar

• Stuart Orkin Lab– Xiaohua Shen– Jongwan Kim

• Steve Altschuler• Ollie Rando• Jun Liu

• Claudia Adams Barr Program