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Computational Epigenetics

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Title: Computational Epigenetics


1
Computational Epigenetics
  • The New Kid on The Block

Shen Jean Lim2, Tin Wee Tan2, Joo Chuan
Tong1,2   1Data Mining Department, Institute for
Infocomm Research 2Department of Biochemistry,
Yong Loo Lin School of Medicine, National
University of Singapore
2
Epigenetics
  • Study of mitotically and/or meiotically heritable
    changes in gene expression that are not encoded
    in the DNA sequence
  • Mediated through chemical modifications of DNA
    and histones
  • Alterations in chromatin structure that blocks or
    promotes transcriptional initiation

Source http//www.neb.com/nebecomm/tech_referenc
e/epigenetics/overviews.asp
3
Levels of Chromatin Packing
4
Histones
Source http//www.mun.ca/biology/scarr/Histone_P
rotein_Structure.html
  • In eukaryotes, nuclear DNA is found assembled
    into chromatin by histones.
  • Ocatameric histone core is made up of two
    molecules of each histone H2A, H2B, H3 and H4
  • Packages approximately 147 base pair segments of
    nuclear DNA into nucleosome core particles (NCP).
  • Histone H1 further condenses the DNA by binding
    the linker segments between the nucleosome core
    particles

5
Histone Modifications
  • Occur on flexible N-and C-terminal tails of the
    histones or within their globular folds in the
    nucleosome core
  • Histone modifications act individually or
    combinatorially
  • Alter chromatin structure
  • Affect transcription, repair, replication and
    chromatin condensation and ultimately gene
    regulation

6
Histone Modifications
Source http//chemistry.gsu.edu/faculty/Zheng/pi
ctures/nucleosome.jpg
  • Enzymes involved in this process include DNA
    methyltransferases,histone deacetylases, histone
    acetylases, histone methyltransferases, histone
    demethylases etc

7
Epigenetics Importance
  • Epigenetic modulations are essential in many
    developmental processes
  • Tissue formation, organ formation and
    allele-specific gene expression
  • Changes in normal epigenetic patterns can
    deregulate patterns of gene expression, resulting
    in adverse clinical outcomes
  • Psychiatric disorders, obesity , schizophrenia,
    Beckwith-Wiedemann syndrome, Alzheimers disease

8
Epigenetics as a research field
  • Highly combinatorial in nature due to the array
    of diverse control elements
  • The human genome contains 23,000 genes that are
    active in specific cells at precise moments!!
  • Post-translational modification may affect almost
    every solvent-accessible histone residue,
    allowing a high level of variability for signal
    transduction events

9
Epigenetics as a research field
  • Enormous combinatorial complexity requires large
    number of experiments for systematic studies
    (e.g. DNA methylation profiling)
  • Large-scale initiatives for the systematic
    mapping of epigenomic and related data
  • Alliance for the Human Epigenome and Disease
    (AHEAD) Task Force
  • The ENCyclopedia Of DNA Elements (ENCODE) Project
    Consortium
  • etc etc.

10
Computational Epigenetics
  • Huge quantity of experimental data generated
    requires appropriate bioinformatics
    infrastructure for meaningful analysis, modeling
    and prediction of DNA-protein interactions
  • General and specialist databases
  • Basic bioinformatics tools
  • Sophisticated algorithms

11
Computational Epigenetics
  • General and specialist databases
  • Basic bioinformatics tools
  • Sophisticated algorithms

12
Computational Epigenetics
  • General and specialist databases
  • Basic bioinformatics tools
  • Sophisticated algorithms

13
General databases
  • Large amount of data relevant for epigenetic
    research are available in scientific literature,
    molecular databases and case reports.
  • PubMed - primary source of data, provides
    high-level descriptions of biological entities
    and processes

14
General databases
  • Molecular databases

Databases described in the Nucleic Acids Research
online Molecular Biology Database Collection
(March 2009)
Total 1,078 molecular biology databases
Galperin MY, Cochrane GR. Nucleic Acids Research
annual Database Issue and the NAR online
Molecular Biology Database Collection in 2009,
Nucleic Acids Res 200937D1-4
15
General databases
  • Major molecular databases
  • GenBank
  • DNA Data Bank of Japan
  • European Molecular Biology Laboratory
  • serve as worldwide repositories for
    nucleotide sequences of different origins

16
General specialist databases
  • Databases for cell-, disease-, organism- and
    stage-specific gene expression
  • General
  • NCBIs Gene Expression Omnibus
  • Specialist
  • Gene Expression Nervous System Atlas
  • StemBase
  • Etc etc
  • Allows for the identification of dynamic changes
    in gene expression in different cell types

17
Epigenetics databases
  • DNA methylation databases
  • For the study of methylation content data and
    methylation patterns
  • MethDB, MethPrimerDB
  • Histone databases
  • Information on histones and histone
    fold-containing proteins
  • Important for research in the compaction and
    accessibility of eukaryotic and probably archaeal
    genomic DNA
  • National Human Genome Research Institute
    (NHGRI)s Histone Database
  • Cancer methylation databases
  • Analyzing irregular methylation patterns that are
    correlated with various cancers
  • PubMeth, MeInfoText

18
Computational Epigenetics
  • General and specialist databases
  • Basic bioinformatics tools
  • Sophisticated algorithms

19
Basic Bioinformatics Tools
  • Traditional sequence analysis tools allow for the
    inference of functional, structural, or
    evolutionary relationships between DNA or protein
    sequences
  • E.g. ClustalW , BLAST (Basic Local Alignment
    Search Tool) software suite, BLAT (BLAST-Like
    Alignment Tool) and TreeView
  • Diverse applications involving
  • Homology searches of ortholog candidates for the
    KEGG/GENES database
  • Predicting the secondary structures of histone
    deacetylases
  • Homology modeling of DNA methyltransferases
  • Optimizing the activities of histone deacetylase
    inhibitors

20
Computational Epigenetics
  • General and specialist databases
  • Basic bioinformatics tools
  • Sophisticated algorithms

21
Sophisticated algorithms
  • Computational models have been used extensively
    to support various epigenome mapping initiatives
  • Identification of ChIP enrichment sites
    (ChIPOTle, TileMap, Ringo)
  • Accurate mapping of short sequence reads
    generated by ChIP-seq to the reference genome
    (Blastn, BLAT)
  • Algorithms for short-read assembly (QPALMA,
    AMOScmp)
  • Data processing and quality assessment of
    bisulfite sequencing

22
Major Research Areas in Computational Epigenetics
DNA Methylation
Histone Modifications
Cancer Informatics
Stem Cell Informatics
23
Major Research Areas in Computational Epigenetics
DNA Methylation
Histone Modifications
Cancer Informatics
Stem Cell Informatics
24
Research area DNA Methylation
  • Modeling and prediction of DNA methylation
    patterns
  • Prediction of methylation sites
  • Focused on arginine and lysine methylations

25
Research area DNA Methylation
  • Epigenome prediction pipeline
  • Integrates DNA methylation, polymerase II
    preinitiation complex binding, histone H3K4 di-
    and trimethylation, histone H3K9/14 acetylation,
    DNase I hypersensitivity and SP1 binding

26
Research area DNA Methylation
  • Limitation
  • Lack of publicly available experimental data
    for model construction

27
Major Research Areas in Computational Epigenetics
DNA Methylation
Histone Modifications
Cancer Informatics
Stem Cell Informatics
28
Research area Histone Modifications
  • Analysis, modeling and prediction of histone
    modifications in DNA sequences
  • Machine-learning algorithms for locating
    histone-occupied and acetylation, methylation and
    phosphorylation positions in DNA sequences
  • Discovery of activating and repressive histone
    modifications
  • Structure-based techniques for the design of
    epigenetic inhibitors
  • Functional annotation of epigenetic factors

29
Research area Histone Modifications
30
Major Research Areas in Computational Epigenetics
DNA Methylation
Histone Modifications
Cancer Informatics
Stem Cell Informatics
31
Research area Cancer Informatics
  • Identify novel methylation patterns that
    correlate with progression to malignancy
  • CancerDip Consortium
  • Abnormal DNA methylation within CpG islands

32
Research area Cancer Informatics
  • Classifying cancer subtypes based on epigenetic
    marks

33
Major Research Areas in Computational Epigenetics
DNA Methylation
Histone Modifications
Cancer Informatics
Stem Cell Informatics
34
Research area Stem Cell Informatics
  • Study epigenetic marks in stem cells
  • DNA methyltransferases and Polycomb/Trithorax
    group response elements (PRE/TRE) possess
    epigenetic signatures that are important for the
    differentiation of both human ES cells and germ
    line stem cells
  • Stem cells are target cells for cancer
  • Epigenetic changes may occur long before they are
    distinguishable as tumor cells

35
Research area Stem Cell Informatics
  • Analyses of up- and down-regulated gene clusters
  • Provide valuable information on the effect of
    exogenous control on ES cell state in human

36
Conclusion
  • Realizing the full benefits of the
    informatics revolution will require significant
    advances in the efficiency of which new data is
    discovered, processed, interpreted and made
    accessible to researchers

37
Conclusion
  • Different bioinformatic and mathematical
    modeling approaches, in combination with advances
    in computational infrastructures, clearly could
    lead to improved understanding of
    posttranslational modifications at multiple
    levels of complexity, from the sub-cellular
    molecular level, to the cellular and systems
    level, and beyond
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