The post-genomic era: epigenetic sequencing applications and data integration

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The post-genomic era: epigenetic sequencing applications and data integration …

The post-genomic era: epigenetic sequencing applications and data integration
by dr. ir. Maté Ongenaert - Center for Medical Genetics, Ghent University

The past decade is known as the post-genomic era. Ever since the first published human genomes, the pace to determine new genomes ever increased. In addition, a number of new sequencing applications gave access to previously unexplored areas at a genome-wide scale such as whole epigenomes.
In this talk, the data generated from a number of sequencing techniques to determine whole DNA-methylomes and whole genome histone marks will be discussed.
Main goal: to convince scientists that the analysis tools have matured to a level that, using a good manual and insight in the mechanisms behind the analysis, they can do their own basic analyses.
Starting from a raw sequence file, over quality control to mapping to the reference genome, peak calling, visualization and identification of differentially methylated sites: within the time-frame of this talk, the entire process will be demonstrated.
As epigenetics regulates genomic processes and literally is a layer above genetics, able to fine-tune regulatory processes, several layers of information should be look at to understand the underlying mechanisms.
Important aspect in the analysis of epigenetic datasets thus is the integration of several data sources (expression results, re-expression results, DNA-methylation information and histone-modifications).

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  • 1. The post-genomic era
    Epigenetic sequencing applications and data integration
    WOUD mini-symposium28/09/2011
    Maté Ongenaert
    Center for Medical Genetics
    Ghent University Hospital, Belgium
  • 2. Overview
    • Epigenetics
    Introduction
    DNA-methylation
    Histonemodifications
    The interplaybetweenmethylationandhistonemodifications
    Applications of epigentics
    Epigeneticsequencing
    Sequencingthe epigenome
    Data analysis andintegration
  • 3. Epigenetics > Introduction
    -genetics
    Heritable changes to the DNA or histones without affecting the DNA sequence
    A whole range of changes are described
    DNA-methylation
    Histonetailmodifications
    Methylation
    Acetylation
    Phosphorylation
    ….
    Epigenetic changes are interconnected
  • 4. Epigenetics > Introduction
  • 5. Epigenetics > Introduction
    DNA-methylation
    Histone tail modifications
  • 6. Epigenetics > DNA-methylation
    DNA-methylationandcancer
    Global hypomethylation
    Localhypermethylation
  • 7. Epigenetics > Interplay
    Interplaybetween DNA-methylationandhistonemodifications
  • 8. Epigenetics > Detection / Prognosis / Prediction
    (Early) detection– diagnostic
    Diagnostic: who
    Screening programs
  • 9. Epigenetics > Detection / Prognosis / Prediction
    Prediction
    Predictive: what
    Treatment
  • 10. Epigenetics > Detection / Prognosis / Prediction
    Prediction
    Predictive: what
    Treatment
  • 11. Epigenetics > Detection / Prognosis / Prediction
    Prediction
    Predictive: what
    Treatment
    Biomarker
  • 12. Epigenetics > Detection / Prognosis / Prediction
    Prediction
    Predictive: what
    Treatment
  • 13. Epigenetics > Detection / Prognosis / Prediction
    Prediction
    Chemotherapy respons (MGMT in brain cancer - temozolomide)
  • 14. Overview
    • Epigenetics
    Introduction
    DNA-methylation
    Histonemodifications
    The interplaybetweenmethylationandhistonemodifications
    Applications of epigentics
    Epigeneticsequencing
    Sequencingthe epigenome
    Data analysis andintegration
  • 15. Sequencing the epigenome
    DNA-methylation
    Restriction-based
    Bisulfite-conversionbased
    Affinity-based
    MeDIP-seq (Antibody)
    MBD-seq (Methyl Binding Domain)
    • Chromatinmarks
    ChIP-seq
  • 16. Sequencing the epigenome
    Shearing of DNA (Covaris)
    Sequencing
    Control of fragment sizeswith high sensitivity DNA chips
    Concentration determination of the fragmented DNA with Fluostar Optima plate reader
    MBD2 immunoprecipitation reaction (MethylCollector Kit)
  • 17. Sequencing the epigenome
    Sequencing data analysis
  • 18. Sequencing the epigenome
    QC (FastQC)
  • 19. Sequencing the epigenome
    Mapping
    @HWUSI-EAS100R:6:73:941:1973#0/1
    GATTTGGGGTTCAAAGCAGTATCGATCAAATAGTAAATCCATTTGTTCAACTCACAGTT
    +HWUSI-EAS100R:6:73:941:1973#0/1
    !''*((((***+))%%%++)(%%%%).1***-+*''))**55CCF>>>>>>CCCCCCC6
    Identifier (Illumina machine name, lane, tile etc.)
    Sequence
    Sequencing quality
  • 20. Sequencing the epigenome
    Mapping
    bowtie -q -n --fr --phred64-quals -x 250 -t -p 4 hg19-1 qseq_2_MID5_W.fastq -2 qseq_2_MID5_C.fastq IMR32.bowtie
    Input FASTQ files (two: paired end)
    Mapping parameters:
    - q: quality aware (--phred64-quals: Iluminaquality scores instead of Phred)--fr: map on forward and reverse strand of the reference genome- x: map paired-end reads maximum 250 bp apart
    - p 4: use 4 processes to map (parallelization)
    - hg19: reference genome
  • 21. Sequencing the epigenome
    Mapping
    HWUSI-EAS509:4:34:13795:1029#0/1 + chr16 57608607 GTCAG… IIIII… 0
    HWUSI-EAS509:4:34:13795:1029#0/3/2 - chr16 57608757 GTCCT… IIIII… 0
    HWUSI-EAS509:4:34:6016:1041#0/3/2 + chr10 94410976 GTTTC… IIIII… 0
    HWUSI-EAS509:4:34:6016:1041#0/1 - chr10 94411127 TGTTT… IIIHH… 0
    HWUSI-EAS509:4:34:7281:1043#0/1 + chr4 54043731 GTCTA… IIIII… 0
    Chromosomal location (strand, chromosome, pos)
    Quality of the mapping
  • 22. Sequencing the epigenome
    Mapping
    macs14 -t IMR32.bowtie -f BOWTIE -g hs -n IMR32 -w --single-wig
    Input: mapped “treatment” reads and format of mapping (you can also provide a control sample)
    Parameters:-g hs: human reference genome (for size estimation)- n: name of output files
    - w: create wig-files for visualisation (counts)
  • 23. Sequencing the epigenome
    Mapping
    Chrstart end length summit tags score fold_enrichment
    Chr1 14862 15572 711 227 17 86.37 13.55
    Chr1 135001 135399 399 197 12 83.27 15.43
    Chr1 229428 229950 523 329 10 62.41 14.03
  • 24. Sequencing the epigenome
  • 25. Sequencing the epigenome
    PCDHB-cluster (neuroblastoma CLs)
  • 26. Sequencing the epigenome
    PCDHB-cluster in neuroblastoma
  • 27. Sequencing the epigenome
    Integrating data sources…
    H3K27 me3
    H3K36 me3
    H3K4 me3
    RNA-seq
    Promoter region
    Gene Body
    Active gene
  • 28. Sequencing the epigenome
  • 29. Conclusions
    Sequencingepigenomesreveals a wealth of information
    There is no suchthing as the epigenome
    Methylome
    Hydroxymethylome
    Different histonemodifications
    Don’tforget the interplayand the dynamics…
    Start exploring the data byyourselfas youknow the application the best
  • 30. Acknowledgments