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The post-genomic era: epigenetic sequencing applications and data integrationby dr. ir. Maté Ongenaert - Center for Medical Genetics, Ghent UniversityThe 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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The post-genomic eraEpigenetic sequencing applications and data integration
WOUD mini-symposium28/09/2011
Maté Ongenaert
Center for Medical GeneticsGhent University Hospital, Belgium
Overview
Epigenetics Introduction DNA-methylation Histone modifications The interplay between methylation and histone
modifications Applications of epigentics
Epigenetic sequencing Sequencing the epigenome Data analysis and integration
-genetics Heritable changes to the DNA or histones without
affecting the DNA sequence A whole range of changes are described
• DNA-methylation• Histone tail modifications
– Methylation– Acetylation– Phosphorylation– ….
Epigenetic changes are interconnected
Epigenetics > Introduction
Epigenetics > Introduction
Epigenetics > Introduction
DNA-methylation
Histone tail modifications
DNA-methylation and cancer
Epigenetics > DNA-methylation
Local hypermethylation
Global hypomethylation
Interplay between DNA-methylation and histone modifications
Epigenetics > Interplay
(Early) detection – diagnostic Diagnostic: who Screening programs
Epigenetics > Detection / Prognosis / Prediction
Prediction Predictive: what Treatment
Epigenetics > Detection / Prognosis / Prediction
Prediction Predictive: what Treatment
Epigenetics > Detection / Prognosis / Prediction
Prediction Predictive: what Treatment
Epigenetics > Detection / Prognosis / Prediction
Biomarker
Prediction Predictive: what Treatment
Epigenetics > Detection / Prognosis / Prediction
Prediction Chemotherapy respons (MGMT in brain cancer -
temozolomide)
Epigenetics > Detection / Prognosis / Prediction
Overview
Epigenetics Introduction DNA-methylation Histone modifications The interplay between methylation and histone
modifications Applications of epigentics
Epigenetic sequencing Sequencing the epigenome Data analysis and integration
DNA-methylation Restriction-based Bisulfite-conversion based Affinity-based
• MeDIP-seq (Antibody)• MBD-seq (Methyl Binding Domain)
Chromatin marks ChIP-seq
Sequencing the epigenome
SequencingControl of fragment sizes with high sensitivity DNA chips
Concentration determination of the fragmented DNA with Fluostar Optima plate reader
MBD2 immunoprecipitation reaction (MethylCollector Kit)
Sequencing the epigenome
Shearing of DNA (Covaris)
Sequencing data analysis
Sequencing the epigenome
QC (FastQC)
Sequencing the epigenome
Mapping
Sequencing the epigenome
@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
Mapping
Sequencing the epigenome
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: Ilumina quality 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
Mapping
Sequencing the epigenome
Chromosomal location (strand, chromosome, pos)
Quality of the 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
Mapping
Sequencing the epigenome
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)
macs14 -t IMR32.bowtie -f BOWTIE -g hs -n IMR32 -w --single-wig
Mapping
Sequencing the epigenome
Chr start 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
Sequencing the epigenome
PCDHB-cluster (neuroblastoma CLs)
Sequencing the epigenome
PCDHB-cluster in neuroblastoma
Sequencing the epigenome
Integrating data sources…
Sequencing the epigenome
H3K27 me3
H3K36 me3
H3K4 me3
RNA-seq
Promoter region Gene BodyActive gene
Sequencing the epigenome
Conclusions
Sequencing epigenomes reveals a wealth of information
There is no such thing as the epigenome Methylome Hydroxymethylome Different histone modifications
Don’t forget the interplay and the dynamics…
Start exploring the data by yourself as you know the application the best
Acknowledgments
Anneleen Decock Frank Speleman Jo Vandesompele
Tim De Meyer Geert Trooskens Wim Van Criekinge
Leander Van Neste Johan Vandersmissen
Jean-Pierre Renard Sarah De Keulenaer
