Global profiling of methylation in the cancer genome Andy Feber UCL Cancer Institute University College London, UK Illumina, Manchester, 7 th September 2010
What determines a cancer phenotype? genetic factors non-genetic factors • epigenetics • environment
Epigenetics and Cancer • How are epigenetics changes involved in cancer? • Definition “The study of heritable changes in gene expression that occur independent of changes in the primary DNA sequence”
Background - epigenetics DNA methylation Histone modifications, e.g., - acetylation - methylation Non-coding RNA (ncRNA) & Micro RNA (miRNA)
One Genome……..Many Methylomes
DNA Methylation • DNA methylation is the addition of methyl group to cytosine generally in CpG dinucleotides • 28.6 million CpG sites in the human genome, 70% of which are methylated • CpG rich regions known CpG Islands (CGIs) are generally located near to the start of genes and associate with promoters • Previously thought to key site of epigenetic regulation of gene expression, and have been the main focus of epigenetic research • Recently changes in methylation at regions out side CGIs, known as CGI sores have been shown to more significantly associated with gene regulation • Only 7% of CpGs reside within CGIs, many CpGs remain un-analyzed by conventional approaches, microarray, PCR, bisulphite sequencing • Next generation sequencing now allows the profiling of over 100x10 6 loci at one time • Combined with enrichment strategies, such as MEDIP (Methylated DNA immunoprecipitation) (MeDIP-Seq), allows whole genome methylation (methylome) to be assessed in a single experiment
MeDIP Seq Reference Sequence ….CGTGATGTCGCGCCTCACTCCGGTGG… TCCGGTGG CCTCACTCCGG CGCGCCTCAC G T TGATGTCGCG C G G C GCTGATGTCG T T A TGTCGCGCC G C A T G C TCGCGCCTC C T G CCTCACTCCG G A T C G C CTCCGGTGG
Determining methylation from read count • How to determine absolute methylation levels both within a genome and between genomes?
Bioinformatic challenge… • Within a given genomic region, MeDIP enrichment is proportional to the number of methylated CpG sites. • Simple enrichment ratios/read counts do not accurately reflect the absolute methylation levels within a particular region of interest. Hypothetical Genomic Region MeDIP Enrichment Absolute Methylation Value A. A. 0% Read B. B. B C Count 50% A C. C. 100%
Batman : Bayesian Tool for Methylation Analysis • Enrichment bias means absolute methylation levels are difficult to quantitate Batman : Bayesian Tool for Methylation Analysis 1 f A | m G A | A r C m , v p base cp c c p
MPNST Methylome Aim • To define the methylome (methylated genome) associated with a malignant phenotype • Using Medip-Seq to identify tumor specific differential methylation which correlates with tumor progression/development Samples • Pools of ten cases per sample cohort – Malignant Peripheral Nerve Sheath Tumors (MPNST) – Benign neurofibromas (NF) – Normal cultured Schwann Cells (SC) • Age and gender matched • MPNST 6 Female, 4 Male, median age 30.7 (range 12 to 58) • NF 6 Female, 4 Male, median age 27.7 (range 15 to 54)
Malignant Peripheral Nerve Sheath Tumors (MPNST) Neurofibromatosis type 1 (NF1) Sporadic Familial 3000 cases/year (often with alterations (Germ line in NF1 , eg LOH) mutation in NF1 ) Benign Disease Plexiform Dermal 10-15% develop malignant disease Malignant Peripheral Nerve Sheath Tumours Only 20% of patients disease free after 5 years
Read Stats Sample Total number Total Total Unique of reads Mapped Mapped Reads Reads MPNST 140119516 133145064 75918388 NF 140442616 134234980 81619250 SC 138120350 131484108 68697944 * Those with a Maq score of >10 and both paired reads mapping uniquely • Covering ~68% of CpGs in each of the three genomes.
Copy Number Correction
Medip-Seq Verification • Verification of medip-seq initially using the Infinium 27K Human BeadChips, Illumina. Interrogate ~27500 CpG sites across the genome. • Comparison of Medip-seq data with arrays showed a high degree of correlation • Similar to correlations observed between:- – BeadArray v bisulphite sequencing – BATMAN v bisulphite sequencing Sample Batman V Infinium Pearson correlation MPNST 0.78 NF 0.80 SC 0.77
Global changes in methylation • What are the global changes involved in MPNST development ? • To assess changes in global methylation, the methylation status of each CpG site was bind into 3 methylation states Low (<40%), High (>60%), intermediate (40-60%) • Global analysis of revealed a small change in global methylation (1%), compared to other tumours which show global loss of methylation ranging from 10-20%. • Analysis of regulatory features of CGIs, CGI shores and promoters, show similar levels of global methylation between MPNST and Schwann cell controls Low methylation Intermediate methylation High methylation
Global repeat methylation • One of the most commonly cited features of the cancer methylome is hypomethylation of repeats • Methylation over LINE and SINE repeats, changes slightly, interestingly LINE repeats appear to lose low methylated CpGs • Largest changes in global methylation seen in Satellite repeats, with a 25% change in methylation between MPNST and non-neoplastic Schwann cells Low methylation Intermediate methylation High methylation
DMR - Differentially Methylated Regions • Regions of differential methylation were defined by average Batman methylation scores over 1kb. • Regions were called differentially methylated if they had an average difference of 33% in batman methylation score • Increasing numbers of DMRs during progression from non-neoplastic schwann cell controls to MPNSTs DMRs Hypermethylated Hypomethylated h2bDMR 45239 46587 (SC v NF) b2mDMR 41886 45230 (NF v MPNST) cDMR 48391 53075 (SC v MPNST)
DMRs in Genomic Features • Comparison of DMRs in different genomic features shows in which regions methylation changes during disease progression • Association of features DMRs with genes allows identification of potential candidate onoc- and tumorsuppressor genes SC v NF SC v MPNST (h2bDMR) (cDMRs) Hypermethylated Hypomethylated Hypermethylated Hypomethylated CGI 49 47 CGI 385 79 CGI shores 996 1382 CGI shores 2119 1669 promoters 484 812 promoters 1097 1098 Non CGI 39 95 Non CGI associated associated promoters promoters 293 175 exons 7885 12104 exons 11858 11432 Introns 48086 49503 Introns 61709 57632 miRNA 19 31 miRNA 22 30 Conserved regions 18566 16113 Conserved regions 16535 27805 Satellite repeats 128 259 Satellite repeats 142 1398 LTR repeats 10805 10773 LTR repeats 14339 12665 LINE repeats 25526 22110 LINE repeats 34515 25359 SINE repeats 28764 36448 SINE repeats 32661 39502
DMR Enrichment • Are DMRs enriched in specific genomic features • Relative enrichment analysis was carried out to identify those features that have a significantly (p<0.001, red bars) higher number of DMRs than would be expected by chance • Significant enrichment of hypomethylated satellite and SINE repeats, also enrichment of hypermethylated LINE repeats • Of those regions assumed to be functionally relevant in the regulation of gene expression, only CGI shores and promoters (not associated with a CGI) to be significantly enriched • Previous studies have focused on CGI and CGI associated promoters, suggesting many possible sites important in cancer have been missed. Hypermethylated Hypomethylated
Enrichment in repeats • Analysis of aberrant methylation in repeats located either within or outside introns showed a distinct pattern of repeat methylation • We see significant enrichment of both hypomethylated non-intronic SINEs and non-intronic satellites repeats • Also significant enrichment of intronic SINE repeats in early disease • Enrichment of hypermethylated intronic LINE repeats, as well as non-intronic LINES Hypermethylated Hypomethylated
Discrete types of satellite repeats show enrichment • Satellite repeats be divided into 19 different types of repeat • Enrichment analysis of sat repeat type highlighted 2 specific types of repeat which under go hypomethylation , SATR1 and ARL • SATR1 appear to early events in tumourigenic progression, whereas ARL hypomethylation may be a later event • Do satellite repeats undergo sequence specific methylation? • Knock-out of specific DNMT family members have been shown to alter specific satellite repeat methylation • What its the role of aberrant satellite repeat methylation in cancer Hypomethylated Hypermethylated
DMRs in Genomic Features • Where to start? • 101,466 unique cDMRs • Do DMRs associate with candidate genes SC v MPNST (cDMRs) Hypermethylated Hypomethylated CGI 385 79 CGI shores 2119 1669 promoters 1097 1098 Non CGI associated promoters 293 175 exons 11858 11432 Introns 61709 57632 miRNA 22 30 Conserved regions 16535 27805 Satellite repeats 142 1398 LTR repeats 14339 12665 LINE repeats 34515 25359 SINE repeats 32661 39502
Candidate genes MEST - Imprinted region, differently methylated in glioblastomas (which also have frequent NF1 mutations) WT1 – Wilms tumor suppressor 1 gene, SC NF MPNST
Recommend
More recommend
