Bisulfite-Sequencing theory and Quality Control Felix Krueger felix.krueger@babraham.ac.uk January 2015 • • • • • • • • • • 9:15-10:15 10:15-10:30 10:30-11:30 11:30-12:30 12:30-13:30 13:30-14:00 14:00-15:30 15:30-15:45 15:45-16:35 16:35-16:45 2 Bisulfite-Seq theory and QC coffee Mapping and QC practical Visualising and Exploring talk Lunch Methylation tools in SeqMonk Visualising and Exploring practical coffee Differential methylation talk & practical Introduction to other cytosine modifications and oxBS DNA Methylation DNA methyl-transferases DNA-demethylase(s)? Hydroxymethyl cytosine? TETs? Passive demethylation? 5-methyl Cytosine Cytosine • • • • • • • 3 Dynamic patterning Correlation with gene expression Reset during development Suppression of repetitive elements X-chromosome inactivation Imprinting Carcinogenesis DNA methylation is sequence context dependent sequence CCAGTCGCTATA CCAGTCGCTATA CCAGTCGCTATA context mammals plants CpG YES YES CHG no** YES CHH no** YES * H being anything but G ** somewhat more relevant in certain cell types 4 Promoter methylation causes transcriptional silencing Developmentally important gene or tumour suppressor gene Adapted from Stephen B Baylin Nature Clinical Practice Oncology (2005) 5 Imprinted Genes: mono-allelic expression Differential allelic DNA methylation X CGI (CpG island) methylated CpG unmethylated CpG Imprinted Genes: Mono-allelic expression with parent-of-origin specificity. Have key roles in energy metabolism, placenta functions. 6 Imprinted Genes: example ICR: Imprinting Control Region DMR: Differentially Methylated Region methylated CGI ICR / DMR unmethylated CGI Rather unusual case where a non-methylated DMR causes silencing of a locus from Ferguson-Smith A. Nat. Rev. Genet. 2011 7 DNA methylation is maintained from W. Reik & J. Walter, Nat. Rev. Genet. 2001 8 DNA methylation is reset during reprogramming 9 Measuring DNA methylation by Bisulfite-sequencing Image by Illumina 10 Bisulfite Informatics me me CCAGTCGCTATAGCGCGATATCGTA Convert TTAGTTGCTATAGTGCGATATTGTA Map TTAGTTGCTATAGTGCGATATTGTA ||||||||||||||||||||||||| ...CCAGTCGCTATAGCGCGATATCGTA... 11 Bisulfite conversion of a genomic locus mC | mC | >>CCGGCATGTTTAAACGCT>> <<GGCCGTACAAATTTGCGA<< Top strand | mC | hmC | mC Bisulfite conversion >>UCGGUATGTTTAAACGUT>> Bottom strand <<GGUCGTACAAATTTGCGA<< PCR amplification OT >>TCGGTATGTTTAAACGTT>> CTOT <<AGCCATACAAATTTGCAA<< >>CCAGCATGTTTAAACGCT>> CTOB <<GGTCGTACAAATTTGCGA<< OB - 2 different PCR products and 4 possible different sequence strands from one genomic locus - each of these 4 sequence strands can theoretically exist in any possible conversion state 12 Mapping a Bisulfite-Seq read sequence of interest TTGGCATGTTTAAACGTT bisulfite convert read (treat sequence as both forward and reverse strand) 5’…TTGGTATGTTTAAATGTT…3’ 5’…TTAACATATTTAAACATT…3’ (1) (2) align to bisulfite converted genomes Bismark (3) …TTGGTATGTTTAAATGTT… …AACCATACAAATTTACAA… forward strand C -> T converted genome (1) (2) (4) …CCAACATATTTAAACACT… …GGTTGTATAAATTTGTGA… forward strand G -> A converted genome (equals reverse strand C -> T conversion) (3) (4) read all 4 alignment outputs and extract the unmodified genomic sequence if the sequence could be mapped uniquely 5’…CCGGCATGTTTAAACGCT…3’ methylation call genomic sequence TTGGCATGTTTAAACGTT CCGGCATGTTTAAACGCT methylation call cc..C.........Z.c. read sequence c C z Z unmethylated C methylated C unmethylated C in CpG context methylated C in CpG context Common sequencing protocols mC | mC | >>CCGGCATGTTTAAACGCT>> <<GGCCGTACAAATTTGCGA<< | mC Top strand | hmC | mC Bottom strand >>UCGGUATGTTTAAACGUT>> <<GGUCGTACAAATTTGCGA<< 1) Directional libraries (vast majority) 2) PBAT libraries 3) Non-directional libraries 14 OT >>TCGGTATGTTTAAACGTT>> <<GGTCGTACAAATTTGCGA<< OB CTOT <<AGCCATACAAATTTGCAA<< >>CCAGCATGTTTAAACGCT>> CTOB OT >>TCGGTATGTTTAAACGTT>> CTOT <<AGCCATACAAATTTGCAA<< >>CCAGCATGTTTAAACGCT>> CTOB <<GGTCGTACAAATTTGCGA<< OB 80 biased unbiased 60 40 20 0 25 50 75 100 Read length (bp) 15 125 150 CpG CHG CHH Mapping efficiency 100 100 80 80 60 60 40 40 20 20 0 0 0 20 40 60 80 Bisulfite conversion rate (%) 100 Mapping efficiency (%) Mapping efficiency (%) 100 Cytosines called unmethylated (%) Validation BS-Seq Analysis Workflow 16 QC Trimming Mapping Analysis Mapped QC Methylation extraction Raw Sequence Data ... up to 1,000,000,000 lines per lane 17 Part I: Initial QC What does QC tell you about your library? • • • • • # of sequences Basecall qualities Base composition Potential contaminants Expected duplication rate 18 QC Raw data: Sequence Quality Error rate 0.1% 1% 10% 19 QC: Base Composition WGSBS RRBS 20 QC: Duplication rate 21 QC: Overrepresented sequences 22 Phred score Common problems in BS-Seq Base content (%) Position in read (bp) Not observed in ‘normal’ libraries, e.g. ChIP or RNA-Seq Position in read (bp) 23 Removing poor quality basecalls Phred score before trimming 24 after trimming Removing adapter contamination before trimming 25 after trimming Summary Adapter/Quality Trimming Important to trim because failure to do so might result in: Low mapping efficiency Mis-alignments Errors in methylation calls since adapters are methylated Basecall errors tend toward 50% (C:mC) 26 Part II: Sequence alignment – Bismark primary alignment output (BAM file) chromosome position Read 1 HISEQ2000-06:366:C3G4NACXX:3:1101:1316:2067_1:N:0: 99 16 71322125 255 100M = 71322232 207 sequence NTTATTTAGTTTTTTAGGGTTTGTGTGTAGGAGTGTGGGAATTATGTTTTTTATGGTTGATATTTATTTAAAAGTGAGTATAAATTATATATATTTTTTT #1=DDDDDAAFFHIIIA:<FGHCCEFGHD?CFFBBBGEHHGHIII<FEHIIIII==DE??EHHFHEEEEEEEC>;>66;@CDEEEDCEEEEEEEDDDCBB quality NM:i:14 XX:Z:G8C2C7C21C13C6CC1C17CC3C4CC4 XM:Z:.........h..h.......x.....................h.............x......hh.h.................hh...h....hh.... XR:Z:CT XG:Z:CT XA:Z:1 HISEQ2000-06:366:C3G4NACXX:3:1101:1316:2067_1:N:0: 147 16 71322232 255 100M = 71322125 -207 GGTTATTTTATTTAGGGTTATTGTTTTAGAGTTTTATTGTTGTGAACAGATATATGATTAAGGTAATTTTTATAAGGATAATATTTAATTGGAGTTGGTT CCCEEECADCFFFFHHGHGHIIGIHFIJJIJIHFGHGGGEHIJIIJGIGFJJJJJJJJJJIGJJJJGJJJJIIIJJIJIJJJJJJIJHHHHHFFFFFCCC NM:i:21 XX:Z:2G2CC1C1C1C11C11C2C10C1C4CC4C2C1C3C5C2C12C3C1 XM:Z:.....hh.h.h.x...........h...........x..x......X...h.h....hh....h..h.h...h.....h..h............x...h. XR:Z:GA XG:Z:CT XB:Z:1 Read 2 methylation call 27 Sequence duplication Complex/diverse library: Duplicated library: 28 percent methylation 55 17 100 100 100 71 100 percent methylation 33 50 100 100 100 50 100 deduplication Deduplication - considerations Advisable for large genomes and moderate coverage - unlikely to sequence several genuine copies of the same fragment amongst >5bn possible fragments with different start sites - maximum coverage with duplication may still be (read length)-fold (even more with paired-end reads) NOT advisable for RRBS or other target enrichment methods where higher coverage is either desired or expected RRBS CCGG CCGG deduplication 29 Methylation extraction Read 1 ....Z.....h..h.......x.....Z.........x......hh.h.............z....hx...h....hh.Z... ...........hh.h.............z....hx...h....hh.Z...hh....x.....Z.h.....h..h......x...h........ redundant methylation calls Read 2 Read 1 ....Z.....h..h.......x.....Z.........x......hh.h.............z....hx...h....hh.Z... hh....x.....Z.h.....h..h......x...h........ Read 2 CpG methylation output read ID 30 meth state chr pos context Methylation extraction CpG methylation output bedGraph/coverage output chr 31 pos methylation percentage meth unmeth Part III: Mapped QC Methylation bias good opportunity to look at conversion efficiency 32 Artificial methylation calls in paired-end libraries end repair + A-tailing 5’3’- 33 GGGNNNNNNNNNNNNNNNNNNNNNNNNNNNCCCA ACCCNNNNNNNNNNNNNNNNNNNNNNNNNNNGGG -3’ -5’ Specialist applications (I): Reduced representation BS-Seq (RRBS) Sequence composition bias 34 High duplication rate Fragment size distribution in RRBS identical (redundant) methylation calls 35 Artificial methylation calls in RRBS libraries C genomic cytosine C unmethylated cytosine 36 Specialist application (II): Post-bisulfite adapter tagging (PBAT) WGBS PBAT suitable for low input material 37 PBAT-Seq trim off/ ignore first couple of basepairs 38 Bismark workflow Pre Alignment FastQC Trim Galore Initial quality control Adapter/quality trimming using Cutadapt; handles RRBS and paired-end reads; Trim Galore and RRBS User guide Alignment Bismark Output BAM Post Alignment Deduplication Methylation extractor optional Output individual cytosine methylation calls; optionally bedGraph or genome-wide cytosine report M-bias analysis bismark2report Graphical HTML report generation Example: http://www.bioinformatics.babraham.ac.uk/projects/bismark/PE_report.html protocol: Quality Control, trimming and alignment of Bisulfite-Seq data 39 Useful links • FastQC www.bioinformatics.babraham.ac.uk/projects/fastqc/ • Trim Galore www.bioinformatics.babraham.ac.uk/projects/trim_galore/ • Cutadapt https://code.google.com/p/cutadapt/ • Bismark www.bioinformatics.babraham.ac.uk/projects/bismark/ • Bowtie http://bowtie-bio.sourceforge.net/ • Bowtie 2 http://bowtie-bio.sourceforge.net/bowtie2/ • SeqMonk www.bioinformatics.babraham.ac.uk/projects/seqmonk/ • Cluster Flow www.bioinformatics.babraham.ac.uk/projects/clusterflow/ protocol: Quality control, trimming and alignment of Bisulfite-Seq data http://www.epigenesys.eu/en/protocols/bio-informatics/483-quality-control-trimming-and-alignment-of-bisulfite-seq-data-prot-57 40 Sierra: A web-based LIMS system for small sequencing facilities SeqMonk: Genome browser, quantitation and data analysis Trim Galore! Quality and adapter trimming for (RRBS) libraries FastQ Screen: organism and contamination detection Bismark: Bisulfite-sequencing alignments and methylation calls Hi-C mapping ASAP: Allele-specific alignments FastQC: quality control for high throughput sequencing 41 www.bioinformatics.babraham.ac.uk