analysis of massively parallel sequencing data – application of … · 2017. 1. 29. · gordon...

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Analysis of Massively Parallel Sequencing Data – Application of Illumina Sequencing to

the Genetics of Human Cancers

Gordon BlackshieldsSenior Bioinformatician

Source BioScience


Next Generation Sequencing ApplicationsTo Cancer Genetics Studies

Introduction

“Next Generation Sequencing” (NGS) on Illumina platform is suitable for clinical applications that require large amounts of information, accurate quantification and high-sensitivity detection

– Mutation detection in tumours (from biopsies / circulating tumour cells (CTC)). – Pathogen detection e.g. organism identification for epidemiological investigations– Gut microbial flora genomics – Detection of the presence of antibiotic resistance genes– Comparison of novel sequences / genes to those in public databases


Applications of NGS to Cancer GeneticsSome Commonly Applied Techniques

“Sequencing The Genome”Reference alignment, targeted resequencing for polymorphism and mutation discoveryDe novo assembly for characterisation of novel genes, genomes.Paired-end sequencing highlights larger structural variants (inherited/acquired)

“Sequencing The Transcriptome”RNA-Seq allows “absolute” quantification of gene expression across transcriptomeNo prior knowledge of content needed – quantify expression of ‘unknown’ genes Profiling of mRNA, ncRNA, miRNA…

“Sequencing The Cistrome”ChIP-Seq allows profiling of cis-acting targets (DNA binding sites) of a trans-acting factor (transcription factor, restriction enzyme, etc) on a genome scale. Determine how proteins interact with DNA to regulate gene expressionDetermine how TFs and other proteins influence phenotype-affecting mechanismsSImilar approach can be used to characterise genomic methylation patterns – “the methylome”


Applications of NGS to Cancer GeneticsLevels of information extraction, data integration

Density on known exons Novel Transcripts

Enriched regions

Binding Sources

Motif finding

Associated GenesDifferential Expression

Expression levels Novel gene models

Associate observed variants with regulation/transcriptional changes; link to external databases

Consensus Sequence

Targeted Resequencing

Variant Detection

Overlapping Genes

Integrate

Analyse

Identify

De novo assembly / reads mapped to (un) annotated reference sequenceProcess

108-109 short DNA fragmentsGenerate

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Variant Detection

ChIP-Seq

Novel Isoforms

RNA-SeqQuantification

RNA-SeqDiscovery

Identify splice-crossing reads


Next Generation Sequencing ApplicationsHuman Resequencing and Variant Detection

Reference Assembly, Targeted ResequencingAnd Variant Detection

Search for alterations at nucleotide level to explain changes in regulation/transcription

Single Ended (SE) sequencing• ~85% of complex genome accessible• suitable for SNPs, small indels (DIPs)

Paired-Ended (PE) sequencing• ~99% of complex genome accessible• Find longer DIPs• Find larger structural variations• Span repeat regions


Next Generation Sequencing ApplicationsHuman Resequencing and Variant Detection

2009 Nature Paper

Cytogenetically normal AML genome sequenced (32x)Comparison with matched normal tissue (14x)

98 full runs on Illumina GA to achieve required depth

Alignment, variant discovery performed by MAQ

97.7% of variants in AML genome also in normal Further restricted to annotated gene-coding regions

Across all tumour cells:found 10 genes with acquired mutations (8 novel )present in all cells at presentation and relapse

“Our study establishes whole genome sequencing as an unbiased method for discovering initiating mutations in cancer genomes, and for identifying novel genes that may respond to targeted therapies”


Next Generation Sequencing ApplicationsPolymorphism detections within P53

P53 Variant detection study• “Guardian of the genome” (Lane, 1992)• Protects fidelity of DNA replication• Directs cell arrest/apoptosis when stressed

• Mutated in more than half of human cancers

http://p53.free.fr/



17p13.1P53 Variant detection study• “Guardian of the genome” (Lane, 1992)• Protects fidelity of DNA replication• Directs cell arrest/apoptosis when stressed

• Mutated in more than half of human cancers• Human TP53 gene located on 17p13.1• Region sometimes deleted in human cancer


PCR amplification


17p13.1P53 Variant detection study• “Guardian of the genome” (Lane, 1992)• Protects fidelity of DNA replication• Directs cell arrest/apoptosis when stressed


Study• Search for variants on P53 gene in matched

tumour samples. • Use gene specific PCR to amplify exons only to

maximise depth of coverage



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Gene position

12000 13000 14000 15000 16000 17000 18000 19000

Coverage of p53 geneP53 Variant detection study• “Guardian of the genome” (Lane, 1992)• Protects fidelity of DNA replication• Directs cell arrest/apoptosis when stressed


Study• Search for variants on P53 gene in matched

tumour samples. • Use gene specific PCR to amplify exons only to

maximise depth of coverage

• Use MAQ for alignment, variant discovery against P53 reference gene

• Comparison with results from 454, Sanger


Next Generation Sequencing ApplicationsPolymorphism detections within BRCA1

BRCA1 Variant detection study• Human tumour suppressor gene • Primarily expressed in breast tissue• Helps repair damaged DNA (if possible)

• Mutations to BRCA1 allow uncontrolled replication of damaged cells.


Next Generation Sequencing ApplicationsPolymorphism detections within BRCA1

CASAVADemultiplex (11 samples)Map reads to ref (BRCA1)

SAMToolsConversion to SAM format

Conversion to Pileup formatConsensus/Indel Calling

Filter for variants

Comparison with Known variants

BRCA1 Variant detection study• Human tumour suppressor gene • Primarily expressed in breast tissue• Helps repair damaged DNA (if possible)

• Mutations to BRCA1 allow uncontrolled replication of damaged cells.

Pilot Study• Search for variants on BRCA1 gene • Use gene specific PCR to amplify exons only to

maximise depth of coverage• Multiplexed – 11 samples loaded into one lane• Use CASAVA for de-multiplexing, alignment• Use SAMtools for consensus/indel calling, filtering• Validation of results against known variants.


Next Generation Sequencing ApplicationsRNA-Seq: Transcriptome Analysis

RNA-Seq• Sequence RNA (translated to cDNA) • Mapped to annotated reference genome

(annotated genes, known variants)• Expression levels deduced from total

number of reads that map to exons of a gene.

RNA-Seq versus Microarray• More sensitive to low-abundance transcripts• “absolute” gene expression levels detectable

– can detect single molecules • no prior knowledge required of content• Greater ability to distinguish isoforms• Ability to determine allelic expression• Less biased


DAVID – Pathways Analysis of deregulated geneshttp://david.abcc.ncifcrf.gov/

DESeq – Differential Gene Expression of RNA-Seq data

BOWTIE – Maps reads to reference genome (hg19)TOPHAT – Identifies splice sites (known/novel)CUFFLINKS – Transcript Assembly, Quantification

Next Generation Sequencing ApplicationsRNA-Seq: Transcriptome Analysis

RNA-Seq Study of ovarian cancer cell lines• Identification of changes in gene expression in strains with

acquired drug-resistance

• Special interest in ncRNA expression data

• Use Bowtie and Tophat to map reads, identify splice sites

• Use Cufflinks to assemble transcripts, calculate abundances• ~87% of reads mapped to genome

• Use DESeq to perform differential expression tests

• Use DAVID (Database for Annotation, Visualisation and Integrated Discovery (http://david.abcc.ncifcrf.gov/)) for pathway analysis

– Found significant representation of cancer pathways and focal adhesion genes


Next Generation Sequencing ApplicationsChIP-Seq: Genome-wide protein-DNA interactions

ChIP-Seq• Chromatin-immunoprecipitation (ChIP) isolates protein-

bound DNA• Follow by deep sequencing of DNA fragments (Seq)• Facilitates genome wide mapping pf DNA-protein

interactions• How TFs, other chromatin associated factors can affect

phenotype. • Regulation/Structural Analysis

ChIP-Seq vs. ChIP-chip• no prior knowledge of content required• Similar approach can be used to map genomic methylation


Next Generation Sequencing ApplicationsChIP-Seq: Genome-wide protein-DNA interactions

ChIP-Seq Study ofHaematopoietic Stem Cells

• Interest in Haematopoiesis and genetic circuitry of blood cell development

• Tal1 – T-cell acute lymphocytic leukaemia protein 1• TF that controls development and differentiation

of Haematopoietic Stem Cells (HSCs)• Very few target genes had been validated.

• ChIP-Seq approach taken to generate a genome-wide catalogue of Tal1 binding events in stem cell line

• Use Illumina BeadStudio ChIP-Seq module to identify peaks (potential chromatin binding sites)

• Followed by in vivo validation (foetal liver, transgenic mice)

• Allows construction of in vivo validated network of 17 factors and respective regulatory elements


Applications of NGS to Cancer GeneticsLevels of information extraction, data integration

Density on known exons Novel Transcripts

Enriched regions

Binding Sources

Motif finding

Associated GenesDifferential Expression

Expression levels Novel gene models

Associate observed variants with regulation/transcriptional changes; link to external databases

Consensus Sequence

Targeted Resequencing

Variant Detection

Overlapping Genes

Integrate

Analyse

Identify

De novo assembly / reads mapped to (un) annotated reference sequenceProcess

108-109 short DNA fragmentsGenerate

Lev

el o

f In

form

atio

n E

xtra

ctio

n

Variant Detection

ChIP-Seq

Novel Isoforms

RNA-SeqQuantification

RNA-SeqDiscovery

Identify splice-crossing reads

analysis of massively parallel sequencing data – application of … · 2017. 1. 29. · gordon...

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