Introduction to NGS - DTU Bioinformatics · 27626 - Next Generation Sequencing Analysis...

27626 - Next Generation Sequencing Analysis

Preprocessing and SNP calling Natasja S. Ehlers, PhD student Center for Biological Sequence Analysis Functional Human Variation Group

Introduction to NGSSimon Rasmussen

Associate ProfessorDTU Bioinformatics

Technical University of Denmark2018

Life science data deluge• Massive unstructured

data from several areas DNA, patient journals, proteomics, imaging, ...

• Impacts Industry, Environment, Health

• Societal grand challenges

• Cheap sequencing technologies results in explosion of DNA data


Reading the order of bases in DNA

fragments

DNA sequencing


Why NGS?

Transforming how we are doing biological science (and bioinformatics)

by

allowing experiments that could not have been done before, and perform

experiments much faster


How ?

by producing massive amounts of sequence data, really fast


First generation: Sanger• Fragment DNA

• Clone into plasmid and amplify

• Sequence using dNTP + labelled ddNTPs (stops reaction)

• Run capillary electrophoresis/gel and “read” DNA code

• Low output, long reads (~800-1200 nt), high quality


1st generation to NGS

cancer genome can be obtained, including all point mutations,rearrangements and copy number changes. Mutations in the accom-panying mitochondrial genomes of the cancer will also be collected.With further adaptation this could be extended to include epigeneticalterations and could be applied to the transcriptomes of cancers toinvestigate the first phenotypic effects of all these changes. This cata-loguewill include all the drivermutations andhence all the cancer genesoperating in that cancer, whether they are protein-coding genes, non-coding RNA genes or more cryptic functional elements of the genome.Indeed, if known or unknown DNA viruses have contributed tooncogenesis thesewill alsobediscovered.The cataloguewill also includeall the passenger mutations that incorporate the signatures of previousexposures, DNA repair defects and other mutational processes thecancer has experienced over the decades during which it was evolving.

Until recently, this was an unattainable fantasy. However, thearrival of second-generation sequencing technologies promises anew era for cancer genomics. These platforms currently generatebillions of bases of DNA sequence per week, yields that are predictedto increase rapidly over the next couple of years (Fig. 3). Several proof-of-principle studies have recently been published applying these tech-nologies to cancer samples. These have demonstrated that the currentgeneration of massively parallel sequencing platforms can identify thefull range of somatically acquired genetic alteration in cancer, includ-ing point mutations on a genome-wide basis57, insertions and dele-tions57, copy number changes56 and genomic rearrangements56, as wellas characterizing the cancer cell transcriptome40,41. Furthermore, theseapproaches have the potential to identify subclonal genetic diversitywithin the population of cancer cells58, with particular relevance to thedetection of subclones carrying drug-resistance mutations59. Indeed,one high-coverage cancer genome sequence has recently beenreported57 and several others will emerge during the course of 2009.

Even with the remarkable technological advances in sequencing,however, the parameters of experiments to catalogue all somaticallyacquired variants in a cancer genome are sobering. To obtain acomplete catalogue of somatic mutations from an individual humancancer may require 20-fold sequence coverage of the cancer genome,and possibly more. Somatic mutations then have to be distinguishedfrom inherited DNA variants. Although most inherited variants thatare common in human populations (.5% allele frequency) have beendiscovered and are registered in databases, there are myriad rareinherited single nucleotide polymorphisms and structural variants thatare not. In most cancer genomes these rare germline variants faroutnumber the somatic mutations present. Therefore, for the foresee-able future at least, a high-coverage sequence of the normal genomefrom the same individual as the cancer will be an inescapable extra

burden to allow identification of the somatic changes. Thus, morethan 100,000,000,000 base pairs of DNA sequence will probably berequired to identify the catalogue of somatic mutations in a singlecancer genome.

Subsequently, it will be necessary to distinguish driver mutationsfrom passengers (see Box 1). The power to distinguish clusters ofdriver mutations in cancer genes from chance clusters of randomlydistributed passenger mutations will depend on how frequently acancer gene is mutated and the prevalence of passenger mutations.To be confident of identifying a cancer gene that is mutated in,5%of a particular type of cancer will require hundreds of cases to besequenced. Each of the.100 cancer types will probably require similarsample sizes.

Coordinating the sequencing of cancer genomesThere is, therefore, much work to be done over the next few years.Ideally, it should be organized to maximize use of resources andharmonize the product. This is the mission of the InternationalCancer Genome Consortium (ICGC, see http://www.icgc.org/home).Buildingon the success of previousmultinational, collaborative initia-tives such as the Human Genome Project and the HapMap consor-tium, the aim of ICGC is to comprehensively characterize somaticallyacquired genetic events in at least fifty classes of cancer, includingthose with the highest global incidence and mortality, requiringhigh-coverage sequencing of 20,000 cancer genomes ormore. The fullcatalogues of somatic mutation from each of these cancers will beintegrated with expression and epigenetic profiles of the same casesand correlated with clinical features.

Projects under the ICGC imprimatur will adhere to predeterminedstandards and procedures for ethical approval, data release,intellectual property, sample quality, clinical annotation, data quality,data storage and sequencing completion. Most importantly, given thedemanding nature of the task, the ICGC will coordinate studies tominimize duplication of effort and enable the most parsimoniousdeployment of resources.

The proposal to sequence large numbers of cancer genomes hasgenerated controversy reminiscent of the debate before sequencingof the reference human genome almost 20 years ago. The experimentswill be expensive and, to some extent, we cannot predict what will befound. However, the human genome is finite. Therefore, with furthertechnological advances in DNA sequencing that are already in sight,this is a deliverable project that will comprehensively elucidate centralquestions relating to the nature of human cancer. The clinical andtranslational implications of such a body of work are profound.Beyond the identification of further potentially druggable cancergenes, a comprehensive catalogue of somatic mutations in carefullycharacterized clinical samples will generate new insights into thegenetic patterns that underpin disease phenotype, prognosis, drugresponse and chemotherapy resistance. As the costs of sequencingwhole cancer genomes drop towards US$1,000, routine sequencingin a clinical, diagnostic setting will become feasible. Such data maydrive individualized therapeutic decision-making through the abilityto predict prognosis, to choose therapeutic regimens known to haveefficacy for the particular genetic subtype of cancer, to sensitivelymonitor response to therapy and to identify rare subclonesharbouringdrug-resistancemutations before therapy is even initiated.Individualized therapeutics will require individualized diagnostics.

The discussion is therefore not about whether to do the experiment,butwhen and how. In amanner similar to theHumanGenomeProjectwe have to coordinate the work internationally to maximize use ofresources and minimize duplication of effort to generate a resourceof high quality so that we only have to do it once, empowering cancerresearch with a lasting legacy for the future.

Forward lookApproximately 100,000 somaticmutations fromcancer genomeshavebeen reported in the quarter of a century since the first somatic

Capillary sequencingCapillary sequencing

1980 1985 1990 1995 2000

10

100

1,000

10,000

100,0000

1,000,000

10,000,000

100,000,000

1,000,000,000

2010 Future

Manualslab gel

Automatedslab gel First-generation

capillary

Second-generationcapillary sequencer

Microwellpyrosequencing

Short-readsequencers

Singlemolecule?

Gel-based systems

Massively parallel sequencing

Year

2005

Kilo

base

s pe

r day

per

mac

hine

Figure 3 | Improvements in the rate of DNA sequencing over the past 30years and into the future. From slab gels to capillary sequencing andsecond-generation sequencing technologies, there has been a more than amillion-fold improvement in the rate of sequence generation over this timescale.

NATUREjVol 458j9 April 2009 REVIEWS

723 Macmillan Publishers Limited. All rights reserved©2009

Stratton et al., Nature 2009

1977 - SangerChain-termination

method

Illumina

454

SolidIon Torrent

Pacific Biosciences

Oxford Nanopore

Complete Genomics

10X Genomics


1st generation to NGS

cancer genome can be obtained, including all point mutations,rearrangements and copy number changes. Mutations in the accom-panying mitochondrial genomes of the cancer will also be collected.With further adaptation this could be extended to include epigeneticalterations and could be applied to the transcriptomes of cancers toinvestigate the first phenotypic effects of all these changes. This cata-loguewill include all the drivermutations andhence all the cancer genesoperating in that cancer, whether they are protein-coding genes, non-coding RNA genes or more cryptic functional elements of the genome.Indeed, if known or unknown DNA viruses have contributed tooncogenesis thesewill alsobediscovered.The cataloguewill also includeall the passenger mutations that incorporate the signatures of previousexposures, DNA repair defects and other mutational processes thecancer has experienced over the decades during which it was evolving.

Until recently, this was an unattainable fantasy. However, thearrival of second-generation sequencing technologies promises anew era for cancer genomics. These platforms currently generatebillions of bases of DNA sequence per week, yields that are predictedto increase rapidly over the next couple of years (Fig. 3). Several proof-of-principle studies have recently been published applying these tech-nologies to cancer samples. These have demonstrated that the currentgeneration of massively parallel sequencing platforms can identify thefull range of somatically acquired genetic alteration in cancer, includ-ing point mutations on a genome-wide basis57, insertions and dele-tions57, copy number changes56 and genomic rearrangements56, as wellas characterizing the cancer cell transcriptome40,41. Furthermore, theseapproaches have the potential to identify subclonal genetic diversitywithin the population of cancer cells58, with particular relevance to thedetection of subclones carrying drug-resistance mutations59. Indeed,one high-coverage cancer genome sequence has recently beenreported57 and several others will emerge during the course of 2009.

Even with the remarkable technological advances in sequencing,however, the parameters of experiments to catalogue all somaticallyacquired variants in a cancer genome are sobering. To obtain acomplete catalogue of somatic mutations from an individual humancancer may require 20-fold sequence coverage of the cancer genome,and possibly more. Somatic mutations then have to be distinguishedfrom inherited DNA variants. Although most inherited variants thatare common in human populations (.5% allele frequency) have beendiscovered and are registered in databases, there are myriad rareinherited single nucleotide polymorphisms and structural variants thatare not. In most cancer genomes these rare germline variants faroutnumber the somatic mutations present. Therefore, for the foresee-able future at least, a high-coverage sequence of the normal genomefrom the same individual as the cancer will be an inescapable extra

burden to allow identification of the somatic changes. Thus, morethan 100,000,000,000 base pairs of DNA sequence will probably berequired to identify the catalogue of somatic mutations in a singlecancer genome.

Subsequently, it will be necessary to distinguish driver mutationsfrom passengers (see Box 1). The power to distinguish clusters ofdriver mutations in cancer genes from chance clusters of randomlydistributed passenger mutations will depend on how frequently acancer gene is mutated and the prevalence of passenger mutations.To be confident of identifying a cancer gene that is mutated in,5%of a particular type of cancer will require hundreds of cases to besequenced. Each of the.100 cancer types will probably require similarsample sizes.

Coordinating the sequencing of cancer genomesThere is, therefore, much work to be done over the next few years.Ideally, it should be organized to maximize use of resources andharmonize the product. This is the mission of the InternationalCancer Genome Consortium (ICGC, see http://www.icgc.org/home).Buildingon the success of previousmultinational, collaborative initia-tives such as the Human Genome Project and the HapMap consor-tium, the aim of ICGC is to comprehensively characterize somaticallyacquired genetic events in at least fifty classes of cancer, includingthose with the highest global incidence and mortality, requiringhigh-coverage sequencing of 20,000 cancer genomes ormore. The fullcatalogues of somatic mutation from each of these cancers will beintegrated with expression and epigenetic profiles of the same casesand correlated with clinical features.

Projects under the ICGC imprimatur will adhere to predeterminedstandards and procedures for ethical approval, data release,intellectual property, sample quality, clinical annotation, data quality,data storage and sequencing completion. Most importantly, given thedemanding nature of the task, the ICGC will coordinate studies tominimize duplication of effort and enable the most parsimoniousdeployment of resources.

The proposal to sequence large numbers of cancer genomes hasgenerated controversy reminiscent of the debate before sequencingof the reference human genome almost 20 years ago. The experimentswill be expensive and, to some extent, we cannot predict what will befound. However, the human genome is finite. Therefore, with furthertechnological advances in DNA sequencing that are already in sight,this is a deliverable project that will comprehensively elucidate centralquestions relating to the nature of human cancer. The clinical andtranslational implications of such a body of work are profound.Beyond the identification of further potentially druggable cancergenes, a comprehensive catalogue of somatic mutations in carefullycharacterized clinical samples will generate new insights into thegenetic patterns that underpin disease phenotype, prognosis, drugresponse and chemotherapy resistance. As the costs of sequencingwhole cancer genomes drop towards US$1,000, routine sequencingin a clinical, diagnostic setting will become feasible. Such data maydrive individualized therapeutic decision-making through the abilityto predict prognosis, to choose therapeutic regimens known to haveefficacy for the particular genetic subtype of cancer, to sensitivelymonitor response to therapy and to identify rare subclonesharbouringdrug-resistancemutations before therapy is even initiated.Individualized therapeutics will require individualized diagnostics.

The discussion is therefore not about whether to do the experiment,butwhen and how. In amanner similar to theHumanGenomeProjectwe have to coordinate the work internationally to maximize use ofresources and minimize duplication of effort to generate a resourceof high quality so that we only have to do it once, empowering cancerresearch with a lasting legacy for the future.

Forward lookApproximately 100,000 somaticmutations fromcancer genomeshavebeen reported in the quarter of a century since the first somatic

Capillary sequencingCapillary sequencing

1980 1985 1990 1995 2000

10

100

1,000

10,000

100,0000

1,000,000

10,000,000

100,000,000

1,000,000,000

2010 Future

Manualslab gel

Automatedslab gel First-generation

capillary

Second-generationcapillary sequencer

Microwellpyrosequencing

Short-readsequencers

Singlemolecule?

Gel-based systems

Massively parallel sequencing

Year

2005

Kilo

base

s pe

r day

per

mac

hine

Figure 3 | Improvements in the rate of DNA sequencing over the past 30years and into the future. From slab gels to capillary sequencing andsecond-generation sequencing technologies, there has been a more than amillion-fold improvement in the rate of sequence generation over this timescale.

NATUREjVol 458j9 April 2009 REVIEWS

723 Macmillan Publishers Limited. All rights reserved©2009

Stratton et al., Nature 2009

1977 - SangerChain-termination

method

Illumina

454

SolidIon Torrent

Pacific Biosciences

Human genome

Oxford Nanopore

Complete Genomics

10X Genomics


Sequencing costs

• Computer speed and storage capacity is doubling every 18 months and this rate is steady

• DNA sequence data is doubling faster than computer speeds!


Human sequencing• First draft genome of human in 2001, final 2004

• Estimated costs $3 billion, time 13 years

• Today:

• 1-2000$ for one genome

• A couple of days!


Storage and analysis

Highest cost is (almost) not the sequencingbut

storage and analysis

A standard human (30-40x) whole-genome sequencing exp. would

create 150 Gb of data

One Illumina HiSeq X Ten system:18,000 human genomes per year!


Distributed data productionWorld wide >900 centers

Data transfer and storage becomes an

issue

>60 Pb pr year (2014)

http://omicsmaps.com

http://omicsmaps.com


The X Genomes projects

• Human population projects

• 1000 genomes project (2500 individuals)

• Genomics England (100k individuals)

• US Precisions medicine (1 million individuals)

• 100K pathogens project, Earth Microbiome project, Cancer genome project, Plants and animals, Insects,…


NGS in the clinic

• Diagnostics of patients (+ fetus)

• Focused treatment of cancer patients

• Sequencing of bacterial isolates

• Country-wide projects:

• UK, US, Qatar, Finland, China, …

• DK: Danish regions want to sequence 100k individuals

• Personalized medicine initiative in DK

• Up to 70% of medicine does not work!

• Sequence 100,000 patients on hospitals

• Use extensive registry data

• Current: 100 mill DKK (estimated 2 bill DKK)

• National Genomics Institute

• Personalized medicine initiative in DK

• Up to 70% of medicine does not work!

• Sequence 100,000 patients on hospitals

• Use extensive registry data

• Current: 100 mill DKK (estimated 2 bill DKK)

• National Genomics Institute

Ethical debate?


NGS & Bioinformatics

• Extreme data size causes problems

• Just transferring and storing the data

• Standard comparisons fail (N*N)

• Standard/old tools can not be used

• Think in fast and parallel programs


What can we use it for?• Whole genome re-sequencing

• Population genomics

• Diagnostics

• Cancer genomics

• Ancient genomes

• Metagenomics

• RNA sequencing

• Single cell sequencing

• Genomic Epidemiology

• anything with DNA


How it works?

Introduction to NGS - DTU Bioinformatics · 27626 - Next Generation Sequencing Analysis...

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