Recent Advances in Genomic Science Julian Sampson Institute of Medical Genetics, Cardiff.

Slides:



Advertisements
Similar presentations
David A Collier Professor of Neuropsychiatric Genetics Institute of Psychiatry Copy Number Variation in neurodevelopmental disorders:
Advertisements

Gene identification by whole genome array CGH Richard Barber 21st February Gene Discovery.
Vanderbilt Center for Quantitative Sciences Summer Institute Sequencing Analysis Yan Guo.
Genetic Approaches to Rare Diseases: What has worked and what may work for AHC Erin L. Heinzen, Pharm.D, Ph.D Center for Human Genome Variation Duke University.
Wrapup. NHGRI strategic plan What does the NIH think genomics should be for the next 10 years? [Nature, Feb. 2011]
Bioinformatics lectures at Rice University Li Zhang Lecture 10: Networks and integrative genomic analysis-2 Genome instability and DNA copy number data.
Targeted Data Introduction  Many mapping, alignment and variant calling algorithms  Most of these have been developed for whole genome sequencing and.
Tumour karyotype Spectral karyotyping showing chromosomal aberrations in cancer cell lines.
Biology and Bioinformatics Gabor T. Marth Department of Biology, Boston College BI820 – Seminar in Quantitative and Computational Problems.
Computational Tools for Finding and Interpreting Genetic Variations Gabor T. Marth Department of Biology, Boston College
I inherited What??? You and Your Genes: The Explosive New World of Genetics David Finegold, M.D.
An Update in Genetics of Epilepsy
Office hours Wednesday 3-4pm 304A Stanley Hall Review session 5pm Thursday, Dec. 11 GPB100.
Polymorphisms – SNP, InDel, Transposon BMI/IBGP 730 Victor Jin, Ph.D. (Slides from Dr. Kun Huang) Department of Biomedical Informatics Ohio State University.
Genome Analysis Determine locus & sequence of all the organism’s genes More than 100 genomes have been analysed including humans in the Human Genome Project.
Presented by Karen Xu. Introduction Cancer is commonly referred to as the “disease of the genes” Cancer may be favored by genetic predisposition, but.
Affymetrix Resequencing Arrays Matthew Smith Trainee Presentation West Midlands Regional Genetics Laboratory.
Bioinformatics Jan Taylor. A bit about me Biochemistry and Molecular Biology Computer Science, Computational Biology Multivariate statistics Machine learning.
Dr Katie Snape Specialist Registrar in Genetics St Georges Hospital
Understanding Genetics of Schizophrenia
Large-Scale Copy Number Polymorphism in the Human Genome J. Sebat et al. Science, 305:525 Luana Ávila MedG 505 Feb. 24 th /24.
Whole Exome Sequencing for Variant Discovery and Prioritisation
Considerations for Analyzing Targeted NGS Data Introduction Tim Hague, CTO.
RExPrimer Pongsakorn Wangkumhang, M.Sc. Biostatistics and Informatics Laboratory, Genome Institute, National Center for Genetic Engineering and Biotechnology.
Epigenome 1. 2 Background: GWAS Genome-Wide Association Studies 3.
Manifestation of Novel Social Challenges of the European Union in the Teaching Material of Medical Biotechnology Master’s Programmes at the University.
Constitutional (germ-line) variants in hereditary conditions
Copy Number Variants: detection and analysis Manuel Ferreira & Shaun Purcell Boulder, 2009.
Gene 210 Genetics of Neurodevelopmental and Neurospychiatric disorders
Computational research for medical discovery at Boston College Biology Gabor T. Marth Boston College Department of Biology
Assay Development Breakout (red) Who was in the room? About half of attendees are active NGS users N=1 doing whole genome analyses Everyone else doing.
Data Analysis Summary. Elephant in the room General Comments General understanding that informatics is integral in medical sequencing and other –omics.
Genetics-multistep tumorigenesis genomic integrity & cancer Sections from Weinberg’s ‘the biology of Cancer’ Cancer genetics and genomics Selected.
CS177 Lecture 10 SNPs and Human Genetic Variation
A Genome-wide association study of Copy number variation in schizophrenia Andrés Ingason CNS Division, deCODE Genetics. Research Institute of Biological.
Nature Genetics Vol.36 Sept 2004 Detection of Large-scale Variation In the Human Genome Iafrate, Feuk, Rivera, Listewnik, Donahoe, Qi, Scherer, Lee any.
Doug Brutlag 2011 Genomics & Medicine Doug Brutlag Professor Emeritus of Biochemistry &
Copy Number Variation Eleanor Feingold University of Pittsburgh March 2012.
Identification of Copy Number Variants using Genome Graphs
Cancer genomics Yao Fu March 4, Cancer is a genetic disease In the early 1970’s, Janet Rowley’s microscopy studies of leukemia cell chromosomes.
Lecture 6. Functional Genomics: DNA microarrays and re-sequencing individual genomes by hybridization.
Lecture 11. Topics in Omic Studies (Cancer Genomics, Transcriptomics and Epignomics) The Chinese University of Hong Kong CSCI5050 Bioinformatics and Computational.
Lecture-3 EXOME SEQUENCING Huseyin Tombuloglu, Phd GBE423 Genomics & Proteomics.
© 2012 Genomatix GeneGrid finding disease causing variants in NGS data Claudia Gugenmus Genomatix Software GmbH Bayerstrasse 85a
Computational Biology and Genomics at Boston College Biology Gabor T. Marth Department of Biology, Boston College
INTERPRETING GENETIC MUTATIONAL DATA FOR CLINICAL ONCOLOGY Ben Ho Park, M.D., Ph.D. Associate Professor of Oncology Johns Hopkins University May 2014.
Unit 1 – Living Cells.  The study of the human genome  - involves sequencing DNA nucleotides  - and relating this to gene functions  In 2003, the.
Notes: Human Genome (Right side page)
Genome Analysis: Future Directions Christian Marshall.
A brief guide to sequencing Dr Gavin Band Wellcome Trust Advanced Courses; Genomic Epidemiology in Africa, 21 st – 26 th June 2015 Africa Centre for Health.
Global Variation in Copy Number in the Human Genome Speaker: Yao-Ting Huang Nature, Genome Research, Genome Research, 2006.
Different microarray applications Rita Holdhus Introduction to microarrays September 2010 microarray.no Aim of lecture: To get some basic knowledge about.
1 Finding disease genes: A challenge for Medicine, Mathematics and Computer Science Andrew Collins, Professor of Genetic Epidemiology and Bioinformatics.
Canadian Bioinformatics Workshops
Moiz Bakhiet, MD, PhD, Professor and Chairman
Interpreting exomes and genomes: a beginner’s guide
NISCHR Academic Health Science Collaboration Launch
THE ROLE OF NEXT GENERATION SEQUENCING IN CLINICAL PRACTICE
Christopher J. Klein, MD, Tatiana M. Foroud, PhD 
Global Variation in Copy Number in the Human Genome
Human Cells Human genomics
Content and Labeling of Tests Marketed as Clinical “Whole-Exome Sequencing” Perspectives from a cancer genetics clinician and clinical lab director Allen.
Christopher J. Klein, MD, Tatiana M. Foroud, PhD 
Figure 1 The genomic nephrology workflow: genetic diagnosis and clinical application Figure 1 |The genomic nephrology workflow: genetic diagnosis and clinical.
Psychiatric Disorders: Diagnosis to Therapy
The Genetic Basis for Cancer Treatment Decisions
100,000 Genomes Project & mainstreaming genomic medicine
Psychiatric Disorders: Diagnosis to Therapy
BF528 - Genomic Variation and SNP Analysis
Presentation transcript:

Recent Advances in Genomic Science Julian Sampson Institute of Medical Genetics, Cardiff

“the human genome sequence offers a unique opportunity to understand genetic factors in health and disease, and to apply this rapidly to prevention, diagnosis and treatment” Francis Collins, Director NHGRI (and now of NIH) to US House of Representatives, May 2003 April 24 th 2003

“the human genome sequence offers a unique opportunity to understand genetic factors in health and disease, and to apply this rapidly to prevention, diagnosis and treatment” Francis Collins, Director NHGRI to US House of Representatives, May 2003 April 24 th 2003

How Far Have We Got ? Changing technologies Set the scene for discussion of application: linking genomic variation and disease (to inform diagnosis, prevention, treatment)

Changing Technology for Testing the Genome: Resolution, Scale, Speed and Cost Karyotype 5-10Mb (≈ 10 7 bp) Several weeks Banding from 1960s

Changing Technology for Testing the Genome: Resolution, Scale, Speed and Cost – 1990s Whole genome or targeted aCGH Karyotype 5-10Mb (≈ 10 7 bp) Several weeks Resolution depends on probe density Days Automated Sanger Sequencing PCR amplicon 1bp Resolution Extremely accurate

Arrayed DNA sequences (oligos) Reference genomic DNA Test sample genomic DNA Image individual spots (n = 2M in DDD) Testing the Genome with DNA Arrays Cy3/Cy5 ratio calculated for each arrayed sequence Identifies deletions or duplications in genome (copy number variants or CNVs) Cy3Cy5

≥2.3kb Deletion aCGH: Child with Seizures, Microcephaly and Developmental Delay Chromosome 14 14q12

DE NOVO DELETED REGION IN THE PATIENT WALES LABORATORY CALL HISTORY (n=2) GENES aCGH: A 2.3kb deletion of FOXG1 at 14q12 DECIPHER database – over 30 overlapping deletions “FOXG1 syndrome” (Decipher has approx. 20,000 entries from >30 countries) - severe developmental delay, brain malformation, seizures, microcephaly Current aCGH detects a genetic cause in 5-20% of patients with developmental disorders But: CNVs that Non-Pathogenic or that are associated with predisposition/variability FOXG1

Changing Technology for Testing the Genome: Resolution, Scale, Speed and Cost Whole genome or targeted aCGH Karyotype 5-10Mb (≈ 10 7 bp) Several weeks <1 kb (≈ 10 2 bp) Several days Sanger sequencing 1st Genome: $3Billion, 13 Years Follow up genomes $100M

Changing Technology for Testing the Genome: Resolution, Scale, Speed and Cost Whole genome or targeted aCGH Karyotype 5-10Mb (≈ 10 7 bp) Several weeks NGS: genes, exomes, genomes Genome at 1bp resolution Days (hours) “$1000” IT / Bioinformatics

Falling Costs of Sequencing a Human Genome (log scale)

Characterising Genomic Variation by NGS Sequence: gene, gene panels (e.g. retina 108, epilepsy 31), exomes, genomes Identify and Characterise: SNPs, insertions, deletions Translocations, inversions CNVs and Aneuploidies i.e. NGS will do virtually everything other technologies can do, and at 1bp resolution

NGS technologies Lack Specificity Mis-calling of bases 0.1-1% Need to distinguish true variants from artifacts “Read depth” important, but varies across exome/genome → filtering algorithms (“variant calling pipelines”) Bioinformatics expertise is in research centres, not in the NHS (more joint working needed)

Cancer Genomes Genomic Instability and somatic variation Constitutional (germline) variation Genome Variation: Constitutional & Somatic

Cancer Genomes Genomic Instability and somatic variation Constitutional (germline) variation Genome Variation: Constitutional & Somatic

LB Alexandrov et al. Nature (2013) The prevalence of somatic mutations across human cancer types.

Cancer Genomes: Genomic instability creates heterogeneous cell populations (many differently evolving clones) Critical mutations (e.g. for drug resistance) may be present in sub-set of cells Distinguishing low level mutations from mis- called bases is bioinformatically challenging – variants require validation

Cancer Genomes and somatic variation Constitutional (germline) variation Genome Variation: Neutral & Disease-Associated “Passenger” and “Driver” Mutations Functional and Polymorphic Variation

Linking Genomic Data and Disease Distinguish disease-related from neutral variation 250 – 300 loss of function mutations per genome in annotated genes Missense variants CNVs Databases of genomic variation and phenotype data Statistical, in silico, in vitro and in vivo approaches

Cataloguing Genomic Variation and relating this to disease Decipher Human Gene Mutation Database (HGMD) Human Genome Variation Project (HGV) 1000 Genomes UK10K 100,000 Genomes (UK) Cosmic The Cancer Genome Atlas (TCGA)

Cataloguing Genomic Variation and relating this to disease Decipher Human Gene Mutation Database (HGMD) Human Genome Variation Project (HGV) 1000 Genomes UK10K 100,000 Genomes (UK) Cosmic The Cancer Genome Atlas (TCGA)

Sequencing for unknown disease-causing variants: Trios de novo mutations (e.g. in Exome or Genome) e.g. Mendelian and developmental disorders (DDD project), autism, schizophrenia

Inherited “Single Gene” (Mendelian) Disorders >20,000 genes in the human genome > 7,000 Mendelian disorders 1 in 17 people have a “rare disease” – i.e. one that affects < 1 in 2000 of the population Individually rare, cumulatively frequent Many genes identified, pathophysiology becoming understood, targeted treatments emerging..

Single Gene Mendelian Disorder Multiple phenotypic effects Multiple Causes Shared Phenotype Complex Disorder

Single Gene Multiple phenotypic effects Multiple Causes Shared Phenotype Stratified Medicine Complex Disorder Mendelian Disorder Targeted Treatment

Many Genomes are Relevant to Human Health Human Genome Model organisms, pathogens and vectors

Many “-Omic” Applications of Next Generation Sequencing Genetics and Genomics Epigenomics (e.g. “methylome”) -probing a mechanism for regulating and adapting the genome Transcriptomics – probing differential genome usage (time, place, environment) Cho et al. Nature 2012 Costello et al. Nat Biotech 2009

Summary Cost of genomic analysis in healthcare is now as affordable as many other technologies Benefits in mendelian / chromosomal disorders and stratified medicine already translating from research to the clinic Diagnostics well developed Targeted therapy and prevention based upon genomic understanding gaining pace