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

2. “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

3. “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

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

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

6. 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

7. 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

8. ≥2.3kb Deletion aCGH: Child with Seizures, Microcephaly and Developmental Delay Chromosome 14 14q12

9. 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

10. 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

11. 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

12. Falling Costs of Sequencing a Human Genome (log scale)

13. 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

14. 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)

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

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

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

18. 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

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

20. 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

21. 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)

22. 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)

23. 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

24. 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..

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

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

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

28. 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

29. 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