1. A basic review of genetics Dr. Danny Chan Associate Professor Assistant Dean (Faculty of Medicine) Department of Biochemistry Department of Biochemistry The University of Hong Kong The University of Hong Kong

2. Cells and genes 50,000,000,000,000 cells

3. Nucleus (99.9% of the genes) Cells and genes Mitochondria (few more genes) ~20, 0000 genes

4. Genes are on DNA Cytosine Thymine Guanine Adenine O CH 2 O OP O O-O- N N O CH 3 O CH 2 O OP O O-O- N N O NH 2 O CH 2 O OP O O-O- H O N N O NH 2 N N O CH 2 O OP O O-O- N N N N NH 2 3’ 5’ DNA sequence  genetic code  genes D Deoxyribose N Nucleic A Acids

5. Genes determine why we are the way we are!

6. Genes are passed on from one generation to the next Genetic traits You have inherited genes from your father that make proteins instructing your hair cells or eye cells to produce hairs and eyes that are the same colours and shape as your father. Genetic traits can also be a behavior, feelings, or responses to a given environment

7. DNA are super-coiled into chromosomes chromosome

8. 22 pairs of autosomes and 1 pair of sex chromosomes Human Genome Autosomes Sex chromosomes

9. 24 pairs of chromosomes Other primate chromosome numbers 21 pairs of chromosomes

10. Other species 30 pairs of chromosomes 39 pairs of chromosomes 4 pairs of chromosomes

11. The genome projects

12. How similar are we to other species? ~98.5%~93%

13. How about with other humans? ~99.5% What makes us different from one another?

14. Variations in DNA sequence or Polymorphisms Variable number tandem repeats (VNTRs) Microsatellites Single nucleotide polymorphisms (SNPs) Small insertions and deletions (Indels) Copy number variations (CNVs)

15. Variations in DNA sequence or Polymorphisms Variable number tandem repeats (VNTRs) Microsatellites Single nucleotide polymorphisms (SNPs) Small insertions and deletions (Indels) Copy number variations (CNVs)

16. Repeat units of nucleotides 1-6bp in length The most widely used are the (CA) n microsatellites CACACACACACA CACACACACACACACA 6 (CA) allele 8 (CA) allele Microsatellites

17. are substitutions, insertions or deletions of a single base TCGAGAGGCTAGGCTAGGA TCGAGAGGCCAGGCTAGGA Substitution T-allele C-allele TCGAGAGGCTTAGGCTAGGA TCGAGAGGCAGGCTAGGA Insertion (+) allele (-) allele Single nucleotide polymorphisms (SNPs) deletion

18. SNPs arise during DNA replication Opportunities for errors Single base errors/changes create 3 x 10 9 bases SNPs 10 7 SNPs

19. Genetic differences and similarities between people You Rest of the world Genetic signature

20. Some SNPs affect the way we look

21. Some affect our susceptibility to diseases

22. Others affect our response to drugs/pain

23. or.. no differences!.. in health, personalities or responses to the environment

24. SNPs affecting gene function mRNA Gene t-RNA Newly synthesized protein Protein Altered Protein

25. Protein function and phenotype Protein Altered Protein Altered protein function Altered Phenotype

26. MumDad Hair color Height Longevity Body fat Intelligence Eye color A pair of homologous chromosomes

27. 2 sets 1 set oocyte Sperm Somatic cell

28. Meiosis I Meiosis II Diploid cell Four haploid cells DNA replication Homologous chromosome pairing Meiosis (making sperm or oocytes)

29. Genetic recombination in meiosis Doubling Cross-over and exchange DNA Genes get shuffled during recombination

30. Phenotypes Observable or measurable traits Genes + environment Begins in the womb and continues throughout life

31. Phenotypes Differences in some phenotype are determined mostly by genes Height How genes influence personality, behavior and perception is less well understood

32. We can now interrogate SNPs across our genome all at once Understand how some SNPs are affecting our phenotype … from our genome Genotype-phenotype relationship Learning more about our phenotypes

33. Correlating genetic variations and diseases phenotypes Family linkage analysis Case-control association study Need a large pedigree!

34. Correlating genetic variations and diseases phenotypes Case-control association study Need a large cohort!

35. Rare genetic diseases Common diseases

36. Rare genetic diseases Single gene Monogenic disorder Early-onset Rare (Osteogenesis imperfecta) (1:30,000 – 1:70,000) (prenatal)

37. An autosomal dominant disease for which the gene resides on this chromosome

38. 6 (CA) allele CACACACACACA 8 (CA) allele CACACACACACACACA 7 (CA) allele CACACACACACACA 1 (CA) allele CA 2 (CA) allele CACA 3 (CA) allele CACACA ……

39. 5 6 4 7 2 3 Marker studied

40. 2 3 1 5 4 4 Marker studied

41. 1 5 3 5 6 7 Marker studied

42. 2 4 2 5 2 7 Marker studied

43. 1 3 1 2 4 5 Marker studied

44. 2 42 42 42 4 2 52 52 52 5 2 72 72 72 7

45. (4) (24) (5) (25) ()(27)()(27)(33)(14) (3) (23) (6) (26) (1) (12) (6) (26) (4) (24)(16)(14) (46) (34)(13)(58) (18) (13)(78) (18) (47) (46)(67) Genotype other family members The key is to identify a genetic marker that is always inherited by family members with the disease but not by those who do not have the disease

46. Disease gene Gene resides here Fine mapping Define the region of maximal linkage Causative mutation!

47. The logarithm (in base 10) of the odds of linkage –the ratio of the likelihood that loci are linked to the likelihood that they are not linked A LOD of 3.0 = odds of 1000/1 in favour of linkage –Equivalent to a 5% chance of error Logarithm of odds (LOD) score Degree of linkage

48. Advantages: –Localization of areas associated with increase disease risk across the genome –Can study multiple markers simultaneously Disadvantages –Multi-generational cases difficult to recruit with high mortality conditions –Difficult to study late-onset diseases/traits –Difficult to study complex traits Family linkage studies

49. Genetics Many genes may be involved Environment Interactions between environment and genes 2 4 1 3 Interaction between genes (common) (Risk factors) Diabetes Osteoporosis Osteoarthritis Alzheimer Cancer Complex traits

50. Linkage deals with a specific genetic relationship between loci on a chromosome Association describes a statistical relationship between genes or genetic variants and the disease/trait of interest Association study for complex traits

51. CaseControl Large Cohort required Good phenotype definition Case-Control Association Studies

52. Allele 1 (T) Allele 2 (A) Gene A An example for one SNP in a gene CaseControl

53. Allele 2 is a possible risk allele Uneven distribution of the SNP variants indicates an association Control case association study CaseControl

54. Identifies disease susceptibility gene variants by comparing genetic variants between people with and without the disease of interest. Any particular association between a genetic variant and a disease does not mean that the variant is important in causation. Association studies

55. “a huge assistance in high throughput mapping of polygenic diseases and a minor pest” Linkage disequilibrium (LD)

56. LD relates to recombination events The nonrandom association between alleles in a population due to their tendency to be co-inherited because of reduced recombination between them Hot spots Cold spots

57. Group of extant chromosomes Ancestral segment New segment introduced by recombination MutationAncestralchromosome

58. Group of extant chromosomes Ancestral segment New segment introduced by recombination Mutation SNPs Ancestralchromosome

59. Ancestral segment New segment introduced by recombination Mutation Ancestralchromosome Group of extant chromosomes

60. Ancestralchromosome Polymorphisms within regions of reduced recombination will mark the same association Haplotype block polymorphic segment of DNA marking an ancestral variant LD Map

61. To identify all common DNA polymorphisms The International HapMap Project Started October 2002 Define the LD pattern for different populations

62. Microsatellites SNPs ~ 10 7 to choose from Using high density of SNPs for disease hunting Enhancing mapping Accuracy and speed

63. Genome wide association scan (GWAS) Now able to assess ~2.5M SNPs in a genome all at once Various platforms are available for mostly common SNPs (>5 % in the general population)

64. NHGRI GWA Catalog www.genome.gov/GWAStudies Published Genome-Wide Associations through 12/2010, 1212 published GWA at p<5x10 -8 for 210 traits Missing heritability Rare SNPs with strong effect not yet identified?

65. Next generation sequencing

66. 1000 genomes project http://www.1000genomes.org

67. Goal of the 1000 genomes project Rare genetic variants Common genetic variants Diabetes Osteoporosis Osteoarthritis Alzheimer Cancer Cystic fibrosis Huntington disease Osteogenesis imperfecta Achondroplasia Knowledge gap ? discover >95 % of SNPs, CNVs, indels ~1% across the genome, 0.1-0.5% in gene regions ?

68. Small insertions and deletions (indels) Copy number variations (CNVs) miRNA Epigenetic controls Other variations for consideration Mega load of genetic data will be available.. Are we ready with the phenotype information?

69. PhenotypePhenotype Phenotype Phenotype $$$ $$$ $$$$$ GenotypeGenotype Genotype Genotype