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A basic review of genetics Dr. Danny Chan Associate Professor Assistant Dean (Faculty of Medicine) Department of Biochemistry The University of Hong Kong Cells and genes 50,000,000,000,000 cells Cells and genes Mitochondria Nucleus (few more genes) (99.9% of the genes) ~20, 0000 genes Genes are on DNA NH2 5’ O O P O N N CH2 Cytosine O O OO CH3 Thymine NH O O P O N CH2 O O OO N N Guanine O O Deoxyribose Nucleic Acids P O CH2 O N N NH2 ONH2 N N Adenine O O P O CH2 N O N O- 3’ DNA sequence genetic code genes Genes determine why we are the way we are! 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 DNA are super-coiled into chromosomes chromosome Human Genome 22 pairs of autosomes and 1 pair of sex chromosomes Autosomes Sex chromosomes Other primate chromosome numbers 24 pairs of chromosomes 21 pairs of chromosomes Other species 30 pairs of chromosomes 4 pairs of chromosomes 39 pairs of chromosomes The genome projects How similar are we to other species? ~93% ~98.5% How about with other humans? What makes us different from one another? ~99.5% 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) 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) Microsatellites Repeat units of nucleotides 1-6bp in length The most widely used are the (CA)n microsatellites 6 (CA) allele CACACACACACA 8 (CA) allele CACACACACACACACA Single nucleotide polymorphisms (SNPs) are substitutions, insertions or deletions of a single base T-allele TCGAGAGGCTAGGCTAGGA Substitution C-allele TCGAGAGGCCAGGCTAGGA Insertion (+) allele TCGAGAGGCTTAGGCTAGGA deletion (-) allele TCGAGAGGCAGGCTAGGA SNPs arise during DNA replication 3 x 109 bases 107 SNPs Opportunities for errors Single base errors/changes create SNPs Genetic differences and similarities between people You Rest of the world Genetic signature Some SNPs affect the way we look Some affect our susceptibility to diseases Others affect our response to drugs/pain or .. no differences! .. in health, personalities or responses to the environment SNPs affecting gene function Newly synthesized protein Gene mRNA t-RNA Altered Protein Protein Protein function and phenotype Altered protein function Altered Phenotype Altered Protein Protein A pair of homologous chromosomes Mum Hair color Height Longevity Body fat Intelligence Eye color Dad Hair color Height Longevity Body fat Intelligence Eye color Sperm Somatic cell 2 sets 1 set oocyte 1 set Meiosis (making sperm or oocytes) Meiosis I Meiosis II Diploid cell DNA replication Homologous chromosome pairing Four haploid cells Genetic recombination in meiosis Doubling Cross-over and exchange DNA Genes get shuffled during recombination Phenotypes Observable or measurable traits Genes + environment Begins in the womb and continues throughout life Phenotypes Differences in some phenotype are determined mostly by genes Height How genes influence personality, behavior and perception is less well understood Learning more about our phenotypes … from our genome We can now interrogate SNPs across our genome all at once Understand how some SNPs are affecting our phenotype Genotype-phenotype relationship phenotypes Correlating genetic variations and diseases • Family linkage analysis • Case-control association study Need a large pedigree! phenotypes Correlating genetic variations and diseases • Case-control association study Need a large cohort! • Rare genetic diseases • Common diseases Rare genetic diseases Single gene Monogenic disorder (Osteogenesis imperfecta) Rare (1:30,000 – 1:70,000) Early-onset (prenatal) An autosomal dominant disease for which the gene resides on this chromosome 1 (CA) allele CA 2 (CA) allele CACA …… 3 (CA) allele CACACA 6 (CA) allele CACACACACACA 7 (CA) allele CACACACACACACA 8 (CA) allele CACACACACACACACA Marker studied 56 47 23 Marker studied 23 15 44 Marker studied 15 35 67 Marker studied 24 25 27 Marker studied 13 12 45 Marker studied 24 25 27 Genotype other family members (23) (16) (14) (26) (34) (13) (58) (12) (13) (78) (24) (46) (33) (14) (18) (25) (18) (26) (47) (27) (46) (67) (24) 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 Define the region of maximal linkage Fine mapping Gene resides here Disease gene Causative mutation! Logarithm of odds (LOD) score • 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 Degree of linkage Family linkage studies • 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 Complex traits (common) Environment Diabetes Osteoporosis Osteoarthritis Alzheimer Cancer Interactions between environment and genes 1 2 Genetics 4 Interaction between genes 3 Many genes may be involved (Risk factors) Association study for complex traits • 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 Case-Control Association Studies Large Cohort required Good phenotype definition Case Control An example for one SNP in a gene Gene A Allele 1 (T) Allele 2 (A) Case Control Control case association study Uneven distribution of the SNP variants indicates an association Case Allele 2 is a possible risk allele Control Association studies • 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. Linkage disequilibrium (LD) “a huge assistance in high throughput mapping of polygenic diseases and a minor pest” 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 Mutation Group of extant chromosomes Ancestral chromosome Ancestral segment New segment introduced by recombination SNPs Mutation Group of extant chromosomes Ancestral chromosome Ancestral segment New segment introduced by recombination Mutation Group of extant chromosomes Ancestral chromosome Ancestral segment New segment introduced by recombination Haplotype block polymorphic segment of DNA marking an ancestral variant Ancestral chromosome LD Map Polymorphisms within regions of reduced recombination will mark the same association The International HapMap Project To identify all common DNA polymorphisms Define the LD pattern for different populations Started October 2002 Using high density of SNPs for disease hunting Microsatellites SNPs Enhancing mapping Accuracy and speed ~ 107 to choose from 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) 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? NHGRI GWA Catalog www.genome.gov/GWAStudies Next generation sequencing 1000 genomes project http://www.1000genomes.org Goal of the 1000 genomes project ? Knowledge gap Rare genetic variants Common genetic variants discover >95 % of SNPs, CNVs, indels ~1% across the genome, 0.1-0.5% in gene regions Cystic fibrosis Huntington disease Osteogenesis imperfecta Achondroplasia ? Diabetes Osteoporosis Osteoarthritis Alzheimer Cancer Other variations for consideration • Small insertions and deletions (indels) • Copy number variations (CNVs) • miRNA • Epigenetic controls Mega load of genetic data will be available .. Are we ready with the phenotype information? Genotype Phenotype $ Genotype Phenotype $$ Genotype Phenotype $$$ Genotype Phenotype $$$$$