Genetic variation and its role in health pharmacology
20 likes7,900 views
Genetic variation exists at different scales, from single nucleotide polymorphisms within individuals of a species to larger structural differences between species. Genetic variation arises through mutations, recombination, gene flow, genetic drift, and the interaction of these processes over time. The effective population size of a species influences how genetic variation is shaped by these evolutionary forces.
More Related Content
Similar to Genetic variation and its role in health pharmacology (20)
Genetic variation and its role in health pharmacology
- 1. What is genetic variation? Polymorphisms: Variation between individuals in a population (within species) Substitutions: Fixed variation between individuals of species (between species) Species A Species B Species C
- 2. What is genetic variation? Differences in the nucleotide sequence: Small scale: mutations in coding or non-coding DNA Protein alignment Hamster-Mouse-Human
- 3. 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 - Between species 1 and 2 - Within species 1 - Within species 2 Genetic variation within and between species Neutral rate of nucleotide substitutions and polymorphisms Nucleotidevariationin25kbwindows
- 4. 80 millions years Differences in the nucleotide sequence at large scale: structural differences across chromosomes Human and mouse genetic similarities Mouse chromosomes Human chromosomes
- 5. From where does genetic variation come?
- 6. Mutations From where does genetic variation come? Basesubstitutionmutationrate(10-9bp/generation
- 7. Recombination Shuffling gene variants (alleles) in a population From where does genetic variation come?
- 8. Recombination From where does genetic variation come?
- 9. Gene flow From where does genetic variation come?
- 10. Genetic drift From where does genetic variation come?
- 11. Effective population size Effective population size: Ne Ne is less than the actual number of potentially reproducing individuals! Sewal-Wrigth (1931) “The effective population size is the number of breeding individuals in an idealised population that show the same amount of dispersion of allele frequencies under random genetic drift or the same amount of inbreeding as the population under consideration"
- 12. Effective population size Sea urchins Strongylocentrotus purpuratus Wheat Triticum aestivum Tiger Panthera tigris
- 13. Effective population size - of Prokaryotes and Archaea?
- 14. Why does effective population size matters?
- 15. Natural selection From where does genetic variation come?
- 16. AGT CTC GGG CTG TGA ser leu gly leu STOP Synonymous mutation Non -synonymous mutation Replacement mutationSilent mutation Natural selection can act on changes in coding sequences AGT CAA GGG CTG TGA ser gln gly leu STOP AGT CTA GGG CTG TGA ser leu gly leu STOP
- 17. Bamshad and Wooding, 2003 Natural selection Different types of selection can change the frequencies of gene variants (alleles)
- 18. How can natural selection act on a locus?
- 19. Effective population size matters
- 21. Mating System Diversity in Wild(10−3) Diversity in Cultivated (10−3) Loci Lπ (%) References Zea mays ssp. parviglumis Zea mays ssp. mays Outbreeding πtotal = 9.7 πtotal = 6.4 774 35 Wright et al. (2005) πsilent = 21.1 πsilent = 13.1 12 38 Tenaillon et al. (2004) Medicago sativa ssp. sativa M. s. ssp. sativa 2 Muller et al. (2006) Outbreeding πtotal = 20.2 πtotal = 13.5 31 πsilent = 29 πsilent = 20 31 Helianthus annuus H. annuus 9 Liu and Burke (2006) Outbreeding πtotal = 12.8 πtotal = 5.6 55 πsilent = 23.4 πsilent = 9.6 59 Mixed Pennisetum glaucum P. glaucum 1 Gaut and Clegg (1993) θsilent = 3.6 θsilent = 2.4 33 Glycine soja Glycine max 102 Hyten et al. (2006) Inbreeding πtotal = 2.17 πtotal = 1.43 34 πsilent = 2.76 πsilent = 1.77 36 Hordeum spontaneum Hordeum vulgare Inbreeding πsilent = 16.7 πsilent = 7.1 5 57 Caldwell et al. (2006) πtotal = 8.3 πtotal = 3.1 7 62 Kilian et al. (2006) Triticum turgidum ssp. dicoccoides Triticum turgidum ssp. dicoccum 21 This study Inbreeding πsilent = 3.6 πsilent = 1.2 65 πtotal = 2.7 πtotal = 0.8 70 “Domestication cost” in crop species Haudry et al, 2007, MBE Lu et al, 2007, Trends Plant Sci Oi: O. sativa ssp Indica Oj: O. sativa spp Japonica Ob: Oryzae brachyantha
- 22. Does a global increase in dN/dS reflects something good or bad? - and how can be address that? - Recombination can be used as a proxy for the efficacy of selection
- 23. Genetic variation in the genome
- 24. Genetic variation in the genome: Different scales Ellegren et al, 2003 (a) Between chromosomes (b) Within chromosomes (c) Within regions (d) Context effects, methylated cytosine mutagenesis at a CpG site Percentdivergence
- 25. How do we measure and describe genetic variation? Neutral variation: - Average nucleotide variation within a genome (heterozygosity) - Average nucleotide variation between genomes Non coding variation Silent site variation (dS) Non-silent variation (dN) The International SNP Map Working Group Nature, 2001 Heterozygosity in the human chromosome 6
- 26. Average divergence between humans and chimpanzees varies across chromosomes Hodgkinson and Eyre-Walker, 2009, Nature Genetics
- 27. Recombination rate is heterogeneous across chromosomes recombination hot spots Genes GC content Meyers et al, 2005
- 28. Assessing signatures of selection across genome sequences Population data: Measures of SNPs across a genome alignment Population data and interspecific comparisons dN/dS ratios (non-synonymous to synonymous variation) (Wednesday)
- 29. Dieter Tautz A selective sweep leaves a strong footprint in the genome
- 30. Plots of Chromosome 2 SNPs with Extreme iHS Values Indicate Discrete Clusters of Signals Voight BF, Kudaravalli S, Wen X, Pritchard JK (2006) A Map of Recent Positive Selection in the Human Genome. PLoS Biol 4(3): e72. doi:10.1371/journal.pbio.0040072 http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040072 iHS is a measure of how unusual the haplotype around a give SNP is Asian European African
- 31. New viral variants arise within one patient The evolution of HIV may be driven by adaptation to the host immune system Nickle et al, 2003, Curr. Opinion Microbiol. Detecting positive selection in HIV
- 32. The HIV genome LTR-long terminal repeats; repetitive sequence of bases gag-group specific antigen gene, encodes viral nucleopcapsid proteins: p24, a nucleoid shell protein, MW=24000; several internal proteins, p7, p15, p17 and p55. pol-polymerase gene; encodes the viral enzyme, protease (p10), reverse transcriptase (p66/55; alpha and beta subunits) and integrase (p32). env-envelope gene; encodes the viral envelope glyocproteins gp120 (extracellular glycoprotein, MW=120 000) and gp41 (transmembrane glycoprotein, MW=41000). tat: encodes transactivator protein rev: encodes a regulator of expression of viral protein vif: associated with viral infectivity vpu: encodes viral protein U vpr: encode viral protein R nef: encodes a 'so-called' negative regulator protein
- 33. Whole Genome Deep Sequencing of HIV-1 Reveals the Impact of Early Minor Variants Upon Immune Recognition During Acute Infection Henn et al, 2012, Plos Pathogens Day 1543Day 476Day 165Day 59Day 3 Day 0 Evolution of HIV population in patient - sequencing of viral genome from six time points
- 34. Rapidly expanding sequence diversity during HIV infection Heat map showing sites exhibiting amino acid diversity
- 36. Genome size and complexity Lynch et al, 2006
- 37. Non-coding DNA matters Kilobases / gene
- 38. Archaea genome statistics Escherichia coli Protein-coding genes: 87.8% Encoding stable RNAs: 0.8% Non-coding repeats: 0.7% Regulatory: 11% Blattner et al, 1997 Monogodin et al, 2005
- 39. Non-coding DNA matters From Lynch 2007 Exon Intron Regulatory Other Saccharomyces 1.44 0.02 0.11 0.37 Aspergillus 1.57 0.27 0.03 1.55 Plasmodium 2.29 0.25 0.04 1.76 Caenorhabiditis 1.25 0.64 0.43 2.41 Drosophila 1.66 2.93 1.37 2.60 Homo/Mus 1.32 32.27 1.95 61.14 Intergenic Average amount of DNA (in kilobases)
- 40. Synteny
- 41. Simulated data Observed data A+B) Macrosynteny C+D) Inversions E+F) Multiple inversions G+H) Only short syntenic regions
- 42. Different recombinational events lead to synteny breakpoints Paracentric inversion Pericentric inversion Inversions Translocations
- 43. BJ Haas et al. Nature (2009) Oomycete plant pathogens Genome alignment of Phyophthora species Black boxes=repetitive sequences
- 44. Genetic variation role in Pharmacology • Drug-related genes show high extent of genetic variability • Cancer drug target genes have many germline functional-variants. • Aggregating risk for functional-variants in targets by drug highlights drug candidates for future pharmacogenomics research. • Drug-related genes show geographic difference in genetic variability.