* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Handout
Metagenomics wikipedia , lookup
Minimal genome wikipedia , lookup
No-SCAR (Scarless Cas9 Assisted Recombineering) Genome Editing wikipedia , lookup
Public health genomics wikipedia , lookup
Human genome wikipedia , lookup
Deoxyribozyme wikipedia , lookup
Genomic library wikipedia , lookup
Pathogenomics wikipedia , lookup
Oncogenomics wikipedia , lookup
Adaptive evolution in the human genome wikipedia , lookup
Non-coding DNA wikipedia , lookup
Genetic engineering wikipedia , lookup
Human genetic variation wikipedia , lookup
Gene expression programming wikipedia , lookup
Artificial gene synthesis wikipedia , lookup
Frameshift mutation wikipedia , lookup
Designer baby wikipedia , lookup
Genome (book) wikipedia , lookup
Genome editing wikipedia , lookup
History of genetic engineering wikipedia , lookup
Polymorphism (biology) wikipedia , lookup
Group selection wikipedia , lookup
Site-specific recombinase technology wikipedia , lookup
Point mutation wikipedia , lookup
Genetic drift wikipedia , lookup
Genome evolution wikipedia , lookup
Koinophilia wikipedia , lookup
How Genomes Evolve and Basic Evolution Jun-Yi Leu (呂俊毅) Introductory Molecular and Cellular Biology 1 What is evolution? 2 History of Life 3 Why do we care about evolution? 4 Evolution Is Relevant to Our Daily Life • What is the difference between us and chimpanzee? (positive selection, drift, trade-off) • Why can bird flu infect human beings? (stabilizing selection, positive selection) • Why is it so difficult to cure cancer cells? (the red queen effect, relaxed selection) • Why do we get old? (relaxed selection, trade-off ) • …… 5 All Life Forms Are Derived from a Common Ancestor A A1 A2 A21 A11 A12 A211 A22 A221 A222 6 All Life Forms Are Derived from a Common Ancestor A A1 A2 A21 A11 A12 A211 A22 A221 mutation, selection, drift, … A222 7 Selection • How does natural selection work? – Genetic variation among individuals creates differential survival or reproductive success (also called fitness) – This survival (or reproductive) success is conditiondependent (the fittest ones in A condition may not be the fittest in B condition) – Both abiotic and biotic factors may contribute to the selection (your neighbors are important!!) 8 The Genome Sequences of Two Species Differ in Proportion to the Length of Time Since They Have Separately Evolved Q1. Why? 9 Phylogenetic Trees Constructed from a Comparison of DNA Sequences Trace the Relationships of All Organisms 10 No All Organisms Accumulate Changes over Evolutionary Time 11 However, life is more complicated than this… 12 When you look into an individual gene (or locus) A A1 A2 A21 A11 A12 A211 A22 A221 A222 13 When you look into an individual gene (or locus) A A1 A2 A21 A11 A12 A211 A22 A221 A222 14 When you look into an individual gene (or locus) A A1 A2 A21 A11 A12 A211 A22 A221 A222 15 What can we learn from sequence comparisons? 16 Imagining that you just identify a gene in your favorite organism… 17 Messages Carried by the Sequence Species 1 Species 2 Species 3 AAG CGT CTG GTC CTA TCT CAT ATT AAA AGA TTA GTA TTG AGC CAC TTT 46% identity ACG AGC CCA GAC TCA ATG CTT TTT 46% identity species 1 species 2 species 3 18 Messages Carried by the Sequence Species 1 Lys Arg Leu Val Leu Ser His Ile AAG CGT CTG GTC CTA TCT CAT ATT Species 2 Lys Arg Leu Ala Leu Ser His Phe AAA AGA TTA GTA TTG AGC CAC TTT 88% identity 46% identity Species 3 Thr Ser Pro Asp Ser Met Leu Phe ACG AGC CCA GAC TCA ATG CTT TTT 0% identity 46% identity Species 4 Lys Arg Leu Val Leu Ser His Phe AAG CGT CTG GTC CTA TCT CAT TTT 88% identity 96% identity • How do we integrate the information from both DNA and protein sequences? 19 Distributions of Synonymous and Nonsynonymous Mutations • 61 universal codons x 9 substitutions = 549 mutations AAA T G C 20 Distributions of Synonymous and Nonsynonymous Mutations • 61 universal codons x 9 substitutions = 549 mutations • Synonymous: a base substitution causing no amino acid change (silent mutations) • Nonsynonymous: a base substitution causing an amino acid change (missense or nonsense mutations) 21 Ka/Ks (Synonymous/Nonsynonymous) • In the protein coding region, the synonymous and nonsynonymous substitutions should be treated differently • Why? Most of the synonymous substitutions are neutral since the protein sequence is not changed. In contrast, the nonsynonymous substitutions are likely under selection. • Ks: the number of synonymous substitutions per site Ka: the number of nonsynonymous substitutions per site • Ka/Ks: indicator of selective constrains 22 When Ka/Ks < 1 • The gene is under stabilizing selection. Species 1 Lys Arg Leu Val Leu Ser His Ile AAG CGT CTG GTC CTA TCT CAT ATT Low Ka Species 2 Lys Arg Leu Ala Leu Ser His Phe AAA AGA TTA GTA TTG AGC CAC TTT 88% identity 46% identity High Ks 23 Stabilizing Selection • Selection against genetic diversity (negative or purifying selection) • The most common selection in nature: almost all genes in the genome are under stabilizing selection. • Genes (or sequences) with important functions tend to under strong stabilizing selection. ⇒ e.g. house keeping genes involved in DNA replication, metabolic pathways etc. 24 Multispecies Sequence Comparisons Identify Conserved DNA Sequences with Specific Functions 25 Messages Carried by the Sequence Species 1 Lys Arg Leu Val Leu Ser His Ile AAG CGT CTG GTC CTA TCT CAT ATT Species 2 Lys Arg Leu Ala Leu Ser His Phe AAA AGA TTA GTA TTG AGC CAC TTT 88% identity 46% identity What does the sequence comparison tell us? Species 4 Lys Arg Leu Val Leu Ser His Phe AAG CGT CTG GTC CTA TCT CAT TTT 88% identity 96% identity 26 When Ka/Ks > 1 • The gene is under positive selection. Species 1 Lys Arg Leu Val Leu Ser His Ile AAG CGT CTG GTC CTA TCT CAT ATT Species 2 Thr Ser Pro Asp Ser Met Leu Phe ACG AGC CCA GAC TCA ATG CTT TTT 0% identity 46% identity 27 Positive Selection • Selection for increasing genetic diversity (that involves multiple rounds of selection) • Not very common in most of the genome ⇒ often driven by host-pathogen interactions (the red queen effect) or sexual selection. • Changes in previously conserved sequences can help decipher critical steps in evolution 28 The Red Queen Effect • Constant evolutionary arms races • between different species: host-parasite • between different cellular components: nucleusmitochondrion • between different genetic components: genomeselfish gene 29 30 selfish mitochondrial DNA lower fitness counteracting mitochondrial mutation counteracting nuclear mutation high fitness complementary nuclear mutation 31 Host-Virus Arms Race 32 Sexual Selection • first described by Darwin as a mechanism that leads to sexual dimorphism in a species. It is caused by mate choice - a big puzzle in evolutionary biology. • the major difference between sexual selection and other types of selection is that under sexual selection the survival rate of the organism is not improved. 33 Q2. using the peacock’s tail as an example, explain why peahens want to choose males with a more flamboyant tail. Q3. please provide other examples of sexual selection. 34 How does sexual selection drive gene evolution? 35 Q4: What is the adaptive advantage of sex? 36 x x ➔ ➔ x x ➔ ➔ ➔ ➔ ➔ The Cost of Sex x x x 37 Q5: Why is the male/female ratio close to one in many organisms? Q6: Why are there only two sexes in most higher eukaryotes? 38 Positive Selection • Selection for increasing genetic diversity (that involves multiple rounds of selection) • Changes in previously conserved sequences can help decipher critical steps in evolution 39 Mutations in the DNA Sequences That Control Gene Expression Have Driven Many of the Evolutionary Changes in Vertebrates 40 When Ka/Ks ~ 1 • The gene is under relaxed selection (no selection). • Genes (or sequences) that have lost their functions or are newly duplicated. 41 Gene Duplication Provides an Important Source of Genetic Novelty During Evolution • The evolution of the globin gene family 42 The Evolution of the Globin Gene Family Shows How DNA Duplications Contribute to the Evolution of Organisms 43 Polyploid Organisms Occur Commonly in Nature or during Evolution fungi plants animals • Polyploidy: organisms contain more than two sets of genomes. But,… how can a neutral mutation become fixed in a population? 45 Fixation: an allele spreads into the whole population beneficial mutations deleterious mutations neutral mutations 46 Fixation of an Allele by Genetic Drift • Expected time for an allele to be fixed by chance: 2Ne generations (Ne = effective population size) • A very slow process in general! • Effective population size Ne: a simplified and idealized population size that can represent the actual population size in a complicated population or during a long term 47 Genetic Drift • Genetic drift: random fluctuation of gene frequencies in populations • Very sensitive to population size 48 Computer Simulation: A Powerful Tool 49 Fixation of an Allele by Genetic Drift • Expected time for an allele to be fixed by chance: 2Ne generations (Ne = effective population size) • A very slow process in general! Example: If the population size is 1000, it takes 2 x 1000 = 2000 generations to fix a mutation by drift. 50 Beneficial Mutations Spread More Quickly • Example Genotype: wild type Fitness: 1 If s = 1, m =1 mutant 1+s m = (1 + 1) m = (1+1)(1+1) after N generations, m = (1+s)N • If the population size is 1000 and the beneficial mutation increases 10% of fitness (s = 0.1), how many generations does it take to fix the mutation? (1.1)N/1000 = 1 (1.1)N = 1000 ln(1.1)N = ln(1000) N x ln(1.1) = ln(1000) N = 72.5 ln(1.1) = 0.0953, ln(1000) = 6.9078 51 Fixation of an Allele by Genetic Drift • Expected time for an allele to be fixed by chance: 2Ne generations (Ne = effective population size) • A very slow process in general! • Effective population size Ne: a simplified and idealized population size that can represent the actual population size in a complicated population or during a long term 52 Examples • Complicated populations: In a population of size N, all the females (N/2) and only a few alpha males take part in the reproductive process. What is the effective population size? • Fluctuating populations: If a population size fluctuates during the time of 10 generations and their actual population sizes are N1~N6 = 100 ; N7~N8 = 10 ; N9~N10 = 53 1000, what is the effective population size? Factors that can Enhance the Effect of Random Genetic Drift • Bottleneck effect: population size is reduced by external factors – e.g., Northern Elephant Seal populations depleted by overhunting, exacerbated by harem system of mating, leads to lack of genetic variation in today's population 54 Factors that can Enhance the Effect of Random Genetic Drift • Founder effect: small sample of population leaves and colonizes a new area (population migration) – e.g., Human populations on Islands of Tristan de Cunha - founded by 15 individuals - high incidence of retinitis pigmentosa (a genetic disease leads to blindness) 55 Neutral Mutations Often Spread to Become Fixed in a Population, with a Probability That Depends on Population Size 56 A Great Deal Can Be Learned from Analyses of the Variation Among Humans 57 Q7: What problems will a population face when it has experienced a small bottleneck? 58 Is genetic drift the only way to spread a bad (or disease-related) mutation? 59 Fixation: an allele spreads into the whole population beneficial mutations deleterious mutations neutral mutations 60 Sickle Cell Allele Is Under Stabilizing Selection in Malaria-Prevailing Areas susceptible to malaria resistant to malaria very sick 61 Balancing Selection • Selection against extreme individuals and for the average phenotype • Overdominant (heterozygote advantage): heterozygote has the highest fitness (s1 > s2) ⇒ e.g. sickle cell trait Genotype: A1A1 Fitness: 1 A1A2 A2A2 1 + s1 1 +s2 • Frequency dependent selection 62 63 Q8: other examples of balancing selection? 64 Chromosomal Mutation • Mutations at chromosomal levels – Deletion or duplication – Inversion – Translocation – Aneuploidy: loss or addition of chromosomes – Whole genome duplication (WGD) 65 Chromosomal Mutation • Mutations at chromosomal levels • Consequences: – Change gene copy numbers – Create new genes or new gene expression patterns – Create genome instability 66 Chromosomal Mutation • Mutations at chromosomal levels – Deletion: Jacobsen syndrome – Duplication: Copper resistance in yeast – Inversion: reduced fertility – Translocation: some antibiotic resistance genes and oncogenes – Aneuploidy: Down syndrome – Whole genome duplication: yeast, fish and mammal 67 A Comparison of Human and Mouse Chromosomes Shows How the Structures of Genomes Diverge 68 The Genome Size Can Differ Dramatically between Species • Genome size: – E. coli: 4.6 x 106 bp (1X); 4288 genes (1X) – Yeast: 1.2 x 107 bp (~3X); 6294 genes (~1.5X) – Fruit fly: 1.7 x 108 bp (~40X); 13600 genes (~3.2X) – Human: 3.2 x 109 bp (~700X); 20251 genes (~4.7X) • Most of large genomes are made up of non-coding or repetitive sequences. 69 The Genome Size Can Differ Dramatically between Species • Genome size: – Human: 3.2 x 109 bp (~8X); 20251 genes – Puffer fish (Fugu): 3.9 x 108 bp (1x); ~22000 genes 70 Q9: Why do different organisms have different numbers of genes? Q10: Do you think that most of the noncoding or repetitive sequences in the expanded genomes are neutral? How can they be maintained? 71 What is evolution? 72 Are we getting better, and better? 73 The Red Queen Effect selfish mitochondrial DNA lower fitness counteracting mitochondrial mutation counteracting nuclear mutation high fitness complementary nuclear mutation 74 The Trade-off Hypothesis 75 Do you know how smart I am? There is no writing exam here :( 76 Recent Advances in Evolutionary Biology • Genome projects: – Whole genome sequences allow us to do more comprehensive comparisons, e.g., promoter sequences or disease allele – Genomic tools allow us to compare the model organisms with their relative species, e.g., S. cerevisiae and S. paradoxus • Experimental evolution: – We can examine evolutionary hypotheses directly – By analyzing the evolved product, we can understand how cells evolve • Systems biology: – Combining computer modeling, physics and genomics to identify the critical parameters of evolution 77