1 / 20

A mixability theory for the role of sex in evolution

A mixability theory for the role of sex in evolution. Ritesh Agarwal ragarw8@uic.edu University of Illinois, Chicago. Original Paper Authors: A. Livnat , C. H. Papadimitriou, J. Dushoff and M. W. Feldman. Outline. Introductory Concepts Abstract idea of paper

ting
Download Presentation

A mixability theory for the role of sex in evolution

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. A mixability theory for the role of sex in evolution RiteshAgarwal ragarw8@uic.edu University of Illinois, Chicago Original Paper Authors: A. Livnat, C. H. Papadimitriou, J. Dushoff and M. W. Feldman.

  2. Outline Introductory Concepts Abstract idea of paper Some important measures w.r.t the research paper Models of sex Experiment Experiment results and observations

  3. Introductory Concepts • Nucleolites – 4 types (A,C,T,G) • Genes (DNA sequence) e.g ACTGGGAC • Allele (is one of the forms of the same gene) • 2 alleles (haploids) • 1 allele (diploids) • Chromosome (structure of DNA containing many coiled genes) • Haploid (cell with one set of chromosomes) • Diploid (cell with one two of chromosomes)

  4. Abstract idea of paper The role sex plays in evolution. Comparison of asex-evolution with sex-evolution. Various measurements identified and calculated to show the same. Experiments conducted using a theoretical model of evolution by varying several parameters. Observation from experiment results and comparisons

  5. Some important measures • - Genome-wide ability of alleles to perform well across different combinations • Mi- Average fitness of allele i • - Population mean fitness • wij- Fitness of a genotype formed using allele i and allele j = 1 + si + tj+ eij • where si- additive contribution of allele i. • tj- additive contribution of allele j. • eij- interaction or epistatisterm.

  6. Haploid 2 locus fitness landscape -A haploid 2-locus fitness landscape -3 alleles per locus. -Alleles A1, A2, and A3 in locus A -B1, B2, and B3 in locus B -9 genotypes AiBj with fitnesseswij, represented by the heights of the bars -(w11 = 0.840, w12 = 1.046, w13 = 1.100, w21 = 1.040, w22 = 1.060, w23 = 1.000, w31 = 1.020, w32 = 1.050, w33 = 0.820) -Asexual selection (A1B3) -Sexual selection (A2B2) – “mixability” -A2 the allele with best average fitness on its locus. -B2 the allele with best average fitness on its locus.

  7. Few more important measures • Pij,t- Frequency of genotype AiBjat generation t. • r – recombination rate (0 <= r <= ½) • - • - .Mi / |L| • Pi,tis frequency of allele iat generation t. • L is the set of Loci (plural for locus)

  8. Evolutionary dynamics of the haploid 2-locus Equal initial genotypic frequencies (1/9 for each of 9 genotypes) Genotypic frequencies for generations 1−500 based on Eq. 1

  9. Models of sex • Haploid (2-locus) recombination • Diploid (1-locus) segregation • Diploid (2-locus) both

  10. Parameters for experiment Model of Sex No of alleles per locus Is selection done using sexual way or asexual method? Recombination factor for sexual selection. Fitness value range

  11. Experiment (Part 1) Generation of fitness matrices and Initial genotype frequency matrices. -‘N’ W(W1, W2, …Wn) and ‘N’ P(P1, P2, …Pn) matrices are randomly chosen from the above generated matrices. -for each model_of_sex in [haploid-2-locus, diploid-1- locus, diploid-2-locus] -for each allele_per_locus_cnt in [2, 3, 4, 5] -if (selection_via_sex_mode) -for each r in [0.5, 0.2, 0.05] -for each f in [1, 2, 3] -generate W(fitness) matrices -generate P(initial genotype frequency) matrices

  12. Experiment (Part 1) Generation of fitness matrices and Initial genotype frequency matrices. -for each W in [W1, W2, …Wn] -for each P in [P1, P2, …Pn] -for each t(generation) in [1…215] -for variants_of_sex in [sex, asex] -”trial below” - Calculate - Calculate

  13. Summarized information captured for basis -Percentage of trials in which -Percentage of trials in which -Percentage of trials in which -Percentage of trials in which The sum of opposite percentage terms may not be 100% because a difference of certain threshold was considered equal.

  14. Experiment results and observations

  15. Experiment results and observations

  16. Experiment results and observations

  17. Experiment results and observations

  18. Questions to authors • Since the fitness matrices and initial genotype frequency matrices are randomly selected, it may be possible to get different observations on different runs. Can we really trust this approach to justify the theory? • Sexual selection process may not be theoretically and correctly derived. How much can we trust the deterministic approach used here? • Are the variations chosen in parameters enough? As we could see that different allele count had drastic differences in the observations.

  19. Conclusions and Final remarks Asexual selection tends to achieve a higher w. Sexual selection tends to achieve a higher M. Less fit genotypes eventually tend to become extinct. No. of alleles per locus show different observations. The paper has provided enough evidence to support its point using the theoretical model.

  20. Thank You!

More Related