Quantitative analysis of adaptive evolution 公开

Ghafari, Mahan (Summer 2018)

Permanent URL: https://etd.library.emory.edu/concern/etds/hm50tr80w?locale=zh
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Abstract

In this work, we first perform a quantitative analysis on the original data from the Luria-Delbruck fluctuation experiment. We compare the performance of the Darwinian model of evolution to the Lamarckian model and a combined model that allows both Darwinian and Lamarckian mechanisms. We also consider the possibility of neither model fitting the experiment. Using a Bayesian model selection approach, we show that although the experiment does, indeed, favor the Darwinian over pure Lamarckian evolution, it does not rule out the combined model and, hence, cannot completely rule out Lamarckian contributions to evolution. Next, we mainly focus on complex adaptations involving three neutral mutations. We show that large populations can cross them rapidly via lineages that acquire multiple mutations while remaining at low frequency. Plateau-crossing is fastest for very large populations. At intermediate population sizes, recombination can greatly accelerate adaptation by combining independent mutant lineages to form triple-mutants. For more frequent recombination, such that the population is kept near linkage equilibrium, we extend our analysis to find simple expressions for the expected time to cross plateaus of arbitrary width.

Table of Contents

1 Introduction                                                                                                                  1

2 Luria-Delbruck, revisited: The classic experiment does not rule outLamarckian evolution     2

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.2.1 Models and Notational preliminaries . . . . . . . . . . . . . . 5

2.2.2 Computational models . . . . . . . . . . . . . . . . . . . . . . 11

2.2.3 Quality of t . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.2.4 Comparing models . . . . . . . . . . . . . . . . . . . . . . . . 13

2.2.5 Statistical power of the tests . . . . . . . . . . . . . . . . . . . 15

2.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2.3.1 Experiment 22 . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.3.2 Experiment 23 . . . . . . . . . . . . . . . . . . . . . . . . . . 19

2.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

3 The expected time to cross extended tness plateaus                                                       25

3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

3.2 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3.3.1 Rare recombination, r << s . . . . . . . . . . . . . . . . . . . . 31

3.3.2 Frequent recombination, r >> s . . . . . . . . . . . . . . . . . 33

3.4 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

3.4.1 Rare recombination (r << s) . . . . . . . . . . . . . . . . . . . 37

3.4.2 Frequent recombination (r >> s) . . . . . . . . . . . . . . . . . 47

3.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

3.A. Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

3.A.1 Small populations with rare recombination . . . . . . . . . . . . 55

References                                                                                                                     63

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