Evolution 2018, Dobzhansky Prize Talk

Transcript

1. BLOODY-MINDED PARASITES Coevolution in natural and experimental populations Amanda Kyle Gibson
2. “The most that the average species can achieve is to dodge its minute enemies…” ~JBS Haldane, 1949
3. “The most that the average species can achieve is to dodge its minute enemies by constantly producing new genotypes” ~JBS Haldane, 1949
4. “The most that the average species can achieve is to dodge its minute enemies by constantly producing new [or rare] genotypes” ~JBS Haldane, 1949
5. dodging minute enemies outline
6. Hypothesis: the Red Queen dodging minute enemies Z Dinges outline
7. Hypothesis: the Red Queen Assumption: adaptation to common hosts dodging minute enemies Z Dinges outline
8. Hypothesis: the Red Queen Assumption: adaptation to common hosts dodging minute enemies Alternative: dodging by dispersal Z Dinges outline
9. Hypothesis Assumption dodging minute enemies Alternative observation experimentation Z Dinges outline
10. Hypothesis: the Red Queen Assumption: adaptation to common hosts dodging minute enemies Alternative: dodging by dispersal Z Dinges outline
11. PART 1 Do parasites drive fluctuations in the frequency of asexual reproduction? Z Dinges
12. sex shouldn’t exist problem
13. sex shouldn’t exist cost of males
14. sex shouldn’t exist Lively 2009 JEB Generation N cost of males sexual
15. sex shouldn’t exist Lively 2009 JEB Generation N cost of males sexual asexual
16. sex shouldn’t exist Lively 2009 JEB Generation N cost of males Two-fold cost of males sexual asexual
17. sex shouldn’t exist Lively 2009 JEB Generation N extinct in <10 generations cost of males sexual asexual
18. “Why all this silly rigmarole of sex? Why this gavotte of chromosomes? Why all these useless males, this striving and wasteful bloodshed, these grotesque horns [and] colors?” ~WD Hamilton, 1975 “Gamblers since life began”
19. Red Queen hypothesis cost of males J Tenniel solution?
20. “The most that the average species can achieve is to dodge its minute enemies by constantly producing new [or rare] genotypes” ~JBS Haldane, 1949 Red Queen hypothesis solution?
21. Red Queen hypothesis Lively 2009 JEB Generation N sexual asexual extinct in <10 generations solution?
22. Red Queen hypothesis Lively 2009 JEB Generation N sexual + coevolving parasites asexual solution?
23. Lively 2009 JEB N sexual asexual Freq. infection Generation
24. Lively 2009 JEB N sexual asexual Freq. infection Generation
25. Lively 2009 JEB Freq. infection *periodic over-infection of common clones Generation solution?
26. Lively 2009 JEB Freq. infection *periodic over-infection of common clones + under-infection of rare clones Generation solution?
27. Do parasites drive fluctuations in the frequency of asexual reproduction? (in nature) Z Dinges
28. a natural host-parasite system system Z Dinges
29. asexual sexual coexist with a natural host-parasite system J Xu K Bensen system
30. asexual sexual coexist with cost of males Gibson et al. 2017 Evol Lett a natural host-parasite system
31. a natural host-parasite system Gabe Harp system
32. Microphallus a natural host-parasite system Gabe Harp system
33. Microphallus a natural host-parasite system Don Farrall Gabe Harp system
34. Do parasites drive fluctuations in the frequency of asexual reproduction? (in nature) Z Dinges
36. Jukka Jokela M Schaffner Curt Lively
38. Year Asexual females Vergara et al. 2014 Am Nat Sexual females Proportion infected (Weighted mean ± se) Are asexuals over-infected? field 4 sites
39. Year Asexual females – 53% Sexual females -42% Proportion infected (Weighted mean ± se) Are asexuals over-infected? field Vergara et al. 2014 Am Nat
40. Year Asexual females – 53% Sexual females -42% Proportion infected (Weighted mean ± se) Sexual Asexual Are asexuals over-infected? Yes! field Vergara et al. 2014 Am Nat
41. Freq. infection *periodic over-infection of asexuals Generation field
42. 6 sites Year Proportion infected (Weighted mean ± se) Asexual females Sexual females Are asexuals over-infected? field Gibson et al. in press; Am Nat
43. Year Proportion infected (Weighted mean ± se) Asexual females – 10% Sexual females – 26% Are asexuals over-infected? field Gibson et al. in press; Am Nat
44. Year Proportion infected (Weighted mean ± se) Sexual Asexual Asexual females – 10% Sexual females – 26% Are asexuals over-infected? NO! field Gibson et al. in press; Am Nat
45. 2001-2005 2012-2016 Asexual females Sexual females Year Proportion infected GEE: year * reproductive mode Shift in relative infection field
46. 2001-2005 2012-2016 Asexual females Sexual females Year Proportion infected GEE: year * reproductive mode Shift driven by variation in asexuals Shift in relative infection field
47. Sexual Asexual 10 years of field sampling 2001-2005 + 2012-2016 Proportion infected Shift in relative infection field Gibson et al. in press; Am Nat
48. No overall difference in infection Sexual Asexual Proportion infected GEE: no effect of reproductive mode 10 years of field sampling 2001-2005 + 2012-2016 field
49. But much greater variation for asexuals Sexual Asexual Proportion infected 10 years of field sampling 2001-2005 + 2012-2016 1.02 [0.80,1.30] 0.66 [0.53,0.79] << Coefficient of variation field GEE: no effect of reproductive mode
50. Asexuals are now less infected than sexuals
51. An opportunity to falsify the Red Queen hypothesis Asexuals are now less infected than sexuals
52. Red Queen predicts: predictions
53. Red Queen predicts: Asexuals are under-infected when rare 1 predictions
54. Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals spread when under-infected 2 predictions
56. Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals spread when under-infected 2 predictions
57. 2001 - 2005 2012 - 2016 past over-infection recent under-infection Proportion asexual Asexuals are under-infected when rare 1 field Gibson et al. in press; Am Nat
58. 2001 - 2005 2012 - 2016 past over-infection recent under-infection Proportion asexual Asexuals are under-infected when rare 35% 23% GLM: sampling period 1 field
59. 2001 - 2005 2012 - 2016 past over-infection recent under-infection Proportion asexual Asexuals are under-infected when rare 35% 23% No asexuals at 3 of 6 sites 1 field GLM: sampling period
60. Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field predictions
61. Reduced infectivity to asexuals Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field predictions
62. Reduced infectivity to asexuals Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field Asexuals spread when under-infected 2 predictions
63. Reduced infectivity to asexuals Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field Asexuals spread when under-infected 2 Do asexuals have a fitness advantage? predictions
65. + parasite eggs juvenile snails 2 Do asexuals have a fitness advantage? experiment
66. Control Exposed 2 Do asexuals have a fitness advantage? experiment
67. Control Exposed 1 year later 2 Do asexuals have a fitness advantage? experiment
68. Control Exposed 1 year later t parental generation t+1 offspring generation 2 Do asexuals have a fitness advantage? experiment
69. Control Exposed 1 year later 2 q freq. asexuals Do asexuals have a fitness advantage? experiment t parental generation t+1 offspring generation
70. Control Exposed 1 year later Sam Klosak Peyton Joachim Julie Xu 12 mesocosms x 4 years = 48 replicates 2 Do asexuals have a fitness advantage? experiment q freq. asexuals t parental generation t+1 offspring generation
71. Control Exposed Control Exposed Generation t Generation t+1 28% 2 Do asexuals have a fitness advantage? experiment Gibson et al. in press; Am Nat q Proportion asexual
72. Control Exposed Control Exposed Generation t Generation t+1 28% 2 Do asexuals have a fitness advantage? experiment Gibson et al. in press; Am Nat q Proportion asexual
73. Control Exposed Control Exposed Generation t Generation t+1 28% 46% 2 Do asexuals have a fitness advantage? experiment Gibson et al. in press; Am Nat q Proportion asexual
74. Control Exposed Control Exposed Generation t Generation t+1 28% 46% 52% GLM: treatment - marginal 2 Do asexuals have a fitness advantage? experiment q Proportion asexual
75. Control Exposed Control Exposed Generation t Generation t+1 1.64x 1.86x GLM: treatment - marginal 2 q Proportion asexual Do asexuals have a fitness advantage? experiment
76. Control Exposed Control Exposed Generation t Generation t+1 1.64x 1.86x GLM: treatment - marginal 2 Do asexuals have a fitness advantage? experiment q freq. asexuals
77. 2 Do asexuals have a fitness advantage? theory q freq. asexuals +1 = ഥ
78. 2 Do asexuals have a fitness advantage? q freq. asexuals +1 = ഥ = fitness cost of sex theory
79. + = 1 + − 1 2 Do asexuals have a fitness advantage? q freq. asexuals theory
80. + = 1 + − 1 2 Do asexuals have a fitness advantage? q freq. asexuals = + net cost of sex theory
81. + = ( + ) 1 + ( + ) − 1 2 Do asexuals have a fitness advantage? q freq. asexuals baseline cost of sex cost of parasites theory = + net cost of sex
82. Control + = ( + ) 1 + ( + ) − 1 2 Do asexuals have a fitness advantage? q freq. asexuals 2.18 [1.85,2.57] cost of parasites theory = + net cost of sex
83. Exposed + = ( + ) 1 + ( + ) − 1 2 Do asexuals have a fitness advantage? q freq. asexuals 2.18 [1.85,2.57] 0.97 [0.19,1.97] theory = + net cost of sex
84. Exposed + = ( + ) 1 + ( + ) − 1 2 Do asexuals have a fitness advantage? q freq. asexuals 2.18 [1.85,2.57] 0.97 [0.19,1.97] theory = . net cost of sex
85. Reduced infectivity to asexuals Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field Asexuals spread when under-infected 2 Asexuals have a fitness advantage predictions
86. Reduced infectivity to asexuals Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field Asexuals spread when under-infected 2 Asexuals have a fitness advantage Do asexuals increase in the field? predictions
87. Reduced infectivity to asexuals Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field Asexuals spread when under-infected 2 Asexuals have a fitness advantage Do asexuals increase in the field? the ultimate test predictions
88. Year Proportion asexual (Mean ± se) 2 Do asexuals increase in the field? field 6 sites Gibson et al. in press; Am Nat
89. Year Proportion asexual (Mean ± se) 2 Do asexuals increase in the field? field GLM: reproductive mode
90. Year Proportion asexual GLM: reproductive mode 11.5% 29.8% 2.6x (Mean ± se) 2 Do asexuals increase in the field? field
91. Reduced infectivity to asexuals Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field Asexuals spread when under-infected 2 Asexuals have a fitness advantage Do asexuals increase in the field? the ultimate test predictions
92. Reduced infectivity to asexuals Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field Asexuals spread when under-infected 2 Asexuals have a fitness advantage Do asexuals increase in the field? predictions
93. Do parasites drive fluctuations in the frequency of asexual reproduction? (in nature) Z Dinges
94. Freq. infection *periodic over-infection + under-infection of asexual hosts Generation asexual sexual summary
95. Vergara et al. 2014 Am Nat Freq. infection *parasites favor sex when asexual hosts are common Generation asexual sexual summary
96. Gibson et al. Am Nat in press Freq. infection parasites favor sex when asexual hosts are common Generation * rare asexuals evade parasite selection and spread summary
97. Gibson et al. Am Nat in press Freq. infection Generation asexual sexual parasite-mediated oscillations in asexual frequency maintenance of sexual females summary
98. “Why all this silly rigmarole of sex? Why this gavotte of chromosomes? Why all these useless males, this striving and wasteful bloodshed, these grotesque horns [and] colors?” ~WD Hamilton, 1975 “Gamblers since life began”
99. "...it seems to me that we need environmental fluctuations around a trend line of change.“ "For the source of these we may look to fluctuations and periodicities...generated by life itself." ~WD Hamilton, 1975 “Gamblers since life began”
100. Year (Mean ± se) Proportion asexual 5 sites Zoe Dinges Fluctuations and periodicities field
101. Year (Mean ± se) Proportion asexual Zoe Dinges 46% 11.5% Fluctuations and periodicities field
102. Year (Mean ± se) Proportion asexual Zoe Dinges 46% 11.5% Will parasites adapt to common clones? Fluctuations and periodicities field
103. Hypothesis: the Red Queen Assumption: adaptation to common hosts dodging minute enemies Alternative: dodging by dispersal Z Dinges outline
104. Hypothesis: the Red Queen Assumption: adaptation to common hosts dodging minute enemies Alternative: dodging by dispersal Z Dinges outline
105. PART 2 Do parasites adapt to common host genotypes?
106. Host Parasite the idea background
107. Host Parasite x x the idea background
108. Host Parasite x x Time Frequency the idea host background
109. Host Parasite x x Time Frequency the idea parasite background
110. Host Parasite x x Time Frequency the idea host background
111. Host Parasite x x Time Frequency the idea parasite background
112. Host Parasite x x Time Frequency the idea parasite (bloody-minded parasites) background
113. Do parasites adapt to common host genotypes? John Lubbock, ca. 1850 Z Dinges Chondrilla juncea Ill. Flora B.C. Chaboudez and Burdon, 1995 Oecologia Lively and Dybdahl, 2000 Nature; Koskella and Lively, 2009 Evolution Wolinska and Spaak, 2009 Evolution
114. Do parasites adapt to common host genotypes?
115. Caenorhabditis elegans Serratia marcescens ImmortalHumans.com a lab host-parasite system system
116. Caenorhabditis elegans Serratia marcescens ImmortalHumans.com a lab host-parasite system system
117. experimental evolution host A (N2) host B (derived from CB4856) design
118. experimental evolution host A (N2) host B (derived from CB4856) relatively divergent design
119. experimental evolution host A host B design 100% 100%
120. experimental evolution host A host B 90% 75% common rare 25% 10% design 100% 0%
121. experimental evolution host A host B rare common design 10% 25% 75% 90% 0% 100%
122. experimental evolution ancestral parasite design 90% 75% 100% 75% 90% 100%
123. experimental evolution 20 passages under selection to kill design 90% 75% 100% 75% 90% 100%
124. experimental evolution control design 90% 75% 100% 75% 90% 100% 20 passages under selection to kill
125. experimental evolution 6 replicates per treatment design control 90% 75% 100% 75% 90% 100% 20 passages under selection to kill
126. Julie Lin Arooj Khalid Helena Baffoe-Bonnie
127. Raythe Owens McKenna Penley Dilys Osei
128. experimental evolution Passage t archived hosts design
129. experimental evolution 30 dead hosts archived hosts 24 hr design Passage t
130. experimental evolution 30 dead hosts 40 parasite colonies archived hosts 24 hr design Passage t
131. experimental evolution 30 dead hosts 40 parasite colonies Passage t+1 archived hosts archived hosts 24 hr design Passage t
132. experimental evolution 30 dead hosts 40 parasite colonies archived hosts archived hosts Passage 20 24 hr design Passage t+1 Passage t
133. Adaptation to common hosts predictions
134. Adaptation to common hosts 100% 100% control 1 Parasites kill sympatric hosts predictions
135. Adaptation to common hosts 90% 75% 75% 90% 1 2 Parasites kill sympatric hosts Parasites kill common hosts predictions
136. Dilys Osei
137. measuring adaptation archived hosts parasite lineage design
138. measuring adaptation 48 hr 48 hr mortality rate mortality rate design archived hosts parasite lineage
139. measuring adaptation 48 hr 48 hr 1 − mortality rate mortality rate design archived hosts parasite lineage
140. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts predictions 100% 100% control
141. Parasites kill sympatric hosts 1 host A host B Mortality Rate Parasite Parasite results
142. Parasites kill sympatric hosts 1 host A host B Mortality Rate Control 0% 100% Control 0% 100% results Parasite
143. Parasites kill sympatric hosts 1 host A host B Mortality Rate Control 0% 100% Control 0% 100% Ancestor ± SEM results Parasite
144. Parasites kill sympatric hosts 1 host A host B Mortality Rate Control 0% 100% Control 0% 100% results Parasite
145. Parasites kill sympatric hosts 1 host A host B Mortality Rate Control 0% 100% Control 0% 100% GLMM: parasite p < 0.001 * results Parasite
146. Parasites kill sympatric hosts 1 host A host B Mortality Rate Control 0% 100% Control 0% 100% GLMM: parasite p < 0.001 * 1.8x results Parasite
147. Parasites kill sympatric hosts 1 host A host B Mortality Rate Control 0% 100% Control 0% 100% GLMM: parasite p < 0.001 GLMM: parasite p = 0.279 * results Parasite
148. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts predictions 100% 100% control
149. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts x predictions 100% 100% control
150. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts x 90% 75% 75% 90% predictions
151. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts x 90% 75% 25% 10% >>> predictions
152. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts x 10% 25% 75% 90% ≅ predictions
153. Parasites kill common hosts host A host B Mortality Rate Rare Common 2 Rare Common results Parasite
154. Parasites kill common hosts host A host B Mortality Rate Rare Common 2 Rare Common GLMM: rare/common p < 0.001 * 1.4x results Parasite
155. Parasites kill common hosts host A host B Mortality Rate Rare Common GLMM: rare/common p < 0.001 * 2 Rare Common GLMM: rare/common p = 0.215 results Parasite
156. Parasites kill common hosts host A host B Mortality Rate Rare Common GLMM: rare/common p < 0.001 * 2 Rare Common GLMM: rare/common p = 0.215 a neutral host? results Parasite
157. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts x predictions
158. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts x x predictions
159. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts x x “defended” “neutral” predictions
160. Defended vs. neutral hosts results Helena Baffoe-Bonnie
161. Defended vs. neutral hosts host A Control 100% Mortality Rate host C Control 100% JU1395 results Helena Baffoe-Bonnie Parasite
162. host A Control 100% Mortality Rate host C Control 100% GLMM: parasite p = 0.037 Defended vs. neutral hosts results Helena Baffoe-Bonnie Parasite
163. host A Control 100% Mortality Rate host C Control 100% GLMM: parasite p = 0.037 GLMM: parasite p < 0.001 Defended vs. neutral hosts results Helena Baffoe-Bonnie Parasite
164. host A Control 100% Mortality Rate host C Control 100% GLMM: parasite p = 0.037 GLMM: parasite p < 0.001 specialization Defended vs. neutral hosts results Helena Baffoe-Bonnie Parasite
165. Defended vs. neutral hosts Helena Baffoe-Bonnie host B Control 100% Mortality Rate host C Control 100% * Prediction no specialization predictions Parasite
166. Adaptation to common hosts 1 Parasites kill sympatric hosts 2 Parasites kill common hosts x x “defended” “neutral” predictions
167. Host Parasite x Adaptation to common hosts x Time Frequency summary
168. Host Parasite x Time Frequency Adaptation to common hosts summary
169. Host Parasite x Time Frequency host Adaptation to common hosts summary
170. Host Parasite x Adaptation to common hosts Time Frequency parasite summary
171. Signe White Adaptation to common hosts Time Frequency parasite summary Poster P-0801 in S16
172. Adaptation to common hosts Parallels in biological control Wergin, Sayre Time Frequency parasite summary
173. Hypothesis: the Red Queen Assumption: adaptation to common hosts dodging minute enemies Alternative: dodging by dispersal Z Dinges outline
174. Hypothesis: the Red Queen Assumption: adaptation to common hosts dodging minute enemies Alternative: dodging by dispersal Z Dinges outline
175. “The most that the average species can achieve is to dodge its minute enemies by constantly producing new [or rare] genotypes” ~JBS Haldane, 1949
176. PART 3 Is space better than sex?
177. “Sex, with attendant genetic change, may allow escape in time.” ~J Jaenike, 1978
178. “Sex, with attendant genetic change, may allow escape in time.” ~J Jaenike, 1978 “Escape in space is the strategy of fugitive species.”
179. “Sex, with attendant genetic change, may allow escape in time.” ~J Jaenike, 1978 “Escape in space is the strategy of fugitive species.” Fontaneto et al. 2008 Wilson and Sherman, 2010 Science; 2013 Proc B
180. dodging by dispersal background
181. dodging by dispersal Time Frequency host parasite background
182. dodging by dispersal Time Frequency x background
183. dodging by dispersal parasite prevalence background Time Frequency x
184. the case of the missing males Caenorhabditis elegans background
185. the case of the missing males Caenorhabditis elegans self background
186. the case of the missing males Caenorhabditis elegans self outcross x background
187. the case of the missing males Caenorhabditis elegans self outcross x lab background Parasites
188. the case of the missing males Caenorhabditis elegans self outcross x lab Morran et al. 2011 Science background coevolution favors outcrossing Parasites
189. the case of the missing males Caenorhabditis elegans self outcross x lab field males are vanishingly rare coevolution favors outcrossing Barrière and Félix 2005 Curr Biol background Parasites
190. lab field Coevolving parasites can maintain outcrossing (lab) background males are vanishingly rare coevolution favors outcrossing Parasites
191. lab field Coevolving parasites can maintain outcrossing (lab) but they don’t (field) background males are vanishingly rare coevolution favors outcrossing Parasites
192. Disconnect between lab and field Why? hypotheses
193. Disconnect between lab and field virulent parasites are absent in the field 1 Why? hypotheses
194. Disconnect between lab and field Why? virulent parasites are absent in the field 1 2 life history limits parasitism hypotheses
195. Disconnect between lab and field Why? virulent parasites are absent in the field 1 2 life history limits parasitism hypotheses
196. There are parasites 1 system
197. 1 Nematocida parisii Troemel et al. 2008 PLoS Biology Felix and Duveau 2012 BMC Biology Gibson and Morran 2017 Journal of Nematology; review There are parasites system
198. 1 Nematocida parisii “nematode killer from Paris” Troemel et al. 2008 PLoS Biology Felix and Duveau 2012 BMC Biology Gibson and Morran 2017 Journal of Nematology; review There are parasites system
199. 1 Nematocida parisii Troemel et al. 2008 PLoS Biology There are parasites system
200. 1 Nematocida parisii Troemel et al. 2008 PLoS Biology There are parasites system
201. 1 Nematocida parisii Troemel et al. 2008 PLoS Biology There are parasites system
202. 1 Nematocida parisii Troemel et al. 2008 PLoS Biology pow There are parasites system
203. 1 Nematocida parisii Troemel et al. 2008 PLoS Biology There are parasites system
204. 1 Nematocida parisii Troemel et al. 2008 PLoS Biology There are parasites system
205. Are they virulent? 1 Exposed design
206. Are they virulent? 1 Exposed design
207. 1 Exposed Healthy Are they virulent? design
208. 1 Exposed Healthy Chase Gornbein Rishika Pandey McKenna Penley Are they virulent? design
209. 1 Exposed Healthy Relative population size lab field N2 HW wild lines Are they virulent? results (Mean ± se) Hosts
210. 1 Exposed Healthy Relative population size lab field N2 HW wild lines (Mean ± se) Are they virulent? results Hosts
211. 1 Exposed Healthy Relative population size lab field N2 HW wild lines GLMM: treatment p < 0.001 (Mean ± se) Are they virulent? results Hosts
212. 1 Exposed Healthy Relative population size lab field N2 HW wild lines GLMM: treatment p < 0.001 (Mean ± se) Are they virulent? Yes results Hosts
213. Disconnect between lab and field Why? virulent parasites are absent in the field 1 2 x life history limits parasitism hypotheses
214. Disconnect between lab and field Why? virulent parasites are absent in the field 1 2 x life history limits parasitism hypotheses
215. Is space better than sex?
216. 2 dodging by dispersal system
217. 2 dodging by dispersal system
218. 2 dodging by dispersal Felix and Duveau 2012 BMC Biol Schulenburg and Felix 2017 Genetics system
219. 2 dodging by dispersal Felix and Duveau 2012 BMC Biol Schulenburg and Felix 2017 Genetics system
220. 2 dodging by dispersal dauer Felix and Duveau 2012 BMC Biol Schulenburg and Felix 2017 Genetics system
221. 2 dodging by dispersal dauer Felix and Duveau 2012 BMC Biol Schulenburg and Felix 2017 Genetics natchapohn system
222. 2 dodging by dispersal dauer Felix and Duveau 2012 BMC Biol Schulenburg and Felix 2017 Genetics system
223. 2 dodging by dispersal Felix and Duveau 2012 BMC Biol Schulenburg and Felix 2017 Genetics system
224. 2 dodging by dispersal parasites? system
225. Disconnect between lab and field Why? virulent parasites are absent in the field 1 2 x life history limits parasitism hypotheses
226. Disconnect between lab and field Why? virulent parasites are absent in the field 1 2 x Do hosts migrate successfully from infected sites? life history limits parasitism hypotheses
227. 2 Do hosts migrate successfully from infected sites? infected migrants Troemel et al. 2008 PLoS Biology Felix and Duveau 2012 BMC Biology predictions
228. 2 infected migrants Troemel et al. 2008 PLoS Biology Felix and Duveau 2012 BMC Biology ? ? ? predictions Do hosts migrate successfully from infected sites?
229. 2 transmission Troemel et al. 2008 PLoS Biology Felix and Duveau 2012 BMC Biology ? ? ? predictions Yes Do hosts migrate successfully from infected sites? coevolution
230. 2 Troemel et al. 2008 PLoS Biology Felix and Duveau 2012 BMC Biology ? ? ? predictions No Do hosts migrate successfully from infected sites? transmission coevolution
231. 2 healthy exposed design Do hosts migrate successfully from infected sites?
232. 2 healthy exposed (Prop ± se) Healthy low mid high Fraction establishing results Exposed (dose) Do hosts migrate successfully from infected sites?
233. 2 healthy exposed results (Prop ± se) Healthy low mid high Fraction establishing Exposed (dose) N=19-20 Do hosts migrate successfully from infected sites?
234. 2 healthy exposed results (Prop ± se) Healthy low mid high Fraction establishing Exposed (dose) N=19-20 Do hosts migrate successfully from infected sites?
235. 2 healthy exposed results (Prop ± se) Healthy low mid high Fraction establishing Exposed (dose) Do hosts migrate successfully from infected sites? No
236. 2 results (Prop ± se) Healthy low mid high Fraction establishing Exposed (dose) Do hosts migrate successfully from infected sites? transmission coevolution No
237. Disconnect between lab and field Why? virulent parasites are absent in the field 1 2 x life history limits parasitism Parasitized hosts don’t migrate successfully hypotheses
238. Coevolving parasites can maintain outcrossing but do they?
239. “The most that the average species can achieve is to dodge its minute enemies by constantly producing new genotypes” ~JBS Haldane, 1949
240. Hypothesis: the Red Queen Assumption: adaptation to common hosts dodging minute enemies Alternative: dodging by dispersal Z Dinges outline
241. Lynda Delph Daniela Vergara Amrita Bhattacharya Zoe Dinges Spencer Hall Christiane Hassel Peyton Joachim Sam Klosak Eliza Oldach Ngaire Perrin Julie Xu McKenna Penley Helena Baffoe-Bonnie Arooj Khalid Julie Lin Raythe Owens Dilys Osei Kayla Stoy Emily Troemel Marie-Anne Felix Gaotian Zhang Acknowledgements Curt Lively Levi Morran
242. University of Virginia positions in 2019
243. Mortality Rate 10% 25% 75% 90% host A
244. Mortality Rate 10% 25% 75% 90% host B
245. Lively 2009 JEB N sexual asexual Freq. infection Generation
246. Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field Are parasites less able to infect asexuals? Freq. infection
248. juvenile snails parasite eggs 2012-2015 1
249. + parasite eggs juvenile snails 1 Are parasites less able to infect asexuals?
250. + parasite eggs juvenile snails 6 control; 6 exposed 2012-2015 1 Are parasites less able to infect asexuals?
251. 1 Mark Dybdahl; Ryan Hechinger
252. + parasite eggs juvenile snails 1 Are parasites less able to infect asexuals? 6 control; 6 exposed 2012-2015 Sexual Asexual
253. Proportion infected Sexual Asexual Sexual Asexual Control Exposed 1 Are parasites less able to infect asexuals?
254. Proportion infected Sexual Asexual Sexual Asexual Control Exposed 1 Are parasites less able to infect asexuals?
255. Proportion infected Sexual Asexual Sexual Asexual Control Exposed 31% 11% GEE: reproductive mode 1 Are parasites less able to infect asexuals?
256. Red Queen predicts: Asexuals are under-infected when rare 1 Asexuals are rare in the field Are parasites less able to infect asexuals? Freq. infection
257. Lively 2009 JEB Freq. infection periodic over-infection + under-infection of asexuals Generation
258. obligately asexual animal species Vrijenhoek 1998 BioScience sexual but it does! problem
259. nematode phylum Gibson and Fuentes 2015 Evolution selfing/asexual (few ♂s) outcrossing (many ♂s) but it does! problem
260. “The most that the average species can achieve is to dodge its minute enemies by constantly producing new [or rare] genotypes” ~JBS Haldane, 1949
261. Intro on sex – can we tie it into parasites? Make it clear where you’re going – parasites Don’t go straight into sex – preview Change arrows with dispersal section Add successfully migrate Don’t use generations in experimental evolution – use passage Add in few more words – make sure you’re clarifying host v. parasite in conclusions/predictions Failed to falsify the red queen – return to this wording Mention how related hosts are when you introduce c Add in poster number Dirty secret Mention what the systems are on intro slide – why snail? Why nematode?