Section	Papers
Newt & Snake	12
Brendan Sugested Papers	3
Genetic-Architecture	13
Genetic Diversity	11
Spatial variation	6
Machine Learning	5
Theory Based Papers	2
Preprints	1
Sigma Papers	3
History of Coevolution	summary
Malaria Related Papers	9
Coevolution Paper Sugestion	4
Peters Suggestions	2
Other Papers	34
Ethics	1

Newt and Snake Papers:

Phenotypic Mismatches Reveal Escape from Arms-Race Coevolution

• This paper is a huge ecology co-evolution natural variation experiment. The collected newts and snakes and measured their poison and resistance (of a toxin) and found that there where areas that matched and mismatched in phenotype matching. This experiment makes me want to do a phenotype matching simulation, where there is a selection mosaic and reciprocal selection interactions. It reminds me of local adaptation that has become maladaptive.

THE EVOLUTIONARY RESPONSE OF PREDATORS TO DANGEROUS PREY:

Parallel Arms Races between Garter Snakes and Newts Involving Tetrodotoxin as the Phenotypic Interface of Coevolution

• This paper was a bit tricky for me because I keep forgetting the scientific names of the newt and the snake... However, this article talks about a similar phenotype change that occurs in sister species of the "original" garter snake and the "original" newt. This paper goes on to explain the similarities between this new interaction to the old interaction. It proposes reasons for seeing similar coevolutnagry escalation are from the interaction of newts and snakes, but because these interactions are occurring in a different area they might be occurring at the same time as the other newts and snakes. The look at ecological and phylogenetic info and determined that evolution is occurring at the same time, thus is parallel.

A Resistant Predator and Its Toxic Prey: Persistence of Newt Toxin Leads to Poisonous (Not Venomous) Snakes

COEVOLUTION OF DEADLY TOXINS AND PREDATOR RESISTANCE: SELF-ASSESSMENT OF RESISTANCE BY GARTER SNAKES LEADS TO BEHAVIORAL REJECTION OF TOXIC NEWT PREY - see if at library

Evolutionary Response of Predators to Dangerous Prey: Reduction of Toxicity of Newts and Resistance of Garter Snakes in Island Populations

Tetrodotoxin affects survival probability of rough-skinned newts (Taricha granulosa) faced with TTX-resistant garter snake predators (Thamnophis sirtalis)

• This paper talked about the life-dinner principle (where fitness consequences are worse for the prey) in order to examine how prey gain the ability to poison predators. They looked into the survivability of prey with more poison and quantified it. They feed newts to snakes and saw which ones survived and newts with more poison survived and dives the escalation of toxin.

Sex linkage of the skeletal muscle sodium channel gene (SCN4A) explains apparent deviations from Hardy–Weinberg equilibrium of tetrodotoxin-resistance alleles in garter snakes (Thamnophis sirtalis)

The skin microbiome facilitates adaptive tetrodotoxin production in poisonous newts

• This article introduces ideas about why the newts are toxic, spoiler they have bacteria that produce the toxin. It also gives a good definition of the chemistry behind how the toxin works. The found some symbiotic bacteria that could produce TTX and that newts have genes similar to snake which allows then to proceed the toxin (not the same genes as snakes, but the same resistance). They didn't get too many new results, but sate that interactions are very complex. I wonder if its difficult to increase toxicity and have a symbiotic relationship with the bacteria? Did this happen at the same time? What kind of Genetic Architecture do these genes have?

The geographic mosaic of arms race coevolution is closely matched to prey population structure Genetic structure of prey populations underlies the geographic mosaic of arms race coevolution (the preprint LOL different names nut is the same paper)

• This paper is very similar to what I want to do, but not exactly the same. They look at population structure and environmental factors that can influence newt and snake traits across a vast area. It talked about how snake levels of resistance are determined by newt toxin levels, but newt toxin levels were determined by the sourcing newt population?. This paper is a great set up for the simulation experiment that I want to run: "Our results imply that processes other than reciprocal selection, like historical biogeography and environmental pressures, represent an important source of variation in the geographic mosaic of coevolution". What is the difference between PCA and PCoA?

The geographic mosaic in parallel: Matching patterns of newt tetrodotoxin levels and snake resistance in multiple predator–prey pairs

• A new paper that came out in 2020 that talks about coevolution occurring in similar species (newt and snake) in the Serbia Nevada. They have discovered another toxin arms race that is following a similar pattern to the other newt and snake (some places the phenotypes are matching in others the snakes are so resistance that they can eat any newt). However, there is some elevation correlation that they discuss (which I wonder if that exists in the other species, or has something to do with the environment). And there was always a newt and snake pair that was found that the snake could not eat the newt (i.e. the could be reciprocal selection occurring)

Predators usurp prey defenses? Toxicokinetics of tetrodotoxin in common garter snakes after consumption of rough-skinned newts

Patterns, Process, and the Parable of the Coffeepot Incident: Arms Races Between Newts and Snakes from Landscapes to Molecules

• This is a GREAT book chapter that describes how snakes and newts interact. It's almost a collection of the history of this interaction told from a personal view point of Brodie III. It describes how snakes eat the newts and how selection could work on this system (which is their behavioral interaction). An interesting part of this chapter is how the snake is the co-evolutionary winner (there was no area where the newt was more toxic than the snakes), this might be due to the mutations that make the snake resistant. Simulation idea: make the snakes move to less poison newt area?

Newts are Toxic, but They were Pressured into it: Butch Brodie’s Studies of Co-Evolutionary Arms Races

Brendan Sugested Papers:

Linking genetic change to community evolution/ insights from studies of bacteria and bacteriophage

• This paper was a review on the coevolutionary experts done with bacteria (E.coli) and phages. It talked a lot about the cost of certain resistance mutations and how populations were controlled by a balance of different states (resistant, sensitive, phage). This was especially true with limited resources. There was a case for coevolutionary arms race and a case where the phage could not evolve past the bacterias resistance. A drawback from these experiments is time, it would be cool to follow these experiments for even longer than what they ran for. Like in the other paper density plays a large role (resource levels). Something that was unique in this paper was the emphasis on how differences in interaction have dramatic effects on the community.

Local migration promotes competitive restraint in a host–pathogen ‘tragedy of the commons’

• This paper runs and discusses an experiment on the effects of phage and E. coli evolution when there are different forms of population structure. Here there were two forms of population structure, structured (control on where well occupants moved) and unstructured (no control on where well occupants moved). The structured population developed a more stable interaction, where there were no/less extinction and a less aggressive phage dominated. When there was no structure, there was extension and a more aggressive phage existed. They also discussed population densities and reasons for why they were not exactly what they expected.

Adaptation varies through space and time in a coevolving host–parasitoid interaction

• This paper discussed an experiment done with bacteria and phage with spatial components (altho the spatial aspects seems similar to an island model). The populations varied in resource levels and different mutations formed under different conditions. They were able to show that spatial structure did have an impact on coevolution of bacteria and phages and increased variation over time. Some things that I wonder about this experiment; why did they only migrate from high to low resource, how would the results differ if there was a non-island like spatial structure, and what does the genome structure have to do with adaptations (why are some more common than others, does this change in other situations)?

Genetic architecture effects on the speed and pattern of coevolution

Ecological

The genetic architecture of disease resistance in plants and the maintenance of recombination by parasites

Theoretical

The Raw Material for Coevolution

COEVOLUTION AND THE ARCHITECTURE OF MUTUALISTIC NETWORKS

THE EVOLUTION OF GENETIC ARCHITECTURE UNDER FREQUENCY-DEPENDENTDISRUPTIVE SELECTION

Host–parasite coevolution and patterns of adaptation across time and space

Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents

ANTAGONISTIC COEVOLUTION MEDIATED BY PHENOTYPIC DIFFERENCES BETWEEN QUANTITATIVE TRAITS

• This is a theory paper that focused on phenotypes that were out competing other phenotypes (not trait matching). There is discussion on wether stabilizing selection or coevolution selection is stronger and their outcomes. In this paper when coevolution selection is stronger than stabilizing selection, the phenotypes becomes cyclic, which leads to maintained diversity. They ran simulations to test their model, by breaking it down into different categories with different assumptions. This paper is full of predictions about the type of coevolution that I am looking. at and would be cool to compare my results to (since I might look at the strength of selection). I liked the part where they point out that trait mismatching can occur without deneflow, genetic drift or extinction/recolonization.

Experimental

Interspecific genetics of speciation phenotypes: song and preference coevolution in Hawaiian crickets

Antagonistic coevolution with parasites maintains host genetic diversity: an experimental test

• This paper focused on running an experiment based off of Haldane's theory (the potential for parasites to drive host diversity). In this paper the researchers used a host, Tribolium castaneum and a microsporidian parasite, Nosema whitei, to test the effects of drift and parasite selection. They found that when there was coevolution with the parasites there was more heterozygosity in the population than just drift alone. There was also a lower than expect amount of differentiation between the different replicas. In other words the might be balancing selection when the host is coevolving with the parasite. This experiment sets up the idea that specific interactions between two species might have a specific result (two of the same species coevolving at completely isolated places can coevolve in the same way). Where they able to look at the genetics of the parasite? - I don't think so

Local adaptation, evolutionary potential and host–parasite coevolution: interactions between migration, mutation, population size and generation time

History

Open questions: what are the genes underlying antagonistic coevolution?

• The authors of this article say that species do not evolve, genes do. They focus on determining how genes are evolving and more importantly how are they coevolving. An important part of this article is that they answer the "why" biologist should study coevolution. - by knowing the genetic architecture and spatial components we can use population genetics to predict temporal dynamic like when mutations might occur, spread of new variants.

Spatial and Temporal Patterns in Coevolving Plant and Pathogen Associations

• This paper looked at the spatial and temporal patters of a host and pathogen (focusing on the Linum-Melampsora system). The found that in order to see patterns they need to look at different populations. They also found that different life history aspects play import roles in how systems coevolve. This article points out that theory can be used to make practical coevolution studies.

Geographic structure and dynamics of coevolutionary selection

• This was a short paper detailing the interaction of a moth (parasitic/pollinator) and a herbaceous plant. They investigated conflicting information that in some areas this moth was a pollinator in other areas this moth was a parasite and found that whether the moth was a parasite or pollinator depended on the community context. The authors describe the interaction as mutualistic, commensal or antagonistic and that it differs geographically. By observing these moths and plants in different contexts the authors concluded that species that are geographically structures will coevolve towards spatial mosaics. This paper made me hesitant to believe the conclusion because there were no movement of species. If I was going to design an experiment I would like to do a transplant experiment to see if the interaction was species dependent.

Genome wide genetic diversity of coevolving species (when are there increases and decrease in GD?)

Ecological

Bacteria-Phage Antagonistic Coevolution in Soil

• This article was focusing on taking the bacteria-phage interaction out of the test tube and into the soil. By placing the interaction in soil the researchers add complexity to their experiment (taking in past, current and future selfs). They wanted to make the link between coevolution of bacteria and phage and the diversity of the micro biome and I am not sure that it made since (to me). Also 3d graphs are difficult to read. They showed that bacteria and phage were evolving, but stated that it was not an arms race potentially because there were cycles in resistance/infectivity because of the bacteria and virus have to be better than their past self. However, if there is a cost to having certain levels of resistance/infectivity I could see the possibility of cycling. It would be cool to run this experiment long term and see if there is a repeat of the cycle or to genotype the bacteria and phages to see how they change and if there is aa cost to resistance/infectivity.

Constraints on the coevolution of bacteria and virulent phage: a model, some experiments, and predictions for natural communities

Host–parasite coexistence: the role of spatial refuges in stabilizing bacteria- phage interactions.

Rapid genetic change underpins antagonistic coevolution in a natural host‐pathogen metapopulation

Theoretical

Plant-Parasite Coevolution: Bridging the Gap between Genetics and Ecology

Local adaptation and the geometry of host–parasite coevolution.

• The researchers use a form of spacial structure to see how migration rate, specificity and virulence can influence the winner of a coevolutionary arms race. They confirm that migration rate is directly related to local adaptation of a population. They also discuss asynchronous convolution in which there are different forces action on a population in different areas. Something that I found cool in this paper was the spiral waves seen in the simulation that the authors ran (reminds me of how my simulation was chasing each other). The author also shows that higher specificity and virulence in parasites that are already winning the coevolutionary arms race lead to higher levels of local adaptation, I was confused on how they interpreted this part...

When Does Coevolution Promote Diversification?

• This was a really cool modeling paper that pick really good parameters. It is very similar to what I want to do (equation wise) but done in SLiM and not as population island (it might be a good idea to use some of these equations in my simulation). They go over different types on interactions and how this interaction can increase diversification (interaction is also referred as mechanism). I wonder if they incorporated "hot and cold spots" in their simulation, would they get the same results? Talked about trophic levels diversification (recent studies have this important why?). The authors of this paper say that diversification only happens when there is a cost to closer matching phenotype, what if I turn the cost off? This article points towards competition being a main force driving diversification.

Coevolution and the Diversification of Life

• This was a fun paper that discussed how the different types of coevolution (mutualism, antagonist, and competition) can promote diversity. The authors specifically talked about the lack of evidence for convolution being a main force in driving speciation. They also went over the history of the butterflies and plants and had a great background over all. This paper made me think about why the newts and snakes seem to still be the same species (respectively) and a possibility to that answer is the way that the interaction is set up, while also talking about the similarity to vertebrae histocompatibility. Red crossbills are also a great example of empirical evidence for coevolution. A part of the paper that I did not understand was about trophic levels and their importance. I also had a hard time understanding why the use the term macroevolutionary.

Local adaptation and gene-for-gene coevolution in a metapopulation model

• This paper created a gene-for-gene model for parasite and human coevolution and they examined gene frequencies and population densities. Gene-for-gene model is different from what I am studying (QTL), but it was still interesting to see how they dealt with population structure (by allowing migration to the next square). They found that demography had a stabilizing effect, less likely that one of the species would die (might be called buffer effect). Demography lead to high levels of polymorphisms, the ability for mutations to be re-introduced to areas, and local adaptation.

Experimental

Antagonistic Coevolution of Marine Planktonic Viruses and Their Hosts

• Different paper than what I typically read. It talked about coevolution in the ocean, which is cool if you were going to model it there would be and added complexity, depth. The background was helpful in thinking about antagonistic coevolution while also highlighting how virus effect ocean beings (part of the carbon and nitrogen cycle). The main goal of this article was to figure out the signatures od coevolution and discuss what they might look like in the ocean. This article made me feel like there was going to be more diffuse rather than pairwise coevolution. In the end they mostly reviewed different coevolution systems and talked about how it could potentially be implemented in a marine environment.

Coevolution in Temporally Variable Environments

• This paper was a bit hard for me to understand. I think the authors were examining how the fluctuation between different interaction types (antagonistic and mutualism) effected the dynamics of coevolution, the term is conditional mutualism. They show that the they can get patterns that are predicted by the geographic mosaic theory without gene flow. The focused on the geometric mean, and depending on its value or sign that would indicate that the interaction was mutualistic or antagonistic.

Spatial variation in interacting phenotypes vs random processes or Coevolution along the Genome

Ecological

Genomic variation across landscapes: insights and applications

• This paper was suggested by Peter to look at how the genome evolves. Basically there is variation in how genomes evolve across landscapes which could highlight the complex interactions between phenotypes and the environment. This paper talks about "landscape genomics", but was confusing because I think here they use landscape to describe areas of the genome. Need more information about it (look here).

Theoretical

Coevolution Creates Complex Mosaics across Large Landscapes

Role of coevolution in generating biological diversity: spatially divergent selection trajectories

The measurement of coevolution in the wild

Identifying coevolving loci using interspecific genetic correlations

• This paper used covariance to determine if two genes were coevolving. To do this they first have a set of candidate gene. Then they calculate the frequency of the genes and then calculate the spatial covariance between the hose and parasite gene. They focused on trying to find which genes seem to covary more than others. The method they proposed worked, they were able to tell if genes were coevolving. However, their method does not work when there are hot and cold spots (places where the genes are and are not locally adapted) and if the genes are polygenic. It was a well explained methods peer that would be good to use as a model.

Experimental

Experimental coevolution of species interactions

Machine Learning:

Detecting adaptive introgression in human evolution using convolutional neural networks

• Peters suggestion for methods discussing machine learning. I enjoyed this paper, but I probably need to look at it again once I try to use ML. This paper uses simulations of adaptive introgression to train a neural network, then does other simulations to test it. This paper demonstrated the use of neural networks in identifying adaptive introgression in human populations. There are also of fine tuning that I did not understand, hopefully by working through this I will understand it a bit more. Some questions that came up when reading this paper: Can I identify some aspect of coevolution (involving spatial structure) for my aim? This leads to other question like would/could I use real data or would it all be simulations? What type of data is important and how much of it does one need?

Predicting the Landscape of Recombination Using Deep Learning

• This article predicts recombination rate with machine learning, by creating a deep learning method (ReLERNN). It was a method paper that compared this new deep learning method to other methods that use log likelihood calculations. The took in genotype alignments and allele frequencies to predict recombination rates (good diagram of what happened in the training process). It might be a good paper to look into the method a bit more to see if I can apply deep learning to my project. I re-read this and it talks about different types of neural networks that might be useful in developing my third aim.

Supervised Machine Learning for Population Genetics: A New Paradigm

• Super cool and easy to read paper that makes me think all of my problems can be solved by machine learning. On more realistic side it gives good examples of where machine learning had been successfully implemented in population genetics. This article states and explains the benefit of using machine learning techniques versus other statistical methods. Specifically, discussion how results from simulations can be used to make inferences on empirical data.

S/HIC: Robust Identification of Soft and Hard Sweeps Using Machine Learning

• Authors use summary statics to train a classifier to classify 5 things (sweeps and neutral models). This is a good paper to understand the methods behind training and using supervise machine learning. Their goal was to detect and identify different types of sweeps. I think I can use parts of their methods to find genes under coevolution. This paper was really cool. They compared and contrasted the results of their methods too many different methods. Over all the NN they built did a good job at detecting sweeps.

The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference

• This paper used methods from Schrider and Kern 2016 (paper currently above) and combined new methods to get a better grasp on identifying population dynamics. Instead of using different summary statistics they used pictures of alignment. By using the alignment picture they were able to not lose information. I found the part where they were talking about how this method doesn't really on the things we know to be fascinating. Its not tied to a specific theory or mathematical formula, which might make the implementation a good piece of my project. This paper also had a part where they talked about what goes on in the "black box", which was kind of helpful and that I would like to read again.

Theory Based Papers:

Reciprocal Selection at the Phenotypic Interface of Coevolution1

• This was a theory paper that used Newts and Snakes as an example of how coevolutionary interactions can change phenotypes of the species involved in the interaction. It has equations that describe the strength of selection in a population undergoing coevolution. There are also some three-d figures that show the the range of toxin/resistance expected when Newts and Snakes are interacting. I might be able to build off this example by add in spatial structure.

Gene Flow and Selection in a Cline

• This is a modeling paper from the 70s that describes how gene flow and natural selection works when there is spatial variation. They also discuss barriers and how they might impact a population. Something I was confused by was characteristic length, because this had to do with the pattern of spatial variation and might be importing on the spatial aspect of my project. This paper made me think of local adaptation with out using the term local adaptation. The conclusions are helpful, but does cline really mean? Cline meant that there was a change in selection across space, is it the same in this paper?

Preprints

Interacting Phenotypes and the Coevolutionary Process

• A theory paper that tried to tie coevolution theory to local evolution theory. There was a lot of things in this paper that I didn't completely understand. Like how did coevolution occur if one species had no genetic variation or how were the traits heritable. They made some decisions that would make the math simpler (although it was still complex), but it might not be biologically accurate. This paper also focused on the plasticity of traits, which can change based on the environment. Is what they discussed in the paper truly coevolution?

Papers about sigma, the high and low population structure:

Isolation By Distance -Side note cool hand drawn figures. Write is describing how to statically tell how different populations are from each other. Write shows that there are different levels of inbreeding between different motifs (small and large dispersal). He also tied these things to the total population size.

Isolation by Distance under Diverse Systems of Mating

• This paper by Wright explores the effects of neighborhood size though different mating systems. This paper also tries to relate the population size to the neighborhood size though different math equations. He found that an effect N was equivalent to 2*sigma (circle radius). It is really cool how Wright goes through each scenario by describing and drawing a picture. This paper also talks about the difference between groups of 20 (great differentiation among large subgroups and neighborhoods) and 200 (moderate differentiation among large subgroups and neighborhoods).

Spatially-explicit estimation of Wright's neighborhood size in continuous populations

• This paper looks at a spatial population and determines the neighborhood size, which varies at different locations. They frame their discoveries in a conservation light to make inferences on how at risk populations should be monitored. It was difficult to determine an unbiased neighborhood size which lead to over and under estimated FIS values. They did determine that there was a possibility of an extinction vortex and that it can be determined through genetic data. But there needs to be more studies done for fluctuating population size and different demographics.

History of Coevolution:

Winter term 2021 I wrote a coevolution overview for a class. In it I discussed how the term coevolution has changed through to the decades. The term coevolution originally did not have an official definition when used in papers. I have seen it used to describe population evolving in tandem and population evolving from reciprocal selection. The term paper I wrote focused on how the term was used in the 1950-1960s to how it is used today and how the definition changes when "coevolution" is used in different contexts. Some of the paper I discussed were Mode 1958 (first theory paper about gene-for-gene coevolution), Erlich and Raven 1964 (butterflies and toxic plant, escape-and-radiate), and Janzen 1966 (ants (Pseudomyrmex) and Acacias, evolution trait matching). I also talk about mutualism, describing Brouat et al. 2001 (ant and plants mutualism, size matching, fig-fig wasp system, and yucca-yucca moth. I also talked about antagonistic interaction, discussing arm race (Bohannan and Lenski, 2000; Brodie, 2003; Thompson, 2005), evolution of sexes (Chapman et al., 2003; de Visser and Elena, 2007), and diffuse coevolution (Parchman et al. 2016, the pine-squirrels-crossbills). The term paper then went on to discuss coevolution over a spatial and temporal setting. In this section I discussed the geographical mosaic of coevolution 2005, Parchman et al., 2016 (new look on the diffuse coevolution crossbills-pine-squirrels). Good general papers that have an excellent background Butler et al., 2009; Eaton, 2008; Hembry et al., 2014).

Malaria Related Papers:

*Plasmodium Genomics and Genetics: New Insights into Malaria Pathogenesis, Drug Resistance, Epidemiology, and Evolution

*MALARIA MOLECULAR EPIDEMIOLOGY: AN EVOLUTIONARY GENETICS PERSPECTIVE

*Stochastic lattice-based modelling of malaria dynamics

Host–parasite interactions for virulence and resistance in a malaria model system

• infected mice with malaria and found that there were limited host-by-parasite interactions. The genotype-genotype interactions had a response to the parasite virulence, but it was mostly the host's genotype that determined the outcome? seemed like a strange and small study.

*Gametocyte carriage in an era of changing malaria epidemiology: A 19-year analysis of a malaria longitudinal cohort

*Insecticide resistance and malaria control: A genetics-epidemiology modeling approach

*Hijacking Malaria Simulators with Probabilistic Programming

• This paper sounded really cool, but was not what I was expecting. They use the random number generator to manipulate simulations while tracking these changes. They implement their manipulated random number generator on Malaria simulators to make a probabilistic generative model. It seems like they are making random processes nonrandom. The researchers implanted this method on population based simulation, how do these differ from individual based simulations? Brought up a good idea about policy making that might be helpful for my stuff

*A Historical Review of WHO Certification of Malaria Elimination

• Three hallmarks of malaria-induced selection in human genomes

More coevolution paper suggestions:

https://scholar.google.com/scholar?cites=16260207723551910615&as_sdt=5,38&sciodt=0,38&hl=en

The Coevolving Web of Life

• One of my favorite papers right now. It contains many ecology/evolution questions about coevolution and the impacts of webs (species that interact with one-another). From reading this paper I became curious about the speciation of the malaria/mosquito and how coevolution (potentially) brought this on? How this separation event brought on new amounts of diversity and questions on why some species still remain.

-The geographic mosaic theory of coevolution provides a bridge among these various approaches, linking the dynamics of adaptation and coadaptation among interacting species within local communities to the diversification of those interactions across complex landscapes (Thompson 1994, 2005).

• I am curious on how different interactions shape species diversity.

Dos and don’ts of testing the geographic mosaic theory of coevolution

• Very interesting review on the Geographic Mosaic of Coevolution (a book I am SLOWLY reading...) outlining how to correctly interpret and design results/experiments pertaining to coevolution. This paper brings up good points about not jumping to conclusions, while discussing the gathering of data that support the coevolution hypothesis. The authors go into length discussing hot and cold spots, selection mosaics and trait remixing. There are some helpful figures, but the most helpful thing that came from this paper was my discussion with Peter about what a selection mosaic is (sill a bit confused on how it would look in life/ and in my simulation). Seems like it selection that carries, while having different rules in different areas. There are some papers that I might want to read from this paper.

Peter's Papers

Parallel Adaptation: One or Many Waves of Advance of an Advantageous Allele?

• This paper discusses how multiple adaptations move in space (has a picture that reminds me how of bread molds) and connects the idea of soft sweeps. It shows the math about the mutation densities, but keeps the wave speed constant. I really like the simulation figures and the description of what happens when the mutation waves meet.

The Role of Standing Variation in Geographic Convergent Adaptation*

• This is sort-of a follow up pater to parallel adaption (which I accidentally read first...). This paper talks about how there can be different responses to shares selection papers and what happens when those responses meet up. They explored how some alleles have a negative pleiotropic effect and what the consequences of that effect are. They then look at how their results compare to malaria, this might be a helpful example of how to relate simulation work to real examples.

Papers:

An individual-based model for the eco-evolutionary emergence of bipartite interaction networks

• Authors did individual-based simulations of mutualist and antagonist interactions, and found that these interactions have an effect on diversity, network structure and phylogenetic signal. Antagonist interactions increase diversity, decreased nestedness (specialist species working with general species) and had an increase in Phylogenetic signal (similar divergence branches in co-evolving species). Mutualist interactions had decreased diversity, increase nestedness and a decrease in phylogenetic signal (because they have some species that interact with many other species). Really cool experiment that can be improved on (like having changing population size and more geographical processes and simultaneous effects of different interaction types).

Variation in infectivity and aggressiveness in space and time in wild host–pathogen systems: causes and consequences

• A review paper that discussed different levels of infectivity/aggressiveness across space (more like it exists in different capacities), and how it might maintained. This review article brings up 2 main factors that might contribute to maintaining diversity: directional arms race dynamics (ARD) and fluctuating selection dynamics (FSD) (which are the poles). In systems its probably a cycle that uses both ARD and FSD and something in-between to generate, maintain, decrease genetic diversity. What happens to initiate this process?

Coevolution in multidimensional trait space favours escape from parasites and pathogens

• This paper discusses how hosts in host-pathogen interactions can/does compete (and win) in an evolutionary contest. The host most likely has an easier time because the pathogen has to overcome quite a few host defense systems. This paper introduces a new idea Kirkpatrick’s concept of maximum evolvability, which was not really explained here... There were some interesting ideas presented in this paper about the number of traits and their likelihood to leading to a win for the host (more traits = victims win). Ideas to further think about difference traits vs matching traits or something in-between. What does highly dimensional trait space mean?

Parasite local adaptation: Red Queen versus Suicide King

• This review paper discussed the similarities and differences between red queen and suicide king while defining infectivity (how well something is able to infect) and virulence (host damage/ death). This paper highlighted the need to study spacial variance while giving examples of recent experiments. Also discussed local adaptation & maladaptation. Idea of looking at dengue/yellow fever? in Nepal

POLYGENIC TRAITS AND PARASITE LOCAL ADAPTATION

• Mathematical modeling paper that had simulations that were confusing. Had really good references link placed under more coevolution paper suggestions. New phrase to look more into: the geographic mosaic theory of coevolution

Multiple reciprocal adaptations and rapid genetic change upon experimental coevolution of an animal host and its microbial parasite

• Ran a coevolution experiment between a TB (parasitic microbe) and a host C.elegans and found that there is reciprocal adaptation within 48 generations. There were some strange figures and story telling, but it was a fun paper to read and think about how I would simulate. What were the levels of diversity between BT within its host and then between hosts?

A Call to Arms: Coevolution of Animal Viruses and Host Innate Immune Responses

• Discusses a molecular arms race involving the innate immune response and RNAi pathway.

Host-pathogen coevolution increases genetic variation in susceptibility to infection

• This paper was presented in journal club! I thought it was going to be a coevolution experiment where they were letting flies and the pathogen coevolve then test diversity, but it was more about looking at genetic variation of a species that has been known as coevolved. They found that that flies that had coevolved with their viruses had more variation in their susceptibility. They also looked at the genetic architecture and found more major effect genes.

The phage-host arms race: Shaping the evolution of microbes

• Phage and bacteria interactions, both red queen and arms race, and the impacts of these interactions on a global scale. Review on the three main types of defense that bacteria have against phages.

Rules of Engagement: Molecular Insights from Host-Virus Arms Races

• Review on a molecular arms race/red queen dynamics between host and viruses with specific examples about protein evolution (proteins that involve the host and the virus). Lots of explanatory figures

Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales

The arms race between bacteria and their phage foes

Unifying the Epidemiological and Evolutionary Dynamics of Pathogens

Virus wars: using one virus to block the spread of another

• Examined the interactions of two viruses in E.coli, where one virus (virus 1) prevented a more deadly virus from infecting the host. Here they developed a mathematical model, ran simulations, and gathered empirical data. They were able to predict dynamics with the model/simulations, however there were differences most likely due to host susceptibility to the viruses (‘phenotypic resistance’).

Biological and Biomedical Implications of the Co-Evolution of Pathogens and Their Hosts

• Review that discusses the evidence of co-evolution in host-pathogen systems. Give solid definitions and examples of the nature, evidence, molecular basis, complications, and future of co-evolution.

The evolution within us

• Review of B-cell adaptations (based on contrasting methods to explain B-cell patterns). There is a potential for B-cells to be co-evolving with pathogens/vaccines maybe? More adaptive immune response. There is a box of interesting pop-gen questions/directions

THE EVOLUTIONARY INTERACTION AMONG SPECIES: Selection, Escalation, and Coevolution

• This paper is a review that focuses on trying to tell the difference between coevolution and escalation. I always thought they there could be coevolution escalation. This review talked about the different models of the time and how they mostly focus on population dynamics and less on the interaction itself. The author gave great coevolution examples that might be helpful to think about after the newts and snakes. After reading this paper what is the difference between escalation and coevolution selection?

Toward a more trait-centered approach to diffuse (co)evolution

• Diffuse evolution relies on selection pressure caused by the presence or absence of a species. This review paper gave examples of traits that changed with the absence/presence of species while discussing that fitness measurements alone do not explain evolution. Defined rules for when diffuse evolution occurs.

Phylodynamic Model Adequacy Using Posterior Predictive Simulations

• Authors were trying out a new package for BEAST2 that allows users to asses phylodynamic models. They used this package to pick a model that better described the viral outbreak (Ebola and H1N1).

Can there be an escalating arms race without coevolution?

• Is it really coevolution when you pick a trait that is based on nutrient intake? Paper warns about correlation on a trait that is not caused by coevolution. This paper discusses how past selection in the ancestral species is reflected by current phenotypic plasticity.

SPEED OF ADAPTATION AND GENOMIC FOOTPRINTS OF HOST–PARASITE COEVOLUTION UNDER ARMS RACE AND TRENCH WARFARE DYNAMICS

• Gave clear examples of trench warfare/ red queen (creates balancing selection) and arms race (selective sweeps) and how the genomic footprints differ between pathogen and host. They used the GFG model (constant population size), compared different life cycles of parasite (monocyclic/polycyclic), and found that different parameters create regions/ patterns of selection that would fall into balancing selection or selective sweeps.

Evolutionary conflicts between viruses and restriction factors shape immunity

• This paper discussed how a host innate immune system uses restriction factors that protects host against ancient viruses (do to viruses evolution rate). It gave several good reasons for why the host is able to "catch up or beat" emerging viruses i.e. virus genome size, host heterozygosity.

Evolution and coevolution in mutualistic networks

• The authors of this article examined how mutualistic networks influence coevolution. They found that not all species are equal in driving evolution, super-generalists (species that interact with many other species) can quickly change an ecosystem. Gave an interesting example of when pairwise and cascading effects are caused by coevolution/ indirect coevolution fig. 1.

Viral phylodynamics and the search for an ‘effective number of infections’

• Good paper describing many different mathematical epidemiological models. The paper also discusses how the shape of phylogenetic trees can be used to infer population dynamics. EM

MHC polymorphism under host-pathogen coevolution

• Authors ran computer simulations to explain why there is a large amount of polymorphism in major histocompatibility (MHC) molecules (from host-pathogen interactions, many viruses). Heterozygote advantage vs coevolution. Really detailed simulation with many references (add to list) and did mention that results would vary on the model used. Results compare alley frequency to fitness to determine that coevolution creates a large enough amount of polymorphism to account for the level of polymorphism we see today.

Local adaptation and the geometry of host–parasite coevolutio

• A deterministic model was used to explore levels of local adaptation caused by (1) host migration rate, (2) parasite migration rate, (3) parasite specificity and (4) parasite virulence. Less migration host/ parasite = more local adaptation, there are sales where both host and parasites migration rates are the same = less local adaptation. For parasite specificity/virulence local adaptation depends on migration rates, both increase when pathogen migration > host; when pathogen migration = host, as virulence increases local adaptation goes up then down while specificity increases local adaptation goes down then up; when pathogen migration < host parity local adaptation goes down. Really cool spacial distribution figures

When Is Correlation Coevolution?

• This paper explores the relationship between coevolution and correlation, there can be coevolution selection without correlation and vice versa. This paper talks about the geographic mosaic theory ("reciprocal selection should lead to significantly correlated traits in only a subset of coevolutionary interactions") and many examples of when it can be proven and what kind of evidence it would take. There a a few areas that discuss host-pathogen interactions that might be useful.

Co-evolution of Pursuit and Evasion II: Simulation Methods and Results

• In this paper they did an interesting prey/predator cognitive motor skills simulation, where prey ran away from predator and predator chased and could collide with prey. There were many parameters & equations (for physical dynamics) that they tested and many different steps that they had to go through to get the simulation in a place where there would be no obvious winner (figure 1). They explored the evolution of sensory-motor morphologies as well as data traces (things like distance, target bearing, velocity, and energy of prey & predator). Fun fact: they made these models into little movies and proposed applications in entertainment industry.

Viral Phylodynamics

• This paper was fun. It talked about how viral phylogenies are shapes. It mainly compared influenza to HIV, but also noted that it could work on DNA viruses. Authors of this paper highlighted some of the dynamics that can be studied using virus phylogenies, and the different simulation models that are currently used to describe them (i.e compartmental: SIR, and forward simulation model) However, it also talked about simulation difficulties. This paper had some other paper I would like to look into and made me think about how to apply these thing to a co-evolving situation.

Phylodynamics of Infectious Disease Epidemics

• This paper connected compartmental epidemic equations (i.e. SIR) to coalescent models. The authors of this paper outlined methods for modeling disease epidemic from viral sequences ("can be used to estimate epidemiological and demographic parameters directly from viral sequence data.") They do state that more can be added to these equations (might be difficult) to make the model better. Downside of this model is that you need to know a lot about the epidemic. -this might be really useful when using covid data, if there was metadata...

Coevolution spreading in complex networks

• This is a physics paper that discusses complex networks. It contains a lot of math that I don't understand, but the ideas about complex networks are cool.

*Detecting the macroevolutionary signal of species interactions

*Phylodynamics of Infectious Disease Epidemics

Statistical properties of polymorphism in host-parasite genetics

• paper about polymorphisms with strange looking statistical data and interesting time lag data. It would be interesting to look into the different levels of diversity between the populations when models have selection, mutation & drift or just under a neutral model. How is polymorphism measured? in a real population or a simulated one?

other papers about modeling and simulations that might be worth looking in to *Apanius et al. 1997

*Holland 1975

*Borghans and De Boer 2001

*Beltman et al. 2002

*Kast et al. 1994

*Frank 1991a, 1991b, 1997

*Gandon et al. 1996

*Lively 1999

Hamilton 1980; Hamilton et al. 1990; Gandon et al. 1998). Haraguchi & Sasaki (1996)

Interesting Places to find more readings: https://mast.queensu.ca/~tday/pub.html

Cool Ideas found in this review: https://www.sciencedirect.com/science/article/pii/S0370157319302583

modeling paper about population structure M. Dickison, S. Havlin, H.E. Stanley, Epidemics on interconnected networks, Phys. Rev. E 85 (2012) 066109.

paper is a recent coevolution experiment https://www.pnas.org/content/pnas/116/3/923.full.pdf

• highlights that qtr are not studied -> referenced this paper https://esj-journals.onlinelibrary.wiley.com/doi/pdf/10.1002/1438-390X.12022

https://www.sciencedirect.com/science/article/pii/S016953472030029X

Ethics:

Addressing selective reporting of experiments through predefined exclusion criteria

• We read and discussed this paper in journal club. We talked about hypothesis testing (also discussed p-hacking) and how it compares to exploratory experiments, which is weird to set a criteria on experiments that you don't really know the answers to. It is a good idea to write down some expectations before running the experiment. I wish there were ethics papers on computation/simulation research.