Requirements for the evolution of evolvability

We have aready discussed how selection can bias variation to be more advantageous, but what are the the requirements for this to happen?
This paper from our colleagues at Southampton models gene regulatory network evolution to address which factors allow the generation of phenotypic variation "tailored" to environmental variation.

10:00 in Darwin's, with fika.

Paper available here

Abstract

One of the most intriguing questions in evolution is how organisms exhibit suitable pheno- typic variation to rapidly adapt in novel selective environments. Such variability is crucial for evolvability, but poorly understood. In particular, how can natural selection favour develop- mental organisations that facilitate adaptive evolution in previously unseen environments? Such a capacity suggests foresight that is incompatible with the short-sighted concept of natural selection. A potential resolution is provided by the idea that evolution may discover and exploit information not only about the particular phenotypes selected in the past, but their underlying structural regularities: new phenotypes, with the same underlying regulari- ties, but novel particulars, may then be useful in new environments. If true, we still need to understand the conditions in which natural selection will discover such deep regularities rather than exploiting ‘quick fixes’ (i.e., fixes that provide adaptive phenotypes in the short term, but limit future evolvability). Here we argue that the ability of evolution to discover such regularities is formally analogous to learning principles, familiar in humans and machines, that enable generalisation from past experience. Conversely, natural selection that fails to enhance evolvability is directly analogous to the learning problem of over-fitting and the sub- sequent failure to generalise.Wesupport the conclusion that evolving systems and learning systems are different instantiations of the same algorithmic principles by showing that exist- ing results from the learning domain can be transferred to the evolution domain. Specifically, we show that conditions that alleviate over-fitting in learning systems successfully predict which biological conditions (e.g., environmental variation, regularity, noise or a pressure for developmental simplicity) enhance evolvability. This equivalence provides access to a well- developed theoretical framework from learning theory that enables a characterisation of the general conditions for the evolution of evolvability.

On the non-random effects of random mutation

The idea that evolution produces (developmental) genetic architectures that make the effects of mutations biased towards particular phenotypes have come up a few times in recent discussions. Next week we will look a little closer at one of the models that have been used to explore the how and why of this problem.

10.00 in Darwin. Fika and entertainment provided.

 You can find the paper here

Epistasis and natural selection shape the mutational architecture of complex traits

Adam G Jones, Reinhard Burger & Stevan Arnold

The evolutionary trajectories of complex traits are constrained by levels of genetic variation as well as genetic correlations among traits. As the ultimate source of all genetic variation is mutation, the distribution of mutations entering populations profoundly affects standing variation and genetic correlations. Here we use an individual-based simulation model to investigate how natural selection and gene interactions (that is, epistasis) shape the evolution of mutational processes affecting complex traits. We find that the presence of epistasis allows natural selection to mould the distribution of mutations, such that mutational effects align with the selection surface. Consequently, novel mutations tend to be more compatible with the current forces of selection acting on the population. These results suggest that in many cases mutational effects should be seen as an outcome of natural selection rather than as an unbiased source of genetic variation that is independent of other evolutionary processes.

Sex difference in lifespan and sexual conflict

For the next week's lab meeting, I would like to use this Drosophila paper as a case, to discuss  the evolution of sexual dimorphism in lifespan. 

Hope to hear your thoughts over fika!

Photo by Qinyang Li

Manipulation of feeding regime alters sexual dimorphism for lifespan and reduces sexual conflict in Drosophila melanogaster

24.04.2017, 15:58 byElizabeth M. L. DuxburyWayne G. RostantTracey Chapman

Sexual dimorphism for lifespan (SDL) is widespread, but poorly understood. A leading hypothesis, which we test here, is that strong SDL can reduce sexual conflict, by allowing each sex to maximize its sex-specific fitness. We used replicated experimental evolution lines of the fruit fly, Drosophila melanogaster, which had been maintained for over 360 generations on either unpredictable ‘Random’ or predictable ‘Regular’ feeding regimes. This evolutionary manipulation of feeding regime led to robust, enhanced SDL in Random over control, Regular lines. Enhanced SDL was associated with a significant increase in the fitness of focal males, tested with wild-type (WT) females. This was due to sex-specific changes to male life history, manifested as increased early reproductive output and reduced survival. In contrast, focal female fitness, tested with WT males, did not differ across regimes. Hence increased SDL was associated with a reduction in sexual conflict, which increased male fitness and maintained fitness in females. Differences in SDL were not associated with developmental time or developmental survival. Overall, the results showed that the expression of enhanced SDL, resulting from experimental evolution of feeding regimes, was associated with male-specific changes in life history, leading to increased fitness and reduced sexual conflict.

One gene to rule them all (in a phylogeny)?

To what extent can one gene (or a handful of them) affect a phylogeny? This paper suggest that even in very large data matrices the resolution of some branches can rely on tiny subsets of data. They show this to be the case in several contentious nodes of plant, animal and fungi data matrices and suggest a framework for quantifying the phylogenetic signal in such difficult cases. 

They also think that humans are more closely related to sponges than ctenophores, which is cool. 

Darwin, 9th of May, 10.00. Blueberry pie to compensate the phylogeny topic.

Contentious relationships in phylogenomic studies can be driven by a handful of genes

Xing-Xing Shen, Chris Todd Hittinger & Antonis Rokas

Phylogenomic studies have resolved countless branches of the tree of life, but remain strongly contradictory on certain, contentious relationships. Here, we use a maximum likelihood framework to quantify the distribution of phylogenetic signal among genes and sites for 17 contentious branches and 6 well-established control branches in plant, animal and fungal phylogenomic data matrices. We find that resolution in some of these 17 branches rests on a single gene or a few sites, and that removal of a single gene in concatenation analyses or a single site from every gene in coalescence-based analyses diminishes support and can alter the inferred topology. These results suggest that tiny subsets of very large data matrices drive the resolution of specific internodes, providing a dissection of the distribution of support and observed incongruence in phylogenomic analyses. We submit that quantifying the distribution of phylogenetic signal in phylogenomic data is essential for evaluating whether branches, especially contentious ones, are truly resolved. Finally, we offer one detailed example of such an evaluation for the controversy regarding the earliest-branching metazoan phylum, for which examination of the distributions of gene-wise and site-wise phylogenetic signal across eight data matrices consistently supports ctenophores as the sister group to all other metazoans.

A plastic Daphnia stuck in the G matrix...

Heja!

Paper for next Tuesday:

The alignment between phenotypic plasticity, the major axis of genetic variation and the response to selection
Martin I. Lind, Kylie Yarlett, Julia Reger, Mauricio J. Carter and Andrew P. Beckerman
Proc. R. Soc. B 282: 20151651.
Link to paper




Abstract:
Phenotypic plasticity is the ability of a genotype to produce more than one phenotype in order to match the environment. Recent theory proposes that the major axis of genetic variation in a phenotypically plastic population can align with the direction of selection. Therefore, theory predicts that plasticity directly aids adaptation by increasing genetic variation in the direction favoured by selection and reflected in plasticity. We evaluated this theory in the freshwater crustaceanDaphnia pulex, facingpredation risk fromtwo contrasting size-selective predators. We estimated plasticity in several life-history traits, the G matrix of these traits, the selection gradients on reproduction and survival, and the predicted responses to selection. Using these data, we tested whether the genetic lines of least resistance and the predicted response to selection alignedwith plasticity. We found predator environment-specific G matrices, but shared genetic architecture across environments resulted in more constraint in the G matrix than in the plasticity of the traits, sometimes preventing alignment of the two. However, as the importance of survival selection increased, the difference between environments in their predicted response to selection increased and resulted in closer alignment between the plasticity and the predicted selection response. Therefore, plasticity may indeed aid adaptation to new environments.

Where?   Darwin
When?    May 2, 10.00 am

There will be fika, of course.

Epistasis and pleiotropy affecting modularity

Recently we have discussed modularity a few times. For those who can't get enough of it: here is another paper. For those who are starting to get fed up with it: focus on the cool results and the methods we animal ecologist can only dream of.

Fika will be provided.
Tuesday, April 25, 10.00 in Darwin.

Epistasis and Pleiotropy Affect the Modularity of the Genotype–Phenotype Map of Cross-Resistance in HIV-1

Robert Polster  Christos J. Petropoulos  Sebastian Bonhoeffer  Frédéric Guillaume
Mol Biol Evol (2016) 33 (12): 3213-3225

DOI: https://doi.org/10.1093/molbev/msw206

Abstract

The genotype–phenotype (GP) map is a central concept in evolutionary biology as it describes the mapping of molecular genetic variation onto phenotypic trait variation. Our understanding of that mapping remains partial, especially when trying to link functional clustering of pleiotropic gene effects with patterns of phenotypic trait co-variation. Only on rare occasions have studies been able to fully explore that link and tend to show poor correspondence between modular structures within the GP map and among phenotypes. By dissecting the structure of the GP map of the replicative capacity of HIV-1 in 15 drug environments, we provide a detailed view of that mapping from mutational pleiotropic variation to phenotypic co-variation, including epistatic effects of a set of amino-acid substitutions in the reverse transcriptase and protease genes. We show that epistasis increases the pleiotropic degree of single mutations and provides modularity to the GP map of drug resistance in HIV-1. Moreover, modules of epistatic pleiotropic effects within the GP map match the phenotypic modules of correlated replicative capacity among drug classes. Epistasis thus increases the evolvability of cross-resistance in HIV by providing more drug- and class-specific pleiotropic profiles to the main effects of the mutations. We discuss the implications for the evolution of cross-resistance in HIV.

Guest seminar by Thomas Madsen

Some of you might have heard about Sweden's southernmost adder population in Smygehuk and the spectacular rescue action in the 90s that even made it into Nature. The man behind the story, Thomas Madsen from Deakin University, AU, is currently visiting Sweden to continue his work on this snake population (they are still going strong!).
Before he disappears back to Australia again, he'll give a seminar at our EXEB meeting on Tuesday, April 18th. While his research interest has recently branched out to cancer in the Tasmanian devil (see e.g. here and here), he'll tell us about predator-prey dynamics between snakes and rats!

Floods and famine: climate-induced collapse of a tropical predator-prey community

Beata Ujvari and Thomas Madsen

Summary

1.     Will climate change threaten wildlife populations by gradual shifts in mean conditions, or by increased frequency of extreme weather events? 

2.     Based on long-term data (from 1991 to 2014), the aim of the present study was to analyze and compare the sensitivity of predator-prey demography to extreme climatic events versus normal, albeit highly variable, annual deviations in climatic conditions in the Australian wet-dry tropics. 

3.     From 1991 to 2005, predators (water pythons, Liasis fuscus) and their main prey (dusky rats, Rattus colletti) showed significant climate-driven fluctuations in numbers. 

4.     These fluctuations were, however, trivial compared to the impact of two massive but brief deluges in 2007 and 2011, which virtually eliminated the dusky rats.  The two floods resulted in the pythons experiencing an unprecedented famine in 7 out of the last 8 years causing a massive shift in python demography i.e. a significant reduction in feeding rates, reproductive output, growth rates, relative body mass, survival, mean body length and numbers (from 3173 in 1992 to 96 in 2013). 

5.     Our results demonstrate that attempts to predict faunal responses to climate change, even if based on long-term studies, may be doomed to failure.  Consequently, biologists may need to confront the uncomfortable truth that increased frequency of brief unpredictable bouts of extreme weather can influence populations far more than gradual deviations in mean climatic conditions.

There will be fika!

Time: Tuesday, April 18, 10.00

Locale: "Darwin", 2nd floor (Ecology Building)