A tér és időbeli heterogenitás szerepe az együttműködés ökológiájában és evolúciójában = The role of environmental heterogeneity in the ecology and evolution of co-operation

Megmutattam, hogy a heterogén forráseloszlás elősegítheti az együttműködés kialakulását. A biológiailag releváns aszinkron döntési szituációban, hótorlasz játékban akkor várhatunk teljes együttműködést, ha strukturált populációban az együttműködés szinergisztikus hatása elég nagy. Dinamikus gráfokon az együttműködés megtelepedésének valószínűsége kisebb, mint statikus gráfokon. A skálafüggetlen gráf tudja a legjobban pufferelni a változás hatását. A szelektív partnerválasztás/kapcsolat megszakítás lehetősége jelentősen növelheti az együttműködés megtelepedésének valószínűségét. Valós RNS enzimek mutagenezis kísérletei alapján készített rátermettségtérkép alapján a fenotipikus hibaküszöb egy nagyságrenddel megengedőbb, mint a genotipikus hibaköszöb. Ez egy jelentős előrelépés az Eigen paradoxon megoldásában. Kimutattuk, hogy metabolikus replikátorok vannak az élőlények metabolizmusában. Az ATP előállítás univerzálisan autokatailitusnak bizonyult. Egyes szervezetekben a NAD, CoA, THF, kinonok és cukrok előállítása is autokatalitikus. A kodon középső betűje szerint csoportosulnak a katalitikusan fontosabb - kevésbé fontos aminosavak. A legfontosabb katalitikus aminosavak (hisztidin, aszparaginsav, glutaminsav) kodonjának közepén adenin van. Megmutattuk, hogy a klonális növények térbeli munkamegosztása előnyös időben állandó vagy nem túlságosan változó környezetben. | We have shown that heterogeneous resource distribution can facilitate cooperation. We expect full cooperation with the biologically relevant asynchronous decision in the Snowdrift game if the population is structured and the synergistic effect of cooperation is high. The fixation probability of cooperation on dynamical graphs is lower than on static graphs. Scale free graphs can buffer the effect of changing interactions the most. Selective partner choice and link abortion can greatly enhance the evolution of cooperation. We have constructed a fitness landscape based on mutagenesis data of real ribozymes. The estimated phenotypic error threshold is one magnitude better than the genotypic one. This is a big leap forward in solving the Eigen's Paradox. We have identified metabolic replicators in the metabolism of organism. It seems that ATP is universally produced in an autocatalytic manner. In certain organisms the production of NAD, CoA, THF, quinines and sugars can also be autocatalytic. The catalytically more important amino acids (histidine, aspartic acid, glutamic acid) share the same middle codon: adenine. The genetic code is structured (among others) by the catalytic propensities of the coded amino acids. We have shown that spatial division of labour in clonal plants is advantageous in stable or not too fluctuating environments

Is there still evolution in the human population?

It is often claimed that humanity has stopped evolving because modern medicine erased all selection on survival. Even if that would be true, and it is not, there would be other mechanisms of evolution which could still led to changes in allelic frequencies. Here I show, by applying basic evolutionary genetics knowledge, that we expect humanity to evolve. The results from genome sequencing projects have repeatedly affirmed that there are still recent signs of selection in our genomes. I give some examples of such adaptation. Then I briefly discuss what our evolutionary future has in store for us. © 2023, The Author(s)

A Confidence-Based Approach for Balancing Fairness and Accuracy

We study three classical machine learning algorithms in the context of algorithmic fairness: adaptive boosting, support vector machines, and logistic regression. Our goal is to maintain the high accuracy of these learning algorithms while reducing the degree to which they discriminate against individuals because of their membership in a protected group. Our first contribution is a method for achieving fairness by shifting the decision boundary for the protected group. The method is based on the theory of margins for boosting. Our method performs comparably to or outperforms previous algorithms in the fairness literature in terms of accuracy and low discrimination, while simultaneously allowing for a fast and transparent quantification of the trade-off between bias and error. Our second contribution addresses the shortcomings of the bias-error trade-off studied in most of the algorithmic fairness literature. We demonstrate that even hopelessly naive modifications of a biased algorithm, which cannot be reasonably said to be fair, can still achieve low bias and high accuracy. To help to distinguish between these naive algorithms and more sensible algorithms we propose a new measure of fairness, called resilience to random bias (RRB). We demonstrate that RRB distinguishes well between our naive and sensible fairness algorithms. RRB together with bias and accuracy provides a more complete picture of the fairness of an algorithm

Resource heterogeneity can facilitate cooperation

Although social structure is known to promote cooperation, by locally exposing selfish agents to their own deeds, studies to date assumed that all agents have access to the same level of resources. This is clearly unrealistic. Here we find that cooperation can be maintained when some agents have access to more resources than others. Cooperation can then emerge even in populations in which the temptation to defect is so strong that players would act fully selfishly if their resources were distributed uniformly. Resource heterogeneity can thus be crucial for the emergence and maintenance of cooperation. We also show that resource heterogeneity can hinder cooperation once the temptation to defect is significantly lowered. In all cases, the level of cooperation can be maximized by managing resource heterogeneity

The evolution of the genetic code: Impasses and challenges

The origin of the genetic code and translation is a “notoriously difficult problem”. In this survey we present a list of questions that a full theory of the genetic code needs to answer. We assess the leading hypotheses according to these criteria. The stereochemical, the coding coenzyme handle, the coevolution, the four-column theory, the error minimization and the frozen accident hypotheses are discussed. The integration of these hypotheses can account for the origin of the genetic code. But experiments are badly needed. Thus we suggest a host of experiments that could (in)validate some of the models. We focus especially on the coding coenzyme handle hypothesis (CCH). The CCH suggests that amino acids attached to RNA handles enhanced catalytic activities of ribozymes. Alternatively, amino acids without handles or with a handle consisting of a single adenine, like in contemporary coenzymes could have been employed. All three scenarios can be tested in in vitro compartmentalized systems

Intermediate landscape disturbance maximizes metapopulation density

The viability of metapopulations in fragmented landscapes has become a central theme in conservation biology. Landscape fragmentation is increasingly recognized as a dynamical process: in many situations, the quality of local habitats must be expected to undergo continual changes. Here we assess the implications of such recurrent local disturbances for the equilibrium density of metapopulations. Using a spatially explicit lattice model in which the considered metapopulation as well as the underlying landscape pattern change dynamically, we show that equilibrium metapopulation density is maximized at intermediate frequencies of local landscape disturbance. On both sides around this maximum, the metapopulation may go extinct. We show how the position and shape of the intermediate viability maximum is responding to changes in the landscape’s overall habitat quality and the population’s propensity for local extinction. We interpret our findings in terms of a dual effect of intensified landscape disturbances, which on the one hand exterminate local populations and on the other hand enhance a metapopulation’s capacity for spreading between habitat clusters

Local Neutral Networks Help Maintain Inaccurately Replicating Ribozymes

The error threshold of replication limits the selectively maintainable genome size against recurrent deleterious mutations for most fitness landscapes. In the context of RNA replication a distinction between the genotypic and the phenotypic error threshold has been made; where the latter concerns the maintenance of secondary structure rather than sequence. RNA secondary structure is treated as a proxy for function. The phenotypic error threshold allows higher per digit mutation rates than its genotypic counterpart, and is known to increase with the frequency of neutral mutations in sequence space. Here we show that the degree of neutrality, i.e. the frequency of nearest-neighbour (one-step) neutral mutants is a remarkably accurate proxy for the overall frequency of such mutants in an experimentally verifiable formula for the phenotypic error threshold; this we achieve by the full numerical solution for the concentration of all sequences in mutation-selection balance up to length 16. We reinforce our previous result that currently known ribozymes could be selectively maintained by the accuracy known from the best available polymerase ribozymes. Furthermore, we show that in silico stabilizing selection can increase the mutational robustness of ribozymes due to the fact that they were produced by artificial directional selection in the first place. Our finding offers a better understanding of the error threshold and provides further insight into the plausibility of an ancient RNA world

Local Neutral Networks Help Maintain Inaccurately Replicating Ribozymes

The error threshold of replication limits the selectively maintainable genome size against recurrent deleterious mutations for most fitness landscapes. In the context of RNA replication a distinction between the genotypic and the phenotypic error threshold has been made; where the latter concerns the maintenance of secondary structure rather than sequence. RNA secondary structure is treated as a proxy for function. The phenotypic error threshold allows higher per digit mutation rates than its genotypic counterpart, and is known to increase with the frequency of neutral mutations in sequence space. Here we show that the degree of neutrality, i.e. the frequency of nearest-neighbour (one-step) neutral mutants is a remarkably accurate proxy for the overall frequency of such mutants in an experimentally verifiable formula for the phenotypic error threshold; this we achieve by the full numerical solution for the concentration of all sequences in mutation-selection balance up to length 16. We reinforce our previous result that currently known ribozymes could be selectively maintained by the accuracy known from the best available polymerase ribozymes. Furthermore, we show that in silico stabilizing selection can increase the mutational robustness of ribozymes due to the fact that they were produced by artificial directional selection in the first place. Our finding offers a better understanding of the error threshold and provides further insight into the plausibility of an ancient RNA world