Biology subjects

Ohtsuki, H.

Publications and source records attributed to Ohtsuki, H..

4 recordsLinked to original sources

bioRxiv2026

The evolution of family reputation extends indirect reciprocity

Reputation plays a major role in supporting cooperation among unrelated individuals through indirect reciprocity. By helping others, individuals build a good personal reputation and receive greater benefits from future partners. Most models of indirect reciprocity assume that a person's reputation reflects only their own behaviour. Yet in many societies, people are also judged by their family's reputation. How family reputation affects the evolution of cooperation, and whether reliance on it can itself evolve, remain unclear. Here we show that reputation inheritance expands the conditions under which indirect reciprocity favours cooperation, increasing helping and favouring greater reciprocity. Greater reciprocity in turn favours stronger reliance on inherited reputation, creating a positive feedback that stabilises cooperation, especially when interactions are infrequent or personal behaviour is difficult to observe. This feedback arises because cooperation generates future benefits both for the individual, through their personal reputation, and for their descendants, through inherited reputation. Reputation inheritance thereby provides a route via which kin selection and reciprocity, often treated as alternative explanations for cooperation, can reinforce one another. Our model helps explain why family-based reputation occurs across diverse human societies and provides an evolutionary framework for studying phenomena organised around family standing, including kin-based institutions, feuds between families and honour-based violence within them.

evolutionary biology↗

bioRxiv2020

Evolutionary feedbacks between genes and their extended effects under limited gene flow and biased ecological inheritance

Organisms continuously modify their living conditions via extended genetic effects on their envi-ronment, microbiome, and in some species culture. These effects can impact the fitness of current but also future conspecifics due to non-genetic transmission via ecological or cultural inheritance. In this case, selection on a gene with extended effects depends on the degree to which current and future genetic relatives are exposed to modified conditions. Here, we detail the selection gradient on a quantitative trait with extended effects in a patch-structured population, when gene flow between patches is limited and ecological inheritance within patches can be biased towards offspring. Such a situation is relevant to understand evolutionary driven changes in individual condition that can be preferentially transmitted from parent to offspring, such as cellular state, micro-environments (e.g., nests), pathogens, microbiome, or culture. Our analysis quantifies how the interaction between limited gene flow and biased ecological inheritance influences the joint evolutionary dynamics of traits together with the conditions they modify, helping understand adaptation via non-genetic modifications. As an illustration, we apply our analysis to a gene-culture coevolution scenario in which genetically-determined learning strategies coevolve with adaptive knowledge. In particular, we show that when social learning is synergistic, selection can favour strategies that generate remarkable levels of knowledge under intermediate levels of both vertical cultural transmission and limited dispersal. More broadly, our theory yields insights into the interplay between genetic and non-genetic inheritance, with implications for how organisms evolve to transform their environments.

evolutionary biology↗

bioRxiv2020

The components of directional and disruptive selection in heterogeneous group-structured populations

We derive how directional and disruptive selection operate on scalar traits in a heterogeneous group-structured population for a general class of models. In particular, we assume that each group in the population can be in one of a finite number of states, where states can affect group size and/or other environmental variables, at a given time. Using up to second-order perturbation expansions of the invasion fitness of a mutant allele, we derive expressions for the directional and disruptive selection coefficients, which are sufficient to classify the singular strategies of adaptive dynamics. These expressions include first- and second-order perturbations of individual fitness (expected number of settled offspring produced by an individual, possibly including self through survival); the first-order perturbation of the stationary distribution of mutants (derived here explicitly for the first time); the first-order perturbation of pairwise relatedness; and reproductive values, pairwise and three-way relatedness, and stationary distribution of mutants, each evaluated under neutrality. We introduce the concept of individual k-fitness (defined as the expected number of settled offspring of an individual for which k - 1 randomly chosen neighbors are lineage members) and show its usefulness for calculating relatedness and its perturbation. We then demonstrate that the directional and disruptive selection coefficients can be expressed in terms individual k-fitnesses with k = 1, 2, 3 only. This representation has two important benefits. First, it allows for a significant reduction in the dimensions of the system of equations describing the mutant dynamics that needs to be solved to evaluate explicitly the two selection coefficients. Second, it leads to a biologically meaningful interpretation of their components. As an application of our methodology, we analyze directional and disruptive selection in a lottery model with either hard or soft selection and show that many previous results about selection in group-structured populations can be reproduced as special cases of our model.

evolutionary biology↗

bioRxiv2017

Allele Frequency Spectrum in a Cancer Cell Population

A cancer grows from a single cell, thereby constituting a large cell population. In this work, we are interested in how mutations accumulate in a cancer cell population. We provided a theoretical framework of the stochastic process in a cancer cell population and obtained near exact expressions of allele frequency spectrum or AFS (only continuous approximation is involved) from both forward and backward treatments under a simple setting; all cells undergo cell division and die at constant rates, b and d, respectively, such that the entire population grows exponentially. This setting means that once a parental cancer cell is established, in the following growth phase, all mutations are assumed to have no effect on b or d (i.e., neutral or passengers). Our theoretical results show that the difference from organismal population genetics is mainly in the coalescent time scale, and the mutation rate is defined per cell division, not per time unit (e.g., generation). Except for these two factors, the basic logic are very similar between organismal and cancer population genetics, indicating that a number of well established theories of organismal population genetics could be translated to cancer population genetics with simple modifications.

cancer biology↗