Biology subjects

Carvajal-Rodriguez, A.

Publications and source records attributed to Carvajal-Rodriguez, A..

11 recordsLinked to original sources

bioRxiv2025

KLinterSel: Intersection among candidates of different selective sweep detection methods

Detecting signals of natural selection, including selective sweeps, in genomic data often involves applying several methods in parallel. Regions identified by multiple approaches are usually considered strong candidates, as agreement among methods is often taken as supporting evidence. However, the extent to which such overlaps exceed random expectations is rarely evaluated formally. When genomic elements are not independent, coincident candidate sites may arise from the underlying structure of the data rather than from genuine methodological concordance. To address this problem, we introduce two complementary statistical tests designed to evaluate whether the observed overlap among candidate sites detected by different methods exceeds what would be expected by chance. The first is a fast parametric test based on a sequentially conditioned hypergeometric framework that evaluates k-way intersections among candidate sets across genomic windows. The second relies on Monte Carlo simulations and compares the observed inter-method distance profiles with those expected under random association, taking into account the empirical distribution of SNPs along the genome. By capturing different aspects of concordance, these approaches allow agreement among methods to be assessed across multiple spatial scales. Both tests are implemented in the program KLinterSel, which also identifies clusters of candidate sites detected by different selection-detection methods within a user-defined distance threshold. We illustrate its application using candidate loci associated with resistance of the common cockle (Cerastoderma edule) to the parasite Marteilia cochillia. The software is written in Python and is available on GitHub together with documentation and precompiled executables for major operating systems.

genomics↗

bioRxiv2024

On non-random mating, adaptive evolution and information theory

Population genetics describes evolutionary processes, focusing on the variation within and between species and the forces shaping this diversity. Evolution reflects information accumulated in genomes, enhancing organisms adaptation to their environment. In this paper, we propose a model that begins with the distribution of matings based on mutual fitness and progresses to viable adult genotype distribution. At each stage the changes result in different measures of information. The evolutionary dynamics of each stage of the model correspond to aspects such as the type of mating, the distributions of genotypes within matings, and the distribution of genotypes and haplotypes in the next generation. Changes in these distributions are caused by variation in fitness and result in Jeffreys divergence values other than zero. As an example, a model of hybrid sterility is developed at a biallelic locus, comparing the information indices associated with each stage of the evolutionary process. In conclusion, the informational perspective seems to facilitate the connection of causes and effects and allows the development of statistics to contrast null models of zero information (random mating, no selection, etc.). The informational perspective could contribute to clarify, deepen and expand the mathematical foundations of evolutionary theory. SIMPLE SUMMARYThe evolutionary process can be seen as a process of acquisition, storage, and updating of information by a population about the environment in which it lives. In this paper I propose a model that starts with the distribution of matings that occur according to mutual mating fitness and ends with the distribution of viable adult genotypes obtained after these matings. The result of the evolutionary dynamics associated with each stage of the model can be described in terms of information. This informational description facilitates the connection between causes and effects, as well as the development of statistics to test the null model of zero information, i.e. random mating and/or no effect of natural selection. Incorporating the informational perspective into the mathematical formalism of population genetics/genomics contributes to clarifying, expanding and deepening the mathematical description of evolutionary theory.

evolutionary biology↗

bioRxiv2024

iHDSel software: The Price equation and the population stability index to detect genomic patterns compatible with selective sweeps. An example with SARS-CoV-2.

A large number of methods have been developed and continue to be developed for detecting the signatures of selective sweeps in genomes. Significant advances have been made, including the combination of different statistical strategies and the incorporation of artificial intelligence (machine learning) methods. Despite these advances, several common problems persist, such as the unknown null distribution of the statistics used, necessitating simulations and resampling to assign significance to the statistics. Additionally, it is not always clear how deviations from the specific assumptions of each method might affect the results. In this work, allelic classes of haplotypes are used along with the informational interpretation of the Price equation to design a statistic with a known distribution that can detect genomic patterns caused by selective sweeps. The statistic consists of Jeffreys divergence, also known as the population stability index, applied to the distribution of allelic classes of haplotypes in two samples. Results with simulated data show optimal performance of the statistic in detecting divergent selection. Analysis of real SARS-CoV-2 genome data also shows that some of the sites playing key roles in the viruss fitness and immune escape capability are detected by the method. The new statistic, called JHAC, is incorporated into the iHDSel (informed HacDivSel) software available at https://acraaj.webs.uvigo.es/iHDSel.html.

evolutionary biology↗

bioRxiv2023

QInfoMating: Sexual selection and assortative mating estimation

BackgroundSexual selection theory is a multifaceted area of evolutionary research that has profound implications across various disciplines, including population genetics, evolutionary ecology, animal behavior, sociology, and psychology. It explores the mechanisms by which certain traits and behaviors evolve due to mate choice and competition within a species. In the context of this theory, the Jeffreys divergence measure, also known as population stability index, plays a key role in quantifying the information obtained when a deviation from random mating occurs for both discrete and continuous data. Despite the critical importance of understanding mating patterns in the context of sexual selection, there is currently no software available that can perform model selection and multimodel inference with quantitative mating data to test hypotheses about the dynamics underlying observed mating patterns. Recognizing this gap, I have developed QInfoMating which provides a comprehensive solution for analyzing and interpreting mating data within the framework of sexual selection theory. ResultsThe program QInfoMating incorporates a user-friendly interface for performing statistical tests, best-fit model selection, and parameter estimation using multimodel inference for both discrete and continuous mating data. A use case is presented with real data of the species Echinolittorina malaccana. ConclusionsThe application of information theory, model selection, and parameter estimation using multimodel inference are presented as powerful tools for the analysis of mating data, whether quantitative or categorical. The QInfoMating program is a tool designed to perform this type of analysis.

evolutionary biology↗

bioRxiv2023

The information theory formalism unifies the detection of the patterns of sexual selection and assortative mating for both discrete and quantitative traits

Sexual selection plays a crucial role in modern evolutionary theory, offering valuable insight into evolutionary patterns and species diversity. Recently, a comprehensive definition of sexual selection has been proposed, defining it as any selection that arises from fitness differences associated with nonrandom success in the competition for access to gametes for fertilization. Previous research on discrete traits demonstrated that non-random mating can be effectively quantified using Jeffreys (or symmetrized Kullback-Leibler) divergence, capturing information acquired through mating influenced by mutual mating propensities instead of random occurrences. This novel theoretical framework allows for detecting and assessing the strength of sexual selection and assortative mating. In this study, we aim to achieve two primary objectives. Firstly, we demonstrate the seamless alignment of the previous theoretical development, rooted in information theory and mutual mating propensity, with the aforementioned definition of sexual selection. Secondly, we extend the theory to encompass quantitative traits. Our findings reveal that sexual selection and assortative mating can be quantified effectively for quantitative traits by measuring the information gain relative to the random mating pattern. The connection of the information indices of sexual selection with the classical measures of sexual selection is established. Additionally, if mating traits are normally distributed, the measure capturing the underlying information of assortative mating is a function of the square of the correlation coefficient, taking values within the non-negative real number set [0, +{infty}). It is worth noting that the same divergence measure captures information acquired through mating for both discrete and quantitative traits. This is interesting as it provides a common context and can help simplify the study of sexual selection patterns.

evolutionary biology↗

bioRxiv2023

1LocusSim a mobile-friendly simulator for teaching population genetics

SummaryBiology students often struggle with the fundamental concepts of evolutionary genetics, including genetic drift, mutation, and selection. To address this problem, 1LocusSim was developed to simulate the interaction of different factors, such as population size, mutation, selection, and dominance, to study their effect on allelic frequency during evolution. With 1LocusSim, students can compare theoretical results with simulation outputs and solve and analyze different problems of population genetics. The 1LocusSim web has a responsive design which means that it has been specifically designed to be used on smartphones. To demonstrate its use, I review the classical overdominance model of population genetics and highlight a characteristic that is often not explicitly stated. Specifically, it is emphasized that the equilibrium of the model does not depend on the homozygous selection coefficients but rather on the ratio of the selection coefficients. This is already clear from the classical formula but maybe not so much for students. Also it implies that the equilibrium can be expressed solely in terms of the dominance coefficient h. To verify these theoretical prediction, I utilize the simulator and calculate the equilibrium for the well-known case of sickle cell anaemia. Simulating basic population genetic models on smartphones can be a powerful learning aid that fosters critical skills and opens up new opportunities for Biology students. By utilizing this tool, students can learn at their own pace and convenience, anywhere and anytime. Software and data availability1LocusSim if freely available at https://1LocusSim-biosdev.pythonanywhere.com/. Website implemented under the Bottle micro web-framework for Python, with all major browsers supported. Contactacraaj@uvigo.es Supplementary informationThe manual and examples are available from the help button of the program or directly at https://acraaj.webs.uvigo.es/1LocusSim/1LocusSim_EN.html. Both the program and the manual pages are in English and Spanish.

scientific communication and education↗

bioRxiv2022

A simulation study of the ecological speciation conditions in the Galician marine snail Littorina saxatilis

In the last years the interest on evolutionary divergence at small spatial scales has increased and so did the study of speciation caused by ecologically-based divergent natural selection. The evolutionary interplay between gene flow and local adaptation can lead to low-dispersal locally adapted specialists. When this occurs the evolutionary interplay between gene flow and local adaptation could eventually lead to speciation. The L. saxatilis system consists of two ecotypes displaying a microhabitat-associated intraspecific dimorphism along the wave-exposed rocky shores of Galicia. In spite of being a well-known system, the dynamics of the ecotype formation remains unclear and cannot be studied from empirical evidence alone. In this study, individual-based simulations were used to incorporate relevant ecological, spatial and genetic information, to check different evolutionary scenarios that could evolve non-random mating preferences and finally may facilitate speciation. As main results, we observed the evolution of intermediate values of choice which matches estimates from empirical data of L. saxatilis in Galician shores and coincides with previous theoretical outcomes. Also, the use of the mating correlation as a proxy for assortative mating led to spuriously inferring greater reproductive isolation in the middle habitat than in the others, which does not happen when directly considering the choice values from the simulations. We also corroborate the well-known fact that the occurrence of speciation is influenced by the strength of selection. Taken together, this means, also according to other L. saxatilis systems, that speciation is not an immediate consequence of local divergent selection and mating preferences, but a fine tuning among several factors including the ecological conditions in the shore levels, the selection strength, the mate choice stringency and cost to choosiness. The L. saxatilis system could correspond to a case of incomplete reproductive isolation, where choice intensity is intermediate and local adaptation within the habitat is strong. These results support previous interpretations of the L. saxatilis model system and indicate that further empirical studies would be interesting to test whether the mate choice mechanism functions as a similarity-like mechanism as has been shown in other littorinids.

evolutionary biology↗

bioRxiv2018

Multi-model inference of mate choice effects from an information theoretic approach

Non-random mating has a significant impact on the evolution of organisms. Here, I developed a modelling framework for discrete traits (with any number of phenotypes) to explore different models connecting the non-random mating causes (intra sexual competition and/or mate choice) and their consequences (sexual selection and/or assortative mating). I derived the formulas for the maximum likelihood estimates of each model and used information criteria for performing multimodel inference. Simulation results showed a good performance of both model selection and parameter estimation. The methodology was applied to data from Galician Littorina saxatilis ecotypes, to show that the mating pattern is better described by models with two parameters that involve both mate choice and intrasexual competition, generating positive assortative mating plus female sexual selection. As far as I know, this is the first standardized methodology for model selection and multimodel inference of mating parameters for discrete traits. The advantages of this framework include the ability of setting up models from which the parameters connect causes, as intrasexual competition and mate choice, with their outcome in the form of data patterns of sexual selection and assortative mating. For some models, the parameters may have a double effect i.e. they cause both kind of patterns, while for others models there are separated parameters for one kind of pattern or another. The full methodology was implemented in a software called InfoMating (available at http://acraaj.webs6.uvigo.es/InfoMating/Infomating.htm).

evolutionary biology↗

bioRxiv2018

A generalization of the informational view of non-random mating: Models with variable population frequencies

Mate choice may generate non-random mating patterns. It has been recently shown that the mating distribution caused by mate choice can be expressed as a gain in information with respect to random mating. In that model, the population phenotypic frequencies were assumed as constant during the breeding season. In the present work such restriction was relaxed to consider different encounter-mating processes in which the population frequencies of available individuals change over mating rounds. As with the constant case, here we describe the change in the mating phenotypes by the flow of information with respect to random mating. This information can be partitioned into sexual selection, sexual isolation and a mixed effect. Likewise, the pairwise statistics for total change, sexual selection and sexual isolation are generalized for variable population frequencies.\n\nThe new tests had more power for the detection of the effects of non-random mating when the population frequencies vary during the breeding season. The differences in power were high for sexual selection but slight for sexual isolation scenarios. However, the application of the new formulas require the estimation of frequencies at each mating round. Therefore, choosing one or another type of statistics would depend on the biological scenario as well as in the availability and easiness to split the sampling in more than one mating round.

evolutionary biology↗

bioRxiv2017

MatSim: Monte Carlo simulation for the generation of mating tables

In species with sexual reproduction, the mating pattern is a meaningful element for understanding evolutionary and speciation processes. Given a mating pool where individuals can encounter each other randomly, the individual mating preferences would define the mating frequencies in the population. However, in every mating process we can distinguish two different steps. First, the encounter between partners. Second, the actual mating once the encounter has occurred. Yet, we cannot always assume that the observed population patterns accurately reflect the individuals preferences. In some scenarios the individuals may have difficulties to achieve their preferred matings, such as in monogamous species with low population size, where the mating process is similar to a sampling without replacement. In the latter, the encounter process will introduce some noise that may disconnect the individual preferences from the obtained mating pattern. Actually, the difference between the mating pattern observed in a population and the mating preferences of the individuals have been shown by different modeling scenarios.\n\nHere I present a program that simulates the mating process for both discrete and continuous traits, under different encounter models and individual preferences, including effects as time dependence and aging. The utility of the software is demonstrated by replicating and extending, a recent study that showed how patterns of positive assortative mating, or marriage in human societies, may arise from non-assortative individual preferences. The previous result is confirmed and is shown to be caused by the marriage among the \"ugliest\" and oldest individuals, who after many attempts were finally able to mate among themselves. In fact, I show that the assortative pattern vanishes if an aging process prevents these individuals from mating altogether. The software MateSim is available jointly with the users manual, at http://acraaj.webs.uvigo.es/MateSim/matesim.htm

evolutionary biology↗

bioRxiv2016

Non-random mating and information theory

In this work, mate choice is modeled by means of the abstract concept of mutual mating propensity. This only assumes that different type of couples can have different mating success. The model is adequate for any population where mating occurs among distinct types. There is no extra assumption about particular mating scheme or preference model. The concept of mutual mating propensity permits to express the observed change in the mating phenotypes as the gain in information with respect to random mating. The obtained expression is a form of the Price equation in which the mapping between ancestral and descendant population is substituted by a mapping between random mating and non random mating population.\n\nAt the same time, this framework provides the connection between mate choice and the exact mathematical partition of the choice effects, namely sexual isolation, sexual selection and a mixed effect. The sexual selection component is the sum of the intra-sexual male and female selection.\n\nThe proposed framework helps to unveil previously hidden invariants. For example, if the mutual preference between partner types is multiplicative there is no sexual isolation (inter-sexual selection) effect on the frequencies, i.e. the only possible effect of mate choice is intra-sexual selection. On the contrary, whatever the contribution of each partner to the mutual preference, if it comes as a non-multiplicative factor, there is at least an inter-sexual selection detectable effect.\n\nThis new view over the mate choice problem, permits to develop general mating propensity models and to make predictions of the mate choice effects that may emerge from such models. This possibility opens up the way for setting a general theory of model fitting and multimodel inference for mate choice.\n\nThus, it is suggested that the proposed framework, by describing mate choice as the flow of information due to non-random mating, provides a new important setting for exploring different mating models and their consequences.

evolutionary biology↗