Biology subjects

Miro Pina, V.

Publications and source records attributed to Miro Pina, V..

4 recordsLinked to original sources

bioRxiv2023

Estimating the Lambda measure in multiple-merger coalescents

Multiple-merger coalescents, also known as {Lambda}-coalescents, have been used to describe the genealogy of populations that have a skewed offspring distribution or that undergo strong selection. Inferring the characteristic measure {Lambda}, which describes the rates of the multiple-merger events, is key to understand these processes. So far, most inference methods only work for some particular families of {Lambda}-coalescents that are described by only one parameter, but not for more general models. This article is devoted to the construction of a non-parametric estimator of the density of {Lambda} that is based on the observation at a single time of the so-called Site Frequency Spectrum (SFS), which describes the allelic frequencies in a present population sample. First, we produce estimates of the multiple-merger rates by solving a linear system, whose coefficients are obtained by appropriately subsampling the SFS. Then, we use a technique that aggregates the information extracted from the previous step through a kernel type of re-construction to give a non-parametric estimation of the measure {Lambda}. We give a consistency result of this estimator under mild conditions on the behavior of {Lambda} around 0. We also show some numerical examples of how our method performs.

evolutionary biology↗

bioRxiv2023

An extension of the Walsh-Hadamard transform to calculate and model epistasis in genetic landscapes of arbitrary shape and complexity

Accurate models describing the relationship between genotype and phenotype are necessary in order to understand and predict how mutations to biological sequences affect the fitness and evolution of living organisms. The apparent abundance of epistasis (genetic interactions), both between and within genes, complicates this task and how to build mechanistic models that incorporate epistatic coefficients (genetic interaction terms) is an open question. The Walsh-Hadamard transform represents a rigorous computational framework for calculating and modeling epistatic interactions at the level of individual genotypic values (known as genetical, biological or physiological epistasis), and can therefore be used to address fundamental questions related to sequence-to-function encodings. However, one of its main limitations is that it can only accommodate two alleles (amino acid or nucleotide states) per sequence position. In this paper we provide an extension of the Walsh-Hadamard transform that allows the calculation and modeling of background-averaged epistasis (also known as ensemble epistasis) in genetic landscapes with an arbitrary number of states per position (20 for amino acids, 4 for nucleotides, etc.). We also provide a recursive formula for the inverse matrix and then derive formulae to directly extract any element of either matrix without having to rely on the computationally intensive task of constructing or inverting large matrices. Finally, we demonstrate the utility of our theory by using it to model epistasis within both simulated and empirical multiallelic fitness landscapes, revealing that both pairwise and higher-order genetic interactions are enriched between physically interacting positions. Author SummaryAn important question in genetics is how the effects of mutations combine to alter phenotypes. Genetic interactions (epistasis) describe non-additive effects of pairs of mutations, but can also involve higher-order (three- and four-way etc.) combinations. Quantifying higher-order interactions is experimentally very challenging requiring a large number of measurements. Techniques based on deep mutational scanning (DMS) represent valuable sources of data to study epistasis. However, the best way to extract the relevant pairwise and higher-order epistatic coefficients (genetic interaction terms) from this data for the task of phenotypic prediction remains an unresolved problem. The Walsh-Hadamard transform represents a rigorous computational framework for calculating and modeling epistatic interactions at the level of individual genotypic values. Critically, this formalism currently only allows for two alleles (amino acid or nucleotide states) per sequence position, hampering applications in more biologically realistic scenarios. Here we present an extension of the Walsh-Hadamard transform that overcomes this limitation and demonstrate the utility of our theory by using it to model epistasis within both simulated and empirical multiallelic genetic landscapes.

systems biology↗

bioRxiv2022

Plasmid stability in fluctuating environments:population genetics of multi-copy plasmids

Plasmids are extra-chromosomal genetic elements that encode a wide variety of phenotypes and can be maintained in bacterial populations through vertical and horizontal transmission, thus increasing bacterial adaptation to hostile environmental conditions like those imposed by antimicrobial sub-stances. To circumvent the segregational instability resulting from randomly distributing plasmids between daughter cells upon division, non-transmissible plasmids tend to be carried in multiple copies per cell, with the added benefit of exhibiting increased gene dosage and resistance levels. But carrying multiple copies also results in a high metabolic burden to the bacterial host, therefore reducing the overall fitness of the population. This trade-off poses an existential question for plasmids: What is the optimal plasmid copy number? In this manuscript, we address this question by postulating and analyzing a population genetics model to evaluate the interaction between selective pressure, the number of plasmid copies carried by each cell, and the metabolic burden associated with plasmid bearing in the absence of selection for plasmid-encoded traits. Parameter values of the model were estimated experimentally using Escherichia coli K12 carrying a multicopy plasmid encoding for a fluorescent protein and blaTEM-1, a gene conferring resistance to {beta}-lactam antibiotics. By numerically determining the optimal plasmid copy number for constant and fluctuating selection regimes, we show that plasmid copy number is a highly optimized evolutionary trait that depends on the rate of environmental fluctuation and balances the benefit between increased stability in the absence of selection with the burden associated with carrying multiple copies of the plasmid.

evolutionary biology↗

bioRxiv2020

Estimating the time since admixture from phased and unphased molecular data

After admixture, recombination breaks down genomic blocks of contiguous ancestry. The breakdown of these blocks forms a new molecular clock, that ticks at a much faster rate than the mutation clock, enabling accurate dating of admixture events in the recent past. However, existing theory on the break down of these blocks, or the accumulation of delineations between blocks, so called junctions, has mostly been limited to using regularly spaced markers on phased data. Here, we present an extension to the theory of junctions using the Ancestral Recombination Graph that describes the expected number of junctions for any distribution of markers along the genome. Furthermore, we provide a new framework to infer the time since admixture using unphased data. We demonstrate both the phased and unphased methods on simulated data and show that our new extensions performs better than previous methods, especially for smaller population sizes and for more ancient admixture times. Lastly, we demonstrate the applicability of our method on an empirical dataset of labcrosses of yeast (Saccharomyces cerevisae) and on two case studies of hybridization in swordtail fish and Populus trees.

evolutionary biology↗