Biology subjects

Leonardi, M.

Publications and source records attributed to Leonardi, M..

At least 19 recordsLinked to original sources

bioRxiv2026

geoGraph: Connectivity modelling across geographic space with hexagonal discrete global grids

1. Estimating the movement and connectivity of organisms across landscapes is central to research in ecology and evolutionary biology. Although graph-based approaches representing geographic space as weighted networks provide a flexible and computationally efficient framework for such analyses, existing tools either perform their computations only on rectangular raster grids, thus introducing systematic directional and area distortions at global scales, or rely on bespoke pipelines that limit the general applicability of recent hexagonal-grid analyses. 2. To overcome these shortcomings, here we present geoGraph, an R package that brings graph-based spatial modelling to discrete global hexagonal grids. By representing landscapes on an equal-area hexagonal tessellation of the sphere, geoGraph enables global-scale analysis without projection distortion while retaining the flexibility of the graph framework and the performance of the graph and RBGL/Boost libraries. The package integrates both raster- and vector-based GIS data into a single cost surface, supports custom grids at various resolutions, and provides a complete pipeline from raw GIS layers to graph-algorithmic outputs, together with tools for visualising and interactively editing graphs. 3. We illustrate geoGraph by revisiting previous studies of isolation by distance among human populations in the Human Genome Diversity Project panel. At a global scale, restricting movement to land raised the correlation between geographic and genetic distance from r = 0.74 (great-circle) to r = 0.84. On a finer grid within Asia, accounting for terrain ruggedness improved the fit, with the best-fitting models implying reduced movement across the Himalaya and Tibetan Plateau. These analyses demonstrate that geoGraph can model movement and connectivity appropriate to the desired spatial scale and that the level of geographic realism required is itself scale-dependent. 4. By combining discrete global grids with the power of graph algorithms, geoGraph enables seamless connectivity analysis from landscape to global scales. It is broadly applicable across landscape genetics, phylogeography, conservation planning, and studies of human dispersal, and is particularly suited to large-scale problems that rectangular-raster tools cannot address without distortion.

bioinformatics↗

bioRxiv2026

From margins to mainstream: restoration of riparian margins to support oil palm sustainability in modern and future climates

Palm oil is the worlds leading vegetable oil, with production continuing to expand, particularly across Southeast Asia. Within established plantations, conserving and restoring riparian margins can reduce erosion, improve connectivity, and support biodiversity. Simultaneously, climate change is increasing thermal stress within tropical agricultural landscapes, raising the potential importance of riparian buffers as microclimatic refugia, although this has not previously been evaluated. The Riparian Ecosystem Restoration in Tropical Agriculture (RERTA) Project is a long-term Before-After Control-Impact experiment established within oil palm plantations in Riau, Indonesia, to evaluate alternative riparian restoration strategies following plantation replanting. Treatments included passive restoration (retaining mature oil palms and allowing natural regeneration), active restoration (enrichment planting with six native tree species), and a control (replanting immature oil palms to the river edge). Six years after restoration, we assessed vegetation structure using terrestrial laser scanning and thermal stability using temperature loggers and thermal imaging. We also evaluated the long-term temperature buffering capacity of each treatment under current and projected climates using CHELSA climate data and downscaled outputs from multiple General Circulation Models under Shared Socioeconomic Pathway scenarios for 2045 and 2085. Active restoration produced greater structural complexity, a more closed canopy, and cooler, more thermally stable conditions than passive restoration and control treatments. Restored margins also contained significantly more cool surface microhabitats, reducing thermal extremes under both current and future climate scenarios. Our findings demonstrate that active restoration of riparian margins can enhance thermal buffering and create microclimatic refugia for biodiversity within tropical oil palm landscapes. As agricultural intensification and climate change continue to reshape tropical ecosystems, restoring structurally complex riparian vegetation will be critical for sustaining biodiversity and the ecosystem services upon which agricultural production depends.

ecology↗

bioRxiv2026

Cell-cycle inhibition preserves robust development but rebalances lineages in mouse gastruloids

Cell differentiation and proliferation are fundamental to the development of multicellular organ-isms. While studies in various non-mammalian species show that development can proceed despite disrupted cell cycle progression, the extent to which normal cell cycle dynamics are re-quired in mammals remains unclear. Using mouse gastruloids, we examined the effects of cell cycle inhibition on development. Despite near-complete growth arrest, gastruloids still underwent symmetry breaking, elongation, and germ layer specification, indicating that core differentiation programs are robust to growth inhibition. However, microscopy and single-cell transcriptomics revealed consistent alterations in cell type proportions, including delayed differentiation and re-duced mesodermal populations. To investigate the origin of these changes, we used the differ-ential kinetics of unspliced and spliced cycling transcripts to compare proliferation rates between cell types. While differences in proliferation partly explained the imbalance, our analysis showed that cell cycle perturbations also modulate lineage-specific differentiation timing and efficiency, highlighting a regulatory role of cell cycle dynamics in mammalian development.

developmental biology↗

bioRxiv2025

Climate Shaped the Global Population Structure of Leopards and their Extinction in Europe

Environmental change is often invoked as a key force shaping species evolution and demography, but quantifying its role is challenging. Leopards (Panthera pardus), a widely distributed generalist species, provide an ideal case for studying the role of the environment. The population dynamics of African and Asian leopards differ dramatically, with near panmixia in Africa versus a strong structure and eight subspecies in Asia. Fossil records show that a population in Europe disappeared after the Last Glacial Maximum (LGM), further pointing to complex range dynamics in Eurasia. In this study, we explicitly test the role of climate in shaping leopards population dynamics across the continents, by quantitatively combining paleoclimatic, demographic, and genetic simulations over the last 450 thousand years. Using an Approximate Bayesian Computational framework, we show that the genetic structure differences between Africa and Asia can be explained by distinct historical climatic conditions in these two continents: most of sub-Saharan Africa and parts of Southeast Asia exhibited a stable range without geographical barriers, while other areas such as Morocco, Afghanistan and Northeast Asia showed expansion and extinction cycles during glacial and interglacials. We further model population dynamics in Europe and validate it against fossil and radiocarbon dates records. We find that European populations were likely fragile, with extinctions repeatedly predicted over multiple glacial cycles, indicating that climate change possibly led to the extinction of the European subspecies following the LGM. Notably, we found that climate during the Holocene should have allowed a more recent recolonisation that did not happen, indicating other factors such as human presence might have blocked it.

zoology↗

bioRxiv2025

tidygenclust: Clustering for Population Genetics in R

BackgroundPopulation structure analysis is crucial for evolutionary research and medical genomics. Clustering methods, broadly categorized as model-based (e.g. ADMIXTURE) or non-model-based (e.g. SCOPE), differ in their methodology and computational efficiency. Recently, fastmixture, a model-based approach, has improved scalability and performance, while replicate alignment tools, such as Clumppling, extend previous methods by also aligning the modes across K values. However, all the existing tools are standalone and generate numerous untracked text files, as well as offering limited plot customisability. ResultsWe introduce an R package, tidygenclust, which brings the functionalities of the original ADMIXTURE, fastmixture and Clumppling software into R, enabling a streamlined and integrated workflow. By integrating with tidypopgen, a package designed to handle large SNP datasets, these new tools maintain metadata, simplify data handling, and produce results as customisable ggplot2 objects for flexible visualisation. ConclusionsThe R package tidygenclust advances population genetic analysis by combining computational efficiency with reproducible workflows and user-friendly plotting. The source code and instructions can be accessed on https://github.com/EvolEcolGroup/tidygenclust.

bioinformatics↗

bioRxiv2025

Malaria shaped human spatial organisation for the last 74 thousand years

The mechanisms driving the spatial organisation of early human societies in Africa are typically addressed through climate variables 1-3. However, genetic and archaeological studies have also suggested diseases as a major source of selection in the Pleistocene. Here, we explore whether P. falciparum-induced malaria, a major world disease, drove habitat choice in human societies between 74 and 5 thousand years ago (kya). Using species distribution models of three main mosquito complexes with palaeoclimatic reconstructions and combining the results with epidemiological information, we estimated an index of malaria transmission risk in sub-Saharan Africa through time. We then correlated it with an independent reconstruction of the human niche over the same time period and region. Our results show that humans strongly avoided or were unsuccessful in potential malaria hotspots. The effects of these choices shaped human demography for the last 74 kya, and likely much earlier, by fragmenting human societies over time and contributing to the formation of modern population structure. Our results highlight the importance of considering disease distributions when modelling estimates of past human demography, demonstrating that factors beyond climate underlay patterns of human habitat choice, exchange, and dispersal. Sentence summaryMalaria shaped human habitat choice, exchange, and dispersal since the late Pleistocene in sub-Saharan Africa.

evolutionary biology↗

bioRxiv2025

Pan-African metapopulation model explains Homo sapiens genetic and morphological evolution

A growing body of evidence has challenged the traditional assumption of a single-region origin for Homo sapiens, suggesting instead that our species originated from multiple geographically distinct populations in Africa, which intermittently exchanged genes and culture. However, our understanding of how this Pan-African metapopulation would have evolved through time is still limited. Furthermore, the drivers of such changes are uncertain, and quantitative models of the respective contributions of different African regions are lacking. Here we provide a complete reconstruction of the meta-population dynamics over the last 200,000 years by quantitatively integrating an ecological niche model, informed by archaeological sites, within a spatially explicit population genetic framework. The inferred metapopulation dynamics account for the divergence among all available contemporary and ancient genomes of African hunter-gatherers used to calibrate the model. In addition, it also accurately predicts the patterns of craniometric diversification across the continent from the Late Middle Pleistocene to the present. Finally, we show how the climate-driven changes in population sizes and connectivity are congruent with major patterns of archaeological and phenotypic diversification over the last 200,000 years across the African continent.

evolutionary biology↗

bioRxiv2024

The environmental context of the Middle-to-Late Stone Age Transition in eastern Africa: seasonality as a key factor

In the transition between the Middle Stone Age (MSA) and the Late Stone Age (LSA) in eastern Africa, the archaeological record shows a gradual and asynchronous decline in MSA features and an increase in LSA characteristics. A link between this pattern and climatic variations has not yet been tested in the region using lithic attribute analysis. To investigate that, we integrated technological data of blades and bladelets from eastern African contexts (Marine Isotope Stages 5-1) with large-scale paleoclimatic reconstructions. A principal component analysis (PCA) finds the first component (reflecting artifacts dimensions) significantly correlating with time. This highlights a progressive reduction in size over time, a trend that has already been suggested for the MSA-LSA transition. The second principal component reflects artifact shape and shows a significant correlation with the marked aridity of the dry season (a common proxy for seasonality in tropical regions), with higher specialization observed in more humid areas. Based on this, we propose a new model where more variable blades reflect greater versatility in foraging strategies as adaptation to environments that become more challenging during part of the year. On the other hand, when it rains more during the dry season and differences through the year are milder, a more specialized toolkit with thinner, longer elements would emerge from refining and adapting to uniform and predictable situations and challenges.

evolutionary biology↗

bioRxiv2024

The Acheulean niche: climate and ecology predict handaxe production in Europe

The Acheulean was the most spatially and temporally vast stone tool industry produced by early humans, persisting for >1.6 million years across three continents. Understanding how behavioral and artifactual variation in these populations relates to climate change and ecology is vital to correctly interpreting the archaeological record, especially given the major climatic and cultural fluctuations during the Pleistocene. Bifacially flaked core tools - which technologically define the tradition - are sometimes regionally and periodically absent within the Acheuleans boundaries. Biface presence is broadly associated with, but rarely formally tested against, environmental conditions. Here, we investigate biface presence/absence and climate/ecological variation at a continental scale between 726 and 130ka. Using a comprehensive sample of European sites matched to paleoenvironmental reconstructions, we demonstrate clear associations between Acheulean presence and specific environments. Acheulean habitat suitability was most strongly associated with mean winter temperatures above -5/-10{degrees}C, and precipitation of the driest month above 15 mm. Two major habitats, warm forest/woodland and shrubland, comprised the European Acheulean niche. Acheulean spatial presence was reconstructed through time: during interglacial and glacial periods it covered most of southwestern Europe, but extended along northern coastal routes during interglacials. Central and Eastern Europe always remained unsuitable. The Acheulean was excluded from areas experiencing both low winter temperatures and low summer precipitation, but reached areas including only one of those two climatic extremes, suggesting seasonal migrations to avoid the harshest seasons. These analyses explain current Acheulean site distributions in Europe and suggest strong links between handaxes, specific ecological conditions, and prehistoric demographic patterns.

evolutionary biology↗

bioRxiv2024

Genome-wide CRISPRa screens nominate modulators of CAR T cell survival within distinct tumor cytokine milieus

Chimeric Antigen Receptor (CAR) T cell therapy has revolutionized the treatment of B cell malignancies and translating this success to other cancers remains an ongoing clinical objective. Next-generation T cell products in development aim to genetically modulate many facets of cell behavior, for which gene-nominating platforms provide a useful framework for prioritization. Among competing screening approaches, CRISPR activation (CRISPRa) technology permits gain-of-function (GoF) gene surveys at genome-wide scale, but routine implementation in primary T cells has been stymied by high cell requirements ([~]107 - 108) and abbreviated activity. Here, we describe a novel cell manufacturing schema using an all-in-one transposon-based gene delivery system coupled with CAR-restricted cell expansion to generate yields (109) of primary T cells bearing CAR and CRISPRa transgenes that are well above the threshold needed for genome-scale screening. CRISPRa activity is sustained via the inclusion of divergent, duplicate Elongation Factor 1 core/human T-cell leukemia virus (EF1-HTLV) hybrid promoters; while guide RNA representation is preserved through late lentiviral transduction, thus preventing bottlenecking and premature candidate pruning. CRISPRa-CAR T cells manufactured via this pipeline retain potent on-target gene-overexpression (>85% target+) across varied cell subsets (e.g. Tim-3+Lag3+ or serial-challenge) and timescales (>14 days). When deployed to survival-based genome-wide selection landscapes, CRISPRa-CAR pools nominate known and novel endogenous genes capable of enhancing CD8+ CAR T survival in cytokine-rich (e.g. MYC, FUT6, IRF4, GSE1) and cytokine-depleted (e.g. CSF2RB, STAT6, IRF4, GSE1) settings of tumor challenge. This system will have broad utility for therapy-enhancing gene discovery.

immunology↗

bioRxiv2024

Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations

Across a range of biological processes, cells undergo coordinated changes in gene expression, resulting in transcriptome dynamics that unfold within a low-dimensional manifold. Single-cell RNA-sequencing (scRNA-seq) only measures temporal snapshots of gene expression. However, information on the underlying low-dimensional dynamics can be extracted using RNA velocity, which models unspliced and spliced RNA abundances to estimate the rate of change of gene expression. Available RNA velocity algorithms can be fragile and rely on heuristics that lack statistical control. Moreover, the estimated vector field is not dynamically consistent with the traversed gene expression manifold. Here, we develop a generative model of RNA velocity and a Bayesian inference approach that solves these problems. Our model couples velocity field and manifold estimation in a reformulated, unified framework, so as to coherently identify the parameters of an autonomous dynamical system. Focusing on the cell cycle, we implemented VeloCycle to study gene regulation dynamics on one-dimensional periodic manifolds and validated using live-imaging its ability to infer actual cell cycle periods. We benchmarked RNA velocity inference with sensitivity analyses and demonstrated one- and multiple-sample testing. We also conducted Markov chain Monte Carlo inference on the model, uncovering key relationships between gene-specific kinetics and our gene-independent velocity estimate. Finally, we applied VeloCycle to in vivo samples and in vitro genome-wide Perturb-seq, revealing regionally-defined proliferation modes in neural progenitors and the effect of gene knockdowns on cell cycle speed. Ultimately, VeloCycle expands the scRNA-seq analysis toolkit with a modular and statistically rigorous RNA velocity inference framework.

systems biology↗

bioRxiv2023

Cadherins modulate the self-organizing potential of gastruloids

Gastruloids have recently emerged as an efficient four-dimensional model for studying some aspects of post-implantation embryonic patterning. They undergo gastrulation-like processes leading to the self-organization into highly reproducible biological objects. Here, we sought to uncover the molecular and cellular mechanism underlying this remarkable property. We report that self-organization competence is associated with a cell-specific coordination of a Cadherin switch. We find that N-Cadherin hinders gastruloids morphogenetic competence, for its inactivation leads to the formation of trunk-like structures in absence of extra-cellular matrix analogues. In contrast, E-Cadherin repression by Snai1 is critical for self-organization: Snai1 establishes a cell-specific repressive pace by triggering the repression of a pluripotency-associated transcription program and its chromatin landscape, thus allowing a proper transition from E-to N-Cadherin to occur. Altogether, this work establishes a molecular mechanism that integrates the exit from pluripotency and the pace of cell differentiation, leading to the observed self-organizing potential of gastruloids.

developmental biology↗

bioRxiv2023

tidysdm: leveraging the flexibility of tidymodels for Species Distribution Modelling in R

In species distribution modelling (SDM), it is common practice to explore multiple machine-learning algorithms and combine their results into ensembles. This is no easy task in R: different algorithms were developed independently, with inconsistent syntax and data structures. Specialised SDM packages integrate multiple algorithms by creating a complex interface between the user (providing a unified input and receiving a unified output), and the back-end code (that tackles the specific needs depending on the algorithm). This requires a lot of work to create and maintain the right interface, and it prevents an easy integration of other methods that may become available. Here we present tidysdm, an R package that solves this problem by taking advantage of the tidymodels universe. Being part of the tidyverse, (i) it has standardised grammar and data structures providing a coherent interface for modelling, (ii) includes packages designed for fitting, tuning, and validating various models, and (iii) allows easy integration of new algorithms and methods. tidysdm allows easy, flexible and quick species distribution modelling by supporting standard algorithms, including additional SDM-oriented functions, and giving the opportunity of using any algorithm or procedure to fit, tune and validate a large number of different models. Additionally, it provides further functions to easily fit models based on paleo/time-scattered data. The package includes two vignettes detailing standard procedures for present-day and time-scattered data. These vignettes also showcase the integration with pastclim (Leonardi et al. 2023) to allow easier access to palaeoclimatic data series, if needed, but users can bring in their own climatic data in standard formats.

ecology↗

bioRxiv2023

Establishment and validation of a High-throughput Micro-Neutralization assay for Respiratory Syncytial Virus (subtypes A and B)

The validation of a bioanalytical method allows us to determine its validity for a designated purpose and to guarantee the reliability of its analytical results. The virus neutralization assay has proved to be suitable for the detection and quantization of specific serum neutralizing antibodies against respiratory syncytial virus subtypes A and B. Respiratory syncytial virus is a negative-sense RNA virus and is responsible for the majority of acute lower respiratory tract infections in infants and older adults worldwide. Owing to its widespread infection, the WHO considers it a target for the development of preventive vaccines. Despite the high impact of its infections, however, no vaccine candidate is currently available. The aim of this paper is to provide a detailed validation process for the micro-neutralization assay and to demonstrate that this method can effectively support the efficacy assessment of candidate vaccines and the definition of correlates of protection.

immunology↗

bioRxiv2023

Niche conservatism in a generalist felid: low differentiation of the climatic niche among subspecies of the leopard (Panthera pardus)

AimSpecies distribution modelling can be used to reveal if the ecology of a species varies across its range, to investigate if range expansions entailed niche shifts, and to help assess ecological differentiation: the answers to such questions are vital for effective conservation. The leopard (Panthera pardus spp.) is a generalist species composed of one African and eight Asian subspecies, reflecting dispersal from an ancestral African range. This study uses species distribution models to compare the niches of leopard subspecies, to investigate if they conserved their niches when moving into new territories or adapted to local conditions and shifted niche. LocationAfrica and Eurasia MethodsWe assembled a database of P. pardus spp. presences. We then associated them with bioclimatic variables to identify which are relevant in predicting the distribution of the leopard. We then constructed a species distribution model and compared the distribution predicted from models based on presences from all subspecies versus the ones built only using African leopards. Finally, we used multivariate analysis to visualise the niche occupied by each subspecies in the climate space, and to compare niche overlaps to assess ecological differentiation. ResultsNiche comparisons and model predictions suggest a general lack of niche separation between all subspecies. Most Asian subspecies have overlapping niches and occupy subsets of the niche of the African leopard. Nevertheless, we found the Persian leopard Panthera pardus saxicolor to have the most distinct niche, giving some evidence for niche expansion in more Northern Asian subspecies. Main conclusionsThese results suggest little ecological differentiation among leopard subspecies and a lack of adaptation to novel climates after dispersal from Africa. This finding complements recent genetic studies in implying that the taxonomy of Asian leopards may not reflect biological differentiation, an issue that is important to resolve due to its relevance for the conservation of the species.

ecology↗

bioRxiv2022

pastclim: an R package to easily access and use paleoclimatic reconstructions

The recent development of continuous paleoclimatic reconstructions covering hundreds of thousands of years paved the way to a large number of studies from disciplines ranging from paleoecology to linguistics, from archaeology to conservation and from population genetics to human evolution. Unfortunately, such climatic data can be challenging to extract and analyze for scholars unfamiliar with such specific climatic file formats. Here we present pastclim, an R package facilitating the access and use of two sets of paleoclimatic reconstructions covering respectively the last 120,000 and 800,000 years. The package contains a set of functions allowing to quickly and easily recover the climate for the whole world or specific areas for time periods of interest, extract data from locations scattered in space and/or time, retrieve time series from individual sites, and easily manage the ice or land coverage. The package can easily be adapted to paleoclimatic reconstructions different from the ones already included, offering a handy platform to include the climate of the past into existing analyses and pipelines.

evolutionary biology↗

bioRxiv2022

COVID-19 mRNA third dose induces a unique hybrid immunity-like antibody response

The continuous evolution of SARS-CoV-2 generated highly mutated variants, like omicron BA.1 and BA.2, able to escape natural and vaccine-induced primary immunity1,2. The administration of a third dose of mRNA vaccines induces a secondary response with increased protection. We investigated, at single-cell level, the longitudinal evolution of the neutralizing antibody response in four donors after three mRNA doses3. A total of 4,100 spike protein specific memory B cells were single cell sorted and 350 neutralizing antibodies were identified. The third dose increased the antibody neutralization potency and breadth against all SARS-CoV-2 variants of concern as previously observed with hybrid immunity3. However, the B cell repertoire that stands behind the response is dramatically different. The increased neutralizing response was largely due to the expansion of B cell germlines poorly represented after two doses, and the reduction of germlines predominant after primary immunization such as IGHV3-53;IGHJ6-1 and IGHV3-66;IGHJ4-1. Divergently to hybrid immunity, cross-protection after a third dose was mainly guided by Class 1/2 antibodies encoded by IGHV1-58;IGHJ3-1 and IGHV1-69;IGHJ4-1 germlines. The IGHV2-5;IGHJ3-1 germline, which induced broadly cross-reactive Class 3 antibodies after infection or viral vector vaccination, was not induced by a third mRNA dose. Our data show that while neutralizing breadth and potency can be improved by different immunization regimens, each of them has a unique molecular signature which should be considered while designing novel vaccines and immunization strategies.

immunology↗

bioRxiv2021

Hybrid immunity improves B cell frequency, antibody potency and breadth against SARS-CoV-2 and variants of concern

To understand the nature of the antibody response to SARS-CoV-2 vaccination, we analyzed at single cell level the B cell responses of five naive and five convalescent people immunized with the BNT162b2 mRNA vaccine. Convalescents had higher frequency of spike protein specific memory B cells and by cell sorting delivered 3,532 B cells, compared with 2,352 from naive people. Of these, 944 from naive and 2,299 from convalescents produced monoclonal antibodies against the spike protein and 411 of them neutralized the original Wuhan SARS-CoV-2 virus. More than 75% of the monoclonal antibodies from naive people lost their neutralization activity against the B.1.351 (beta) and B.1.1.248 (gamma) variants while this happened only for 61% of those from convalescents. The overall loss of neutralization was lower for the B.1.1.7 (alpha) and B.1.617.2 (delta) variants, however it was always significantly higher in those of naive people. In part this was due to the IGHV2-5;IGHJ4-1 germline, which was found only in convalescents and generated potent and broadly neutralizing antibodies. Overall, vaccination of seropositive people increases the frequency of B cells encoding antibodies with high potency and that are not susceptible to escape by any of the four variants of concern. Our data suggest that people that are seropositive following infection or primary vaccination will produce antibodies with increased potency and breadth and will be able to better control SARS-CoV-2 emerging variants.

immunology↗