Biology subjects

Benazzo, A.

Publications and source records attributed to Benazzo, A..

11 recordsLinked to original sources

bioRxiv2026

Dissecting the phenotypic and genetic determinants of maize-bean interactions in intercropping

O_LICereal-legume intercropping is a cornerstone of agroecological systems because interactions between species can enhance agroecosystem resilience. Yet, the mechanisms underlying these interactions remain poorly understood. To address this gap, we investigated the maize-bean association under low-input conditions. C_LIO_LIWe conducted a two-year intercropping experiment with 200 climbing bean lines grown alongside three maize landraces in France and Romania. We evaluated bean phenotypic responses above- and below-ground to 3 maize landraces, treated as distinct biotic environments (E). Direct and indirect genetic effects were assessed by mapping bean and maize phenotypic traits onto the bean genome (G), with G x E interactions tested using contrasts among maize landraces. C_LIO_LICompetitive interactions dominated, maize acting as the stronger competitor. Maize landraces created distinct biotic environments affecting bean traits. Best-performing partners varied across experimental fields, with no evidence of bean local adaptation. The most productive and balanced mixtures were obtained with the traditionally intercropped maize landrace. Genome-wide association analyses identified loci underlying direct and indirect genetic effects, including candidate genes associated with neighbor perception. C_LIO_LIThese findings reveal the genetic complexity of maize-bean interactions and highlight competitive tolerance in bean and reduced aggressiveness in maize as key traits for improving cereal-legume intercrop performance. C_LI

genetics↗

bioRxiv2026

The relationship between genomic variation and genetic load: insights from small island populations

Small populations face high extinction risks. This can be explained by several non-genetic and genetic factors, the latter including the loss of genetic diversity and evolutionary potential, as well as the accumulation of harmful mutations (genetic load). Using whole-genome data from island populations with different effective sizes, we estimated genetic variation and load and explored the relationship between these quantities. An extremely small population of the Aeolian wall lizard, Podarcis raffonei, likely isolated for tens of thousands of years, shows the lowest genome-wide heterozygosity observed in wild eukaryotes (one polymorphic site every 300 kb on average). Despite this, its realized genetic load is comparable to that observed in another larger and more genetically variable population. Both populations have lower variation and higher load than the much more abundant sister species, the Sicilian wall lizard. These observations are consistent with the hypothesis that populations experiencing severe bottlenecks may persist for extended periods with extremely low genomic variation, provided that their burden of deleterious mutations remains within tolerable bounds.

genomics↗

bioRxiv2025

Coexisting with humans: genomic and behavioural consequences in a small and isolated bear population

Climate and land use change have increased human-wildlife interactions, potentially reducing wild species density and prompting behavioural adaptations to urbanised environments. It is still debated if behavioural responses are mainly the result of phenotypic plasticity or if they were driven by anthropic selective pressures, especially in small populations. Our study focused on the Apennine brown bear population (Ursus arctos marsicanus), which has coexisted with humans in Central Italy for millennia. We characterised genomic diversity and identified adaptation signals distinctive to this population by comparing whole genome resequencing data across the Holarctic species range. We show that Apennine brown bears possess a unique genomic diversity pattern including selective signatures at genes associated with reduced aggressiveness, possibly involving alternative splicing mechanism. Our findings suggest that even in small and long-isolated populations, selection may shape behavioural traits. We hypothesise that human-induced selection has influenced these changes, reducing conflicts and contributing to the long-term persistence of the Apennine bear and its coexistence with humans.

genomics↗

bioRxiv2025

Inference of human pigmentation from ancient DNA by genotype likelihood

Light eyes, hair and skins probably evolved several times as Homo sapiens dispersed from Africa. In areas with lower UV radiation, light pigmentation alleles increased in frequency because of their adaptive advantage and of other contingent factors such as migration and drift. However, the tempo and mode of their spread is not known. Phenotypic inference from ancient DNA is complicated, both because these traits are polygenic, and because of low sequence depth. We evaluated the effects of the latter by randomly removing reads in two high-coverage ancient samples, the Paleolithic Ust-Ishim from Russia and the Mesolithic SF12 from Sweden. We could thus compare three approaches to pigmentation inference, concluding that, for suboptimal levels of coverage (<8x), a probabilistic method estimating genotype likelihoods leads to the most robust predictions. We then applied that protocol to 348 ancient genomes from Eurasia, describing how skin, eye and hair color evolved over the past 45,000 years. The shift towards lighter pigmentations turned out to be all but linear in time and place, and slower than expected, with half of the individuals showing dark or intermediate skin colors well into the Copper and Iron ages. We also observed a peak of light eye pigmentation in Mesolithic times, and an accelerated change during the spread of Neolithic farmers over Western Eurasia, although localized processes of gene flow and admixture, or lack thereof, also played a significant role.

genomics↗

bioRxiv2024

Low-ABC: a robust demographic Inference from low-coverage whole-genome data through ABC

The reconstruction of past demographic histories relies on the pattern of genetic variation shown by the sampled populations; this means that an accurate estimation of genotypes is crucial for a reliable inference of past processes. A commonly adopted approach to reconstruct complex demographic dynamics is the Approximate Bayesian Computation (ABC) framework. It exploits coalescent simulations to generate the expected level of variation under different evolutionary scenarios. Demographic inference is then performed by comparing the simulated data with the genotypes called in the sampled individuals. Low sequencing coverage drastically affects the ability to reliably call genotypes, thus making low-coverage data unsuitable for such powerful inferential approaches. Here, we present Low-ABC, a new ABC approach to infer past population processes using low-coverage whole-genome data. Under this framework, both observed and simulated genetic variation are not directly compared using called genotypes, but rather obtained using genotype likelihoods to consider the uncertainty caused by the low sequencing coverage. We first evaluated the inferential power of this procedure in distinguishing among different demographic models and in inferring model parameters under different experimental conditions, including a wide spectrum of sequencing coverage (1x to 30x), number of individuals, number, and size of genetic loci. We showed that the use of genotype likelihoods integrated into an ABC framework provides a reliable inference of past population dynamics, thus making possible the application of model-based inference also for low-coverage data. We then applied Low-ABC to shed light on the relationship between Mesolithic and Early Neolithic European populations.

genomics↗

bioRxiv2023

Adaptive gene loss in the common bean pan-genome during range expansion and domestication

The common bean (Phaseolus vulgaris L.) is a crucial grain legume crop [1,2] whose life history offers an ideal evolutionary model to identify and study adaptive variants in wild and domestication populations [3]. Here we present the first common bean pan-genome based on five high-quality genomes and whole-genome reads representing 339 genotypes. We found [~]243 Mb of additional sequences containing 7,495 protein-coding genes missing from the reference, constituting 51% of the total presence/absence variations (PAVs). There were more putatively deleterious mutations in PAVs than core genes, probably reflecting the lower effective population size of PAVs as well as fitness advantages due to the purging effect of gene loss. Our results suggest strong pan-genome shrinkage occurred during wild range expansion from Mexico to South America, with more PAV loss per individual in Andean vs Mesoamerican populations. Selection signatures during wild spreading and domestication were also associated with PAV loss involved in important adaptive traits. Our findings provide evidence that partial or complete gene loss was a key adaptive trait leading to localized and genome-wide reductions. This novel result has major implications for the understanding of the process of plant adaptation and claims for a paradigm shift in evolutionary genetics. Moreover, the common bean pan-genome is a valuable resource for food legume research and breeding towards climate change mitigation, and sustainable agriculture.

evolutionary biology↗

bioRxiv2023

The evolutionary history of the common bean (Phaseolus vulgaris) revealed by chloroplast and nuclear genomes.

The remarkable evolutionary history of the common bean (Phaseolus vulgaris L.) has led to the emergence of three wild main genepools corresponding to three different ecogeographic areas: Mesoamerica, the Andes and northern Peru/Ecuador. Recent works proposed novel scenarios and the northern Peru/Ecuador population has been described as a new species called P. debouckii, rekindling the debate about the origin of P. vulgaris. Here we shed light on the origin of P. vulgaris by analysing the chloroplast and nuclear genomes of a large varietal collection representing the entire geographical distribution of wild forms. We assembled 37 chloroplast genomes de novo and used them to construct a time frame for the divergence of the genotypes under investigation, revealing that the separation of the Mesoamerican and northern Peru/Ecuador genepools occurred [~]0.15 Mya. Our results clearly support a Mesoamerican origin of the common bean and reject the recent P. deboukii hypothesis. These results also imply two independent migratory events from Mesoamerica to the North and South Andes, probably facilitated by birds. Our work represents a paradigmatic example of the importance of taking into account recombination events when investigating phylogeny and of the analysis of wild forms when studying the evolutionary history of a crop species.

genetics↗

bioRxiv2022

Selection and adaptive introgression guided the complex evolutionary history of European common bean

Domesticated crops have been disseminated by humans over vast geographic areas. After 1492, the common bean (Phaseolus vulgaris L.) was introduced in Europe. Here, we combine whole-genome profiling, metabolic fingerprinting and phenotypic characterisation, and we show that the first common bean cultigens successfully introduced into Europe were of Andean origin, after Francisco Pizarros expedition to northern Peru in 1529. We show that hybridisation, selection and recombination have shaped the genomic diversity of the European common bean in parallel with political constraints. There is clear evidence of adaptive introgression into the Mesoamerican-derived European genotypes, with 44 Andean introgressed genomic segments shared by more than 90% of European accessions and distributed across all chromosomes except PvChr11. Genomic scans for signatures of selection highlight the role of genes relevant to flowering and environmental adaptation, suggesting that introgression has been crucial for the dissemination of this tropical crop to the temperate regions of Europe.

genomics↗

bioRxiv2019

Ancient genomes reveal early Andean farmers selected common beans while preserving diversity

All crops are the product of a domestication process that started less than 12,000 years ago from one or more wild populations [1, 2]. Farmers selected desirable phenotypic traits, such as improved energy accumulation, palatability of seeds or reduced natural shattering [3], while leading domesticated populations through several more or less gradual demographic contractions [2, 4]. As a consequence, erosion of wild genetic variation [5] is typical of modern cultivars making them highly susceptible to pathogens, pests and environmental change [6,7]. The loss of genetic diversity hampers further crop improvement programs to increase food production in a changing world, posing serious threats to food security [8,9]. Using both ancient and modern seeds, we analyzed the temporal dynamic of genetic variation and selection during the domestication process of the common bean (Phaseolus vulgaris) that occurred in the Southern Andes. Here we show that most domestic traits were selected for prior to 2,500 years ago, with no or only minor loss of whole-genome variation. In fact, i) all ancient domestic genomes dated between 600 and 2,500 years ago are highly variable - at least as variable as a modern genome from the wild; the genetic erosion that we observe in modern cultivars is therefore a recent process that occurred in the last centuries; ii) the majority of changes at coding genes that differentiate wild and domestic genomes are already present in the ancient genomes analyzed here. Considering that most desirable phenotypic traits are likely controlled by multiple polymorphic genes [10], a likely explanation of this decoupling of selection and genomic erosion is that early farmers applied a relatively weak selection pressure [2] by using many phenotypically similar but genomically diverse individuals as breeders. Selection strategies during the last few centuries were probably less sustainable and produced further improvements focusing on few plants carrying the traits of interest, at the cost of marked genetic erosion.

genomics↗

bioRxiv2018

A new Approximate Bayesian Computation framework to distinguish among complex evolutionary models using whole-genome data

Inferring past demographic histories is crucial in population genetics, and the amount of complete genomes now available should in principle facilitate this inference. In practice, however, the available inferential methods suffer from severe limitations. Although hundreds complete genomes can be simultaneously analyzed, complex demographic processes can easily exceed computational constraints, and the procedures to evaluate the reliability of the estimates contribute to increase the computational effort. Here we present an Approximate Bayesian Computation (ABC) framework, based on the Random Forest algorithm, to infer complex past population processes using complete genomes. To do this, we propose to summarize the data by the full genomic distribution of the four mutually exclusive categories of segregating sites (FDSS), a statistic fast to compute from unphased genome data. We constructed an efficient ABC pipeline and tested how accurately it allows one to recognize the true model among models of increasing complexity, using simulated data and taking into account different sampling strategies in terms of number of individuals analyzed, number and size of the genetic loci considered. We tested the power of the FDSS to be informative about even complex evolutionary histories and compared the results with those obtained summarizing the data through the unfolded Site Frequency Spectrum, thus highlighting for both statistics the experimental conditions maximizing the inferential power. Finally, we analyzed two datasets, testing models (a) on the dispersal of anatomically modern humans out of Africa and (b) the evolutionary relationships of the three species of Orangutan inhabiting Borneo and Sumatra.

genetics↗

bioRxiv2018

Evolution of the CLTCL1 Gene Encoding CHC22 Clathrin Reveals Selection Influencing CHC22’s Role in Human Glucose Metabolism

CHC22 clathrin plays a key role in intracellular membrane traffic of the insulin-responsive glucose transporter GLUT4 in humans. We performed population genetic and phylogenetic analyses of the CHC22-encoding CLTCL1 gene, revealing independent gene loss in at least two vertebrate lineages, after arising from gene duplication. All vertebrates retained the paralogous CLTC gene encoding CHC17 clathrin, which mediates endocytosis. For vertebrates retaining CLTCL1, strong evidence for purifying selection supports CHC22 functionality. All human populations maintained two high frequency CLTCL1 allelic variants, encoding either methionine or valine at position 1316. Functional studies indicated that CHC22-V1316, which is more frequent in farming populations than in hunter-gatherers, has different cellular dynamics than M1316-CHC22 and is less effective at controlling GLUT4 membrane traffic, attenuating its insulin-regulated response. These analyses suggest that ancestral human dietary change influenced selection of allotypes that affect CHC22s role in metabolism and have potential to differentially influence the human insulin response.

genetics↗