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Vajana, E.

Publications and source records attributed to Vajana, E..

12 recordsLinked to original sources

Rapid evolutionary responses to climate change in maritime pine (Pinus pinaster Ait.) despite widespread adaptive lag

Climate change is profoundly affecting species worldwide and poses a major threat to their long-term persistence. Although trees may have the potential for rapid adaptation to changing climates, empirical evidence remains limited, and whether these long-lived organisms can adapt quickly enough to keep pace with ongoing climate change is still an open question. To investigate real-time responses to contemporary climate change, we combined genomic data from 82 range-wide populations of the widespread tree Pinus pinaster Ait. with intensive sampling of two successive cohorts from two natural populations. Using an original genotype-environment association (GEA) approach to quantify climate (mal)adaptation, we found that most individuals from both target populations showed evidence of an adaptive lag to current climatic conditions, and are predicted to face substantial risk of maladaptation under future climates. Importantly, changes in genomic composition at climate-associated loci between cohorts were consistent with rapid evolutionary responses to ongoing climate change and could not be explained by neutral demographic processes alone, as supported by forward-time genetic simulations. We also observed a lower realised genetic load in the younger cohort, suggesting that the dynamics of deleterious mutations may change with climatic pressure. Our work provides evidence suggesting genetic responses to contemporary climate change within a single generation, including signals of rapid evolutionary changes in genomic composition at climate-associated loci and signatures of purifying selection, despite widespread adaptive lag to current climates. These findings challenge the view that trees only respond slowly to environmental change and highlight the need to integrate evolutionary dynamics into predictive models of species persistence under future climates.

genomics↗

Demographic history shapes forest tree vulnerability to climate change

Demographic history is expected to play a central role in shaping population vulnerability to climate change through its lasting effects on effective population sizes and genetic connectivity. However, existing studies report contrasting outcomes, and the consequences of alternative demographic histories have seldom been assessed concurrently across multiple taxa. Here, we analysed population genomic data from six of the major European forest tree species to address this gap. Across species, genetic isolation reduced adaptive potential, as reflected in lower standing genetic diversity. Greater genetic differentiation was also associated with increased maladaptation to climate, whereas the purge or accumulation of deleterious mutations depended on the severity of past demographic events. Finally, the beneficial effects of gene flow were evidenced across the six species by more optimal climate adaptation in highly connected populations. Altogether, our results provide valuable insights into how genetic differentiation, reflecting the combined effects of genetic drift and limited historical gene flow, influences current vulnerability of forest tree populations to climate change.

evolutionary biology↗

The FORGENIUS genomic resources: new genotyping tools and genomic data for 23 forest tree species and their Genetic Conservation Units

Genetic diversity is a critical but often overlooked component of biological diversity. The European H2020 FORGENIUS project is precisely aimed at increasing the quality and quantity of genetic data to start monitoring the European network of forest Genetic Conservation Units (GCUs). A first step in this direction was developing standardized genomic resources for 23 forest tree species, spanning from rare and scattered (e.g., Abies nebrodensis and Torminalis glaberrima) to widespread, economically relevant ones (e.g., Fagus sylvatica, Picea abies and Pinus sylvestris). Here, we describe the development and application of targeted genotyping tools, primarily based on Single Primer Enrichment Technology (SPET), along with existing SNP arrays for the selected species. The SPET panels developed in FORGENIUS were designed to capture {square}10,000 loci per species, balancing species-specific and randomly distributed regions to ensure broad genome coverage and minimize ascertainment bias. Across 7,192 genotyped trees, we identified over 1.8 million single nucleotide polymorphisms (SNPs) covering approximately 50 Mb of DNA sequence. SPET panels demonstrated high genotyping efficiency and cross-species transferability, especially within genera such as Quercus and Abies. They represent a cost-effective, flexible, and scalable solution for population-level genetic assessments across diverse taxa, enabling standardized, genome-wide characterization of the GCU network. These resources not only promote the establishment of genetic monitoring, support genetically informed conservation strategies and improve our understanding of adaptive responses in European forests, but also enhance species delimitation and hybrid detection, and enable the characterization of phylogenetically related but previously underexplored species.

genomics↗

Genomic signatures of climate-driven (mal)adaptation in an iconic conifer, the English yew (Taxus baccata L.)

The risk of climate maladaptation is increasing for numerous species, including trees. Developing robust methods to assess population maladaptation remains a critical challenge. Genomic offset approaches aim to predict climate maladaptation by characterising the genomic changes required for populations to maintain their fitness under changing climates. In this study, we assessed the risk of climate maladaptation in European populations of English yew (Taxus baccata), a long-lived tree with a patchy distribution across Europe, the Atlas Mountains, and the Near East, where many populations are small or threatened. We found evidence suggesting local climate adaptation by analysing 8,616 SNPs in 475 trees from 29 European T. baccata populations, with climate explaining 18.1% of genetic variance and 100 unlinked climate-associated loci identified via genotype- environment association (GEA). Then, we evaluated the deviation of populations from the overall gene-climate association to assess variability in local adaptation or different adaptation trajectories across populations and found the highest deviations in low latitude populations. Moreover, we predicted genomic offsets and successfully validated these predictions using fitness proxies assessed in plants from 26 populations grown in a comparative experiment. Finally, we integrated information from current local adaptation, genomic offset, historical genetic differentiation and effective migration rates to show that Mediterranean and high-elevation T. baccata populations face higher vulnerability to climate change than low-elevation Atlantic and continental populations. Our study demonstrates the practical use of the genomic offset framework in conservation genetics, offers insights for its further development, and highlights the need for a population-centred approach that incorporates additional statistics and data sources to credibly assess climate vulnerability in wild plant populations.

genomics↗

Spatial conservation prioritisation for intraspecific genetic diversity of three forest tree species with a fragmented distribution in Italy

The Kunming-Montreal Global Biodiversity Framework recognised the urgency of taking action to conserve intraspecific genetic diversity (IGD) as an insurance against habitat degradation and environmental change. Recent work suggests that 90-99% of IGD should be conserved to safeguard viability of future generations. Here, we addressed such a conservation issue in three forest tree species in Italy: silver fir (Abies alba Mill.), Heldreichs pine (Pinus heldreichii H. Christ), and pedunculate oak (Quercus robur L.). We used microsatellite markers to measure IGD of 36 (A. alba), 15 (P. heldreichii) and 25 (Q. robur) natural sites, including several putative glacial refugia. We developed a spatial conservation planning (SCP) analysis to quantify the genetic irreplaceability of each site and identify the minimum set coverage ensuring IGD protection. Finally, we compared SCP results with the contributions to allelic diversity within and between sites, total allelic diversity and private allelic richness. We found that between 44% and 73% of sites were required to conserve 90-99% of the alleles, and that this conservation effort held even when targeting lower percentages of alleles to protect (50-75%). Glacial refugia were often included in the minimum set coverage, confirming theoretical and biogeographical expectations. Finally, sites with high genetic irreplaceability were found to have higher private allelic richness on average. These results are discussed in the light of the biogeographic history of the species studied and the current policies for the conservation of forest genetic resources.

evolutionary biology↗

The latitudinal trend in genetic diversity and distinctiveness of Quercus robur rear edge forest remnants calls for new conservation priorities

Knowledge of the spatial distribution of intraspecific genetic variation is essential for planning conservation actions, designing networks of protected areas, and informing possible assisted migration strategies. Although the Italian peninsula harbours unique genetic variation as a legacy of Quaternary migrations, only sporadic genetic information is available for forest tree species. Here, we present the first geographically comprehensive genetic characterisation of Quercus robur, an iconic broadleaved species of European floodplain forests, in an area which acted as a primary glacial refugium for the species. 745 individuals from 25 populations were sampled and genotyped with 16 microsatellite markers. Their genetic structure was assessed through various metrics of diversity and distinctiveness, as well as by Bayesian clustering and multivariate methods. The demographic history of inferred gene pools was evaluated through Approximate Bayesian Computation analysis. Genetic distinctiveness showed a decline with increasing latitude, while allelic richness reached its peak in central Italy. A south-to-north trend in the complexity of the genetic structure was observed, with peninsular Italy being characterised by intermingled gene pools in contrast to the relative homogeneity exhibited by northern populations. Demographic inference indicated that the southern gene pool has been genetically isolated since the penultimate interglacial, whereas populations from central Italy persisted locally in a mosaic of small refugia during the last glaciation. Our results brought out the complexity of the genetic structure of forest trees populations in southern Europe. At least three Q. robur refugia contributed to the genetic layout of extant populations after the last glacial period, but refugial areas were probably even more numerous in central Italy. Such a detailed characterization sheds new light on the priorities to be established for the conservation of highly fragmented Q. robur populations in an area rich in diversified genetic lineages.

genetics↗

Genetic signatures of divergent selection in European beech (Fagus sylvatica L.) are associated with the variation in temperature and precipitation across its distribution range

High genetic variation and extensive gene flow may help forest trees with adapting to ongoing climate change, yet the genetic bases underlying their adaptive potential remain largely unknown. We investigated range-wide patterns of potentially adaptive genetic variation in 64 populations of European beech (Fagus sylvatica L.) using 270 SNPs from 139 candidate genes involved either in phenology or in stress responses. We inferred neutral genetic structure and processes (drift and gene flow) and performed differentiation outlier analyses and gene-environment association (GEA) analyses to detect signatures of divergent selection. Beech range-wide genetic structure was consistent with the species previously identified postglacial expansion scenario and recolonization routes. Populations showed high diversity and low differentiation along the major expansion routes. A total of 52 loci were found to be putatively under selection and 15 of them turned up in multiple GEA analyses. Temperature and precipitation related variables were equally represented in significant genotype-climate associations. Signatures of divergent selection were detected in the same proportion for stress response and phenology-related genes. The range-wide adaptive genetic structure of beech appears highly integrated, suggesting a balanced contribution of phenology and stress-related genes to local adaptation, and of temperature and precipitation regimes to genetic clines. Our results imply a best-case scenario for the maintenance of high genetic diversity during range shifts in beech (and putatively other forest trees) with a combination of gene flow maintaining within-population neutral diversity and selection maintaining between-population adaptive differentiation.

evolutionary biology↗

Big dairy data to disentangle the effect of geo-environmental, physiological and morphological factors on milk production of mountain-pastured Braunvieh cows

1. SummaryThe transhumance system, which consists in moving animals to high mountain pastures during summer, plays a considerable role in preserving both local biodiversity and traditions, as well as protecting against natural hazard. In cows, particularly, milk production is observed to decline as a response to food shortage and climatic stress, leading to atypical lactation curves that are barely described by current lactation models. Here, we relied on five million monthly milk records from over 200,000 Braunvieh and Original Braunvieh cows to devise a new model accounting for transhumance, and test the influence of environmental, physiological, and morphological factors on cattle productivity. Counter to expectations, environmental conditions in the mountain showed a globally limited impact on milk production during transhumance, with cows in favourable conditions producing only 10% less compared to cows living in adverse conditions, and with precipitation in spring and altitude revealing to be the most production-affecting variables. Conversely, physiological factors as lactation number and pregnancy stage presented an important impact over the whole lactation cycle with 20% difference in milk production, and may therefore alter the way animals respond to transhumance. Finally, the considered morphological factors (cow height and foot angle) presented a smaller impact during the whole lactation cycle (10% difference in milk production). The present findings can help farmers to establish sustainable strategies for alleviating the negative effects of transhumance on productivity and preserving this important livestock practice.Competing Interest StatementThe authors have declared no competing interest.View Full Text

zoology↗

Sampling strategy optimization to increase statistical power in landscape genomics: a simulation-based approach

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. The implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistic constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies.\n\nIn this study, we computed simulated genomic datasets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographic representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical performances (power and false discoveries) under two antithetical demographic scenarios.\n\nOur results highlight the importance of selecting an appropriate sample size, which should be modified based on the demographic characteristics of the studied population. For species with limited dispersal, sample sizes above 200 units are generally sufficient to detect most adaptive signals, while in random mating populations this threshold should be increased to 400 units. Furthermore, we describe a design approach that maximizes both environmental and geographical representativeness of sampling sites and show how it systematically outperforms random or regular sampling schemes. Finally, we show that although having more sampling locations (between 40 and 50 sites) increase statistical power and reduce false discovery rate, similar results can be achieved with a moderate number of sites (20 sites). Overall, this study provides valuable guidelines for optimizing sampling strategies for landscape genomics experiments.

evolutionary biology↗

Indication of spatially random infection of chlamydia-like organisms in Bufo bufo tadpoles from ponds located in the Geneva metropolitan area

Occurrence of bacteria belonging to the order Chlamydiales was investigated for the first time in common toad (Bufo bufo) tadpole populations collected from 41 ponds in the Geneva metropolitan area, Switzerland. A Chlamydiales-specific Real-Time PCR was used to detect and amplify the Chlamydiales 16S rRNA-encoding gene from the tails of 375 tadpoles. We found the studied amphibian populations to be infected by \"Chlamydia-like organisms\" (CLOs) attributable to the genera Similichlamydia, Neochlamydia, Protochlamydia and Parachlamydia (belonging to the family Parachlamydiaceae), Simkania (family Simkaniaceae) and Estrella (family Criblamydiaceae); additionally, DNA from the genus Thermoanaerobacter (family Thermoanaerobacteriaceae) was detected. A global autocorrelation analysis did not reveal a spatial structure in the observed CLOs infection rates, and association tests involving land cover characteristics did not evidence any clear effect on CLOs infection rates in B. bufo. Despite preliminary, these results suggest a random and ubiquitous distribution of CLOs in the environment, which would support the biogeographical expectation \"everything is everywhere\" for the concerned microorganisms and their amoeba vectors.

epidemiology↗

Combining landscape genomics and ecological modelling to investigate local adaptation of indigenous Ugandan cattle to East Coast fever

East Coast fever (ECF) is a fatal sickness affecting cattle populations of eastern, central, and southern Africa. The disease is transmitted by the tick Rhipicephalus appendiculatus, and caused by the protozoan Theileria parva parva, which invades host lymphocytes and promotes their clonal expansion. Importantly, indigenous cattle show tolerance to infection in ECF-endemically stable areas. Here, the putative genetic bases underlying ECF-tolerance were investigated using molecular data and epidemiological information from 823 indigenous cattle from Uganda. Vector distribution and host infection risk were estimated over the study area and subsequently tested as triggers of local adaptation by means of landscape genomics analysis. We identified 41 and seven candidate adaptive loci for tick resistance and infection tolerance, respectively. Among the genes associated with the candidate adaptive loci are PRKG1 and SLA2. PRKG1 was already described as associated with tick resistance in indigenous South African cattle, due to its role into inflammatory response. SLA2 is part of the regulatory pathways involved into lymphocytes proliferation. Additionally, local ancestry analysis suggested the zebuine origin of the genomic region candidate for tick resistance.\n\nAuthor summaryThe tick-borne parasite Theileria parva parva infects cattle populations of eastern, central and southern Africa, by causing a highly fatal pathology called \"East Coast fever\". The disease is especially severe for the exotic breeds imported to Africa, as well as outside the endemic areas of East Africa. In these regions, indigenous cattle populations can survive to infection, and this tolerance might result from unique adaptations evolved to fight the disease. We investigated this hypothesis by using a method named \"landscape genomics\", with which we compared the genetic characteristics of indigenous Ugandan cattle coming from areas at different infection risk, and located genomic sites potentially attributable to tolerance. In particular, the method pinpointed two genes, one (PRKG1) involved into inflammatory response and potentially affecting East Coast fever vector attachment, the other (SLA2) involved into lymphocytes proliferation, a process activated by T. parva parva infection. Our findings can orientate future research on the genetic basis of East Coast fever-tolerance, and derive from a general method that can be applied to investigate adaptation in analogous host-vector-parasite systems. Characterization of the genetic factors underlying East Coast-fever-tolerance represents an essential step towards enhancing sustainability and productivity of local agroecosystems.

evolutionary biology↗

BITE: an R package for biodiversity analyses

Nowadays, molecular data analyses for biodiversity studies often require advanced bioinformatics skills, preventing many life scientists from analyzing their own data autonomously. BITE R package provides complete and user-friendly functions to handle SNP data and third-party software results (i.e. Admixture, TreeMix), facilitating their visualization, interpretation and use. Furthermore, BITE implements additional useful procedures, such as representative sampling and bootstrap for TreeMix, filling the gap in existing biodiversity data analysis tools.\n\nAvailabilityhttps://github.com/marcomilanesi/BITE

bioinformatics↗