Biology subjects

Marchi, M.

Publications and source records attributed to Marchi, M..

8 recordsLinked to original sources

bioRxiv2025

Seed origin determines cork oak germination: the warmer the higher, faster and more synchronized

The early life stages of trees, particularly germination, are crucial to fitness and highly sensitive to climate. The influence of temperature on recalcitrant seed germination has rarely been studied due to their desiccation sensitivity, which hampers storage. However, Mediterranean recalcitrant oaks would be particularly affected by the expected increased temperature in this region. Here we investigated the effect of warming temperatures on germination of 975 acorns from 8 range-wide Quercus suber populations. We sowed the acorns at 15, 20 and 25 {degrees}C in climatic chambers, and monitored germination during 4 months. The germination dynamics in each chamber was explored by a Cox proportional hazards model. We assessed environment (germination experiment temperatures), population (climate of seed origin) and their interaction effects on germination percentage, time, and synchrony using generalized linear mixed-effects models. Genetic clines on germination percentage, time and synchrony were mostly triggered by temperature, with seeds from warmer origins showing higher germination, earlier timing, and greater synchrony than colder ones. Higher sowing temperatures promoted advanced germination, and this effect was higher in seeds originating from regions with stronger seasonality. Earlier and synchronous germination found in seeds from warm origin may reduce the desiccation probability for acorns and seedlings, while late germination and low synchrony found in seeds from cold origin might be an adaptive response to unpredictable frost events that would impair seedling survival. The germination synchrony adaptive response was unexpected and further investigation on recalcitrant seeds germination dynamics in response to increased temperatures is needed to confirm it.

ecology↗

bioRxiv2025

Near-infrared spectroscopy-based models correctly classify Abies alba seed origin and predict germination properties

Forestry industry requires high-quantity and quality seeds for afforestation and assisted migration programs. Finding reliable non-destructive methods to characterize seeds would significantly enhance efforts to identify climate-adapted populations. This study presents near-infrared (NIR) spectroscopy models to classify seed origin and predict germination characteristics at different temperatures non-destructively. We focus on Abies alba Mill., a key European forest tree with genetic variation along climatic gradients and seeds with shallow physiological dormancy. Seeds from six populations were analyzed using NIR spectroscopy, and germination was tested at 15{degrees}C, 20{degrees}C, and 25{degrees}C after stratification treatments at 4{degrees}C (0 or 3 weeks). Population classification accuracy using Partial Least Squares Discriminant Analysis was 69%, with significant NIR peaks at 1712, 1929, and 2111 nm, linked to moisture content and storage compounds. NIR spectra explained 51% and 65% of the variation in germination probability and timing using Partial Least Squares Regression, with significant peaks at 1712, 1929, 2111, 1632, and 2073 nm. General Linear Mixed-Effects Models showed that a NIR predictor contributed to 39% of the germination probability variance explained by fixed-effects, and the stratification treatment was the most important driver explaining germination time. Our results proved the utility of NIR-based tools to effectively classify bulked seeds and predict germination, opening new perspectives to nursery and forestry sectors and populations adaptation and adjustments to warming climate. This study will facilitate further investigations on the physiological processes that occur during dormancy, a critical process for forest regeneration given the expected impact of shorter and warmer winters on seed behavior.

ecology↗

bioRxiv2025

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↗

bioRxiv2024

Unexplored Yeast diversity in Seed Microbiota

Yeasts are known to be fantastic biotechnological resources for medical, food, and industrial applications, but their potential remains untapped in agriculture, especially for plant biostimulation and biocontrol. In particular, yeasts have been reported as part of the core microbiome of seeds using next generation sequencing methods, but their diversity and functional roles remain largely undescribed. Focusing on yeasts and excluding filamentous fungi, this study aimed to characterize the diversity of seed-associated yeasts across nine plant species (crops and non-cultivated species) using culturomics and microscopy. Comparison with available metabarcoding data was performed to assess the representativeness of the strain collection in seed samples. Our results show that seed-associated yeasts largely belong to Basidiomycota phylum and more particularly to the Tremellomycetes class. This yeast collection covers 15 genera (2 of Ascomycota and 13 of Basidiomycota). Out of the 229 isolates described, the most frequently isolated yeasts were Holtermanniella, Vishniacozyma, Filobasidium, Naganishia and Sporobolomyces. The yeasts from these dominant genera were isolated from multiple plant species (4 to 8), except for Naganishia which only originated from Solanum lycopersicum L. These results are also consistent with the fact that these dominant taxa were recently identified as members of the core seed microbiome, indicating their high prevalence and abundance across diverse plant hosts and environments. Compared to previous plant yeast diversity surveys, the members from Ascomycota yeasts are less frequent in seeds and only represented here by the Aureobasidium and Taphrina genera. Altogether, these results suggest that yeasts are generally well-adapted to the aboveground habitats of plants, but seeds represent a specific habitat that diverse Basidiomycota yeasts can colonize. Take away messageO_LI229 yeasts isolated from seeds and seedlings of diverse plant species C_LIO_LIMost isolates are Basidiomycota yeasts, especially of the Tremellomycetes class C_LIO_LIThe most frequently isolated yeasts belong to Holtermanniella, Vishniacozyma, Filobasidium and Sporobolomyces genera C_LIO_LIThe collection is representative of taxa found in seed microbiota of multiple plant species, including core members C_LI

microbiology↗

bioRxiv2024

Evaluating genomic offset predictions in a forest tree with high population genetic structure

Predicting how tree populations will respond to climate change is an urgent societal concern. An increasingly popular way to make such predictions is the genomic offset (GO) approach, which aims to use genomic and climate data to identify populations that may experience climate maladaptation in the near future. More precisely, GO tries to represent the change in allele frequencies required to maintain the current gene-climate relationships under climate change. However, the GO approach has major limitations and, despite promising validation of its predictions using height data from common gardens, it still lacks broad empirical testing. In the present study, we evaluated the consistency and empirical validity of GO predictions in maritime pine (Pinus pinaster Ait.), a tree species from southwestern Europe and North Africa with a marked population genetic structure. First, gene-climate relationships were estimated using 9,817 SNPs genotyped in 454 trees from 34 populations; and candidate SNPs potentially involved in climate adaptation were identified. Second, GO was predicted using four methods, namely Gradient Forest (GF), Redundancy Analysis (RDA), latent factor mixed model (LFMM) and Generalised Dissimilarity Modeling (GDM), two sets of SNPs (candidate and control SNPs) and five climate general circulation models (GCMs) to account for uncertainty in future climate predictions. Last, the empirical validity of GO predictions was evaluated within a Bayesian framework by estimating the associations between GO predictions and two independent data sources: mortality data from National Forest Inventories (NFI), and mortality and height data from five common gardens in contrasting environments. We found high variability in GO predictions across methods, SNP sets and GCMs. Regarding validation, GO predictions with GDM and GF (and to a lesser extent RDA) based on the candidate SNPs showed the strongest and most consistent associations with mortality rates in common gardens and NFI plots. We found almost no association between GO predictions and tree height in common gardens, most likely due to the overwhelming effect of population genetic structure on tree height in this species. Our study demonstrates the imperative to validate GO predictions with a range of independent data sources before they can be used as informative and reliable metrics in conservation or management strategies.

evolutionary biology↗

bioRxiv2024

Deciphering the Influence of Socioeconomic Status on Brain Structure: Insights from Mendelian Randomization

Socioeconomic status (SES) influences physical and mental health, however its relation with brain structure is less well documented. Here, we examine the role of SES on brain structure using Mendelian randomisation. First, we conduct a multivariate genome-wide association study of SES using individual, household, and area-based measures of SES, with an effective sample size of n=893,604. We identify 469 loci associated with SES and distil these loci into those that are common across measures of SES and those specific to each indicator. Second, using an independent sample of [~]35,000 we provide evidence to suggest that total brain volume is a causal factor in higher SES, and that SES is protective against white matter hyperintensities as a proportion of intracranial volume (WMHicv). Third, we find evidence that whilst differences in cognitive ability explain some of the causal effect of SES on WMHicv, differences in SES still afford a protective effect against WMHicv, independent of that made by cognitive ability.

genetics↗

bioRxiv2023

COQ4 is required for the oxidative decarboxylation of the C1 carbon of Coenzyme Q in eukaryotic cells

Coenzyme Q (CoQ) is a redox lipid that fulfills critical functions in cellular bioenergetics and homeostasis. CoQ is synthesized by a multi-step pathway that involves several COQ proteins. Two steps of the eukaryotic pathway, the decarboxylation and hydroxylation of position C1, have remained uncharacterized. Here, we provide evidence that these two reactions occur in a single oxidative decarboxylation step catalyzed by COQ4. We demonstrate that COQ4 complements an Escherichia coli strain deficient for C1 decarboxylation and hydroxylation and that COQ4 displays oxidative decarboxylation activity in the non-CoQ producer Corynebacterium glutamicum. Overall, our results substantiate that COQ4 contributes to CoQ biosynthesis, not only via its previously proposed structural role, but also via oxidative decarboxylation of CoQ precursors. These findings fill a major gap in the knowledge of eukaryotic CoQ biosynthesis, and shed new light on the pathophysiology of human primary CoQ deficiency due to COQ4 mutations.

biochemistry↗

bioRxiv2023

Germination timing under climate change: warmer springs favor early germination of range-wide cork oak populations

Climate change is favoring the northward shift of Mediterranean species which are expanding their ranges at their leading edges, becoming natural candidates for increasing forest biodiversity in these regions. However, current knowledge on tree populations responses to climate change is mostly based on adult trees, even if tree early developmental stages are far more sensitive to climate and tightly linked to fitness. To fill this knowledge gap, we investigated the potential adaptation of cork oak range-wide populations to increasing spring temperature in germination and post-germination traits. We sowed 701 acorns from 11 populations at 15, 20 and 25{degrees}C, monitored germination daily and measured post-germination traits. We model germination timing through Coxs proportional-hazards models, assess populations adaptation to spring temperature transfer distances and quantify the effect of acorn mass and storage duration on all considered traits with fixed-effects models. We predict germination and post-germination climate niches under current and RCP 8.5 2080 scenarios. Large differences in germination timing are due to both the population origin and temperature treatment; germination and survival rates showed a sub-optimality towards warmer-than-origin temperatures and heavier acorns produced faster growing seedlings. The timing of germination is the early stage trait most affected by increasing spring temperatures, with germination in 2080 predicted to be 12 days earlier than to date in the northern part of the species range. Warmer spring temperatures will significantly accelerate the germination of other recalcitrant Mediterranean species, which could alter seedlings developmental environment and ultimately populations regeneration and species composition. As such, germination timing should receive more attention by scientists and stakeholders, and should be included in forest vulnerability assessments and assisted migration programs aiming at long-term forest regeneration to adapt forests to climate change.

ecology↗