Biology subjects

Garnier, E.

Publications and source records attributed to Garnier, E..

6 recordsLinked to original sources

bioRxiv2026

u4atac regulates cilium biogenesis through splicing of the minor intron of tmem107l and rfx7b in zebrafish developing brain

Bi-allelic variants of RNU4ATAC, transcribed into the minor spliceosome component U4atac snRNA, are associated to variable severity of microcephaly, growth retardation, skeletal dysplasia and immunodeficiency as main features. Previous studies highlighted the dramatic effect of U4atac deficiency on splicing of U12-type introns, which represent less than 1% of all introns in the human genome. More recently, our team evidenced a link between U4atac and the primary cilium/centrosome complex through the identification of patients carrying RNU4ATAC bi-allelic variants and exhibiting an atypical Joubert syndrome, a well-known ciliopathy. Yet, the underlying mechanisms remain elusive. Here, we further explored the link of RNU4ATAC to primary cilium and aimed at identifying ciliary U12-type intron containing genes that contribute to the brain abnormalities seen in patients. For that, we performed a transcriptomic analysis of heads of our morpholino oligonucleotide (MO)-mediated u4atac zebrafish model. Through the combined analysis of the generated dataset with those obtained from RNU4ATAC patient cells, we identified two candidate genes: TMEM107, coding for a structural protein of the cilium transition zone, and RFX7, encoding a transcription factor involved in primary cilium formation. By conducting complementary genetic approaches in zebrafish model, we showed that both gene orthologues, tmem107l and rfx7b, functionally interact with u4atac and are required for correct brain development. Altogether, our findings establish TMEM107 and RFX7 as key components of the molecular pathway linking U4atac dysfunction to ciliary defects and impaired brain development, providing new physiopathological insights and therapeutic perspectives for RNU4ATAC-related disorders.

genetics↗

bioRxiv2025

FAIRTraits: an environmentally, methodologically and semantically enriched database of plant traits from Mediterranean populations of 240 species

Trait-based approaches have proven, and continue to offer strong potential to tackle key issues in ecology, including: (i) understanding the functioning of organisms and how it relates to the environment, (ii) identifying the rules governing the assembly of communities and the coexistence of species, (iii) understanding how the functioning of organisms scales up to that of ecosystems and controls some of the services they deliver to humans. We present FAIRTraits, a data set of plant traits assembled from a set of studies designed to address these issues in the pedo-climatic context of the Northern Mediterranean Basin, considered both a biodiversity and a climatic hotspot. The FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles were followed to ensure maximum visibility and reusability of these data. FAIRTraits compiles and standardizes trait data collected over the 1997-2023 period on six sites by the same research group, ensuring that a consistent methodology was followed. These data were obtained on individuals from 1,955 populations of 240 species belonging to 155 genera and 48 families (172 herbaceous and 39 woody species). It contains 189,452 records for 183 quantitative traits from the different plant organs (leaves, stems, roots, and reproductive parts), which have been grouped into 10 categories: allocation ratio, architecture, chemistry, dynamics, mechanics, microbial associations, morphology, phenology, physiology and plant size. Trait values are given at the level of individual measurements. Species-level values of height and phenology taken from a Mediterranean flora are also given. Species are characterized by plant family, life cycle, Raunkiaer lifeform, photosynthetic pathway and by an original successional stage indicator value. As trait values strongly depend on environmental conditions, we also provide information on the climatic conditions and soil properties of the sites, as well as on disturbance regimes of the plots in which sampled individuals were collected. The following steps were taken to ensure the FAIRness of the data set. Findable: metadata are described using the Ecological Metadata Language, and are deposited both on the InDoRES (CNRS/MNHN) metadata catalogue and on the GBIF data portal (see below); Accessible: FAIRTraits is available on the InDoRES repository, with a subset available on the GBIF data portal (see below); Interoperable: recognized taxonomical and terminological resources to qualify taxa and attributes have been used whenever possible, and fully described sampling protocols and measurement methods are given both for traits and environmental data. A subset of the data could be mapped onto the Darwin Core biodiversity standard, making it possible to display part of the data set on the GBIF portal, more traditionally used for taxonomic occurrence data. Reusable: (meta)data are thoroughly described using domain-relevant community standards, and the full data set is released under the CC-BY 4.0 license. We believe that these multiple efforts, spanning from the very content of the data set to its careful formatting, will make of FAIRTraits a highly valuable resource for trait-based research, both in terms of data analysis and reusability.

ecology↗

bioRxiv2024

Fine-scale co-ocurrence patterns in grasslands reflect competition for space rather than broad plant strategies

O_LIEstimating the sign and strength of interactions among plants is central to understand the dynamics and functioning of communities, but is challenging to do for species-rich communities. Instead, spatial relationships between plants (clustering or spatial segregation) are sometimes used as a surrogate for the net effect of interactions ocurring between plants (positive or negative, respectively). However, this approach remains poorly tested outside of arid and alpine ecosystems, the ecological settings it originated from. C_LIO_LIIn experimental rangelands, we explored how management intensification, sheep exclusion and a natural soil depth gradient control the level of plant spatial segregation, or negative co-occurrence, usually considered as a measurement of competition intensity. We link these spatial patterns to classical broad plant strategies defined by 11 locally measured functional traits, and to the realized vegetation height and cover. C_LIO_LIPlant segregation was highest when both grazing and fertilization were applied. Unexpectedly, general plant strategies (competitive, and acquisitive strategies) had little relationship with plant spatial patterns. Instead, spatial constraints increased segregation wherever cover was high and free bare ground was limited, or where plant growth is restricted by grazing to a few centimeters above ground. C_LIO_LIThese results show that fine-scale spatial patterns appear to capture competition for space, rather than for light or resources, as suggested by broad plant strategies. This may explain discrepancies in conclusions drawn from spatial patterns in grasslands, and clarifies the way towards a mechanistic understanding of spatial patterns. C_LIO_LISynthesis. The fine scale spatial organization of plant communities has been thought to reflect the intensity of competition among plants, but this approach has struggled to provide consistent results in grasslands. We show here that spatial patterns reflect competition for space rather than broad plant strategies captured by plant functional traits, helping us read observed plant spatial patterns to map interactions among plants in the field. C_LI

ecology↗

bioRxiv2022

Functional traits trade-offs define plant population stability worldwide

O_LIEcological theory posits that temporal stability patterns in plant populations are associated with differences in species ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, specially across different ecosystems. C_LIO_LITo address this, we compiled a global collection of long-term permanent vegetation records (>7000 plots from 78 datasets) from a wide range of habitats and combined this with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits and multivariate axes of trait variations (PCoA axes). C_LIO_LIWe found that species with greater leaf dry matter content and seed mass were consistently more stable over time (lower variability in species abundance) although other leaf traits played a significant role as well, albeit weaker. Using multivariate axes did not improve predictions by specific traits. C_LIO_LIOur results confirm existing theory, providing compelling empirical evidence on the importance of specific traits, which point at ecological trade-offs in different resource use and dispersal strategies, on the stability of plant populations worldwide. C_LI

ecology↗

bioRxiv2021

LOTVS: a global collection of permanent vegetation plots

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of vascular plants in permanent plots. With 79 datasets from five continents and 7789 vegetation time-series monitored for at least six years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology.

ecology↗

bioRxiv2018

Climate as a driver of adaptive variations in ecological strategies in Arabidopsis thaliana

Background and aimsThe CSR classification categorizes plant species between stress-tolerators, ruderals (R) and competitors (C). Initially proposed as a general framework to describe ecological strategies at the interspecific level, this scheme has recently been used to investigate the variation of strategies within species. For instance, ample variation along the S-R axis was found in Arabidopsis thaliana, with stress-tolerator accessions predominating in hot and dry regions.\n\nMethodsIn this study, the range of CSR strategies within A. thaliana was evaluated across 426 accessions originating from North Africa to Scandinavia. A position in the CSR strategy space was allocated for every accession based on three functional traits: leaf area, leaf dry matter content (LDMC) and specific leaf area (SLA). Results were related to climate at origin and compared to a previous study performed on the same species. Furthermore, the role of natural selection in phenotypic differentiation between lineages was investigated with Qst-Fst comparisons, using the large genetic information available for this species.\n\nKey resultsSubstantial variation in ecological strategies along the S-R axis was found in A. thaliana. By contrast with previous findings, stress-tolerator accessions predominated in cold climates, notably Scandinavia, where late flowering was associated with traits related to resource conservation such as high LDMC and low SLA. Because of trait plasticity, variations in CSR classification to growth conditions were also observed for the same genotypes.\n\nConclusionsThere is a latitudinal gradient of ecological strategies in A. thaliana as a result of within-species adaptation to climate. Our study also underlines the importance of growth conditions and of the methodology used for trait measurement, notably age versus stage measurement, to infer the strength and direction of trait-environment relationships. Taken together, this highlights the potential and limitations of the CSR classification to explain functional adaptation to the environment.

ecology↗