Biology subjects

Fournier, D.

Publications and source records attributed to Fournier, D..

5 recordsLinked to original sources

bioRxiv2026

AnthropInsect: a global database of insect traits and anthropogenic associations.

Insect research remains hindered by limited data availability and fragmented knowledge compared to other, better-documented taxonomic groups. Yet, both the macroecological and the insect research communities highlight the need to integrate large-scale ecological trait datasets for insects. Insects and humans are interconnected through diverse relationships, ranging from beneficial interactions, such as the use of insects as nutritional resources, to adverse impacts, including their role in to the emergence and spread of biological invasions. Understanding the traits of insects associated with human use, movement and impact is therefore important for linking insects to ecosystem function and global change. We present AnthropInsect, one of the largest database on insect traits to date, which uniquely includes variables describing human-insect associations. AnthropInsect describes species through 35 variables grouped into five categories: (i) taxonomic descriptors; (ii) ecological descriptors (native bioregions and habitat); (iii) human-insect associations (edibility and invasive status); (iv) functional traits (behavior, morphology, life history and feeding); (v) and macroecological descriptors of native-range geography and climate. AnthropInsect currently includes 5867 species across six major orders: Coleoptera, Lepidoptera, Hemiptera, Hymenoptera, Orthoptera and Blattodea. Data extracted from peer-reviewed, grey literature and from existing databases were standardized and validated with expert knowledge to ensure accuracy. By providing traits data with information on insect-human interactions, this rigorously curated resource supports global research in entomology, ecology, conservation, and global change.

ecology↗

bioRxiv2022

Mitotic bookmarking redundancy by nuclear receptors mediates robust post-mitotic reactivation of the pluripotency network.

Mitotic bookmarking transcription factors (TFs) are thought to mediate rapid and accurate post-mitotic gene reactivation. However, the loss of individual bookmarking TFs often leads to the deregulation of only a small proportion of their mitotic targets, raising doubts on the significance and importance of their bookmarking function. Here, we used targeted proteomics of the mitotic bookmarking TF ESRRB, an orphan nuclear receptor, to discover an unexpected redundancy among members of the protein superfamily of nuclear receptors. Focusing on the nuclear receptor NR5A2, which together with ES-RRB is essential for mouse pluripotency, we demonstrate conjoint bookmarking activity of both factors on promoters and enhancers of a large fraction of active genes, particularly the most rapidly and strongly reactivated ones. Upon fast and simultaneous degradation of both factors during mitotic exit, hundreds of mitotic targets of ESRRB/NR5A2, including key players of the pluripotency network, display attenuated transcriptional reactivation. We propose that redundancy in mitotic bookmarking TFs, especially by nuclear receptors, confers robustness to the reestablishment of gene regulatory networks after mitosis.

molecular biology↗

bioRxiv2018

Imputation of posterior linkage probability relations reveals a significant influence of structural 3D constraints on linkage disequilibrium

Genetic association studies have become increasingly important in unraveling the genetics of diseases or complex traits. Despite their value for modern genetics, conflicting conclusions often arise through the difficulty of confirming and replicating experimental results. We argue that this problem is largely based on the application of statistical relation measures that are not appropriate for genomic data analysis and demonstrate that the standard measures used for Genome-wide association studies or genomics linkage analysis bear a statistic bias. This may come from the violation of underlying assumptions (such as independence or stationarity) as well as from other conceptual limitations in the measures or relations, such as missing invariance with respect to coding or the inability to reflect latent factors. Attempts to introduce unbiased relation measures that avoid these limitations are usually computationally expensive and do not scale for large data sizes being typical for genomics applications.\n\nTo tackle these problems, we propose a straightforwardly computable relation measure called Linkage Probability (LP). This measure provides the posterior probability of a relation between two categorical data sets and considers potential biases from latent variables. We compare several aspects of popular relation measures through an illustrative example and human genomics data. We demonstrate that the application of LP to the analysis of Single Nucleotide Polymorphisms (SNP) reveals latent 3D steric effects within 1D SNP data, that approximate to chromatin loops captured by high resolution Hi-C maps.

bioinformatics↗

bioRxiv2017

Deciphering the histone code to build the genome structure

Histones are punctuated with small chemical modifications that alter their interaction with DNA. One attractive hypothesis stipulates that certain combinations of these histone modifications may function, alone or together, as a part of a predictive histone code to provide ground rules for chromatin folding. We consider four features that relate histone modifications to chromatin folding: charge neutralisation, molecular specificity, robustness and evolvability. Next, we present evidence for the association among different histone modifications at various levels of chromatin organisation and show how these relationships relate to function such as transcription, replication and cell division. Finally, we propose a model where the histone code can set critical checkpoints for chromatin to fold reversibly between different orders of the organisation in response to a biological stimulus.

cell biology↗

bioRxiv2016

Histone code and higher-order chromatin folding: A hypothesis

Histone modifications alone or in combination are thought to modulate chromatin structure and function; a concept termed histone code. By combining evidence from several studies, we investigated if the histone code can play a role in higher-order folding of chromatin. Firstly using genomic data, we analyzed associations between histone modifications at the nucleosome level. We could dissect the composition of individual nucleosomes into five predicted clusters of histone modifications. Secondly, by assembling the raw reads of histone modifications at various length scales, we noticed that the histone mark relationships that exist at nucleosome level tend to be maintained at the higher orders of chromatin folding. Recently, a high-resolution imaging study showed that histone marks belonging to three of the five predicted clusters show structurally distinct and anti-correlated chromatin domains at the level of chromosomes. This made us think that the histone code can have a significant impact in the overall compaction of DNA: at the level of nucleosomes, at the level of genes, and finally at the level of chromosomes. As a result, in this article, we put forward a theory where the histone code drives not only the functionality but also the higher-order folding and compaction of chromatin.

biophysics↗