Biology subjects

Depuydt, T.

Publications and source records attributed to Depuydt, T..

6 recordsLinked to original sources

bioRxiv2024

Transit amplifying cells balance growth and differentiation in above-ground meristems

In both animals and plants, stem cell niches balance between cell-renewal and the generation of progeny cells that differentiate into specialized tissues. The multipotent and highly proliferative transit amplifying cells (TACs) integrate signals from stem cells and their differentiating progeny cells. Here we used spatial transcriptomics mapped to individual cells to illustrate the localization of TACs in maize meristems based on transcriptional gradients. Through genetic interactions and fluctuations in the transcriptional gradients we show that the multiplicative cell divisions are independently controlled from the TAC cell divisions. The dynamic nature of transcriptional variation in response to cell state or environment, together with the potential to improve yield by their modulation highlights the importance of finetuned modulation of networks rather than constitutive perturbations for crop improvement.

plant biology↗

bioRxiv2023

MINI-EX version 2: cell-type-specific gene regulatory network inference using an integrative single-cell transcriptomics approach

Understanding and predicting cell-type-specific gene regulatory networks (GRNs) is essential for unraveling the complex interactions between transcription factors (TFs) that modulate the expression of target genes and control diverse biological processes in multicellular organisms. MINI-EX (Motif-Informed Network Inference based on single-cell EXpression data) is an integrative tool tailored for identifying cell-type-specific GRNs in plants. Leveraging single-cell transcriptomics data, MINI-EX constructs expression-based networks and integrates TF motif information to produce GRNs with increased accuracy. Furthermore, it assigns regulatory modules to distinct cell types and prioritizes candidate regulators by employing a strategy that encompasses network centrality measures, functional annotations, and expression specificity. Taken together, MINI-EX offers a powerful approach to identify cell-type-specific transcriptional cascades and enhance our understanding of TF functions in plant biology. Here, we discuss recent advancements in the tools latest version and explain how single-cell GRNs can be identified for non-model species lacking TF motif information. Additionally, we provide a comprehensive guide to use MINI-EX, covering the entire pipeline from preparing input files starting from a single-cell experiment, over configuring parameters, to interpreting output data.

plant biology↗

bioRxiv2023

MINI-AC: Inference of plant gene regulatory networks using bulk or single-cell accessible chromatin profiles

Gene regulatory networks (GRNs) represent the interactions between transcription factors (TF) and their target genes. GRNs control transcriptional programs involved in growth, development and stress responses, ultimately affecting diverse agricultural traits. While recent developments in accessible chromatin (AC) profiling technologies make it possible to identify context-specific regulatory DNA, learning the underlying GRNs remains a major challenge. We developed MINI-AC (Motif-Informed Network Inference based on Accessible Chromatin), a method that combines AC data from bulk or single-cell experiments with TF binding site information to learn GRNs in plants. We benchmarked MINI-AC using bulk AC datasets from different Arabidopsis thaliana tissues and showed that it outperforms other methods to identify correct TFs binding sites. In maize, a crop with a complex genome and abundant distal AC regions, MINI-AC successfully inferred leaf GRNs with experimentally confirmed, both proximal and distal, TF-target gene interactions. Furthermore, we showed that both AC regions and footprints are valid alternatives to infer AC-based GRNs with MINI-AC. Finally, we combined MINI-AC predictions from bulk and single-cell AC datasets to identify general and cell-type specific maize leaf regulators. Focusing on C4 metabolism, we identified diverse regulatory interactions in specialized cell types for this photosynthetic pathway. MINI-AC represents a powerful tool for inferring accurate AC-derived GRNs in plants and identifying known and novel candidate regulators, improving our understanding of gene regulation in plants.

bioinformatics↗

bioRxiv2022

Regulatory and evolutionary annotation identifies KAN1, MYB44 and PIF4 as regulators of Arabidopsis lincRNAs expressed in root

Thousands of long intergenic noncoding RNAs (lincRNAs) have been identified in plant genomes. While some lincRNAs have been characterized as important regulators in different biological processes, little is known about the transcriptional regulation for most plant lincRNAs. Through the integration of eight annotation resources, we defined 6,599 high-confidence lincRNA loci in Arabidopsis thaliana. For lincRNAs belonging to different evolutionary age categories, we identified major differences in sequence and chromatin features, as well as in the level of conservation and purifying selection acting during evolution. Spatiotemporal gene expression profiles combined with transcription factor (TF) chromatin immunoprecipitation data were used to construct a TF- lincRNA regulatory network containing 2,659 lincRNAs and 15,686 interactions. We found that properties characterizing lincRNA expression, conservation and regulation differ between plants and animals. Experimental validation confirmed the role of three TFs, KAN1, MYB44, and PIF4, as key regulators controlling root- specific lincRNA expression, demonstrating the predictive power of our network. Furthermore, we identified 58 lincRNAs, regulated by these TFs, showing strong root cell-type specific expression or chromatin accessibility, which are linked with GWAS genetic associations related to root system development and growth. The multi-level genome-wide characterization covering chromatin state information, promoter conservation, and ChIP-based TF binding, for all detectable lincRNAs across 769 expression samples, permits to rapidly define the biological context and relevance of lincRNAs in Arabidopsis regulatory networks. One-line sentenceA multi-level Arabidopsis gene regulatory network identifies novel regulators controlling root-specific lincRNA expression, offering a promising strategy to identify lincRNAs involved in plant biology.

plant biology↗

bioRxiv2021

Multi-omics network-based functional annotation of unknown Arabidopsis genes

Unraveling gene functions is pivotal to understand the signaling cascades controlling plant development and stress responses. Given that experimental profiling is costly and labor intensive, the need for high-confidence computational annotations is evident. In contrast to detailed gene-specific functional information, transcriptomics data is widely available in both model and crop species. Here, we developed a novel automated function prediction (AFP) algorithm, leveraging complementary information present in multiple expression datasets through the analysis of study-specific gene co-expression networks. Benchmarking the prediction performance on recently characterized Arabidopsis thaliana genes, we showed that our method outperforms state-of-the-art expression-based approaches. Next, we predicted biological process annotations for known (n=15,790) and unknown (n=11,865) genes in A. thaliana and validated our predictions using experimental protein-DNA and protein-protein interaction data (covering >220 thousand interactions in total), obtaining a set of high-confidence functional annotations. 5,054 (42.6%) unknown genes were assigned at least one validated annotation, and 3,408 (53.0%) genes with only computational annotations gained at least one novel validated function. These omics-supported functional annotations shed light on a variety of developmental processes and molecular responses, such as flower and root development, defense responses to fungi and bacteria, and phytohormone signaling, and help alleviate the knowledge gap of biological process annotations in Arabidopsis. An in-depth analysis of two context-specific networks, modeling seed development and response to water deprivation, shows how previously uncharacterized genes function within the respective networks. Moreover, our AFP approach can be applied in future studies to facilitate gene discovery for crop improvement. Significance statementFor the majority of plant genes, it is unknown in which processes they are involved. Using a multi-omics approach, leveraging transcriptome, protein-DNA and protein-protein interaction data, we functionally annotated 42.6% of unknown Arabidopsis thaliana genes, providing insight into a variety of developmental processes and molecular responses, as well as a resource of annotations which can be explored by the community to facilitate future research.

plant biology↗

bioRxiv2020

Systematic and functional analysis of horizontal gene transfer events in diatoms.

1.Diatoms are a diverse group of mainly photosynthetic algae, responsible for 20% of worldwide oxygen production, which can rapidly respond to favourable conditions and often outcompete other phytoplankton. We investigated the contribution of horizontal gene transfer (HGT) to its ecological success. A systematic phylogeny-based bacterial HGT detection procedure across nine sequenced diatoms showed that 3-5% of their proteome has a horizontal origin and a large influx occurred at the ancestor of diatoms. More than 90% of HGT genes are expressed, and species-specific HGT genes in Phaeodactylum tricornutum undergo strong purifying selection. They are implicated in several processes including environmental sensing, and expand the metabolic toolbox. Cobalamin (vitamin B12) is an essential cofactor for roughly half of the diatoms and is only produced by bacteria. Genes involved in its final synthesis were detected as HGT, including five consecutive enzymes in Fragilariopsis cylindrus. This might give diatoms originating from the Southern Ocean, a region typically depleted in cobalamin, a competitive advantage. Overall, we show that HGT is a prevalent mechanism that is actively used in diatoms to expand its adaptive capabilities.

evolutionary biology↗