Biology subjects

Martin, M.-L.

Publications and source records attributed to Martin, M.-L..

7 recordsLinked to original sources

bioRxiv2026

How to be dispensable: genomic and transcriptomic determinants in maize genes

BackgroundPlant genomes harbour a substantial proportion of dispensable genes - present only in a subset of individuals - that differ from ubiquitously shared core genes in multiple genomic and expression features. While these differences have been repeatedly documented, the factors shaping gene dispensability remain poorly understood. ResultsWe assembled a pan-gene set from eight maize inbred lines from American and European germplasms, together with their transcriptomic profile across 22 tissues/conditions, revealing the genomic and transcriptomic determinants of maize gene dispensability. Multivariate analysis demonstrates that gene expression level and purifying selection - rather than gene size - are the primary factors distinguishing core from dispensable genes. Dispensable genes overlap Helitrons at 4.6 times the rate of core genes, implicating Helitron-mediated gene capture as a major mechanism of dispensable gene formation. Classifying genes into stably expressed, variably expressed, and on-off categories shows that all three classes contain dispensable genes, though in different proportions than for core genes. Contrary to previous assumptions, we show that dispensable genes can participate in basal biological functions just as core genes, and that gene duplication likely provides only a partial mechanism for functional complementation of accessory genes absence. ConclusionsOur results provide novel insights into the molecular and evolutionary factors distinguishing core from dispensable genes and into the biological mechanisms shaping gene dispensability in maize, and demonstrate that classifying genes by transcriptional patterns provides a powerful framework for understanding the biological functions and evolutionary dynamics of both core and dispensable genes.

plant biology↗

bioRxiv2026

Ancestral Genome Reconstruction.

AGR, for Ancestral Genome Reconstruction, is an automatic publicly available and open-source pipeline to infer paleogenomes from modern species genome comparisons exploiting the concept of inter-species chromosomal synteny relationships hierarchical clustering that can be used to unveil how ancestral genomes, genes, sequences and functions have been shaped during million years of present-day plant evolution.

genomics↗

bioRxiv2026

Comparative cross-species transcriptomic analysis identifies new candidates of Pooideae nitrate response

Nitrogen fertilizers are essential for crop productivity but cause environmental harm, necessitating the development of cultivars that thrive under limited nitrogen. This study investigates the transcriptomic response to nitrate in Arabidopsis thaliana (a model dicot), Brachypodium distachyon (a model Pooideae), and Hordeum vulgare (barley, a domesticated Pooideae) to identify conserved and species-specific molecular mechanisms. Using RNA-seq after 1.5 and 3 hours of nitrate treatment, we found that core nitrate-responsive biological processes - such as nitrate transport, assimilation, carbon metabolism, and hormone signaling - are largely conserved across species. However, comparative analysis at gene level based on orthology revealed specificities between the species. For instance, rRNA processing was uniquely stimulated in Arabidopsis, while cysteine biosynthesis from serine and gibberellin biosynthesis were specifically regulated in Brachypodium and barley. Orthologs of key nitrate-responsive genes (e.g., NRT, NLP, TCP20) exhibited variable regulation, reflecting potential adaptations linked to domestication or nutrient acquisition strategies. These findings highlight the importance of integrating model and crop species to uncover targets for improving nitrogen use efficiency in cereals. This study provides a general pipeline combining Gene Ontology enrichment and orthology analysis to compare transcriptomic responses across species. This workflow is highly useful for any comparative transcriptomic study in which differences in annotation quality and gene divergence between genomes may bias interpretation.

plant biology↗

bioRxiv2026

Root phenolics as potential drivers of preformed defenses and reduced disease susceptibility in a paradigm bread wheat mixture

Plant-plant interactions modulate foliar disease susceptibility in intraspecific mixtures. However, the molecular events including signals and responses underlying the reduction in disease susceptibility remain largely unexplored. Here, we developed an experimental system that can abolish root-mediated interactions between plants in a model of bread wheat varietal mixture. We then performed transcriptomic and metabolomic analyses to uncover the molecular responses linked to decreased susceptibility to Septoria tritici blotch in plant-plant interactions. Our analysis revealed that disrupting root chemical interactions impaired the reduction in susceptibility to Septoria and identified phenolic compounds as potential key mediators. The plant-plant interactions under study triggered significant molecular changes in specialized metabolism, biotic interactions, transporters, and responses to resources. Disrupting root interactions canceled both the macroscopic and molecular responses, thus providing a strong link between them. These insights provide a deeper understanding of the molecular basis of plant-plant interactions and the processes involved in reducing disease susceptibility in intraspecific mixtures. Significance statementNeighboring plants mediate resistance to leaf fungal pathogens by releasing root-derived molecules. These interactions trigger multi-omic reprogramming of defenses in both leaves and roots. Enhanced resistance in varietal mixtures is associated with the early activation of defense pathways. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=186 SRC="FIGDIR/small/699261v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@16f02a9org.highwire.dtl.DTLVardef@117b872org.highwire.dtl.DTLVardef@4e5243org.highwire.dtl.DTLVardef@1fac682_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

plant biology↗

bioRxiv2025

Unravelling the Genetic Architecture of Field Traits through Multi-Omics Platform Data integration

BackgroundIdentifying the genes and regulatory regions underlying a complex trait is a long-standing challenge. GWAS is generally used, but it suffers from insufficient power, lack of resolution and inefficiency to systematically screen for epistasis. We propose a systems genetics approach integrating multi-omics to overcome these limits. It was applied to a panel of maize with the objective to analyze the genetic determinism of yield in a multi-environment trials by combining genomics with transcriptomics measured on a platform. ResultsDespite the contrasted conditions between the platform and the fields, transcriptomics could be used to identify candidate genes. A presence-absence variation was in particular detected, and the transcripts allowed the identification of causal genes, increasing resolution in comparison to GWAS. In total, 47 genes were identified along the genome, and we could characterize their contrasted effect on yield according to environmental covariates. We demonstrated that the cis- and also the trans-eQTLs of these genes had an important contribution to genetic variance, suggesting a key role of epistatic interactions. In terms of predictive ability, the cis-eQTL resulted in an increase of 39 to 52% on average across the environments, in comparison to random SNP sets. ConclusionsBy efficiently combining multi-omics, it is possible to considerably increase our understanding of genetic architecture in comparison to standard GWAS. We demonstrated that omics data even measured on a phenotyping platform can be used for the analysis of field traits, opening the way for their routine use in plant breeding both for marker-assisted selection and bio-informed predictions.

genetics↗

bioRxiv2022

Plant-PLMview: a database for identifying cis-regulatory sequences with preferential positions in gene-proximal regions of plants

BackgroundEstablishing relationships between transcription factors and target genes is essential for understanding the mechanisms regulating gene expression, which play a fundamental role in plant adaptation to the local environment. Despite the importance of this research area and the tremendous progress in sequencing methods such as ChIP-seq and DAP-seq, we are still far from a complete reconstruction of the cis-regulatory landscape. Only a small number of transcription factors can be assessed from experimental data to identify their cis-regulatory binding sites. This highlights the role that in silico approaches can play to complement experimental data. ResultsWe have developed Plant-PLMview, a web-accessible database for detecting preferentially cis-regulatory sequences in the gene-proximal regions of 20 plant species. Users of Plant-PLMview can (i) access the proximal regions of controlled genes from 20 plant species, (ii) query their own DNA motifs or access 840 cis-regulatory sequences from various plant resources, and (iii) use a tool called PLMdetect to search for preferentially located motifs in the gene-proximal regions of a list of genes. Results are displayed via a web interface with a list of DNA motifs preferentially located in a region near the start or end of genes, the distribution of these motifs and associated annotations. In addition, a graphical map of the preferential locations of the motifs in the 5 and 3-proximal regions of genes provides an overview of all motifs and genes examined. ConclusionPlant-PLMview provides the opportunity to study the proximal landscape of gene regulation in 20 plant genomes. The originality of the database lies in its ease of use thanks to the curated data (cis-regulatory sequences and proximal regions of genes) and the possibility to search through PLMdetect in the 5-gene-proximal region, but also in the 3-gene-proximal region, which is rarely explored. The web interface provides numerous graphical views that allow the users to get an overview and interpret the results more easily.

bioinformatics↗

bioRxiv2022

Genome-wide identification of preferentially located motifs in gene-proximal regions provides new insights into cis-regulatory sequences in plants

The identification of cis-regulatory elements controlling gene expression is an arduous challenge that is being actively explored to discover the key genetic factors responsible for traits of agronomic interest. Here, we have used a de novo and genome-wide approach for preferentially located motif (PLM) detection to investigate the proximal cis-regulatory landscape of Arabidopsis thaliana and Zea mays. We report three groups of PLMs in each gene-proximal region and emphasize conserved PLMs in both species, particularly in the 3-gene-proximal region. Comparison with resources of transcription factor and microRNA binding sites indicates that 79% of the identified PLMs are unassigned, although some are supported by MNase-defined cistrome occupancy analysis. Enrichment analyses further reveal that unassigned PLMs provide functional predictions distinct from those inferred by transcription factor and microRNA binding sites. Our study provides a comprehensive map of PLMs and points at their potential utility for future characterization of orphan genes in plants.

genomics↗