Biology subjects

Daric, V.

Publications and source records attributed to Daric, V..

3 recordsLinked to original sources

bioRxiv2026

A gapless telomere-to-telomere reference genome of Ostreococcus tauri RCC4221 with expanded annotation of medium-sized ncRNAs

Marine photosynthetic microbes contribute substantially to global primary production, yet many algal lineages still lack reference genomes with the continuity and annotation quality required for fine-scale structural, regulatory and comparative analyses. Ostreococcus tauri, one of the smallest known free-living photosynthetic eukaryotes, has been a model marine picoeukaryote for over two decades. Despite successive improvements to its historical reference genome, previous assemblies retained hundreds of gaps and incomplete genes, hampering high-resolution genomic analyses. Here, we present O. tauri RCC4221 genome version 2026, a telomere-to-telomere assembly of all 20 chromosomes spanning 13.34 Mb with no gaps. This assembly combines PacBio long-read sequencing, Illumina short-read polishing, correction of unresolved regions guided by independent Nanopore-based assemblies. The updated reference supports a curated annotation comprising 7,683 protein-coding genes, 48 tRNA genes, 3 rRNA operons, 116 medium-sized noncoding RNAs, one signal recognition particle RNA and 138 small nucleolar RNAs. It also improves gene-model integrity and recovers candidate coding loci absent from the 2014 reference. Structural analyses resolved the organization of the two atypical low-GC chromosome 2 and 19 that contain duplicated regions that were collapsed or misrepresented in previous assemblies. Finally, bisulfite sequencing and PacBio SMRT sequencing revealed a dual DNA methylation landscape, with CG-context cytosine methylation concentrated in gene bodies and N6-methyladenosine (m6A) enriched at the start codon. The updated O. tauri 2026 assembly provides a complete and curated reference resource for chromosome biology, comparative genomics, epigenomics and RNA biology in a model marine picoeukaryote.

genomics↗

bioRxiv2024

Unveiling Crocosphaera responses to phosphorus depletion: insights from genome analysis and functional characterization

Unicellular, nitrogen-fixing cyanobacteria (UCYN) thrive and support primary production in oligotrophic oceans, playing a significant role in the marine nitrogen cycle. Crocosphaera sp, a model for studying marine nitrogen fixation, is adapted to low phosphate (Pi) conditions. Yet, how Crocosphaera copes with Pi depletion is rather poorly understood. We present genomics analysis of Pi stress-responsive genes in this genus, encompassing six C. watsonii genomes and two strains isolated in coastal environments, C. subtropica and C. chwakensis. We identified genes involved in Pi signaling, uptake, and dissolved organic phosphorus (DOP) hydrolysis. Results showed different genetic potentials to cope with Pi scarcity between the Crocosphaera strains. Physiological monitoring of cultures of C. watsonii WH8501 exposed to Pi depletion highlighted a capacity to divide several times and survive for a few more days, albeit with a skewed C:N:P stoichiometry. Upon addition of DOP, cultures efficiently recovered to a growth rate and cell composition equivalent to those observed under favorable conditions. The concomitant transcription analysis revealed diel expression patterns of Pi-related genes and endogenous clock genes, suggesting a possible circadian regulation. Our data deepen our understanding of the growth strategies Crocosphaera employs in Pi-limited environments, offering broader insights into microbial resilience in marine ecosystems.

microbiology↗

bioRxiv2020

ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture

BackgroundDeep learning methods have outperformed previous techniques in most computer vision tasks, including image-based plant phenotyping. However, massive data collection of root traits and the development of associated artificial intelligence approaches have been hampered by the inaccessibility of the rhizosphere. Here we present ChronoRoot, a system which combines 3D printed open-hardware with deep segmentation networks for high temporal resolution phenotyping of plant roots in agarized medium. ResultsWe developed a novel deep learning based root extraction method which leverages the latest advances in convolutional neural networks for image segmentation, and incorporates temporal consistency into the root system architecture reconstruction process. Automatic extraction of phenotypic parameters from sequences of images allowed a comprehensive characterization of the root system growth dynamics. Furthermore, novel time-associated parameters emerged from the analysis of spectral features derived from temporal signals. ConclusionsAltogether, our work shows that the combination of machine intelligence methods and a 3D-printed device expands the possibilities of root high-throughput phenotyping for genetics and natural variation studies as well as the screening of clock-related mutants, revealing novel root traits.

plant biology↗