Biology subjects

Monat, C.

Publications and source records attributed to Monat, C..

6 recordsLinked to original sources

bioRxiv2026

SaVanache: indexing and visualizing pangenome variation graphs

With the rapid increase in genome sequencing and the growing availability of genomic resources, genomics is shifting toward pangenome representations that capture intra- and inter-specific diversity by integrating multiple genomes into a single entity. These pangenomes are increasingly modeled as graphs, encoding complex genomic variations in structures such as de Bruijn or variation graphs. However, while genome browsers provide standard and effective solutions for visualizing single or limited numbers of genomes, equivalent interactive tools for graph-based pangenomes remain limited, particularly for variation graph models. We developed SaVanache, a multi-resolution visualization interface designed to explore pangenome variation graphs at various depths. SaVanache enables the exploration of both global diversity and structural variations (SVs) across genomes relative to a user-defined linear pivot genome. Unlike synteny viewers, SaVanache emphasizes variations by representing SV types through a dedicated set of glyphs, facilitating intuitive one-to-many comparisons. To support smooth exploration, SaVanache preprocesses a Graphical Fragment Assembly (GFA) pangenome file into optimized index and data structures, enabling fast, real-time queries on large pangenome graphs. By combining advanced visualization techniques with efficient data handling, SaVanache provides a robust tool for scientists to analyze and visualize genetic variation within genomes and pangenomes, facilitating the identification of genetic determinants associated with phenotypes of interest and fully exploiting current genomic resources. Author summaryWe introduce SaVanache, an innovative tool that transforms the way we explore genomic resources. SaVanache allows visualization and analysis of pangenome variation graphs (PVGs), which capture genomic diversity by integrating structural variants (SV) and single nucleotide polymorphisms (SNPs) across multiple genomes. Unlike traditional genome browsers limited to a few genomes, SaVanache offers a multi-level, user-friendly interface that allows users to explore from whole pangenomes down to individual structural variants, enabling multidimensional research and development. Using a linear pivot genome as a visual reference, SaVanache simplifies complex PVG structures into intuitive comparisons. It efficiently handles large datasets and speeds up data retrieval through internal parsing. The front-end, built with modern JavaScript frameworks, provides interactive and responsive visualization, while the Python/Django backend supports real-time data updates. Users can detect and classify SVs by comparing syntenic segments between genomes, visualized through a novel glyph-based system that uses shapes and colors to represent complex rearrangements. SaVanache supports seamless zooming from chromosome-wide to nucleotide-level views, interactive diversity scatterplots, dynamic pivot genome switching, and grouping genomes by metadata to explore genotype-phenotype links. In addition, export functions bridge visualization with downstream bioinformatics. Developed with user feedback, SaVanache balances biological relevance and computational efficiency, overcoming PVG complexity to empower users with unprecedented insight into genomic diversity and SVs.

bioinformatics↗

bioRxiv2022

Wheat Panache - a pangenome graph database representing presence/absence variation across 16 bread wheat genomes

Bread wheat is one of humanitys most important staple crops, characterized by a large and complex genome with a high level of gene presence/absence variation between cultivars, hampering genomic approaches for crop improvement. With the growing global population and the increasing impact of climate change on crop yield, there is an urgent need to apply genomic approaches to accelerate wheat breeding. With recent advances in DNA sequencing technology, a growing number of high-quality reference genomes are becoming available, reflecting the genetic content of a diverse range of cultivars. However, information on the presence or absence of genomic regions has been hard to visualize and interrogate due to the size of these genomes and the lack of suitable bioinformatics tools. To address this limitation, we have produced a wheat pangenome graph maintained within an online database to facilitate interrogation and comparison of wheat cultivar genomes. The database allows users to visualize regions of the pangenome to assess presence/absence variation between bread wheat genomes. Database URL: http://www.appliedbioinformatics.com.au/wheat_panache

bioinformatics↗

bioRxiv2021

Long-read and chromosome-scale assembly of the hexaploid wheat genome achieves higher resolution for research and breeding

The sequencing of the wheat (Triticum aestivum) genome has been a methodological challenge for many years due to its large size (15.5 Gb), repeat content, and hexaploidy. Many initiatives aiming at obtaining a reference genome of cultivar Chinese Spring have been launched in the past years and it was achieved in 2018 as the result of a huge effort to combine short-read sequencing with many other resources. Reference-quality genome assemblies were then produced for other accessions but the rapid evolution of sequencing technologies offers opportunities to reach high-quality standards at lower cost. Here, we report on an optimized procedure based on long-reads produced on the ONT (Oxford Nanopore Technology) PromethION device to assemble the genome of the French bread wheat cultivar Renan. We provide the most contiguous and complete chromosome-scale assembly of a bread wheat genome to date. Coupled with an annotation based on RNA-Seq data, this resource will be valuable for the crop community and will facilitate the rapid selection of agronomically important traits. We also provide a framework to generate high-quality assemblies of complex genomes using ONT.

genomics↗

bioRxiv2019

TRITEX: chromosome-scale sequence assembly of Triticeae genomes with open-source tools

Chromosome-scale genome sequence assemblies underpin pan-genomic studies. Recent genome assembly efforts in the large-genome Triticeae crops wheat and barley have relied on the commercial closed-source assembly algorithm DeNovoMagic. We have developed TRITEX, an open-source computational workflow that combines paired-end, mate-pair, 10X Genomics linked-read with chromosome conformation capture sequencing data to construct sequence scaffolds with megabase-scale contiguity ordered into chromosomal pseudomolecules. We evaluated the performance of TRITEX on publicly available sequence data of tetraploid wild emmer and hexaploid bread wheat, and constructed an improved annotated reference genome sequence assembly of the barley cultivar Morex as a community resource.

genomics↗

bioRxiv2018

TOGGLe, a flexible framework for easily building complex workflows and performing robust large-scale NGS analyses

The advent of NGS has intensified the need for robust pipelines to perform high-performance automated analyses. The required softwares depend on the sequencing method used to produce raw data (e.g. Whole genome sequencing, Genotyping By Sequencing, RNASeq) as well as the kind of analyses to carry on (GWAS, population structure, differential expression). These tools have to be generic and scalable, and should meet the biologists needs.\n\nHere, we present the new version of TOGGLe (Toolbox for Generic NGS Analyses), a simple and highly flexible framework to easily and quickly generate pipelines for large-scale second-and third-generation sequencing analyses, including multi-threading support. TOGGLe comprises a workflow manager designed to be as effortless as possible to use for biologists, so the focus can remain on the analyses. Embedded pipelines are easily customizable and supported analyses are reproducible and shareable. TOGGLe is designed as a generic, adaptable and fast evolutive solution, and has been tested and used in large-scale projects with numerous samples and organisms. It is freely available at http://toggle.southgreen.fr/ under the GNU GPLv3/CeCill-C licenses) and can be deployed onto HPC clusters as well as on local machines.

bioinformatics↗

bioRxiv2018

Comparison of two African rice species through a new pan-genomic approach on massive data

Pangenome theory implies that individuals from a given group/species share only a given part of their genome (core-genome), the remaining part being the dispensable one. Domestication process implies a small number of founder individuals, and thus a large core-genome compared to dispensable at the first steps of domestication. We sequenced at high depth 120 cultivated African rice Oryza glaberrima and of 74 wild relatives O. barthii, and mapped them on the external reference from Asian rice O. sativa. We then use a novel DepthOfCoverage approach to identif missing genes. After comparing the two species, we shown that the cultivated species has a smaller core-genome than the wild one, as well as an expected smaller dispensable one. This unexpected output however replaces in perspective the inadequacy of cultivated crops to wilderness.

genomics↗