Biology subjects

Lavenier, D.

Publications and source records attributed to Lavenier, D..

9 recordsLinked to original sources

bioRxiv2025

SNooPy: a statistical framework for long-read metagenomic variant calling

Current long-read single-nucleotide variant callers were designed primarily for genomic data--particularly human genomes. While some have been used on metagenomic data, their underlying assumptions and training procedures fail to account for the inherent complexity of metagenomic samples. To date, no long-read variant caller has been purpose-built for metagenomic applications. To address this gap, we present SNooPy, a SNP-calling tool that implements a new statistical framework tailored to long-read metagenomic data. Unlike previous genomic methods, our approach makes no assumptions about the number of haplotypes present, their evolutionary relationships, or their sequence divergence. We demonstrate that SNooPy outperforms both traditional statistical and deep learning-based SNP callers. Our results suggest that future integration of this framework with deep learning approaches could further enhance variant calling performance. SNooPy is freely available on github.com/rolandfaure/snoopy.

bioinformatics↗

bioRxiv2025

Alice: fast and haplotype-aware assembly of high-fidelity reads based on MSR sketching

BackgroundLong-read metagenomic assembly is becoming a critical bottleneck in microbiome analysis, as deep sequencing generates massive datasets that existing methods struggle to assemble while maintaining strain resolution. ResultsWe present Alice, a lightweight long-read assembler that achieves orders-of-magnitude speedups through a new sequence sketching technique, MSR sketching, compatible with classical assembly methods. Alice assembles a 235 Gbp soil metagenome in 5 hours using only 84 GB RAM--a task that causes most competing methods to exhaust our computational resources (500 GB RAM and 7 days runtime). Across diverse benchmarks, Alice delivered strain-resolved assemblies an order of magnitude faster than state-of-the-art approaches, while producing the most complete assemblies in some cases. ConclusionsMSR sketching overcomes computational barriers in metagenomic assembly, enabling fast, memory-efficient strain-resolved analysis of massive datasets. While Alices assemblies were more fragmented than with other assemblers, this approach establishes a promising paradigm for scalable metagenomic analysis.

bioinformatics↗

bioRxiv2025

De Bruijn Graph Partitioning for Scalable and Accurate DNA Storage Processing

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSDNA-based data storage offers a compelling solution for long-term, high-density archiving. In this framework, accurately reconstructing high-quality encoded sequences after sequencing is critical, as it has a direct impact on the design of error-correcting codes optimized for DNA storage. Furthermore, efficient and scalable processing is essential to manage the large volumes of data expected in such applications. ResultsWe introduce a novel method based on de Bruijn graph partitioning, enabling fast and accurate processing of sequencing data regardless of the underlying sequencing technology and without requiring prior knowledge of the information encoded in the oligonucleotides. Evaluated on both synthetic and real datasets, the method achieves excellent precision and recall. It is implemented in C++ within the software ConCluD and optimized for multi-core servers. Our experiments demonstrated that a dataset of 55 million reads, corresponding to a 135 MB binary file, can be processed in less than 10 minutes on a 16 hyper-threaded core server.

bioinformatics↗

bioRxiv2025

Comprehensive annotation of olfactory and gustatory receptor genes and transposable elements revealed their evolutionary dynamics in aphids

Understanding the molecular evolution of genes involved in parasite adaptation and the role of transposable elements (TEs) in driving their diversification is key to unraveling how populations adapt to their environments. In phytophagous insects like aphids, olfactory (OR) and gustatory receptor (GR) genes are crucial for host recognition, yet their post-duplication evolution remains insufficiently explored. Here, we analyzed 521 OR and 399 GR genes, alongside TEs, across 12 aphid genomes with varying host ranges. Aphid lineages with broader host ranges exhibited higher evolutionary rates, driven by gene family expansions linked to host interaction, including lipid metabolism, immune function, and transposase activity. The evolution of OR and GR genes post-duplication was shaped by diversifying selection, with bursts of positive selection followed by long periods of purifying selection, consistent with adaptation to new hosts. OR and GR genes originated from proximal and tandem duplications, with younger TE activity enriched near these genes compared to other genomic regions, suggesting a role for TEs in catalyzing tandem duplications and fueling diversification. The star-like topology of the OR phylogenetic tree, low synteny, and recent TE activity around OR genes support a faster evolutionary rate for ORs than GRs - a trend observed in other insect taxa. This study provides insights into molecular mechanisms underlying host adaptation in aphids and presents the first high-quality genome assembly of Dysaphis plantaginea, a major apple pest, with a comprehensive annotation of chemosensory genes and TEs. These resources offer a foundation for research on aphid genome evolution, insect-plant interactions.

molecular biology↗

bioRxiv2024

HairSplitter: haplotype assembly from long, noisy reads

MotivationLong-read assemblers face challenges in discerning closely related viral or bacterial strains, often collapsing similar strains into a single sequence. This limitation has been hampering metagenome analysis, as diverse strains may harbor crucial functional distinctions. ResultsWe introduce a novel software, HairSplitter, designed to retrieve strains from a partially or totally collapsed assembly and long reads. The method uses a custom variant-calling process to operate with erroneous long reads and introduces a new read binning algorithm to recover an a priori unknown number of strains. On noisy long reads, HairSplitter recovers more strains while being faster than state-of-the-art tools, both in the cases of viruses and bacteria. AvailabilityHairSplitter is freely available on GitHub at github.com/RolandFaure/HairSplitter. Contactroland.faure@irisa.fr

bioinformatics↗

bioRxiv2023

In vitro construction and long read sequencing analysis of a 24 kb long artificial DNA sequence encoding the Universal Declaration of the Rights of Man and of the Citizen.

In absence of DNA template, the ab initio production of long double-stranded DNA molecules of predefined sequences is particularly challenging. The DNA synthesis step remains a bottleneck for many applications such as functional assessment of ancestral genes, analysis of alternative splicing or DNA-based data storage. We propose in this report a fully in vitro protocol to generate very long double-stranded DNA molecule starting from commercially available short DNA blocks in less than 3 days. This innovative application of Golden Gate assembly allowed us to streamline the assembly process to produce a 24 kb long DNA molecule storing part of the Universal Declaration of Human rights and citizens. The DNA molecule produced can be readily cloned into suitable host/vector system for amplification and selection.

synthetic biology↗

bioRxiv2019

SVJedi: Genotyping structural variations with long reads

MotivationStudies on structural variants (SV) are expanding rapidly. As a result, and thanks to third generation sequencing technologies, the number of discovered SVs is increasing, especially in the human genome. At the same time, for several applications such as clinical diagnoses, it is important to genotype newly sequenced individuals on well defined and characterized SVs. Whereas several SV genotypers have been developed for short read data, there is a lack of such dedicated tool to assess whether known SVs are present or not in a new long read sequenced sample, such as the one produced by Pacific Biosciences or Oxford Nanopore Technologies. ResultsWe present a novel method to genotype known SVs from long read sequencing data. The method is based on the generation of a set of reference sequences that represent the two alleles of each structural variant. Long reads are aligned to these reference sequences. Alignments are then analyzed and filtered out to keep only informative ones, to quantify and estimate the presence of each SV allele and the allele frequencies. We provide an implementation of the method, SVJedi, to genotype insertions and deletions with long reads. The tool has been applied to both simulated and real human datasets and achieves high genotyping accuracy. We also demonstrate that SV genotyping is considerably improved with SVJedi compared to other approaches, namely SV discovery and short read SV genotyping approaches. Availabilityhttps://github.com/llecompte/SVJedi.git Contactlolita.lecompte@inria.fr

bioinformatics↗

bioRxiv2017

Global optimization approach for circular and chloroplast genome assembly

We describe a global optimization approach for genome assembly where the steps of scaffolding, gap-filling, and scaffold extension are simultaneously solved in the framework of a common objective function. The approach is based on integer programming model for solving genome scaffolding as a problem of finding a long simple path in a specific graph that satisfies additional constraints encoding the insert-size information. The optimal solution of this problem allows one to obtain new kind of contigs that we call distance-based contig. We test the algorithm on a benchmark of chloroplasts and compare the quality of the results with recent scaffolders.

bioinformatics↗

bioRxiv2017

Critical Assessment of Metagenome Interpretation - a benchmark of computational metagenomics software

In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions.

bioinformatics↗