Daniel Gautheret

MOCHI enables systematic identification of candidate independent intronic transcriptional signals from short-read RNA-seq data

MOCHI identifies candidate independent intronic transcripts from short-read RNA-seq data, revealing novel transcripts associated with cancer survival.

Metappuccino: Large Language Model-driven Reconstruction of Sequence Read Archive Metadata for Cancer Research

Metappuccino uses a fine-tuned large language model to enrich metadata from RNA-seq datasets, improving accuracy and consistency for cancer research.

A specialized bacterial group II intron is a highly efficient retrotransposon

The paper investigates the mobility of an Escherichia coli group II intron, showing it is a highly efficient and site-specific retrotransposon capable of colonizing the groEL gene.

REINDEER2: practical abundance index at scale

REINDEER2 provides a scalable, dynamic abundance index for RNA datasets, achieving faster construction and accurate abundance recovery.

Deciphering the RNA-based regulation mechanism of the phage-encoded AbiF system in Clostridioides difficile

The paper identifies a new AbiF-like system in C. difficile and shows its regulation by a non-coding RNA through RNA-protein interactions.

Dual RNA-seq study of the dynamics of coding and non-coding RNAs expression during Clostridioides difficile infection in a mouse model

This paper uses dual RNA-seq to study coding and non-coding RNA expression dynamics in C. difficile infection in mice, identifying new ncRNA genes and host miRNAs associated with infection.

Cell cycle-dependent mRNA localization in P-bodies

This study examines how mRNA localization to P-bodies changes during the cell cycle, revealing that mRNA dynamics in P-bodies are not solely linked to translation status but are regulated by RNA features and RBPs.

KaMRaT: a C++ toolkit for k-mer count matrix dimension reduction

KaMRaT reduces the dimensionality of k-mer count matrices from high-throughput sequencing data to identify condition-specific sequences.

Exploring a large cancer cell line RNA-sequencing dataset with k-mers

The paper introduces a k-mer-based method to quantify RNA sequences from large RNA-seq datasets, demonstrating its accuracy for variant RNA detection in cancer cell lines.

The contribution of uncharted RNA sequences to tumor identity in lung adenocarcinoma

The paper uses a k-mer based method to analyze RNA-seq data at the nucleotide level in lung adenocarcinoma, identifying novel tumor-specific RNA features and their clinical relevance.

Kmerator Suite: design of specific k-mer signatures andautomatic metadata discovery in large RNA-Seq datasets.

The paper introduces Kmerator Suite, a set of tools for extracting k-mer signatures and inferring metadata from RNA-seq datasets, showing high accuracy in gene expression quantification and metadata discovery.

2-kupl: mapping-free variant detection from DNA-seq data of matched samples

2-kupl detects variants between DNA-seq samples without mapping, achieving higher precision than existing methods and identifying novel variants in hard-to-map regions.

REINDEER: efficient indexing of k-mer presence and abundance in sequencing datasets

REINDEER indexes k-mer presence and abundance across large sequencing datasets efficiently, processing 2,585 human RNA-seq experiments in 45 hours with 56 GB RAM.

Highly reproducible characterization of Escherichia coli tRNA epitranscriptome with a simple method of library preparation for deep sequencing

The paper develops a method to characterize the tRNA epitranscriptome of Escherichia coli by optimizing library preparation and deep sequencing to detect modifications without demethylation.

TOP the Transcription Orientation Pipeline and its use to investigate the transcription of non-coding regions: assessment with CRISPR direct repeats and intergenic sequences.

The paper introduces TOP, a pipeline to determine transcription orientation of sequences using RNA-Seq data, validated on CRISPR repeats and small RNAs in Staphylococcus aureus.

Blind exploration of the unreferenced transcriptome reveals novel RNAs for prostate cancer diagnosis

The paper introduces a reference-free computational method to identify novel RNAs for prostate cancer diagnosis, finding that 9 unannotated lncRNAs outperform existing biomarkers.

Exhaustive capture of biological variation in RNA-seq data through k-mer decomposition

This paper introduces DE-kupl, a k-mer-based method to capture RNA variation without a reference, identifying novel transcripts and biological events from RNA-seq data.

In plants, decapping prevents RDR6-dependent production of small interfering RNAs from endogenous mRNAs

The paper shows that decapping prevents RDR6-dependent production of rqc-siRNAs from endogenous mRNAs, revealing a link between RNA quality control and post-transcriptional gene silencing in plants.