Biology subjects

Gobet, N.

Publications and source records attributed to Gobet, N..

4 recordsLinked to original sources

bioRxiv2026

ALK variants Differentially Modulate Neuroblastoma Tumor Behavior and Transcriptome in a Cellular Context-Dependent Manner

High-risk neuroblastoma remains a major clinical challenge despite intensive multimodal treatment. Alterations in the anaplastic lymphoma kinase (ALK) gene are frequent in NB and correlate with poor outcome. ALK-F1174L and ALK-R1275Q are the most prevalent activating mutations, but their specific effects on tumor behavior remain unclear. Here, we compared the impacts of ALK-wild-type (wt), ALK-F1174L and ALK-R1275Q in several NB xenograft models. In the SK-N-Be2c model, ALK-F1174L mediated numerous transcriptomic alterations without affecting tumor behavior. In GIMEN cells, only ALK-F1174L and ALK-R1275Q conferred tumorigenicity with distinct growth kinetics and transcriptional programs. In the mesenchymal SH-EP model, ALK variants induced distinct phenotypes, with ALK-wt and ALK-F1174L promoting partial transition toward neuroblastic identity. All ALK variants induced lung metastases, but with allele-specific dissemination patterns. Transcriptomic profiling of SH-EP tumors and corresponding metastases revealed partly opposing pathway regulation between ALK-F1174L and ALK-R1275Q. Overall, ALK variants differentially modulate NB behavior in a context-dependent manner.

cancer biology↗

bioRxiv2022

Repeat Detector: accurate, efficient, and flexible sizing of expanded CAG/CTG repeats from targeted DNA sequencing

Targeted DNA sequencing approaches will improve how the size of short tandem repeats is measured for diagnostic tests and pre-clinical studies. The expansion of these sequences causes dozens of disorders, with longer tracts generally leading to a more severe disease. Interrupted alleles are sometimes present within repeats and can alter disease manifestation. Determining repeat size mosaicism and identifying interruptions in targeted sequencing datasets remains a major challenge. This is in part because standard alignment tools are ill-suited for repetitive and unstable sequences. To address this, we have developed Repeat Detector (RD), a deterministic profile weighting algorithm for counting repeats in targeted sequencing data. We tested RD using blood-derived DNA samples from Huntingtons disease and Fuchs endothelial corneal dystrophy patients sequenced using either Illumina MiSeq or Pacific Biosciences single-molecule, real-time sequencing platforms. RD was highly accurate in determining repeat sizes of 609 blood-derived samples from Huntingtons disease individuals and did not require prior knowledge of the flanking sequences. Furthermore, RD can be used to identify alleles with interruptions and provide a measure of repeat instability within an individual. RD is therefore highly versatile and may find applications in the diagnosis of expanded repeat disorders and the development of novel therapies.

neuroscience↗

bioRxiv2021

Towards mouse genetic-specific RNA-sequencing read mapping

Genetic variations affect behavior and cause disease but understanding how these variants drive complex traits is still an open question. A common approach is to link the genetic variants to intermediate molecular phenotypes such as the transcriptome using RNA-sequencing (RNA-seq). Paradoxically, these variants between the samples are usually ignored at the beginning of RNA-seq analyses of many model organisms. This can skew the transcriptome estimates that are used later for downstream analyses, such as expression quantitative trait locus (eQTL) detection. Here, we assessed the impact of reference-based analysis on the transcriptome and eQTLs in a widely-used mouse genetic population: the BXD panel of recombinant inbred lines. We highlight existing reference bias in the transcriptome data analysis and propose practical solutions which combine available genetic variants, genotypes, and genome reference sequence. The use of custom BXD line references improved downstream analysis compared to classical genome reference. These insights would likely benefit genetic studies with a transcriptomic component and demonstrate that genome references might need to be reassessed and improved.

bioinformatics↗

bioRxiv2019

A multi-omics digital research object for the genetics of sleep regulation.

More and more researchers make use of multi-omics approaches to tackle complex cellular and organismal systems. It has become apparent that the potential for re-use and integrate data generated by different labs can enhance knowledge. However, a meaningful and efficient re-use of data generated by others is difficult to achieve without in depth understanding of how these datasets were assembled. We therefore designed and describe in detail a digital research object embedding data, documentation and analytics on mouse sleep regulation. The aim of this study was to bring together electrophysiological recordings, sleep-wake behavior, metabolomics, genetics, and gene regulatory data in a systems genetics model to investigate sleep regulation in the BXD panel of recombinant inbred lines. We here showcase both the advantages and limitations of providing such multi-modal data and analytics. The reproducibility of the results was tested by a bioinformatician not implicated in the original project and the robustness of results was assessed by re-annotating genetic and transcriptome data from the mm9 to the mm10 mouse genome assembly.

bioinformatics↗