Past, present, and future of genomic technologies in cerebellar ataxias.

Fiche publication

Date publication

novembre 2025

Journal

Journal of neurology

Auteurs

Membres identifiés du Cancéropôle Est :
Mr DUFFOURD Yannis , Pr THAUVIN-ROBINET Christel

Tous les auteurs :
Lucain M, Duffourd Y, Malbos M, Vitobello A, Thauvin-Robinet C, Thomas Q

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/41204993

Résumé

Inherited cerebellar ataxias (ICA) are a group of rare, genetically and clinically heterogeneous neurodegenerative disorders, often caused by a broad spectrum of genetic variants, including single nucleotide variants, structural variations, and especially short tandem repeat (STR) expansions. Over time, advances in genomic technologies have profoundly reshaped the diagnostic approach and scientific understanding of ICA. This review traces the evolution of genomic tools, from first-generation methods, such as Sanger sequencing and southern blot, through the revolution brought by short-read second-generation sequencing, including gene panels, exome sequencing (ES), and genome sequencing (GS). These technologies significantly increased diagnostic yield and enabled the discovery of numerous ICA genes, although short-read sequencing remained limited in its ability to detect STR expansions and structural variants accurately. Recently, third-generation long-read sequencing (LRS) technologies, such as Single Molecule Real Time (SMRT) and nanopore sequencing, have emerged, offering reliable detection of all classes of variants, including complex and previously undetectable STR expansions. Optical genome mapping is also highlighted as a powerful, non-sequencing alternative for detecting large SVs and STRs. The manuscript underscores the reciprocal relationship between technological advances and medical knowledge in ICA. With LRS and integrated multi-omics approaches, the field stands at the cusp of a new era in diagnostics, enabling comprehensive variant detection and deeper insights into ICA pathophysiology. However, challenges related to cost, data interpretation, and population biases in reference databases remain.