Gene Discovery

Research

Hunting for New Therapies

There is a treasure trove of valuable information in both the mapped and unmapped reads of the genome.

Gene Discovery involves identifying novel genes implicated in causing rare disease, developing methods to identify patient’s predisposition to a rare disease and building the knowledge base to improve clinical management of novel genetic disease.

At RCIGM, this work is led by Matthew Bainbridge, PhD, Assistant Director of Translational Research. His team develops novel analysis techniques to squeeze every last bit of information from WGS and to attempt to identify uncommon disease mechanisms (such as ALU insertions and deep intronic mutations) in the pediatric patient population. 

Bioinformatic analysis of Whole Genome Sequencing (WGS) data is used to gain a better understanding of the mechanisms by which pathogenic genomic variants contribute to the development of rare diseases.

Traditional wet-lab modeling of novel diseases is used to functionalize variants of uncertain significance.

Research Projects

Several grant funded research projects are currently under Dr. Bainbridge’s direction:

  • Oligogenic Models of Cardiomyopathy
    The goal is to identify synergistic and modifier mutations that impact structural cardiomyopathies.  Bioinformatically identified variants are prioritized and then functionally tested by Dr. Neil Chi at UC San Diego. Learn More

Matthew Bainbridge, PhD

RCIGM Assistant Director of Translational Research

View Dr. Bainbridge’s full publication bibliography

Publications

Systematic analysis of snRNA genes reveals frequent RNU2-2 variants in dominant and recessive developmental and epileptic encephalopathies

  • Leitão E, Santini A, Cogne B, Essid M, Athanasiadou M, LaFlamme CW, Marijon P, Bernard V, Jousselin K, Chatron N, Barcia G, Keren B, Mignot C, Charles P, Besnard T, Paluch R, de Sainte Agathe JM, Almanza Fuerte EP, Sengupta S, Milh M, Ramond F, Allan T, An I, Araujo C, Arpin S, Austin-Tse C, Auvin S, Baer S, Bahi-Buisson N, Bak M, Barth M, Baulac S, Bednarek-Weirauch N, Begemann M, Bennett MF, Bensabath U, Bézieau S, Bhouri R, Biehler M, Hammer TB, Bogoin J, Bonanno E, Boussion S, Bris C, Brosseau-Beauvir A, Bruel AL, Briand-Suleau A, Buratti J, Celse T, Chambon P, Chemaly N, Chesneau B, Colin E, Colmard M, Colson C, Conrad S, Courtin T, Creveaux I, Cullier AC, Dang LT, de Saint Martin A, de Vanssay de Blavous Legendre C, Demeer B, Denommé-Pichon AS, Diekhoff P, DiTroia S, Doco-Fenzy M, Dubourg C, Dubucs C, Ducreux S, Dufour L, Duquet R, Durand B, El Chehadeh S, Elbracht M, Faivre L, Faoucher M, Faudet A, Forlani S, Fradin M, Gaignard P, Ganne B, Garde A, Géraud J, Gill D, Goldenberg A, Grabli D, Grisel C, Gueden S, Gueguen P, Guerrot AM, Guichet A, Haack TB, Härting N, Häusler MG, Heide S, Herget T, Héron B, Héron D, Herwig J, Heulin M, Holling T, Houdayer C, Isidor B, Jacquette A, Januel L, Jean-Marçais N, Kaiser FJ, Kaya S, King C, Konyukh M, Kraft F, Krause J, Kirstetter R, Kuechler A, Kurth I, Kutsche K, Labalme A, Laloy JS, Laugel V, Le Bricquir F, Lèbre AS, Lebrun M, Leguern E, Levy J, Lieffering N, Lyonnet S, Lüthy K, Macdonald SMW, Mansour-Hendili L, Maraval J, Marquardt I, Mattausch C, Mercier S, Messaoud O, Morel G, Mortreux J, Munnich A, Nabbout R, Nambot S, Navarro V, Neale A, Nguyen L, Nizon M, Nowak F, O'Leary MC, Odent S, Ojeda NM, Olin V, Olivieri S, Õunap K, Pais LS, Panagiotakaki E, Patat O, Perrin-Sabourin L, Petit F, Philippe C, Piton A, Planes M, Poirsier C, Pouzet A, Prouteau C, Quéméner-Redon S, Renaud M, Richard AC, Rio M, Rivier C, Robin-Renaldo F, Rollier P, Rossi M, Roubertie A, Ruault V, Rupin-Mas M, Saugier-Veber P, Saunier A, Saneto R, Sarrazin E, Sarret C, Schaefer E, Schluth-Bolard C, Schneider A, Schumann I, Seplyarskiy VB, Spranger S, Smol T, Sturm M, Sunyaev SR, Sperelakis-Beedham B, Stenton SL, Stock F, Tharreau M, Torun D, Toulouse J, Thiyagarajah H, Valence S, Valleix S, Van-Gils J, Villard L, Ville D, Villeneuve N, Vitobello A, Waernessyckle A, Wagner J, Weber Y, Wieczorek D, Witkowski T, Yadavilli M, Yammine T, Zaafrane-Khachnaoui K, Zaki MS, Ziegler A, Bramswig NC, Lermine A, Nicolas G, Gleeson JG, Sadleir LG, Hildebrand MS, Scheffer IE, Whiffin N, O'Donnell-Luria A, Mefford HC, Blanc P, Thevenon J, Charbonnier C, Charenton C, Depienne C, Lesca G, Nava C.

Nat Genet. 2026 Mar 30. doi: 10.1038/s41588-026-02547-5. Online ahead of print.

ABSTRACT

Small nuclear RNAs (snRNAs) are essential components of the spliceosome. De novo variants in snRNA genes RNU4-2 (ReNU syndrome), RNU5B-1 and RNU2-2 have been linked to dominant neurodevelopmental disorders (NDDs), revealing a large unexpected contribution of noncoding RNA genes to genetic diseases. Here, through international collaborations, we analyze systematically 200 potentially functional snRNA genes in a French cohort of 34,329 people with rare disorders. We report RNU2-2 variants in 141 individuals, including 35 with recurrent dominant pathogenic variants and 91 affected members from 73 families with biallelic variants. Recessive RNU2-2 NDD is at least twice as frequent as the dominant form and often involves a de novo variant in trans with an inherited allele, consistent with the high mutability of snRNA genes. Dominant and recessive RNU2-2 NDDs share overlapping clinical features, with frequent epilepsy. Blood transcriptomics and DNA methylation analyses revealed subtle, variant-specific effects on splicing and episignatures. Our results support a gradient-of-impact model bridging dominant and recessive inheritance, and establish RNU2-2 variants as a principal contributor to NDDs, nearly as prevalent as ReNU syndrome.

PMID:41912934 | DOI:10.1038/s41588-026-02547-5

Reconstructing the three-dimensional architecture of extrachromosomal DNA with ec3D

  • Chowdhury B, Zhu K, Li C, Alsing J, Luebeck J, Stefanova ME, Chapman OS, Kraft K, Zhang S, Lim JYS, Xie Y, Kim YJ, Wu S, Chavez L, Nir G, Henssen AG, Mischel PS, Chang HY, Bafna V.

Nat Commun. 2025 Dec 20. doi: 10.1038/s41467-025-67614-7. Online ahead of print.

ABSTRACT

Extrachromosomal DNAs (ecDNAs) are circular DNA molecules prevalent in human cancers that drive tumor evolution and drug resistance. Their circular topology, which disrupts topological domains and rewires regulatory circuits, has typically been studied via pairwise interactions. Here we develop ec3D, a computational method for reconstructing three-dimensional ecDNA structures from Hi-C data. Given a candidate ecDNA sequence and whole-genome Hi-C data, ec3D reconstructs spatial structures by maximizing the Poisson likelihood of observed interactions. We validate ec3D using simulated structures, previously characterized cancer cell lines, and microscopy imaging. Our reconstructions reveal that ecDNAs occupy spherical configurations and mediate unique long-range regulatory interactions involved in gene regulation. Through algorithmic innovations, ec3D can resolve complex structures with duplicated segments, identify multi-way interactions, and identify potential intermolecular (trans) interactions. Our findings provide insights into how ecDNA’s spatial organization bypasses normal chromosomal constraints and contributes to increased oncogene expression.

PMID:41422275 | DOI:10.1038/s41467-025-67614-7

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