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BMJ Publishing Group, Journal of Medical Genetics, 8(56), p. 526-535, 2019

DOI: 10.1136/jmedgenet-2018-105778

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Whole genome paired-end sequencing elucidates functional and phenotypic consequences of balanced chromosomal rearrangement in patients with developmental disorders

Journal article published in 2019 by Caroline Schluth-Bolard ORCID, Flavie Diguet, Nicolas Chatron, Pierre-Antoine Rollat-Farnier, Claire Bardel, Yline Capri, Alexandra Afenjar, Patrick Collignon, Marie-Pierre Cordier, Florence Amblard, Christine Coubes, Benedicte Demeer ORCID, Jeanne Amiel, Annabelle Chaussenot, Florence Demurger and other authors.
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

BackgroundBalanced chromosomal rearrangements associated with abnormal phenotype are rare events, but may be challenging for genetic counselling, since molecular characterisation of breakpoints is not performed routinely. We used next-generation sequencing to characterise breakpoints of balanced chromosomal rearrangements at the molecular level in patients with intellectual disability and/or congenital anomalies.MethodsBreakpoints were characterised by a paired-end low depth whole genome sequencing (WGS) strategy and validated by Sanger sequencing. Expression study of disrupted and neighbouring genes was performed by RT-qPCR from blood or lymphoblastoid cell line RNA.ResultsAmong the 55 patients included (41 reciprocal translocations, 4 inversions, 2 insertions and 8 complex chromosomal rearrangements), we were able to detect 89% of chromosomal rearrangements (49/55). Molecular signatures at the breakpoints suggested that DNA breaks arose randomly and that there was no major influence of repeated elements. Non-homologous end-joining appeared as the main mechanism of repair (55% of rearrangements). A diagnosis could be established in 22/49 patients (44.8%), 15 by gene disruption (KANSL1, FOXP1, SPRED1, TLK2, MBD5, DMD, AUTS2, MEIS2, MEF2C, NRXN1, NFIX, SYNGAP1, GHR, ZMIZ1) and 7 by position effect (DLX5, MEF2C, BCL11B, SATB2, ZMIZ1). In addition, 16 new candidate genes were identified. Systematic gene expression studies further supported these results. We also showed the contribution of topologically associated domain maps to WGS data interpretation.ConclusionPaired-end WGS is a valid strategy and may be used for structural variation characterisation in a clinical setting.