Éditeur(s) : HAL CCSD Wiley/Blackwell
Résumé : International audience
Microsatellites are widely used in population genetics to uncover recent evolutionary events. They are typically genotyped using capillary sequencer, which capacity is usually limited to 9, at most 12 loci for each run, and which analysis is a tedious task that is performed by hand. With the rise of next-generation sequencing (NGS), a much larger number of loci and individuals are available from sequencing: for example, on a single run of a GS Junior, 28 loci from 96 individuals are sequenced with a 30X cover. We have developed an algorithm to automatically and efficiently genotype microsatellites from a collection of reads sorted by individual (e.g. specific PCR amplifications of a locus or a collection of reads that encompass a locus of interest). As the sequencing and the PCR amplification introduce artefactual insertions or deletions, the set of reads from a single microsatellite allele shows several length variants. The algorithm infers, without alignment, the true unknown allele(s) of each individual from the observed distributions of microsatellites length of all individuals. MicNeSs, a python implementation of the algorithm, can be used to genotype any microsatellite locus from any organism and has been tested on 454 pyrosequencing data of several loci from fruit flies (a model species) and red deers (a nonmodel species). Without any parallelization, it automatically genotypes 22 loci from 441 individuals in 11 hours on a standard computer. The comparison of MicNeSs inferences to the standard method shows an excellent agreement, with some differences illustrating the pros and cons of both methods.
ISSN: 1755-098X

hal-01544754
https://hal.archives-ouvertes.fr/hal-01544754
DOI : 10.1111/1755-0998.12467

Éditeur(s) : HAL CCSD
Résumé : International audience
Background Orodental diseases include several clinically and genetically heterogeneous disorders that can present in isolation or as part of a genetic syndrome. Due to the vast number of genes implicated in these disorders, establishing a molecular diagnosis can be challenging. We aimed to develop a targeted next-generation sequencing (NGS) assay to diagnose mutations and potentially identify novel genes mutated in this group of disorders. Methods We designed an NGS gene panel that targets 585 known and candidate genes in orodental disease. We screened a cohort of 101 unrelated patients without a molecular diagnosis referred to the Reference Centre for Oro-Dental Manifestations of Rare Diseases, Strasbourg, France, for a variety of orodental disorders including isolated and syndromic amelogenesis imperfecta (AI), isolated and syndromic selective tooth agenesis (STHAG), isolated and syndromic dentinogenesis imperfecta, isolated dentin dysplasia, otodental dysplasia and primary failure of tooth eruption. Results We discovered 21 novel pathogenic variants and identified the causative mutation in 39 unrelated patients in known genes (overall diagnostic rate: 39%). Among the largest subcohorts of patients with isolated AI (50 unrelated patients) and isolated STHAG (21 unrelated patients), we had a definitive diagnosis in 14 (27%) and 15 cases (71%), respectively. Surprisingly, COL17A1 mutations accounted for the majority of autosomal-dominant AI cases. Conclusions We have developed a novel targeted NGS assay for the efficient molecular diagnosis of a wide variety of orodental diseases. Furthermore, our panel will contribute to better understanding the contribution of these genes to orodental disease. Trial registration numbers NCT01746121 and NCT02397824
Journal of Medical Genetics

hal-01272929
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01272929
DOI : 10.1136/jmedgenet-2015-103302
PUBMED : 26502894