Next generation sequencing revolutionizes the identification of ID genes

(Wei Chen, Hao Hu, Vera Kalscheuer, Reinhard Ullmann, Andreas Tzschach, Andreas Kuss)

To elucidate the genetic defects underlying ID and related disorders, we have employed a wide spectrum of approaches, including breakpoint mapping in patients with disease-associated balanced chromosome rearrangements (DBCRs), screening for disease-associated copy number variants by array CGH, and linkage mapping in families and mutation screening of candidate genes, as outlined previously3. While array CGH-based screening for pathogenic copy number variants, the study of DBCRs and linkage mapping in patients and families remain useful strategies for the elucidation of genetic disorders, as illustrated by several recent publications of our group, our decision paid off to invest early into genomic enrichment techniques, high throughput sequencing and the storage, handling and interpretation of next generation sequencing data.

Development of mutation detection pipelines

(Hao  Hu;  together with  Stefan  Haas  and  co-workers,  Dept.  Computational Molecular Biology)

Various  members  of  the  Department  of  Computational  Molecular  Biology (Head: Martin Vingron) contributed to this effort by developing a bioinformatic mutation detection pipeline, which was first used to look for de novo mutations on the X-chromosome in patient-parent trios with a suspected X-linked dominant disorders (Chen W. et al, unpublished observations). Later on, this pipeline was instrumental in our comprehensive collaborative effort to identify the molecular defects underlying X-linked mental retardation (see below).

Independently, Hao Hu developed another algorithm for identifying pathogenic changes in whole genome and whole exome sequences. This algorithm has been employed successfully to look for mutations in consanguineous families with autosomal recessive ID and has been described in several publications5; a more comprehensive description is in preparation. Since 2010, these methods have become the mainstay of our research into the genetic causes of ID and related disorders.

X-linked ID genes: draining the pond

(Vera Kalscheuer, Hao Hu, Chen Wei, Thomas Wienker; in cooperation with Stefan Haas, Tomasz Zemojtel, Martin Vingron, Dept. Computational Molecular Biology)

Employing a custom-made hybrid capture kit to enrich 7591 X-chromosomal exons,  or  875  genes, we  have performed targeted exon sequencing in  248

European families with X-linked forms of ID. In the vast majority of these families, X-linkage was virtually certain because of affected males in separate sibships that were connected through healthy females. Apparently deleterious DNA variants were identified in 13 genes that had not been implicated in ID before, and their identity as novel genes for X-linked ID (XLID) was corroborated in various ways. This study raises the number of known XLID genes to 110. Using the same parameters to distinguish pathogenic from clinically irrelevant sequence variants, we have also reanalyzed the results of a previous study encompassing 208 Caucasian families, which had been screened for mutations by large-scale Sanger sequencing6. Under the (plausible) assumption that the cohorts analyzed by the two studies are part of the same population, this enabled us to estimate the total number of XLID genes as 123 (95% confidence limits: 91-155). This estimate is lower than expected and cannot be reconciled easily with our finding that mutations in the known 110 genes account for at most 71% of the XLID families. One possible explanation for this discrepancy is that most of the missing mutations may reside in non-coding, e.g. intronic sequences which were not analyzed in these studies (Kalscheuer et al, unpublished).