Copy-number variation is a common source of genomic variation and an important genetic cause of disease. Microarray-based analysis of copy-number variants (CNVs) has become a first-tier diagnostic test for patients with neurodevelopmental disorders, with a diagnostic yield of 10-20%. However, for most other genetic disorders, the role of CNVs is less clear and most diagnostic genetic studies are generally limited to the study of single-nucleotide variants (SNVs) and other small variants. With the introduction of exome and genome sequencing, it is now possible to detect both SNVs and CNVs using an exome- or genome-wide approach with a single test. We performed exome-based read-depth CNV screening on data from 2,603 patients affected by a range of genetic disorders for which exome sequencing was performed in a diagnostic setting. In total, 123 clinically relevant CNVs ranging in size from 727 bp to 15.3 Mb were detected, which resulted in 51 conclusive diagnoses and an overall increase in diagnostic yield of ~2% (ranging from 0 to -5.8% per disorder). This study shows that CNVs play an important role in a broad range of genetic disorders and that detection via exome-based CNV profiling results in an increase in the diagnostic yield without additional testing, bringing us closer to single-test genomics.Genet Med advance online publication 27 October 2016.

Cancer is generally characterized by acquired genomic aberrations in a broad spectrum of types and sizes, ranging from single nucleotide variants to structural variants (SVs). At least 30% of cancers have a known pathogenic SV used in diagnosis or treatment stratification. However, research into the role of SVs in cancer has been limited due to difficulties in detection. Biological and computational challenges confound SV detection in cancer samples, including intratumor heterogeneity, polyploidy, and distinguishing tumor-specific SVs from germline and somatic variants present in healthy cells. Classification of tumor-specific SVs is challenging due to inconsistencies in detected breakpoints, derived variant types and biological complexity of some rearrangements. Full-spectrum SV detection with high recall and precision requires integration of multiple algorithms and sequencing technologies to rescue variants that are difficult to resolve through individual methods. Here, we explore current strategies for integrating SV callsets and to enable the use of tumor-specific SVs in precision oncology.

The fusion gene MLL/AF4 defines a high-risk subtype of pro-B acute lymphoblastic leukemia. Relapse can be associated with a lineage switch from acute lymphoblastic to acute myeloid leukemia, resulting in poor clinical outcomes caused by resistance to chemotherapies and immunotherapies. In this study, the myeloid relapses shared oncogene fusion breakpoints with their matched lymphoid presentations and originated from various differentiation stages from immature progenitors through to committed B-cell precursors. Lineage switching is linked to substantial changes in chromatin accessibility and rewiring of transcriptional programs, including alternative splicing. These findings indicate that the execution and maintenance of lymphoid lineage differentiation is impaired. The relapsed myeloid phenotype is recurrently associated with the altered expression, splicing, or mutation of chromatin modifiers, including CHD4 coding for the ATPase/helicase of the nucleosome remodelling and deacetylation complex. Perturbation of CHD4 alone or in combination with other mutated epigenetic modifiers induces myeloid gene expression in MLL/AF4+ cell models, indicating that lineage switching in MLL/AF4 leukemia is driven and maintained by disrupted epigenetic regulation.

Purpose The interpretation of genetic variants after genome-wide analysis is complex in heterogeneous disorders such as intellectual disability (ID). We investigate whether algorithms can be used to detect if a facial gestalt is present for three novel ID syndromes and if these techniques can help interpret variants of uncertain significance. Methods Facial features were extracted from photos of ID patients harboring a pathogenic variant in three novel ID genes (PACS1, PPM1D, and PHIP) using algorithms that model human facial dysmorphism, and facial recognition. The resulting features were combined into a hybrid model to compare the three cohorts against a background ID population. Results We validated our model using images from 71 individuals with Koolen–de Vries syndrome, and then show that facial gestalts are present for individuals with a pathogenic variant in PACS1 (p = 8 × 10⁻⁴), PPM1D (p = 4.65 × 10⁻²), and PHIP (p = 6.3 × 10⁻³). Moreover, two individuals with a de novo missense variant of uncertain significance in PHIP have significant similarity to the expected facial phenotype of PHIP patients (p < 1.52 × 10⁻²). Conclusion Our results show that analysis of facial photos can be used to detect previously unknown facial gestalts for novel ID syndromes, which will facilitate both clinical and molecular diagnosis of rare and novel syndromes.