We report on the development of a methylation analysis workflow for optical detection of fluorescent methylation profiles along chromosomal DNA molecules. In combination with Bionano Genomics genome mapping technology, these profiles provide a hybrid genetic/epigenetic genome-wide map composed of DNA molecules spanning hundreds of kilobase pairs. The method provides kilobase pair-scale genomic methylation patterns comparable to whole-genome bisulfite sequencing (WGBS) along genes and regulatory elements. These long single-molecule reads allow for methylation variation calling and analysis of large structural aberrations such as pathogenic macrosatellite arrays not accessible to single-cell second-generation sequencing. The method is applied here to study facioscapulohumeral muscular dystrophy (FSHD), simultaneously recording the haplotype, copy number, and methylation status of the disease-associated, highly repetitive locus on Chromosome 4q.

The premise of Open Science is that research and medical management will progress faster if data and knowledge are openly shared. The value of Open Science is nowhere more important and appreciated than in the rare disease (RD) community. Research into RDs has been limited by insufficient patient data and resources, a paucity of trained disease experts, and lack of therapeutics, leading to long delays in diagnosis and treatment. These issues can be ameliorated by following the principles and practices of sharing that are intrinsic to Open Science. Here, we describe how the RD community has adopted the core pillars of Open Science, adding new initiatives to promote care and research for RD patients and, ultimately, for all of medicine. We also present recommendations that can advance Open Science more globally.

Background

Sturge-Weber syndrome (SWS) is caused by a somatic mutation in GNAQ leading to capillary venous malformations in the brain presenting with various neurological, ophthalmic, and cognitive symptoms of variable severity. This clinical variability makes accurate prognosis difficult. We hypothesized that the greater extent of physical factors (extent of skin, eye, and brain involvement), presence of possible genetic factors (gender and family history), and age of seizure onset may be associated with greater symptom severity and need for surgery in patients with SWS.

Methods

The questionnaire was collected from 277 participants (age: two months to 66 years) with SWS brain involvement at seven US sites.

Results

Bilateral brain involvement was associated with both learning disorder and intellectual disability, whereas port-wine birthmark extent was associated with epilepsy and an increased likelihood of glaucoma surgery. Subjects with family history of vascular birthmarks were also more likely to report symptomatic strokes, and family history of seizures was associated with earlier seizure onset. Learning disorder, intellectual disability, strokelike episodes, symptomatic stroke, hemiparesis, visual field deficit, and brain surgery were all significantly associated with earlier onset of seizures.

Conclusion

The extent of brain and skin involvement in SWS, as well as the age of seizure onset, affect prognosis. Other genetic factors, particularly variants involved in vascular development and epilepsy, may also contribute to neurological prognosis, and further study is needed.

Background

Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells.

Results

Here, the Brain Somatic Mosaicism Network conducts a coordinated, multi-institutional study to examine the ability of existing methods to detect simulated somatic single-nucleotide variants (SNVs) in DNA mixing experiments, generate multiple replicates of whole-genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual, devise strategies to discover somatic SNVs, and apply various approaches to validate somatic SNVs. These efforts lead to the identification of 43 bona fide somatic SNVs that range in variant allele fractions from ~ 0.005 to ~ 0.28. Guided by these results, we devise best practices for calling mosaic SNVs from 250× whole-genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrate that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees.

Conclusions

This study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.