Diaphonospondylodysotosis (DSD) and ischiospinal dysostosis (ISD) are rare skeletal dysplasias with variants in the bone morphogenetic protein-binding endothelial regulator (BMPER). There is a continuum of clinical presentation, with DSD at the severe end of the spectrum whilst ISD is towards the milder end. Both are caused due to pathogenic variants in BMPER. Previous studies have reported 20 patients from 13 families. Common features in the cohort reported so far are spinal and rib anomalies but other findings illustrate phenotypic variation. Survival ranges from death within the neonatal period to alive and well at 19 years. We present three siblings with variable phenotype, adding to the evidence for a single definition of BMPER-related skeletal dysplasia. We highlight the need for ongoing care planning and guarded prognostication, with regular review by clinical teams.

Structural variations (SVs) are mutations in the genome of size at least fifty nucleotides. They contribute to the phenotypic differences among healthy individuals, cause severe diseases and even cancers by breaking or linking genes. Thus, it is crucial to systematically profile SVs in the genome. In the past decade, many next-generation sequencing (NGS)-based SV detection methods have been proposed due to the significant cost reduction of NGS experiments and their ability to unbiasedly detect SVs to the base-pair resolution. These SV detection methods vary in both sensitivity and specificity, since they use different SV-property-dependent and library-property-dependent features. As a result, predictions from different SV callers are often inconsistent. Besides, the noises in the data (both platform-specific sequencing error and artificial chimeric reads) impede the specificity of SV detection. Poorly characterized regions in the human genome (e.g., repeat regions) greatly impact the reads mapping and in turn affect the SV calling accuracy. Calling of complex SVs requires specialized SV callers. Apart from accuracy, processing speed of SV caller is another factor deciding its usability. Knowing the pros and cons of different SV calling techniques and the objectives of the biological study are essential for biologists and bioinformaticians to make informed decisions. This paper describes different components in the SV calling pipeline and reviews the techniques used by existing SV callers. Through simulation study, we also demonstrate that library properties, especially insert size, greatly impact the sensitivity of different SV callers. We hope the community can benefit from this work both in designing new SV calling methods and in selecting the appropriate SV caller for specific biological studies.

The study of the developing brain has begun to shed light on the underpinnings of both early and adult onset neuropsychiatric disorders. Neuroimaging of the human brain across developmental time points and the use of model animal systems have combined to reveal brain systems and gene products that may play a role in autism spectrum disorders, attention deficit hyperactivity disorder, obsessive compulsive disorder and many other neurodevelopmental conditions. However, precisely how genes may function in human brain development and how they interact with each other leading to psychiatric disorders is unknown. Because of an increasing understanding of neural stem cells and how the nervous system subsequently develops from these cells, we have now the ability to study disorders of the nervous system in a new way - by rewinding and reviewing the development of human neural cells. Induced pluripotent stem cells (iPSCs), developed from mature somatic cells, have allowed the development of specific cells in patients to be observed in real time. Moreover, they have allowed some neuronal-specific abnormalities to be corrected with pharmacological intervention in tissue culture. These exciting advances based on the use of iPSCs hold great promise for understanding, diagnosing and, possibly, treating psychiatric disorders. Specifically, examination of iPSCs from typically developing individuals will reveal how basic cellular processes and genetic differences contribute to individually unique nervous systems. Moreover, by comparing iPSCs from typically developing individuals and patients, differences at stem cell stages, through neural differentiation, and into the development of functional neurons may be identified that will reveal opportunities for intervention. The application of such techniques to early onset neuropsychiatric disorders is still on the horizon but has become a reality of current research efforts as a consequence of the revelations of many years of basic developmental neurobiological science.

An enormous number of high-quality Web-based resources are now available to facilitate research into genome variation. Although identification of the most appropriate and informative resources can be challenging, a number of key sites provide links to more specialized resources that may be useful to follow up. Given ongoing research, focussing on the sequencing of many different genomes, we can expect sequence databases and their associated polymorphism-based resources to greatly increase in depth and complexity in a relatively short period of time. However, databases and tools developed to date, and described here, provide a sound basis for accommodating this next generation of genomic data. As well as sequence-oriented resources this review presents databases providing genotypic and common disease phenotype data, copy number variation, genetic maps, cytogenetic data, and gives an overview of key software tools, with the emphasis on analysis of the genetic basis of common disease.