DENALI IN A BOX: ANALOG EXPERIMENTS MODELED AFTER A NATURAL SETTING PROVIDE INSIGHT ON GENTLE RESTRAINING BEND DEFORMATION

The Mount McKinley restraining bend (MMRB) creates an ~18° left-step in the arcuate surface trace of the dextral Denali Fault in south-central Alaska. Despite being a large, crustal-scale fault, little is understood about the controls on deformation within the MMRB. Similarities between previous wet kaolin analog modeling and the MMRB suggest that the first-order deformation patterns may derive from similar mechanisms. We compare uplift patterns, localization of deformation, formation of new faults, and displacement fields from the analog model and the natural setting to assess the influence of different variables on the overall system. Despite strong rheological heterogeneity in the MMRB, this natural setting exhibits the same distribution of deformation across the restraining bend as the homogeneous analog model suggesting this first-order deformation patterns is independent of upper crustal heterogeneity. The active thrust faults of the MMRB are purely dip-slip, whereas the thrust faults formed in the model exhibit oblique slip. Conventional understanding suggests migrating restraining bends cannot produce high topography; we conclude that with a specific combination of geometry, slip rate, and migration rate, high topography is capable of forming within a migrating system

Stereovision Combined With Particle Tracking Velocimetry Reveals Advection and Uplift Within a Restraining Bend Simulating the Denali Fault

Scaled physical experiments allow us to directly observe deformational processes that take place on time and length scales that are impossible to observe in the Earth’s crust. Successful evaluation of advection and uplift of material within a restraining bend along a strike-slip fault zone depends on capturing the evolution of strain in three dimensions. Consequently, we require deformation within the horizontal plane as well as vertical motions. While 3D digital image correlation systems can provide this information, their high costs have prompted us to develop techniques that require only two DSLR cameras and a few Matlab® toolboxes, which are available to researchers at many institutions. Matlab® plug-ins can perform particle image velocimetry (PIV), a technique used in many analog modeling studies to map the incremental displacements fields. For tracking material advection throughout experiments more suitable Matlab® plug-ins perform particle tracking velocimetry (PTV), which tracks the complete two-dimensional displacement path of individual particles. To capture uplift the Matlab®Computer Vision ToolboxTM, uses pairs of photos to capture the evolving topography of the experiment. The stereovision approach eliminates the need to stop the experiment to perform 3D laser scans, which can be problematic when working with materials that have time dependent rheology. We demonstrate how the combination of PIV, PTV, and stereovision analysis of experiments that simulate the Mount McKinley restraining bend reveal the evolution of the fault system and three-dimensional advection of material through the bend

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Prevalence and architecture of de novo mutations in developmental disorders.

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year

Prevalence, phenotype and architecture of developmental disorders caused by de novo mutation: The Deciphering Developmental Disorders Study

Individuals with severe, undiagnosed developmental disorders (DDs) are enriched for damaging de novo mutations (DNMs) in developmentally important genes. We exome sequenced 4,293 families with individuals with DDs, and meta-analysed these data with published data on 3,287 individuals with similar disorders. We show that the most significant factors influencing the diagnostic yield of de novo mutations are the sex of the affected individual, the relatedness of their parents and the age of both father and mother. We identified 94 genes enriched for damaging de novo mutation at genome-wide significance (P < 7 × 10−7), including 14 genes for which compelling data for causation was previously lacking. We have characterised the phenotypic diversity among these genetic disorders. We demonstrate that, at current cost differentials, exome sequencing has much greater power than genome sequencing for novel gene discovery in genetically heterogeneous disorders. We estimate that 42% of our cohort carry pathogenic DNMs (single nucleotide variants and indels) in coding sequences, with approximately half operating by a loss-of-function mechanism, and the remainder resulting in altered-function (e.g. activating, dominant negative). We established that most haplo insufficient developmental disorders have already been identified, but that many altered-function disorders remain to be discovered. Extrapolating from the DDD cohort to the general population, we estimate that developmental disorders caused by DNMs have an average birth prevalence of 1 in 213 to 1 in 448 (0.22-0.47% of live births), depending on parental age

Large-scale discovery of novel genetic causes of developmental disorders

Despite three decades of successful, predominantly phenotype-driven discovery of the genetic causes of monogenic disorders1, up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. Particularly challenging are those disorders rare enough to have eluded recognition as a discrete clinical entity, those with highly variable clinical manifestations, and those that are difficult to distinguish from other, very similar, disorders. Here we demonstrate the power of using an unbiased genotype-driven approach2 to identify subsets of patients with similar disorders. By studying 1,133 children with severe, undiagnosed developmental disorders, and their parents, using a combination of exome sequencing3,4,5,6,7,8,9,10,11 and array-based detection of chromosomal rearrangements, we discovered 12 novel genes associated with developmental disorders. These newly implicated genes increase by 10% (from 28% to 31%) the proportion of children that could be diagnosed. Clustering of missense mutations in six of these newly implicated genes suggests that normal development is being perturbed by an activating or dominant-negative mechanism. Our findings demonstrate the value of adopting a comprehensive strategy, both genome-wide and nationwide, to elucidate the underlying causes of rare genetic disorders

Bi-allelic Loss-of-Function CACNA1B Mutations in Progressive Epilepsy-Dyskinesia.

The occurrence of non-epileptic hyperkinetic movements in the context of developmental epileptic encephalopathies is an increasingly recognized phenomenon. Identification of causative mutations provides an important insight into common pathogenic mechanisms that cause both seizures and abnormal motor control. We report bi-allelic loss-of-function CACNA1B variants in six children from three unrelated families whose affected members present with a complex and progressive neurological syndrome. All affected individuals presented with epileptic encephalopathy, severe neurodevelopmental delay (often with regression), and a hyperkinetic movement disorder. Additional neurological features included postnatal microcephaly and hypotonia. Five children died in childhood or adolescence (mean age of death: 9 years), mainly as a result of secondary respiratory complications. CACNA1B encodes the pore-forming subunit of the pre-synaptic neuronal voltage-gated calcium channel Cav2.2/N-type, crucial for SNARE-mediated neurotransmission, particularly in the early postnatal period. Bi-allelic loss-of-function variants in CACNA1B are predicted to cause disruption of Ca2+ influx, leading to impaired synaptic neurotransmission. The resultant effect on neuronal function is likely to be important in the development of involuntary movements and epilepsy. Overall, our findings provide further evidence for the key role of Cav2.2 in normal human neurodevelopment.MAK is funded by an NIHR Research Professorship and receives funding from the Wellcome Trust, Great Ormond Street Children's Hospital Charity, and Rosetrees Trust. E.M. received funding from the Rosetrees Trust (CD-A53) and Great Ormond Street Hospital Children's Charity. K.G. received funding from Temple Street Foundation. A.M. is funded by Great Ormond Street Hospital, the National Institute for Health Research (NIHR), and Biomedical Research Centre. F.L.R. and D.G. are funded by Cambridge Biomedical Research Centre. K.C. and A.S.J. are funded by NIHR Bioresource for Rare Diseases. The DDD Study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute (grant number WT098051). We acknowledge support from the UK Department of Health via the NIHR comprehensive Biomedical Research Centre award to Guy's and St. Thomas' National Health Service (NHS) Foundation Trust in partnership with King's College London. This research was also supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. J.H.C. is in receipt of an NIHR Senior Investigator Award. The research team acknowledges the support of the NIHR through the Comprehensive Clinical Research Network. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, Department of Health, or Wellcome Trust. E.R.M. acknowledges support from NIHR Cambridge Biomedical Research Centre, an NIHR Senior Investigator Award, and the University of Cambridge has received salary support in respect of E.R.M. from the NHS in the East of England through the Clinical Academic Reserve. I.E.S. is supported by the National Health and Medical Research Council of Australia (Program Grant and Practitioner Fellowship)

Recovery of stereopsis through perceptual learning in human adults with abnormal binocular vision

Stereopsis, the perception of depth based on the disparity of the images projected to the retinas of the two eyes, is an important process in our three-dimensional world; however, 3–5% of the population is stereoblind or has seriously impaired stereovision. Here we provide evidence for the recovery of stereopsis through perceptual learning, the repetitive practice of a demanding visual task, in human adults long deprived of normal binocular vision. We used a training paradigm that combines monocular cues that were correlated perfectly with the disparity cues. Following perceptual learning (thousands of trials) with stereoscopic gratings, five adults who initially were stereoblind or stereoanomalous showed substantial recovery of stereopsis, both on psychophysical tests with stimuli that contained no monocular cues and on clinical testing. They reported that depth “popped out” in daily life, and enjoyed 3D movies for the first time. After training, stereo tests with dynamic random-dot stereograms and band-pass noise revealed the properties of the recovered stereopsis: It has reduced resolution and precision, although it is based on perceiving depth by detecting binocular disparity. We conclude that some human adults deprived of normal binocular vision can recover stereopsis at least partially