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While de novo mutations (DNMs) are key to genetic diversity, they are also responsible for a high number of rare disorders. To date, no study has systematically examined the rate and distribution of DNMs in multiplex families in highly consanguineous populations. Leveraging WGS profiles of 645 individuals in 146 families, we implemented a combinatorial approach using 3 complementary tools for DNM discovery in 353 unique trio combinations. We found a total of 27,168 DNMs (median: 70 single-nucleotide and 6 insertion-deletions per individual). Phasing revealed around 80% of DNMs were paternal in origin. Notably, using whole-genome methylation data of spermatogonial stem cells, these DNMs were significantly more likely to occur at highly methylated CpGs (OR: 2.03; p value = 6.62 × 10−11). We then examined the effects of consanguinity and ethnicity on DNMs, and found that consanguinity does not seem to correlate with DNM rate, and special attention has to be considered while measuring such a correlation. Additionally, we found that Middle-Eastern families with Arab ancestry had fewer DNMs than African families, although not significant (p value = 0.16). Finally, for families with diseased probands, we examined the difference in DNM counts and putative impact across affected and unaffected siblings, but did not find significant differences between disease groups, likely owing to the enrichment for recessive disorders in this part of the world, or the small sample size per clinical condition. This study serves as a reference for DNM discovery in multiplex families from the globally under-represented populations of the Middle-East.Other Information Published in: Journal of Human Genetics License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1038/s10038-022-01054-9

Clefts of the lip and/or palate (CL/P) are considered the most common form of congenital anomalies occurring either in isolation or in association with other clinical features. Van der woude syndrome (VWS) is associated with about 2% of all CL/P cases and is further characterized by having lower lip pits. Popliteal pterygium syndrome (PPS) is a more severe form of VWS, normally characterized by orofacial clefts, lower lip pits, skin webbing, skeletal anomalies and syndactyly of toes and fingers. Both syndromes are inherited in an autosomal dominant manner, usually caused by heterozygous mutations in the Interferon Regulatory Factor 6 (IRF6) gene. Here we report the case of a two-generation family where the index presented with popliteal pterygium syndrome while both the father and sister had clinical features of van der woude syndrome, but without any point mutations detected by re-sequencing of known gene panels or microarray testing. Using whole genome sequencing (WGS) followed by local de novo assembly, we discover and validate a copy-neutral, 429 kb complex intra-chromosomal rearrangement in the long arm of chromosome 1, disrupting the IRF6 gene. This variant is copy-neutral, novel against publicly available databases, and segregates in the family in an autosomal dominant pattern. This finding suggests that missing heritability in rare diseases may be due to complex genomic rearrangements that can be resolved by WGS and de novo assembly, helping deliver answers to patients where no genetic etiology was identified by other means.

In this study, we present an automated system for feature recognition in digital images. Such a system is very important for morphometric analysis as it will replace the time consuming and labour intensive process of manual identification. The analysis system is constructed from four key stages: a feature based detection of the fly wing structure, recording the compact invariant shape descriptors using the pairwise geometric histogram (PGH) representation, global estimation of the pose using the probabilistic Hough transform and finally a correlation based refinement of individual features. The performance of the system, its reliability and robustness are evaluated in comparison to the expert manual performance.

Our aim is to develop a completely automated and reliable system to identify morphological landmarks in digital images. The performance of the system is aimed to replicate manual digitization with equivalent accuracy and reliability, based upon a small number of training examples. The analysis system is constructed from four stages; a feature based detection of fly wing structure, correspondence matching based upon the pairwise geometric histogram (PGH) representation, global location of the wing using a Probabilistic Hough Transform (PHT), and finally local correlation bas ed refinement of individual features. We evaluate this system and compare quantitative results to manually digitized data. 1 Background Morphological landmarks are points that can be located precisely and establish an unambiguous one-to-one correspondence among all the specimens and are widely used in shape analysis [1]. Points like the tip of the nose or the oute r corner of the left eye are possible landmark points of the human face. Analyses of shape investigate the arrangement of landmark points relative to each other. A substantial body of statistical methods is available for the analysis of configurations of landmark p oints [2]. This framework of shape analysis by landmarks is increasingly used in many biological and medical applications and widely applied in many other fields. The configuration of landmarks have helped identify the possible source of re-infesting specimens and encounter the epidemiologically challenging vectors of Chagas disease [3]. The potential of using geometrical morphometric techniques as an invaluable tool for recognizing taxonomic data is being explored [4]. Other scientific applicat ions include investigating the study of size and shape to examine the effects of experimental treatments, genotype or other factors directly in the anatomical aspect. The use of l andmarks has been adapted to specific biological contexts such as genetics [5, 6, 7]; geog raphic differentiation [8], and the study of morphological integration [9, 10]. The process of identifying the landmarks is an important and labour-intensive part of any such analysis. Presently, this is usually done manually. Plugins for the ImageJ software (for digitizing the standard sets of landmarks) on fly wi ngs and mouse mandibles), increases speed and reliability over a completely unaided process [11]. However, there is still a requirement for an observer to manually identify each landmark point and therefore this process can be time-consuming, and quite often, the research questions are dependant on the duration of obtaining these data.

The authors present an automated system for feature recognition in digital images. Morphometric landmarks are points that can be defined in all specimens and located precisely. They are widely used in shape analysis and a typical shape analysis study involves several hundred digital images. Presently, the extraction of landmarks is usually done manually and the process of identifying the landmarks is an important and labour-intensive part of any such analysis. This process is time-consuming, and quite often the research questions are dependent on the duration of obtaining these data. The authors show that a single training image with its landmark co-ordinates is enough to independently estimate the landmarks of any individual within a particular data set. The reliability and accuracy of the method can be further enhanced by using multiple training images. The precision, repeatability and robustness of the algorithm have been evaluated. It is shown in this study that the method is sufficiently accurate to replace the manual identification of landmarks. The generic nature and intrinsic capability of the feature recognition process enables this method to be easily incorporated into other recognition tasks.