Unsolved Cases Research Articles

Targeted long-read sequencing identifies missing pathogenic variants in unsolved Werner syndrome cases

BackgroundWerner syndrome (WS) is an autosomal recessive progeroid syndrome caused by variants in WRN. The International Registry of Werner Syndrome has identified biallelic pathogenic variants in 179/188 cases of classical...

German reference network for rare eye diseases (DRN-EYE). The way to national networking

The German reference network for rare eye diseases (DRN-EYE) is anational network of ophthalmologists, who treat patients with rare eye diseases in Germany. The aim of DRN-EYE is to create atransparent structure that facilitates and improves the medical care of rare diseases of the eye for patients and for ophthalmologists. The competence of DRN-EYE lies in the area of anterior eye segment diseases as well as of the retina, neuro-ophthalmology and the orbit. The network also offers open virtual meetings every 3 months to present unsolved clinical cases as well as further education and overview of the currently running clinical trials.

A flow approach to the Musielak-Orlicz-Gauss image problem

In this paper, the extended Musielak-Orlicz-Gauss image problem is studied. Such a problem aims to characterize the Musielak-Orlicz-Gauss image measure C˜G,Ψ,λ(Ω,⋅) of convex body Ω in Rn+1 containing the origin (but the origin is not necessary in its interior). In particular, we provide solutions to the extended Musielak-Orlicz-Gauss image problem based on the study of suitably designed parabolic flows, and by the use of approximation technique (for general measures). Our parabolic flows involve two Musielak-Orlicz functions and hence contain many well-studied curvature flows related to Minkowski type problems as special cases. Our results not only generalize many previously known solutions to the Minkowski type and Gauss image problems, but also provide solutions to those problems in many unsolved cases.

On vertex-weighted realizations of acyclic and general graphs

Consider the following natural variation of the degree realization problem. Let G=(V,E) be a simple undirected graph of order n. Let f∈R≥0n be a vector of vertex requirements, and let w∈R≥0n be a vector of provided services at the vertices. Then w satisfies f on G if the constraints ∑j∈N(i)wj=fi are satisfied for all i∈V, where N(i) denotes the neighbourhood of vector i. Given a requirements vector f, the Vertex-Weighted Graph Realization problem asks for a suitable graph G and a vector w of provided services that satisfy f on G.In this paper, we consider two avenues. We initiate a study that focuses on weighted realizations where the graph is required to be of a specific class by providing a full characterization of realizable requirement vectors for paths and acyclic graphs. However, checking the respective criteria is shown to be NP-hard.In the second part, we advance the study in general graphs which was started in [2]. For the unsolved cases, the question of whether a vector f is realizable can be formulated as whether its largest requirement lies within certain intervals. We describe several new, realizable intervals and show the existence of an interval that cannot be realized. The complete classification for general graphs is an open problem.

Whole Genome Sequencing, Focused Assays and Functional Studies Increasing Understanding in Cryptic Inherited Retinal Dystrophies.

The inherited retinal dystrophies (IRDs) are a clinically and genetically complex group of disorders primarily affecting the rod and cone photoreceptors or other retinal neuronal layers, with emerging therapies heralding the need for accurate molecular diagnosis. Targeted capture and panel-based strategies examining the partial or full exome deliver molecular diagnoses in many IRD families tested. However, approximately one in three families remain unsolved and unable to obtain personalised recurrence risk or access to new clinical trials or therapy. In this study, we investigated whole genome sequencing (WGS), focused assays and functional studies to assist with unsolved IRD cases and facilitate integration of these approaches to a broad molecular diagnostic clinical service. The WGS approach identified variants not covered or underinvestigated by targeted capture panel-based clinical testing strategies in six families. This included structural variants, with notable benefit of the WGS approach in repetitive regions demonstrated by a family with a hybrid gene and hemizygous missense variant involving the opsin genes, OPN1LW and OPN1MW. There was also benefit in investigation of the repetitive GC-rich ORF15 region of RPGR. Further molecular investigations were facilitated by focused assays in these regions. Deep intronic variants were identified in IQCB1 and ABCA4, with functional RNA based studies of the IQCB1 variant revealing activation of a cryptic splice acceptor site. While targeted capture panel-based methods are successful in achieving an efficient molecular diagnosis in a proportion of cases, this study highlights the additional benefit and clinical value that may be derived from WGS, focused assays and functional genomics in the highly heterogeneous IRDs.

Genomic answers for children: Dynamic analyses of >1000 pediatric rare disease genomes

PurposeThis study aimed to provide comprehensive diagnostic and candidate analyses in a pediatric rare disease cohort through the Genomic Answers for Kids program. MethodsExtensive analyses of 960 families with suspected genetic disorders included short-read exome sequencing and short-read genome sequencing (srGS); PacBio HiFi long-read genome sequencing (HiFi-GS); variant calling for single nucleotide variants (SNV), structural variant (SV), and repeat variants; and machine-learning variant prioritization. Structured phenotypes, prioritized variants, and pedigrees were stored in PhenoTips database, with data sharing through controlled access the database of Genotypes and Phenotypes. ResultsDiagnostic rates ranged from 11% in patients with prior negative genetic testing to 34.5% in naive patients. Incorporating SVs from genome sequencing added up to 13% of new diagnoses in previously unsolved cases. HiFi-GS yielded increased discovery rate with >4-fold more rare coding SVs compared with srGS. Variants and genes of unknown significance remain the most common finding (58% of nondiagnostic cases). ConclusionComputational prioritization is efficient for diagnostic SNVs. Thorough identification of non-SNVs remains challenging and is partly mitigated using HiFi-GS sequencing. Importantly, community research is supported by sharing real-time data to accelerate gene validation and by providing HiFi variant (SNV/SV) resources from >1000 human alleles to facilitate implementation of new sequencing platforms for rare disease diagnoses.

Solving the genetic aetiology of hereditary gastrointestinal tumour syndromes– a collaborative multicentre endeavour within the project Solve-RD

BackgroundPatients and families with suspected, but genetically unexplained (unsolved) genetic tumour risk syndromes lack appropriate treatment and prevention, leading to preventable morbidity and mortality. To tackle this problem, patients from the European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS) are analysed in the European Commission's research project “Solving the unsolved rare diseases” (Solve-RD). The aim is to uncover known and novel cancer predisposing genes by reanalysing available whole-exome sequencing (WES) data of large cohorts in a combined manner, and applying a multidimensional omics approach. ApproachAround 500 genetically unsolved cases with suspected hereditary gastrointestinal tumour syndromes (polyposis, early-onset/familial colorectal cancer and gastric cancer) from multiple European centres are aimed to be included. Currently, clinical and germline WES data from 294 cases have been analysed. In addition, an extensive molecular profiling of gastrointestinal tumours from these patients is planned and deep learning techniques will be applied. The ambitious, multidisciplinary project is accompanied by a number of methodical, technical, and logistic challenges, which require the development and implementation of new analysis tools, the standardisation of bioinformatics pipelines, and strategies to exchange data and knowledge. Resultsand Outlook. The first re-analysis of 229 known and proposed cancer predisposition genes allowed solving 2–3% of previously unsolved GENTURIS cases. The integration of expert knowledge and new technologies will help to identify the genetic basis of additional unsolved cases within the ongoing project. The ERN GENTURIS approach might serve as a model for other genomic initiatives.

Genetic characteristics of 234 Italian patients with macular and cone/cone-rod dystrophy

Two-hundred and thirty-four Italian patients with a clinical diagnosis of macular, cone and cone-rod dystrophies (MD, CD, and CRD) were examined using next-generation sequencing (NGS) and gene sequencing panels targeting a specific set of genes, Sanger sequencing and—when necessary—multiplex ligation-dependent probe amplification (MLPA) to diagnose the molecular cause of the aforementioned diseases. When possible, segregation analysis was performed in order to confirm unsolved cases. Each patient’s retinal phenotypic characteristics were determined using focal and full-field ERGs, perimetry, spectral domain optical coherence tomography and fundus autofluorescence. We identified 236 potentially causative variants in 136 patients representing the 58.1% of the total cohort, 43 of which were unpublished. After stratifying the patients according to their clinical suspicion, the diagnostic yield was 62.5% and 53.8% for patients with MD and for those with CD/CRD, respectively. The mode of inheritance of all cases confirmed by genetic analysis was 70% autosomal recessive, 26% dominant, and 4% X-linked. The main cause (59%) of both MD and CD/CRD cases was the presence of variants in the ABCA4 gene, followed by variants in PRPH2 (9%) and BEST1 (6%). A careful morpho-functional evaluation of the phenotype, together with genetic counselling, resulted in an acceptable diagnostic yield in a large cohort of Italian patients. Our study emphasizes the role of targeted NGS to diagnose MDs, CDs, and CRDs, as well as the clinical usefulness of segregation analysis for patients with unsolved diagnosis.

OP038: Novel whole methylome automated data analysis tool for investigation of unsolved diagnostic odyssey cases

The study of epigenetics has changed the lens in which we view both health and disease. Emerging tools in this field have brought new discoveries to the forefront of preventive, diagnostic and therapeutic markers. DNA methylation is an essential process that regulates chromatin structure and gene expression, and therefore affects many cellular functions including gene imprinting and cell differentiation. Using the power of molecular techniques and bioinformatics, we can now gain insight into methylation patterns at a single nucleotide level throughout the genome. In this study, we developed a methylation automated data analyzer to investigate putative multi-locus methylation defects in diagnostic odyssey cases, and to further appreciate differences in methylation patterns across the lifespan. Individual pathway analyses for genes DNMT3A, NLRP5, NLRP7, NPM2, PADI6 and ZFP42 were conducted. These genes were chosen because they are either known methyltransferases or may cause hypermethylation of H19 and/or hypomethylation of LIT1 . Additional genes from this analysis were chosen based on known direct interactions with the original input gene and co-expression with the input gene resulting in a final list of 15 genes of interest. Next, we filtered through the history of our exome sequencing (ES) cases from our clinical laboratory with high impact variants in these 15 genes of interest. Cases were chosen based on impact of the variant and allele frequency in gnomAD, which resulted in 11 cases, 10 of which were unsolved by ES. Methylation profiling was performed on all 11 cases using the Infinium MethylationEPIC 850K array. Using Python3.7, we developed our own unique Methylation Automation Data Analyzer (MADA). Using MADA, each case was analyzed and compared to either 74 female or 75 male healthy controls of various ages spanning from newborn to 81 years. Probes with a difference greater than or equal to 0.5 between the patient beta value and the mean beta value of the controls were selected. This final list of probes was investigated further based on genomic region, gene content, proximity to a CpG island and the individual patient’s phenotype. To investigate methylation patterns of various genomic regions across the lifespan, a separate algorithm within MADA was constructed. This analysis uses our cohort of healthy individuals (74 males and 75 females) and calculates the mean beta value for each age for each probe and thus allows for the observation of changes in methylation over time in healthy individuals from age newborn to 81 years. MADA provided insight into methylation of genomic regions that had otherwise been overlooked by conventional genetic testing in diagnostic odyssey cases. Here, we highlight three patients. Patient #1, a 13-year old male, had a de novo point variant in DNMT1 c.4636C>G; p.Pro1546Ala (NM_001130823.2) by ES. MADA produced a final list of 13 probes for which the genomic regions were all significantly hypermethylated compared to controls. This patient had additional clinical features that were atypical for the DNMT1 spectrum of phenotypes and MADA revealed other interesting findings that could potentially be contributing to the additional features. Patient #2, a 7-year old male, had a heterozygous maternally inherited variant in KHDC3L c.31_39dup9 p.Val11_Leu13dup (NM_001017361.3) by ES. MADA identified 11 probes of interest of which four regions covered by these probes were hypomethylated (including LARS2) and seven were hypermethylated as compared to the controls. This patient’s phenotype includes abnormal facial shape, autistic behavior delayed speech and language development, developmental regression, hyperpigmentation of the skin, intellectual disability, neurodevelopmental abnormality, and abnormal gait. Patient #3, a 10-year-old male with a paternally inherited variant NLRP7 c.2243_2249del7 (NM_001127255.1) identified through ES. The patient’s phenotype included absent speech, anxiety, aplasia cutis congenita of scalp, autistic behavior, brachycephaly, cortical dysplasia, dental crowding, intellectual disability, thin ear helix and progressive language deterioration. MADA identified 13 hits, including AFF2 and LARS2 both of which are hypomethylated in the patient compared to the controls. The second analysis investigated methylation patterns of various genomic regions across the lifespan. This tool allows for the input of any gene covered by the Illumina Infinium platform to be analyzed. We observed that there are critical points in an individual’s lifespan during which methylation of various genomic regions is altered that have not been previously described. These periods are related to important developmental stages such as infancy and puberty, among others. MADA can hence be used as a tool to further understand epigenomic changes during these critical periods throughout the lifespan, and the consequences of deviations from normal methylation patterns. There is growing evidence of “episignatures” or DNA methylation biomarkers for over 40 rare disorders in association with more than 60 genes. This study describes the development of a novel whole methylome automated data analysis tool, MADA, for the investigation of unsolved diagnostic odyssey cases. MADA offers an easy, streamlined approach for analysis of the methylome in undiagnosed ES cases and for uncovering potential episignatures in rare disorders.

EP338: Efficacy of next generation sequencing data reanalysis in unsolved cases with suspected Mendelian disorders: A systematic review and meta-analysis

Over the past decade, next generation sequencing (NGS) has revolutionized the diagnosis of Mendelian disorders. By simultaneously testing all known disease-causing and potentially novel genes in a hypothesis-free manner, it has led to significant improvements in both diagnostic yield and turnaround time compared to traditional approaches such as targeted Sanger sequencing of candidate genes. However, despite these improvements, more than 50% of cases typically remain unsolved after initial NGS analysis.

EP477: A classifier prioritizing exome and genome sequencing cases for re-analysis

It remains difficult to diagnose rare diseases by means of Genome or Exome Sequencing (GS or ES), with diagnostic yield of these tests estimated to range from 25% to 40%. Initially unsolved cases can become more solvable over time as knowledgebase annotations become more complete or as an individual patient’s phenotypic profile develops. However, it is not feasible to allocate human effort to re-analyzing the growing backlog of unsolved cases at a regular interval. The goal of this work is to identify cases which are most likely to be solvable based on a combination of demographic information and quantitative markers of the likely causality of genetic variation present in each patient. In a cohort of 611 patients who received ES, 187 (30.6%) were diagnosed and 79 had no medically meaningful findings. These groups were designated “solvable” and “not solvable”, respectively. The remaining 345 cases were designated as “potentially solvable”. For each patient, 28 features were recorded: sex, age, time since previous analysis, and the Likelihood Ratio (LR) scores of the top 25 variants as calculated by a modified version of LIRICAL, a likelihood ratio-driven algorithm which computes the post-test probability that each variant found in a patient’s Variant Call File (VCF) is causative of their phenotype. With an 80:20 train-test split of the 266 cases marked as either “solvable” or “not solvable”, we evaluated logistic regression and random forest models from a parameter grid search by 5-fold cross validation, resolving the LR scores into their principal components decomposition and using SMOTE to correct for class imbalances. This grid search selected a random forest model on 100 trees with maximum depth 10 and no minimum impurity split requirement. The selected model classified the test set with recall = 0.868 and precision = 0.767. Of the 345 potentially solvable cases, the model labeled 234 as “solvable”; based on the model’s precision, we estimate 179 of these cases are likely to be solvable with the remainder being false positives. Based on the model’s false negative rate, we estimate the model misses 23 solvable cases, implying a total of 202 solvable cases among the 345 potentially solvable cases. Thus, the model recovers 179/202 (88.6%) of the remaining solvable cases, while requiring inspection of only 234 (67.8%) of the 345 potentially solvable cases. By contrast, we would expect 234 randomly chosen potentially solvable cases to include approximately 118/202 (58.4%) of the remaining solvable cases. A machine learning approach has potential to prioritize re-analysis effort and obtain higher diagnostic yield at a lower human effort cost. This approach does not altogether depart from the default approach of re-analysis in order of previous analysis, as the time since previous analysis was a highly-weighted feature in many of the parameter configurations searched. Using a framework which includes both biological data and case-level demographics at regular intervals should give all cases a chance to eventually be considered for re-analysis.

EP158: The utility of transcriptomics to increase diagnostic yield in cases of rare genetic disease

Rare diseases affect less than 1 in 200,000 individuals by definition, however, collectively are common, with approximately 30 million individuals in the United States impacted. Frequently individuals experience an arduous journey towards a rare disease diagnosis, often termed a “diagnostic odyssey”. Exome sequencing (ES) has become standard of care for patients with suspected rare genetic disease, with a diagnostic yield of 30%. Here we report on preliminary results of the largest study to date integrating transcriptome sequencing (RNAseq) with ES to increase diagnostic yield for rare disease patients. A cohort of 406 patients who were consented into the Mayo Clinic Diagnostic Odyssey study were selected for study. All patients had received clinical or research exome sequencing which failed to result in a definitive diagnosis. RNA was extracted from whole blood collected in PAXgene tubes, and sequencing libraries prepared using a hybridization capture protocol with the TruSeq RNA Access Library Prep Kit (Illumina, San Diego, CA). Paired-end 101-basepair reads were sequenced using Illumina instruments. Resulting RNA sequences were analyzed for fusion using two algorithms, LeafCutterMD and Fraser, with results integrated for review. Allele specific expression was determined using AnevaDot. Gene expression was analyzed for outlier expression patterns in individual patients compared to the entire cohort using Outrider. Fusion analysis was performed using an internal workflow previously described. The major advantages RNAseq in addition to ES are the high-throughput functional characterization of DNA variation and the detection of aberrations not identifiable by ES sequencing alone. Recent work has shown a 7.5-35% yield using RNAseq in unsolved rare disease cases, dependent on tissue and methodology. In this study RNAseq was performed on blood from 406 individuals with suspected rare genetic disease for whom clinical ES was non-diagnostic. The transcriptome data was analyzed to interrogate four different effects: genes with outlier expression, aberrant RNA-splicing, gene fusions, and allele specific expression. Splicing analysis utilized two complementary algorithms, FRASER and LeafcutterMD, to identify modified intron usage, shifted splice donor and acceptor sites, intron retention events, and creation of cryptic exons. All data were studied for ultra-rare modifications with potential disease ramifications, using the remaining patient cohort as a control RNASeq population. Our preliminary results include gene fusion events, splice site variants with confirmed splicing alterations, and significantly altered outlier gene expression which were integral to the patient’s genetic diagnosis. RNA sequencing is complementary to DNA sequencing in the search for genetic diagnoses in Mendelian disease. When analyzing RNA data, care must be taken to evaluate all forms of RNA mediated events to obtain a thorough representation of the underlying genetics. Here we discuss a 406 patient cohort study using RNA and DNA sequencing to profile patient seen at the Mayo Clinic. Complete results of this study will provide valuable information regarding the clinical utility of RNAseq in tandem with ES for identifying a genetic diagnosis for rare disease patients.

EP141: Expansion of long-read genome sequencing for the molecular diagnosis of neurodevelopmental disorders and multiple congenital anomalies

Exome and genome sequencing (ES/GS) have proven to be effective tools for the diagnosis of rare disorders, including neurodevelopmental disorders (NDDs), and multiple congenital anomalies (MCA), many of which are due to highly penetrant, often de novo, variation. However, while discovery power and diagnostic yield of genomic testing have consistently improved over time, most cases of NDD/MCAs cannot be attributed to currently detectable genetic variation. We have recently applied long-reads produced using the Pacific Biosciences circular consensus sequence (CCS) technology to unsolved cases.

On 3-Coloring of (2P_4,C_5)-Free Graphs

The 3-coloring of hereditary graph classes has been a deeply-researched problem in the last decade. A hereditary graph class is characterized by a (possibly infinite) list of minimal forbidden induced subgraphs H_1,H_2,ldots ; the graphs in the class are called (H_1,H_2,ldots )-free. The complexity of 3-coloring is far from being understood, even for classes defined by a few small forbidden induced subgraphs. For H-free graphs, the complexity is settled for any H on up to seven vertices. There are only two unsolved cases on eight vertices, namely 2P_4 and P_8. For P_8-free graphs, some partial results are known, but to the best of our knowledge, 2P_4-free graphs have not been explored yet. In this paper, we show that the 3-coloring problem is polynomial-time solvable on (2P_4,C_5)-free graphs.

Methods to Improve Molecular Diagnosis in Genomic Cold Cases in Pediatric Neurology.

During the last decade, genetic testing has emerged as an important etiological diagnostic tool for Mendelian diseases, including pediatric neurological conditions. A genetic diagnosis has a considerable impact on disease management and treatment; however, many cases remain undiagnosed after applying standard diagnostic sequencing techniques. This review discusses various methods to improve the molecular diagnostic rates in these genomic cold cases. We discuss extended analysis methods to consider, non-Mendelian inheritance models, mosaicism, dual/multiple diagnoses, periodic re-analysis, artificial intelligence tools, and deep phenotyping, in addition to integrating various omics methods to improve variant prioritization. Last, novel genomic technologies, including long-read sequencing, artificial long-read sequencing, and optical genome mapping are discussed. In conclusion, a more comprehensive molecular analysis and a timely re-analysis of unsolved cases are imperative to improve diagnostic rates. In addition, our current understanding of the human genome is still limited due to restrictions in technologies. Novel technologies are now available that improve upon some of these limitations and can capture all human genomic variation more accurately. Last, we recommend a more routine implementation of high molecular weight DNA extraction methods that is coherent with the ability to use and/or optimally benefit from these novel genomic methods.

Sporadic hypothalamic hamartoma is a ciliopathy with somatic and bi-allelic contributions.

Hypothalamic hamartoma with gelastic seizures is a well-established cause of drug-resistant epilepsy in early life. The development of novel surgical techniques has permitted the genomic interrogation of hypothalamic hamartoma tissue. This has revealed causative mosaic variants within GLI3, OFD1 and other key regulators of the sonic-hedgehog pathway in a minority of cases. Sonic-hedgehog signalling proteins localize to the cellular organelle primary cilia. We therefore explored the hypothesis that cilia gene variants may underlie hitherto unsolved cases of sporadic hypothalamic hamartoma. We performed high-depth exome sequencing and chromosomal microarray on surgically resected hypothalamic hamartoma tissue and paired leukocyte-derived DNA from 27 patients. We searched for both germline and somatic variants under both dominant and bi-allelic genetic models. In hamartoma-derived DNA of seven patients we identified bi-allelic (one germline, one somatic) variants within one of four cilia genes-DYNC2I1, DYNC2H1, IFT140 or SMO. In eight patients, we identified single somatic variants in the previously established hypothalamic hamartoma disease genes GLI3 or OFD1. Overall, we established a plausible molecular cause for 15/27 (56%) patients. Here, we expand the genetic architecture beyond single variants within dominant disease genes that cause sporadic hypothalamic hamartoma to bi-allelic (one germline/one somatic) variants, implicate three novel cilia genes and reconceptualize the disorder as a ciliopathy.

Induction of Decision Trees to Diagnose Incipient Faults in Power Transformers

This article describes the use of a decision tree (DT) approach based on computational intelligence (CI) for the analysis and diagnosis of incipient faults in power transformers. The method relies on measuring the combustible gas concentration in parts per million (ppm) from samples of the insulating oil. Currently, the Duval triangle method is one of the most traditional techniques used for the dissolved gas analysis (DGA), but it has limited accuracy. To overcome such conventional performance problems, CI techniques as artificial neural networks, fuzzy systems, and more recently DTs have been proposed as possible solutions. In this context, by using the gain ratio as a metric for attribute selection, this work demonstrates that the DT algorithm is capable of extracting as much information as possible from each class. It can also provide a solution for unsolved cases by using the traditional diagnosis method. Overall, it is reasonable to state that DT plays an important role in the improvement of DGA performance, this being a promising tool that can be combined with other traditional techniques. Another important aspect is that in the end of training the tree generates clear and ease-of-use rules. The proposed technique results in fast and accurate solutions for diagnosing faults in power transformers. It can be effectively implemented in corrective maintenance to avoid permanent burning and damage of equipment.

An evaluation of pipelines for DNA variant detection can guide a reanalysis protocol to increase the diagnostic ratio of genetic diseases

Clinical exome (CE) sequencing has become a first-tier diagnostic test for hereditary diseases; however, its diagnostic rate is around 30–50%. In this study, we aimed to increase the diagnostic yield of CE using a custom reanalysis algorithm. Sequencing data were available for three cohorts using two commercial protocols applied as part of the diagnostic process. Using these cohorts, we compared the performance of general and clinically relevant variant calling and the efficacy of an in-house bioinformatic protocol (FJD-pipeline) in detecting causal variants as compared to commercial protocols. On the whole, the FJD-pipeline detected 99.74% of the causal variants identified by the commercial protocol in previously solved cases. In the unsolved cases, FJD-pipeline detects more INDELs and non-exonic variants, and is able to increase the diagnostic yield in 2.5% and 3.2% in the re-analysis of 78 cancer and 62 cardiovascular cases. These results were considered to design a reanalysis, filtering and prioritization algorithm that was tested by reassessing 68 inconclusive cases of monoallelic autosomal recessive retinal dystrophies increasing the diagnosis by 4.4%. In conclusion, a guided NGS reanalysis of unsolved cases increases the diagnostic yield in genetic disorders, making it a useful diagnostic tool in medical genetics.

Molecular Sexing and Species Detection of Antlered European Hunting Game for Forensic Purposes.

Simple SummaryThe reasons behind illegal hunting can be widely different. There are also tricky methods that hunters use in the attempt to legalize their illegally-acquired trophies, specifically, introducing them in later seasons, and registering the eviscerated corpses as hinds. During certain periods of the year, hunters are only able to acquire a license for the shooting of female deer exclusively, with the male-hunting season beginning later. The eviscerated and decapitated carcass of the animal delivered to the wild game processing house cold store can be falsely registered as a female based on phenotype. If the hunting association suspects that the animal’s sex has been falsely reported, a forensic genetic investigation can be proposed. In other criminal events, there are no carcasses at all. When several biological remains left on the crime scene need to be tested, a fast and cost-effective detection of a given species or species-group might be substantial before subsequent analysis. Therefore, sex and species detection can provide an early-stage credibility to the resolution of illegal activities related to trophy animals, and additionally may disclose potential poaching disputes.Molecular sexing techniques are widely applied in conservation biology, although the range of forensically validated methods is fairly limited. The primary aim of this work was to develop forensically validated assays, using two PCR panels for sex and species assignment for the abundant antlered European game species: red deer (Cervus elaphus), roe deer (Capreolus capreolus) and fallow deer (Dama dama). Segments of the SRY and Amelogenin X/Y genes for sex determination, additionally species-specific cytochrome b regions for species detection were targeted and separately amplified in two multiplex reactions. These assays can reliably analyze trace amounts of DNA. The results of both can easily be visualized and interpreted practically, either on agarose gel or by capillary electrophoresis. These simple, fast molecular assays are able to affect the early-stage resolution of disputed or unsolved poaching cases, without the need of individualization or sequencing of forensic samples.

Genomic variants reducing expression of two endocytic receptors in 46,XY differences of sex development.

Transporter-dependent steroid hormone uptake into target cells was demonstrated in genetically engineered mice and fruit flies. We hypothesized that mutations in such transporters may cause differences in sex development (DSD) in humans. Exome sequencing was performed in 16 genetically unsolved cases of 46,XY DSD selected from an anonymized collection of 708 lines of genital fibroblasts (GF) that were taken from individuals with incomplete virilization. Selection criteria were based on available biochemical characterization of GF compatible with reduced androgen uptake. Two unrelated individuals were identified with mutations in LDL receptor-related protein 2 (LRP2), a gene previously associated with partial sex steroid insensitivity in mice. Like Lrp2-/- mice, affected individuals had non-descended testes. Western blots on GF confirmed reduced LRP2 expression, and endocytosis of sex hormone-binding globulin was reduced. In three unrelated individuals, two with undescended testes, mutations in another endocytic receptor gene, limb development membrane protein 1 like (LMBR1L), were detected. Two of these individuals had mutations affecting the same codon. In a transfected cell model, mutated LMBR1L showed reduced cell surface expression. Our findings suggest that endocytic androgen uptake in complex with sex hormone-binding globulin is relevant in human. LMBR1L may play a similar role in androgen uptake.