Genotype-phenotype Relationships Research Articles

Non-syndromic Intellectual Disability: An Experimental In-Depth Exploration of Inheritance Pattern, Phenotypic Presentation, and Genomic Composition.

Background Intellectual disability (ID), also termed mental retardation (MR), is a neurodevelopmental disorder characterized by an intelligence quotient (IQ) of 70 or below and a deficit in at least two behaviors associated with adaptive functioning. The condition is further classified into syndromic intellectual disability (S-ID) and non-syndromic intellectual disability (NS-ID). This study highlights the genes associated with NS-ID. Objectives A genetic study was performed on two Pakistani families to know the inheritance patterns, clinical phenotypes, and molecular genetics of affected individuals with NS-ID. Methodology Samples were collected from two families: families A and B. All affected individuals in both families were diagnosed by a neurologist. Written informed consent was taken from the affected individuals and guardians before collecting the data and sample. Family A belongs to the Swabi District of Pakistan having four affected individuals, out of whom three were male and one was female. Family B also belongs to the Swabi District of Pakistan having two affected individuals, out of whom one was male and one was female. A total of 10 candidate genes were selected and were further screened by microarray analysis. Results In family A, this analysis identified a region of 9.6 Mb on chromosome 17q11.2-q12 between the single nucleotide polymorphisms (SNPs) rs953527 and rs2680398. The region was genotyped using microsatellite markers to confirm the haplotypes in all family members. Based on the phenotype-genotype relationship, 10 possible candidate genes were selected out of more than 140 genes in this critical region of 9.6 Mb. In family B, homozygosity mapping through microarray identified four homozygous areas of affected individuals: two (27,324,822-59,122,062 and 96,423,252123,656,241) on chromosome 8, one (14,785,224-19,722,760) on chromosome 9, and one (126173647-126215644) on chromosome 11. Conclusion An autosomal recessive pattern was found in the pedigrees of both families A and B. Phenotypically affected individuals showed IQ levels below 70. Three genes, CDK5R1, OMG, and EV12A, were found on chromosome 17q11.2-q12 region of affected individuals in family A with high expression in the frontal cortex of the brain, hippocampus, and spinal cord, respectively. Other regions on chromosomes 8, 9, and 11 as evident from the affected individuals in family B can also contribute to the non-syndromic autosomal recessive intellectual disability (NS-ARID). Further research is needed to find the association of these genes with intelligence and other neuropsychiatric conditions.

Using Cluster Analysis to Overcome the Limits of Traditional Phenotype-Genotype Correlations: The Example of RYR1-Related Myopathies.

Thanks to advances in gene sequencing, RYR1-related myopathy (RYR1-RM) is now known to manifest itself in vastly heterogeneous forms, whose clinical interpretation is, therefore, highly challenging. We set out to develop a novel unsupervised cluster analysis method in a large patient population. The objective was to analyze the main RYR1-related characteristics to identify distinctive features of RYR1-RM and, thus, offer more precise genotype-phenotype correlations in a group of potentially life-threatening disorders. We studied 600 patients presenting with a suspicion of inherited myopathy, who were investigated using next-generation sequencing. Among them, 73 index cases harbored variants in RYR1. In an attempt to group genetic variants and fully exploit information derived from genetic, morphological, and clinical datasets, we performed unsupervised cluster analysis in 64 probands carrying monoallelic variants. Most of the 73 patients with positive molecular diagnoses were clinically asymptomatic or pauci-symptomatic. Multimodal integration of clinical and histological data, performed using a non-metric multi-dimensional scaling analysis with k-means clustering, grouped the 64 patients into 4 clusters with distinctive patterns of clinical and morphological findings. In addressing the need for more specific genotype-phenotype correlations, we found clustering to overcome the limits of the "single-dimension" paradigm traditionally used to describe genotype-phenotype relationships.

Targeting lipid metabolism as a new therapeutic strategy for inherited cardiomyopathies.

Inherited cardiomyopathies caused by pathological genetic variants include multiple subtypes of heart disease. Advances in next-generation sequencing (NGS) techniques have allowed for the identification of numerous genetic variants as pathological variants. However, the disease penetrance varies among mutated genes. Some can be associated with more than one disease subtype, leading to a complex genotype-phenotype relationship in inherited cardiomyopathies. Previous studies have demonstrated disrupted metabolism in inherited cardiomyopathies and the importance of metabolic adaptations in disease onset and progression. In addition, genotype- and phenotype-specific metabolic alterations, especially in lipid metabolism, have been revealed. In this mini-review, we describe the metabolic changes that are associated with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM), which account for the largest proportion of inherited cardiomyopathies. We also summarize the affected expression of genes involved in fatty acid oxidation (FAO) in DCM and HCM, highlighting the potential of PPARA-targeting drugs as FAO modulators in treating patients with inherited cardiomyopathies.

Skin manifestations of inborn errors of NF-κB.

More than 400 single gene defects have been identified as inborn errors of immunity, including many arising from genes encoding proteins that affect NF-κB activity. We summarise the skin phenotypes in this subset of disorders and provide an overview of pathogenic mechanisms. NF-κB acts cell-intrinsically in basal epithelial cells during differentiation of skin appendages, influences keratinocyte proliferation and survival, and both responses to and amplification of inflammation, particularly TNF. Skin phenotypes include ectodermal dysplasia, reduction and hyperproliferation of keratinocytes, and aberrant recruitment of inflammatory cells, which often occur in combination. Phenotypes conferred by these rare monogenic syndromes often resemble those observed with more common defects. This includes oral and perineal ulceration and pustular skin disease as occurs with Behcet's disease, hyperkeratosis with microabscess formation similar to psoriasis, and atopic dermatitis. Thus, these genotype-phenotype relations provide diagnostic clues for this subset of IEIs, and also provide insights into mechanisms of more common forms of skin disease.

Evolutionary Landscape of SOX Genes to Inform Genotype-to-Phenotype Relationships.

The SOX transcription factor family is pivotal in controlling aspects of development. To identify genotype-phenotype relationships of SOX proteins, we performed a non-biased study of SOX using 1890 open-reading frame and 6667 amino acid sequences in combination with structural dynamics to interpret 3999 gnomAD, 485 ClinVar, 1174 Geno2MP, and 4313 COSMIC human variants. We identified, within the HMG (High Mobility Group)- box, twenty-seven amino acids with changes in multiple SOX proteins annotated to clinical pathologies. These sites were screened through Geno2MP medical phenotypes, revealing novel SOX15 R104G associated with musculature abnormality and SOX8 R159G with intellectual disability. Within gnomAD, SOX18 E137K (rs201931544), found within the HMG box of ~0.8% of Latinx individuals, is associated with seizures and neurological complications, potentially through blood-brain barrier alterations. A total of 56 highly conserved variants were found at sites outside the HMG-box, including several within the SOX2 HMG-box-flanking region with neurological associations, several in the SOX9 dimerization region associated with Campomelic Dysplasia, SOX14 K88R (rs199932938) flanking the HMG box associated with cardiovascular complications within European populations, and SOX7 A379V (rs143587868) within an SOXF conserved far C-terminal domain heterozygous in 0.716% of African individuals with associated eye phenotypes. This SOX data compilation builds a robust genotype-to-phenotype association for a gene family through more robust ortholog data integration.

Identification and characterization of novel carboxyl ester lipase gene variants in patients with different subtypes of diabetes

IntroductionMutations of CEL gene were first reported to cause a new type of maturity-onset diabetes of the young (MODY) denoted as MODY8 and then were also found in patients with...

What's new in the WHO 2022 classification of kidney tumours?

The World Health Organization (WHO) 2022 classification of urinary and male genital tumours (5th edition) has significantly improved our understanding of the morphologic, immunohistochemical, and molecular characteristics of renal tumours. The aim of this review is to outline the most important changes and diagnostic updates in the WHO 2022 classification of kidney tumours. A major change in this edition is the grouping of renal tumours into broader categories that include "clear cell renal tumours", "papillary renal tumours", "oncocytic and chromophobe renal tumours", "collecting duct tumours" as well as adding two categories of "other renal tumours" and "molecularly defined renal carcinomas". Novel entities included in the WHO 2022 classification are eosinophilic solid and cystic renal cell carcinoma (ESC RCC), anaplastic lymphoma kinase (ALK)-rearranged RCC and ELOC (formerly TCEB1)-mutated RCC. The category of "other renal tumours" includes a group of diverse, unrelated renal tumours that do not fit into other categories. The group of "molecularly defined renal carcinomas" reflects recent discoveries in the renal tumour genomics. These molecularly-defined renal entities demonstrate a set of morphologic features reflecting genotype-phenotype relationships. Final diagnosis of such entities rests on phenotypic and immunohistochemical (IHC) correlation, usually associated with IHC surrogate makers that reflect specific genetic abnormalities.

A pedigree with retinitis pigmentosa and its concomitant ophthalmic diseases.

To characterize the ophthalmic clinical phenotype of a family with retinitis pigmentosa (RP) and closed-angle glaucoma and to detect pathogenic genes and mutation sites causing RP in this family. Ophthalmic clinic performance was examined in detail in 8 enrolled family members. Genomic DNA was extracted from the peripheral blood of 4 family members for whole-exome sequencing (WES) to select potential genetic mutations whose structures were identified by bioinformatics analysis. Then, Sanger sequencing was used in 12 family members and control group members to validate and confirm the disease-causing mutation loci, and we analyzed the genotype-phenotype relationships. The known c.512C>T (p.P171L) mutation in the rhodopsin (RHO) gene was only found in afflicted family members and was confirmed by WES and Sanger sequencing as the pathogenic mutation in this family. In addition to being diagnosed with RP, family member III:4 was found to have bilateral closed-angle glaucoma, high myopia, and concurrent cataracts, and family members II:2 and II:4 had pathological changes of anterior chamber angle narrowing. Family members IV:3 and IV:4 were found to have retinoschisis. Glaucoma and related pathological changes, such as retinoschisis, in family members are preliminarily considered RP complications caused by RHO mutation.

Expectile Neural Networks for Genetic Data Analysis of Complex Diseases.

The genetic etiologies of common diseases are highly complex and heterogeneous. Classic methods, such as linear regression, have successfully identified numerous variants associated with complex diseases. Nonetheless, for most diseases, the identified variants only account for a small proportion of heritability. Challenges remain to discover additional variants contributing to complex diseases. Expectile regression is a generalization of linear regression and provides complete information on the conditional distribution of a phenotype of interest. While expectile regression has many nice properties, it has rarely been used in genetic research. In this paper, we develop an expectile neural network (ENN) method for genetic data analyses of complex diseases. Similar to expectile regression, ENN provides a comprehensive view of relationships between genetic variants and disease phenotypes, which can be used to discover variants predisposing to sub-populations. We further integrate the idea of neural networks into ENN, making it capable of capturing non-linear and non-additive genetic effects (e.g., gene-gene interactions). Through simulations, we showed that the proposed method outperformed an existing expectile regression when there exist complex genotype-phenotype relationships. We also applied the proposed method to the data from the Study of Addiction: Genetics and Environment (SAGE), investigating the relationships of candidate genes with smoking quantity.

Patient-Induced Pluripotent Stem Cell–Derived Hepatostellate Organoids Establish a Basis for Liver Pathologies in Telomeropathies

Dyskeratosis congenita (DC) is a telomere biology disorder caused primarily by mutations in the DKC1 gene. Patients with DC and related telomeropathies resulting from premature telomere dysfunction experience multiorgan failure. In the liver, DC patients present with nodular hyperplasia, steatosis, inflammation, and cirrhosis. However, the mechanism responsible for telomere dysfunction-induced liver disease remains unclear. We used isogenic human induced pluripotent stem cells (iPSCs) harboring a causal DC mutation in DKC1 or a CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/Cas9)-corrected control allele to model DC liver pathologies. We differentiated these iPSCs into hepatocytes (HEPs) or hepatic stellate cells (HSCs) followed by generation of genotype-admixed hepatostellate organoids. Single-cell transcriptomics were applied to hepatostellate organoids to understand cell type-specific genotype-phenotype relationships. Directed differentiation of iPSCs into HEPs and stellate cells and subsequent hepatostellate organoid formation revealed a dominant phenotype in the parenchyma, withDC HEPs becoming hyperplastic and also eliciting a pathogenic hyperplastic, proinflammatory response in stellate cells independent of stellate cell genotype. Pathogenic phenotypes in DKC1-mutant HEPs and hepatostellate organoids could be rescued via suppression of serine/threonine kinase AKT (protein kinase B) activity, a central regulator of MYC-driven hyperplasia downstream of DKC1 mutation. Isogenic iPSC-derived admixed hepatostellate organoids offer insight into the liver pathologies in telomeropathies and provide a framework for evaluating emerging therapies.

Gain-of-Function Variomics and Multi-omics Network Biology for Precision Medicine.

Traditionally, disease causal mutations were thought to disrupt gene function. However, it becomes more clear that many deleterious mutations could exhibit a "gain-of-function" (GOF) behavior. Systematic investigation of such mutations has been lacking and largely overlooked. Advances in next-generation sequencing have identified thousands of genomic variants that perturb the normal functions of proteins, further contributing to diverse phenotypic consequences in disease. Elucidating the functional pathways rewired by GOF mutations will be crucial for prioritizing disease-causing variants and their resultant therapeutic liabilities. In distinct cell types (with varying genotypes), precise signal transduction controls cell decision, including gene regulation and phenotypic output. When signal transduction goes awry due to GOF mutations, it would give rise to various disease types. Quantitative and molecular understanding of network perturbations by GOF mutations may provide explanations for 'missing heritability" in previous genome-wide association studies. We envision that it will be instrumental to push current paradigm toward a thorough functional and quantitative modeling of all GOF mutations and their mechanistic molecular events involved in disease development and progression. Many fundamental questions pertaining to genotype-phenotype relationships remain unresolved. For example, which GOF mutations are key for gene regulation and cellular decisions? What are the GOF mechanisms at various regulation levels? How do interaction networks undergo rewiring upon GOF mutations? Is it possible to leverage GOF mutations to reprogram signal transduction in cells, aiming to cure disease? To begin to address these questions, we will cover a wide range of topics regarding GOF disease mutations and their characterization by multi-omic networks. We highlight the fundamental function of GOF mutations and discuss the potential mechanistic effects in the context of signaling networks. We also discuss advances in bioinformatic and computational resources, which will dramatically help with studies on the functional and phenotypic consequences of GOF mutations.

Novel PAX9 compound heterozygous variants in a Chinese family with non-syndromic oligodontia and genotype-phenotype analysis of PAX9 variants.

Studies have reported that >91.9% of non-syndromic tooth agenesis cases are caused by seven pathogenic genes. To report novel heterozygous PAX9 variants in a Chinese family with non-syndromic oligodontia and summarize the reported genotype-phenotype relationship of PAX9 variants. We recruited 28 patients with non-syndromic oligodontia who were admitted to the Hospital of Stomatology Hebei Medical University (China) from 2018 to 2021. Peripheral blood was collected from the probands and their core family members for whole-exome sequencing (WES) and variants were verified by Sanger sequencing. Bioinformatics tools were used to predict the pathogenicity of the variants. SWISS-MODEL homology modeling was used to analyze the three-dimensional structural changes of variant proteins. We also analyzed the genotype-phenotype relationships of PAX9 variants. We identified novel compound heterozygous PAX9 variants (reference sequence NM_001372076.1) in a Chinese family with non-syndromic oligodontia: a new missense variant c.1010C>A (p.T337K) in exon 4 and a new frameshift variant c.330_331insGT (p.D113Afs*9) in exon 2, which was identified as the pathogenic variant in this family. This discovery expands the known variant spectrum of PAX9; then, we summarized the phenotypes of non-syndromic oligodontia with PAX9 variants. We found that PAX9 variants commonly lead to loss of the second molars.

Functional identification of two novel variants and a hypomorphic variant in ASS1 from patients with Citrullinemia type I.

Background: Citrullinemia type I (CTLN1) is a rare autosomal recessive inborn error of the urea cycle caused by mutations in the gene encoding the arginosuccinate synthetase (ASS1) enzyme. Classic CTLN1 often manifests with acute hyperammonemia and neurological symptoms. Molecular genetic testing is critical for patient diagnosis. Methods: Three unrelated families with clinically suspected CTLN1 were included in this study. Potential pathogenic variants were identified using whole exome sequencing (WES) and validated using Sanger sequencing. Western blotting, quantitative PCR, immunofluorescent staining, and ELISA were used to assess functional changes in candidate ASS1 variants. Results: Five variants were identified, two of which were novel, and one has been reported, but its pathogenicity was not validated. The novel variant c.649-651del (p.P217del) and the 5'UTR variant (c.-4C>T) resulted in a decrease in ASS1 expression at both the protein and transcription levels. The other novel variant, c.1048C>T (p.Q350*), showed a marked decrease in expression at the protein level, with the formation of truncated proteins but an increased transcription. Both c.649_651del (p.P217del) and c.1048C>T (p.Q350*) showed a highly significant reduction in enzyme activity, while c.-4C>T had no effect. Conclusion: We identified two novel variants and a hypomorphic non-coding variant in ASS1 and validated the pathogenicity using functional studies. Our findings contribute to expanding the spectrum of ASS1 variants and understanding the genotype-phenotype relationships of CTLN1.

IMPORTANCE OF ETHOLOGY APPLIED BY VETERINARIANS FOR ADAPTATION SYNDROME IN ZOO ANIMALS

Animal rearing regimes in zoos can be strongly altered according to the adaptation of animals to the captive environment. These changes can modulate animal well-being. In this review, we approach studies of ethological action and its impacts on the adaptation syndrome of captive animals. Zoos offer multiple ways of making adaptations of animals more difficult. strongly favoring the appearance of this syndrome. Animal organisms have their own characteristics, which allow us to identify their state of adaptation to the environment. This fact facilitates significant progress in our general understanding of the genotype-phenotype relationships of animals. The action of the veterinarian in zoos is thus favored. Knowledge of the basic characteristics of animals provides basic behavioral insights and enhances our understanding of the ways in which adaptation can modulate the lives of animals in suitable environments. There are also several and important applications, such as increasing well-being, preventing pathologies and promoting the advancement of scientific knowledge.

Mechanism based therapies enable personalised treatment of hypertrophic cardiomyopathy

Cardiomyopathies have unresolved genotype–phenotype relationships and lack disease-specific treatments. Here we provide a framework to identify genotype-specific pathomechanisms and therapeutic targets to accelerate the development of precision medicine. We use human cardiac electromechanical in-silico modelling and simulation which we validate with experimental hiPSC-CM data and modelling in combination with clinical biomarkers. We select hypertrophic cardiomyopathy as a challenge for this approach and study genetic variations that mutate proteins of the thick (MYH7R403Q/+) and thin filaments (TNNT2R92Q/+, TNNI3R21C/+) of the cardiac sarcomere. Using in-silico techniques we show that the destabilisation of myosin super relaxation observed in hiPSC-CMs drives disease in virtual cells and ventricles carrying the MYH7R403Q/+ variant, and that secondary effects on thin filament activation are necessary to precipitate slowed relaxation of the cell and diastolic insufficiency in the chamber. In-silico modelling shows that Mavacamten corrects the MYH7R403Q/+ phenotype in agreement with hiPSC-CM experiments. Our in-silico model predicts that the thin filament variants TNNT2R92Q/+ and TNNI3R21C/+ display altered calcium regulation as central pathomechanism, for which Mavacamten provides incomplete salvage, which we have corroborated in TNNT2R92Q/+ and TNNI3R21C/+ hiPSC-CMs. We define the ideal characteristics of a novel thin filament-targeting compound and show its efficacy in-silico. We demonstrate that hybrid human-based hiPSC-CM and in-silico studies accelerate pathomechanism discovery and classification testing, improving clinical interpretation of genetic variants, and directing rational therapeutic targeting and design.

Assessing the haplotype and spectro-functional traits interactions to explore the intraspecific diversity of common reed in Central Italy

As reflectance measured via remote sensing is connected to plant light use and morpho-structural features, it can be used to derive spectral proxies of functional traits, or spectro-functional traits. Focusing on disentangling intraspecific trait variability in nature, we evaluated the links between haplotype and spectro-functional traits in Phragmites australis populations. Haplotypes sequencing and multi-seasonal satellite data were used to evaluate the temporal dynamics of spectro-functional traits for reed stands sampled from seven wetlands in Central Italy, investigating meteo-climatic drivers, the differences across ecological statuses, sites, and haplotypes, and quantifying intraspecific variability due to haplotype or phenotypic plasticity. Five haplotypes were identified, including an unedited one, which explained a substantial portion of intraspecific variability in canopy traits, differing for aquatic and terrestrial stands. We found that meteo-climatic factors impact on aquatic reeds traits (not over terrestrial ones) and a dualism between most and less common haplotypes, pointing to different evolutionary strategies. Dynamics in reed canopy traits were linked to ecological status, site and haplotype, with signs of haplotype-variable effects of dieback on aquatic stands. Evaluating the spectro-functional variability over reed haplotypes may provide a straightforward approach for monitoring the genotype–phenotype relations across scales and assessing their ecological drivers.

Natural selection of immune and metabolic genes associated with health in two lowland Bolivian populations

A growing body of work has addressed human adaptations to diverse environments using genomic data, but few studies have connected putatively selected alleles to phenotypes, much less among underrepresented populations such as Amerindians. Studies of natural selection and genotype-phenotype relationships in underrepresented populations hold potential to uncover previously undescribed loci underlying evolutionarily and biomedically relevant traits. Here, we worked with the Tsimane and the Moseten, two Amerindian populations inhabiting the Bolivian lowlands. We focused most intensively on the Tsimane, because long-term anthropological work with this group has shown that they have a high burden of both macro and microparasites, as well as minimal cardiometabolic disease or dementia. We therefore generated genome-wide genotype data for Tsimane individuals to study natural selection, and paired this with blood mRNA-seq as well as cardiometabolic and immune biomarker data generated from a larger sample that included both populations. In the Tsimane, we identified 21 regions that are candidates for selective sweeps, as well as 5 immune traits that show evidence for polygenic selection (e.g., C-reactive proteinlevels and the response to coronaviruses). Genes overlapping candidate regions were strongly enriched for known involvement in immune-related traits, such as abundance of lymphocytes and eosinophils. Importantly, we were also able to draw on extensive phenotype information for the Tsimane and Moseten and link five regions (containing PSD4, MUC21 and MUC22, TOX2, ANXA6, and ABCA1) with biomarkers of immune and metabolic function. Together, our work highlights the utility of pairing evolutionary analyses with anthropological and biomedical data to gain insight into the genetic basis of health-related traits.

Co-expression pan-network reveals genes involved in complex traits within maize pan-genome

BackgroundWith the advances in the high throughput next generation sequencing technologies, genome-wide association studies (GWAS) have identified a large set of variants associated with complex phenotypic traits at a very fine scale. Despite the progress in GWAS, identification of genotype-phenotype relationship remains challenging in maize due to its nature with dozens of variants controlling the same trait. As the causal variations results in the change in expression, gene expression analyses carry a pivotal role in unraveling the transcriptional regulatory mechanisms behind the phenotypes.ResultsTo address these challenges, we incorporated the gene expression and GWAS-driven traits to extend the knowledge of genotype-phenotype relationships and transcriptional regulatory mechanisms behind the phenotypes. We constructed a large collection of gene co-expression networks and identified more than 2 million co-expressing gene pairs in the GWAS-driven pan-network which contains all the gene-pairs in individual genomes of the nested association mapping (NAM) population. We defined four sub-categories for the pan-network: (1) core-network contains the highest represented ~ 1% of the gene-pairs, (2) near-core network contains the next highest represented 1–5% of the gene-pairs, (3) private-network contains ~ 50% of the gene pairs that are unique to individual genomes, and (4) the dispensable-network contains the remaining 50–95% of the gene-pairs in the maize pan-genome. Strikingly, the private-network contained almost all the genes in the pan-network but lacked half of the interactions. We performed gene ontology (GO) enrichment analysis for the pan-, core-, and private- networks and compared the contributions of variants overlapping with genes and promoters to the GWAS-driven pan-network.ConclusionsGene co-expression networks revealed meaningful information about groups of co-regulated genes that play a central role in regulatory processes. Pan-network approach enabled us to visualize the global view of the gene regulatory network for the studied system that could not be well inferred by the core-network alone.

Exome sequencing in 116 patients with inherited thrombocytopenia that remained of unknown origin after systematic phenotype-driven diagnostic workup.

Inherited thrombocytopenias (IT) are genetic diseases characterized by low platelet count, sometimes associated with congenital defects or a predisposition to develop additional conditions. Next-generation sequencing has substantially improved our knowledge of IT, with more than 40 genes identified so far, but obtaining a molecular diagnosis remains a challenge especially for patients with non-syndromic forms, having no clinical or functional phenotypes that raise suspicion about specific genes. We performed exome sequencing (ES) in a cohort of 116 IT patients (89 families), still undiagnosed after a previously validated phenotype-driven diagnostic algorithm including a targeted analysis of suspected genes. ES achieved a diagnostic yield of 36%, with a gain of 16% over the diagnostic algorithm. This can be explained by genetic heterogeneity and unspecific genotype-phenotype relationships that make the simultaneous analysis of all the genes, enabled by ES, the most reasonable strategy. Furthermore, ES disentangled situations that had been puzzling because of atypical inheritance, sex-related effects or false negative laboratory results. Finally, ES-based copy number variant analysis disclosed an unexpectedly high prevalence of RUNX1 deletions, predisposing to hematologic malignancies. Our findings demonstrate that ES, including copy number variant analysis, can substantially contribute to the diagnosis of IT and can solve diagnostic problems that would otherwise remain a challenge.

Cell migration is impaired in XPA-deficient cells.

Xeroderma pigmentosum (XP) is a hereditary disorder characterized by photosensitivity, predisposition to skin cancers, and neurological abnormalities including microcephaly and progressive neurodegeneration. A lack of nucleotide excision repair (NER) in patients with XP can cause hypersensitivity to the sun, leading to skin cancer, whereas the etiology of the neuronal symptoms of XP remains ambiguous. There are various neurological disorders that perturb neuronal migration, causing mislocalization and disorganization of the cortical lamination. Here, we investigated the role of the XP group-A (Xpa) gene in directed cell migration. First, we adopted an in utero electroporation method to transduce shRNA vectors into the murine embryonic cerebral cortex for the in vivo knockdown of Xpa. Xpa-knockdown neurons in the embryonic cerebral cortex showed abnormal cell migration, cell cycle exit, and differentiation. The genotype-phenotype relationship between the lack of XPA and cell migration abnormalities was confirmed using both a scratch assay and time-lapse microscopy in XP-A patient-derived fibroblasts. Unlike healthy cells, these cells showed impairment in overall mobility and the direction of motility. Therefore, abnormal cell migration may explain neural tissue abnormalities in patients with XP-A.