25 research outputs found

    Identification of a RAI1-associated disease network through integration of exome sequencing, transcriptomics, and 3D genomics.

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    Smith-Magenis syndrome (SMS) is a developmental disability/multiple congenital anomaly disorder resulting from haploinsufficiency of RAI1. It is characterized by distinctive facial features, brachydactyly, sleep disturbances, and stereotypic behaviors. We investigated a cohort of 15 individuals with a clinical suspicion of SMS who showed neither deletion in the SMS critical region nor damaging variants in RAI1 using whole exome sequencing. A combination of network analysis (co-expression and biomedical text mining), transcriptomics, and circularized chromatin conformation capture (4C-seq) was applied to verify whether modified genes are part of the same disease network as known SMS-causing genes. Potentially deleterious variants were identified in nine of these individuals using whole-exome sequencing. Eight of these changes affect KMT2D, ZEB2, MAP2K2, GLDC, CASK, MECP2, KDM5C, and POGZ, known to be associated with Kabuki syndrome 1, Mowat-Wilson syndrome, cardiofaciocutaneous syndrome, glycine encephalopathy, mental retardation and microcephaly with pontine and cerebellar hypoplasia, X-linked mental retardation 13, X-linked mental retardation Claes-Jensen type, and White-Sutton syndrome, respectively. The ninth individual carries a de novo variant in JAKMIP1, a regulator of neuronal translation that was recently found deleted in a patient with autism spectrum disorder. Analyses of co-expression and biomedical text mining suggest that these pathologies and SMS are part of the same disease network. Further support for this hypothesis was obtained from transcriptome profiling that showed that the expression levels of both Zeb2 and Map2k2 are perturbed in Rai1 (-/-) mice. As an orthogonal approach to potentially contributory disease gene variants, we used chromatin conformation capture to reveal chromatin contacts between RAI1 and the loci flanking ZEB2 and GLDC, as well as between RAI1 and human orthologs of the genes that show perturbed expression in our Rai1 (-/-) mouse model. These holistic studies of RAI1 and its interactions allow insights into SMS and other disorders associated with intellectual disability and behavioral abnormalities. Our findings support a pan-genomic approach to the molecular diagnosis of a distinctive disorder

    The Drosophila melanogaster Genetic Reference Panel

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    A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics

    Unraveling genetic predisposition to familial or early onset gastric cancer using germline whole-exome sequencing

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    Recognition of individuals with a genetic predisposition to gastric cancer (GC) enables preventive measures. However, the underlying cause of genetic susceptibility to gastric cancer remains largely unexplained. We performed germline whole-exome sequencing on leukocyte DNA of 54 patients from 53 families with genetically unexplained diffuse-type and intestinal-type GC to identify novel GC-predisposing candidate genes. As young age at diagnosis and familial clustering are hallmarks of genetic tumor susceptibility, we selected patients that were diagnosed below the age of 35, patients from families with two cases of GC at or below age 60 and patients from families with three GC cases at or below age 70. All included individuals were tested negative for germline CDH1 mutations before or during the study. Variants that were possibly deleterious according to in silico predictions were filtered using several independent approaches that were based on gene function and gene mutation burden in controls. Despite a rigorous search, no obvious candidate GC predisposition genes were identified. This negative result stresses the importance of future research studies in large, homogeneous cohorts

    Biallelic variants in KIF14 cause intellectual disability with microcephaly.

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    Kinesin proteins are critical for various cellular functions such as intracellular transport and cell division, and many members of the family have been linked to monogenic disorders and cancer. We report eight individuals with intellectual disability and microcephaly from four unrelated families with parental consanguinity. In the affected individuals of each family, homozygosity for likely pathogenic variants in KIF14 were detected; two loss-of-function (p.Asn83Ilefs*3 and p.Ser1478fs), and two missense substitutions (p.Ser841Phe and p.Gly459Arg). KIF14 is a mitotic motor protein that is required for spindle localization of the mitotic citron rho-interacting kinase, CIT, also mutated in microcephaly. Our results demonstrate the involvement of KIF14 in development and reveal a wide phenotypic variability ranging from fetal lethality to moderate developmental delay and microcephaly

    Paralog Studies Augment Gene Discovery: DDX and DHX Genes

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    PubMedID: 31256877Members of a paralogous gene family in which variation in one gene is known to cause disease are eight times more likely to also be associated with human disease. Recent studies have elucidated DHX30 and DDX3X as genes for which pathogenic variant alleles are involved in neurodevelopmental disorders. We hypothesized that variants in paralogous genes encoding members of the DExD/H-box RNA helicase superfamily might also underlie developmental delay and/or intellectual disability (DD and/or ID) disease phenotypes. Here we describe 15 unrelated individuals who have DD and/or ID, central nervous system (CNS) dysfunction, vertebral anomalies, and dysmorphic features and were found to have probably damaging variants in DExD/H-box RNA helicase genes. In addition, these individuals exhibit a variety of other tissue and organ system involvement including ocular, outer ear, hearing, cardiac, and kidney tissues. Five individuals with homozygous (one), compound-heterozygous (two), or de novo (two) missense variants in DHX37 were identified by exome sequencing. We identified ten total individuals with missense variants in three other DDX/DHX paralogs: DHX16 (four individuals), DDX54 (three individuals), and DHX34 (three individuals). Most identified variants are rare, predicted to be damaging, and occur at conserved amino acid residues. Taken together, these 15 individuals implicate the DExD/H-box helicases in both dominantly and recessively inherited neurodevelopmental phenotypes and highlight the potential for more than one disease mechanism underlying these disorders. © 2019 American Society of Human GeneticsNational Heart, Lung, and Blood Institute Aicardi Syndrome Foundation: 2T32NS043124-16 National Institute on Drug Abuse National Institute of Diabetes and Digestive and Kidney Diseases: K12 DK083014 National Heart, Lung, and Blood Institute Fondazione Telethon National Institute of Neurological Disorders and Stroke: U54-HG003273 GSP15001 Deutsche Forschungsgemeinschaft California Department of Fish and Game: LE 4223/1 National Human Genome Research Institute National Institutes of Health: K08 HG008986, DK088767 National Cancer Institute R01 NS058529, R35 NS105078 National Institute of Mental Health National Institute of Neurological Disorders and StrokeThis work was supported in part by grants UM1 HG006542 (J.R.L) and UM1 HG006493 (M.B.) from the National Human Genome Research Institute (NHGRI) and the National Heart, Lung, and Blood Institute (NHLBI) to the Baylor Hopkins Center for Mendelian Genomics and the University of Washington Center for Mendelian Genomics, R01 NS058529 and R35 NS105078 (J.R.L.) from the National Institute of Neurological Disorders and Stroke (NINDS), U54-HG003273 (R.A.G.) from NHGRI , and Telethon Undiagnosed Diseases Program (TUDP) GSP15001 (N.B.-P.) from the Telethon Foundation , and also by the Aicardi Syndrome Foundation. I.P. was supported by 2T32NS043124-16 through the National Institutes of Health . J.E.P. was supported by NHGRI K08 HG008986 . F.H. was supported by the National Institutes of Health ( DK088767 ). M.R.B. was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) K12 DK083014 . D.L was supported by the Werner Otto Stiftung and the German Research Foundation ( DFG; LE 4223/1 ). The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health , and by the National Cancer Institute , NHGRI , NHLBI , the National Institute on Drug Abuse , the National Institute of Mental Health , and NINDS . The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 10/29/18. The authors would like to thank Hans-Jurgen Kreienkamp for the help in identifying helicase core motifs and the Genome Aggregation Database (gnomAD) and the groups that provided exome and genome variant data to this resource. A full list of contributing groups can be found at https://gnomad.broadinstitute.org/about

    Phenotypic expansion illuminates multilocus pathogenic variation

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    PubMedID: 29790871Purpose: Multilocus variation—pathogenic variants in two or more disease genes—can potentially explain the underlying genetic basis for apparent phenotypic expansion in cases for which the observed clinical features extend beyond those reported in association with a “known” disease gene. Methods: Analyses focused on 106 patients, 19 for whom apparent phenotypic expansion was previously attributed to variation at known disease genes. We performed a retrospective computational reanalysis of whole-exome sequencing data using stringent Variant Call File filtering criteria to determine whether molecular diagnoses involving additional disease loci might explain the observed expanded phenotypes. Results: Multilocus variation was identified in 31.6% (6/19) of families with phenotypic expansion and 2.3% (2/87) without phenotypic expansion. Intrafamilial clinical variability within two families was explained by multilocus variation identified in the more severely affected sibling. Conclusion: Our findings underscore the role of multiple rare variants at different loci in the etiology of genetically and clinically heterogeneous cohorts. Intrafamilial phenotypic and genotypic variability allowed a dissection of genotype–phenotype relationships in two families. Our data emphasize the critical role of the clinician in diagnostic genomic analyses and demonstrate that apparent phenotypic expansion may represent blended phenotypes resulting from pathogenic variation at more than one locus. © 2018, American College of Medical Genetics and Genomics.National Heart, Lung, and Blood Institute National Human Genome Research Institute: UM1 HG006542 R01 NS058529, R35 NS105078 K08 HG008986 National Institute of Neurological Disorders and Stroke: U54-HG003273J.E.P. was supported by a Chao Physician-Scientist Award through the Ting Tsung and Wei Fong Chao Foundation and K08 HG008986 through the National Human Genome Research Institute. This work was supported in part by grants UM1 HG006542 (J.R.L.) from the National Human Genome Research Institute/National Heart, Lung, and Blood Institute to the Baylor Hopkins Center for Mendelian Genomics, R01 NS058529 and R35 NS105078 (J.R.L.) from the National Institute of Neurological Disorders and Stroke, and U54-HG003273 (R.A.G.) from the National Human Genome Research Institute

    Biallelic loss-of-function variants in the splicing regulator NSRP1 cause a severe neurodevelopmental disorder with spastic cerebral palsy and epilepsy

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    Purpose: Alternative splicing plays a critical role in mouse neurodevelopment, regulating neurogenesis, cortical lamination, and synaptogenesis, yet few human neurodevelopmental disorders are known to result from pathogenic variation in splicing regulator genes. Nuclear Speckle Splicing Regulator Protein 1 (NSRP1) is a ubiquitously expressed splicing regulator not known to underlie a Mendelian disorder. Methods: Exome sequencing and rare variant family-based genomics was performed as a part of the Baylor-Hopkins Center for Mendelian Genomics Initiative. Additional families were identified via GeneMatcher. Results: We identified six patients from three unrelated families with homozygous loss-of-function variants in NSRP1. Clinical features include developmental delay, epilepsy, variable microcephaly (Z-scores �0.95 to �5.60), hypotonia, and spastic cerebral palsy. Brain abnormalities included simplified gyral pattern, underopercularization, and/or vermian hypoplasia. Molecular analysis identified three pathogenic NSRP1 predicted loss-of-function variant alleles: c.13591362delAAAG (p.Glu455AlafsTer20), c.1272dupG (p.Lys425GlufsTer5), and c.52C>T (p.Gln18Ter). The two frameshift variants result in a premature termination codon in the last exon, and the mutant transcripts are predicted to escape nonsense mediated decay and cause loss of a C-terminal nuclear localization signal required for NSRP1 function. Conclusion: We establish NSRP1 as a gene for a severe autosomal recessive neurodevelopmental disease trait characterized by developmental delay, epilepsy, microcephaly, and spastic cerebral palsy. © 2021, The Author(s), under exclusive licence to the American College of Medical Genetics and Genomics
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