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      SRSF1 haploinsufficiency is responsible for a syndromic developmental disorder associated with intellectual disability

      research-article
      1 , 2 , 46 , 3 , 4 , 46 , 5 , 46 , 6 , 7 , 46 , 3 , 8 , 1 , 2 , 1 , 2 , 3 , 8 , 9 , 10 , 11 , 10 , 11 , 10 , 11 , 12 , 13 , 14 , 15 , 15 , 16 , 17 , 18 , 17 , 3 , 19 , 3 , 19 , 7 , 7 , 6 , 7 , 7 , 20 , 20 , 21 , 22 , 21 , 22 , 23 , 23 , 23 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 31 , 32 , 32 , 32 , 32 , 33 , 34 , 35 , 36 , 32 , 37 , 38 , 38 , 39 , 39 , 40 , 39 , 41 , 42 , 42 , 42 , 43 , 42 , 31 , 32 , 34 , 44 , 3 , 8 , 3 , 8 , 45 , 3 , 4 , 6 , 7 , 46 , 5 , 46 , 1 , 2 , 46 , , 3 , 8 , 46 , ∗∗
      American Journal of Human Genetics
      Elsevier
      SRSF1, splicing, neurodevelopmental disorder, haploinsufficiency, Drosophila, epigenetic signature

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          Summary

          SRSF1 (also known as ASF/SF2) is a non-small nuclear ribonucleoprotein (non-snRNP) that belongs to the arginine/serine (R/S) domain family. It recognizes and binds to mRNA, regulating both constitutive and alternative splicing. The complete loss of this proto-oncogene in mice is embryonically lethal. Through international data sharing, we identified 17 individuals (10 females and 7 males) with a neurodevelopmental disorder (NDD) with heterozygous germline SRSF1 variants, mostly de novo, including three frameshift variants, three nonsense variants, seven missense variants, and two microdeletions within region 17q22 encompassing SRSF1. Only in one family, the de novo origin could not be established. All individuals featured a recurrent phenotype including developmental delay and intellectual disability (DD/ID), hypotonia, neurobehavioral problems, with variable skeletal (66.7%) and cardiac (46%) anomalies. To investigate the functional consequences of SRSF1 variants, we performed in silico structural modeling, developed an in vivo splicing assay in Drosophila, and carried out episignature analysis in blood-derived DNA from affected individuals. We found that all loss-of-function and 5 out of 7 missense variants were pathogenic, leading to a loss of SRSF1 splicing activity in Drosophila, correlating with a detectable and specific DNA methylation episignature. In addition, our orthogonal in silico, in vivo, and epigenetics analyses enabled the separation of clearly pathogenic missense variants from those with uncertain significance. Overall, these results indicated that haploinsufficiency of SRSF1 is responsible for a syndromic NDD with ID due to a partial loss of SRSF1-mediated splicing activity.

          Abstract

          Thanks to a large international data-sharing effort, in silico structural protein modeling, DNA methylation episignature analyses, and in vivo splicing assays in Drosophila, Bogaert et al. demonstrate that haploinsufficiency of SRSF1, which encodes a pre-mRNA splicing factor, causes a syndromic neurodevelopmental disorder with mild to moderate intellectual disability.

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          Most cited references67

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          limma powers differential expression analyses for RNA-sequencing and microarray studies

          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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            circlize Implements and enhances circular visualization in R.

            Circular layout is an efficient way for the visualization of huge amounts of genomic information. Here we present the circlize package, which provides an implementation of circular layout generation in R as well as an enhancement of available software. The flexibility of this package is based on the usage of low-level graphics functions such that self-defined high-level graphics can be easily implemented by users for specific purposes. Together with the seamless connection between the powerful computational and visual environment in R, circlize gives users more convenience and freedom to design figures for better understanding genomic patterns behind multi-dimensional data.
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              Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.

              The recently released Infinium HumanMethylation450 array (the '450k' array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years. Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods. http://bioconductor.org/packages/release/bioc/html/minfi.html. khansen@jhsph.edu; rafa@jimmy.harvard.edu Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Journal
                Am J Hum Genet
                Am J Hum Genet
                American Journal of Human Genetics
                Elsevier
                0002-9297
                1537-6605
                17 April 2023
                04 May 2023
                17 April 2023
                : 110
                : 5
                : 790-808
                Affiliations
                [1 ]Center for Medical Genetics, Ghent University Hospital, 9000 Ghent, Belgium
                [2 ]Department of Biomolecular Medicine, Faculty of Medicine and Health Sciences, Ghent University, 9000 Ghent, Belgium
                [3 ]UMR1231 GAD, Inserm - Université de Bourgogne, Dijon, France
                [4 ]Centre de Référence Maladies Rares "Anomalies du Développement et Syndromes Malformatifs", Centre de Génétique, FHU-TRANSLAD, CHU Dijon Bourgogne, 21000 Dijon, France
                [5 ]University Grenoble Alpes, Inserm U1209, CNRS UMR 5309, Institute for Advanced Biosciences (IAB), 38000 Grenoble, France
                [6 ]Department of Pathology and Laboratory Medicine, Western University, London, ON N5A 3K7, Canada
                [7 ]Verspeeten Clinical Genome Centre, London Health Science Centre, London, ON N6A 5W9, Canada
                [8 ]Unité Fonctionnelle Innovation en Diagnostic génomique des maladies rares, FHU-TRANSLAD, CHU Dijon Bourgogne, 21000 Dijon, France
                [9 ]GeneDx, Gaithersburg, MD, USA
                [10 ]Division of Medical Genetics, Department of Pediatrics, McGovern Medical School at the University of Texas Health Science Center at Houston (UTHealth Houston), Houston, TX, USA
                [11 ]Children’s Memorial Hermann Hospital, Houston, TX, USA
                [12 ]Unité de Génétique Chromosomique, CHU Montpellier, Montpellier, France
                [13 ]Montpellier University, Inserm U1183, Montpellier, France
                [14 ]Reference center for rare disease developmental anomaly malformative syndrome, Department of Medical Genetics, Montpellier Hospital, Montpellier, France
                [15 ]Greenwood Genetic Center, Greenwood, SC, USA
                [16 ]Department of Paediatrics, Odense University Hospital, Odense, Denmark
                [17 ]Department of Clinical Genetics, Odense University Hospital, 5000 Odense, Denmark
                [18 ]Human Genetics, Department of Clinical Research, Health Faculty, University of Southern Denmark, 5000 Odense, Denmark
                [19 ]Laboratoire de Génétique Chromosomique et Moléculaire, Pôle de Biologie, CHU de Dijon, Dijon, France
                [20 ]Translational Cytogenomics Research Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
                [21 ]Telethon Institute of Genetics and Medicine, Pozzuoli, Italy
                [22 ]Department of Translational Medicine, University of Naples Federico II, Naples, Italy
                [23 ]Medical Genetics Department, CHU Bordeaux, Bordeaux, France
                [24 ]INSERM U1211, Laboratoire MRGM, Bordeaux University, Bordeaux, France
                [25 ]Pathology Department, CHU Bordeaux, Bordeaux, France
                [26 ]Service de génétique, CHU de Reims, Reims, France
                [27 ]Service de génétique médicale, CHU de Nantes, Nantes, France
                [28 ]L’institut du thorax, INSERM, CNRS, UNIV Nantes, CHU de Nantes, Nantes, France
                [29 ]Broad Center for Mendelian Genomics, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
                [30 ]Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, VIC, Australia
                [31 ]Department of Pediatrics, Baylor College of Medicine, San Antonio, TX, USA
                [32 ]Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
                [33 ]Section of Pediatric Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
                [34 ]Texas Children’s Hospital, Houston, TX, USA
                [35 ]Internal Medicine A, Danek Gertner Institute of Human Genetics, Sheba Medical Center, Ramat Gan, Israel
                [36 ]Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
                [37 ]Baylor Genetics Laboratories, Houston, TX, USA
                [38 ]Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
                [39 ]UO Genetica Medica, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
                [40 ]Neonatal Intensive Care Unit, Maggiore Hospital, Bologna, Italy
                [41 ]Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
                [42 ]Université Paris Cité, Imagine Institute, INSERM UMR1163, Paris 75015, France
                [43 ]Department of Neurology, Ghent University Hospital, 9000 Ghent, Belgium
                [44 ]Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
                [45 ]Centre de Référence Maladies Rares « Déficiences intellectuelles de causes rares », Centre de Génétique, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
                Author notes
                []Corresponding author bart.dermaut@ 123456ugent.be
                [∗∗ ]Corresponding author antonio.vitobello@ 123456u-bourgogne.fr
                [46]

                These authors contributed equally

                Article
                S0002-9297(23)00100-3
                10.1016/j.ajhg.2023.03.016
                10183470
                37071997
                2ead0a83-f7f7-46dd-9843-9ea1a24afe22
                © 2023 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 14 December 2022
                : 23 March 2023
                Categories
                Article

                Genetics
                srsf1,splicing,neurodevelopmental disorder,haploinsufficiency,drosophila,epigenetic signature
                Genetics
                srsf1, splicing, neurodevelopmental disorder, haploinsufficiency, drosophila, epigenetic signature

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