Developmental MYH3 Myopathy Associated with Expression of Mutant Protein and Reduced Expression Levels of Embryonic Myhc
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Targeted Genes and Methodology Details for Neuromuscular Genetic Panels
Targeted Genes and Methodology Details for Neuromuscular Genetic Panels Reference transcripts based on build GRCh37 (hg19) interrogated by Neuromuscular Genetic Panels Next-generation sequencing (NGS) and/or Sanger sequencing is performed Motor Neuron Disease Panel to test for the presence of a mutation in these genes. Gene GenBank Accession Number Regions of homology, high GC-rich content, and repetitive sequences may ALS2 NM_020919 not provide accurate sequence. Therefore, all reported alterations detected ANG NM_001145 by NGS are confirmed by an independent reference method based on laboratory developed criteria. However, this does not rule out the possibility CHMP2B NM_014043 of a false-negative result in these regions. ERBB4 NM_005235 Sanger sequencing is used to confirm alterations detected by NGS when FIG4 NM_014845 appropriate.(Unpublished Mayo method) FUS NM_004960 HNRNPA1 NM_031157 OPTN NM_021980 PFN1 NM_005022 SETX NM_015046 SIGMAR1 NM_005866 SOD1 NM_000454 SQSTM1 NM_003900 TARDBP NM_007375 UBQLN2 NM_013444 VAPB NM_004738 VCP NM_007126 ©2018 Mayo Foundation for Medical Education and Research Page 1 of 14 MC4091-83rev1018 Muscular Dystrophy Panel Muscular Dystrophy Panel Gene GenBank Accession Number Gene GenBank Accession Number ACTA1 NM_001100 LMNA NM_170707 ANO5 NM_213599 LPIN1 NM_145693 B3GALNT2 NM_152490 MATR3 NM_199189 B4GAT1 NM_006876 MYH2 NM_017534 BAG3 NM_004281 MYH7 NM_000257 BIN1 NM_139343 MYOT NM_006790 BVES NM_007073 NEB NM_004543 CAPN3 NM_000070 PLEC NM_000445 CAV3 NM_033337 POMGNT1 NM_017739 CAVIN1 NM_012232 POMGNT2 -
Genequery™ Human Skeletal Muscle Contraction And
GeneQuery™ Human Skeletal Muscle Contraction and Muscular Dystrophies qPCR Array Kit (GQH-SKC) Catalog #GK065 Product Description ScienCell's GeneQuery™ Human Skeletal Muscle Contraction and Muscular Dystrophies qPCR Array (GQH-SKC) profiles 88 key genes involved in the contraction of skeletal muscle. There are three major muscle types in the human body: skeletal, cardiac, and smooth. Skeletal muscle is a striated muscle that relaxes and contracts to generate movement and force in the body. Of the three main muscle types, it is the only one under voluntary control. Neuromuscular diseases involving skeletal muscle dysfunction are very diverse and range from myopathies to muscular dystrophies. Below are brief examples of how included genes may be grouped according to their function in skeletal muscle biology: • Myogenesis: MYOD1, MYOG, PAX3, UTRN, MYF6, MDTN • Contractility: MYH2, SLC2A4, LMNA, DYSF, APT2A1 • Sarcomere Assembly : NEB, TRIM63, TTN, CAPN3, ACTA1 • Muscle Atrophy: NOS2, TRIM63, FOXO1, MAPK8, AKT1 • Muscular Dystrophy Development: POMT2, FKRP, ANO5, FRG1, SGCB Note : all gene names follow their official symbols by the Human Genome Organization Gene Nomenclature Committee (HGNC). GeneQuery™ qPCR array kits are qPCR ready in a 96-well plate format, with each well containing one primer set that can specifically recognize and efficiently amplify a target gene's cDNA. The carefully designed primers ensure that: (i) the optimal annealing temperature in qPCR analysis is 65°C (with 2 mM Mg 2+ , and no DMSO); (ii) the primer set recognizes all known transcript variants of target gene, unless otherwise indicated; and (iii) only one gene is amplified. Each primer set has been validated by qPCR with melt curve analysis, and gel electrophoresis. -
Human Periprostatic Adipose Tissue: Secretome from Patients With
CANCER GENOMICS & PROTEOMICS 16 : 29-58 (2019) doi:10.21873/cgp.20110 Human Periprostatic Adipose Tissue: Secretome from Patients With Prostate Cancer or Benign Prostate Hyperplasia PAULA ALEJANDRA SACCA 1, OSVALDO NÉSTOR MAZZA 2, CARLOS SCORTICATI 2, GONZALO VITAGLIANO 3, GABRIEL CASAS 4 and JUAN CARLOS CALVO 1,5 1Institute of Biology and Experimental Medicine (IBYME), CONICET, Buenos Aires, Argentina; 2Department of Urology, School of Medicine, University of Buenos Aires, Clínical Hospital “José de San Martín”, Buenos Aires, Argentina; 3Department of Urology, Deutsches Hospital, Buenos Aires, Argentina; 4Department of Pathology, Deutsches Hospital, Buenos Aires, Argentina; 5Department of Biological Chemistry, School of Exact and Natural Sciences, University of Buenos Aires, Buenos Aires, Argentina Abstract. Background/Aim: Periprostatic adipose tissue Prostate cancer (PCa) is the second most common cancer in (PPAT) directs tumour behaviour. Microenvironment secretome men worldwide. While most men have indolent disease, provides information related to its biology. This study was which can be treated properly, the problem consists in performed to identify secreted proteins by PPAT, from both reliably distinguishing between indolent and aggressive prostate cancer and benign prostate hyperplasia (BPH) disease. Evidence shows that the microenvironment affects patients. Patients and Methods: Liquid chromatography-mass tumour behavior. spectrometry-based proteomic analysis was performed in Adipose tissue microenvironment is now known to direct PPAT-conditioned media (CM) from patients with prostate tumour growth, invasion and metastases (1, 2). Adipose cancer (CMs-T) (stage T3: CM-T3, stage T2: CM-T2) or tissue is adjacent to the prostate gland and the site of benign disease (CM-BPH). Results: The highest number and invasion of PCa. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Communication Pathways in Human Nonmuscle Myosin-2C 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Authors: 25 Krishna Chinthalapudia,B,C,1, Sarah M
1 Mechanistic Insights into the Active Site and Allosteric 2 Communication Pathways in Human Nonmuscle Myosin-2C 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Authors: 25 Krishna Chinthalapudia,b,c,1, Sarah M. Heisslera,d,1, Matthias Prellera,e, James R. Sellersd,2, and 26 Dietmar J. Mansteina,b,2 27 28 Author Affiliations 29 aInstitute for Biophysical Chemistry, OE4350 Hannover Medical School, 30625 Hannover, 30 Germany. 31 bDivision for Structural Biochemistry, OE8830, Hannover Medical School, 30625 Hannover, 32 Germany. 33 cCell Adhesion Laboratory, Department of Integrative Structural and Computational Biology, The 34 Scripps Research Institute, Jupiter, Florida 33458, USA. 35 dLaboratory of Molecular Physiology, NHLBI, National Institutes of Health, Bethesda, Maryland 36 20892, USA. 37 eCentre for Structural Systems Biology (CSSB), German Electron Synchrotron (DESY), 22607 38 Hamburg, Germany. 39 1K.C. and S.M.H. contributed equally to this work 40 2To whom correspondence may be addressed: E-mail: [email protected] or 41 [email protected] 42 43 1 44 Abstract 45 Despite a generic, highly conserved motor domain, ATP turnover kinetics and their activation by 46 F-actin vary greatly between myosin-2 isoforms. Here, we present a 2.25 Å crystal pre- 47 powerstroke state (ADPVO4) structure of the human nonmuscle myosin-2C motor domain, one 48 of the slowest myosins characterized. In combination with integrated mutagenesis, ensemble- 49 solution kinetics, and molecular dynamics simulation approaches, the structure reveals an 50 allosteric communication pathway that connects the distal end of the motor domain with the 51 active site. -
Microrna Regulatory Pathways in the Control of the Actin–Myosin Cytoskeleton
cells Review MicroRNA Regulatory Pathways in the Control of the Actin–Myosin Cytoskeleton , , Karen Uray * y , Evelin Major and Beata Lontay * y Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary; [email protected] * Correspondence: [email protected] (K.U.); [email protected] (B.L.); Tel.: +36-52-412345 (K.U. & B.L.) The authors contributed equally to the manuscript. y Received: 11 June 2020; Accepted: 7 July 2020; Published: 9 July 2020 Abstract: MicroRNAs (miRNAs) are key modulators of post-transcriptional gene regulation in a plethora of processes, including actin–myosin cytoskeleton dynamics. Recent evidence points to the widespread effects of miRNAs on actin–myosin cytoskeleton dynamics, either directly on the expression of actin and myosin genes or indirectly on the diverse signaling cascades modulating cytoskeletal arrangement. Furthermore, studies from various human models indicate that miRNAs contribute to the development of various human disorders. The potentially huge impact of miRNA-based mechanisms on cytoskeletal elements is just starting to be recognized. In this review, we summarize recent knowledge about the importance of microRNA modulation of the actin–myosin cytoskeleton affecting physiological processes, including cardiovascular function, hematopoiesis, podocyte physiology, and osteogenesis. Keywords: miRNA; actin; myosin; actin–myosin complex; Rho kinase; cancer; smooth muscle; hematopoiesis; stress fiber; gene expression; cardiovascular system; striated muscle; muscle cell differentiation; therapy 1. Introduction Actin–myosin interactions are the primary source of force generation in mammalian cells. Actin forms a cytoskeletal network and the myosin motor proteins pull actin filaments to produce contractile force. All eukaryotic cells contain an actin–myosin network inferring contractile properties to these cells. -
Cldn19 Clic2 Clmp Cln3
NewbornDx™ Advanced Sequencing Evaluation When time to diagnosis matters, the NewbornDx™ Advanced Sequencing Evaluation from Athena Diagnostics delivers rapid, 5- to 7-day results on a targeted 1,722-genes. A2ML1 ALAD ATM CAV1 CLDN19 CTNS DOCK7 ETFB FOXC2 GLUL HOXC13 JAK3 AAAS ALAS2 ATP1A2 CBL CLIC2 CTRC DOCK8 ETFDH FOXE1 GLYCTK HOXD13 JUP AARS2 ALDH18A1 ATP1A3 CBS CLMP CTSA DOK7 ETHE1 FOXE3 GM2A HPD KANK1 AASS ALDH1A2 ATP2B3 CC2D2A CLN3 CTSD DOLK EVC FOXF1 GMPPA HPGD K ANSL1 ABAT ALDH3A2 ATP5A1 CCDC103 CLN5 CTSK DPAGT1 EVC2 FOXG1 GMPPB HPRT1 KAT6B ABCA12 ALDH4A1 ATP5E CCDC114 CLN6 CUBN DPM1 EXOC4 FOXH1 GNA11 HPSE2 KCNA2 ABCA3 ALDH5A1 ATP6AP2 CCDC151 CLN8 CUL4B DPM2 EXOSC3 FOXI1 GNAI3 HRAS KCNB1 ABCA4 ALDH7A1 ATP6V0A2 CCDC22 CLP1 CUL7 DPM3 EXPH5 FOXL2 GNAO1 HSD17B10 KCND2 ABCB11 ALDOA ATP6V1B1 CCDC39 CLPB CXCR4 DPP6 EYA1 FOXP1 GNAS HSD17B4 KCNE1 ABCB4 ALDOB ATP7A CCDC40 CLPP CYB5R3 DPYD EZH2 FOXP2 GNE HSD3B2 KCNE2 ABCB6 ALG1 ATP8A2 CCDC65 CNNM2 CYC1 DPYS F10 FOXP3 GNMT HSD3B7 KCNH2 ABCB7 ALG11 ATP8B1 CCDC78 CNTN1 CYP11B1 DRC1 F11 FOXRED1 GNPAT HSPD1 KCNH5 ABCC2 ALG12 ATPAF2 CCDC8 CNTNAP1 CYP11B2 DSC2 F13A1 FRAS1 GNPTAB HSPG2 KCNJ10 ABCC8 ALG13 ATR CCDC88C CNTNAP2 CYP17A1 DSG1 F13B FREM1 GNPTG HUWE1 KCNJ11 ABCC9 ALG14 ATRX CCND2 COA5 CYP1B1 DSP F2 FREM2 GNS HYDIN KCNJ13 ABCD3 ALG2 AUH CCNO COG1 CYP24A1 DST F5 FRMD7 GORAB HYLS1 KCNJ2 ABCD4 ALG3 B3GALNT2 CCS COG4 CYP26C1 DSTYK F7 FTCD GP1BA IBA57 KCNJ5 ABHD5 ALG6 B3GAT3 CCT5 COG5 CYP27A1 DTNA F8 FTO GP1BB ICK KCNJ8 ACAD8 ALG8 B3GLCT CD151 COG6 CYP27B1 DUOX2 F9 FUCA1 GP6 ICOS KCNK3 ACAD9 ALG9 -
A Curated Gene List for Reporting Results of Newborn Genomic Sequencing
© American College of Medical Genetics and Genomics ORIGINAL RESEARCH ARTICLE A curated gene list for reporting results of newborn genomic sequencing Ozge Ceyhan-Birsoy, PhD1,2,3, Kalotina Machini, PhD1,2,3, Matthew S. Lebo, PhD1,2,3, Tim W. Yu, MD3,4,5, Pankaj B. Agrawal, MD, MMSC3,4,6, Richard B. Parad, MD, MPH3,7, Ingrid A. Holm, MD, MPH3,4, Amy McGuire, PhD8, Robert C. Green, MD, MPH3,9,10, Alan H. Beggs, PhD3,4, Heidi L. Rehm, PhD1,2,3,10; for the BabySeq Project Purpose: Genomic sequencing (GS) for newborns may enable detec- of newborn GS (nGS), and used our curated list for the first 15 new- tion of conditions for which early knowledge can improve health out- borns sequenced in this project. comes. One of the major challenges hindering its broader application Results: Here, we present our curated list for 1,514 gene–disease is the time it takes to assess the clinical relevance of detected variants associations. Overall, 954 genes met our criteria for return in nGS. and the genes they impact so that disease risk is reported appropri- This reference list eliminated manual assessment for 41% of rare vari- ately. ants identified in 15 newborns. Methods: To facilitate rapid interpretation of GS results in new- Conclusion: Our list provides a resource that can assist in guiding borns, we curated a catalog of genes with putative pediatric relevance the interpretive scope of clinical GS for newborns and potentially for their validity based on the ClinGen clinical validity classification other populations. framework criteria, age of onset, penetrance, and mode of inheri- tance through systematic evaluation of published evidence. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Rashid Thesis 2015
Protein Profile and Directed Gene Expression of Developing C2C12 cells By Susan Rashid Submitted in Partial Fulfillment of the Requirements For the Degree of Master of Science In the Biological Sciences Program YOUNGSTOWN STATE UNIVERSITY August 3, 2015 Protein Profile and Directed Gene Expression of Developing C2C12 cells Susan Rashid I hereby release this thesis to the public. I understand that this will be made available from the OhioLINK ETD Center and the Maag Library Circulation Desk for public access. I also authorize the University or other individuals to make copies of this thesis as needed for scholarly research. Signature: ___________________________________________________ Susan Rashid, Student Date Approvals: ___________________________________________________ Dr. Gary Walker, Thesis Advisor 'ate ___________________________________________________ Dr. Jonathan Caguiat, Committee Member Date ___________________________________________________ Dr. David Asch, Committee Member Date ___________________________________________________ Dr. Sal Sanders, Associate Dean, Graduate Studies Date ABSTRACT Myogenesis is a tightly regulated process resulting in unique structures called myotubes or myofibers, which compose skeletal muscle. Myotubes are multi-nucleated fibers containing a functional unit composed of cytoskeletal proteins called the sarcomere. The specific arrangement of these proteins in the sarcomere works to contract and relax muscles. During embryonic and post-embryonic development, fluctuations in expression of growth factors throughout the program account for the dramatic structural changes from cell to mature muscle fiber. In vivo, these growth factors are strictly spatiotemporally regulated according to a ‘myogenic program.’ In order to assess the dynamics of protein expression throughout this program, we conducted a time course study using the mouse myoblast cell line C2C12, in which cells were allowed to differentiate and insoluble protein fractions were collected at seven time points. -
Distinct Fiber Type Signature in Mouse Muscles Expressing a Mutant Lamin a Responsible for Congenital Muscular Dystrophy in a Patient
cells Article Distinct Fiber Type Signature in Mouse Muscles Expressing a Mutant Lamin A Responsible for Congenital Muscular Dystrophy in a Patient Alice Barateau 1,*, Nathalie Vadrot 1, Onnik Agbulut 2, Patrick Vicart 1, Sabrina Batonnet-Pichon 1 and Brigitte Buendia 1 1 Unité de Biologie Fonctionnelle et Adaptative (BFA), CNRS UMR 8251, Université Paris Diderot, Sorbonne Paris Cité, 75013 Paris, France; [email protected] (N.V.); [email protected] (P.V.); [email protected] (S.B.-P.); [email protected] (B.B.) 2 Biological Adaptation and Ageing, UMR CNRS 8256, Institut de Biologie Paris-Seine (IBPS), UPMC Univ Paris 06, Sorbonne Universités, 75005 Paris, France; [email protected] * Correspondence: [email protected]; Tel.: +33-157-277-958 Academic Editor: Thomas Dechat Received: 9 January 2017; Accepted: 20 April 2017; Published: 24 April 2017 Abstract: Specific mutations in LMNA, which encodes nuclear intermediate filament proteins lamins A/C, affect skeletal muscle tissues. Early-onset LMNA myopathies reveal different alterations of muscle fibers, including fiber type disproportion or prominent dystrophic and/or inflammatory changes. Recently, we identified the p.R388P LMNA mutation as responsible for congenital muscular dystrophy (L-CMD) and lipodystrophy. Here, we asked whether viral-mediated expression of mutant lamin A in murine skeletal muscles would be a pertinent model to reveal specific muscle alterations. We found that the total amount and size of muscle fibers as well as the extent of either inflammation or muscle regeneration were similar to wildtype or mutant lamin A. -
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Expanding genotype/phenotype of neuromuscular diseases by comprehensive target capture/NGS Xia Tian, PhD* ABSTRACT * Wen-Chen Liang, MD Objective: To establish and evaluate the effectiveness of a comprehensive next-generation * Yanming Feng, PhD sequencing (NGS) approach to simultaneously analyze all genes known to be responsible for Jing Wang, MD the most clinically and genetically heterogeneous neuromuscular diseases (NMDs) involving spi- Victor Wei Zhang, PhD nal motoneurons, neuromuscular junctions, nerves, and muscles. Chih-Hung Chou, MS Methods: All coding exons and at least 20 bp of flanking intronic sequences of 236 genes causing Hsien-Da Huang, PhD NMDs were enriched by using SeqCap EZ solution-based capture and enrichment method fol- Ching Wan Lam, PhD lowed by massively parallel sequencing on Illumina HiSeq2000. Ya-Yun Hsu, PhD ; 3 Thy-Sheng Lin, MD Results: The target gene capture/deep sequencing provides an average coverage of 1,000 per Wan-Tzu Chen, MS nucleotide. Thirty-five unrelated NMD families (38 patients) with clinical and/or muscle pathologic Lee-Jun Wong, PhD diagnoses but without identified causative genetic defects were analyzed. Deleterious mutations Yuh-Jyh Jong, MD were found in 29 families (83%). Definitive causative mutations were identified in 21 families (60%) and likely diagnoses were established in 8 families (23%). Six families were left without diagnosis due to uncertainty in phenotype/genotype correlation and/or unidentified causative Correspondence to genes. Using this comprehensive panel, we not only identified mutations in expected genes but Dr. Wong: also expanded phenotype/genotype among different subcategories of NMDs. [email protected] or Dr. Jong: Conclusions: Target gene capture/deep sequencing approach can greatly improve the genetic [email protected] diagnosis of NMDs.