Recurrent Copy Number Variations As Risk Factors for Autism Spectrum Disorders: Analysis of the Clinical Implications
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Resolving Transcriptional States and Predicting Lineages in the Annelid Capitella Teleta Using 1 Single-Cell Rnaseq 2 3 Abhinav
bioRxiv preprint doi: https://doi.org/10.1101/2020.10.16.342709; this version posted October 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Resolving transcriptional states and predicting lineages in the annelid Capitella teleta using 2 single-cell RNAseq 3 4 Abhinav Sur1 and Néva P. Meyer2* 5 6 1Unit on Cell Specification and Differentiation, National Institute of Child Health and Human 7 Development (NICHD), Bethesda, Maryland, USA, 20814 8 9 2Department of Biology, Clark University, 950 Main Street, Worcester, Massachusetts, USA, 10 01610. 11 12 13 [email protected] 14 [email protected] 15 16 *Corresponding author 17 18 19 20 21 Keywords: neurogenesis, single-cell RNAseq, annelid, cell type, differentiation trajectory, 22 pseudotime, RNA velocity, gene regulatory network. 23 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.16.342709; this version posted October 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 24 Abstract 25 Evolution and diversification of cell types has contributed to animal evolution. However, gene 26 regulatory mechanisms underlying cell fate acquisition during development remains largely 27 uncharacterized in spiralians. Here we use a whole-organism, single-cell transcriptomic approach 28 to map larval cell types in the annelid Capitella teleta at 24- and 48-hours post gastrulation 29 (stages 4 and 5). -
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International Journal of Molecular Sciences Article Phenotypic Subtyping and Re-Analysis of Existing Methylation Data from Autistic Probands in Simplex Families Reveal ASD Subtype-Associated Differentially Methylated Genes and Biological Functions Elizabeth C. Lee y and Valerie W. Hu * Department of Biochemistry and Molecular Medicine, The George Washington University, School of Medicine and Health Sciences, Washington, DC 20037, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-202-994-8431 Current address: W. Harry Feinstone Department of Molecular Microbiology and Immunology, y Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA. Received: 25 August 2020; Accepted: 17 September 2020; Published: 19 September 2020 Abstract: Autism spectrum disorder (ASD) describes a group of neurodevelopmental disorders with core deficits in social communication and manifestation of restricted, repetitive, and stereotyped behaviors. Despite the core symptomatology, ASD is extremely heterogeneous with respect to the severity of symptoms and behaviors. This heterogeneity presents an inherent challenge to all large-scale genome-wide omics analyses. In the present study, we address this heterogeneity by stratifying ASD probands from simplex families according to the severity of behavioral scores on the Autism Diagnostic Interview-Revised diagnostic instrument, followed by re-analysis of existing DNA methylation data from individuals in three ASD subphenotypes in comparison to that of their respective unaffected siblings. We demonstrate that subphenotyping of cases enables the identification of over 1.6 times the number of statistically significant differentially methylated regions (DMR) and DMR-associated genes (DAGs) between cases and controls, compared to that identified when all cases are combined. Our analyses also reveal ASD-related neurological functions and comorbidities that are enriched among DAGs in each phenotypic subgroup but not in the combined case group. -
SS18 (SYT) (18Q11) Gene Rearrangement by FISH Indications for Ordering Genetics
SS18 (SYT) (18q11) Gene Rearrangement by FISH Indications for Ordering Genetics Diagnosis of synovial sarcoma in conjunction with histologic Translocations – SS18-SSX1, SS18-SSX2 and clinical information Structure/function Test Description • SS18 is located on chromosome 18 • SSX1 and SSX2 are located on the X-chromosome Fluorescence in situ hybridization • Each gene in the translocation codes for proteins that have opposite transcriptional functions Tests to Consider o SS18 – activator of oncogenes Primary test o SSX1, SSX2 – tumor suppression SS18 (SYT) (18q11) Gene Rearrangement by FISH 3001303 Test Interpretation • Molecular diagnosis of synovial sarcoma Results Related test • Positive – SS18 rearrangement is detected Chromosome FISH, Interphase 2002298 o SSX translocation partner is not identified with this • Specific probe for SS18 (SYT) rearrangement must be testing methodology requested o Synovial sarcoma likely • Fresh tissue specimens only • Negative – no SS18 rearrangement detected Disease Overview o Does not entirely exclude the presence of an SS18 rearrangement as some translocations are cryptic and Incidence – rare not evaluable by this testing methodology • Synovial sarcomas account for 8-10% of all soft tissue o Does not entirely exclude diagnosis of synovial sarcoma sarcomas Limitations Diagnostic/prognostic issues • Testing using tissue fixed in alcohol-based or non-formalin • Synovial sarcomas may resemble other neoplasms, fixatives has not been validated using this method particularly those displaying an epithelioid, spindle cell, or • SS18 fusion partners are not detected with this test combined morphology • t(X;18)(p11.2;q11.2) translocation serves as a specific marker for synovial sarcoma o SS18 (SYT) gene fuses with SSX gene . Fusion with SSX1 in ~65% of synovial sarcomas . -
Transcriptional Regulation of RKIP in Prostate Cancer Progression
Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Sciences Transcriptional Regulation of RKIP in Prostate Cancer Progression Submitted by: Sandra Marie Beach In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Sciences Examination Committee Major Advisor: Kam Yeung, Ph.D. Academic William Maltese, Ph.D. Advisory Committee: Sonia Najjar, Ph.D. Han-Fei Ding, M.D., Ph.D. Manohar Ratnam, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: May 16, 2007 Transcriptional Regulation of RKIP in Prostate Cancer Progression Sandra Beach University of Toledo ACKNOWLDEGMENTS I thank my major advisor, Dr. Kam Yeung, for the opportunity to pursue my degree in his laboratory. I am also indebted to my advisory committee members past and present, Drs. Sonia Najjar, Han-Fei Ding, Manohar Ratnam, James Trempe, and Douglas Pittman for generously and judiciously guiding my studies and sharing reagents and equipment. I owe extended thanks to Dr. William Maltese as a committee member and chairman of my department for supporting my degree progress. The entire Department of Biochemistry and Cancer Biology has been most kind and helpful to me. Drs. Roy Collaco and Hong-Juan Cui have shared their excellent technical and practical advice with me throughout my studies. I thank members of the Yeung laboratory, Dr. Sungdae Park, Hui Hui Tang, Miranda Yeung for their support and collegiality. The data mining studies herein would not have been possible without the helpful advice of Dr. Robert Trumbly. I am also grateful for the exceptional assistance and shared microarray data of Dr. -
Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. -
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Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes. -
Extensive Genomic and Transcriptional Diversity Identified Through Massively Parallel DNA and RNA Sequencing of Eighteen Korean Individuals
ARTICLES Extensive genomic and transcriptional diversity identified through massively parallel DNA and RNA sequencing of eighteen Korean individuals Young Seok Ju1,2,9, Jong-Il Kim1,3–5,9, Sheehyun Kim1,2,9, Dongwan Hong1,8, Hansoo Park1,6, Jong-Yeon Shin1,5, Seungbok Lee1,4, Won-Chul Lee1,4, Sujung Kim5, Saet-Byeol Yu5, Sung-Soo Park5, Seung-Hyun Seo5, Ji-Young Yun5, Hyun-Jin Kim1,4, Dong-Sung Lee1,4, Maryam Yavartanoo1,4, Hyunseok Peter Kang1, Omer Gokcumen6, Diddahally R Govindaraju6, Jung Hee Jung2, Hyonyong Chong2,7, Kap-Seok Yang2, Hyungtae Kim2, Charles Lee6 & Jeong-Sun Seo1–5,7 Massively parallel sequencing technologies have identified a broad spectrum of human genome diversity. Here we deep sequenced and correlated 18 genomes and 17 transcriptomes of unrelated Korean individuals. This has allowed us to construct a genome- wide map of common and rare variants and also identify variants formed during DNA-RNA transcription. We identified 9.56 million genomic variants, 23.2% of which appear to be previously unidentified. From transcriptome sequencing, we discovered 4,414 transcripts not previously annotated. Finally, we revealed 1,809 sites of transcriptional base modification, where the transcriptional landscape is different from the corresponding genomic sequences, and 580 sites of allele-specific expression. Our findings suggest that a considerable number of unexplored genomic variants still remain to be identified in the human genome, and that the integrated analysis of genome and transcriptome sequencing is powerful for understanding the diversity and functional aspects of human genomic variants. Massively parallel sequencing technologies have revolutionized traits has actually been explained18, presumably because, in part, of our understanding of human genome architecture. -
A Novel Type of SYT/SSX Fusion
A Novel Type of SYT/SSX Fusion: Methodological and Biological Implications Maria Törnkvist, M.Sc., Bertha Brodin, Ph.D., Armando Bartolazzi, M.D., Ph.D., Olle Larsson, M.D., Ph.D. Department of Cellular and Molecular Tumor Pathology, Cancer Centrum Karolinska, Karolinska Hospital (MT, BB, AB, OL), Stockholm, Sweden; and Department of Pathology, Regina Elena Cancer Institute (AB), Rome, Italy the presence of SYT/SSX transcripts in two cases Synovial sarcoma (SS) is a rare soft-tissue tumor using the proposed RT-PCR approach. Applications that affects children and young adults. It is charac- of optimized RT-PCR can contribute to reduce false- terized by the chromosomal translocation t(X; negative SYT/SSX SS cases reported in literature. 18)(p11.2;q11.2), which results in the fusion of the SYT gene on chromosome 18 with a SSX gene on KEY WORDS: RT-PCR, Synovial sarcoma, SYT/SSX chromosome X. In the majority of cases, SYT is fusion gene, SYT/SSX variants. fused to exon 5 of SSX1 (64%), SSX2 (36%), or, Mod Pathol 2002;15(6):679–685 rarely, SSX4. A novel fusion transcript variant deriv- ing from the fusion of SYT to exon 6 of SSX4 gene Synovial sarcomas (SS) account for 7 to 10% of all (SYT/SSX4v) was found coexpressed in one of the human soft-tissue sarcomas and are mainly located previously reported SYT/SSX4 cases. In the present in the extremities in the vicinity of large joints (1). investigation, we describe a new SS case that was Depending on histomorphological appearance, SSs previously shown to be negative for SYT/SSX1 and are usually subdivided into two major forms, bipha- SYT/SSX2 expression by conventional reverse tran- sic and monophasic. -
Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights Into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle
animals Article Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle Masoumeh Naserkheil 1 , Abolfazl Bahrami 1 , Deukhwan Lee 2,* and Hossein Mehrban 3 1 Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj 77871-31587, Iran; [email protected] (M.N.); [email protected] (A.B.) 2 Department of Animal Life and Environment Sciences, Hankyong National University, Jungang-ro 327, Anseong-si, Gyeonggi-do 17579, Korea 3 Department of Animal Science, Shahrekord University, Shahrekord 88186-34141, Iran; [email protected] * Correspondence: [email protected]; Tel.: +82-31-670-5091 Received: 25 August 2020; Accepted: 6 October 2020; Published: 9 October 2020 Simple Summary: Hanwoo is an indigenous cattle breed in Korea and popular for meat production owing to its rapid growth and high-quality meat. Its yearling weight and carcass traits (backfat thickness, carcass weight, eye muscle area, and marbling score) are economically important for the selection of young and proven bulls. In recent decades, the advent of high throughput genotyping technologies has made it possible to perform genome-wide association studies (GWAS) for the detection of genomic regions associated with traits of economic interest in different species. In this study, we conducted a weighted single-step genome-wide association study which combines all genotypes, phenotypes and pedigree data in one step (ssGBLUP). It allows for the use of all SNPs simultaneously along with all phenotypes from genotyped and ungenotyped animals. Our results revealed 33 relevant genomic regions related to the traits of interest. -
Meta-Analyses of Expression Profiling Data in the Postmortem
META-ANALYSES OF EXPRESSION PROFILING DATA IN THE POSTMORTEM HUMAN BRAIN by Meeta Mistry B.Sc., McMaster University, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES (Bioinformatics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) July 2012 © Meeta Mistry, 2012 Abstract Schizophrenia is a severe psychiatric illness for which the precise etiology remains unknown. Studies using postmortem human brain have become increasingly important in schizophrenia research, providing an opportunity to directly investigate the diseased brain tissue. Gene expression profiling technologies have been used by a number of groups to explore the postmortem human brain and seek genes which show changes in expression correlated with schizophrenia. While this has been a valuable means of generating hypotheses, there is a general lack of consensus in the findings across studies. Expression profiling of postmortem human brain tissue is difficult due to the effect of various factors that can confound the data. The first aim of this thesis was to use control postmortem human cortex for identification of expression changes associated with several factors, specifically: age, sex, brain pH and postmortem interval. I conducted a meta-analysis across the control arm of eleven microarray datasets (representing over 400 subjects), and identified a signature of genes associated with each factor. These genes provide critical information towards the identification of problematic genes when investigating postmortem human brain in schizophrenia and other neuropsychiatric illnesses. The second aim of this thesis was to evaluate gene expression patterns in the prefrontal cortex associated with schizophrenia by exploring two methods of analysis: differential expression and coexpression. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
A Novel FISH Assay for SS18–SSX Fusion Type in Synovial Sarcoma
Laboratory Investigation (2004) 84, 1185–1192 & 2004 USCAP, Inc All rights reserved 0023-6837/04 $30.00 www.laboratoryinvestigation.org A novel FISH assay for SS18–SSX fusion type in synovial sarcoma Cecilia Surace1,2, Ioannis Panagopoulos1, Eva Pa˚lsson1, Mariano Rocchi2, Nils Mandahl1 and Fredrik Mertens1 1Department of Clinical Genetics, Lund University Hospital, Lund, Sweden and 2DAPEG, Section of Genetics, University of Bari, Bari, Italy Synovial sarcoma is a morphologically, clinically and genetically distinct entity that accounts for 5–10% of all soft tissue sarcomas. The t(X;18)(p11.2;q11.2) is the cytogenetic hallmark of synovial sarcoma and is present in more than 90% of the cases. It produces three types of fusion gene formed in part by SS18 from chromosome 18 and by SSX1, SSX2 or, rarely, SSX4 from the X chromosome. The SS18–SSX fusions do not seem to occur in other tumor types, and it has been shown that in synovial sarcoma a clear correlation exists between the type of fusion gene and histologic subtype and, more importantly, clinical outcome. Previous analyses regarding the type of fusion genes have been based on PCR amplification of the fusion transcript, requiring access to good- quality RNA. In order to obtain an alternative tool to diagnose and follow this malignancy, we developed a fluorescence in situ hybridization (FISH) assay that could distinguish between the two most common fusion genes, that is, SS18–SSX1 and SS18–SSX2. The specificity of the selected bacterial artificial chromosome clones used in the detection of these fusion genes, as well as the sensitivity of the analysis in metaphase and interphase cells, was examined in a series of 28 synovial sarcoma samples with known fusion gene status.