Identification of Common Pathogenetic Processes Between
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KCTD13 Is a Major Driver of Mirrored Neuroanatomical Phenotypes Associated with the 16P11.2 CNV
KCTD13 is a Major Driver of Mirrored Neuroanatomical Phenotypes Associated with the 16p11.2 CNV The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. Citation Golzio, Christelle, Jason Willer, Michael E. Talkowski, Edwin C. Oh, Yu Taniguchi, Sébastien Jacquemont, Alexandre Reymond, et al. 2012. KCTD13 is a major driver of mirrored neuroanatomical phenotypes associated with the 16p11.2 CNV. Nature 485(7398): 363-367. Published Version doi:10.1038/nature11091 Accessed February 19, 2015 11:53:26 AM EST Citable Link http://nrs.harvard.edu/urn-3:HUL.InstRepos:10579139 Terms of Use This article was downloaded from Harvard University's DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA (Article begins on next page) NIH Public Access Author Manuscript Nature. Author manuscript; available in PMC 2012 November 16. Published in final edited form as: Nature. ; 485(7398): 363–367. doi:10.1038/nature11091. KCTD13 is a major driver of mirrored neuroanatomical phenotypes associated with the 16p11.2 CNV $watermark-text $watermark-text $watermark-text Christelle Golzio1, Jason Willer1, Michael E Talkowski2,3, Edwin C Oh1, Yu Taniguchi5, Sébastien Jacquemont4, Alexandre Reymond6, Mei Sun2, Akira Sawa5, James F Gusella2,3, Atsushi Kamiya5, Jacques S Beckmann4,7, and Nicholas Katsanis1,8 1Center for Human Disease Modeling and Dept of Cell biology, -
Small Cell Ovarian Carcinoma: Genomic Stability and Responsiveness to Therapeutics
Gamwell et al. Orphanet Journal of Rare Diseases 2013, 8:33 http://www.ojrd.com/content/8/1/33 RESEARCH Open Access Small cell ovarian carcinoma: genomic stability and responsiveness to therapeutics Lisa F Gamwell1,2, Karen Gambaro3, Maria Merziotis2, Colleen Crane2, Suzanna L Arcand4, Valerie Bourada1,2, Christopher Davis2, Jeremy A Squire6, David G Huntsman7,8, Patricia N Tonin3,4,5 and Barbara C Vanderhyden1,2* Abstract Background: The biology of small cell ovarian carcinoma of the hypercalcemic type (SCCOHT), which is a rare and aggressive form of ovarian cancer, is poorly understood. Tumourigenicity, in vitro growth characteristics, genetic and genomic anomalies, and sensitivity to standard and novel chemotherapeutic treatments were investigated in the unique SCCOHT cell line, BIN-67, to provide further insight in the biology of this rare type of ovarian cancer. Method: The tumourigenic potential of BIN-67 cells was determined and the tumours formed in a xenograft model was compared to human SCCOHT. DNA sequencing, spectral karyotyping and high density SNP array analysis was performed. The sensitivity of the BIN-67 cells to standard chemotherapeutic agents and to vesicular stomatitis virus (VSV) and the JX-594 vaccinia virus was tested. Results: BIN-67 cells were capable of forming spheroids in hanging drop cultures. When xenografted into immunodeficient mice, BIN-67 cells developed into tumours that reflected the hypercalcemia and histology of human SCCOHT, notably intense expression of WT-1 and vimentin, and lack of expression of inhibin. Somatic mutations in TP53 and the most common activating mutations in KRAS and BRAF were not found in BIN-67 cells by DNA sequencing. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Identification and Validation of a Blood-Based 18-Gene Expression Signature in Colorectal Cancer
Published OnlineFirst March 27, 2013; DOI: 10.1158/1078-0432.CCR-12-3851 Clinical Cancer Imaging, Diagnosis, Prognosis Research Identification and Validation of a Blood-Based 18-Gene Expression Signature in Colorectal Cancer Ye Xu1,4, Qinghua Xu1,6,7, Li Yang1,4, Xun Ye6,7, Fang Liu6,7, Fei Wu6,7, Shujuan Ni1,2,3,5, Cong Tan1,2,3,5, Guoxiang Cai1,4, Xia Meng6,7, Sanjun Cai1,4, and Xiang Du1,2,3,5 Abstract Purpose: The early detection of colorectal cancer (CRC) is crucial for successful treatment and patient survival. However, compliance with current screening methods remains poor. This study aimed to identify an accurate blood-based gene expression signature for CRC detection. Experimental Design: Gene expression in peripheral blood samples from 216 patients with CRC tumors and 187 controls was investigated in the study.Wefirstconductedamicroarrayanalysistoselect candidate genes that were significantly differentially expressed between patients with cancer and con- trols. A quantitative reverse transcription PCR assay was then used to evaluate the expression of selected genes. A gene expression signature was identified using a training set (n ¼ 200) and then validated using an independent test set (n ¼ 160). Results: We identified an 18-gene signature that discriminated the patients with CRC from controls with 92% accuracy, 91% sensitivity, and 92% specificity. The signature performance was further validated in the independent test set with 86% accuracy, 84% sensitivity, and 88% specificity. The area under the receiver operating characteristics curve was 0.94. The signature was shown to be enriched in genes related to immune functions. Conclusions: This study identified an 18-gene signature that accurately discriminated patients with CRC from controls in peripheral blood samples. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Supp Material.Pdf
Supplementary Information Estrogen-mediated Epigenetic Repression of Large Chromosomal Regions through DNA Looping Pei-Yin Hsu, Hang-Kai Hsu, Gregory A. C. Singer, Pearlly S. Yan, Benjamin A. T. Rodriguez, Joseph C. Liu, Yu-I Weng, Daniel E. Deatherage, Zhong Chen, Julia S. Pereira, Ricardo Lopez, Jose Russo, Qianben Wang, Coral A. Lamartiniere, Kenneth P. Nephew, and Tim H.-M. Huang S1 Method Immunofluorescence staining Approximately 2,000 mammosphere-derived epithelial cells (MDECs) cells seeded collagen I-coated coverslips were fixed with methanol/acetone for 10 min. After blocking with 2.5% bovine serum albumin (Sigma) for 1 hr, these cells were incubated with anti-ESR1 antibody (Santa Cruz) overnight at 4˚C. The corresponding secondary FITC-conjugated antibody was applied followed by DAPI staining (Molecular Probes) for the nuclei. Photographs were captured by Zeiss fluorescence microscopy (Zeiss). The percentages of ESR1 subcellular localization were calculated in ten different optical fields (~10 cells per field) by two independent researchers. References Carroll, J.S., Meyer, C.A., Song, J., Li, W., Geistlinger, T.R., Eeckhoute, J., Brodsky, A.S., Keeton, E.K., Fertuck, K.C., Hall, G.F., et al. 2006. Genome-wide analysis of estrogen receptor binding sites. Nat. Genet. 38: 1289-1297. Neve, R.M., Chin, K., Fridlyand, J., Yeh, J., Baehner, F.L., Fevr, T., Clark, L., Bayani, N., Coppe, J.P., Tong, F., et al. 2006. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell 10: 515-527. S2 Hsu et al. Supplementary Information A Figure S1. Integrative mapping of large genomic regions subjected to ERα-mediated epigenetic repression. -
Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes. -
Mutpred2: Inferring the Molecular and Phenotypic Impact of Amino Acid Variants
bioRxiv preprint doi: https://doi.org/10.1101/134981; this version posted May 9, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. MutPred2: inferring the molecular and phenotypic impact of amino acid variants Vikas Pejaver1, Jorge Urresti2, Jose Lugo-Martinez1, Kymberleigh A. Pagel1, Guan Ning Lin2, Hyun-Jun Nam2, Matthew Mort3, David N. Cooper3, Jonathan Sebat2, Lilia M. Iakoucheva2, Sean D. Mooney4, and Predrag Radivojac1 1Indiana University, Bloomington, Indiana, U.S.A. 2University of California San Diego, La Jolla, California, U.S.A. 3Cardiff University, Cardiff, U.K. 4University of Washington, Seattle, Washington, U.S.A. Contact: [email protected]; [email protected]; [email protected] Abstract We introduce MutPred2, a tool that improves the prioritization of pathogenic amino acid substitutions, generates molecular mechanisms potentially causative of disease, and returns interpretable pathogenicity score distributions on individual genomes. While its prioritization performance is state-of-the-art, a novel and distinguishing feature of MutPred2 is the probabilistic modeling of variant impact on specific as- pects of protein structure and function that can serve to guide experimental studies of phenotype-altering variants. We demonstrate the utility of MutPred2 in the iden- tification of the structural and functional mutational signatures relevant to Mendelian disorders and the prioritization of de novo mutations associated with complex neu- rodevelopmental disorders. We then experimentally validate the functional impact of several variants identified in patients with such disorders. We argue that mechanism- driven studies of human inherited diseases have the potential to significantly accelerate the discovery of clinically actionable variants. -
Associated 16P11.2 Deletion in Drosophila Melanogaster
ARTICLE DOI: 10.1038/s41467-018-04882-6 OPEN Pervasive genetic interactions modulate neurodevelopmental defects of the autism- associated 16p11.2 deletion in Drosophila melanogaster Janani Iyer1, Mayanglambam Dhruba Singh1, Matthew Jensen1,2, Payal Patel 1, Lucilla Pizzo1, Emily Huber1, Haley Koerselman3, Alexis T. Weiner 1, Paola Lepanto4, Komal Vadodaria1, Alexis Kubina1, Qingyu Wang 1,2, Abigail Talbert1, Sneha Yennawar1, Jose Badano 4, J. Robert Manak3,5, Melissa M. Rolls1, Arjun Krishnan6,7 & 1234567890():,; Santhosh Girirajan 1,2,8 As opposed to syndromic CNVs caused by single genes, extensive phenotypic heterogeneity in variably-expressive CNVs complicates disease gene discovery and functional evaluation. Here, we propose a complex interaction model for pathogenicity of the autism-associated 16p11.2 deletion, where CNV genes interact with each other in conserved pathways to modulate expression of the phenotype. Using multiple quantitative methods in Drosophila RNAi lines, we identify a range of neurodevelopmental phenotypes for knockdown of indi- vidual 16p11.2 homologs in different tissues. We test 565 pairwise knockdowns in the developing eye, and identify 24 interactions between pairs of 16p11.2 homologs and 46 interactions between 16p11.2 homologs and neurodevelopmental genes that suppress or enhance cell proliferation phenotypes compared to one-hit knockdowns. These interac- tions within cell proliferation pathways are also enriched in a human brain-specific network, providing translational relevance in humans. Our study indicates a role for pervasive genetic interactions within CNVs towards cellular and developmental phenotypes. 1 Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA. 2 Bioinformatics and Genomics Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA. -
Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement. -
Sla2 (NM 029983) Mouse Untagged Clone – MC201875 | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for MC201875 Sla2 (NM_029983) Mouse Untagged Clone Product data: Product Type: Expression Plasmids Product Name: Sla2 (NM_029983) Mouse Untagged Clone Tag: Tag Free Symbol: Sla2 Synonyms: A930009E21Rik; AI430952; SLAP-2; SLAP2 Vector: PCMV6-Kan/Neo E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin Fully Sequenced ORF: >BC052655 sequence for NM_029983 AAGAGGTAATCCGGCCACGCTCTTTGTCCCTGCTGTGCTGGGTGGGAGGGCCCAACCTGGTTTCTCTGAG AAGCAAAGGACTGCTGTACTAGTTTCGTGGAGATTGTCTGCTGACAAAGAAGCTTGATCACAGTACCTCA GCCTACTCTGACTCCTTTCTGGTGACCGATCCTCCAGGCTGCTGGGGCCTGAGATGCCGACTACCTTAGG ACCTGCAAAGGCCTGACCTGTCGGGTCAGTGTGCACATTGGCTGACTACCCTCATCAAACGTCTGATGGC AAACCTTTCCCTTTCCAGGTTCAGTGTGCTTGTGAGCGTCTGCTGAGTGATGGGAAGTTTGTCCAGCAGA GGGAAAACCTCCAGCCCCAGCCCCAGCTCCTCTGGTCCAGACCAGGAACCCGTGTCCATGCAACCAGAAA GACGCAAGGTCACAGCTGTGGCCCTGGGCAGTTTCCCAGCAGGTGAACAGGCCAGACTATCTCTGAGACT CGGGGAGCCGCTGACCATCATCTCTGAGGATGGAGATTGGTGGACAGTCCAGTCGGAAGTCTCAGGCAGA GAGTACCACATGCCCAGTGTGTATGTGGCTAAAGTCGCCCACGGGTGGCTGTACGAGGGCCTGAGCCGGG AGAAAGCCGAGGAACTACTCCTGTTACCTGGGAACCCCGGAGGGGCCTTCCTCATCCGGGAGAGCCAGAC CAGGAGAGGCTGCTATTCCCTGTCCGTCCGACTCAGCCGCCCTGCATCTTGGGACCGGATCAGACACTAC AGGATACAGCGTCTTGACAATGGCTGGCTGTACATCTCACCTCGCCTCACCTTCCCCTCACTCCACGCCT TGGTGGAGCATTACTCTGAGCTAGCAGATGGCATCTGCTGTCCCCTCAGGGAGCCGTGTGTCCTGCAGAA GCTTGGGCCACTACCTGGCAAAGATACACCTCCACCTGTGACTGTGCCAACATCATCACTAAATTGGAAA -
ARHGDIA: a Novel Gene Implicated in Nephrotic Syndrome
Developmental defects J Med Genet: first published as 10.1136/jmedgenet-2012-101442 on 22 February 2013. Downloaded from ORIGINAL ARTICLE ARHGDIA: a novel gene implicated in nephrotic syndrome Indra Rani Gupta,1,2,3 Cindy Baldwin,4 David Auguste,4,5 Kevin C H Ha,3,6 Jasmine El Andalousi,2 Somayyeh Fahiminiya,3,6 Martin Bitzan,1,2 Chantal Bernard,7 Mohammad Reza Akbari,8,9 Steven A Narod,8,9 David S Rosenblatt,1,3,4 Open Access 3,6 2,4,5 Scan to access more Jacek Majewski, Tomoko Takano free content ▸ Additional material is ABSTRACT the barrier into the urine. The glomerular filtration published online only. To view Background Congenital nephrotic syndrome arises barrier consists of fenestrated endothelial cells, the please visit the journal online fi (http://dx.doi.org/10.1136/ from a defect in the glomerular ltration barrier that acellular glomerular basement membrane that is jmedgenet-2012-101442). permits the unrestricted passage of protein across the about 300 nm thick, and specialised epithelial cells barrier, resulting in proteinuria, hypoalbuminaemia, and called podocytes. The majority of children with For numbered affiliations see end of article. severe oedema. While most cases are due to mutations congenital nephrotic syndrome have a monogenic in one of five genes, in up to 15% of cases, a genetic basis for their disease due to mutations in genes Correspondence to cause is not identified. We investigated two sisters with that affect the structure and function of the actin Dr Indra Rani Gupta, a presumed recessive form of congenital nephrotic cytoskeleton within podocytes.1 In a large survey, Department of Pediatrics, ∼ Division of Nephrology, syndrome.