Overview of Inactivating Mutations in the Protein-Coding Genome of the Mouse Reference Strain C57BL/6J
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Open Dogan Phdthesis Final.Pdf
The Pennsylvania State University The Graduate School Eberly College of Science ELUCIDATING BIOLOGICAL FUNCTION OF GENOMIC DNA WITH ROBUST SIGNALS OF BIOCHEMICAL ACTIVITY: INTEGRATIVE GENOME-WIDE STUDIES OF ENHANCERS A Dissertation in Biochemistry, Microbiology and Molecular Biology by Nergiz Dogan © 2014 Nergiz Dogan Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy August 2014 ii The dissertation of Nergiz Dogan was reviewed and approved* by the following: Ross C. Hardison T. Ming Chu Professor of Biochemistry and Molecular Biology Dissertation Advisor Chair of Committee David S. Gilmour Professor of Molecular and Cell Biology Anton Nekrutenko Professor of Biochemistry and Molecular Biology Robert F. Paulson Professor of Veterinary and Biomedical Sciences Philip Reno Assistant Professor of Antropology Scott B. Selleck Professor and Head of the Department of Biochemistry and Molecular Biology *Signatures are on file in the Graduate School iii ABSTRACT Genome-wide measurements of epigenetic features such as histone modifications, occupancy by transcription factors and coactivators provide the opportunity to understand more globally how genes are regulated. While much effort is being put into integrating the marks from various combinations of features, the contribution of each feature to accuracy of enhancer prediction is not known. We began with predictions of 4,915 candidate erythroid enhancers based on genomic occupancy by TAL1, a key hematopoietic transcription factor that is strongly associated with gene induction in erythroid cells. Seventy of these DNA segments occupied by TAL1 (TAL1 OSs) were tested by transient transfections of cultured hematopoietic cells, and 56% of these were active as enhancers. Sixty-six TAL1 OSs were evaluated in transgenic mouse embryos, and 65% of these were active enhancers in various tissues. -
Identifying Glaucoma Susceptibility Genes in Extended Families
Identifying Glaucoma Susceptibility Genes in Extended Families by Patricia Stacey Graham BSc(Hons), GradDipEd Menzies Institute for Medical Research | College of Health and Medicine Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy (Medical Studies) University of Tasmania, March 2020 Declaration of Originality This thesis contains no material which has been accepted for a degree or diploma by the University or any other institution, except by way of background information and duly acknowledged in the thesis, and to the best of my knowledge and belief no material previously published or written by another person except where due acknowledgement is made in the text of the thesis, nor does the thesis contain any material that infringes copyright. 13/3/2020 i Authority of access This thesis may be made available for loan and limited copying and communication in accordance with the Copyright Act 1968. 13/3/2020 ii Statement of ethical conduct The research associated with this thesis abides by the international and Australian codes on human experimentation and the guidelines and the rulings of the Ethics Committee of the University. Ethics Approval Numbers: University of Tasmania Human Research Ethics Committee H0014085 Oregon Health and Science University Institutional Review Board #1306 13/3/2020 iii Dedication To my parents Susie and Micky Lowry Who instilled in me the love of learning and who would have been so proud iv Acknowledgements What a rollercoaster the last four years have been …. it’s been an amazing ride. Rollercoasters are no fun alone, and I would sincerely like to thank the following people who kept the ride rolling and to those who sat with me in the carriage and didn’t let me fall out. -
Evolution of the DAN Gene Family in Vertebrates
bioRxiv preprint doi: https://doi.org/10.1101/794404; this version posted June 29, 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 4.0 International license. RESEARCH ARTICLE Evolution of the DAN gene family in vertebrates Juan C. Opazo1,2,3, Federico G. Hoffmann4,5, Kattina Zavala1, Scott V. Edwards6 1Instituto de Ciencias Ambientales y Evolutivas, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, Chile. 2David Rockefeller Center for Latin American Studies, Harvard University, Cambridge, MA 02138, USA. 3Millennium Nucleus of Ion Channels-Associated Diseases (MiNICAD). 4 Department of Biochemistry, Molecular Biology, Entomology, and Plant Pathology, Mississippi State University, Mississippi State, 39762, USA. Cite as: Opazo JC, Hoffmann FG, 5 Zavala K, Edwards SV (2020) Institute for Genomics, Biocomputing, and Biotechnology, Mississippi State Evolution of the DAN gene family in University, Mississippi State, 39762, USA. vertebrates. bioRxiv, 794404, ver. 3 peer-reviewed and recommended by 6 PCI Evolutionary Biology. doi: Department of Organismic and Evolutionary Biology, Harvard University, 10.1101/794404 Cambridge, MA 02138, USA. This article has been peer-reviewed and recommended by Peer Community in Evolutionary Biology Posted: 29 June 2020 doi: 10.24072/pci.evolbiol.100104 ABSTRACT Recommender: Kateryna Makova The DAN gene family (DAN, Differential screening-selected gene Aberrant in Neuroblastoma) is a group of genes that is expressed during development and plays fundamental roles in limb bud formation and digitation, kidney formation and morphogenesis and left-right axis specification. -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
Snps Detection in DHPS-WDR83 Overlapping Genes Mapping On
Zambonelli et al. BMC Genetics 2013, 14:99 http://www.biomedcentral.com/1471-2156/14/99 RESEARCH ARTICLE Open Access SNPs detection in DHPS-WDR83 overlapping genes mapping on porcine chromosome 2 in a QTL region for meat pH Paolo Zambonelli1*, Roberta Davoli1, Mila Bigi1, Silvia Braglia1, Luigi Francesco De Paolis1, Luca Buttazzoni2,3, Maurizio Gallo3 and Vincenzo Russo1 Abstract Background: The pH is an important parameter influencing technological quality of pig meat, a trait affected by environmental and genetic factors. Several quantitative trait loci associated to meat pH are described on PigQTL database but only two genes influencing this parameter have been so far detected: Ryanodine receptor 1 and Protein kinase, AMP-activated, gamma 3 non-catalytic subunit. To search for genes influencing meat pH we analyzed genomic regions with quantitative effect on this trait in order to detect SNPs to use for an association study. Results: The expressed sequences mapping on porcine chromosomes 1, 2, 3 in regions associated to pork pH were searched in silico to find SNPs. 356 out of 617 detected SNPs were used to genotype Italian Large White pigs and to perform an association analysis with meat pH values recorded in semimembranosus muscle at about 1 hour (pH1) and 24 hours (pHu) post mortem. The results of the analysis showed that 5 markers mapping on chromosomes 1 or 3 were associated with pH1 and 10 markers mapping on chromosomes 1 or 2 were associated with pHu. After False Discovery Rate correction only one SNP mapping on chromosome 2 was confirmed to be associated to pHu. -
Protein Complex Prediction Via Dense Subgraphs and False Positive Analysis
RESEARCH ARTICLE Protein complex prediction via dense subgraphs and false positive analysis Cecilia Hernandez1,2*, Carlos Mella1, Gonzalo Navarro2, Alvaro Olivera-Nappa3, Jaime Araya1 1 Computer Science, University of ConcepcioÂn, ConcepcioÂn, Chile, 2 Center for Biotechnology and Bioengineering (CeBiB), Department of Computer Science, University of Chile, Santiago, Chile, 3 Center for Biotechnology and Bioengineering (CeBiB), Department of Chemical Engineering and Biotechnology, University of Chile, Santiago, Chile * [email protected] a1111111111 Abstract a1111111111 a1111111111 Many proteins work together with others in groups called complexes in order to achieve a a1111111111 specific function. Discovering protein complexes is important for understanding biological a1111111111 processes and predict protein functions in living organisms. Large-scale and throughput techniques have made possible to compile protein-protein interaction networks (PPI net- works), which have been used in several computational approaches for detecting protein complexes. Those predictions might guide future biologic experimental research. Some OPEN ACCESS approaches are topology-based, where highly connected proteins are predicted to be Citation: Hernandez C, Mella C, Navarro G, Olivera- complexes; some propose different clustering algorithms using partitioning, overlaps Nappa A, Araya J (2017) Protein complex among clusters for networks modeled with unweighted or weighted graphs; and others prediction via dense subgraphs and false positive analysis. PLoS ONE 12(9): e0183460. https://doi. use density of clusters and information based on protein functionality. However, some org/10.1371/journal.pone.0183460 schemes still require much processing time or the quality of their results can be improved. Editor: Jianhua Ruan, University of Texas at San Furthermore, most of the results obtained with computational tools are not accompanied Antonio, UNITED STATES by an analysis of false positives. -
Anti-VARS (Aa 994-1102) Polyclonal Antibody (DPAB-DC3179) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use
Anti-VARS (aa 994-1102) polyclonal antibody (DPAB-DC3179) This product is for research use only and is not intended for diagnostic use. PRODUCT INFORMATION Antigen Description Aminoacyl-tRNA synthetases catalyze the aminoacylation of tRNA by their cognate amino acid. Because of their central role in linking amino acids with nucleotide triplets contained in tRNAs, aminoacyl-tRNA synthetases are thought to be among the first proteins that appeared in evolution. The protein encoded by this gene belongs to class-I aminoacyl-tRNA synthetase family and is located in the class III region of the major histocompatibility complex. Immunogen VARS (NP_006286, 994 a.a. ~ 1102 a.a) partial recombinant protein with GST tag. The sequence is AVRLSNQGFQAYDFPAVTTAQYSFWLYELCDVYLECLKPVLNGVDQVAAECARQTLYTCLDVG LRLLSPFMPFVTEELFQRLPRRMPQAPPSLCVTPYPEPSECSWKDP Source/Host Mouse Species Reactivity Human Conjugate Unconjugated Applications WB (Recombinant protein), ELISA, Size 50 μl Buffer 50 % glycerol Preservative None Storage Store at -20°C or lower. Aliquot to avoid repeated freezing and thawing. GENE INFORMATION Gene Name VARS valyl-tRNA synthetase [ Homo sapiens (human) ] Official Symbol VARS Synonyms VARS; valyl-tRNA synthetase; G7A; VARS1; VARS2; valine--tRNA ligase; valRS; protein G7a; valyl-tRNA synthetase 2; valine tRNA ligase 1, cytoplasmic; 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 1 © Creative Diagnostics All Rights Reserved Entrez Gene ID 7407 Protein Refseq NP_006286 UniProt ID A0A024RCN6 Chromosome Location 6p21.3 Pathway Aminoacyl-tRNA biosynthesis; Cytosolic tRNA aminoacylation; tRNA Aminoacylation; Function ATP binding; aminoacyl-tRNA editing activity; valine-tRNA ligase activity; 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 2 © Creative Diagnostics All Rights Reserved. -
A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family
Rockefeller University Digital Commons @ RU Student Theses and Dissertations 2018 A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family Linda Molla Follow this and additional works at: https://digitalcommons.rockefeller.edu/ student_theses_and_dissertations Part of the Life Sciences Commons A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY A Thesis Presented to the Faculty of The Rockefeller University in Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy by Linda Molla June 2018 © Copyright by Linda Molla 2018 A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY Linda Molla, Ph.D. The Rockefeller University 2018 APOBEC2 is a member of the AID/APOBEC cytidine deaminase family of proteins. Unlike most of AID/APOBEC, however, APOBEC2’s function remains elusive. Previous research has implicated APOBEC2 in diverse organisms and cellular processes such as muscle biology (in Mus musculus), regeneration (in Danio rerio), and development (in Xenopus laevis). APOBEC2 has also been implicated in cancer. However the enzymatic activity, substrate or physiological target(s) of APOBEC2 are unknown. For this thesis, I have combined Next Generation Sequencing (NGS) techniques with state-of-the-art molecular biology to determine the physiological targets of APOBEC2. Using a cell culture muscle differentiation system, and RNA sequencing (RNA-Seq) by polyA capture, I demonstrated that unlike the AID/APOBEC family member APOBEC1, APOBEC2 is not an RNA editor. Using the same system combined with enhanced Reduced Representation Bisulfite Sequencing (eRRBS) analyses I showed that, unlike the AID/APOBEC family member AID, APOBEC2 does not act as a 5-methyl-C deaminase. -
Meta-Analysis of Gene Expression in Individuals with Autism Spectrum Disorders
Meta-analysis of Gene Expression in Individuals with Autism Spectrum Disorders by Carolyn Lin Wei Ch’ng BSc., University of Michigan Ann Arbor, 2011 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Bioinformatics) The University of British Columbia (Vancouver) August 2013 c Carolyn Lin Wei Ch’ng, 2013 Abstract Autism spectrum disorders (ASD) are clinically heterogeneous and biologically complex. State of the art genetics research has unveiled a large number of variants linked to ASD. But in general it remains unclear, what biological factors lead to changes in the brains of autistic individuals. We build on the premise that these heterogeneous genetic or genomic aberra- tions will converge towards a common impact downstream, which might be reflected in the transcriptomes of individuals with ASD. Similarly, a considerable number of transcriptome analyses have been performed in attempts to address this question, but their findings lack a clear consensus. As a result, each of these individual studies has not led to any significant advance in understanding the autistic phenotype as a whole. The goal of this research is to comprehensively re-evaluate these expression profiling studies by conducting a systematic meta-analysis. Here, we report a meta-analysis of over 1000 microarrays across twelve independent studies on expression changes in ASD compared to unaffected individuals, in blood and brain. We identified a number of genes that are consistently differentially expressed across studies of the brain, suggestive of effects on mitochondrial function. In blood, consistent changes were more difficult to identify, despite individual studies tending to exhibit larger effects than the brain studies. -
Subchromosomal Anomalies in Small for Gestational-Age Fetuses And
Archives of Gynecology and Obstetrics (2019) 300:633–639 https://doi.org/10.1007/s00404-019-05235-4 MATERNAL-FETAL MEDICINE Subchromosomal anomalies in small for gestational‑age fetuses and newborns Ying Ma1 · Yan Pei1 · Chenghong Yin2 · Yuxin Jiang3 · Jingjing Wang4 · Xiaofei Li4 · Lin Li5 · Karl Oliver Kagan6 · Qingqing Wu4 Received: 9 January 2019 / Accepted: 27 June 2019 / Published online: 4 July 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract Purpose To analyze copy number variants (CNVs) in subjects with small for gestational age (SGA) in China. Methods A total of 85 cases with estimated fetal weight (EFW) or birth weight below the 10th percentile for gestational age were recruited, including SGA associated with structural anomalies (Group A, n = 20) and isolated SGA (Group B, n = 65). In all cases, cytogenetic karyotyping and infection screening were normal. We examined DNA from fetuses (amniocentesis or cordocentesis) and newborns (cord blood) to detect CNVs using a single nucleotide polymorphism (SNP, n = 75) array or low-pass whole-genome sequencing (WGS, n = 10). Results Of 85 total cases, 3 (4%) carried pathogenic chromosomal abnormalities, including 2 cases with pathological CNVs and 1 case with upd(22)pat. In Group A, the mean gestational age at the time of diagnosis was 26.8 (SD 4.1) weeks and mean EFW/birth weight was 907.2 (SD 567.8) g. In Group B, the mean gestational age at the time of diagnosis was 34.1 (SD 5.8) weeks. Mean EFW/birth weight was 1879.2 (SD 714.5) g. The pathologic detection rate was 10% (2/20) in Group A and 2% (1/65) in Group B. -
Supplemental Materials For: a C9orf72-CARM1 Axis Regulates Lipid Metabolism Under Glucose Starvation-Induced Nutrient Stress
Supplemental materials for: A C9orf72-CARM1 Axis Regulates Lipid Metabolism Under Glucose Starvation-induced Nutrient Stress Yang Liu1,2, Tao Wang1,2, Yon Ju Ji1,2, Kenji Johnson1,2, Honghe Liu1,2, Kaitlin Johnson1, Scott Bailey1, Yongwon Suk1,2, Yu-Ning Lu1,2, Mingming Liu1,2, Jiou Wang1,2* Corresponding author: Jiou Wang, [email protected] This file includes: Supplemental Figures and Legends S1 to S7 Supplemental Tables S1 to S2 Supplemental Figure S1. The proteomic analysis showing altered lipid metabolism under glucose starvation upon the loss of C9orf72. (A) The scheme of Quantitative proteomic analysis. WT and C9orf72-/- MEFs were cultured with complete medium (CM) or treated with glucose starvation (GS) for 6 hours and then harvested for quantitative proteomic analysis. Ratios of C9orf72-/- (GS) / C9orf72 (CM) and WT (GS) / WT (CM) mean the extent of the protein amount variation induced by glucose starvation in C9orf72-/- and WT MEFs, respectively. Further comparison of the two ratios reflects the differential influence of glucose starvation on protein amounts, especially lipid metabolism relative (LMR) proteins, which were identified using the UniProt database as described in methods. The further a ratio is from 1, the more change it indicates for the protein level as a result of glucose starvation in C9orf72-/- MEFs relative to WT cells; on the other hand, a ratio closer to 1 indicates that glucose starvation induces a similar change in the protein level in C9orf72-/- MEFs as in WT cells. (B) Glucose starvation induced upregulation of 48 LMR proteins and downregulation of 23 LMR proteins in C9orf72-/- MEFs relative to WT MEFs. -
Downloaded Per Proteome Cohort Via the Web- Site Links of Table 1, Also Providing Information on the Deposited Spectral Datasets
www.nature.com/scientificreports OPEN Assessment of a complete and classifed platelet proteome from genome‑wide transcripts of human platelets and megakaryocytes covering platelet functions Jingnan Huang1,2*, Frauke Swieringa1,2,9, Fiorella A. Solari2,9, Isabella Provenzale1, Luigi Grassi3, Ilaria De Simone1, Constance C. F. M. J. Baaten1,4, Rachel Cavill5, Albert Sickmann2,6,7,9, Mattia Frontini3,8,9 & Johan W. M. Heemskerk1,9* Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome‑wide transcriptomes (57.8 k mRNAs). For 14.8 k protein‑coding transcripts, we assigned the proteins to 21 UniProt‑based classes, based on their preferential intracellular localization and presumed function. This classifed transcriptome‑proteome profle of platelets revealed: (i) Absence of 37.2 k genome‑ wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein‑coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43–0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identifed proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma‑derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identifed proteome of nuclear‑related, membrane and signaling proteins, as well proteins with low‑level transcripts.