Mouse Epb42 Knockout Project (CRISPR/Cas9)

Total Page:16

File Type:pdf, Size:1020Kb

Mouse Epb42 Knockout Project (CRISPR/Cas9) https://www.alphaknockout.com Mouse Epb42 Knockout Project (CRISPR/Cas9) Objective: To create a Epb42 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Epb42 gene (NCBI Reference Sequence: NM_013513 ; Ensembl: ENSMUSG00000023216 ) is located on Mouse chromosome 2. 13 exons are identified, with the ATG start codon in exon 1 and the TAA stop codon in exon 13 (Transcript: ENSMUST00000102490). Exon 2~5 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Homozygotes for a targeted null mutation exhibit erythrocytic abnormalities including mild spherocytosis, altered ion transport, and dehydration. Exon 2 starts from about 0.53% of the coding region. Exon 2~5 covers 31.07% of the coding region. The size of effective KO region: ~5547 bp. The KO region does not have any other known gene. Page 1 of 9 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 2 3 4 5 13 Legends Exon of mouse Epb42 Knockout region Page 2 of 9 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 1985 bp section upstream of Exon 2 is aligned with itself to determine if there are tandem repeats. No significant tandem repeat is found in the dot plot matrix. So this region is suitable for PCR screening or sequencing analysis. Overview of the Dot Plot (down) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 1230 bp section downstream of Exon 5 is aligned with itself to determine if there are tandem repeats. No significant tandem repeat is found in the dot plot matrix. So this region is suitable for PCR screening or sequencing analysis. Page 3 of 9 https://www.alphaknockout.com Overview of the GC Content Distribution (up) Window size: 300 bp Sequence 12 Summary: Full Length(1985bp) | A(28.72% 570) | C(20.3% 403) | T(25.34% 503) | G(25.64% 509) Note: The 1985 bp section upstream of Exon 2 is analyzed to determine the GC content. No significant high GC-content region is found. So this region is suitable for PCR screening or sequencing analysis. Overview of the GC Content Distribution (down) Window size: 300 bp Sequence 12 Summary: Full Length(1230bp) | A(28.46% 350) | C(23.25% 286) | T(23.58% 290) | G(24.72% 304) Note: The 1230 bp section downstream of Exon 5 is analyzed to determine the GC content. No significant high GC-content region is found. So this region is suitable for PCR screening or sequencing analysis. Page 4 of 9 https://www.alphaknockout.com BLAT Search Results (up) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN ----------------------------------------------------------------------------------------------- browser details YourSeq 1985 1 1985 1985 100.0% chr2 - 121034599 121036583 1985 browser details YourSeq 107 297 644 1985 84.7% chr9 - 103918676 103919020 345 browser details YourSeq 107 322 644 1985 77.5% chr13 + 91727519 91727804 286 browser details YourSeq 104 264 627 1985 90.0% chr6 - 85926240 85926637 398 browser details YourSeq 102 396 651 1985 84.4% chr18 + 10166780 10167049 270 browser details YourSeq 100 380 615 1985 86.7% chr13 - 107335305 107335549 245 browser details YourSeq 98 407 629 1985 87.7% chr1 + 179590699 179590951 253 browser details YourSeq 96 407 638 1985 85.8% chr2 + 70382565 70382826 262 browser details YourSeq 95 301 644 1985 86.9% chr7 - 114555601 114555962 362 browser details YourSeq 95 303 644 1985 89.4% chr9 + 80189433 80189776 344 browser details YourSeq 94 437 644 1985 89.5% chr5 - 148477055 148477573 519 browser details YourSeq 94 446 638 1985 86.7% chr17 - 75141858 75142066 209 browser details YourSeq 94 437 644 1985 90.7% chr16 - 23377270 23377614 345 browser details YourSeq 94 262 551 1985 91.4% chr11 + 88782882 88783180 299 browser details YourSeq 88 420 638 1985 89.2% chr12 - 98993269 98993505 237 browser details YourSeq 85 413 599 1985 89.8% chr5 + 126311488 126311676 189 browser details YourSeq 85 460 644 1985 90.6% chr17 + 35319924 35320282 359 browser details YourSeq 84 437 644 1985 92.0% chr19 - 4638969 4639201 233 browser details YourSeq 83 379 644 1985 86.0% chr15 + 40128726 40129022 297 browser details YourSeq 81 303 538 1985 81.9% chr19 - 18941297 18941513 217 Note: The 1985 bp section upstream of Exon 2 is BLAT searched against the genome. No significant similarity is found. BLAT Search Results (down) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN ----------------------------------------------------------------------------------------------- browser details YourSeq 1230 1 1230 1230 100.0% chr2 - 121027822 121029051 1230 browser details YourSeq 152 439 802 1230 88.4% chr4 - 106668720 106669087 368 browser details YourSeq 125 536 787 1230 85.4% chr16 + 43836060 43836334 275 browser details YourSeq 122 439 681 1230 88.2% chr10 + 86831118 86831364 247 browser details YourSeq 120 445 690 1230 88.1% chr7 - 65673317 65673567 251 browser details YourSeq 119 450 681 1230 85.3% chr8 - 43250195 43250431 237 browser details YourSeq 119 439 690 1230 87.4% chr12 - 52809512 52809765 254 browser details YourSeq 113 541 790 1230 89.1% chr8 - 119310700 119310963 264 browser details YourSeq 113 450 682 1230 87.1% chr17 + 85092268 85092501 234 browser details YourSeq 112 523 690 1230 89.6% chr15 - 32037235 32037405 171 browser details YourSeq 111 450 794 1230 88.3% chr7 - 127832301 127832652 352 browser details YourSeq 109 539 797 1230 86.7% chr2 + 118564086 118564342 257 browser details YourSeq 108 450 678 1230 85.2% chr11 - 93794865 93795095 231 browser details YourSeq 105 400 690 1230 89.5% chr4 + 149811459 149811749 291 browser details YourSeq 104 439 794 1230 87.7% chr1 - 64969085 64969442 358 browser details YourSeq 101 538 794 1230 92.5% chr8 - 118501610 118501911 302 browser details YourSeq 101 523 665 1230 86.8% chr19 - 24240249 24334012 93764 browser details YourSeq 101 450 792 1230 86.5% chr7 + 145288121 145288462 342 browser details YourSeq 101 457 638 1230 82.5% chr18 + 15028028 15028209 182 browser details YourSeq 100 447 792 1230 85.8% chr10 - 124914750 124915096 347 Note: The 1230 bp section downstream of Exon 5 is BLAT searched against the genome. No significant similarity is found. Page 5 of 9 https://www.alphaknockout.com Gene and protein information: Epb42 erythrocyte membrane protein band 4.2 [ Mus musculus (house mouse) ] Gene ID: 13828, updated on 12-Aug-2019 Gene summary Official Symbol Epb42 provided by MGI Official Full Name erythrocyte membrane protein band 4.2 provided by MGI Primary source MGI:MGI:95402 See related Ensembl:ENSMUSG00000023216 Gene type protein coding RefSeq status REVIEWED Organism Mus musculus Lineage Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Glires; Rodentia; Myomorpha; Muroidea; Muridae; Murinae; Mus; Mus Also known as Epb4.2 Summary The protein encoded by this gene is the key component of a macromolecular complex involved in the structure of Expression erythrocytes. [provided by RefSeq, Aug 2015] Orthologs Biased expression in liver E14.5 (RPKM 57.9), liver E14 (RPKM 55.2) and 3 other tissues See more human all Genomic context Location: 2 E5; 2 60.37 cM See Epb42 in Genome Data Viewer Exon count: 14 Annotation release Status Assembly Chr Location 108 current GRCm38.p6 (GCF_000001635.26) 2 NC_000068.7 (121017891..121036877, complement) Build 37.2 previous assembly MGSCv37 (GCF_000001635.18) 2 NC_000068.6 (120843953..120862491, complement) Chromosome 2 - NC_000068.7 Page 6 of 9 https://www.alphaknockout.com Transcript information: This gene has 7 transcripts Gene: Epb42 ENSMUSG00000023216 Description erythrocyte membrane protein band 4.2 [Source:MGI Symbol;Acc:MGI:95402] Gene Synonyms Epb4.2 Location Chromosome 2: 121,017,891-121,037,072 reverse strand. GRCm38:CM000995.2 About this gene This gene has 7 transcripts (splice variants), 131 orthologues, 8 paralogues, is a member of 1 Ensembl protein family and is associated with 13 phenotypes. Transcripts Name Transcript ID bp Protein Translation ID Biotype CCDS UniProt Flags Epb42-202 ENSMUST00000102490.9 4115 691aa ENSMUSP00000099548.3 Protein coding CCDS16631 P49222 TSL:1 GENCODE basic APPRIS P1 Epb42-201 ENSMUST00000023987.5 2695 673aa ENSMUSP00000023987.5 Protein coding - Q3UV95 TSL:1 GENCODE basic Epb42-205 ENSMUST00000145812.1 625 No protein - Retained intron - - TSL:3 Epb42-203 ENSMUST00000124703.7 2513 No protein - lncRNA - - TSL:1 Epb42-206 ENSMUST00000147444.7 1752 No protein - lncRNA - - TSL:1 Epb42-207 ENSMUST00000152217.1 680 No protein - lncRNA - - TSL:5 Epb42-204 ENSMUST00000128360.1 366 No protein - lncRNA - - TSL:5 Page 7 of 9 https://www.alphaknockout.com 39.18 kb Forward strand 121.01Mb 121.02Mb 121.03Mb 121.04Mb Genes Ccndbp1-201 >protein coding (Comprehensive set... Ccndbp1-202 >protein coding Ccndbp1-203 >protein coding Ccndbp1-206 >lncRNA Ccndbp1-208 >protein coding Ccndbp1-207 >retained intron Ccndbp1-205 >retained intron Ccndbp1-204 >lncRNA Contigs AL844548.7 > Genes (Comprehensive set... < Epb42-202protein coding < Tgm5-201protein coding < Epb42-206lncRNA < Epb42-201protein coding < Epb42-203lncRNA < Epb42-204lncRNA < Epb42-205retained intron < Epb42-207lncRNA Regulatory Build 121.01Mb 121.02Mb 121.03Mb 121.04Mb Reverse strand 39.18 kb Regulation Legend CTCF Open Chromatin Promoter Promoter Flank Gene Legend Protein Coding merged Ensembl/Havana Ensembl protein coding Non-Protein Coding processed transcript RNA gene Page 8 of 9 https://www.alphaknockout.com Transcript: ENSMUST00000102490 < Epb42-202protein coding Reverse strand 19.18 kb ENSMUSP00000099... Low complexity (Seg) Superfamily Immunoglobulin E-set Papain-like cysteine peptidase superfamily Transglutaminase, C-terminal domain superfamily SMART Transglutaminase-like Pfam Transglutaminase, N-terminal Transglutaminase-like Transglutaminase, C-terminal PROSITE patterns Transglutaminase, active site PIRSF Protein-glutamine gamma-glutamyltransferase, animal PANTHER PTHR11590:SF44 PTHR11590 Gene3D Immunoglobulin-like fold Transglutaminase-like superfamily All sequence SNPs/i..
Recommended publications
  • Identification of the Binding Partners for Hspb2 and Cryab Reveals
    Brigham Young University BYU ScholarsArchive Theses and Dissertations 2013-12-12 Identification of the Binding arP tners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non- Redundant Roles for Small Heat Shock Proteins Kelsey Murphey Langston Brigham Young University - Provo Follow this and additional works at: https://scholarsarchive.byu.edu/etd Part of the Microbiology Commons BYU ScholarsArchive Citation Langston, Kelsey Murphey, "Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non-Redundant Roles for Small Heat Shock Proteins" (2013). Theses and Dissertations. 3822. https://scholarsarchive.byu.edu/etd/3822 This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of BYU ScholarsArchive. For more information, please contact [email protected], [email protected]. Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non-Redundant Roles for Small Heat Shock Proteins Kelsey Langston A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Master of Science Julianne H. Grose, Chair William R. McCleary Brian Poole Department of Microbiology and Molecular Biology Brigham Young University December 2013 Copyright © 2013 Kelsey Langston All Rights Reserved ABSTRACT Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactors and Non-Redundant Roles for Small Heat Shock Proteins Kelsey Langston Department of Microbiology and Molecular Biology, BYU Master of Science Small Heat Shock Proteins (sHSP) are molecular chaperones that play protective roles in cell survival and have been shown to possess chaperone activity.
    [Show full text]
  • Views of the NIH
    CLINICAL EPIDEMIOLOGY www.jasn.org Genetic Variants Associated with Circulating Fibroblast Growth Factor 23 Cassianne Robinson-Cohen ,1 Traci M. Bartz,2 Dongbing Lai,3 T. Alp Ikizler,1 Munro Peacock,4 Erik A. Imel,4 Erin D. Michos,5 Tatiana M. Foroud,3 Kristina Akesson,6,7 Kent D. Taylor,8 Linnea Malmgren,6,7 Kunihiro Matsushita,5,9,10 Maria Nethander,11 Joel Eriksson,12 Claes Ohlsson,12 Daniel Mellström,12 Myles Wolf,13 Osten Ljunggren,14 Fiona McGuigan,6,7 Jerome I. Rotter,8 Magnus Karlsson,6,7 Michael J. Econs,3,4 Joachim H. Ix,15,16 Pamela L. Lutsey,17 Bruce M. Psaty,18,19 Ian H. de Boer ,20 and Bryan R. Kestenbaum 20 Due to the number of contributing authors, the affiliations are listed at the end of this article. ABSTRACT Background Fibroblast growth factor 23 (FGF23), a bone-derived hormone that regulates phosphorus and vitamin D metabolism, contributes to the pathogenesis of mineral and bone disorders in CKD and is an emerging cardiovascular risk factor. Central elements of FGF23 regulation remain incompletely under- stood; genetic variation may help explain interindividual differences. Methods We performed a meta-analysis of genome-wide association studies of circulating FGF23 con- centrations among 16,624 participants of European ancestry from seven cohort studies, excluding par- ticipants with eGFR,30 ml/min per 1.73 m2 to focus on FGF23 under normal conditions. We evaluated the association of single-nucleotide polymorphisms (SNPs) with natural log–transformed FGF23 concentra- tion, adjusted for age, sex, study site, and principal components of ancestry.
    [Show full text]
  • Supplemental Information
    Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig.
    [Show full text]
  • Comprehensive Array CGH of Normal Karyotype Myelodysplastic
    Leukemia (2011) 25, 387–399 & 2011 Macmillan Publishers Limited All rights reserved 0887-6924/11 www.nature.com/leu LEADING ARTICLE Comprehensive array CGH of normal karyotype myelodysplastic syndromes reveals hidden recurrent and individual genomic copy number alterations with prognostic relevance A Thiel1, M Beier1, D Ingenhag1, K Servan1, M Hein1, V Moeller1, B Betz1, B Hildebrandt1, C Evers1,3, U Germing2 and B Royer-Pokora1 1Institute of Human Genetics and Anthropology, Medical Faculty, Heinrich Heine University, Duesseldorf, Germany and 2Department of Hematology, Oncology and Clinical Immunology, Heinrich Heine University, Duesseldorf, Germany About 40% of patients with myelodysplastic syndromes (MDSs) 40–50% of MDS cases have a normal karyotype. MDS patients present with a normal karyotype, and they are facing different with a normal karyotype and low-risk clinical parameters are courses of disease. To advance the biological understanding often assigned into the IPSS low and intermediate-1 risk groups. and to find molecular prognostic markers, we performed a high- resolution oligonucleotide array study of 107 MDS patients In the absence of genetic or biological markers, prognostic (French American British) with a normal karyotype and clinical stratification of these patients is difficult. To better prognosticate follow-up through the Duesseldorf MDS registry. Recurrent these patients, new parameters to identify patients at higher risk hidden deletions overlapping with known cytogenetic aberra- are urgently needed. With the more recently introduced modern tions or sites of known tumor-associated genes were identi- technologies of whole-genome-wide surveys of genetic aberra- fied in 4q24 (TET2, 2x), 5q31.2 (2x), 7q22.1 (3x) and 21q22.12 tions, it is hoped that more insights into the biology of disease (RUNX1, 2x).
    [Show full text]
  • Downloaded from Here
    bioRxiv preprint doi: https://doi.org/10.1101/017566; this version posted November 19, 2015. 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 1 Testing for ancient selection using cross-population allele 2 frequency differentiation 1;∗ 3 Fernando Racimo 4 1 Department of Integrative Biology, University of California, Berkeley, CA, USA 5 ∗ E-mail: [email protected] 6 1 Abstract 7 A powerful way to detect selection in a population is by modeling local allele frequency changes in a 8 particular region of the genome under scenarios of selection and neutrality, and finding which model is 9 most compatible with the data. Chen et al. [2010] developed a composite likelihood method called XP- 10 CLR that uses an outgroup population to detect departures from neutrality which could be compatible 11 with hard or soft sweeps, at linked sites near a beneficial allele. However, this method is most sensitive 12 to recent selection and may miss selective events that happened a long time ago. To overcome this, 13 we developed an extension of XP-CLR that jointly models the behavior of a selected allele in a three- 14 population tree. Our method - called 3P-CLR - outperforms XP-CLR when testing for selection that 15 occurred before two populations split from each other, and can distinguish between those events and 16 events that occurred specifically in each of the populations after the split.
    [Show full text]
  • Download Special Issue
    BioMed Research International Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data Guest Editors: Julia Tzu-Ya Weng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data BioMed Research International Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data Guest Editors: Julia Tzu-Ya Weng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Copyright © 2014 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data,JuliaTzu-YaWeng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Volume2014,ArticleID814092,3pages Evolution of Network Biomarkers from Early to Late Stage Bladder Cancer Samples,Yung-HaoWong, Cheng-Wei Li, and Bor-Sen Chen Volume 2014, Article ID 159078, 23 pages MicroRNA Expression Profiling Altered by Variant Dosage of Radiation Exposure,Kuei-FangLee, Yi-Cheng Chen, Paul Wei-Che Hsu, Ingrid Y. Liu, and Lawrence Shih-Hsin Wu Volume2014,ArticleID456323,10pages EXIA2: Web Server of Accurate and Rapid Protein Catalytic Residue Prediction, Chih-Hao Lu, Chin-Sheng
    [Show full text]
  • Ccndbp1 Is a New Positive Regulator of Skeletal Myogenesis
    © 2016. Published by The Company of Biologists Ltd | Journal of Cell Science (2016) 129, 2767-2777 doi:10.1242/jcs.184234 RESEARCH ARTICLE Ccndbp1 is a new positive regulator of skeletal myogenesis Yan Huang1,2,*, Bohong Chen1,*, Miaoman Ye1, Puping Liang1, Yingnan Zhangfang1, Junjiu Huang1, Mingyao Liu3, Zhou Songyang1,2 and Wenbin Ma1,2,‡ ABSTRACT many tissues (Londhe and Davie, 2011). The DNA-binding Skeletal myogenesis is a multistep process in which basic helix-loop- specificity of E-proteins is dependent on the E-box consensus helix (bHLH) transcription factors, such as MyoD (also known as sequence CANNTG (Cordle et al., 1991; Voronova and Lee, 1994). MyoD1), bind to E-boxes and activate downstream genes. Ccndbp1 The other group of bHLH members, the MyoD family, is is a HLH protein that lacks a DNA-binding region, and its function in specifically expressed in muscle. Proteins of this group are also skeletal myogenesis is currently unknown. We generated Ccndbp1- known as myogenic regulatory factors (MRFs), which include null mice by using CRISPR–Cas9. Notably, in Ccndbp1-null mice, the MyoD (also known as MyoD1) (Tapscott et al., 1988), myogenin cross sectional area of the skeletal tibialis anterior muscle was (Wright et al., 1989), Myf5 (Braun et al., 1989) and MRF4 (Rhodes smaller, and muscle regeneration ability and grip strength were and Konieczny, 1989). Comprising a basic region and two impaired, compared with those of wild type. This phenotype amphipathic helices, the bHLH domain in the MRFs and E- resembled that of myofiber hypotrophy in some human myopathies proteins is required for DNA binding and protein dimerization – or amyoplasia.
    [Show full text]
  • Quantitative Trait Loci Mapping of Macrophage Atherogenic Phenotypes
    QUANTITATIVE TRAIT LOCI MAPPING OF MACROPHAGE ATHEROGENIC PHENOTYPES BRIAN RITCHEY Bachelor of Science Biochemistry John Carroll University May 2009 submitted in partial fulfillment of requirements for the degree DOCTOR OF PHILOSOPHY IN CLINICAL AND BIOANALYTICAL CHEMISTRY at the CLEVELAND STATE UNIVERSITY December 2017 We hereby approve this thesis/dissertation for Brian Ritchey Candidate for the Doctor of Philosophy in Clinical-Bioanalytical Chemistry degree for the Department of Chemistry and the CLEVELAND STATE UNIVERSITY College of Graduate Studies by ______________________________ Date: _________ Dissertation Chairperson, Johnathan D. Smith, PhD Department of Cellular and Molecular Medicine, Cleveland Clinic ______________________________ Date: _________ Dissertation Committee member, David J. Anderson, PhD Department of Chemistry, Cleveland State University ______________________________ Date: _________ Dissertation Committee member, Baochuan Guo, PhD Department of Chemistry, Cleveland State University ______________________________ Date: _________ Dissertation Committee member, Stanley L. Hazen, MD PhD Department of Cellular and Molecular Medicine, Cleveland Clinic ______________________________ Date: _________ Dissertation Committee member, Renliang Zhang, MD PhD Department of Cellular and Molecular Medicine, Cleveland Clinic ______________________________ Date: _________ Dissertation Committee member, Aimin Zhou, PhD Department of Chemistry, Cleveland State University Date of Defense: October 23, 2017 DEDICATION I dedicate this work to my entire family. In particular, my brother Greg Ritchey, and most especially my father Dr. Michael Ritchey, without whose support none of this work would be possible. I am forever grateful to you for your devotion to me and our family. You are an eternal inspiration that will fuel me for the remainder of my life. I am extraordinarily lucky to have grown up in the family I did, which I will never forget.
    [Show full text]
  • 1 Human Cells Contain Myriad Excised Linear Introns With
    bioRxiv preprint doi: https://doi.org/10.1101/2020.09.07.285114; this version posted March 4, 2021. 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. Human cells contain myriad excised linear introns with potential functions in gene regulation and as RNA biomarkers Jun Yao,1 Hengyi Xu,1 Shelby Winans,1 Douglas C. Wu,1,3 Manuel Ares, Jr.,2 and Alan M. Lambowitz1,4 1Institute for Cellular and Molecular Biology and Departments of Molecular Biosciences and Oncology University of Texas at Austin Austin TX 78712 2Department of Molecular, Cell, and Developmental Biology University of California, Santa Cruz Santa Cruz, California 95064 Running Title: Human excised linear intron RNAs 3Present address: Invitae Corporation 4To whom correspondence should be addressed. E-mail: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.09.07.285114; this version posted March 4, 2021. 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. Abstract We used thermostable group II intron reverse transcriptase sequencing (TGIRT-seq), which gives full-length end-to-end sequence reads of structured RNAs, to identify > 8,500 short full- length excised linear intron (FLEXI) RNAs (≤ 300 nt) originating from > 3,500 different genes in human cells and tissues.
    [Show full text]
  • Integrated Bioinformatics Analysis Reveals Novel Key Biomarkers and Potential Candidate Small Molecule Drugs in Gestational Diabetes Mellitus
    bioRxiv preprint doi: https://doi.org/10.1101/2021.03.09.434569; this version posted March 10, 2021. 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. Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus Basavaraj Vastrad1, Chanabasayya Vastrad*2, Anandkumar Tengli3 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India. 3. Department of Pharmaceutical Chemistry, JSS College of Pharmacy, Mysuru and JSS Academy of Higher Education & Research, Mysuru, Karnataka, 570015, India * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2021.03.09.434569; this version posted March 10, 2021. 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 Gestational diabetes mellitus (GDM) is one of the metabolic diseases during pregnancy. The identification of the central molecular mechanisms liable for the disease pathogenesis might lead to the advancement of new therapeutic options. The current investigation aimed to identify central differentially expressed genes (DEGs) in GDM. The transcription profiling by array data (E-MTAB-6418) was obtained from the ArrayExpress database. The DEGs between GDM samples and non GDM samples were analyzed with limma package. Gene ontology (GO) and REACTOME enrichment analysis were performed using ToppGene. Then we constructed the protein-protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING) and module analysis was performed.
    [Show full text]
  • Missense Mutations in the Human Nanophthalmos Gene TMEM98
    bioRxiv preprint doi: https://doi.org/10.1101/513846; this version posted March 23, 2019. 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. 1 Missense Mutations in the Human Nanophthalmos Gene TMEM98 2 Cause Retinal Defects in the Mouse 3 4 Sally H. Cross1*, Lisa Mckie1, Margaret Keighren1, Katrine West1, Caroline Thaung2,3, Tracey 5 Davey4, Dinesh C. Soares1,5, Luis Sanchez-Pulido1 and Ian J. Jackson1 6 1MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University 7 of Edinburgh, Crewe Road, Edinburgh EH4 2XU, United Kingdom 8 2Moorfields Eye Hospital NHS Foundation Trust, 162 City Road, London EC1V 2PD, United 9 Kingdom. 10 3UCL Institute of Ophthalmology, 11-43 Bath Street, London EC1V 9EL, United Kingdom. 11 4Electron Microscopy Research Services, Newcastle University, Newcastle NE2 4HH, United 12 Kingdom. 13 5current address ACS International Ltd., 267 Banbury Road, Oxford OX2 7HT, United 14 Kingdom 15 *corresponding author Email: [email protected] Tel: +44 131 651 8500 16 17 Running Title: Human TMEM98 Nanophthalmos Mutations in the Mouse 18 Grant information: funded by the MRC University Unit award to the MRC Human Genetics 19 Unit 1 bioRxiv preprint doi: https://doi.org/10.1101/513846; this version posted March 23, 2019. 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. 20 ABSTRACT 21 PURPOSE. We previously found a dominant mutation, Rwhs, causing white spots on the 22 retina accompanied by retinal folds.
    [Show full text]
  • A Novel Senescence-Evasion Mechanism Involving Grap2 And
    Published OnlineFirst May 11, 2010; DOI: 10.1158/0008-5472.CAN-09-3791 Published OnlineFirst on May 11, 2010 as 10.1158/0008-5472.CAN-09-3791 Molecular and Cellular Pathobiology Cancer Research A Novel Senescence-Evasion Mechanism Involving Grap2 and Cyclin D Interacting Protein Inactivation by Ras Associated with Diabetes in Cancer Cells under Doxorubicin Treatment Inkyoung Lee1, Seon-Yong Yeom1, Sook-Ja Lee1, Won Ki Kang1,2, and Chaehwa Park1,2 Abstract Ras associated with diabetes (Rad) is a Ras-related GTPase that promotes cell growth by accelerating cell cycle transitions. Rad knockdown induced cell cycle arrest and premature senescence without additional cel- lular stress in multiple cancer cell lines, indicating that Rad expression might be critical for the cell cycle in these cells. To investigate the precise function of Rad in this process, we used human Rad as bait in a yeast two-hybrid screening system and sought Rad-interacting proteins. We identified the Grap2 and cyclin D inter- acting protein (GCIP)/DIP1/CCNDBP1/HHM, a cell cycle–inhibitory molecule, as a binding partner of Rad. Further analyses revealed that Rad binds directly to GCIP in vitro and coimmunoprecipitates with GCIP from cell lysates. Rad translocates GCIP from the nucleus to the cytoplasm, thereby inhibiting the tumor suppressor activity of GCIP, which occurs in the nucleus. Furthermore, in the presence of Rad, GCIP loses its ability to reduce retinoblastoma phosphorylation and inhibit cyclin D1 activity. The function of Rad in transformation is also evidenced by increased telomerase activity and colony formation according to Rad expression level. In vivo tumorigenesis analyses revealed that tumors derived from Rad knockdown cells were significantly smaller than those from control cells (P = 0.0131) and the preestablished tumors are reduced in size after the injection of siRad (P = 0.0064).
    [Show full text]