Mouse Troap Knockout Project (CRISPR/Cas9)

Total Page:16

File Type:pdf, Size:1020Kb

Mouse Troap Knockout Project (CRISPR/Cas9) https://www.alphaknockout.com Mouse Troap Knockout Project (CRISPR/Cas9) Objective: To create a Troap knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Troap gene (NCBI Reference Sequence: NM_001162506 ; Ensembl: ENSMUSG00000032783 ) is located on Mouse chromosome 15. 14 exons are identified, with the ATG start codon in exon 2 and the TGA stop codon in exon 14 (Transcript: ENSMUST00000230054). Exon 4~10 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: Exon 4 starts from about 16.72% of the coding region. Exon 4~10 covers 35.73% of the coding region. The size of effective KO region: ~3963 bp. The KO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 4 5 6 7 8 9 10 14 Legends Exon of mouse Troap Knockout region Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 1490 bp section upstream of Exon 4 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 584 bp section downstream of Exon 10 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 8 https://www.alphaknockout.com Overview of the GC Content Distribution (up) Window size: 300 bp Sequence 12 Summary: Full Length(1490bp) | A(23.69% 353) | C(24.03% 358) | T(29.66% 442) | G(22.62% 337) Note: The 1490 bp section upstream of Exon 4 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(584bp) | A(21.75% 127) | C(25.51% 149) | T(29.62% 173) | G(23.12% 135) Note: The 584 bp section downstream of Exon 10 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 8 https://www.alphaknockout.com BLAT Search Results (up) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN -------------------------------------------------------------------------------------------------------------- browser details YourSeq 1490 1 1490 1490 100.0% chr15 + 99075799 99077288 1490 browser details YourSeq 300 417 765 1490 96.4% chr9 + 73062414 73062969 556 browser details YourSeq 285 415 766 1490 93.9% chr13 - 74516324 74516736 413 browser details YourSeq 278 421 755 1490 94.6% chr4 + 37500962 37501456 495 browser details YourSeq 264 421 758 1490 93.5% chr4 - 149490440 149491039 600 browser details YourSeq 262 415 729 1490 95.2% chr11 + 115735335 115735972 638 browser details YourSeq 257 415 717 1490 94.8% chr1 - 136702002 136702405 404 browser details YourSeq 235 415 709 1490 91.9% chr5 - 139470229 139470500 272 browser details YourSeq 219 418 724 1490 95.9% chr5 - 23730677 23731172 496 browser details YourSeq 205 417 689 1490 88.9% chr12 + 102444689 102444939 251 browser details YourSeq 201 169 594 1490 91.9% chr4 - 155079076 155079490 415 browser details YourSeq 199 418 739 1490 93.5% chr1 - 135270857 135271183 327 browser details YourSeq 198 418 906 1490 92.7% chr11 + 62673852 62674424 573 browser details YourSeq 195 415 957 1490 88.8% chr16 - 94229979 94230407 429 browser details YourSeq 195 182 613 1490 97.2% chrX + 48595519 48596139 621 browser details YourSeq 192 418 956 1490 86.5% chr4 + 149190446 149190854 409 browser details YourSeq 191 158 594 1490 94.5% chr8 + 111986386 111986865 480 browser details YourSeq 190 421 951 1490 87.3% chr19 + 18724733 18725108 376 browser details YourSeq 188 418 756 1490 94.8% chr11 - 97111417 97112052 636 browser details YourSeq 188 415 691 1490 96.6% chr7 + 30128911 30129560 650 Note: The 1490 bp section upstream of Exon 4 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 584 1 584 584 100.0% chr15 + 99081252 99081835 584 browser details YourSeq 151 181 343 584 97.6% chr17 - 24683614 25031257 347644 browser details YourSeq 140 181 343 584 91.6% chr10 - 110524763 110524918 156 browser details YourSeq 136 186 340 584 91.4% chr3 + 95788783 95788933 151 browser details YourSeq 135 195 343 584 96.6% chr11 + 12436689 12437016 328 browser details YourSeq 133 187 350 584 91.6% chr11 - 74196933 74197094 162 browser details YourSeq 131 178 343 584 93.5% chr2 + 28504011 28634549 130539 browser details YourSeq 130 144 341 584 90.6% chr14 - 54655119 54655467 349 browser details YourSeq 130 190 340 584 90.6% chr13 + 41525034 41525171 138 browser details YourSeq 130 190 343 584 90.0% chr11 + 106066871 106067020 150 browser details YourSeq 129 181 318 584 97.1% chr2 - 163092903 163093054 152 browser details YourSeq 128 193 339 584 91.5% chr5 - 150837706 150837847 142 browser details YourSeq 128 204 344 584 93.4% chr5 - 123893835 123893971 137 browser details YourSeq 128 195 346 584 94.5% chr18 - 58853070 58853300 231 browser details YourSeq 128 192 340 584 90.2% chr15 + 8491735 8491877 143 browser details YourSeq 127 195 343 584 95.1% chr12 - 55243401 55243552 152 browser details YourSeq 127 168 341 584 95.1% chr2 + 25078240 25078441 202 browser details YourSeq 126 195 343 584 89.6% chrX - 20750551 20750694 144 browser details YourSeq 126 188 343 584 90.9% chr5 - 105560269 105560425 157 browser details YourSeq 126 197 341 584 90.8% chr18 - 36843637 36843777 141 Note: The 584 bp section downstream of Exon 10 is BLAT searched against the genome. No significant similarity is found. Page 5 of 8 https://www.alphaknockout.com Gene and protein information: Troap trophinin associated protein [ Mus musculus (house mouse) ] Gene ID: 78733, updated on 12-Aug-2019 Gene summary Official Symbol Troap provided by MGI Official Full Name trophinin associated protein provided by MGI Primary source MGI:MGI:1925983 See related Ensembl:ENSMUSG00000032783 Gene type protein coding RefSeq status VALIDATED Organism Mus musculus Lineage Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Glires; Rodentia; Myomorpha; Muroidea; Muridae; Murinae; Mus; Mus Also known as tastin; AW476063; E130301L11Rik Expression Broad expression in limb E14.5 (RPKM 9.0), CNS E11.5 (RPKM 8.9) and 20 other tissues See more Orthologs human all Genomic context Location: 15; 15 F1 See Troap in Genome Data Viewer Exon count: 15 Annotation release Status Assembly Chr Location 108 current GRCm38.p6 (GCF_000001635.26) 15 NC_000081.6 (99074973..99083409) Build 37.2 previous assembly MGSCv37 (GCF_000001635.18) 15 NC_000081.5 (98905404..98913840) Chromosome 15 - NC_000081.6 Page 6 of 8 https://www.alphaknockout.com Transcript information: This gene has 6 transcripts Gene: Troap ENSMUSG00000032783 Description trophinin associated protein [Source:MGI Symbol;Acc:MGI:1925983] Gene Synonyms E130301L11Rik, tastin Location Chromosome 15: 99,074,575-99,083,409 forward strand. GRCm38:CM001008.2 About this gene This gene has 6 transcripts (splice variants), 92 orthologues and is a member of 1 Ensembl protein family. Transcripts Name Transcript ID bp Protein Translation ID Biotype CCDS UniProt Flags Troap-204 ENSMUST00000230054.1 2639 668aa ENSMUSP00000155404.1 Protein coding CCDS57008 B7ZNG4 GENCODE basic APPRIS P1 Troap-201 ENSMUST00000039665.7 2255 668aa ENSMUSP00000035389.6 Protein coding CCDS57008 B7ZNG4 TSL:1 GENCODE basic APPRIS P1 Troap-203 ENSMUST00000229740.1 865 No protein - Retained intron - - - Troap-205 ENSMUST00000230311.1 819 No protein - Retained intron - - - Troap-206 ENSMUST00000230868.1 714 No protein - Retained intron - - - Troap-202 ENSMUST00000229224.1 451 No protein - Retained intron - - - 28.84 kb Forward strand 99.07Mb 99.08Mb 99.09Mb Genes (Comprehensive set... Troap-204 >protein coding Dnajc22-202 >lncRNA Troap-201 >protein coding Troap-206 >retained intron Mir6960-201 >miRNA Troap-205 >retained intron Troap-203 >retained intron Troap-202 >retained intron Contigs < AC157610.2 Genes < Gm34284-201lncRNA < C1ql4-201protein coding (Comprehensive set... Regulatory Build 99.07Mb 99.08Mb 99.09Mb Reverse strand 28.84 kb Regulation Legend CTCF Open Chromatin Promoter Promoter Flank Transcription Factor Binding Site Gene Legend Protein Coding merged Ensembl/Havana Ensembl protein coding Non-Protein Coding RNA gene processed transcript Page 7 of 8 https://www.alphaknockout.com Transcript: ENSMUST00000230054 8.84 kb Forward strand Troap-204 >protein coding ENSMUSP00000155... MobiDB lite Low complexity (Seg) PANTHER Tastin All sequence SNPs/i... Sequence variants (dbSNP and all other sources) Variant Legend inframe insertion inframe deletion missense variant synonymous variant Scale bar 0 60 120 180 240 300 360 420 480 540 600 668 We wish to acknowledge the following valuable scientific information resources: Ensembl, MGI, NCBI, UCSC. Page 8 of 8.
Recommended publications
  • 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.
    [Show full text]
  • Screening and Identification of Hub Genes in Bladder Cancer by Bioinformatics Analysis and KIF11 Is a Potential Prognostic Biomarker
    ONCOLOGY LETTERS 21: 205, 2021 Screening and identification of hub genes in bladder cancer by bioinformatics analysis and KIF11 is a potential prognostic biomarker XIAO‑CONG MO1,2*, ZI‑TONG ZHANG1,3*, MENG‑JIA SONG1,2, ZI‑QI ZHOU1,2, JIAN‑XIONG ZENG1,2, YU‑FEI DU1,2, FENG‑ZE SUN1,2, JIE‑YING YANG1,2, JUN‑YI HE1,2, YUE HUANG1,2, JIAN‑CHUAN XIA1,2 and DE‑SHENG WENG1,2 1State Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine; 2Department of Biotherapy, Sun Yat‑Sen University Cancer Center; 3Department of Radiation Oncology, Sun Yat‑Sen University Cancer Center, Guangzhou, Guangdong 510060, P.R. China Received July 31, 2020; Accepted December 18, 2020 DOI: 10.3892/ol.2021.12466 Abstract. Bladder cancer (BC) is the ninth most common immunohistochemistry and western blotting. In summary, lethal malignancy worldwide. Great efforts have been devoted KIF11 was significantly upregulated in BC and might act as to clarify the pathogenesis of BC, but the underlying molecular a potential prognostic biomarker. The present identification mechanisms remain unclear. To screen for the genes associated of DEGs and hub genes in BC may provide novel insight for with the progression and carcinogenesis of BC, three datasets investigating the molecular mechanisms of BC. were obtained from the Gene Expression Omnibus. A total of 37 tumor and 16 non‑cancerous samples were analyzed to Introduction identify differentially expressed genes (DEGs). Subsequently, 141 genes were identified, including 55 upregulated and Bladder cancer (BC) is the ninth most common malignancy 86 downregulated genes. The protein‑protein interaction worldwide with substantial morbidity and mortality.
    [Show full text]
  • Supplementary Data
    SUPPLEMENTARY DATA A cyclin D1-dependent transcriptional program predicts clinical outcome in mantle cell lymphoma Santiago Demajo et al. 1 SUPPLEMENTARY DATA INDEX Supplementary Methods p. 3 Supplementary References p. 8 Supplementary Tables (S1 to S5) p. 9 Supplementary Figures (S1 to S15) p. 17 2 SUPPLEMENTARY METHODS Western blot, immunoprecipitation, and qRT-PCR Western blot (WB) analysis was performed as previously described (1), using cyclin D1 (Santa Cruz Biotechnology, sc-753, RRID:AB_2070433) and tubulin (Sigma-Aldrich, T5168, RRID:AB_477579) antibodies. Co-immunoprecipitation assays were performed as described before (2), using cyclin D1 antibody (Santa Cruz Biotechnology, sc-8396, RRID:AB_627344) or control IgG (Santa Cruz Biotechnology, sc-2025, RRID:AB_737182) followed by protein G- magnetic beads (Invitrogen) incubation and elution with Glycine 100mM pH=2.5. Co-IP experiments were performed within five weeks after cell thawing. Cyclin D1 (Santa Cruz Biotechnology, sc-753), E2F4 (Bethyl, A302-134A, RRID:AB_1720353), FOXM1 (Santa Cruz Biotechnology, sc-502, RRID:AB_631523), and CBP (Santa Cruz Biotechnology, sc-7300, RRID:AB_626817) antibodies were used for WB detection. In figure 1A and supplementary figure S2A, the same blot was probed with cyclin D1 and tubulin antibodies by cutting the membrane. In figure 2H, cyclin D1 and CBP blots correspond to the same membrane while E2F4 and FOXM1 blots correspond to an independent membrane. Image acquisition was performed with ImageQuant LAS 4000 mini (GE Healthcare). Image processing and quantification were performed with Multi Gauge software (Fujifilm). For qRT-PCR analysis, cDNA was generated from 1 µg RNA with qScript cDNA Synthesis kit (Quantabio). qRT–PCR reaction was performed using SYBR green (Roche).
    [Show full text]
  • TROAP Switches DYRK1 Activity to Drive Hepatocellular Carcinoma
    Li et al. Cell Death and Disease (2021) 12:125 https://doi.org/10.1038/s41419-021-03422-3 Cell Death & Disease ARTICLE Open Access TROAP switches DYRK1 activity to drive hepatocellular carcinoma progression Lei Li1,2,3,Jia-RuWei4, Ye Song5,ShuoFang6,YanyuDu6,ZhuoLi1, Ting-Ting Zeng1,Ying-HuiZhu 1, Yan Li 1 and Xin-Yuan Guan 1,2,3 Abstract Hepatocellular carcinoma (HCC) is one of the common malignancy and lacks effective therapeutic targets. Here, we demonstrated that ectopic expression of trophinin-associated protein (TROAP) dramatically drove HCC cell growth assessed by foci formation in monolayer culture, colony formation in soft agar and orthotopic liver transplantation in nude mice. Inversely, silencing TROAP expression with short-hairpin RNA attenuated the malignant proliferation of HCC cells in vitro and in vivo. Next, mechanistic investigation revealed that TROAP directly bound to dual specificity tyrosine phosphorylation regulated kinase 1A/B (DYRK1A/B), resulting in the cytoplasmic retention of proteins DYRK1A/B and promoting cell cycle process via activation of Akt/GSK-3β signaling. Combination of cisplatin with an inhibitor of DYRK1 AZ191 effectively inhibited tumor growth in mouse model for HCC cells with high level of TROAP. Clinically, TROAP was significantly upregulated by miR-142-5p in HCC tissues, which predicted the poor survival of patients with HCC. Therefore, TROAP/DYRK1/Akt axis may be a promising therapeutic target and prognostic indicator for patients with HCC. 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Introduction 19952. It as a cytoplasmic protein is composed of 778 Hepatocellular carcinoma (HCC) is the most common amino acid residues and contains potential phosphoryla- pathological type of liver cancer, accounting for 75%–85% tion sites for protein kinases.
    [Show full text]
  • Genome-Wide Transcriptional Sequencing Identifies Novel Mutations in Metabolic Genes in Human Hepatocellular Carcinoma DAOUD M
    CANCER GENOMICS & PROTEOMICS 11 : 1-12 (2014) Genome-wide Transcriptional Sequencing Identifies Novel Mutations in Metabolic Genes in Human Hepatocellular Carcinoma DAOUD M. MEERZAMAN 1,2 , CHUNHUA YAN 1, QING-RONG CHEN 1, MICHAEL N. EDMONSON 1, CARL F. SCHAEFER 1, ROBERT J. CLIFFORD 2, BARBARA K. DUNN 3, LI DONG 2, RICHARD P. FINNEY 1, CONSTANCE M. CULTRARO 2, YING HU1, ZHIHUI YANG 2, CU V. NGUYEN 1, JENNY M. KELLEY 2, SHUANG CAI 2, HONGEN ZHANG 2, JINGHUI ZHANG 1,4 , REBECCA WILSON 2, LAUREN MESSMER 2, YOUNG-HWA CHUNG 5, JEONG A. KIM 5, NEUNG HWA PARK 6, MYUNG-SOO LYU 6, IL HAN SONG 7, GEORGE KOMATSOULIS 1 and KENNETH H. BUETOW 1,2 1Center for Bioinformatics and Information Technology, National Cancer Institute, Rockville, MD, U.S.A.; 2Laboratory of Population Genetics, National Cancer Institute, National Cancer Institute, Bethesda, MD, U.S.A.; 3Basic Prevention Science Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, U.S.A; 4Department of Biotechnology/Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN, U.S.A.; 5Department of Internal Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea; 6Department of Internal Medicine, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan, Korea; 7Department of Internal Medicine, College of Medicine, Dankook University, Cheon-An, Korea Abstract . We report on next-generation transcriptome Worldwide, liver cancer is the fifth most common cancer and sequencing results of three human hepatocellular carcinoma the third most common cause of cancer-related mortality (1). tumor/tumor-adjacent pairs.
    [Show full text]
  • 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.
    [Show full text]
  • Transcriptome Profiling of the Newborn Mouse Lung Response to Acute Ozone Exposure
    toxicological sciences 138(1), 175–190 2014 doi:10.1093/toxsci/kft276 Advance Access publication December 12, 2013 Transcriptome Profiling of the Newborn Mouse Lung Response to Acute Ozone Exposure Kelsa Gabehart,* Kelly A. Correll,* Jing Yang,* Maureen L. Collins,* Joan E. Loader,*,1, Sonia Leach,† Carl W. White,*,1 and Azzeddine Dakhama*,2 *Department of Pediatrics and †Department of Medicine, National Jewish Health, Denver, Colorado 80206 1Present address: Department of Pediatrics, Children’s Hospital, University of Colorado Denver-Anschutz Medical Campus, Aurora, Colorado 80206. 2To whom correspondence should be addressed at Department of Pediatrics, National Jewish Health, 1400 Jackson Street, Denver, CO 80206. Fax: (303) 270-2182. E-mail: [email protected]. Received August 21, 2013; accepted December 3, 2013 respiratory health, including alterations in the structure of the Ozone pollution is associated with adverse effects on respira- airway epithelium, increased sensitivity to inhaled allergens, tory health in adults and children but its effects on the neonatal increased airway inflammation, and altered lung function (Mar lung remain unknown. This study was carried out to define the and Koenig, 2009; Romieu et al., 2002; Strickland et al., 2010). effect of acute ozone exposure on the neonatal lung and to pro- file the transcriptome response. Newborn mice were exposed to Young children are particularly vulnerable to developing ozone or filtered air for 3 h. Total RNA was isolated from lung adverse respiratory health effects from O3 exposure due to higher tissues at 6 and 24 h after exposure and was subjected to micro- ventilation rates, potentially leading to higher doses of inhaled O3 array gene expression analysis.
    [Show full text]
  • Exploring the Human Genome with Functional Maps Curtis Huttenhower1,2,†, Erin M
    Downloaded from genome.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Exploring the human genome with functional maps Curtis Huttenhower1,2,†, Erin M. Haley3,†, Matthew A. Hibbs4, Vanessa Dumeaux5, Daniel R. Barrett1, Hilary A. Coller3,‡, Olga G. Troyanskaya1,2,‡,* 1 Department of Computer Science, Princeton University, Princeton, NJ, 08540 2 Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, 08544 3 Department of Molecular Biology, Princeton University, Princeton, NJ, 08544 4 Jackson Laboratory, Bar Harbor, ME, 04609 5 Institute of Community Medicine, Tromsø University, Tromsø, Norway * To whom correspondence should be addressed: [email protected], phone 609-258-7014, fax 609-258-7599 † These authors contributed equally to this work. ‡ Co-principle investigators. Running title: Exploring the human genome with functional maps Manuscript type: Resource Keywords: human data integration, functional interaction network, computational predictions, disease and process associations 1 Downloaded from genome.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract biological truths: the size of the human genome, the complexity of human tissue types and regulatory Human genomic data of many types are readily mechanisms, and the sheer amount of available data all available, but the complexity and scale of human contribute to the analytical complexity of understanding molecular biology make it difficult to integrate this body human functional genomics. of data, understand it from a systems level, and apply it In order to take advantage of large collections of to the study of specific pathways or genetic disorders. genomic data, they must be integrated, summarized, An investigator could best explore a particular protein, and presented in a biologically informative manner.
    [Show full text]
  • Dual-Specificity, Tyrosine Phosphorylation-Regulated Kinases
    International Journal of Molecular Sciences Review Dual-Specificity, Tyrosine Phosphorylation-Regulated Kinases (DYRKs) and cdc2-Like Kinases (CLKs) in Human Disease, an Overview Mattias F. Lindberg and Laurent Meijer * Perha Pharmaceuticals, Perharidy Peninsula, 29680 Roscoff, France; [email protected] * Correspondence: [email protected] Abstract: Dual-specificity tyrosine phosphorylation-regulated kinases (DYRK1A, 1B, 2-4) and cdc2- like kinases (CLK1-4) belong to the CMGC group of serine/threonine kinases. These protein ki- nases are involved in multiple cellular functions, including intracellular signaling, mRNA splicing, chromatin transcription, DNA damage repair, cell survival, cell cycle control, differentiation, ho- mocysteine/methionine/folate regulation, body temperature regulation, endocytosis, neuronal development, synaptic plasticity, etc. Abnormal expression and/or activity of some of these kinases, DYRK1A in particular, is seen in many human nervous system diseases, such as cognitive deficits associated with Down syndrome, Alzheimer’s disease and related diseases, tauopathies, demen- tia, Pick’s disease, Parkinson’s disease and other neurodegenerative diseases, Phelan-McDermid syndrome, autism, and CDKL5 deficiency disorder. DYRKs and CLKs are also involved in dia- betes, abnormal folate/methionine metabolism, osteoarthritis, several solid cancers (glioblastoma, breast, and pancreatic cancers) and leukemias (acute lymphoblastic leukemia, acute megakaryoblas- Citation: Lindberg, M.F.; Meijer, L. tic leukemia), viral infections (influenza, HIV-1, HCMV, HCV, CMV, HPV), as well as infections Dual-Specificity, Tyrosine caused by unicellular parasites (Leishmania, Trypanosoma, Plasmodium). This variety of pathological Phosphorylation-Regulated Kinases implications calls for (1) a better understanding of the regulations and substrates of DYRKs and (DYRKs) and cdc2-Like Kinases CLKs and (2) the development of potent and selective inhibitors of these kinases and their evaluation (CLKs) in Human Disease, an as therapeutic drugs.
    [Show full text]
  • US 2009/0270267 A1 Akiyama Et Al
    US 20090270267A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2009/0270267 A1 Akiyama et al. (43) Pub. Date: Oct. 29, 2009 (54) COMPOSITION AND METHOD FOR (86). PCT No.: PCT/UP2006/309.177 DAGNOSINGESOPHAGEAL CANCER AND METASTASS OF ESOPHAGEAL CANCER S371 (c)(1), (2), (4) Date: Jan. 8, 2008 (75) Inventors: Hideo Akiyama, Kanagawa (JP); O O Satoko Kozono, Kanagawa (JP); (30) Foreign Application Priority Data 6A yet S. (JP): (JP): May 2, 2005 (JP) ................................. 2005-134530 Sam Nomura, Kanagaway): Sep. 13, 2005 (JP) ................................. 2005-265645 Hitoshi Nobumasa, Shiga (JP); Sep. 13, 2005 (JP) 2005-265678 Yoshinori Tanaka, Kanagawa (JP); O. l. 4UUC ) . Shiori Tomoda, Tokyo (JP); Publication Classification Yutaka Shimada, Kyoto (JP); Gozoh Tsujimoto, Kyoto (JP) (51) Int. Cl. C40B 30/04 (2006.01) Correspondence Address: CI2O I/68 (2006.01) BRCH STEWARTKOLASCH & BRCH GOIN 33/53 (2006.01) PO BOX 747 C40B 40/08 (2006.01) FALLS CHURCH, VA 22040-0747 (US) (52) U.S. Cl. ..................... 506/9; 435/6: 435/7.1:506/17 (73) Assignees: TORAY INDUSTRIES, INC., (57) ABSTRACT Tokyo (JP); Kyoto University, This invention relates to a composition, kit, or DNA chip Kyoto-shi (JP) comprising polynucleotides and antibodies as probes for detecting, determining, or predicting the presence or metasta (21) Appl. No.: 11/919,679 sis of esophageal cancer, and to a method for detecting, deter mining, or predicting the presence or metastasis of esoph (22) PCT Filed: May 2, 2006 ageal cancer using the same. Patent Application Publication Oct. 29, 2009 Sheet 1 of 5 US 2009/0270267 A1 Fig.
    [Show full text]
  • Dual RNA-Seq Analysis of Mus Musculus and Leishmania Donovani Transcriptomes
    Dual RNA-Seq analysis of Mus musculus and Leishmania donovani transcriptomes ALEXANDRA HART MASTER OF SCIENCE BY RESEARCH UNIVERSITY OF YORK BIOLOGY DECEMBER 2017 ABSTRACT Parasitic protozoa of the genus Leishmania cause a spectrum of disease, affecting 12 million people worldwide. This project aimed to investigate the effect of Leishmania donovani infection on the gene expression of healthy/WT (Black 6) and immunocompromised (RAG2KO) mice. Differences in the gene expression of parasites in inoculum and tissue were also elucidated. WT and RAG mice were infected using an L. donovani inoculum, and were euthanised after 28 days. Harvested spleens (and the inoculum) were used to generate RNA samples, from which mRNA was isolated and purified. Transcriptome data was generated using dual RNA-Seq approaches from the mRNA samples. After appropriate pre-processing, data underwent a number of bioinformatic analyses to explore differential gene expression, such as Gene Ontology, Gene Set Enrichment, and KEGG Pathway analysis. Comparison of different mouse spleen transcriptomes revealed that even in uninfected mice, WT mice more highly express genes related to immunoglobulins when compared with their immunocompromised counterparts. Healthy mice were found to react to infection through the induction of inflammatory response, and the production of NOX generating species. RAG mice still upregulated immunoglobulin-related genes in response to infection, despite their inability to generate antibodies, T-cells, and B-cells. However, RAG modulation of haeme and iron metabolism may contribute to defence against the parasites despite a lack of acquired immunity. Differences in the amastin, the key glycoprotein on the surface on intracellular-stage parasites, are apparent between the inoculum and tissue parasites, which may reflect microenvironment adaptation.
    [Show full text]
  • Leveraging Models of Cell Regulation and GWAS Data in Integrative Network-Based Association Studies
    PERSPECTIVE Leveraging models of cell regulation and GWAS data in integrative network-based association studies Andrea Califano1–3,11, Atul J Butte4,5, Stephen Friend6, Trey Ideker7–9 & Eric Schadt10,11 Over the last decade, the genome-wide study of both heritable and straightforward: within the space of all possible genetic and epigenetic somatic human variability has gone from a theoretical concept to a variants, those contributing to a specific trait or disease likely have broadly implemented, practical reality, covering the entire spectrum some coalescent properties, allowing their effect to be functionally of human disease. Although several findings have emerged from these canalized via the cell communication and cell regulatory machin- studies1, the results of genome-wide association studies (GWAS) have ery that allows distinct cells to interact and regulates their behavior. been mostly sobering. For instance, although several genes showing Notably, contrary to random networks, whose output is essentially medium-to-high penetrance within heritable traits were identified by unconstrained, regulatory networks produced by adaptation to spe- these approaches, the majority of heritable genetic risk factors for most cific fitness landscapes are optimized to produce only a finite number common diseases remain elusive2–7. Additionally, due to impractical of well-defined outcomes as a function of a very large number of exog- requirements for cohort size8 and lack of methodologies to maximize enous and endogenous signals. Thus, if a comprehensive and accurate power for such detections, few epistatic interactions and low-pen- map of all intra- and intercellular molecular interactions were avail- etrance variants have been identified9. At the opposite end of the able, then genetic and epigenetic events implicated in a specific trait or germline versus somatic event spectrum, considering that tumor cells disease should cluster in subnetworks of closely interacting genes.
    [Show full text]