Mouse Zfyve28 Knockout Project (CRISPR/Cas9)

Total Page:16

File Type:pdf, Size:1020Kb

Mouse Zfyve28 Knockout Project (CRISPR/Cas9) https://www.alphaknockout.com Mouse Zfyve28 Knockout Project (CRISPR/Cas9) Objective: To create a Zfyve28 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Zfyve28 gene (NCBI Reference Sequence: NM_001015039 ; Ensembl: ENSMUSG00000037224 ) is located on Mouse chromosome 5. 13 exons are identified, with the ATG start codon in exon 1 and the TGA stop codon in exon 13 (Transcript: ENSMUST00000094868). Exon 2~4 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: Mice homozygous for a knock-out allele exhibit normal kidney morphology and function. Exon 2 starts from about 1.47% of the coding region. Exon 2~4 covers 17.75% of the coding region. The size of effective KO region: ~9029 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 2 3 4 13 Legends Exon of mouse Zfyve28 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 2000 bp section upstream of Exon 2 is aligned with itself to determine if there are tandem repeats. Tandem repeats are found in the dot plot matrix. The gRNA site is selected outside of these tandem repeats. Overview of the Dot Plot (down) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 890 bp section downstream 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. Page 3 of 8 https://www.alphaknockout.com Overview of the GC Content Distribution (up) Window size: 300 bp Sequence 12 Summary: Full Length(2000bp) | A(25.65% 513) | C(21.1% 422) | T(25.3% 506) | G(27.95% 559) Note: The 2000 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(890bp) | A(22.7% 202) | C(20.9% 186) | T(24.38% 217) | G(32.02% 285) Note: The 890 bp section downstream 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. 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 2000 1 2000 2000 100.0% chr5 - 34243314 34245313 2000 browser details YourSeq 135 573 733 2000 92.0% chr10 - 41671538 41671693 156 browser details YourSeq 133 558 733 2000 95.4% chr10 - 93468193 93468393 201 browser details YourSeq 130 571 735 2000 95.1% chr17 + 89776004 89776223 220 browser details YourSeq 129 575 733 2000 88.2% chr4 - 134885624 134885768 145 browser details YourSeq 129 574 733 2000 90.3% chr4 + 76994986 76995139 154 browser details YourSeq 126 574 741 2000 94.8% chr11 + 18527426 18527619 194 browser details YourSeq 125 575 722 2000 92.7% chr5 - 61092735 61092877 143 browser details YourSeq 124 575 737 2000 90.5% chr5 + 50660651 50660807 157 browser details YourSeq 124 583 733 2000 95.2% chr4 + 141128856 141129218 363 browser details YourSeq 123 573 732 2000 88.3% chr18 - 80792734 80792873 140 browser details YourSeq 123 574 796 2000 94.6% chr12 + 72491859 72492475 617 browser details YourSeq 122 573 726 2000 89.7% chr6 - 140660037 140660181 145 browser details YourSeq 122 558 737 2000 83.4% chr3 + 13130937 13131102 166 browser details YourSeq 121 554 732 2000 92.4% chr8 + 111253069 111253581 513 browser details YourSeq 121 575 725 2000 88.5% chr18 + 79899187 79899317 131 browser details YourSeq 120 575 726 2000 88.6% chr7 - 39833780 39833917 138 browser details YourSeq 120 574 733 2000 87.8% chr2 - 97526508 97526656 149 browser details YourSeq 120 571 708 2000 93.0% chr15 - 28767531 28767661 131 browser details YourSeq 120 558 709 2000 97.1% chr10 - 93468168 93468417 250 Note: The 2000 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 890 1 890 890 100.0% chr5 - 34233395 34234284 890 browser details YourSeq 27 648 690 890 76.7% chr10 - 75280471 75280506 36 browser details YourSeq 25 802 831 890 82.2% chr11 + 115935861 115935888 28 browser details YourSeq 22 386 409 890 95.9% chr14 + 64191281 64191304 24 browser details YourSeq 21 643 663 890 100.0% chr11 - 106180468 106180488 21 browser details YourSeq 21 845 865 890 100.0% chr9 + 123399931 123399951 21 browser details YourSeq 20 674 693 890 100.0% chr1 - 40106323 40106342 20 browser details YourSeq 20 161 180 890 100.0% chr14 + 68325877 68325896 20 Note: The 890 bp section downstream of Exon 4 is BLAT searched against the genome. No significant similarity is found. Page 5 of 8 https://www.alphaknockout.com Gene and protein information: Zfyve28 zinc finger, FYVE domain containing 28 [ Mus musculus (house mouse) ] Gene ID: 231125, updated on 12-Aug-2019 Gene summary Official Symbol Zfyve28 provided by MGI Official Full Name zinc finger, FYVE domain containing 28 provided by MGI Primary source MGI:MGI:2684992 See related Ensembl:ENSMUSG00000037224 Gene type protein coding RefSeq status PROVISIONAL Organism Mus musculus Lineage Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Glires; Rodentia; Myomorpha; Muroidea; Muridae; Murinae; Mus; Mus Also known as Gm146; mKIAA1643; 9630058O20Rik Expression Biased expression in cerebellum adult (RPKM 4.9), cortex adult (RPKM 3.0) and 12 other tissues See more Orthologs human all Genomic context Location: 5; 5 B2 See Zfyve28 in Genome Data Viewer Exon count: 21 Annotation release Status Assembly Chr Location 108 current GRCm38.p6 (GCF_000001635.26) 5 NC_000071.6 (34194893..34288368, complement) Build 37.2 previous assembly MGSCv37 (GCF_000001635.18) 5 NC_000071.5 (34537543..34630973, complement) Chromosome 5 - NC_000071.6 Page 6 of 8 https://www.alphaknockout.com Transcript information: This gene has 6 transcripts Gene: Zfyve28 ENSMUSG00000037224 Description zinc finger, FYVE domain containing 28 [Source:MGI Symbol;Acc:MGI:2684992] Gene Synonyms 9630058O20Rik Location Chromosome 5: 34,194,893-34,288,449 reverse strand. GRCm38:CM000998.2 About this gene This gene has 6 transcripts (splice variants), 201 orthologues, 12 paralogues, is a member of 1 Ensembl protein family and is associated with 12 phenotypes. Transcripts Name Transcript ID bp Protein Translation ID Biotype CCDS UniProt Flags Zfyve28-201 ENSMUST00000094868.9 3983 905aa ENSMUSP00000092464.3 Protein coding CCDS39068 Q6ZPK7 TSL:1 GENCODE basic APPRIS P1 Zfyve28-202 ENSMUST00000114368.1 712 137aa ENSMUSP00000110008.1 Protein coding - D3Z3F0 CDS 3' incomplete TSL:3 Zfyve28-204 ENSMUST00000114370.7 1499 No protein - Retained intron - - TSL:1 Zfyve28-206 ENSMUST00000132104.1 666 No protein - Retained intron - - TSL:3 Zfyve28-203 ENSMUST00000114369.2 1086 No protein - lncRNA - - TSL:5 Zfyve28-205 ENSMUST00000130435.4 650 No protein - lncRNA - - TSL:3 113.56 kb Forward strand 34.20Mb 34.22Mb 34.24Mb 34.26Mb 34.28Mb Genes Gm42848-201 >lncRNA Cfap99-201 >protein coding (Comprehensive set... Contigs < AC104889.10 Genes < Mxd4-201protein coding < Gm15513-201lncRNA< Zfyve28-203lncRNA (Comprehensive set... < Mxd4-202protein coding < Zfyve28-206retained intro<n Zfyve28-202protein coding < Zfyve28-201protein coding < Zfyve28-205lncRNA < Zfyve28-204retained intron Regulatory Build 34.20Mb 34.22Mb 34.24Mb 34.26Mb 34.28Mb Reverse strand 113.56 kb Regulation Legend CTCF Enhancer 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: ENSMUST00000094868 < Zfyve28-201protein coding Reverse strand 93.43 kb ENSMUSP00000092... MobiDB lite Low complexity (Seg) Coiled-coils (Ncoils) Superfamily Zinc finger, FYVE/PHD-type SMART FYVE zinc finger Pfam FYVE zinc finger PROSITE profiles Zinc finger, FYVE-related PANTHER PTHR46465 Gene3D Zinc finger, RING/FYVE/PHD-type CDD cd15731 All sequence SNPs/i... Sequence variants (dbSNP and all other sources) Variant Legend missense variant synonymous variant Scale bar 0 80 160 240 320 400 480 560 640 720 800 905 We wish to acknowledge the following valuable scientific information resources: Ensembl, MGI, NCBI, UCSC. Page 8 of 8.
Recommended publications
  • Cytogenomic SNP Microarray - Fetal ARUP Test Code 2002366 Maternal Contamination Study Fetal Spec Fetal Cells
    Patient Report |FINAL Client: Example Client ABC123 Patient: Patient, Example 123 Test Drive Salt Lake City, UT 84108 DOB 2/13/1987 UNITED STATES Gender: Female Patient Identifiers: 01234567890ABCD, 012345 Physician: Doctor, Example Visit Number (FIN): 01234567890ABCD Collection Date: 00/00/0000 00:00 Cytogenomic SNP Microarray - Fetal ARUP test code 2002366 Maternal Contamination Study Fetal Spec Fetal Cells Single fetal genotype present; no maternal cells present. Fetal and maternal samples were tested using STR markers to rule out maternal cell contamination. This result has been reviewed and approved by Maternal Specimen Yes Cytogenomic SNP Microarray - Fetal Abnormal * (Ref Interval: Normal) Test Performed: Cytogenomic SNP Microarray- Fetal (ARRAY FE) Specimen Type: Direct (uncultured) villi Indication for Testing: Patient with 46,XX,t(4;13)(p16.3;q12) (Quest: EN935475D) ----------------------------------------------------------------- ----- RESULT SUMMARY Abnormal Microarray Result (Male) Unbalanced Translocation Involving Chromosomes 4 and 13 Classification: Pathogenic 4p Terminal Deletion (Wolf-Hirschhorn syndrome) Copy number change: 4p16.3p16.2 loss Size: 5.1 Mb 13q Proximal Region Deletion Copy number change: 13q11q12.12 loss Size: 6.1 Mb ----------------------------------------------------------------- ----- RESULT DESCRIPTION This analysis showed a terminal deletion (1 copy present) involving chromosome 4 within 4p16.3p16.2 and a proximal interstitial deletion (1 copy present) involving chromosome 13 within 13q11q12.12. This
    [Show full text]
  • Genome-Wide DNA Methylation Map of Human Neutrophils Reveals Widespread Inter-Individual Epigenetic Variation
    www.nature.com/scientificreports OPEN Genome-wide DNA methylation map of human neutrophils reveals widespread inter-individual Received: 15 June 2015 Accepted: 29 October 2015 epigenetic variation Published: 27 November 2015 Aniruddha Chatterjee1,2, Peter A. Stockwell3, Euan J. Rodger1, Elizabeth J. Duncan2,4, Matthew F. Parry5, Robert J. Weeks1 & Ian M. Morison1,2 The extent of variation in DNA methylation patterns in healthy individuals is not yet well documented. Identification of inter-individual epigenetic variation is important for understanding phenotypic variation and disease susceptibility. Using neutrophils from a cohort of healthy individuals, we generated base-resolution DNA methylation maps to document inter-individual epigenetic variation. We identified 12851 autosomal inter-individual variably methylated fragments (iVMFs). Gene promoters were the least variable, whereas gene body and upstream regions showed higher variation in DNA methylation. The iVMFs were relatively enriched in repetitive elements compared to non-iVMFs, and were associated with genome regulation and chromatin function elements. Further, variably methylated genes were disproportionately associated with regulation of transcription, responsive function and signal transduction pathways. Transcriptome analysis indicates that iVMF methylation at differentially expressed exons has a positive correlation and local effect on the inclusion of that exon in the mRNA transcript. Methylation of DNA is a mechanism for regulating gene function in all vertebrates. It has a role in gene silencing, tissue differentiation, genomic imprinting, chromosome X inactivation, phenotypic plasticity, and disease susceptibility1,2. Aberrant DNA methylation has been implicated in the pathogenesis of sev- eral human diseases, especially cancer3–5. Variation in DNA methylation patterns in healthy individuals has been hypothesised to alter human phenotypes including susceptibility to common diseases6 and response to drug treatments7.
    [Show full text]
  • Open Data for Differential Network Analysis in Glioma
    International Journal of Molecular Sciences Article Open Data for Differential Network Analysis in Glioma , Claire Jean-Quartier * y , Fleur Jeanquartier y and Andreas Holzinger Holzinger Group HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, 8036 Graz, Austria; [email protected] (F.J.); [email protected] (A.H.) * Correspondence: [email protected] These authors contributed equally to this work. y Received: 27 October 2019; Accepted: 3 January 2020; Published: 15 January 2020 Abstract: The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes.
    [Show full text]
  • Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
    Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo
    [Show full text]
  • Genome-Wide Expression Profiling Establishes Novel Modulatory Roles
    Batra et al. BMC Genomics (2017) 18:252 DOI 10.1186/s12864-017-3635-4 RESEARCHARTICLE Open Access Genome-wide expression profiling establishes novel modulatory roles of vitamin C in THP-1 human monocytic cell line Sakshi Dhingra Batra, Malobi Nandi, Kriti Sikri and Jaya Sivaswami Tyagi* Abstract Background: Vitamin C (vit C) is an essential dietary nutrient, which is a potent antioxidant, a free radical scavenger and functions as a cofactor in many enzymatic reactions. Vit C is also considered to enhance the immune effector function of macrophages, which are regarded to be the first line of defence in response to any pathogen. The THP- 1 cell line is widely used for studying macrophage functions and for analyzing host cell-pathogen interactions. Results: We performed a genome-wide temporal gene expression and functional enrichment analysis of THP-1 cells treated with 100 μM of vit C, a physiologically relevant concentration of the vitamin. Modulatory effects of vitamin C on THP-1 cells were revealed by differential expression of genes starting from 8 h onwards. The number of differentially expressed genes peaked at the earliest time-point i.e. 8 h followed by temporal decline till 96 h. Further, functional enrichment analysis based on statistically stringent criteria revealed a gamut of functional responses, namely, ‘Regulation of gene expression’, ‘Signal transduction’, ‘Cell cycle’, ‘Immune system process’, ‘cAMP metabolic process’, ‘Cholesterol transport’ and ‘Ion homeostasis’. A comparative analysis of vit C-mediated modulation of gene expression data in THP-1cells and human skin fibroblasts disclosed an overlap in certain functional processes such as ‘Regulation of transcription’, ‘Cell cycle’ and ‘Extracellular matrix organization’, and THP-1 specific responses, namely, ‘Regulation of gene expression’ and ‘Ion homeostasis’.
    [Show full text]
  • Heterogeneity Between Primary Colon Carcinoma and Paired Lymphatic and Hepatic Metastases
    MOLECULAR MEDICINE REPORTS 6: 1057-1068, 2012 Heterogeneity between primary colon carcinoma and paired lymphatic and hepatic metastases HUANRONG LAN1, KETAO JIN2,3, BOJIAN XIE4, NA HAN5, BINBIN CUI2, FEILIN CAO2 and LISONG TENG3 Departments of 1Gynecology and Obstetrics, and 2Surgical Oncology, Taizhou Hospital, Wenzhou Medical College, Linhai, Zhejiang; 3Department of Surgical Oncology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang; 4Department of Surgical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang; 5Cancer Chemotherapy Center, Zhejiang Cancer Hospital, Zhejiang University of Chinese Medicine, Hangzhou, Zhejiang, P.R. China Received January 26, 2012; Accepted May 8, 2012 DOI: 10.3892/mmr.2012.1051 Abstract. Heterogeneity is one of the recognized characteris- Introduction tics of human tumors, and occurs on multiple levels in a wide range of tumors. A number of studies have focused on the Intratumor heterogeneity is one of the recognized charac- heterogeneity found in primary tumors and related metastases teristics of human tumors, which occurs on multiple levels, with the consideration that the evaluation of metastatic rather including genetic, protein and macroscopic, in a wide range than primary sites could be of clinical relevance. Numerous of tumors, including breast, colorectal cancer (CRC), non- studies have demonstrated particularly high rates of hetero- small cell lung cancer (NSCLC), prostate, ovarian, pancreatic, geneity between primary colorectal tumors and their paired gastric, brain and renal clear cell carcinoma (1). Over the past lymphatic and hepatic metastases. It has also been proposed decade, a number of studies have focused on the heterogeneity that the heterogeneity between primary colon carcinomas and found in primary tumors and related metastases with the their paired lymphatic and hepatic metastases may result in consideration that the evaluation of metastatic rather than different responses to anticancer therapies.
    [Show full text]
  • The Genetic Basis for Response to the Ketogenic Diet in Drug
    The genetic basis for response to the Ketogenic diet in drug- resistant epilepsy Natasha Emma Schoeler A thesis for submission to UCL for the degree of Doctor of Philosophy 1 Declaration I, Natasha Emma Schoeler, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Signed: ………………………………………………… Date: 2 Statement of contribution The idea for this thesis was a joint effort between Profs Sanjay Sisodiya, Helen Cross, Ley Sander and I (I am referred to as ‘the researcher’ throughout the thesis). I completed all ethics applications and amendments. All recruitment and collection of blood samples was undertaken by me, with the exception of participants recruited from Bristol Royal Hospital for Sick Children, Alder Hey Children’s Hospital and The Royal Children's Hospital in Melbourne; some participants from Birmingham Children’s Hospital, St George’s Hospital and Matthew’s Friends clinics were recruited by a specialist nurse (Bernie Concannon), a dietitian (Orla Stone) or keto-assistant (Valerie Aldridge) respectively, and some participants were recruited by me. I collected all phenotypic data, with the exception of individuals recruited from The Royal Children's Hospital in Melbourne, for whom Miss Jacinta McMahon provided phenotypic data. DNA collected in the UK was extracted by clinical geneticists at GOSH. I prepared all DNA samples to be sent to various centres for genotyping or sequencing. Miss Anna Tostevin introduced me to the laboratory setting and assisted with some dilutions and packaging. Sequencing of SLC2A1 was completed by Dr Suzanne Drury; sequencing of KCNJ11 and BAD was completed by members of Professor Sian Ellard’s team at Royal Devon & Exeter Hospital; whole exome sequencing was completed by Miss Deborah Hughes and Dr Alan Pittman.
    [Show full text]
  • Eicher Webinar Slides (PDF)
    Examining the Genetic Underpinnings of Commonly Comorbid Language Disorders: Dyslexia and Language Impairment John Eicher Golden Helix Webinar Department of Genetics Yale University May 13, 2014 Two Common Language Disorders • Dyslexia/Reading Disability (RD) Defense Di---fens • Language Impairment (LI) Bull---dog What are Reading Disability (RD) and Language Impairment (LI)? RD LI Shared Reading Disability (RD) Comorbidity of RDLanguage and LI Impairment (LI) Prevalence: 5-17% 50% of LI cases develop RDPrevalence: 5-8% Reading Decoding/ComprehensionRD cases more likely to have/hadVerbal Comprehension LI Phonological ProcessingPhonological ImpairmentsExpressive/Receptive Language Written Language Involve overall language VerbaldeficitsLanguage Brief History of Genetics of RD/LI • Genetic components of RD and LI – Heritability estimates of RD: 54-85% – Heritability estimates of LI : 45-73% • Strongest candidate genes include: – DCDC2 and KIAA0319 in DYX2 (chr. 6) DYX2 Locus on 6p22 DCDC2 GPLD1 KIAA0319 ACOT13 GMNN CMAHP NRSN1 MRS2 ALDH5A1 TDP2 C6orf62 FAM65B DYX2 Locus (Chromosome 6p22) DCDC2 GPLD1 KIAA0319 ACOT13 GMNN CMAHP NRSN1 MRS2 ALDH5A1 TDP2 C6orf62 FAM65B DCDC2READ1 KIAA0319KIAA0319 risk haplotype ••“RegulatoryNeuronal Migration Element • Located• Neuronal within Migrationthe KIAA0319 Associated• Grey/white with matter Dyslexia 1” promoter• Grey/white into TDP2 matter ••HighlyMicrotubule polymorphic binding domain •Associated• Signaling with protein reduced expression ••ModulatesReplicated expressionmultiple times of KIAA0319• Replicated multiple times • Specifically binds TF ETV6 • Locus associated with RD and LI Brief History of Genetics of RD/LI • Genetic components of RD and LI – Heritability estimates of RD: 54-85% – Heritability estimates of LI : 45-73% • Strongest candidate genes include: – KIAA0319 and DCDC2 in DYX2 (chr. 6) – DYX1C1 in DYX1 (chr. 15) – FOXP2 and CNTNAP2 (chr.
    [Show full text]
  • Integrative Analysis of Next Generation Sequencing for Small Non-Coding
    Beck et al. BMC Medical Genomics 2011, 4:19 http://www.biomedcentral.com/1755-8794/4/19 RESEARCHARTICLE Open Access Integrative analysis of next generation sequencing for small non-coding RNAs and transcriptional regulation in Myelodysplastic Syndromes Dominik Beck1,2, Steve Ayers4, Jianguo Wen3, Miriam B Brandl1,2, Tuan D Pham1, Paul Webb4, Chung-Che Chang3*, Xiaobo Zhou1* Abstract Background: Myelodysplastic Syndromes (MDSS) are pre-leukemic disorders with increasing incident rates worldwide, but very limited treatment options. Little is known about small regulatory RNAs and how they contribute to pathogenesis, progression and transcriptome changes in MDS. Methods: Patients’ primary marrow cells were screened for short RNAs (RNA-seq) using next generation sequencing. Exon arrays from the same cells were used to profile gene expression and additional measures on 98 patients obtained. Integrative bioinformatics algorithms were proposed, and pathway and ontology analysis performed. Results: In low-grade MDS, observations implied extensive post-transcriptional regulation via microRNAs (miRNA) and the recently discovered Piwi interacting RNAs (piRNA). Large expression differences were found for MDS- associated and novel miRNAs, including 48 sequences matching to miRNA star (miRNA*) motifs. The detected species were predicted to regulate disease stage specific molecular functions and pathways, including apoptosis and response to DNA damage. In high-grade MDS, results suggested extensive post-translation editing via transfer RNAs (tRNAs), providing a potential link for reduced apoptosis, a hallmark for this disease stage. Bioinformatics analysis confirmed important regulatory roles for MDS linked miRNAs and TFs, and strengthened the biological significance of miRNA*. The “RNA polymerase II promoters” were identified as the tightest controlled biological function.
    [Show full text]
  • TP-MAP - an Integrated Software Package for the Analysis of 1D and 2D Thermal Profiling Data
    bioRxiv preprint doi: https://doi.org/10.1101/2021.02.22.432361; this version posted February 24, 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-ND 4.0 International license. TP-MAP - an Integrated Software Package for the Analysis of 1D and 2D Thermal Profiling Data Felix Feyertag1,2 and Kilian V.M. Huber1,2* 1 Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom 2 Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom * Corresponding author: [email protected] Abstract Thermal profiling (TP) has emerged as a promising experimental methodology for elucidating the molecular targets of drugs and metabolites on a proteome-wide scale. Here, we present the Thermal Profiling Meltome Analysis Program (TP-MAP) software package for the analysis and ranking of 1D and 2D thermal profiling datasets. TP-MAP provides a user-friendly interface to quickly identify hit candidates and further explore targets of interest via intersection and crosslinking to public databases. 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.02.22.432361; this version posted February 24, 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-ND 4.0 International license. Introduction Assessing molecular perturbations in living cells caused by drug treatment, environmental changes, genetic mutations or alterations in metabolic flux in an unbiased and proteome- wide manner constitutes a key challenge in chemical biology and systems pharmacology.
    [Show full text]
  • Fish Possess Multiple Copies of Fgfrl1, the Gene for a Novel FGF Receptor
    Biochimica et Biophysica Acta 1727 (2005) 65–74 http://www.elsevier.com/locate/bba Fish possess multiple copies of fgfrl1, the gene for a novel FGF receptor Beat Trueba,*, Stephan C.F. Neuhaussb, Stefan Baertschia, Thorsten Rieckmanna, Christof Schilda, Sara Taeschlera aITI Research Institute, University of Bern, Murtenstrasse 35, CH-3010 Bern, Switzerland bSwiss Federal Institute of Technology, Department of Biology, and Brain Research Institute of the University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland Received 30 August 2004; received in revised form 17 November 2004; accepted 6 December 2004 Available online 23 December 2004 Abstract FGFRL1 is a novel FGF receptor that lacks the intracellular tyrosine kinase domain. While mammals, including man and mouse, possess a single copy of the FGFRL1 gene, fish have at least two copies, fgfrl1a and fgfrl1b. In zebrafish, both genes are located on chromosome 14, separated by about 10 cM. The two genes show a similar expression pattern in several zebrafish tissues, although the expression of fgfrl1b appears to be weaker than that of fgfrl1a. A clear difference is observed in the ovary of Fugu rubripes, which expresses fgfrl1a but not fgfrl1b. It is therefore possible that subfunctionalization has played a role in maintaining the two fgfrl1 genes during the evolution of fish. In human beings, the FGFRL1 gene is located on chromosome 4, adjacent to the SPON2, CTBP1 and MEAEA genes. These genes are also found adjacent to the fgfrl1a gene of Fugu, suggesting that FGFRL1, SPON2, CTBP1 and MEAEA were preserved as a coherent block during the evolution of Fugu and man.
    [Show full text]
  • Glucocorticoid Signature in a Neuronal Genomic Context Issue Date: 2016-05-10 Glucocorticoid Signature in a Neuronal Genomic Context
    Cover Page The handle http://hdl.handle.net/1887/39295 holds various files of this Leiden University dissertation Author: Polman, J.A.E. Title: Glucocorticoid signature in a neuronal genomic context Issue Date: 2016-05-10 Glucocorticoid Signature in a Neuronal Genomic Context Japke Anne Elisabeth Polman Glucocorticoid Signature in a Neuronal Genomic Context Japke Anne Elisabeth Polman Thesis, Leiden University May 10, 2016 ISBN: 978-94-6299-326-6 Cover design: J.A.E. Polman & M.A. Groeneweg Layout: M.A. Groeneweg Printing: Ridderprint BV, www.ridderprint.nl © J.A.E. Polman No part of this thesis may be reproduced or transmitted in any form or by any means without written permission of the author. Glucocorticoid Signature in a Neuronal Genomic Context Proefschrift ter verkrijging van de graad van Doctor aan de Universiteit Leiden, op gezag van Rector Magnificus prof. mr. C.J.J.M. Stolker, volgens besluit van het College voor Promoties te verdedigen op dinsdag 10 mei 2016 klokke 16:15 uur door Japke Anne Elisabeth Polman Geboren te Gouda in 1980 Promotor Prof. dr. E.R. de Kloet Co-promotor Dr. N.A. Datson Leden promotiecommissie Prof. dr. S.M. van der Maarel Prof. dr. P.J. Lucassen (University of Amsterdam) Prof. dr. G.J. Martens (Radboud University, Nijmegen) Prof. dr. O.C. Meijer Prof. dr. P.E. Slagboom Dr. E. Vreugdenhil The studies described in this thesis were performed at the Department of Medical Pharma- cology of the Leiden Academic Centre for Drug Research (LACDR) and Leiden University Medical Center (LUMC), the Netherlands. This research was financially supported by grants from the Netherlands Organization for Scientific Research (NWO) (836.06.010), Top Insti- tute (TI) Pharma (T5-209), Human Frontiers of Science Program (HFSP) (RGP39) and the Royal Netherlands Academy of Arts and Sciences (KNAW).
    [Show full text]