Mouse Zyg11b Conditional Knockout Project (CRISPR/Cas9)

Total Page:16

File Type:pdf, Size:1020Kb

Mouse Zyg11b Conditional Knockout Project (CRISPR/Cas9) http://www.alphaknockout.com/ Mouse Zyg11b Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Zyg11b conditional knockout mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Zyg11b gene ( NCBI Reference Sequence: NM_001033634 ; Ensembl: ENSMUSG00000034636 ) is located on mouse chromosome 4. 14 exons are identified , with the ATG start codon in exon 1 and the TGA stop codon in exon 14 (Transcript Zyg11b- 201: ENSMUST00000043616). Exon 3 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the mouse Zyg11b gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP24-272K18 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 3 starts from about 8.83% of the coding region. The knockout of Exon 3 will result in frameshift of the gene. The size of intron 2 for 5'-loxP site insertion: 5645 bp, and the size of intron 3 for 3'-loxP site insertion: 5727 bp. The size of effective cKO region: ~1570 bp. This strategy is designed based on genetic information in existing databases. Due to the complexity of biological processes, all risk of loxP insertion on gene transcription, RNA splicing and protein translation cannot be predicted at existing technological level. Page 1 of 7 http://www.alphaknockout.com/ Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 3 14 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Zyg11b Homology arm cKO region loxP site Page 2 of 7 http://www.alphaknockout.com/ Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region 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 GC Content Distribution Window size: 300 bp Sequence 12 Summary: Full Length(7755bp) | A(25.2% 1954) | C(20.77% 1611) | G(22.04% 1709) | T(31.99% 2481) Note: The sequence of homologous arms and cKO region 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 3 of 7 http://www.alphaknockout.com/ BLAT Search Results (up) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN ----------------------------------------------------------------------------------------------- browser details YourSeq 3000 1 3000 3000 100.0% chr4 - 108266823 108269822 3000 browser details YourSeq 269 1 1783 3000 90.7% chr10 + 60020924 60262168 241245 browser details YourSeq 256 1 1783 3000 90.5% chr12 + 84860247 85006115 145869 browser details YourSeq 129 1 153 3000 93.4% chr18 - 84923595 84923751 157 browser details YourSeq 129 1607 1783 3000 86.0% chr17 - 47503598 47503748 151 browser details YourSeq 128 1 147 3000 94.6% chrX + 103339017 103339290 274 browser details YourSeq 127 1624 1783 3000 88.6% chr5 - 132788768 132788920 153 browser details YourSeq 127 1631 1783 3000 92.1% chr5 - 93163370 93163528 159 browser details YourSeq 126 1637 1783 3000 93.8% chr14 - 70756208 70756373 166 browser details YourSeq 126 1639 1783 3000 90.8% chr11 - 103949882 103950022 141 browser details YourSeq 126 1641 1785 3000 92.3% chr15 + 91166450 91166592 143 browser details YourSeq 124 1646 1785 3000 94.3% chr11 + 68478232 68478371 140 browser details YourSeq 123 1664 1858 3000 93.1% chr16 - 94337756 94338093 338 browser details YourSeq 123 1638 1783 3000 92.5% chr5 + 52856225 52856375 151 browser details YourSeq 123 1641 1783 3000 92.1% chr11 + 78570924 78571063 140 browser details YourSeq 122 1644 1783 3000 91.3% chr9 + 70550191 70550327 137 browser details YourSeq 122 1640 1783 3000 93.1% chr2 + 129811722 129811877 156 browser details YourSeq 122 1642 1783 3000 92.8% chr18 + 75406202 75406342 141 browser details YourSeq 122 1640 1783 3000 92.4% chr12 + 28917449 28917592 144 browser details YourSeq 121 1639 1783 3000 91.8% chr17 - 29498705 29498849 145 Note: The 3000 bp section upstream of Exon 3 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 3000 1 3000 3000 100.0% chr4 - 108262568 108265567 3000 browser details YourSeq 218 1984 2337 3000 87.4% chr14 - 91648319 91648577 259 browser details YourSeq 216 1984 2326 3000 86.4% chr3 - 115846682 115846939 258 browser details YourSeq 205 1997 2334 3000 92.2% chr11 - 10732938 10733276 339 browser details YourSeq 199 1984 2327 3000 93.9% chr5_JH584299_random + 313173 313761 589 browser details YourSeq 182 1984 2322 3000 85.0% chr4 + 22763988 22764275 288 browser details YourSeq 179 1984 2322 3000 83.6% chr14 + 27132757 27133007 251 browser details YourSeq 176 1984 2324 3000 86.5% chr1 - 125378428 125378627 200 browser details YourSeq 174 2020 2326 3000 91.8% chr5 + 94379672 94380290 619 browser details YourSeq 171 2000 2334 3000 85.8% chr15 + 93426720 93426950 231 browser details YourSeq 166 1988 2323 3000 84.0% chr17 + 32871386 32871587 202 browser details YourSeq 148 1994 2175 3000 89.0% chr3 + 126084596 126084758 163 browser details YourSeq 137 1993 2259 3000 91.5% chr3 - 44985679 44986056 378 browser details YourSeq 134 2036 2322 3000 84.0% chr1 - 130617595 130617828 234 browser details YourSeq 130 2004 2150 3000 91.7% chr16 - 41441863 41442006 144 browser details YourSeq 120 1995 2144 3000 84.9% chr14 + 27132757 27132896 140 browser details YourSeq 119 2281 2412 3000 95.5% chr4 - 108270502 108270636 135 browser details YourSeq 115 1995 2264 3000 95.3% chr19 - 5201036 5201392 357 browser details YourSeq 115 953 1127 3000 90.9% chr16 + 18933134 18933329 196 browser details YourSeq 115 2040 2334 3000 78.4% chr1 + 132396175 132396338 164 Note: The 3000 bp section downstream of Exon 3 is BLAT searched against the genome. No significant similarity is found. Page 4 of 7 http://www.alphaknockout.com/ Gene and protein information: Zyg11b zyg-ll family member B, cell cycle regulator [ Mus musculus (house mouse) ] Gene ID: 414872, updated on 17-Dec-2020 Gene summary Official Symbol Zyg11b provided by MGI Official Full Name zyg-ll family member B, cell cycle regulator provided by MGI Primary source MGI:MGI:2685277 See related Ensembl:ENSMUSG00000034636 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 Gm431; D4Mgi2; D4Mgi23; mKIAA1730; 1110046I03Rik; 2810482G21Rik Expression Ubiquitous expression in CNS E18 (RPKM 15.5), whole brain E14.5 (RPKM 12.1) and 26 other tissues See more Orthologs human all NEW Try the new Gene table Try the new Transcript table Genomic context Location: 4; 4 C7 See Zyg11b in Genome Data Viewer Exon count: 14 Annotation release Status Assembly Chr Location 109 current GRCm39 (GCF_000001635.27) 4 NC_000070.7 (108084952..108158330, complement) 108.20200622 previous assembly GRCm38.p6 (GCF_000001635.26) 4 NC_000070.6 (108227755..108301125, complement) Build 37.2 previous assembly MGSCv37 (GCF_000001635.18) 4 NC_000070.5 (107900360..107973695, complement) Chromosome 4 - NC_000070.7 Page 5 of 7 http://www.alphaknockout.com/ Transcript information: This gene has 2 transcripts Gene: Zyg11b ENSMUSG00000034636 Description zyg-ll family member B, cell cycle regulator [Source:MGI Symbol;Acc:MGI:2685277] Gene Synonyms 1110046I03Rik, 2810482G21Rik, D4Mgi23, LOC242610 Location Chromosome 4: 108,086,921-108,158,293 reverse strand. GRCm39:CM000997.3 About this gene This gene has 2 transcripts (splice variants), 273 orthologues and 2 paralogues. Transcripts UniProt Name Transcript ID bp Protein Translation ID Biotype CCDS Flags Match Zyg11b- ENSMUST00000043616.7 8691 744aa ENSMUSP00000043844.7 Protein coding CCDS18448 Q3UFS0-1 TSL:1 201 GENCODE basic APPRIS P1 Zyg11b- ENSMUST00000130508.2 447 No - Processed - - TSL:3 202 protein transcript 91.37 kb Forward strand 108.08Mb 108.10Mb 108.12Mb 108.14Mb 108.16Mb Contigs BX293563.9 > AL627238.15 > Genes (Comprehensive set from GENCODE M... < Zyg11b-201protein coding < Zyg11b-202processed transcript < Gm12742-201processed pseudogene Regulatory Build 108.08Mb 108.10Mb 108.12Mb 108.14Mb 108.16Mb Reverse strand 91.37 kb Regulation Legend CTCF Enhancer Open Chromatin Promoter Promoter Flank Gene Legend Protein Coding merged Ensembl/Havana Non-Protein Coding pseudogene processed transcript Page 6 of 7 http://www.alphaknockout.com/ Transcript: ENSMUST00000043616 < Zyg11b-201protein coding Reverse strand 71.37 kb ENSMUSP000000438... Low complexity (Seg) Superfamily SSF52047 Armadillo-type fold PROSITE profiles Leucine-rich repeat PANTHER Protein zyg-11 homologue B PTHR12904 Gene3D Leucine-rich repeat domain superfamily Armadillo-like helical All sequence SNPs/in... Sequence variants (dbSNP and all other sources) Variant Legend missense variant synonymous variant Scale bar 0 80 160 240 320 400 480 560 640 744 We wish to acknowledge the following valuable scientific information resources: Ensembl, MGI, NCBI, UCSC, VectorBuilder. Page 7 of 7.
Recommended publications
  • 4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
    Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4).
    [Show full text]
  • A SARS-Cov-2 Protein Interaction Map Reveals Targets for Drug Repurposing
    Article A SARS-CoV-2 protein interaction map reveals targets for drug repurposing https://doi.org/10.1038/s41586-020-2286-9 A list of authors and affiliations appears at the end of the paper Received: 23 March 2020 Accepted: 22 April 2020 A newly described coronavirus named severe acute respiratory syndrome Published online: 30 April 2020 coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than Check for updates 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efcacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and eforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identifed the human proteins that physically associated with each of the SARS-CoV-2 proteins using afnity-purifcation mass spectrometry, identifying 332 high-confdence protein–protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors.
    [Show full text]
  • The Changing Chromatome As a Driver of Disease: a Panoramic View from Different Methodologies
    The changing chromatome as a driver of disease: A panoramic view from different methodologies Isabel Espejo1, Luciano Di Croce,1,2,3 and Sergi Aranda1 1. Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain 2. Universitat Pompeu Fabra (UPF), Barcelona, Spain 3. ICREA, Pg. Lluis Companys 23, Barcelona 08010, Spain *Corresponding authors: Luciano Di Croce ([email protected]) Sergi Aranda ([email protected]) 1 GRAPHICAL ABSTRACT Chromatin-bound proteins regulate gene expression, replicate and repair DNA, and transmit epigenetic information. Several human diseases are highly influenced by alterations in the chromatin- bound proteome. Thus, biochemical approaches for the systematic characterization of the chromatome could contribute to identifying new regulators of cellular functionality, including those that are relevant to human disorders. 2 SUMMARY Chromatin-bound proteins underlie several fundamental cellular functions, such as control of gene expression and the faithful transmission of genetic and epigenetic information. Components of the chromatin proteome (the “chromatome”) are essential in human life, and mutations in chromatin-bound proteins are frequently drivers of human diseases, such as cancer. Proteomic characterization of chromatin and de novo identification of chromatin interactors could thus reveal important and perhaps unexpected players implicated in human physiology and disease. Recently, intensive research efforts have focused on developing strategies to characterize the chromatome composition. In this review, we provide an overview of the dynamic composition of the chromatome, highlight the importance of its alterations as a driving force in human disease (and particularly in cancer), and discuss the different approaches to systematically characterize the chromatin-bound proteome in a global manner.
    [Show full text]
  • Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
    Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ......................................................
    [Show full text]
  • Transcription of Endogenous Retrovirus Group K Members and Their Neighboring Genes in Chicken Skeletal Muscle Myoblasts
    http://www.jstage.jst.go.jp/browse/jpsa doi:10.2141/ jpsa.0200021 Copyright Ⓒ 2021, Japan Poultry Science Association. Transcription of Endogenous Retrovirus Group K Members and Their Neighboring Genes in Chicken Skeletal Muscle Myoblasts Tomohide Takaya1, 2, 3, Yuma Nihashi1, Tamao Ono2 and Hiroshi Kagami2 1 Department of Science and Technology, Graduate School of Medicine, Science and Technology, Shinshu University, Nagano 399-4598, Japan 2 Department of Agricultural and Life Science, Faculty of Agriculture, Shinshu University, Nagano 399-4598, Japan 3 Department of Biomolecular Innovation, Institute for Biomedical Sciences, Shinshu University, Nagano 399-4598, Japan Skeletal muscle myoblasts are myogenic precursor cells that generate myofibers during muscle development and growth. We recently reported that broiler myoblasts, compared to layer myoblasts, proliferate and differentiate more actively and promptly into myocytes, which corresponds well with the muscle phenotype of broilers. Furthermore, RNA sequencing (RNA-seq) revealed that numerous genes are differentially expressed between layer and broiler myoblasts during myogenic differentiation. Based on the RNA-seq data, we herein report that chicken myoblasts transcribe endogenous retrovirus group K member (ERVK) genes. In total, 16 ERVKs were highly expressed in layer myoblasts and two (termed BrK1 and BrK2) were significantly induced in broiler myoblasts. These transcribed ERVKs had a totalof 182 neighboring genes within ±100 kb on the chromosomes, of which 40% were concentrated within ±10 kb of the ERVKs. We further investigated whether the transcription of ERVKs affects the expression of their neighboring genes. BrK1 had two neighboring genes; LOC107052719 was overlapping with BrK1 and down- regulated in the broiler myoblasts, and FAM19A2 was upregulated in the broiler myoblasts as well as BrK1.
    [Show full text]
  • Detection of H3k4me3 Identifies Neurohiv Signatures, Genomic
    viruses Article Detection of H3K4me3 Identifies NeuroHIV Signatures, Genomic Effects of Methamphetamine and Addiction Pathways in Postmortem HIV+ Brain Specimens that Are Not Amenable to Transcriptome Analysis Liana Basova 1, Alexander Lindsey 1, Anne Marie McGovern 1, Ronald J. Ellis 2 and Maria Cecilia Garibaldi Marcondes 1,* 1 San Diego Biomedical Research Institute, San Diego, CA 92121, USA; [email protected] (L.B.); [email protected] (A.L.); [email protected] (A.M.M.) 2 Departments of Neurosciences and Psychiatry, University of California San Diego, San Diego, CA 92103, USA; [email protected] * Correspondence: [email protected] Abstract: Human postmortem specimens are extremely valuable resources for investigating trans- lational hypotheses. Tissue repositories collect clinically assessed specimens from people with and without HIV, including age, viral load, treatments, substance use patterns and cognitive functions. One challenge is the limited number of specimens suitable for transcriptional studies, mainly due to poor RNA quality resulting from long postmortem intervals. We hypothesized that epigenomic Citation: Basova, L.; Lindsey, A.; signatures would be more stable than RNA for assessing global changes associated with outcomes McGovern, A.M.; Ellis, R.J.; of interest. We found that H3K27Ac or RNA Polymerase (Pol) were not consistently detected by Marcondes, M.C.G. Detection of H3K4me3 Identifies NeuroHIV Chromatin Immunoprecipitation (ChIP), while the enhancer H3K4me3 histone modification was Signatures, Genomic Effects of abundant and stable up to the 72 h postmortem. We tested our ability to use H3K4me3 in human Methamphetamine and Addiction prefrontal cortex from HIV+ individuals meeting criteria for methamphetamine use disorder or not Pathways in Postmortem HIV+ Brain (Meth +/−) which exhibited poor RNA quality and were not suitable for transcriptional profiling.
    [Show full text]
  • Thirty Loci Identified for Heart Rate Response to Exercise and Recovery
    ARTICLE DOI: 10.1038/s41467-018-04148-1 OPEN Thirty loci identified for heart rate response to exercise and recovery implicate autonomic nervous system Julia Ramírez 1,2, Stefan van Duijvenboden1,2, Ioanna Ntalla1, Borbala Mifsud1,3, Helen R Warren1,3, Evan Tzanis1,3, Michele Orini 4,5, Andrew Tinker1,3, Pier D. Lambiase2,4 & Patricia B. Munroe 1,3 Δ ex 1234567890():,; Impaired capacity to increase heart rate (HR) during exercise ( HR ), and a reduced rate of recovery post-exercise (ΔHRrec) are associated with higher cardiovascular mortality rates. Currently, the genetic basis of both phenotypes remains to be elucidated. We conduct genome-wide association studies (GWASs) for ΔHRex and ΔHRrec in ~40,000 individuals, followed by replication in ~27,000 independent samples, all from UK Biobank. Six and seven single-nucleotide polymorphisms for ΔHRex and ΔHRrec, respectively, formally replicate. In a full data set GWAS, eight further loci for ΔHRex and nine for ΔHRrec are genome-wide significant (P ≤ 5×10−8). In total, 30 loci are discovered, 8 being common across traits. Processes of neural development and modulation of adrenergic activity by the autonomic nervous system are enriched in these results. Our findings reinforce current understanding of HR response to exercise and recovery and could guide future studies evaluating its con- tribution to cardiovascular risk prediction. 1 Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK. 2 Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK. 3 NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.
    [Show full text]
  • Exome Sequencing Identifies Pathogenic and Modifier Mutations
    ORIGINAL RESEARCH Exome Sequencing Identifies Pathogenic and Modifier Mutations in a Child With Sporadic Dilated Cardiomyopathy Pamela A. Long, BS; Brandon T. Larsen, MD, PhD; Jared M. Evans, MS; Timothy M. Olson, MD Background-—Idiopathic dilated cardiomyopathy (DCM) is typically diagnosed in adulthood, yet familial cases exhibit variable age- dependent penetrance and a subset of patients develop sporadic DCM in childhood. We sought to discover the molecular basis of sporadic DCM in an 11-year-old female with severe heart failure necessitating cardiac transplantation. Methods and Results-—Parental echocardiograms excluded asymptomatic DCM. Whole exome sequencing was performed on the family trio and filtered for rare, deleterious, recessive, and de novo variants. Of the 8 candidate genes identified, only 2 had a role in cardiac physiology. A de novo missense mutation in TNNT2 was identified, previously reported and functionally validated in familial DCM with markedly variable penetrance. Additionally, recessive compound heterozygous truncating mutations were identified in XIRP2, a member of the ancient Xin gene family, which governs intercalated disc (ICD) maturation. Histomorphological analysis of explanted heart tissue revealed misregistration, mislocalization, and shortening of ICDs, findings similar to Xirp2À/À mice. Conclusions-—The synergistic effects of TNNT2 and XIRP2 mutations, resulting in perturbed sarcomeric force generation and transmission, respectively, would account for an early-onset heart failure phenotype. Whereas the importance
    [Show full text]
  • Supplemental Data
    Supplemental Table 1: List of the 570 genes with conserved Stat3 binding sites (CBS) in at least four species differentially expressed between C56BL/6 and FVB/N remnant kidneys 60 days after nephron reduction. Gene Symbol Ratio CBS in Name Abhd1 27.86 5 species abhydrolase domain containing 1 Pi4k2b 19.99 4 species phosphatidylinositol 4-kinase type 2 beta Pik3c2g 11.64 4 species phosphoinositide-3-kinase, class 2, gamma polypeptide Snap91 11.31 4 species synaptosomal-associated protein, 91kDa homolog (mouse) Ocel1 10.58 ≥ 6 species occludin/ELL domain containing 1 Slc34a2 8.86 4 species solute carrier family 34 (sodium phosphate), member 2 Psmc3ip 8.68 ≥ 6 species PSMC3 interacting protein Hddc3 7.17 ≥ 6 species HD domain containing 3 Lcn2 6.52 4 species lipocalin 2 Pea15a 5.09 5 species phosphoprotein enriched in astrocytes 15 Gfra1 5.09 4 species GDNF family receptor alpha 1 H2-DMb2 4.94 4 species major histocompatibility complex, class II, DM beta Atf3 4.88 4 species activating transcription factor 3 Wdfy1 4.85 4 species WD repeat and FYVE domain containing 1 Serpina10 4.73 4 species serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 10 Pm20d1 4.71 4 species peptidase M20 domain containing 1 Aldh4a1 4.35 4 species aldehyde dehydrogenase 4 family, member A1 Wasf2 4.10 4 species WAS protein family, member 2 Edn1 4.07 4 species endothelin 1 Zkscan1 3.98 4 species zinc finger with KRAB and SCAN domains 1 Cyr61 3.94 4 species cysteine-rich, angiogenic inducer, 61 Adamts1 3.76 5 species ADAM metallopeptidase
    [Show full text]
  • Structure-Function Relationships of Rna and Protein in Synaptic Plasticity
    University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2017 Structure-Function Relationships Of Rna And Protein In Synaptic Plasticity Sarah Middleton University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, Biology Commons, and the Neuroscience and Neurobiology Commons Recommended Citation Middleton, Sarah, "Structure-Function Relationships Of Rna And Protein In Synaptic Plasticity" (2017). Publicly Accessible Penn Dissertations. 2474. https://repository.upenn.edu/edissertations/2474 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/2474 For more information, please contact [email protected]. Structure-Function Relationships Of Rna And Protein In Synaptic Plasticity Abstract Structure is widely acknowledged to be important for the function of ribonucleic acids (RNAs) and proteins. However, due to the relative accessibility of sequence information compared to structure information, most large genomics studies currently use only sequence-based annotation tools to analyze the function of expressed molecules. In this thesis, I introduce two novel computational methods for genome-scale structure-function analysis and demonstrate their application to identifying RNA and protein structures involved in synaptic plasticity and potentiation—important neuronal processes that are thought to form the basis of learning and memory. First, I describe a new method for de novo identification of RNA secondary structure motifs enriched in co-regulated transcripts. I show that this method can accurately identify secondary structure motifs that recur across three or more transcripts in the input set with an average recall of 0.80 and precision of 0.98. Second, I describe a tool for predicting protein structural fold from amino acid sequence, which achieves greater than 96% accuracy on benchmarks and can be used to predict protein function and identify new structural folds.
    [Show full text]
  • Modeling Gene Regulation from Paired Expression and Chromatin Accessibility Data
    Modeling gene regulation from paired expression and PNAS PLUS chromatin accessibility data Zhana Durena,b,c, Xi Chenb, Rui Jiangd,1, Yong Wanga,c,1, and Wing Hung Wongb,1 aAcademy of Mathematics and Systems Science, National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing 100080, China; bDepartment of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, CA 94305; cSchool of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; and dMinistry of Education Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, Tsinghua National Laboratory for Information Science and Technology, Department of Automation, Tsinghua University, Beijing 100084, China Contributed by Wing Hung Wong, May 8, 2017 (sent for review March 20, 2017; reviewed by Christina Kendziorski and Sheng Zhong) The rapid increase of genome-wide datasets on gene expression, gene expression data, accessibility data are available for a diverse set chromatin states, and transcription factor (TF) binding locations offers of cellular contexts (Fig. 1, blue boxes). In fact, we expect the an exciting opportunity to interpret the information encoded in amount of matched expression and accessibility data (i.e., measured genomes and epigenomes. This task can be challenging as it requires on the same sample) will increase very rapidly in the near future. joint modeling of context-specific activation of cis-regulatory ele- The purpose of the present work is to show that, by using ments (REs) and the effects on transcription of associated regulatory matched expression and accessibility data across diverse cellular factors. To meet this challenge, we propose a statistical approach contexts, it is possible to recover a significant portion of the in- based on paired expression and chromatin accessibility (PECA) data formation in the missing data on binding location and chromatin across diverse cellular contexts.
    [Show full text]
  • A Dissertation Entitled Mapping and CRISPR/Cas9 Gene Editing For
    A Dissertation entitled Mapping and CRISPR/Cas9 Gene Editing for Identifying Novel Genomic Factors Influencing Blood Pressure by Harshal Waghulde Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Biomedical Sciences _________________________________________ Bina Joe, PhD, Committee Chair _________________________________________ Guillermo Vazquez, PhD, Committee Member ________________________________________ Kathryn Eisenmann, PhD, Committee Member _________________________________________ Jennifer Hill, PhD, Committee Member _________________________________________ Jiang Tian, PhD, Committee Member _________________________________________ Amanda Bryant-Friedrich, PhD, Dean College of Graduate Studies The University of Toledo August 2016 Copyright 2016, Harshal Bhanudas Waghulde This document is copyrighted material. Under copyright law, no parts of this document may be reproduced without the expressed permission of the author. An Abstract of Mapping and CRISPR/Cas9 Gene Editing for Identifying Novel Genomic Factors Influencing Blood Pressure by Harshal Waghulde Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Biomedical Sciences Degree in Doctor of Philosophy Degree in Biomedical Sciences The University of Toledo August 2016 Hypertension is a complex polygenic trait and a significant risk factor for cardiovascular and metabolic diseases. Rodent models serve as tools to identify causal genes for complex traits. This dissertation is comprised of two projects. Project 1 utilizes substitution mapping as an approach to locate blood pressure quantitative trait loci (BP QTLs) on rat chromosome 5 (RNO5) and project 2 utilizes Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR Associated proteins 9 (Cas9) genetic engineering as an approach to explore the physiological function of G-protein coupled estrogen receptor (Gper1) in a rat model of hypertension.
    [Show full text]