Molecular Triggers of Symptoms of Parosmia and Insights Into the Underlying Mechanism
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Genetic Variation Across the Human Olfactory Receptor Repertoire Alters Odor Perception
bioRxiv preprint doi: https://doi.org/10.1101/212431; this version posted November 1, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 4.0 International license. Genetic variation across the human olfactory receptor repertoire alters odor perception Casey Trimmer1,*, Andreas Keller2, Nicolle R. Murphy1, Lindsey L. Snyder1, Jason R. Willer3, Maira Nagai4,5, Nicholas Katsanis3, Leslie B. Vosshall2,6,7, Hiroaki Matsunami4,8, and Joel D. Mainland1,9 1Monell Chemical Senses Center, Philadelphia, Pennsylvania, USA 2Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, New York, USA 3Center for Human Disease Modeling, Duke University Medical Center, Durham, North Carolina, USA 4Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina, USA 5Department of Biochemistry, University of Sao Paulo, Sao Paulo, Brazil 6Howard Hughes Medical Institute, New York, New York, USA 7Kavli Neural Systems Institute, New York, New York, USA 8Department of Neurobiology and Duke Institute for Brain Sciences, Duke University Medical Center, Durham, North Carolina, USA 9Department of Neuroscience, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA *[email protected] ABSTRACT The human olfactory receptor repertoire is characterized by an abundance of genetic variation that affects receptor response, but the perceptual effects of this variation are unclear. To address this issue, we sequenced the OR repertoire in 332 individuals and examined the relationship between genetic variation and 276 olfactory phenotypes, including the perceived intensity and pleasantness of 68 odorants at two concentrations, detection thresholds of three odorants, and general olfactory acuity. -
An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors
Ecology and Evolutionary Biology 2021; 6(3): 53-77 http://www.sciencepublishinggroup.com/j/eeb doi: 10.11648/j.eeb.20210603.11 ISSN: 2575-3789 (Print); ISSN: 2575-3762 (Online) An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors Miguel Angel Fuertes*, Carlos Alonso Department of Microbiology, Centre for Molecular Biology “Severo Ochoa”, Spanish National Research Council and Autonomous University, Madrid, Spain Email address: *Corresponding author To cite this article: Miguel Angel Fuertes, Carlos Alonso. An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors. Ecology and Evolutionary Biology. Vol. 6, No. 3, 2021, pp. 53-77. doi: 10.11648/j.eeb.20210603.11 Received: April 24, 2021; Accepted: May 11, 2021; Published: July 13, 2021 Abstract: Capturing conserved patterns in genes and proteins is important for inferring phenotype prediction and evolutionary analysis. The study is focused on the conserved patterns of the G protein-coupled receptors, an important superfamily of receptors. Olfactory receptors represent more than 2% of our genome and constitute the largest family of G protein-coupled receptors, a key class of drug targets. As no crystallographic structures are available, mechanistic studies rely on the use of molecular dynamic modelling combined with site-directed mutagenesis data. In this paper, we hypothesized that human-mouse orthologs coding for G protein-coupled receptors maintain, at speciation events, shared compositional structures independent, to some extent, of their percent identity as reveals a method based in the categorization of nucleotide triplets by their gross composition. The data support the consistency of the hypothesis, showing in ortholog G protein-coupled receptors the presence of emergent shared compositional structures preserved at speciation events. -
Identification of Candidate Biomarkers and Pathways Associated with Type 1 Diabetes Mellitus Using Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2021.06.08.447531; this version posted June 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2021.06.08.447531; this version posted June 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were then performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. -
Single Cell Derived Clonal Analysis of Human Glioblastoma Links
SUPPLEMENTARY INFORMATION: Single cell derived clonal analysis of human glioblastoma links functional and genomic heterogeneity ! Mona Meyer*, Jüri Reimand*, Xiaoyang Lan, Renee Head, Xueming Zhu, Michelle Kushida, Jane Bayani, Jessica C. Pressey, Anath Lionel, Ian D. Clarke, Michael Cusimano, Jeremy Squire, Stephen Scherer, Mark Bernstein, Melanie A. Woodin, Gary D. Bader**, and Peter B. Dirks**! ! * These authors contributed equally to this work.! ** Correspondence: [email protected] or [email protected]! ! Supplementary information - Meyer, Reimand et al. Supplementary methods" 4" Patient samples and fluorescence activated cell sorting (FACS)! 4! Differentiation! 4! Immunocytochemistry and EdU Imaging! 4! Proliferation! 5! Western blotting ! 5! Temozolomide treatment! 5! NCI drug library screen! 6! Orthotopic injections! 6! Immunohistochemistry on tumor sections! 6! Promoter methylation of MGMT! 6! Fluorescence in situ Hybridization (FISH)! 7! SNP6 microarray analysis and genome segmentation! 7! Calling copy number alterations! 8! Mapping altered genome segments to genes! 8! Recurrently altered genes with clonal variability! 9! Global analyses of copy number alterations! 9! Phylogenetic analysis of copy number alterations! 10! Microarray analysis! 10! Gene expression differences of TMZ resistant and sensitive clones of GBM-482! 10! Reverse transcription-PCR analyses! 11! Tumor subtype analysis of TMZ-sensitive and resistant clones! 11! Pathway analysis of gene expression in the TMZ-sensitive clone of GBM-482! 11! Supplementary figures and tables" 13" "2 Supplementary information - Meyer, Reimand et al. Table S1: Individual clones from all patient tumors are tumorigenic. ! 14! Fig. S1: clonal tumorigenicity.! 15! Fig. S2: clonal heterogeneity of EGFR and PTEN expression.! 20! Fig. S3: clonal heterogeneity of proliferation.! 21! Fig. -
Strand Breaks for P53 Exon 6 and 8 Among Different Time Course of Folate Depletion Or Repletion in the Rectosigmoid Mucosa
SUPPLEMENTAL FIGURE COLON p53 EXONIC STRAND BREAKS DURING FOLATE DEPLETION-REPLETION INTERVENTION Supplemental Figure Legend Strand breaks for p53 exon 6 and 8 among different time course of folate depletion or repletion in the rectosigmoid mucosa. The input of DNA was controlled by GAPDH. The data is shown as ΔCt after normalized to GAPDH. The higher ΔCt the more strand breaks. The P value is shown in the figure. SUPPLEMENT S1 Genes that were significantly UPREGULATED after folate intervention (by unadjusted paired t-test), list is sorted by P value Gene Symbol Nucleotide P VALUE Description OLFM4 NM_006418 0.0000 Homo sapiens differentially expressed in hematopoietic lineages (GW112) mRNA. FMR1NB NM_152578 0.0000 Homo sapiens hypothetical protein FLJ25736 (FLJ25736) mRNA. IFI6 NM_002038 0.0001 Homo sapiens interferon alpha-inducible protein (clone IFI-6-16) (G1P3) transcript variant 1 mRNA. Homo sapiens UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 15 GALNTL5 NM_145292 0.0001 (GALNT15) mRNA. STIM2 NM_020860 0.0001 Homo sapiens stromal interaction molecule 2 (STIM2) mRNA. ZNF645 NM_152577 0.0002 Homo sapiens hypothetical protein FLJ25735 (FLJ25735) mRNA. ATP12A NM_001676 0.0002 Homo sapiens ATPase H+/K+ transporting nongastric alpha polypeptide (ATP12A) mRNA. U1SNRNPBP NM_007020 0.0003 Homo sapiens U1-snRNP binding protein homolog (U1SNRNPBP) transcript variant 1 mRNA. RNF125 NM_017831 0.0004 Homo sapiens ring finger protein 125 (RNF125) mRNA. FMNL1 NM_005892 0.0004 Homo sapiens formin-like (FMNL) mRNA. ISG15 NM_005101 0.0005 Homo sapiens interferon alpha-inducible protein (clone IFI-15K) (G1P2) mRNA. SLC6A14 NM_007231 0.0005 Homo sapiens solute carrier family 6 (neurotransmitter transporter) member 14 (SLC6A14) mRNA. -
Sean Raspet – Molecules
1. Commercial name: Fructaplex© IUPAC Name: 2-(3,3-dimethylcyclohexyl)-2,5,5-trimethyl-1,3-dioxane SMILES: CC1(C)CCCC(C1)C2(C)OCC(C)(C)CO2 Molecular weight: 240.39 g/mol Volume (cubic Angstroems): 258.88 Atoms number (non-hydrogen): 17 miLogP: 4.43 Structure: Biological Properties: Predicted Druglikenessi: GPCR ligand -0.23 Ion channel modulator -0.03 Kinase inhibitor -0.6 Nuclear receptor ligand 0.15 Protease inhibitor -0.28 Enzyme inhibitor 0.15 Commercial name: Fructaplex© IUPAC Name: 2-(3,3-dimethylcyclohexyl)-2,5,5-trimethyl-1,3-dioxane SMILES: CC1(C)CCCC(C1)C2(C)OCC(C)(C)CO2 Predicted Olfactory Receptor Activityii: OR2L13 83.715% OR1G1 82.761% OR10J5 80.569% OR2W1 78.180% OR7A2 77.696% 2. Commercial name: Sylvoxime© IUPAC Name: N-[4-(1-ethoxyethenyl)-3,3,5,5tetramethylcyclohexylidene]hydroxylamine SMILES: CCOC(=C)C1C(C)(C)CC(CC1(C)C)=NO Molecular weight: 239.36 Volume (cubic Angstroems): 252.83 Atoms number (non-hydrogen): 17 miLogP: 4.33 Structure: Biological Properties: Predicted Druglikeness: GPCR ligand -0.6 Ion channel modulator -0.41 Kinase inhibitor -0.93 Nuclear receptor ligand -0.17 Protease inhibitor -0.39 Enzyme inhibitor 0.01 Commercial name: Sylvoxime© IUPAC Name: N-[4-(1-ethoxyethenyl)-3,3,5,5tetramethylcyclohexylidene]hydroxylamine SMILES: CCOC(=C)C1C(C)(C)CC(CC1(C)C)=NO Predicted Olfactory Receptor Activity: OR52D1 71.900% OR1G1 70.394% 0R52I2 70.392% OR52I1 70.390% OR2Y1 70.378% 3. Commercial name: Hyperflor© IUPAC Name: 2-benzyl-1,3-dioxan-5-one SMILES: O=C1COC(CC2=CC=CC=C2)OC1 Molecular weight: 192.21 g/mol Volume -
Epigenetic Mechanisms Are Involved in the Oncogenic Properties of ZNF518B in Colorectal Cancer
Epigenetic mechanisms are involved in the oncogenic properties of ZNF518B in colorectal cancer Francisco Gimeno-Valiente, Ángela L. Riffo-Campos, Luis Torres, Noelia Tarazona, Valentina Gambardella, Andrés Cervantes, Gerardo López-Rodas, Luis Franco and Josefa Castillo SUPPLEMENTARY METHODS 1. Selection of genomic sequences for ChIP analysis To select the sequences for ChIP analysis in the five putative target genes, namely, PADI3, ZDHHC2, RGS4, EFNA5 and KAT2B, the genomic region corresponding to the gene was downloaded from Ensembl. Then, zoom was applied to see in detail the promoter, enhancers and regulatory sequences. The details for HCT116 cells were then recovered and the target sequences for factor binding examined. Obviously, there are not data for ZNF518B, but special attention was paid to the target sequences of other zinc-finger containing factors. Finally, the regions that may putatively bind ZNF518B were selected and primers defining amplicons spanning such sequences were searched out. Supplementary Figure S3 gives the location of the amplicons used in each gene. 2. Obtaining the raw data and generating the BAM files for in silico analysis of the effects of EHMT2 and EZH2 silencing The data of siEZH2 (SRR6384524), siG9a (SRR6384526) and siNon-target (SRR6384521) in HCT116 cell line, were downloaded from SRA (Bioproject PRJNA422822, https://www.ncbi. nlm.nih.gov/bioproject/), using SRA-tolkit (https://ncbi.github.io/sra-tools/). All data correspond to RNAseq single end. doBasics = TRUE doAll = FALSE $ fastq-dump -I --split-files SRR6384524 Data quality was checked using the software fastqc (https://www.bioinformatics.babraham. ac.uk /projects/fastqc/). The first low quality removing nucleotides were removed using FASTX- Toolkit (http://hannonlab.cshl.edu/fastxtoolkit/). -
KLF3 and PAX6 Are Candidate Driver Genes in Late-Stage, MSI-Hypermutated Endometrioid
medRxiv preprint doi: https://doi.org/10.1101/2021.04.26.21256125; this version posted April 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license. 1 KLF3 and PAX6 are candidate driver genes in late-stage, MSI-hypermutated endometrioid 2 endometrial carcinomas 3 4 Meghan L. Rudd1,#a, Nancy F. Hansen1, Xiaolu Zhang1#b, Mary Ellen Urick1, Suiyuan Zhang2, 5 Maria J. Merino3, National Institutes of Health Intramural Sequencing Center Comparative 6 Sequencing Program4; James C. Mullikin1, Lawrence C. Brody5, and Daphne W. Bell1* 7 8 1 Cancer Genetics and Comparative Genomics Branch, National Human Genome Research 9 Institute, National Institutes of Health, Bethesda, Maryland, United States of America. 10 2 Computational and Statistical Genomics Branch, National Human Genome Research Institute, 11 National Institutes of Health, Bethesda, Maryland, United States of America. 12 3 Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National 13 Institutes of Health, Bethesda, Maryland, United States of America. 14 4 NIH Intramural Sequencing Center, National Human Genome Research Institute, National 15 Institutes of Health, Rockville, Maryland, United States of America. 16 5 Medical Genomics and Metabolic Genetics Branch, National Human Genome Research 17 Institute, National Institutes of Health, Bethesda, Maryland, United States of America. 18 #a Current address: NIH Training Center, Workforce Support and Development Division, 19 National Institutes of Health, Bethesda, Maryland, United States of America. -
Genetic Characterization of Greek Population Isolates Reveals Strong Genetic Drift at Missense and Trait-Associated Variants
ARTICLE Received 22 Apr 2014 | Accepted 22 Sep 2014 | Published 6 Nov 2014 DOI: 10.1038/ncomms6345 OPEN Genetic characterization of Greek population isolates reveals strong genetic drift at missense and trait-associated variants Kalliope Panoutsopoulou1,*, Konstantinos Hatzikotoulas1,*, Dionysia Kiara Xifara2,3, Vincenza Colonna4, Aliki-Eleni Farmaki5, Graham R.S. Ritchie1,6, Lorraine Southam1,2, Arthur Gilly1, Ioanna Tachmazidou1, Segun Fatumo1,7,8, Angela Matchan1, Nigel W. Rayner1,2,9, Ioanna Ntalla5,10, Massimo Mezzavilla1,11, Yuan Chen1, Chrysoula Kiagiadaki12, Eleni Zengini13,14, Vasiliki Mamakou13,15, Antonis Athanasiadis16, Margarita Giannakopoulou17, Vassiliki-Eirini Kariakli5, Rebecca N. Nsubuga18, Alex Karabarinde18, Manjinder Sandhu1,8, Gil McVean2, Chris Tyler-Smith1, Emmanouil Tsafantakis12, Maria Karaleftheri16, Yali Xue1, George Dedoussis5 & Eleftheria Zeggini1 Isolated populations are emerging as a powerful study design in the search for low-frequency and rare variant associations with complex phenotypes. Here we genotype 2,296 samples from two isolated Greek populations, the Pomak villages (HELIC-Pomak) in the North of Greece and the Mylopotamos villages (HELIC-MANOLIS) in Crete. We compare their genomic characteristics to the general Greek population and establish them as genetic isolates. In the MANOLIS cohort, we observe an enrichment of missense variants among the variants that have drifted up in frequency by more than fivefold. In the Pomak cohort, we find novel associations at variants on chr11p15.4 showing large allele frequency increases (from 0.2% in the general Greek population to 4.6% in the isolate) with haematological traits, for example, with mean corpuscular volume (rs7116019, P ¼ 2.3 Â 10 À 26). We replicate this association in a second set of Pomak samples (combined P ¼ 2.0 Â 10 À 36). -
Chromophobe Renal Cell Carcinoma with and Without Sarcomatoid Change: a Clinicopathological, Comparative Genomic Hybridization, and Whole-Exome Sequencing Study
Am J Transl Res 2015;7(11):2482-2499 www.ajtr.org /ISSN:1943-8141/AJTR0014993 Original Article Chromophobe renal cell carcinoma with and without sarcomatoid change: a clinicopathological, comparative genomic hybridization, and whole-exome sequencing study Yuan Ren1*, Kunpeng Liu1*, Xueling Kang3, Lijuan Pang1, Yan Qi1, Zhenyan Hu1, Wei Jia1, Haijun Zhang1, Li Li1, Jianming Hu1, Weihua Liang1, Jin Zhao1, Hong Zou1*, Xianglin Yuan2, Feng Li1* 1Department of Pathology, School of Medicine, First Affiliated Hospital, Shihezi University, Key Laboratory of Xinjiang Endemic and Ethnic Diseases, Ministry of Education of China, Shihezi, China; 2Tongji Hospital Cancer Center, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; 3Department of Pathology, Shanghai General Hospital, Shanghai, China. *Equal contributors. Received August 24, 2015; Accepted October 13, 2015; Epub November 15, 2015; Published November 30, 2015 Abstract: Chromophobe renal cell carcinomas (CRCC) with and without sarcomatoid change have different out- comes; however, fewstudies have compared their genetic profiles. Therefore, we identified the genomic alteration- sin CRCC common type (CRCC C) (n=8) and CRCC with sarcomatoid change (CRCC S) (n=4) using comparative genomic hybridization (CGH) and whole-exome sequencing. The CGH profiles showed that the CRCC C group had more chromosomal losses (72 vs. 18) but fewer chromosomal gains (23 vs. 57) than the CRCC S group. Losses of chromosomes 1p, 8p21-23, 10p16-20, 10p12-ter, 13p20-30, and 17p13 and gains of chromosomes 1q11, 1q21-23, 1p13-15, 2p23-24, and 3p21-ter differed between the groups. Whole-exome sequencing showed that the mutational status of 270 genes differed between CRCC (n=12) and normal renal tissues (n=18). -
The Effect of Compound L19 on Human Colorectal Cells (DLD-1)
Stephen F. Austin State University SFA ScholarWorks Electronic Theses and Dissertations Spring 5-16-2018 The Effect of Compound L19 on Human Colorectal Cells (DLD-1) Sepideh Mohammadhosseinpour [email protected] Follow this and additional works at: https://scholarworks.sfasu.edu/etds Part of the Biotechnology Commons Tell us how this article helped you. Repository Citation Mohammadhosseinpour, Sepideh, "The Effect of Compound L19 on Human Colorectal Cells (DLD-1)" (2018). Electronic Theses and Dissertations. 188. https://scholarworks.sfasu.edu/etds/188 This Thesis is brought to you for free and open access by SFA ScholarWorks. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of SFA ScholarWorks. For more information, please contact [email protected]. The Effect of Compound L19 on Human Colorectal Cells (DLD-1) Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License. This thesis is available at SFA ScholarWorks: https://scholarworks.sfasu.edu/etds/188 The Effect of Compound L19 on Human Colorectal Cells (DLD-1) By Sepideh Mohammadhosseinpour, Master of Science Presented to the Faculty of the Graduate School of Stephen F. Austin State University In Partial Fulfillment Of the Requirements For the Degree of Master of Science in Biotechnology STEPHEN F. AUSTIN STATE UNIVERSITY May, 2018 The Effect of Compound L19 on Human Colorectal Cells (DLD-1) By Sepideh Mohammadhosseinpour, Master of Science APPROVED: Dr. Beatrice A. Clack, Thesis Director Dr. Josephine Taylor, Committee Member Dr. Rebecca Parr, Committee Member Dr. Stephen Mullin, Committee Member Pauline Sampson, Ph.D. -
Clinical, Molecular, and Immune Analysis of Dabrafenib-Trametinib
Supplementary Online Content Chen G, McQuade JL, Panka DJ, et al. Clinical, molecular and immune analysis of dabrafenib-trametinib combination treatment for metastatic melanoma that progressed during BRAF inhibitor monotherapy: a phase 2 clinical trial. JAMA Oncology. Published online April 28, 2016. doi:10.1001/jamaoncol.2016.0509. eMethods. eReferences. eTable 1. Clinical efficacy eTable 2. Adverse events eTable 3. Correlation of baseline patient characteristics with treatment outcomes eTable 4. Patient responses and baseline IHC results eFigure 1. Kaplan-Meier analysis of overall survival eFigure 2. Correlation between IHC and RNAseq results eFigure 3. pPRAS40 expression and PFS eFigure 4. Baseline and treatment-induced changes in immune infiltrates eFigure 5. PD-L1 expression eTable 5. Nonsynonymous mutations detected by WES in baseline tumors This supplementary material has been provided by the authors to give readers additional information about their work. © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 eMethods Whole exome sequencing Whole exome capture libraries for both tumor and normal samples were constructed using 100ng genomic DNA input and following the protocol as described by Fisher et al.,3 with the following adapter modification: Illumina paired end adapters were replaced with palindromic forked adapters with unique 8 base index sequences embedded within the adapter. In-solution hybrid selection was performed using the Illumina Rapid Capture Exome enrichment kit with 38Mb target territory (29Mb baited). The targeted region includes 98.3% of the intervals in the Refseq exome database. Dual-indexed libraries were pooled into groups of up to 96 samples prior to hybridization.