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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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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. -
OR1J1 Rabbit Pab Antibody
OR1J1 rabbit pAb antibody Catalog No : Source: Concentration : Mol.Wt. (Da): A19043 Rabbit 1 mg/ml Applications WB,ELISA Reactivity Human Dilution WB 1:500-2000 ELISA 1:5000-20000 Storage -20°C/1 year Specificity OR1J1 Polyclonal Antibody detects endogenous levels of protein. Source / Purification The antibody was affinity-purified from rabbit antiserum by affinity- chromatography using epitope-specific immunogen. Immunogen Synthesized peptide derived from part region of human protein Uniprot No Q8NGS3 Alternative names Form Liquid in PBS containing 50% glycerol, and 0.02% sodium azide. Clonality Polyclonal Isotype IgG Conjugation Background olfactory receptor family 1 subfamily J member 1(OR1J1) Homo sapiens Olfactory receptors interact with odorant molecules in the nose, to initiate a neuronal response that triggers the perception of a smell. The olfactory receptor proteins are members of a large family of G-protein-coupled receptors (GPCR) arising from single coding-exon genes. Olfactory receptors share a 7-transmembrane domain structure with many neurotransmitter and hormone receptors and are responsible for the recognition and G protein- mediated transduction of odorant signals. The olfactory receptor gene family is the largest in the genome. The nomenclature assigned to the olfactory receptor genes and proteins for this organism is independent of other organisms. [provided by RefSeq, Jul 2008], Other OR1J1, Olfactory receptor 1J1 (Olfactory receptor OR9-18) Produtc Images: A AAB Biosciences Products www.aabsci.cn FOR RESEARCH USE ONLY. NOT FOR HUMAN OR DIAGNOSTIC USE. Application Key: WB-Western IP-Immunoprecipitation IHC-Immunohistochemistry ChIP-Chromatin Immunoprecipitation IF-Immunofluorescence F-Flow Cytometry E-P-ELISA-Peptide Species Cross-Reactivity Key: H-Human M-Mouse R-Rat Hm-Hamster Mk-Monkey Vir-Virus Mi-Mink C-Chicken Dm-D. -
Sequencing of 50 Human Exomes Reveals Adaptation to High Altitude
REPORTS Digestive and Kidney Diseases) and The University of Omnibus, with accession code GSE21661. These data, as Figs. S1 to S6 Luxembourg–Institute for Systems Biology Program to well as phenotype data, are also available on our Tables S1 to S12 C.D.H. T.S.S. was supported by NIH Genetics Training laboratory Web site, http://jorde-lab.genetics.utah. References Grant T32. All studies have been performed with edu. Please contact R.L.G. for access to DNA samples. informed consent approved by the Institutional Board of 10 March 2010; accepted 6 May 2010 Qinghai Medical College of Qinghai University in Supporting Online Material Published online 13 May 2010; Xining, Qinghai Province, People’s Republic of China. All www.sciencemag.org/cgi/content/full/science.1189406/DC1 10.1126/science.1189406 SNP genoptypes are deposited in Gene Expression Materials and Methods Include this information when citing this paper. also estimated single-nucleotide polymorphism Sequencing of 50 Human Exomes (SNP) probabilities and population allele frequen- cies for each site. A total of 151,825 SNPs were Reveals Adaptation to High Altitude inferred to have >50% probability of being var- iable within the Tibetan sample, and 101,668 had Xin Yi,1,2* Yu Liang,1,2* Emilia Huerta-Sanchez,3* Xin Jin,1,4* Zha Xi Ping Cuo,2,5* John E. Pool,3,6* >99% SNP probability (table S2). Sanger se- Xun Xu,1 Hui Jiang,1 Nicolas Vinckenbosch,3 Thorfinn Sand Korneliussen,7 Hancheng Zheng,1,4 quencing validated 53 of 56 SNPs that had at least Tao Liu,1 Weiming He,1,8 Kui Li,2,5 Ruibang Luo,1,4 Xifang Nie,1 Honglong Wu,1,9 Meiru Zhao,1 95% SNP probability and minor allele frequencies Hongzhi Cao,1,9 Jing Zou,1 Ying Shan,1,4 Shuzheng Li,1 Qi Yang,1 Asan,1,2 Peixiang Ni,1 Geng Tian,1,2 between 3% and 50%. -
Incorporating Genetic Networks Into Case-Control Association Studies with High-Dimensional DNA Methylation Data Kipoong Kim and Hokeun Sun*
Kim and Sun BMC Bioinformatics (2019) 20:510 https://doi.org/10.1186/s12859-019-3040-x METHODOLOGY ARTICLE Open Access Incorporating genetic networks into case-control association studies with high-dimensional DNA methylation data Kipoong Kim and Hokeun Sun* Abstract Background: In human genetic association studies with high-dimensional gene expression data, it has been well known that statistical selection methods utilizing prior biological network knowledge such as genetic pathways and signaling pathways can outperform other methods that ignore genetic network structures in terms of true positive selection. In recent epigenetic research on case-control association studies, relatively many statistical methods have been proposed to identify cancer-related CpG sites and their corresponding genes from high-dimensional DNA methylation array data. However, most of existing methods are not designed to utilize genetic network information although methylation levels between linked genes in the genetic networks tend to be highly correlated with each other. Results: We propose new approach that combines data dimension reduction techniques with network-based regularization to identify outcome-related genes for analysis of high-dimensional DNA methylation data. In simulation studies, we demonstrated that the proposed approach overwhelms other statistical methods that do not utilize genetic network information in terms of true positive selection. We also applied it to the 450K DNA methylation array data of the four breast invasive carcinoma cancer subtypes from The Cancer Genome Atlas (TCGA) project. Conclusions: The proposed variable selection approach can utilize prior biological network information for analysis of high-dimensional DNA methylation array data. It first captures gene level signals from multiple CpG sites using data a dimension reduction technique and then performs network-based regularization based on biological network graph information. -
1 Genome-Wide Comparisons of Variation in Linkage Disequilibrium
Downloaded from genome.cshlp.org on September 30, 2021 - Published by Cold Spring Harbor Laboratory Press Genome-wide comparisons of variation in linkage disequilibrium Yik Y. Teo1,*, Andrew E. Fry1, Kanishka Bhattacharya1, Kerrin S. Small1, Dominic P. Kwiatkowski1,2, Taane G. Clark1,2 1 Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom 2 Wellcome Trust Sanger Institute, Hinxton, United Kingdom Running title: Genome-wide comparisons of LD Keywords: linkage disequilibrium, imputation, positive selection, meta-analysis, genome-wide association study * Corresponding author: Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford OX3 7BN, United Kingdom. Email: [email protected], phone: +44 1865 287712, fax: +44 1865 287 501. ABSTRACT Current genome-wide surveys of common diseases and complex traits fundamentally aim to detect indirect associations where the SNPs carrying the association signals are not biologically active but are in linkage disequilibrium (LD) with some unknown functional polymorphisms. Reproducing any novel discoveries from these genome-wide scans in independent studies is now a prerequisite for the putative findings to be accepted. Significant differences in patterns of LD between populations can affect the portability of phenotypic associations when the replication effort or meta-analyses are attempted in populations that are distinct from the original population which the genome-wide study is performed in. Here we introduce a novel method for genome-wide analyses of LD variations between populations that allow the identification of candidate regions with different patterns of LD. The evidence of LD variation provided by the introduced method correlated with the degree of differences in the frequencies of the most common haplotype across the populations. -
Anti-OR10V1 (Aa 280-309) Polyclonal Antibody (DPABH-21566) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use
Anti-OR10V1 (aa 280-309) polyclonal antibody (DPABH-21566) This product is for research use only and is not intended for diagnostic use. PRODUCT INFORMATION Antigen Description Olfactory receptors interact with odorant molecules in the nose, to initiate a neuronal response that triggers the perception of a smell. The olfactory receptor proteins are members of a large family of G-protein-coupled receptors (GPCR) arising from single coding-exon genes. Olfactory receptors share a 7-transmembrane domain structure with many neurotransmitter and hormone receptors and are responsible for the recognition and G protein-mediated transduction of odorant signals. The olfactory receptor gene family is the largest in the genome. The nomenclature assigned to the olfactory receptor genes and proteins for this organism is independent of other organisms. Immunogen Synthetic peptide conjugated to KLH, corresponding to a region within C terminal amino acids 280-309 of Human OR10V1 (NP_001005324.1). Isotype IgG Source/Host Rabbit Species Reactivity Human Purification Immunogen affinity purified Conjugate Unconjugated Applications WB Format Liquid Size 400 μl Buffer Constituent: 99% PBS Preservative 0.09% Sodium Azide Storage Store at 4°C (up to 6 months). For long term storage store at -20°C GENE INFORMATION 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 1 © Creative Diagnostics All Rights Reserved Gene Name OR10V1 olfactory receptor, family 10, subfamily V, member 2 [ Homo sapiens ] Official Symbol OR10V1 Synonyms OR10V1; olfactory receptor, family 10, subfamily V, member 1; OR11-256; olfactory receptor 10V1; olfactory receptor OR11-256; Entrez Gene ID 390201 Protein Refseq NP_001005324.1 UniProt ID Q8NGI7 Pathway GPCR downstream signaling; Olfactory transduction; Signal Transduction. -
WO 2019/068007 Al Figure 2
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/068007 Al 04 April 2019 (04.04.2019) W 1P O PCT (51) International Patent Classification: (72) Inventors; and C12N 15/10 (2006.01) C07K 16/28 (2006.01) (71) Applicants: GROSS, Gideon [EVIL]; IE-1-5 Address C12N 5/10 (2006.0 1) C12Q 1/6809 (20 18.0 1) M.P. Korazim, 1292200 Moshav Almagor (IL). GIBSON, C07K 14/705 (2006.01) A61P 35/00 (2006.01) Will [US/US]; c/o ImmPACT-Bio Ltd., 2 Ilian Ramon St., C07K 14/725 (2006.01) P.O. Box 4044, 7403635 Ness Ziona (TL). DAHARY, Dvir [EilL]; c/o ImmPACT-Bio Ltd., 2 Ilian Ramon St., P.O. (21) International Application Number: Box 4044, 7403635 Ness Ziona (IL). BEIMAN, Merav PCT/US2018/053583 [EilL]; c/o ImmPACT-Bio Ltd., 2 Ilian Ramon St., P.O. (22) International Filing Date: Box 4044, 7403635 Ness Ziona (E.). 28 September 2018 (28.09.2018) (74) Agent: MACDOUGALL, Christina, A. et al; Morgan, (25) Filing Language: English Lewis & Bockius LLP, One Market, Spear Tower, SanFran- cisco, CA 94105 (US). (26) Publication Language: English (81) Designated States (unless otherwise indicated, for every (30) Priority Data: kind of national protection available): AE, AG, AL, AM, 62/564,454 28 September 2017 (28.09.2017) US AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, 62/649,429 28 March 2018 (28.03.2018) US CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, (71) Applicant: IMMP ACT-BIO LTD. -
Olfactory Receptors in Non-Chemosensory Tissues
BMB Reports Invited Mini Review Olfactory receptors in non-chemosensory tissues NaNa Kang & JaeHyung Koo* Department of Brain Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 711-873, Korea Olfactory receptors (ORs) detect volatile chemicals that lead to freezing behavior (3-5). the initial perception of smell in the brain. The olfactory re- ORs are localized in the cilia of olfactory sensory neurons ceptor (OR) is the first protein that recognizes odorants in the (OSNs) in the olfactory epithelium (OE) and are activated by olfactory signal pathway and it is present in over 1,000 genes chemical cues, typically odorants at the molecular level, in mice. It is also the largest member of the G protein-coupled which lead to the perception of smell in the brain (6). receptors (GPCRs). Most ORs are extensively expressed in the Tremendous research was conducted since Buck and Axel iso- nasal olfactory epithelium where they perform the appropriate lated ORs as an OE-specific expression in 1991 (7). OR genes, physiological functions that fit their location. However, recent the largest family among the G protein-coupled receptors whole-genome sequencing shows that ORs have been found (GPCRs) (8), constitute more than 1,000 genes on the mouse outside of the olfactory system, suggesting that ORs may play chromosome (9, 10) and more than 450 genes in the human an important role in the ectopic expression of non-chemo- genome (11, 12). sensory tissues. The ectopic expressions of ORs and their phys- Odorant activation shows a distinct signal transduction iological functions have attracted more attention recently since pathway for odorant perception. -
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 -
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). -
Table S3. RAE Analysis of Well-Differentiated Liposarcoma
Table S3. RAE analysis of well-differentiated liposarcoma Model Chromosome Region start Region end Size q value freqX0* # genes Genes Amp 1 145009467 145122002 112536 0.097 21.8 2 PRKAB2,PDIA3P Amp 1 145224467 146188434 963968 0.029 23.6 10 CHD1L,BCL9,ACP6,GJA5,GJA8,GPR89B,GPR89C,PDZK1P1,RP11-94I2.2,NBPF11 Amp 1 147475854 148412469 936616 0.034 23.6 20 PPIAL4A,FCGR1A,HIST2H2BF,HIST2H3D,HIST2H2AA4,HIST2H2AA3,HIST2H3A,HIST2H3C,HIST2H4B,HIST2H4A,HIST2H2BE, HIST2H2AC,HIST2H2AB,BOLA1,SV2A,SF3B4,MTMR11,OTUD7B,VPS45,PLEKHO1 Amp 1 148582896 153398462 4815567 1.5E-05 49.1 152 PRPF3,RPRD2,TARS2,ECM1,ADAMTSL4,MCL1,ENSA,GOLPH3L,HORMAD1,CTSS,CTSK,ARNT,SETDB1,LASS2,ANXA9, FAM63A,PRUNE,BNIPL,C1orf56,CDC42SE1,MLLT11,GABPB2,SEMA6C,TNFAIP8L2,LYSMD1,SCNM1,TMOD4,VPS72, PIP5K1A,PSMD4,ZNF687,PI4KB,RFX5,SELENBP1,PSMB4,POGZ,CGN,TUFT1,SNX27,TNRC4,MRPL9,OAZ3,TDRKH,LINGO4, RORC,THEM5,THEM4,S100A10,S100A11,TCHHL1,TCHH,RPTN,HRNR,FLG,FLG2,CRNN,LCE5A,CRCT1,LCE3E,LCE3D,LCE3C,LCE3B, LCE3A,LCE2D,LCE2C,LCE2B,LCE2A,LCE4A,KPRP,LCE1F,LCE1E,LCE1D,LCE1C,LCE1B,LCE1A,SMCP,IVL,SPRR4,SPRR1A,SPRR3, SPRR1B,SPRR2D,SPRR2A,SPRR2B,SPRR2E,SPRR2F,SPRR2C,SPRR2G,LELP1,LOR,PGLYRP3,PGLYRP4,S100A9,S100A12,S100A8, S100A7A,S100A7L2,S100A7,S100A6,S100A5,S100A4,S100A3,S100A2,S100A16,S100A14,S100A13,S100A1,C1orf77,SNAPIN,ILF2, NPR1,INTS3,SLC27A3,GATAD2B,DENND4B,CRTC2,SLC39A1,CREB3L4,JTB,RAB13,RPS27,NUP210L,TPM3,C1orf189,C1orf43,UBAP2L,HAX1, AQP10,ATP8B2,IL6R,SHE,TDRD10,UBE2Q1,CHRNB2,ADAR,KCNN3,PMVK,PBXIP1,PYGO2,SHC1,CKS1B,FLAD1,LENEP,ZBTB7B,DCST2, DCST1,ADAM15,EFNA4,EFNA3,EFNA1,RAG1AP1,DPM3 Amp 1 -
Chr CNV Start CNV Stop Gene Gene Feature 1 37261312 37269719
chr CNV start CNV stop Gene Gene feature 1 37261312 37269719 Tmem131 closest upstream gene 1 37261312 37269719 Cnga3 closest downstream gene 1 41160869 41180390 Tmem182 closest upstream gene 1 41160869 41180390 2610017I09Rik closest downstream gene 1 66835123 66839616 1110028C15Rik in region 2 88714200 88719211 Olfr1206 closest upstream gene 2 88714200 88719211 Olfr1208 closest downstream gene 2 154840037 154846228 a in region 3 30065831 30417157 Mecom closest upstream gene 3 30065831 30417157 Arpm1 closest downstream gene 3 35476875 35495913 Sox2ot closest upstream gene 3 35476875 35495913 Atp11b closest downstream gene 3 39563408 39598697 Fat4 closest upstream gene 3 39563408 39598697 Intu closest downstream gene 3 94246481 94410611 Celf3 in region 3 94246481 94410611 Mrpl9 in region 3 94246481 94410611 Riiad1 in region 3 94246481 94410611 Snx27 in region 3 104311901 104319916 Lrig2 in region 3 144613709 144619149 Clca6 in region 3 144613709 144619149 Clca6 in region 4 108673 137301 Vmn1r2 closest downstream gene 4 3353037 5882883 6330407A03Rik in region 4 3353037 5882883 Chchd7 in region 4 3353037 5882883 Fam110b in region 4 3353037 5882883 Impad1 in region 4 3353037 5882883 Lyn in region 4 3353037 5882883 Mos in region 4 3353037 5882883 Penk in region 4 3353037 5882883 Plag1 in region 4 3353037 5882883 Rps20 in region 4 3353037 5882883 Sdr16c5 in region 4 3353037 5882883 Sdr16c6 in region 4 3353037 5882883 Tgs1 in region 4 3353037 5882883 Tmem68 in region 4 5919294 6304249 Cyp7a1 in region 4 5919294 6304249 Sdcbp in region 4 5919294