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The human olfactory transcriptome

Tsviya Olender, Ifat Keydar, Jayant M. Pinto, Pavlo Tatarskyy, Anna Alkelai, Ming-Shan Chien, Simon Fishilevich, Diego Restrepo, Hiroaki Matsunami, Yoav Gilad, Doron Lancet
2016 BMC Genomics  
Olfaction is a versatile sensory mechanism for detecting thousands of volatile odorants. Although molecular basis of odorant signaling is relatively well understood considerable gaps remain in the complete charting of all relevant gene products. To address this challenge, we applied RNAseq to four well-characterized human olfactory epithelial samples and compared the results to novel and published mouse olfactory epithelium as well as 16 human control tissues. Results: We identified 194
more » ... ctory receptor (OR) genes that are overexpressed in human olfactory tissues vs. controls. The highest overexpression is seen for lipocalins and bactericidal/permeability-increasing (BPI)-fold proteins, which in other species include secreted odorant carriers. Mouse-human discordance in orthologous lipocalin expression suggests different mammalian evolutionary paths in this family. Of the overexpressed genes 36 have documented olfactory function while for 158 there is little or no previous such functional evidence. The latter group includes GPCRs, neuropeptides, solute carriers, transcription factors and biotransformation enzymes. Many of them may be indirectly implicated in sensory function, and~70 % are over expressed also in mouse olfactory epithelium, corroborating their olfactory role. Nearly 90 % of the intact OR repertoire, and~60 % of the OR pseudogenes are expressed in the olfactory epithelium, with the latter showing a 3-fold lower expression. ORs transcription levels show a 1000-fold inter-paralog variation, as well as significant inter-individual differences. We assembled 160 transcripts representing 100 intact OR genes. These include 1-4 short 5' non-coding exons with considerable alternative splicing and long last exons that contain the coding region and 3' untranslated region of highly variable length. Notably, we identified 10 ORs with an intact open reading frame but with seemingly non-functional transcripts, suggesting a yet unreported OR pseudogenization mechanism. Analysis of the OR upstream regions indicated an enrichment of the homeobox family transcription factor binding sites and a consensus localization of a specific transcription factor binding site subfamily (Olf/EBF). Conclusions: We provide an overview of expression levels of ORs and auxiliary genes in human olfactory epithelium. This forms a transcriptomic view of the entire OR repertoire, and reveals a large number of over-expressed uncharacterized human non-receptor genes, providing a platform for future discovery.
doi:10.1186/s12864-016-2960-3 pmid:27515280 pmcid:PMC4982115 fatcat:hgxwhfsnufawtpm4pv345dg2ue

Genic insights from integrated human proteomics in GeneCards

Simon Fishilevich, Shahar Zimmerman, Asher Kohn, Tsippi Iny Stein, Tsviya Olender, Eugene Kolker, Marilyn Safran, Doron Lancet
2016 Database: The Journal of Biological Databases and Curation  
GeneCards is a one-stop shop for searchable human gene annotations
doi:10.1093/database/baw030 pmid:27048349 pmcid:PMC4820835 fatcat:o2qmsm6l2ve7bpyvhbj2pnu6re

MOPED Enables Discoveries through Consistently Processed Proteomics Data

Roger Higdon, Elizabeth Stewart, Larissa Stanberry, Winston Haynes, John Choiniere, Elizabeth Montague, Nathaniel Anderson, Gregory Yandl, Imre Janko, William Broomall, Simon Fishilevich, Doron Lancet (+2 others)
2013 Journal of Proteome Research  
The Model Organism Protein Expression Database (MOPED,, is an expanding proteomics resource to enable biological and biomedical discoveries. MOPED aggregates simple, standardized and consistently processed summaries of protein expression and metadata from proteomics (mass spectrometry) experiments from human and model organisms (mouse, worm and yeast). The latest version of MOPED adds new estimates of protein abundance and concentration, as well as relative
more » ... ential) expression data. MOPED provides a new updated query interface that allows users to explore information by organism, tissue, localization, condition, experiment, or keyword. MOPED supports the Human Proteome Project's efforts to generate chromosome and diseases specific proteomes by providing links from proteins to chromosome and disease information, as well as many complementary resources. MOPED supports a new omics metadata checklist in order to harmonize data integration, analysis and use. MOPED's development is driven by the user community, which spans 90 countries guiding future development that will transform MOPED into a multi-omics resource. MOPED encourages users to submit data in a simple format. They can use the metadata a checklist generate a data publication for this submission. As a result, MOPED will provide even greater insights into complex biological processes and systems and enable deeper and more comprehensive biological and biomedical discoveries.
doi:10.1021/pr400884c pmid:24350770 pmcid:PMC4039175 fatcat:7hfwgk62abesjl7b63gieste2y

Rational confederation of genes and diseases: NGS interpretation via GeneCards, MalaCards and VarElect

Noa Rappaport, Simon Fishilevich, Ron Nudel, Michal Twik, Frida Belinky, Inbar Plaschkes, Tsippi Iny Stein, Dana Cohen, Danit Oz-Levi, Marilyn Safran, Doron Lancet
2017 BioMedical Engineering OnLine  
A key challenge in the realm of human disease research is next generation sequencing (NGS) interpretation, whereby identified filtered variant-harboring genes are associated with a patient's disease phenotypes. This necessitates bioinformatics tools linked to comprehensive knowledgebases. The GeneCards suite databases, which include GeneCards (human genes), MalaCards (human diseases) and PathCards (human pathways) together with additional tools, are presented with the focus on MalaCards utility
more » ... for NGS interpretation as well as for large scale bioinformatic analyses.
doi:10.1186/s12938-017-0359-2 pmid:28830434 pmcid:PMC5568599 fatcat:nr5iblpqh5bn5glqnrgelrdehm

MOESM2 of Genome analysis and knowledge-driven variant interpretation with TGex

Dvir Dahary, Yaron Golan, Yaron Mazor, Ofer Zelig, Ruth Barshir, Michal Twik, Tsippi Iny Stein, Guy Rosner, Revital Kariv, Fei Chen, Qiang Zhang, Yiping Shen (+3 others)
2019 Figshare  
Additional file 2. TGex report for the trichohepatoenteric syndrome Demo example
doi:10.6084/m9.figshare.11480619 fatcat:3hgdptj3rbgxldp5sb354ma7m4

Genome analysis and knowledge-driven variant interpretation with TGex

Dvir Dahary, Yaron Golan, Yaron Mazor, Ofer Zelig, Ruth Barshir, Michal Twik, Tsippi Iny Stein, Guy Rosner, Revital Kariv, Fei Chen, Qiang Zhang, Yiping Shen (+3 others)
2019 BMC Medical Genomics  
The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient's phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants. We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform,
more » ... remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex's main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex's broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards' recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. Examining use-cases from a variety of TGex users world-wide, we demonstrate its high diagnostic yields (42% for single exome and 50% for trios in 1500 rare genetic disease cases) and critical actionable genetic findings. The platform's support for integration with EHR and LIMS through dedicated APIs facilitates automated retrieval of patient data for TGex's customizable reporting engine, establishing a rapid and cost-effective workflow for an entire range of clinical genetic testing, including rare disorders, cancer predisposition, tumor biopsies and health screening. TGex is an innovative tool for the annotation, analysis and prioritization of coding and non-coding genomic variants. It provides access to an extensive knowledgebase of genomic annotations, with intuitive and flexible configuration options, allows quick adaptation, and addresses various workflow requirements. It thus simplifies and accelerates variant interpretation in clinical genetics workflows, with remarkable diagnostic yield, as exemplified in the described use cases. TGex is available at
doi:10.1186/s12920-019-0647-8 pmid:31888639 pmcid:PMC6937949 fatcat:ixi7j3mqqzflrgzaj5wwwb3xjm

GeneHancer: genome-wide integration of enhancers and target genes in GeneCards

Simon Fishilevich, Ron Nudel, Noa Rappaport, Rotem Hadar, Inbar Plaschkes, Tsippi Iny Stein, Naomi Rosen, Asher Kohn, Michal Twik, Marilyn Safran, Doron Lancet, Dana Cohen
2017 Database: The Journal of Biological Databases and Curation  
Citation details: Fishilevich,S., Nudel,R., Rappaport,N. et al. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards.  ... 
doi:10.1093/database/bax028 pmid:28605766 pmcid:PMC5467550 fatcat:xslg453wargdbalhgq7rmj73pq

Genome-wide association study identifies 16 genomic regions associated with circulating cytokines at birth

Yunpeng Wang, Ron Nudel, Michael E. Benros, Kristin Skogstrand, Simon Fishilevich, Doron Lancet, Jiangming Sun, David M. Hougaard, Ole A. Andreassen, Preben Bo Mortensen, Alfonso Buil, Thomas F. Hansen (+4 others)
2020 PLoS Genetics  
(PDF) Software: Ron Nudel, Simon Fishilevich, Doron Lancet. Supervision: Michael E. Benros, Thomas Werge.  ... 
doi:10.1371/journal.pgen.1009163 pmid:33227023 fatcat:3dlkgzfyxjdjlff6t4gkycktf4

VarElect: the phenotype-based variation prioritizer of the GeneCards Suite

Gil Stelzer, Inbar Plaschkes, Danit Oz-Levi, Anna Alkelai, Tsviya Olender, Shahar Zimmerman, Michal Twik, Frida Belinky, Simon Fishilevich, Ron Nudel, Yaron Guan-Golan, David Warshawsky (+9 others)
2016 BMC Genomics  
These relations include shared pathways, shared drugs/compounds, shared protein domains, shared mouse phenotypes, shared normal tissue expression patterns (Fishilevich et al. submitted) and shared publications  ... 
doi:10.1186/s12864-016-2722-2 pmid:27357693 pmcid:PMC4928145 fatcat:zbmio3et65h23phhmmgyve46z4

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases

RNAcentral Consortium, Blake A Sweeney, Anton I Petrov, Carlos E Ribas, Robert D Finn, Alex Bateman, Maciej Szymanski, Wojciech M Karlowski, Stefan E Seemann, Jan Gorodkin, Jamie J Cannone, Robin R Gutell (+81 others)
2020 Nucleic Acids Research  
RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world's largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and
more » ... izable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at
doi:10.1093/nar/gkaa921 pmid:33106848 pmcid:PMC7779037 fatcat:nodb7xauq5fbzlw5qdlm66jni4

Rare Variant Burden Analysis within Enhancers Identifies CAV1 as an ALS Risk Gene

Johnathan Cooper-Knock, Sai Zhang, Kevin P. Kenna, Tobias Moll, John P. Franklin, Samantha Allen, Helia Ghahremani Nezhad, Alfredo Iacoangeli, Nancy Y. Yacovzada, Chen Eitan, Eran Hornstein, Eran Ehilak (+42 others)
2020 Cell Reports  
As previously described (Fishilevich et al., 2017) , we identified high-quality manually curated links between enhancers and coding genes based on agreement between correlated expression between genes  ...  within Enhancers and Coding Regions Linked to CAV1 and CAV2 (A) Pipeline for variant filtering and burden testing; enhancers are first associated with genes based on epigenetic and transcriptome data (Fishilevich  ... 
doi:10.1016/j.celrep.2020.108456 pmid:33264630 pmcid:PMC7710676 fatcat:buuumxa6azachcx6cx26jjnr6a

Dissecting the DNA binding landscape and gene regulatory network of p63 and p53 [article]

Konstantin Riege, Helene Kretzmer, Simon S McDade, Steve Hoffmann, Martin Fischer
2020 biorxiv/medrxiv   pre-print
10) through binding within 5 kb from their TSS or through double-elite enhancer-gene associations (Fishilevich et al., 2017) .  ...  10) that are linked through TSS proximity (within 5 kb) or double-elite enhancer:gene associations (Fishilevich et al., 2017) to genes with a |p63 Expression Score|| !  ... 
doi:10.1101/2020.06.11.145540 fatcat:dx2mmb55kfbwhedj23iimnkos4

Dissecting the DNA binding landscape and gene regulatory network of p63 and p53

Konstantin Riege, Helene Kretzmer, Arne Sahm, Simon S McDade, Steve Hoffmann, Martin Fischer
2020 eLife  
We only used p63 binding sites supported by at least half of the datasets (≥10) that are linked through TSS proximity (within 5 kb) or double-elite enhancer:gene associations 267 (Fishilevich et al.,  ...  To resolve this 260 issue, we integrated the p63 binding data and the p63 Expression Score based on 261 enhancer:gene association information (Fishilevich et al., 2017) in addition to proximity 262 binding  ... 
doi:10.7554/elife.63266 pmid:33263276 pmcid:PMC7735755 fatcat:witk75plerbsznbvvgo76imzg4

DSL-Notch Signaling in the Drosophila Brain in Response to Olfactory Stimulation

Toby Lieber, Simon Kidd, Gary Struhl
2011 Neuron  
., 2005; Fishilevich and Vosshall, 2005) , and CO 2 activates Gr21a receptor expressing ORNs that project to V (Couto et al., 2005; Scott et al., 2001; Suh et al., 2004) .  ...  These receptors are expressed in unique populations of ORNs, each of which projects to a single glomerulus (Couto et al., 2005; Fishilevich and Vosshall, 2005; Scott et al., 2001; Suh et al., 2004) and  ... 
doi:10.1016/j.neuron.2010.12.015 pmid:21315258 pmcid:PMC3216490 fatcat:biciigb6vfho7ninnnv7e5auqi

The role of cVA and the Odorant binding protein Lush in social and sexual behavior in Drosophila melanogaster

Jean-Christophe Billeter, Joel D. Levine
2015 Frontiers in Ecology and Evolution  
Other factors are surely also at play such as the availability of food (Simon et al., 2011) and the genotype of males (Saltz and Foley, 2011) , but cVA is likely part of a key mechanism in social niche  ...  Interestingly, mutants for the Or47b receptor, another Or expressed in trichoid sensilla, are not attracted to Oe − flies (Couto et al., 2005; Fishilevich and Vosshall, 2005; Wang et al., 2011) .  ... 
doi:10.3389/fevo.2015.00075 fatcat:pq4ye6n2k5cnhdcjgnfxycw3sy
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