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The human olfactory transcriptome
2016
BMC Genomics
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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
doi:10.1186/s12864-016-2960-3
pmid:27515280
pmcid:PMC4982115
fatcat:hgxwhfsnufawtpm4pv345dg2ue
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... 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.
Genic insights from integrated human proteomics in GeneCards
2016
Database: The Journal of Biological Databases and Curation
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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
2013
Journal of Proteome Research
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The Model Organism Protein Expression Database (MOPED, http://moped.proteinspire.org), 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
doi:10.1021/pr400884c
pmid:24350770
pmcid:PMC4039175
fatcat:7hfwgk62abesjl7b63gieste2y
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... 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.
Rational confederation of genes and diseases: NGS interpretation via GeneCards, MalaCards and VarElect
2017
BioMedical Engineering OnLine
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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
doi:10.1186/s12938-017-0359-2
pmid:28830434
pmcid:PMC5568599
fatcat:nr5iblpqh5bn5glqnrgelrdehm
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... for NGS interpretation as well as for large scale bioinformatic analyses.
MOESM2 of Genome analysis and knowledge-driven variant interpretation with TGex
2019
Figshare
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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
2019
BMC Medical Genomics
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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,
doi:10.1186/s12920-019-0647-8
pmid:31888639
pmcid:PMC6937949
fatcat:ixi7j3mqqzflrgzaj5wwwb3xjm
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... 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 http://tgex.genecards.org/.
GeneHancer: genome-wide integration of enhancers and target genes in GeneCards
2017
Database: The Journal of Biological Databases and Curation
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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
2020
PLoS Genetics
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(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
2016
BMC Genomics
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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
2020
Nucleic Acids Research
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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
doi:10.1093/nar/gkaa921
pmid:33106848
pmcid:PMC7779037
fatcat:nodb7xauq5fbzlw5qdlm66jni4
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... 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 https://rnacentral.org.
Rare Variant Burden Analysis within Enhancers Identifies CAV1 as an ALS Risk Gene
2020
Cell Reports
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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]
2020
biorxiv/medrxiv
pre-print
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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
2020
eLife
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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
2011
Neuron
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., 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
2015
Frontiers in Ecology and Evolution
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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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