Characterizing the expression of the human olfactory receptor gene family using a novel DNA microarray View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2007-05

AUTHORS

Xiaohong Zhang, Omar De la Cruz, Jayant M Pinto, Dan Nicolae, Stuart Firestein, Yoav Gilad

ABSTRACT

BACKGROUND: Olfactory receptor (OR) genes were discovered more than a decade ago, when Buck and Axel observed that, in rats, certain G-protein coupled receptors are expressed exclusively in the olfactory epithelium. Subsequently, protein sequence similarity was used to identify entire OR gene repertoires of a number of mammalian species, but only in mouse were these predictions followed up by expression studies in olfactory epithelium. To rectify this, we have developed a DNA microarray that contains probes for most predicted human OR loci and used that array to examine OR gene expression profiles in olfactory epithelium tissues from three individuals. RESULTS: We detected expression of 437 (76%) human OR genes in these olfactory epithelia. Interestingly, we detected widespread expression of OR pseudogenes, an observation that may shed light on the mechanism of OR gene choice in the olfactory sensory neurons. To address the hypothesis that OR genes may carry out additional functions, we also characterized the expression of OR genes in a number of non-olfactory tissues. CONCLUSION: While our results corroborate the functional annotation of the majority of predicted human odorant receptors, we find that a large number of putative human OR genes are expressed in non-olfactory tissues, sometimes exclusively so. Our evolutionary analysis of ectopically expressed human OR genes does not lend support to the hypothesis that these genes have alternative functions. More... »

PAGES

r86

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/gb-2007-8-5-r86

DOI

http://dx.doi.org/10.1186/gb-2007-8-5-r86

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1000783702

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17509148


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/gb-2007-8-5-r86'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/gb-2007-8-5-r86'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/gb-2007-8-5-r86'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/gb-2007-8-5-r86'


 

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