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A purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers

BACKGROUND: In most mammals, a vast array of genes coding for chemosensory receptors mediates olfaction. Odorant receptor (OR) genes generally constitute the largest multifamily (> 1100 intact members in the mouse). From the whole pool, each olfactory neuron expresses a single OR allele following...

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Autores principales: Degl’Innocenti, Andrea, Meloni, Gabriella, Mazzolai, Barbara, Ciofani, Gianni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6744719/
https://www.ncbi.nlm.nih.gov/pubmed/31521109
http://dx.doi.org/10.1186/s12859-019-3012-1
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author Degl’Innocenti, Andrea
Meloni, Gabriella
Mazzolai, Barbara
Ciofani, Gianni
author_facet Degl’Innocenti, Andrea
Meloni, Gabriella
Mazzolai, Barbara
Ciofani, Gianni
author_sort Degl’Innocenti, Andrea
collection PubMed
description BACKGROUND: In most mammals, a vast array of genes coding for chemosensory receptors mediates olfaction. Odorant receptor (OR) genes generally constitute the largest multifamily (> 1100 intact members in the mouse). From the whole pool, each olfactory neuron expresses a single OR allele following poorly characterized mechanisms termed OR gene choice. OR genes are found in genomic aggregations known as clusters. Nearby enhancers, named elements, are crucial regulators of OR gene choice. Despite their importance, searching for new elements is burdensome. Other chemosensory receptor genes responsible for smell adhere to expression modalities resembling OR gene choice, and are arranged in genomic clusters — often with chromosomal linkage to OR genes. Still, no elements are known for them. RESULTS: Here we present an inexpensive framework aimed at predicting elements. We redefine cluster identity by focusing on multiple receptor gene families at once, and exemplify thirty — not necessarily OR-exclusive — novel candidate enhancers. CONCLUSIONS: The pipeline we introduce could guide future in vivo work aimed at discovering/validating new elements. In addition, our study provides an updated and comprehensive classification of all genomic loci responsible for the transduction of olfactory signals in mammals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-3012-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-67447192019-09-18 A purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers Degl’Innocenti, Andrea Meloni, Gabriella Mazzolai, Barbara Ciofani, Gianni BMC Bioinformatics Research Article BACKGROUND: In most mammals, a vast array of genes coding for chemosensory receptors mediates olfaction. Odorant receptor (OR) genes generally constitute the largest multifamily (> 1100 intact members in the mouse). From the whole pool, each olfactory neuron expresses a single OR allele following poorly characterized mechanisms termed OR gene choice. OR genes are found in genomic aggregations known as clusters. Nearby enhancers, named elements, are crucial regulators of OR gene choice. Despite their importance, searching for new elements is burdensome. Other chemosensory receptor genes responsible for smell adhere to expression modalities resembling OR gene choice, and are arranged in genomic clusters — often with chromosomal linkage to OR genes. Still, no elements are known for them. RESULTS: Here we present an inexpensive framework aimed at predicting elements. We redefine cluster identity by focusing on multiple receptor gene families at once, and exemplify thirty — not necessarily OR-exclusive — novel candidate enhancers. CONCLUSIONS: The pipeline we introduce could guide future in vivo work aimed at discovering/validating new elements. In addition, our study provides an updated and comprehensive classification of all genomic loci responsible for the transduction of olfactory signals in mammals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-3012-1) contains supplementary material, which is available to authorized users. BioMed Central 2019-09-14 /pmc/articles/PMC6744719/ /pubmed/31521109 http://dx.doi.org/10.1186/s12859-019-3012-1 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Degl’Innocenti, Andrea
Meloni, Gabriella
Mazzolai, Barbara
Ciofani, Gianni
A purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers
title A purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers
title_full A purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers
title_fullStr A purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers
title_full_unstemmed A purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers
title_short A purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers
title_sort purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6744719/
https://www.ncbi.nlm.nih.gov/pubmed/31521109
http://dx.doi.org/10.1186/s12859-019-3012-1
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