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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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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. |
format | Online Article Text |
id | pubmed-6744719 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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