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Journal Article

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


Degl'Innocenti,  Andrea
Department of Molecular Neurogenetics, Max Planck Institute of Biophysics, Max Planck Society;
Smart Bio-Interfaces, Istituto Italiano di Tecnologia, Pontedera (Pisa), Italy;

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Degl'Innocenti, A., Meloni, G., Mazzolai, B., & Ciofani, G. (2019). A purely bioinformatic pipeline for the prediction of mammalian odorant receptor gene enhancers. BMC Bioinformatics, 20(1): 474. doi:10.1186/s12859-019-3012-1.

Cite as: https://hdl.handle.net/21.11116/0000-0004-C4CC-9
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.