Sequence-based prediction of olfactory receptor responses

Abstract

SummaryComputational prediction of how strongly an olfactory receptor responds to various odors can help in bridging the widening gap between the large number of receptors that have been sequenced and the small number of experiments measuring their responses. Previous efforts in this area have predicted the responses of a receptor to some odors, using the known responses of the same receptor to other odors. Here we present a method to predict the responses of a receptor without any known responses, by using available data about the responses of other conspecific receptors and their sequences. We applied this method to olfactory receptors in insects Drosophila melanogaster (both adult and larva) and Anopheles gambiae, and to mouse and human olfactory receptors. We found the predictions to be in significant agreement with the experimental measurements. The method also provides clues about the response-determining positions within the receptor sequences.

Evolution of a pest: towards the complete neuroethology of Drosophila suzukii and the subgenus Sophophora

“…However, the persistent dearth of viable ecological and natural history information for the majority of the known Drosophila species makes the extrapolation towards evolutionary pressures or niche partitioning difficult 59 . This paucity of ecological and host information leaves several species without known ligands for either ab2B or ab3A, despite a chemically diverse and robust screening of these OSNs in the present study using known host materials from other members of this subgenus.…”

Mosquito Olfactory Response Ensemble: a curated database of behavioral and electrophysiological responses enables pattern discovery

“…Having all this data in one place, in a structured format, can enable systematic large-scale analyses to discover trends that cannot be seen with individual studies (Crasto et al, 2002;Liu et al, 2004Liu et al, , 2011Marenco et al, 2016;Olender et al, 2013). The Database of Odorant Responses (DoOR) catalogs the OR responses of different odors in Drosophila melanogaster (Galizia et al, 2010;Münch and Galizia, 2016) and has proved to be very useful in enabling large-scale computational analyses (Chepurwar et al, 2019;Dasgupta et al, 2018;Saberi and Seyed-Allaei, 2016;Zwicker et al, 2016). However, no such curated dataset is available for mosquitoes.…”