Transcriptional advantage influence odorant receptor gene choice.

Odorant receptors (ORs) obey mutual exclusivity and monoallelic mode of expression. Efforts are ongoing to decipher the molecular mechanism that drives the 'one-neuron-one-receptor' rule of olfaction. Recently, single-cell profiling of olfactory sensory neurons (OSNs) revealed the expression of multiple ORs in the immature neurons, suggesting that the OR gene choice mechanism is much more complex than previously described by the silence-all-and-activate-one model. These results also led to the genesis of two possible mechanistic models i.e. winner-takes-all and stochastic selection. We developed Reverse Cell Tracking (RCT), a novel computational framework that facilitates OR-guided cellular backtracking by leveraging Uniform Manifold Approximation and Projection embeddings from RNA Velocity Workflow. RCT-based trajectory backtracking, coupled with statistical analysis, revealed the OR gene choice bias for the transcriptionally advanced (highest expressed) OR during neuronal differentiation. Interestingly, the observed selection bias was uniform for all ORs across different spatial zones or their relative expression within the olfactory organ. We validated these findings on independent datasets and further confirmed that the OR gene selection may be regulated by Upf3b. Lastly, our RNA dynamics-based tracking of the differentiation cascade revealed a transition cell state that harbors mixed molecular identities of immature and mature OSNs, and their relative abundance is regulated by Upf3b.

Quantification of Age-Related Decline in Transcriptional Homeostasis.

Age-dependent dysregulation of transcription regulatory machinery triggers modulations in the gene expression levels leading to the decline in cellular fitness. Tracking of these transcripts along the temporal axis in multiple species revealed a spectrum of evolutionarily conserved pathways, such as electron transport chain, translation regulation, DNA repair, etc. Recent shreds of evidence suggest that aging deteriorates the transcription machinery itself, indicating the hidden complexity of the aging transcriptomes. This reinforces the need for devising novel computational methods to view aging through the lens of transcriptomics. Here, we present Homeostatic Divergence Score (HDS) to quantify the extent of messenger RNA (mRNA) homeostasis by assessing the balance between spliced and unspliced mRNA repertoire in single cells. We validated its utility in two independent aging datasets, and identified sets of genes undergoing age-related breakdown of transcriptional homeostasis. Moreover, testing of our method on a subpopulation of human embryonic stem cells revealed a set of differentially processed transcripts segregating these subpopulations. Our preliminary analyses in this direction suggest that mRNA processing level information offered by single-cell RNA sequencing (scRNA-seq) data is a superior determinant of chronological age as compared to transcriptional noise.

Challenges and possible solutions for decoding extranasal olfactory receptors.

Olfactory receptors are primarily known to be expressed in the olfactory epithelium of the nasal cavity and therefore assist in odor perception. With the advent of high-throughput omics technologies such as tissue microarray or RNA sequencing, a large number of olfactory receptors have been reported to be expressed in the nonolfactory tissues. Although these technologies uncovered the expression of these olfactory receptors in the nonchemosensory tissues, unfortunately, they failed to reveal the information about their cell type of origin. Accurate characterization of the cell types should be the first step towards devising cell type-specific assays for their functional evaluation. Single-cell RNA-sequencing technology resolved some of these apparent limitations and opened new means to interrogate the expression of these extranasal olfactory receptors at the single-cell resolution. Moreover, the availability of large-scale, multi-organ/species single-cell expression atlases offer ample resources for the systematic reannotation of these receptors in a cell type-specific manner. In this Viewpoint article, we discuss some of the technical limitations that impede the in-depth understanding of these extranasal olfactory receptors, with a special focus on odorant receptors. Moreover, we also propose a list of single cell-based omics technologies that could further promulgate the opportunity to decipher the regulatory network that drives the odorant receptors expression at atypical locations.