The "developmental hourglass" concept suggests that intermediate developmental stages are most resistant to evolutionary changes and that differences between species arise through divergence later in development. This high conservation during middevelopment is illustrated by the "waist" of the hourglass and it represents a low probability of evolutionary change. Earlier molecular surveys both on animals and on plants have shown that the genes expressed at the waist stage are more ancient and more conserved in their expression. The existence of such a developmental hourglass has not been explored in fungi, another eukaryotic kingdom. In this study, we generated a series of transcriptomic data covering the entire lifecycle of a model mushroom-forming fungus, Coprinopsis cinerea, and we observed a molecular hourglass over its development. The "young fruiting body" is the stage that expresses the evolutionarily oldest (lowest transcriptome age index) transcriptome and gives the strongest signal of purifying selection (lowest transcriptome divergence index). We also demonstrated that all three kingdoms-animals, plants, and fungi-display high expression levels of genes in "information storage and processing" at the waist stages, whereas the genes in "metabolism" become more highly expressed later. Besides, the three kingdoms all show underrepresented "signal transduction mechanisms" at the waist stages. The synchronic existence of a molecular "hourglass" across the three kingdoms reveals a mutual strategy for eukaryotes to incorporate evolutionary innovations.

Transcriptome profiling is essential for gene regulation studies in development and disease. Current web-based tools enable functional characterization of transcriptome data, but most are restricted to applying gene-list-based methods to single datasets, inefficient in leveraging up-to-date and species-specific information, and limited in their visualization options. Additionally, there is no systematic way to explore data stored in the largest transcriptome repository, NCBI GEO. To fill these gaps, we have developed eVITTA (easy Visualization and Inference Toolbox for Transcriptome Analysis; https://tau.cmmt.ubc.ca/eVITTA/). eVITTA provides modules for analysis and exploration of studies published in NCBI GEO (easyGEO), detailed molecular- and systems-level functional profiling (easyGSEA), and customizable comparisons among experimental groups (easyVizR). We tested eVITTA on transcriptomes of SARS-CoV-2 infected human nasopharyngeal swab samples, and identified a downregulation of olfactory signal transducers, in line with the clinical presentation of anosmia in COVID-19 patients. We also analyzed transcriptomes of Caenorhabditis elegans worms with disrupted S-adenosylmethionine metabolism, confirming activation of innate immune responses and feedback induction of one-carbon cycle genes. Collectively, eVITTA streamlines complex computational workflows into an accessible interface, thus filling the gap of an end-to-end platform capable of capturing both broad and granular changes in human and model organism transcriptomes.

Caenorhabditis elegans Nuclear Hormone Receptor NHR-49, an orthologue of mammalian Peroxisome Proliferator-Activated Receptor alpha (PPARα). We show that nhr-49 is required for animal survival in hypoxia and is synthetic lethal with hif-1 in this context, demonstrating that these factors act in parallel. RNA-seq analysis shows that in hypoxia nhr-49 regulates a set of genes that are hif-1-independent, including autophagy genes that promote hypoxia survival. We further show that Nuclear Hormone Receptor nhr-67 is a negative regulator and Homeodomain-interacting Protein Kinase hpk-1 is a positive regulator of the NHR-49 pathway. Together, our experiments define a new, essential hypoxia response pathway that acts in parallel with the well-known HIF-mediated hypoxia response.