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Inferring gene regulatory networks from gene expression data is an important and challenging problem in the biology community. We propose OTVelo, a methodology that takes time-stamped single-cell gene expression data as input and predicts gene regulation across two time points. It is known that the rate of change of gene expression, which we will refer to as gene velocity, provides crucial information that enhances such inference; however, this information is not always available due to the limitations in sequencing depth. Our algorithm overcomes this limitation by estimating gene velocities using optimal transport. We then infer gene regulation using time-lagged correlation and Granger causality via regularized linear regression. Instead of providing an aggregated network across all time points, our method uncovers the underlying dynamical mechanism across time points. We validate our algorithm on 13 simulated datasets with both synthetic and curated networks and demonstrate its efficacy on 9 experimental data sets. 

Abstract Although multiple high-performing epigenetic aging clocks exist, few are based directly on gene expression. Such transcriptomic aging clocks allow us to extract age-associated genes directly. However, most existing transcriptomic clocks model a subset of genes and are limited in their ability to predict novel biomarkers. With the growing popularity of single-cell sequencing, there is a need for robust single-cell transcriptomic aging clocks. Moreover, clocks have yet to be applied to investigate the elusive phenomenon of sex differences in aging. We introduce TimeFlies, a pan-cell-type scRNA-seq aging clock for theDrosophila melanogasterhead. TimeFlies uses deep learning to classify the donor age of cells based on genome-wide gene expression profiles. Using explainability methods, we identified key marker genes contributing to the classification, with lncRNAs showing up as highly enriched among predicted biomarkers. The top biomarker gene across cell types is lncRNA:roX1, a regulator of X chromosome dosage compensation, a pathway previously identified as a top biomarker of aging in the mouse brain. We validated this finding experimentally, showing a decrease in survival probability in the absence of roX1in vivo. Furthermore, we trained sex-specific TimeFlies clocks and noted significant differences in model predictions and explanations between male and female clocks, suggesting that different pathways drive aging in males and females. Graphical Abstract 

Abstract Comparative studies of aging are a promising approach to identifying general properties of and processes leading to aging. While to date, many comparative studies of aging in animals have focused on relatively narrow species groups, methodological innovations now allow for studies that include evolutionary distant species. However, comparative studies of aging across a wide range of species that have distinct life histories introduce additional challenges in experimental design. Here, we discuss these challenges, highlight the most pressing problems that need to be solved, and provide suggestions based on current approaches to successfully carry out comparative aging studies across the animal kingdom. 

During the essential and conserved process of zygotic genome activation (ZGA), chromatin accessibility must increase to promote transcription. Drosophila is a well-established model for defining mechanisms that drive ZGA. Zelda (ZLD) is a key pioneer transcription factor (TF) that promotes ZGA in the Drosophila embryo. However, many genomic loci that contain GA-rich motifs become accessible during ZGA independent of ZLD. Therefore, we hypothesized that other early TFs that function with ZLD have not yet been identified, especially those that are capable of binding to GA-rich motifs such as chromatin-linked adaptor for male-specific lethal (MSL) proteins (CLAMP). Here, we demonstrate that Drosophila embryonic development requires maternal CLAMP to (1) activate zygotic transcription; (2) increase chromatin accessibility at promoters of specific genes that often encode other essential TFs; and (3) enhance chromatin accessibility and facilitate ZLD occupancy at a subset of key embryonic promoters. Thus, CLAMP functions as a pioneer factor that plays a targeted yet essential role in ZGA.