Biology subjects

Tarashansky, A. J.

Publications and source records attributed to Tarashansky, A. J..

4 recordsLinked to original sources

bioRxiv2021

A cell atlas of the fly kidney

Like humans, insects rely on precise regulation of their internal environments to survive. The insect renal system consists of Malpighian tubules and nephrocytes that share similarities to the mammalian kidney. Studies of the Drosophila Malpighian tubules and nephrocytes have provided many insights into our understanding of the excretion of waste products, stem cell regeneration, protein reabsorption, and as human kidney disease models. Here, we analyzed single-nucleus RNA sequencing (snRNA-seq) data sets to characterize the cell types of the adult fly kidney. We identified 11 distinct clusters representing renal stem cells (RSCs), stellate cells (SCs), regionally specific principal cells (PCs), garland nephrocyte cells (GCs) and pericardial nephrocytes (PNs). Analyses of these clusters revealed many new interesting features. For example, we found a new, previously unrecognized cell cluster: lower segment PCs that express Esyt2. In addition, we find that the SC marker genes RhoGEF64c, Frq2, Prip and CG10939 regulate their unusual cell shape. Further, we identified transcription factors specific to each cluster and built a network of signaling pathways that are potentially involved in mediating cell-cell communication between Malpighian tubule cell types. Finally, cross-species analysis allowed us to match the fly kidney cell types to mouse kidney cell types and planarian protonephridia - knowledge that will help the generation of kidney disease models. To visualize this dataset, we provide a web-based resource for gene expression in single cells (https://www.flyrnai.org/scRNA/kidney/). Altogether, our study provides a comprehensive resource for addressing gene function in the fly kidney and future disease studies.

developmental biology↗

bioRxiv2020

Mapping single-cell atlases throughout Metazoa unravels cell type evolution

Comparing single-cell transcriptomic atlases from diverse organisms can elucidate the origins of cellular diversity and assist the annotation of new cell atlases. Yet, comparison between distant relatives is hindered by complex gene histories and diversifications in expression programs. Previously, we introduced the self-assembling manifold (SAM) algorithm to robustly reconstruct manifolds from single-cell data (Tarashansky et al., 2019). Here, we build on SAM to map cell atlas manifolds across species. This new method, SAMap, identifies homologous cell types with shared expression programs across distant species within phyla, even in complex examples where homologous tissues emerge from distinct germ layers. SAMap also finds many genes with more similar expression to their paralogs than their orthologs, suggesting paralog substitution may be more common in evolution than previously appreciated. Lastly, comparing species across animal phyla, spanning mouse to sponge, reveals ancient contractile and stem cell families, which may have arisen early in animal evolution.

bioinformatics↗

bioRxiv2020

Single-cell analysis of Schistosoma mansoni reveals a conserved genetic program controlling germline stem cell fate

Schistosomes are parasitic flatworms causing one of the most prevalent infectious diseases from which millions of people are currently suffering. Their germline outputs many fertilized eggs, which are both the transmissible agents and the cause of the infection-associated pathology. Given its significance, the schistosome germline has been a research focus for more than a century. Nonetheless, little is known about the molecular mechanisms that regulate its development. Here, we construct a transcriptomic cell type atlas of juvenile schistosomes. This allows us to capture germline stem cells (GSCs) during de novo gonadal development. We identify a genetic program that balances the fate of GSC between proliferation and differentiation. This program is controlled by onecut, a homeobox transcription factor, and boule, an mRNA binding protein. Evaluating this genetic program in schistosomes free-living evolutionary cousin, the planarian, shows that this germline-specific regulatory program is conserved but its function has changed significantly during evolution.

developmental biology↗

bioRxiv2018

Self-assembling Manifolds in Single-cell RNA Sequencing Data

Single-cell RNA sequencing has spurred the development of computational methods that enable researchers to classify cell types, delineate developmental trajectories, and measure molecular responses to external perturbations. Many of these technologies rely on their ability to detect genes whose cell-to-cell variations arise from the biological processes of interest rather than transcriptional or technical noise. However, for datasets in which the biologically relevant differences between cells are subtle, identifying these genes is a challenging task. We present the self-assembling manifold (SAM) algorithm, an iterative soft feature selection strategy to quantify gene relevance and improve dimensionality reduction. We demonstrate its advantages over other state-of-the-art methods with experimental validation in identifying novel stem cell populations of Schistosoma, a prevalent parasite that infects hundreds of millions of people. Extending our analysis to a total of 56 datasets, we show that SAM is generalizable and consistently outperforms other methods in a variety of biological and quantitative benchmarks.

bioinformatics↗