scholarly journals Towards Tabula Gallus

2022 ◽  
Vol 23 (2) ◽  
pp. 613
Author(s):  
Masahito Yamagata
Keyword(s):  
Developmental Biology ◽  
Molecular Biology ◽  
Human Cell ◽  
Cell Biology ◽  
Gallus Gallus ◽  
Chick Embryos ◽  
Transcriptome Data ◽  
Cell Type ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

The Tabula Gallus is a proposed project that aims to create a map of every cell type in the chicken body and chick embryos. Chickens (Gallus gallus) are one of the most recognized model animals that recapitulate the development and physiology of mammals. The Tabula Gallus will generate a compendium of single-cell transcriptome data from Gallus gallus, characterize each cell type, and provide tools for the study of the biology of this species, similar to other ongoing cell atlas projects (Tabula Muris and Tabula Sapiens/Human Cell Atlas for mice and humans, respectively). The Tabula Gallus will potentially become an international collaboration between many researchers. This project will be useful for the basic scientific study of Gallus gallus and other birds (e.g., cell biology, molecular biology, developmental biology, neuroscience, physiology, oncology, virology, behavior, ecology, and evolution). It will eventually be beneficial for a better understanding of human health and diseases.

scholarly journals In search of a core cellular network in single cell transcriptome data

2021 ◽  
Author(s):  
Ming Yang ◽  
Benjamin R. Harrison ◽  
Daniel E.L. Promislow
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cellular Network ◽  
Cell Types ◽  
Specific Gene ◽  
Transcriptome Data ◽  
Cell Type ◽  
Cell Type Specific ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractBackgroundAlong with specialized functions, cells of multicellular organisms also perform essential functions common to most if not all cells. Whether diverse cells do this by using the same set of genes, interacting in a fixed coordinated fashion to execute essential functions, remains a central question in biology. Single-cell RNA-sequencing (scRNA-seq) measures gene expression of individual cells, enabling researchers to discover gene expression patterns that contribute to the diversity of cell functions. Current analyses focus primarily on identifying differentially expressed genes across cells. However, patterns of co-expression between genes are probably more indicative of biological processes than are the expression of individual genes. Using single cell transcriptome data from the fly brain, here we focus on gene co-expression to search for a core cellular network.ResultsIn this study, we constructed cell type-specific gene co-expression networks using single cell transcriptome data of brains from the fruit fly, Drosophila melanogaster. We detected a set of highly coordinated genes preserved across cell types in fly brains and defined this set as the core cellular network. This core is very small compared with cell type-specific gene co-expression networks and shows dense connectivity. Modules within this core are enriched for basic cellular functions, such as translation and ATP metabolic processes, and gene members of these modules have distinct evolutionary signatures.ConclusionsOverall, we demonstrated that a core cellular network exists in diverse cell types of fly brains and this core exhibits unique topological, structural, functional and evolutionary properties.

scholarly journals Super-cells untangle large and complex single-cell transcriptome networks

2021 ◽  
Author(s):  
Mariia Bilous ◽  
Loc Tran ◽  
Chiara Cianciaruso ◽  
Santiago J Carmona ◽  
Mikael J Pittet ◽  
...  
Keyword(s):  
Single Cell ◽  
Coarse Graining ◽  
Cell Populations ◽  
Cell Type ◽  
Large Numbers ◽  
Single Cell Rna Sequencing ◽  
Gene Correlation ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Single-cell RNA sequencing (scRNA-seq) technologies offer unique opportunities for exploring heterogeneous cell populations. However, in-depth single-cell transcriptomic characterization of complex tissues often requires profiling tens to hundreds of thousands of cells. Such large numbers of cells represent an important hurdle for downstream analyses, interpretation and visualization. Here we develop a network-based coarse-graining framework where highly similar cells are merged into super-cells. We demonstrate that super-cells not only preserve but often improve the results of downstream analyses including visualization, clustering, differential expression, cell type annotation, gene correlation, imputation, RNA velocity and data integration. By capitalizing on the redundancy inherent to scRNA-seq data, super-cells significantly facilitate and accelerate the construction and interpretation of single-cell atlases, as demonstrated by the integration of 1.46 million cells from COVID-19 patients in less than two hours on a standard desktop.

scholarly journals Targeting Subsets of Mammalian Neurons

2020 ◽  
Vol 15 ◽  
pp. 263310552090853
Author(s):  
Boris V. Zemelman
Keyword(s):  
In Vivo Imaging ◽  
Inhibitory Neuron ◽  
Human Perception ◽  
Cell Populations ◽  
Inhibitory Interneurons ◽  
Transcriptome Data ◽  
Functional Studies ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Functional dissection of mammalian neuronal circuits depends on accurate targeting of constituent cell classes. Transgenic mice offer precise and predictable access to genetically defined cell populations, but there is the pressing need to target neuronal assemblies in species less amenable to genomic manipulations, such as the primate, which is an important animal model for human perception, cognition, and action. We have developed several virus-based methods for accessing all forebrain inhibitory interneurons as well as the major excitatory and inhibitory neuron subclasses. These methods rely on the wealth of emerging single-cell transcriptome data and harness gene expression variations to refine neuron targeting. Our approach enables nuanced functional studies, including in vivo imaging and manipulation, of the diverse cell populations of the mammalian neocortex, and it represents a timely blueprint for transgenics-independent interrogation of functionally significant cell classes.

scholarly journals Deep sequencing reveals cell-type-specific patterns of single-cell transcriptome variation

2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Hannah Dueck ◽  
Mugdha Khaladkar ◽  
Tae Kyung Kim ◽  
Jennifer M. Spaethling ◽  
Chantal Francis ◽  
...  
Keyword(s):  
Single Cell ◽  
Deep Sequencing ◽  
Cell Type ◽  
Transcriptome Variation ◽  
Cell Type Specific ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

scholarly journals A Single-Cell Transcriptome Atlas for Zebrafish Development

2019 ◽  
Author(s):  
Dylan R. Farnsworth ◽  
Lauren Saunders ◽  
Adam C. Miller
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Types ◽  
Developmental Time ◽  
Cell Type ◽  
Specific Expression ◽  
Transcriptional Profiles ◽  
Larval Stages ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

ABSTRACTThe ability to define cell types and how they change during organogenesis is central to our understanding of animal development and human disease. Despite the crucial nature of this knowledge, we have yet to fully characterize all distinct cell types and the gene expression differences that generate cell types during development. To address this knowledge gap, we produced an Atlas using single-cell RNA-sequencing methods to investigate gene expression from the pharyngula to early larval stages in developing zebrafish. Our single-cell transcriptome Atlas encompasses transcriptional profiles from 44,102 cells across four days of development using duplicate experiments that confirmed high reproducibility. We annotated 220 identified clusters and highlighted several strategies for interrogating changes in gene expression associated with the development of zebrafish embryos at single-cell resolution. Furthermore, we highlight the power of this analysis to assign new cell-type or developmental stage-specific expression information to many genes, including those that are currently known only by sequence and/or that lack expression information altogether. The resulting Atlas is a resource of biologists to generate hypotheses for genetic (mutant) or functional analysis, to launch an effort to define the diversity of cell-types during zebrafish organogenesis, and to examine the transcriptional profiles that produce each cell type over developmental time.

scholarly journals Cell Type Purification by Single-Cell Transcriptome-Trained Sorting

Cell ◽  
2019 ◽  
Vol 179 (2) ◽  
pp. 527-542.e19 ◽  
Author(s):  
Chloé S. Baron ◽  
Aditya Barve ◽  
Mauro J. Muraro ◽  
Reinier van der Linden ◽  
Gitanjali Dharmadhikari ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Type ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome
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