scholarly journals Neighbor-specific gene expression revealed from physically interacting cells during mouse embryonic development

2021 ◽  
Author(s):  
Junil Kim ◽  
Michaela Mrugala Rothová ◽  
Linbu Liao ◽  
Siyeon Rhee ◽  
Guangzheng Weng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Spatial Information ◽  
Dimensional Space ◽  
Cell Types ◽  
Cell Contact ◽  
Specific Gene ◽  
Neighboring Cell ◽  
Cell Fate Decisions ◽  
Specific Gene Expression

ABSTRACTCells continuously communicate with the neighboring cells during development. Direct interaction of different cell types can induce molecular signals dictating lineage specification and cell fate decisions. The current single cell RNAseq (scRNAseq) technology cannot study cell contact dependent gene expression due to the loss of spatial information. To overcome this issue and determine cell contact specific gene expression during embryogenesis, we performed RNA sequencing of physically interacting cells (PICseq) and assessed alongside our single cell transcriptomes (scRNAseq) derived from developing mouse embryos between embryonic day (E) 7.5 and E9.5. Analysis of PICseq data identifies an interesting suite of gene expression signatures depending on neighboring cell types. For instance, neural progenitor (NP) cells expressed Nkx2-1 when interacting with definitive endoderm (DE) and DE cells expressed Gsc when interacting with NP. Based on the identified cell contact specific genes, we devised a means to predict the neighboring cell types from individual cell transcriptome. We further developed spatial-tSNE to show the pseudo-spatial distribution of cells in a 2-dimensional space. In sum, we suggest an approach to study contact specific gene regulation during embryogenesis.

Analysis of a tissue-specific enhancer: ARF6 regulates adipogenic gene expression

1992 ◽  
Vol 12 (3) ◽  
pp. 1202-1208
Author(s):  
R A Graves ◽  
P Tontonoz ◽  
B M Spiegelman
Keyword(s):  
Gene Expression ◽  
Cultured Cells ◽  
Mutational Analysis ◽  
Cell Types ◽  
Specific Gene ◽  
Enhancer Activity ◽  
Cis Acting ◽  
Specific Gene Expression ◽  
Nuclear Extracts ◽  
Adipogenic Gene

The molecular basis of adipocyte-specific gene expression is not well understood. We have previously identified a 518-bp enhancer from the adipocyte P2 gene that stimulates adipose-specific gene expression in both cultured cells and transgenic mice. In this analysis of the enhancer, we have defined and characterized a 122-bp DNA fragment that directs differentiation-dependent gene expression in cultured preadipocytes and adipocytes. Several cis-acting elements have been identified and shown by mutational analysis to be important for full enhancer activity. One pair of sequences, ARE2 and ARE4, binds a nuclear factor (ARF2) present in extracts derived from many cell types. Multiple copies of these elements stimulate gene expression from a minimal promoter in preadipocytes, adipocytes, and several other cultured cell lines. A second pair of elements, ARE6 and ARE7, binds a separate factor (ARF6) that is detected only in nuclear extracts derived from adipocytes. The ability of multimers of ARE6 or ARE7 to stimulate promoter activity is strictly adipocyte specific. Mutations in the ARE6 sequence greatly reduce the activity of the 518-bp enhancer. These data demonstrate that several cis- and trans-acting components contribute to the activity of the adipocyte P2 enhancer and suggest that ARF6, a novel differentiation-dependent factor, may be a key regulator of adipogenic gene expression.

scholarly journals Enabling out-of-clinic human immunity studies via single-cell profiling of capillary blood

2020 ◽  
Author(s):  
Tatyana Dobreva ◽  
David Brown ◽  
Jong Hwee Park ◽  
Matt Thomson
Keyword(s):  
Gene Expression ◽  
Immune System ◽  
Environmental Factors ◽  
Single Cell ◽  
Immune Cell ◽  
Cell Types ◽  
Capillary Blood ◽  
Specific Gene ◽  
Human Immune ◽  
Over Time

AbstractAn individual’s immune system is driven by both genetic and environmental factors that vary over time. To better understand the temporal and inter-individual variability of gene expression within distinct immune cell types, we developed a platform that leverages multiplexed single-cell sequencing and out-of-clinic capillary blood extraction to enable simplified, cost-effective profiling of the human immune system across people and time at single-cell resolution. Using the platform, we detect widespread differences in cell type-specific gene expression between subjects that are stable over multiple days.SummaryIncreasing evidence implicates the immune system in an overwhelming number of diseases, and distinct cell types play specific roles in their pathogenesis.1,2 Studies of peripheral blood have uncovered a wealth of associations between gene expression, environmental factors, disease risk, and therapeutic efficacy.4 For example, in rheumatoid arthritis, multiple mechanistic paths have been found that lead to disease, and gene expression of specific immune cell types can be used as a predictor of therapeutic non-response.12 Furthermore, vaccines, drugs, and chemotherapy have been shown to yield different efficacy based on time of administration, and such findings have been linked to the time-dependence of gene expression in downstream pathways.21,22,23 However, human immune studies of gene expression between individuals and across time remain limited to a few cell types or time points per subject, constraining our understanding of how networks of heterogeneous cells making up each individual’s immune system respond to adverse events and change over time.

scholarly journals Single-cell genomic atlas of great ape cerebral organoids uncovers human-specific features of brain development

2019 ◽  
Author(s):  
Sabina Kanton ◽  
Michael James Boyle ◽  
Zhisong He ◽  
Malgorzata Santel ◽  
Anne Weigert ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Adult Brain ◽  
The Other ◽  
Specific Gene ◽  
Great Ape ◽  
Specific Gene Expression ◽  
Gene Regulatory ◽  
Human Specific

ABSTRACTThe human brain has changed dramatically since humans diverged from our closest living relatives, chimpanzees and the other great apes1–5. However, the genetic and developmental programs underlying this divergence are not fully understood6–8. Here, we have analyzed stem cell-derived cerebral organoids using single-cell transcriptomics (scRNA-seq) and accessible chromatin profiling (scATAC-seq) to explore gene regulatory changes that are specific to humans. We first analyze cell composition and reconstruct differentiation trajectories over the entire course of human cerebral organoid development from pluripotency, through neuroectoderm and neuroepithelial stages, followed by divergence into neuronal fates within the dorsal and ventral forebrain, midbrain and hindbrain regions. We find that brain region composition varies in organoids from different iPSC lines, yet regional gene expression patterns are largely reproducible across individuals. We then analyze chimpanzee and macaque cerebral organoids and find that human neuronal development proceeds at a delayed pace relative to the other two primates. Through pseudotemporal alignment of differentiation paths, we identify human-specific gene expression resolved to distinct cell states along progenitor to neuron lineages in the cortex. We find that chromatin accessibility is dynamic during cortex development, and identify instances of accessibility divergence between human and chimpanzee that correlate with human-specific gene expression and genetic change. Finally, we map human-specific expression in adult prefrontal cortex using single-nucleus RNA-seq and find developmental differences that persist into adulthood, as well as cell state-specific changes that occur exclusively in the adult brain. Our data provide a temporal cell atlas of great ape forebrain development, and illuminate dynamic gene regulatory features that are unique to humans.

scholarly journals Unsupervised cell functional annotation for single-cell RNA-Seq

2021 ◽  
Author(s):  
Dongshunyi Li ◽  
Jun Ding ◽  
Ziv Bar-Joseph
Keyword(s):  
Single Cell ◽  
Dimensional Space ◽  
Cell Types ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Type ◽  
Sequencing Data ◽  
Gene Sets ◽  
Supervised Methods ◽  
Low Dimensional

One of the first steps in the analysis of single cell RNA-Sequencing data (scRNA-Seq) is the assignment of cell types. While a number of supervised methods have been developed for this, in most cases such assignment is performed by first clustering cells in low-dimensional space and then assigning cell types to different clusters. To overcome noise and to improve cell type assignments we developed UNIFAN, a neural network method that simultaneously clusters and annotates cells using known gene sets. UNIFAN combines both, low dimension representation for all genes and cell specific gene set activity scores to determine the clustering. We applied UNIFAN to human and mouse scRNA-Seq datasets from several different organs. As we show, by using knowledge on gene sets, UNIFAN greatly outperforms prior methods developed for clustering scRNA-Seq data. The gene sets assigned by UNIFAN to different clusters provide strong evidence for the cell type that is represented by this cluster making annotations easier.

Cell type-specific gene expression underpins remodelling of cell wall pectin in exocarp and cortex during apple fruit development

2019 ◽  
Vol 70 (21) ◽  
pp. 6085-6099
Author(s):  
Patrick P Collins ◽  
Erin M O’donoghue ◽  
Ria Rebstock ◽  
Heather R Tiffin ◽  
Paul W Sutherland ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Wall ◽  
Fruit Development ◽  
Cell Types ◽  
Apple Fruit ◽  
Epidermal Cells ◽  
Specific Gene ◽  
Cell Type ◽  
Specific Gene Expression ◽  
Cell Type Specific

Young apple epidermal cells process cell wall pectic arabinan and galactan side chains different from other cell types, resulting in debranched linear arabinans and the absence of galactans.

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