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Transcriptomic profiling maps anatomically patterned subpopulations among single embryonic cardiac cells [RNA-seq]

ABSTRACT: Embryonic gene expression intricately reflects anatomical context, developmental stage, and cell type. To address whether the precise spatial origins of cardiac cells can be deduced solely from their transcriptional profiles, we established a genome-wide expression database from 118, 949, and 1166 single murine heart cells at embryonic days (e)8.5, 9.5, and 10.5, respectively. We segregated these cells by type using unsupervised bioinformatic analysis and identified novel chamber-specific genes. Using a random forest algorithm, we reconstructed the spatial origin of single e9.5 and e10.5 cardiomyocytes with 92.0+/-3.2% and 91.2+/-2.8% accuracy respectively (99.4+/-1.0% and 99.1+/-1.1% if a +/-1 zone margin is permitted) and predicted the second heart field distribution of Isl1-lineage descendants. When applied to Nkx2-5-/- cardiomyocytes from murine e9.5 hearts, we showed their transcriptional alteration and lack of ventricular phenotype. Our database and zone classification algorithm will enable the discovery of novel mechanisms in early cardiac development and disease.

ORGANISM(S): Mus musculus

PROVIDER: GSE76118 | GEO | 2016/11/10

SECONDARY ACCESSION(S): PRJNA306360

REPOSITORIES: GEO

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Transcriptomic profiling maps anatomically patterned subpopulations among single embryonic cardiac cells [qPCR]

Project description:Embryonic gene expression intricately reflects anatomical context, developmental stage, and cell type. To address whether the precise spatial origins of cardiac cells can be deduced solely from their transcriptional profiles, we established a genome-wide expression database from 118, 949, and 1166 single murine heart cells at embryonic days (e)8.5, 9.5, and 10.5, respectively. We segregated these cells by type using unsupervised bioinformatic analysis and identified novel chamber-specific genes. Using a random forest algorithm, we reconstructed the spatial origin of single e9.5 and e10.5 cardiomyocytes with 92.0+/-3.2% and 91.2+/-2.8% accuracy respectively (99.4+/-1.0% and 99.1+/-1.1% if a +/-1 zone margin is permitted) and predicted the second heart field distribution of Isl1-lineage descendants. When applied to Nkx2-5-/- cardiomyocytes from murine e9.5 hearts, we showed their transcriptional alteration and lack of ventricular phenotype. Our database and zone classification algorithm will enable the discovery of novel mechanisms in early cardiac development and disease.

2016-11-10 | GSE89465 | GEO

Single cell- Cluster-RNA seq and Spatial Transcriptomics from the trunk of mouse embryos of different genotypes (wild type, Pax2-GFP, Pax2-GFP; Gata3 knockout) and developmental stages (E8.75, E9.5, E11.5) [Spatial Transcriptomics]

Project description:To study cell heterogeneity and state transitions in the developing urinary tract we performed spatial transcriptomics from the trunk of E9.5 Pax2GFP mouse embryos using the 10X Genomics Visium Spatial Gene Expression protocol

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Simultaneous proteome localization and turnover analysis of cardiomyocytes under proteasome inhibition

Project description:To examine the protein spatial and temporal changes upon carfilzomib-mediated proteasome inhibition in cardiac cells, we produced human iPSC-derived cardiomyocytes using a standard small molecule based protocol. Cardiomyocyte identity was confirmed by morphology, observation of contraction, and the presence of GFP tagged MLC-2a in the reporter line. We then applied the SPLAT protocol to untreated and carfilzomib-exposed iPSC-cardiomyocytes.

2023-04-28 | PXD041386 | JPOST Repository

Simultaneous proteome localization and turnover analysis, Rep. 3

2023-11-03 | PXD046649 | JPOST Repository

Single cell RNA Sequencing Analysis of Gene Expression Profile in Dgcr8 Conditional KO Embryonic Hearts

Project description:Purpose: To compare the single cell transcriptome of wild type and Mesp1Cre+/Dgcr8-/- embryonic heart at embryonic stage E9.5 Methods: For single cell sample preparation, Ventricular part of E9.5 heart tubes were dissected and digested into single cells by 0.04% Trypsin combined with 0.05% Collagenase IV, and then transferred into DMEM containing 10% fetal bovine serum for termination. After washed in PBS without Ca2+, the single cells were manually transferred into cell lysis buffer with a mouth pipette. Total RNA was reverse transcribed and amplified using Smart-seq2 protocol (Picelli et al., 2014), followed by Tn5 tagmentation and PCR enrichment to generate libraries using TruePrep DNA Library Prep Kit V2 for illumina (Vazyme, TD501-503) according to the manufacturer’s suggested protocol. Clean reads were mapped to mouse genome (mm10) using Salmon. Results: Genes significantly differentially expressed in the E9.5 Dgcr8 cKO single cardiomyocyte compared with wild type group were identified. Conclusions: Dgcr8 cKO caused important gene expression changes in E9.5 cardiomyocytes at single cell level

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Spatial Regulation of Gene Expression in Articular Cartilage Assessed by Laser Captured Microdissection and Microarray

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2014-10-20 | E-GEOD-51994 | biostudies-arrayexpress

The lncRNA locus Handsdown regulates cardiac gene programs and is essential for early mouse development

Project description:WT and Handsdown mutant ESC were differentatied into the meosdermal cell lineage and harvested at desiganted timepoints für differential expression profiling (n=3). Hearts of E9.5 mouse embryos were harvested and profiled to generate a represantative picture of RNAs (n=1). 4C-seq analysis of mESCs, cardiomyocytes and whole hearts from E11.5 mouse embryos

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Single-cell analysis of non-myocytes during heart regeneration reveals sequential coordinated responses from distinct cell populations [scRNA-seq]

Project description:Cardiac regeneration occurs primarily through proliferation of existing cardiomyocytes, yet the regenerative response also involves complex interactions between distinct cardiac cell types including not only cardiomyocytes, but also non-cardiomyocytes (nonCMs). However, the molecular features and cellular functions of the highly heterogeneous populations of nonCMs and how these populations cooperate to regenerate the injured heart remain largely unexplored. Using the newly developed LIGER algorithm that allows flexible modeling across highly diverse single-cell datasets, we analyzed the transcriptome dynamics of 61,977 individual nonCMs isolated at multiple time points during zebrafish heart regeneration. Combining single-cell analysis and in situ hybridization, we identified major nonCM cell types, including multiple novel subpopulations with unique tempo-spatial distributions and highly cooperative interactions in the regenerating heart. Interestingly, genetic perturbation of macrophage function by kit knockout led to accumulation of fibrotic deposits and severely compromised cardiomyocyte proliferation and myocardium regeneration. Our single-cell transcriptomic analysis of nonCMs during cardiac regeneration provides a blueprint for interrogating the molecular and cellular basis of cardiac regeneration.

2021-09-06 | GSE145980 | GEO

Single-cell analysis of non-myocytes during heart regeneration reveals sequential coordinated responses from distinct cell populations [bulk RNA-seq]

2021-09-06 | GSE145979 | GEO

Identification of stress response and recovery mechanisms by multi-scale analyses of drought effect in the maize leaf growth zone.

Project description:We use the gowth zone of the maize leaf as a model system to study the growth reduction in response to drought stress. The spatial gradient and the relatively large size of the maize leaf allowed us to sample at a subzonal rezolution and to examine different developmental stages at the same time. We compared the response to different levels of drought stress (mild and severe) of proliferating (meristem), expanding (elongation zone) and differentiated (mature zone) tissue. Three separate loop designs were used for the three zones of the maize leaf (meristem, elongation zone, and mature zone). In each loop three treatments were contrasted (control, mild stress, and severe stress). Four biological replicates were used for each zone/condition (4 replicates x 3 zones x 3 conditions = 36 samples).

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