Gene Expression Variation in Arabidopsis Embryos at Single-Nucleus Resolution
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA716169 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14027792.fastq.gz | Fastqsanger.gz | |||
| SRR14027793.fastq.gz | Fastqsanger.gz | |||
| SRR14027794.fastq.gz | Fastqsanger.gz | |||
| SRR14027795.fastq.gz | Fastqsanger.gz | |||
| SRR14027796.fastq.gz | Fastqsanger.gz |
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Project description:Soon after fertilization of egg and sperm, plant genomes become transcriptionally activated and drive a series of coordinated cell divisions to form the basic body plan during embryogenesis. Early embryonic cells rapidly diversify from each other, and investigation of the corresponding gene expression dynamics can help elucidate underlying cellular differentiation programs. However, current plant embryonic transcriptome datasets either lack cell-specific information or have RNA contamination from surrounding non-embryonic tissues. We have coupled fluorescence-activated nuclei sorting together with single-nucleus mRNA-sequencing to construct a gene expression atlas of Arabidopsis thaliana early embryos at single-cell resolution. In addition to characterizing cell-specific transcriptomes, we found evidence that distinct epigenetic and transcriptional regulatory mechanisms operate across emerging embryonic cell types. These datasets and analyses, as well as the approach we devised, are expected to facilitate the discovery of molecular mechanisms underlying pattern formation in plant embryos. This article has an associated 'The people behind the papers' interview.
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Project description:Transcriptome analysis during embryogenesis usually requires pooling of embryos to obtain sufficient RNA. Hence, the measured levels of gene-expression represent the average mRNA levels of pooled samples and the biological variation among individuals is lost for inclusion into statistical models used to analyze transcriptome data. This can irreversibly reduce the robustness, resolution and expressiveness of the experiment. Therefore, we developed a robust method to isolate abundant high-quality RNA from individual embryos to perform single embryo transcriptome analyses using the zebrafish as a model.
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Project description:Transcriptome analysis during embryogenesis usually requires pooling of embryos to obtain sufficient RNA. Hence, the measured levels of gene-expression represent the average mRNA levels of pooled samples and the biological variation among individuals is lost for inclusion into statistical models used to analyze transcriptome data. This can irreversibly reduce the robustness, resolution and expressiveness of the experiment. Therefore, we developed a robust method to isolate abundant high-quality RNA from individual embryos to perform single embryo transcriptome analyses using the zebrafish as a model. Zebrafish embryos were selected from the germ ring stage. RNA from 4 individual embryos and RNA from 4 pooled embryos and afterwards splitted material was isolated. These 8 samples were hybridized against a common reference made from a pool of 20 embryos.
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