Transcriptome-wide variability in single embryonic development cells.

Vincent Piras,Masaru Tomita,Kumar Selvarajoo

doi:10.1038/srep07137

Vincent Piras, Masaru Tomita + Show 1 more

Open Access

https://doi.org/10.1038/srep07137

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Abstract

Molecular heterogeneity of individual molecules within single cells has been recently shown to be crucial for cell fate diversifications. However, on a global scale, the effect of molecular variability for embryonic developmental stages is largely underexplored. Here, to understand the origins of transcriptome-wide variability of oocytes to blastocysts in human and mouse, we examined RNA-Seq datasets. Evaluating Pearson correlation, Shannon entropy and noise patterns (η2 vs. μ), our investigations reveal a phase transition from low to saturating levels of diversity and variability of transcriptome-wide expressions through the development stages. To probe the observed behaviour further, we utilised a stochastic transcriptional model to simulate the global gene expressions pattern for each development stage. From the model, we concur that transcriptome-wide regulation initially begins from 2-cell stage, and becomes strikingly variable from 8-cell stage due to amplification and quantal transcriptional activity.

Highlights

Molecular heterogeneity of individual molecules within single cells has been recently shown to be crucial for cell fate diversifications
To understand global gene expression structure and noise patterns of single cells during mammalian developmental stages, we investigated transcriptome-wide RNA-Seq expressions of several cells during human[8] and mouse[9] embryogenesis
To observe gene expression variability between 2 single cells at each developmental stage, we plotted pair-wise distributions of single cell transcriptomes (Figure 1)

Summary

Introduction

Molecular heterogeneity of individual molecules within single cells has been recently shown to be crucial for cell fate diversifications. Immunofluorescence flow cytometry showed that Sca-1 expressions in multipotent murine hematopoietic cells follow a Gaussian-like distribution[1], and the monitoring of green fluorescent proteins in Escherichia coli displayed fluctuations in their expression levels over time[2] Such heterogeneous or noisy characteristics have shown to play pivotal roles for the survival of species to diverse environmental conditions or for cell fate decisions[3,4,5]. To understand global gene expression structure and noise patterns of single cells during mammalian developmental stages, we investigated transcriptome-wide RNA-Seq expressions of several cells during human[8] and mouse[9] embryogenesis. A total of 7 human and 10 murine cell origins, from oocytes to blastocysts, were analysed using high-dimensional statistical techniques, such as correlation metrics[10,11,12,13,14,15,16], Shannon entropy[17,18,19] and noise analyses[20]

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