Semicoordinated allelic-bursting shape dynamic random monoallelic expression in pregastrulation embryos

Abstract

Recently, allele-specific single-cell RNA-seq analysis has demonstrated widespread dynamic random monoallelic expression of autosomal genes (aRME) in different cell types. However, the prevalence of dynamic aRME during pregastrulation remains unknown. Here, we show that dynamic aRME is widespread in different lineages of pregastrulation embryos. Additionally, the origin of dynamic aRME remains elusive. It is believed that independent transcriptional bursting from each allele leads to dynamic aRME. Here, we show that allelic burst is not perfectly independent; instead it happens in a semicoordinated fashion. Importantly, we show that semicoordinated allelic bursting of genes, particularly with low burst frequency, leads to frequent asynchronous allelic bursting, thereby contributing to dynamic aRME. Furthermore, we found that coordination of allelic bursting is lineage specific and genes regulating the development have a higher degree of coordination. Altogether, our study provides significant insights into the prevalence and origin of dynamic aRME and their developmental relevance during early development.

Lineage-specific dynamics of erasure of X-upregulation during inactive-X reactivation

“…We performed allele-specific analysis of RNA-Seq data as described previously (Naik et al, 2021(Naik et al, , 2022. In brief, we created in silico reference genome by incorporating strain-specific SNPs in to the mm10 reference genome.…”

Single-cell analysis reveals X upregulation is not global in pre-gastrulation embryos

“…These embryos were derived from two divergent mouse strains (C57BL/6J and CAST/EiJ) and therefore harbored polymorphic sites across the genome, allowing us to profile gene expression with allelic resolution ( Figure 1 A). First, we classified the cells of E5.5, E6.25, and E6.5 mouse embryos into the three lineages: epiblast (EPI), extraembryonic ectoderm (ExE), and visceral endoderm (VE) based on our previous work (see detail in STAR Methods ) ( Naik et al., 2021 ) ( Figure 1 A). Next, we categorized the cells of different lineages of the female embryos based on their XCI status: cells with no XCI (X a X a ), partial or undergoing XCI (X a X p ), and complete XCI (X a X i ) through profiling the fraction of maternal allele expression ( Figure 1 B).…”

“…We collected the data related to classification of different lineages (EPI, ExE and VE) of pre-gastrulation embryos from our previous work ( Naik et al., 2021 ). In brief, all single cells were subjected to t-distributed stochastic neighbour embedding (t-SNE) to cluster cells and identify lineages.…”

“…We normalized allelic read counts using Spike-in control as described in Naik et al. (2021) ( Naik et al., 2021 ). In brief, we calculated the sum of reads mapping to all Spike-in molecule in individual cell and then we divided each cell’s Spike-in reads with the highest Spike in value to deduce the normalization factors.…”

VariableDNAtopology is an epigenetic generator of physiological heterogeneity in bacterial populations

“…Transcriptional “burstiness” means that, at any given time, some gene copies remain silent while others are firing, and those genes that are firing do so in bursts. This phenomenon is not restricted to bacteria: it occurs in all cell types, including those of humans (Larsson et al, 2021 ; Naik et al, 2021 ). Bursting reflects the stochastic operation of numerous processes that facilitate or inhibit RNA polymerase activity in both simple and complex organisms (Bahar Halpern et al, 2015 ; Chubb et al, 2006 ; Corrigan et al, 2016 ; Dar et al, 2012 ; Golding et al, 2005 ; Levsky et al, 2002 ; Raj et al, 2006 ; Raj & van Oudenaarden, 2008 , 2009 ; Suter et al, 2011 ).…”