Epigenetics regulations have an important role in fertilization and proper embryonic development, and several human diseases are associated with epigenetic modification disorders, such as Rett syndrome, Beckwith-Wiedemann syndrome and Angelman syndrome. However, the dynamics and functions of long non-coding RNAs (lncRNAs), one type of epigenetic regulators, in human pre-implantation development have not yet been demonstrated. In this study, a comprehensive analysis of human and mouse early-stage embryonic lncRNAs was performed based on public single-cell RNA sequencing data. Expression profile analysis revealed that lncRNAs are expressed in a developmental stage-specific manner during human early-stage embryonic development, whereas a more temporal-specific expression pattern was identified in mouse embryos. Weighted gene co-expression network analysis suggested that lncRNAs involved in human early-stage embryonic development are associated with several important functions and processes, such as oocyte maturation, zygotic genome activation and mitochondrial functions. We also found that the network of lncRNAs involved in zygotic genome activation was highly preservative between human and mouse embryos, whereas in other stages no strong correlation between human and mouse embryo was observed. This study provides insight into the molecular mechanism underlying lncRNA involvement in human pre-implantation embryonic development.
Temporal-specific expression of lncRNAs
(A) Boxplot indicating the distribution of Spearman’s rank correlation coefficients between each embryonic sample pair derived from lncRNAs and coding genes (* means P-value < 0.05). (B) Distribution of JSD-based specificity of genes in various stages. (C) Distribution of maximal expression (log10-normalized FPKM counts estimated by Cufflinks) of lncRNAs and coding genes in human pre-implantation development. (D) Pearson correlation coefficient distributions for expression levels across the samples in human pre-implantation development. The random pairs are 10,000 random pairs of protein-coding genes.