Chemical reprogramming provides a powerful platform for exploring the molecular dynamics that lead to pluripotency. Although previous studies have uncovered an intermediate extraembryonic endoderm (XEN)-like state during this process, the molecular underpinnings of pluripotency acquisition remain largely undefined. Here, we profile 36,199 single-cell transcriptomes at multiple time points throughout a highly efficient chemical reprogramming system using RNA-sequencing and reconstruct their progression trajectories. Through identifying sequential molecular events, we reveal that the dynamic early embryonic-like programs are key aspects of successful reprogramming from XEN-like state to pluripotency, including the concomitant transcriptomic signatures of two-cell (2C) embryonic-like and early pluripotency programs and the epigenetic signature of notable genome-wide DNA demethylation. Moreover, via enhancing the 2C-like program by fine-tuning chemical treatment, the reprogramming process is remarkably accelerated. Collectively, our findings offer a high-resolution dissection of cell fate dynamics during chemical reprogramming and shed light on mechanistic insights into the nature of induced pluripotency.

Circular RNAs (circRNAs) are emerging as a new class of endogenous and regulatory noncoding RNAs in latest years. With the widespread application of RNA sequencing (RNA-seq) technology and bioinformatics prediction, large numbers of circRNAs have been identified. However, at present, we lack a comprehensive characterization of all these circRNAs in interested samples. In this study, we integrated 87 935 circRNAs sequences that cover most of circRNAs identified till now represented in circBase to design microarray probes targeting back-splice site of each circRNA to profile expression of those circRNAs. By comparing the circRNA detection efficiency of RNA-seq with this circRNA microarray, we revealed that microarray is more efficient than RNA-seq for circRNA profiling. Then, we found ∼80 000 circRNAs were expressed in cervical tumors and matched normal tissues, and ∼25 000 of them were differently expressed. Notably, many of these circRNAs detected by this microarray can be validated by quantitative reverse transcription polymerase chain reaction (RT-qPCR) or RNA-seq. Strikingly, as many as ∼18 000 circRNAs could be robustly detected in cell-free plasma samples, and the expression of ∼2700 of them differed after surgery for tumor removal. Our findings provided a comprehensive and genome-wide characterization of circRNAs in paired normal tissues and tumors and plasma samples from multiple individuals. In addition, we also provide a rich resource with 41 microarray data sets and 10 RNA-seq data sets and strong evidences for circRNA expression in cervical cancer. In conclusion, circRNAs could be efficiently profiled by circRNA microarray to target their reported back-splice sites in interested samples.

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