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Alternative polyadenylation (APA) generates different 3′‐untranslated regions (3′UTRs) to regulate gene expression and localization, and affects a variety of biological processes. Here, we characterized the 3′UTR dynamics during the oocyte‐to‐zygote transition by analysing our previously reported porcine single‐cell RNA‐seq (scRNA‐seq) datasets (in vitro matured metaphase II (MII) oocytes, in vitro fertilized zygotes (IVF1) and parthenogenetically activated 1‐cell embryos (PA1)). After IVF1 versus MII comparison, dynamic analyses of APA from RNA‐seq (DaPars) method identified 139 mRNAs with significantly different 3′UTRs (padj. ≤.05), mainly enriched in cell cycle, regulation of cyclin‐dependent protein kinase activity, histone modification, mRNA surveillance, and regulation of actin cytoskeleton. For PA1 versus MII comparison, 105 mRNAs with significantly different 3′UTRs (padj. ≤.05) were identified to be mainly enriched in intracellular transport, mitotic spindle organization, cell cycle, pyruvate metabolism and glycolysis/gluconeogenesis. Furthermore, there were 7 mRNAs with more significant 3′UTR differences (|△PDUI| ≥ 0.45 and |log2[PDUI ratio]| ≥ 0.59) respectively in IVF1 versus MII (Lrp2bp, Mtfr2, Nhlrc2, Psip1, Smu1, Ssr1 and Wtap) and PA1 versus MII (Asf1b, Dimt1, Nap1l1, Ncoa4, Nudt21, Pnn and Rpl15) comparisons. Integrative genomics viewer analysis further identified that 3′UTRs of Psip1, Smu1, Ssr1 and Wtap had more than 140 nt average length changes, whereas those of Dimt1, Nap1l1 and Rpl15 were shortened with more than 460 nt. Regulatory elements (PAS, CPE, microRNA binding sites and m6A sites) in 3′UTRs of different lengths were predicted. Our findings provide useful information to further investigate the molecular mechanism of 3′UTR in regulating the oocyte‐to‐zygote transition of pig embryos. [ABSTRACT FROM AUTHOR]

Knowledge of the transcription factor binding landscape (TFBL) is necessary to analyze gene regulatory networks for important agronomic traits. However, a low‐cost and high‐throughput in vivo chromatin profiling method is still lacking in plants. Here, we developed a transient and simplified cleavage under targets and tagmentation (tsCUT&Tag) that combines transient expression of transcription factor proteins in protoplasts with a simplified CUT&Tag without nucleus extraction. Our tsCUT&Tag method provided higher data quality and signal resolution with lower sequencing depth compared with traditional ChIP‐seq. Furthermore, we developed a strategy combining tsCUT&Tag with machine learning, which has great potential for profiling the TFBL across plant development. [ABSTRACT FROM AUTHOR]