Nascent transcriptome of embryonic genome activation reveals a regulatory axis linking transcriptional priming to early lineage specification in mouse embryos

Embryonic genome activation (EGA) marks a critical developmental transition, yet its regulatory architecture remains incompletely defined. Here, we employed optimized low-input SLAM-seq (thiol(SH)-linked alkylation for the metabolic sequencing) to map the temporal hierarchy of nascent transcription during mouse EGA. We uncovered patterns of transcriptional priming characterized by pre-activated genes (PAGs) with permissive chromatin states, followed by pronounced accumulation of PAGs-encoded proteins in blastocysts, suggesting that EGA memory propagates from early transcriptional activation to later lineage commitment. Furthermore, Integrative analysis nominated two-cell nascent transcription factors (TFs) as candidate regulators of the first lineage specification. Functional investigations demonstrated KLF17 as a key TF linking EGA to the first lineage specification via regulation of PAGs transcription. KLF17 deficiency led to the failure of transcriptional activation in approximately half of PAGs at the two-cell stage. Our work provides a detailed framework for decoding mammalian EGA and offers insights into how embryonic transcriptional priming is coordinated with early cell fate specification.

Authors

Institutions

Publication Details

Journal
Nucleic Acids Research
Published
2026-02-17
DOI
https://doi.org/10.1093/nar/gkag173
Primary Topic
Pluripotent Stem Cells Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nascent transcriptome of embryonic genome activation reveals a regulatory axis linking transcriptional priming to early lineage specification in mouse embryos

Zhangyi Ouyang, Ou Zhong, Siqi Wang, Yue Hu et al.
Nucleic Acids Research
Pluripotent Stem Cells Research
article

Nascent transcriptome of embryonic genome activation reveals a regulatory axis linking transcriptional priming to early lineage specification in mouse embryos

Zhangyi Ouyang, Ou Zhong, Siqi Wang, Yue Hu, Ran Huo, Yuxiang Wang, Tianyin Miao, Chao Ren, Wenjie Shu, Yuanlin He, Maosheng Ye, Li Liu
article en

Abstract

Embryonic genome activation (EGA) marks a critical developmental transition, yet its regulatory architecture remains incompletely defined. Here, we employed optimized low-input SLAM-seq (thiol(SH)-linked alkylation for the metabolic sequencing) to map the temporal hierarchy of nascent transcription during mouse EGA. We uncovered patterns of transcriptional priming characterized by pre-activated genes (PAGs) with permissive chromatin states, followed by pronounced accumulation of PAGs-encoded proteins in blastocysts, suggesting that EGA memory propagates from early transcriptional activation to later lineage commitment. Furthermore, Integrative analysis nominated two-cell nascent transcription factors (TFs) as candidate regulators of the first lineage specification. Functional investigations demonstrated KLF17 as a key TF linking EGA to the first lineage specification via regulation of PAGs transcription. KLF17 deficiency led to the failure of transcriptional activation in approximately half of PAGs at the two-cell stage. Our work provides a detailed framework for decoding mammalian EGA and offers insights into how embryonic transcriptional priming is coordinated with early cell fate specification.

Nucleic Acids ResearchVol. 54(5)
Academy of Military Medical Sciences (CN), Soochow University (CN), Suzhou Municipal Hospital (CN), Beijing Radiation Center (CN), Institute of Bioinformatics (IN), Changzhou No.2 People's Hospital (CN), Changzhou University (CN), Nanjing Medical University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Tsinghua University, Tongji University, Nanjing Medical University, National Key Research and Development Program of China
Openalex Percentile: Top 40%
Pluripotent Stem Cells Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.