Really cool work led by @huaigengxu.bsky.social. Too bad, I don't get to see it live. 🤞

Thanks for the shout-out, we appreciate it.

Thanks for your kind words, and your amazing contributions!

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This experience underscores the need for a more supportive review process to effectively promote the next generation of scientists.
We thank those reviewers and editors who were tough but fair sports, providing constructive feedback that helped improve our work. Also, we thank NIH for support.

6/
• Reviewer defamatory language 😔
• Lack of reviewer argumentation (claim, reason, support, and warrant)
• De novo concerns in 2nd round review
• Lack of support from journal team despite 8 months of costly revision experiments

5/
However, our journey wasn’t without challenges. Previous submission to a major NPG journal faced:

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📃 Our findings highlight critical new functions of KMT2C/KMT2D beyond transcriptional regulation, essential for understanding diseases associated with mutations in these genes.

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📊 Key Findings:
• Chromatin state predicts local RT in steady state and its changes during differentiation.
• H3K4me1 emerges as a top predictor.
• Loss of H3K4me1 locally impairs RT changes independent of transcription.
• H3K4me1 locally promotes replication origin activation.

2/
🔬 Approach:
• Developed an improved biotin-based DNA RT profiling method.
• Profiled 21 chromatin features by CUT&Tag during early pluripotency cell state transition.
• Used machine learning to identify chromatin features predictive of RT in steady state and during differentiation.

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I am grateful to have led this research, working alongside an incredible team: Liana Goehring (@lianagoehring.bsky.social), Ryan Boileau (@bffswithbiology.bsky.social), Kayla Lenshoek (@klenshoek.bsky.social), Tony Huang, and Robert Blelloch (@robertblelloch.bsky.social). 🙏