@manoliskellis@xinchen_w@MelinaClaussnit@JasonErnstLab Thank you so much for your patience and generous mentorship, Manolis! It's been an incredible journey of over 7 years, and it’s been worth every moment. I’ve learned so much from your group!👑
1/ Excited to share our latest paper published in @ScienceTM! 🧬 https://t.co/cw8w876Ogi. This journey was a true team effort with @ypp_lab, Liang, and Matt, under the guidance of @DavidHaflerMD and @manoliskellis. Here's a breakdown of our findings.
Thank you, Yongjin! This has been one of the best collaborations I've ever had. I’m so proud to be working with you, Liang, and Matt! Let’s keep up the great work together.
13/ This work was a massive collaboration—thank you to everyone involved! We hope these findings pave the way for new insights into Treg dysfunction and autoimmune disease. Stay tuned for more!
12/ Using CRISPRa, we pinpointed a specific regulatory element within the PRDM1 locus tied to PRDM1-S, with an AP-1/IRF composite motif. This supports our theory that these TFs are key in driving PRDM1-S expression.
Great paper. I strongly agree that causal gene regulatory network inference (i.e. where u can actually claim gene A causally and directly regulates gene B) using mRNA alone is impossible IMHO. Even from perturbation expts. I think this is impossible. 1/