Thrilled to share our research on designing better 3' UTRs for mRNA therapeutics and vaccines!
By integrating high-throughput stability assays, machine learning models, and mRNA domain expertise, we engineered 3' UTRs that improve mRNA stability and protein production in vivo.
Excited to share our recent work at @Ginkgo . TLDR: high quality mRNA stability data -> performant ML models -> design 3’UTRs that increase stability -> in vivo validated ML 3’UTRs beat benchmark. https://t.co/z7PUAHaHHg
@AlyssaKMorrow@laserson Check out the manuscript for insights on the behavior of ML model architectures and design strategies when interpreting mRNA sequence,
And for important results on the translation of mRNA sequence activity between contexts -- a consistent challenge in therapeutic development.
Excited to share our recent work at @Ginkgo . TLDR: high quality mRNA stability data -> performant ML models -> design 3’UTRs that increase stability -> in vivo validated ML 3’UTRs beat benchmark. https://t.co/z7PUAHaHHg
🚨Our work on multi-modal, single-cell pooled CRISPR screens to study GWAS variant-to-function, STING-seq, is now out in @ScienceMagazine! Read on for 6⃣ of the main findings from our study, led by myself and co-advised by @nevillesanjana and @tuuliel! 🎉
https://t.co/0LUM3m40v3
last talk: Ruchi Iohia from @JesseAGillis lab talking about chromatin interactions. Does a meta-analysis of Hi-C experiments, and found it did a better job of capturing interactions as validated by eQTLs gene co-expression: especially trans effects! #ashg22
also appreciated the intro to HARs and HAQERs, the most highly divergent between chimp-human ancestor + humans. They're located near chromosome ends, enriched in bivalent chromatin states, and enriched in disease-linked variation (particularly for bipolar disorder, schizophrenia)
Now @riley_mangan using single cell in vivo brain MPRA to find regulatory effects of human accelerated region (HAR) regulatory elements. Finds hominin-specific and cell-type-specific effects! #ashg22
Maya Bose from @theparkerlab with a talk about position-dependent effects of regulatory elements in an MPRA. Many TFBSs had larger effect upstream of promoter vs. downstream (including E2F, ETS), and activity was heavily biased for the forward strand #ashg22
@bowennjin finished up a great talk of promoter kinetics in cell lines: TF binding influences transcriptional burst frequency, not burst size. If frequency/size have opposite effects, they may be masked in classic eQTL studies #ashg22
Great meeting of the @GeneticsSociety Program Committee! It was an intense 1.5 days but we have an exciting program coming up for you. See you all in Los Angeles in October.
Have you wondered what eQTLs are or how they work?? @tuuliel_lab and I wrote a review about determining causal variants, elucidating molecular mechanisms, and understanding the context variability of eQTLs. https://t.co/yoyaypzhaW