AI Article Synopsis

  • The study examines the processes regulating mRNA in cells by tracking its movement through different compartments using a technique called subcellular TimeLapse-seq.
  • The findings reveal that transcripts from functionally similar genes exhibit comparable movement rates, and a relationship between the DDX3X protein and nuclear export of RNA is established.
  • The research also shows that mRNA with longer chromatin residency tends to have longer poly(A) tails, while machine learning techniques were used to predict the various lifecycles of these mRNAs based on their molecular characteristics.

Article Abstract

Dissecting the regulatory mechanisms controlling mammalian transcripts from production to degradation requires quantitative measurements of mRNA flow across the cell. We developed subcellular TimeLapse-seq to measure the rates at which RNAs are released from chromatin, exported from the nucleus, loaded onto polysomes, and degraded within the nucleus and cytoplasm in human and mouse cells. These rates varied substantially, yet transcripts from genes with related functions or targeted by the same transcription factors and RNA-binding proteins flowed across subcellular compartments with similar kinetics. Verifying these associations uncovered a link between DDX3X and nuclear export. For hundreds of RNA metabolism genes, most transcripts with retained introns were degraded by the nuclear exosome, while the remaining molecules were exported with stable cytoplasmic lifespans. Transcripts residing on chromatin for longer had extended poly(A) tails, whereas the reverse was observed for cytoplasmic mRNAs. Finally, machine learning identified molecular features that predicted the diverse life cycles of mRNAs.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11315470PMC
http://dx.doi.org/10.1016/j.molcel.2024.06.008DOI Listing

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