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Genome-wide quantification of RNA flow across subcellular compartments reveals determinants of the mammalian transcript life cycle
被引:10
|作者:
Ietswaart, Robert
[1
,6
]
Smalec, Brendan M.
[1
]
Xu, Albert
[2
]
Choquet, Karine
[1
]
Mcshane, Erik
[1
]
Jowhar, Ziad Mohamoud
[2
]
Guegler, Chantal K.
[1
]
Baxter-Koenigs, Autum R.
[1
]
West, Emma R.
[1
]
Fu, Becky Xu Hua
[3
]
Gilbert, Luke
[3
,4
,5
]
Floor, Stephen N.
[2
,4
]
Churchman, L. Stirling
[1
]
机构:
[1] Harvard Med Sch, Blavatnik Inst, Dept Genet, Boston, MA 02115 USA
[2] Univ Calif San Francisco, Dept Cell & Tissue Biol, San Francisco, CA 94143 USA
[3] Arc Inst, Palo Alto, CA 94305 USA
[4] Univ Calif San Francisco, Helen Diller Family Comprehens Canc Ctr, San Francisco, CA 94143 USA
[5] Univ Calif San Francisco, Dept Urol, San Francisco, CA 94518 USA
[6] Cellforma, Cambridge, MA 02139 USA
基金:
美国国家卫生研究院;
美国国家科学基金会;
加拿大健康研究院;
关键词:
PRE-MESSENGER-RNA;
TRANSLATION INITIATION;
HELICASE DDX3;
NUCLEAR EXPORT;
PROTEIN;
GENE;
DYNAMICS;
MUTATIONS;
IDENTIFICATION;
DEGRADATION;
D O I:
10.1016/j.molcel.2024.06.008
中图分类号:
Q5 [生物化学];
Q7 [分子生物学];
学科分类号:
071010 ;
081704 ;
摘要:
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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页码:2765 / 2784.e16
页数:37
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