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Spliceosome Profiling Visualizes Operations of a Dynamic RNP at Nucleotide Resolution
Author(s) -
Jordan E. Burke,
Adam D Longhurst,
Daria Merkurjev,
Jade Sales-Lee,
Beiduo Rao,
James J. Moresco,
John R. Yates,
Jingyi Jessica Li,
Hiten D. Madhani
Publication year - 2018
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2018.03.020
Subject(s) - biology , spliceosome , profiling (computer programming) , computational biology , genetics , resolution (logic) , rna splicing , rna , gene , artificial intelligence , computer science , operating system
Tools to understand how the spliceosome functions in vivo have lagged behind advances in the structural biology of the spliceosome. Here, methods are described to globally profile spliceosome-bound pre-mRNA, intermediates, and spliced mRNA at nucleotide resolution. These tools are applied to three yeast species that span 600 million years of evolution. The sensitivity of the approach enables the detection of canonical and non-canonical events, including interrupted, recursive, and nested splicing. This application of statistical modeling uncovers independent roles for the size and position of the intron and the number of introns per transcript in substrate progression through the two catalytic stages. These include species-specific inputs suggestive of spliceosome-transcriptome coevolution. Further investigations reveal the ATP-dependent discard of numerous endogenous substrates after spliceosome assembly in vivo and connect this discard to intron retention, a form of splicing regulation. Spliceosome profiling is a quantitative, generalizable global technology used to investigate an RNP central to eukaryotic gene expression.

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