Principles of RNA processing from analysis of enhanced CLIP maps for 150 RNA binding proteins

Nostrand, Eric L. Van; Pratt, Gabriel A.; Yee, Brian A.; Wheeler, Emily C.; Blue, Steven M.; Mueller, Jasmine R.; Park, Samuel S.; Garcia, Keri E.; Gelboin-Burkhart, Chelsea; Nguyen, Thai B.; Rabano, Ines; Stanton, Rebecca; Sundararaman, Balaji; Wang, Ruth; Fu, Xiang‐Dong; Graveley, Brenton R.; Yeo, G

doi:10.1101/807008

Cited by 43 publications

(75 citation statements)

References 77 publications

(103 reference statements)

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“…For example, the entropy of sequence TCACTCTCCCACACTCTCTCTCTCTCACACACACACACACACACACACACACACAC ACAC, which has many repeats of AC and TC is 2.1, while the entropy of sequence GAAAGTGTATAACTACAATCACCTAATGCCCACAAGGTACTCTGTGGATATCCCCT TGGA is 4.0. Sequence entropy is expected to be a highly informative predictor of false positive spliced alignments for two reasons: (1) reverse transcriptase or PCR enzymes are known to generate sequences of low entropy ("PCR stutter") 15 , and PCR crossover is common in these regions; (2) these low-entropy sequences typically map to many places in the genome 28 . Also, the entropy could be more informative and variable in scRNA-seq compared to bulk RNA-seq ( Supplementary Figure 1).…”

Section: Methodsmentioning

confidence: 99%

Specific splice junction detection in single cells with SICILIAN

Dehghannasiri

Olivieri

Salzman

2020

Preprint

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Precise splice junction calls are currently unavailable in scRNA-seq pipelines such as the 10x Chromium platform but are critical for understanding single-cell biology.Here, we introduce SICILIAN, a new method that assigns statistical confidence to splice junctions from a spliced aligner to improve precision. SICILIAN's precise splice detection achieves high accuracy on simulated data, improves concordance between matched single-cell and bulk datasets, increases agreement between biological replicates, and reliably detects un-annotated splicing in single cells, enabling the discovery of novel splicing regulation. Main text:Alternative splicing is essential for the specialized functions of eukaryotic cells, necessary for development 1 , and a greater contributor to genetic disease burden than mutations 2 . Despite the importance of splicing and massive RNA-seq data generated on single cells, the extent to which the diversity of RNA splicing in single cells is regulated and functional versus transcriptional noise remains contentious 3 .Given the resolution and massive number of available single-cell RNA-seq (scRNA-seq) datasets, precise quantification of splicing in single cells has great promise for discovering regulatory and functional splicing biology. While there are a number of methods developed for isoform quantification at the single-cell level 4,5 , a problem that has not been addressed is the precise discovery of splice junctions. There is a great need for precise junction detection: spliced aligners are designed for bulk RNA-seq and, in addition, generate many artifacts 6-10 , which will be referred to in this paper as "false positives". The problem is exacerbated in scRNA-seq analysis due to the high-level and single-cell-specific biochemical noise and multiple testing errors arising from the analysis of thousands of cells. This problem is typically addressed through the use of simple filters on junction calls, which remove many true positives, especially when the data is sparse such as scRNA-seq. Because of these challenges, there is debate

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Section: Methodsmentioning

confidence: 99%

Specific splice junction detection in single cells with SICILIAN

Dehghannasiri

Olivieri

Salzman

2020

Preprint

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“…Yet, association and dissociation kinetics of RBPs at individual cellular binding sites have not been experimentally accessible. In cells, steady-state patterns of RNA-protein interactions have been measured [3][4][5] . RBP binding and dissociation kinetics have only been determined in vitro 2,6 .…”

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confidence: 99%

The kinetic landscape of an RNA binding protein in cells

Sharma

Zagore

Brister

et al. 2020

Preprint

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4) Corresponding authors 2 ABSTRACT Gene expression in higher eukaryotic cells orchestrates interactions between thousands of RNA binding proteins (RBPs) and tens of thousands of RNAs 1 . The kinetics by which RBPs bind to and dissociate from their RNA sites are critical for the coordination of cellular RNAprotein interactions 2 . However, these kinetics were experimentally inaccessible in cells. Here we show that time-resolved RNA-protein crosslinking with a pulsed femtosecond UV laser, followed by immunoprecipitation and high throughput sequencing allows the determination of binding and dissociation kinetics of the RBP Dazl for thousands of individual RNA binding sites in cells. This kinetic crosslinking and immunoprecipitation (KIN-CLIP) approach reveals that Dazl resides at individual binding sites only seconds or shorter, while the sites remain Dazl-free markedly longer. The data further indicate that Dazl binds to many RNAs in clusters of multiple proximal sites. The impact of Dazl on mRNA levels and ribosome association correlates with the cumulative probability of Dazl binding in these clusters. Integrating kinetic data with mRNA features quantitatively connects Dazl-RNA binding to Dazl function. Our results show how previously inaccessible, kinetic parameters for RNA-protein interactions in cells can be measured and how these data quantitatively link RBP-RNA binding to cellular RBP function.

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“…Given that the RS splicing machinery utilizes a specific AGGT site while ignoring others (Duff et al, 2015;Hayashi et al, 2018;Joseph et al, 2018;Pai et al, 2018;Sibley et al, 2016;Sibley et al, 2015;Zhang et al, 2018), the RS sites may carry unique features compared to the non-RS AGGT sites. We found that RS sites exhibit specific primary sequence context of U1 snRNA binding site and polypyrimidine tract, which may recruit RNA binding proteins (RBPs), such as exon junction complex and polypyrimidine tract binding proteins (Blazquez et al, 2018;Cai et al, 2020;Duff et al, 2015;Patton et al, 2020;Ule and Blencowe, 2019;Van Nostrand et al, 2020;Xue et al, 2009), to facilitate the recognition of 3'SS. Thus, profiling RBP bindings and RNA structures around the RS and non-RS AGGT sites are necessary to further illustrate the molecular basis of RS.…”

Section: Discussionmentioning

confidence: 99%

Recursive splicing is a rare event in the mouse brain

Moon

Zhao

2020

Preprint

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SummaryRecursive splicing (RS) is a mechanism to excise long introns from messenger RNA precursors. We focused on nuclear RNA, which is enriched for RS splicing intermediates and nascent transcripts, to investigate RS in the mouse brain. We identified new RS sites and discovered that RS is constitutive between excitatory and inhibitory neurons and between sexes in the mouse cerebral cortex. Moreover, we found that the primary sequence context, including the U1 snRNA binding site, the polypyrimidine tract, and a strong 3’ splice site, determines RS sites in long introns. We also uncovered a new type of exon-like RS events termed exonicRS that may represent an intermediate stage of RS sites evolving into annotated exons. Furthermore, the strengths of 5’ splice sites are able to classify RS events into RS sites and exonicRS. Overall, these findings provide mechanistic insights into the splicing and evolution of long genes.

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Principles of RNA processing from analysis of enhanced CLIP maps for 150 RNA binding proteins

Cited by 43 publications

References 77 publications

Specific splice junction detection in single cells with SICILIAN

Specific splice junction detection in single cells with SICILIAN

The kinetic landscape of an RNA binding protein in cells

Recursive splicing is a rare event in the mouse brain

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