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Gildea MA, Dwyer ZW, Pleiss JA. Transcript-specific determinants of pre-mRNA splicing revealed through in vivo kinetic analyses of the 1 st and 2 nd chemical steps. Mol Cell 2022; 82:2967-2981.e6. [PMID: 35830855 PMCID: PMC9391291 DOI: 10.1016/j.molcel.2022.06.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 01/31/2022] [Accepted: 06/12/2022] [Indexed: 10/17/2022]
Abstract
We generate high-precision measurements of the in vivo rates of both chemical steps of pre-mRNA splicing across the genome-wide complement of substrates in yeast by coupling metabolic labeling, multiplexed primer-extension sequencing, and kinetic modeling. We demonstrate that the rates of intron removal vary widely, splice-site sequences are primary determinants of 1st step but have little apparent impact on 2nd step rates, and the 2nd step is generally faster than the 1st step. Ribosomal protein genes (RPGs) are spliced faster than non-RPGs at each step, and RPGs share evolutionarily conserved properties that may contribute to their faster splicing. A genetic variant defective in the 1st step of the pathway reveals a genome-wide defect in the 1st step but an unexpected, transcript-specific change in the 2nd step. Our work demonstrates that extended co-transcriptional association is an important determinant of splicing rate, a conclusion at odds with recent claims of ultra-fast splicing.
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Affiliation(s)
- Michael A Gildea
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14850, USA
| | - Zachary W Dwyer
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14850, USA
| | - Jeffrey A Pleiss
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14850, USA.
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Desgranges E, Caldelari I, Marzi S, Lalaouna D. Navigation through the twists and turns of RNA sequencing technologies: Application to bacterial regulatory RNAs. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2020; 1863:194506. [PMID: 32068131 DOI: 10.1016/j.bbagrm.2020.194506] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 02/11/2020] [Accepted: 02/13/2020] [Indexed: 12/20/2022]
Abstract
Discovered in the 1980s, small regulatory RNAs (sRNAs) are now considered key actors in virtually all aspects of bacterial physiology and virulence. Together with transcriptional and translational regulatory proteins, they integrate and often are hubs of complex regulatory networks, responsible for bacterial response/adaptation to various perceived stimuli. The recent development of powerful RNA sequencing technologies has facilitated the identification and characterization of sRNAs (length, structure and expression conditions) and their RNA targets in several bacteria. Nevertheless, it could be very difficult for non-experts to understand the advantages and drawbacks related to each offered option and, consequently, to make an informed choice. Therefore, the main goal of this review is to provide a guide to navigate through the twists and turns of high-throughput RNA sequencing technologies, with a specific focus on those applied to the study of sRNAs. This article is part of a Special Issue entitled: RNA and gene control in bacteria edited by Dr. M. Guillier and F. Repoila.
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Affiliation(s)
- Emma Desgranges
- Université de Strasbourg, CNRS, ARN UPR 9002, F-67000 Strasbourg, France
| | - Isabelle Caldelari
- Université de Strasbourg, CNRS, ARN UPR 9002, F-67000 Strasbourg, France
| | - Stefano Marzi
- Université de Strasbourg, CNRS, ARN UPR 9002, F-67000 Strasbourg, France
| | - David Lalaouna
- Université de Strasbourg, CNRS, ARN UPR 9002, F-67000 Strasbourg, France.
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Foria S, Copetti D, Eisenmann B, Magris G, Vidotto M, Scalabrin S, Testolin R, Cipriani G, Wiedemann-Merdinoglu S, Bogs J, Di Gaspero G, Morgante M. Gene duplication and transposition of mobile elements drive evolution of the Rpv3 resistance locus in grapevine. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 101:529-542. [PMID: 31571285 DOI: 10.1111/tpj.14551] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 09/12/2019] [Accepted: 09/18/2019] [Indexed: 05/08/2023]
Abstract
A wild grape haplotype (Rpv3-1) confers resistance to Plasmopara viticola. We mapped the causal factor for resistance to an interval containing a TIR-NB-LRR (TNL) gene pair that originated 1.6-2.6 million years ago by a tandem segmental duplication. Transient coexpression of the TNL pair in Vitis vinifera leaves activated pathogen-induced necrosis and reduced sporulation compared with control leaves. Even though transcripts of the TNL pair from the wild haplotype appear to be partially subject to nonsense-mediated mRNA decay, mature mRNA levels in a homozygous resistant genotype were individually higher than the mRNA trace levels observed for the orthologous single-copy TNL in sensitive genotypes. Allelic expression imbalance in a resistant heterozygote confirmed that cis-acting regulatory variation promotes expression in the wild haplotype. The movement of transposable elements had a major impact on the generation of haplotype diversity, altering the DNA context around similar TNL coding sequences and the GC-content in their proximal 5'-intergenic regions. The wild and domesticated haplotypes also diverged in conserved single-copy intergenic DNA, but the highest divergence was observed in intraspecific and not in interspecific comparisons. In this case, introgression breeding did not transgress the genetic boundaries of the domesticated species, because haplotypes present in modern varieties sometimes predate speciation events between wild and cultivated species.
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Affiliation(s)
- Serena Foria
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
| | - Dario Copetti
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
- Istituto di Genomica Applicata, via Jacopo Linussio 51, 33100, Udine, Italy
- Institute of Agricultural Sciences, ETH Zürich, Universitätstrasse 2, 8092, Zürich, Switzerland
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zürich, Switzerland
| | - Birgit Eisenmann
- State Education and Research Center of Viticulture, Horticulture and Rural Development, Breitenweg 71, 67435, Neustadt an der Weinstraße, Germany
- Centre for Organismal Studies Heidelberg, University of Heidelberg, 69120, Heidelberg, Germany
| | - Gabriele Magris
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
- Istituto di Genomica Applicata, via Jacopo Linussio 51, 33100, Udine, Italy
| | - Michele Vidotto
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
| | - Simone Scalabrin
- Istituto di Genomica Applicata, via Jacopo Linussio 51, 33100, Udine, Italy
| | - Raffaele Testolin
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
| | - Guido Cipriani
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
| | | | - Jochen Bogs
- State Education and Research Center of Viticulture, Horticulture and Rural Development, Breitenweg 71, 67435, Neustadt an der Weinstraße, Germany
- Technische Hochschule Bingen, 55411, Bingen am Rhein, Germany
| | | | - Michele Morgante
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
- Istituto di Genomica Applicata, via Jacopo Linussio 51, 33100, Udine, Italy
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On the optimal design of metabolic RNA labeling experiments. PLoS Comput Biol 2019; 15:e1007252. [PMID: 31390362 PMCID: PMC6699717 DOI: 10.1371/journal.pcbi.1007252] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Revised: 08/19/2019] [Accepted: 07/08/2019] [Indexed: 01/16/2023] Open
Abstract
Massively parallel RNA sequencing (RNA-seq) in combination with metabolic labeling has become the de facto standard approach to study alterations in RNA transcription, processing or decay. Regardless of advances in the experimental protocols and techniques, every experimentalist needs to specify the key aspects of experimental design: For example, which protocol should be used (biochemical separation vs. nucleotide conversion) and what is the optimal labeling time? In this work, we provide approximate answers to these questions using the asymptotic theory of optimal design. Specifically, we investigate, how the variance of degradation rate estimates depends on the time and derive the optimal time for any given degradation rate. Subsequently, we show that an increase in sample numbers should be preferred over an increase in sequencing depth. Lastly, we provide some guidance on use cases when laborious biochemical separation outcompetes recent nucleotide conversion based methods (such as SLAMseq) and show, how inefficient conversion influences the precision of estimates. Code and documentation can be found at https://github.com/dieterich-lab/DesignMetabolicRNAlabeling. Massively parallel RNA sequencing (RNA-seq) in combination with metabolic labeling has become the de facto standard approach to study alterations in RNA transcription, processing or decay. In our manuscript, we address several key aspects of experimental design: 1) The optimal labeling time, 2) the number of replicate samples over sequencing depth and 3) the choice of experimental protocol. We provide approximate answers to these questions using asymptotic theory of optimal design.
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Wachutka L, Caizzi L, Gagneur J, Cramer P. Global donor and acceptor splicing site kinetics in human cells. eLife 2019; 8:45056. [PMID: 31025937 PMCID: PMC6548502 DOI: 10.7554/elife.45056] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Accepted: 04/25/2019] [Indexed: 11/13/2022] Open
Abstract
RNA splicing is an essential part of eukaryotic gene expression. Although the mechanism of splicing has been extensively studied in vitro, in vivo kinetics for the two-step splicing reaction remain poorly understood. Here, we combine transient transcriptome sequencing (TT-seq) and mathematical modeling to quantify RNA metabolic rates at donor and acceptor splice sites across the human genome. Splicing occurs in the range of minutes and is limited by the speed of RNA polymerase elongation. Splicing kinetics strongly depends on the position and nature of nucleotides flanking splice sites, and on structural interactions between unspliced RNA and small nuclear RNAs in spliceosomal intermediates. Finally, we introduce the 'yield' of splicing as the efficiency of converting unspliced to spliced RNA and show that it is highest for mRNAs and independent of splicing kinetics. These results lead to quantitative models describing how splicing rates and yield are encoded in the human genome.
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Affiliation(s)
- Leonhard Wachutka
- Department of Informatics, Technical University of Munich, Garching, Germany
| | - Livia Caizzi
- Department of Molecular Biology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany
| | - Julien Gagneur
- Department of Informatics, Technical University of Munich, Garching, Germany
| | - Patrick Cramer
- Department of Molecular Biology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany
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