N3‐kethoxal Based Bioorthogonal Intracellular RNA Labeling

ChemBioChem ◽  
2021 ◽  
Author(s):  
Jinguo Huang ◽  
Ruiqi Zhao ◽  
Jing Mo ◽  
Fang Wang ◽  
xiaocheng weng ◽  
...  
Keyword(s):  
Rna Labeling

scholarly journals Native molecule sequencing by nano-ID reveals synthesis and stability of RNA isoforms

2019 ◽  
Author(s):  
Kerstin C. Maier ◽  
Saskia Gressel ◽  
Patrick Cramer ◽  
Björn Schwalb
Keyword(s):  
Rna Stability ◽  
Tail Length ◽  
Rna Metabolism ◽  
Synthesis Rate ◽  
Specific Gene ◽  
Nanopore Sequencing ◽  
Rna Molecules ◽  
Eukaryotic Genes ◽  
Rna Labeling ◽  
Long Read

AbstractEukaryotic genes often generate a variety of RNA isoforms that can lead to functionally distinct protein variants. The synthesis and stability of RNA isoforms is however poorly characterized. The reason for this is that current methods to quantify RNA metabolism use ‘short-read’ sequencing that cannot detect RNA isoforms. Here we present nanopore sequencing-based Isoform Dynamics (nano-ID), a method that detects newly synthesized RNA isoforms and monitors isoform metabolism. nano-ID combines metabolic RNA labeling, ‘long-read’ nanopore sequencing of native RNA molecules and machine learning. Application of nano-ID to the heat shock response in human cells reveals that many RNA isoforms change their synthesis rate, stability, and splicing pattern. nano-ID also shows that the metabolism of individual RNA isoforms differs strongly from that estimated for the combined RNA signal at a specific gene locus. And although combined RNA stability correlates with poly(A)-tail length, individual RNA isoforms can deviate significantly. nano-ID enables studies of RNA metabolism on the level of single RNA molecules and isoforms in different cell states and conditions.

scholarly journals Live imaging and biophysical modeling support a button-based mechanism of somatic homolog pairing in Drosophila

2020 ◽  
Author(s):  
Myron Child ◽  
Jack R. Bateman ◽  
Amir Jahangiri ◽  
Armando Reimer ◽  
Nicholas C. Lammers ◽  
...  
Keyword(s):  
Spatial Configuration ◽  
Live Imaging ◽  
Biophysical Model ◽  
Structural Basis ◽  
Biophysical Modeling ◽  
Homologous Chromosomes ◽  
3D Genome ◽  
Homolog Pairing ◽  
Rna Labeling ◽  
Regulated Gene Expression

AbstractThe spatial configuration of the eukaryotic genome is organized and dynamic, providing the structural basis for regulated gene expression in living cells. In Drosophila melanogaster, 3D genome organization is characterized by somatic homolog pairing, where homologous chromosomes are intimately paired from end to end; however, the process by which homologs identify one another and pair has remained mysterious. A recent model proposed that specifically interacting “buttons” encoded along the lengths of homologous chromosomes drive somatic homolog pairing. Here, we turned this hypothesis into a precise biophysical model to demonstrate that a button-based mechanism can lead to chromosome-wide pairing. We tested our model and constrained its free parameters using live-imaging measurements of chromosomal loci tagged with the MS2 and PP7 nascent RNA labeling systems. Our analysis showed strong agreement between model predictions and experiments in the separation dynamics of tagged homologous loci as they transition from unpaired to paired states, and in the percentage of nuclei that become paired as embryonic development proceeds. In sum, as a result of this dialogue between theory and experiment, our data strongly support a button-based mechanism of somatic homolog pairing in Drosophila and provide a theoretical framework for revealing the molecular identity and regulation of buttons.

Current Approaches for RNA Labeling in Vitro and in Cells Based on Click Reactions

ChemBioChem ◽  
2014 ◽  
Vol 15 (16) ◽  
pp. 2342-2347 ◽  
Author(s):  
Daniela Schulz ◽  
Andrea Rentmeister
Keyword(s):  
Click Reactions ◽  
Rna Labeling ◽  
In Cells

scholarly journals Tag‐Free Internal RNA Labeling and Photocaging Based on mRNA Methyltransferases

2020 ◽  
Author(s):  
Anna Ovcharenko ◽  
Florian P. Weissenboeck ◽  
Andrea Rentmeister
Keyword(s):  
Rna Labeling

Quantum Dot Nanobeacons for Single RNA Labeling and Imaging

2019 ◽  
Vol 141 (34) ◽  
pp. 13454-13458 ◽  
Author(s):  
Yingxin Ma ◽  
Guobin Mao ◽  
Weiren Huang ◽  
Guoqiang Wu ◽  
Wen Yin ◽  
...  
Keyword(s):  
Quantum Dot ◽  
Rna Labeling

scholarly journals Single-molecule analysis of gene expression using two-color RNA labeling in live yeast

2012 ◽  
Vol 10 (2) ◽  
pp. 119-121 ◽  
Author(s):  
Sami Hocine ◽  
Pascal Raymond ◽  
Daniel Zenklusen ◽  
Jeffrey A Chao ◽  
Robert H Singer
Keyword(s):  
Gene Expression ◽  
Single Molecule ◽  
Rna Labeling ◽  
Single Molecule Analysis ◽  
Live Yeast

scholarly journals NUCLEOLAR AND NUCLEAR RNA SYNTHESIS DURING THE CELL LIFE CYCLE IN MONKEY AND PIG KIDNEY CELLS IN VITRO

1967 ◽  
Vol 33 (2) ◽  
pp. 273-279 ◽  
Author(s):  
Jane L. Showacre ◽  
W. G. Cooper ◽  
D. M. Prescott
Keyword(s):  
Life Cycle ◽  
Rna Synthesis ◽  
Kidney Cells ◽  
Pig Kidney ◽  
Rna Labeling ◽  
Cell Life ◽  
Nuclear Rna ◽  
Nucleolar Rna ◽  
Pig Kidney Cells

The incorporation of 5-3H-uridine and 5-3H-cytidine into nucleolar and nonnucleolar RNA in the nucleus of monkey and pig kidney cells was measured in vitro during the cell life cycle. Time-lapse cinematographic records were made of cells during asynchronous exponential proliferation, in order to identify the temporal position of individual cells in relation to the preceding mitosis. Immediately following cinematography, cells were labeled with uridine-3H and cytidine-3H for a short period, fixed, and analyzed by radioautography. Since the data permit correlation of the rate of RNA labeling with the position of a cell within the cycle, curves could be constructed describing the rate of RNA synthesis over the average cell cycle. RNA synthesis was absent in early telophase, and rose very abruptly in rate in late telophase and in very early G1 in both the nucleus and the reconstituting nucleolus. Thereafter, through the G1 and S periods the rate of nuclear RNA synthesis rose gradually. When we used a 10-min pulse, there was no detectable change in the rate for nucleolar RNA labeling in monkey kidney cells during G1 or S. When we used a 30-min labeling time, the rate of nucleolar RNA labeling rose gradually in pig kidney cells. With increasing time after mitosis, the data became more variable, which may, in part, be related to the variation in generation times for individual cells.

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