scholarly journals A high-content RNAi screen reveals multiple roles for long noncoding RNAs in cell division

2019 ◽  
Author(s):  
Lovorka Stojic ◽  
Aaron T L Lun ◽  
Patrice Mascalchi ◽  
Christina Ernst ◽  
Aisling M Redmond ◽  
...  
Keyword(s):  
Cell Division ◽  
Genome Stability ◽  
Noncoding Rnas ◽  
Cell Types ◽  
Long Noncoding Rnas ◽  
Genomic Locus ◽  
Daughter Cells ◽  
Acting Mechanism ◽  
Multiple Cell ◽  
Necessary And Sufficient

ABSTRACTGenome stability relies on proper coordination of mitosis and cytokinesis, where dynamic microtubules capture and faithfully segregate chromosomes into daughter cells. The role of long noncoding RNAs (lncRNAs) in controlling these processes however remains largely unexplored. To identify lncRNAs with mitotic functions, we performed a high-content RNAi imaging screen targeting more than 2,000 human lncRNAs. By investigating major hallmarks of cell division such as chromosome segregation, mitotic duration and cytokinesis, we discovered numerous lncRNAs with functions in each of these processes. The chromatin-associated lncRNA, linc00899, was selected for in-depth studies due to the robust mitotic delay observed upon its depletion. Transcriptome analysis of linc00899-depleted cells together with gain-of-function and rescue experiments across multiple cell types identified the neuronal microtubule-binding protein, TPPP/p25, as a target of linc00899. Linc00899 binds the genomic locus of TPPP/p25 and suppresses its transcription through a cis-acting mechanism. In cells depleted of linc00899, the consequent upregulation of TPPP/p25 alters microtubule dynamics and is necessary and sufficient to delay mitosis. Overall, our comprehensive screen identified several lncRNAs with roles in genome stability and revealed a new lncRNA that controls microtubule behaviour with functional implications beyond cell division.

scholarly journals Mitotic antipairing of homologous and sex chromosomes via spatial restriction of two haploid sets

2018 ◽  
Vol 115 (52) ◽  
pp. E12235-E12244 ◽  
Author(s):  
Lisa L. Hua ◽  
Takashi Mikawa
Keyword(s):  
Genome Instability ◽  
Cell Types ◽  
Parental Origin ◽  
Meridional Plane ◽  
Homologous Chromosomes ◽  
Daughter Cells ◽  
Homologous Chromosome Pairing ◽  
Multiple Cell ◽  
Mouse Cells ◽  
Nuclear Polarity

Pairing homologous chromosomes is required for recombination. However, in nonmeiotic stages it can lead to detrimental consequences, such as allelic misregulation and genome instability, and is rare in human somatic cells. How mitotic recombination is prevented—and how genetic stability is maintained across daughter cells—is a fundamental, unanswered question. Here, we report that both human and mouse cells impede homologous chromosome pairing by keeping two haploid chromosome sets apart throughout mitosis. Four-dimensional analysis of chromosomes during cell division revealed that a haploid chromosome set resides on either side of a meridional plane, crossing two centrosomes. Simultaneous tracking of chromosome oscillation and the spindle axis, using fluorescent CENP-A and centrin1, respectively, demonstrates collective genome behavior/segregation of two haploid sets throughout mitosis. Using 3D chromosome imaging of a translocation mouse with a supernumerary chromosome, we found that this maternally derived chromosome is positioned by parental origin. These data, taken together, support the identity of haploid sets by parental origin. This haploid set-based antipairing motif is shared by multiple cell types, doubles in tetraploid cells, and is lost in a carcinoma cell line. The data support a mechanism of nuclear polarity that sequesters two haploid sets along a subcellular axis. This topological segregation of haploid sets revisits an old model/paradigm and provides implications for maintaining mitotic fidelity.

scholarly journals Generation of asymmetry during development. Segregation of type-specific proteins in Caulobacter.

1979 ◽  
Vol 81 (1) ◽  
pp. 123-136 ◽  
Author(s):  
N Agabian ◽  
M Evinger ◽  
G Parker
Keyword(s):  
Cell Cycle ◽  
Cell Division ◽  
Messenger Rna ◽  
Cell Types ◽  
Specific Protein ◽  
Soluble Proteins ◽  
Specific Cell ◽  
Daughter Cells ◽  
Specific Proteins ◽  
Entire Cell

An essential event in developmental processes is the introduction of asymmetry into an otherwise undifferentiated cell population. Cell division in Caulobacter is asymmetric; the progeny cells are structurally different and follow different sequences of development, thus providing a useful model system for the study of differentiation. Because the progeny cells are different from one another, there must be a segregation of morphogenetic and informational components at some time in the cell cycle. We have examined the pattern of specific protein segregation between Caulobacter stalked and swarmer daughter cells, with the rationale that such a progeny analysis would identify both structurally and developmentally important proteins. To complement the study, we have also examined the pattern of protein synthesis during synchronous growth and in various cellular fractions. We show here, for the first time, that the association of proteins with a specific cell type may result not only from their periodicity of synthesis, but also from their pattern of distribution at the time of cell division. Several membrane-associated and soluble proteins are segregated asymmetrically between progeny stalked and swarmer cells. The data further show that a subclass of soluble proteins becomes associated with the membrane of the progeny stalked cells. Therefore, although the principal differentiated cell types possess different synthetic capabilities and characteristic proteins, the asymmetry between progeny stalked and swarmer cells is generated primarily by the preferential association of specific soluble proteins with the membrane of only one daughter cell. The majority of the proteins which exhibit this segregation behavior are synthesized during the entire cell cycle and exhibit relatively long, functional messenger RNA half-lives.

scholarly journals Integrative Genome-Wide Analysis of Long Noncoding RNAs in Diverse Immune Cell Types of Melanoma Patients

2018 ◽  
Vol 78 (15) ◽  
pp. 4411-4423 ◽  
Author(s):  
Lei Wang ◽  
Sara J. Felts ◽  
Virginia P. Van Keulen ◽  
Adam D. Scheid ◽  
Matthew S. Block ◽  
...  
Keyword(s):  
Immune Cell ◽  
Noncoding Rnas ◽  
Cell Types ◽  
Long Noncoding Rnas ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Melanoma Patients

scholarly journals When Long Noncoding Becomes Protein Coding

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Corrine Corrina R. Hartford ◽  
Ashish Lal
Keyword(s):  
Cell Division ◽  
Cell Signaling ◽  
Transcription Regulation ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Open Reading Frames ◽  
Protein Coding ◽  
Small Proteins ◽  
Coding Potential ◽  
Reading Frames

ABSTRACT Recent advancements in genetic and proteomic technologies have revealed that more of the genome encodes proteins than originally thought possible. Specifically, some putative long noncoding RNAs (lncRNAs) have been misannotated as noncoding. Numerous lncRNAs have been found to contain short open reading frames (sORFs) which have been overlooked because of their small size. Many of these sORFs encode small proteins or micropeptides with fundamental biological importance. These micropeptides can aid in diverse processes, including cell division, transcription regulation, and cell signaling. Here we discuss strategies for establishing the coding potential of putative lncRNAs and describe various functions of known micropeptides.

scholarly journals A pitfall for machine learning methods aiming to predict across cell types

2019 ◽  
Author(s):  
Jacob Schreiber ◽  
Ritambhara Singh ◽  
Jeffrey Bilmes ◽  
William Stafford Noble
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Cell Types ◽  
Chromatin Domain ◽  
Genomic Locus ◽  
Enhancer Activity ◽  
Domain Boundaries ◽  
Multiple Cell ◽  
Average Activity ◽  
Predict Gene Expression

AbstractMachine learning models used to predict phenomena such as gene expression, enhancer activity, transcription factor binding, or chromatin conformation are most useful when they can generalize to make accurate predictions across cell types. In this situation, a natural strategy is to train the model on experimental data from some cell types and evaluate performance on one or more held-out cell types. In this work, we show that when the training set contains examples derived from the same genomic loci across multiple cell types, the resulting model can be susceptible to a particular form of bias related to memorizing the average activity associated with each genomic locus. Consequently, the trained model may appear to perform well when evaluated on the genomic loci that it was trained on but tends to perform poorly on loci that it was not trained on. We demonstrate this phenomenon by using epigenomic measurements and nucleotide sequence to predict gene expression and chromatin domain boundaries, and we suggest methods to diagnose and avoid the pitfall. We anticipate that, as more data and computing resources become available, future projects will increasingly risk suffering from this issue.

scholarly journals Widespread localisation of long noncoding RNAs to ribosomes: Distinguishing features and evidence for regulatory roles.

2015 ◽  
Author(s):  
Juna Carlevaro-Fita ◽  
Anisa Rahim ◽  
Roderic Guigo ◽  
Leah Vardy ◽  
Rory Johnson
Keyword(s):  
Transcriptional Regulation ◽  
Noncoding Rnas ◽  
Cell Types ◽  
Long Noncoding Rnas ◽  
Open Reading Frames ◽  
Translation Machinery ◽  
Evolutionary Selection ◽  
Regulatory Interactions ◽  
Distinguishing Features ◽  
Reading Frames

The function of long noncoding RNAs (lncRNAs) depends on their location within the cell. While most studies to date have concentrated on their nuclear roles in transcriptional regulation, evidence is mounting that lncRNA also have cytoplasmic roles. Here we comprehensively map the cytoplasmic and ribosomal lncRNA population in a human cell. Three-quarters (74%) of lncRNAs are detected in the cytoplasm, the majority of which (62%) preferentially cofractionate with polyribosomes. Ribosomal lncRNA are highly expressed across tissues, under purifying evolutionary selection, and have cytoplasmic-to-nuclear ratios comparable to mRNAs and consistent across cell types. LncRNAs may be classified into three groups by their ribosomal interaction: non-ribosomal cytoplasmic lncRNAs, and those associated with either heavy or light polysomes. A number of mRNA-like features destin lncRNA for light polysomes, including capping and 5′UTR length, but not cryptic open reading frames or polyadenylation. Surprisingly, exonic retroviral sequences antagonise recruitment. In contrast, it appears that lncRNAs are recruited to heavy polysomes through basepairing to mRNAs. Finally, we show that the translation machinery actively degrades lncRNA. We propose that light polysomal lncRNAs are translationally engaged, while heavy polysomal lncRNAs are recruited indirectly. These findings point to extensive and reciprocal regulatory interactions between lncRNA and the translation machinery.

scholarly journals TedSim: temporal d​ynamics sim​ulation of single cell RNA-sequencing data and cell division history

2021 ◽  
Author(s):  
Xinhai Pan ◽  
Hechen Li ◽  
Xiuwei Zhang
Keyword(s):  
Cell Division ◽  
Single Cell ◽  
Genome Editing ◽  
Computational Methods ◽  
Temporal Dynamics ◽  
Cell Types ◽  
Sequencing Data ◽  
Gene Expressions ◽  
Cell Lineages ◽  
Multiple Cell

Recently, the combined scRNA-seq and CRISPR/Cas9 genome editing technologies have enabled simultaneous readouts of gene expressions and lineage barcodes, which allows for the reconstruction of the cell division tree, and makes it possible to trace the origin of each cell type. Computational methods are emerging to take advantage of the jointly profiled scRNA-seq and lineage barcode data to better reconstruct the cell division history or to infer the cell state trajectories. Here, we present TedSim (single cell Temporal dynamics Simulator), a simulator that simulates the cell division events from the root cell to present-day cells, simultaneously generating the CRISPR/Cas9 genome editing lineage barcodes and scRNA-seq data. In particular, TedSim generates cells from multiple cell types through cell division events. TedSim can be used to benchmark and investigate computational methods which use either or both of the two types of data, scRNA-seq and lineage barcodes, to study cell lineages or trajectories. TedSim is available at: https://github.com/Galaxeee/TedSim.

scholarly journals A dynamic control of human telomerase holoenzyme

2019 ◽  
Author(s):  
Mohammed E. Sayed ◽  
Ao Cheng ◽  
Gaya Yadav ◽  
Andrew T. Ludlow ◽  
Jerry W. Shay ◽  
...  
Keyword(s):  
Active Sites ◽  
Genome Stability ◽  
Dynamic Control ◽  
Cell Types ◽  
Telomerase Activity ◽  
Kinetic Properties ◽  
Catalytic Sites ◽  
Multiple Cell ◽  
Human Telomerase ◽  
Linear Chromosomes

ABSTRACTHuman telomerase functions in maintaining genome stability by adding telomeric repeats to the termini of linear chromosomes. Past studies have revealed profound insights into telomerase functions. However, low abundance of functional telomerase and difficulty in quantifying its activity leave partially characterized its thermodynamic and kinetic properties. Using a newly developed method to count individual extension products, we demonstrate that human telomerase holoenzymes contain fast- and slow-acting catalytic sites. Surprisingly, both active sites become inactive after two consecutive rounds of catalysis. The fast active sites turn off ~40-fold quicker than the slow ones and exhibit higher affinity to substrates. In dimeric enzymes, the two sites work in tandem with the faster site functioning before the slower one. In monomeric enzymes, the active sites also perform single-run catalysis. Interestingly, the inactive enzymes can be reactivated by intracellular telomerase-activating factors (iTAFs) available in multiple cell types. Together, the single-run catalysis and the iTAF-triggered reactivation serve as a novel control circuit to ensure that the telomerase holoenzymes are dynamically controlled to match their number of active sites with the number of telomeres they extend. Such exquisite kinetic control of telomerase activity is expected to play important roles in cell division and ageing.

scholarly journals Significance of Long Noncoding RNAs in Regenerative Medicine

2017 ◽  
Vol 3 ◽  
pp. 0
Author(s):  
Raheleh Amirkhah
Keyword(s):  
Next Generation Sequencing ◽  
Noncoding Rnas ◽  
Cell Types ◽  
Long Noncoding Rnas ◽  
Rna Seq ◽  
Huge Data ◽  
Paracrine Action ◽  
Different Cell Types ◽  
Generation Sequencing ◽  
Heterogeneous Class

Long noncoding RNAs (lncRNAs) are a heterogeneous class of RNAs with generally longer than 200 nucleotides. It has been proposed that LncRNAs as a piece of paracrine action would control cellular pluripotency, differentiation, maintenance and regulate tissue development, organogenesis and regeneration. Next generation sequencing (RNA-seq) has produced huge data about lncRNAs expression profile in different cell types and condition, but understanding the roles and functions of these novel lncRNAs is poorly understood.

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