The cell-cycle transcriptional network generates and transmits a pulse of transcription once each cell cycle

Cho, Chun-Yi; Kelliher, Christina M.; Haase, Steven B.

doi:10.1080/15384101.2019.1570655

Cited by 19 publications

(21 citation statements)

References 72 publications

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“…The regulatory network in Figure 3 is a simplified version of the wavepool model, introduced in [22]. This model has been corroborated experimentally [31,32,33] and describes the mechanism for controlling the cell-cycle transcriptional program.…”

Section: Cell Cycle Data Modelmentioning

confidence: 82%

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Using extremal events to characterize noisy time series

Berry¹,

Cummins²,

Nerem³

et al. 2020

J. Math. Biol.

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Experimental time series provide an informative window into the underlying dynamical system, and the timing of the extrema of a time series (or its derivative) contains information about its structure. However, the time series often contain significant measurement errors. We describe a method for characterizing a time series for any assumed level of measurement error ε by a sequence of intervals, each of which is guaranteed to contain an extremum for any function that ε-approximates the time series. Based on the merge tree of a continuous function, we define a new object called the normalized branch decomposition, which allows us to compute intervals for any level ε.We show that there is a well-defined total order on these intervals for a single time series, and that it is naturally extended to a partial order across a collection of time series comprising a dataset. We use the order of the extracted intervals in two applications. First, the partial order describing a single dataset can be used to pattern match against switching model output [1], which allows the rejection of a network model. Second, the comparison between graph distances of the partial orders of different datasets can be used to quantify similarity between biological replicates.

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Section: Cell Cycle Data Modelmentioning

confidence: 82%

“…This data can be then compared to a partial order computed from the experimental time series data, at different levels of assumed experimental measurement uncertainty ε. We illustrate our approach on data from the yeast cell cycle, where the regulatory network is welldescribed and has substantial experimental validation [22,40,28,41,31,42].…”

Section: Discussionmentioning

confidence: 99%

Using extremal events to characterize noisy time series

Berry¹,

Cummins²,

Nerem³

et al. 2020

J. Math. Biol.

Self Cite

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“…7 ). YOX1 , a TF expressed in mid-G1 through early S phage, interplays with S-specific TF— YHP1 , function as transcriptional repressor to negatively regulate MCM1 - FKH2 - NDD1 -mediated G2/M-G1 transition during cell cycle progression 95 . Recently, a research has reported that ROX1 is in promotion of RAP1 - HAP1 - MSN4 module, which is an important branch for G2/M to G1 phase transition in yeast 96 .…”

Section: Resultsmentioning

confidence: 99%

Accessible chromatin reveals regulatory mechanisms underlying cell fate decisions during early embryogenesis

Fan

Huang

2021

Sci Rep

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This study was conducted to investigate epigenetic landscape across multiple species and identify transcription factors (TFs) and their roles in controlling cell fate decision events during early embryogenesis. We made a comprehensively joint-research of chromatin accessibility of five species during embryogenesis by integration of ATAC-seq and RNA-seq datasets. Regulatory roles of candidate early embryonic TFs were investigated. Widespread accessible chromatin in early embryos overlapped with putative cis-regulatory sequences. Sets of cell-fate-determining TFs were identified. YOX1, a key cell cycle regulator, were found to homologous to clusters of TFs that are involved in neuron and epidermal cell-fate determination. Our research provides an intriguing insight into evolution of cell-fate decision during early embryogenesis among organisms.

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“…Another study in budding yeast has provocatively demonstrated that, although a large portion of the genome is transcribed cyclically during the cell division cycle, a significant fraction (~70%) of these genes can continue to express periodically even in the absence of a robust cell cycle progression ( Orlando et al, 2008 ). This striking finding has rightly inspired a number of more recent work ( Cho et al, 2019 ; Cho et al, 2017 ; Rahi et al, 2016 ) to validate these findings, and although there does not seem to be a strict consensus, it is somehow clear that the periodic transcription in arrested cells may not be as global as it was originally postulated. Importantly, however, there appear to be some genes that can display periodic expression in the absence of a robust cell cycle oscillator.…”

Section: Molecular Determinants and Roles Of Autonomous Clocksmentioning

confidence: 90%

Autonomous clocks that regulate organelle biogenesis, cytoskeletal organization, and intracellular dynamics

Mofatteh

Iturra

Alamban

et al. 2021

eLife

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How do cells perceive time? Do cells use temporal information to regulate the production/degradation of their enzymes, membranes, and organelles? Does controlling biological time influence cytoskeletal organization and cellular architecture in ways that confer evolutionary and physiological advantages? Potential answers to these fundamental questions of cell biology have historically revolved around the discussion of ‘master’ temporal programs, such as the principal cyclin-dependent kinase/cyclin cell division oscillator and the circadian clock. In this review, we provide an overview of the recent evidence supporting an emerging concept of ‘autonomous clocks,’ which under normal conditions can be entrained by the cell cycle and/or the circadian clock to run at their pace, but can also run independently to serve their functions if/when these major temporal programs are halted/abrupted. We begin the discussion by introducing recent developments in the study of such clocks and their roles at different scales and complexities. We then use current advances to elucidate the logic and molecular architecture of temporal networks that comprise autonomous clocks, providing important clues as to how these clocks may have evolved to run independently and, sometimes at the cost of redundancy, have strongly coupled to run under the full command of the cell cycle and/or the circadian clock. Next, we review a list of important recent findings that have shed new light onto potential hallmarks of autonomous clocks, suggestive of prospective theoretical and experimental approaches to further accelerate their discovery. Finally, we discuss their roles in health and disease, as well as possible therapeutic opportunities that targeting the autonomous clocks may offer.

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The cell-cycle transcriptional network generates and transmits a pulse of transcription once each cell cycle

Cited by 19 publications

References 72 publications

Using extremal events to characterize noisy time series

Using extremal events to characterize noisy time series

Accessible chromatin reveals regulatory mechanisms underlying cell fate decisions during early embryogenesis

Autonomous clocks that regulate organelle biogenesis, cytoskeletal organization, and intracellular dynamics

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