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1. Nonmodular oscillator and switch based on RNA decay drive regeneration of multimodal gene expression

   https://doi.org/10.1093/nar/gkac217  

   Nordick, Benjamin; Yu, Polly Y; Liao, Guangyuan; Hong, Tian (April 2022, Nucleic Acids Research)

   Abstract Periodic gene expression dynamics are key to cell and organism physiology. Studies of oscillatory expression have focused on networks with intuitive regulatory negative feedback loops, leaving unknown whether other common biochemical reactions can produce oscillations. Oscillation and noise have been proposed to support mammalian progenitor cells’ capacity to restore heterogenous, multimodal expression from extreme subpopulations, but underlying networks and specific roles of noise remained elusive. We use mass-action-based models to show that regulated RNA degradation involving as few as two RNA species—applicable to nearly half of human protein-coding genes—can generate sustained oscillations without explicit feedback. Diverging oscillation periods synergize with noise to robustly restore cell populations’ bimodal expression on timescales of days. The global bifurcation organizing this divergence relies on an oscillator and bistable switch which cannot be decomposed into two structural modules. Our work reveals surprisingly rich dynamics of post-transcriptional reactions and a potentially widespread mechanism underlying development, tissue regeneration, and cancer cell heterogeneity. 

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2. TedSim: temporal dynamics simulation of single-cell RNA sequencing data and cell division history

   https://doi.org/10.1093/nar/gkac235  

   Pan, Xinhai; Li, Hechen; Zhang, Xiuwei (April 2022, Nucleic Acids Research)

   Abstract Recently, lineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes, which allows for the reconstruction of the cell division tree and makes it possible to reconstruct ancestral cell types and trace the origin of each cell type. Meanwhile, trajectory inference methods are widely used to infer cell trajectories and pseudotime in a dynamic process using gene expression data of present-day cells. Here, we present TedSim (single-cell temporal dynamics simulator), which simulates the cell division events from the root cell to present-day cells, simultaneously generating two data modalities for each single cell: the lineage barcode and gene expression data. TedSim is a framework that connects the two problems: lineage tracing and trajectory inference. Using TedSim, we conducted analysis to show that (i) TedSim generates realistic gene expression and barcode data, as well as realistic relationships between these two data modalities; (ii) trajectory inference methods can recover the underlying cell state transition mechanism with balanced cell type compositions; and (iii) integrating gene expression and barcode data can provide more insights into the temporal dynamics in cell differentiation compared to using only one type of data, but better integration methods need to be developed. 

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3. High-Frequency Dielectrophoresis Reveals That Distinct Bio-Electric Signatures of Colorectal Cancer Cells Depend on Ploidy and Nuclear Volume

   https://doi.org/10.3390/mi14091723  

   Duncan, Josie L.; Bloomfield, Mathew; Swami, Nathan; Cimini, Daniela; Davalos, Rafael V. (September 2023, Micromachines)

   Aneuploidy, or an incorrect chromosome number, is ubiquitous among cancers. Whole-genome duplication, resulting in tetraploidy, often occurs during the evolution of aneuploid tumors. Cancers that evolve through a tetraploid intermediate tend to be highly aneuploid and are associated with poor patient prognosis. The identification and enrichment of tetraploid cells from mixed populations is necessary to understand the role these cells play in cancer progression. Dielectrophoresis (DEP), a label-free electrokinetic technique, can distinguish cells based on their intracellular properties when stimulated above 10 MHz, but DEP has not been shown to distinguish tetraploid and/or aneuploid cancer cells from mixed tumor cell populations. Here, we used high-frequency DEP to distinguish cell subpopulations that differ in ploidy and nuclear size under flow conditions. We used impedance analysis to quantify the level of voltage decay at high frequencies and its impact on the DEP force acting on the cell. High-frequency DEP distinguished diploid cells from tetraploid clones due to their size and intracellular composition at frequencies above 40 MHz. Our findings demonstrate that high-frequency DEP can be a useful tool for identifying and distinguishing subpopulations with nuclear differences to determine their roles in disease progression. 

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4. Multiple Lineages of Transmissible Neoplasia in the Basket Cockle ( C. nuttallii ) With Repeated Horizontal Transfer of Mitochondrial DNA

   https://doi.org/10.1111/mec.17682  

   Yonemitsu, Marisa_A; Sevigny, Jordana_K; Vandepas, Lauren_E; Dimond, James_L; Giersch, Rachael_M; Gurney‐Smith, Helen_J; Abbott, Cathryn_L; Supernault, Janine; Withler, Ruth; Smith, Peter_D; et al (February 2025, Molecular Ecology)

   ABSTRACT Transmissible cancers are clonal lineages of neoplastic cells able to infect multiple hosts, spreading through populations in the environment as an infectious disease. Transmissible cancers have been identified in Tasmanian devils, dogs, and bivalves. Several lineages of bivalve transmissible neoplasias (BTN) have been identified in multiple bivalve species. In 2019 in Puget Sound, Washington, USA, disseminated neoplasia was observed in basket cockles (Clinocardium nuttallii), a species that is important to the culture and diet of the Suquamish Tribe as well as other tribes with traditional access to the species. To test whether disseminated neoplasia in cockles is a previously unknown lineage of BTN, a nuclear locus was amplified from cockles from Agate Pass, Washington, and sequences revealed evidence of transmissible cancer in several individuals. We used a combination of cytology and quantitative PCR to screen collections of cockles from 11 locations in Puget Sound and along the Washington coastline to identify the extent of contagious cancer spread in this species. Two BTN lineages were identified in these cockles, with one of those lineages (CnuBTN1) being the most prevalent and geographically widespread. Within the CnuBTN1 lineage, multiple nuclear loci support the conclusion that all cancer samples form a single clonal lineage. However, the mitochondrial alleles in each cockle with CnuBTN1 are different from each other, suggesting mitochondrial genomes of this cancer have been replaced multiple times during its evolution, through horizontal transmission. The identification and analysis of these BTNs are critical for broodstock selection, management practices, and repopulation of declining cockle populations, which will enable continued cultural connection and dietary use of the cockles by Coast Salish Tribes. 

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5. LinRace: cell division history reconstruction of single cells using paired lineage barcode and gene expression data

   https://doi.org/10.1038/s41467-023-44173-3  

   Pan, Xinhai; Li, Hechen; Putta, Pranav; Zhang, Xiuwei (December 2023, Nature Communications)

   Abstract Lineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes in single cells, which allows for inference of cell lineage and cell types at the whole organism level. While most state-of-the-art methods for lineage reconstruction utilize only the lineage barcode data, methods that incorporate gene expressions are emerging. Effectively incorporating the gene expression data requires a reasonable model of how gene expression data changes along generations of divisions. Here, we present LinRace (Lineage Reconstruction with asymmetric cell division model), which integrates lineage barcode and gene expression data using asymmetric cell division model and infers cell lineages and ancestral cell states using Neighbor-Joining and maximum-likelihood heuristics. On both simulated and real data, LinRace outputs more accurate cell division trees than existing methods. With inferred ancestral states, LinRace can also show how a progenitor cell generates a large population of cells with various functionalities. 

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