keyword
MENU ▼
Read by QxMD icon Read
search

Cell lineage tree

keyword
https://www.readbyqxmd.com/read/28584083/gene-regulatory-networks-and-cell-lineages-that-underlie-the-formation-of-skeletal-muscle
#1
Margaret Buckingham
Skeletal muscle in vertebrates is formed by two major routes, as illustrated by the mouse embryo. Somites give rise to myogenic progenitors that form all of the muscles of the trunk and limbs. The behavior of these cells and their entry into the myogenic program is controlled by gene regulatory networks, where paired box gene 3 (Pax3) plays a predominant role. Head and some neck muscles do not derive from somites, but mainly form from mesoderm in the pharyngeal region. Entry into the myogenic program also depends on the myogenic determination factor (MyoD) family of genes, but Pax3 is not expressed in these myogenic progenitors, where different gene regulatory networks function, with T-box factor 1 (Tbx1) and paired-like homeodomain factor 2 (Pitx2) as key upstream genes...
June 6, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28582478/model-based-branching-point-detection-in-single-cell-data-by-k-branches-clustering
#2
Nikolaos K Chlis, F Alexander Wolf, Fabian J Theis
Motivation: The identification of heterogeneities in cell populations by utilizing single-cell technologies such as single-cell RNA-Seq, enables inference of cellular development and lineage trees. Several methods have been proposed for such inference from high-dimensional single-cell data. They typically assign each cell to a branch in a differentiation trajectory. However, they commonly assume specific geometries such as tree-like developmental hierarchies and lack statistically sound methods to decide on the number of branching events...
June 5, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28564607/specification-and-diversification-of-pericytes-and-smooth-muscle-cells-from-mesenchymoangioblasts
#3
Akhilesh Kumar, Saritha Sandra D'Souza, Oleg V Moskvin, Huishi Toh, Bowen Wang, Jue Zhang, Scott Swanson, Lian-Wang Guo, James A Thomson, Igor I Slukvin
Elucidating the pathways that lead to vasculogenic cells, and being able to identify their progenitors and lineage-restricted cells, is critical to the establishment of human pluripotent stem cell (hPSC) models for vascular diseases and development of vascular therapies. Here, we find that mesoderm-derived pericytes (PCs) and smooth muscle cells (SMCs) originate from a clonal mesenchymal progenitor mesenchymoangioblast (MB). In clonogenic cultures, MBs differentiate into primitive PDGFRβ(+)CD271(+)CD73(-) mesenchymal progenitors, which give rise to proliferative PCs, SMCs, and mesenchymal stem/stromal cells...
May 30, 2017: Cell Reports
https://www.readbyqxmd.com/read/28533395/integrative-modeling-of-gene-and-genome-evolution-roots-the-archaeal-tree-of-life
#4
Tom A Williams, Gergely J Szöllősi, Anja Spang, Peter G Foster, Sarah E Heaps, Bastien Boussau, Thijs J G Ettema, T Martin Embley
A root for the archaeal tree is essential for reconstructing the metabolism and ecology of early cells and for testing hypotheses that propose that the eukaryotic nuclear lineage originated from within the Archaea; however, published studies based on outgroup rooting disagree regarding the position of the archaeal root. Here we constructed a consensus unrooted archaeal topology using protein concatenation and a multigene supertree method based on 3,242 single gene trees, and then rooted this tree using a recently developed model of genome evolution...
June 6, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28533331/chronic-stimulation-of-renin-cells-leads-to-vascular-pathology
#5
Masafumi Oka, Silvia Medrano, Maria Luisa S Sequeira-Lόpez, R Ariel Gómez
Experimental or spontaneous genomic mutations of the renin-angiotensin system or its pharmacological inhibition in early life leads to renal abnormalities, including poorly developed renal medulla, papillary atrophy, hydronephrosis, inability to concentrate the urine, polyuria, polydipsia, renal failure, and anemia. At the core of such complex phenotype is the presence of unique vascular abnormalities: the renal arterioles do not branch or elongate properly and they have disorganized, concentric hypertrophy...
May 22, 2017: Hypertension
https://www.readbyqxmd.com/read/28528574/esc-track-a-computer-workflow-for-4-d-segmentation-tracking-lineage-tracing-and-dynamic-context-analysis-of-escs
#6
Laura Fernández-de-Manúel, Covadonga Díaz-Díaz, Daniel Jiménez-Carretero, Miguel Torres, María C Montoya
Embryonic stem cells (ESCs) can be established as permanent cell lines, and their potential to differentiate into adult tissues has led to widespread use for studying the mechanisms and dynamics of stem cell differentiation and exploring strategies for tissue repair. Imaging live ESCs during development is now feasible due to advances in optical imaging and engineering of genetically encoded fluorescent reporters; however, a major limitation is the low spatio-temporal resolution of long-term 3-D imaging required for generational and neighboring reconstructions...
May 1, 2017: BioTechniques
https://www.readbyqxmd.com/read/28508298/stability-of-control-networks-in-autonomous-homeostatic-regulation-of-stem-cell-lineages
#7
Natalia L Komarova, P van den Driessche
Design principles of biological networks have been studied extensively in the context of protein-protein interaction networks, metabolic networks, and regulatory (transcriptional) networks. Here we consider regulation networks that occur on larger scales, namely the cell-to-cell signaling networks that connect groups of cells in multicellular organisms. These are the feedback loops that orchestrate the complex dynamics of cell fate decisions and are necessary for the maintenance of homeostasis in stem cell lineages...
May 15, 2017: Bulletin of Mathematical Biology
https://www.readbyqxmd.com/read/28446158/parameter-inference-for-stochastic-single-cell-dynamics-from-lineage-tree-data
#8
Irena Kuzmanovska, Andreas Milias-Argeitis, Jan Mikelson, Christoph Zechner, Mustafa Khammash
BACKGROUND: With the advance of experimental techniques such as time-lapse fluorescence microscopy, the availability of single-cell trajectory data has vastly increased, and so has the demand for computational methods suitable for parameter inference with this type of data. Most of currently available methods treat single-cell trajectories independently, ignoring the mother-daughter relationships and the information provided by the population structure. However, this information is essential if a process of interest happens at cell division, or if it evolves slowly compared to the duration of the cell cycle...
April 26, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28424352/chromatin-module-inference-on-cellular-trajectories-identifies-key-transition-points-and-poised-epigenetic-states-in-diverse-developmental-processes
#9
Sushmita Roy, Rupa Sridharan
Changes in chromatin state play important roles in cell fate transitions. Current computational approaches to analyze chromatin modifications across multiple cell types do not model how the cell types are related on a lineage or over time. To overcome this limitation, we have developed a method called CMINT (Chromatin Module INference on Trees), a probabilistic clustering approach to systematically capture chromatin state dynamics across multiple cell types. Compared to existing approaches, CMINT can handle complex lineage topologies, capture higher quality clusters, and reliably detect chromatin transitions between cell types...
April 19, 2017: Genome Research
https://www.readbyqxmd.com/read/28399402/hematopoiesis-lineage-tree-uprooted-every-cell-is-a-rainbow
#10
Karen K Hirschi, Stefania Nicoli, Kenneth Walsh
Differentiation of hematopoietic stem cells into distinct cell types was thought to occur through a series of discrete, stable progenitor states. Work from Velten et al. (2017) now shows that hematopoietic cells differentiate via a mechanism of continuous lineage priming and thus represent a CLOUD-HSPC.
April 10, 2017: Developmental Cell
https://www.readbyqxmd.com/read/28376782/image-analysis-driven-single-cell-analytics-for-systems-microbiology
#11
Athanasios D Balomenos, Panagiotis Tsakanikas, Zafiro Aspridou, Anastasia P Tampakaki, Konstantinos P Koutsoumanis, Elias S Manolakos
BACKGROUND: Time-lapse microscopy is an essential tool for capturing and correlating bacterial morphology and gene expression dynamics at single-cell resolution. However state-of-the-art computational methods are limited in terms of the complexity of cell movies that they can analyze and lack of automation. The proposed Bacterial image analysis driven Single Cell Analytics (BaSCA) computational pipeline addresses these limitations thus enabling high throughput systems microbiology. RESULTS: BaSCA can segment and track multiple bacterial colonies and single-cells, as they grow and divide over time (cell segmentation and lineage tree construction) to give rise to dense communities with thousands of interacting cells in the field of view...
April 4, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28319093/human-haematopoietic-stem-cell-lineage-commitment-is-a-continuous-process
#12
Lars Velten, Simon F Haas, Simon Raffel, Sandra Blaszkiewicz, Saiful Islam, Bianca P Hennig, Christoph Hirche, Christoph Lutz, Eike C Buss, Daniel Nowak, Tobias Boch, Wolf-Karsten Hofmann, Anthony D Ho, Wolfgang Huber, Andreas Trumpp, Marieke A G Essers, Lars M Steinmetz
Blood formation is believed to occur through stepwise progression of haematopoietic stem cells (HSCs) following a tree-like hierarchy of oligo-, bi- and unipotent progenitors. However, this model is based on the analysis of predefined flow-sorted cell populations. Here we integrated flow cytometric, transcriptomic and functional data at single-cell resolution to quantitatively map early differentiation of human HSCs towards lineage commitment. During homeostasis, individual HSCs gradually acquire lineage biases along multiple directions without passing through discrete hierarchically organized progenitor populations...
April 2017: Nature Cell Biology
https://www.readbyqxmd.com/read/28304126/transcript-profiling-of-a-novel-plant-meristem-the-monocot-cambium
#13
Matthew Zinkgraf, Suzanne Gerttula, Andrew Groover
While monocots lack the ability to produce a vascular cambium or woody growth, some monocot lineages evolved a novel lateral meristem, the monocot cambium, which supports secondary radial growth of stems. In contrast to the vascular cambium found in woody angiosperm and gymnosperm species, the monocot cambium produces secondary vascular bundles, which have an amphivasal organization of tracheids encircling a central strand of phloem. Currently there is no information concerning the molecular genetic basis of the development or evolution of the monocot cambium...
March 17, 2017: Journal of Integrative Plant Biology
https://www.readbyqxmd.com/read/28296636/discovering-sparse-transcription-factor-codes-for-cell-states-and-state-transitions-during-development
#14
Leon A Furchtgott, Samuel Melton, Vilas Menon, Sharad Ramanathan
Computational analysis of gene expression to determine both the sequence of lineage choices made by multipotent cells and to identify the genes influencing these decisions is challenging. Here we discover a pattern in the expression levels of a sparse subset of genes among cell types in B- and T-cell developmental lineages that correlates with developmental topologies. We develop a statistical framework using this pattern to simultaneously infer lineage transitions and the genes that determine these relationships...
March 15, 2017: ELife
https://www.readbyqxmd.com/read/28294138/machine-learning-applications-in-cell-image-analysis
#15
REVIEW
Andrey Kan
Machine learning refers to a set of automatic pattern recognition methods that have been successfully applied across various problem domains, including biomedical image analysis. This review focuses on machine learning applications for image analysis in light microscopy experiments with typical tasks of segmenting and tracking individual cells, and modelling of reconstructed lineage trees. After describing a typical image analysis pipeline and highlighting challenges of automatic analysis (e.g., variability in cell morphology, tracking in presence of clutters) this review gives a brief historical outlook of machine learning, followed by basic concepts and definitions required for understanding examples...
March 15, 2017: Immunology and Cell Biology
https://www.readbyqxmd.com/read/28267748/inferring-fitness-landscapes-and-selection-on-phenotypic-states-from-single-cell-genealogical-data
#16
Takashi Nozoe, Edo Kussell, Yuichi Wakamoto
Recent advances in single-cell time-lapse microscopy have revealed non-genetic heterogeneity and temporal fluctuations of cellular phenotypes. While different phenotypic traits such as abundance of growth-related proteins in single cells may have differential effects on the reproductive success of cells, rigorous experimental quantification of this process has remained elusive due to the complexity of single cell physiology within the context of a proliferating population. We introduce and apply a practical empirical method to quantify the fitness landscapes of arbitrary phenotypic traits, using genealogical data in the form of population lineage trees which can include phenotypic data of various kinds...
March 2017: PLoS Genetics
https://www.readbyqxmd.com/read/28264564/quantitative-analysis-of-synthetic-cell-lineage-tracing-using-nuclease-barcoding
#17
Stephanie Tzouanas Schmidt, Stephanie M Zimmerman, Jianbin Wang, Stuart K Kim, Stephen R Quake
Lineage tracing by the determination and mapping of progeny arising from single cells is an important approach enabling the elucidation of mechanisms underlying diverse biological processes ranging from development to disease. We developed a dynamic sequence-based barcode system for synthetic lineage tracing and have demonstrated its performance in C. elegans, a model organism whose lineage tree is well established. The strategy we use creates lineage trees based upon the introduction of synthetically controlled mutations into cells and the propagation of these mutations to daughter cells at each cell division...
March 10, 2017: ACS Synthetic Biology
https://www.readbyqxmd.com/read/28231507/the-phytochelatin-synthase-gene-in-date-palm-phoenix-dactylifera-l-phylogeny-evolution-and-expression
#18
Chaâbene Zayneb, Rekik Hakim Imen, Kriaa Walid, C Douglas Grubb, Khemakhem Bassem, Vandenbulcke Franck, Mejdoub Hafedh, Elleuch Amine
We studied date palm phytochelatin synthase type I (PdPCS1), which catalyzes the cytosolic synthesis of phytochelatins (PCs), a heavy metal binding protein, in plant cells. The gene encoding PdPCS1 (Pdpcs) consists of 8 exons and 7 introns and encodes a protein of 528 amino acids. PCs gene history was studied using Notung phylogeny. During evolution, gene loss from several lineages was predicted including Proteobacteria, Bilateria and Brassicaceae. In addition, eleven gene duplication events appeared toward interior nodes of the reconciled tree and four gene duplication events appeared toward the external nodes...
June 2017: Ecotoxicology and Environmental Safety
https://www.readbyqxmd.com/read/28222255/stemness-signature-of-equine-marrow-derived-mesenchymal-stem-cells
#19
Morteza Zahedi, Abbas Parham, Hesam Dehghani, Hossein Kazemi Mehrjerdi
Background: Application of competent cells such as mesenchymal stem cells (MSCs) for treatment of musculoskeletal disorders in equine athletes is increasingly needed. Moreover, similarities of horse and human in size, load and types of joint injuries, make horse as a good model for MSCs therapy studies. This study was designed to isolate and characterize stemness signature of equine bone marrow-derived mesenchymal stem cells (BM-MSCs). Methods: BM of three mares was aspirated and the mononuclear cells (MNCs) were isolated using density gradient...
May 30, 2017: International Journal of Stem Cells
https://www.readbyqxmd.com/read/28207402/reconstructing-the-temporal-progression-of-biological-data-using-cluster-spanning-trees
#20
Ryan Eshleman, Rahul Singh
Identifying the temporal progression of a set of biological samples is crucial for comprehending the dynamics of the underlying molecular interactions. It is often also a basic step in data denoising and synchronization. Finally, identifying the progression order is crucial for problems like cell lineage identification, disease progression, tumor classification, and epidemiology and thus impacts the spectrum of disciplines spanning basic biology, drug discovery, and public health. Current methods that attempt solving this problem, face difficulty when it is necessary to factor-in complex relationships within the data, such as grouping, partial ordering or bifurcating or multifurcating progressions...
March 2017: IEEE Transactions on Nanobioscience
keyword
keyword
37160
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"