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Cell Cycle and Cell...
Cell Cycle and Cell Size Dependent Gene Expression Reveals Distinct Subpopulations at Single-Cell Level
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- Dolatabadi, Soheila (author)
- Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för patologi,Sahlgrenska Cancer Center,Institute of Biomedicine, Department of Pathology
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Candia, J. (author)
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- Akrap, Nina (author)
- Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för patologi,Sahlgrenska Cancer Center,Institute of Biomedicine, Department of Pathology
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- Vannas, Christoffer (author)
- Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för patologi,Sahlgrenska Cancer Center,Institute of Biomedicine, Department of Pathology
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- Tomic, Tajana Tesan (author)
- Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för patologi,Sahlgrenska Cancer Center,Institute of Biomedicine, Department of Pathology
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Losert, W. (author)
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- Landberg, Göran, 1963 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för patologi,Sahlgrenska Cancer Center,Institute of Biomedicine, Department of Pathology
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- Åman, Pierre, 1953 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för patologi,Sahlgrenska Cancer Center,Institute of Biomedicine, Department of Pathology
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- Ståhlberg, Anders, 1975 (author)
- Gothenburg University,Göteborgs universitet,Sahlgrenska Cancer Center,Institutionen för biomedicin, avdelningen för patologi,Institute of Biomedicine, Department of Pathology
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(creator_code:org_t)
- 2017-01-25
- 2017
- English.
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In: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 8
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Abstract
Subject headings
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- Cell proliferation includes a series of events that is tightly regulated by several checkpoints and layers of control mechanisms. Most studies have been performed on large cell populations, but detailed understanding of cell dynamics and heterogeneity requires single-cell analysis. Here, we used quantitative real-time PCR, profiling the expression of 93 genes in single-cells from three different cell lines. Individual unsynchronized cells from three different cell lines were collected in different cell cycle phases (GO/G1 - S - G2/M) with variable cell sizes. We found that the total transcript level per cell and the expression of most individual genes correlated with progression through the cell cycle, but not with cell size. By applying the random forests algorithm, a supervised machine learning approach, we show how a multi-gene signature that classifies individual cells into their correct cell cycle phase and cell size can be generated. To identify the most predictive genes we used a variable selection strategy. Detailed analysis of cell cycle predictive genes allowed us to define subpopulations with distinct gene expression profiles and to calculate a cell cycle index that illustrates the transition of cells between cell cycle phases. In conclusion, we provide useful experimental approaches and bioinformatics to identify informative and predictive genes at the single-cell level, which opens up new means to describe and understand cell proliferation and subpopulation dynamics.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinsk bioteknologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Medical Biotechnology (hsv//eng)
Keyword
- cell cycle
- cell size
- single-cell gene expression
- machine learning
- variable selection
- random forests
- cell subpopulations
- cell transitions
- mammalian-cells
- transcription
- breast
- roles
- dna
- Genetics & Heredity
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Dolatabadi, Sohe ...
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Candia, J.
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Akrap, Nina
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Vannas, Christof ...
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Tomic, Tajana Te ...
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Losert, W.
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show more...
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Landberg, Göran, ...
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Åman, Pierre, 19 ...
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Ståhlberg, Ander ...
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- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Medical Biotechn ...
- Articles in the publication
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Frontiers in Gen ...
- By the university
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University of Gothenburg