• Molecules and Cells
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• v.42 no.2
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• pp.104-112
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• 2019

Tracking the fate of individual cells and their progeny through lineage tracing has been widely used to investigate various biological processes including embryonic development, homeostatic tissue turnover, and stem cell function in regeneration and disease. Conventional lineage tracing involves the marking of cells either with dyes or nucleoside analogues or genetic marking with fluorescent and/or colorimetric protein reporters. Both are imaging-based approaches that have played a crucial role in the field of developmental biology as well as adult stem cell biology. However, imaging-based lineage tracing approaches are limited by their scalability and the lack of molecular information underlying fate transitions. Recently, computational biology approaches have been combined with diverse tracing methods to overcome these limitations and so provide high-order scalability and a wealth of molecular information. In this review, we will introduce such novel computational methods, starting from single-cell RNA sequencing-based lineage analysis to DNA barcoding or genetic scar analysis. These novel approaches are complementary to conventional imaging-based approaches and enable us to study the lineage relationships of numerous cell types during vertebrate, and in particular human, development and disease.

• BMB Reports
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• v.48 no.12
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• pp.655-667
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• 2015

Lineage tracing is a widely used method for understanding cellular dynamics in multicellular organisms during processes such as development, adult tissue maintenance, injury repair and tumorigenesis. Advances in tracing or tracking methods, from light microscopy-based live cell tracking to fluorescent label-tracing with two-photon microscopy, together with emerging tissue clearing strategies and intravital imaging approaches have enabled scientists to decipher adult stem and progenitor cell properties in various tissues and in a wide variety of biological processes. Although technical advances have enabled time-controlled genetic labeling and simultaneous live imaging, a number of obstacles still need to be overcome. In this review, we aim to provide an in-depth description of the traditional use of lineage tracing as well as current strategies and upcoming new methods of labeling and imaging.

• Molecules and Cells
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• v.27 no.4
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• pp.397-401
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• 2009

Olig2 transcription factor is widely expressed throughout the central nervous system; therefore, it is considered to have multiple functions in the developing, mature and injured brain. In this mini-review, we focus on Olig2 in the forebrain (telencephalon and diencephalon) and discuss the functional significance of Olig2 and the differentiation properties of Olig2-expressing progenitors in the development and injured states. Short- and long-term lineage analysis in the developing forebrain elucidated that not all late Olig2+ cells are direct cohorts of early cells and that Olig2 lineage cells differentiate into neurons or glial cells in a region- and stage-dependent manner. Olig2-deficient mice revealed large elimination of oligodendrocyte precursor cells and a decreased number of astrocyte progenitors in the dorsal cortex, whereas no reduction in the number of GABAergic neurons. In addition to Olig2 function in the developing cortex, Olig2 is also reported to be important for glial scar formation after injury. Thus, Olig2 can be essential for glial differentiation during development and after injury.

• Molecules and Cells
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• v.44 no.3
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• pp.127-135
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• 2021

Since the introduction of RNA sequencing (RNA-seq) as a high-throughput mRNA expression analysis tool, this procedure has been increasingly implemented to identify cell-level transcriptome changes in a myriad of model systems. However, early methods processed cell samples in bulk, and therefore the unique transcriptomic patterns of individual cells would be lost due to data averaging. Nonetheless, the recent and continuous development of new single-cell RNA sequencing (scRNA-seq) toolkits has enabled researchers to compare transcriptomes at a single-cell resolution, thus facilitating the analysis of individual cellular features and a deeper understanding of cellular functions. Nonetheless, the rapid evolution of high throughput single-cell "omics" tools has created the need for effective hypothesis verification strategies. Particularly, this issue could be addressed by coupling cell engineering techniques with single-cell sequencing. This approach has been successfully employed to gain further insights into disease pathogenesis and the dynamics of differentiation trajectories. Therefore, this review will discuss the current status of cell engineering toolkits and their contributions to single-cell and genome-wide data collection and analyses.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.11
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• pp.4769-4775
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• 2015

Background: Hepatocellular carcinoma (HCC) is the fifth most prevalent cancer and thirdly leading cause of cancer-related death worldwide. The estimated risk of hepatocellular carcinoma is 15 to 20 times as high among persons infected with HCV as it is among those who are not infected, with most of the excess risk limited to those with advanced hepatic fibrosis or cirrhosis. Glypican3 (GPC3) plays a key role in relation to signaling with growth factors, regulating the proliferative activity of cancer cells. Glutamine synthetase (GS) catalyzes the synthesis of glutamine from glutamate and ammonia in the mammalian liver. GS was suggested as a specific marker for tracing cell lineage relationships during hepatocarcinogenesis. In normal liver, GS expression is seen in pericentral hepatocytes, but not by midzonal or periportal hepatocytes. In HCC, strong and diffuse GS expression in seen in tumor cells. Results: Glypican3 immunopositvity was highly specific and sensitive indicator for hepatocellular carcinoma as well as glutamine synthetase which was found to be a sensitive and specific indicator for development of hepatocellular carcinoma when compared to cirrhosis, liver cell dyspalsia and metastatic carcinomas. Statistical analysis revealed a significant association between GPC3 and GS with tumor size (P=0.003, p=0.006, respectively). Diffuse staining significantly associated with large tumor size while, focal and mixed staining was detected more with small tumor size. Studying the relation with tumor grade also revealed significant association between diffuse GPC3 and GS staining with high tumor grade. Diffuse staining was detected in 91.7% and 100% respectively of poorly differentiated specimens and only in 33.3% and 22.2% of well differentiated specimens. Conclusions: While using GPC3 and GS to screen for premalignant hepatic lesions remains controversial, our data suggest that GPC3 and GS may be a reliable diagnostic immunomarkers to distinguish HCC from benign hepatocellular lesions. However, negative immunostaining should not exclude the diagnosis of HCC.