Determining cell division symmetry through the dissection of dividing cells using single-cell expression analysis

2014 ◽  
Vol 9 (3) ◽  
pp. 505-516 ◽  
Author(s):  
Lukasz Jasnos ◽  
Tomoyuki Sawado
Keyword(s):  
Cell Division ◽  
Single Cell ◽  
Expression Analysis ◽  
Dividing Cells ◽  
Cell Expression

On-Chip Cell Sorter for Single Cell Expression Analysis

2001 ◽  
pp. 271-273 ◽  
Author(s):  
T. Ichiki ◽  
T. Ujiie ◽  
T. Hara ◽  
Y. Horiike ◽  
K. Yasuda
Keyword(s):  
Single Cell ◽  
Expression Analysis ◽  
Cell Sorter ◽  
On Chip ◽  
Cell Expression

scholarly journals Single cell expression analysis reveals anatomical and cell cycle-dependent transcriptional shifts during heart development

Development ◽  
2019 ◽  
Vol 146 (12) ◽  
pp. dev173476 ◽  
Author(s):  
Guang Li ◽  
Lei Tian ◽  
William Goodyer ◽  
Eric J. Kort ◽  
Jan W. Buikema ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Expression Analysis ◽  
Heart Development ◽  
Cycle Dependent ◽  
Cell Expression

scholarly journals Single-cell expression analysis of BMP15 and GDF9 in mature oocytes and BMPR2 in cumulus cells of women with polycystic ovary syndrome undergoing controlled ovarian hyperstimulation

2012 ◽  
Vol 29 (10) ◽  
pp. 1057-1065 ◽  
Author(s):  
Luciana Ochuiuto Teixeira de Resende ◽  
Alessandra Aparecida Vireque ◽  
Laura Ferreira Santana ◽  
Daniel Antunes Moreno ◽  
Ana Carolina Japur de Sá Rosa e Silva ◽  
...  
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Single Cell ◽  
Expression Analysis ◽  
Polycystic Ovary ◽  
Cumulus Cells ◽  
Controlled Ovarian Hyperstimulation ◽  
Ovarian Hyperstimulation ◽  
Ovary Syndrome ◽  
Cell Expression

Single cell expression analysis – pharmacogenomic potential

2002 ◽  
Vol 3 (6) ◽  
pp. 809-822 ◽  
Author(s):  
AK Dixon ◽  
K Lee ◽  
PJ Richardson ◽  
MI Bell ◽  
MJ Skynner
Keyword(s):  
Single Cell ◽  
Expression Analysis ◽  
Cell Expression

scholarly journals Uncovering Transcriptional Dark Matter via Gene Annotation Independent Single-Cell RNA Sequencing Analysis

2020 ◽  
Author(s):  
Michael F.Z. Wang ◽  
Madhav Mantri ◽  
Shao-Pei Chou ◽  
Gaetano J. Scuderi ◽  
David McKellar ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Expression Analysis ◽  
Cell Biology ◽  
Gene Annotation ◽  
Active Regions ◽  
Sequencing Analysis ◽  
Stage Of Development ◽  
Single Cell Rna Sequencing ◽  
Cell Expression

ABSTRACTSingle-cell RNA sequencing (scRNA-seq) enables the study of cell biology with high resolution. scRNA-seq expression analyses rely on the availability of a high quality annotation of genes in the genome. Yet, as we show here with scRNA-seq experiments and analyses spanning human, mouse, chicken, mole rat, lemur and sea urchin, gene annotations often fail to cover the full transcriptome of every cell type at every stage of development, in particular for organisms that are not routinely studied. To overcome this hurdle, we created a scRNA-seq analysis routine that recovers biologically relevant information beyond the scope of the best available gene annotation. This is achieved by performing single-cell expression analysis on any region in the genome for which transcriptional products are detected. Our routine identifies transcriptionally active regions (TARs) using a hidden Markov model, generates a matrix of expression levels for all TARs across all cells in a dataset, performs single-cell TAR expression analysis to identify TARs that are biologically significant, and then annotates biologically significant TARs using gene homology analysis. This procedure leverages single-cell expression analyses as a filter to direct annotation efforts to biologically significant transcripts in complex tissues and thereby uncovers biology to which scRNA-seq would otherwise be in the dark.

scholarly journals Single cell expression analysis of primate-specific retroviruses-derived HPAT lincRNAs in viable human blastocysts identifies embryonic cells co-expressing genetic markers of multiple lineages

Heliyon ◽  
2018 ◽  
Vol 4 (6) ◽  
pp. e00667 ◽  
Author(s):  
Gennadi Glinsky ◽  
Jens Durruthy-Durruthy ◽  
Mark Wossidlo ◽  
Edward J. Grow ◽  
Jason L. Weirather ◽  
...  
Keyword(s):  
Single Cell ◽  
Genetic Markers ◽  
Expression Analysis ◽  
Embryonic Cells ◽  
Cell Expression
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