Literature DB >> 29789704

Single-cell RNA sequencing for the study of development, physiology and disease.

S Steven Potter1.   

Abstract

An ongoing technological revolution is continually improving our ability to carry out very high-resolution studies of gene expression patterns. Current technology enables the global gene expression profiles of single cells to be defined, facilitating dissection of heterogeneity in cell populations that was previously hidden. In contrast to gene expression studies that use bulk RNA samples and provide only a virtual average of the diverse constituent cells, single-cell studies enable the molecular distinction of all cell types within a complex population mix, such as a tumour or developing organ. For instance, single-cell gene expression profiling has contributed to improved understanding of how histologically identical, adjacent cells make different differentiation decisions during development. Beyond development, single-cell gene expression studies have enabled the characteristics of previously known cell types to be more fully defined and facilitated the identification of novel categories of cells, contributing to improvements in our understanding of both normal and disease-related physiological processes and leading to the identification of new treatment approaches. Although limitations remain to be overcome, technology for the analysis of single-cell gene expression patterns is improving rapidly and beginning to provide a detailed atlas of the gene expression patterns of all cell types in the human body.

Entities:  

Mesh:

Year:  2018        PMID: 29789704      PMCID: PMC6070143          DOI: 10.1038/s41581-018-0021-7

Source DB:  PubMed          Journal:  Nat Rev Nephrol        ISSN: 1759-5061            Impact factor:   28.314


  93 in total

1.  Regulation of noise in the expression of a single gene.

Authors:  Ertugrul M Ozbudak; Mukund Thattai; Iren Kurtser; Alan D Grossman; Alexander van Oudenaarden
Journal:  Nat Genet       Date:  2002-04-22       Impact factor: 38.330

Review 2.  GDNF/Ret signaling and the development of the kidney.

Authors:  Frank Costantini; Reena Shakya
Journal:  Bioessays       Date:  2006-02       Impact factor: 4.345

3.  Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing.

Authors:  Dmitry Usoskin; Alessandro Furlan; Saiful Islam; Hind Abdo; Peter Lönnerberg; Daohua Lou; Jens Hjerling-Leffler; Jesper Haeggström; Olga Kharchenko; Peter V Kharchenko; Sten Linnarsson; Patrik Ernfors
Journal:  Nat Neurosci       Date:  2014-11-24       Impact factor: 24.884

Review 4.  Computational and analytical challenges in single-cell transcriptomics.

Authors:  Oliver Stegle; Sarah A Teichmann; John C Marioni
Journal:  Nat Rev Genet       Date:  2015-01-28       Impact factor: 53.242

5.  Transcriptional Profiling of Quiescent Muscle Stem Cells In Vivo.

Authors:  Cindy T J van Velthoven; Antoine de Morree; Ingrid M Egner; Jamie O Brett; Thomas A Rando
Journal:  Cell Rep       Date:  2017-11-14       Impact factor: 9.423

6.  Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing.

Authors:  Chunhong Zheng; Liangtao Zheng; Jae-Kwang Yoo; Huahu Guo; Yuanyuan Zhang; Xinyi Guo; Boxi Kang; Ruozhen Hu; Julie Y Huang; Qiming Zhang; Zhouzerui Liu; Minghui Dong; Xueda Hu; Wenjun Ouyang; Jirun Peng; Zemin Zhang
Journal:  Cell       Date:  2017-06-15       Impact factor: 41.582

7.  The Drosophila embryo at single-cell transcriptome resolution.

Authors:  Nikos Karaiskos; Philipp Wahle; Jonathan Alles; Anastasiya Boltengagen; Salah Ayoub; Claudia Kipar; Christine Kocks; Nikolaus Rajewsky; Robert P Zinzen
Journal:  Science       Date:  2017-08-31       Impact factor: 47.728

8.  Single-cell RNA-sequence analysis of mouse glomerular mesangial cells uncovers mesangial cell essential genes.

Authors:  Yuqiu Lu; Yuting Ye; Qianqian Yang; Shaolin Shi
Journal:  Kidney Int       Date:  2017-03-18       Impact factor: 10.612

9.  Stromal gene expression predicts clinical outcome in breast cancer.

Authors:  Greg Finak; Nicholas Bertos; Francois Pepin; Svetlana Sadekova; Margarita Souleimanova; Hong Zhao; Haiying Chen; Gulbeyaz Omeroglu; Sarkis Meterissian; Atilla Omeroglu; Michael Hallett; Morag Park
Journal:  Nat Med       Date:  2008-04-27       Impact factor: 53.440

10.  Amplification of multiple genomic loci from single cells isolated by laser micro-dissection of tissues.

Authors:  Dan Frumkin; Adam Wasserstrom; Shalev Itzkovitz; Alon Harmelin; Gideon Rechavi; Ehud Shapiro
Journal:  BMC Biotechnol       Date:  2008-02-20       Impact factor: 2.563

View more
  109 in total

1.  How to Find a Resident Kidney Macrophage: the Single-Cell Sequencing Solution.

Authors:  Menna R Clatworthy
Journal:  J Am Soc Nephrol       Date:  2019-04-04       Impact factor: 10.121

Review 2.  Preparation of single-cell suspensions of mouse glomeruli for high-throughput analysis.

Authors:  Ben Korin; Jun-Jae Chung; Shimrit Avraham; Andrey S Shaw
Journal:  Nat Protoc       Date:  2021-07-19       Impact factor: 13.491

Review 3.  Tools for the analysis of high-dimensional single-cell RNA sequencing data.

Authors:  Yan Wu; Kun Zhang
Journal:  Nat Rev Nephrol       Date:  2020-03-27       Impact factor: 28.314

4.  Single cell transcriptomics identifies focal segmental glomerulosclerosis remission endothelial biomarker.

Authors:  Rajasree Menon; Edgar A Otto; Paul Hoover; Sean Eddy; Laura Mariani; Bradley Godfrey; Celine C Berthier; Felix Eichinger; Lalita Subramanian; Jennifer Harder; Wenjun Ju; Viji Nair; Maria Larkina; Abhijit S Naik; Jinghui Luo; Sanjay Jain; Rachel Sealfon; Olga Troyanskaya; Nir Hacohen; Jeffrey B Hodgin; Matthias Kretzler; Kidney Precision Medicine Project Kpmp
Journal:  JCI Insight       Date:  2020-03-26

5.  High Dimensional Renal Profiling: Towards a Better Understanding or Renal Transplant Immune Suppression.

Authors:  Cyd M Castro-Rojas; Rita R Alloway; E Steve Woodle; David A Hildeman
Journal:  Curr Transplant Rep       Date:  2019-01-14

6.  Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at single-cell resolution.

Authors:  Abdel Nasser Hosein; Huocong Huang; Zhaoning Wang; Kamalpreet Parmar; Wenting Du; Jonathan Huang; Anirban Maitra; Eric Olson; Udit Verma; Rolf A Brekken
Journal:  JCI Insight       Date:  2019-07-23

Review 7.  Using single-cell technologies to map the human immune system - implications for nephrology.

Authors:  Benjamin J Stewart; John R Ferdinand; Menna R Clatworthy
Journal:  Nat Rev Nephrol       Date:  2019-12-12       Impact factor: 28.314

Review 8.  Use of Single-Cell -Omic Technologies to Study the Gastrointestinal Tract and Diseases, From Single Cell Identities to Patient Features.

Authors:  Mirazul Islam; Bob Chen; Jeffrey M Spraggins; Ryan T Kelly; Ken S Lau
Journal:  Gastroenterology       Date:  2020-05-14       Impact factor: 22.682

Review 9.  Brown Adipose Tissue Development and Metabolism.

Authors:  Su Myung Jung; Joan Sanchez-Gurmaches; David A Guertin
Journal:  Handb Exp Pharmacol       Date:  2019

10.  Dynamic single-cell phenotyping of immune cells using the microfluidic platform DropMap.

Authors:  Yacine Bounab; Klaus Eyer; Sophie Dixneuf; Magda Rybczynska; Cécile Chauvel; Maxime Mistretta; Trang Tran; Nathan Aymerich; Guilhem Chenon; Jean-François Llitjos; Fabienne Venet; Guillaume Monneret; Iain A Gillespie; Pierre Cortez; Virginie Moucadel; Alexandre Pachot; Alain Troesch; Philippe Leissner; Julien Textoris; Jérôme Bibette; Cyril Guyard; Jean Baudry; Andrew D Griffiths; Christophe Védrine
Journal:  Nat Protoc       Date:  2020-08-12       Impact factor: 13.491

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.