Literature DB >> 33714967

Single-cell RNA sequencing to study vascular diversity and function.

Feiyang Ma1, Gloria E Hernandez1, Milagros Romay2, M Luisa Iruela-Arispe2.   

Abstract

PURPOSE OF REVIEW: Single-cell RNA sequencing (scRNA-seq) can capture the transcriptional profile of thousands of individual cells concurrently from complex tissues and with remarkable resolution. Either with the goal of seeking information about distinct cell subtypes or responses to a stimulus, the approach has provided robust information and promoted impressive advances in cardiovascular research. The goal of this review is to highlight strategies and approaches to leverage this technology and bypass potential caveats related to evaluation of the vascular cells. RECENT
FINDINGS: As the most recent technological development, details associated with experimental strategies, analysis, and interpretation of scRNA-seq data are still being discussed and scrutinized by investigators across the vascular field. Compilation of this information is valuable for those using the technology but particularly important to those about to start utilizing scRNA-seq to seek transcriptome information of vascular cells.
SUMMARY: As our field progresses to catalog transcriptomes from distinct vascular beds, it is undeniable that scRNA-seq technology is here to stay. Sharing approaches to improve the quality of cell dissociation procedures, analysis, and a consensus of best practices is critical as information from this powerful experimental platform continues to emerge.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

Entities:  

Mesh:

Year:  2021        PMID: 33714967      PMCID: PMC8262106          DOI: 10.1097/MOH.0000000000000651

Source DB:  PubMed          Journal:  Curr Opin Hematol        ISSN: 1065-6251            Impact factor:   3.284


  35 in total

Review 1.  Design and Analysis of Single-Cell Sequencing Experiments.

Authors:  Dominic Grün; Alexander van Oudenaarden
Journal:  Cell       Date:  2015-11-05       Impact factor: 41.582

2.  A comparison of single-cell trajectory inference methods.

Authors:  Wouter Saelens; Robrecht Cannoodt; Helena Todorov; Yvan Saeys
Journal:  Nat Biotechnol       Date:  2019-04-01       Impact factor: 54.908

3.  Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution.

Authors:  Samuel G Rodriques; Robert R Stickels; Aleksandrina Goeva; Carly A Martin; Evan Murray; Charles R Vanderburg; Joshua Welch; Linlin M Chen; Fei Chen; Evan Z Macosko
Journal:  Science       Date:  2019-03-28       Impact factor: 47.728

4.  Single-cell sequencing reveals dissociation-induced gene expression in tissue subpopulations.

Authors:  Susanne C van den Brink; Fanny Sage; Ábel Vértesy; Bastiaan Spanjaard; Josi Peterson-Maduro; Chloé S Baron; Catherine Robin; Alexander van Oudenaarden
Journal:  Nat Methods       Date:  2017-09-29       Impact factor: 28.547

5.  DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors.

Authors:  Christopher S McGinnis; Lyndsay M Murrow; Zev J Gartner
Journal:  Cell Syst       Date:  2019-04-03       Impact factor: 10.304

Review 6.  Harnessing Single-Cell RNA Sequencing to Better Understand How Diseased Cells Behave the Way They Do in Cardiovascular Disease.

Authors:  Farwah Iqbal; Adrien Lupieri; Masanori Aikawa; Elena Aikawa
Journal:  Arterioscler Thromb Vasc Biol       Date:  2020-12-17       Impact factor: 8.311

7.  The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.

Authors:  Cole Trapnell; Davide Cacchiarelli; Jonna Grimsby; Prapti Pokharel; Shuqiang Li; Michael Morse; Niall J Lennon; Kenneth J Livak; Tarjei S Mikkelsen; John L Rinn
Journal:  Nat Biotechnol       Date:  2014-03-23       Impact factor: 54.908

8.  Single-cell analysis of early progenitor cells that build coronary arteries.

Authors:  Tianying Su; Geoff Stanley; Rahul Sinha; Gaetano D'Amato; Soumya Das; Siyeon Rhee; Andrew H Chang; Aruna Poduri; Brian Raftrey; Thanh Theresa Dinh; Walter A Roper; Guang Li; Kelsey E Quinn; Kathleen M Caron; Sean Wu; Lucile Miquerol; Eugene C Butcher; Irving Weissman; Stephen Quake; Kristy Red-Horse
Journal:  Nature       Date:  2018-07-04       Impact factor: 49.962

9.  EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data.

Authors:  Aaron T L Lun; Samantha Riesenfeld; Tallulah Andrews; The Phuong Dao; Tomas Gomes; John C Marioni
Journal:  Genome Biol       Date:  2019-03-22       Impact factor: 13.583

10.  Assessment of computational methods for the analysis of single-cell ATAC-seq data.

Authors:  Huidong Chen; Caleb Lareau; Tommaso Andreani; Michael E Vinyard; Sara P Garcia; Kendell Clement; Miguel A Andrade-Navarro; Jason D Buenrostro; Luca Pinello
Journal:  Genome Biol       Date:  2019-11-18       Impact factor: 13.583

View more
  2 in total

1.  Aortic intimal resident macrophages are essential for maintenance of the non-thrombogenic intravascular state.

Authors:  Gloria E Hernandez; Feiyang Ma; Guadalupe Martinez; Nadia B Firozabadi; Jocelynda Salvador; Lih Jiin Juang; Jerry Leung; Peng Zhao; Diego A López; Reza Ardehali; Anna E Beaudin; Christian J Kastrup; Matteo Pellegrini; Matthew J Flick; M Luisa Iruela-Arispe
Journal:  Nat Cardiovasc Res       Date:  2022-01-12

2.  Isolation of Murine Retinal Endothelial Cells for Next-Generation Sequencing.

Authors:  Nicholas W Chavkin; Shelby Cain; Kenneth Walsh; Karen K Hirschi
Journal:  J Vis Exp       Date:  2021-10-11       Impact factor: 1.355

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.