Literature DB >> 34116424

Potentials of single-cell genomics in deciphering cellular phenotypes.

Abbas Shojaee1, Michelle Saavedra1, Shao-Shan Carol Huang2.   

Abstract

Single-cell genomics, particularly single-cell transcriptome profiling by RNA sequencing have transformed the possibilities to relate genes to functions, structures, and eventually phenotypes. We can now observe changes in each cell's transcriptome and among its neighborhoods, interrogate the sequence of transcriptional events, and assess their influence on subsequent events. This paradigm shift in biology enables us to infer causal relationships in these events with high accuracy. Here we review the latest single-cell studies in plants that uncover how cellular phenotypes emerge as a result of the transcriptome process such as waves of expression, trajectories of development and responses to the environment, and spatial information. With an eye on the advances made in animal and human studies, we further highlight some of the needed areas for future research and development, including computational methods.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Causal inference; Chromatin accessibility; Expression waves; Multi-omics; Plant biology; Pseudotime; RNA sequencing; Single cell; Spatial transcriptomics

Mesh:

Year:  2021        PMID: 34116424      PMCID: PMC8545747          DOI: 10.1016/j.pbi.2021.102059

Source DB:  PubMed          Journal:  Curr Opin Plant Biol        ISSN: 1369-5266            Impact factor:   9.396


  55 in total

Review 1.  Concepts and limitations for learning developmental trajectories from single cell genomics.

Authors:  Sophie Tritschler; Maren Büttner; David S Fischer; Marius Lange; Volker Bergen; Heiko Lickert; Fabian J Theis
Journal:  Development       Date:  2019-06-27       Impact factor: 6.868

2.  Spatiotemporal Developmental Trajectories in the Arabidopsis Root Revealed Using High-Throughput Single-Cell RNA Sequencing.

Authors:  Tom Denyer; Xiaoli Ma; Simon Klesen; Emanuele Scacchi; Kay Nieselt; Marja C P Timmermans
Journal:  Dev Cell       Date:  2019-03-25       Impact factor: 12.270

Review 3.  Status and Potential of Single-Cell Transcriptomics for Understanding Plant Development and Functional Biology.

Authors:  Muhammad Munir Iqbal; Bhavna Hurgobin; Andrea Lisa Holme; Rudi Appels; Parwinder Kaur
Journal:  Cytometry A       Date:  2020-08-28       Impact factor: 4.355

4.  Global Dynamic Molecular Profiling of Stomatal Lineage Cell Development by Single-Cell RNA Sequencing.

Authors:  Zhixin Liu; Yaping Zhou; Jinggong Guo; Jiaoai Li; Zixia Tian; Zhinan Zhu; Jiajing Wang; Rui Wu; Bo Zhang; Yongjian Hu; Yijing Sun; Yan Shangguan; Weiqiang Li; Tao Li; Yunhe Hu; Chenxi Guo; Jean-David Rochaix; Yuchen Miao; Xuwu Sun
Journal:  Mol Plant       Date:  2020-06-24       Impact factor: 13.164

5.  Vascular transcription factors guide plant epidermal responses to limiting phosphate conditions.

Authors:  Jos R Wendrich; BaoJun Yang; Niels Vandamme; Kevin Verstaen; Wouter Smet; Celien Van de Velde; Max Minne; Brecht Wybouw; Eliana Mor; Helena E Arents; Jonah Nolf; Julie Van Duyse; Gert Van Isterdael; Steven Maere; Yvan Saeys; Bert De Rybel
Journal:  Science       Date:  2020-09-17       Impact factor: 47.728

Review 6.  Integrative Methods and Practical Challenges for Single-Cell Multi-omics.

Authors:  Anjun Ma; Adam McDermaid; Jennifer Xu; Yuzhou Chang; Qin Ma
Journal:  Trends Biotechnol       Date:  2020-03-26       Impact factor: 19.536

7.  In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes.

Authors:  Aviv Regev; Feng Zhang; Paola Arlotta; Xin Jin; Sean K Simmons; Amy Guo; Ashwin S Shetty; Michelle Ko; Lan Nguyen; Vahbiz Jokhi; Elise Robinson; Paul Oyler; Nathan Curry; Giulio Deangeli; Simona Lodato; Joshua Z Levin
Journal:  Science       Date:  2020-11-27       Impact factor: 47.728

8.  Single-cell chromatin accessibility reveals principles of regulatory variation.

Authors:  Jason D Buenrostro; Beijing Wu; Ulrike M Litzenburger; Dave Ruff; Michael L Gonzales; Michael P Snyder; Howard Y Chang; William J Greenleaf
Journal:  Nature       Date:  2015-06-17       Impact factor: 49.962

Review 9.  Single-Cell RNA-Seq Technologies and Related Computational Data Analysis.

Authors:  Geng Chen; Baitang Ning; Tieliu Shi
Journal:  Front Genet       Date:  2019-04-05       Impact factor: 4.599

10.  Simultaneous lineage tracing and cell-type identification using CRISPR-Cas9-induced genetic scars.

Authors:  Bastiaan Spanjaard; Bo Hu; Nina Mitic; Pedro Olivares-Chauvet; Sharan Janjuha; Nikolay Ninov; Jan Philipp Junker
Journal:  Nat Biotechnol       Date:  2018-04-09       Impact factor: 54.908

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  2 in total

1.  Trafficking and localization of KNOTTED1 related mRNAs in shoot meristems.

Authors:  Munenori Kitagawa; Xiaosa Xu; David Jackson
Journal:  Commun Integr Biol       Date:  2022-07-06

Review 2.  Cell types as species: Exploring a metaphor.

Authors:  Jeff J Doyle
Journal:  Front Plant Sci       Date:  2022-08-22       Impact factor: 6.627

  2 in total

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