Literature DB >> 27848892

Single-Cell Sequencing for Drug Discovery and Drug Development.

Charles Wang1, Shixiu Wu2, Hongjin Wu2,1.   

Abstract

Next-generation sequencing (NGS), particularly single-cell sequencing, has revolutionized the scale and scope of genomic and biomedical research. Recent technological advances in NGS and singlecell studies have made the deep whole-genome (DNA-seq), whole epigenome and whole-transcriptome sequencing (RNA-seq) at single-cell level feasible. NGS at the single-cell level expands our view of genome, epigenome and transcriptome and allows the genome, epigenome and transcriptome of any organism to be explored without a priori assumptions and with unprecedented throughput. And it does so with single-nucleotide resolution. NGS is also a very powerful tool for drug discovery and drug development. In this review, we describe the current state of single-cell sequencing techniques, which can provide a new, more powerful and precise approach for analyzing effects of drugs on treated cells and tissues. Our review discusses single-cell whole genome/exome sequencing (scWGS/scWES), single-cell transcriptome sequencing (scRNA-seq), single-cell bisulfite sequencing (scBS), and multiple omics of single-cell sequencing. We also highlight the advantages and challenges of each of these approaches. Finally, we describe, elaborate and speculate the potential applications of single-cell sequencing for drug discovery and drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Entities:  

Keywords:  Drug discovery; NGS; RNA-seq; Single-cell bisulfite sequencing; Single-cell sequencing

Mesh:

Year:  2017        PMID: 27848892     DOI: 10.2174/1568026617666161116145358

Source DB:  PubMed          Journal:  Curr Top Med Chem        ISSN: 1568-0266            Impact factor:   3.295


  6 in total

1.  A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples.

Authors:  Wanqiu Chen; Yongmei Zhao; Xin Chen; Zhaowei Yang; Xiaojiang Xu; Yingtao Bi; Vicky Chen; Jing Li; Hannah Choi; Ben Ernest; Bao Tran; Monika Mehta; Parimal Kumar; Andrew Farmer; Alain Mir; Urvashi Ann Mehra; Jian-Liang Li; Malcolm Moos; Wenming Xiao; Charles Wang
Journal:  Nat Biotechnol       Date:  2020-12-21       Impact factor: 54.908

2.  Deep learning tackles single-cell analysis-a survey of deep learning for scRNA-seq analysis.

Authors:  Mario Flores; Zhentao Liu; Tinghe Zhang; Md Musaddaqui Hasib; Yu-Chiao Chiu; Zhenqing Ye; Karla Paniagua; Sumin Jo; Jianqiu Zhang; Shou-Jiang Gao; Yu-Fang Jin; Yidong Chen; Yufei Huang
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 13.994

3.  Utilizing Genome-Wide mRNA Profiling to Identify the Cytotoxic Chemotherapeutic Mechanism of Triazoloacridone C-1305 as Direct Microtubule Stabilization.

Authors:  Jarosław Króliczewski; Sylwia Bartoszewska; Magdalena Dudkowska; Dorota Janiszewska; Agnieszka Biernatowska; David K Crossman; Karol Krzymiński; Małgorzata Wysocka; Anna Romanowska; Maciej Baginski; Michal Markuszewski; Renata J Ochocka; James F Collawn; Aleksander F Sikorski; Ewa Sikora; Rafal Bartoszewski
Journal:  Cancers (Basel)       Date:  2020-04-02       Impact factor: 6.639

Review 4.  DNA Methylation and Histone Modification in Hypertension.

Authors:  Shaunrick Stoll; Charles Wang; Hongyu Qiu
Journal:  Int J Mol Sci       Date:  2018-04-12       Impact factor: 5.923

Review 5.  Editorial focus: understanding off-target effects as the key to successful RNAi therapy.

Authors:  Rafal Bartoszewski; Aleksander F Sikorski
Journal:  Cell Mol Biol Lett       Date:  2019-12-09       Impact factor: 5.787

Review 6.  Personalized Medicine Using Cutting Edge Technologies for Genetic Epilepsies.

Authors:  Sheila Garcia-Rosa; Bianca de Freitas Brenha; Vinicius Felipe da Rocha; Ernesto Goulart; Bruno Henrique Silva Araujo
Journal:  Curr Neuropharmacol       Date:  2021       Impact factor: 7.363

  6 in total

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