Misra Pratibha, Jadhav Amruta R, Bapat Sharmila A
Senior Advisor (Pathology & Biochemistry), 151 Base Hospital, Guwahati, India.
Senior Research Fellow, National Centre for Cell Science (NCCS), Pune, India.
Med J Armed Forces India. 2022 Sep;78(Suppl 1):S7-S13. doi: 10.1016/j.mjafi.2022.08.006. Epub 2022 Aug 26.
The rapid development of advanced high throughput technologies and introduction of high resolution "omics" data through analysis of biological molecules has revamped medical research. Single-cell sequencing in recent years, is in fact revolutionising the field by providing a deeper, spatio-temporal analyses of individual cells within tissues and their relevance to disease. Like conventional sequencing, the single-cell approach deciphers the sequence of nucleotides in a given Deoxyribose Nucleic Acid (DNA), Ribose Nucleic Acid (RNA), Micro Ribose Nucleic Acid (miRNA), epigenetically modified DNA or chromatin DNA; however, the unit of analyses is changed to single cells rather than the entire tissue. Further, a large number of single cells analysed from a single tissue generate a unique holistic perception capturing all kinds of perturbations across different cells in the tissue that increases the precision of data. Inherently, execution of the technique generates a large amount of data, which is required to be processed in a specific manner followed by customised bioinformatic analysis to produce meaningful results. The most crucial role of single-cell sequencing technique is in elucidating the inter-cell genetic, epigenetic, transcriptomic and proteomic heterogeneity in health and disease. The current review presents a brief overview of this cutting-edge technology and its applications in medical research.
先进的高通量技术的快速发展以及通过生物分子分析引入高分辨率的“组学”数据,彻底改变了医学研究。近年来,单细胞测序实际上正在彻底改变该领域,它能对组织内的单个细胞进行更深入的时空分析以及分析它们与疾病的相关性。与传统测序一样,单细胞方法能够解读给定的脱氧核糖核酸(DNA)、核糖核酸(RNA)、微小核糖核酸(miRNA)、表观遗传修饰的DNA或染色质DNA中的核苷酸序列;然而,分析单位变为了单个细胞而非整个组织。此外,从单个组织中分析大量的单细胞会产生一种独特的整体认知,能够捕捉组织中不同细胞间的各种扰动,从而提高数据的精确性。本质上,该技术的实施会产生大量数据,需要以特定方式进行处理,随后进行定制的生物信息学分析以产生有意义的结果。单细胞测序技术最关键的作用在于阐明健康和疾病状态下细胞间的遗传、表观遗传、转录组和蛋白质组异质性。本综述简要概述了这项前沿技术及其在医学研究中的应用。