Single‐cell RNA sequencing methodology, analysis, applications, and future directions with special focus on cotton

生物 计算生物学 基因 原生质体 核糖核酸 基因表达 基因调控网络 植物发育 生物技术 基因表达调控 形态发生 分离(微生物学) 拟南芥 战斗或逃跑反应 DNA测序 适应(眼睛) 再生(生物学) 领域(数学) 光学(聚焦) 细胞 小RNA 植物种类
作者
Prabhakar Kumar Verma,Saikrisha Lekkala,Bello Usman,Sriharsha V. Lankireddy,Archana Khadgi,Luca d’Agostino,Praveen Kumar Balne,Gunvant Patil,Venkateswara R. Sripathi,Madhusudhana R. Janga
出处
期刊:Plant Biology [Wiley]
卷期号:28 (1): 31-44
标识
DOI:10.1111/plb.70131
摘要

Single-cell RNA sequencing (scRNA-seq) has emerged as a revolutionary technology that has significantly increased our understanding of plant cellular diversity and gene expression. Unlike bulk RNA sequencing, scRNA-seq reveals gene expression profiles at the cellular level and identifies rare cell populations and complex regulatory networks. Innovations in single-cell isolation have addressed previous challenges unique to plant cells, such as large cell sizes and rigid walls. Data analysis pipelines have also improved quality control, normalization, clustering, and downstream analyses of high-dimension scRNA-seq data. These improvements enhance our understanding of plant morphogenesis and cellular heterogeneity, opening avenues for further investigation into the complex interplay between gene expression and plant development. This review explores recent advances in sample preparation, such as protoplast preparation and nuclei isolation, library preparation, sequencing, and a detailed data analysis pipeline. Further, we explored the diverse applications of scRNA-seq in the field of cotton research, such as fibre development, gland development, salt and stress responses, as well as elucidating molecular mechanisms in anther development and uncovering critical regulatory networks involved in plant regeneration. Despite the potential and recent advances of scRNA-seq, some challenges, such as protoplast preparation, cell size variability, and the requirement for reliable marker genes, still need to be addressed. Thus, future research should prioritize optimizing scRNA-seq methodologies, enhancing high-throughput capabilities, and integrating multi-omics approaches to address changing environmental conditions.
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