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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

Ribosome Profiling

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

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Updated: Jun 28, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Navigating single-cell RNA-sequencing: protocols, tools, databases, and applications.

Ankish Arya¹, Prabhat Tripathi¹, Nidhi Dubey¹

¹Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Jhalwa, Prayagraj, 211015, Uttar Pradesh, India.

Genomics & Informatics

|May 17, 2025

Summary

This summary is machine-generated.

Single-cell RNA-sequencing (scRNA-seq) revolutionizes biology by analyzing cellular heterogeneity. This review details scRNA-seq methods, challenges, and applications in areas like drug discovery and personalized medicine.

Keywords:

Cellular heterogeneity Databases Drug discovery Protocols and tools Single-cell RNA sequencing

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Single-cell RNA-sequencing (scRNA-seq) enables detailed analysis of cellular heterogeneity.
It offers unprecedented insights into biological systems at the individual cell level.
Challenges exist in data analysis, interpretation, and multi-omics integration.

Purpose of the Study:

To review the complexities and optimization strategies for scRNA-seq.
To discuss current single-cell databases and analytical tools.
To explore diverse applications and case studies of scRNA-seq.

Main Methods:

Comprehensive literature review of scRNA-seq protocols and analytical methodologies.
Exploration of innovative techniques for enhanced single-cell resolution and accuracy.
Analysis of scRNA-seq applications across various biological and medical domains.

Main Results:

Identification of key challenges in scRNA-seq data analysis and integration.
Overview of available tools and databases for scRNA-seq analysis.
Demonstration of scRNA-seq utility in drug discovery, tumor microenvironment studies, biomarker discovery, and microbial profiling.

Conclusions:

scRNA-seq is crucial for advancing personalized medicine and understanding complex biological systems.
Optimization of scRNA-seq approaches is vital for maximizing its potential.
The technology facilitates the discovery of novel and rare cell types, enhancing biological insights.