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Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.

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...

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Updated: May 26, 2026

Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

miRNA data analysis: next-gen sequencing.

Preethi H Gunaratne¹, Cristian Coarfa, Benjamin Soibam

¹Department of Biology and Biochemistry, University of Houston, Houston, TX, USA. phgunaratne@uh.edu

Methods in Molecular Biology (Clifton, N.J.)

|December 7, 2011

Summary

This summary is machine-generated.

MicroRNAs (miRNAs) regulate gene expression and are linked to diseases. New sequencing technologies reveal miRNA complexity, necessitating advanced analysis tools for discovery and profiling.

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MicroRNA Amplification and Recognition through Locked-nucleic-acid In situ Hybridization as a Novel Detection and Quantification Method

MicroRNA Amplification and Recognition through Locked-nucleic-acid In situ Hybridization as a Novel Detection and Quantification Method

Published on: October 7, 2025

Area of Science:

Molecular Biology
Genetics
Bioinformatics

Background:

MicroRNAs (miRNAs) are short, noncoding RNAs regulating gene expression across signaling pathways.
Specific miRNA sets define cell lineages; their dysregulation is implicated in various diseases.
Next-generation sequencing (NGS) reveals miRNA complexity, including length heterogeneity and RNA editing.

Purpose of the Study:

To review available analysis platforms for miRNA discovery and profiling.
To highlight the importance of data analysis tools for small RNA sequencing data.
To discuss the identification of functional miRNA-mRNA interactions in biological and disease contexts.

Main Methods:

Summary of existing miRNA analysis platforms.
Discussion of data analysis requirements for NGS small RNA data.
Exploration of methods for identifying miRNA-mRNA interactions.

Main Results:

NGS platforms like Illumina, SOLiD, and 454 generate vast amounts of small RNA sequencing data.
Previous microarray studies did not uncover the complexity observed with deep sequencing.
Numerous analysis tools are emerging to handle the volume and complexity of miRNA data.

Conclusions:

Advanced bioinformatics tools are crucial for analyzing complex miRNA sequencing data.
Effective analysis facilitates miRNA discovery, profiling, and understanding of miRNA-mRNA interactions.
These tools are vital for advancing research in biology and disease associated with miRNAs.