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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...

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Updated: Feb 17, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Deriving genotypes from RAD-seq short-read data using Stacks.

Nicolas C Rochette¹, Julian M Catchen¹

¹Department of Animal Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.

Nature Protocols

|December 1, 2017

Summary

This summary is machine-generated.

This study presents a protocol for analyzing Restriction site-associated DNA sequencing (RAD-seq) data using the Stacks pipeline. The method enables reliable genome-wide SNP discovery and genotyping for population genetics and ecological studies.

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Area of Science:

Genomics
Population Genetics
Bioinformatics

Background:

Restriction site-associated DNA sequencing (RAD-seq) is a powerful tool for genome-wide single-nucleotide polymorphism (SNP) discovery and genotyping.
Analyzing RAD-seq data, especially from diverse genomes, presents challenges in generating reliable genotype data from short-read sequencing data.

Purpose of the Study:

To present a robust protocol for analyzing RAD-seq data using the Stacks pipeline.
To provide guidance on assessing data, mapping reads, inferring loci, calling genotypes, and filtering results for ecological and population genetics research.

Main Methods:

The protocol details steps for data assessment, demultiplexing, read mapping, RAD loci inference, genotype calling, and output data filtering.
Emphasis is placed on checking procedural soundness and selecting key parameters based on data properties.

Main Results:

The Stacks pipeline protocol facilitates the conversion of RAD-seq data into reliable genotype data.
The protocol includes two examples of downstream biological analyses for practical application.

Conclusions:

This protocol offers a standardized and efficient approach to RAD-seq data analysis for population genetics and ecology.
The methodology is adaptable to various genomic properties and can be implemented within a reasonable timeframe.