AmpliRAD: A new method combining amplicon and RAD sequencing

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Authors: Tasha Q. Thompson, Michael Ryan Miller, Matthew R. Sloat
Cited by: 0

Abstract

This dataset provides the genomic data and computational framework supporting the development and validation of AmpliRAD, a novel sequencing method that integrates targeted amplicon sequencing with a genome-wide reduced-representation (RAD-seq) approach. The data was generated to demonstrate a streamlined workflow that enables simultaneous analysis of specific adaptive markers and broad population structure in non-model organisms. A primary focus of the dataset is the technical evaluation of the AmpliRAD method, including a direct comparison of sequencing yields and target enrichment success against samples processed using a traditional RAD-seq protocol. These comparative metrics include read counts mapping to target regions and the assessment of coverage evenness across 39 target loci, providing a benchmark for the method's efficiency. Additionally, the dataset includes genomic information from 96 Chinook salmon (Oncorhynchus tshawytscha) collected from the Dean River, British Columbia, including 55 adults and 41 juveniles. These data include targeted genotypes for SNPs on chromosome 28 associated with adult migration timing—specifically within the GREB1L region—as well as a panel of over 31,000 RAD-seq SNPs used to assess fine-scale population structure. Researchers can reuse this dataset as a template for implementing analysis of AmpliRAD data in other species or to explore the genetic basis of migration timing in northern salmon populations. While many different approaches could be used to analyze AmpliRAD data, the included bioinformatics pipeline offers a complete path from raw reads to population structure analysis, designed to be accessible to researchers seeking cost-effective genomic tools.

Fields of Study & Subjects

Genetic diversity and population structure Genetic Mapping and Diversity in Plants and Animals Genomics and Phylogenetic Studies

Publication details

Journal / source
DRYAD
Publication date
12 January 2026
Language
EN
Document type
Dataset