RAD-Seq Service
Overview
CD Genomics provides advanced Restriction Site Associated DNA Sequencing (RAD-Seq) to identify genetic variations, driving discoveries in conservation and precise medicine. Our services employ restriction enzymes to digest and target specific genomic regions, enabling cost-effective, high-depth analysis of both genetic and epigenetic variations. Utilizing state-of-the-art sequencing platforms and expert bioinformatics analysis, we deliver high resolution population genomic data tailored to your research needs, from disease studies to population genetics and evolutionary research.
Beyond traditional RAD-Seq, our genotyping service portfolio includes 2b-RAD, ddRAD-Seq, and Genotyping-by-Sequencing (GBS) to address diverse applications.
What is RAD-Seq Service
RAD-Seq employs restriction enzymes to recognize and cleave specific sites within genomic DNA, resulting in DNA fragments of varying sizes. These fragments are subsequently labeled with molecular identifiers (MIDs), which facilitate the association of sequence reads to their respective individuals. RAD-Seq effectively detects the presence-absence of restriction sites and identifies polymorphisms, such as SNPs and indels, in the regions flanking these restriction sites. This technique significantly reduces genome complexity, enabling cost-effective, high-depth representative sampling and analysis of the entire genome.
The Process of RAD-Seq. (Davey and Blaxter, 2011)
Sequencing Platforms
NextSeq 500
Illumina NovaSeq
PacBio Sequel II
Workflow of RAD-Seq in Population Genetics
Our RAD-Seq service workflow includes sample collection, library preparation, high-throughput sequencing, quality control, and detailed variant analysis to uncover genetic variations and population insights. Customers are encouraged to ensure proper sample handling and share specific research goals for tailored analysis. For any questions about sample requirements, sequencing, or data interpretation, our team is always ready to assist.
Bioinformatics Content
| Basic Analysis | Advanced analysis |
| Raw Data Quality Control: Per-base sequence quality, GC content distribution and adapter contamination ratio. Sequence Alignment: Retain uniquely mapped reads and mark duplicates. Variant Calling: SNP and indels identification. Data Format Conversion and Integration |
Population Genetic Structure: Principal Component Analysis(PCA) and ancestry component analysis. Phylogeny and Demographic History: Phylogenetic tree construction and demographic dynamics. Landscape Genomics |
Why CD Genomics
- Cutting-edge Sequencing Platforms: Compatible with NGS (Illumina) and third-gen (PacBio/Nanopore) platforms.
- High-throughput, High-quality Sequencing: Deliver premium-quality sequencing data faster, at lower cost, and with unmatched efficiency.
- One-Stop Service: End-to-end analysis from raw data QC, variant calling to population structure analysis, and provide expert data interpretation support.
- Integration of Comprehensive Genomics Analysis: Offer various omics technology services, including advanced and customized genomics analysis solutions.
Sample Requirements
- High DNA Quality: Free from RNA, protein, or exogenous DNA contamination, OD260/280≈1.8-2.0. Clear electrophoresis bands, no smearing.
- Sample Type: Fresh and frozen tissues, blood, saliva, etc., especially those with high nucleic acid content(avoid long-term preservation and repeatedly frozen).
- Sample Sizes Required: Plant tissue(≥1 g), animal tissue(>0.5 g), blood from mammals(≥1 mL), blood containing nucleated RBCs(≥0.5 mL), cells(>5 × 10^6, Log-phase growth, adherent cells should be trypsinized), nucleic acid(total DNA ≥ 300 ng, concentration ≥ 10 ng/μL).
Demo Results
Genetic diversity statistics results for 30 WGS and RAD-seq datasets
ADMIXTURE output based on RAD-seq
( Xu et al., BMC Plant Biology, 2025）
Case Study
Next-generation sequencing-based population genetics unravels the evolutionary history of Rhodomyrtus tomentosa in China
Journal:BMC Plant Biology
Published:2025
https://doi.org/10.1186/s12870-025-06364-6
Rhodomyrtus tomentosa (Ait.) Hassk. is useful for its ornamental, medicinal, and ecological characteristics. It has been considered a "Neglected and Underutilized Crop Species". However, the geographic structure and evolutionary history of its wild populations is poorly understood. To address this gap, this study investigated genomic data from 284 samples of R. tomentosa from 28 wild populations in southern China. Researchers employed next-generation sequencing technologies (RAD-seq and whole-genome sequencing) to comprehensively investigate the genetic diversity, population structure, driving forces of divergence, and evolutionary history of wild R. tomentosa populations in China. They particularly focus on the impacts of Pleistocene climate changes and geographical events on the distribution patterns. These findings demonstrate that Pleistocene climate shifts and geography shaped R. tomentosa's genetic divergence, bottlenecks, and current distribution. This study provides a foundation for its genetic conservation and improvement.
- RAD-Seq
- whole-genome sequencing
- Bioinfomatics
After initial quality filtering, RAD-Seq data from 284 samples across 28 Rhodomyrtus tomentosa populations were retained for subsequent analyses. Based on integrated evidence from ADMIXTURE, principal components analysis (PCA), and population geographic distributions, these 28 populations were classified into three distinct genetic groups. GROUP1 comprised 17 populations in the eastern mainland (Guangdong, Fujian, Zhejiang, and Hunan provinces). GROUP2 included eight populations in the western mainland (Guangxi, Yunnan, and Guizhou provinces). GROUP3 consisted of three populations on Hainan Island.
ADMIXTURE assignments for 28 populations.with its assignment probability to genetic clusters represented by different colors.
The consensus tree generated using BEAST revealed that the 28 R. tomentosa populations can be categorized into three groups. Clade 3 diverged earlier at 0.93 million years ago (MYA; 95% HPD: 0.78–1.10), while Clades 1 and 2 began diversifying more recently at approximately 0.09 MYA (95% HPD: 0.06–0.13). With a few exceptions, grouping in the chloroplast tree aligned closely with the population divisions inferred from the ADMIXTURE analysis.
BEAST time tree with node heights scaled to median divergence time estimates.
(Xu, et al. 2025)
FAQs
RAD-Seq (Restriction-site Associated DNA sequencing) eliminates dependence on reference genomes, making it suitable for non-model organisms. Through restriction enzyme-mediated targeting of specific genomic regions, it reduces complexity and lowers sequencing costs. These attributes render RAD-Seq ideal for large-scale population studies. Furthermore, It eliminates additional genotyping experiments by capturing polymorphic loci near restriction sites.
For genetic mapping projects, parental lines must meet ≥10X coverage to ensure accurate variant calling. While progeny from permanent populations require 0.6–1X depth per individual at a minimum cohort size of ≥100 specimens.
In population genetics analyses, no parental sequencing is needed. Instead, ≥1.5X depth per individual is recommended, with minimum sample sizes of ≥15 individuals for plant studies or ≥10 for animal systems.
References
- Davey, J. W., Blaxter, M. L., et al. RADseq: next-generation population genetics. Brief. Funct. Genomics, 416–423(2010). https://doi.org/10.1093/bfgp/elq031
- Xu, X. M., Liao, B. Y., et al. Next-generation sequencing-based population genetics unravels the evolutionary history of Rhodomyrtus tomentosa in China. BMC Plant Biol., 25:338(2025). https://doi.org/10.1186/s12870-025-06364-6
Related
Services
Download
