Genotyping By Sequencing (GBS) Service

Overview

CDG offers advanced Genotyping by Sequencing services to efficiently identify genome-wide genetic variation across large populations. Unlike whole-genome sequencing, GBS leverages restriction enzyme digestion to reduce genome complexity while retaining high-resolution SNP discovery and genotyping capabilities. This approach is particularly suited for high-throughput studies of population structure, genetic diversity, linkage mapping, and marker-assisted selection. Utilizing state-of-the-art sequencing platforms and streamlined bioinformatics pipelines, we deliver accurate, cost-effective genotypic data tailored to the needs of population genetics, evolutionary biology, and breeding programs.

What is Genotyping By Sequencing

Genotyping By Sequencing is a reduced-representation sequencing technique that enables rapid and cost-effective discovery of genome-wide genetic variation, especially single nucleotide polymorphisms (SNPs), across a large number of individuals. Unlike Whole Genome Re-sequencing, which sequences the entire genome, GBS selectively captures informative genomic regions using restriction enzymes, focusing on a representative subset of the genome. This targeted yet high-throughput approach makes GBS particularly suitable for population-scale studies, enabling efficient analysis of genetic diversity, population structure, and evolutionary dynamics. By capturing both neutral and potentially adaptive variants, GBS supports research in natural selection, gene flow, demographic history, and local adaptation—providing a scalable solution for modern population genomics and breeding applications.

Genotyping By Sequencing Service pipeline. (Scheben, et al. 2019)

Sequencing Platforms

NextSeq 500

Illumina NovaSeq

PacBio Sequel II

Workflow of GBS in Population Genetics

Our Genotyping By Sequencing service follows an optimised workflow encompassing sample collection, restriction enzyme digestion, library construction, high-throughput sequencing, stringent quality control, and SNP genotyping through advanced bioinformatics analysis. This efficient pipeline enables the accurate detection of genome-wide genetic variants, particularly SNPs, which are essential for studies in population genetics, association mapping, and genomic selection. To ensure high-quality results, we advise clients to adhere to recommended sample preservation protocols and clearly communicate their research goals prior to project initiation. Our experienced team is available to assist with selecting suitable enzyme combinations, customizing sequencing strategies, and interpreting results, providing full support at every stage of your project.

Data Analysis

Data analysis of Genotyping By Sequencing Service. (Peterson, et al. 2014)

Why CD Genomics

Cutting-edge GBS Technology: Leverage advanced high-throughput sequencing platforms and refined enzymatic digestion protocols to efficiently profile genome-wide SNPs across a wide range of species and population sizes.

Cost-effective, High-throughput Genotyping: Achieve accurate, scalable, and affordable genotyping solutions tailored for large population studies—ideal for applications in population genetics, breeding programs, and evolutionary biology.

Robust Bioinformatics Pipeline: Our expert bioinformatics team provides standardised and customizable pipelines for SNP calling, genetic diversity analysis, population structure inference, GWAS, and marker discovery.

Extensive Experience in Population-scale Genotyping: With years of experience in GBS and related techniques, our team supports every stage of your project—from experimental design to biological interpretation—ensuring reliable and publication-ready results.

Customizable GBS Solutions: We tailor enzyme selection, library preparation strategies, and downstream analyses to meet your specific research objectives, whether you're studying selection signals, local adaptation, gene flow, or genetic differentiation.

Demo Results

Genotyping-By-Sequencing for Plant Genetic Diversity Analysis (Peterson, et al. 2014)

Case Study

Applications of genotyping-by-sequencing in maize genetics and breeding

Journal: Scientific Reports

Published: 2020

https://doi.org/10.1038/s41598-020-73321-8

Genotyping-by-Sequencing is a low-cost, high-throughput genotyping method that relies on restriction enzymes to reduce genome complexity. GBS is being widely used for various genetic and breeding applications. In the present study, 2240 individuals from eight maize populations, including two association populations (AM), backcross first generation (BC1), BC1F2, F2, double haploid (DH), intermated B73 × Mo17 (IBM), and a recombinant inbred line (RIL) population, were genotyped using GBS. A total of 955,120 of raw data for SNPs was obtained for each individual, with an average genotyping error of 0.70%. The rate of missing genotypic data for these SNPs was related to the level of multiplex sequencing: ~ 25% missing data for 96-plex and ~ 55% for 384-plex. Imputation can greatly reduce the rate of missing genotypes to 12.65% and 3.72% for AM populations and bi-parental populations, respectively, although it increases total genotyping error. For analysis of genetic diversity and linkage mapping, unimputed data with a low rate of genotyping error is beneficial, whereas, for association mapping, imputed data would result in higher marker density and would improve map resolution. Because imputation does not influence the prediction accuracy, both unimputed and imputed data can be used for genomic prediction. In summary, GBS is a versatile and efficient SNP discovery approach for homozygous materials and can be effectively applied for various purposes in maize genetics and breeding.

Genotyping-by-Sequencing
Bioinfomatics

Both unimputed and imputed data from eight populations were used to observe the impact of imputation on population structure analysis using PCA and multidimensional scaling (MDS). When using unimputed data, different subgroups could be separated by PCA in both association panels (Fig.1A, C). For Pop1, clusters of lines from CIMMYT-Columbia, CIMMYT-Zimbabwe, and some CIMMYT-Physiology lines extended in three directions, while others were concentrated in the middle (Fig.1A), which was consistent with the observations in a previous study34. For Pop2, different subgroups clustered along the PC1 axis, with popcorn and sweet corn on one side, and the non-stiff stalk lines on the other side. The stiff stalk and tropical lines could not be separated by the first two PCs (Fig.1C), which was in congruence with Romay's study35. When using imputed data, the two PCs explained more information, but the distribution of the lines was the sameforPop1 and Pop2 (Fig.1B, D).

Principal component analysis of Pop1 and Pop2 using unimputed and imputed data. (A) Pop1 using unimputed data; (B) Pop1 using imputed data; (C) Pop2 using unimputed data; (D) Pop2 using imputed data.

FAQs

What is Genotyping By Sequencing (GBS) Coverage Efficiency?

Genotyping By Sequencing (GBS) coverage efficiency refers to the proportion of the genome's targeted regions that are effectively captured and sequenced at sufficient depth to enable accurate SNP genotyping. Unlike Whole Genome Re-sequencing, which provides uniform coverage across the entire genome, GBS focuses on a reduced representation of the genome using restriction enzymes to selectively sequence consistent, reproducible loci. This approach greatly enhances efficiency and cost-effectiveness in population-scale studies. High GBS coverage efficiency ensures reliable detection of genetic variation in shared genomic regions, enabling robust analysis of population structure, genetic diversity, and marker-trait associations.

How Efficient is GBS in Variant Detection?

GBS is highly efficient for detecting genome-wide single nucleotide polymorphisms (SNPs) across large numbers of individuals, particularly in species with limited genomic resources. Although it does not capture the entire genome, GBS consistently targets specific subsets of the genome, generating high-density SNP datasets suitable for a wide range of population genetics applications. GBS excels at identifying common and moderately frequent variants, supporting studies such as genetic mapping, population differentiation, and genomic selection. Its low cost, scalability, and streamlined analysis pipeline make GBS an ideal choice for variant detection in large populations, especially in breeding programs and evolutionary studies.

What is the Recommended Sequencing Depth for GBS in Population Genetics?

The appropriate sequencing depth in GBS depends on study goals, population size, and desired marker density:

3X–5X per sample: Adequate for broad-scale genotyping, enabling detection of common SNPs across large populations with minimal cost—ideal for genetic diversity surveys and population structure analysis.
6X–10X per sample: Recommended for higher accuracy in genotype calling, especially in diploid and polyploid species or when performing genome-wide association studies (GWAS).
10X or higher: Suitable for applications requiring precise allele frequency estimation, parentage analysis, or detecting rare variants within the captured genomic regions.

References

Peterson, G. W., Dong, Y., Horbach, C., & Fu, Y.-B. (2014). Genotyping-By-Sequencing for Plant Genetic Diversity Analysis: A Lab Guide for SNP Genotyping. Diversity, 6(4), 665-680. https://doi.org/10.3390/d6040665
Scheben, A., Batley, J., & Edwards, D. (2017). Genotyping-by-sequencing approaches to characterise crop genomes: choosing the right tool for the right application. Plant biotechnology journal, 15(2), 149–161. https://doi.org/10.1111/pbi.12645
Wang, N., Yuan, Y., Wang, H., Yu, D., Liu, Y., Zhang, A., Gowda, M., Nair, S. K., Hao, Z., Lu, Y., San Vicente, F., Prasanna, B. M., Li, X., & Zhang, X. (2020). Applications of genotyping-by-sequencing (GBS) in maize genetics and breeding. Scientific reports, 10(1), 16308. https://doi.org/10.1038/s41598-020-73321-8

* Designed for biological research and industrial applications, not intended for individual clinical or medical purposes.