GWAS Services
Genome-Wide Association Study (GWAS), in the study of plants and animals, is used to understand genetic variation among individuals of different plants and animals by identifying sequence variants that exist genome-wide, from which all or most of the genes between different individuals in a given species can be detected.
CD Genomics provides genome-wide association analysis, which has the advantage of rapid and accurate localization of important traits, especially complex traits, in plant and animal research. Based on high-throughput sequencing to genotype a representative variety, endemic or wild species of a crop or livestock, combined with accurate phenotypic data, important complex traits of crops or livestock can be localized. Especially, in a population containing wild species, domesticated species and improved species, combining population evolutionary analysis to locate important genes that received domestication and improvement provides researchers with an important idea to study the microevolution of crops or livestock and the phenotype of domestication and improvement.
Types of GWAS services
- Plant Phenotyping
- Yield-Related Traits Analysis
- Disease Resistance Traits Analysis
- Insect Resistance Traits Analysis
Characterization of GWAS
- High throughput detection of genome-wide SNPs and association analysis to eliminate blind spots in localization.
- Heavy screening of SNPs, multiple testing for significance, high accuracy of results.
- Simultaneous targeting of multiple traits.
- Localization accuracy up to single gene level.
GWAS can be used in the following research
- Genome-wide localization of multiple traits.
- Basic biological studies of target traits.
How to start your GWAS project
Sample Selection Strategy
- No obvious subpopulation differentiation: To ensure reliability, selected samples should come from a relatively homogeneous population, avoiding the impact of subpopulation differentiation on results.
- Strong genetic heritability of phenotype: Choose phenotypes with a clear genetic component to detect associations between genes and phenotypes easier.
- Representative sampling: Samples should represent the diversity of the study population to ensure the generalizability of results.
- Sample size of at least 200: For statistical significance, it is recommended to have a sample size of at least 200.
Sequencing Strategy
| Sequencing Strategy | Depth Recommendation | Applicability |
|---|---|---|
| Genome Resequencing | At least 5X per sample | Reference genome required |
| Reduced-Representation Genome Sequencing (RRGS) | Reference genome size ≤1G, 1G per sample | Dealing with a large reference genome |
| 1G≤ Reference genome size ≤5G, 2~3G per sample | ||
| 5G≤ Reference genome size ≤20G, 3~5G per sample |
Instructions for providing samples
| Sample type | Different varieties, subspecies, local species/germplasm bank/mixed lineage/wild resources/semi-sibling lineage/whole sibling lineage/wild resources
|
|---|---|
| Sample selection requirements | There should be no obvious subpopulation differentiation among the samples, and the polymorphism should be wide, while it is recommended to select a few more important phenotypic traits as the focus of the study. |
| Target trait selection requirements | Select traits with high heritability and try to have consistent phenotypic identification sites for all individual traits, preferably with multiple years of phenotypic data. |
Technical route of GWAS
Our advantages and features
- The advanced technology platform and perfect technology integration ensure the accuracy of accurate and reliable results to the maximum extent and shorten the project turnaround time.
- With comprehensive GWAS-related technology coverage and abundant GWAS microarray types, we have been leading the industry in the field of GWAS services.
- Fast, accurate and efficient resolution of differences between genomes and access to a wide range of molecular markers.
CD Genomics has a wide range of association analysis models to provide customized and personalized analysis services according to the different needs of our customers. Our experienced team of experts and strong biomarker analysis team can quickly analyze SNP profiles obtained from SNP microarrays or whole genome sequencing while achieving a rapid turnaround of experiments. With our GWAS services, we can directly identify genetic loci or marker loci that are closely associated with phenotypic variants and have specific functions. Holistic studies on a genome-wide scale can provide a profile overview of superior traits at once, and are suitable for studies that tap into superior traits. If you are interested in us, please feel free to contact us.
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