Genome-Wide Association Study (GWAS) for Plant Breeding

Lifeasible is a plant biotechnology company offering a wide array of molecular breeding services. Our goal is to help plant breeders identify and introduce desirable traits into plant varieties with high efficiency.

What Is Genome-Wide Association Study (GWAS)?

GWAS is a method for the study of associations between a genome-wide set of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits. The quantitative evaluation is based on linkage disequilibrium (LD) through genotyping and phenotyping of diverse individuals. Generally, a GWAS infers these associations through a hypothesis test with pertinent test statistics such as Pearson's x² -test, Fisher's exact test, the F-test, or a regression model under a null hypothesis assumes no association.

As a result of continuously dropping cost for DNA sequencing, whole genome sequencing has been largely available in a wide range of species with phenotype variations, promoting the application of GWAS.

The process of GWAS

What We Offer

Being a group with diverse knowledge background in genetics, molecular biology, statistics, and bioinformatics, Lifeasible provides worldwide customers with specialized and customized one-stop services in GWAS plant breeding. Our services cover genome sequencing, SNPs discovery, association statistical analysis, as well as validation of candidate gene functions. Our cross-disciplinary experience with a wide range of plant species guarantees superior plant breeding services with a real competitive edges.

Our services cover SNP detection and annotation, phylogenetic tree construction, linkage disequilibrium analysis, principal component analysis (PCA), group structure analysis, kinship analysis, personalized analysis, etc. In general, three graphs are used for visualization of results:

• Manhattan plot: A scatter plot that displays p-values in the –log₁₀ (p) scale versus the genomic position of the SNPs and their chromosome numbers. Large peaks correspond to small p-values indicate that the corresponding genomic region has a strong association with the trait.
• Quantile-quantile (Q-Q) plot: A plot used to evaluate how well the model used in the GWAS accounts for specific population structure and familial relatedness. The SNPs on the upper right section of the graph deviate from the diagonal are most likely to be associated with the trait of study.
• Principal component (PC) plot: A method to estimate the effect of the population structure by analyzing multivariate data in terms of covariance structure of the data.

Why Choose Lifeasible?