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Transcriptome-Wide Association Studies (TWAS) in Animal Breeding - BioVenic
Advances in high-throughput sequencing technologies have revealed the important genomic regulatory role played by non-coding regions in gene transcriptional activity. The Transcriptome-Wide Association Study (TWAS), developed in 2005, is a data integration bioinformatics approach designed to identify genes that result in complex traits due to gene-regulated transcriptional activity. TWAS uses expression prediction models from genotypes trained on expression reference panels, such as eQTL (expression quantitative trait loc) cohorts with expression and genotype data, to discover gene-trait associations from GWAS datasets. With experience in animal-related R&D research, BioVenic has an advanced technology platform and data analysis team that can develop customized TWAS services for our clients' different animal breeding programs.
Fig.1 Workflow of Theprobabilistic Transcriptome-wide Association Study (PTWAS) Analysis1,2.
Advantages of TWAS
Biologically Significant Genetic Units
The gene is a much easier biological unit to interpret than a related locus because the locus often contains multiple significant SNPs in LD that may not be in the gene and/or marker variants in multiple genes.
Less Multiple Comparison Burden
The lower total number of genes means that the burden of multiple testing is greatly reduced relative to all SNPs.
More Sensitive
Combining cis-SNPs into a single predictor may capture heterogeneity signals better than individual SNPs or cis eQTLs (Expression Quantitative Trait Locus).
More Accurate
Focusing the prediction on the genetic component of expression also avoids interference from environmental differences caused by traits that may affect expression.
Application of TWAS in Animal Breeding
Thanks to the advent of technologies that allow quantification of endophenotypes such as mRNA, metabolite, or protein abundance, mapping and trait profiling can now be performed between intermediate levels of biological organization, which is referred to as TWAS. Testing and correlating these endophenotypes with traits of interest provides insight into biological mechanisms, serves as an independent source of evidence for association, and facilitates prioritization of potential causal variants while linking genes directly to traits, making it possible to integrate the effects of multiple independent genetic variants.
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TWAS Applications for Unique Traits
TWAS can link unique phenotypes of animals to gene expression in animal breeding, facilitating screening for specific phenotypes and reproductive traits in animals. For common economic animals, TWAS can be used to analyze gene expression in relation to a variety of economically important traits such as fat area and distribution, body size, body weight, and growth rate, as well as milk production and milk quality in cows and egg production and quality in chickens. -
TWAS Applications for Genetic Disorders
As well as screening animals for unique traits, TWAS can be used to explore the relationship between gene expression and inherited diseases in animals. This is particularly important for companion animals such as cats and dogs, where many purebred companion animals may suffer from genetic disorders.
Our Services
TWAS is a powerful and ideal tool to analyze gene expression associated with economically important phenotypes or diseases, facilitating more effective animal breeding. As a pioneer in scientific animal breeding, BioVenic offers multiple types of animal breeding solutions to meet the needs of our diverse customers. We have an experienced and professional data analysis team to provide customized data analysis services to facilitate our clients' animal breeding projects.
Workflow of TWAS
Want to Learn More?
BioVenic is a pioneer in the field of animal breeding. Our top-notch instruments and platforms and professional team of experts provide TWAS-based animal breeding services. We collaborate and communicate deeply with our clients to develop optimal strategies for different projects and provide the most reliable data analysis results. If you are interested in our services, please contact us and tell us more about your project.
Reference
- Zhang, Yuhua, et al. "PTWAS: investigating tissue-relevant causal molecular mechanisms of complex traits using probabilistic TWAS analysis." Genome biology 21 (2020): 1-26.
- Image retrieved from Figure 1 "Workflow of the PTWAS analysis". Zhang, Yuhua, et al., 2020, used under CC BY 4.0. The original image was modified by changing title to "Workflow of Theprobabilistic Transcriptome-wide Association Study (PTWAS) Analysis".