Understanding How Traits Are Inherited in Farm Animals

Jenn Hoskins
14th July, 2024

Understanding How Traits Are Inherited in Farm Animals

In a simple simulation where genetic architecture was not stratified, both the GREML and BayesRR-RC methods used in the study accurately estimated the average heritability contribution of open chromatin regions, but the high variability of the results highlights the low precision of these approaches in livestock populations.

Image adapted from: Yuan et al. / CC BY (Source)

Key Findings

  • The study from the University of Liège focused on Belgian Blue beef cattle to understand the genetic basis of traits like muscular development and height
  • Regulatory genetic variants significantly contribute to the genetic variance of complex traits in livestock
  • Variants in open chromatin regions (OCR) and coding regions have the highest impact on genetic variance and heritability enrichment, respectively
Understanding the genetic architecture of complex traits in livestock is crucial for improving traits of economic value, such as milk production, fertility, and growth rates. A recent study from the University of Liège has advanced this understanding by applying heritability partitioning approaches to livestock populations[1]. This method estimates the contribution of different functional classes, such as coding or regulatory variants, to the genetic variance of complex traits. Although these methods have been extensively tested on human genomic data, livestock populations present unique challenges, including high levels of relatedness, small effective population sizes, and long-range linkage disequilibrium. Earlier studies have laid the groundwork for this research. For example, a comprehensive gene atlas built by analyzing RNA-seq data from 91 tissues and cell types in cattle demonstrated the tissue specificity of genes and their evolution patterns[2]. Another study created a Cattle Genotype-Tissue Expression atlas (CattleGTEx) that explored the transcriptomic landscape of over 100 tissues and cell types, linking gene expression to economically important traits[3]. Additionally, a catalog of cis-acting regulatory elements in cattle provided insights into the regulatory potential of these elements and their association with genetic variants[4]. The current study from the University of Liège builds on these foundational works by focusing on heritability partitioning. This approach allows researchers to estimate how much of the genetic variance in complex traits can be attributed to different functional classes of genetic variants, such as coding regions or regulatory elements. This is particularly important for livestock, where traits like milk production or fertility are influenced by multiple genes and environmental factors. The study's application of heritability partitioning to livestock populations addresses the unique genetic characteristics of these populations. Livestock often have high levels of relatedness due to selective breeding practices, which can complicate genetic analyses. Additionally, the small effective population size and long-range linkage disequilibrium in livestock can affect the accuracy of genomic selection. By accounting for these factors, the study provides a more accurate understanding of the genetic architecture of complex traits in livestock. One of the key findings of the study is the significant contribution of regulatory variants to the genetic variance of complex traits. This aligns with previous findings that identified hundreds of thousands of genetic associations with gene expression and alternative splicing in cattle[3]. The study also highlights the importance of tissue-specific regulatory elements, which were shown to be under purifying selection in earlier research[4]. By integrating these insights, the current study offers a more comprehensive view of how different functional classes of genetic variants contribute to complex traits in livestock. The implications of this research are profound. By improving our understanding of the genetic architecture of complex traits, heritability partitioning can enhance the accuracy of genomic selection in livestock. This could lead to more efficient breeding programs, ultimately increasing the rate of genetic gain for economically important traits. Furthermore, the study's findings can inform future research on the molecular mechanisms underlying these traits, providing a basis for targeted genetic interventions. In summary, the study from the University of Liège offers valuable insights into the genetic architecture of complex traits in livestock by applying heritability partitioning approaches. Building on previous research that mapped gene expression and regulatory elements in cattle[2][3][4], this study provides a more nuanced understanding of how different functional classes of genetic variants contribute to traits of economic value. This knowledge has the potential to significantly improve the accuracy of genomic selection, paving the way for more efficient and effective livestock breeding programs.

AgricultureGeneticsAnimal Science

References

Main Study

1) Evaluation of heritability partitioning approaches in livestock populations

Published 13th July, 2024

https://doi.org/10.1186/s12864-024-10600-y

Related Studies

2) Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle.

https://doi.org/10.1101/gr.250704.119

3) A multi-tissue atlas of regulatory variants in cattle.

https://doi.org/10.1038/s41588-022-01153-5

4) An organism-wide ATAC-seq peak catalog for the bovine and its use to identify regulatory variants.

https://doi.org/10.1101/gr.277947.123


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