Dataset Information

Tracing the Origin of the RSPO2 Long-Hair Allele and Epistatic Interaction between FGF5 and RSPO2 in Sapsaree Dog.

ABSTRACT: Genetic analysis of the hair-length of Sapsaree dogs, a Korean native dog breed, showed a dominant mode of inheritance for long hair. Genome-Wide Association Study (GWAS) analysis and subsequent Mendelian segregation analysis revealed an association between OXR1, RSPO2, and PKHD1L1 on chromosome 13 (CFA13). We identified the previously reported 167 bp insertion in RSPO2 3' untranslated region as a causative mutation for hair length variations. The analysis of 118 dog breeds and wolves revealed the selection signature on CFA13 in long-haired breeds. Haplotype analysis showed the association of only a few specific haplotypes to the breeds carrying the 167 bp insertion. The genetic diversity in the neighboring region linked to the insertion was higher in Sapsarees than in other Asian and European dog breeds carrying the same variation, suggesting an older history of its insertion in the Sapsaree genome than in that of the other breeds analyzed in this study. Our results show that the RSPO2 3' UTR insertion is responsible for not only the furnishing phenotype but also determining the hair length of the entire body depending on the genetic background, suggesting an epistatic interaction between FGF5 and RSPO2 influencing the hair-length phenotype in dogs.

SUBMITTER: Kang M

PROVIDER: S-EPMC8775186 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:An epistatic interaction between two genes occurs when the phenotypic impact of one gene depends on another gene, often exposing a functional association between them. Due to experimental scalability and to evolutionary significance, abundant work has been focused on studying how epistasis affects cellular growth rate, most notably in yeast. However, epistasis likely influences many different phenotypes, affecting our capacity to understand cellular functions, biochemical networks adaptation, and genetic diseases. Despite its broad significance, the extent and nature of epistasis relative to different phenotypes remain fundamentally unexplored. Here we use genome-scale metabolic network modeling to investigate the extent and properties of epistatic interactions relative to multiple phenotypes. Specifically, using an experimentally refined stoichiometric model for Saccharomyces cerevisiae, we computed a three-dimensional matrix of epistatic interactions between any two enzyme gene deletions, with respect to all metabolic flux phenotypes. We found that the total number of epistatic interactions between enzymes increases rapidly as phenotypes are added, plateauing at approximately 80 phenotypes, to an overall connectivity that is roughly 8-fold larger than the one observed relative to growth alone. Looking at interactions across all phenotypes, we found that gene pairs interact incoherently relative to different phenotypes, i.e. antagonistically relative to some phenotypes and synergistically relative to others. Specific deletion-deletion-phenotype triplets can be explained metabolically, suggesting a highly informative role of multi-phenotype epistasis in mapping cellular functions. Finally, we found that genes involved in many interactions across multiple phenotypes are more highly expressed, evolve slower, and tend to be associated with diseases, indicating that the importance of genes is hidden in their total phenotypic impact. Our predictions indicate a pervasiveness of nonlinear effects in how genetic perturbations affect multiple metabolic phenotypes. The approaches and results reported could influence future efforts in understanding metabolic diseases and the role of biochemical regulation in the cell.

Dataset Information

Tracing the Origin of the RSPO2 Long-Hair Allele and Epistatic Interaction between FGF5 and RSPO2 in Sapsaree Dog.

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