Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Deep Sequencing of Korean Jindo Dog Reveals Evolutionary Trajectory of Coat Color Variations


ABSTRACT: The inherent diversity of canines is closely intertwined with the unique color patterns of each dog population. These variations in color patterns are believed to have originated through mutations and selective breeding practices that occurred during and after the domestication of dogs from wolves. To address the significant gaps that persist in comprehending the evolutionary processes that underlie the development of these patterns, we generated and analyzed deep-sequenced genomes of 113 Korean indigenous Jindo dogs that represent five distinct color patterns to identify the associated mutations in CBD103, ASIP, and MC1R. The degree of linkage disequilibrium and estimated allelic ages consistently indicate that the black-and-tan dogs descend from the first major founding population on Jindo island, compatible with the documented literature. We additionally demonstrate that black-and-tan dogs, in contrast to other color variations within the breed, exhibit a closer genetic affinity to ancient wolves from western Eurasia than those from eastern Eurasia. Lastly, population-specific genetic variants with moderate effects were identified, particularly in loci associated with traits underlying body size and behavioral variations, potentially explaining the observed phenotypic diversity based on coat colors. Overall, comparisons of whole genome sequences of each coat color population diverged from the same breed provided an unprecedented glimpse into the properties of evolutionary processes maintaining variation in Korean Jindo dog populations that were previously inaccessible.

INSTRUMENT(S): Illumina NovaSeq 6000, -

ORGANISM(S): Canis lupus familiaris

SUBMITTER: Dayeon Kang 

PROVIDER: E-MTAB-13939 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

Similar Datasets

2013-12-26 | GSE53657 | GEO
2016-11-09 | GSE74225 | GEO
| PRJNA657492 | ENA
2013-12-26 | E-GEOD-53657 | biostudies-arrayexpress
2015-11-19 | GSE69040 | GEO
2014-11-20 | GSE63439 | GEO
2022-08-18 | GSE135963 | GEO
2018-01-17 | GSE86058 | GEO
2015-11-19 | E-GEOD-69040 | biostudies-arrayexpress
2015-07-30 | GSE70454 | GEO