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The Korean native horse (Jeju horse) is one of the most important animals in Korean historical, cultural, and economical viewpoints. In the early 1980s, the Jeju horse was close to extinction. The aim of this study is to explore the phylogenomics of Korean native horse focusing on spatio-temporal dynamics. We determined complete mitochondrial genome sequences for the first Korean native (n = 6) and additional Mongolian (n = 2) horses. Those sequences were analyzed together with 143 published ones using Bayesian coalescent approach as well as three different phylogenetic analysis methods, Bayesian inference, maximum likelihood, and neighbor-joining methods. The phylogenomic trees revealed that the Korean native horses had multiple origins and clustered together with some horses from four European and one Middle Eastern breeds. Our phylogenomic analyses also supported that there was no apparent association between breed or geographic location and the evolution of global horses. Time of the most recent common ancestor of the Korean native horse was approximately 13,200-63,200 years, which was much younger than 0.696 My of modern horses. Additionally, our results showed that all global horse lineages including Korean native horse existed prior to their domestication events occurred in about 6000-10,000 years ago. This is the first study on phylogenomics of the Korean native horse focusing on spatio-temporal dynamics. Our findings increase our understanding of the domestication history of the Korean native horses, and could provide useful information for horse conservation projects as well as for horse genomics, emergence, and the geographical distribution.

Objective Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. Methods This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

Previous studies in Holstein have shown 35% to 51.8% heritability in milk production traits, such as milk yield, fat, and protein, using pedigree data. Other studies in complex human traits could be captured by common single-nucleotide polymorphisms (SNPs), and their genetic variations, attributed to chromosomes, are in proportion to their length. Using genome-wide estimation and partitioning approaches, we analyzed three quantitative Holstein traits relevant to milk production in Korean Holstein data harvested from 462 individuals genotyped for 54,609 SNPs. For all three traits (milk yield, fat, and protein), we estimated a nominally significant (p = 0.1) proportion of variance explained by all SNPs on the Illumina BovineSNP50 Beadchip (h (2) G ). These common SNPs explained approximately most of the narrow-sense heritability. Longer genomic regions tended to provide more phenotypic variation information, with a correlation of 0.46~0.53 between the estimate of variance explained by individual chromosomes and their physical length. These results suggested that polygenicity was ubiquitous for Holstein milk production traits. These results will expand our knowledge on recent animal breeding, such as genomic selection in Holstein.

Milk-related traits (milk yield, fat and protein) have been crucial to selection of Holstein. It is essential to find the current selection trends of Holstein. Despite this, uncovering the current trends of selection have been ignored in previous studies. We suggest a new formula to detect the current selection trends based on single nucleotide polymorphisms (SNP). This suggestion is based on the best linear unbiased prediction (BLUP) and the Fisher's fundamental theorem of natural selection both of which are trait-dependent. Fisher's theorem links the additive genetic variance to the selection coefficient. For Holstein milk production traits, we estimated the additive genetic variance using SNP effect from BLUP and selection coefficients based on genetic variance to search highly selective SNPs. Through these processes, we identified significantly selective SNPs. The number of genes containing highly selective SNPs with p-value

The modern horse (Equus caballus) is the product of over 50 million yrs of evolution. The athletic abilities of the horse have been enhanced during the past 6000 yrs under domestication. Therefore, the horse serves as a valuable model to understand the physiology and molecular mechanisms of adaptive responses to exercise. The structure and function of skeletal muscle show remarkable plasticity to the physical and metabolic challenges following exercise. Here, we reveal an evolutionary layer of responsiveness to exercise-stress in the skeletal muscle of the racing horse. We analysed differentially expressed genes and their co-expression networks in a large-scale RNA-sequence dataset comparing expression before and after exercise. By estimating genome-wide d(N)/d(S) ratios using six mammalian genomes, and F-ST and iHS using re-sequencing data derived from 20 horses, we were able to peel back the evolutionary layers of adaptations to exercise-stress in the horse. We found that the oldest and thickest layer (d(N)/d(S)) consists of system-wide tissue and organ adaptations. We further find that, during the period of horse domestication, the older layer (F-ST) is mainly responsible for adaptations to inflammation and energy metabolism, and the most recent layer (iHS) for neurological system process, cell adhesion, and proteolysis.

Linkage disequilibrium between markers or genetic variants underlying interesting traits affects many genomic methodologies. In many genomic methodologies, the effective population size (N-e) is important to assess the genetic diversity of animal populations. In this study, dairy cattle were genotyped using the Illumina BovineHD Genotyping BeadChips for over 777,000 SNPs located across all autosomes, mitochondria and sex chromosomes, and 70,000 autosomal SNPs were selected randomly for the final analysis. We characterized more accurate linkage disequilibrium in a sample of 96 dairy cattle producing milk in Korea. Estimated linkage disequilibrium was relatively high between closely linked markers (>0.6 at 10 kb) and decreased with increasing distance. Using formulae. that related the expected linkage disequilibrium to N-e, and assuming a constant actual population size, N-e was estimated to be approximately 122 in this population. Historical N-e, calculated assuming linear population growth, was suggestive of a rapid increase N-e over the past 10 generations, and increased slowly thereafter. Additionally, we corrected the genomic relationship structure per chromosome in calculating r(2) and estimated N-e. The observed N-e based on r(2) corrected by genomics relationship structure can be rationalized using current knowledge of the history of the dairy cattle breeds producing milk in Korea.