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http://dx.doi.org/10.5713/ajas.17.0460

Analysis of cross-population differentiation between Thoroughbred and Jeju horses  

Lee, Wonseok (Department of Agricultural Biotechnology, Animal Biotechnology, and Research Institute of Agriculture and Life Sciences, Seoul National University)
Park, Kyung-Do (Department of Animal Biotechnology, College of Agricultural and Life Sciences, Chonbuk National University)
Taye, Mengistie (Department of Agricultural Biotechnology, Animal Biotechnology, and Research Institute of Agriculture and Life Sciences, Seoul National University)
Lee, Chul (Interdisciplinary Program in Bioinformatics, Seoul National University)
Kim, Heebal (Department of Agricultural Biotechnology, Animal Biotechnology, and Research Institute of Agriculture and Life Sciences, Seoul National University)
Lee, Hak-Kyo (Department of Animal Biotechnology, College of Agricultural and Life Sciences, Chonbuk National University)
Shin, Donghyun (Department of Animal Biotechnology, College of Agricultural and Life Sciences, Chonbuk National University)
Publication Information
Asian-Australasian Journal of Animal Sciences / v.31, no.8, 2018 , pp. 1110-1118 More about this Journal
Abstract
Objective: This study was intended to identify genes positively selected in Thoroughbred horses (THBs) that potentially contribute to their running performances. Methods: The genomes of THB and Jeju horses (JH, Korean native horse) were compared to identify genes positively selected in THB. We performed cross-population extended haplotype homozygosity (XP-EHH) and cross-population composite likelihood ratio test (XP-CLR) statistical methods for our analysis using whole genome resequencing data of 14 THB and 6 JH. Results: We identified 98 (XP-EHH) and 200 (XP-CLR) genes that are under positive selection in THB. Gene enrichment analysis identified 72 gene ontology biological process (GO BP) terms. The genes and GO BP terms explained some of THB's characteristics such as immunity, energy metabolism and eye size and function related to running performances. GO BP terms that play key roles in several cell signaling mechanisms, which affected ocular size and visual functions were identified. GO BP term Eye photoreceptor cell differentiation is among the terms annotated presumed to affect eye size. Conclusion: Our analysis revealed some positively selected candidate genes in THB related to their racing performances. The genes detected are related to the immunity, ocular size and function, and energy metabolism.
Keywords
Eye; Positive Selection; Thoroughbred; XP-CLR; XP-EHH;
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1 Howland HC, Merola S, Basarab JR. The allometry and scaling of the size of vertebrate eyes. Vision Res 2004;44:2043-65.   DOI
2 Heard-Booth AN, Kirk EC. The influence of maximum running speed on eye size: a test of Leuckart's Law in mammals. Anat Rec 2012;295:1053-62.   DOI
3 Chen H, Patterson N, Reich D. Population differentiation as a test for selective sweeps. Genome Res 2010;20:393-402.   DOI
4 Ohshima T. Neuronal migration and protein kinases. Front Neurosci 2014;8:458.
5 Quach TT, Wilson SM, Rogemond V, et al. Mapping CRMP3 domains involved in dendrite morphogenesis and voltage-gated calcium channel regulation. J Cell Sci 2013;126:4262-73.   DOI
6 Dalva MB, Takasu MA, Lin MZ, et al. EphB receptors interact with NMDA receptors and regulate excitatory synapse formation. Cell 2000;103:945-56.   DOI
7 Zerial M, McBride H. Rab proteins as membrane organizers. Nat Rev Mol Cell Biol 2001;2:107-17.   DOI
8 Waites CL, Craig AM, Garner CC. Mechanisms of vertebrate synaptogenesis. Annu Rev Neurosci 2005;28:251-74.   DOI
9 Puigserver P, Spiegelman BM. Peroxisome proliferator-activated receptor-${\gamma}$ coactivator $1{\alpha}$ (PGC-$1{\alpha}$): transcriptional coactivator and metabolic regulator. Endocr Rev 2003;24:78-90.   DOI
10 Sharma A, Huard C, Vernochet C, et al. Brown fat determination and development from muscle precursor cells by novel action of bone morphogenetic protein 6. PloS One 2014;9:e92608.   DOI
11 Laurie GW, Olsakovsky LA, Conway BP, et al. Dry eye and designer ophthalmics. Optom Vis Sci 2008;85:643-52.   DOI
12 Jan Y-N, Jan LY. The control of dendrite development. Neuron 2003;40:229-42.   DOI
13 Kim K, Yang YH, Lee SS, et al. Phylogenetic relationships of Cheju horses to other horse breeds as determined by mtDNA D-loop sequence polymorphism. Anim Genet 1999;30:102-8.   DOI
14 Ma Y, Zhang H, Zhang Q, Ding X. Identification of selection footprints on the X chromosome in pig. PLoS One 2014;9:e94911.   DOI
15 Park W, Kim J, Kim H, et al. Investigation of de novo unique differentially expressed genes related to evolution in exercise. PLoS One 2014;9:e91418.   DOI
16 Sabeti PC, Varilly P, Fry B, et al. Genome-wide detection and characterization of positive selection in human populations. Nature 2007;449:913-8.   DOI
17 Chang-Yeon C, Sung-Heum Y, Byung-Wook C, and Gil-Jae C. Genetic characterization and polymorphisms for parentage testing of the Jeju horse using 20 microsatellite loci. J Vet Med Sci 2008;70:1111-5.   DOI
18 McKenna A, Hanna M, Banks E, et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010;20:1297-303.   DOI
19 Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012;9:357-9.   DOI
20 Li H, Handsaker B, Wysoker A, et al. The sequence alignment/map format and SAMtools. Bioinformatics 2009;25:2078-9.   DOI
21 Browning SR, Browning BL. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet 2007;81:1084-97.   DOI
22 Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 2011;88:76-82.   DOI
23 Price AL, Patterson NJ, Plenge RM, et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 2006;38:904-9.   DOI
24 Ricard A, Bruns E, Cunningham E. Genetics of performance traits. The genetics of the horse. Wallingford, UK: CABI Publishing; 2000. pp. 411-538.
25 Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559-75.   DOI
26 Pickrell JK, Pritchard JK. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet 2012;8:e1002967.   DOI
27 Lee H-J, Kim J, Lee T, et al. Deciphering the genetic blueprint behind Holstein milk proteins and production. Genome Biol Evol 2014;6:1366-74.   DOI
28 Bindea G, Mlecnik B, Hackl H, et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 2009;25:1091-3.   DOI
29 Cho G-J. Genetic relationship and characteristics using microsatellite DNA loci in horse breeds. J Life Sci 2007;17:699-705.   DOI
30 Kelley JL, Madeoy J, Calhoun JC, Swanson W, Akey JM. Genomic signatures of positive selection in humans and the limits of outlier approaches. Genome Res 2006;16:980-9.   DOI
31 Evans DT, Serra-Moreno R, Singh RK, Guatelli JC. BST-2/tetherin: a new component of the innate immune response to enveloped viruses. Trends Microbiol 2010;18:388-96.   DOI
32 Yin X, Guo M, Gu Q, et al. Antiviral potency and functional analysis of tetherin orthologues encoded by horse and donkey. Virol J 2014;11:151.   DOI
33 O'Leary NA, Wright MW, Brister JR, et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res 2016;44:D733-D45.   DOI
34 Moon S, Lee JW, Shin D, et al. A genome-wide scan for selective sweeps in racing horses. Asian-Australas J Anim Sci 2015;28:1525-31.   DOI
35 Montgomery ES. The Thoroughbred. London, UK: Thomas Yoseloff Ltd.; 1971.
36 Gu J, Orr N, Park SD, et al. A genome scan for positive selection in thoroughbred horses. PloS one 2009;4:e5767.   DOI
37 Hinchcliff KW, Kaneps AJ, and Geor RJ. Equine exercise physiology: the science of exercise in the athletic horse. Melbourne, Australia: Elsevier Health Sciences; 2008.