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Animals : an open access journal from MDPI2024; 14(16); 2420; doi: 10.3390/ani14162420

Exploring the Genetic Landscape of Vitiligo in the Pura Raza Español Horse: A Genomic Perspective.

Abstract: Vitiligo is a depigmentation autoimmune disorder characterized by the progressive loss of melanocytes leading to the appearance of patchy depigmentation of the skin. The presence of vitiligo in horses is greater in those with grey coats. The aim of this study was therefore to perform a genome-wide association study (GWAS) to identify genomic regions and putative candidate loci associated with vitiligo depigmentation and susceptibility in the Pura Raza Español population. For this purpose, we performed a wssGBLUP (weighted single step genomic best linear unbiased prediction) using data from a total of 2359 animals genotyped with Affymetrix Axiom™ Equine 670 K and 1346 with Equine GeneSeek Genomic Profiler™ (GGP) Array V5. A total of 60,136 SNPs (single nucleotide polymorphisms) present on the 32 chromosomes from the consensus dataset after quality control were employed for the analysis. Vitiligo-like depigmentation was phenotyped by visual inspection of the different affected areas (eyes, mouth, nostrils) and was classified into nine categories with three degrees of severity (absent, slight, and severe). We identified one significant genomic region for vitiligo around the eyes, eight significant genomic regions for vitiligo around the mouth, and seven significant genomic regions for vitiligo around the nostrils, which explained the highest percentage of variance. These significant genomic regions contained candidate genes related to melanocytes, skin, immune system, tumour suppression, metastasis, and cutaneous carcinoma. These findings enable us to implement selective breeding strategies to decrease the incidence of vitiligo and to elucidate the genetic architecture underlying vitiligo in horses as well as the molecular mechanisms involved in the disease's development. However, further studies are needed to better understand this skin disorder in horses.
Publication Date: 2024-08-21 PubMed ID: 39199954PubMed Central: PMC11350783DOI: 10.3390/ani14162420Google Scholar: Lookup
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  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The study focuses on the genetic factors behind the appearance of vitiligo in the Pura Raza Español horse breed. The researchers performed genome-wide testing to identify potential genomic regions and related genes that could be associated with the development of vitiligo in these horses.

Study Design and Methods

The researchers used a weighted single step genomic best linear unbiased prediction (wssGBLUP) on data from 2359 horses genotyped with Affymetrix Axiom Equine 670 K and 1346 with Equine GeneSeek Genomic Profiler (GGP) Array V5. This was done to:

  • Perform a comprehensive survey of the genetic material.
  • Identify specific single nucleotide polymorphisms (SNPs, or genetic variations) which can indicate potential genes impacting disease susceptibility.

Vitiligo-like skin changes in these horses were classified based on the visual inspection of affected areas (eyes, mouth, nostrils), divided into nine categories with varying severity levels.

Findings and Implications

After performing the genomic analysis, the authors identified key genomic regions associated with vitiligo around the eyes, mouth, and nostrils. These regions contribute to the highest variance percentage, implying they likely play a significant role in the development of vitiligo.

The identified regions contain candidate genes connected mainly to melanocytes (skin cells producing pigment), skin health, the immune system, tumour suppression, metastasis, and a type of skin cancer. This discovery:

  • Allows for the possibility of selective breeding strategies.
  • Helps in understanding the genetic architecture and molecular mechanics related to vitiligo in horses.

The researchers proposed that further studies are required for better comprehension of this skin disorder in horses.

Research Limitations

While the findings are significant, they are limited by certain factors:

  • The study is based on categorizing severity visually, which may have some subjective interpretations.
  • The study does not definitively prove that these genetic factors cause vitiligo; it only establishes a pattern of association.
  • Further research is needed to validate these findings and understand in more depth the role these genes play in vitiligo genesis.

Cite This Article

APA
Laseca N, Molina A, Perdomo-González D, Ziadi C, Azor PJ, Valera M. (2024). Exploring the Genetic Landscape of Vitiligo in the Pura Raza Español Horse: A Genomic Perspective. Animals (Basel), 14(16), 2420. https://doi.org/10.3390/ani14162420

Publication

ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 14
Issue: 16
PII: 2420

Researcher Affiliations

Laseca, Nora
  • Departamento de Agronomía, Escuela Técnica Superior de Ingeniería Agronómica, Universidad de Sevilla, Ctra. Utrera Km 1, 41013 Sevilla, Spain.
  • Real Asociación Nacional de Criadores de Caballos de Pura Raza Española (ANCCE), Cortijo de Cuarto (Viejo), 41014 Sevilla, Spain.
Molina, Antonio
  • Departamento de Genética, Universidad de Córdoba, Ctra. Madrid Km 396, 44014 Córdoba, Spain.
Perdomo-González, Davinia
  • Departamento de Agronomía, Escuela Técnica Superior de Ingeniería Agronómica, Universidad de Sevilla, Ctra. Utrera Km 1, 41013 Sevilla, Spain.
Ziadi, Chiraz
  • Departamento de Genética, Universidad de Córdoba, Ctra. Madrid Km 396, 44014 Córdoba, Spain.
Azor, Pedro J
  • Real Asociación Nacional de Criadores de Caballos de Pura Raza Española (ANCCE), Cortijo de Cuarto (Viejo), 41014 Sevilla, Spain.
Valera, Mercedes
  • Departamento de Agronomía, Escuela Técnica Superior de Ingeniería Agronómica, Universidad de Sevilla, Ctra. Utrera Km 1, 41013 Sevilla, Spain.

Grant Funding

  • PRJ202304941 / Contrato FIUS - ANCCE

Conflict of Interest Statement

The authors declare no conflicts of interest.

References

This article includes 49 references
  1. Taieb A, Alomar A, Böhm M, Dell’Anna M.L, De Pase A, Eleftheriadou V, Ezzedine K, Gauthier Y, Gawkrodger D.J, Jouary T. Guidelines for the management of vitiligo: The European Dermatology Forum consensus.. Br. J. Dermatol. 2013;168:5–19.
  2. Mohammed G.F, Gomaa A.H, Al-Dhubaibi M.S. Highlights in pathogenesis of vitiligo.. World J. Clin. Cases 2015;3:221–230.
    doi: 10.12998/wjcc.v3.i3.221pmc: PMC4360494pubmed: 25789295google scholar: lookup
  3. Bibeau K, Pandya A.G, Ezzedine K, Jones H, Gao J, Lindley A, Harris J.E. Vitiligo prevalence and quality of life among adults in Europe, Japan and the USA.. J. Eur. Acad. Dermatol. Venereol. 2022;36:1831–1844.
    doi: 10.1111/jdv.18257pmc: PMC9544885pubmed: 35611638google scholar: lookup
  4. Tham H.L, Linder K.E, Olivry T. Autoimmune diseases affecting skin melanocytes in dogs, cats and horses: Vitiligo and the uveodermatological syndrome: A comprehensive review.. BMC Vet. Res. 2019;15:251.
    doi: 10.1186/s12917-019-2003-9pmc: PMC6639964pubmed: 31324191google scholar: lookup
  5. Lindgren G, Naboulsi R, Frey R, Solé M. Genetics of Skin Disease in Horses.. Vet. Clin. N. Am. Equine Pract. 2020;36:323–339.
    doi: 10.1016/j.cveq.2020.03.010pubmed: 32534850google scholar: lookup
  6. Sánchez-Guerrero M.J, Solé M, Azor P.J, Sölkner J, Valera M. Genetic and environmental risk factors for vitiligo and melanoma in Pura Raza Español horses.. Equine Vet. J. 2019;51:606–611.
    doi: 10.1111/evj.13067pubmed: 30624804google scholar: lookup
  7. Druml T, Brem G, Velie B, Lindgren G, Horna M, Ricard A, Grilz-Seger G. Equine vitiligo-like depigmentation in grey horses is related to genes involved in immune response and tumor metastasis.. BMC Vet. Res. 2021;17:336.
    doi: 10.1186/s12917-021-03046-xpmc: PMC8543801pubmed: 34696794google scholar: lookup
  8. Curik I, Druml T, Seltenhammer M, Sundström E, Pielberg G.R, Andersson L, Sölkner J. Complex Inheritance of Melanoma and Pigmentation of Coat and Skin in Grey Horses.. PLoS Genet. 2013;9:e1003248.
  9. Shen C, Gao J, Sheng Y, Dou J, Zhou F, Zheng X, Ko R, Tang X, Zhu C, Yin X. Genetic Susceptibility to Vitiligo: GWAS Approaches for Identifying Vitiligo Susceptibility Genes and Loci.. Front. Genet. 2016;7:3.
    doi: 10.3389/fgene.2016.00003pmc: PMC4740779pubmed: 26870082google scholar: lookup
  10. Gupta I, Narang A, Singh P, Manchanda V, Khanna S, Mukerji M, Natarajan V.T, Dash D. VitiVar: A locus specific database of vitiligo associated genes and variations.. Gene. 2019;721:100018.
    doi: 10.1016/j.gene.2019.100018pubmed: 34530999google scholar: lookup
  11. Jin Y, Andersen G, Yorgov D, Ferrara T.M, Ben S, Brownson K.M, Holland P.J, Birlea S.A, Siebert J, Hartmann A. Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants.. Nat. Genet. 2016;48:1418–1424.
    doi: 10.1038/ng.3680pmc: PMC5120758pubmed: 27723757google scholar: lookup
  12. Lei Z, Yu S, Ding Y, Liang J, Halifu Y, Xiang F, Zhang D, Wang H, Hu W, Li T. Identification of key genes and pathways involved in vitiligo development based on integrated analysis.. Medicine. 2020;99:e21297.
    doi: 10.1097/md.0000000000021297pmc: PMC7402735pubmed: 32756109google scholar: lookup
  13. Dutta T, Mitra S, Saha A, Ganguly K, Pyne T, Sengupta M. A comprehensive meta-analysis and prioritization study to identify vitiligo associated coding and non-coding SNV candidates using web-based bioinformatics tools.. Sci. Rep. 2022;12:14543.
    doi: 10.1038/s41598-022-18766-9pmc: PMC9411560pubmed: 36008553google scholar: lookup
  14. Cheng L, Liang B, Tang X.-F, Cai X.-Y, Cheng H, Zheng X.-D, Zheng J, Wang M.-W, Zhu J, Zhou F.-S. Validation of Susceptibility Loci for Vitiligo Identified by GWAS in the Chinese Han Population.. Front. Genet. 2020;11:542275.
    doi: 10.3389/fgene.2020.542275pmc: PMC7744663pubmed: 33343616google scholar: lookup
  15. Montes L.F, Wilborn W.H, Hyde B.M, Vaughan J.T, Bennett J.S. Vitiligo in a Quarter Horse Filly: Clinicopathologic, Ultrastructural, and Nutritional Study.. J. Equine Vet. Sci. 2008;28:171–175.
  16. Hofmanova B, Vostry L, Majzlik I, Vostra-Vydrova H. Characterization of greying, melanoma, and vitiligo quantitative inheritance in Old Kladruber horses.. Czech J. Anim. Sci. 2015;60:443–451.
  17. Solé M, Valera M, Sánchez M.J, Azor P.J, Fernández J. Drawbacks and consequences of selective strategies in the design of semen banks: Case study of the Pura Raza Español horse breed.. Livest. Sci. 2019;226:93–98.
  18. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M.A.R, Bender D, Maller J, Sklar P, de Bakker P.I.W, Daly M.J. PLINK: A tool set for whole-genome association and population-based linkage analyses.. Am. J. Hum. Genet. 2007;81:559–575.
    doi: 10.1086/519795pmc: PMC1950838pubmed: 17701901google scholar: lookup
  19. Aguilar I, Misztal I, Johnson D.L, Legarra A, Tsuruta S, Lawlor T.J. Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score1.. J. Dairy Sci. 2010;93:743–752.
    doi: 10.3168/jds.2009-2730pubmed: 20105546google scholar: lookup
  20. VanRaden P.M. Efficient Methods to Compute Genomic Predictions.. J. Dairy Sci. 2008;91:4414–4423.
    doi: 10.3168/jds.2007-0980pubmed: 18946147google scholar: lookup
  21. Wang H, Misztal I, Aguilar I, Legarra A, Muir W.M. Genome-wide association mapping including phenotypes from relatives without genotypes.. Genet. Res. 2012;94:73–83.
    doi: 10.1017/S0016672312000274pubmed: 22624567google scholar: lookup
  22. Misztal I, Tsuruta S, Lourenco D, Masuda Y, Aguilar I, Legarra A, Vitezica Z. Manual for BLUPF90 Family of Programs.. University of Georgia; Athens, GA, USA: 2016.
  23. Kinsella R.J, Kähäri A, Haider S, Zamora J, Proctor G, Spudich G, Almeida-King J, Staines D, Derwent P, Kerhornou A. Ensembl BioMarts: A hub for data retrieval across taxonomic space.. Database. 2011;2011:bar030.
    doi: 10.1093/database/bar030pmc: PMC3170168pubmed: 21785142google scholar: lookup
  24. Sherman B.T, Hao M, Qiu J, Jiao X, Baseler M.W, Lane H.C, Imamichi T, Chang W. DAVID: A web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res. 2022;50:W216–W221.
    doi: 10.1093/nar/gkac194pmc: PMC9252805pubmed: 35325185google scholar: lookup
  25. Carbon S, Ireland A, Mungall C.J, Shu S, Marshall B, Lewis S, the AmiGO Hub, the Web Presence Working Group. AmiGO: Online access to ontology and annotation data.. Bioinformatics. 2009;25:288–289.
  26. VanRaden P.M, Tooker M.E, O’Connell J.R, Cole J.B, Bickhart D.M. Selecting sequence variants to improve genomic predictions for dairy cattle.. Genet. Sel. Evol. 2017;49:32.
    doi: 10.1186/s12711-017-0307-4pmc: PMC5339980pubmed: 28270096google scholar: lookup
  27. Encina A, Valera M, Ligero M, Rodriguez Sainz de los Terreros A, Sánchez-Guerrero M.J. Characterisation of white facial markings in Pura Raza Española horses (a worldwide population genetic study). Ital. J. Anim. Sci. 2024;23:929–937.
  28. Encina A, Ligero M, Sánchez-Guerrero M.J, Rodríguez-Sainz de los Terreros A, Bartolomé E, Valera M. Phenotypic and Genetic Study of the Presence of Hair Whorls in Pura Raza Español Horses.. Animals. 2023;13:2943.
    doi: 10.3390/ani13182943pmc: PMC10525084pubmed: 37760344google scholar: lookup
  29. McCreery M.Q, Halliwill K.D, Chin D, Delrosario R, Hirst G, Vuong P, Jen K.-Y, Hewinson J, Adams D.J, Balmain A. Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers.. Nat. Med. 2015;21:1514–1520.
    doi: 10.1038/nm.3979pmc: PMC5094808pubmed: 26523969google scholar: lookup
  30. Yang C, Georgiou M, Atkinson R, Collin J, Al-Aama J, Nagaraja-Grellscheid S, Johnson C, Ali R, Armstrong L, Mozaffari-Jovin S. Pre-mRNA Processing Factors and Retinitis Pigmentosa: RNA Splicing and Beyond.. Front. Cell Dev. Biol. 2021;9:700276.
    doi: 10.3389/fcell.2021.700276pmc: PMC8355544pubmed: 34395430google scholar: lookup
  31. Loftus S.K, Baxter L.L, Cronin J.C, Fufa T.D, Program N.C.S, Pavan W.J. Hypoxia-induced HIF1α targets in melanocytes reveal a molecular profile associated with poor melanoma prognosis.. Pigment Cell Melanoma Res. 2017;30:339–352.
    doi: 10.1111/pcmr.12579pmc: PMC5411287pubmed: 28168807google scholar: lookup
  32. Bosch P.J, Peek S.L, Smolikove S, Weiner J.A. Akirin proteins in development and disease: Critical roles and mechanisms of action.. Cell. Mol. Life Sci. 2020;77:4237–4254.
    doi: 10.1007/s00018-020-03531-wpmc: PMC7606436pubmed: 32361777google scholar: lookup
  33. Briard B, Place D.E, Kanneganti T.-D. DNA Sensing in the Innate Immune Response.. Physiology. 2020;35:112–124.
    doi: 10.1152/physiol.00022.2019pmc: PMC7276919pubmed: 32027562google scholar: lookup
  34. Valdivia-Silva J, Ramírez Díaz C. Melanocytes in vitiligo and melanoma: A lesson between autoimmunity and tumor immunity.. Dermatol. Peru. 2013;23:155–162.
  35. Huang Y, Wang Y, Wang Y, Wang N, Duan Q, Wang S, Liu M, Bilal M.A, Zheng Y. LPCAT1 Promotes Cutaneous Squamous Cell Carcinoma via EGFR-Mediated Protein Kinase B/p38MAPK Signaling Pathways.. J. Investig. Dermatol. 2022;142:303–313.e9.
    doi: 10.1016/j.jid.2021.07.163pubmed: 34358528google scholar: lookup
  36. Choquet H, Jiang C, Yin J, Kim Y, Hoffmann T.J, Aslibekyan S, Auton A, Babalola E, Bell R.K, Bielenberg J. Multi-ancestry genome-wide meta-analysis identifies novel basal cell carcinoma loci and shared genetic effects with squamous cell carcinoma.. Commun. Biol. 2024;7:33.
    doi: 10.1038/s42003-023-05753-7pmc: PMC10770328pubmed: 38182794google scholar: lookup
  37. Maloberti T, De Leo A, Coluccelli S, Sanza V, Gruppioni E, Altimari A, Comito F, Melotti B, Marchese P.V, Dika E. Molecular Characterization of Advanced-Stage Melanomas in Clinical Practice Using a Laboratory-Developed Next-Generation Sequencing Panel.. Diagnostics. 2024;14:800.
  38. Lu W, Mengxuan Z, Ming R, Zixu G, Yong Z, Simin Z, Yang Y, Leqi Q, Kangjie S, Yanlin L. TRIP13/FLNA Complex Promotes Tumor Progression and Is Associated with Unfavorable Outcomes in Melanoma.. J. Oncol. 2022;2022:1419179.
    doi: 10.1155/2022/1419179pmc: PMC9578791pubmed: 36268276google scholar: lookup
  39. Mason L.D, Chava S, Reddi K.K, Gupta R. The BRD9/7 Inhibitor TP-472 Blocks Melanoma Tumor Growth by Suppressing ECM-Mediated Oncogenic Signaling and Inducing Apoptosis.. Cancers. 2021;13:5516.
    doi: 10.3390/cancers13215516pmc: PMC8582741pubmed: 34771678google scholar: lookup
  40. Dreier M.R, de la Serna I.L. SWI/SNF Chromatin Remodeling Enzymes in Melanoma.. Epigenomes. 2022;6:10.
    doi: 10.3390/epigenomes6010010pmc: PMC8947417pubmed: 35323214google scholar: lookup
  41. Hazane F, Valenti K, Sauvaigo S, Peinnequin A, Mouret C, Favier A, Beani J.-C. Ageing effects on the expression of cell defence genes after UVA irradiation in human male cutaneous fibroblasts using cDNA arrays.. J. Photochem. Photobiol. B Biol. 2005;79:171–190.
  42. Liu J, Rebecca V.W, Kossenkov A.V, Connelly T, Liu Q, Gutierrez A, Xiao M, Li L, Zhang G, Samarkina A. Neural Crest-Like Stem Cell Transcriptome Analysis Identifies LPAR1 in Melanoma Progression and Therapy Resistance.. Cancer Res. 2021;81:5230–5241.
  43. Kim D, Khin P.P, Lim O.K, Jun H.-S. LPA/LPAR1 signaling induces PGAM1 expression via AKT/mTOR/HIF-1α pathway and increases aerobic glycolysis, contributing to keratinocyte proliferation.. Life Sci. 2022;311:121201.
    doi: 10.1016/j.lfs.2022.121201pubmed: 36400203google scholar: lookup
  44. Bharadwaj R, Lusi C.F, Mashayekh S, Nagar A, Subbarao M, Kane G.I, Wodzanowski K.A, Brown A.R, Okuda K, Monahan A. Methotrexate suppresses psoriatic skin inflammation by inhibiting muropeptide transporter SLC46A2 activity.. Immunity. 2023;56:998–1012.e8.
  45. Ahmed M.B, Islam S.U, Lee Y.S. PRP4 Promotes Skin Cancer by Inhibiting Production of Melanin, Blocking Influx of Extracellular Calcium, and Remodeling Cell Actin Cytoskeleton.. Int. J. Mol. Sci. 2021;22:6992.
    doi: 10.3390/ijms22136992pmc: PMC8268783pubmed: 34209674google scholar: lookup
  46. Liu Y, Wang Z, De La Torre R, Barling A, Tsujikawa T, Hornick N, Hanifin J, Simpson E, Wang Y, Swanzey E. Trim32 Deficiency Enhances Th2 Immunity and Predisposes to Features of Atopic Dermatitis.. J. Investig. Dermatol. 2017;137:359–366.
    doi: 10.1016/j.jid.2016.09.020pmc: PMC5258687pubmed: 27720760google scholar: lookup
  47. Ono C, Yu Z, Kasahara Y, Kikuchi Y, Ishii N, Tomita H. Fluorescently Activated Cell Sorting Followed by Microarray Profiling of Helper T Cell Subtypes from Human Peripheral Blood.. PLoS ONE. 2014;9:e111405.
  48. Pośpiech E, Kukla-Bartoszek M, Karłowska-Pik J, Zieliński P, Woźniak A, Boroń M, Dąbrowski M, Zubańska M, Jarosz A, Grzybowski T. Exploring the possibility of predicting human head hair greying from DNA using whole-exome and targeted NGS data.. BMC Genom. 2020;21:538.
    doi: 10.1186/s12864-020-06926-ypmc: PMC7430834pubmed: 32758128google scholar: lookup
  49. Min J, Zaslavsky A, Fedele G, McLaughlin S.K, Reczek E.E, De Raedt T, Guney I, Strochlic D.E, MacConaill L.E, Beroukhim R. An oncogene–tumor suppressor cascade drives metastatic prostate cancer by coordinately activating Ras and nuclear factor-κB.. Nat. Med. 2010;16:286–294.
    doi: 10.1038/nm.2100pmc: PMC2903662pubmed: 20154697google scholar: lookup

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