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Scientific reports2018; 8(1); 6374; doi: 10.1038/s41598-018-24865-3

An epistatic effect of KRT25 on SP6 is involved in curly coat in horses.

Abstract: Curly coat represents an extraordinary type of coat in horses, particularly seen in American Bashkir Curly Horses and Missouri Foxtrotters. In some horses with curly coat, a hypotrichosis of variable extent was observed, making the phenotype appear more complex. In our study, we aimed at investigating the genetic background of curly coat with and without hypotrichosis using high density bead chip genotype and next generation sequencing data. Genome-wide association analysis detected significant signals (p = 1.412 × 10-05-1.102 × 10-08) on horse chromosome 11 at 22-35 Mb. In this significantly associated region, six missense variants were filtered out from whole-genome sequencing data of three curly coated horses of which two variants within KRT25 and SP6 could explain all hair phenotypes. Horses heterozygous or homozygous only for KRT25 variant showed curly coat and hypotrichosis, whereas horses with SP6 variant only, exhibited curly coat without hypotrichosis. Horses with mutant alleles in both variants developed curly hair and hypotrichosis. Thus, mutant KRT25 allele is masking SP6 allele effect, indicative for epistasis of KRT25 variant over SP6 variant. In summary, genetic variants in two different genes, KRT25 and SP6, are responsible for curly hair. All horses with KRT25 variant are additionally hypotrichotic due to the KRT25 epistatic effect on SP6.
Publication Date: 2018-04-23 PubMed ID: 29686323PubMed Central: PMC5913262DOI: 10.1038/s41598-018-24865-3Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't

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 provides deep insights into the genetic factors causing the curly coat appearance in horses, particularly found in American Bashkir Curly Horses and Missouri Foxtrotters. Through the use of genome-wide sequencing, the researchers identify variants in two specific genes, KRT25 and SP6, that contribute to this phenotype.

Background

  • The research investigates the genetic background of the curly coat phenotype in horses, a peculiar coat texture observed predominantly in American Bashkir Curly Horses and Missouri Foxtrotters. Some of these horses also show hypotrichosis, a condition characterized by lesser hair than usual, adding complexity to the phenotype.

Methods

  • Researchers used high density bead chip genotype and next generation sequencing data to explore the genetic cause of this distinctive coat texture.
  • A genome-wide association analysis was conducted, which produced significant signals in a certain region on horse chromosome 11.

Findings

  • From the significantly associated region, six missense variants were sifted out from the genome sequencing data of three curly coated horses. Out of these six, two variants within KRT25 and SP6 were found to explain all hair phenotypes.
  • Horses only carrying the KRT25 variant showed both curly coat and hypotrichosis, while those only carrying the SP6 variant demonstrated curly coat but without hypotrichosis.
  • Horses carrying mutant alleles in both genes manifested both curly hair and hypotrichosis. This suggests that the mutant KRT25 allele masks the effect of the SP6 allele, indicative of an epistasis of the KRT25 variant over the SP6 variant.

Conclusion

  • The findings suggest that genetic variants in both KRT25 and SP6 genes are responsible for the formation of curly hair in horses.
  • Horses carrying the KRT25 variant also exhibit hypotrichosis due to a dominant effect of the KRT25 gene over SP6, referred to as the KRT25 epistatic effect on SP6.

Cite This Article

APA
Thomer A, Gottschalk M, Christmann A, Naccache F, Jung K, Hewicker-Trautwein M, Distl O, Metzger J. (2018). An epistatic effect of KRT25 on SP6 is involved in curly coat in horses. Sci Rep, 8(1), 6374. https://doi.org/10.1038/s41598-018-24865-3

Publication

ISSN: 2045-2322
NlmUniqueID: 101563288
Country: England
Language: English
Volume: 8
Issue: 1
Pages: 6374

Researcher Affiliations

Thomer, Annika
  • Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover Foundation, Hannover, 30559, Germany.
Gottschalk, Maren
  • Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover Foundation, Hannover, 30559, Germany.
Christmann, Anna
  • Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover Foundation, Hannover, 30559, Germany.
Naccache, Fanny
  • Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover Foundation, Hannover, 30559, Germany.
Jung, Klaus
  • Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover Foundation, Hannover, 30559, Germany.
Hewicker-Trautwein, Marion
  • Department of Pathology, University of Veterinary Medicine Hannover Foundation, Hannover, 30559, Germany.
Distl, Ottmar
  • Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover Foundation, Hannover, 30559, Germany. ottmar.distl@tiho-hannover.de.
Metzger, Julia
  • Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover Foundation, Hannover, 30559, Germany.

MeSH Terms

  • Animal Fur / chemistry
  • Animals
  • Chromosomes, Mammalian
  • Epistasis, Genetic
  • Genome-Wide Association Study
  • Genotype
  • High-Throughput Nucleotide Sequencing
  • Horses / genetics
  • Horses / physiology
  • Hypotrichosis / genetics
  • Keratins, Hair-Specific / genetics
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Sp Transcription Factors / genetics

Conflict of Interest Statement

The authors declare no competing interests.

References

This article includes 69 references
  1. Ludwig A. Coat color variation at the beginning of horse domestication. Science 2009;324:485.
    doi: 10.1126/science.1172750pmc: PMC5102060pubmed: 19390039google scholar: lookup
  2. Outram AK. The earliest horse harnessing and milking. Science 2009;323:1332–1335.
    doi: 10.1126/science.1168594pubmed: 19265018google scholar: lookup
  3. Petersen JL. Genome-wide analysis reveals selection for important traits in domestic horse breeds. PLoS Genet 2013;9:e1003211.
  4. Mitlehner W. Allergy against horses. Are curly horses an alternative for horse-allergic riders. Allergo J 2013;22:244–251.
  5. Blakeslee L, Hudson R, Hunt H. Curly coat of horses. J. Hered. 1943;34:115–118.
  6. Shchekin V, Kalaev V. Inheritance of curliness in the horse. Dokl. Akad. Nauk SSSR 1940;26:262–263.
  7. Scott D. Skin of the neck, mane and tail of the curly horse. Equine Veterinary Education 2004;16:201–206.
  8. Bowling A, Alderson L. Population genetics of curly horses. Gent. cons. dom. livest. 186–202 (1990).
  9. Sponenberg D. Dominant curly coat in horses. Genet Select Evol 1990;22:1.
    doi: 10.1186/1297-9686-22-1-1google scholar: lookup
  10. Thomas S, Alderson L. The Curly Horse identification project of the CS fund conservancy (a case study). Gent. cons. dom. livest. 154–159 (CAB International, 1990).
  11. Gandolfi B. The naked truth: Sphynx and Devon Rex cat breed mutations in KRT71. Mamm. Genome 2010;21:509–515.
    doi: 10.1007/s00335-010-9290-6pmc: PMC2974189pubmed: 20953787google scholar: lookup
  12. Gandolfi B. To the root of the curl: a signature of a recent selective sweep identifies a mutation that defines the Cornish Rex cat breed. PLoS ONE 2013;8:e67105.
  13. Daetwyler HD. Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle. Nat. Genet. 2014;46:858–865.
    doi: 10.1038/ng.3034pubmed: 25017103google scholar: lookup
  14. Cadieu E. Coat variation in the domestic dog is governed by variants in three genes. Science 2009;326:150–153.
    doi: 10.1126/science.1177808pmc: PMC2897713pubmed: 19713490google scholar: lookup
  15. Kuramoto T, Hirano R, Kuwamura M, Serikawa T. Identification of the rat Rex mutation as a 7-bp deletion at splicing acceptor site of the Krt71 gene. J Vet Med Sci 2010;72:909–912.
    doi: 10.1292/jvms.09-0554pubmed: 20179389google scholar: lookup
  16. Ishikawa A, Hirunagi K, Oda S, Namikawa T, Tomita T. Kinky coat, a new autosomal recessive mutation in the musk shrew, Suncus murinus. Jikken dobutsu. Experimental animals 1992;41:203–214.
    doi: 10.1538/expanim1978.41.2_203pubmed: 1577081google scholar: lookup
  17. Diribarne M. A deletion in exon 9 of the LIPH gene is responsible for the rex hair coat phenotype in rabbits (Oryctolagus cuniculus). PLoS ONE 2011;6:e19281.
  18. Rhoad A. Woolly hair in swine. J. Hered. 1934;25:371–375.
  19. Thibaut S, Gaillard O, Bouhanna P, Cannell D, Bernard B. Human hair shape is programmed from the bulb. Br J Dermatol 2005;152:632–638.
  20. Gandolfi B. A splice variant in KRT71 is associated with curly coat phenotype of Selkirk Rex cats. Sci. Rep-UK 2013.
    pmc: PMC3683669pubmed: 23770706
  21. Crew F, Auerbach C. Rex: a dominant autosomal monogenic coat texture character in the mouse. J. Genet. 1939;38:341–344.
    doi: 10.1007/BF02982178google scholar: lookup
  22. Kikkawa Y. A small deletion hotspot in the type II keratin gene mK6irs1/Krt2-6g on mouse chromosome 15, a candidate for causing the wavy hair of the caracul (Ca) mutation. Genetics 2003;165:721–733.
    pmc: PMC1462786pubmed: 14573483
  23. Johansson I. Reduced phalanges and curly coat: Two mutant characters in native swedish cattle. Hereditas 1942;28:278–288.
  24. Kjaer KW. Novel Connexin 43 (GJA1) mutation causes oculo–dento–digital dysplasia with curly hair. American Journal of Medical Genetics Part A 2004;127:152–157.
    doi: 10.1002/ajmg.a.20614pubmed: 15108203google scholar: lookup
  25. Shimomura Y. Disruption of P2RY5, an orphan G protein–coupled receptor, underlies autosomal recessive woolly hair. Nat. Genet. 2008;40:335–339.
    doi: 10.1038/ng.100pubmed: 18297072google scholar: lookup
  26. Shimomura Y, Wajid M, Petukhova L, Kurban M, Christiano AM. Autosomal-dominant woolly hair resulting from disruption of keratin 74 (KRT74), a potential determinant of human hair texture. Am. J. Hum. Genet. 2010;86:632–638.
    doi: 10.1016/j.ajhg.2010.02.025pmc: PMC2850421pubmed: 20346438google scholar: lookup
  27. Adzhubei IA. A method and server for predicting damaging missense mutations. Nat. Methods 2010;7:248–249.
    doi: 10.1038/nmeth0410-248pmc: PMC2855889pubmed: 20354512google scholar: lookup
  28. Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat. Protoc. 2009;4:1073–1081.
    doi: 10.1038/nprot.2009.86pubmed: 19561590google scholar: lookup
  29. Sievers F. Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 2011;7:539.
    doi: 10.1038/msb.2011.75pmc: PMC3261699pubmed: 21988835google scholar: lookup
  30. Thibaut S, Barbarat P, Leroy F, Bernard BA. Human hair keratin network and curvature. Int. J. Dermatol. 2007;46:7–10.
  31. Piérard-Franchimont C, Paquet P, Quatresooz P, Piérard GE. Mechanobiology and cell tensegrity: the root of ethnic hair curling?. J. Cosmet. Dermatol. 2011;10:163–167.
  32. Tanaka S. Mutations in the helix termination motif of mouse type I IRS keratin genes impair the assembly of keratin intermediate filament. Genomics 2007;90:703–711.
    doi: 10.1016/j.ygeno.2007.07.013pubmed: 17920809google scholar: lookup
  33. Morgenthaler C. A missense variant in the coil1A domain of the keratin 25 gene is associated with the dominant curly hair coat trait (Crd) in horse. Genet Sel Evol 2017;49:85.
    doi: 10.1186/s12711-017-0359-5pmc: PMC5686958pubmed: 29141579google scholar: lookup
  34. Ito M. Wnt-dependent de novo hair follicle regeneration in adult mouse skin after wounding. Nature 2007;447:316–320.
    doi: 10.1038/nature05766pubmed: 17507982google scholar: lookup
  35. Mardaryev AN. Lhx2 differentially regulates Sox9, Tcf4 and Lgr5 in hair follicle stem cells to promote epidermal regeneration after injury. Development 2011;138:4843–4852.
    doi: 10.1242/dev.070284pmc: PMC4067271pubmed: 22028024google scholar: lookup
  36. Ito M. Stem cells in the hair follicle bulge contribute to wound repair but not to homeostasis of the epidermis. Nat. Med. 2005;11:1351–1354.
    doi: 10.1038/nm1328pubmed: 16288281google scholar: lookup
  37. Veniaminova NA. Keratin 79 identifies a novel population of migratory epithelial cells that initiates hair canal morphogenesis and regeneration. Development 2013;140:4870–4880.
    doi: 10.1242/dev.101725pmc: PMC3848186pubmed: 24198274google scholar: lookup
  38. Runkel F. Morphologic and molecular characterization of two novel Krt71 (Krt2-6g) mutations: Krt71 rco12 and Krt71 rco13. Mamm. Genome 2006;17:1172–1182.
    doi: 10.1007/s00335-006-0084-9pubmed: 17143583google scholar: lookup
  39. Coletta A. Low-complexity regions within protein sequences have position-dependent roles. BMC Syst. Biol. 2010;4:43.
    doi: 10.1186/1752-0509-4-43pmc: PMC2873317pubmed: 20385029google scholar: lookup
  40. Nakamura T. The Krüppel-like factor epiprofin is expressed by epithelium of developing teeth, hair follicles, and limb buds and promotes cell proliferation. J. Biol. Chem. 2004;279:626–634.
    doi: 10.1074/jbc.M307502200pubmed: 14551215google scholar: lookup
  41. Hertveldt V. The development of several organs and appendages is impaired in mice lacking Sp6. Dev. Dyn. 2008;237:883–892.
    doi: 10.1002/dvdy.21355pubmed: 18297738google scholar: lookup
  42. Smith TA, Parry DA. Three-dimensional modelling of interchain sequence similarities and differences in the coiled-coil segments of keratin intermediate filament heterodimers highlight features important in assembly. J. Struct. Biol. 2008;162:139–151.
    doi: 10.1016/j.jsb.2007.11.005pubmed: 18178101google scholar: lookup
  43. Ansar M. A homozygous missense variant in type I keratin KRT25 causes autosomal recessive woolly hair. Journal of medical genetics 2015;52:676–680.
  44. Langbein L. K25 (K25irs1), K26 (K25irs2), K27 (K25irs3), and K28 (K25irs4) represent the type I inner root sheath keratins of the human hair follicle. J. Invest. Dermatol. 2006;126:2377–2386.
    doi: 10.1038/sj.jid.5700494pubmed: 16874310google scholar: lookup
  45. Rogers GE. Electron microscope studies of hair and wool. Ann. N. Y. Acad. Sci. 1959;83:378–399.
  46. Marshall RC, Orwin DF, Gillespie JM. Structure and biochemistry of mammalian hard keratin. Electron Microsc. Rev. 1991;4:47–83.
    doi: 10.1016/0892-0354(91)90016-6pubmed: 1714783google scholar: lookup
  47. Miller S, Dykes D, Polesky H. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic acids research 1988;16:1215.
    doi: 10.1093/nar/16.3.1215pmc: PMC334765pubmed: 3344216google scholar: lookup
  48. Browning BL, Browning SR. Genotype Imputation with Millions of Reference Samples. Am. J. Hum. Genet. 2016;98:116–126.
    doi: 10.1016/j.ajhg.2015.11.020pmc: PMC4716681pubmed: 26748515google scholar: lookup
  49. Schmieder R, Edwards R. Quality control and preprocessing of metagenomic datasets. Bioinformatics 2011;27:863–864.
  50. Li H, Durbin R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 2009;25:1754–1760.
  51. Li H. The sequence alignment/map format and SAMtools. Bioinformatics 2009;25:2078–2079.
  52. McKenna A. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome research 2010;20:1297–1303.
    doi: 10.1101/gr.107524.110pmc: PMC2928508pubmed: 20644199google scholar: lookup
  53. Cingolani P. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strainw1118; iso-2; iso-3. Fly 2012;6:80–92.
    doi: 10.4161/fly.19695pmc: PMC3679285pubmed: 22728672google scholar: lookup
  54. Abecasis GR, Cherny SS, Cookson WO, Cardon LR. Merlin—rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 2002;30:97–101.
    doi: 10.1038/ng786pubmed: 11731797google scholar: lookup
  55. Thiele H, Nürnberg P. HaploPainter: a tool for drawing pedigrees with complex haplotypes. Bioinformatics 2005;21:1730–1732.
    doi: 10.1093/bioinformatics/bth488pubmed: 15377505google scholar: lookup
  56. Quadros L, Ghosh K, Shetty S. Establishment of a new mismatch PCR‐RFLP technique for detection of G10430A common mutation present in moderate to mild haemophilia B patients belonging to Gujarati community from the western part of India. Haemophilia 2008;14:628–629.
  57. Marchler-Bauer A. CDD/SPARCLE: functional classification of proteins via subfamily domain architectures. Nucleic Acids Research 2016;45:D200–D203.
    doi: 10.1093/nar/gkw1129pmc: PMC5210587pubmed: 27899674google scholar: lookup
  58. Team RC. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.[WWW document]. http://www.R-project.org/. [Accessed December 24, 2013] (2013).
  59. DePristo MA. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 2011;43:491–498.
    doi: 10.1038/ng.806pmc: PMC3083463pubmed: 21478889google scholar: lookup
  60. Anders S, Huber W. Differential expression analysis for sequence count data. Genome biology 2010;11:1.
    doi: 10.1186/gb-2010-11-10-r106pmc: PMC3218662pubmed: 20979621google scholar: lookup
  61. Dillies M-A. A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis. Briefings in bioinformatics 2013;14:671–683.
    doi: 10.1093/bib/bbs046pubmed: 22988256google scholar: lookup
  62. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the royal statistical society. Series B (Methodological) 1995;57:289–300.
  63. Jung K, Becker B, Brunner E, Beißbarth T. Comparison of global tests for functional gene sets in two-group designs and selection of potentially effect-causing genes. Bioinformatics 2011;27:1377–1383.
    doi: 10.1093/bioinformatics/btr152pubmed: 21441576google scholar: lookup
  64. Consortium GO. Gene ontology consortium: going forward. Nucleic acids research 2015;43:D1049–D1056.
    doi: 10.1093/nar/gkᅹpmc: PMC4383973pubmed: 25428369google scholar: lookup
  65. Durinck S, Spellman PT, Birney E, Huber W. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nature protocols 2009;4:1184–1191.
    doi: 10.1038/nprot.2009.97pmc: PMC3159387pubmed: 19617889google scholar: lookup
  66. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2− ΔΔCT method. methods 2001;25:402–408.
    doi: 10.1006/meth.2001.1262pubmed: 11846609google scholar: lookup
  67. Warde-Farley D. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010;38:W214–220.
    doi: 10.1093/nar/gkq537pmc: PMC2896186pubmed: 20576703google scholar: lookup
  68. Stark C. BioGRID: a general repository for interaction datasets. Nucleic Acids Res. 2006;34:D535–539.
    doi: 10.1093/nar/gkj109pmc: PMC1347471pubmed: 16381927google scholar: lookup
  69. Orchard S. The MIntAct project–IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res. 2014;42:D358–363.
    doi: 10.1093/nar/gkt1115pmc: PMC3965093pubmed: 24234451google scholar: lookup