Journals / Turkish Journal of Veterinary and Animal Sciences / 2018 / Cilt: 42 - Sayı: 6

Comparison of different paternity test panels in sheep

Pages
633–641
Publication Date
2018-12-10
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The overall mean value of the polymorphic information content (PIC) (0.78) indicated that the microsatellite panels were highly polymorphic.

📌 3 Key Takeaways

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Objective & Hypothesis:The aims of this study were to evaluate different paternity test panels with 17 microsatellite markers for their effectiveness in paternity analysis and to identify pedigree error rates in the Kangal Akkaraman breed of sheep.
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Key Findings & Data:The animal material for the study consisted of 175 Kangal Akkaraman sheep, 35 rams, and their 140 offspring, raised on farms and bred using controlled mating.
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Conclusion & Impact:The overall mean value of the polymorphic information content (PIC) (0.78) indicated that the microsatellite panels were highly polymorphic.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Paternity test · microsatellite · probability of exclusion

Abstract

The aims of this study were to evaluate different paternity test panels with 17 microsatellite markers for their effectiveness in paternity analysis and to identify pedigree error rates in the Kangal Akkaraman breed of sheep. The animal material for the study consisted of 175 Kangal Akkaraman sheep, 35 rams, and their 140 offspring, raised on farms and bred using controlled mating. The panels were created according to probability of exclusion (PE) of 17 studied microsatellites. A total of 240 alleles were detected across 17 microsatellite loci. The overall mean value of the polymorphic information content (PIC) (0.78) indicated that the microsatellite panels were highly polymorphic. Probability of identity (PI) values ranged between 0.02 and 0.13. It can be said that pedigree error (2.94%) occurred at a low rate in this study. The highest combined PE values were obtained from Panel-16 (0.9999771) as expected. Panel-8 and Panel-9 met the PE value accepted in the literature (0.999). The results show that these panels are cheaper and more practical than other panels formed for Kangal Akkaraman.

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Cite This Article

YILMAZ, O., CEMAL, İ., COŞKUN, B., OĞRAK, Y. Z., ATA, N., KARACA, O. (2018). Comparison of different paternity test panels in sheep. Turkish Journal of Veterinary and Animal Sciences, Cilt: 42 - Sayı: 6, 633–641. https://ajindex.com/articles/121276

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References (12)

  1. Weller JI, Feldmesser E, Golik M, Tager-Cohen I, Domochovsky R, Alus O, Ezra E, Ron M. Factors affecting incorrect paternity assignment in the Israeli Holstein population. J Dairy Sci 2004; 87: 2627-2640.
  2. Harder B, Bennewitz J, Reinsch N, Mayer M, Kalm E. Effect of missing sire information on genetic evaluation. Arch Tierzucht 2005; 48: 219-232.
  3. Vandeputte M, Mauger S, Dupont-Nivet M. An evaluation of allowing for mismatches as a way to manage genotyping errors in parentage assignment by exclusion. Mol Ecol Notes 2006; 6: 265-267.
  4. Sanders K, Bennewitz J, Kalm E. Wrong and missing sire information affects genetic gain in the Angeln dairy cattle population. J Dairy Sci 2006; 89: 315-321.
  5. Geldermann H, Pieper U, Weber WE. Effect of misidentification on the estimation of breeding value and heritability in cattle. J Anim Sci 1986; 63: 1759-1768.
  6. Arruga MV, Monteagudo LV, Tejedor MT, Barrao R, Ponz R. Analysis of microsatellites and paternity testing in Rasa Aragonesa sheep. Res Vet Sci 2011; 70: 271-273.
  7. Banos G, Wiggans GR, Powell RL. Impact of paternity errors in cow identification on genetic evaluations and international comparisons. J Dairy Sci 2001; 84: 2523-2529.
  8. Baron EE, Martinez ML, Verneque RS, Coutinho LL. Parentage testing and effect of misidentification on the estimation of breeding value in Gir cattle. Genet Mol Biol 2002; 25: 389-394.
  9. Jimenez-Gamero I, Dorado G, Munoz-Serrano A, Analla M, Alonso-Moraga A. DNA microsatellites to ascertain pedigree- recorded information in a selecting nucleus of Murciano– Granadina dairy goats. Small Ruminant Res 2006; 65: 266-273.
  10. Ma H, Zhu H, Guan F, Cherng S. Paternity Testing. J Amer Sci 2006; 2: 76-92.
  11. Maichomo KM, Gitau WGK, Gathuma JM, Ndung’u JM, Kosura O, Olivier HO. Extent and implications of incorrect offspring-sire relationships in pastoral production system in Kajiado District, Kenya. Livest Res Rural Dev 2008; 20: e80. Rosa AJM, Sardina MT, Mastrangelo S, Tolone M, Portolano B. Parentage verification of Valle del Belice dairy sheep using multiplex microsatellite panel. Small Ruminant Res 2013; 113: 62-65.
  12. Heaton MP, Leymaster KA, Kalbfleisch TS, Kijas JW, Clarke SM, McEwan J, Maddox JF, Basnayake V, Petrik DT, Simpson B et al. The International Sheep Genomics Consortium. SNPs for parentage testing and traceability in globally diverse breeds of sheep. Plos One 2014; 9: e94851. Simm G. Molecular genetic technologies. In: Simm G, editor. Genetic Improvement of Cattle and Sheep. Ipswich, UK: Farming Press