The use and abuse of genetic marker-based estimates of relatedness and inbreeding.

Helen R Taylor
Author Information
  1. Helen R Taylor: Allan Wilson Centre, School of Biological Sciences, Victoria University of Wellington Kelburn Parade, Wellington, New Zealand.

Abstract

Genetic marker-based estimators remain a popular tool for measuring relatedness (r xy ) and inbreeding (F) coefficients at both the population and individual level. The performance of these estimators fluctuates with the number and variability of markers available, and the relatedness composition and demographic history of a population. Several methods are available to evaluate the reliability of the estimates of r xy and F, some of which are implemented in the program COANCESTRY. I used the simulation module in COANCESTRY since assess the performance of marker-based estimators of r xy and F in a species with very low genetic diversity, New Zealand's little spotted kiwi (Apteryx owenii). I also conducted a review of published papers that have used COANCESTRY as its release to assess whether and how the reliability of the estimates of r xy and F produced by genetic markers are being measured and reported in published studies. My simulation results show that even when the correlation between true (simulated) and estimated r xy or F is relatively high (Pearson's r = 0.66-0.72 and 0.81-0.85, respectively) the imprecision of the estimates renders them highly unreliable on an individual basis. The literature review demonstrates that the majority of studies do not report the reliability of marker-based estimates of r xy and F. There is currently no standard practice for selecting the best estimator for a given data set or reporting an estimator's performance. This could lead to experimental results being interpreted out of context and render the robustness of conclusions based on measures of r xy and F debatable.

Keywords

References

  1. Mol Ecol. 2012 Jun;21(11):2788-804 [PMID: 22497583]
  2. Mol Ecol. 2013 Dec;22(23):5779-92 [PMID: 24102888]
  3. Hum Hered. 1993 Jan-Feb;43(1):45-52 [PMID: 8514326]
  4. Mol Ecol. 2012 Apr;21(7):1727-40 [PMID: 22335253]
  5. Genetics. 2007 May;176(1):421-40 [PMID: 17339212]
  6. Mol Ecol Resour. 2011 Jan;11(1):141-5 [PMID: 21429111]
  7. Nat Rev Genet. 2006 Oct;7(10):771-80 [PMID: 16983373]
  8. Genetics. 1921 Mar;6(2):111-23 [PMID: 17245958]
  9. Genetics. 1999 Aug;152(4):1753-66 [PMID: 10430599]
  10. Mol Ecol. 2001 Jun;10(6):1539-49 [PMID: 11412374]
  11. Mol Ecol. 2013 Nov;22(21):5313-28 [PMID: 24118220]
  12. Mol Ecol. 2010 Apr;19(7):1439-51 [PMID: 20149098]
  13. Philos Trans R Soc Lond B Biol Sci. 2014 Mar 31;369(1642):20130565 [PMID: 24686941]
  14. J Hered. 2009 Jan-Feb;100(1):25-33 [PMID: 18815116]
  15. Conserv Biol. 2010 Dec;24(6):1617-25 [PMID: 20586788]
  16. Theor Popul Biol. 1971 Dec;2(4):507-24 [PMID: 5162702]
  17. Evolution. 1989 Mar;43(2):258-275 [PMID: 28568555]
  18. Proc Biol Sci. 2008 Mar 22;275(1635):613-21 [PMID: 18211868]
  19. PLoS One. 2012;7(3):e33378 [PMID: 22428037]
  20. Genetics. 2002 Mar;160(3):1203-15 [PMID: 11901134]
  21. Am J Hum Genet. 2008 Sep;83(3):359-72 [PMID: 18760389]
  22. BMC Genet. 2012 Aug 14;13:70 [PMID: 22888858]
  23. Genetics. 1984 Dec;108(4):985-97 [PMID: 17246245]
  24. J Evol Biol. 2014 Mar;27(3):518-30 [PMID: 24444019]
  25. Mol Ecol. 2004 Sep;13(9):2829-40 [PMID: 15315693]
  26. Mol Ecol Resour. 2015 May;15(3):557-61 [PMID: 25186958]
  27. Philos Trans R Soc Lond B Biol Sci. 2004 Jun 29;359(1446):873-90 [PMID: 15306404]
  28. BMC Genomics. 2013 May 31;14:363 [PMID: 23721540]
  29. Proc Natl Acad Sci U S A. 2011 Jul 26;108(30):12348-53 [PMID: 21709235]
  30. PLoS One. 2013 Oct 31;8(10):e78314 [PMID: 24205195]
  31. Science. 1994 Aug 26;265(5176):1193-201 [PMID: 7915048]
  32. Evolution. 1996 Jun;50(3):1062-1073 [PMID: 28565279]
  33. J Hered. 2010 Sep-Oct;101(5):581-90 [PMID: 20484384]
  34. Mol Ecol. 2011 Nov;20(22):4643-53 [PMID: 22004175]
  35. Mol Ecol. 2005 Jan;14(1):9-17 [PMID: 15643947]
  36. Theor Popul Biol. 2006 Nov;70(3):300-21 [PMID: 16388833]
  37. Proc Biol Sci. 2010 Dec 7;277(1700):3677-84 [PMID: 20591862]
  38. Genetics. 2006 Aug;173(4):2091-101 [PMID: 16783017]
  39. Science. 1988 Nov 25;242(4882):1155-7 [PMID: 17799732]
  40. Proc Biol Sci. 2013 May 15;280(1762):20130576 [PMID: 23677342]
  41. Genet Res (Camb). 2011 Feb;93(1):47-64 [PMID: 21226974]
  42. Genet Res. 2007 Jun;89(3):135-53 [PMID: 17894908]

Word Cloud

Created with Highcharts 10.0.0rxyFestimatesmarker-basedestimatorsrelatednessCOANCESTRYinbreedingperformancereliabilitygeneticpopulationindividualmarkersavailableusedsimulationassessreviewpublishedstudiesresultsGeneticremainpopulartoolmeasuringcoefficientslevelfluctuatesnumbervariabilitycompositiondemographichistorySeveralmethodsevaluateimplementedprogrammodulesincespecieslowdiversityNewZealand'slittlespottedkiwiApteryxoweniialsoconductedpapersreleasewhetherproducedmeasuredreportedshowevencorrelationtruesimulatedestimatedrelativelyhighPearson'sr = 066-072081-085respectivelyimprecisionrendershighlyunreliablebasisliteraturedemonstratesmajorityreportcurrentlystandardpracticeselectingbestestimatorgivendatasetreportingestimator'sleadexperimentalinterpretedcontextrenderrobustnessconclusionsbasedmeasuresdebatableuseabuse

Similar Articles

Cited By