Genealogical lineage sorting leads to significant, but incorrect Bayesian multilocus inference of population structure.
Over the past decades, the use of molecular markers has revolutionized biology and led to the foundation of a new research discipline-phylogeography. Of particular interest has been the inference of population structure and biogeography. While initial studies focused on mtDNA as a molecular marker, it has become apparent that selection and genealogical lineage sorting could lead to erroneous inferences. As it is not clear to what extent these forces affect a given marker, it has become common practice to use the combined evidence from a set of molecular markers as an attempt to recover the signals that approximate the true underlying demography. Typically, the number of markers used is determined by either budget constraints or by statistical power required to recognize significant population differentiation. Using microsatellite markers from Drosophila and humans, we show that even large numbers of loci (>50) can frequently result in statistically well-supported, but incorrect inference of population structure using the software BAPS. Most importantly, genomic features, such as chromosomal location, variability of the markers, or recombination rate, cannot explain this observation. Instead, it can be attributed to sampling variation among loci with different realizations of the stochastic lineage sorting. This phenomenon is particularly pronounced for low levels of population differentiation. Our results have important implications for ongoing studies of population differentiation, as we unambiguously demonstrate that statistical significance of population structure inferred from a random set of genetic markers cannot necessarily be taken as evidence for a reliable demographic inference.
Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.
Pablo
P
Orozco-terWengel
Jukka
J
Corander
Christian
C
Schlötterer
D000818:Animals; D001499:Bayes Theorem; D004331:Drosophila melanogaster; D005828:Genetics, Population / Q000379:methods*; D018895:Microsatellite Repeats / Q000235:genetics
Genetics. 2000 Dec;156(4):1837-52
11102378
Methods Mol Biol. 2000;132:365-86
10547847
Mol Ecol. 2008 Jul;17(13):3062-77
18494766
Gene. 2010 Sep 1;463(1-2):18-20
20452408
PLoS Comput Biol. 2009 Sep;5(9):e1000501
19749978
Genetics. 2002 Jan;160(1):247-56
11805060
Nat Genet. 2001 Nov;29(3):265-9
11685208
Nat Genet. 2010 Apr;42(4):348-54
20208533
Mol Biol Evol. 2005 Oct;22(10):2119-30
15987874
Mol Ecol. 2001 Feb;10(2):319-36
11298948
Genetica. 2009 Apr;135(3):439-55
18651229
Nat Genet. 2010 Apr;42(4):355-60
20208535
Heredity (Edinb). 2009 Oct;103(4):285-98
19623208
Genet Res. 2001 Dec;78(3):209-12
11865709
Genetics. 2006 Jan;172(1):265-74
16204208
Genetics. 2008 Jan;178(1):385-92
18202381
Nat Rev Genet. 2009 Sep;10(9):639-50
19687804
Genetics. 2003 Nov;165(3):1269-78
14668381
Mol Ecol Resour. 2009 Sep;9(5):1322-32
21564903
Genetics. 1988 Sep;120(1):199-212
2906026
Trends Ecol Evol. 2009 Jun;24(6):332-40
19307040
Proc Natl Acad Sci U S A. 1994 Apr 12;91(8):3166-70
8159720
Genetics. 1996 Sep;144(1):389-99
8878702
Heredity (Edinb). 2009 Feb;102(2):120-6
18766200
Mol Ecol. 2006 Sep;15(10):2833-43
16911204
Mol Biol Evol. 2003 May;20(5):792-9
12679536
Nature. 1993 Oct 7;365(6446):548-50
8413609
Bioinformatics. 2002 Feb;18(2):337-8
11847089
Trends Ecol Evol. 2005 Aug;20(8):435-40
16701414
Mol Ecol. 2008 Oct;17(20):4470-9
18986493
Nat Genet. 2010 Mar;42(3):260-3
20101244
Proc Natl Acad Sci U S A. 2005 Nov 1;102(44):15942-7
16243969
Genetics. 2000 Jun;155(2):945-59
10835412
Ann Hum Genet. 2009 Jan;73(1):95-108
19040659
Genetics. 2006 Jan;172(1):287-92
16204221
J Comput Biol. 2005 Nov;12(9):1183-201
16305328
J Hered. 1997 Sep-Oct;88(5):335-42
9378905
Genetics. 1973 May;74(1):175-95
4711903
Ann Hum Genet. 2006 Nov;70(Pt 6):841-7
17044859