TY - JOUR
T1 - Geographic sampling scheine as a determinant of the major axis of genetic variation in principal components analysis
AU - DeGiorgio, Michael
AU - Rosenberg, Noah A.
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013/2
Y1 - 2013/2
N2 - Principal component (PC) maps, which plot the values of a given PC estimated on the basis of allele frequency variation at the geographic sampling locations of a set of populations, are often used to investigate the properties of past range expansions. Some studies have argued that in a range expansion, the axis of greatest variation (i.e., the first PC) is parallel to the axis of expansion. In contrast, others have identified a pattern in which the axis of greatest variation is perpendicular to the axis of expansion. Here, we seek to understand this difference in outcomes by investigating the effect of the geographic sampling scheme on the direction of the axis of greatest variation under a two-dimensional range expansion model. From datasets simulated using each of two different schemes for the geographic sampling of populations under the model, we create PC maps for the first PC. We find that depending on the geographic sampling scheme, the axis of greatest variation can be either parallel or perpendicular to the axis of expansion. We provide an explanation for this result in terms of intra- and interpopulation coalescence times.
AB - Principal component (PC) maps, which plot the values of a given PC estimated on the basis of allele frequency variation at the geographic sampling locations of a set of populations, are often used to investigate the properties of past range expansions. Some studies have argued that in a range expansion, the axis of greatest variation (i.e., the first PC) is parallel to the axis of expansion. In contrast, others have identified a pattern in which the axis of greatest variation is perpendicular to the axis of expansion. Here, we seek to understand this difference in outcomes by investigating the effect of the geographic sampling scheme on the direction of the axis of greatest variation under a two-dimensional range expansion model. From datasets simulated using each of two different schemes for the geographic sampling of populations under the model, we create PC maps for the first PC. We find that depending on the geographic sampling scheme, the axis of greatest variation can be either parallel or perpendicular to the axis of expansion. We provide an explanation for this result in terms of intra- and interpopulation coalescence times.
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U2 - 10.1093/molbev/mss233
DO - 10.1093/molbev/mss233
M3 - Article
C2 - 23051843
AN - SCOPUS:84873583931
VL - 30
SP - 480
EP - 488
JO - Molecular Biology and Evolution
JF - Molecular Biology and Evolution
SN - 0737-4038
IS - 2
ER -