1
Supplementary information for manuscript# 2003-02-00378A:
Supplementary Table S1. Observed (HO) and expected (HE) heterozygosity
values and mean value of Garza & Williamson’s1 M* for each M. s.
natalensis colony in South Africa.
Colony (No of each sex
Variance
HO
HE
M
De Hoop (22♀; 17♂)
0.626
0.712
0.783
0.025
Die Hel (4♀; 15♂)
0.621
0.774
0.699
0.050
Steenkampskraal (8♀; 12♂)
0.597
0.697
0.728
0.047
Koegelbeen (20♀; 20♂)
0.598
0.691
0.839
0.035
Grahamstown (17♀; 20♂)
0.650
0.673
0.785
0.022
Maitland Mines (20♀; 17♂)
0.654
0.693
0.761
0.021
Shongweni Dam (14♀; 15♂)
0.664
0.724
0.739
0.059
Jozini Dam (19♀: 9♂)
0.705
0.708
0.770
0.035
Peppercorn (10 ♀; 9 ♂)
0.649
0.772
0.823
0.038
Sudwala (15♀; 18♂)
0.652
0.720
0.860
0.023
sampled)**
of M
*M is the mean ratio between the number of microsatellite alleles (k) and the range of allele
sizes (r), and can be used to predict the demographic history of the M. s. natalensis colonies. It
was calculated using AGARst2. Values of M above 0.70 are indicative of historically stable,
outbred populations1.
**♀= number of females; ♂= number of males. In total, 307 individuals were sampled, but six
were excluded from the microsatellite analysis due to lack of PCR amplification at four or more
loci.
2
Supplementary Table S2. Pairwise Rho (below diagonal) and ()2 values
(above diagonal) indicating the extent of genetic differentiation between
M. s. natalensis colonies‡ in South Africa.
DHP
DHL
SKK
KB
G
MM
SHD
JD
PC
SW
-
0.105
4.242
5.286
3.326
2.635
3.203
2.899
2.666
2.265
-
3.419
4.313
2.842
2.259
2.794
2.487
2.157
1.931
-
0.098
2.408
2.445
1.524
1.959
1.033
1.646
0.014
-
2.594
2.793
1.807
2.232
1.312
2.103
-
0.084
0.446
0.107
0.355
0.388
0.005
-
0.344
0.062
0.319
0.206
0.045
-
0.138
0.234
0.257
DHP
DHL 0.013
SKK 0.590* 0.498*
KB
G
0.686* 0.602*
0.594* 0.520* 0.382* 0.445*
MM 0.551* 0.475* 0.374* 0.449*
SHD 0.546* 0.477* 0.269* 0.336* 0.068*
JD
0.555* 0.481* 0.320* 0.386*
-0.005
0.005
-
0.194
0.176
PC
0.482* 0.400* 0.152* 0.215* 0.073** 0.034
0.023
0.015
-
0.122
SW
0.532* 0.453* 0.283* 0.374* 0.067*
0.040
0.024
-0.004
-
0.007
0.030
*Significant differentiation at p  0.01.
**Significant differentiation at p  0.05.
‡Names
of colonies are abbreviated as follows: DHP = De Hoop, DHL = Die Hel, SKK =
Steenkampskraal, KB = Koegelbeen, G = Grahamstown, MM = Maitland Mines, SHD =
Shongweni Dam, JD = Jozini Dam, PC = Peppercorn, SW = Sudwala.
3
Supplementary Table S3. Results of an assignment test3 on ten M. s.
natalensis colonies* in South Africa: the percentage of individuals
correctly assigned to each colony, the modal and range of likelihood
ratios between most likely and second most likely colonies, and the
colonies to which individuals were incorrectly assigned** are shown.
Percent of
Modal
Range of
individuals likelihood ratio: likelihood ratios:
SubColony* correctly
most likely
most likely
population
assigned to colony to 2nd
colony to 2nd
colony
most likely
most likely
Southern
Western
Northeastern
Colonies to which individuals were
incorrectly assigned**
(% of individuals incorrectly
assigned)
DHP
82
14.60
1.20 - 1.30x103 DHL (18%)
DHL
74
18.40
1.18 - 1.42x103 DHP & KB (~10% each); SKK (5%)
SKK
90
98.40
1.33 - 8.82x102 KB (10%)
KB
90
10.50
1.11 - 2.43x103 SKK (10%)
G
70
5.10
1.13 - 111.00
MM (16%); JD (5%); SHD, PC & SW
(3% each)
MM
62
2.41
1.08 - 27.70
G (24%); SHD (5%); SW, KB & SKK (3%
each)
SHD
69
8.77
1.02 - 341.00
MM (14%); JD (7%); SW, PC & DHP
(~3% each)
JD
76
5.70
1.22 - 52.40
SHD, G & SW (7% each); MM (~3%)
PC
80
3.07
1.07 - 1.12x103 JD (~10%); MM & G (5% each)
SW
73
8.16
1.10 - 3.68x103 G (12%); JD (9%); PC (6%)
*Names of colonies are abbreviated as follows: DHP = De Hoop, DHL = Die Hel, SKK =
Steenkampskraal, KB = Koegelbeen, G = Grahamstown; MM = Maitland Mines, SHD =
Shongweni Dam, JD = Jozini Dam, PC = Peppercorn, SW = Sudwala
**In most cases, incorrect assignments placed individuals in colonies located within the same
subpopulation as the colony from which they were actually sampled (in bold text).
4
Supplementary Table S4. Pairwise comparisons of aspect ratio between
M. s. natalensis colonies‡ in South Africa (Dunn’s method4).
DHL
SKK
KB
G
MM
SHD
JD
PC
SW
DHP
NS
NS
NS
NS
NS
5.005
5.689
4.917
NS
DHL
-
NS
5.154
NS
NS
6.596
7.056
6.569
4.499
-
NS
NS
NS
4.865
5.445
4.874
NS
-
3.953
4.047
NS
NS
NS
NS
-
NS
6.009
6.695
5.817
NS
-
6.118
6.793
5.903
NS
-
NS
NS
NS
-
NS
NS
-
NS
SKK
KB
G
MM
SHD
JD
PC
*NS, not significant at p ≤ 0.01; critical Q0.01;10 = 3.692
‡Names
of colonies are abbreviated as follows: DHP = De Hoop, DHL = Die Hel, SKK =
Steenkampskraal, KB = Koegelbeen, G = Grahamstown, MM = Maitland Mines, SHD =
Shongweni Dam, JD = Jozini Dam, PC = Peppercorn, SW = Sudwala.
5
Table S5. Results of mismatch distribution5-7 and linkage disequilibrium
(LD)8 analyses for mtDNA haplotypes obtained from M. s. natalensis.
Raggedness
statistic (r)9
KolmogorovSmirnov (ks)
statistic*
p-value for ks
statistic
% sites
showing
significant LD**
Total
population
0.006
0.263
0.144
22
Southern
subpopulation
0.041
0.581
<0.0001
0
Western
subpopulation
0.042
0.429
0.003
0
Northeastern
subpopulation
0.019
0.355
0.04
5
*Observed mismatch distributions (see also Supplementary Figure S2) were compared to
expected Poisson distributions for an expanding population by means of Kolmogorov-Smirnov
tests.
**In the LD analysis, Fisher’s exact test was used to determine the number of pairwise
comparisons of informative sites that showed significant (p < 0.05) LD, after Bonferroni
correction. Both mismatch distribution and LD analyses were performed in DnaSP10.
6
Supplementary Figure S1 Legend
Figure S1. Graphical representations of the results of an assignment test3 for
M. s. natalensis individuals captured in a, the western, b, southern and c,
north-eastern subpopulations. In each case, the log likelihood of each
individual belonging to the subpopulation where it was sampled is plotted
against the log likelihood of it belonging to one of the other two subpopulations.
In all three plots, the gene frequencies of the subpopulations are highly
distinctive, with the majority of individuals falling above the diagonal (along
which the log likelihood of an individual belonging to the subpopulation where it
was captured is equal to that of another subpopulation). Some migrants or
dispersers are evident in the southern (b) and north-eastern subpopulations (c),
where a few data points fall below the diagonal.
7
Supplementary Figure S2 Legend
Figure S2. Observed mismatch distributions (pairwise differences, calculated in
DnaSP10) of M. s. natalensis mtDNA control region haplotypes (dashed line)
compared to the expected Poisson distribution (solid line) for a population
experiencing either expansion or decline; a, the entire South African
population, b, the southern subpopulation, c, the western subpopulation, d, the
northeastern subpopulation.
8
Supplementary References
1. Garza,J.C. & Williamson,E.G. Detection of reduction in population size using data
from microsatellite loci. Mol. Ecol. 10, 305-318 (2001).
2. Harley,E.H. AGARst. A program for calculating Allele frequencies, Gst and Rst from
microsatellite data plus a number of other population genetic estimates and outputting
files formatted for "Genepop", "RstCalc" and "PCA-Gen" v. 2.4 (Department of
Chemical Pathology, University of Cape Town, Cape Town, 2001).
3. Paetkau,D., Waits,L.P., Clarkson,P.L., Craighead,L. & Strobeck,C. An empirical
evaluation of genetic distance statistics using microsatellite data from bear (Ursidae)
populations. Genetics 147, 1943-1957 (1997).
4. Zar,J.H. Biostatistical Analysis. 2nd edn (Prentice-Hall International, Inc., New
Jersey, 1984).
5. Harpending,H.C. et al. Genetic traces of ancient demography. Proc. Natl. Acad. Sci.
U. S. A 95, 1961-1967 (1998).
6. Rogers,A.R. & Harpending,H. Population growth makes waves in the distribution of
pairwise genetic differences. Mol. Biol. Evol. 9, 552-569 (1992).
7. Schneider,S. & Excoffier,L. Estimation of past demographic parameters from the
distribution of pairwise differences when the mutation rates vary among sites:
application to human mitochondrial DNA. Genetics 152, 1079-1089 (1999).
8. Slatkin,M. Linkage Disequilibrium in Growing and Stable Populations. Genetics 137,
331-336 (1994).
9. Harpending,H.C. Signature of ancient population growth in a low-resolution
mitochondrial DNA mismatch distribution. Hum. Biol. 66, 591-600 (1994).
9
10. Rozas,J. & Rozas,R. DnaSP version 3: an integrated program for molecular
population genetics and molecular evolution analysis. Bioinformatics 15, 174-175
(1999).