Microsatellite Variation and Evolution in the Mimulus guttatus Species
Complex with Contrasting Mating Systems
Philip Awadalla
Department
and Kermit Ritland’
of Botany, University
of Toronto
Mutational variability at microsatellite
loci is shaped by both population history and the mating system. In turn,
alternate mating systems in flowering plants can resolve aspects of microsatellite
loci evolution. Five species of
yellow monkeyflowers
(Mimulus sect. Simiolis) differing for historical rates of inbreeding were surveyed for variation at six microsatellite
loci. High levels of diversity at these loci were found in both outcrossing and selfing
taxa. In line with allozyme studies, inbreeders showed more partitioning of diversity among populations, and diversity in selfing taxa was lower than expected from reductions in effective population size due to selfing alone,
suggesting the presence of either population bottlenecks or background selection in selfers. Evaluation of the stepwise mutation model (a model of DNA replication slippage) suggests that these loci evolve in a stepwise fashion.
Inferred coalescent times of microsatellite
alleles indicate that past bottlenecks of population size or colonization
events were important in reducing diversity in the inbreeding taxon.
Introduction
Empirical studies have demonstrated
that outcrossing plant species tend to have more genetic variation
within populations
than self-fertilizing
plant species,
but, in contrast,
among-population
differentiation
is
greater in selfers (Loveless and Hamrick 1984; Hamrick
and Godt 1990; Schoen and Brown 1991). Two primary
factors-drift
and selection-both
can play roles in reducing genetic diversity of inbreeders.
The effective
population
size (N,) of highly selfing populations
is
about one half that of outcrossers, provided N,p, (p =
mutation rate) is small (Pollack 1987). This, possibly
combined with reduced gene flow between populations
of selfers, increases the effect of genetic drift (Hamrick
and Godt 1990). Second, in highly selfing populations,
the effective recombination
rate is lower than the absolute or actual rate (Narrain 1966). Neutral alleles consequently “hitchhike”
with either selectively favored alleles or deleterious mutations, ultimately reducing variation at neutral loci (Hedrick 1980; Kaplan, Hudson, and
Langley 1989; Charlesworth, Morgan, and Charlesworth
1993; Hudson and Kaplan 1995; Nordborg, Charlesworth, and Charlesworth
1996).
However, the relative roles of these forces on levels
of genetic variation are still unclear, and their resolution
awaits further theoretical and empirical studies, particularly those based on new types of molecular data. Herein, we develop assays for microsatellite
markers (simple
sequence repeats [SSRs]) in Mimulus and seek inferences about these forces using both SSR and isozyme
variation patterns among species of Mimulus with contrasting mating systems.
Studies of genetic diversity have traditionally
been
based on isozymes, but the relatively low level of vari* Present address: Department of Forest Sciences, University of
British Columbia, Vancouver.
Key words: microsatellites, allozymes, Mimulus, mating systems,
genetic diversity, stepwise mutation model, self-fertilization.
Address for correspondence and reprints: Philip Awadalla, Department of Botany, University of Toronto, Toronto, Ontario M5S 3B 1,
Canada. E-mail: [email protected].
Mol.Biol. Evol.14( 10): 1023-1034.
0 1997 by the Society for Molecular
1997
Biology
and Evolution.
ISSN: 0737-4038
ation at isozyme loci hampers inferences about population processes. SSR loci are highly polymorphic
genetic markers. They consist of l-7 bp and tandemly repeated motifs, and variation is expressed as repeat number differences among alleles. Mutation rates are high,
approximately
lop2 to 10e4 per generation (Tautz 1989;
Weber and Wong 1993). SSRs are probably selectively
neutral, although allele size constraints have been documented (Garza, Slatkin, and Freimer 1995). These loci
are ubiquitously
distributed in eukaryotic genomes, with
perhaps one occuring every 10 kb (Tautz and Renz
1984; Tautz 1989). Their high heterozygosity
makes
them the marker of choice for constructing
genetic
maps. Furthermore,
their polymorphic
nature should
make them extremely sensitive to changes in population
breeding size, structure, and rates of dispersal (Slatkin
1995a).
Little is known about microsatellite allele dynamics
and their mutational mechanisms
(Valdes, Slatkin, and
Freimer 1993; Di Rienzo et al. 1994; Estoup et al.
1995a, 1995b), yet proper populational
inferences such
as estimation of genetic distance are dependent on the
mode of mutation (Slatkin 1995a). Slipped-strand
mispairing during DNA replication is thought to be the predominant mode of mutation at these loci (Levinson and
Gutman 1987; Schlotterrer and Tautz 1992), but gene
conversion may play a role (Di Rienzo et al. 1994; Garza, Slatkin, and Freimer
1995). Interestingly,
recent
work has shown how the distribution of allele sizes observed in population samples can be used to indirectly
infer modes of mutation. The stepwise mutation model
(SMM; Ohta and Kimura 1973) can be evaluated against
data from SSR loci (Valdes, Slatkin, and Freimer 1993;
Di Rienzo et al. 1994; Estoup et al. 1995a). Valdes,
Slatkin, and Freimer (1993) developed coalescent theory
to predict the time of coalescence of microsatellite
alleles assuming a simple stepwise mutation process.
Current understanding
of the dynamics of microsatellite evolution has come mainly from studies of intraspecific
polymorphism,
predominantly
in humans.
Little attention has been given to patterns of transpecific
microsatellite
evolution, which requires conservation
of
priming sites within flanking sequences
and mainte1023
1024
Awadalla
and Ritland
nance of repeat arrays across species (Fitzsimmons,
Moritz, and Moore 1995). Microsatellite
loci have been isolated in a number of plant species (e.g., Senior and Heun
1993; Wang et al. 1994) but in only a few wild (nondomesticated)
plant species (e.g., Smith and Devey
1993; Chase, Kesseli, and Bawa 1996). Transpecific applications are reported for few plant taxa (e.g., Smith
and Devey 1993; Roder et al. 1995). Microsatellites
have also been isolated from the chloroplast genomes of
four Pinus species by Powell et al. (1995), and homologous loci were found in Oryza and Murchantia species.
Mimulus DC (Scrophulariaceae)
consists of approximately
150 species in lo-12 sections (Grant 1924;
Pennell 1951). The Mimulus guttutus species complex
lies within the Simiolus section and consists of 8-12
intercrossable
taxa known as “yellow monkeyflowers”
with a center of diversity in California (Vickery 1964,
1978). The most abundant member of this group is Mimulus guttutus (the common
monkeyflower),
a larger
flowered outbreeder. In a study of eight of these taxa,
Ritland and Ritland (1989) documented a wide range of
inbreeding and reproductive morphology. Allozyme and
chloroplast DNA (cpDNA) RFLP analyses have also indicated that among these closely related taxa, inbreeding
has multiple, independent
origins (Ritland and Ritland
1989; Fenster and Ritland 1992).
This study examines levels of microsatellite
variation in Mimulus sect. Simiolus species of contrasting
mating systems and compares these patterns with those
observed for isozyme variation. In doing so, we consider
the problems with obtaining model parameter estimates
based on microsatellite
variation; these problems include
excessive polymorphism,
the sampling of rare alleles,
high mutation rate, and sensitivity to the mode of mutation. Observing
these precautions,
we explore the
unique evolutionary
information provided by inbreeders.
Relative to outcrossers, selfing populations exhibit lower
migration rates, as the predominant
dispersal mode of.
pollen flow is absent. Thus, observed polymorphisms
in
selfers can be more clearly compared to theoretical expectations of the one-step stepwise mutation model. We
show that the one-step stepwise mutation model explains the observed frequency distributions
at SSR loci
in distinct selfing M. Zuciniutus populations.
Applying
this model to the distribution
of microsatellite
allele
sizes, we use coalescent theory to infer coalescent times
and past bottlenecks of population size in selfers.
Materials and Methods
Species
and Populations
Sampled
The following five taxa and nine populations were
collected as seed during 1988-1995: M. guttutus (#138,
1.6 km east of Bingen, Oreg.), M. guttutus (#142, Pt.
Reyes, Calif.), A4. guttutus (#143, Stagecoach Canyon,
Calif.), M. nusutus (#202, Lake Co. line and Hwy 20,
Calif.), M. pZutycuZyx (#606, Joy Rd. and Bodega Rd.,
Sonoma C., Calif.), M. Zuciniutus (#711, Hetch Hetchy
Rd., Calif.), M. Zuciniutus (#712, Meadow Lake, Calif.),
M. Zuciniutus (#713, 7.5 km from junction of Yosemite
Pk., Calif.), M. guttutus var. depuuperutus
(#4200, 7.9
m east of Bingen, Oreg.). Progeny were grown in a
growth chamber at 14 h light (18°C) : 10 h dark (10°C).
All these taxa are intercrossable;
M. Zuciniutus is an inbreeder and occurs at medium elevations (1,500-2,000
m) in the Sierra Nevada; A4. nusutus is a facultative
inbreeder with variable flower size; M. pZutycuZyx is an
inbreeder
with a rather limited distribution
in North
Coastal California; M. guttutus var. depuuperutus
is a
cleistogamous
selfer found in Oregon and Washington.
DNA was isolated from one or two flowers of individual
plants (see table 2 for sample sizes) using a standard
maxi-prep protocol (Doyle and Doyle 1987).
Microsatellite
Screening
and Sequencing
A genomic library was constructed by digestion of
M. guttutus genomic DNA (ca. 1 pg) with Suu3A1, ligation to BumHI-digested
pUC 19 plasmid (Pharmacia),
and transformation
of fresh competent
E. coli cells
(DHSo). Transformed E. coli were plated on LB plates
containing
ampicillin
(100 pg/ml; Sambrook, Fritsch,
and Maniatis 1989). Oligonucleotides
complimentary
to
(GA/CT)i2 repeats were synthesized and purified using
thin-layer chromatography
(TLC). The oligonucleotides
were end-labeled
with [Y~~-P]ATP and T4 polynucleotide kinase (Pharmacia) and column purified using standard protocols (Sambrook, Fritsch, and Maniatis 1989).
Plates with transformed
colonies
were alkaline
Southern blotted onto nylon membranes (Hybond) using
a standard protocol (Sambrook, Fritsch, and Maniatis
1989). Membranes were prehybridized
in 5 X SSPE (0.9
M NaCl, 50 mM NaH2P04, 5 mM EDTA); 5 X Denhardt’s (0.2% ficoll400,0.5%
polyvinylpyrolidine,
0.2%
bovine serum albumin); 0.1% SLS, and 50 pg/ml denatured carrier DNA at 60°C and hybridized in the same
solution overnight with radiolabeled probe at a concentration of 1.O X lo6 cpm/ml of hybridization
buffer at
60°C. Membranes were washed three times in 2 X SSC,
0.1% SLS at 55”C, allowed to dry, and exposed to X-ray
film for 4-8 h. Positive colonies were identified, and
those showing the strongest signal were selected from
the original genomic library and plated out on LB-ampicillin. Another round of colony lifts, screening, and
plating was then performed.
Positive colonies were
grown on LB-amp media overnight, and recombinant
plasmid DNA was isolated from the positive clones using a standard maxi-prep (Sambrook, Fritsch, and Maniatis 1989). The isolated plasmid DNA was run on a 1%
agarose gel, and Southern hybridization
(under the same
conditions as above) was performed with the synthetic
oligo to confirm the presence of GA repeats in the inserts. Fourteen clones were sequenced via the Sanger
dideoxy-chain-termination
method of alkali-denatured
plasmid DNA using the Sequenase kit (U.S. Biochemical) and an automated laser fluorescence sequencer (Applied Biosystems, HSC Biotech).
Primer Design
and PCR Analysis
Sequences containing
simple sequence repeats of
more than 12 repeat units were chosen for PCR primer
design. Primers were designed using DNAsis Prov. 3
(Hitachi) with parameters designed to ensure stringent
Microsatellite
Table 1
Primers for Microsatellite
Locus
Mimct-8
Loci, PCR Conditions,
Microsatellite
Forward
........
.......
Mimct-I 1
.......
Mimct-12
.......
Mimct-14
.......
KAMCT),,
Mimct-15
.......
(ThNdTMTh6
........
Mimct-c
........
Mimct-k
........
and Reverse Primers
-Annealing
Temperature
(“C)
5’-ATATGGCTTCTCAGAGGATG-3’
5’-GGAGCTTCTTAATGCTTTAGAAACC-3’
5’-ACGTCAAATTTCCAAATTCGCTCCC-3’
5’-AACTGCTCCACAAATCATGGATACC-3’
5’-CTTCAACTTTGCATGGGCCATAAGC-3’
5’-TTGCAGCTTTCTCCAGACCTCCGGG-3’
5’-CTCCGATGAAGCATTCGAGATTTCA-3’
5’-TGAATCTGAAGAAGATCCCCGAGCA-3’
5’-CCCCCTCTTTGGTAGAGGTAATTCT-3’
5’-AATTCCCGTCGTTCGCCCATGTTTC-3’
5’-GTTCGTCGTGTGTAAATAGGCGAG-3’
5’-GGCACCTTCGGTTAATTCACACAGA-3’
5’-CTGTGTGAATTAACCGAAGGTGCCT-3’
5’-GGTCGACTCTAGAGGATCAT-3’
5’-CATTGCTCCTGCAAATCGAG-3’
5’-CGCGGGCTTTACGCAATCGATCTCG-3’
5’-CATCCCACTTAGCTCATATCAATCC-3’
(AT),dGA)>sb
AAGAGGAAGAAG
(CA),,
in Mimulus
spp.
1025
of Loci
5’-GATCATTAGTTATATCTGAC-3’
Mimct-IO
Mimca-b
and Descriptions
Evolution
PCR Product
Size (bp) and
Rangea
WWM
(mM)
55
1.7
-170
50
1.5
55
1.2
52
1.7
50
2.0
50
1.5
-305
(155-470)
-138
(80-200)
-335
(175440)
-120
(70-2 15)
-150
55
1.5
55
1.5
49
2.0
-220
(140-370)
-170
-170
(130-175)
a Initial PCR product size based on the sequenced clones used to design primers. Range of PCR products observed after population assay.
b Complete sequence unobtainable; interrupted or homoplastic repeats present (Estoup et al. 1995a).
PCR annealing conditions. To avoid primer dimer conformations, simulations of the PCR reactions were performed using the program AMPLIFY.
PCR reactions for all analyses were similar to the
following protocol. Reactions were performed in a volume of 50 ~1 in a Per-kin Elmer thermocycler
or in
96-well plates in a Stratagene Gradient 96 Robo-thermocycler. The reaction mixture contained
1 X PCR
buffer (50 mM KCl, 10 mM Tris [pH 8.31, 0.01% gelatin), 0.2 mM of each deoxynucleotide,
1.5-2.0 mM of
Table 2
Microsatellite
Variability
MgC12, 0.5 U of AmpliTaq Polymerase (Perkin ElmerCetus), 500 r&l of each primer, and -0.1 pg of template
DNA. Temperature conditions were as follows; 94°C for
3 min, 50°C for 1 min, and 72°C for 1 min for one cycle;
94°C for 1 min, 55°C for 1 min (in some cases 50°C
and 52”C), and 72°C for 1 min for 34 cycles; and a final
elongation step of 72°C for 10 min prior to cooling at
4°C.
The loci, descriptions, lengths of repeats, size ranges of PCR products, and PCR conditions are described
in Mimulus Populations
M.
M.
GUTIATUS
NASUTUS
Locus
Mimct-11.
.....
Mimct-12.
.. ...
Mimct-14.
.....
n,
n
H
Mimct-b.
......
n,
n
H
Mimct-10.
... ..
n,
n
H
Mimct-k.
.... ..
n,
n
H
n
H
na
n
H
n,
Average n, . . . .
Average H . . . .
PLP9,. . . . . . . . .
Allozyme
H
...
138
142
48
0.83
9.00
40
0.26
4.00
48
0.30
2.00
38
0.78
5.00
36
0.50
5.00
28
0.57
4.00
44
0.74
7.00
42
0.53
4.00
44
0.08
3.00
42
0.68
5.00
36
0.70
6.00
36
0.70
5.00
46
0.46
4.00
4.67
0.52
100
4.67
0.56
100
0.20
143
M.
M. G. VAR.
LACINIATUS
DEPAUPERMUS
606
711
712
713
4200
48
0.45
2.00
48
0.81
6.00
40
0.76
8.00
26
0.56
5.00
30
0.49
3.00
22
0.52
3.00
23
0.50
3.00
28
0.61
4.00
36
0.64
6.00
22
0.68
5.00
36
0.00
1.oo
34
0.38
3.00
26
0.80
4.00
32
0.71
6.00
42
0.62
4.00
36
0.00
1.oo
42
0.18
2.00
40
0.50
2.00
18
0.69
3.00
38
0.36
3.00
36
0.61
4.00
42
0.00
1.00
36
0.15
3.00
24
0.00
1.oo
36
0.33
3.00
26
0.77
5.00
44
0.39
4.00
36
0.09
2.00
44
0.20
3.00
36
0.56
4.00
36
0.17
3.00
30
0.82
8.00
36
0.20
3.00
40
0.00
1.00
36
0.00
1.00
34
0.59
5.00
36
0.00
1.00
32
0.82
5.00
2.40
0.42
75
4.00
0.49
83
3.50
0.40
67
2.00
0.37
83
2.00
0.23
33
3.33
0.37
100
2.67
0.27
50
0.23
0.09
-
-
202
M.
PLATYCALYX
0.22
0.10
NOTE.--n is the number of gametes sampled, H is expected heterozygosity, and n, is the number of alleles observed at the locus. PLP,, is the percentage of
polymorphic loci.
1026
Awadalla
and Ritland
in table 1. Repeat lengths ranged from 13 repeat units
to more than 50 repeats. For this study, ca. 24 individuals from each of nine populations were assayed for six
microsatellite
loci, which totaled over 1,500 PCR reactions. Of the nine loci for which primers were designed,
six gave consistent
amplification
across all taxa and
were polymorphic.
Separation
of Amplified
Microsatellite
Alleles
A novel, nonradioactive
method was used to separate and visualize
alleles: horizontal
polyacrylamide
gel electrophoresis
followed by ethidium bromide staining. Seven-microliter
aliquots of PCR products were
mixed with one fifth volume of loading buffer (0.25%
bromophenol
blue, 40% [w/v] sucrose in water). Gels
consisted of 10% polyacrylamide
(0.75 X TAE) in 1 X
TAE buffer and were run in a Sea-Elchrom Electrophoresis tank at 6 V/cm for 4-5 h in a circulating buffer
set at a controlled temperature of 20°C. Ten- and lOO-bp
ladders (Gibco-BRL)
were used as size standards. Gels
were subsequently
stained in an ethidium bromide bath
and destained for - 1 h before visualizing with UV light.
Data Analysis
Larger alleles were pooled to the nearest 5 bp,
while smaller alleles were pooled to the nearest 2 bp.
After scoring, gene frequencies were calculated, and the
mean number of alleles per locus, the expected heterozygosity, and the total heterozygosity
were calculated.
The program FSTAT ver. 1.2 (Goudet 1995) was used
to estimate Wright’s fixation indices @‘is, FST; Wright
1965) using Weir and Cockerham’s (1984) method, and
to calculate
expected heterozygosity
using Levene’s
(1949) correction for small samples. FST was estimated
for the three populations of A4. guttutus and M. Zaciniatus separately. Confidence limits on the F statistics were
estimated from jackknifing
over samples and loci. The
significance of the F statistics (the null hypothesis being
that F,, is not greater than 0) was calculated per locus
and over all loci using permutations
of alleles within
samples and between samples (Excoffier, Smouse, and
Quattro 1992; Hudson, Boos, and Kaplan 1992; Goudet
1995). These tests were performed to avoid the deficiencies of existing tests such as the x2 test (Workman
and Niswander
1970; Hart1 and Clarke 1989), which
cannot use sparse samples (expected classes less than
3), and Fisher’s exact test, which cannot incorporate the
nonindependence
of loci when data depart from HardyWeinberg equilibrium
(Goudet 1995).
The Stepwise
Mutation
Model
The one-step SMM was tested for five of the six
microsatellite
loci in M. guttatus and A4. laciniatus
(Mimct-14 was excluded due to low polymorphism).
Following Valdes, Slatkin, and Freimer (1993) and Di
Rienzo et al. (1994), the gene genealogy of a sample of
n alleles was generated by computer simulation using a
modification
of Hudson’s (1990) coalescence
routine.
The genealogy was created by working upward from the
root given the parameter 2Nt.~ (Hudson 1990; Valdes,
Slatkin, and Freimer 1993). To compare the theory with
the Mimulus data, 2Np was estimated using the allele
size variance observed for each locus (see below), and
confidence intervals of genetic diversity were obtained
as the bottom and top 2.5 percentiles of 1,000 replications. Overlap of the simulated confidence intervals with
the observed diversity for each locus was used as the
basis for acceptance of the model. Runs were performed
separately for (1) random mating panmictic populations
and (2) selfing populations (using estimated selfing rates
found in M. Zaciniatus). To model changes of population
size in the selfing species, a “bottleneck
function”
(Hudson 1990) was utilized in the program. In this, both
the time backward to the bottleneck and the proportional
reduction of population size are specified, and different
parameters are tried for each locus and species in an
attempt to account for the observed specieswide allele
size variation.
Mimct-11, Mimca-b, and Mimct-k had much smaller flanking regions relative to their respective repeating
arrays than did Mmct-10 and Mimct-12, which had perfect and imperfect repetitive regions flanking the repeat
array. These regions are likely to contribute to variation
at these loci and may themselves be evolving toward
perfect repeats via the mutation process modeled here
(Di Rienzo et al. 1994; Garza, Slatkin, and Freimer
1995). There is no reason to exclude such compound
microsatellites,
as they are likely to evolve by the same
mutational
mechanisms
as do perfect repeats (but see
Estoup et al. 1995b).
Inferences About Colonization
in Selfers
For a population of constant size N at equilibrium
under mutation and genetic drift, the expected variance
in repeat number is m2 = 2Npa2, where I_Lis the mutation rate and u2 is the net increase in variance under
mutation (Shriver et al. 1993; Valdes, Slatkin, and Freimer 1993). The quantity 2N is also the expected time
(7) in the past that two randomly selected genes share a
common ancestor (Hudson 1990; Di Rienzo et al. 1994).
If l.~ is specified and o2 is assumed to equal one (onestep mutation), then m2/p estimates 2N = 7. Now, if
population size varies, r differs from the neutral expectation of 2N. In particular, if a population has a bottleneck backward at time t, then no alleles have a common
ancestry after time t, and, hence, the average coalescence time T is less than t.
The effect of a bottleneck is to change a continuous
distribution of allele size to a more clustered or clumpy
distribution of allele sizes. Thus, to infer bottlenecks (or
a colonization
event), one can use the discrepancy between the variances in allele size within populations (averaged over populations)
versus for the species as a
whole (variances
calculated
with allele frequencies
pooled across populations).
The parameters for the bottleneck simulation were defined by the level of diversity
calculated through simulations using NI_Las estimated by
the average within-population
variance.
Results
Frequencies of Simple Sequence Repeats in M.
guttatus
Assuming an average insert size of 256 bp among
the ca. 2,500 recombinant
plasmids in our genomic li-
Microsatellite
brary, from which 22 strongly positive clones hybridizing to (GA),, were detected, we estimate that there is
an average of one GA/CT repeat region every 29 kb in
M. guttatus DNA. This estimate is similar to that reported for GA repeats in other plant genomes (Lagercrantz, Ellegren, and Andersson
1993; Morgante and
Olivieri
1993; Smith and Devey 1993; Wang et al.
1994), although our high stringencies for hybridization
likely selected for longer repeats (>30 repeats), reducing the density of detected loci.
Microsatellite
Polymorphism
The six microsatellite loci were highly polymorphic
both within and among species (table 2). The average
numbers
of alleles observed
within populations
and
among all the populations
surveyed were, by locus:
Mmct-1O: 2.2, 14; Mmct-11:
5.4, 18; A4imct-12: 2.6,
15; Mimct-14: 1.9, 8; Mimca-b: 3.8, 21; Mimct-k: 5.0,
24 (locus means: 3.4, 16.7). The mean number of alleles
per locus and total number of alleles ranged from 2.00
+ 0.78 to 5.4 2 2.13 (the actual number of alleles is
likely greater, as allele sizes were binned). The total
number of alleles was especially high for loci Mmca-b
and Mimct-k, yet Mimca-b also had the fewest shared
alleles across species. This is reflected in the large range
in allele size for this locus. Also, in contrast to the general pattern observed here and in other studies, at locus
Mimct-k, the number of alleles was greatest in the “nonsource species ” (species from which microsatellites
were not isolated from libraries) M. Zaciniatus, M. platycalyx, and M. guttatus var. depauperatus
(all inbreeders). The number of alleles averaged for outcrossing species (M. guttatus and M. nasutus) was greater than that
for selfing species (M. laciniatus, A4. plat-ycalyx, and M.
guttatus var. depauperatus);
however, this difference
was not statistically significant (Fl,lo = 2.60, P > 0.05).
Mimulus guttatus and M. laciniatus shared few alleles, with each species exhibiting many unique alleles
(contributing
to larger allele size ranges; see table 1).
Nonshared
alleles in selfing populations
either were
fixed in the population or occurred at low frequencies;
only populations
of M. Zaciniatus and M. guttatus var.
depauperatus were monomorphic
at any locus (table 2).
Locus Mmct-11
was very polymorphic
across all populations except for M. guttatus var. depauperatus,
a putative selfing variety for which no previous estimate of
selfing has been determined.
Locus Mimca-b had the
highest number of alleles, but also the least number of
shared alleles between species.
Average expected heterozygosity
values (HE or
gene diversity) were high (relative to those from previous allozyme studies in plants) for all populations and
varied across populations
and species (table 2). Values
per population
across outcrossing
and selfing species
ranged from 0.56 2 0.25 to 0.23 ? 0.40, but the range
in diversity was much narrower within outcrossing than
within inbreeding
species. The average HE’s for outcrossing and selfing populations were 0.58 + 0.11 and
0.33 ? 0.08, respectively,
which were significantly different from each other (GLM, f,,49 = 8.62, P < 0.01).
The HE differences between M. guttatus and M. lacinia-
Evolution
in Mimulus
spp. 1027
tus were also significant (F1,31 = 7.97, P < 0.01). Total
genetic diversities (HT’s) for M. guttatus and M. laciniatus were calculated to be 0.657 + 0.24 and 0.642 +
0.30, respectively
and were not significantly
different
=
0.675,
P
>
0.05).
(F 1,lO
The observed heterozygosities
(Ho) also differed
significantly
between outcrossing
and selfing populations (0.37 + 0.04 and 0.12 + 0.09, respectively;
Fl,49
= 19.13, P < 0.001). As well, Ho values for M. guttatus
and M. Zaciniatus significantly
differed (0.405 + 0.01
and 0.10 5 0.06, respectively;
F1,31 = 30.86, P <
0.001). No heterozygotes
were observed in one selfing
population (M. Zaciniatus, population 711). Both lower
HE and lower Ho values were observed for one M. guttutus population (143), which may indicate a recent bottleneck event, genetic isolation, or a change in outcrossing rate. However, there were difficulties amplifying loci
from individuals
for this population (only three out of
six loci gave storable amplifications),
which may affect
estimates of Ho and HE for this population.
Still, the
high level of polymorphism
at each locus provides information about genetic diversity and selfing rates in this
population.
Microsatellite-based
measures of diversity per species were higher than allozyme estimates, as would be
expected. Yet, the ratio of average HE for outcrossers
versus selfers was almost 2 for allozymes but only 1.6
for microsatellites.
There was a significant relationship between average microsatellite
Ho and allozyme genetic distance
from M. guttatus (allozyme data from Ritland and Ritland 1989; linear regression; r* = 0.893, P < 0.01). This
is because more distantly related taxa from A4. guttatus
tend to be selfers. By contrast, the expected microsatellite heterozygosity
HE was not associated with these genetic distances (r* = -0.14, P > 0.05), showing there
is no effect on measures of diversity when using microsatellites from a nonsource taxon.
Gene diversity was negatively correlated with selfing rate (r = -0.39, P < O.Ol), as was number of alleles
per locus (r = -0.40, P < 0.01; fig. 1). Also, with one
outlier removed, we observed a strong significant relationship between the among-locus variances of diversity
for each population and the selfing rate (r = 0.92, P <
0.00 1).
Population Subdivision,
and Selfing Rates
Heterozygote
Deficiencies,
Table 3 gives estimates of FIs (termedf) and selfing
rates for each population, assuming inbreeding equilibrium, S(J), where f = S/(2 - s). All values of F,, were
significantly
different from zero (P < 0.001). Mimulus
guttatus var. depauparatus
and M. laciniatus showed
80%-95% selfing (which accords with their reduced floral size and greater autofertility),
while other taxa
showed selfing rates of 40%-50%
(“mixed mating”).
Table 4 gives FST values for M. guttatus and M. laciniatus (each taxon sampled for three populations)
by
locus. Their values indicate that the more highly inbreeding M. Zaciniatus has greater among-population
differentiation
than does M. guttatus. FIT values also in-
1028
Awadalla
and Ritland
a
Table 4
Estimates
of Population
Differentiation,
FsT, for M.
guttatus and M. lacinhtus
Locus
Mimct-10
Mimct-11
Mimct-12
Mimct-14
Mimct-b
Mimct-k
........
........
........
........
.........
.........
Mean
1
l
t
l
l
01
0.6
0.4
M. laciniatus
0.53
0.20
0.63
1.06
0.21
0.46
0.37
0.47
0.90
0.85
0.87
0.50
2 0.20
+- 0.12
2 0.35
2 0.49
2 0.10
z 0.41
0.32 2 0.09
+
+
+
+
2
+
0.20
0.07
0.06
0.03
0.35
0.35
0.60 + 0.09
NOTE.----Standard errors for each locus were calculated from jackknifing over
populations, and standard errors for totals were calculated from bootstrapping
over 10~1. P(F,,> 0) < 0.001was calculated for all estimates using permutations of alleles per locus and over loci (Goudet 1995).
t
1
0.8
M. guttatus
selfing rate
step SMM to data at each of five loci in A4. guttatus and
M. Zaciniatus, for two different demographic
assumptions. Table 5 gives results of the first assumption (random mating); only three estimates of total genetic diversity fell within the simulated confidence limits (see
table 5). For all other loci, the one-step SMM could be
rejected because the heterozygosities
for both M. guttutus and M. Zaciniatus, as generated by simulations of
the SMM, were significantly
lower than those observed
in the actual microsatellite
data.
b
0.8
l$
0.7
l
l
l
l
l
l
::
I
Colonization
Events and Expectations
in Selfing A4. laciniatus
0.6
0.8
selfing rate
FIG. 1 .-Microsatellite
variation in relation to inferred selfing rate
(with fitted regressions).
a, Number of alleles versus selfing rate. b,
Expected heterozygosity
versus selfing rate. Each point represents a
population variable for a locus.
dicated higher global heterozygote deficit in A4. Zaciniatus than in M. guttatus populations (significantly
different from zero, P < 0.001, data not shown).
Tests of the Stepwise
Random Mating
Mutation
Model Assuming
Tables 5 and 6 present results of the procedure of
Di Rienzo et al. (1994), which tests the fit of the oneTable 3
Estimates of Inbreeding Coefficients f and Selfing Rates
(inferred fromh in Mimzdus Based on Microsatellite Data
Species
M. guttatus
Population
....... ..
M. nasutus. . . . . . . . . .
M. platycalyx. . . . . . . .
M. laciniatus . . . . . . . .
M. guttatus var.
depauperatus
......
The skewed distributions
in allele size and large
numbers of unique alleles observed for M. Zaciniatus
(fig. 2) suggest that colonization
and subsequent isolation of populations is common in this species. The differences between the variances in allele size computed
within populations
versus for pooled populations
were
much higher in this selfing taxon versus M. guttutus.
Our simulations of the SMM used parameters estimated
from average variances for each population in A4. Zaciniatus. Four of five comparisons
(between the model
prediction of HE and that observed in the data) fell within the simulated confidence limits (table 6). In general,
Table 5
Comuarison of Simulation Results of the One-Sten1 SMM
with *Observed Values in M. gut&&s and M. Zaciniudzm
Population and
Group
Locus
Mimct-11
Mimct-k
P
. . . . M. guttatus
.....
SC?>
138
142
143
202
606
711
712
713
0.30
0.38
0.31
0.28
0.36
1.oo
0.84
0.56
0.46
0.55
0.47
0.44
0.53
1.00
0.91
0.72
4200
0.67
0.80
Under the SMM
Mimca-b. . . . .
Mimct-12
....
Mimct-10
... .
M.
M.
M.
M.
M.
M.
M.
M.
M.
laciniatus
guttatus
laciniatus
guttatus
laciniatus
guttatus
laciniatus
guttatus
laciniatus
@?I
HT
Confidence
Interval for
Simulated HT
34.38
18.88
24.53
38.88
28.99
39.57
74.08
1.28
56.84
3.30
0.63
0.72
0.56
0.85*
0.87*
0.76
0.53
0.03
0.72
0.78”
0.78-0.91
0.80-0.89
0.73-0.90
0.78-0.92
0.76-0.91
0.79-0.92
0.83-0.93
0.15-0.73
0.83-0.93
0.3 l-O.79
Observed
NoTE.<omparison
of simulated HT 95% confidence intervals to observed
HT values. The variances in allele size, a,,,,
2 for each locus were used to set the
parameters for each simulation for each comparison (see text). Asterisks mark
values that fall within the computed confidence limits.
Microsatellite
Evolution
in Mimulus
spp.
1029
Table 6
Results of One-Step Mutation and Bottleneck Simulations with Comparisons to Observed
Values for the Selfer M. Zuciniiztzm
Mean WithinPopulation
Variance
Variance of
Pooled
Populations
Observed
Mimct-11. . . . . .
16.27
18.88
0.54”
0.54-0.79
t = 20, r-f = 1,250
t = 4, ?-f = 10
t = 1, q = 1.5
Mimct-k. . . . . . .
9.70
38.88
0.65*
0.50-0.80
39.57
0.35
0.76-0.89
t = 4, rf = 125
t=l,rf=7
t = 0.5, rf = 3
t=5,$=8
t=3,rf=2
t = 1, Q- = 1.25
t = 5, rf = 85
t = 3, rf = 10
t= l,rf=2
t=3,rf=
loo
t= 1.5,$=20
t = 0.5, rf = 8
Locus
Mimca-b
......
16.4
HE
Confidence
Interval of
Simulated HE
Mimct-12.
.... .
0.73
1.28
0.03”
0.00-0.68
Mimct-IO.
.....
1.85
3.30
0.40”
0.00-0.74
Bottleneck
Parameters t,
rf
NOTE.--The
mean of the variances in allele size within populations for each locus was used to estimate N,k to set the
initial parameters for each simulation for each comparison (see text). Changes in population size were simulated with the
bottleneck function to mimic drastic changes in population size. rf is the factor by which the population size differs from
the current population size. t is the relative time since the population changed (see Hudson 1990). Asterisks mark values
that fall within the computed confidence limits. To account for the variance in allele size, population reductions were
simulated.
SSR variability for each locus in M. Zuciniatus fell just
within the bottom confidence limits, due largely to pooling of alleles, which reduces our observed diversity estimates. HE for iVimca-b was much lower than the bottom confidence
limit. Allele size variances averaged
among loci were lower than the pooled allele frequency
data for M. guttutus, but when similar simulations were
performed for individual
M. guttutus population
data,
only expected heterozygosity
for loci Mimct-11
and
Mimct-12 fell within the confidence limits of the onestep model (data not shown). All other loci fell below
the confidence
limits, suggesting that other processes
such as migration are contributing
to the variation observed at the loci in these populations.
Estimating
Coalescent
or Colonization
Events
Estimated mutation rates have been previously reported for dinucleotide loci (Schlotterer and Tautz 1992)
to be in the range of 1O-2 to 10e5. As discussed earlier,
these values can be used to calculate effective population sizes, based on observed allele size variance, via
the relationship m2 = 2Nepcr2 (Shriver et al. 1993) if we
assume a one-step mutation model (a2 = 1). Assuming
this, we find values of N, for M. Zaciniatus populations
to range from about 5.24 X lo2 to 10.19 X lo5 individuals. Also, as discussed earlier, we can use the relationship 2N = r to estimate the time since population expansion r (or the time since colonization)
for M. Zaciniatus (table 7).
Discussion
Few
the effects
variation,
Mimulus,
studies have used microsatellite loci to address
of alternate mating systems on neutral genetic
and this is the first such study for plants. In
the effect of selfing on microsatellite
diversity
is similiar to that found for allozyme diversity in these
taxa: within-population
genetic diversity is lower in selfers than in outcrossers. However, the proportional
reduction in microsatellite
diversity in selfers relative to
that in outcrossers is less than that documented for allozyme variation.
Of interest is the information about population history provided by the distribution
of allele sizes within
and among populations.
The observed level of polymorphism fits the expectations of a model for variation
generated
through slippage during DNA replication
(SMM). Coalescent theory developed for the SMM allows us to estimate coalescent times for inbreeding taxa.
Based on simulations, it appears that bottlenecks in population size affect species wide diversity in selfing populations, although HT did not significantly
differ between mixed-mating
A4. guttatus and A4. laciniatus, an
observation that differs from some allozyme-based
stndies (e.g., Fenster and Ritland 1992). In addition, the increased polymorphism
at microsatellite
loci gives greater power to estimate inbreeding coefficients and detect
outcrossing events.
Microsatellite
Loci Properties
Among
Mmulus
Taxa
As inferred from colony screens, M. guttutus has
numbers of microsatellite
loci similar to those of other
plants. Of nine primer pairs tested, six were polymorphic. Primers also amplified well across species. In contrast, Roder et al. (1995) found more limited amplification across wheat, rye, and barley. Studies in mammals have had greater success in cross-taxa amplification (e.g., Bowcock et al. 1994; Pepin et al. 1995).
Primer site conservation
in yellow monkeyflowers
may
be due to recent divergence or to introgressive
hybridization (Vickery 1964; unpublished
data).
1030
Awadalla
and Ritland
a
Locus Mimca-b
1.00 0.90 0.80 0.70 0.60 0.50 0.40 -
p
0.30 0.20 0.10 0.00 -’
285
305
295
315
325
335
345
355
365
allele size (in base pairs)
b
Locus
Mimct-k
0.80
0.60
78
86
92
98
104 110 116 122 128 134 140 146 152 158
allele
FIG. 2.-Allele
frequency distribution
frequency of alleles occuring in population
for three M. laciniarus populations for (a) locus Mimca-b and (b) locus Mimct-k. Black denotes the
7 11, dark grey denotes that in population 7 12, and light grey denotes that in population 7 13.
Large differences
in allele size were observed at
SSR loci, in line with other studies. Inbreeders seem to
have particularly
large ranges (see Viard et al. 1996).
High mutation rates and strong genetic drift increase the
allele size range; yet, excessive size range is undesirable, as the population information
content is less reliable when allele sizes are not shared across populations.
Table 7
Coalescent Times (generations) for 44 i’uciniutza
Populations Based on the SMM
A4. L,.~CINIATUS
(WITHIN
711
Variance in allele size . . . .
Assumed mutation rate
10-z.................
lo-3.................
10-4.. . . . . . . . . . . . . . . .
5.24
524
5,240
52,400
164 170
size (in base pairs)
712
5.24
524
5,240
52,400
POFTJLATI~NS)
713
10.19
1,019
10,190
101,900
Nauta and Weissing (1996) demonstrated
that, given a
high mutation
rate, random-mating
populations
will
reach uniform allele frequency distributions
over time,
thus limiting population information. Genetic drift slows
down this homogenizing
effect by promoting diversification among populations,
as it would among selfing
populations, where effective population sizes are smaller
and admixture is limited. On the other hand, if mutation
is moderate (for SSRs 10e5) and drift is strong, few
alleles will be shared among recently diverged populations, providing little phylogenetic
information.
Polymorphism
in A4imuZus varied across loci. A
number of factors, either stochastic or deterministic,
could contribute to this variation and may involve the
mode of mutation. Mutation rates may depend on the
repeat type and number (although Valdes, Slatkin, and
Freimer [1993] showed there was no relationship
between allele size and level of polymorphism).
Rates may
depend on the sequences of the flanking regions or the
Microsatellite
location of the microsatellite
locus (introns, flanking
coding sequences, etc.). The latter effect may favor evolution toward smaller repeat arrays and fewer alleles
(Garza, Slatkin, and Freimer 1995). Deterministic
factors such as linkage to novel deleterious (background
selection)
or advantageous
(hitchhiking)
alleles may
cause the loss or initial fixation of alleles, yet variation
at these loci should quickly recover due to high mutation
rates (Slatkin 199%). The effects of low mutation rates,
background
selection, hitchhiking,
and bottlenecks
are
difficult to disentangle (Slatkin 199%; Nordborg, Charlesworth, and Charlesworth
1996). At least, bottlenecks
tend to create genomewide reductions in diversity, while
mutational
variability
causes localized effects. We did
not observe global reductions in diversity across all loci,
and, in fact, we observed a positive correlation between
the among-locus
variance of diversity and the selfing
rate. Therefore, we think that changes in the overall diversity are not solely due to bottlenecks and colonization
events, or to reductions in N, caused by the selfing habit,
but are also due to differences in linkage relationships
between selfers and outcrossers.
Flanking many of the sequenced dinucleotide
repeats in A4. guttutus are AT-rich regions or imperfect
repetitive regions of varying size ranges. Primers flanking these putatively unstable regions were designed to
ensure amplification
both within and between species.
Thus, polymorphism
at these loci may also occur in the
flanking regions and involve length differences
other
than dinucleotide
additions or deletions. The evolution
of a single microsatellite
locus from such “undeveloped” regions (consisting of imperfect repeating units)
may involve other mutational mechanisms
such as unequal crossing over and could cause dramatic mutations
of allele sizes. Other types of mutation, such as point
mutations, may also hinder the replication slippage process through
the disruption
of perfectly
repeating
regions, creating mosaics of interrupted or adjacent repeats (Fitzsimrnons,
Moritz, and Moore 1995). Persistence of microsatellite
arrays, albeit in modified form,
has been reported among divergent mammalian families;
however, the ,proportion of polymorphic
loci seems to
drop rapidly with increasing evolutionary
divergence in
mammals (Stallings et al. 1991; Fitzsimmons,
Moritz,
and Moore 1995).
Microsatellite
Diversity and Inbreeding
Outcrossing and Selfing Taxa
Among
It is now well known that, for a wide range of plant
species, the mating system affects patterns of genetic
variability both within and among populations. Hamrick
and Godt (1990) generalized that in outcrossed species,
the majority of the total genetic diversity (Z&) resides
within (Hs) populations,
while in selfing species, more
is proportioned
among populations
(FST). Indeed, mean
FST values for microsatellites
were greater among populations of A4. Zuciniatus than among M. guttatus populations, and selfing populations
were characterized by
relatively high HT values and low Hs values. Thus, selfing Mimulus populations
maintain as much diversity as
outcrossing populations,
but more is distributed among
Evolution
in Mimulus
spp. 103 1
populations (see Schoen and Brown 1991). Colonization
events are thought to be important in patterning
this
variation, as colonization,
which is frequently associated
with selfing populations (Schoen and Brown 1991), increases the among-population
component of genetic diversity but decreases within-population
heterozygosity
and numbers of alleles (Waples 1989). The observed
frequency distributions
of alleles and the large difference in the variance of allele sizes within populations
relative to that among populations is indicative of past
colonization
events.
With selfing species, novel alleles are less likely to
spread to other populations. If a population experiences
a bottleneck, the novel alleles are lost and HT is reduced.
In outcrossing
species, novel alleles are buffered from
being lost through migration to other populations. HT’s
for outcrossing M. guttatus and selfing M. Zuciniatus did
not significantly
differ. Yet, HT for A4. Zuciniatus was
significantly
lower than expected for the SMM without
bottlenecks (table 5), suggesting that colonization
does
influence specieswide diversity. If colonization
occured
at a time in the distant past, SSR diversity would be
allowed to largely recover given the high mutation rates
observed at these loci.
Slatkin (1995~) suggests that for loci evolving via
a one-step
or multi-step
stepwise mutation
process
(where mutations of greater than one or two repeat units
are permitted), RST, an analogue of FST, is more reliable
than FST. RST was developed for loci mutating at a high
rate via a replication/stepwise
process and allows for the
possibility
of mutation reversals (Slatkin 1995a). As
with Fsr, migration rates can be inferred from RST estimates (see below). However, no significant difference
between estimates of Rho (an estimator of RST; Michalakis and Excoffier 1996) and Weir and Cockerham’s
(1984) FST were found for microsatellites
in Mimulus
(unpublished
data). As the mutation process approaches
the infinite-alleles
model (mutations other than stepwise
increases or decreases in size are contributing
to variation), the two estimators
become the same (Rousset
1996). Gene diversity estimates were almost always on
the low end of range of confidence limits derived from
simulations.
Larger mutations
may be increasing
the
sizes of the confidence limits (see next section), which
may account for the similiar estimates for the two estimators.
Microsatellite
Evolution
Mutation Model
and the One-Step
Stepwise
When we assume random mating and no bottlenecks, the one-step stepwise mutation model (SMM)
predicts too much among-population
variation in Mimulus. However, for the selfing M. Zaciniatus, if we assume no gene flow among populations
(high FST) and
predominant
selfing (high Frs), the observed allelic variation within populations
does fit the SMM model. Although the bottleneck simulations
are not necessary to
test the SMM, the remaining variability of the species
as a whole can be explained by bottlenecks of various
magnitudes
and times in the past, simulating historical
colonization
events. The bottleneck
simulations
also
1032
Awadalla
and Ritland
suggest that polymorphisms
do not predate population
divergence or colonization
and that allelic variability in
selfing populations
is due primarily to strong drift and
high mutation rates.
Our approach is similar to those of Valdes, Slatkin,
and Freimer (1993) and Di Rienzo et al. (1994) in that
we find approximate
confidence
intervals for withinpopulation diversity statistics but differs as we fit a bottleneck model to the specieswide data. Di Rienzo et al.
(1994) fit a model that incorporates mutations of larger
size. Since the one-step model fit the within-population
data for M. Zuciniatus, we can assume that the bottleneck
routine is an appropriate model for the specieswide data
(Hr), rather than incorporating
a second phase (Di Rienzo et al. 1994) which allows for mutations of more than
one or two repeat units.
For populations of selfing taxa such as M. Zaciniatus, we can estimate the coalescent times of colonization
events (Di Rienzo et al. 1994). These estimates are given
in table 7. We regard such inferences as inappropriate
for the outcrossing A4. guttutus due to the effect of higher migration on the distribution
of allele sizes within
populations. Even for A4. Zuciniatus, the estimates are an
upper limit, for if mutations also involve more repeat
units, then ai, the variance in mutation, is greater than
one (Di Rienzo et al. 1994), reducing coalescent time
estimates. Our simulations
indicate one-step mutations
predominate at SSR loci in Mimzdus, but do not exclude
“multi-step”
mutations at a small but undetectable
frequency.
The pattern of variation within and among populations in M. guttutus is more difficult to assess with the
SMM for a number of reasons. First, our simulations
assumed a branching
phylogeny
of populations.
The
modes of gene dispersal (including the dispersal of seed
through water [Waser, Vickery, and Price 19821) suggest
that a stepping-stone
model of gametic exchange is more
appropriate than a radiating population model (Di Rienzo et al. 1994). For example, M. caespitosus (mountain
monkeyflower)
populations
have a similar range and
habitat to M. guttatus and exhibit closer genetic affinities for populations
along the same stream relative to
populations on different mountains (Ritland 1988). Second, fluctuating population
sizes and outcrossing rates
can also add another level of complication
(Maruyama
and Kimura 1980; Pollack 1987). Third, without taking
into account migration rates between populations,
it is
difficult to determine how much variation is attributed
to one-step mutations versus multi-step mutations versus
gene flow. Crude estimates of gene flow based on pairwise FST and RST estimates suggests that migration is
four times higher in M. guttutus than in M. Zuciniatus
(unpublished
data). Further study is needed of the properties of microsatellite
evolution with the additional factors of metapopulation
structure (gene flow), partial selfing, and variable population size.
In taxa exhibiting evolution of mating system, as
in this section of A4imuZus, past mating system evolution
to selfing) may also influence esti(e.g., outcrossing
mates of coalescent times and ancestral effective population sizes. If a studied selfing population has evolved
from an outcrossing population during the occurrence of
gene coalescence at the microsatellite
loci, the assumption of selfing will be violated over historical time, and
estimates
of coalescent
times will be biased (D. J.
Schoen, personal communication).
This will probably
not affect the interpretation
of coalescent times for individual populations of M. Zaciniatus, but it may affect
higher-level N, estimates, such as those for the species
or section.
Acknowledgments
We thank E Strumas for growth chamber assistance
and M. Ghassemian,
E Ferreira, B. Wong, C. Ritland,
and J. Scott for assistance in the laboratory. We also
thank S. Stewart, J.-Z. Lin, S. Graham, D. Charlesworth,
D. Schoen, and two anonymous reviewers for comments
and encouragement.
This work was funded by a National Science and Engineering
Research Council (Canada)
grant to K.R.
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editor