Microsatellite Analysis Reveals Population Structure

and Population Expansion of Tecia solanivora in

Solanum tuberosum in Colombia
Author(s): D. F. Villanueva-Mejía, V. Ramírez-Ríos, R. E. Arango-
Isaza and C. I. Saldamando-Benjumea
Source: Southwestern Entomologist, 40(1):37-52.
Published By: Society of Southwestern Entomologists
DOI: http://dx.doi.org/10.3958/059.040.0104
URL: http://www.bioone.org/doi/full/10.3958/059.040.0104

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VOL. 40, NO. 1 SOUTHWESTERN ENTOMOLOGIST MAR. 2015

Microsatellite Analysis Reveals Population Structure and Population

Expansion of Tecia solanivora1 in Solanum tuberosum in Colombia

D. F. Villanueva-Mejía2,3,4,5, V. Ramírez-Ríos3, R. E. Arango-Isaza2,4, and

C. I. Saldamando-Benjumea2,4

Abstract. Tecia solanivora (Lepidoptera: Gelechiidae) (Povolny 1973), is the most

important insect pest of potato (Solanum tuberosum L.) in Central and South
America, and Spain. The species was recently reported in Mexico, demonstrating
the power of invasion by this insect. In Peru, the insect is quarantined, and could
become a damaging pest in America. Larvae attack potato tubers, causing
economic loss of 50 to 100%. We used eight microsatellites in 152 individuals from
Antioquia (North), Boyacá (Center), Nariño (South), and Norte de Santander (East),
Colombia, and found T. solanivora genetically different based on an AMOVA test
(FST = 0.094, P < 0.01, RST = 0.175, P < 0.01). The differentiation was supported by
Bayesian analysis where we estimated K = 2. The outcome suggests populations
from Antioquia and Boyacá are genetically similar whereas populations from Nariño
and Norte de Santander differ because of geographical separation from other
regions. We found T. solanivora had not undergone a recent bottleneck effect
suggested by other authors. On the contrary we found that this species has
undergone recent population expansion in the country. We suggest that movement
of potatoes caused genetic homogenization. Movement occurs from Boyacá where
most potatoes are produced, to the rest of Colombia.

Introduction

Microsatellites or simple sequence-repeat loci have been referred to as

variable numbers of tandem repeats and simple sequence-length polymorphisms
throughout the nuclear genomes of most eukaryotes and to a lesser extent in
prokaryotes (Jarne and Lagoda 1996, Vaughan and Lloyd 2003). They are tandem
repeated (usually five to 20 times) in the genome, with a minimal repeat length of 12
base pairs (Goodfellow 1992, Vaughan and Lloyd 2003, Ellegren 2004). They
range from one to six nucleotides in length and are classified as mono-, di-, tri-,
tetra-, penta-, or hexanucleotide repeats (van Oppen et al. 2000). Comparative
studies in insects, with some exceptions (Thoren et al. 1995, Toth et al. 2000), have
suggested that microsatellite length and frequency correlate with genome size
(Hancock 1996). Because of much polymorphism, reliability and reproducibility in

1
(Lepidoptera: Gelechiidae)
2
Facultad de Ciencias, Postgrado de Biotecnología, Universidad Nacional de Colombia, sede
Medellín, Antioquía, Colombia.
3
Escuela de Ciencias, Programa de Biología, Universidad Eafit, Medellín, Antioquia, Colombia.
4
Laboratorio de Biotecnología Vegetal, Corporación para investigaciones Biológicas, Medellín,
Antioquia, Colombia.
5
Address correspondence: dvillanu@eafit.edu.co

37
PCR, and genotyping, these sequences are the most powerful nuclear DNA
markers for population genetic and evolutionary studies (Zhang 2004).
Microsatellites provide insight into the effect of gene flow on the genetic
structure of populations (Freeland 2005) with implications for evolutionary
processes underlying population genetics, conservation biology, and pest
management (Peccoud et al. 2008, Ross and Shoemaker 2008, Ma et al. 2011).
They provide information on genetic variation within and between individuals of a
population based on the numbers of alleles per individual, alleles fixed in a
population, and alleles shared between populations (Freeland 2005). The markers
have been used for several species of insect pests including Bemisia tabaci
(whitefly) (Gennadius 1889) (Hemiptera: Aleyrodidae) from the Asia-Pacific region
where De Barro et al. (2005) found six distinct populations because of no gene flow
among them; invasive behavior of Brontispa longissima (coconut hispine beetle)
(Gestro 1885) (Coleoptera: Hispidae), the most serious pest of Cocos nucifera
(Linn) (Arecaceae: Arecales) in Southeast Asia (Ma et al. 2011); to estimate the
number of founders in the United States of Solenopsis invicta (fire ant) (Buren 1972)
(Hymenoptera: Formicidae) the World Conservation Union considers one of the 100
worst invasive alien species (Ross and Shoemaker 2008); to determine lack of
genetic differentiation among populations of the moth Plutella xyllostella
(diamondback moth) (Linnaeus 1758) (Lepidoptera: Yponomeutoidea) in Australia
(Endersby et al. 2006); and determine little genetic differentiation in the moth Cydia
pomonella (L.) (Lepidoptera: Tortricidae) in Chile (Fuentes-Contreras et al. 2008).
Torres-Leguizamón et al. (2009) isolated and characterized nine
microsatellites from Tecia solanivora (Povolny) (Lepidoptera: Gelechiidae) in
Central America (Costa Rica and Guatemala). T. solanivora is the most important
insect pest affecting potato (Solanum tuberosum L.) in Central and South America,
and Spain (Hilje 1994, Herrera 1997, Torres 1998, García et al. 2002, Pozo and
Zambrano 2002, Niño 2004, Bosa et al. 2005, Valderrama et al. 2007, Pulliandre et
al. 2008, Villanueva et al. 2009, Torres-Leguizamón et al. 2011) because larvae
attack potato tubers in the field and storage, causing economic loss between 50 and
100% (Zeddam et al. 2008). The species was recently reported in Mexico (Roblero
et al. 2011), demonstrating the power of invasion by the insect. In Peru, the insect
is quarantined, and might become a serious pest in America (Torres-Leguizamón et
al. 2011). Control options are based on intensive use of insecticide that might
generate insect resistance and environmental problems (Valderrama et al. 2007).
For these reasons, alternative biological control methods such as use of Bacillus
thuringiensis insecticidal proteins (Valderrama et al. 2007, Villanueva et al. 2009)
and Baculovirus (Baculoviridae) (Cuartas et al. 2009; Chaparro et al. 2010; Quiroga
et al. 2011; Espinel-Correal et al. 2010, 2012) have been proposed.
Fragments of mitochondrial gene Cytochrome B (cytb) were sequenced by
Pulliandre et al. (2008) on T. solanivora collected in Central and South America.
They found few haplotypes of T. solanivora in Colombia, Ecuador, and Venezuela
and believed the main reason was a bottleneck effect. Villanueva-Mejía et al.
(2014) found more haplotypes of the species from Colombia by sequencing
mitochondrial genes Cytochrome Oxidase I (COI) and cytb. The authors studied
population genetics of the moth from four regions of Colombia and found T.
solanivora is genetically structured. By using the Tajima test for analyzing
population reductions or expansions, they found the insect dispersing in Central
Colombia (Boyacá). Considering the results of the two studies, the purpose of this
work was to determine whether microsatellites demonstrate that populations of T.

38
solanivora are genetically structured and whether the species had a population
bottleneck in Colombia. The implications of this work are important for pest
management because populations with little genetic difference are expected to be
controlled more easily than genetically variable populations (Freeland 2005).

Materials and Methods

Larval, pupal, and adult T. solanivora were collected from infested potato
tubers in the field or storage in the regions of Antioquia, Boyacá, Norte de
Santander, and Nariño in Colombia (Fig. 1) during 2011 and 2012. Samples were
put into 70% ethanol in 2.0-ml plastic tubes and stored at -70ºC until processed.

Fig. 1. Map of Colombia showing regions (Nariño, Norte de Santander, Antioquia,

and Boyacá) sampled for Tecia solanivora.

39
 Genomic DNA of T. solanivora was extracted using the protocol described by
Salinas-Hernández and Saldamando-Benjumea (2011), with modification. The
anterior or posterior body of the larva and entire pupa or adult was macerated in
liquid nitrogen followed by homogenization in 400 μl of extraction buffer (100 mM
Tris-HCL pH 8.0, 1.4M NaCl, 0.02m EDTA, 2x CTAB), and 4 Pl of β-
mercaptoethanol. The contents of each tube were mixed by inversion every 10
minutes during 30 minutes of incubation at 65ºC, 300 μl of chloroform were added
and mixed by inversion, followed by centrifugation (10,000x g for 10 minutes at
4ºC).
The supernatant was collected and the chloroform step was repeated. The
aqueous phase was transferred to a 1.5-ml vial, and an equivalent volume of
isopropanol was added. Each sample was incubated at -20ºC for 2 hours, and the
phases were separated by centrifugation (10,000x g for 10 minutes at 4ºC) to obtain
a DNA pellet. The DNA pellet was washed with 200 μl of 70% ethanol and
centrifuged (10,000x g for 15 minutes at 4ºC) twice before left to dry for 30 minutes
at room temperature. The resulting DNA was resuspended in 40 μl of TE buffer
(1x) (TRIS HCL 100 mM, EDTA 10 mM, pH 8.0), and 1 Pl of RNAse A (1 mg/ml)
was added to each tube and incubated for 1 hour at 37ºC for RNA removal. Each
sample was analyzed by electrophoresis, and the DNA concentration was quantified
using a NanoDrop 2000 (Thermo Scientific, Wilmington, USA).
Eight microsatellite loci (1A3, 5D11, 11A8, 15B5, 15F1, 15H1, 16H3, and
16H5) were amplified using primers designed by Torres-Leguizamón (2009), with
conditions standardized in this work. Reactions amplified by each locus contained
25 μl of reaction buffer (1x), (50 mM KCl, 10 mM Tris-HCL, pH 8.0), 2 mM MgCl2,
0.2 mM dNTPs, 0.16 μM of each primer, 0.2 g/liter BSA, 1.5 U of Taq DNA
polymerase (MBI Fermentas, Vilnius, Lithuania), and 100 ng of DNA template. The
amplifications were in an iCycler termocycler (BioRad, California, USA) using an
initial step at 94ºC (2 minutes), followed by 35 cycles at 94ºC (20 seconds), 55ºC
(10 seconds), and 70ºC (20 seconds), with a final extension at 70ºC for 8 minutes.
All PCR products were separated in 10% denaturing polyacrylamide gels and
results were visualized using silver staining. The change of all loci was verified
three times per individual.
Microsatellite genotypes at the eight studied loci standardized by Torres-
Leguizamón et al. (2009) were used to infer population genetic parameters of T.
solanivora among the four sampled regions of Colombia. Methods to analyze
population structure were traditional FST estimates among populations separated
and the estimator most used for microsatellites RST (Slatkin 1995) by using
GENALEX 6.501 (Peakal and Smouse 2006) with 99,999 permutations.
ARLEQUIN 3.11 (Excoffier et al. 2005) was used for analyzing genetic structure of
the samples of the moth (genetic diversity, linkage disequilibria with 999,999
permutations per locus pair, and Hardy-Weinberg equilibrium). We inferred gene
flow rates (Nm) among populations using Nm = 1/(4 × FST).
Population genetics demography was analyzed by the software
BOTTLENECK 1.2 (Piry et al. 1999) because we expected a species that
experienced a recent bottleneck simultaneously decreased the allele number and
expected levels of heterozygosity. However, the allele number (ko) was reduced
faster than the expected heterozygosity. Therefore, the value of the expected
heterozygosity calculated through the allele number by a coalescence procedure
(Heq) was less than the heterozygosity estimated directly from allele frequencies
(He). For neutral markers, in a population with gene mutation drift equilibrium, there

40
is an equal probability a given locus has a slight excess or deficit of heterozygosity
compared to heterozygosity calculated from the number of alleles. In contrast, in a
bottlenecked population, a large fraction of the loci exhibit significantly more than
expected heterozygosity. To measure this probability, four tests were used: a) sign
test, b) standardized difference, c) Wilcoxon´s signed rank, and d) graphical
descriptor of the shape of the allele frequency distribution. A population that did not
suffer a recent bottleneck event will yield an L-shaped distribution (such as
expected in a stable population in mutation-gene drift equilibrium), whereas a
recently bottlenecked population will show a mode-shift distribution. The
Wilcoxon´s signed rank test probably has greatest power when few loci are
analyzed (Piry et al. 1999, Ruiz-Garcia 2013).
The model-based clustering analysis STRUCTURE 2.2 (Pritchard et al.
2000) was used to assess the most probable cluster membership for each individual
from all populations (Antioquia, Boyacá, Norte de Santander, and Nariño). The
program was run for 1,000,000 Markov chain Monte Carlo steps after a burn-in
period of 100,000 interactions from K = 1-10 under an admixture model. Each K
was calculated from 10 independent runs. The ad hoc estimated likelihood of K
(delta K) (Evanno et al. 2005) was used to estimate the most likely number of
populations (K) based on the rate of change in log probability of data [Ln Pr (X/K)].

Results

Analysis of the microsatellite data revealed two to nine effective alleles in all
eight microsatellites (Table 1). Microsatellite 1 produced the most alleles (Nariño =
nine, Norte de Santander = seven, Antioquia = six, and Boyacá = four), followed by
microsatellites 2, 3, 4, 7, and 8; Microsatellite 6 produced the fewest alleles (Boyacá
= five, Antioquia = four, Nariño = three, and Norte de Santander = two).
Significant differences between observed and expected heterozygozyties
were found for most of the microsatellites in all four regions where 7/28 Hardy
Weinberg equilibrium comparisons were not significant (data not shown). The
number of pairs of loci that significantly deviated from linkage disequilibria varied
between five and eight among the four Colombian regions (Chi-square test, P <
0.00178 after Bonferroni correction).
Analyses of molecular variance for RST = 0.175 (P < 0.01) and FST = 0.094 (P
< 0.01) were significant (Table 2), suggesting populations of T. solanivora from
Colombia are genetically different. FST paired values suggested the differentiation
pattern among populations, with populations from Nariño and Norte de Santander
most different from the others (Table 3). Microsatellites that produced the greatest
FST values were 4, 5, and 6, whereas microsatellites 6 and 7 produced larger FIS
and FIT values (Table 4). The RST value was greater than the FST value,
demonstrating the power of the first estimator when applied in microsatellites
(Slatkin 1985).
The number of clusters produced by genotype groupings generated with
STRUCTURE by associated populations when most grouped individuals in a
particular location showed high probability (70-100%) of clustering with individuals
from another population (Keever et al. 2013). Results suggested that populations of
T. solanivora from Antioquia, Boyacá, Norte de Santander, and Nariño are
represented by two probable population clusters (K = 2) (Fig. 2). Although the
maximum likelihood value was found at K = 9 populations (Ln(P|D) = -2640.3,
variance = 380.5), the delta-K method of Evanno et al. (2005) estimated K = 2

41
clusters as the best fit because it produced the greatest likelihood improvement
value ΔK = 0.54 (Fig. 2, Table 5).
Bottleneck simulations suggested that populations of T. solanivora from
Colombia have not undergone recent bottleneck effects because the sign test,
standardized difference test, Wilcoxon´s signed rank test, and graphical descriptor
of the shape of the allele-frequency distribution produced nonsignificant P values,
except for Boyacá and Norte de Santander with the Wilcoxon´s test (Table 6).

Table 1. Characteristics of Each Microsatellite Locus in Tecia solanivora from

Colombia, including Total Number of Alleles (Na), Number of Effective Alleles (Ne),
Observed Heterozygocity (Ho), Expected Heterozygocity (He), Unbiased Expected
Heterozygocity (UHe), and F (Fixation Index)
Population Locus N Na Ne I Ho He uHe F
Antioquia Micro 1 38 6 5.157 1.716 0.921 0.806 0.817 -0.143
Micro 2 37 7 2.590 1.273 0.297 0.614 0.622 0.516
Micro 3 35 5 3.032 1.265 0.371 0.670 0.680 0.446
Micro 4 38 4 1.632 0.665 0.211 0.387 0.392 0.456
Micro 5 38 6 4.079 1.509 0.368 0.755 0.765 0.512
Micro 6 33 4 3.170 1.199 0.061 0.685 0.695 0.911
Micro 7 38 6 4.997 1.675 0.105 0.800 0.811 0.868
Micro 8 38 5 2.722 1.222 0.132 0.633 0.641 0.792
Boyacá Micro 1 25 4 3.388 1.278 0.880 0.705 0.719 -0.249
Micro 2 36 4 2.554 1.082 0.194 0.608 0.617 0.680
Micro 3 38 7 3.780 1.475 0.368 0.735 0.745 0.499
Micro 4 34 5 3.099 1.206 0.441 0.677 0.687 0.349
Micro 5 38 5 2.796 1.174 0.684 0.642 0.651 -0.065
Micro 6 32 5 3.879 1.445 0.156 0.742 0.754 0.789
Micro 7 38 7 5.906 1.847 0.026 0.831 0.842 0.968
Micro 8 37 6 4.430 1.608 0.459 0.774 0.785 0.407
Norte de Micro 1 36 7 4.909 1.738 0.944 0.796 0.808 -0.186
Santander Micro 2 38 4 3.021 1.198 0.579 0.669 0.678 0.135
Micro 3 37 6 3.248 1.392 0.270 0.692 0.702 0.609
Micro 4 37 4 2.788 1.149 0.459 0.641 0.650 0.284
Micro 5 38 4 2.415 1.052 0.605 0.586 0.594 -0.033
Micro 6 12 2 2.000 0.693 0.000 0.500 0.522 1.000
Micro 7 38 7 4.878 1.720 0.000 0.795 0.806 1.000
Micro 8 38 4 2.938 1.185 0.132 0.660 0.668 0.801
Nariño Micro 1 37 9 3.574 1.669 0.568 0.720 0.730 0.212
Micro 2 37 7 2.931 1.369 0.351 0.659 0.668 0.467
Micro 3 38 6 3.198 1.408 0.500 0.687 0.696 0.273
Micro 4 38 4 2.470 1.030 0.211 0.595 0.603 0.646
Micro 5 38 4 1.904 0.790 0.368 0.475 0.481 0.224
Micro 6 25 3 1.771 0.760 0.160 0.435 0.444 0.632
Micro 7 38 4 3.967 1.382 0.000 0.748 0.758 1.000
Micro 8 38 3 2.111 0.839 0.289 0.526 0.533 0.450

42
Table 2. Analysis of Molecular Variance in Tecia solanivora from Colombia to
Obtain Estimators of FST (a) and RST (b)
a)
Source df SS MS Est. var. % F-statistics P Nm
Among Pops 3 78.345 26.115 0.288 9 Fst = 0.094 0.010 2.422
Among Indiv 148 630.026 4.257 1.471 48 Fis = 0.528 0.010
Within Indiv 152 200.000 1.316 1.316 43 Fit = 0.572 0.010
Total 303 908.372 3.074 100
b)
Source df SS MS Est. var. % R-statistics P Nm
Among Pops 3 934.296 311.432 3.704 17 Rst = 0.175 0.010 1.180
Among Indiv 148 4423.789 29.890 12.406 59 Ris = 0.710 0.010
Within Indiv 152 772.000 5.079 5.079 24 Rit = 0.760 0.010
Total 303 6130.086 21.189 100

Table 3. Paired FST Values Obtained for Tecia solanivora in Antioquia, Boyacá,
Nariño, and Norte de Santander Regions of Colombia
Antioquia Boyacá Norte de Santander Nariño
Antioquia
Boyacá 0.045
Norte de Santander 0.083 0.049
Nariño 0.101 0.063 0.036 0.000

Table 4. FIS, FIT, and FST Values Obtained for Each Microsatellite for Tecia
solanivora from Colombia
Locus Fis Fit Fst Nm
Micro 1 -0.094 -0.034 0.055 4.320
Micro 2 0.442 0.476 0.060 3.901
Micro 3 0.458 0.473 0.027 8.871
Micro 4 0.426 0.496 0.123 1.786
Micro 5 0.176 0.308 0.161 1.307
Micro 6 0.840 0.870 0.185 1.103
Micro 7 0.959 0.960 0.047 5.106
Micro 8 0.610 0.637 0.071 3.280

Mean 0.477 0.523 0.091 3.709

SE 0.120 0.111 0.020 0.901

43
Fig. 2. Result of heuristic Bayesian clustering analysis of Tecia solanivora
determined by STRUCTURE. Colors represent different clusters among the four
geographical regions sampled in Colombia.

Table 5. Evano´s Test for Tecia solanivora to Determine the Number of K Clusters
LnP = Likelihood Function, Var = Variance, L´k = L (k)n – L(k)n-1, L´´ (k) = L´(k)n
L´(k)n-1, Delta K’ = [L´´ (k]/stdev, and Delta K = Delta K’ (-1).
k Ln P(D) Var [LnP(D)] L´k L´´k Delta K’ Delta K
1 -3478.6 23.3
2 -3258.4 109.5 220.2000 -60.0000 -0.547945 0.5479452
3 -3098.2 156.2 160.2000 -67.4000 -0.431498 0.4314981
4 -3005.4 212.3 92.8000 21.8000 0.1026849 -0.102685
5 -2890.8 249.7 114.6000 -36.3000 -0.145374 0.1453744
6 -2812.5 291.5 78.3000 -2.2000 -0.007547 0.0075472
7 -2736.4 308.0 76.1000 -78.1000 -0.253571 0.2535714
8 -2738.4 450.4 -2.0000 100.1000 0.2222469 -0.222247
9 -2640.3 380.5 98.1000 -133.500 -0.350854 0.3508541
10 -2675.7 563.7 -35.4000 35.4000 0.0627994 -0.062799

Discussion

The number of alleles for all microsatellites in T. solanivora from Colombia

was less compared to the study by Torres-Leguizamón et al. (2009) who found
eight to 22 alleles in populations from Costa Rica and Guatemala. They analyzed
30 individuals from Costa Rica and 28 from Guatemala. We analyzed 38
individuals per region, for a total of 152 individuals. Differences between the two
studies might be explained by dissimilarities in visualization of the band pattern
because they used autoradiography and we used silver staining. Another
explanation is that they analyzed populations of T. solanivora from two countries
(Costa Rica and Guatemala) where the species might have originated (Torres-
Leguizamón et al. 2011) and we analyzed populations from South America invaded
by the species in 1985. Given that source populations vary more genetically than
founder populations, our results coincided with the evolutionary biology and history
of the species. However, the number of alleles found by Torres-Leguizamón et al.
(2009) is relatively high for only 58 individuals of the species.

44
 Table 6. Results of Analysis to Determine Recent Population Bottleneck Effect in
Tecia solanivora from Colombia. Ko = number of observed alleles, He = expected
heterozycosity, Heq = expected heterozygocity under coalescence model, SD =
standard deviation, P = probability, and SMM = Step mutation model.
Under S.M.M.
Population Locus Ko He Heq SD DH/sd P
Antioquia Micro 1 76 0.817 0.730 0.069 1.264 0.027
-
Micro 2 74 0.622 0.773 0.055 2.757 0.027
Micro 3 70 0.68 0.676 0.083 0.046 0.417
-
Micro 4 76 0.392 0.593 0.109 1.849 0.059
Micro 5 76 0.765 0.735 0.063 0.472 0.380
Micro 6 66 0.695 0.600 0.102 0.936 0.157
Micro 7 76 0.811 0.733 0.064 1.200 0.054
-
Micro 8 76 0.641 0.679 0.083 0.462 0.248
Sign test Wilcoxon test
SMM P (one tail
for H excess) =
SMM P = 0.58217 0.47266
Standardized
differences
test Mode Shift
Normal L-shaped
SMM P = 0.34204 distribution
Boyacá Micro 1 4 0.719 0.610 0.100 1.093 0.080
Micro 2 4 0.617 0.595 0.107 0.204 0.496
-
Micro 3 7 0.745 0.776 0.051 0.609 0.224
Micro 4 5 0.687 0.680 0.08 0.088 0.458
-
Micro 5 5 0.651 0.676 0.082 0.302 0.303
Micro 6 5 0.754 0.682 0.075 0.958 0.149
Micro 7 7 0.842 0.776 0.050 1.324 0.037
Micro 8 6 0.785 0.734 0.066 0.774 0.217
Sign test Wilcoxon test
SMM P (one tail
for H excess) =
SMM P = 0.30167 0.03711
Standardized
differences
test Mode Shift
Normal L-shaped
SMM P = 0.10605 distribution
Norte de Micro 1 7 0.808 0.778 0.048 0.615 0.312
Santander Micro 2 4 0.678 0.586 0.109 0.839 0.188
-
Micro 3 6 0.702 0.735 0.064 0.523 0.238

45
 Micro 4 4 0.650 0.601 0.101 0.483 0.383
Micro 5 4 0.594 0.597 0.108 -0.03 0.403
Micro 6 2 0.522 0.3 0.158 1.400 0.023
Micro 7 7 0.806 0.773 0.053 0.608 0.315
Micro 8 4 0.668 0.594 0.108 0.690 0.278
Sign test Wilcoxon test
SMM P (one tail
for H excess) =
SMM P = 0.27687 0.01367
Standardized
differences
test Mode Shift
Normal L-shaped
SMM P = 0.07446 distribution
0.830 0.038 -2.663 -
Nariño
Micro 1 9 0.730 0.0200 0.038 2.663 0.020
0.773 0.053 -
Micro 2 7 0.668 1.982 0.0530 0.053 -1982 0.053
0.731 0.067 - -
Micro 3 6 0.696 0.519 0.2390 0.067 0.519 0.239
0.594 0.102 0.089
Micro 4 4 0.603 0.4620 0.102 0.089 0.462
0.594 0.106 - -
Micro 5 4 0.481 1.065 0.1350 0.106 1.065 0.135
0.477 0.138 -0.239 -
Micro 6 3 0.444 0.3350 0.138 0.239 0.335
0.598 0.106 1.505
Micro 7 4 0.758 0.0000 0.106 1.505 0
0.471 0.135 0.462
Micro 8 3 0.533 0.3670 0.135 0.462 0.367
Sign test Wilcoxon test
SMM P (one tail
for H excess) =
SMM P = 0.17714 0.87500
Standardized
differences
test Mode Shift
Normal L-shaped
SMM P = 0.0594 distribution

Both RST and FST values obtained with the AMOVA test suggested T.
solanivora from Colombia was genetically different where the RST value was greater
than FST. These results corroborate a previous study by Villanueva-Mejía et al.
(2014) who sequenced two mitochondrial genes, Cytochrome Oxidase I (COI) and
Cytochrome B (Cyt B), that produced significant FST; for this reason, they suggested
the species had reduced gene flow in Colombia. Paired FST values showed
populations from Boyacá and Antioquia followed by Boyacá and Norte de

46
Santander most genetically similar. In addition, Norte de Santander and Nariño
also produced low FST values suggesting slight genetic difference between the two
locations. Boyacá is the main distributor of potatoes to the rest of Colombia; tuber
movement might be the main cause of genetic homogenization of T. solanivora
populations in Colombia. Norte de Santander was the first place invaded by the
pest in Colombia in 1985 and thus, genetic composition of the moth differs from that
in other regions (Niño 2004, Pulliandre et al. 2008). Potatoes in the region are
produced mostly for domestic consumption and not distributed to other regions of
Colombia. Insects from Nariño were most genetically different from those in other
regions. This might be explained because Nariño is most geographically distant
from other populations in Colombia, and also many potato varieties including Diacol
Capira, ICA Purace, Parda Pastusa, and Tucarreña are grown (Espinal et al. 2005,
Agronet 2014), whereas in the rest of Colombia the only variety produced is Diacol
Capira. In Nariño, T. solanivora has more food supply and more possibilities of host
shift than in other regions of Colombia. Also, in Nariño, Solanum phureja potato is
produced and might be another host for the pest. Further ecological and genetic
studies are needed to determine if the pest infests this species of potato.
Although T. solanivora is genetically different in Colombia, RST and FST
values were low. This might be explained by the colonization history of the species
that invaded Colombia in 1985. A similar result was obtained with Plutella xyllostela
(Lepidoptera: Plutellidae) that invaded Australia 120 years ago, but unlike T.
solanivora, P. xyllostela has not genetically differentiated in that country (Endersby
et al. 2006). The biology of T. solanivora might also explain results obtained in the
AMOVA test because the species has low dispersal ability (Fedepapa 1995,
Villanueva and Saldamando 2013), and populations with low dispersal tend to have
low gene flow and produce structured populations as found here.
Results from the program STRUCTURE showed T. solanivora different in K
= 2 populations in Colombia. This supports results generated by the AMOVA test.
The K = 2 is composed by a first K that clustered Antioquia and Boyacá and a
second K that clustered Nariño and Norte de Santander. Fig. 2 shows Boyacá
shares most genotypes among all regions because it is in the center of distribution
of the K clusters. This might be because this location in the central region
distributes potatoes throughout Colombia and is the main receptor from other
regions. Potato movement from Boyacá to other regions homogenizes T.
solanivora populations from the source to other locations where potato is an
important crop. Antioquia is a major producer of potatoes in Colombia and receives
tubers mainly from Boyacá and Cundinamarca. Potato movement might explain
genetic similarities between the region and Boyacá. Norte de Santander was the
first place invaded by the species in Colombia while Nariño grows diverse potato
varieties and is close to Ecuador where many potato varieties and species of the
genus Solanum are produced. Nariño is geographically distant and separated from
other regions of Colombia by the Andes. This chain of mountains could be a barrier
to gene flow as Diaz-Montilla et al. (2013) demonstrated by population genetic
analysis by sequencing the Cytochrome Oxidase I gene in 109 individuals of
Neoleucinodes elegantalis (Lepidoptera: Crambidea) from Colombia. They also
suggested the Andes reduced gene flow because they found four genetically
different haplotypes of the pest. This pest species is associated with solanaceous
crops (Solanum quitoese, S. melongena, S. betaceum, S. artroporpureum, among
others) and with T. solanivora has shown greater genetic variability particularly at
Macizo Colombiano in the Nariño region of South Colombia.

47
 T. solanivora is a monophagous species and N. elegantalis oligophaous. In
Colombia, both pest species are genetically different whereas Spodoptera
frugiperda (Lepidoptera: Noctuidae) is a polyphagous species without genetic
differences in Colombia (Salinas-Hernández and Saldamando-Benjumea 2011).
Results might be explained by the amount of association between the moths and
their respective hosts because the first two species have restricted food availability
compared to the last species. Host plant association is relevant at the level of
genetic differentiation of insect pests; T. solanivora is a species genetically different
because of its association with S. tuberosum and low dispersal ability.
The software BOTTLENECK produced results suggesting T. solanivora has
not undergone a recent population bottleneck as believed by Pulliandre et al.
(2008). We suggest differences between the studies might be because the authors
analyzed few individuals per population and thus, few haplotypes were obtained
from Colombia, Ecuador, and Venezuela. This low number of haplotypes was
assumed to be produced by a bottleneck effect and not by few samples (i.e.,
genetic drift). Villanueva-Mejía et al. (2014) found a greater number of haplotypes
in T. solanivora from Colombia because they genotyped more samples per
population (region). They also used two molecular mitochondrial markers COI and
cytb to compare genetic differences in the species with two genes that have
different mutation rates. Villanueva-Mejía et al. used a Tajima test that suggested
the species has not suffered a bottleneck; on the contrary, Boyacá populations are
expanding. The results corroborate potato tuber movement from the central to
other regions of Colombia and the invasive behavior of the species.
Insecticide resistance management strategies for T. solanivora require
information obtained in this work, given the gene flow of the species from Boyacá to
other regions of Colombia. Management of the species should differ between
Antioquia and Boyacá versus Nariño and Norte de Santander as found by the FST
paired values and the K = 2 subpopulations obtained with STRUCTURE. Also,
there is possibility of movement of genes that confer resistance to insecticides
between populations with high levels of gene flow because resistance alleles have
potential to spread quickly throughout the country because of T. solanivora
dispersal patterns. T. solanivora individuals from Nariño and Norte de Santander
regions should be included in future bioassays when new insecticides are tested in
Colombia because of high allelic richness in the regions that might suggest
populations would respond differently to control.

Acknowledgment

We would like to thank Dr. Tito Bacca, Dra. Nancy Barreto, and Luisa Torres
for collections of T. solanivora at Nariño, Boyacá, and Norte de Santander.
Additionally, we thank Sergio Castro for initial support in the laboratory. This work
was funded by Fundación Banco de la República de Colombia (project number
3009) and Universidad Nacional de Colombia (project number 20101009540).
Diego Villanueva Mejía was funded by Departamento de Ciencia Tecnología e
Innovación (Colciencias) in the scholarship system created for Ph.D. students. We
thank the Ministry of Environment of Colombia for providing a genetic access permit
to Universidad Nacional de Colombia to study molecular ecology in March 2014.

48
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