ArticlePDF Available

Abstract and Figures

The recent expansion of the Italian wolf population through the Apennine and western Alps, after centuries of contractions, is causing conflicts with human activities leading to a rise in poaching or illegal killings. Here we show how molecular population genetics has been used to identify a suspect serial wolf killer. We analysed DNA extracted from a necklace made of ten presumed wolf canine teeth, confiscated in 2008 to a man living in the northern Italian Apennine (Liguria Region). Individual genotypes were determined using 12 unlinked autosomal microsatellites (STRs), mtDNA control-region sequences, a male-specific ZFX/ZFY restriction-site and three Y-linked STRs. Results indicate that the teeth belonged to six different individuals (three males and three females), which were assigned to the Italian wolf population with p > 0.90 by Bayesian procedures. One of these genotypes matched with the genetic profile of a male wolf previously found-dead and already non-invasively sampled in the same area. Another genotype matched with that of a female wolf non-invasively sampled twice in the same area 1 year before. These data are being used as forensic genetic evidence in the ongoing criminal trial against the suspect serial wolf killer.
Content may be subject to copyright.
Case report
Forensic DNA against wildlife poaching: Identification of a serial
wolf killing in Italy
Romolo Caniglia *, Elena Fabbri, Claudia Greco, Marco Galaverni, Ettore Randi
Institute for Environmental Protection and Research (ISPRA), Laboratory of Genetics, Via Ca
`Fornacetta 9, 40064 Ozzano dell’Emilia (BO), Italy
1. Introduction
After centuries of population decline and worldwide range
contraction due to habitat changes, decline of natural prey species
and direct persecution by humans, the wolf (Canis lupus)is
expanding again in Italy and other parts of Europe [1]. Wolves in
Italy were confined south of the Po River since the turn of the last
century, and less than 100 individuals survived in the 1970s in two
fragmented areas in the central-southern Apennine [2]. This
declining demographic trend quickly reversed in the 1980s, when
wolves started to expand in parts of their historical range in the
Apennine, reaching the south-western Alps, France and Switzer-
land [3–5]. The return of wolves in anthropic areas is fuelling
conflicts with local communities, mainly with hunters and
livestock breeders. While hunters wrongly maintain the idea that
wolves are competitors for the same wild ungulate game (wild
boar, red deer, roe deer and fallow deer), livestock breeders some
time really suffer significant economical losses caused by
predations on domestic herds. Although both national and local
authorities have activated damage prevention and compensation
policies, their actions are rarely enforced rapidly and efficiently.
Consequently, and despite legal protection accorded to the wolf
since 1976, poaching and various forms of illegal killings are
widely practised [6]. An estimated 20% of the total wolf population
(numbering c. 800 animals; [1]) is illegally or accidentally killed
every year in Italy [6]. In addition to intentional shooting and
poisoning, wolves are accidentally, but always illegally, killed by
poisoned baits against foxes and small carnivores, or by snares for
wild boars. Hence, poaching is widespread and perhaps remains
the major threat to wolf survival [7,8]. Nevertheless, poachers in
Italy have never been identified and prosecuted by law, so far.
Here we describe how molecular genetic identification
methods are being used to contrast the illegal killing of wolves
in Italy. In 2008 the Provincial Police of Genova confiscated a
necklace (Fig. 1) made by ten canine teeth to a man living in a small
village in the northern Italian Apennine, Liguria Region, Genova
Province. After a few days the Provincial Police discovered in the
same area a male wolf carcass without the entire muzzle. The
necklace and wolf tissue samples were sent to the Laboratory of
Genetics of ISPRA (Institute for Environmental Protection and
Research) where DNA was extracted and multilocus individual
genotypes were determined at the mtDNA control-region [9],12
unlinked autosomal microsatellites [10] and three Y-linked STRs
[11], and sexed using a male-specific ZFX/ZFY restriction-site [12].
The genotypes were matched with a large database of wolf and dog
genotypes that is being implemented at ISPRA, in compliance with
European Community and national laws that require that wolf
populations, as well as other protected large predators (brown
Forensic Science International: Genetics 4 (2010) 334–338
ARTICLE INFO
Article history:
Received 26 August 2009
Received in revised form 14 October 2009
Accepted 27 October 2009
Keywords:
Canis lupus
Wildlife poaching
Microsatellite
mtDNA control-region
Bayesian analysis
Non-invasive sample
ABSTRACT
The recent expansion of the Italian wolf population through the Apennine and western Alps, after
centuries of contractions, is causing conflicts with human activities leading to a rise in poaching or illegal
killings. Here we show how molecular population genetics has been used to identify a suspect serial wolf
killer. We analysed DNA extracted from a necklace made of ten presumed wolf canine teeth, confiscated
in 2008 to a man living in the northern Italian Apennine (Liguria Region). Individual genotypes were
determined using 12 unlinked autosomal microsatellites (STRs), mtDNA control-region sequences, a
male-specific ZFX/ZFY restriction-site and three Y-linked STRs. Results indicate that the teeth belonged
to six different individuals (three males and three females), which were assigned to the Italian wolf
population with p>0.90 by Bayesian procedures. One of these genotypes matched with the genetic
profile of a male wolf previously found-dead and already non-invasively sampled in the same area.
Another genotype matched with that of a female wolf non-invasively sampled twice in the same area 1
year before. These data are being used as forensic genetic evidence in the ongoing criminal trial against
the suspect serial wolf killer.
ß2009 Elsevier Ireland Ltd. All rights reserved.
* Corresponding author. Tel.: +39 0516512251; fax: +39 051796628.
E-mail address: romolo.caniglia@gmail.com (R. Caniglia).
Contents lists available at ScienceDirect
Forensic Science International: Genetics
journal homepage: www.elsevier.com/locate/fsig
1872-4973/$ – see front matter ß2009 Elsevier Ireland Ltd. All rights reserved.
doi:10.1016/j.fsigen.2009.10.012
bear, lynx), are monitored [6,13]. The Italian wolf database consists
of multilocus genotypes obtained from DNA extracted from found-
dead wolves collected throughout the entire Italian wolf range
distribution in the last 15 years (n= 417), from non-invasive
samples (scats) collected during a monitoring project in the
Apennine from 2000 to 2009 (n= 341 [14]) and the western Alps
from 1999 to 2004 (n= 130) [4]).
The database is used by managers to obtain detailed informa-
tion on wolf presence, distribution range, population size and
structure in the northern Apennine and western Alps [14]. These
data were analysed aiming to: (1) identify the species and the
population of origin of each sample, either if wolf or dog; (2)
determine the individual genotypes and count the number of
individuals to which the ten teeth belonged; (3) assess any
eventual match between each tooth genotype and the found-dead
wolf; and (4) search the database for additional matches with
wolves that were non-invasively identified during the ongoing
population monitoring project.
2. Materials and methods
2.1. DNA extraction and molecular analyses
DNA was extracted from a small fragment of muscular tissue
(stored at 20 8C in 10 volumes of 95% ethanol) of the wolf carcass,
and from dental pulpsamples obtained by slow drilling the roots of
the confiscated teeth, using a guanidinium-silica protocol [15].All
DNA samples were PCR-amplified using canine specific primers for:
(1) 350 bp of the mtDNA control-region, which contains diagnostic
mutations for the identification of the Italian wolf haplotype W14
[9]; (2) 12 unlinked autosomal microsatellites, including seven
dinucleotides (CPH2, CPH4, CPH5, CPH8, CPH12; [16]; C09.250 and
C20.253; [17]), and five tetranucleotides (FH2004, FH2079, FH2088,
FH2096 and FH2137; [18]), that were selected for their high
polymorphism in the Italian wolf population [10]. This panel of
microsatellites allows determining the individual genotypes with
probabilityof identity PID = 7.1 10
9
, and expected PID among full
sib dyads PIDsibs = 3.1 10
4
, in the Italian wolf population
[19,20,4]. The genotypes were sexed by PCR-RFLP of diagnostic
ZFX/ZFY sequences [12,20] and male individuals were also amplified
at three Y-linked microsatellites: MS34A, MS34B, MS41B [11].PCR-
amplificationswere carried out in 10
m
l reactions,using respectively
1
m
lor2
m
l DNA solutions from tissueor tooth extractions, plus 2
m
g
of BSA, and were optimised for each primer pair and for tissue or
tooth samples(protocols are availableupon request). Toothpulp and
tissue samples were extracted and amplified in dedicated separate
rooms under sterile UV laminar flood hood, and pulp samples
genotyped using a wolf-specific non-invasive multiple-tube proto-
col [14]. Negative (no DNA in PCR)and positive (samples withknown
genotypes) controls were always used. PCR products were analysed
in an automated sequencer ABI 3130XL (Foster City, CA), using the
software Sequencing Analysis v.3.7 and Seqscape v.2.5 for
sequences, and Genescan v.3.7 and Genmapper v.4.0 for micro-
satellites.
The quality of tooth DNA was initially screened by four
replicated PCRs of two microsatellites (FH2096 and FH2137). Only
those samples showing more than 50% positive PCRs (i.e., PCRs
producing the expected amplicons) were further amplified four
times at each of the remaining ten microsatellites and sexed. The
software Reliotype was used to assess genotype reliability [21],
and unreliable loci (at score threshold R= 0.95) were additionally
replicated other four times. All those samples that were not
reliably typed at all loci after eight PCR replicates were definitively
discarded. Consensus genotypes were reconstructed using the
software Gimlet v.1.3.3 (http://pbil.univ-lyon1.fr/software/Gim-
let/gimlet.htm)[22], accepting heterozygotes only if the two
alleles were seen at least in two replicates and homozygotes only if
the allele was seen at least in four replicates. Individual genotypes
were recorded in Excel and the software GenAlEx v. 6.1 (http://
www.anu.edu.au/BoZo/Genalex)[23] was used to estimate the
values of population genetic parameters.
2.2. Bayesian admixture analyses
The software Structure v. 2.2 [24] was used to assign individuals
to baseline wolf or dog populations, independent of any prior non-
genetic information. The baseline wolf population included the
genotypes determined in 176 randomly selected tissue samples
obtained from found-dead wild-living wolves that were acciden-
tally or illegally killed in Italy. All these animals had the typical
Italian wolf coat colour pattern and did not show any detectable
phenotypic and genetic signals of hybridisation [9,10,25]. The
baseline dog population was composed by the genotypes
determined in 118 blood samples collected from dogs living in
rural areas in Italy. We run Structure with five repetitions of 10
5
iterations following a burn-in period of 10
4
iterations, selecting the
‘‘admixture model’’ (each individual may have ancestry in more
than one parental population) and the ‘‘I model’’ (independent
allele frequencies). According to previous studies [10,25] the
optimal number of populations was set at K= 2, the value that
maximised the posterior probability of the data. At K=2, we
assessed the average proportion of membership (Q
i
) of the sampled
populations to the inferred clusters. Then, we assigned each
individual genotype to one cluster if the proportion of membership
was q
i
>0.90, or to both clusters if the proportion of membership
was q
i
<0.90 (admixed individuals). Individual multilocus scores
were computed using Genetix v.4.05 (http://www.genetix.univ-
montp2.fr/genetix/genetix.htm)[26] and patterns of differentia-
tion were visualized by Factorial Correspondence Analysis FCA
[27].
3. Results and discussion
3.1. Genetic identifications
We obtained clean mtDNA sequences from nine of the tooth
samples and from the muscle. These sequences were aligned
Fig. 1. The confiscated wolf tooth necklace.
R. Caniglia et al. / Forensic Science International: Genetics 4 (2010) 334–338
335
with homologous canine control-region sequences downloaded
from GenBank. The alignment showed that all these sequences
were identical among them, and exactly corresponding to the
diagnostic Italian wolf mtDNA control-region haplotype, that
was named W14 by Randi et al. [9]. This finding indicated that
the teeth and the carcass originated from native Italian wolves,
and not from dogs or from non-Italian wolves. Only one of the ten
teeth did not produce amplifiable DNA. Hence, it was not possible
to generate any mtDNA sequence and microsatellite genotypes at
most of the PCRs. Therefore this sample was definitively
discarded. The other nine tooth samples produced more than
50% positive PCRs and successfully passed the screening step.
After the first four PCR replicates per locus, one sample (11% of
the total positively screened tooth samples) showed a reliability
score R<0.95. This sample was thus further amplified other four
times at each unreliable locus. After these additional PCR
replicates even this genotype resulted completely reliable
(R>0.95). The nine consensus tooth genotypes were determined
and the regrouping procedure led to the identification of six
different individuals, three males and three females. Four teeth
matched to the same individual (a male that was named
WGE9M), while the other five teeth showed five distinct
genotypes (Table 1). The three males shared the same Y-linked
haplotype U, which is the most frequent (89%) in the Italian wolf
population (unpublished results) confirming that all the teeth
belonged to native Italian wolves. The probability of these six
genotypes to be generated by chance a second time in the Italian
wolf population was comprised between 3.1 10
4
and
7.5 10
9
. The expected number of individuals with the same
genotype in the Italian wolf population (calculated as respective
probability population size) was 1.2 10
6
(as estimated with
PID) or 5.4 10
2
(as estimated with PIDsibs), meaning that all
genotypes identify distinct individuals and that it is very unlikely
that two wolves shared by chance the same genotype. After a
comparing procedure of the identified genotypes, one of the
tooth genetic profiles (WGE12M) completely matched with the
genotype of the found-dead wolf (ID sample W1016). The six
genotypes were finally matched with the ISPRA wolf database,
revealing two perfect matches: one between the genetic profile
of one tooth and the genotype of a female wolf (named WGE3F),
non-invasively sampled twice during year 2007 in an area distant
just 10 km from the suspect poacher’s house, and the other
between the genetic profile of the tooth belonging to the carcass
and the genotype of a male wolf (named WGE12M), non-
invasively sampled in 2007 in the same area (Table 1).
3.2. Bayesian admixture and population assignment analyses
Results of five replicated runs of Structure with prior value of
K= 2 showed that all baseline dogs were assigned to the same
cluster with Q
d
= 0.99, and all baseline wolves were assigned to the
same wolf cluster with Q
w
= 1.00 (Fig. 2). Individual assignment
values ranged between 0.84 <q
d
<1.00 in dogs, and
0.94 <q
w
<1.00 in wolves. Only one of the 118 dogs (0.85%)
and no wolf were assigned to their respective clusters with
individual assignment values q
i
<0.90. The six genotypes identi-
fied in this study were assigned to the Italian wolf clusters with
Q
w
= 0.99 (Fig. 2). Their individual assignment values ranged
between 0.98 <q
w
<1.00, and no one of them was assigned to the
Italian wolf clusters with individual assignment values q
i
<0.90,
confirming that these animals belong to the Italian wolf popula-
tion. A Factorial Correspondence Analysis of individual multilocus
scores computed using Genetix showed a sharp distinction
between baseline wolves and dogs, which clearly split apart.
Table 1
Genetic identification of DNA samples extracted from the confiscated tooth necklace and carcass.
ID
a
Sample
b
mtDNA
c
Y-haplotype
d
Genotype
e
q
w
(90% CI)
f
W1006 Tooth W14 WGE8F 1.00 (0.99–1.00)
W1007 Tooth W14 U WGE9M 1.00 (0.99–1.00)
W1008 Tooth W14 WGE3F 1.00 (0.99–1.00)
W1009 Tooth W14 WGE10F 0.98 (0.87–1.00)
W1010 Tooth W14 U WGE11M 1.00 (0.99–1.00)
W1011 Tooth W14 U WGE9M 1.00 (0.99–1.00)
W1012 Tooth W14 U WGE9M 1.00 (0.99–1.00)
W1013 Tooth W14 U WGE9M 1.00 (0.99–1.00)
W1014
g
Tooth nd nd nd nd
W1015 Tooth W14 U WGE12M 0.98 (0.90–1.00)
W1016 Tissue W14 U WGE12M 0.98 (0.90–1.00)
a
ID indicates sample identification number.
b
Teeth or tissue indicate the biological type of each analysed sample.
c
W14 is the unique and diagnostic control-region haplotype of the Italian wolf population.
d
U is the most frequent (89%) Y-microsatellite haplotype in the Italian wolf population.
e
Individual genotype acronyms (W = wolf, GE = Genova Province of the Liguria Region; F = female; M = male) of each sample determined using non-invasive genetic
methods and 12 unlinked microsatellite markers.
f
q
w
is the proportion of membership of individual genotypes to cluster the wolf cluster in a Structure analysis with K= 2; 90% CI is the credibility interval of the q
w
values.
g
DNA extracted from sample W1014 was not amplifiable and the genotype was not-detected (nd), perhaps because it was too degraded.
Fig. 2. Structure results. Bar plotting of the results obtained assuming K= 2 genetic clusters: the baseline wolves (dark grey) and the baseline dogs (light grey). Each individual
is represented as a vertical line partitioned into Kcoloured segments, whose length is proportional to the individual coefficients of membership in the Kclusters. All the
genotypes obtained from the tooth DNA samples (dark grey, at the right end of the plot) were assigned to the Italian wolf population, with individual q
i
>0.90.
R. Caniglia et al. / Forensic Science International: Genetics 4 (2010) 334–338
336
The tooth genotypes clearly plot within the swarm of the Italian
wolf genotypes (Fig. 3).
4. Conclusions
The results of this study showed that the panel of molecular
markers used to describe the population genetic structure of Italian
wolves and dogs were able to identify very efficiently the origin of
confiscated biological samples. In this case, and for the first time as
far as we know, DNA evidence has been successfully used to
unambiguously identify a case of wolf poaching and, in the mean
time, to contribute to link the evidence to the suspected. Now these
data are being used as forensic genetic evidence in the ongoing
criminal trial against the suspect illegal hunter. This case was
particularly interesting because the suspect acted as a serial wolf
killer, shooting illegally at least six wolves belonging to the Italian
populations. Two of them were living very close to the suspected
village. These results were obtained thanks to the use of updated
molecular methods in the field of wildlife forensics. Identifications
were strongly aided also by the possibility to match the genotypes
of the confiscated samples with a large genetic data base of Italian
wolves, which proved to be useful for both population monitoring
purposes and anticrime activities, as well.
Acknowledgments
We thank the Provincial Police officers that confiscated the
samples, Mr. F. Crosio and Ms. M. Barone.Mr. A. De Faveri and Ms. A.
De Marinis for their suggestions about the tooth sample treatment.
We also thank two anonymous referees for constructive comments
and for helping with manuscript revision. The laboratory analyses
were supported by the Liguria Region. The Italian wolf database is
maintained thanks to the support of the Italian Ministry of
Environment and of the Emilia-Romagna Region.
References
[1] L. Boitani, Wolf conservation and recovery, in: L.D. Mech, L. Boitani (Eds.), Wolves.
Behavior, Ecology, and Conservation, University of Chicago, Chicago and London,
2003, pp. 317–340.
[2] L. Boitani, E. Zimen, Number and distribution of wolves in Italy, Z. Fur Sauge-
tierkunde 40 (1975) 102–112.
[3] N. Valie
`re, L. Fumagalli, L. Gielly, C. Miquel, B. Lequette, M. Poulle, J. Weber, R.
Arlettaz, P. Taberlet, Long distance wolf recolonization of France and Switzerland
inferred from noninvasive genetic sampling over a period of 10 years, Anim.
Conserv. 6 (2003) 83–92.
[4] E. Fabbri, C. Miquel, V. Lucchini, A. Santini, R. Caniglia, C. Duchamp, J.M. Weber, B.
Lequette, F. Marucco, L. Boitani, L. Fumagalli, P. Taberlet, E. Randi, From the
Apennines to the Alps: colonization genetics of the naturally expanding Italian
wolf (Canis lupus) population, Mol. Ecol. 16 (2007) 1661–1671.
[5] F. Marucco, D.H. Pletscher,L. Boitani, M.K. Schwartz, K.L. Pilgrim,J.D. Lebreton, Wolf
survival and population trend using non-invasive capture-recapture techniques in
the Western Alps, J. Appl. Ecol. (2009), doi:10.1111/j.1365-2664.2009.01696.x.
[6] P. Genovesi (Ed.), National Action Plan for Wolf (Canis lupus) Conservation in Italy,
Nature Conservation Report 13, Ministry of Environment-National Wildlife Insti-
tute, 2002 (in Italian).
[7] L. Boitani, P. Ciucci, Wolves in Italy: critical issues for their conservation, in: C.
Promberger, W. Shroeder (Eds.), Wolves in Europe, Status and Perspectives, WGM,
Oberammergau, Germania, 1993, pp. 75–90.
[8] S. Lovari, A. Sforzi, C. Scala, R. Fico, Mortality parameters of the wolf in Italy: does
the wolf keep himself from the door? J. Zool. 272 (2007) 117–124.
[9] E. Randi, V. Lucchini, M.F. Christensen, N. Mucci, S.M. Funk, G. Dolf, V. Loeschcke,
Mitochondrial DNA variability in Italian and east European wolf: detecting the
consequence of small population size and hybridization, Conserv. Biol. 14 (2000)
464–473.
[10] E. Randi, V. Lucchini, Detecting rare introgression of domestic dog genes into wild
wolf (Canis lupus) populations by Bayesian admixture analyses of microsatellite
variation, Conserv. Genet. 3 (2002) 31–45.
[11] A.K. Sundqvist, H. Ellegren, M. Olivier, C. Vila
`, Y chromosome haplotyping in
Scandinavian wolves (Canis lupus) based on microsatellite markers, Mol. Ecol. 10
(2001) 1959–1966.
[12] E. Garcia-Muro, M.P. Aznar, C. Rodellar, P. Zaragoza, Sex specific PCR/RFLPs in the
canine ZFX/ZFY loci, Anim. Genet. 28 (1997) 156.
[13] L. Boitani, Action Plan for the Conservation of Wolves in Europe (Canis lupus),
Nature and Environment, Council Europe Publishing, 2000, p. 113.
[14] R. Caniglia, E. Fabbri, C. Greco, E. Randi, Non-invasive genetic monitoring of the
wolf (Canis lupus) population in Emilia-Romagna, Proceeding of the Conference:
Scientific Research and Management for Wolf Conservation in Italy, Ministry of
Environment (in press), (in Italian).
[15] U. Gerloff, C. Schlotterer, K. Rassmann, I. Rambold, G. Hohmann, B. Fruth, D. Tautz,
Amplification of hypervariable simple sequence repeats (microsatellites) from
excremental DNA of wild livingBonobos (Pan paniscus), Mol.Ecol. 4 (1995) 515–518.
[16] M. Fredholm, A.K. Wintero, Variation of short tandem repeats within and between
species belonging to the Canidae family, Mamm. Genome 6 (1995) 11–18.
[17] E.A. Ostrander, G.F. Sprague, J. Rine, Identification andcharacterization of dinucleo-
tide repeat(CA)nmarkersfor genetic mapping in dog,Genomics 16 (1993) 207–213.
[18] L.V. Francisco, A.A. Langston, C.S. Mellersh, C.L. Neal, E.A. Ostrander, A class of
highly polymorphic tetranucleotide repeats for canine genetic mapping, Mamm.
Genome 7 (1996) 359–362.
[19] L.P. Waits, G. Luikart, P. Taberlet, Estimating the probability of identity among
genotypes in natural populations: cautions and guidelines, Mol. Ecol. 10 (2001)
249–256.
[20] V. Lucchini, E. Fabbri, F. Marucco, S. Ricci, L. Boitani, E. Randi, Noninvasive
molecular tracking of colonizing wolf (Canis lupus) packs in the western Italian
Alps, Mol. Ecol. 11 (2002) 857–868.
Fig. 3. . Factorial Correspondence Analysis (FCA). Scores of individual baseline wolf (grey dots), dog (black dots) and tooth (black triangles) microsatellite genotypes plotted on
the first two axes of a FCA performed using Genetix.
R. Caniglia et al. / Forensic Science International: Genetics 4 (2010) 334–338
337
[21] C. Miller, P. Joyce, L.P. Waits, Assessing allelic dropout and genotype reliability
using maximum likelihood, Genetics 160 (2002) 357–366.
[22] N. Valie
`re, Gimlet: a computer program for analysing genetic individual identi-
fication data, Mol. Ecol. Notes 10 (2002) 1046.
[23] R. Peakall, P.E. Smouse, GenAlEx v.6.1: genetic analysis in Excel. Population
genetic software for teaching and research, Mol. Ecol. Notes 6 (2006) 288–295.
[24] D. Falush, M. Stephens, J.K. Pritchard, Inference of population structure using
multilocus genotype data: linked loci and correlated allele frequencies, Genetics
164 (2003) 1567–1587.
[25] A. Verardi, V. Lucchini, E. Randi, Detecting introgressive hybridisation between
free-ranging domestic dogs and wild wolves (Canis lupus) by admixture linkage
disequilibrium analysis, Mol. Ecol. 15 (2006) 2845–2855.
[26] K. Belkhir, P. Borsa, L. Chikhi, N. Raufaste, F. Bonhomme, GENETIX 4.05, population
genetic software in Windows TM, in: Genome Laboratory, Populations, Interac-
tions, CNRS UMR 5000, University of Montpellier II, Montpellier, France, 1996–
2004 (in French).
[27] J.P. Benze
´cri, Data Analysis. Volume 2. Correspondence Analysis, Dunod, Paris,
France, 1973 (in French).
R. Caniglia et al. / Forensic Science International: Genetics 4 (2010) 334–338
338
... Pontosabb eredményeket hoztak a biparentális mikroszatellitákat használó vizsgálatok, amelyeket vagy önmagukban [28,56,57], vagy uniparentális markerekkel kiegészítve alkalmaznak [4,58]. A két markertípus együttes használata a korábbiaknál megbízhatóbb és pontosabb eredményt ad, így manapság is javasolt közel rokon taxonok megkülönböztetésére, valamint a hibridek detektálására [18,19,23,24,59,[60][61][62][63][64][65][66][67][68][69][70][71][72][73][74][75]. ...
... Magyarország már 2010 óta rendelkezik egy kis létszámú, de növekvő farkas populációval [7], ezért minket is érint a faj védelme és a farkas-ember konfliktusok megelőzése, megoldása. Eddigi tapasztalatok alapján, ahol az emberi településekhez közeli farkaspopuláció növekszik, ott előbb-utóbb megjelenhet a haszonállatok megtizedelése [64,95,96], az emberek elleni vélt vagy valós támadások bejelentése [65,97] valamint a farkasok illegális vadászata és termékeikkel való kereskedelem [2,66]. Az ilyen igazságügyi esetek hátterének felderítéséhez általában különböző típusú molekuláris genetikai markereket, ill. ...
... Az ilyen igazságügyi esetek hátterének felderítéséhez általában különböző típusú molekuláris genetikai markereket, ill. ezek analízisének ötvözetét használják [2,47,[64][65][66]. Munkánk során mi is megkezdtük azon markerek tesztelését, amelyek a kitűzött céljainknak leginkább megfelnek, és az összesített eredményeink alapján többnyire sikeresnek bizonyultak a bi-és uniparentális módszerekkel végzett genetikai kutatásaink. ...
Article
Full-text available
ÖSSZEFOGLALÁS A szerzők a kutyák és farkasok különböző genetikai markerekkel történő elkülönítésének lehetőségeit vizsgálják és bemutatják ennek fontosságát az igazságügyi alkalmazás területén. A rendelkezésre álló farkas-és kutyaeredetű mintákból meghatározott mitokondriális kontrollrégió haplotípusok és a 14 vizsgált mikro-szatellita-alléleloszlás adatai alapján különbség látható a farkas-és kutyaminták között. Az eddigi hazai eredmények is alátámasztják annak lehetőségét, hogy különböző genetikai markerek párhuzamos vizsgálatával − amelyek megfelelnek az igazságügyi célú alkalmazás kritériumainak −, kellő valószínűséggel alátámasztható egy kérdéses eredetű minta alfajszintű besorolása. SUMMARY Background: After several decades of absence, the grey wolf (Canis lupus) has started recolonizing its former territories in Hungary at the beginning of the 21 st century. Due to the intense presence of mankind, wolves are forced to share great areas of land with humans, which potentially leads to several conflicts. From the wolves' perspective, it means the decimation of domestic livestock. As far as humans are concerned, these conflicts may manifest in the illegal hunting of wolves and trading with their products. When facing such case, it should be examined whether the perpetrator/victim is a wolf or a dog. Objective: The aim of our study was to test genetic methods which can be used for forensic application as well to distinguish between wolves, dogs, or their hybrids. Materials and Methods: Altogether 22 samples (hair, skin, faeces, saliva, and purified DNA) from wolves and wolf-dog hybrids were collected. For the comparative canine database DNA samples from Hungarian dog populations were used. After DNA isolation, the mitochondrial hypervariable region I (HVI) and 14 autoso-mal microsatellite markers were amplified by PCR (Polymerase Chain Reaction). Mitochondrial haplotypes determined by sequencing were grouped using PopART. Genetic profiles based on the detected microsatellite alleles were analysed using Structure 2.3.4 and were grouped based on a Bayesian approach. Results and Discussion: The mitochondrial control region (HVI) haplotypes were successfully determined from the examined samples; these sequences were uploaded to the GenBank database. We did not find similar point mutation patterns between wolves and dogs. However, difference between wolf and dog groups was shown based on the detected microsatellite allele distribution, to make the results even more reliable further markers and more wolf samples should be involved. Overall, our preliminary results support that simultaneous application of large number of genetic markers meeting the standards of forensic application criteria-, could be adequate to determine the precise taxonomic origin of questionable samples.
... In addition, crimes in the rural include cases in which farmers are the offenders; a perspective which has been generally ignored by mainstream criminology . Other examples include illegal criminal enterprises, such as in the meat trade ; environmental wildlife crimes (Caniglia et al. 2010;Fyfe and Reeves 2011;Loeffler 2013;Wellsmith 2011); and the illegal killing of predators or "pests" . Brisman et al. (2014, p. 482) suggest, for example, that the study of the rural and the subject of rural criminology create a fertile ground for the development of a "green-cultural criminology of the rural," which could include connections between the global and the rural; agribusiness and the food/profit chain; farming the land and polluting the water and air; the cultural and media images and narratives of rural life; and forms of resistance to environmental damage. ...
Chapter
Full-text available
This chapter starts by listing 20 reasons why crime and safety in rural areas is a subject worth examining in its own right. We present reasons from common misconceptions of crime in rural areas to illustrations of how globalization and climate change link to crime and safety in areas on the rural-urban continuum, as well as how all these are associated with rural development and sustainability.
... In this case study, we analysed the DNA contained in the remains of a canid faecal deposition collected in a forested area of central Italy to determine the individual multilocus genetic profiles of both the predator and the prey. In particular, we exploited the availability of reliable forensic genetic protocols [24], well-performing panels of canid [25] and felid [26] unlinked autosomal STRs and robust statistical procedures [21] to genotype non-invasive samples, assess their origin and clarify if they had wild, domestic or admixed ancestry. ...
Article
Full-text available
Non-invasive genetic sampling is a practical tool to monitor pivotal ecological parameters and population dynamic patterns of endangered species. It can be particularly suitable when applied to elusive carnivores such as the Apennine wolf (Canis lupus italicus) and the European wildcat (Felis silvestris silvestris), which can live in overlapping ecological contexts and sometimes share their habitats with their domestic free-ranging relatives, increasing the risk of anthropogenic hybridisation. In this case study, we exploited all the ecological and genetic information contained in a single biological canid faecal sample, collected in a forested area of central Italy, to detect any sign of trophic interactions between wolves and European wildcats or their domestic counterparts. Firstly, the faecal finding was morphologically examined, showing the presence of felid hair and claw fragment remains. Subsequently, total genomic DNA contained in the hair and claw samples was extracted and genotyped, through a multiple-tube approach, at canid and felid diagnostic panels of microsatellite loci. Finally, the obtained individual multilocus genotypes were analysed with reference wild and domestic canid and felid populations to assess their correct taxonomic status using Bayesian clustering procedures. Assignment analyses classified the genotype obtained from the endothelial cells present on the hair sample as a wolf with slight signals of dog ancestry, showing a qi = 0.954 (C.I. 0.780–1.000) to the wolf cluster, and the genotype obtained from the claw as a domestic cat, showing a qi = 0.996 (95% C.I. = 0.982–1.000) to the domestic cat cluster. Our results clearly show how a non-invasive multidisciplinary approach allows the cost-effective identification of both prey and predator genetic profiles and their taxonomic status, contributing to the improvement of our knowledge about feeding habits, predatory dynamics, and anthropogenic hybridisation risk in threatened species.
... In addition, crimes in the rural include cases in which farmers are the offenders; a perspective which has been generally ignored by mainstream criminology . Other examples include illegal criminal enterprises, such as in the meat trade ; environmental wildlife crimes (Caniglia et al. 2010;Fyfe and Reeves 2011;Loeffler 2013;Wellsmith 2011); and the illegal killing of predators or "pests" . Brisman et al. (2014, p. 482) suggest, for example, that the study of the rural and the subject of rural criminology create a fertile ground for the development of a "green-cultural criminology of the rural," which could include connections between the global and the rural; agribusiness and the food/profit chain; farming the land and polluting the water and air; the cultural and media images and narratives of rural life; and forms of resistance to environmental damage. ...
... In addition, crimes in the rural include cases in which farmers are the offenders, a perspective which has been greatly ignored by mainstream criminology (Collins, 2016). Other examples include illegal criminal enterprises, such as in the meat trade (Smith & McElwee, 2013), environmental wildlife crimes (Caniglia et al., 2010;Fyfe & Reeves, 2011;Loeffler, 2013;Maingi et al., 2012;Wellsmith, 2011) and the illegal killing of predators or 'pests' (Enticott, 2011;Gargiulo et al., 2016). ...
Chapter
Rural crime and safety is a neglected area of research. This chapter considers 15 reasons why the topic is worth investigating, taking each reason in turn and applying an international lens. The chapter discusses common misconceptions concerning rural crime and safety and in so doing makes a powerful case for far greater attention to the dynamics of crime and safety for those living in the rural/urban continuum and, more importantly, engaging societal and academic action into this process.
... In addition, crimes in the rural include cases in which farmers are the offenders; a perspective which has been generally ignored by mainstream criminology . Other examples include illegal criminal enterprises, such as in the meat trade ; environmental wildlife crimes (Caniglia et al. 2010;Fyfe and Reeves 2011;Loeffler 2013;Wellsmith 2011); and the illegal killing of predators or "pests" . Brisman et al. (2014, p. 482) suggest, for example, that the study of the rural and the subject of rural criminology create a fertile ground for the development of a "green-cultural criminology of the rural," which could include connections between the global and the rural; agribusiness and the food/profit chain; farming the land and polluting the water and air; the cultural and media images and narratives of rural life; and forms of resistance to environmental damage. ...
Book
Full-text available
Crime is not simply an urban phenomenon. Yet, until recently, criminology and other related sciences have neglected the nature and levels of crime outside urban areas (Donnermeyer 2016). There exists a multitude of reasons why scholars, policy and decision-makers as well as individuals in general should care about crime and safety in rural areas. This book, best understood as an extended essay, examines the evidence of crime in rural contexts, feelings of perceived safety or lack thereof, rural policing with examples of crime prevention practices. The aim of this book is to demonstrate the importance of crime and safety in areas on the rural-urban continuum in general, and from a social sustainability perspective in particular. This aim is achieved by first outlining 20 reasons as to why crime and safety matter, which also serves to delineate the field of research and illustrate its complexity, with many interdisciplinary ramifications. Then, by reviewing the international literature, the book reports four decades of English-language studies within the field and, finally, presents a research agenda which takes into consideration emergent areas of research, implications for practice, and the UN 2030 Agenda for Sustainable Development. Expanding our knowledge on rural crime and safety is not only an important step for the future of criminology, but a prerequisite for ever obtaining a truly sustainable society.
... The term "poaching" describes a number of illegal actions that directly harm animals and threaten the sustainability of their populations, including killing and trapping animals . In the media, poaching is often associated with illegal hunting in Africa (e.g., , South America (e.g., Wright et al., 2001), and Asia (e.g., Loeffler, 2013), but this violence against nature can be found anywhere in the world: in Europe (e.g., Caniglia, Fabbri, Greco, Galaverni, & Randi, 2010), Australia (e.g., Davis, Russ, Williamson, & Evans, 2004), and North America (e.g., Saumure, Herman, & Titman, 2007). In Sweden, report that the country imports and, to a lesser extent, exports animals and plants. ...
Article
Full-text available
... That shows that illegal killing may have a significant impact on lowland wolves. Two discovered sites of serial killing in the Polish lowlands provide an insight into the scale of the problem, also reported in Italy (Caniglia et al., 2010). Thus, illegal shooting might not be restricted to one case in a particular site, andif not addressed properly may escalate into a series of events, having a severe cumulative effect on the local wolf population. ...
Article
Full-text available
In central Europe, wolves Canis lupus prey on wild ungulates - main game species and occasionally kill livestock. The recovery of wolf population across the continent coincides with an increasing incidence of illegal killing, which level remains unknown. We analysed the illegal killing of wolves in Poland, where the species is strictly protected since 1998. We opportunistically collected data on wolves illegally shot and snared from 2002 to 2020, revealing their geographical extent and sex and age structure. Furthermore, we estimated their mortality rate due to illegal shooting on the basis of 16 GPS/GSM collared individuals between 2014 and 2020. We recorded 54 illegally shot and 37 snared wolves. The majority (63.7%) were killed between 2017 and 2020, mostly in Western Poland. The sex structure was similar between shot and snared individuals. In both groups, the wolves over one-year old prevailed, although there were 18 pups among shot wolves. We identified 6 shot and 3 snared breeders. Out of 16 GPS/GSM collared individuals, six were shot giving the mortality rate of 0.33 per year. Simulations revealed that the pooled number of wolves illegally shot in Poland annually, is between 147 and 1134 (99% highest density interval) or 216 and 1000 (95%). In six out of seven cases, in which the person who shot a wolf was eventually sentenced, hunters were responsible. We conclude that the present regulations concerning the prevention of illegal killing, pursuing and punishing the perpetrators of the illegal killing of wolves, require urgent improvements in order to effectively mitigate the problem.
... Genetic techniques are commonly used in the field of wildlife forensics to identify particular species or populations that are illegally poached and sold (Caniglia et al., 2010;Dalton & Kotze, 2011;Sanches et al., 2011;Domingues, de Amorim & Hilsdorf, 2013;Hobbs et al., 2019). The ubiquitous application of COI gene sequencing has made it the de facto gene marker in DNA barcoding work (Smith, Poyarkov & Hebert, 2008;Pentinsaari et al., 2016;Ip et al., 2019), especially for its efficiency in identifying animal products . ...
Article
Full-text available
• Giant guitarfishes (Glaucostegidae) and wedgefishes (Rhinidae) are some of the most threatened marine taxa in the world, with 15 of the 16 known species exhibiting global population declines and categorized as Critically Endangered according to the International Union for Conservation of Nature (IUCN) Red List of Threatened Species. The recent inclusion of all species in Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) necessitates more rigorous enforcement by regulatory authorities. • Challenges in regulating the trade of giant guitarfish and wedgefish products due to difficulties in visual identification of processed products and labelling issues impede enforcement. The aim of this study is to characterize the diversity and origins of associated traded products that were commercially available in Singapore, one of the world's top importers and re‐exporters of shark and ray products. • A total of 176 samples of elasmobranch products were obtained between June and December 2019 from fishery ports and various retailers in Singapore. By applying cytochrome c oxidase subunit I gene barcoding, 31 elasmobranch species were detected, with 55% of the species considered threatened (Critically Endangered, Endangered, or Vulnerable) based on the IUCN Red List and 35% of species listed in CITES Appendix II. Four species of giant guitarfishes and wedgefishes were commercially available to consumers in fresh forms of whole fish, fillet, and fin, as well as dried and cooked meats. • DNA barcoding has proven to be an effective tool for identifying elasmobranch products that are impossible to recognize visually and would aid enforcement of CITES trade regulations. This work underscores the urgent need to step up enforcement of marine wildlife regulations and draw public attention to the elasmobranch trade.
... The term "poaching" describes a number of illegal actions that directly harm animals and threaten the sustainability of their populations, including killing and trapping animals (Fyfe & Reeves, 2011). In the media, poaching is often associated with illegal hunting in Africa (e.g., Lemieux, 2011), South America (e.g., Wright et al., 2001), and Asia (e.g., Loeffler, 2013), but this violence against nature can be found anywhere in the world: in Europe (e.g., Caniglia, Fabbri, Greco, Galaverni, & Randi, 2010), Australia (e.g., Davis, Russ, Williamson, & Evans, 2004), and North America (e.g., Saumure, Herman, & Titman, 2007). In Sweden, Korsell and Hagstedt (2008) report that the country imports and, to a lesser extent, exports animals and plants. ...
Chapter
Full-text available
This chapter deals with two topics that are relatively neglected areas of research in the criminological literature: farm crime, and environmental and wildlife crime. The chapter has two sections, and both place Sweden in an international context. These offenses involve from diesel theft to drug manufacture, but also cases of crimes and harm against nature, such as illegal hunting. They present trends over time using Swedish police statistics and, data permitting, alternative data sources. Finally, geographical patterns of environmental and wildlife crimes (EWC) are discussed focusing mostly on urban–rural differences.
Article
Full-text available
Information on population parameters is rarely collected from carcasses. This method can be particularly useful – with limitations – when protected species are involved (e.g. the grey wolf Canis lupus in Italy). Local data on population structure, reproduction, survivorship and causes of mortality are necessary to build reliable conservation models to assess the state of a population and to predict its evolution. On the other hand, ‘best guesses’ or data from ecologically different areas have often been used to build population viability analysis and other conservation-oriented models. A sample of 154 wolf carcasses was found, collected and analysed from 1991 to 2001 in central-eastern Italy, the historic core of the wolf distribution range. Collision with a vehicle was the main cause of death in both sexes; however, road kills may be biased with a greater detectability, and we treated our data accordingly. Road kills were concentrated on the younger (≤4 years old) age classes, whereas fully adult wolves died mainly because of poaching, intraspecific strife and pathologies. Cubs and subadults (≤2 years old) showed a mortality peak in November/December, at the beginning of the dispersal period, whereas adults died mainly in January/February (mating season). The population structure of our sample of wolf carcasses appeared to be well balanced, although perinatal and cub mortality was underestimated. The sex ratio was 1:1 in the younger age classes and 1:0.7 in the older age classes. Only 20.7% of females, 2–6 years old, showed signs of reproduction; placental scar and embryo number varied from one to seven (mean, 4.4) per individual. Survivorship theoretical curves indicated a fair survival of cubs and subadults, but a steep decline as wolves approached maximum life span (9 years old). Our data and other published data on food habits and genetic features of the wolf in central-eastern Italy suggest that, despite ongoing heavy human-induced losses, this predator has fully recovered in the last 30 years from the brink of extinction.
Article
Full-text available
The Italian wolf (Canis lupus) population has declined continuously over the last few centuries and become isolated as a result of the extermination of other populations in central Europe and the Alps during the nineteenth century. In the 1970s, approximately 100 wolves survived in 10 isolated areas in the central and southern Italian Apennines. Loss of genetic variability, as suggested by preliminary studies of mitochondrial DNA (mtDNA) sequences, hybridization with feral dogs, and the illegal release of captive, non-native wolves are considered potential threats to the viability of the Italian wolf population. We sequenced 546 base pairs of the mtDNA control region in a comprehensive set of Italian wolves and compared them to those of dogs and other wolf populations from Europe and the Near East. Our data confirm the absence of mtDNA variability in Italian wolves: all 101 individuals sampled across their distribution in Italy had the same, unique haplotype, whereas seven haplotypes were found in only 26 wolves from an outbred population in Bulgaria. Most haplotypes were specific either to wolves or dogs, but some east European wolves shared haplotypes with dogs, indicative of hybridization. In contrast, neither hybridization with dogs nor introgression of non-native wolves was detected in the Italian population. These findings exclude the introgression of dog genes via matings between male wolves and female dogs, the most likely direction of hybridization. The observed mtDNA monomorphism is the possible outcome of random drift in the declining and isolated Italian wolf population, which probably existed at low effective population size during the last 100–150 years. Low effective population size and the continued loss of genetic variability might be a major threat to the long-term viability of Italian wolves. A controlled demographic increase, leading to recolonization of the historical wolf range in Italy, should be enforced.
Article
Full-text available
Hybridization with free-ranging dogs isthought to threat the genetic integrity ofwolves in Europe, although available mtDNA dataevidenced only sporadic cases of crossbreeding.Here we report results of population assignmentand genetic admixture analyses in 107wild-living Italian wolves, 95 dogs including30 different breeds and feral dogs, andcaptive-reared wolves of unknown or hybridorigins, which were genotyped at 18microsatellites. Two Italian wolves showedunusually dark coats (``black wolves''), and oneshowed a spur in both hindlegs (``fifth fingerwolf''), suggesting hybridization. Italianwolves showed significant deficit ofheterozygotes, positive FIS values anddeviations from Hardy-Weinberg equilibrium.Genetic variability was significantlypartitioned between groups, suggesting thatwolves and dogs represent distinct gene pools.Multivariate ordination of individual genotypesand clustering of inter-individual geneticdistances split wolves and dogs into twodifferent clusters congruent with the priorphenotypic classification, but hybrids andwolves of unknown origin were not identifiedfrom genetic information alone. By contrast, aBayesian admixture analysis assigned all theItalian wolves and dogs to two differentclusters, independent of any prior phenotypicinformation, and simultaneously detected theadmixed gene composition of the hybrids, whichwere assigned to more than one cluster.Captive-reared wolves of unknown origin wereprevalently assigned to the Italian wolfpopulation. Admixture analyses showed that one``black wolf'' had mixed ancestry in the dog genepool and could be a hybrid, while the other twowolves with unusual phenotypes were assigned tothe Italian wolf population.
Article
We describe extensions to the method of Pritchard et al. for inferring population structure from multilocus genotype data. Most importantly, we develop methods that allow for linkage between loci. The new model accounts for the correlations between linked loci that arise in admixed populations (“admixture linkage disequilibium”). This modification has several advantages, allowing (1) detection of admixture events farther back into the past, (2) inference of the population of origin of chromosomal regions, and (3) more accurate estimates of statistical uncertainty when linked loci are used. It is also of potential use for admixture mapping. In addition, we describe a new prior model for the allele frequencies within each population, which allows identification of subtle population subdivisions that were not detectable using the existing method. We present results applying the new methods to study admixture in African-Americans, recombination in Helicobacter pylori, and drift in populations of Drosophila melanogaster. The methods are implemented in a program, structure, version 2.0, which is available at http://pritch.bsd.uchicago.edu.
Article
1. Reliable estimates of population parameters are often necessary for conservation management but these are hard to obtain for elusive, rare and wide-ranging species such as wolves Canis lupus. This species has naturally recolonized parts of its former habitat in Western Europe; however, an accurate and cost-effective method to assess population trend and survival has not been implemented yet. 2. We used open-model capture–recapture (CR) sampling with non-invasive individual identifications derived from faecal genotyping to estimate survival and trend in abundance for wolves in the Western Alps between 1999 and 2006. Our sampling strategy reduced individual heterogeneity in recaptures, thus minimizing bias and increasing the precision of the estimates. 3. Young wolves had lower apparent annual survival rates (0·24 ± 0·06) than adult wolves (0·82 ± 0·04); survival rates were lower in the summer than in the winter for both young and adults. The wolf population in the study area increased from 21 ± 9·6 wolves in 1999 to 47 ± 11·2 wolves in late winter 2005; the population growth rate (λ = 1·04 ± 0·27) was lower than that recorded for other recolonizing wolf populations. 4. We found a positive trend in wolf abundance, regardless of the method used. However, the abundance estimate based on snow-tracking was on average 36·2% (SD = 13·6%) lower than that from CR modelling, because young dispersing wolves are likely to have lower sign detection rates in snow-track surveys, a problem adequately addressed by CR sampling. 5. Synthesis and applications. We successfully implemented a new method to assess large carnivore population trend and survival at large spatial scales. These are the first such estimates for wolves in Italy and in the Alps and have important management implications. Our approach can be widely applied to broader spatial and temporal scales for other elusive and wide-ranging species in Europe and elsewhere.
Article
In the early 1900s, the wolf (Canis lupus) was extirpated from France and Switzerland. There is growing evidence that the species is presently recolonizing these countries in the western Alps. By sequencing the mitochondrial DNA (mtDNA) control region of various samples mainly collected in the field (scats, hairs, regurgitates, blood or tissue; n= 292), we could (1) develop a non-invasive method enabling the unambiguous attribution of these samples to wolf, fox (Vulpes vulpes) or dog (Canis familiaris), among others; (2) demonstrate that Italian, French and Swiss wolves share the same mtDNA haplotype, a haplotype that has never been found in any other wolf population world-wide. Combined together, field and genetic data collected over 10 years corroborate the scenario of a natural expansion of wolves from the Italian source population. Furthermore, such a genetic approach is of conservation significance, since it has important consequences for management decisions. This first long-term report using non-invasive sampling demonstrates that long-distance dispersers are common, supporting the hypothesis that individuals may often attempt to colonize far from their native pack, even in the absence of suitable corridors across habitats characterized by intense human activities.
Article
We show that nuclear DNA extracted from faeces of free living bonobos (Pan paniscus) can be used to amplify hypervariable simple sequence repeats, which can be used for paternity analysis and kinship studies. Of 130 DNA extractions of samples from 33 different animals, about two-thirds yielded PCR products at the first attempt. For several samples only a second extraction resulted in positive amplifications. Consistency tests revealed that in some cases only one of the two alleles was amplified. Presumably this is due to a very limited amount of bonobo DNA in the sample and we suggest therefore that a sample found to be homozygous at a given locus should be typed repeatedly for verification.
Article
Growing interest in microsatellite genotyping, combined with noninvasive genetic sampling has led to the increased production of data. New tools to analyse these data are required. gimlet is a user-friendly software package designed to perform several simple tasks: (i) construction of consensus genotypes from repeated genotyping; (ii) estimation of genotyping error rates; (iii) identification of identical genotypes; (iv) comparison of new genotypes to a set of reference genotypes; (v) determination of the kinship; and (vi) estimation of several population parameters such as allele frequencies, heterozygosity, probability of identity, and population size.