Botanical DNA evidence in criminal cases: Knotgrass (Polygonum aviculare L.) as a model species

Forensic Science International: Genetics 6 (2012) 366–374

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Forensic Science International: Genetics journal homepage: www.elsevier.com/locate/fsig

Research Article

Botanical DNA evidence in criminal cases: Knotgrass (Polygonum aviculare L.) as a model species Wim J.M. Koopman a,*, Irene Kuiper b, Dick J.A. Klein-Geltink a, Gerda J.H. Sabatino a, Marinus J.M. Smulders a a b

Plant Research International, Wageningen UR, P.O. Box 16, 6700 AA Wageningen, The Netherlands Netherlands Forensic Institute, Laan van Ypenburg 6; 2497 GB The Hague, The Netherlands

A R T I C L E I N F O

A B S T R A C T

Article history: Received 23 December 2010 Received in revised form 25 July 2011 Accepted 26 July 2011

The possibilities and strategies for using DNA characteristics to link a botanical sample to a specific source plant or location vary with its breeding system. For inbreeding species, which often form small patches of identical genotypes, knotgrass (Polygonum aviculare L.) is a suitable model species because of its (1) occurrence in a wide range of natural environments, (2) abundant presence in pieces of evidence, and (3) ease in molecular processing. The value of knotgrass for forensic casework was demonstrated using data from a homicide case. Using the DNA fingerprinting technique AFLP1 we were able to identify the knotgrass population at the crime site as the most likely origin of the botanical evidence. We expect that the development of tailored marker systems for knotgrass and other frequently occurring (model) species will considerably accelerate the use of botanical DNA evidence in criminal cases. ß 2011 Elsevier Ireland Ltd. All rights reserved.

Keywords: Amplified fragment length polymorphism (AFLP) Breeding system DNA barcoding Forensic botany Forensic science Polygonum aviculare

1. Introduction In 1993, molecular forensic botany got off to a jump start with the famous Maricopa case. A year earlier, a woman’s body had been found in the Arizona desert at a factory site surrounded by Palo Verde trees (Parkinsonia florida (Benth. ex A. Gray) S. Watson). One of the trees showed damage from a recent collision, and two seed pods were found in the back of the suspect’s truck. The seed pods were identified as Palo Verde. The pods, the damaged tree, and 29 reference trees were sampled and genotyped with 47 RAPD markers. All trees showed different genotypes, but the genotype of both seed pods were identical to that of the damaged tree, thus tying the truck to the murder site. In the ensuing trial, the RAPD data became the first molecular botanical results in history to be accepted as convincing evidence in court. Based on these results, the suspect was found guilty of murder [1–3]. The Maricopa example illustrates the two steps typically taken in a plant forensic classification scheme [4]: (1) identification of the species in the sample, and (2) attribution of the sample to a source plant or source population of the proper species.

* Corresponding author. Current address: Koopman Scientific Services, P.O. Box 404, 1600 AK Enkhuizen, The Netherlands. Tel.: +31 649412844. E-mail address: [email protected] (Wim J.M. Koopman). 1872-4973/$ – see front matter ß 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.fsigen.2011.07.013

In the first step, species are traditionally identified based on their morphology. In many cases, however, the sample is too small, or the tissue or developmental stage does not show sufficient differentiating characters for a positive identification. Molecular identification can provide a solution here, enabling identification of very small samples regardless of their developmental stage or morphology. To date, most work on molecular species identification in general is conducted within the Barcode of Life framework (CBOL, http:// www.barcodeoflife.org). More targeted approaches also exist, e.g. for the forensic identification of grasses [5–7] and plants from Taiwan [8]. The CBOL Plant Working Group has recently proposed a basic set of two DNA sequences for the identification of land plants [9]. Supplemented with selected sequences for specific taxonomical groups, these sequences are expected to enable a rapid species identification in most botanical samples [9,10]. This species identification is needed to enable the collection of proper reference material for the second step in the forensic classification scheme. In this second step, the sample is assigned to a source plant or source population of the proper species, using highly polymorphic molecular markers such as microsatellites (also called SSRs, see [11] for a review) or SNPs (reviewed in [12]). The markers ideally provide resolution at the genotype level, enabling the identification of each individual genotype. Unfortunately, highly polymorphic markers tend to be highly species-specific as well, and most markers will only amplify in a limited set of closely related species. This specificity presents forensic botanists with a challenging problem unfamiliar to

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human forensics: the need to develop or select specific polymorphic markers for virtually every new (group of) species encountered in botanical samples. A second problem unfamiliar to human forensics is the presence of various modes of reproduction in plants. Roughly, four reproduction systems can be distinguished: cross breeding, selfing, apomixis, and clonal propagation [13,14]. Cross breeding (or outbreeding) in plants is similar to that in humans: two different individuals are needed for reproduction, and if their genetic difference is large enough, their progeny will show a plethora of distinct genotypes identifying every single individual. Selfing (or inbreeding) is a breeding system very common in plants but rare in animals. With selfing, the same individual is both the male and the female parent of the progeny. The genetic variation in the progeny is proportional to the genetic diversity of the parent. Repeated selfing eventually leads to an offspring population with genetically identical individuals, rendering recognition of individual plants by their genotype impossible. Clonal propagation, also a common mode of reproduction in plants, does not involve any breeding at all: each new plant develops from a part of the parental plant (e.g. a cutting), and thus has the same genotype. Apomixis has identical implications, but is far less frequent than clonal propagation is. In the case of apomixis, the offspring results from true seeds that have the exact parental genotype. Combinations of breeding systems commonly occur [13–16], with e.g. inbreeders [15,16] or apomicts [17] showing a certain degree of cross breeding, or cross breeding species resorting to inbreeding at the end of the flowering season (e.g. [18,19], a phenomenon known as end of season (pseudo) compatibility [20]). The propagation system of a plant species has a huge impact on the way genotype data can be used in forensics. Cross breeding will generally lead to a situation in which every plant has a different genotype, enabling a very precise assessment of geographical location such as in the Maricopa case. However, finding the matching individual may be very difficult, especially when individuals are small and many individuals are present in the area of interest. The latter is often the case for e.g. grasses, a species group abundantly present in botanical evidence [5,6]. In contrast, clonal propagation and apomixis will usually create large numbers of genetically identical plants, and individual genotypes may occupy large areas [17,21]. Given these large areas, chances of retrieving a specific genotype are relatively high, but the corresponding geographical location will not be very well defined. Inbreeding species usually occupy an intermediate position, showing patches of genetically identical or related individuals only on a local scale. The size of these patches will vary with the degree of inbreeding. Repeated inbreeding for many generations will result in large populations with identical genotypes, while occasional cross breeding events will break up the uniform population structure and locally introduce new genotypes into the population. As a result of this balance, chances of finding a matching genotype are relatively favorable for inbreeders (even when a location is occupied by large numbers of individuals), while the presence of genetic differentiation assures the required geographical accuracy, especially over larger distances. Therefore, we hold that inbreeders are the species of choice to yield useful molecular botanical evidence. In the present paper, we demonstrate the suitability of the commonly occurring inbreeding species knotgrass (Polygonum aviculare L.) as a source of botanical evidence. The evidence presented concerns a homicide case in which a body was disposed in a stream near a knotgrass covered roadside, and several knotgrass seeds were retrieved from the wheel case of the suspect’s car. Using AFLPs11 [22] as molecular markers, we were able to identify the 1 The AFLP1 technology is covered by patents and patent applications owned by KeyGene N.V.

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crime site as the most likely origin of one of the knotgrass seeds. Based on these results, we propose that knotgrass is a suitable model species for obtaining molecular botanical evidence, both as a target species in actual crime cases, and as a reference standard for other inbreeding plant species. For those unfamiliar with botanical species, it should be noted that notwithstanding its common name, knotgrass is not a grass. Instead, it belongs to the Polygonaceae family, which makes it closely related to species such as sorrel, buckwheat, and rhubarb [23,24]. 2. Materials and methods 2.1. Sample collection Samples were collected in three batches. Firstly, eight P. aviculare seeds were collected from soil out of the wheel case of a suspect’s car (denoted BE). Secondly, 57 soil samples were collected from a P. aviculare population at the crime site (CS; see Fig. 1 for details), and 41 from a population in the suspect’s backyard (BY). Sampling was performed in autumn when the original plants had died off, and therefore each soil sample was collected directly underneath the remains of an individual P. aviculare plant. In addition, young leafs were collected from four surviving BY plants. The sampling covered most of the recognizable plant remains at both sites. Thirdly, during the following season, samples from 15 living plants were collected from each of eight additional reference sites covering the geographical area commonly travelled by the suspect. To examine population identity and variation near the crime site and backyard, populations were sampled at 2 and 10 km from crime site (OHE and LBT) and backyard (PTH and BRM), respectively. Variation in the remaining part of the South of the Netherlands was sampled from two populations located 20 km from the crime site and 20 km apart (AST and LAA). Variation in the rest of the relevant part of the Netherlands was sampled from two populations 60 and 100 km to the North of the crime site (LHS and REN) (Table 1 and Fig. 2; the WGS84 coordinates given in Table 1 are for each population the coordinates of one of the collected plants, and can be used to ‘‘fly’’ to the locations in Google Earth). To make each sample as much as possible representative for each population, we adjusted the sampling pattern to the population structure at the various sites. Plants from populations with a relatively uniform shape and plant

Fig. 1. Location of the CS samples at the crime site. The closest match to the BE is indicated by an arrow (sample CS012).

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Table 1 Sampled populations with numbers of plants specified per type of AFLP profile. The locations are presented from south to north (see Fig. 2). The WGS84 coordinates can be used to fly to the locations in Google Earth. For privacy reasons, no coordinates are given for the Back Yard. Note that for several populations, the number of plants with a Type 1 profile is larger than the number of different Type 1 profiles in that population, because several plants showed the same profile. Code

Location

Coordinates (WGS84)

No. of plants analysed per population

No. of plants per population with a Type 1 profile

No. of different Type 1 profiles per population

No. of plants per population with a Type 2 profile

BE BRM

Wheel case Brommelen

1 14

1 11

1 10

– 3 (22%)

BY PTH

Back Yard Puth

51 15

51 15

5 14

– -

LBT

Limbricht

15

11

11

4 (27%)

CS

Crime site

48

42

37

6 (13%)

OHE

Ohe´

15

15

14

-

AST

Asselt

15

12

12

3 (20%)

LAA

Laar

15

12

10

3 (20%)

LHS

Landhorst

14

12

12

2 (14%)

REN

Renkum

– 508540 27.7400 N 058430 56.3800 E – 508570 47.1500 N 058520 26.5100 E 518010 06.8600 N 058490 32.0800 E 518050 37.2700 N 058500 12.5300 E 518060 40.6700 N 058510 00.3900 E 518130 39.0500 N 068010 12.6200 E 518160 33.4800 N 058420 30.8200 E 518370 11.6100 N 058460 54.9400 E 518580 22.2800 N 058440 06.0400 E

15

–

–

15 (100%)

Fig. 2. Geographical location of crime site (CS), suspect’s backyard (BY), and additional reference populations throughout the south-eastern part of the Netherlands.

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density were sampled at more or less equal distances along a transect through the population. In populations with a more patchy structure, densely populated patches were sampled more thoroughly than patches with fewer plants. The seeds from the BE sample were germinated in Petri dishes, individually transferred to pots, and raised under standard greenhouse conditions. Only one of the seeds yielded a mature plant. Additionally, 10 seeds were recovered from each of the soil samples and raised to small plants as above. Leaf tissue was collected from the BE plant and from two young plants from each of the soil samples, frozen in liquid nitrogen and stored at 80 8C. To enable a rough estimate of the coverage of the sampling, three additional plants were collected from samples CS078 and BY009, and four additional plants from samples CS041 and BY060. For each of the reference populations, young leaves were collected directly in liquid nitrogen and stored at 80 8C.

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than longer ones, and this also goes for the shorter bands we selected. Because the gel space between adjacent gel positions increases likewise, the shorter bands can still be reliably distinguished. Secondly, selected bands had to be clearly separated from nearby bands. The Sequagel-6 polyacrylamide gels we used in our study are sequencing gels, thus allowing a one base pair band resolution. Bands that did not unequivocally show this separation or bands that seemed to occupy multiple band positions were not used for scoring. Note that notwithstanding this criterion, in several cases bands were selected close to (but clearly separated from) adjacent bands. In these cases, the adjacent bands provided a reference line enabling a reliable scoring of the selected bands. Thirdly, selected bands had to have a high and constant band intensity on all of the gels. Bands with a varying intensity, or bands that were not clearly absent or present in one or more lanes on one or more of the gels were excluded from scoring.

2.2. DNA extraction 2.4. Data processing Leaf samples were freeze-dried immediately prior to DNA extraction. DNA was extracted from the dried leafs using a Qiagen Dneasy 96 Plant Kit (Qiagen Benelux BV, Venlo, The Netherlands) according to the manufacturer’s instructions. DNA was extracted for one plant from each of the CS and BY soil samples and from all of the additional CS and BY plants. The BE sample was extracted in duplicate, starting from two portions of leaf material independently harvested on two separate dates. 2.3. AFLP procedure Twenty-seven primer combinations (pcs) were tested for their usefulness as forensic molecular markers using a set of five samples: the BE sample, two CS samples, and two BY samples. The primer combinations were compared using three criteria: (1) presence of sufficient but not excessive numbers of bands, (2) presence of sufficient polymorphisms, (3) absence of anomalies such as smears and extremely fat bands. Based on these criteria, pcs E12/M49 (EcoRI-AC/MseI-CAG), E12/M51 (EcoRI-AC/MseICCA), and E12/M54 (EcoRI-AC/MseI-CCT) were selected to generate the final dataset. To avoid any bias in the selection of pcs, the rate of similarity among the samples was not included as a selection criterion. The AFLP procedure was performed essentially as described by Vos et al. [22] with some modifications [25,26]. For the selective amplification, the EcoRI primer was labeled with 33P. Reaction products were loaded on a 6% polyacrylamide gel (Sequagel-6, Biozym TC, Landgraaf, The Netherlands) in 1 TBE electrophoresis buffer using a SequiGen 38  50 cm gel apparatus (BioRad Laboratories, Nazareth Eke, Belgium). To enable a detailed comparison of BE and references, each seventh lane on the gel contained a BE sample. Samples from both BE replicates were alternated on the gel. Gels were dried on Whatmann 3 MM paper, and X-ray films (Kodak X-OMAT, Rochester, New York, USA) were exposed for 1–3 weeks at room temperature. The films were scored manually and bands were coded binary (present = 1, absent = 0). To assure the highest possible reproducibility of AFLP bands across the entire dataset, bands had to meet strict criteria to be selected for final scoring. Firstly, they had to be sufficiently sharp. Selected bands had to have clear boundaries, and bands that were too blurry in one of the lanes on one of the gels were excluded from scoring. Note that the amount of gel space occupied by a single band position increases with decreasing band length, which can be seen on the gel images in Supplementary Figures Sup. 1, Sup. 2, and Sup. 3 (see [27,28] for a theoretical background on this phenomenon). As a result, shorter bands are inherently blurrier

To obtain background information on the population structure in the sampled area, AMOVA’s and pairwise comparisons among the populations were performed on the entire dataset, and on a subset of the data without populations CS and BY. We used AMOVA-PREP 1.01 [29] to prepare separate datasets for the distance measure of Excoffier et al. [30] and for the Simple Matching coefficient [29]. The analyses were performed with the program AMOVA version 1.55 [30]. For a more detailed examination of the relationship among the BE and the sampled populations, cluster analyses were performed for the separate and the combined pcs, using the program Treecon for Windows 1.3b [31]. Each analysis comprised two steps. In the first step, a distance matrix was calculated using Nei and Li [32] distances. In the second step a phenetic tree was constructed based on the distance matrix, using UPGMA clustering [33]. The resulting tree showed the AFLP similarities among all samples. In several cases, different plants showed identical profiles for the combined pcs. In a final analysis, the data were summarized by entering these profiles only once. To examine the relationships among BE, CS, BY, and reference plants in more detail, additional rounds of cluster analyses were conducted on the dataset with the combined pcs, including duplicate profiles. Prior to each successive round, the plant that clustered most closely to the BE sample in the previous round was removed. Thus, the dataset was reduced with one plant in each round. The plant clustering most closely with the BE sample was recorded for each successive round. A further quantification of the relationships among BE, CS, BY, and reference plants was done by counting the number of AFLP band differences between the BE sample and the plants from the other populations. Each of these populations contains multiple plants, which vary in numbers of bands differing from the BE sample. Therefore, the differences between BE sample and reference populations will be depicted as a range rather than a number. 3. Results 3.1. Seed and soil samples The BE seeds from the wheel case were positively identified as P. aviculare based on their morphology. Due to the poor quality of the seeds, only one of the eight seeds grew to an adult plant. Better germination rates were obtained for the fresh soil samples: 41 of the 59 CS samples and 40 out of 41 BY samples yielded at least one plant.

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3.2. AFLP primer and band selection The selection resulted in a total of 64 unambiguous bands for the three pcs: 25 bands for E12/M49 (from which 23 were variable), 19 bands for E12/M51 (16 variable), and 20 for E12/M54 (18 variable). For each primer combination, the selected bands are indicated by closed arrows in Supplementary Figures Sup. 1, Sup. 2, and Sup. 3, respectively. 3.3. BE sample and references The dataset contained two clearly distinct types of AFLP profiles (designated Type 1 and Type 2, see Supplementary Figures Sup. 1, Sup. 2, Sup. 3, and Table 1). Compared to the Type 1 profiles, Type 2 profiles contained more bands, and many of these bands were unique to the Type 2 profiles. Several of the bands (examples of which are marked by open arrows in the supplementary figures) are diagnostic for Type 2 profiles, i.e. they were present in all Type 2 plants but in none of the Type 1 plants. As can be seen in the supplementary figures, the BE sample and most of the reference samples belong to Type 1, and therefore Type 2 was excluded from further analysis. The AMOVA for the entire dataset showed that most of the genetic variation (77.55% for both distance measures) is located within the populations. Nevertheless, the remaining 22.45% variation among the populations represents a highly significant population differentiation (phiST = 0.225, p < 0.0001). This differentiation is confirmed by the pairwise comparisons, showing significant differences (p < 0.0001) between all population pairs except CH/BRM (for the Excoffier measure) and OHE/AST (for both measures). For the data set without CS and BY, the population differentiation was less pronounced, with 85.64% of the variation located within the populations. However, the remaining 14.36% variation among the populations still points to a highly significant population differentiation (phiST = 0.144, p < 0.0001). All pairwise comparisons except for OHE/AST with the simple matching coefficient, showed significant differences at p < 0.0001. The cluster analysis of the combined pcs showed that in 11 cases, several plants in a population showed the same Type 1 AFLP profile. In four cases, these were plants from the reference sites: 2 plants out of the 11 (=18%) on location BRM, 2 out of 15 plants (13%) on locations PTH and OHE, and 3 out of 12 (25%) on LAA. On the crime site, 8 plants out of 42 (19%) showed non-unique genotypes: two profiles were shared by 2 plants, and one profile was shared by 4 plants. The BY population included as much as 98% of plants with shared genotypes, resulting in only five different Type 1 profiles for 51 plants. One of these profiles was unique to one plant, the other four were shared by 4, 5, 8, and 33 plants, respectively. Fig. 3 (indicating the total number of plants showing a certain profile between brackets), and Table 1 (giving the total number of different Type 1 profiles left in each of the populations) summarize the above results. The locations in Table 1 are presented from South to North to show the absence of a geographical trend in the proportion of Type 2 profiles per population. The results for the separate pcs (not shown) were similar to those for the combined pcs. The cluster analysis (Fig. 3) reveals the close relationship between the BE sample (indicated by an arrow in Fig. 3) and the plants on the crime site. Firstly, the BE sample clusters with plant CS 010, differing from it in only one band. Secondly, the BE sample is located within a larger cluster of plants (denoted by an asterisk in Fig. 3) mainly (29 out of 33 plants) originating from the crime site. The additional tests with successive removal of plants confirmed the close match of the BE sample with the CS plants. The 17 plants most similar to the BE sample all originated from the crime site. Only after removal of these 17 plants from the dataset, the BE sample clustered with a non-CS plant (AST 177) for the first time.

Fig. 3. UPGMA clustering based on Nei and Li distances for the combined pcs E12/ M49, E12/M51, and E12/M54. The botanical evidence (BE) is indicated by an arrow. The asterisk indicates the group of mainly crime site (CS) samples clustering with the BE sample. Scale bar indicates Nei and Li distances.

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Fig. 4. Ranges of band differences of the BE sample with the CS, BY, and additional reference population samples.

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substantial effort is required to develop and optimize a set of markers for a specific species, although it must be noted that developments in this field are growing rapidly and costs are steadily decreasing. At present, sets of STR markers are available for many agriculturally important species, but for forensic purposes development of STR or SNP markers is economically feasible only for commonly encountered species such as Cannabis sativa L. ([34–37]). AFLP markers are much easier to adapt to a specific species, because one only needs to make a selection from the available pool of primer combinations. For that and many other reasons, AFLP fingerprinting has become a firmly established molecular marker technique for many applications [38], including forensic work on e.g. Marijuana (C. sativa L.) [4,39]. For the present study into the feasibility of knotgrass as a source of botanical forensic evidence, we therefore opted for the AFLP technique. 4.3. Population structure of knotgrass

An easy way to quantify the relationships among the BE sample and the plants from the other sites is by counting the number of AFLP band differences between them. The counts showed that plants from the crime site differ in 1–18 bands from the BE sample, while BY plants differ from it in at least 11 bands and plants from the reference sites in at least 7 bands (Fig. 4). Detailed examination of the individual plant data showed that as many as 16 out of the 42 plants on the crime site (38%) are more similar to the BE sample than is any of the reference samples (comprising no less than eight locations, including BY). 4. Discussion 4.1. Identification of the BE sample A plant forensic classification scheme typically comprises two steps: (1) species identification, and (2) attribution of the sample to a plant or population (see [4] and Section 1). Considering the first step, molecular methods are extremely powerful in that they often enable species identification when the forensic sample lacks distinguishing morphological characters, or when the relevant taxonomic expertise is not at hand. In the case presented here, the seeds showed sufficient characteristics to enable a morphological identification, and hence there was no need for molecular methods. In the second step, the application of a molecular method was indispensible. Firstly, our results showed that the BE sample is genetically much more related to many plants on the crime site than it is related to plants from the backyard or from other reference populations. Secondly, we were able to pinpoint plant CS012 as a genetically very close relative of the BE seed sample. Interestingly, plant CS012 (indicated by an arrow in Fig. 1) was sampled at the edge of a fork in the road at the crime site. Such a location is consistent with the theory that mud containing the BE sample splashed into the wheel case of the suspect’s car at this very spot. Given the difficulties with morphological identification of knotgrass plants, it would not have been possible to make such a match with a population or an individual using morphological features. 4.2. Selection of markers The molecular method employed must be tailored to fit the variation expected at the population level. This need for variation precludes the use of commonly employed taxonomic sequences, because these are too conserved. Markers typically used for the studies of population level variation include STRs (Short Tandem Repeats), AFLPs (usually referred to as Amplified Fragment Length Polymorphisms), and SNPs (Single Nucleotide Polymorphisms). Relative to AFLPs, STRs and SNPs have the disadvantage that a

In the reference populations, plants were sampled approximately 5–20 m apart, depending on the location and the local coverage with knotgrass. Fig. 3 shows that within some populations (but never among populations), several samples shared the same genotype. Given the fact that the knotgrass plants we typically encountered occupied approx. 20  20 cm of space, and assuming that we took a representative sample, this means that larger areas, containing numerous plants, will be occupied by a single genotype. The advantage of this situation is that it increases the chances of retrieving a certain genotype within the population, since the chances of hitting a genotype increase with its frequency in the population. The disadvantage is that it becomes impossible to match a sample with an exact plant, because plants with the same genotype cannot be distinguished. In our dataset, the proportion of plants on a certain location sharing the same genotype was in the range of 13–25%. Consequently, most plants showed unique genotypes, thus providing sufficient resolution for intra-population matching of the sample. Population BY was a clear exception to this rule, with 98% of the plants sharing genotypes. The large difference in genetic variation between BY and the other populations may be explained by its location in a backyard parking lot, surrounded by brick walls. Firstly, the number of founding genotypes for this population may have been limited. Most of the area was covered with tarmac (the plants we sampled were mostly growing in cracks therein), and the application of this tarmac to the originally bare ground will have eradicated most of the original vegetation. Secondly, a possible influx of seeds or pollen from outside the BY populations will be hampered by the presence of the walls. Still, five different genotypes were present in the population, enabling at least some intra-population resolution. This presence of both shared and unique genotypes is characteristic (but not unique) for knotgrass populations, typically consisting of mixtures of inbreeding lines [40]. 4.4. Breeding system of knotgrass In the botanical literature, knotgrass is consistently reported to be an inbreeding species ([40–43]). It should be noted, however, that the distinction among the various breeding systems is not an absolute one, and that inbreeders usually show some degree of outbreeding (see [13–16] and Section 1). For a species to serve as a model for inbreeders, it is important that the level of outbreeding is very low, and knotgrass appears to satisfy this criterion. A detailed study into the breeding system of knotgrass has yet to be conducted, but the presently available sources indicate a very low level of outbreeding for P. aviculare. Based on morphological features and chromosome counts, Love and Love [41] recognized

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the presence of both natural and artificial hybrids between P. aviculare sensu stricto and closely related (sub)species. However, they noted that the hybridization frequency was very low, and attributed this low frequency to the ‘‘pronounced autogamous (=inbreeding)’’ breeding system of the (sub)species. In numerous field observations, Styles [42] did not observe any insects visiting P. aviculare flowers, while his hybridization attempts were unsuccessful. He concluded that the ‘‘flowers appear always to be selffertilized’’. Schmid [43] reported that the occurrence of plants with intermediate characteristics and the abundant presence of insects in P. aviculare stands suggested that the possibility of cross breeding could not be ruled out. However, he also noted that no insects were observed to actually visit the flowers, and that many flowers were already self-pollinated when they opened. Given these data, he characterized the breeding system as ‘‘for the largest part pure autogamous’’ (=inbreeding), and even ‘‘of an cleistogamous-like behavior’’ (cleistogamous flowers do not open at all, thus rendering cross-pollination largely impossible). More recently, an allozyme study of Meerts et al. [40] confirmed the above observations. They concluded that virtually all of their results were consistent with P. aviculare being an inbreeding species, but that the presence of one deviating genotype suggested that inbreeding in P. aviculare is not absolute. Crossing experiments performed as part of the same study were unsuccessful. It is interesting to note that in the above studies all indications for cross breeding are circumstantial, while the bulk of the results identify P. aviculare as a (very strict) inbreeder. Therefore, it seems justified to conclude that P. aviculare is a proper model for inbreeding species, notwithstanding the possibility of some occasional outbreeding.

degraded [49,50], when it contains substances hindering DNA extraction such as polysaccharides [51] or acids [52], or when it is contaminated with microorganisms [53]. In the present study we used freeze-dried tissue from leaves collected fresh from plants raised in the greenhouse and from plants growing along roadsides. DNA extraction from this tissue yielded good quality DNA without any problems, indicating an absence of hindering substances. The quality of the starting material will vary with each case, but roadside observations by the first author suggest that knotgrass leaf tissue is not particularly susceptible to degradation. Moreover, many roadside locations include warm and dry spots where desiccated leaf- and stem-tissue may be relatively well preserved. The seeds of knotgrass have a tough outer surface that protects the soft tissue inside, enabling their prolonged survival in the soil. The seeds are relatively large (1.2–5 mm; [24]), providing sufficient starting material for DNA extraction from the inner tissue. A peculiarity of knotgrass is the large variation in leaf and stem morphology, which has given rise to the description of numerous intraspecific taxa in the past (reviewed in e.g. [54,55]). More recently, detailed studies have revealed that a large part of this variation is determined by environmental factors such as soil fertility, plant density, and trampling [56,57]. On top of that, the morphological differentiation among the subspecies is small and obscured by the presence of individuals and populations with an intermediate morphology [54,58]. Given this plasticity and variation, distinction of subspecies will be highly impractical [24,55] in field situations, and we suggest that for forensic purposes P. aviculare is to be treated as a single species (P. aviculare sensu lato) as proposed by e.g. Costea and Tardif [55].

4.5. Knotgrass as a forensic model species

4.6. Development of tailored markers

As described above, the breeding system and population structure of knotgrass fit that of an inbreeder with a very small amount of cross breeding. As such, it could serve as a forensic model for inbreeding species. To be widely applicable as a model species however, knotgrass should also meet other requirements. Most notably, it should be: (1) abundant in nature; (2) commonly present in pieces of evidence, and (3) suitable for molecular processing and identification. Knotgrass easily meets the first criterion since it occurs almost circumglobal [23,24,44–48], and as such it is a potentially useful species in most jurisdictions. On top of that, it is a common weed in arable land, on waste ground and by the roadside, and as such it can be expected at crime sites in most environments. The occurrence of knotgrass along roadsides is especially useful, since roadsides are common primary or secondary crime site locations. As was established in our investigations, knotgrass seeds are locally abundant in roadside dirt and are easily picked up by cars along with this dirt. The abundance of knotgrass seeds in roadside dirt is also important in meeting the second criterion, since soil (including roadside dirt) is frequently encountered as trace evidence. Palynological examination of Dutch soil samples showed a frequent occurrence of knotgrass pollen, indicating the presence of knotgrass plants in close association with these soil samples. Indeed, knotgrass seeds were accidentally encountered in several such samples (Personal observation of the second author based on casework at the NFI during the last 7 years). Given the accidental retrieval of knotgrass seeds and the abundant presence of soil samples with knotgrass pollen, it is to be expected that knotgrass seeds will be found in many more cases when they are specifically searched for. Thus, knotgrass will also meet the presence criterion. The third criterion relates to one of the major bottlenecks in molecular forensic work: the availability of sufficient quality DNA. Problems may be encountered when the starting material is

The main reason we used AFLPs in the present study is that our set of preselected AFLP markers could easily be adapted for the use in a new species such as knotgrass. However, the AFLP technique also has its disadvantages, most importantly the need for high quality template DNA, and the susceptibility to contamination. Also, concerns are sometimes raised about the reproducibility of AFLPs, and about their transferability among labs. From our own experience with AFLPs we found that much depends on the experience of the labs involved, and the proper selection of primer combinations and bands. Comparison studies (e.g. [59]) indicate that the reproducibility and transferability of AFLPs are very high when properly performed by experienced labs, and far better than the reproducibility and transferability of RAPD markers. In the present work, we strived for the highest possible reproducibility in several ways. Firstly, starting from a pool of 27 pcs preselected in previous studies for generally yielding good patterns in plants [25], we selected the three pcs that performed best in our test data set. As can be seen from Supplementary Figures 1, 2 and 3, these primer combinations yield patterns with generally clear and well-defined bands. Secondly, only bands that were well defined, discernable, and 100% reproducible across all gels were selected for the final scoring (see Section 2.3 for the exact selection criteria). Thirdly, the reproducibility of the selected bands was verified using numerous duplicates across the various gels. Most important of these was a BE duplicate for which the two samples were extracted independently from two portions of leaf material harvested on two separate dates. This procedure enabled a verification of the entire AFLP procedure. In addition, the final amplification of the BE duplicate was performed anew for each new gel, together with the final amplification of the other samples on the gel. Thus, the reproducibility of the final amplifications was verified. The results showed a 100% reproducibility of the selected bands of the BE duplicates across all gels and all primer

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combinations (see Supplementary Figures 1, 2 and 3; remaining data not shown). The above results demonstrate that when properly performed, the AFLP procedure will yield highly reproducible markers. For routine use in forensic casework however, it may be safer to use more robust markers such as (mini) STRs or SNPs. Firstly, they are less demanding as to the quality of the template DNA. Whereas application of the AFLP technique requires high molecular weight i.e. not obviously degraded DNA [38], STRs and SNPs can still be reliably generated when the DNA is (moderately) degraded [49,50]. Therefore, on the poorly preserved DNA that is often retrieved from crime scenes, STRs and SNPs are expected to yield more reliable results than AFLPs do. Secondly, in contrast to AFLPs, STRs and SNPs are taxon specific. Unlike AFLPs, which are generated from all DNA in a sample regardless of its origin, STRs and SNPs are only amplified from a target species or its close relatives, using species-specific primers. Since this precludes the amplification of DNA from non-target species, STRs and SNPs will be less susceptible to contamination of a sample with e.g. fungi and bacteria [49,50]. 5. Conclusions Knotgrass (P. aviculare L.) is a suitable model for the use of inbreeding plant species in criminal investigations because of its occurrence in a wide range of natural environments, abundant presence in pieces of evidence, and ease in molecular processing. Its value for forensic casework was demonstrated in an AFLP study identifying a knotgrass population at a crime site as the most likely origin of the botanical evidence in a homicide case. Given the peculiarities of the various breeding systems, knotgrass will probably not suffice as a general model for all plants, rather each breeding system will require its own model species. We expect that the development of tailored marker systems for knotgrass and other frequently occurring (model) plant species will considerably accelerate the use of botanical DNA evidence in criminal cases. Conflict of interest None. Acknowledgements We thank Jan Bravenboer (Centre for Genetic Resources, the Netherlands) for important information on the vernalization and germination of knotgrass seeds, and Rinie Verwoert and his Unifarm team for their special care in preparing the seeds and raising the plants. Two anonymous reviewers are acknowledged for their helpful comments on the manuscript. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.fsigen.2011.07.013. References [1] [2] [3] [4]

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