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Do longer sequences improve the accuracy of identification of forensically important Calliphoridae species?

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Species identification is a crucial step in forensic entomology. In particular, the calculation of the age of the insects collected from a cadaver or a crime scene allows the estimation of the time of oviposition that, except in case of myiasis, can be considered as the minimum Post-Mortem Interval (mPMI) (Erzinclioĝlu, 1983; Marchenko, 1982; Smith, 1986; Amendt et al., 2007; Vanin et al., 2017). This method is particularly precise when insects of the first colonization wave—mainly Diptera in the family Calliphoridae, Sarcophagidae and Muscidae—are considered. Insect development is temperature dependent and each species has a different growth rate. Thus, the correct identification of the species leads to an accurate mPMI estimation. Species identification is classically performed by morphological analysis of the specimens, but the lack of complete identification keys for immature stages represents a limitation to this approach. In the last twenty years, to overcome this limit, several authors have suggested a DNA-based identification method which is frequently used today because of the new sequencing technologies and the relative reduction of the costs (Benecke, 1998; Sperling, Anderson & Hickey, 1994; Stevens & Wall, 1996). Most of the publications about identification of forensically important species focused on the analysis of the genes coding for the cytochrome c oxidase subunit I (COI) as summarized by Tuccia and co-workers (Tuccia, Giordani & Vanin, 2016) and cytochrome c oxidase subunit II (COII) (Sperling, Anderson & Hickey, 1994; Aly, Wen & Wang, 2013; Boehme, Amendt & Zehner, 2012; Malgorn & Coquoz, 1999; Wallman & Donnellan, 2001; Xiong et al., 2012). Tested target markers other than COI and COII were: Cytb (GilArriortua et al., 2013; GilArriortua et al., 2014; GilArriortua et al., 2015; Giraldo, Uribe & Lopez, 2011), ND1 (Giraldo, Uribe & Lopez, 2011), ND5 (Zaidi et al., 2011; Zehner et al., 2004), 28S rDNA (Gibson et al., 2011; McDonagh & Stevens, 2011; Stevens & Wall, 2001; Tourle, Downie & Villet, 2009), mt16S rDNA (Guo et al., 2014; Li et al., 2010), CAD (Gibson et al., 2011; Meiklejohn et al., 2013; Schnell Schühli, Barros de Carvalho & Wiegmann, 2007), EF-1α (Gibson et al., 2011; Schnell Schühli, Barros de Carvalho & Wiegmann, 2007; McDonagh, García & Stevens, 2009), ITS1 (Zaidi et al., 2011), ITS2 (GilArriortua et al., 2014; GilArriortua et al., 2015; Zaidi et al., 2011; Ferreira et al., 2011; Nelson, Wallman & Dowton, 2008; Song, Wang & Liang, 2008; Yusseff-Vanegas & Agnarsson, 2017), PER (Guo et al., 2014) and Bicoid (Park et al., 2013). Analysis of mitochondrial DNA (mtDNA), in particular COI gene, seems to provide good species identification among Diptera, although a correct identification is still problematic for closely related species (Tourle, Downie & Villet, 2009; Harvey et al., 2008; Sonet et al., 2012). Nuclear DNA, especially ITS2 gene, presents a lack of intra-specific genetic divergence but high inter-specific variation in the genus Lucilia Robineau-Desvoidy, 1830, leading to a better resolution of closely related species (GilArriortua et al., 2014; GilArriortua et al., 2015). ITS2 was able to fully resolve the relationship within the species in the genus Cochliomyia Townsend 1915 (Yusseff-Vanegas & Agnarsson, 2016), otherwise, the same gene appeared to be not useful for Chrysomya Robineau-Desvoidy, 1830 genus studies (Nelson, Wallman & Dowton, 2008).

Previous works indicate that the combination of nuclear and mitochondrial markers is a much more accurate approach for species identification. In a recent paper, the study of Caribbean blow-flies through DNA markers highlights the possibility to resolve phylogenetic relations using a combination of COI and ITS2 genes. In fact, COI failed in demonstrating a monophyly in recently diverged species, leading to uncertain identification. The addition of a second nuclear marker, such as ITS2, increases certainty in species identification (Yusseff-Vanegas & Agnarsson, 2017). McDonagh and co-worker tested a multi- loci approach (28S rRNA, COI and EF-1α) finding that multiple-gene phylogenies permit the use of genes that have evolved at different rates, and also allow the identification of experimental errors in species identification and sequencing (McDonagh & Stevens, 2011). Zaidi et al. (2011) based the identification of Diptera species on five genes and demonstrated that such a multi-gene approach allows to overcome and clarify the misdiagnosis given by a single gene identification.

We focused our attention on dipteran specimens morphologically identified in order to evaluate the accuracy of the molecular approach in the identification of forensically important species. Sequences of four different markers, two mitochondrial (COI and ND5) and two nuclear (EF-1α and PER) were used. According to literature, identification based on a single gene had showed discordant outcomes compared with morphological results (Meier et al., 2006; Vilgalys, 2003) especially in the case of closely related species. In order to clarify the accuracy of a molecular multiple-loci approach in the identification of forensically important species, we built concatenated sequences using the four different markers.

Materials and Methods

Eighty specimens (Table 1) were collected between 2011 and 2014 in Italy (Emilia Romagna, Veneto and Calabria), England (West Yorkshire) and Belgium, and preserved in absolute ethanol. The specimens were observed under the microscope and identified using taxonomic keys (Table 2). DNA extraction from adult insects was performed on abdominal tissues carefully dissected, to prevent external contaminations and to preserve the external structure of the insect for future examination. Full puparia and larvae were instead entirely processed, after a photographic documentation to allow further observations. DNA was extracted using the QIAamp DNA Mini Kit® (QIAGEN, Germantown, MD, USA), following the manufacture protocol “DNA Purification from Tissue” (QIAGEN). Sterile deionized water was used to elute the DNA. The amplification of DNA was carried out on selected regions of four genes. In particular the barcoding region of the COI gene, and portions within ND5, EF-1α and PER genes were amplified. COI gene was selected as mainstream component of the analysis, and conversely ND5, EF-1α and PER genes were selected because only a little information is available on these DNA portions. A list of the used primers and their specifications are reported in Table 3. PCR was performed using 4 µl of the DNA extract as template for a 40 µl reaction final volume, using 0.5 µl of GoTaq® Flexi DNA Polymerase (Promega, Madison, WI, USA) per reaction. Each 40 µl reaction consisted of 8 µl of 5X Colorless GoTaq® Flexi Buffer (Promega), 4 µl of MgCl2 (25 mM), 1 µl of each of the two primers (10 pmol/µl), 1 µl of 10 mM nucleotide mix (Promega), and 20.5 µl sterile distilled water. Thermal cycler program used for the amplification consisted of an initial denaturation step at 95 °C for 1 min, followed by 35 cycles of 1 min at 95 °C, 1 min at the annealing temperature and 1 min at 72 °C; with a final extension at 72 °C for 10 min. Annealing temperatures were 49.8 °C for COI, 53 °C for ND5, 55 °C for EF-1α and 58 °C for PER. Amplifications were confirmed by standard gel electrophoresis, using 2% w/v agarose/TBE gels, stained with ethidium bromide. Thirty-five µl of PCR products were purified using QIAquick PCR Purification kit® (QIAGEN, Germantown, MD, USA) following the manufacturer protocol and were sequenced by Eurofins Genomics (Ebersberg, Germany). Sequences were considered for species identification purposes using nBLAST® (Altschul et al., 1990) to confirm the previous morphological identification. A total of 309 sequences were analysed, from them 257 were sequenced in this work (Table 4), and 52 were downloaded from GenBank (Table 5). Analyses based on the phylogenetic relationships between the studied species were carried out to confirm the identification. It is worth mentioning that in order to obtain consistent blocks of nucleotides for all the species, the sequences were processed with Gblock and manually checked (Talavera & Castresana, 2007; Castresana, 2000). Subsequently, sequences were aligned using Clustal Omega (Sievers et al., 2011) and concatenated with FASconCAT v1.0 (Kück & Meusemann, 2010). Trees were built using the Neighbour Joining and the Maximum Likelihood methods on MEGA 7.0 (Kumar, Stecher & Tamura, 2016) using Kimura 2-parameter (K2P) evolutionary model (Čandek & Kuntner, 2015). A bootstrap of 1,000 replicates was used for the phylogenetic reconstructions. Trees were visualised with ITOL (Letunic & Bork, 2016). In the trees reconstruction Piophilidae and Muscidae species were considered as outgroups.

Table 1:
List of species analysed, with the number of samples, stage of development (A, adult; P, pupae; III L, third larval instar) and country of origin (B, Belgium; UK, United Kingdom; I, Italy).
Species Nr. of samples Stage of development Country of origin
Calliphora vicina Robineau-Desvoidy, 1830 28 A B, UK, I
Calliphora vomitoria (Linnaeus 1758) 10 A UK, I
Lucilia sericata (Linnaeus 1758) 22 A B, UK, I
Lucilia illustris (Meigen 1826) 4 A I
Lucilia caesar (Meigen 1826) 3 A I
Chrysomya albiceps (Wiedemann 1819) 3 A, III L I
Phormia regina (Meigen 1826) 1 P I
Cynomya mortuorum (Linnaeus 1761) 1 A B
Sarcophaga africa (Wiedemann, 1824) 1 A I
Sarcophaga sp. Meigen 1826 1 III L UK
Hydrotaea sp. Robineau-Desvoidy 1830 2 P UK
Fannia scalaris (Fabricius 1794) 2 III L I
Piophila sp. Fallen 1810 1 P UK
Megaselia scalaris (Loew 1866) 1 A I
DOI: 10.7717/peerj.5962/table-1
Table 2:
Taxonomical keys used for morphological identification of the specimens.
Family Identification key
Calliphoridae Rognes (1991), Szpila (2010)
Sarcophagidae Pape (1996)
Muscidae Skidmore (1985)
Fanniidae Skidmore (1985)
Phoridae McAlpine (1987)
Piophilidae McAlpine (1987)
DOI: 10.7717/peerj.5962/table-2
Table 3:
List of primers used in this study.
Gene Primer name and sequence Reference
COI LCO1490 5′- GGTCAACAAATCATAAAGATATTGG -3′ Folmer et al. (1994)
ND5 ND5(a) 5′- CCAAAATATTCWGATCAHCCYTG -3′ Zehner et al. (2004)
EF-1α B1 5′- CCCATYTCCGGHTGGCACGG -3′ McDonagh, García & Stevens (2009)
DOI: 10.7717/peerj.5962/table-3
Table 4:
New sequences with geographical origin and GenBank code listed by gene.
Morphological identification Sequence ID Geographical origin Genbank code
Calliphora vicina 2BGCvi Belgium - B MH401768 MH401920 MH401958 MH401876
ITMA8Cvi Italy - I MH401769 MH588583
ITMO3Cvi Italy - I MH401773 MH401924 MH401961 MH401879
1ITCvi Italy - I MH401777 MH588588
2ITCvi Italy - I MH588592 MH588602 MH588607
3ITCvi Italy - I MH401780 MH588589 MH588601
4ITCvi Italy - I MH401782 MH401915 MH401963 MH401866
5ITCvi Italy - I MH401784 MH401916 MH401965 MH401863
6ITCvi Italy - I MH401786 MH401917 MH401966 MH401869
7ITCvi Italy - I MH401788 MH588584 MH588603
8ITCvi Italy - I MH401790 MH588593
9ITCvi Italy - I MH401792 MH401918 MH401967 MH401873
10ITCvi Italy - I MH401776 MH588585 MH588604
ITMACvi1 Italy - I MH401803 MH588590
ITMACvi2 Italy - I MH401804 MH588591
ITMOCvi3 Italy - I MH401805 MH401904 MH401946 MH401861
ITMOCvi4 Italy - I MH401806 MH401902 MH401944 MH401859
ITMOII1Cvi Italy - I MH401807 MH401884 MH401928 MH401839
ITMOII2Cvi Italy - I MH401809 MH401885 MH401929 MH401840
ITMOII3Cvi Italy - I MH401834 MH401886 MH401930 MH401841
ITMOII4Cvi Italy - I MH401810 MH401887 MH401931 MH401842
ITMOII5Cvi Italy - I MH401811 MH401888 MH401932 MH401843
ITTVCvi1 Italy - I MH401818 MH588582 MH588605
ITTVCvi2 Italy - I MH401819 MH588586
ITTVCvi3 Italy - I MH401820 MH401901 MH401943 MH401858
BOX4UKPrt United Kingdom - UK MH401798 MH588587
Calliphora vomitoria CvoUK United Kingdom - UK MH401764 MH401923 MH401960 MH401878
ITMO1Cvo Italy - I MH401767 MH401925 MH401964 MH401881
ITMA1Cvo Italy - I MH401775 MH588580
BOX3UKCvo United Kingdom - UK MH401795 MH401898 MH401855
ITTVCvo1 Italy - I MH401821 MH401899 MH401969 MH401856
ITTVCvo2 Italy - I MH401822 MH588579
ITTVCvo3 Italy - I MH401823 MH401900 MH401942 MH401857
UKCvo United Kingdom - UK MH401832 MH401893 MH401938 MH401849
70UKCvo United Kingdom - UK MH588581 MH588599 MH588606
99UKCvo United Kingdom - UK MH588578 MH588600 MH401882
Chrysomya albiceps ITVVChalbA Italy - I MH401800 MH588568 MH588596
ITVVChalbL Italy - I MH401801 MH588567
ITChalb Italy - I MH401833 MH588569 MH605069
Cynomya mortuorum 3BGCym Belgium - B MH401763 MH401921 MH401959 MH401877
Fannia sp. FanniaL Italy - I MH401835 MH588563
FanniaP Italy - I MH401836 MH588564
Hydrotaea sp. BOX4UKH United Kingdom - UK MH588560 MH588595
BOX6UKH United Kingdom - UK MH401799 MH588559
Lucilia caesar ITTVLc1 Italy - I MH401824 MH401926 MH401941 MH401853
ITTVLc2 Italy - I MH401825 MH588572 MH401968 MH401854
ITTVLc3 Italy - I MH401826 MH588573 MH605070
Lucilia illustris ITMO2Li Italy - I MH401766 MH401922 MH401962 MH401880
ITNOai15Li Italy - I MH401771 MH588571
ITMOLi1 Italy - I MH401816 MH588570 MH588608
ITTVLill1 Italy - I MH401827 MH588574
Lucilia sericata ITMA3Lse Italy - I MH401765 MH588575 MH588598
1BGLs Belgium - B MH401772 MH401919 MH401957 MH401875
ITMO1Ls Italy - I MH401774 MH588577
1ITLs Italy - I MH401778 MH401906 MH401948 MH401864
2ITLs Italy - I MH401779 MH401907 MH401949 MH401862
3ITLs Italy - I MH401781 MH401908 MH401950 MH401865
4ITLs Italy - I MH401783 MH401909 MH401951 MH401867
5ITLs Italy - I MH401785 MH401910 MH401952 MH401868
6ITLs Italy - I MH401787 MH401911 MH401953 MH401870
7ITLs Italy - I MH401789 MH401912 MH401954 MH401871
8ITLs Italy - I MH401791 MH401913 MH401955 MH401872
9ITLs Italy - I MH401793 MH401914 MH401956 MH401874
BOX3UKLs United Kingdom - UK MH588576 MH588597
ITVVLs Italy - I MH401802 MH401905 MH401947 MH401848
ITMOII10Ls Italy - I MH401808 MH401883 MH401927 MH401838
ITMOII6Ls Italy - I MH401812 MH401889 MH401933 MH401844
ITMOII7Ls Italy - I MH401813 MH401890 MH401934 MH401845
ITMOII8Ls Italy - I MH401814 MH401891 MH401935 MH401846
ITMOII9Ls Italy - I MH401815 MH401892 MH401936 MH401847
ITTVLs1 Italy - I MH401828 MH401894 MH401937 MH401850
ITTVLs2 Italy - I MH401829 MH401895 MH401939 MH401851
ITTVLs3 Italy - I MH401830 MH401896 MH401940 MH401852
Megaselia scalaris Ms Italy - I MH588562 MH401837
Phormia regina ITQC2Phr Italy - I MH401770 MH588566
Piophila sp. UKPio United Kingdom - UK MH401817 MH588561 MH588594
Sarcophaga africa ITTVSA Italy - I MH401831 MH401903 MH401945 MH401860
Sarcophaga sp. BOX1UKSL United Kingdom MH401794 MH588565
DOI: 10.7717/peerj.5962/table-4
Table 5:
Sequences selected from GenBank listed by gene.
Country of origin and its abbreviation used in the cladograms are reported.
Gene Species GenBank # Country Abbreviation
COI C.vicina JX438024 Portugal P
KC617807 USA USA
C.vomitoria JX438025 Portugal P
KC775967 Portugal P
C. albiceps JX438026 Portugal P
HE814059 Germany D
P. regina KM569886 Canada CDN
KM569803 Canada CDN
P. terraenovae KM570349 Canada CDN
KF908116 Belgium B
L. sericata JX438041 Portugal P
KC776060 Portugal P
L. illustris KM571189 Canada CDN
KM570007 Canada CDN
L. caesar KJ635700 Spain E
KJ635701 Spain E
S. africa JQ413455 Kenya EAK
S. melanura JQ413457 Belgium B
H. dentipes HM891630 Sweden S
F. canicularis JX438029 Portugal P
KC617819 USA USA
M. scalaris KC407774 Korea ROK
JQ941746 China RC
ND5 C.vicina NC_019639 France F
JX_913760 France F
C. albiceps NC_019631 Zambia Z
P. regina NC_026668 USA USA
P. terraenovae NC_019636 France F
L. sericata FJ614877 China RC
FJ614876 China RC
L. illustris KM571189 China RC
KM570007 China RC
S. africa NC_025944 China RC
M. scalaris NC_023794 China RC
PER L. sericata JN792856 USA USA
JN792853 South Africa ZA
L. illustris KF839550 USA USA
KF839549 USA USA
L. caesar KF839532 France F
JN792858 France F
S. africa KC966442 China RC
KC966441 China RC
M. scalaris KC178059 USA USA
EF 1 alfa C.vomitoria JQ307782 United Kingdom UK
FJ025666 Singapore SGP
P. terraenovae JQ307784 United Kingdom UK
L. sericata JQ307785 United Kingdom UK
L. illustris JQ307786 United Kingdom UK
L. caesar JQ307787 United Kingdom UK
JQ307787 United Kingdom UK
H. dentipes FJ025679 China RC
F. canicularis AJ871202 Canada CDN
DOI: 10.7717/peerj.5962/table-5


The analysed specimens belonged to fourteen species, with Calliphora vicina Robineau-Desvoidy, 1830 and Lucilia sericata (Meigen, 1826) (Diptera, Calliphoridae) as the most abundant taxa representing 29.8 and 27.4% respectively. The first analysis step was based on a local alignment using GenBank BLAST (Altschul et al., 1990) and the percentage of correct identification was evaluated. In particular, the molecular one-gene identification was compared with the morphological identification obtaining a percentage value match of 87.5% for COI, 72.5% for ND5, 77.1% for EF-1α and 67.9% for PER. Concerning Calliphoridae, the percentages were 77.5, 64.1, 71.2 and 64.2% respectively. A phylogenetic approach was used to verify the molecular identification efficiency, however, the sequencing of EF-1α and PER regions was successful only in 72.6% and 69.1% of the specimens respectively. Independent analysis of COI (Fig. 1A, Fig. S1) recovered the monophyly of all families. All the subfamilies (Calliphorinae, Luciliinae and Chrysomynae) are separated with robust bootstrap values ranging from 0.8 to 1 in a scale between 0 and 1. Among the genus Lucilia, L. sericata sequences cluster together and are clearly distinct from the other co-generic species (bootstrap 1), while the pattern of Lucilia illustris Meigen, 1826 and Lucilia Caesar (Linnaeus, 1758) is not clearly resolved with L. illustris showing a paraphyletic pattern. The genus Calliphora Robineau-Desvoidy, 1830 was also recovered as paraphyletic, in this case C. vicina branches with Cynomya mortuorum (Linnaeus, 1761), but with a weak support, instead of branching with C. vomitoria.

Simplified phylogenetic trees.

Figure 1: Simplified phylogenetic trees.

Simplified representation of the phylogenetic trees obtained using COI (A), ND5 (B), EF-1α (C) and PER (D) genes. Original trees are reported in the Supplemental Information.

Phylogenetic reconstruction based on the ND5 marker (Fig. 1B, Fig. S2) shows an unresolved topology with problems of determination at all taxonomic levels (family, subfamily, genus and species). Lucilia caesar and L. illustris are not clearly distinct and in addition Protophormia terraenovae Robineau-Desvoidy, 1830 sequence clusters with L. sericata sequences. A small number of sequences was available for both EF-1α (Fig. 1C, Fig. S3) and PER gene (Fig. 1D, Fig. S4). Both phylogenetic reconstructions obtained using these markers showed the same problems reported for COI and ND5, with L. illustris and L. caesar not clearly distinct.

In order to increase the molecular information three concatenated sequences were generated using the previous genes (DeSalle, Egan & Siddall, 2005). The phylogenetic reconstruction based on the chimeric sequence generated on the two mitochondrial genes (COI and ND5) (Fig. 2A, Fig. S5) does not provide a better resolution for L. illustris/L. caesar species as well as for the position of C. mortuorum among the Calliphorinae. These two points are not better clarified when the nuclear sequences are included and two more chimeric sequences with three (COI, ND5 and EF-1α) (Fig. 2B, Fig. S6) and four (COI, ND5, EF-1α and PER) (Fig. 2C, Fig. S7) genes are generated. Table 6 summarizes the information of the sequences used in the phylogenetic reconstructions.

Simplified phylogenetic trees.

Figure 2: Simplified phylogenetic trees.

Simplified representations of the phylogenetic threes obtained using COI and ND5 (A), COI, ND5 and EF-1α (B) and COI, ND5, EF-1α and PER (C) genes. Original trees are reported in the Supplemental Information.


The results obtained with a local alignment demonstrate that the match of the molecular identification with the morphological identification of the specimens was never higher than 90% also considering COI gene (87.5%), currently used for species identification (DNA Barcoding Project (http://www.barcodeoflife.org/)). The analysis of ND5 gene, a mitochondrial gene, was difficult for Calliphora vomitoria (Linnaeus, 1758) due to a complete lack of ND5 sequences from this species in the database (GenBank) at the moment of the analysis. The molecular analysis of the closely related though morphologically well distinct species, L. illustris and L. caesar, does not allow a unambiguous identification of them, as already reported in previous works where different phylogenetic approaches (e.g., Maximum Parsimony) were also used (GilArriortua et al., 2015; Wells, Wall & Stevens, 2007). In fact, GilArriortua and co-workers (GilArriortua et al., 2015) indicated that Lcaesar and L. illustris species appear to share mitochondrial genomes with a divergence value lower than the minimum inter-specific threshold value for mitochondrial loci. ND5 gene showed the same problem in the discrimination of the close Lucilia species. To our knowledge, the analysis of closely related species in blowflies using ND5 gene was only reported by Zaidi and co-workers who showed a good identification performance using this gene (Zaidi et al., 2011). In addition, the same mitochondrial region was used to analyse the evolutionary relationship between flesh flies with a good resolution (Zehner et al., 2004). The analysis of EF-1α gene is in agreement with a previous study (McDonagh & Stevens, 2011) that demonstrated a good ability of this gene to separate blowflies according to morphological classification. However, in our reconstruction both the position of the Lucilia species and Cynomya, within Calliphorinae, are not well resolved. To our knowledge, PER gene was studied for identification purposes only in flesh flies (Guo et al., 2014). This work showed the possibility to use successfully PER gene for identification purposes, although public datasets might be enriched with further DNA sequences belonging to different family of Diptera.

Table 6:
Size (bp) and number of sequences analysed.
Gene Concatenated sequences
Length (bp) 605 329 309 327 934 1,243 1,570
Nr. of sequences 72 + 23* 78 + 11* 55 + 9* 52 + 9* 72 + 10* 50 + 3* 43 + 2*
DOI: 10.7717/peerj.5962/table-6


indicates the sequence from GenBank.

The analysis of the concatenated sequences generated with COI, ND5, EF-1α and PER markers unfortunately does not improve the resolution of the investigation despite previous works indicate that the combination of nuclear and mitochondrial genes for species identification is a much more accurate approach. In fact the combination of markers that have different evolutionary histories, fast and slow evolving genes, allows a better resolution of the phylogenies. In particular, the multi-loci analysis of COI, EF-1α, and 28S rRNA genes and the combined analysis of COI, CYTB, ND5, and ITS1 and ITS2 genes has demonstrated to be more successful compared to the single-locus phylogeny, leading to a better grouping of species belonging to the same family (Zaidi et al., 2011; McDonagh & Stevens, 2011; Grzywacz, Wallman & Piwczyński, 2017). However, as underlined by Sonet et al. (2012), not always the addition of more genes with different evolutionary histories resolves the monophyly of closely related species such as L. illustris and L. caesar. The monophyly of these two species was clearly demonstrated only by two research groups: one working with the gene Bicoid (Park et al., 2013) and another one using the AFLP (Amplified Fragment Length Polymorphism) approach (Picard et al., 2018). In both cases the two species were well resolved with a strong basal support, confirming the conclusions obtained from the morphological analysis of male and female specimens of both species.

At the moment, because of the small number of sequences available for these two species, we cannot exclude phenomena of hybridization at least in some parts of the distribution area of the species, but this point needs further investigations and a larger dataset to be analysed.

The importance to have complete and correct dataset is a crucial point to reach a correct species identification, with both local alignment systems and/or phylogenetic methods. Molecular approach is strongly related to the quality of information stored in databases, and the possibility to improve the amount of genetic markers from different specimens from different geographical locations is important to recover the best resolution in phylogenetic trees. The availability of genetic data from different populations allows to have information about the intraspecific variability that, in closely related species can affect the phylogenetic reconstruction. The use of a single gene approach to identify animal species is an open argument, especially for closely related species. In particular, mtDNA does not seem to be significantly different from any other marker group revealing an overall success rate of 71% (Dupuis, Roe & Sperling, 2012). In fact, the mitochondrial evolution reduces its applicability for detailed systematic or taxonomic analysis for closely related species (Dupuis, Roe & Sperling, 2012; Will, Mishler & Wheeler, 2005; De Carvalho et al., 2008). Dupuis and co-workers (Dupuis, Roe & Sperling, 2012) highlighted two main results: (i) marker classes (mtDNA, ribosomal DNA, autosomal loci, sex-linked loci, and anonymous loci) were moderately successful to delimit closely related species, if used as unique identifier, and (ii) multi-locus power analysis data support investigation and use of multiple markers for species delimitation. Several papers have discussed multi-locus analysis as species identification methods for animal kingdom. In particular, sex-linked markers showed a high success ratio in delimiting closely related species in Diptera and Lepidoptera (Coyne & Orr, 1989; Roe & Sperling, 2007). The improvement of genetic datasets and the concatenation of different mitochondrial and nuclear loci could improve the capability of molecular approach to identify closely related species but this aspect has to be further explored considering as well the taxon’s specificity.

It is worth mentioning as well that in this kind of studies the species choice and intra-specific sampling scheme can strongly affect the level of resolution of the analysis. In our study, a further investigation including a larger sequence dataset of species in the genus Lucilia from different geographical contexts would better clarify the results here reported and the derived conclusions.


Nowadays, in forensic entomology, the morphological identification approach for some species is not completely replaceable by the molecular one if based on a single gene. The two methodologies can complement each other. In addition, because of the lack of information in databases, a phylogenetic approach can increase the ability of species identification when the molecular approach is used. The analysis of mitochondrial genes is considered the best approach because of the peculiarity of this kind of DNA, in terms of haploidy, high copy numbers, low recombination and lack of introns (Hebert et al., 2003). However, considering the nature of mitochondrial evolution and the results of this and previous studies, the use of mtDNA does not provide a good level of resolution for some of the Lucilia species. In addition, the analysis of nuclear genes, such as EF-1α and PER, cannot improve this point. Additional work using mtDNA in association with other genetic markers (i.e., sex-linked loci) could clarify and resolve the relationships among the Lucilia genus as well as other close related species. It is worth mentioning that the investigation for the best marker has to be done at the genus level, in fact some markers that have been suggested in addition to COI (e.g., ITS2) work for the resolution of certain taxa but not for others. In addition, given the problems in the resolution of several genera/species in the family Calliphoridae as highlighted as well in this paper, an approach based on NGS technologies (e.g., WGS –whole genome shotgun) will probably provide enough information to distinguish the taxa.

Supplemental Information

Phylogenetic tree based on Neighbour Joining and Maximum Likelihood analysis of 605 bp sequence of the COI gene

Numbers indicate the bootstrap value in the range 0–1. The size of the spots is directly proportional to the bootstrap value. * indicates the sequence from GenBank

DOI: 10.7717/peerj.5962/supp-1

Phylogenetic tree based on Neighbour Joining and Maximum Likelihood analysis of 329 bp sequence of the ND5 gene

Numbers indicate the bootstrap value in the range 0–1. The size of the spots is directly proportional to the bootstrap value. * indicates the sequence from GenBank

DOI: 10.7717/peerj.5962/supp-2

Phylogenetic tree based on Neighbour Joining and Maximum Likelihood analysis of 309 bp sequence of the EF-1α gene

Numbers indicate the bootstrap value in the range 0–1. The size of the spots is directly proportional to the bootstrap value. * indicates the sequence from GenBank

DOI: 10.7717/peerj.5962/supp-3

Phylogenetic tree based on Neighbour Joining and Maximum Likelihood analysis of 327 bp sequence of the PER gene

Numbers indicate the bootstrap value in the range 0-1. The size of the spots is directly proportional to the bootstrap value. * indicates the sequence from GenBank

DOI: 10.7717/peerj.5962/supp-4

Phylogenetic tree based on Neighbour Joining and Maximum Likelihood analysis of 934 bp of the COI+ND5 concatenated sequences

Numbers indicate the bootstrap value in the range 0–1. The size of the spots is directly proportional to the bootstrap value. * indicates the sequence from GenBank

DOI: 10.7717/peerj.5962/supp-5

Phylogenetic tree based on Neighbour Joining and Maximum Likelihood analysis of 1,243 bp of the COI+ND5+EF-1α concatenated sequences

Numbers indicate the bootstrap value in the range 0–1. The size of the spots is directly proportional to the bootstrap value. * indicates the sequence from GenBank

DOI: 10.7717/peerj.5962/supp-6

Phylogenetic tree based on Neighbour Joining and Maximum Likelihood analysis of 1570 bp of the COI+ND5+EF-1α+PER concatenated sequences

Numbers indicate the bootstrap value in the range 0–1. The size of the spots is directly proportional to the bootstrap value. * indicates the sequence from GenBank

DOI: 10.7717/peerj.5962/supp-7

Sequences used to create all the phylogenetic trees

DOI: 10.7717/peerj.5962/supp-8