Mitochondrial genomes of two phlebotomine sand flies, Phlebotomus chinensis and Phlebotomus papatasi (Diptera: Nematocera), the first representatives from the family Psychodidae
© Ye et al. 2015
Received: 5 May 2015
Accepted: 10 September 2015
Published: 17 September 2015
Leishmaniasis is a worldwide but neglected disease of humans and animal transmitted by sand flies, vectors that also transmit other important diseases. Mitochondrial genomes contain abundant information for population genetic and phylogenetic studies, important in disease management. However, the available mitochondrial sequences of these crucial vectors are limited, emphasizing the need for developing more mitochondrial genetic markers.
The complete mitochondrial genome of Phlebotomus chinensis was amplified in eight fragments and sequenced using primer walking. The mitochondrial genome of Phlebotomus papatasi was reconstructed from whole-genome sequencing data available on Genbank. The phylogenetic relationship of 24 selected representatives of Diptera was deduced from codon positions 1 and 2 for 13 protein coding genes, using Bayesian inference (BI) and maximum likelihood (ML) methods.
We provide the first Phlebotomus (P. chinensis and P. papatasi) mitochondrial genomes. Both genomes contain 13 protein-coding genes, 22 transfer RNA genes, two ribosomal RNA genes, and an A + T-rich region. The gene order of Phlebotomus mitochondrial genomes is identical with the ancestral gene order of insect. Phylogenetic analyses demonstrated that Psychodidae and Tanyderidae are sister taxa. Potential markers for population genetic study of Phlebotomus species were also revealed.
The generated mitochondrial genomes of P. chinensis and P. papatasi represent a useful resource for comparative genomic studies and provide valuable future markers for the population genetic study of these important Leishmania vectors. Our results also preliminary demonstrate the phylogenetic placement of Psychodidae based on their mitochondrial genomes.
KeywordsPhlebotomus chinensis Phlebotomus papatasi Leishmaniasis Mitochondrial genome Psychodidae Phylogenetic analysis
Phlebotomine sand flies are small insects in the family Psychodidae, and are important vectors of human disease including protozoal parasite, bacteria, and viruses  making these insects a global public health concern. Leishmaniasis is one of the world’s most neglected diseases transmitted by phlebotomine sand flies, causing significant mortality and morbidity in more than 80 countries of both the Old and New World. The majority of Old World vector species belong to the genus Phlebotomus (42 vector species) while the New World is dominated by the genus Lutzomyia (56 vector species) . Of Phlebotomus species, two are of particular interest; Phlebotomus chinensis and Phlebotomus papatasi. Phlebotomus chinensis, the main vector of mountainous sub-type of zoonotic visceral leishmaniasis, has wide geographical distribution extending from the Yangtze River to northeast China [3–5]. In recent years, the number of visceral leishmaniasis (VL) cases and its endemic foci has increased (54.37 % and 41.86 % respectively) compared to that of the 1990s in China. Until now, six provinces/autonomous regions still reported autochthonous cases. The area of mountainous sub-type of zoonotic VL covers four provinces which possess almost half of the total cases [6–8]. Prevention and control of vector P. chinensis is important to reduce the public health threat of VL in endemic regions. Phlebotomus papatasi is the vector of sand fly fever and zoonotic cutaneous leishmaniasis in Middle East and Mediterranean regions and is also an important model organism used to study sand flies-host-parasite interactions [9–12].
In recent years, the mitochondrial genome has become increasingly important in phylogenetic analysis, biological identification and population studies, due to its rapid evolutionary rate, low recombination and maternal inheritance [13, 14]. Although microsatellites and individual gene sequences, such as Cytb and ND4, have been used for sand fly studies in the past [15–17], the mitochondrial genome of phlebotomine sand flies has gone largely unstudied which is surprising given their pathogenic potential. The complete mitochondrial genome contains important information not available in examining individual genes, including genome-level characteristics for phylogenetic reconstruction. Additionally, due to the varying rates of gene evolution, the mitochondrial genome can also provide various molecular markers for studying phylogenetic relationships at different taxonomic levels, including intraspecies population structure.
Despite these benefits, information on the mitochondrial genomes of Diptera is still limited, especially for representatives of Nematocera. Most of these genomes are sequenced by long PCR with primer walking method. As the widespread application of next-generation sequencing (NGS), long PCR with next-generation sequencing, and direct shotgun sequencing methods has been utilized in mitochondrial genomes determination [18, 19]. Although the Sanger sequencing is still the indispensable method, the NGS method is relatively fast and inexpensive especially for direct shotgun sequencing method. In fact, this method for reconstruction of mitochondrial genomes becomes one of the simplest approaches. In the present study, we determined the complete mitochondrial genome of two important Leishmania vectors, P. chinensis and P. papatasi with long PCR with primer walking method and reconstruction from direct shotgun sequencing data respectively, reporting their genome features and analyzing the overall phylogenetic status of Psychodidae within Diptera. The addition of new mitochondrial genomes from nematoceran species would be of critical importance in understanding the evolution of Nematocera mitochondrial genome and examining the phylogeny in the Nematocera and Diptera.
Specimen collection and DNA extraction
Specimens of P. chinensis were collected from Wen County (104.25°E, 33.18°N), Gansu province, China. All specimens were preserved in 95 % ethanol and stored at −20 °C until DNA extraction. DNA was extracted from the single adult P. chinensis using the TIANamp Micro DNA Kit (Tiangen Biotech, Beijing, China) according to the manufacturer’s protocol.
Mitochondrial genome determination
List of PCR primer combinations used to amplify the mitochondrial genome of Phlebotomus chinensis
Contiguous sequence fragments were assembled using Staden Package v1.7.0 . Protein coding genes (PCGs) and ribosomal RNA (rRNA) genes were identified based on homologous regions of other dipteran insects using the Clustal X . Transfer RNAs (tRNA) and their potential cloverleaf structures were identified by tRNAscan-SE 1.21 . The secondary structure of the two rRNA genes was determined mainly by comparison with the published rRNA secondary structures of Drosophila melanogaster and Drosophila virilis . Tandem Repeat Finder v4.07 was used to identify tandem repeats in A + T-rich region . The base composition and codon usage were calculated with MEGA 5.1 . AT and GC skew were calculated according to the formulae: AT skew = (fA − fT) / (fA + fT) and GC skew = (fG − fC) / (fG + fC). Sliding window analyses were performed using DnaSP v5 . A sliding window of 500 bp (in 25 bp overlapping steps) was used to estimate nucleotide diversity Pi (π) across the alignment of P. chinensis, P. papatasi and Lutzomyia umbratilis  mitochondrial genomes excluding the A + T-rich region.
The species and their GenBank accession numbers used in our phylogenetic analyses
Atyame et al. unpublished data
Ho et al. unpublished data
Azeredo-Espin et al. unpublished data
Lessinger et al. unpublished data
Results and discussion
Genome organization and composition
The organization of the mitochondrial genome of Phlebotomus chinensis and Phlebotomus papatasi
A + T-rich region
Composition and skewness of mitochondrial genomes of Phlebotomus chinensis, Phlebotomus papatasi and Lutzomyia umbratilis
First codon position
Second codon position
Third codon position
A + T-rich region
Protein-coding genes and codon usage
All the protein-coding genes of P. chinensis start with the typical ATN codon except for COI (Table 3). In comparison with P. chinensis, only ND2 and ND3 have the different start codon in P. papatasi. The start codon of COI in P. chinensis and P. papatasi is uncommon start codon TCG, which is also reported for COI in some nematoceran mitochondrial gneomes [34–36]. The conventional stop codons TAA or TAG were used in all the PCGs of P. chinensis, while ND4 of P. papatasi terminates with the incomplete stop codon T. The conserved 7-bp overlap (ATGATAR) between ATP8 and ATP6 present in all known nematoceran mitochondrial genomes was found in Phlebotomus. However, the typical nematoceran 7-bp overlapping region between ND4 and ND4L was not observed in the mitochondrial genomes of phlebotomine sand flies, in contrast, these two genes overlapped by one nucleotide.
Transfer and Ribosomal RNAs
All typical tRNA genes of metazoan mitochondrial genomes were identified in both Phlebotomus mitochondrial genomes studied. All the 22 tRNAs of P. chinensis, P. papatasi, and L. umbratilis have the common cloverleaf secondary structure, while the DHU arm of trnS AGN is short with only one complementary base pair. All anticodon usage is identical with that described for other nematoceran mitochondrial genomes, except for trnS AGN of L. umbratilis, which uses TCT instead of the common GCT. Considering the codon usage, the RSCU of codon AGA (the corresponding codon to anticodon of trnS AGN) is overwhelmingly higher than those of other three synonymous codons in L. umbratilis. The frequency of AGA is moderate rich in P. chinensis and P. papatasi, however the corresponding codon (AGC) to anticodon (GCT) of their trnS AGN is rarely used. The most conserved tRNAs among P. chinensis, P. papatasi, and L. umbratilis are trnL UUR, trnL CUN, trnS UCN and trnI, however trnA, trnR and trnC exhibit low level of identical nucleotides.
The A + T-rich region
The A + T-rich regions of P. chinensis and P. papatasi are 1,433 bp and 723 bp respectively, which harbor a high rate of A + T base composition (91.1 % for P. chinensis and 92.3 % for P. papatasi). The A + T-rich regions of P. chinensis contains seven identical tandem repeat units of 159-bp sequence and another shortened tandem repeat unit with only 79-bp. In P. papatasi, there are three tandem repeat units, the first two (162-bp) are nearly identical with one substitution at the 159th position, while the third one is a shortened repeat unit (89-bp). All the tandem repeat sequences of P. chinensis and P. papatasi begin in the rrnS gene, but the tandem repeat sequences (372-bp for repeat unit) of L. umbratilis are located in the central region of A + T-rich region. Additionally, the alignments of tandem repeat units of P. chinensis and P. papatasi show 60.2 % similarity, but there is no evidence for homologous repeat motifs between species of Phlebotomus and L. umbratilis. Abundant microsatellite-like elements occur throughout the region between the tandem repeat sequence and trnI (e.g. (AT)3, (AT)5, (AT)6, (AT)8, (TA)4, and (TA)6 in P. papatasi). These tandem repeat units and microsatellite-like elements are potentially useful markers for the study of geographical population structure .
The accurate estimation of length and number of repeats and assembly of A + T-rich region are often difficult, particularly for including various complex repeat regions. For obtaining the accurate A + T-rich region of P. chinensis, Sanger sequencing with paired ends can cover the length of repeat region (approximate 1.2 kb), and agarose gel electrophoresis for amplified control region was used to determine the correct size and number of the length of repeat region. In control region of P. papatasi, we reconstructed the similar pattern of architecture for P. chinensis. The high coverage and comparatively long read length also make sequence accurate.
Nucleotide diversity of mitochondrial genome among Phlebotomus chinensis, P. papatasi and Lutzomyia umbratilis
Low flight capacity, a preference to remain close to area of emergence, geographic barriers and variability in climate across their distribution has led to genetically structured populations of phlebotomine sand flies, with cryptic species also being recorded [47, 48]. Genetically distinct species and populations have demonstrated a varying ability to both transmit Leishmania and resist insecticides [49–51] highlighting the need to quantify their population structure and delineate cryptic species. The sliding window analysis presented in this study provides a useful comparison of the evolutionary rates of each gene, allowing future researchers to design population genetic and large-scale phylogenetic studies utilizing the most appropriate marker for their task. One immediate use for such data will be the exploration of the relationships between P. chinensis and another disputed and close relative vector species Phlebotomus sichuanensis or ‘large type of P. chinensis’ [52–54]. It is debated whether these two nominal species are in fact distinct or if they are different populations of the same species occupying different altitudes [16, 53, 55].
NGS technology has been routinely used in genomic research with Illumina and 454 platforms. Although, these sequencing technology have been verified to obtain mitochondrial genomes for insects, the A + T-rich region is still difficult to assemble owing to various complex repeat regions [56, 57]. Ramakodi et al.  reported that the coverage may not have the crucial factors for reconstruction of control region using 454 reads, and known repeat sequences can help to reconstruct the full length of control region. In the present study, we successfully retrieved the complete mitochondrial genome with entire A + T rich region using P. chinensis as the reference. Both these control regions contain a similar pattern of repeat sequences, and the repeat units also hold 60.2 % similarity suggesting control region (or repeat sequences) of closely related species may contributes to the reconstruction of a new control region. Furthermore, the results also indicate that mitochondrial genome of closely related species as reference are more appropriate than shot target sequences for reconstruction of the full length of control region, in particular to that including complex repeat sequences. In other words, it suggests the reference species and sequence must be carefully selected when using the same approach. These first Phlebotomus mitochondrial genomes will make it easier to generate additional mitochondrial genomes data including control region from different population and species which will provide insight into the speciation, distribution pattern, evolution and divergence times of sand flies at the genome-level [58–61].
The present study determined the mitochondrial genomes of P. chinensis and P. papatasi, and conducted a comparative analysis of three sand fly mitochondrial genomes. We present the first examination of the phylogenetic status of the Psychodidae and, based on all mitochondrial PCGs, provide stable support that families Psychodidae and Tanyderidae are sister taxa. We confirmed the known sequences in control region of closely related species facilitate the reconstruction of uncharted control region using the similar approach. Our results also provide a source of genetic markers for future studies on the population biology and molecular phylogeny of these important vectors.
This research was supported by the National Natural Science Foundation of China (31372158).
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Maroli M, Feliciangeli MD, Bichaud L, Charrel RN, Gradoni L. Phlebotomine sandflies and the spreading of leishmaniases and other diseases of public health concern. Med Vet Entomol. 2013;27:123–47.View ArticlePubMedGoogle Scholar
- World Health Organization (WHO). Control of the leishmaniasis: Report of a Meeting of the WHO Expert Committee on the Control of Leishmaniasis, Geneva, 22–26 March 2010. WHO Tech Rep Ser. 2010;949:xii–xiii. 1–186.Google Scholar
- Leng YJ, Zhang LM. Check list and geographical distribution of phlebotomine sandflies in China. Ann Trop Med Parasitol. 1993;87:83–94.PubMedGoogle Scholar
- Zhang LM, Leng YJ. Eighty-year research of phlebotomine sandflies (Diptera: Psychodidae) in China (1915-1995). II. Phlebotomine vectors of leishmaniasis in China. Parasite. 1997;4:299–306.View ArticlePubMedGoogle Scholar
- Wei F, Shang L, Jin H, Lian H, Liu W, Li Z, et al. Molecular detection and genetic diversity of Leishmania donovani in naturally infected Phlebotomus chinensis from southwestern China. Vector Borne Zoonotic Dis. 2011;11:849–52.View ArticlePubMedGoogle Scholar
- Wang JY, Cui G, Chen HT, Zhou XN, Gao CH, Yang YT. Current epidemiological profile and features of visceral leishmaniasis in People’s Republic of China. Parasit Vectors. 2012;5:31.PubMed CentralView ArticlePubMedGoogle Scholar
- Fu Q, Li SZ, Wu WP, Hou YY, Zhang S, Feng Y, et al. Endemic characteristics of infantile visceral leishmaniasis in the People’s Republic of China. Parasit Vectors. 2013;6:143.PubMed CentralView ArticlePubMedGoogle Scholar
- Guan LR, Shen WX. Recent advances in visceral leishmaniasis in China. Southeast Asian J Trop Med Public Health. 1991;22:291–8.PubMedGoogle Scholar
- Chelbi I, Kaabi B, Bejaoui M, Derbali M, Zhioua E. Spatial correlation between Phlebotomus papatasi Scopoli (Diptera: Psychodidae) and incidence of zoonotic cutaneous leishmaniasis in Tunisia. J Med Entomol. 2009;46:400–2.View ArticlePubMedGoogle Scholar
- Tesh RB, Saidi S, Gajdamovič SJ, Rodhain F, Vesenjak-Hirjan J. Serological studies on the epidemiology of sandfly fever in the Old World. Bull World Health Organ. 1976;54:663–74.PubMed CentralPubMedGoogle Scholar
- Wasserberg G, Yarom I, Warburg A. Seasonal abundance patterns of the sandfly Phlebotomus papatasi in climatically distinct foci of cutaneous leishmaniasis in Israeli deserts. Med Vet Entomol. 2003;17:452–6.View ArticlePubMedGoogle Scholar
- Hamarsheh O. Distribution of Leishmania major zymodemes in relation to populations of Phlebotomus papatasi sand flies. Parasit Vectors. 2011;4:9.PubMed CentralView ArticlePubMedGoogle Scholar
- Gissi C, Iannelli F, Pesole G. Evolution of the mitochondrial genome of Metazoa as exemplified by comparison of congeneric species. Heredity. 2008;101:301–20.View ArticlePubMedGoogle Scholar
- Boore JL. Animal mitochondrial genomes. Nucleic Acids Res. 1999;27:1767–80.PubMed CentralView ArticlePubMedGoogle Scholar
- Hamarsheh O, Presber W, Abdeen Z, Sawalha S, Al-Lahem A, Schönian G. Genetic structure of Mediterranean populations of the sandfly Phlebotomus papatasi by mitochondrial cytochrome b haplotype analysis. Med Vet Entomol. 2007;21:270–7.View ArticlePubMedGoogle Scholar
- Zhang L, Ma Y, Xu J. Genetic differentiation between sandfly populations of Phlebotomus chinensis and Phlebotomus sichuanensis (Diptera: Psychodidae) in China inferred by microsatellites. Parasit Vectors. 2013;6:115.PubMed CentralView ArticlePubMedGoogle Scholar
- Depaquit J, Lienard E, Verzeaux-Griffon A, Ferté H, Bounamous A, Gantier JC, et al. Molecular homogeneity in diverse geographical populations of Phlebotomus papatasi (Diptera, Psychodidae) inferred from ND4 mtDNA and ITS2 rDNA epidemiological consequences. Infect Genet Evol. 2008;8:159–70.View ArticlePubMedGoogle Scholar
- Tang M, Tan M, Meng G, Yang S, Su X, Liu S, et al. Multiplex sequencing of pooled mitochondrial genomes––a crucial step toward biodiversity analysis using mito-metagenomics. Nucleic Acids Res. 2014;42:e166.PubMed CentralView ArticlePubMedGoogle Scholar
- Cameron SL. How to sequence and annotate insect mitochondrial genomes for systematic and comparative genomics research. Syst Entomol. 2014;39:400–11.View ArticleGoogle Scholar
- Hahn C, Bachmann L, Chevreux B. Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach. Nucl Acids Res. 2013;41:e129.PubMed CentralView ArticlePubMedGoogle Scholar
- Dietrich C, Brune A. The complete mitogenomes of six higher termite species reconstructed from metagenomic datasets (Cornitermes sp., Cubitermes ugandensis, Microcerotermes parvus, Nasutitermes corniger, Neocapritermes taracua, and Termes hospes). Mitochondrial DNA. 2014. doi:https://doi.org/10.3109/19401736.2014.987257.PubMedGoogle Scholar
- Zhang D, Huang J, Zhou F, Gong F, Jiang S. The complete mitochondrial genome of banana shrimp Fenneropenaeus merguiensis with phylogenetic consideration. Mitochondrial DNA. 2015. doi:https://doi.org/10.3109/19401736.2015.1041116.Google Scholar
- Staden R, Beal KF, Bonfield JK. The Staden package, 1998. Methods in Molecular Biology. 2000;132:115–30.PubMedGoogle Scholar
- Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG. The CLUSTAL_X Windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 1997;25:4876–82.PubMed CentralView ArticlePubMedGoogle Scholar
- Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25:955–64.PubMed CentralView ArticlePubMedGoogle Scholar
- Cannone JJ, Subramanian S, Schnare MN, Collett JR, D’Souza LM, Du Y, et al. The Comparative RNA Web (CRW) site: an online database of comparative sequence and structure information for ribosomal, intron, and other RNAs. BMC Bioinformatics. 2002;3:2.PubMed CentralView ArticlePubMedGoogle Scholar
- Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999;27:573–80.PubMed CentralView ArticlePubMedGoogle Scholar
- Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28:2731–9.PubMed CentralView ArticlePubMedGoogle Scholar
- Librado P, Rozas J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009;25:1451–2.View ArticlePubMedGoogle Scholar
- Kocher A, Gantier JC, Holota H, Jeziorski C, Coissac E, Bañuls AL, et al. Complete mitochondrial genome of Lutzomyia (Nyssomyia) umbratilis (Diptera: Psychodidae), the main vector of Leishmania guyanensis. Mitochondrial DNA. 2015. doi:https://doi.org/10.3109/19401736.2015.1022748.PubMedGoogle Scholar
- Posada D. jModelTest: phylogenetic model averaging. Mol Biol Evol. 2008;25:1253–6.View ArticlePubMedGoogle Scholar
- Ronquist F, Huelsenbeck JP. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics. 2003;19:1572–4.View ArticlePubMedGoogle Scholar
- Stamatakis A, Ludwig T, Meier H. RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees. Bioinformatics. 2005;21:456–63.View ArticlePubMedGoogle Scholar
- Beckenbach AT. Mitochondrial genome sequences of Nematocera (lower Diptera): evidence of rearrangement following a complete genome duplication in a winter crane fly. Genome Biol Evol. 2012;4:89–101.PubMed CentralView ArticlePubMedGoogle Scholar
- Mitchell SE, Cockburn AF, Seawright JA. The mitochondrial genome of Anopheles quadrimaculatus species A: complete nucleotide sequence and gene organization. Genome. 1993;36:1058–73.View ArticlePubMedGoogle Scholar
- Logue K, Chan ER, Phipps T, Small ST, Reimer L, Henry-Halldin C, et al. Mitochondrial genome sequences reveal deep divergences among Anopheles punctulatus sibling species in Papua New Guinea. Malar J. 2013;12:64.PubMed CentralView ArticlePubMedGoogle Scholar
- Pons J, Bauzà-Ribot MM, Jaume D, Juan C. Next-generation sequencing, phylogenetic signal and comparative mitogenomic analyses in Metacrangonyctidae (Amphipoda: Crustacea). BMC Genomics. 2014;15:566.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang KJ, Zhu WC, Rong X, Zhang YK, Ding XL, Liu J, et al. The complete mitochondrial genomes of two rice planthoppers, Nilaparvata lugens and Laodelphax striatellus: conserved genome rearrangement in Delphacidae and discovery of new characteristics of atp8 and tRNA genes. BMC Genomics. 2013;14:417.PubMed CentralView ArticlePubMedGoogle Scholar
- Cameron SL, Lambkin CL, Barker SC, Whiting MF. A mitochondrial genome phylogeny of Diptera: whole genome sequence data accurately resolve relationships over broad timescales with high precision. Syst Entomol. 2007;32:40–59.View ArticleGoogle Scholar
- Zhao Z, Su T, Chesters D, Wang S, Ho SYW, Zhu C, et al. The mitochondrial genome of Elodia flavipalpis Aldrich (Diptera: Tachinidae) and the evolutionary timescale of tachinid flies. PLoS ONE. 2013;8:e61814.PubMed CentralView ArticlePubMedGoogle Scholar
- Nelson LA, Lambkin CL, Batterham P, Wallman JF, Dowton M, Whiting MF, et al. Beyond barcoding: A mitochondrial genomics approach to molecular phylogenetics and diagnostics of blowflies (Diptera: Calliphoridae). Gene. 2012;511:131–42.View ArticlePubMedGoogle Scholar
- Nardi F, Carapelli A, Boore JL, Roderick GK, Dallai R, Frati F. Domestication of olive fly through a multi-regional host shift to cultivated olives: Comparative dating using complete mitochondrial genomes. Mol Phylogenet Evol. 2010;57:678–86.View ArticlePubMedGoogle Scholar
- Wiegmann BM, Trautwein MD, Winkler IS, Barr NB, Kim JW, Lambkin C, et al. Episodic radiations in the fly tree of life. Proc Natl Acad Sci USA. 2011;108:5690–5.PubMed CentralView ArticlePubMedGoogle Scholar
- Bertone MA, Courtney GW, Wiegmann BM. Phylogenetics and temporal diversification of the earliest true flies (Insecta: Diptera) based on multiple nuclear genes. Syst Entomol. 2008;33:668–87.View ArticleGoogle Scholar
- Hennig W. Ordnung Diptera (Zweiflügler). In: Helmcke JG, Starck D, Wermuth H, editors. Handbuch der Zoologie, Bd. 4: Arthropoda, 2.Hälfter: Insecta, 2. Aufl., 2 Teil Spezielles. Berlin: Walter de Gruyter; 1973. p. 1–377.Google Scholar
- Wood DM, Borkent A. Phylogeny and classification of the Nematocera. In: McAlpine JF, Wood DM, editors. Manual of Nearctic Diptera, vol. 3. Ottawa: Agriculture Canada Research Branch; 1989. p. 1333–70.Google Scholar
- Alexander B, Young DG. Dispersal of phlebotomine sand flies (Diptera: Psychodidae) in a Colombian focus of Leishmania (Viannia) braziliensis. Mem Inst Oswaldo Cruz. 1992;87:397–403.View ArticlePubMedGoogle Scholar
- Dujardin JP, Le Pont F, Cruz M, Leon R, Tarrieu LF, Guderian R, et al. Cryptic speciation in Lutzomyia (Nyssomyia) trapidoi (Fairchild & Hertig) (Diptera: Psychodidae) detected by multilocus enzyme electrophoresis. Am J Trop Med Hyg. 1996;54:42–5.PubMedGoogle Scholar
- Lanzaro GC, Ostrovska K, Herrero MV, Lawyer PG, Warburg A. Lutzomyia longipalpis is a species complex: genetic divergence and interspecific hybrid sterility among three populations. Am J Trop Med Hyg. 1993;48:839–47.PubMedGoogle Scholar
- Hassan MM, Widaa SO, Osman OM, Numiary MSM, Ibrahim MA, Abushama HM. Insecticide resistance in the sand fly, Phlebotomus papatasi from Khartoum State, Sudan. Parasit Vectors. 2012;5:46.PubMed CentralView ArticlePubMedGoogle Scholar
- Alexander B, Maroli M. Control of phlebotomine sandflies. Med Vet Entomol. 2003;17:1–18.View ArticlePubMedGoogle Scholar
- Leng YJ, Yin ZC. The taxonomy of phlebotomine sandflies (Diptera: Psychodidae) of Sichuan Province, China, with descriptions of two species, Phlebotomus (Adlerius) sichuanensis sp. n. and Sergentomyia (Neophlebotomus) zhengjiani sp. n. Ann Trop Med Parasitol. 1983;77:421–31.PubMedGoogle Scholar
- Xiong GH, Jin CF, Hong YM. A preliminary investigation on the types of Phlebotomus chinensis in relation to longitudinal altitude distribution in southern Gansu and northern Sichuan. Endemic Disease Bulletin. 1988;3:48–56.Google Scholar
- Xiong GH, Jin CF. Studies on the longitudinal distribution of sandfly Phlebotomus chinensis and its relation Kala-azar in southern Gansu and northern Sichuan. Endemic Disease Bulletin. 1989;4:15–21.Google Scholar
- Zhang L, Ma Y. Identification of Phlebotomus chinensis (Diptera: Psychodidae) inferred by morphological characters and molecular markers. Entomotaxonomia. 2012;34:71–80.Google Scholar
- Ramakodi MP, Singh B, Wells JD, Guerrero F, Ray DA. A 454 sequencing approach to dipteran mitochondrial genome research. Genomics. 2015;105:53–60.View ArticlePubMedGoogle Scholar
- Rasmussen DA, Noor MAF. What can you do with 0.1× genome coverage? A casestudy based on a genome survey of the scuttle fly Megaselia scalaris (Phoridae). BMC Genomics. 2009;10:382.PubMed CentralView ArticlePubMedGoogle Scholar
- Ma C, Yang P, Jiang F, Chapuis MP, Shali Y, Sword GA, et al. Mitochondrial genomes reveal the global phylogeography and dispersal routes of the migratory locust. Mol Ecol. 2012;21:4344–58.View ArticlePubMedGoogle Scholar
- Gu XB, Liu GH, Song HQ, Liu TY, Yang GY, Zhu XQ. The complete mitochondrial genome of the scab mite Psoroptes cuniculi (Arthropoda: Arachnida) provides insights into Acari phylogeny. Parasit Vectors. 2014;7:340.Google Scholar
- Timmermans MJTN, Dodsworth S, Culverwell CL, Bocak L, Ahrens D, Littlewood DTJ, et al. Why barcode? High-throughput multiplex sequencing of mitochondrial genomes for molecular systematics. Nucleic Acids Res. 2010;38:e197.PubMed CentralView ArticlePubMedGoogle Scholar
- Liu GH, Chen F, Chen YZ, Song HQ, Lin RQ, Zhou DH, et al. Complete mitochondrial genome sequence data provides genetic evidence that the brown dog tick Rhipicephalus sanguineus (Acari: Ixodidae) represents a species complex. Int J Biol Sci. 2013;9:361–9.PubMed CentralView ArticlePubMedGoogle Scholar
- Simon C, Buckley TR, Frati F, Stewart JB, Beckenbach AT. Incorporating molecular evolution into phylogenetic analysis, and a new compilation of conserved polymerase chain reaction primers for animal mitochondrial DNA. Annu Rev Ecol Evol Syst. 2006;37:545–79.View ArticleGoogle Scholar
- Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotech. 1994;3:294–9.Google Scholar
- Matsumoto Y, Yanase T, Tsuda T, Noda H. Species-specific mitochondrial gene rearrangements in biting midges and vector species identification. Med Vet Entomol. 2009;23:47–55.View ArticlePubMedGoogle Scholar
- Beard CB, Hamm DM, Collins FC. The mitochondrial genome of the mosquito Anopheles gambiae: DNA sequence, genome organization, and comparisons with mitochondrial sequences of other insects. Insect Mol Biol. 1993;2:103–24.View ArticlePubMedGoogle Scholar
- Spanos L, Koutroumbas G, Kotsyfakis M, Louis C. The mitochondrial genome of the Mediterranean fruitfly Ceratitis capitata. Insect Mol Biol. 2000;9:139–44.View ArticlePubMedGoogle Scholar
- Clary DO, Goddard JM, Martin SC, Fauron CM, Wolstenholme DR. Drosophila mitochondrial DNA: a novel gene order. Nucleic Acids Res. 1982;10:6619–37.PubMed CentralView ArticlePubMedGoogle Scholar
- Lessinger AC, Martins Junqueira AC, Lemos TA, Kemper EL, Da Silva FR, Vettore AL, et al. The mitochondrial genome of the primary screwworm fly Cochliomyia hominivorax (Diptera: Calliphoridae). Insect Mol Biol. 2000;9:521–9.View ArticlePubMedGoogle Scholar
- Beckenbach AT. Mitochondrial genome sequences of representatives of three families of scorpionflies (Order Mecoptera) and evolution in a major duplication of coding sequence. Genome. 2011;54:368–76.View ArticlePubMedGoogle Scholar