Open Access
How to translate text using browser tools
1 December 2015 Prevalence of a New Genetic Group, MEAM-K, of the Whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) in Karnataka, India, as Evident from mtCOI Sequences
H. K. Roopa, R. Asokan, K. B. Rebijith, Ranjitha H. Hande, Riaz Mahmood, N. K. Krishna Kumar
Author Affiliations +
Abstract

The whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is an economically important agricultural pest globally that costs growers billions of dollars to control. Given the pest status of B. tabaci and its propensity for invasiveness, a detailed work to resolve the prevalence of B. tabaci genetic groups is warranted. Hence, we analyzed mitochondrial cytochrome oxidase I sequences from 71 samples of B. tabaci to determine the prevalence of genetic groups on various host plants in India. Results revealed the prevalence of the 4 previously existing genetic groups, namely Asia-I, Asia-II-7, Asia-II-8, and Middle East Asia Minor-1 (MEAM-1), and of a new group called Middle East Asia Minor-K, which is genetically close (92.6%) to MEAM-1.

Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a pest of global importance that causes significant crop loss as a direct pest and as a vector of 120 geminiviruses, especially begomoviruses (Jones 2003). It is highly polyphagous, feeding on an estimated 900 hosts of agricultural, fiber, vegetable, and ornamental crops (Cahill et al. 1996; Jones 2003). It stands as one of the world's 100 invasive species (International Union for Conservation of Nature and Natural Resources [IUCN] list:  http://www.issg.org). Emerging new genetic groups of B. tabaci increase the risk of transmission of geminiviruses to many crops worldwide and of development od high levels of resistance of this insect to various insecticides, especially neonicotinoids (Horowitz et al. 2003, 2004; Rauch & Nauen 2003). Bemisia tabaci is a species complex that contains morphologically indistinguishable biotypes or cryptic species or genetic groups (Dinsdale et al. 2010; De Barro et al. 2011; Liu et al. 2012). However, biotypes—as designated based on esterase banding pattern (Costa & Brown 1991)—and genotypes have recently been elevated to putative species of B. tabaci (Dinsdale et al. 2010; De Barro et al. 2011).

The nymphs and adults actively feed on the phloem sap and excrete copious amounts of honeydew, which supports the growth of sooty mold that in turn impedes photosynthesis (Byrne & Bellows 1991). Several studies examined the host-related phenotypic variations in B. tabaci and concluded that variations are evident not only among the populations on different hosts but also among individuals occurring on the same host (Mound 1963; Palaniswami et al. 1996; Lisha et al. 2003). Morphometric analysis of 4th instar nymphs revealed phenotypic variations corresponding to variations in the leaf anatomy of the host plant (Maruthi et al. 2007). Bemisia tabaci is known to be an aggressive colonizer of crops, with varying traits at the morphological (Bellows et al. 1994; Costa et al. 1995; Rosell et al. 1997), biochemical (Costa & Brown 1991; Brown et al. 2000; Perring 2001), and molecular levels (Gawel & Bartlett 1993; De Barro et al. 2005; Boykin et al. 2007).

Different geographical and ecological variations with host plant specialization offer an ideal system for the study of sympatric speciation in B. tabaci, direct damage to crops and vector ability (Chu et al. 2007). De Barro et al. (2011) stated that asymmetrical mating interference provides a clear mechanism that could contribute to formation of global genetic structure. Genetic differentiation of different populations in the species complex was analyzed mainly based on the ribosomal internal transcribed spacer 1 (rITS-1) and mitochondrial cytochrome oxidase I (mtCOI) sequences worldwide (Simon et al. 1994; Hu et al. 2011; Zasada et al. 2014). Dinsdale et al. (2010) identified 3.5% pair-wise genetic divergence as the considered boundary for separating different species; this was further supported with either complete or partial mating isolation between a number of putative B. tabaci “species” (Xu et al. 2010; Wang et al. 2011). Considering all the past taxonomical approaches, Boykin et al. (2012) defined species in the B. tabaci species complex. In the present study, we examined the genetic variation in the mtCOI region of the genome of B. tabaci, collected on 30 different host plants from different locations in Karnataka, India, to assess the presence and prevalence of various genetic groups.

Materials and Methods

Nymphs and adults of B. tabaci were collected with a handheld aspirator from different locations in Karnataka, India, on 30 different hosts (Fig. 1 and Table 1) and preserved in 70% alcohol until further use.

GENOMIC DNA EXTRACTION AND AMPLIFICATION

The total DNA was extracted from individual adult B. tabaci specimens using DNAeasy Tissue Kit (Qiagen GmbH, Hilden, Germany) according to the manufacturer's protocol and stored at −80 °C until further use. Polymerase chain reaction (PCR) was performed with mtCOI primers F-C1-J-2195 (5′-TTGATTTTTTGGTCATCCAGAAGT-3′) and R-L2-N-3014 (5′-TCCAATGCACTAATCTGCCATATTA-3′) (Simon et al. 1994; Frohlich et al. 1999). The 25 μL PCR consisted of 50 ng/μL template,10 picomoles of each primer, 0.25 mM dNTP mix, 1.5 mM MgCl2, 1 U Taq polymerase, and 2.5 μL Taq buffer (Fermentas GmBH, St. Leon-Rot, Germany). The PCR cycling was carried out in a thermal cycler (Applied Biosystems, Veriti 96 wells, USA) with the following parameters: 94 °C for 5 min as initial denaturation followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 54 °C for 45 s, and extension at 72 °C for 50 s, and 72 °C for 10 min as the final extension. The amplified products were resolved in 1.0% agarose gel, stained with ethidium bromide (10 μg/mL), and visualized under UV light. Amplified PCR products were eluted using the gel extraction kit Nucleospin® Extract II (Macherey-Nagel, Duren, Germany) according to the manufacturer's protocol, and sequencing was performed in M13 forward and reverse directions.

SEQUENCE ANALYSES

All mtCOI sequences corresponding to different genetic groups of B. tabaci were downloaded from the National Center for Biotechnology Information (NCBI) GenBank (Suppl. Table 1, available online at  http://purl.fcla.edu/fcla/entomologist/browse). Sequence alignment was performed employing MUSCLE implemented in Seaview (Thompson et al. 1994). Genetic divergence was calculated employing MEGA5 (Tamura et al. 2011). The nucleotide substitution model for the best fits and the model parameters were estimated using Akaike Information Criterion implemented in the program MODELTEST 3.7 (Posada & Crandall 1998) in conjunction with PAUP*. Maximum parsimony and maximum likelihood analyses were performed with PAUP* 4.0b10 (Swofford 1998), using the heuristic search procedure with 1,000 random additions of sequences and 10 trees held at each pseudo-replicate, and the tree bisection reconnection branch swapping method with all characters was treated as unordered and equally weighted. The chosen model with estimated parameters was used to derive the maximum likelihood tree in RaxML with the heuristic search settings. The same software was used to generate consensus trees using the CONSENSE program ( http://evolution.genetics.washington.edu/phylip/doc/consense.html), and the tree was rooted with the outgroup Bemisia afer (Priesner & Hosny) (Hemiptera: Aleyrodidae). Phylogenetic analysis was performed using MrBayes (Huelsenbeck & Ronquist 2001). MrBayes 3.1 was run for 10 million generations by using 8 chains and sampled every 1,000 generations. All runs reached a plateau in the likelihood score, and the same was indicated by standard deviations of split frequencies (0.0023). Our 4 Markov Chain Monte-Carlo chains were converged, indicated by the potential scale reduction factor, which was close to one. The burn-in parameter was estimated employing Tracer version 1.5 (Rambaut & Drummond 2009), and the trees corresponding to the first 20% of generations were discarded. We performed 2 independent MrBayes runs to ensure the analyses were not trapped in the local optima, after which topologies and posterior probabilities (PP) from these 2 runs were compared for congruence purpose. The trees obtained were visualized using FigTree v1.3.1 (Rambaut 2009).

Results

The mtCOI gene was successfully amplified and sequenced from 71 individual adult B. tabaci. We analyzed 131 sequences, including the 71 generated from this study. The sequence analysis revealed that out of 816 bp, 332 nucleotides were conserved, 484 were variable, and 379 were parsimony informative. Absence of stop codons indicated that no pseudogenes were amplified within the sequences, and similar base composition indicated no indels. Bemisia tabaci nucleotide frequencies were 24.46% (A), 43.10% (T/U), 19.23% (C), and 13.22% (G). Rates of different transitional substitutions are shown in bold and those of transversional substitutions are shown in italics in Table 2. The base composition of the mtCOI gene fragment was biased toward adenine (A) and thymine (T) with an overall 67.56%. The transition/transversion rate ratios were k1 = 6.255 (purines) and k2 = 6.190 (pyrimidines). The overall transition/transversion bias was R = 2.629. All sequences were deposited in the NCBI GenBank with the accession numbers KF790634 to KF790689 and HQ268814, HQ268813, HQ268812, HQ268811, HQ331246, HQ331245, and HQ331244.

PHYLOGENETIC ANALYSIS

Based on the phylogenetic analyses, the Indian B. tabaci samples were clustered into Asia-I, Asia-II-7, Asia-II-8, Middle East Asia Minor-1 (MEAM-1), and MEAM-K groups (Figs. 2a and 2b). The Asia-I genetic group was predominant representing 44 of the 71 (61.97%) samples sequenced. The Asia-I population had 17 different host plant species (Table 1), of which Solanum lycopersicum L., Solanum melongena L. (Solanales: Solanaceae), Gossypium hirsutum L., and Abelmoschus esculentus (L.) Moench (Malvales: Malvaceae) were the most frequent host plants and are widely distributed in Karnataka (Fig. 2b). Few samples collected from Karnataka clustered with Asia-II-7 and were found on 9 host plant species. The Asia-II-8 genetic group contained 5 samples, which had been collected on 5 different host plants. The most important genetic groups MEAM-1 and MEAM-2 formed 2 subclusters representing B and B2 genotypes. Here, MEAM-1 comprised 5 sequences, which had been collected on 3 host plants (mostly cabbage). However, 3 sequences from speci mens collected on Phaseolus vulgaris L. (Fabales: Fabaceae) at Kolar, H-Cross, and Malur (Karnataka, India) diverged from all the MEAM-1, MEAM-2, Indian Ocean, and Mediterranean groups. Thus, they formed an independent genetic group, which we named MEAM-K group. The genetic divergence ranged from 4.0 to 24.0% with an average of 15.7% (Table 3 and Fig. 3).

Fig. 1.

Map indicating different locations of Bemisia tabaci sampling and distribution of genetic groups in Karnataka, India.

f01_1062.jpg

Discussion

“There is probably no other concept in biology that has remained as consistently controversial as the species concept” (Mayr 1982). This quote is remarkably true with B. tabaci, because this species is difficult to be diagnosed using morphological, cytological, behavioral, molecular, and biochemical methods, and its identification is complicated further by reproductive isolation (Rosell et al. 1997; Maruthi et al. 2007). Molecular studies on various insects of agricultural importance have helped to identify new species (Ball & Armstrong 2006), biotypes (Perring 2001), cryptic species (Hebert et al. 2004), and haplotypes (Toda &Murai 2007), which are difficult to identify through morphology due to phenotypic plasticity and lack of distinguishing morphological features (Russell 1957; Mound 1963; Rosell et al. 1997; Maruthi et al. 2007).

Table 1.

Details of Bemisia tabaci mtCOI sequences generated for this study along with place of collection, accession number, voucher specimen number, respective genetic group, and host plants.

t01a_1062.gif

Continued

t01b_1062.gif

Fig. 2a.

Phylogenetic tree showing the relationship of the Bemisia tabacimt mtCOI sequences collected in this study to consensus sequences of Dinsdale et al. (2010). Bayesian analyses were performed employing MrBayes under the best-fit model GTR+I+G of molecular evolution for 20 million generations and 25% discarded as burn-in. Posterior probabilities are shown above the branches and maximum likelihood scores from RaxML indicated below the branches. Asia-I condensed is shown in Fig. 2b.

f02a_1062.jpg

Fig. 2b.

Phylogenetic tree indicating the Asia-I group, which was the most abundant genetic group in this study.

f02b_1062.jpg

Table 2.

Maximum composite likelihood estimate of the pattern of nucleotide substitution from Bemisia tabaci populations collected on various host plants in Karnataka, India.

t02_1062.gif

Considering the vector potential of B. tabaci, it is necessary to analyze the molecular diversity of the same species or species complex collected on various host plants. In this regard, the resistant tomato varieties Arka Ananya (against tomato leaf curl virus) and Arka Abhay and Arka Anamika (against Bhendi yellow vein mosaic virus) have become susceptible again, and this breakdown of resistance may be correlated with the existence of various species of vectors or virus, but the exact plant physiological mechanism is still unknown. In 1991, the biotype nomenclature was introduced to the B. tabaci species complex based on esterase banding patterns but was no longer used after the advent of Random Amplified Polymorphic DNA-PCR and mtCOI and ITS sequencing (Perring 2001; Simon et al. 2003; Zang et al. 2006; Boykin 2013). In the discussion on B. tabaci nomenclature, it remains unclear whether to call a new biotype a genetic group or a putative species with novel binomial nomenclature, such as Bemisia argentifolii Bellows & Perring (De Barro et al. 2011; Boykin et al. 2013).

Bemisia tabaci can attack a wide range of host plants globally, and its species complex is composed of at least 34 morphologically indistinguishable species (Boykin et al. 2012, 2013; Boykin 2014). Different cropping patterns and diverse climatic conditions may be responsible for the apparent diversity in B. tabaci, which otherwise is grouped by geographic location (Rekha et al. 2005). The current study revealed the existence of 5 genetic groups within Karnataka State, India, namely Asia-I, Asia-II-7, Asia-II-8, MEAM-1, and MEAM-K, with the latter being a new group identified in this study.

The genetic divergence ranged from 4.0 to 24.0% with an average of 15.7%. According to Dinsdale et al. (2010), the genetic divergence among 198 mtCOI sequences of B. tabaci and sequences of the outgroup species B. afer, B. atriplex (Froggatt), and B. subdecipiens Martin (Hemiptera: Aleyrodidae) ranged from zero to 34%. However, Lee et al. (2013) analyzed the genetic divergence after excluding the outgroup sequences and concluded that it ranged from zero to 24.0%, which was on par with our study.

Of the reported 5 genetic groups, the major group was Asia-I with members collected on 19 different host plants although most had been collected on eggplant; this group was found previously to be prevalent across Asia (Boykin et al. 2007; Dinsdale et al. 2010; Hu et al. 2011). The eggplant-associated Asia-I B. tabaci can transmit several begomoviruses (Govindappa 2002; Muniyappa et al. 2003) and was shown to transmit eggplant yellow mosaic virus in Thailand (Green et al. 2003). In this study, we report another 17 host plants for Asia-I including cotton, pumpkin, ridge gourd, okra, capsicum, sunflower, potato, carrot, mustard, and tomato. However, a previous study showed that tomato is not a preferred host plant for Asia-I because it is associated with low fecundity (Chowda-Reddy et al. 2012). Host-associated variations in B. tabaci influence its rate of fecundity, which could be due to premating or post-mating selection against migrants and hybrid progeny (Liou & Price 1994; Brunner et al. 2004). However, the most to least preferred hosts, in terms of oviposition, were eggplant, cotton, pumpkin, tomato, and cassava (Venkatesh 2000). Our study also supported this finding, wherein eggplant and cotton were the most frequent host plants for Asia-I. Apart from the Jatropha genetic group, which occurs in a separate ecological niche, most of the putative species exhibit high levels of polyphagy (Burban et al. 1992; Brown et al. 1995). According to Chowda-Reddy et al. (2012), MEAM-1 has a wide host range and produces higher quantities of honeydew than other genetic groups. This is also true for genetic groups Asia-I, Asia-II-7, and Asia-II-8, of which Asia-I had the greatest number of host plants in our study.

We identified Asia-II-7 from Karnataka occurring on 9 different host plants, mostly on ornamental plants. Asia-II-7 was reported first in 1998 in India (Ramappa et al. 1998) and in China (Qiu et al. 2006). A previous study suggested that this putative species adapts readily to ornamental plants rather than vegetables (Shah et al. 2013). The 3rd genetic group identified in this study was Asia-II-8, which was recently named as B. gossypiperda (Boykin 2014) and was collected on 5 different host plants including cotton (Chowda-Reddy et al. 2012). Significantly, we here report the occurrence of a previously unreported subclade for Middle East genetic groups (MEAM-1 and 2). We named it MEAM-K because the samples were collected on P. vulgaris from Kolar, Karnataka, the native location for MEAM-1. For Kolar and nearby areas where both species have become established, our study raises questions about the relative pest status of MEAM-1and MEAM-K. We do not know to what extent these genetic groups differ with respect to important factors such as their ability in feeding and reproduction, their efficiency as vectors, or their susceptibility to insecticides. These high levels of molecular and ecological resolution will be needed to mitigate quarantine disputes arising from the detection of morphologically indistinguishable members of the B. tabaci genetic groups. Thus, our study may stand as a link to detect and identify B. tabaci genetic groups, determine areas of occurrence, identify areas of invasion, and design management strategies.

Table 3.

Estimates of net evolutionary divergence between groups of sequences showing pair-wise genetic distances for Bemisia tabaci populations collected on various host plants in Karnataka, India.

t03_1062.gif

Fig. 3.

Graph indicating net evolutionary divergence between groups of sequences.

f03_1062.jpg

In conclusion, the current study revealed the existence of 5 genetic groups of B. tabaci in Karnataka, India, identified as Asia-I, Asia-II-7, Asia-II-8, MEAM-1, and a previously unreported genetic group, MEAMK. Thus, our work will help in rapid and accurate identification of these putative genetic groups of B. tabaci, which in turn will help in further elucidating the epidemiology and management of geminiviruses and be of value in the operation of quarantines.

Acknowledgments

This paper is part of the doctoral degree work of the senior author. We gratefully acknowledge the financial support received for the “Outreach Programme on Management of Sucking Pests in Horticultural Crops” from the Indian Council for Agricultural Research (ICAR), New Delhi, India. We are thankful to the director at the Indian Institute of Horticultural Research (IIHR) for the support and facilities.

References Cited

1.

SL Ball , KF. Armstrong 2006. DNA barcodes for insect pest identification: a test case with tussock moths (Lepidoptera: Lymantriidae). Canadian Journal of Forest Research 36: 337–350. Google Scholar

2.

TS Bellows , TM Perring , RJ Gill , DH. Headrick 1994. Description of a species of Bemisia (Homoptera: Aleyrodidae). Annals of the Entomological Society of America 87: 195–206. Google Scholar

3.

LM. Boykin 2014. Bemisia tabaci nomenclature: lessons learned. Pest Management Science 70: 1454–1459. Google Scholar

4.

LM Boykin , RG Shatters Jr , RC Rosell , CL McKenzie , RA Bagnall , PJ De Barro , DR. Frohlich 2007. Global relationships of Bemisia tabaci (Hemiptera: Aleyrodidae) revealed using Bayesian analysis of mitochondrial COI DNA sequences. Molecular Phylogenetics and Evolution 44: 1306–1319. Google Scholar

5.

LM Boykin , KF Armstrong , L Kubatko , PJ. De Barro 2012. Species delimitation and global biosecurity. Evolutionary Bioinformatic Online 8: 1–37. Google Scholar

6.

LM Boykin , CD Bell , G Evans , I Small , PJ. De Barro 2013. Is agriculture driving the diversification of the Bemisia tabaci species complex (Hemiptera: Sternorrhyncha: Aleyrodidae)? Dating, diversification and biogeographic evidence revealed. BMC Evolutionary Biology 13: 228. Google Scholar

7.

JK Brown , DR Frohlich , RC. Rosell 1995. The sweetpotato or silverleaf whiteflies: biotypes of Bemisia tabaci or a species complex. Annual Review of Entomology 40: 511–534. Google Scholar

8.

JK Brown , TM Perring , AD Cooper , ID Bedford , PG. Markham 2000. Genetic analysis of Bemisia tabaci (Hemiptera: Aleyrodidae) populations by isoelectric focusing electrophoresis. Biochemical Genetics 38: 13–25. Google Scholar

9.

PC Brunner , EK Chatzivassiliou , NI Katis , JE. Frey 2004. Host-associated genetic differentiation in Thrips tabaci (Insecta; Thysanoptera), as determined from mtDNA sequence data. Heredity 93: 364–370. Google Scholar

10.

C Burban , LDC Fishpool , C Fauquet , D Fargette , JC. Thouvenel 1992. Host-associated biotypes within West African populations of the whitefly Bemisia tabaci (Genn.) (Hom., Aleyrodidae). Journal of Applied Entomology 113: 416–423. Google Scholar

11.

DN Byrne , Jr TS. Bellows 1991. Whitefly biology. Annual Review of Entomology 36: 431–457. Google Scholar

12.

M Cahill , I Denholm , G Ross , K Gorman , D. Johnston 1996. Relationship between bioassay data and the simulated field performance of insecticides against susceptible and resistant adult Bemisia tabaci. Bulletin of Entomological Research 86: 109–116. Google Scholar

13.

RV Chowda-Reddy , M Kiran Kumar , SE Seal , V Muniyappa , GB Valand , MR Govindappa , J. Colvin 2012. Bemisia tabaci phylogenetic groups in India and the relative transmission efficacy of tomato leaf curl Bangalore virus by an indigenous and an exotic population. Journal of Integrative Agriculture 11: 235–248. Google Scholar

14.

D Chu , T Jiang , GX Liu , DF Jiang , YL Tao , ZX Fan , HX Zhou , YP. Bi 2007. Biotype status and distribution of Bemisia tabaci (Hemiptera: Aleyrodidae) in Shandong Province of China based on mitochondrial DNA markers. Environmental Entomology 36: 1290–1295. Google Scholar

15.

HS Costa , JK. Brown 1991. Variation in biological characteristics and in esterase patterns among populations of Bemisia tabaci (Genn.) and the association of one population with silver leaf symptom development. Entomologia Experimentalis et Applicata 61: 211–219. Google Scholar

16.

HS Costa , DM Westcot , DE Ullman , R Rosell , JK Brown , MW. Johnson 1995. Morphological variation in Bemisia endosymbionts. Protoplasma 189: 194–202. Google Scholar

17.

PJ De Barro , JWH Trueman , DR. Frohlich 2005. Bemisia argentifolii is a race of B. tabaci (Hemiptera: Aleyrodidae): the molecular genetics differentiation of B. tabaci populations around the world. Bulletin of Entomological Research 95: 193–203. Google Scholar

18.

PJ De Barro , SS Liu , LM Boykin , A. Dinsdale 2011. Bemisia tabaci: a statement of species status. Annual Review of Entomology 56: 1–19. Google Scholar

19.

A Dinsdale , L Cook , C Riginos , YM Buckley , PJ. De Barro 2010. Refined global analysis of Bemisia tabaci (Hemiptera: Sternorrhyncha: Aleyrodoidea: Aleyrodidae) mitochondrial cytochrome oxidase I to identify species level genetic boundaries. Annals of the Entomological Society of America 103: 196–208. Google Scholar

20.

DR Frohlich , I Torres-Jerez , ID Bedford , PG Markham , JK. Brown 1999. A phylogeographical analysis of the Bemisia tabaci species complex based on mitochondrial DNA markers. Molecular Ecology 8: 1683–1691. Google Scholar

21.

NJ Gawel , AC. Bartlett 1993. Characterization of differences between whiteflies using RAPD-PCR. Insect Molecular Biology 2: 33–38. Google Scholar

22.

MR. Govindappa 2002. Detection and transmission of tomato leaf curl virus and interactions studies with host plants and whitefly Bemisia tabaci Genn. in relation to epidemics. Ph.D. thesis, University of Agricultural Sciences, Bangalore, India. Google Scholar

23.

SK Green , WS Tsai , SL. Shih 2003. Molecular characterization of a new begomovirus associated with tomato yellow leaf curl and eggplant yellow mosaic diseases in Thailand. Plant Disease 87: 446. Google Scholar

24.

PDN Hebert , EH Penton , JM Burns , DH Janzen , W. Hallwachs 2004. Ten species in one: DNA barcoding reveals cryptic species in the Neotropical skipper butterfly Astraptes fulgerator. Proceedings of the National Academy of Sciences of the USA 101: 14812–14817. Google Scholar

25.

AR Horowitz , K Gorman , G Ross , I. Denholm 2003. Inheritance of pyriproxyfen resistance in the whitefly, Bemisia tabaci (Q biotype). Archives of Insect Biochemistry and Physiology 54: 177–186. Google Scholar

26.

AR Horowitz , S Kontsedalov , I. Ishaaya 2004. Dynamics of resistance to the neonicotinoids acetamiprid and thiamethoxam in Bemisia tabaci (Homoptera: Aleyrodidae). Journal of Economic Entomology 97: 2051–2056. Google Scholar

27.

J Hu , PJ De Barro , H Zhao , J Wang , F Nardi , SS. Liu 2011. An extensive field survey combined with a phylogenetic analysis reveals rapid and widespread invasion of two alien whiteflies in China. PLoS One 6: e16061. Google Scholar

28.

JP Huelsenbeck , F. Ronquist 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17: 754–755. Google Scholar

29.

DR. Jones 2003. Plant viruses transmitted by whiteflies. European Journal of Plant Pathology 109: 195–219. Google Scholar

30.

W Lee , J Park , GS Lee , S Lee , SI. Akimoto 2013. Taxonomic status of the Bemisia tabaci complex (Hemiptera: Aleyrodidae) and reassessment of the number of its constituent species. PLoS One 8: e63817. Google Scholar

31.

LW Liou , TD. Price 1994. Speciation by reinforcement of premating isolation. Evolution 48: 1451–1459. Google Scholar

32.

VS Lisha , B Antony , MS Palaniswami , TJ. Henneberry 2003. Bemisia tabaci (Homoptera: Aleyrodidae) biotypes in India. Journal of Economic Entomology 96: 322–327. Google Scholar

33.

SS Liu , J Colvin , PJ. De Barro 2012. Species concepts as applied to the whitefly Bemisia tabaci systematics: How many species are there? Journal of Integrative Agriculture 11: 176–186. Google Scholar

34.

MN Maruthi , AR Rekha , P Sseruwagi , RJ. Hillocks 2007. Mitochondrial DNA variability and development of a PCR diagnostic test for populations of the whitefly Bemisia afer (Priesner and Hosny). Molecular Biotechnology 35: 31–40. Google Scholar

35.

E. Mayr 1982. The Growth of Biological Thought. Harvard University Press, Cambridge, Massachusetts, USA. Google Scholar

36.

AL. Mound 1963. Host-correlated variations in Bemisia tabaci (Gennadius) (Homoptera: Aleyrodidae). Proceedings of the Royal Entomological Society of London, Series A, General Entomology 38: 171–180. Google Scholar

37.

V Muniyappa , MN Maruthi , CR Babitha , J Colvin , RW Briddon , KT. Rangaswamy 2003. Characterization of pumpkin yellow vein mosaic virus from India. Annals of Applied Biology 142: 323–331. Google Scholar

38.

MS Palaniswami , RR Nair , KS Pillai , M. Thankappan 1996. Whiteflies on cassava and its role as vector of cassava mosaic disease in India. Journal of Root Crops 22: 1–8. Google Scholar

39.

TM. Perring 2001. The Bemisia tabaci species complex. Crop Protection 20: 725–737. Google Scholar

40.

D Posada , KA. Crandall 1998. MODELTEST: testing the model of DNA substitution. Bioinformatics 14: 817–818. Google Scholar

41.

BL Qiu , SX Ren , NS Mandour , SY. Wen 2006. Population differentiation of Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) by DNA polymorphism in China. Journal of South China Agricultural University 27: 29–34. Google Scholar

42.

HK Ramappa , V Muniyappa , J. Colvin 1998. The contribution of tomato and alternative host plants to tomato leaf curl virus inoculum pressure in different areas of South India. Annals of Applied Biology 133: 187–198. Google Scholar

43.

A. Rambaut 2009. FigTree Version 1.3.1,  http://tree.bio.ed.ac.uk/software/figtree/ (last accessed 6 Mar 2015). Google Scholar

44.

A Rambaut , AJ. Drummond 2009. Tracer Version 1.5,  http://beast.bio.ed.ac.uk/ Tracer (last accessed 6 Mar 2015). Google Scholar

45.

N Rauch , R. Nauen 2003. Identification of biochemical markers linked to neonicotinoid cross resistance in Bemisia tabaci (Hemiptera: Aleyrodidae). Archives of Insect Biochemistry and Physiology 54: 165–176. Google Scholar

46.

AR Rekha , MN Maruthi , V Muniyappa , J. Colvin 2005. Occurrence of three genotypic clusters of Bemisia tabaci and the rapid spread of the B biotype in South India. Entomologia Experimentalis et Applicata 117: 221–233. Google Scholar

47.

RC Rosell , ID Bedford , DR Frohlich , RJ Gill , JK Brown , PG. Markham 1997. Analysis of morphological variation in distinct populations of Bemisia tabaci (Homoptera: Aleyrodidae). Annals of the Entomological Society of America 90: 575–589. Google Scholar

48.

LM. Russell 1957. Synonyms of Bemisia tabaci (Gennadius) (Homoptera: Aleyrodidae). Bulletin of the Brooklyn Entomological Society 52: 122–123. Google Scholar

49.

SHJ Shah , AH Malik , J. Qazi 2013. Identification of new genetic variant of Bemisia tabaci from Pakistan. International Journal of Entomological Research 1: 16–24. Google Scholar

50.

B Simon , JL Cenis , S Demichelis , C Rapisarda , P Caciagli , D. Bosco 2003. Survey of Bemisia tabaci (Hemiptera: Aleyrodidae) biotypes in Italy with the description of a new biotype (T) from Euphorbia characias. Bulletin of Entomological Research 93: 259–264. Google Scholar

51.

C Simon , F Frati , A Beckenbach , B Crespi , H Liu , P. Flook 1994. Evolution, weighting, and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Annals of the Entomological Society of America 87: 651–701. Google Scholar

52.

DL. Swofford 1998. PAUP* Phylogenetic analysis using parsimony (*and other methods). Version 4. Sinaue Associates, Sunderland, Massachusetts, USA. Google Scholar

53.

F Tajima , M. Nei 1984. Estimation of evolutionary distance between nucleotide sequences. Molecular Biology and Evolution 1: 269–285. Google Scholar

54.

K Tamura , D Peterson , N Peterson , G Stecher , M Nei , S. Kumar 2011. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular Biology and Evolution 28: 2731–2739. Google Scholar

55.

JD Thompson , DG Higgins , JJ. Gibson 1994. CLUSTAL W: improving the sensitivity of progressive multiple alignment through sequence weighting, positionspecific gap penalties and weight matrix choice. Nucleic Acids Research 11: 4673–4680. Google Scholar

56.

S Toda , T. Murai 2007. Phylogenetic analysis based on mitochondrial COI gene sequences in Thrips tabaci Lindeman (Thysanoptera: Thripidae) in relation to reproductive forms and geographical distribution. Applied Entomology and Zoology 42: 309–316. Google Scholar

57.

HM. Venkatesh 2000. Studies on tomato leaf curl geminivirus and Bemisia tabaci (Gennadius): molecular detection, farmers' perception and sustainable management. Ph.D. thesis, Department of Plant Pathology, University of Agricultural Sciences, Bangalore, India. Google Scholar

58.

P Wang , D Sun , B Qiu , SS. Liu 2011. The presence of six cryptic species of the whitefly Bemisia tabaci complex in China as revealed by crossing experiments. Insect Science 18: 67–77. Google Scholar

59.

J Xu , PJ De Barro , SS. Liu 2010. Reproductive incompatibility among genetic groups of Bemisia tabaci supports the proposition that the whitefly is a cryptic species complex. Bulletin of Entomological Research 100: 359–366. Google Scholar

60.

LS Zang , WQ Chen , SS. Liu 2006. Comparison of performance on different host plants between the B biotype and a non-B biotype of Bemisia tabaci from Zhejiang, China. Entomologia Experimentalis et Applicata 121: 221–227. Google Scholar

61.

IA Zasada , A Peetz , DK Howe , LJ Wilhelm , D Cheam , DR Denver , AB. Smythe 2014. Using mitogenomic and nuclear ribosomal sequence data to investigate the phylogeny of the Xiphinema americanum species complex. PLoS One 9: e90035. Google Scholar

Notes

[1] Supplementary material for this article in Florida Entomologist 98(4) (Dec 2015) is online at  http://purl.fcla.edu/fcla/entomologist/browse

H. K. Roopa, R. Asokan, K. B. Rebijith, Ranjitha H. Hande, Riaz Mahmood, and N. K. Krishna Kumar "Prevalence of a New Genetic Group, MEAM-K, of the Whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) in Karnataka, India, as Evident from mtCOI Sequences," Florida Entomologist 98(4), 1062-1071, (1 December 2015). https://doi.org/10.1653/024.098.0409
Published: 1 December 2015
KEYWORDS
Asia de Medio Oriente Menor-K
citocromo oxidasa I mitocondrial
especies putativas
Middle East Asia Minor-K
mitochondrial cytochrome oxidase I
putative species
Back to Top