Genetic Differentiation Analyses Based on mtDNA CO ΙΙ Gene Sequences Among Different Geographic Populations of Aphis glycines (Hemiptera: Aphididae) in Northeast China

Li Ran, Han Lan-lan, Ye Le-fu, Zhang Hong-yu, Sun Wen-peng, Tong Xin, and Zhao Kui-jun

College of Agriculture, Northeast Agricultural University, Harbin 150030, China

Genetic Differentiation Analyses Based on mtDNA CO ΙΙ Gene Sequences Among Different Geographic Populations of Aphis glycines (Hemiptera: Aphididae) in Northeast China

Li Ran, Han Lan-lan, Ye Le-fu, Zhang Hong-yu, Sun Wen-peng, Tong Xin, and Zhao Kui-jun*

College of Agriculture, Northeast Agricultural University, Harbin 150030, China

Aphis glycines (Hemiptera: Aphididae) is considered as a cosmopolitan pest of cultivated soybean, major difficulties in its control measures may be due to its higher genetic diversity; however, the knowledge about population genetic diversity of this species is limited. This study aimed to represent the genetic differentiation among different geographic populations of soybean aphid in Northeast China. In order to investigate and assess the genetic diversity, genetic differentiation, molecular variance, population structure, ecological importance and evolutionary history of A. glycines, we sequenced a fragment of one protein-coding gene, the cytochrome c oxidaseⅡof mitochondrial DNA gene. The results showed that four haplotypes were defined among COⅡ gene of 180 sequences of soybean aphid in Northeast China including H1 shared by all the populations. Lower haplotype diversity (Hd=0.3590± 0.0420) and nucleotide diversity (Pi=0.0012±0.0002) were observed and high gene flow was detected in every two populations, while most of the variation (80.81%) arose from variability within A. glycines from individuals. Low genetic differentiation and high gene flow (Nm=2.106) indicated a high migration rate between the populations, which might reveal that gene flow in different geographic populations did not affect by geographical distance. The phylogenetic tree and the haplotype network of A. glycines were obtained based on sequences of COⅡ gene, there were no significant genealogical branches or clusters recognized in NJ tree, and no clear distribution, delineation of haplotypes were demonstrated in the haplotype network according to geographical location. This study rejected the vicariance hypothesis: geographic isolation could be a barrier and it restricted A. glycines gene flow among 10 populations.

Aphis glycines, mtDNA COⅡ, geographic population, gene flow, genetic differentiation

Introduction

Aphids is one of the most destructive pest of agriculture, particularly in temperate regions, it causes direct damage to arable and horticultural crops as well as serve as a vector for many plant diseases (Vandermoten et al., 2012; Basky and Nasser, 1989). Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is the most common pest on soybean, and distributes in many areas of Asia, Africa, America and Australia (Liu, 2007). It is a native pest of eastern Asia (Gariepy et al., 2015; Blackman et al., 2000), and damages relatively seriously in Northeast China where the main soybean production region is (Xue, 2013; Li, 2006). It spreads widely in North America since it is discovered infesting soybean in 2000 (Zhang et al., 2009; Ragsdale et al., 2011), leading to yield lossesand increasing large control costs (Kim et al., 2008) since that it has become the most important pest of soybean (Ragsdale et al., 2011).

Mitochondrial DNA (mtDNA) has some traits, such as maternal inheritance, absence of intermolecular genetic recombination, a fast evolutionary rate relative to nuclear DNA, the availability of efficient PCR primers, and a wealth of comparative data (Li et al., 2014; Barrette et al., 1994). Therefore, it is extensively applied in entomology, zoology (Li et al., 2014; Lakra et al., 2010; Chen et al., 2009; Puillandre et al., 2014) and has been proven to be very informative in genetic structure and gene flow (Li et al., 2013; Liu et al., 2012; Wang et al., 2014). So mtDNA has been widely used for studying population structure, phylogeography and phylogenetic relationship at various taxonomic levels (Wang et al., 2014; Xu et al., 2014). While sequences encoding of mitochondrial cytochrome oxidase subunit Ⅱ (COⅡ) are recognized as an appropriate tool for intraspecific analyses, due to the high degree of polymorphism observed (Li et al., 2010; Bu et al., 2005). In this study, partial sequences of mtDNA-COⅡgene of A. glycines from 10 locations of major soybean-growing areas in Northeast China were sequenced. The sequence data was used to assess the extent and characters of the genetic variation of A. glycines populations in Northeast China.

Materials and Methods

Sample collection and preparation

A. glycines were sampled from 10 different sites in Northeast China, the geographic locations are given in Fig. 1. All the samples were identified based on morphological characteristics and preserved in anhydrous ethanol, and then stored at -20℃ until DNA extraction.

Fig. 1 Map of Northeast China, showing localities of sampling Aphis glycinesThe 10 sampling localities were CC (Changchun), DL (Dalian), GZL (Gongzhuling), HH (Heihe), HRB (Harbin), JMS (Jiamusi), JX (Jixi), MDJ (Mudanjiang), SY (Shenyang), and TH (Tonghua).

DNA extraction and PCR amplification

Total DNA was extracted from single soybean aphid following the method previously described (Yang et al., 2005), but omitting the phenol-chloroform protocol steps (Sambrook and Russell, 2001). DNAwas diluted to a final concentration of 50 ng · mL-1.

We designed a pair of primers COⅡ (F: 5-CATTC ATATGCAGAATTACC-3′ and 5′- GAGATCGTTAC TTTGCTTTT -3′) to amplify a fragment (673 bp) of COⅡ gene based on complete A. glycines mtDNA (KC840675.1). While each PCR was performed with a 50 μL reaction volume, containing 2 μL of genomic template DNA, 1 μL of each primer, 4 μL of dNTPs, 1 U of Taq DNA polymerase, 5 μL 10×reaction buffer, and ultrapure water. Amplification was carried out in a PCR system consisted of denaturation at 94℃ for 5 min, followed by 35 cycles of 94℃ for 60 s, 49.2℃for 50 s, and 72℃ for 50 s, with a final extension step at 72℃ for 10 min.

Sequencing of PCR products

PCR products were directed by electrophoresis in a 1.2% agarose gel and purified using DNA gel purification kit (Traans GenBitech). All PCR fragments were directly sequenced after purification by Beijing Huada Gene Research Center.

Data analyses

COⅡ gene sequences were aligned by ClustalX 1.83 (Thompson et al., 1997). While software program DnaSP 5.0 (Librado and Rozas, 2009) was used to calculate genetic parameters including the nucleotide composition, number of polymorphic sites, haplotype diversity (Hd) (Nei, 1987), and the nucleotide diversity (Pi) (Lynch and Crease, 1990). These genetic parameters were calculated for each geographic population of A. glycines. The phylogenetic tree were constructed through neighbor-joining (NJ) method (Saitou and Nei, 1987) by using Kimura-2-parameter (K2P) model (Kimura, 1980) in MEGA 5.0 (Tamura et al., 2011).

Historical demographic and spatial expansions were studied using a distinct statistical approach, Tajima' D (Tajima, 1989) was calculated to verify the null hypothesis of selective neutrality in relation to mtDNA sequences, which would be expected with population expansion. While large negative D was characteristic of population expansion.

A haplotype network was created using the medianjoining method by Network 4.1 software (Rohl, 2003) to depict phylogenetic and geographical relationships of the haplotypic sequences. The hierarchical nesting were used to reveal the geographical structure of genetic variation, which was estimated by using the analysis of molecular variance (AMOVA) approach, and calculated by using Arlequin 3.0 (Excoffier et al., 2005). In addition, fixation indexes (Fst) were calculated on the basis of the information of haplotypes and their frequencies, while we derived the values for Nm using the formula Fst=1/(1+2 Nm), which was specific to organelle genetic data (Goldberg and Ruvolo, 1997).

Results

Variation of mtDNA sequences

A 673 bp fragment of mtDNA cytochronme oxidase subunitⅡgene (COⅡ) of A. glycines was amplified and sequenced in all of the collected samples. The average nucleotide frequencies of thymine (T), cytosine (C), adenine (A), and guanine (G) were 39.8%, 11.9%, 40.5%, and 7.8%, respectively. Among 180 collected individuals, nine variable sites, four haplotypes were observed, and no single variable sites were found. The sequences were deposited in GenBank (KP757883, KP757884, KP757885, KP757888 for haplotypes H1-H4).

Genetic diversity

The number of haplotypes, the values of nucleotide diversity and haplotype diversity, within each and among the total populations are shown in Table 1. There were seven populations whose haplotype diversity and nucleotide diversity were 0 in 10 populations. In remaining three populations, the haplotype diversities were 0.7433 ± 0.0350 (HRB), 0.3410 ± 0.0780 (JX) and 0.6020 ± 0.0570 (MDJ), while nucleotide diversity were 0.0043 ± 0.0005, 0.0005 ± 0.0001 (JX) and 0.0020 ± 0.0003 (MDJ), respectively.

Table 1 Distribution of haplotypes, genetic diversity and neutral test among different geographic populations of Aphis glycines based on CO II gene

Tests of neutrality and estimates of population expansion

Tajima' D test was carried out to identify the presence of a selective sweep or a balancing selection in A. glycines populations (Harpending et al., 1998) and to test whether the COⅡ fragment evolved under neutrality or not. Tajima' D resulted in negative values for the total populations (Table 1), and the values suggested no significant deviations (P＞0.10). This statistical finding was consistent with the possibilities that A. glycines populations from these locations may have not experienced population selection or expansion. Values for the statistic ranged from 0.6295 to 1.072 and no statistically significant (P＞0.10) were found, indicating a significant correlation between the observed and expected outcomes.

Population structure analysis

AMOVA test (Table 2) revealed that 80.81% of the genetic variation occurred within groups, and 19.19% occurred among groups. The genetic variation components showed that genetic variation within populations was significantly greater than that among populations, which suggested that the genetic differentiation of A. glycines populations in Northeast China occurred primarily within populations, whereas the genetic variation among populations was relatively low. Fixation indexes (Fst) were calculated on the basis of the information of haplotypes and their frequencies, Fst=0.1919, and Nm=2.106.

Gene flow and genetic differentiation analysisThe values of fixation index (Fst) and gene flow (Nm) (Table 3) among pairs of 10 populations showed that the pairwise fixation index (Fst) ranged from 0 to 0.1914. The average Fst value was 0.009301 (P＞0.05), which suggested no genetic variation among 10 populations, Fst values were calculated for populations together as a group and separately for all pairs. Consistent with AMOVA test, the pairwise Fst analysis revealed insignificant genetic differentiation among the sampled regions. In addition, Nm could estimate the gene flow among 10 populations and estimate expected numbers of migrants exchanged among populations in each generation. According to Table 3, all Nm values between pairs of populations were greater than one. These results suggested that the extensive gene flow occurred among 10 populations of A. glycines.

Table 2 Analysis of molecular variance (AMOVA) among 10 populations of Aphis glycines

Table 3 Fst value (below diagonal) and gene flow Nm (above diagonal) among 10 populations of Aphis glycines based on CO II

Phylogenetic and network analysis

To further depict the phylogenetic and geographical relationship among the identified sequences, the haplotype networks were constructed using the median-joining method in Network 4.1 software (Fig. 2). The results revealed that the sequences of COⅡwere mostly related to a central and most abundant haplotype (H1), the dominant haplotype 1 accounted for 78.89% (142/180) of all A. glycines specimens and appeared in each sampled population, while H2 haplotype contained three individuals of the HRB population, H3 contained 22 individuals which were distributed in three populations (HRB, JX, and MDJ), and H4 was shared by two sample regions (HRB and MDJ).

Fig. 2 Median-joining network of haplotypes of Aphis glycines based on CO II gene of mtDNACircle areas are proportional to haplotype frequencies, colored portions represent the proportions of the same haplotype that occurs in each sampling region, while red numbers represent variable sites.

A neighbor-joining tree among four haplotypes was constructed based on the Kimura-2-parameter distance model (Fig. 3). While some closely related species were selected as the outgroups, all haplotypes in the populations were significantly separated from outgroups. There was no clear evidence of a geographical spectrum among the haplotypes, and each cluster confidence coefficient was low. The haplotypes H2 had a distant relationship compared with other three halotypes, the result was similar to the haplotype networks. H1, H3 and H4 were closely related and divided into the same cluster, whereas H2 divided into other clusters. All the four haplotypes were divided into the same cluster.

Fig. 3 Neighbor-joining phylogenetic tree of haplotypes of different geographic populations of Aphis glycines based on CO II gene sequence, other aphids are used as outgroups.

Discussion

The sequence COⅡ of A. glycines (Hemiptera: Aphididae) was 673 bp in length, its nucleotide composition was highly A+T biased (80.30%), the result conformed to the composition and structure characteristics of mtDNA gene sequences of hemipteran insects, whose A+T content of mitogenomes ranged from 68.86% to 86.33% (Zhang et al., 2014). Genetic diversity provided a potential genetic resource for future adaptation (Hurt and Hedrick, 2004), and could be a key factor to the adaptability of a population. In addition, biological characteristics and the dependence on habitats of insect will lead to the different levels of genetic diversity (Li et al., 2003). In this study, we found low haplotype diversity (Hd) and nucleotide diversity within individual populations of all samples, the result might reflect its biological characteristics, and the ability to adapt hostile environment condition of A. glycines was relatively weak. Therefore, the limited habitat, food and simple survival environment might lead to relatively low genetic diversity within A. glycines populations. The difference of the values of haplotype diversity (Hd) and nucleotide diversity in each population might due to the wide distribution of A. glycines in Northeast China where the natural ecological conditions had some differences.

The demographic history of A. glycines provides further evident from neutrality tests. The negative values for Tajima' D test (Tajima' D=-1.145) indicated that it conformed to the neutral evolutionmodel and the population had not undergone a recent bottleneck (Wang, 2014; Tajima, 1989; Nohara et al., 2010). Historical factors play an important role in population phylogeny and evolution, the results of Tajima's D test were no statistically significant for all populations indicated that A. glycines did not experience a recent population expansion (P＞0.05) among 10 populations, while population size remained in relatively stable state. All of these observations were not statistically significant for genetic differentiation (P＞0.05) which suggested that all the populations formed one genetic group.

Fst can be a measurement of the variance in gene frequencies among populations (Garcia et al., 2003), and bears a direct relationship to Nm. In this study, Fst value (Fst=0.1919) implied a higher genetic differentiation within populations (Weight, 1978). Consistent with AMOVA study, genetic differentiation mainly occurred within populations. AMOVA was to determine if this molecular variation correlated with the geographical isolation of the different populations, indicated moderate differentiation between the populations (Haynes et al., 2014). The result of AMOVA showed that most of the variations (80.81%) arose from variability within populations, suggesting the geographical isolation was not the main reason which resulted in the genetic differentiation. These results showed that 10 populations had no apparent divergence and shared a great amount of gene flow. Nm for all the groups was greater than one, indicating that geographic isolation did not act as a barrier for the gene flow and led to lower genetic differentiation and lower genetic diversity among populations. It was so inferred that A. glycines had been mingling their genes by migration or other ways.

Median-joining network for COⅡshowed that H1 was the most common haplotype, and shared by 10 populations, suggesting that potential adaptive existed in A. glycines populations, which might due to neutral processes like genetic bottleneck effects. The most prevalent haplotype (haplotype 1) showed a typical starlike topology, haplotype 2 was derived from a single substitution, each of other haplotypes which appeared to show star-like topologies and independently of each other. However, the rare haplotype in each population also revealed that genetic differentiation existed among populations to some extent.

The data from mtDNA COⅡ sequences revealed low genetic diversity and insignificant genetic differentiation in A. glycines of Northeast China existed. Further studies including nuclear markers and more samples are needed to extend and corroborate the present findings, and other classes of molecular markers, such as nuclear microsatellites, which might reveal another aspect of A. glycines population structure and gain greater understanding and insights into the comprehensive population structure of A. glycines. Use of multiple genetic marker systems could increase resolving power of the future genetic studies (Gruenthal et al., 2007). These studies would help us to understand the comprehensive population evolution and gene flow in A. glycines, and thus achieve better prevention and control measures.

Barrette R J, Crease T J, Hebert P D N, et al. 1994. Mitochondrial DNA diversity in the pea aphid Acyrthosiphon pissum. Genome,37: 858-865.

Basky Z, Nasser M A. 1989. The activity of virus vector aphids on cucumbers. Agr Ecosyst Environ,25: 337-342.

Blackman R L, Eastop V F. 2000. Aphids on the world's crops: an identification and information guide. 2nd ed. Wiley, New York.

Bu Y, Zheng Z M, Guo K. 2005. Sequence analysis of mtDNA-COⅡgene and molecular phylogeny on five species of Pehtatoma (Hemiptera: Pentatomidae). Entomotaxonomia,27(2): 90-96.

Chen J X, Song Z H, Rong M J, et al. 2009. The association analysis between Cytb polymorphism and growth traits in three Chinese donkey breeds. Livestock Science,126: 306-309.

Excoffier L, Laval G, Schneider S. 2005. Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinform,1: 47-50.

Fu Y X. 1997. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics,147: 915-925.

Garcia B A, Manfredi C, Fichera L, et al. 2003. Short report: variation in mitochondrial 12s and 16s ribosomal DNA sequences in natural populations of Triatomainfestans (Hemiptera: Reduviidae). Am J Trop Med Hyg,68: 692-694.

Gariepy V, Boivin G, Brodeur J. 2015. Why two species of parasitoids showed promise in the laboratory but failed to control the soybean aphid under field conditions. Biol Control,80: 1-7.

Goldberg T L, Ruvolo M. 1997. The geographic apportionment of mitochondrial genetic diversity in east African chimpanzees, Pan troglodytes schwein furthii. Mol Biol Evol,14(9): 976-984.

Gruenthal K M, Acheson L K, Burton R S. 2007. Genetic structure of natural populations of California red abalone (Haliotis rufescens) using multiple genetic markers. Mar Biol,152: 1237-1248.

Harpending H C, Batzer M A, Gurven M, et al. 1998. Genetic traces of ancient demography. Proc Natl Acad Sci U S A,95(4): 1961-1967.

Haynes B T, Marcus A D, Higgins D P, et al. 2014. Unexpected absence of genetic separation of a highly diverse population of hookworms from geographically isolated hosts. Infect, Genet Evol,28: 192-200.

Hurt C, Hedrick P. 2004. Conservation genetics in aquatic species: general approaches and case studies in fishes and springsnails of arid lands. Aquat Sci,66: 402-413.

Kim C S, Schaible G, Carrett L, et al. 2008. Economic impacts of the US soybean aphid infestation: a multi-regional competitive dynamic analysis. Agric Res Econ Rev,37: 227-242.

Kimura M. 1980. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol,16: 111-120.

Lakra W S, Goswami M, Gopalakrishnan A, et al. 2010. Genetic relatedness among fish species of Genus Channa using mitochondrial DNA genes. Biochem Syst Ecol,38(6): 1212-1219.

Li C X, Ma E B, Zheng X Y. 2003. Genetic differentiation of different populations of four locust species in China. Acta Genetica Sinica,30: 234-244.

Li D, Qin J C, Zhou C F. 2014. The phylogeny of Ephemeroptera in Pterygota revealed by the mitochondrial genome of Siphluriscus chinensis (Hexapoda: Insecta). Gene,545:132-140.

Li J, Zhang Y, Wang Z Y, et al. 2010. Genetic differentiation and gene flow among different geographical populations of the Asian corn borer, Ostrinia furnacalis (Lepidoptera: Crambidae) in China estimated by mitochondrial COⅡ gene sequences. Acta Entomologica Sinica,53(10): 1135-1143.

Li J J, Ye Y Y, Wu C W, et al. 2013. Genetic variation of Mytilus coruscus gould (Bivalvia: Mytilidae) populations in the East China Sea inferred from mtDNA COⅠgene sequence. Biochem Syst Ecology,50: 30-38.

Li Y R. 2006. The agricultural entomology. Higher Education Press, Beijing. pp. 212-216.

Librado P, Rozas J. 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics,25(11): 1451-1452.

Liu H J, Liu M, Ge S S, et al. 2012. Population structuring and historical demography of a common clam worm Perinereris aibuhitensis near the coasts of Shandong Peninsula. Biochem Syst Ecology,44: 70-78.

Liu J Ed. 2007. Study on the predation of natural enemies on soybean aphid. Agricultural Science and Technology of China Press, Beijing. pp. 1-2.

Lynch M, Crease T J. 1990. The analysis of population survey data on DNA sequence variation. Mol Biol Evol,7: 377-394.

Nei M, 1987. Molecular Evolutionary Genetics. Columbia University Press, New York, USA. pp. 10-88.

Nohara K, Takeuchi H, Tsuzaki T, et al. 2010. Genetic variability and stock structure of red tilefish Branchiostegus japonicus inferred from mtDNA sequence analysis. Fish Sci,76: 75-81.

Puillandre N, Bouchet P, Duda T F, et al. 2014. Molecular phylogeny and evolution of the cone snails (Gastropoda, Conoidea). Mol Phylogenet Evol,78: 290-303.

Ragsdale D W, Landis D A, Brodeur J, et al. 2011. Ecology and management of soybean aphid in North America. Annu Rev Entomol,56: 375-399.

Saitou N, Nei M. 1987. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol,4: 406-425.

Sambrook J, Russell D W. 2001. Molecular cloning: a laboratory manual. 3 rd. Cold Spring Harbor Laboratory Press, New York.

Tajima F. 1989. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics,123: 585-595.

Tamura K, Peterson D, Peterson N, et al. 2011. MEGA 5, molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol,28(10): 2731-2739.

Thompson J D, Gibson T J, Plewniak F, et al. 1997. The CLUSTAL-X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucl Acids Res,25: 4876-4882.

Vandermoten S, Mescher M C, Francis F, et al. 2012. Aphid alarm pheromone: an overview of current knowledge on biosynthesis andfunctions. Insect Biochem Mol Biol,42: 155-163.

Wang H, Xu Z X, Han L L, et al. 2014. Analysis of the genetic diversity in geographic populations of Leguminivora glycinivorella (Lepidoptera: Olethreutidae) from northeastern China based on mitochondrial DNA COI gene sequences. Acta Entomologica Sinica,57(9): 1051-1060.

Wang X Y, Xu G Q. 2014. Genetic differentiation and gene flow among geographic populations of Spodoptera exigua (Lepidoptera: Noctuidae) in China. Acta Entomologica Sinica,57(9): 1061-1074.

Weight S. 1978. Evolution and the genetics of population. In: Wright S. Variability within and among natural populations. University of Chicago Press, Chicago. pp. 10-15.

Xu H X, Zhang Y R, Xu D D, et al. 2014. Genetic population structure of miiuy croaker (Miichthys miiuy) in the Yellow and East China Seas base on mitochondrial COⅠsequences. Biochem Syst Ecol,54: 240-246.

Xue Q X. 2013. Analysis on the change of 30 years' soybean areas, production and yield in China and Northeast China. Chinese Agricultural Science Bulletin,29(35): 102-106.

Yang Z X, Feng Y, Chen X M. 2005. An effective method for extraction genomic DNA from aphids. Forest Research,18(5): 641-Cover three.

Zhang B, Ma C, Edwards O, et al. 2014. The mitochondrial genome of the Russian wheat aphid Diuraphis noxia: large repetitive sequences between trnE and trnF in aphids. Gene,533: 253-260.

Zhang Y, Wu K M, Wyckhuys K A G, et al. 2009. Effect of parasitism on flight behavior of the soybean aphid, Aphis glycines. Biol Control,51: 475-479.

Q81

A

1006-8104(2015)-03-0023-09

Received 20 June 2015

Supported by the Special funds for Construction of Modern Agricultural Technology System (CARS-04); Public Welfare Industry (Agriculture) Special Fund (201103002)

Li Ran (1989-), female, Master, engaged in the research of insect ecology. E-mail: lirannl@126.com

* Corresponding author. Zhao Kui-jun, professor, supervisor of Ph. D student, engaged in the research of insect ecology. E-mail: kjzhao@163.com