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A THESIS
FOR THE DEGREE OF MASTER OF SCIENCE
Genetic Diversity Analysis of Sogatella furcifera
(Horváth) (Hemiptera: Delphacidae) by Using Novel
Microsatellite Markers
초위성체 마커를 이용한 흰등멸구 개체군의 유전적
다양성 분석
BY
HWA YEUN NAM
ENTOMOLOGY PROGRAM
DEPARTMENT OF AGRICULTURAL BIOTECHNOLOGY SEOUL NATIONAL UNIVERSITY
A THESIS FOR THE DEGREE OF MASTER OF SCIENCE
Genetic Diversity Analysis of Sogatella furcifera (Horváth)
(Hemiptera: Delphacidae) by Using Novel Microsatellite
Markers
UNDER THE DIRECTION OF ADVISER JOON-HO LEE
SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF SEOUL NATIONAL UNIVERSITY
BY HWA YEUN NAM ENTOMOLOGY PROGRAM
DEPARTMENT OF AGRICULTURAL BIOTECHNOLOGY SEOUL NATIONAL UNIVERSITY
AUGUST, 2014
APPROVED AS A QUALIFIED THESIS OF HWA YEUN NAM FOR THE DEGREE OF MASTER OF SCIENCE
BY THE COMMITTEE MEMBERS
Chairman Dr. Si Hyeock Lee ____________________ Vice Chairman Dr. Joon-Ho Lee ____________________ Member Dr. Yeon Ho Je ____________________
I
ABSTRACT
Genetic Diversity Analysis of Sogatella furcifera (Horváth)
(Hemiptera:Delphacidae) by Using Novel Microsatellite
Markers
Hwa Yeun Nam Entomology Program Department of Agricultural Biotechnology Seoul National University
White-backed planthopper, Sogatella furcifera (Horváth) (Hemiptera: Delphacidae), is known as a major rice and long-range migratory pest in Asia. Microsatellite marker (SSR) is widely used to perceive the origins and genetic diversity of insect pest. Samples were collected from Laos, Vietnam and 3 localities in Bangladesh, and we characterized novel 10 microsatellite loci of S. furcifera by using next-generation Roche 454 pyrosequencing technologies. We used 40 adult individuals collected from Shinan to test utility of ten microsatellite loci. The average of alleles per locus were 7.7. The mean of observed (HO) and expected heterozygosities (HE) were 0.648
II
and 0.748 respectively. These new microsatellite markers will be widely used in future ecological genetic studies of S. furcifera, including gene flow and genetic diversity among the population that are necessary for effective management and observing of the species.
Furthermore, we used these markers to determine genetic diversity for
S. furcifera specimens collected from Korea (Shin-an), Laos, Nepal,
Thailand, Vietnam and three different sites of Bangladesh in 2012, and Bangladesh, China, Nepal ,Thailand, and fifteen different sites of Korea in 2013. The genetic variability estimates for each S. furcifera population infer from the ten microsatellite loci included the observed (HO) and expected (HE)
heterozygosity and the inbreeding coefficient. HO ranged from 0.259 – 0.604
(mean = 0.435) and HE ranged from 0.488 - 0.768 (mean = 0.669). The FIS
ranged from 0.1867 in WBPH_T17 to 0.5855 in WBPH_T11, with mean of 0.3598 across loci. In genetic variability estimates for each S. furcifera population in Asia, inferred from ten microsatellite markers, Shinan has a highest number of HO 0.648. This result shows the possibility of variation of
the migration source. We speculate Laos, Vietnam and China as the origin of S. furcifera in Korea by the low number of FIS and high number of HO.
The genetic variability estimates for each S. furcifera population in Korea, Changnyung, Gosung, Milyang and Shinan show high estimation of HO. All
III
variability of migration origin. This study provides useful data to forecast the migration and origin of S. furcifera. This information about migration pattern may develop sustainable pest management strategies of this long-range migratory pest.
Key words: white backed planthopper, Sogatella furcifera, genetic diversity, microsatellite marker, next generation sequencing
IV
List of Contents
Abstract --- I List of contents --- IV List of Tables --- VI List of Figures --- VIII
I. Literature Review --- 1
1-1. General characteristic of white backed planthopper --- 2
1-2. New generation sequencing (NGS) --- 3
1-3. Microsatellite marker--- 6
II. Developing Novel microsatellite markers of Sogatella furcifera (Horváth) (Hemiptera: Delphacidae)--- 7
2-1. Introduction --- 8
2-2. Materials and Methods --- 10
2-2-1. Microsatellite marker development --- 10
2-2-2. Roche 454 library preparation and sequencing --- 13
2-2-3. Microsatellite marker development --- 16
2-2-4. DNA sample and Microsatellite genotyping --- 17
2-2-5. Data analysis --- 17
V
2-4. Discussion --- 25
III. Genetic diversity analysis of Sogatella furcifera (Horváth) (Hemiptera: Delphacidae) in Asia --- 27
3-1. Introduction --- 28
3-2. Material and Methods --- 30
3-2-1. Study insect and sample collection --- 30
3-2-2. Microsatellite genotyping --- 35
3-2-3. Statistical analysis --- 36
3-3. Results --- 37
3-4. Discussion --- 44
IV. Literature Cited --- 45
VI
List of Tables
Table 1. Sampling information of Sogatella furcifera ---11
Table 2. Primer sequences used to create pooled plant hopper libraries for sequencing on the Roche 454. Underlined, grey highlighted and black highlighted regions respectively correspond to the key, Midtag (4 or 11), and adapter sequences --- 15
Table 3. Summary of newly designed primers --- 20
Table 4. Modified twelve proper microsatellite markers --- 23
Table 5. Characteristics of the ten S. furcifera microsatellite loci tested in S.
furcifera specimens from countries --- 24
Table 6. 2012 and 2013 samples of S. furcifera --- 33
Table 7. Characteristics of the ten S. furcifera microsatellite loci tested in S.
VII
Table 8. Genetic variability estimates for each S. furcifera population in Asia, deduced from ten microsatellite loci. Number of alleles, expected heterozygosity (HE), observed heterozygosity (HO) at HWE and inbreeding
coefficient (FIS) --- 40
Table 9. Genetic variability estimates for each S. furcifera population in Korea, deduced from ten microsatellite loci. Number of alleles, expected heterozygosity (HE), observed heterozygosity (HO) at HWE and inbreeding
VIII
List of Figures
Fig 1. Map of S. furcifera collecting sites --- 12
Fig 2. Selecting new microsatellite markers by using GeneMapper program --- 22
Fig 3. Sampling sites in East Asia (2012) --- 31
Fig 4. Sampling sites in East Asia (2013) --- 31
1
Chapter 1.
2
1-1. General characteristics of white backed planthopper
Sogatella furcifera (Horvárth) (Hemiptera: Delphacidae) is a very serious
long-range migratory pest, which existed since the early 1970s in Korea. The nymphs and adults suck the phloem sap and reduced plant vigor, stunting, yellowing of leaves and delayed tillering and shrivel grain formation (Khan and Saxena 1984). Moreover, heavy infestation may cause hopper burn symptoms toward crop maturity stage, resulting in complete death of rice plants (Pathak 1968).
This species is apparently unable to overwinter in Korea and undergoes long-distance migration each year from southern China (Park 1973, Kisimoto 1976, Asahina and Tsruoka 1986, Uhm et al. 1988). Male are usually monomorphic macropterous. On the other hand, adult females of S.
furcifera reveal wing dimorphism and occur in two forms; macropters and
brachpters. Macropterous females are fully winged and can migrate long distances, although brachypterous females have reduced wing and unable to fly and migrate. The production of macropters is influenced most by nymphal population density (Kisimoto 1956). For better adaptation, it is benefit to migrate and colonize new habitats when the population density is high, and macroptery is required for migration.
3
1-2. New generation sequencing (NGS)
In late 1970s, Fred Sanger et al. (1997a, b) published the papers on the chain-termination methods of DNA sequence. This has remained the most commonly used DNA sequencing technique to date and was used to complete human genome sequencing enterprise led by the International Human Genome Sequencing Consortium and Celera Genomics (Lander et
al. 2001, Venter et al. 2001, International Human Genome Sequencing
Consortium 2004). Recently, the Sanger method has been partially replaced by several “next-generation” sequencing technologies which offer impressively increases in cost-effective sequence throughput, although expense of read lengths of sequence (Morozova et al. 2008). Nowadays, there are three commercial next-generation DNA sequencing systems: Roche's (454) GS FLX Genome Analyzer promoted by Roche Applied Sciences, Illumina's Solexa 1G sequencer, and most recently Applied Biosystem's SOLiD system. In this study we utilized Roche (454) GS FLX Genome Analyzer.
Roche (454) was first commercially introduced in 2004 and works on principle of “pyrosequencing” (Margulies et al. 2005). Clonal sequencing features are produced by emulsion PCR, with amplicons apprehended to the surface of 28-μm beads (Dressman et al. 2003). In emulsion PCR,
4
individual DNA fragment-carrying streptavidin beads, and adapters are used to acquire through shearing the DNA and associating the fragments to the beads, are captured into separate emulsion droplets. The droplets act as individual amplification reactors, which producing ~107 clonal copies of a
unique DNA template per bead (Margulies et al. 2005). Afterward, each template-containing bead is transferred into a well of a picotiter plate and the clonally related templates are analyzed using a pyrosequencing reaction. The use of the picotiter plate allows hundreds of thousands of pyrosequencing reactions to be carried out in parallel, which is increasing the sequencing throughput (Margulies et al. 2005). The sequencing-by synthesis technique that measures the release of inorganic pyrophosphate (PP) by Chemiluminescence is the pyrosequencing approach (Nyren et al. 2008, Ronaghi et al. 2008). The template DNA is immobilized, and solutions of dNTPs are added one at a time which is releasing of PP whenever the complementary nucleotide is incorporated. This is detectable by light produced by a chemiluminescent enzyme present in the reaction mix. The sequence of DNA template is verified from a “pyrogram,” which corresponds to the order of correct nucleotides that had been incorporated. Since chemiluminescent signal intensity is proportional to the amount of pyrophosphate released and hence the number of bases included, the pyrosequencing approach is prone to errors that result from incorrectly
5
estimating the length of homopolymeric sequence stretches (Morozova et
al. 2008). Roche 454 is capable of generating 80–120 Mb of sequence in
200- to 300-bp reads in a 4-h run. The 454 technology has been the most widely published next-generation technology, and the per- base cost of sequencing with the Roche 454 platform is much greater than other platforms (e.g., SOLiD and Solexa)
6
1-3. Microsatellite marker
Microsatellites, simple sequence repeats (SSR) marker, are well distributed and high efficiency as molecular markers. SSRs were first studied in humans and nowadays, this markers are widely used for other eukaryotes: laboratory and domesticated mammals, birds, fish, insects, yeast and several monocot and dicot plant species.
Important characteristics of microsatellite loci is their high level of allelic diversity, and valuable as genetic markers. SSRs are highly variable in the number of repeats they contain and are co-dominantly inherited (Johansson
et al. 1992). They can be used for assessment of the level of gene flow and
genetic connectivity among populations, genomic mapping, population and evolutionary studies as well as for fingerprinting and pedigree analyses (Hazan et al. 1992, Plashke et al. 1995, Rongwen et al. 1995, Guilford et al. 1997). In this study, SSR marker may use to verify the migration route and genetic diversity of S. furcifera.
7
Chapter 2.
Developing Novel microsatellite
markers of Sogatella furcifera
8
2-1. Introduction
The white backed planthopper (Horvárth) (Hemiptera: Delphacidae) is a major rice pest and widely populated in South and East Asia (Dyck and Thomas 1979). Prior to 1978, S. furcifera only caused intermittent damage in rice (Tang et al. 1996). As the adoption of hybrid rice variations extended in East Asia, the area of damage of S. furcifera increased rapidly (Tang et
al. 1998). Nevertheless, S. furcifera has been reported as an outbreak of
long-range migratory pest in China, Japan, and Korea beginning of the 21st
century (Zhai and Cheng 2006, Otuka et al. 2007).
S. furcifera hibernate in Indochina Peninsula and migrate to China by the
southwest atmospheric current from March to July. Moreover, small population of S. furcifera hibernate in spring rice and ratoon rice in southwestern Yunnan Province and southern Guangxi Province (National Coordinated Research Group 1981). This pest starts to migrate in the early stage of the growth of rice, especially in nurseries (Park 1973, Kisimoto 1976, Asahina and Tsruoka 1986, Uhm et al. 1988). S. furcifera cannot hibernate in Korea. The first small batch starts to migrate from the other countries by atmospheric current in mid-June, and immigration of copious population occurrs during mid- to late-July. However, the exact primary source of S. furcifera in Korea remains a matter of debate (Sogawa
9
1997). Therefore, figuring out the genetic diversity of S. furcifera may implicate the migration route and provide the forecasting strategies for this long-range migratory pest. Simple sequence repeat (SSR) marker has been widely used. The capability of this marker is similar to molecular markers and also used as population genetic studies tools (Valdes et al. 1993, Akkaya et al. 1995, Schuler et al. 1996). However, SSR marker of S.
furcifera has not been developed and requires further progress in
development. In this study, we developed novel microsatellite markers (SSR) of S. furcifera by using next-generation Roche 454 pyrosequencing technologies, and verified characterization of 10 polymorphic loci from S.
furcifera by using S.furcifera population collected from Shinan (n=40), Korea
10
2-2. Materials and Methods
Microsatellite marker development
Individuals of the white backed planthopper, S. furcifera, were collected from 5 sites in 3 countries: Laos, Vietnam and Bangladesh (Table 1, Fig 1). Samples were collected by institution of AFACI (Asian Food and Agriculture Cooperation Initiative) in 2012 and placed in 95% ethanol and stored at -20°C until DNA extraction was examined.
DNA of stored S. furcifera were extracted by QIAamp DNA Mini Kit (Qiagen, Germany). DNA samples were conveyed to USDA_ARS corn insect & crop Genetic research unit in Iowa. Microsatellite loci were isolated from S. furcifera genomic DNA based on the Roche 454 methods described by Purtiz and Toonen (2013).
11 Table 1. Sampling information of Sogatella furcifera
Country Sample site Sampling date Sample size Coordinates
Bangladesh #1 Tarash, Sirajgonj 5/10/2012 45 N24°23’45.0 E89°22’39.7"
Bangladesh #2 BRRi R/S, Gazipur 11/7/2012 60 N23°98’60.3" E90°41’14.6"
Bangladesh #3 Sagordi, Barisal 9/27/2012 63 N22°67’71.6" E90°36’43.4"
Laos Vientiane,Phontong 8/11/2012 50 N18°30'39.0" E102°25'05.7"
12 Fig 1. Map of S. furcifera collecting sites
13
Roche 454 library preparation and sequencing
Approximately ~0.5 ug of total genomic DNA from locations 2, 3, 6, 7 and 9 were each digested with 5U each of EcoRI and PstI enzymes in a 40 ul reaction at 37 C for 4 hrs, and then ligated to adapters EcoRI- and PstI-Ad (Vuylsteke et al. 1999) as described by Vos et al. (1995). PCR amplification was carried out using 4.0 μl of digested and ligated template, 10 μM of each primers PriA_454M04_Eco and PriB_454M11_Pst (Table 2) and the high-fidelity LongAmp polymerase (New England Biolabs, Ipswich, MA, USA) according to manufacturer's instructions. Thermocycler conditions included and initial denaturation of 95 ºC for 2 min, then a 6 touchdown cycles of 95 ºC for 30 sec, 65 ºC for 30 sec -2ºC/cycle, and 65 ºC for 2 min, then 32 cycle of 95 ºC for 30 sec, 55 ºC for 20 sec, and 65 ºC for 2 min. Resulting PCR products were checked on 1.5% agarose, and successful reaction products treated with Exonuclease I and shrimp alkaline phosphatase (New England Biolabs) at 37 ºC for 1 hr, which was inactivated at 72 ºC for 5 min. Reaction products were further column purified using IBI Gel/PCR DNA Fragment Extraction Kit (Peosta, IA, USA) according to manufacturer's instructions, and eluted DNA quantified on a NanoDrop2000 (Thermo Scientific, Wilmington, DE, USA). Products were diluted to 20
14
ng/10μl and sent to the University of Illinois, W.M, Keck Center for Comparative and Functional Genomics, High-Throughput Sequencing and Genotyping Unit and sequence data was generated from a ~1/4 of a Roche 454 titanium plate.
15
Table 2. Primer sequences used to create pooled plant hopper libraries for sequencing on the Roche 454. Underlined, grey highlighted and black highlighted regions respectively correspond to the key, Midtag (4 or 11), and adapter sequences
¹ Eco Adapter primer sequence 5'-CTCGTAGACTGCGTACC-3', 3'-CATCTGACGCATGGTTAA-5’
² Pst Adapter primer sequence 5'-CTCGTAGACTGCGTACATGCA-3, '3'-CATCTGACGCATGT-5'
Primer name Primer sequence
PriA_454M04_Eco¹ CGTATCGCCTCCCTCGCGCCATCAGAGCACTGTAGTTCCCTACACGACGCTCTTCCT
16
Data quality control and microsatellite predictions
Three files, .sff, .fna, and .qual, were obtained from the W.M, Keck Center for Comparative and Functional Genomics. Homopolymer stretches ≥ 6 nt were trimmed to a maximum of 6 bases from .fna and .qual files using the PERL script HomopolymerTrimming.pl according to the NGSToolkit (Patel and Jain 2012). The resulting .fna and .qual files were merged into a single .fastq file using the custom script Fasta2Fastq.pl, and then each read was simultaneously trimmed of Midtag and adapter sequence, and sequence of quality scores (q) < 20 using the script TrimmingReads.pl from the NGSToolkit (Patel and Jain, 2012). The final processed and trimmed read data were converted to a .fasta file using the FastqToFasta script (NGSToolkit Patel and Jain, 2012), and used as input for the program SciRoKo (Koefler et al. 2007). Mismatched microsatellite di-, tri-, tetra-, and pentanucleotide repeat motifs >3 units in length, and a base substitution mismatch penalty of 5, seed length of 8, and max mismatches of 1. Sequence ±300 bp of each predicted motif was obtained using a custom PERL script and output into a .fasta file.
17
DNA samples and microsatellite genotyping
S. furcifera samples (thorax, n=40) were collected from Shinan, Korea in
2012. Genomic DNA was extracted from the whole body of individuals without abdomen using the AccuPrep DNA Extraction Kit (BIONEER, USA).
Data analysis
GENEALEX 6.501 (Peakall et al. 2006) was used to verify the three measure of genetic diversity: the number of alleles (A) per locus, observed heteozygosity (HO), and expected heterozygosity (HE). Hardy-Weinberg
equilibrium (HWE) test for each locus in each population was tested by using GENEPOP version 4.2.1 (Raymond et al. 2006).
18
2-3. Results
A total 636 microsatellite loci were found in next generation Roche 454 pyrosequencing technologies. After screening of microsatellites with tri-nucleotide repeats motif, total of 22 loci were selected (Table 3). Amplification of 22 microsatellite maker was conducted in total 10 ㎕ reaction volume to genotype the samples: 4.9 ㎕ distilled water, 1 ㎕ 10X PCR buffer, 1 ㎕ 10mM dNTP Mixture, 0.5 ㎕ of each primer, 0.1 ㎕ of Taq polymerase, and 2.0 ㎕ template DNA. For this examination, we used only three S. furcifera to test positive PCR reaction. The PCR was performed under the following conditions: initial denaturation for 4 min at 94°C, followed by 35 cycles of 94°C for 30 s, annealing at 61°C for 30 s, 72°C for 40 s, a final extension was performed at 72°C for 15 min. The forward primer was labeled with fluorescent dye (either Hex, 6Fam or NED dyes). Amplified PCR mixtures were separated electrophoresed on an ABI Prim 3730 XL DNA Analyzer (Applied Biosystems Inc., USA) with the GENESCAN-500 (Rox) size standard. The genotype data were analyzed by using GeneMapper version 3.7 (Applied Biosystems INC., USA).
In GeneMapper version 3.7 (Applied Biosystems INC., USA) program, we verified the allele size and the real peak in the size range of the microsatellite marker (Fig 2.). As a result, we selected proper 12
19
microsatellite markers (Table 4), T3, T4, T5, T7, T8, T9, T11, T13, T15, T16, T17, T18, but T7 and T8 were not included in this examination.
For genotyping, ten microsatellite loci and individual specimen were collected from Shinan, Korea in 2012. All microsatellite markers were polymorphic, with the alleles per locus ranging from eight to eleven (mean = 9.9) (Table 5). The mean HO and HE values were 0.648 (0.400 – 0.875)
and 0.748 (0.558 - 0.852) respectively (Table 6.) The FIS ranged from
-0.5582 in WBPH_T4 to 0.4000 in WBPH_T5, with mean of 0.0744 across loci. Therefore, these 10 microsatellite markers are important to verify the genetic diversity of S. furcifera.
20 Table 3. Summary of newly designed primers
Locus Primer Sequence (5’-3’) Repeat
motif
melting temperature Size Range (bp)
WBPH_T1 F:(NED)- TCCCTTCTCCTTTTATCCTCCTC R: CAGCCCGCTCAGTCAGTGATA TCT 63.1 167 – 179 WBPH_T2 F:(HEX)- CCCTGCACAACAACAACATCA R: CAGCCCGCTCAGTCAGTGATA CAA 63.9 125 – 137 WBPH_T3 F: (6-FAM)- CGACAGCACGTACTCCTGCTT R: ACACGACGCTCTTCCTCCTTC GAG 67.1 236 – 248 WBPH_T4 F: (6-FAM)- GGAAGAAACGGATGGAATTACG R: ACGACGCTCTTCCTCCTCATC AGA 62.5 128 – 140 WBPH_T5 F: (NED)- TCCAATCCTGCTTACAGTCCAA R: GCGTACATGCAGTGGACAGAT TTC 63.1 230 – 242 WBPH_T6 F: (HEX)- GCCAGAGGGTCTTCTCTGCTT R: CGCCATCAGTCAAAGCACTGT GGA 66.5 163 – 175 WBPH_T7 F: (HEX)- CCCTCTTCTCTCGCCCTCT R: GTCGTGCTGAGGCTCGTC GAC 60.1 (78bp) 95 - 107 WBPH_T8 F: (NED)- TCAGCCAGAGCTGTAGAATCAA R: CAGCGTCTCTGTCCATTCG AGA 60.0 (112bp) 105- 117 WBPH_T9 F: (NED)- GCCGCCCAGTTCTGTAAAGTC R: CTGATGCTGCCGCTGTTGT GCA 66.7 85 – 97 WBPH_T10 F: (6-FAM)- CCCGATTTTCAGCGTACAAC R: ACGAGGATCGTCAATTCCAG ACG 60 (167bp) 319 – 331
21 WBPH_T11 F:(6-FAM)- CTAAAACGCTCGCGTCTGC R: GCTCAGTCAGTGATACGTCTTCG GAT 65.2 182 – 194 WBPH_T12 F: (HEX)- AGCATCAATGAAAGGCACTGG R: TACACGACGCTCTTCCACCTC GAG 64.4 228 - 300 WBPH_T13 F: (HEX)- GCCTCCTCTGCTGTTGAGAAA R: CATTGGCCATCTTGGTGACTG GAA 64.7 374 – 386 WBPH_T14 F: (6-FAM)- CCACCCGACACGTTTATATG R: GCTGACCGTTGCTACACAAA GCA 59.0 (161bp) 278 – 290 WBPH_T15 F: (6-FAM)- GCGCGCGCATATATACAGTTG R: AAGCGACGCAAGTGACGATAA CGT 64.3 187 – 199 WBPH_T16 F: (HEX)- GGGTACACCGTTCGAGTCGTT R: CCGCTCAGTCAGTGATACGC CGT 66.2 232 – 244 WBPH_T17 F: (NED)- TCCTGAGGCACGCTAACTGAC R: CTTGTGCGTGGGTCATGAGAT ATC 65.8 353 – 365 WBPH_T18 F: (HEX)- GTGCGAAGGGAAATGCAGAAG R: TTCTCCATCGCATCTCTTGTTCT GAA 63.6 201 – 213 WBPH_T19 F: (NED)- TGTAGGTACATGGTGGTGTTTAGGA R: CTCGCGCCATCAGTCAGAG AGA 64.2 137 – 149 WBPH_T20 F: (NED)- TTCCCTACACGACGCTCTTCC R: CAGCCCGCTCAGTCAGTGATA TTC 66.1 303 – 315 WBPH_T21 F: (NED)- GCTTACAGTCCAAGGCCTCCT R: GCTCAGTCAGTGATACGTCTTCG TTC 65.7 244 – 156 WBPH_T22 F: (6-FAM)- AACGTCAAAGATGGCGTGTTG R: CGCGTACTTGTTCGCGTACTT GAC 64.8 123- 135
22
Fig 2. Selecting new microsatellite markers by using GeneMapper program
23 Table 4. Modified twelve proper microsatellite markers
Locus Primer Sequence (5’-3’) Repeat motif Size Range (bp)
WBPH_T3 F: (6-FAM)- CGACAGCACGTACTCCTGCTT R: ACACGACGCTCTTCCTCCTTC GAG 236 – 248 WBPH_T4 F: (6-FAM)- GGAAGAAACGGATGGAATTACG R: ACGACGCTCTTCCTCCTCATC AGA 128 – 140 WBPH_T5 F: (NED)- TTCCAATCCTGCTTACAGTCCAA R: GCGTACATGCAGTGGACAGAT TTC 230 – 242 WBPH_T7 F: (HEX)- CCCTCTTCTCTCGCCCTCT R: GTCGTGCTGAGGCTCGTC GAC 95 - 107 WBPH_T8 F: (NED)- TCAGCCAGAGCTGTAGAATCAA R: CAGCGTCTCTGTCCATTCG AGA 105- 117 WBPH_T9 F: (NED)- GCCGCCCAGTTCTGTAAAGTC R: CTGATGCTGCCGCTGTTGT GCA 85 – 97 WBPH_T11 F: (6-FAM)- CTAAAACGCTCGCGTCTGC R: GCTCAGTCAGTGATACGTCTTCG GAT 182 – 194 WBPH_T13 F: (HEX)- GCCTCCTCTGCTGTTGAGAAA R: CATTGGCCATCTTGGTGACTG GAA 374 – 386 WBPH_T15 F: (6-FAM)- GCGCGCGCATATATACAGTTG R: AAGCGACGCAAGTGACGATAA CGT 187 – 199 WBPH_T16 F: (HEX)- GGGTACACCGTTCGAGTCGTT R: CCGCTCAGTCAGTGATACGC CGT 232 – 244 WBPH_T17 F: (NED)- TCCTGAGGCACGCTAACTGAC R: CTTGTGCGTGGGTCATGAGAT ATC 353 – 365 WBPH_T18 F: (HEX)- GTGCGAAGGGAAATGCAGAAG R: TTCTCCATCGCATCTCTTGTTCT GAA 201 – 213
24
Table 5. Characteristics of the ten S. furcifera microsatellite loci tested in S. furcifera specimens from countries
Locus Primer Sequence (5’-3’) Repeat motif Mean of N No. alleles Size Range (bp) HO HE FIS WBPH_T3 F: (6-FAM)- CGACAGCACGTACTCCTGCTT R: ACACGACGCTCTTCCTCCTTC GAG 40 8 236 – 248 0.575 0.739 0.2337 WBPH_T4 F: (6-FAM)- GGAAGAAACGGATGGAATTACG R: ACGACGCTCTTCCTCCTCATC AGA 40 5 128 – 140 0.875 0.558 -0.5582 WBPH_T5 F: (NED)- TTCCAATCCTGCTTACAGTCCAA R: GCGTACATGCAGTGGACAGAT TTC 40 7 230 – 242 0.400 0.655 0.4000 WBPH_T9 F: (NED)- GCCGCCCAGTTCTGTAAAGTC R: CTGATGCTGCCGCTGTTGT GCA 40 9 85 – 97 0.875 0.852 -0.0149 WBPH_T11 F: (6-FAM)- CTAAAACGCTCGCGTCTGC R: GCTCAGTCAGTGATACGTCTTCG GAT 40 9 182 – 194 0.625 0.703 0.1232 WBPH_T13 F: (HEX)- GCCTCCTCTGCTGTTGAGAAA R: CATTGGCCATCTTGGTGACTG GAA 40 9 374 – 386 0.500 0.786 0.3604 WBPH_T15 F: (6-FAM)- GCGCGCGCATATATACAGTTG R: AAGCGACGCAAGTGACGATAA CGT 40 7 187 – 199 0.500 0.786 0.3747 WBPH_T16 F: (HEX)- GGGTACACCGTTCGAGTCGTT R: CCGCTCAGTCAGTGATACGC CGT 40 8 232 – 244 0.600 0.833 0.2914 WBPH_T17 F: (NED)- TCCTGAGGCACGCTAACTGAC R: CTTGTGCGTGGGTCATGAGAT ATC 40 10 353 – 365 0.700 0.807 0.1445 WBPH_T18 F: (HEX)- GTGCGAAGGGAAATGCAGAAG R: TTCTCCATCGCATCTCTTGTTCT GAA 40 6 201 – 213 0.825 0.774 -0.0528 Across Loci 7.7 0.648 0.748 0.0744
Microsatellite primer sequences with fluorescent labeled dyes, repeat motifs, mean of individuals (N), number of alleles (A), size of PCR products in base pairs (bp), expected heteozygosity (HE), observed heterozygosity (HO) and inbreeding
25
2-4. Discussions
Twelve polymorphic microsatellite markers were developed in this study, although only ten microsatellite markers have been successfully applied to obtain population genetics parameters for 40 S. furcifera species in Korea. In further study, marker WBPH_T7 and WBPH_T8 will be examined and applied to verify the genetic diversity and characteristic of S. furcifera.
These ten new microsatellite markers will facilitate the study of the gene flow and migration rout of S. furcifera in Asia. For example, these microsatellites could be suitable to elucidate invasion routes of the insects form China to Korea using the Approximate Bayesian Computation method as was done to reveal frequent and ongoing introduction of western corn rootworm from North to Europe (Miller et al. 2005). These markers can be used to the study migration and genetic structure of insect genetic structure data of migration insect. For example, Llwellyn et al. (2003) used microsatellite to study genetic variability of the grain aphid, Sitobion avenae, in Britain relate to climate and clonal fluctuation. These markers are also suitable to explain migration routes of these insect from Korea and other countries. These markers can characterize the migration patterns, gene flow, and genetic connectivity among geographic populations of S. furcifera in
26
Asia. Successful results from this examination will contribute to map effectively strategies for the migration route and origin of this species.
27
Chapter 3.
Genetic diversity analysis of
Sogatella furcifera (Horváth)
28
3-1. Introduction
The white backed planthopper, Sogatella furcifera (Horváth) (Hemiptera: Delphacidae), originated from tropical region. This pest does not hibernate in middle China, Korea and Japan, but does migrate into these countries each year with the new rice growing season (Park 1973, Kisimoto, 1976, Asahina and Tsruoka, 1986, Uhm et al. 1988). In Korea, a small population of this pest migrates by atmospheric current in mid-June, and further immigration occurs during mid- to late-July. However, the exact primary source of S. furcifera in Korea remains a matter of debate (Sogawa 1997). Therefore, characterizing the genetic diversity of S. furcifera may implicate the migration route and provide the forecasting strategies for this long-range migratory pest,
Previous studies about the origins of S. furcifera have used mitochondrial DNA sequence (Mun et al. 1999) and inter-simpler sequence repeat (ISSR) marker (Liu et al. 2010). However, basis of difference in mitochondrial DNA sequence may difficult to verify the origin of S. furcifera population (Matsumoto 2013). Inter-simple sequence repeat markers are cost-effective, rapid and efficiently sensitive (Gui et al. 2008, Zietkiewicz et al. 1994), however these markers are limited to distinguish genetic diversity of individual species.
29
In this study, we used ten simple sequence markers (SSR) which we developed by next-generation Roche 454 pyrosequencing. Simple sequence repeat (SSR) marker determined the genetic diversity and movement of individuals (Kim et al. 2008b). We conducted a genetic diversity study of S. furcifera in Bangladesh, China, Laos, Nepal, South Korea, Thailand and Vietnam, and analyzed microsatellite marker data to estimate migration route.
30
3-2. Material and methods
Study insect and sample collection
S. furcifera was collected from Korea (Shin-an), Laos, Nepal, Thailand,
Vietnam and three different sites of Bangladesh in 2012 (Fig 3), and Bangladesh, China, Nepal, Thailand, and fifteen different sites of Korea in 2013 (Fig 4, Fig 5, Table 6), including the initial occurrence locations (Table 6). Samples of East Asia were collected by institution of AFACI (Asian Food and Agriculture Cooperation Initiative) and Korea were collected by sweeping and light trap. All samples were placed in 95% ethanol and stored at -20°C until DNA extraction was performed.
31 Fig 3. Sampling sites in East Asia (2012)
32
33 Table 6. 2012 and 2013 samples of S. furcifera
Country Sampling
name
Sampling Site Sampling Date Coordinates
Bangladesh Ban Dobila,Tarash, Sirajgonj 05/10/2012 N24°23'45.0",E89°22'39.7"
Bangla Ghargram,Tarash, Sirajgonj 05/10/2012 N24°23'32.6",E89°21'95.1"
Banglad BRRI R/S, Gazipur 11/07/2012 N23°98'60.3",E90°41'14.6"
B Sagordi,Barisal 11/20/2012 N22°67'71.6",E90°36'43.4""
Vietnam V Nam Dinh, Hai Loc 09/28/2012 N20°10'55.85",E106°20'07.79"
Thailand TH Chiang Rai (Research Field) 03/22/2012 N19°50'08.5",E99°44'43.9"
Nepal Ne PN Sharma np-L2-A-WBPH 10/17/2012 N28°01'53.8",E84°16'27.7"
Korea SA Jeonlabuk-do Shinangeun July - August (2012) N34°45'20.8",E126°07'34.0"
Laos La Vientiane,Phontong 8/11/2012 N18°30'39.0",E102°25'05.7"
Korea JC Jaecheonshi, Chungcheongbuk-do 9/10/2013 N37°09'44.5",E128°10'32.9"
TA Taeangeun, Chungcheongnam-do 7/10/2013 N36°45'19.0",E126°20'40.5"
BA Buangeun, Jeonlabuk-do 9/2/2013 N35°43'47.7",E126°43'09.6"
JS Jangsoogeun, Jeonlabuk-do 7/6 - 7/12/2013 N35°38'05.1",E127°30'47.1"
GR Guryegeun, Jeonlanam-do 9/5/2013 N35°11'52.1",E127°27'37.2"
JD Jindogeun, Jeonlanam-do 7/6 - 7/21/2013 N34°32'51.6",E126°18'17.3"
SAN Shinangeun, Jeonlanam-do 7/6 - 7/12/2013 N34°45'20.8",E126°07'34.0"
34
CW Cheolwongeun, Gangwon-do 9/6/2013 N38°13'15.4",E127°15'01.2"
KP Kimposhi, Kyunggi-do 9/6/2013 N37°42'26.1",E126°33'18.4"
NYJ Namyangjooshi, Kyunggi-do July (2013) N37°38'55.0",E127°11'45.4"
CG Chilgokgeun, Kyungsangbuk-do August (2013) N36°02'23.7",E128°22'56.0"
CN Changnyunggeun, Kyungsangnam-do July - August (2013) N35°33'04.3",E128°28'40.2"
GS Gosungguen, Kyungsangnam-do 7/22 - 7/28/2013 N34°58'40.1",E128°18'59.9"
MY Milyangshi, Kyungsangnam-do July – August (2013) N35°31'52.2",E128°44'57.7"
Bangladesh Bang BRRI R/S, Gazipur 04/23/2013 N23°98'60.3",E90°41'14.6"
Bangl BRRI R/S, Gazipur 9/1 - 9/7/2013 N23°98'60.3",E90°41'14.6"
China Ch Pyeongdam agriculture Center, Guangdong 6/8/2013 N23°02'25.1",E114°35'30.0"
Nepal Nepal PN Sharma np-L2-A-WBPH 10/23/2013 N28°01'53.8",E84°16'27.7"
35
Microsatellite genotyping
Genomic DNA was extracted from the whole body of S. furcifera individuals without abdomen using the AccuPrep DNA Extraction Kit (BIONEER, USA). The novel ten microsatellite loci were used for genotyping (Table 5). Multiplex polymerase chain reaction (PCR) was designed using the program Multiplex Manage 1.0 (Holleley et al. 2009) and conducted in two separated reaction: (i) for markers WBPH_T5, WBPH_T9, WBPH_T11, WBPH_T13, WBPH_T17 and WBPH_T16; and (ii) for markers WBPH_T3, WBPH_T4, WBPH_T15 and WBPH_T18. For multiplex 1, we conducted total 10 ㎕ reaction volume to genotype the samples: 3.5 ㎕ distilled water, 1 ㎕ 10X PCR buffer, 1 ㎕ 10mM dNTP Mixture, 0.2 ㎕ of each primer, 0.1 ㎕ of Taq polymerase, and 2.0 ㎕ template DNA. For multiplex 2, we conducted total 10 ㎕ reaction volume to genotype the samples: 4.3 ㎕ distilled water, 1 ㎕ 10X PCR buffer, 1 ㎕ 10mM dNTP Mixture, 0.2 ㎕ of each primer, 0.1 ㎕ of Taq polymerase, and 2.0 ㎕ template DNA. The PCR was performed under the following conditions: initial denaturation for 4 min at 94°C, followed by 35 cycles of 94°C for 30 s, annealing at 61°C for 30 s, 72°C for 40 s, a final extension was performed at 72°C for 15 min.
36
Statistical analysis
Microsatellite Toolkit (Park, 2001) was used to verify the mean number of alleles (A) per locus, observed heteozygosity (HO), and expected
heterozygosity (HE). Hardy-Weinberg equilibrium (HWE) test for each locus
in each population was tested by using GENEPOP program (Raymond and Rousset 1995).
37
3-3. Results
A total of 99 alleles were detected across ten microsatellite loci for 1152
S. furcifera individulas from among the 29 location in Asia. The genetic
variability estimates for each S. furcifera population included the observed (HO) and expected (HE) heterozygosity and the inbreeding coefficient (FIS).
HO ranged from 0.259 – 0.604 (mean = 0.435) and HE ranged from 0.488 -
0.768 (mean = 0.669). The FIS ranged from 0.1867 in WBPH_T17 to 0.5855 in WBPH_T11, with mean of 0.3598 across loci. Therefore, these 10 microsatellite markers verified the genetic diversity of S. furcifera in Asia (Table 7).
In genetic variability estimates for each S.furcifera population in Asia, inferred from ten microsatellite markers, Shinan has the highest number of HO 0.648. This result shows the possibility of variation of migration source.
The S. furcifera in Korea is expected to originated from Laos, Vietnam and China as the number of FIS was low and number of HO was high (Table 8).
The genetic variability estimates for each S. furcifera population in Korea, Changnyung, Gosung, Milyang and Shinan showed high estimation of HO.
All of these sites located in south and southeast part of Korea and may have variety of migration origin (Table 9). KP and NYJ resulted low estimation
38
of HO which located in north part of Korea. This proves that S. furcifera
migrated from unique country. JD and WD were located in South part of Korea and showed low density of HO which means that atmospheric current
may affected the migration route and S. furcifera may have migrated from unique place (Table 9).
39
Table 7. Characteristics of the ten S. furcifera microsatellite loci tested in S. furcifera speciemens from countries
Locus Primer Sequence (5’-3’) Repeat motif Mean of N No. alleles Size Range (bp) HO HE FIS WBPH_T3 F: (6-FAM)- CGACAGCACGTACTCCTGCTT R: ACACGACGCTCTTCCTCCTTC GAG 39.724 11 236 – 248 0.434 0.731 0.4166 WBPH_T4 F: (6-FAM)- GGAAGAAACGGATGGAATTACG R: ACGACGCTCTTCCTCCTCATC AGA 39.724 8 128 – 140 0.329 0.488 0.3359 WBPH_T5 F: (NED)- TTCCAATCCTGCTTACAGTCCAA R: GCGTACATGCAGTGGACAGAT TTC 39.724 11 230 – 242 0.325 0.701 0.5454 WBPH_T9 F: (NED)- GCCGCCCAGTTCTGTAAAGTC R: CTGATGCTGCCGCTGTTGT GCA 39.724 10 85 – 97 0.604 0.751 0.2077 WBPH_T11 F: (6-FAM)- CTAAAACGCTCGCGTCTGC R: GCTCAGTCAGTGATACGTCTTCG GAT 39.724 11 182 – 194 0.259 0.698 0.5855 WBPH_T13 F: (HEX)- GCCTCCTCTGCTGTTGAGAAA R: CATTGGCCATCTTGGTGACTG GAA 39.724 9 374 – 386 0.326 0.513 0.3754 WBPH_T15 F: (6-FAM)- GCGCGCGCATATATACAGTTG R: AAGCGACGCAAGTGACGATAA CGT 39.724 9 187 – 199 0.284 0.561 0.5021 WBPH_T16 F: (HEX)- GGGTACACCGTTCGAGTCGTT R: CCGCTCAGTCAGTGATACGC CGT 39.724 10 232 – 244 0.577 0.763 0.2580 WBPH_T17 F: (NED)- TCCTGAGGCACGCTAACTGAC R: CTTGTGCGTGGGTCATGAGAT ATC 39.724 9 353 – 365 0.589 0.713 0.1867 WBPH_T18 F: (HEX)- GTGCGAAGGGAAATGCAGAAG R: TTCTCCATCGCATCTCTTGTTCT GAA 39.724 11 201 – 213 0.592 0.768 0.2414 Across Loci 9.9 0.435 0.669 0.3598
Microsatellite primer sequences with fluorescent labeled dyes, repeat motifs, mean of individuals (N), number of alleles (A), size of PCR products in base pairs (bp), expected heteozygosity (HE), observed heterozygosity
40
Table 8. Genetic variability estimates for each S. furcifera population in Asia, deduced from ten microsatellite loci. Number of alleles, expected heterozygosity (HE), observed heterozygosity (HO) at HWE and inbreeding
coefficient (FIS)
Population Sample Size No. of alleles HO HE FIS
Ban 40 6.30 0.320 0.607 0.4828 Bangla 37 7.30 0.332 0.664 0.5096 Banglad 41 8.30 0.463 0.765 0.4046 B 39 8.80 0.569 0.747 0.2498 V 40 7.50 0.590 0.609 0.0435 TH 40 6.90 0.403 0.603 0.3438 Ne 39 6.80 0.513 0.619 0.1844 SA 40 7.70 0.648 0.748 0.1462 La 40 8.50 0.621 0.723 0.1548 JC 40 7.10 0.378 0.655 0.4343 TA 39 8.70 0.477 0.793 0.4097 BA 40 7.80 0.384 0.728 0.4822 JS 40 6.70 0.283 0.599 0.5375 GR 40 8.10 0.345 0.688 0.5081
41 JD 40 7.10 0.220 0.613 0.6485 SAN 40 8.00 0.430 0.671 0.3702 WD 40 6.50 0.238 0.533 0.5628 CW 40 8.90 0.490 0.668 0.2785 KP 40 7.80 0.340 0.707 0.5280 NYJ 40 7.20 0.263 0.608 0.5770 CG 40 7.10 0.393 0.600 0.3564 CN 40 7.50 0.445 0.733 0.4034 GS 40 6.90 0.570 0.628 0.1046 MY 40 7.40 0.450 0.697 0.3652 Bang 40 7.50 0.558 0.695 0.1396 Bangl 38 7.80 0.395 0.733 0.4710 Ch 40 6.10 0.595 0.639 0.0544 Nepal 40 8.40 0.533 0.695 0.2461 THAI 40 7.60 0.385 0.700 0.4598
42
Table 9. Genetic variability estimates for each S. furcifera population in Korea, deduced from ten microsatellite loci. Number of alleles, expected heterozygosity (HE), observed heterozygosity (HO) at HWE and inbreeding
coefficient (FIS)
Population Sample Size No. of alleles HO HE FIS
SA 40 7.70 0.648 0.748 0.1046 JC 40 7.10 0.378 0.655 0.4343 TA 39 8.70 0.477 0.793 0.4097 BA 40 7.80 0.384 0.728 0.4822 JS 40 6.70 0.283 0.599 0.5375 GR 40 8.10 0.345 0.688 0.5081 JD 40 7.10 0.220 0.613 0.6485 SAN 40 8.00 0.430 0.671 0.3702 WD 40 6.50 0.238 0.533 0.5628 CW 40 8.90 0.490 0.668 0.2785 KP 40 7.80 0.340 0.707 0.5280 NYJ 40 7.20 0.263 0.608 0.5770 CG 40 7.10 0.393 0.600 0.3564 CN 40 7.50 0.445 0.733 0.4034
43
S 40 6.90 0.570 0.628 0.1046
44
3-4. Discussion
In this study, a significant difference in genetic diversity among the S.
furcifera population in Asia was found. The S. furcifera might have migrated
to Korea from Laos, China or Vietnam. There are possibility of multiple migration routes of S. fucifera; China to Korea or Vietnam and China to Korea or Vietnam, Laos and China to Korea. This speculation was supported by Liu et al. (2010), as they indicated that S. furcifera migrates to China by two routes, one from northern Vietnam and Laos to the Red River Delta which is in the southeastern Yunnan Province, China; and the other one from Myanmar to the southwestern areas of Yunnan Province.
Migration may be affected by the weather condition, and there are studies on going about the relationship between weather condition and long distance migration of the planhoppers (Kisimoto 1976, 1991, Cheng 1991, 1997, Sogawa 1997). Due to global warming, the atmospheric current and rice harvest season may change and this may affect the migration route and migration season of S. furcifera in Korea. Therefore, knowing the origin of
S. furcifera may forecast the migration pattern of this insect. Moreover,
knowing the migration pattern may develop sustainable pest management strategies of S. furcifera.
45
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초위성체 마커를 이용한 흰등멸구 개체군의 유전적
다양성 분석
서울대학교 대학원 농생명공학부 곤충학전공 남화연 초록 흰등멸구(Sogatella Furcifera)는 아시아 지역의 중요한 벼 해충 중 하나이다. 우리나라에서는 월동을 하지 않고 매년 해외에서 비래하는 것으로 알려져 있다. 본 연구에서는 NGS 를 통한 흰등멸구 초위성체 마커를 개발하여 흰등멸구의 지역 간의 유전적 다양성을 비교 분석 하였다. 마커 개발을 위한 흰등멸구의 해외 샘플들은 베트남, 라오스 그리고 방글라데시의 세 지역에서 채집되었으며, 최대한 많은 샘플들을 모아 QIAamp DNA Mini Kit 를 사용하여 DNA 를 추출하였다. Roche 454 (차세대 염기서열 분석)의 시퀸싱을 통해 636 개의 초위성체 좌위 (Microsatellite loci)를 찾아, 이 중 tri-nucleotide 반복되어 있는 22 개의 프라이머 후보를 선정하였고, 최종적으로 12 개 프라이머를 선정하였다. 이 중 10 개 마커를 이용한 흰등멸구의 유전적 다양성을 확인하기 위해 2012 년에 채집된 국내(신안)와 국외(네팔, 라오스, 태국, 베트남, 방글라데시의 세 지역) 지역의 표본과 2013 년 국내 15 개 지역(제천, 태안, 부안, 장수, 구례, 진도, 신안, 완도, 철원, 김포, 남양주, 칠곡, 창녕, 고성, 밀양)과 국외(방글라데시, 중국, 네팔,54 태국)에서 채집된 표본을 사용하였다. 실험결과, 10 개 마커의 평균 allele 수는 9.9 이었으며, 지역별 유전적 다양성의 경우, HE 값은 0.488 - 0.768 (평균값 = 0.669) 이며, HO 값은 0.259 – 0.604 (평균값 = 0.435) 이었다. FIS 값의 범위는 최솟값 WBPH_T17 의 0.1867 에서 최곳값 WHPH_T11 의 0.5855 이었다. 마커를 활용하여 아시아 지역의 유전적 다양성 값을 비교해 보면, 신안에서 HO 값이 0.648 로 제일 높게 나왔다. 이는 비래 근원지역이 다양함을 예측해준다. 즉, FIS 값이 낮게 나온 라오스, 베트남 그리고 중국이 한국에 비래하는 흰등멸구의 근원지라고 예측할 수 있다. 한국 지역의 유전적 다양성 값을 비교하면, 창녕, 고성, 밀양, 그리고 신안에서 HO 값이 높게 나왔다. 이 모든 지역들은 한국의 남쪽과 남동쪽에 위치해있으며 비래 근원지역이 다양할 것으로 예측할 수 있다. 본 연구는 국내에 비래하는 흰등멸구 개체군의 비래 원과 비래 경로를 분자생물학적 방법으로 추정할 수 있는 기초자료를 제공하며, 이 자료들을 통해 비래 해충의 지속적인 방제관리를 발전시킬 것이다. 검색어: 흰등멸구, 유전적 다양성, 초위성체 마커, 차세대 염기서열 분석 학번: 2012-23374
