中国麦红吸浆虫不同地理种群的遗传结构及遗传多样性研究
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摘要
麦红吸浆虫Sitodiplosis mosellana（Gehin）是小麦生产上的主要害虫，在我国北方麦区广泛分布。近些年来，受全球气候变化、耕作制度改变、小麦品种更换、人类活动及其他因素的影响，麦红吸浆虫的发生危害不断加重，发生范围不断扩大。这种情况的出现不仅给防治工作带来很大的难度，同时也给我们带来新的思考：麦红吸浆虫新发生区的虫源来自何处？老发生区的虫源为什么会消失？麦红吸浆虫不同地理种群的遗传多样性及遗传结构是否发生了改变？
本研究采用微卫星与线粒体DNA（mtDNA）分子标记相结合的方法，对分布在我国的麦红吸浆虫16个不同地理种群的遗传多样性、遗传结构及种群间的遗传分化程度等进行了分析，并分析了与其相关的影响因素。本研究主要获得以下研究结果：
1.对来自麦红吸浆虫唾腺的1217条EST序列进行了SSR查找、SSR引物设计和多态性引物筛选。结果共找到141个SSR位点，分布于106个unigenes中。在20对能够扩增出稳定目的条带的引物中，有9对表现出多态性。
2.选用4个微卫星位点对麦红吸浆虫16个地理种群的遗传多样性和遗传结构进行分析。结果表明，在4个位点上，共检测到35个等位基因。各地理种群的平均等位基因数为5.75，平均观测杂合度为0.45，平均期望杂合度为0.72，平均等位基因丰富度为5.24，平均多态信息含量为0.59，平均Shannon信息指数为0.62。相关性分析结果表明，等位基因丰富度、期望杂合度和遗传多样性与海拔成负相关（r=-0.629，P <0.01；r=-0.601，P <0.05；r=-0.588，P <0.05），与经度成正相关（r=0.569， P <0.05；r=0.562，P <0.05；r=0.553，P <0.05）。
3.对麦红吸浆虫不同地理种群的4个线粒体基因片段COX3、CytB、ND4和ND5进行PCR扩增并测序分析。结果表明，在16个地理种群中共检测出COX3基因单倍型27种，CytB基因单倍型30种，ND4基因单倍型42种，ND5基因单倍型26种。其中COX3和ND4基因具有较高的遗传变异度，平均核苷酸多样度分别为0.0056和0.0076，变异位点占序列长度的比例分别为4.87%和7.13%。
4.基于微卫星的数据分析，麦红吸浆虫16个地理种群间的遗传相似系数在0.7150~0.9653之间，Nei’s遗传距离在0.0353~0.3355之间，遗传分化系数（FSTs）在0.082~0.132之间。以COX3基因序列数据求得的麦红吸浆虫种群间的遗传分化系数FSTs在0.002~0.883之间，CytB数据的FSTs在0.002~0.688之间，ND4数据的FSTs在0.003~0.552之间，ND5数据的FSTs在0.000~0.883之间。基于两种分子标记的分析表明，麦红吸浆虫大多数地理种群的遗传多样性较高，种群间存在不同程度的遗传分化，尤其是东部区域种群与西部区域种群间的遗传分化非常明显。
5.基于微卫星数据的Nei遗传距离的NJ聚类分析、STRUCTURE遗传结构分析和线粒体DNA单倍型的NJ聚类分析及单倍型网络图的分析等，结果表明，麦红吸浆虫的16个地理种群可划分为2个类群。其中，第1类群在地理分布上主要为来自太行山脉以西的6个种群（HuaX、ZZ、LF、LT、WW和YC），第2类群在地理分布上主要为来自太行山脉以东的10个种群（LY、JN、FN、XS、XT、TJ、BJ、NY、HX和LC）。基于微卫星数据的AMOVA分析结果表明，大部分的遗传变异来自种群内，小部分的遗传变异来自类群内种群间和类群间；基于线粒体DNA的AMOVA分析结果表明，大部分的遗传变异来自类群间和种群内，小部分的遗传变异来自于类群内种群间。相关性分析结果表明，环境因子（地理因子和气候因子）对麦红吸浆虫不同地理种群的遗传多样性、种群间的遗传分化程度和遗传结构的形成等均具有一定的影响。Mantel检测结果表明，麦红吸浆虫各地理种群间的遗传距离与地理距离间存在显著的相关性。
6.基于微卫星数据的瓶颈效应分析结果显示，我国的麦红吸浆虫种群在过去较近的历史时期内没有经历瓶颈效应。4个mtDNA的核酸错配分布分析及中性检验的结果表明，麦红吸浆虫群体的核酸错配分布为双峰模式，Tajima’s D和Fu’s Fs中性检验值总体上均不显著（P>0.05），表明麦红吸浆虫群体在过去较近的历史时期内没有经历种群扩张事件，群体大小保持相对稳定。
本研究为了解我国北方麦区麦红吸浆虫的发生和扩散趋势提供了理论依据，为揭示其成灾规律、预测预报和开展有效的综合防治提供了重要的参考，同时也为进一步了解其对环境的适应性和进化机制提供帮助。
The wheat midge (or orange wheat blossom midge), Sitodiplosis mosellana (Gehin), is a major pestof wheat production, and occurs throughout the wheat-producing areas of north China. In recent years,the damage to wheat crops by this pest has increased significantly, and the scope of its occurrence hasbeen expanded by global climate change, farming systems change, replacement of wheat varieties,human activities and other factors. This phenomenon not only brings great difficulty to prevention andcontrol of this pest, but also brings us new thinking: Where the new insect source came from? Why didthis pest in the old region disappear? Whether the genetic diversity and genetic structure of this pestchanged or not?
In this research, genetic diversity, population structure and genetic differentiation of16geographical populations of S. mosellana were analyzed using both microsatellite and mitochondrialDNA markers. The primary achievements of this dissertation are listed as follows:
1.141SSRs, distributed in106unigenes, were found from a total of1217EST sequences from thesalivary glands of S. mosellana.26SSRs primers were designed and screened. Results showed that thestable target band could be amplified from20pairs of them, and9were detected polymorphisms.
2. Four microsatellite loci were used for the analyses of genetic diversity and genetic structure in S.mosellana populations. A total of35alleles were detected. The average number of alleles per populationwas5.75. The average observed and expected heterozygosity were0.45and0.72, respectively. Themean allelic richness was5.24. The average polymorphism information content was0.59and theaverage shannon information index was0.62. Correlation analyses showed that allele richness, expectedheterozygosity and genetic diversity were negatively correlated with altitude (r=-0.629, P <0.01; r=-0.601, P <0.05; r=-0.588, P <0.05), and positively correlated with longitude (r=0.569, P <0.05; r=0.562, P <0.05; r=0.553, P <0.05).
3. Four mitochondrial genes including COX3, CytB, ND4and ND5fragments were amplified fromdifferent geographic populations of S. mosellana, and analyzed with the nucleotide sequences. A total of27haplotypes were observed in COX3,30haplotypes in CytB,42haplotypes in ND4and26haplotypesin ND5, respectively. The results showed higher genetic diversity in COX3and ND4genes. The averagenucleotide diversity of them were0.0056and0.0076, respectively, and the proportion of variable siteswere4.87%and7.13%of the full sequence length, respectively.
4. With microsatellite DNA markers, Nei's genetic identity between populations ranged from0.7150to0.9653, Nei's genetic distance ranged from0.0353to0.3355and the pairwise geneticdifferentiation (FSTs) ranged between0.082and0.132. The pairwise genetic differentiation (FSTs) inCOX3ranged between0.0024and0.8833, between0.002and0.688in Cytb, between0.003and0.552in ND4, and between0.000and0883in ND5. Based on the analyses of two molecular markers, thegenetic diversity among most populations was high. The genetic differentiation varied among differentpairwise populations, and this phenonmenon was especially obvious between these populations of theeastern region and that of the western region.
5. Analyses based on two molecular markers showed that16geographical populations of S.mosellana could be divided into two groups. The analysis of molecular variance (AMOVA) based onmicrosatellite markers showed that most of the genetic variation was from individuals, only a small partfrom populations and groups. AMOVA analyses based on mtDNA markers indicated that most of thegenetic variation was from groups and individuals, and only a small part from populations. Thecorrelation analysis showed that environmental factors (geographic factors and climatic factors) hadgreat influence on the genetic diversity, genetic differentiation and genetic structure of differentgeographical populations of S. mosellana. Mantel test results showed there was a significant correlationbetween genetic distances and geographic distances among pairwise populations.
6. Bottleneck analysis (microsatellite data) revealed no bottleneck in the recent past among S.mosellana populations. Mismatch distribution analysis (mtDNA) showed bimodel. Results of Tajima’sD and Fu’s Fs neutrality tests (not significant, P>0.05)(mtDNA) implied there might not be apopulation expansion in recent time, and S. mosellana populations was at demographic equilibrium.
This study provides a theoretical basis for understanding the occurrence and diffusion trend of S.mosellana in northern China, the important references for revealing the disaster law, forecasting andeffectively comprehensive prevention and control of this pest, and helps to understand the adaptabilityto the environment and evolution mechanism of this pest.
本研究采用微卫星与线粒体DNA（mtDNA）分子标记相结合的方法，对分布在我国的麦红吸浆虫16个不同地理种群的遗传多样性、遗传结构及种群间的遗传分化程度等进行了分析，并分析了与其相关的影响因素。本研究主要获得以下研究结果：
1.对来自麦红吸浆虫唾腺的1217条EST序列进行了SSR查找、SSR引物设计和多态性引物筛选。结果共找到141个SSR位点，分布于106个unigenes中。在20对能够扩增出稳定目的条带的引物中，有9对表现出多态性。
2.选用4个微卫星位点对麦红吸浆虫16个地理种群的遗传多样性和遗传结构进行分析。结果表明，在4个位点上，共检测到35个等位基因。各地理种群的平均等位基因数为5.75，平均观测杂合度为0.45，平均期望杂合度为0.72，平均等位基因丰富度为5.24，平均多态信息含量为0.59，平均Shannon信息指数为0.62。相关性分析结果表明，等位基因丰富度、期望杂合度和遗传多样性与海拔成负相关（r=-0.629，P <0.01；r=-0.601，P <0.05；r=-0.588，P <0.05），与经度成正相关（r=0.569， P <0.05；r=0.562，P <0.05；r=0.553，P <0.05）。
3.对麦红吸浆虫不同地理种群的4个线粒体基因片段COX3、CytB、ND4和ND5进行PCR扩增并测序分析。结果表明，在16个地理种群中共检测出COX3基因单倍型27种，CytB基因单倍型30种，ND4基因单倍型42种，ND5基因单倍型26种。其中COX3和ND4基因具有较高的遗传变异度，平均核苷酸多样度分别为0.0056和0.0076，变异位点占序列长度的比例分别为4.87%和7.13%。
4.基于微卫星的数据分析，麦红吸浆虫16个地理种群间的遗传相似系数在0.7150~0.9653之间，Nei’s遗传距离在0.0353~0.3355之间，遗传分化系数（FSTs）在0.082~0.132之间。以COX3基因序列数据求得的麦红吸浆虫种群间的遗传分化系数FSTs在0.002~0.883之间，CytB数据的FSTs在0.002~0.688之间，ND4数据的FSTs在0.003~0.552之间，ND5数据的FSTs在0.000~0.883之间。基于两种分子标记的分析表明，麦红吸浆虫大多数地理种群的遗传多样性较高，种群间存在不同程度的遗传分化，尤其是东部区域种群与西部区域种群间的遗传分化非常明显。
5.基于微卫星数据的Nei遗传距离的NJ聚类分析、STRUCTURE遗传结构分析和线粒体DNA单倍型的NJ聚类分析及单倍型网络图的分析等，结果表明，麦红吸浆虫的16个地理种群可划分为2个类群。其中，第1类群在地理分布上主要为来自太行山脉以西的6个种群（HuaX、ZZ、LF、LT、WW和YC），第2类群在地理分布上主要为来自太行山脉以东的10个种群（LY、JN、FN、XS、XT、TJ、BJ、NY、HX和LC）。基于微卫星数据的AMOVA分析结果表明，大部分的遗传变异来自种群内，小部分的遗传变异来自类群内种群间和类群间；基于线粒体DNA的AMOVA分析结果表明，大部分的遗传变异来自类群间和种群内，小部分的遗传变异来自于类群内种群间。相关性分析结果表明，环境因子（地理因子和气候因子）对麦红吸浆虫不同地理种群的遗传多样性、种群间的遗传分化程度和遗传结构的形成等均具有一定的影响。Mantel检测结果表明，麦红吸浆虫各地理种群间的遗传距离与地理距离间存在显著的相关性。
6.基于微卫星数据的瓶颈效应分析结果显示，我国的麦红吸浆虫种群在过去较近的历史时期内没有经历瓶颈效应。4个mtDNA的核酸错配分布分析及中性检验的结果表明，麦红吸浆虫群体的核酸错配分布为双峰模式，Tajima’s D和Fu’s Fs中性检验值总体上均不显著（P>0.05），表明麦红吸浆虫群体在过去较近的历史时期内没有经历种群扩张事件，群体大小保持相对稳定。
本研究为了解我国北方麦区麦红吸浆虫的发生和扩散趋势提供了理论依据，为揭示其成灾规律、预测预报和开展有效的综合防治提供了重要的参考，同时也为进一步了解其对环境的适应性和进化机制提供帮助。
The wheat midge (or orange wheat blossom midge), Sitodiplosis mosellana (Gehin), is a major pestof wheat production, and occurs throughout the wheat-producing areas of north China. In recent years,the damage to wheat crops by this pest has increased significantly, and the scope of its occurrence hasbeen expanded by global climate change, farming systems change, replacement of wheat varieties,human activities and other factors. This phenomenon not only brings great difficulty to prevention andcontrol of this pest, but also brings us new thinking: Where the new insect source came from? Why didthis pest in the old region disappear? Whether the genetic diversity and genetic structure of this pestchanged or not?
In this research, genetic diversity, population structure and genetic differentiation of16geographical populations of S. mosellana were analyzed using both microsatellite and mitochondrialDNA markers. The primary achievements of this dissertation are listed as follows:
1.141SSRs, distributed in106unigenes, were found from a total of1217EST sequences from thesalivary glands of S. mosellana.26SSRs primers were designed and screened. Results showed that thestable target band could be amplified from20pairs of them, and9were detected polymorphisms.
2. Four microsatellite loci were used for the analyses of genetic diversity and genetic structure in S.mosellana populations. A total of35alleles were detected. The average number of alleles per populationwas5.75. The average observed and expected heterozygosity were0.45and0.72, respectively. Themean allelic richness was5.24. The average polymorphism information content was0.59and theaverage shannon information index was0.62. Correlation analyses showed that allele richness, expectedheterozygosity and genetic diversity were negatively correlated with altitude (r=-0.629, P <0.01; r=-0.601, P <0.05; r=-0.588, P <0.05), and positively correlated with longitude (r=0.569, P <0.05; r=0.562, P <0.05; r=0.553, P <0.05).
3. Four mitochondrial genes including COX3, CytB, ND4and ND5fragments were amplified fromdifferent geographic populations of S. mosellana, and analyzed with the nucleotide sequences. A total of27haplotypes were observed in COX3,30haplotypes in CytB,42haplotypes in ND4and26haplotypesin ND5, respectively. The results showed higher genetic diversity in COX3and ND4genes. The averagenucleotide diversity of them were0.0056and0.0076, respectively, and the proportion of variable siteswere4.87%and7.13%of the full sequence length, respectively.
4. With microsatellite DNA markers, Nei's genetic identity between populations ranged from0.7150to0.9653, Nei's genetic distance ranged from0.0353to0.3355and the pairwise geneticdifferentiation (FSTs) ranged between0.082and0.132. The pairwise genetic differentiation (FSTs) inCOX3ranged between0.0024and0.8833, between0.002and0.688in Cytb, between0.003and0.552in ND4, and between0.000and0883in ND5. Based on the analyses of two molecular markers, thegenetic diversity among most populations was high. The genetic differentiation varied among differentpairwise populations, and this phenonmenon was especially obvious between these populations of theeastern region and that of the western region.
5. Analyses based on two molecular markers showed that16geographical populations of S.mosellana could be divided into two groups. The analysis of molecular variance (AMOVA) based onmicrosatellite markers showed that most of the genetic variation was from individuals, only a small partfrom populations and groups. AMOVA analyses based on mtDNA markers indicated that most of thegenetic variation was from groups and individuals, and only a small part from populations. Thecorrelation analysis showed that environmental factors (geographic factors and climatic factors) hadgreat influence on the genetic diversity, genetic differentiation and genetic structure of differentgeographical populations of S. mosellana. Mantel test results showed there was a significant correlationbetween genetic distances and geographic distances among pairwise populations.
6. Bottleneck analysis (microsatellite data) revealed no bottleneck in the recent past among S.mosellana populations. Mismatch distribution analysis (mtDNA) showed bimodel. Results of Tajima’sD and Fu’s Fs neutrality tests (not significant, P>0.05)(mtDNA) implied there might not be apopulation expansion in recent time, and S. mosellana populations was at demographic equilibrium.
This study provides a theoretical basis for understanding the occurrence and diffusion trend of S.mosellana in northern China, the important references for revealing the disaster law, forecasting andeffectively comprehensive prevention and control of this pest, and helps to understand the adaptabilityto the environment and evolution mechanism of this pest.
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