| 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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