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Phenotypic Evaluation And QTL Mapping For Tillering-related Traits In Lowland Switchgrass

Posted on:2017-08-02Degree:DoctorType:Dissertation
Country:ChinaCandidate:D ChangFull Text:PDF
GTID:1363330542985594Subject:Grassland
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Switchgrass(Panicum virgatum L.)is a perennial tall grass classified into Panicum in Gramineae.It has been selected as a model species by the U.S.Department of Energy for producing biofuel feedstock.As cellulosic bioenergy plants,yield and quality are the two important standards for selection,greatly improving biomass yield was the primary goal for bredding bioenergy varieties in switchgrass.Agronomic components of switchgrass were valued differently due to various effects of each trait on its biomass yield.Plant tillering related traits are morphologically important components contributing to switchgrass biomass yield.A first generation selfed population of 'NL94' plant including 265 individuals and a hybrid population including 176 progenies between 'NL94' and'SL93'plants were field established in a randomized complete block design with three replications in Stillwater and Perkins,OK.Total 8 tillering related traits including plant base size,plant girth,tillering ability,tiller diameter,node number/tiller,tiller dry weight,plant vigor and spring green-up were evaluated morphologically and identified quantitative trait loci(QTLs).Phenotypic data were collected from two to four years and genotypic data were obtained by genotyping 74 and 100 simple sequence repeat(SSR)markers selected from hybrid and selfed preexisting genetic maps,respectively.The objectives of this study were to characterize tillering related traits,estimate broad-sense heritabilities for tillering related traits,analyze correlations between biomass yield and the traits and to identify quantitative trait loci(QTLs)for them.The findings add to the knowledge base regarding the genetics of tillering related traits that could be used in accelerating the development of high yielding cultivars through marker-assisted selection and aiding further identification for the major QTL of higher generation population.The major results are as follows:1.Linkage groups(LGs)with increased genotypic data by selecting SSR markers flanking significant QTLs identified from two preexisting genetic maps were reconstrcuted for hybrid and selfed population.The identified 74 markers from hybrid population and 100 markers from selfed population were genotyped and produced 11 new LGs for each of the two populations.The LGs of the hybrid population consisted of 1a,1b,2a,2b,3 a,3b,5a,5b,6b,8b,9a while the LGs of the selfed population included 1a,2a,2b,3b,5a,5b,6b,7a,8a,9a and 9b.2.In order to evaluate phenotypic diversity and characteristics of these tillering related traits in two populations and provide information for switchgrass breeding research as well as its production and utilization,phenotypic data of the 8 tillering related traits were collected in different environments of years and locations and analysed for morphological variation.The results showed large genetic variation existed in these tillering related traits in both individual and joint environments.Phenotypic variation also indicated heterosis in hybrid popualtion and selfing depression in selfed population.Larger genetic variation in hybrid population than selfed population was also resulted from these variation analysis.3.The significance of differences for variance components were examined by analysis of variance(ANOVA).The results showed the 8 tillering related traits were sensitive to different environments in both the hybrid population and selfed populations.Significant genotype × environment interactions effects were detected between the traits and environments.And genotypic variation was significant or extremely significant for all the traits in the two populations.Totally variation of variance components for node number/tiller was not significant as other tillering related traits in this study.Compared to other variance components,the variation of year,location and genotype×year×location was not significant as other sources in both two populations.4.Correlations analysis were performed between biomass yield and the traits in hybrid and selfed population,respectively.The results showed plant base size and plant vigor were significantly associated with biomass yield in all environmental analysis in the two populations and higher correlation coefficients between the two traits and biomass yield were calculated from the analysis.Based on the results,plant base size and plant vigor were recommended as indirect selection methods for improving biomass yield in switchgrass.Node number/tiller was not significantly correlated with biomass yield in the two populations indicated the trait was relatively independent to biomass yield.5.Broad-sense heritability were calculated by estimating the environmental and genetic effects portion controlling the tillering related traits under different growth conditions.The stability of heritability for some traits showed consistence in the two populations.Plant base size,tiller diameter,tiller dry weight and plant vigor showed middle to high heritability and good stability based on individual and joint environments analysis in the two populations.Node number/tiller showed lower heritability and poor stability almost in all environments analysis both in the two populations.6.Genotypic data and phenotypic data of individual and joint environments within each population were used for finding stable QTLs of the tillering related traits.Twenty-six QTLs including 10 high frequency QTLs and 28 QTLs including 14 high frequency QTLs for the tillering related traits were identified by both interval mapping(IM)model Multiple-QTL model(MQM)in the hybrid population and selfed population,respectively.Among the QTLs,two major QTLs were detected from the analysis,one on LG 5a between PVCAG-2197/2198 and PVGA-1649/1650 in the hybrid population and another on LG 9a between PVGA-1405/1406-sww-2364/sww2285 were stably detected in multiple environments and they explained 92.4%and 56.4%phenotypic variation,respectively.
Keywords/Search Tags:Switchgrass, genetic linkagemap, analysis of variance, heritability, correlation analysis, QTL detection
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