Genetic Analysis And QTL Mpping Of Seed And Seedling Rincipal Traits In Cucumber

Seed and seedling traits are important horticultural traits of cucumber, and can influence thedevelopment of plant. However, there are few genetic reports about seed and seedling characters, andthe correlation researches are rarely reported in detail. In this study, positive and negative cross sixgenerations and a160recombinant inbred line (RILs), stemmed from a cross between PI183967andNorthern Chinese inbred line931, were used to identify the genetic inherence combining the jointsegregation analysis model. A SSR genetic map was constructed using the SSR molecular markertechnology to finish QTL mapping of seed traits (seed length (Sl), seed width (Swd) and100-seedweight(100-Swt)) and seedling principal traits (cotyledon length (Cl), cotyledon width (Cw), hypocotyllength (Hl), first true leaf length (Fll), first true leaf width (Flw), aboveground fresh biomass (Afb) andaboveground dry biomass (Adb). Results were as followings in detail:(1) By the method of joint segregation analysis, results showed that traits of Sl and Swd in positiveand negative six generations, Cl, Cw, Fll, Flw and Afb in positive six generations and Hl, Adb innegative six generations all fitted into C-0(Additive dominance-epistasis polygene inheritancemodel).Combining the frequency distributions of RIL population, we first identified that seed andseedling traits were controlled by multiple genes. Pearson correlation analysis of seed and seedlingprincipal traits in RILs showed that there existed dramatic relations between seed and seedling traits.(2) By screening2112SSR markers, we obtained1125polymorphic SSRs with53.2%polymorphicrate. The genetic map contained307SSR markers which spanned993.3cM, and average distance ofmarkers was3.23cM. In addition, each linkage was correspondent with each chromosome of cucumber.(3) In all, we detected49QTLs including13QTLs for seed traits and36QTLs for seedling traits.These QTLs were located on the Chr.1,2,3,5,6with7.6to23.6%of observed phenotypic variation,and LOD between2.50and9.21. In addition,31QTLs which could explain over10%contribution rateaccounted for63.3%of all the QTLs, and9QTLs could be detected in different environments.(4) QTLs of seed length and100-seed weight could be detected in2012and2013spring including Sl4.1(SSR11074-SSR07431) on Chr.4and Sl5.1(SSR15321-SSR07711) on Chr.5for seed length,100Swt1.1(SSR12070-SSR17184) on Chr.1and100Swt2.1(SSR05743-SSR13131) on Chr.2for100-seed weight.(5) Cl5.3, Hl2.1, Flw5.1, Afb5.1and Adb5.1could be detected in different environments. Theremight exist some relative genes in the three regions SSR23148-SSR00182, SSR15321-SSR07711andSSR14436-SSR10542, which could control the seeding traits.(6) Combining the results of genome predicted annotation, we focused on the gene prediction of majorQTLs associated with seedling principal traits. There were487candidate genes between SSR00030andSSR10522. The markers SSR23148-SSR00182of Cl5.1,Cw5.1and Hl5.1, there were205candidate genes.However, we could not assure the relationship between candidate genes and seedling traits. Therefore, somefurther research to identify the most impossible genes are needed to carry out.