Quantitative Trait Locus Analysis Of Bacteria Wilt Resistancein Peanut(Arachis Hypogaea L.)

Cultivated peanut（Arachis hypogaea L.） is one of the most important oilseed and cash crops in China, being a major source of vegetable oil and protein. Bacterial wilt（BW） caused by Ralstonia solanacearum is one of the important diseases affecting peanut production in China. Breeding and planting resistant cultivars are the best approach to manage the disease. However, the available BW-resistant peanut cultivarshave lower yield, poor quality and undesirable resistance to other diseases. In oreder to reveal genetic basis and identification of quantitative trait loci（QTLs） for BW resistance, 57 peanut cultivars were used to identify SSR makers associated with bacterial wilt resistance through correlation analysis. Recombinant inbred line（RIL） mapping population derived from Yuanza 9102 and Xuzhou 68-4, were also used to identify QTLs for bacterial wilt resistance. The main results were as follows.1. A total of 72 polymorphic SSR markers were used to detect the genetic diversity of 57 peanut cultivars with different resistance to bacterial wilt. According to UPGMA cluster analysis, the 57 cultivars were clustered into two groups when the threshold valve of coefficients of genetic similarity was 0.69. The clustering result of the 57 cultivars by SSR data was highly consistent with the botanical type and resistance. The genetic diversity among the resistant cultivars was slightly greater than that of the susceptible cultivars. A total of 10 SSR loci related to BW resistance were detected through correlation analysis and multiple linear regression analysis, among which, 3 loci including 1B9-3, IPAHM288-1 and ARS590-1 were highly significantly associated with the BW resistance.2. The phenotyping trials showed higher resistance index in Yuanza 9102（resistant parent） and lower index in Xuzhou 68-4（susceptible parent）. As to the RILs, wide range of BW resistance was observed. Analysis of variance of the phenotypic data showed that genotype effect（G）, environment effect（E） and genotype × environment interaction effect（GE） had significant effect on the resistance, but the genetic factors were dominating. The frequency distribution of the two years for BW resistance showed a bimodal distribution and skewed distribution for the parents. A genetic linkage map was constructed with 744 SSR loci out of 821 SSR loci. It comprised 22 LGs and covered a total length of 1241.95 cM, with an average maker density of 1.66 cM. The map has good consistency with previously published intergrative maps and has relatively high marker number in a single mapping population of peanut.3. QTL analysis was performed for BW resistance through windows QTLCartographer and QTLNETWORK. Using windows QTLCartographer, a total of 19 QTLs were identified and QTL qBWRB02.12014, qBWRB02.42015 and qBWRB02.3mean were repeatedly detected in all the three settings（BW₂014,BW₂015, BW_mean） franked by AGGS1592 and AHTE0775, with PVE of 6.91-18.68%. Using QTLNETWORK, a total of 14 QTLs were detected and QTL qBWRB02.12014, qBWRB02.12015, qBWRB02.1two-year were repeatedly detected in all the three settings（BW₂014, BW₂015, BW_two-year） franked by GM2196 and AHGS2344, with PVE of 25.91-28.72%. The interval AGGS1592- AHTE0775 was closed to the interval GM2196- AHGS2344, indicating that there would be a major effective QTL for BW resistance located on the interval. Through comprehensive analysis of the markers identified using cultivar population and RIL population, marker 1B9（corresponding to 1B9-3） located at 56.242 cM on B02 was near to the main QTL interval AGGS1592- AHTE0775 and GM2196-AHGS2344. Marker ARS590（corresponding to ARS590-1） located at 69.838 cM on B05, was near to the interval AHGS0729-1-AGGS2216 of QTL qBWRB05.1Mean and the interval AHGS1672-TC19E1 of QTL qBWRB05.1Two-year. The results revealed that the markers identified for BW resistance were reliable.4. Through comprehensive analysis of the QTLs for BW resistance and the QTLs previously detected for yield-related traits, it was cleared that the QTLs for BW resistance located on A05, B05 and B02 possessed overlapping interval, or nearby interval with the QTLs for yield related traits. In the interval AGGS1592- AHTE0775 on B02, QTLs for both BW and for yiled-related traits were detected. Meanwhile, in this interval the additive effect of QTLs for BW resistance was positive butfor seed weight（SW） and hundred seed weight（HSW） was negative, which might indicate that the QTLs of BW resistance and the QTLs for yield-related traits were negative correlated. In the interval A5460-AGGS1233 on A05, QTLs for BW resistance were detected as well as for seed length（SL）, SW and HSW, and in the interval AHGS0729-1- AGGS2216 on B05, QTLs for BW resistance were detected and QTLs for SL and HSW. In these intervals, the additive of QTLs for BW resistance and QTLs for yield-related traits were positive. The results would be useful in breeding parent selection and developing molecular breeding techniques in peanut.