Genetic Model Analysis and QTL Mapping of Agronomic and Quality Traits in Soybean
|School||Henan Agricultural University|
|Course||Crop Genetics and Breeding|
|Keywords||Soybean Agronomic Traits Quality Traits Genetic Model Analysis QTL Localization|
Abstract: In this study 116 lines were a RILs （Recombination Inbreeding Lines） population derived from a cross between Jinbean 23 and Huibuzhi. The genetic map spreads over 27 linkage groups and contains 231 SSR markers was constructed by Liang Hui Zhen. With this map the agronomic and quality traits were genetically analyzed, and developed inheritance models and molecular technology were used to study the above aspects. The main results were described as follows:1. Genetic analysis important agronomic and quality traits of soybeanA mixed major gene plus polygene inheritance model was used to perform the genetic analysis of the agronomic traits and quality related traits of soybean in the RIL population .The joint segregation analysis results showed that:（1） For 100-seed weight and yield, the best fitting model was three major genes （F）;（2）For Bottom pod height, plant height, knob number of main stem, the effective number of branches, pods trait, protein and oil content, all of the best fitting models were two major genes plus polygene （E）.In addition, the genetic parameters of the genetic models for the yield and quality related traits were estimated, the results showed that 100-seed weight and yield were mainly controlled by major gene and was sensitive to the environmental At the same time. what’s more ,the Bottom pod height, knob number of main stem and oil content were mainly controlled by polygene, while plant height, the effective number of branches, pods trait, protein and content were mainly controlled by major genes plus polygene.2. QTL localization of agronomic and quality traitsBy using composite interval mapping （CIM） method, the molecular genetic map was adopted to map and analyze QTL for yield and quality related traits including plant height, Bottom pod height, knob number of main stem, the effective number of branches, pods trait, protein and oil content in soybean.35 QTLs were identified.（1） 4 QTLs were detected for 100-seed weight in 2009 year, they distributed on LGa1,LGd1a and LGm and two QTLs can explained variance 11.99%,10.98%, respectively. 2 QTLs were detected for Bottom pod height, they can explained variance11.08% and 7.43%, respectively. Only 3 QTLs was detected for pods trait, they explained variance range 7.43%-12.18%.3 QTLs were detected for protein content, 2 QTLs of them distributed on LGg and LGh1 can explained variance 10.03%,10.92%, respectively, and the another QTL can explained variance 8.81%. 2 QTLs were detected for oil content, they distributed on LGd1a and LGn explained variance 14.93%.（2） 3 QTLs were detected for 100-seed weight in 2010 year, the QTLs distributed on LGb2,LGh1, LGj2 and LGk3.Only 1 QTL for plant height was detected and distributed on LGb1,that can explained variance14.18%. 8 QTLs for pods number were detected in 2010 year , the QTLs can explained variance range from 7.19% to 19.43%.The QTL of main stem node number at the same loci with plant height QTL. One QTL was detected for the effective number of branches, it distributed on LGd2 and explained variance 14.48%. 4 QTLs were detected for soybean yield in 2010 year, the QTLs distributed on LGa1,LGb1, LGc1.One main QTL was detected for protein content located in LGc2, and its genetic contribution rate is 44.04%.2 QTLs were detected for oil content, they explained variance 6.17% and 6.54%, respectively. Grain weight ratio is an important indicator of soybean economic factors, the study found one QTL located on linkage group h2, which explained variance10.44%, its additive effect is negative.4 QTLs for soybean yield were identified,they distributed on LGa1,LGb1 and LGc1 and explained variance range from 8.79%-18.47%. 3. Results for correlation analysis of phenotypicCorrelation analysis of field performance indicated that, a positive correlation was existed between yield and plant height, main stem node number, the effective number of branches, pods and seed weight ratio.the knob number of main stem nodes to grain weight, bottom pod height, plant height were significant positive correlation. Bottom pod height and three pod were significant negative correlation. The effective branch number to pods trait （except for four pod） were significantly positive correlation. Three pod to protein content was negatively correlated. Between protein content and fat content also had significant negative correlation. However, the inconsistent results or even opposite results were found in data analysis of two years, which maybe related to the environment.