Mapping And Analysis Of QTLs For Agronomic And Quality Traits Using RIL Population Of “shanhua15×zhonghua12” In Peanut(arachis Hypogaea L.)

In recent years,peanut has drawn more and more attentions to its high yield and high quality.While increasing the yield of peanut,increasing the oil content and oleic acid content of peanuthas become the main breeding goal for modern agriculture.QTL mapping for yield,quality and other related traits has important theoretical significance and application value,which can provide a reference for high yield and quality breeding of peanut.In this study,a recombinant inbred line population of 441 lines,derived from a cross between variety Shanhua15(P1)and varietyZhonghua12(P2).was used to construct a peanut genetic map,and identify QTLs for 31 plants,pods,leaves,and quality traits in three years(2014 to 2016).The main results were as follows:1?On the basis of F5-7 RIL(recombinant inbred lines)population derived from Shanhua15×Zhonghua12,statistic analysis was made aiming at 31 agronomic and quality traits,the result showed that:all the agronomic traits and quality appears continuous variation and normal distribution.So those traits belong to quantitative traits,they are suitable to analyze the genetic development and QTL location.2?A genetic linkage map of cultivated peanut was constructed by Join Map 4.0.The map consisted of 96 simple sequence repeat markers in 23 linkage groups,had a total length of 1582.88 cM with average and minimum marker intervals of 16.49 and 1.7 cM.Among the 23 linkage groups,LG01 ~ LG11 were located on the chromosome A01 ~ A10,LG12 ~ LG23 were located on the chromosome B01 ~ B09.3?QTL identification for all 30 agronomic and qulity traits were identified by using ICIM model(Inclusive Composite Interval Mapping)in QTL Ici Mapping V4.0.A total of 241 QTLs were detected in three environments.including fourteen for main stem height,seventeen for lateral branch length,eleven for total branching number,four for pod length,one for pod width,four forpod shell thickness,one forsingle-pod weigh,four forsingle-seed weigh,three for leaf length,fives forleaf width,one for chlorophyll content,eleven for oil content,eleven for crude protein content,thirteen for oleic acid content,thirteen for linoleic acid content,fives for arachidic acid content,nine for behenic acid content,six for stearic acid content,six for palmitic acid content,nine for phenylalanine content,fives for methionine content,twelve for arginine content,ten for lysine content,eleven for leucine content,fives for proline content,ten for threonine content,eleven for valine content,ten for isoleucine content,four for histidine content.every single QTL explained 1.04%~9.59% of the phenotypic variation explained(PVE).Twenty QTLs were detected in two environments: one for main stem height,two for lateral branch length,one for total branching number,one for leaf length,one for pod length,two for oil content,one for oleic acid content,one for linoleic acid content,one for behenic acid content,one for tetradecanoic acid content,one for phenylalanine acid content,two for arginine acid content,one for leucine acid content,two for threonine acid content.Three QTLs were detected in three environments: one for main stem height,each QTLexplained 4.74%~7.95%;one for lateral branch length,each QTLexplained 3.06%~7.58%;one forcrude protein content,each QTLexplained 4.02%~5.71%.We also detected thirty-nineareas which associated with more than one trait.Seven areas associated with four to eight traits.Multiple trait QTLs were co-segregated with eight markers.The area AHGS1776 ~ AHGS2335_c1,five QTLs were co-segregation from the mark AHGS1776;the area AHGS1627_c1 to TC1E01_c1,six QTLs were co-segregation from the mark AHGS1776.