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玉米持绿相关QTL整合图谱构建及一致性QTL区域内候选基因发掘
引用本文:方永丰,李永生,白江平,慕平,孟亚雄,张金林,王汉宁,尚勋武.玉米持绿相关QTL整合图谱构建及一致性QTL区域内候选基因发掘[J].草业学报,2012,21(4):175-185.
作者姓名:方永丰  李永生  白江平  慕平  孟亚雄  张金林  王汉宁  尚勋武
作者单位:甘肃省作物遗传改良与种质创新重点实验室;甘肃省干旱生境作物学重点实验室;甘肃农业大学农学院;兰州大学草地农业科技学院
基金项目:973计划前期研究专项(2012CB722902);甘肃省科技攻关计划项目(2GS064-A41-001-05)资助
摘    要: 以玉米高密度遗传连锁图谱IBM22008Neighbors为参考图谱,收集来自不同实验中的173个玉米持绿相关数量性状位点(quantitativetraitlocus,QTL)信息,利用BioMercator2.1软件,构建出玉米持绿相关QTL 整合图谱;采用元分析技术,在1,4,5,9号染色体上发掘出5个持绿“一致性”QTL 区间。根据“一致性”QTL 区间两端标记在玉米物理图谱B73RefGen_v2上的位置,将“一致性”QTL 区间进行物理图谱定位,利用PlantGDB(http://www.plantgdb.org/)在线区段批量下载工具(downloadregiondata)下载“一致性”区间的1445个预测基因序列并进行生物信息学分析,发现预测基因主要参与具体的细胞过程,执行结合功能,催化、转移酶活性和氧化还原酶活性等分子功能。根据“一致性”QTL 区间的基因位点名称,在NCBI中下载相关基因序列,与所在“一致性”QTL 区 间所有预测基因保守结构域进行比对,在5个“一致性”持绿QTL 区间内初步确定8个持绿相关候选基因。利用GRAMENE 网站(http://www.gramene.org/)的Cmap功能,将水稻持绿基因狊犵狉(staygreen)转定位于玉米物理图谱B73RefGen_v2上,找到与其同源的玉米候选基因GRMZM2G091837_T01,其序列与已发表的玉米衰老诱导叶绿体持绿蛋白基因狊犵狉1序列一致。

关 键 词:玉米  持绿性  数量性状位点(QTL)  整合图谱  元分析
收稿时间:2012-02-20

Construction of integration QTL map and identification of candidate genes for stay-green in maize
FANG Yong-feng,LI Yong-sheng,BAI Jiang-ping,MU Ping,MENG Ya-xiong,ZHANG Jin-lin,WANG Han-ning,SHANG Xun-wu.Construction of integration QTL map and identification of candidate genes for stay-green in maize[J].Acta Prataculturae Sinica,2012,21(4):175-185.
Authors:FANG Yong-feng  LI Yong-sheng  BAI Jiang-ping  MU Ping  MENG Ya-xiong  ZHANG Jin-lin  WANG Han-ning  SHANG Xun-wu
Institution:1.Gansu Key Laboratory of Crop Improvement and Germplasm Enhancement,Lanzhou 730070,China; 2.Gansu Provincial Key Laboratory of Aridland Crop Science,Lanzhou 730070,China; 3.College of Agronomy,Gansu Agricultural University,Lanzhou 730070,China; 4.College of Pastoral Agriculture Science and Technology, Lanzhou University,Lanzhou 730020,China)
Abstract:Leaf senescence is a character of plant development.Delayed leaf senescence or stay green character has received considerable attention because of its negative impact on photosynthesis and its role in nutrient redistribution within the plant.In the past few decades,a wealth of QTLs(quantitative trait locus) mapping data for stay green and its related traits in maize has been produced using molecular marker approaches.In order to unlock the full potential of the information contained in these independent experiments,173 stay-green and related QTLs in maize were collected from maize genomic database(maize GDB),and were compiled to construct the integration QTL map for stay-green in maize(Zea mays).The high-scale genetic linkage map of maize IBM2 2008 Neighbors was used as reference and the map were constructed with BioMercator 2.1 software based on the method of meta analysis.Five consensus QTL for maize stay green were identified on maize chromosomes 1,4,5 and 9,respectively.After project the consensus QTL region on maize physical map of B73 RefGen_v2,a total of 1 445 candidate genes in the consensus QTL region were discovered and downloaded from Plant GDB(http://www.plantgdb.org/).Meanwhile,according to the results of gene ontology analysis,most candidate genes might take part in the cell development,catalytic process,enzymatic activity and other biological progresses.The sequences of eight stay-green candidate genes were identified by comparatively analyzing the sequences of stay-green gene sequence from other crops.Using a syntonic conservation approach,which is used to comparatively analyze the rice genetic map and maize physical map,one rice gene(sgr) that is coding for the senescence-inducible chloroplast stay-green protein was projected onto the physical map of maize B73RefGen_v2.Therefore,the results suggested that this approach provided an useful tool for identifying QTL conferring stay-green and other candidate genes in maize.
Keywords:Zea mays  stay green  quantitative trait locus(QTL)  integration map  meta-analysis
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