摘要
玉米叶面积的大小及分布特征不仅影响其光合效率、蒸腾速率,而且与其耐旱性、耐密性、抗倒伏性及产量形成紧密相关。深入剖析不同水旱环境下玉米不同生育时期不同叶位叶面积的分子遗传机理对玉米耐旱高产新品种的选育具有重要意义。本研究以构建的2套F_(2∶3)群体为试材,在8种水分环境下,采用复合区间作图法(CIM)和基于混合线性模型的复合区间作图法(MCIM)对玉米相应叶(V_(18)时期第10片叶、R_1时期穗三叶)叶面积进行单环境和多环境联合QTL分析;参考玉米基因组B73 RefGen_v3挖掘稳定表达的QTLs(sQTLs)区间内的候选基因,并对其进行功能分析。结果表明,采用CIM法,单环境下2个生育时期2套F_(2∶3)群体间总共定位到了7个玉米相应叶叶面积QTLs,主要受显性(81.0%)、部分显性(14.3%)和超显性(4.7%)等遗传效应的调控,其中在干旱环境下定位到了5个QTLs。采用MCIM法,在2套F_(2∶3)群体间总共检测到6个相应叶叶面积的联合QTLs,其中1个表现为显著的QTL与环境的互作(QTL×E,Bin 2.08~2.09),1对QTLs(Bin 1.08~1.10与Bin 2.08~2.09)参与了显著的加性与加性(AA)上位性互作。结合CIM和MCIM法进一步分析在2套F_(2∶3)群体间检测到了6个sQTLs,其分别位于Bin 1.08~1.10、Bin 2.08~2.09、Bin 4.08~4.09、Bin 6.05、Bin 8.03和Bin 10.03处,并在这些sQTLs区间内确定了12个玉米叶发育相关候选基因。采用生物信息学,总共收集了75个玉米叶发育相关候选基因,通过系统进化树分析表明,这些候选基因划分为3大进化分支,且上述检测到的12个候选基因分布于这3大进化分支上。这些结果为系统地解析玉米不同生育时期不同水旱环境下相应叶叶面积的分子遗传机理提供理论依据,检测到的sQTLs可作为叶面积改良的重要染色体区段,检测到的候选基因为其进一步克隆、功能分析及育种应用提供了信息参考。
Leaf area(LA)and its distribution influences the efficiency of photosynthesis and transpiration rate,and is also closely related to drought tolerance,planting density,degree of lodging and grain yield in maize(Zea mays).Indepth analysis of the molecular mechanisms controlling LA under different moisture levels at different growth stages is of great significance for the breeding of drought tolerant and high-yielding new maize varieties.In this study,composite interval mapping(CIM)and mixed linear model mapping based on composite interval mapping(MCIM)was carried out across two F2∶3 populations under eight different‘environments’.Specifically,experiments were set up in Gansu Province between 1508 and 1785 m altitude at Wuwei and Zhangye in 2014 and Gulang and Jingtai in 2015,and each of the four experiments had contrasting fully watered and moisture deficit treatments.Quantitative trait loci(QTLs)for LA(determined by measuring the 10th-12th leaves in late vegetative and three ear-leaves in early reproductive growth stages)were analyzed in single environments and across all environments.The candidate genes in the stable QTLs(sQTLs)were identified and the corresponding gene functions were determined using the reference genome B73 RefGenv3.A total of seven QTLs were identified by CIM mapping cross vegetative and reproductive growth stages of the two F_(2∶3) populations in all eight environments,five of these in fully watered treatments,five in moisture deficit treatments and three shared by both fully watered and moisture deficit treatments.These QTLs exhibited dominance(81.0%),partial-dominance(14.3%),and over-dominance(4.7%)effects.Six joint QTLs for LA were found among all environments by joint analysis with MCIM,three from each of the two populations.One QTL was involved in a significant QTL by environment interaction(QTL×E;Bin 2.08-2.09),and one significant epistasis(Bin 1.08-1.10 and Bin 2.08-2.09)was mapped with an additive by additive(AA)effect.Combining CIM and MCIM methods for further analysis,six stable QTLs(sQTLs)were detected in Bin1.08-1.10,Bin 2.08-2.09,Bin 4.08-4.09,Bin 6.05,Bin 8.03,and Bin 10.03,and 12 candidate genes that regulated leaf development in maize were located in these sQTL intervals.From bioinformatic data,75 candidate genes related to leaf development were collected and their phylogenetic tree constructed.The phylogenetic tree of these 75 genes comprised three major evolutionary branches,and the 12 candidate genes identified above were distributed on the three branches.These results lay a foundation for systematic understanding of the molecular mechanisms governing LA in different environments at different plant growth stages.These detected sQTLs identify important genomic regions for LA improvement,and the detected candidate genes can provide reference sequences for further gene cloning,functional analysis,and other breeding applications.
作者
赵小强
钟源
周文期
ZHAO Xiao-qiang;ZHONG Yuan;ZHOU Wen-qi(Gansu Provincial Key Laboratory of Aridland Crop Science,Gansu Agricultural University,Lanzhou 730070,China;Crop Research Institute,Gansu Academy of Agricultural Sciences,Lanzhou 730070,China)
出处
《草业学报》
CSCD
北大核心
2021年第5期103-120,共18页
Acta Prataculturae Sinica
基金
甘肃农业大学甘肃省干旱生境作物学重点实验室开放基金(GSCS-2019-8,GSCS-2020-5)
国家自然科学基金项目(32060486)
甘肃农业大学科技创新基金-公招博士科研启动基金(GAU-KYQD-2018-19,GAU-KYQD-2018-12)
甘肃省高等学校创新能力提升项目(2019A-052
2019A-054)
兰州青绿仪器技术有限公司横向项目(WT20191025)资助。
