Puttamadanayaka Shashikumara, Balaramaiah Manu, Biradar Sunil, Parmeshwarappa Sunilkumar V, Sinha Nivedita, Prasad S V Sai, Mishra P C, Jain Neelu, Singh Pradeep Kumar, Singh Gyanendra Pratap, Prabhu Kumble Vinod
ICAR-Indian Grassland and Fodder Research Institute, Jhansi, 284003, India.
ICAR-Indian Agricultural Research Institute, New Delhi, 110 012, India.
Sci Rep. 2020 Dec 10;10(1):21646. doi: 10.1038/s41598-020-78671-x.
Identification of markers associated with major physiological and yield component traits under moisture deficit stress conditions in preferred donor lines paves the way for marker-assisted selection (MAS). In the present study, a set of 183 backcross inbred lines (BILs) derived from the cross HD2733/2*C306 were genotyped using 35K Axiom genotyping array and SSR markers. The multi-trait, multi-location field phenotyping of BILs was done at three locations covering two major wheat growing zones of India, north-western plains zone (NWPZ) and central zone (CZ) under varying moisture regimes. A linkage map was constructed using 705 SNPs and 86 SSR polymorphic markers. A total of 43 genomic regions and QTL × QTL epistatic interactions were identified for 14 physiological and yield component traits, including NDVI, chlorophyll content, CT, CL, PH, GWPS, TGW and GY. Chromosomes 2A, 5D, 5A and 4B harbors greater number of QTLs for these traits. Seven Stable QTLs were identified across environment for DH (QDh.iari_6D), GWPS (QGWPS.iari_5B), PH (QPh.iari_4B-2, QPh.iari_4B-3) and NDVI (QNdvi1.iari_5D, QNdvi3.iari_5A). Nine genomic regions identified carrying major QTLs for CL, NDVI, RWC, FLA, PH, TGW and biomass explaining 10.32-28.35% of the phenotypic variance. The co-segregation of QTLs of physiological traits with yield component traits indicate the pleiotropic effects and their usefulness in the breeding programme. Our findings will be useful in dissecting genetic nature and marker-assisted selection for moisture deficit stress tolerance in wheat.
在优良供体系中鉴定与水分亏缺胁迫条件下主要生理和产量构成性状相关的标记，为标记辅助选择（MAS）铺平了道路。在本研究中，利用35K Axiom基因分型芯片和SSR标记对一组由HD2733/2*C306杂交衍生的183个回交自交系（BILs）进行基因分型。在印度两个主要小麦种植区，即西北平原区（NWPZ）和中部区（CZ）的三个地点，在不同水分条件下对BILs进行了多性状、多地点的田间表型分析。利用705个SNP和86个SSR多态性标记构建了连锁图谱。共鉴定出43个基因组区域以及QTL×QTL上位性互作，涉及14个生理和产量构成性状，包括归一化植被指数（NDVI）、叶绿素含量、冠层温度（CT）、冠层导度（CL）、株高（PH）、孕穗期单株干重（GWPS）、千粒重（TGW）和产量（GY）。2A、5D、5A和4B染色体上这些性状的QTL数量较多。在不同环境中鉴定出7个稳定的QTL，分别为DH（QDh.iari_6D）、GWPS（QGWPS.iari_5B）、PH（QPh.iari_4B-2、QPh.iari_4B-3）和NDVI（QNdvi1.iari_5D、QNdvi3.iari_5A）。鉴定出9个基因组区域携带CL、NDVI、相对含水量（RWC）、旗叶面积（FLA）、PH、TGW和生物量的主要QTL，解释了10.32%-28.35%的表型变异。生理性状QTL与产量构成性状的共分离表明了多效性效应及其在育种计划中的实用性。我们的研究结果将有助于剖析小麦水分亏缺胁迫耐受性的遗传本质并进行标记辅助选择。
