DataSheet2_Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis.PDF

The parasitic weed, Striga is a major biological constraint to cereal production in sub-Saharan Africa (SSA) and threatens food and nutrition security. Two hundred and twenty-three (223) F2:3 mapping population involving individuals derived from TZdEI 352 x TZEI 916 were phenotyped for four Striga-adaptive traits and genotyped using the Diversity Arrays Technology (DArT) to determine the genomic regions responsible for Striga resistance in maize. After removing distorted SNP markers, a genetic linkage map was constructed using 1,918 DArTseq markers which covered 2092.1 cM. Using the inclusive composite interval mapping method in IciMapping, twenty-three QTLs influencing Striga resistance traits were identified across four Striga-infested environments with five stable QTLs (qGY4, qSC2.1, qSC2.2, qSC5, and qSC6) detected in more than one environment. The variations explained by the QTLs ranged from 4.1% (qSD2.3) to 14.4% (qSC7.1). Six QTLs each with significant additive × environment interactions were also identified for grain yield and Striga damage. Gene annotation revealed candidate genes underlying the QTLs, including the gene models GRMZM2G077002 and GRMZM2G404973 which encode the GATA transcription factors, GRMZM2G178998 and GRMZM2G134073 encoding the NAC transcription factors, GRMZM2G053868 and GRMZM2G157068 which encode the nitrate transporter protein and GRMZM2G371033 encoding the SBP-transcription factor. These candidate genes play crucial roles in plant growth and developmental processes and defense functions. This study provides further insights into the genetic mechanisms of resistance to Striga parasitism in maize. The QTL detected in more than one environment would be useful for further fine-mapping and marker-assisted selection for the development of Striga resistant and high-yielding maize cultivars.

列当属寄生杂草（Striga）是撒哈拉以南非洲（sub-Saharan Africa, SSA）谷类作物生产的主要生物胁迫因素，同时威胁当地粮食与营养安全。本研究以223个源自TZdEI 352 × TZEI 916的F₂:₃作图群体为材料，对4个列当适应性性状进行表型鉴定，并利用多样性阵列技术（Diversity Arrays Technology, DArT）进行基因分型，以解析玉米抗列当的基因组区域。经过过滤畸变的SNP标记后，研究人员利用1918个DArTseq标记构建了总长2092.1 cM的遗传连锁图谱。采用IciMapping软件中的包容复合区间作图法，在4个列当侵染环境中共鉴定出23个调控列当抗性相关性状的数量性状基因座（quantitative trait locus, QTL），其中5个稳定QTL（qGY4、qSC2.1、qSC2.2、qSC5和qSC6）可在多个环境中被检测到。各QTL的表型解释率介于4.1%（qSD2.3）至14.4%（qSC7.1）之间。此外，针对籽粒产量与列当为害程度，还鉴定出6个均存在显著加性×环境互作的QTL。基因注释结果显示，这些QTL区域内存在候选基因，包括编码GATA转录因子的GRMZM2G077002与GRMZM2G404973、编码NAC转录因子的GRMZM2G178998与GRMZM2G134073、编码硝酸盐转运蛋白的GRMZM2G053868与GRMZM2G157068，以及编码SBP转录因子的GRMZM2G371033。这些候选基因在植物生长发育过程及防御功能中发挥关键作用。本研究进一步解析了玉米抗列当寄生的遗传机制，而在多个环境中均可检测到的QTL可用于后续的精细定位与标记辅助选择，以培育抗列当且高产的玉米品种。