数字农科院2.0

Root system architecture change in response to waterlogging stress in a 448 global collection of rapeseeds (Brassica napus L.)

文献类型: 外文期刊

作者: Naseeb Ullah;Fang Qian;Rudan Geng;Yujun Xue;Wenjie Guan;Gaoxiang Ji;Hao Li;Qian Huang;Guangqin Cai;Guixin Yan;Xiaoming Wu

作者机构:

关键词: Brassica napus;Image analysis;Membership function value;Root system architecture;Seedling stage;Waterlogging tolerance

期刊名称: Planta

ISSN: 0032-0935

年卷期: 2024 年 259 卷 5 期

页码:

收录情况: SCIE(2024版)

摘要: Main conclusions: A novel image-based screening method for precisely identifying genotypic variations in rapeseed RSA under waterlogging stress was developed. Five key root traits were confirmed as good indicators of waterlogging and might be employed in breeding, particularly when using the MFVW approach. Abstract: Waterlogging is a vital environmental factor that has detrimental effects on the growth and development of rapeseed (Brassica napus L.). Plant roots suffer from hypoxia under waterlogging, which ultimately confers yield penalty. Therefore, it is crucially important to understand the genetic variation of root system architecture (RSA) in response to waterlogging stress to guide the selection of new tolerant cultivars with favorable roots. This research was conducted to investigate RSA traits using image-based screening techniques to better understand how RSA changes over time during waterlogging at the seedling stage. First, we performed a t-test by comparing the relative root trait value between four tolerant and four sensitive accessions. The most important root characteristics associated with waterlogging tolerance at 12 h are total root length (TRL), total root surface area (TRSA), total root volume (TRV), total number of tips (TNT), and total number of forks (TNF). The root structures of 448 rapeseed accessions with or without waterlogging showed notable genetic diversity, and all traits were generally restrained under waterlogging conditions, except for the total root average diameter. Additionally, according to the evaluation and integration analysis of 448 accessions, we identified that five traits, TRL, TRSA, TRV, TNT, and TNF, were the most reliable traits for screening waterlogging-tolerant accessions. Using analysis of the membership function value (MFVW) and D-value of the five selected traits, 25 extremely waterlogging-tolerant materials were screened out. Waterlogging significantly reduced RSA, inhibiting root growth compared to the control. Additionally, waterlogging increased lipid peroxidation, accompanied by a decrease in the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). This study effectively improves our understanding of the response of RSA to waterlogging. The image-based screening method developed in this study provides a new scientific guidance for quickly examining the basic RSA changes and precisely predicting waterlogging-tolerant rapeseed germplasms, thus expanding the genetic diversity of waterlogging-tolerant rapeseed germplasm available for breeding.

分类号:

  • 相关文献

[1]Combining Ability and Genetic Effects of Germination Traits of Brassica napus L. Under Waterlogging Stress Condition. Cheng Yong,Cong Ye,Zou Chong-shun,Zhang Xue-kun,Wang Han-zhong,Gu Min. 2010

[2]Glyphosate-induced GhAG2 is involved in resistance to salt stress in cotton. Yu, Wancong,Xue, Zhaohui,Zhao, Xianzheng,Zhang, Rui,Liu, Jiping,Guo, Sandui. 2022

[3]The ERF-VII transcription factor AvERF75 positively regulates the waterlogging tolerance by interacting with AvLOB41 in kiwifruit (Actinidia valvata). Danfeng Bai,Shichao Gu,Xiujuan Qi,Leiming Sun,Miaomiao Lin,Ran Wang,Chungen Hu,Yukuo Li,Yunpeng Zhong,Jinbao Fang. 2023

[4]Identification of stable quantitative trait loci underlying waterlogging tolerance post-anthesis in common wheat (Triticum aestivum). Ding, Fugong,Tong, Jingyang,Xu, Rui,Chen, Jing,Xu, Xiaoting,Nadeem, Muhammad,Wang, Shuping,Zhang, Yingxin,Zhu, Zhanwang,Wang, Fengju,Fang, Zhengwu,Hao, Yuanfeng. 2023

[5]Effects of Kiwifruit Rootstocks with Opposite Tolerance on Physiological Responses of Grafting Combinations under Waterlogging Stress. Bai, Danfeng,Li, Zhi,Gu, Shichao,Li, Qiaohong,Sun, Leiming,Qi, Xiujuan,Fang, Jinbao,Zhong, Yunpeng,Hu, Chungen. 2022

[6]Research on the nonenzymatic browning reactions in model systems based on apple slices dried by instant controlled pressure drop drying. Gao, Kun,Zhou, Linyan,Bi, Jinfeng,Yi, Jianyong,Wu, Xinye,Xiao, Min.

[7]Assessment Method of Beef Quality Based on Image Analysis. Hu, Lin,Tang, Xiaoyan.

[8]Acquisition and analysis of migration data from the digitised display of a scanning entomological radar. Wu, KM,Tian, Z,Wen, LP,Shen, ZR. 2002

[9]Simultaneous Determination of Multi Rice Quality Parameters Using Image Analysis Method. Fang, Changyun,Hu, Xianqiao,Sun, Chengxiao,Duan, Binwu,Xie, Lihong,Zhou, Ping.

[10]Machine learning for image-based multi-omics analysis of leaf veins. Yubin Zhang,Ning Zhang,Xiujuan Chai,Tan Sun. 2023

[11]Smartphone-based digital phenotyping for genome-wide association study of intramuscular fat traits in longissimus dorsi muscle of pigs. Shen, Yang,Chen, Yuxi,Zhang, Shufeng,Wu, Ze,Lu, Xiaoyu,Liu, Weizhen,Liu, Bang,Zhou, Xiang. 2024

[12]Kinetics of volume expansion properties of cooked rice and correlation analysis upon the physicochemical factors with image analysis. Hu, Zhanqiang,Wu, Youzhi,Lu, Lin,Hu, Xianqiao,Xia, Baolin. 2024

[13]GRABSEEDS: extraction of plant organ traits through image analysis. Haibao Tang,Wenqian Kong,Pheonah Nabukalu,Johnathan S. Lomas,Michel Moser,Jisen Zhang,Mengwei Jiang,Xingtan Zhang,Andrew H. Paterson,Won Cheol Yim. 2024

[14]Identification of quantitative trait loci for drought tolerance at seedling stage by screening a large number of introgression lines in maize. Hao, Z.,Liu, X.,Li, X.,Xie, C.,Li, M.,Zhang, D.,Zhang, S.,Hao, Z.,Xu, Y..

[15]Genetic diversity and association mapping for salinity tolerance in Bangladeshi rice landraces. Reza M. Emon , Mirza M. Islam *, Jyotirmoy Halder , Yeyang Fan *. 2015

[16]Proteomic Analysis Revealed Different Molecular Mechanisms of Response to PEG Stress in Drought-Sensitive and Drought-Resistant Sorghums. Li Y.,Tan B.,Wang D.,Mu Y.,Li G.,Zhang Z.,Pan Y.,Zhu L.. 2022

[17]BEAR1, a bHLH Transcription Factor, Controls Salt Response Genes to Regulate Rice Salt Response. Teng, Yantong,Lv, Min,Zhang, Xiangxiang,Cai, Maohong,Chen, Tao. 2022

[18]Comparative Transcriptome Analysis Reveals the Mechanisms Underlying Differences in Salt Tolerance Between indica and japonica Rice at Seedling Stage. Weilong Kong,Tong Sun,Chenhao Zhang,Xiaoxiao Deng,Yangsheng Li. 2021

[19]Transcriptomic and Metabolomic Analysis of Seedling-Stage Soybean Responses to PEG-Simulated Drought Stress. Wang, Xiyue,Song, Shuang,Wang, Xin,Liu, Jun,Dong, Shoukun. 2022

[20]Detection of Clubroot Disease Resistance in Brassica juncea Germplasm at the Seedling Stage. Wenlong Yang,Jiangping Song,Xiaohui Zhang,Chu Xu,Jiaqi Han,Zhijie Li,Yang Wang,Huixia Jia,Haiping Wang. 2024

作者其他论文 更多>>