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作物学报 ›› 2024, Vol. 50 ›› Issue (7): 1719-1727.doi: 10.3724/SP.J.1006.2024.34186

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

谷子籽粒类黄酮含量和粒色的QTL定位

秦娜1(), 叶珍言2, 朱灿灿1, 付森杰1, 代书桃1, 宋迎辉1, 景雅1, 王春义1, 李君霞1,*()   

  1. 1河南省农业科学院粮食作物研究所, 河南郑州 450002
    2郑州大学农学院, 河南郑州 450001
  • 收稿日期:2023-11-09 接受日期:2024-01-30 出版日期:2024-07-12 网络出版日期:2024-02-20
  • 通讯作者: *李君霞, E-mail: lijunxia@126.com
  • 作者简介:E-mail: qinna2004@126.com
  • 基金资助:
    河南省科研计划联合基金项目(232301420105);财政部和农业农村部国家现代农业产业技术体系建设专项(CARS-06);河南省重点研发专项(231111110300);河南省农业良种攻关项目(2022010401);河南省中央引导地方科技发展资金项目(Z20221341070)

QTL mapping for flavonoid content and seed color in foxtail millet

QIN Na1(), YE Zhen-Yan2, ZHU Can-Can1, FU Sen-Jie1, DAI Shu-Tao1, SONG Ying-Hui1, JING Ya1, WANG Chun-Yi1, LI Jun-Xia1,*()   

  1. 1Cereal Crops Institute, Henan Academy of Agricultural Sciences, Zhengzhou 450002, Henan, China
    2Agriculture College, Zhengzhou University, Zhengzhou 450001, Henan, China
  • Received:2023-11-09 Accepted:2024-01-30 Published:2024-07-12 Published online:2024-02-20
  • Contact: *E-mail: lijunxia@126.com
  • Supported by:
    Scientific Research Plan Joint Fund of Henan Province(232301420105);China Agricultural Research System of the MOF and MARA(CARS-06);Key Research and Development Projects of Henan Province(231111110300);Joint Research on Agriculture Varieties of Henan Province(2022010401);Central Guidance on Science and Technology Development Project of Henan Province(Z20221341070)

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摘要：

谷子(Setaria italica L.)是我国北方地区重要的粮食作物, 籽粒营养丰富, 且富含多种类黄酮物质, 对生长发育和品质形成发挥着重要作用。目前谷子籽粒类黄酮合成及粒色形成相关调控机制研究较少。分析谷子类黄酮含量及粒色性状相关的QTL, 为类黄酮合成关键基因的精细定位、克隆及功能研究奠定基础, 同时, 也为揭示谷子类黄酮合成及代谢机制和培育富含类黄酮谷子品种提供技术支撑。本研究以红粒色高类黄酮品种金苗红酒谷和黄粒色低类黄酮品种豫谷28为亲本构建的包含150个家系的重组自交系(RIL)群体为试验材料, 在谷子成熟期对籽粒粒色和类黄酮含量相关性状进行分析。同时, 采用复合区间作图法(composite interval mapping, CIM)对粒色和类黄酮含量进行QTL定位与分析, 并对QTL置信区间内的候选基因进行预测。相关性分析表明, 类黄酮含量与粒色呈显著正相关。共定位到4个与类黄酮含量相关和11个与粒色相关的QTL, 分别位于1号、2号、5号、6号、7号、8号和9号染色体上, 单个QTL的表型贡献率为2.01%~29.25%, 6个为主效QTL, 其中, qSC1-2和qFLA1-1、qSC7-1和qFLA7-1、qSC9-3和qFLA9-1为2个性状下共同定位到的QTL。通过基因预测与功能注释, 筛选出QTL置信区间内5个与类黄酮物质合成及代谢相关的候选基因, 表明类黄酮物质的合成、代谢及利用相关基因极有可能控制了这些基因的表达。15个QTL分别聚集于7条染色体上, 基于基因功能注释, 共筛选了5个与谷子类黄酮合成及代谢相关的候选基因, 表明不同QTL位点参与到了共同遗传机制, 并可通过分子标记辅助选择进行类黄酮合成及代谢等有利基因的聚合育种。

关键词: 谷子, 类黄酮含量, 粒色, QTL定位, 候选基因

Abstract:

Foxtail millet (Setaria italica L.) is an important grain crop in northern China. The grain is rich in nutrients and many kinds of flavonoid, which plays an important role in growth and quality formation. At present, there are few studies on the regulatory mechanisms of flavonoid synthesis and seed color formation in foxtail millet. The quantitative trait loci (QTL) analysis of flavonoid content and seed color traits in foxtail millet laid a foundation for fine mapping, cloning, and functional study of key genes for flavonoid synthesis, and it also provided technical support for revealing the mechanism of flavonoid synthesis and metabolism in foxtail millet and cultivating millet varieties rich in flavonoid. In this study, a recombinant inbred line (RIL) population consisting of 150 families was used as the experimental materials, which was constructed using a red seed-color high-flavonoid variety Jinmiaohongjiugu and a yellow seed-color low-flavonoid variety Yugu 28 as the parents. The related traits of seed color and flavonoid content were analyzed at maturity stage in foxtail millet. At the same time, composite interval mapping (CIM) was used to locate and analyze QTL for seed color and flavonoid content, and the candidate genes within the QTL confidence intervals were predicted. Correlation analysis showed that flavonoid content was significantly positively correlated with seed color. A total four and eleven QTL associated with flavonoids content and seed color were located on chromosomes 1, 2, 5, 6, 7, 8, and 9, respectively, and individual QTL phenotypic contribution rate was 2.01%-29.25%, six major QTLs were identified, qSC1-2 and qFLA1-1, qSC7-1 and qFLA7-1, qSC9-3, and qFLA9-1 were co-localized QTL under both two traits. Through gene prediction and functional annotation, five candidate genes related to flavonoid synthesis and metabolism in the confidence interval of QTL were screened, indicating that the genes related to flavonoid synthesis, metabolism, and utilization were most probably to regulate the expression of these genes. 15 QTL were clustered on seven chromosomes, respectively, and five candidate genes related to flavonoid synthesis and metabolism were screened based on gene functional annotation, indicating that different QTL loci were involved in the common genetic mechanism, and the pyramiding breeding of beneficial genes such as flavonoid synthesis and metabolism could be carried out through molecular marker-assisted selection.

Key words: foxtail millet, flavonoid content, seed colour, QTL mapping, candidate genes

表1

亲本和重组自交系群体类黄酮含量和粒色性状变异分析"

性状
Trait		 年份
Year		 亲本 Parents RILs群体 RILs populations
金苗红酒谷
Jinmiaohongjiugu		 豫谷28
Yugu 28		 范围
Range		 平均值
Mean		 标准差
SD
类黄酮 2021 10.39 5.38 4.07-11.37 6.92 0.60
Flavonoid (mg g-1) 2022 10.28 5.46 4.12-10.48 6.78 0.62
粒色 2021 红粒 Red seed 黄粒 Yellow seed 0-2 0.80 0.11
Seed color 2022 红粒 Red seed 黄粒 Yellow seed 0-2 0.78 0.13

图1

重组自交系群体粒色性状变异 RIL: 重组自交系群体。"

表2

谷子RIL群体籽粒类黄酮含量和粒色相关性分析"

类黄酮 Flavonoid 粒色 Seed color
2021 2022 2021 2022
类黄酮Flavonoid
2021 1
2022 0.969** 1
粒色 Seed color
2021 0.756** 0.866** 1
2022 0.832** 0.841** 0.987** 1

图2

谷子RIL群体中类黄酮含量(A)和粒色(B)表型频率分布图 RIL: 重组自交系群体。"

图3

RIL群体遗传图谱及控制粒色和类黄酮含量的QTL在染色体上的分布 RIL: 重组自交系群体。"

表3

谷子籽粒粒色和类黄酮QTL分析"

QTL 染色体
Chr.		 环境
Environment		 标记区间
Markers interval		 遗传位置
Genetic
position (cM)		 LOD值
LOD value		 表型贡献率
Phenotypic variance efficiency (%)		 加性效应
Additive
effect
qSC1-1 1 BLUP (2021, 2022) SICAAS1049-SICAAS1006 30.39-50.57 10.70 7.87 0.27
qSC1-2 1 BLUP (2021, 2022) SICAAS1052-SICAAS1068 134.52-175.47 31.59 29.25 -0.78
qSC1-3 1 BLUP SICAAS1068-SICAAS1008 175.47-192.79 6.04 9.08 0.43
qSC2-1 2 BLUP (2022) SICAAS2035-SICAAS2038 0-35.40 6.45 5.93 0.34
qSC5-1 5 BLUP (2021, 2022) SICAAS5034-SICAAS5035 40.16-59.87 2.89 2.01 -0.11
qSC6-1 6 BLUP (2022) SICAAS6081-SICAAS6002 27.38-41.67 5.23 11.48 0.40
qSC7-1 7 BLUP SICAAS7019-SICAAS7073 49.53-61.76 3.01 10.67 0.32
qSC8-1 8 BLUP SICAAS8001-SICAAS8019 5.39-45.95 2.78 3.51 0.06
qSC9-1 9 BLUP (2021) SICAAS9023-SICAAS9107 0-68.88 3.86 3.68 0.02
qSC9-2 9 BLUP (2022) SICAAS9107-SICAAS9131 68.88-123.22 2.79 3.52 -0.01
qSC9-3 9 BLUP (2021, 2022) SICAAS9131-SICAAS9042 123.33-169.79 2.94 3.51 0.03
qFLA1-1 1 BLUP (2021, 2022) SICAAS1052-SICAAS1068 134.52-175.47 4.52 16.89 0.71
qFLA5-1 5 BLUP (2021, 2022) SICAAS5046-SICAAS5008 133.79-153.33 2.70 10.87 0.60
qFLA7-1 7 BLUP (2022) SICAAS7019-SICAAS7073 49.53-61.76 3.05 9.63 0.54
qFLA9-1 9 BLUP SICAAS9131-SICAAS9042 123.33-169.79 3.56 18.05 0.62

表4

候选基因注释"

QTL 染色体
Chr.		 标记
Marker		 候选基因
Candidate genes		 功能注释
Functional annotation		 基因物理位置
Gene physical location (Mb)
qSC1-2 1 SICAAS1052-SICAAS1068 Seita.1G240600 苯丙氨酸解氨酶
Phenylalanine ammonia-lyase		 31,806,380-31,808,846
qFLA5-1 5 SICAAS5046-SICAAS5008 Seita.5G070500 异黄酮还原酶
Isoflavone reductase		 6,041,130-6,042,851
qSC5-1 5 SICAAS5060-SICAAS5034 Seita.5G124200 UDP-糖基转移酶
UDP-glycosyltransferase		 10,408,350-10,412,722
qSC8-1 8 SICAAS8001-SICAAS8019 Seita.8G188600 香豆酰辅酶A
Agmatine coumaroyl CoA		 33,585,009-33,586,364
qFLA9-1 9 SICAAS9131-SICAAS9042 Seita.9G169100 醛酮还原酶
Aldo/keto reductase		 55,949,693-55,952,956
[1] Yang X Y, Wan Z W, Perry L, Lu H Y, Wang Q, Zhao C H, Li J, Xie F, Yu J C, Cui T X, Wang T, Ge Q S. Early millet use in northern China. Proc Natl Acad Sci USA, 2012, 109: 3726-3730.
doi: 10.1073/pnas.1115430109 pmid: 22355109
[2] Lu H, Zhang J, Liu K B, Wu N Q, Li Y M, Zhou K S, Ye M L, Zhang T Y, Zhang H J, Yang X Y, Shen L C, Xu D K, Li Q. Earliest domestication of common millet (Panicum miliaceum) in east Asia extended to 10,000 years ago. Proc Natl Acad Sci USA, 2009, 106: 7367-7372.
doi: 10.1073/pnas.0900158106 pmid: 19383791
[3] Diao X M. Foxtail millet production in China and its future development tendency. In: Chai Y, Wan F S, eds. The Industrial Development of China Special Crops. Beijing: China Agricultural Science and Technology Press, 2007. pp 32-43.
[4] 李建锐. 谷子SiASR4基因参与植物响应干旱和盐胁迫的功能研究. 中国农业大学博士学位论文, 北京, 2018.
Li J R. Function Analysis of the Foxtail Millet (Setaria italica) Gene, SiASR4, in Response to Drought and Salt Stresses of Plants. PhD Dissertation of China Agricultural University, Beijing, China, 2018 (in Chinese with English abstract).
[5] 张文英. 谷子种质资源抗旱性评价. 中国农业科学院硕士学位论文, 北京, 2014.
Zhang W Y. Evaluation of the Drought Tolerance of Germplasm Resources in Foxtail Millet, Setaria italica L. MS Thesis of Chinese Academy of Agricultural Sciences, Beijing, China, 2014 (in Chinese with English abstract).
[6] Vauzour D, Vafeiadou K, Rodriguez-Mateos A, Rendeiro C, Jeremy-Spencer P E. The neuroprotective potential of flavonoids: a multiplicity of effects. Genes Nutr, 2008, 3: 115-126.
doi: 10.1007/s12263-008-0091-4 pmid: 18937002
[7] Pandey K B, Rizvi S I. Plant polyphenols as dietary antioxidants in human health and disease. Oxidat Med Cell Longev, 2009, 2: 270-278.
[8] 张丽玲, 郄倩茹, 罗韶凡, 牛文康, 朱喆标, 高雨柔, 李旭凯, 韩渊怀. 谷子12种黄酮类代谢物合成通路分析. 山西农业大学学报(自然科学版), 2020, 40(4): 10-18.
Zhang L L, Qie Q R, Luo S F, Niu W K, Zhu Z B, Gao Y R, Li X K, Han Y H. Analysis of synthesis pathway of twelve flavonoid metabolites in foxtail millet. J Shanxi Agric Univ (Nat Sci Edn), 2020, 40(4): 10-18 (in Chinese with English abstract).
[9] Zhang Y K, Gao J H, Qie Q R, Yang Y L, Hou S Y, Wang X C, Li X K, Han Y H. Comparative analysis of flavonoid metabolites in foxtail millet (Setaria italica) with different eating quality. Life (Basel), 2021, 11: 578.
[10] 韩尚玲, 霍轶琼, 李辉, 韩华蕊, 侯思宇, 孙朝霞, 韩渊怀, 李红英. 基于WGCNA发掘谷子穗部类黄酮合成途径调控关键基因. 作物学报, 2022, 48: 1645-1657.
doi: 10.3724/SP.J.1006.2022.14107
Han S L, Huo Y Q, Li H, Han H R, Hou S Y, Sun Z X, Han Y H, Li H Y. Identification of regulatory genes related to flavonoids synthesis by weighted gene correlation network analysis in the panicle of foxtail millet. Acta Agron Sin, 2022, 48: 1645-1657 (in Chinese with English abstract).
[11] 张瑞杰. 基于转录组水平对谷子叶片花青素积累机制的初探. 山西农业大学硕士学位论文, 山西太谷, 2019.
Zhang R J. Preliminary Study on the Mechanism of Anthocyanin Accumulation in Foxtail Millet Leaves Based on the Transcriptome. MS Thesis of Shanxi Agricultural University, Taigu, Shanxi, China, 2019 (in Chinese with English abstract).
[12] Wang F, Ji G S, Xu Z B, Feng B, Zhou Q, Fan X L, Wang T. Metabolomics and transcriptomics provide insights into anthocyanin biosynthesis in the developing grains of purple wheat (Triticum aestivum L.). J Agric Food Chem, 2021, 69: 11171-11184.
[13] Li J R, Todd T C, Trick H N. Rapid in planta evaluation of root expressed transgenes in chimeric soybean plants. Plant Cell Rep, 2010, 29: 113-123.
doi: 10.1007/s00299-009-0803-2 pmid: 20012965
[14] 陈衡, 潘相文, 王飞飞, 刘长锴, 王雪, 李彦生, 张秋英. 大豆异黄酮生物合成与调控的分子机制研究进展. 土壤与作物, 2021, 10(2): 126-142.
Chen H, Pan X W, Wang F F, Liu C K, Wang X, Li Y S, Zhang Q Y. Molecular mechanisms of isoflavone biosynthesis and regulation in soybean: a review. Soil Crops, 2021, 10(2): 126-142 (in Chinese with English abstract).
[15] 李海权, 耿玲玲, 智慧, 王永芳, 李振侠, 相金英, 刁现民, 刘国庆. 基于谷子剩余杂合体的谷子颖壳颜色基因精细定位. 见: 中国作物学会2015年学术年会论文摘要集. 北京: 中国作物学会, 2015. p 35.
Li H Q, Geng L L, Zhi H, Wang Y F, Li Z X, Xiang J Y, Diao X M, Liu G Q. Fine mapping of glume shell colour genes based on residual heterozygote in foxtail millet. In: Proceedings of 2015 Annual Conference of the Crop Science Society of China. Beijing: Crop Science Society of China, 2015. p 35 (in Chinese).
[16] 高俊华, 王润奇, 毛丽萍, 刁现民. 安矮3号谷子矮秆基因的染色体定位. 作物学报, 2003, 29: 152-154.
Gao J H, Wang R Q, Mao L P, Diao X M. Chromosome locating of dwarf gene in foxtail millet An’ai 3. Acta Agron Sin, 2003, 29: 152-154 (in Chinese with English abstract).
[17] 张义茹. 基于代谢组学对小米蒸煮风味、脂质及谷子籽粒灌浆期代谢物累积特征的研究. 山西农业大学博士学位论文, 山西太谷, 2019.
Zhang Y R. Study on the Cooking Aroma, Lipid Change Patterns and Metabolite Accumulation during Grain Filling based on Metabolomics in Foxtail Millet. PhD Dissertation of Shanxi Agricultural University, Taigu, Shanxi, China, 2019 (in Chinese with English abstract).
[18] 邵丽华, 王莉, 白文文, 刘雅娟. 山西谷子资源叶酸含量分析及评价. 中国农业科学, 2014, 47: 1265-1272.
doi: 10.3864/j.issn.0578-1752.2014.07.003
Shao L H, Wang L, Bai W W, Liu Y J. Evaluation and analysis of folic acid content in millet from different ecological regions in Shanxi province. Sci Agric Sin, 2014, 47: 1265-1272 (in Chinese with English abstract).
doi: 10.3864/j.issn.0578-1752.2014.07.003
[19] Zhang S, Tang C J, Zhao Q, Li J, Yang L F, Qie L F, Fan X K, Li L, Zhang N, Zhao M C, Liu X T, Chai Y, Zhang X, Wang H L, Li Y T, Li W, Zhi H, Jia G Q, Diao X M. Development of highly polymorphic simple sequence repeat markers using genome-wide microsatellite variant analysis in Foxtail millet [Setaria italica (L.) P. Beauv.]. BMC Genomics, 2014, 15: 78.
doi: 10.1186/1471-2164-15-78 pmid: 24472631
[20] Bennetzen J L, Schmutz J, Wang H, Percifield R, Hawkins J, Pontaroli A C, Estep M, Feng L, Vaughn J N, Grimwood J, Jenkins J, Barry K, Lindquist E, Hellsten U, Deshpande S, Wang X W, Wu X M, Mitros T, Triplett J, Yang X H, Ye C Y, Mauro- Herrera M, Wang L, Li P H, Sharma M, Sharma R, Ronald P C, Panaust O, Kellogg E A, Brutnell T P, Doust A N, Tuskan G A, Rokhsar D, Devos K M. Reference genome sequence of the model plant setaria. Nat Biotechnol, 2012, 30: 555-564.
doi: 10.1038/nbt.2196 pmid: 22580951
[21] Bai H, Cao Y H, Quan J Z, Dong L, Li Z Y, Zhu Y B, Zhu L H, Dong Z P, Li D Y. Identifying the genome-wide sequence variations and developing new molecular markers for genetics research by re-sequencing a landrace cultivar of foxtail millet. PLoS One, 2013, 8: e73514.
[22] Yin C B, Li H H, Li S S, Xu L D, Zhao Z G, Wang J K. Genetic dissection on rice grain shape by the two-dimensional image analysis in one japonica × indica population consisting of recombinant inbred lines. Theor Appl Genet, 2015, 128: 1969-1986.
[23] 孙子淇, 李慧慧, 张鲁燕, 王健康. QTL作图中零假设检验统计量分布特征及LOD临界值估计方法. 作物学报, 2013, 39: 1-11.
doi: 10.3724/SP.J.1006.2013.00001
Sun Z Q, Li H H, Zhang L Y, Wang J K. Properties of the test statistic under null hypothesis and the calculation of LOD threshold in quantitative trait loci (QTL) mapping. Acta Agron Sin, 2013, 39: 1-11 (in Chinese with English abstract).
[24] Li S S, Wang J K, Zhang L Y. Inclusive composite interval mapping of QTL by environment interactions in biparental populations. PLoS One, 2015, 10: e0132414.
[25] 李慕男, 兰凤英. 小米的营养成分及保健功能研究进展. 河北北方学院学报, 2017, 33(7): 56-60.
Li M N, Lan F Y. Nutritional health function and product development of millet. J Hebei North Univ, 2017, 33(7): 56-60 (in Chinese with English abstract).
[26] 王海岗, 贾冠清, 智慧, 温琪汾, 董俊丽, 陈凌, 王君杰, 曹晓宁, 刘思辰, 王纶, 乔治军, 刁现民. 谷子核心种质表型遗传多样性分析及综合评. 作物学报, 2016, 42: 19-30.
doi: 10.3724/SP.J.1006.2016.00019
Wang H G, Jia G Q, Zhi H, Wen Q F, Dong J L, Chen L, Wang J J, Cao X N, Liu S C, Wang L, Qiao Z J, Diao X M. Phenotypic diversity evaluations of foxtail millet core collections. Acta Agron Sin, 2016, 42: 19-30 (in Chinese with English abstract).
[27] 薛其勤, 别茹, 常宇涵, 邢明, 杨会, 张昆, 刘风珍, 万勇善. 花生种皮颜色及花青素含量的遗传分析. 花生学报, 2020, 49(1): 19-24.
Xue Q Q, Bie R, Chang Y H, Xing M, Yang H, Zhang K, Liu F Z, Wan Y S. Genetic analysis of peanut testa color and anthocyanin content. J Peanut Sci, 2020, 49(1): 19-24 (in Chinese with English abstract).
[28] 宋健. 大豆种皮色相关基因的图位克隆及功能解析. 中国农业科学院博士学位论文, 北京, 2019.
Song J. Map-Based Cloning and Functional Analysis of Genes Controlling Seed Coat Color in Soybean (Glycine max (L.) Merr.). PhD Dissertation of Chinese Academy of Agricultural Sciences, Beijing, China, 2019 (in Chinese with English abstract).
[29] 白春明, 王春语, 王平, 朱振兴, 陆晓春. 高粱子粒单宁含量和颜色QTL分析. 植物遗传资源学报, 2017, 18: 860-866.
doi: 10.13430/j.cnki.jpgr.2017.05.007
Bai C M, Wang C Y, Wang P, Zhu Z X, Lu X C. QTLs analysis of tannin content and color of grain in sorghum. J Plant Genet Resour, 2017, 18: 860-866 (in Chinese with English abstract).
doi: 10.13430/j.cnki.jpgr.2017.05.007
[30] 王艳花. 大黄油菜粒色性状候选基因的定位克隆及功能分析. 青海大学博士学位论文, 青海西宁, 2017.
Wang Y H. Positional Cloning and Functional Study of Seed Coat Color Gene in Dahuang (a landrace of Brassica rapa L.). PhD Dissertation of Qinghai University, Xining, Qinghai, China, 2017 (in Chinese with English abstract).
[31] Meyer P, Heidmann I, Forkmann G, Saedler H. A new petunia a flower colour generated by transformation of a mutant with a maize gene. Nature, 1987, 330: 677-678.
[32] Vanderkrol A R, Lenting P E, Veenstra J, Vandermeer I M, Koes R E, Gerats A G M, Mol J N M, Stuitije A R. An anti-sense chalcone synthases gene in transgenic plants inhibits flower pigmentation. Nature, 1988, 333: 866-869.
[33] 李秋琳, 李燕, 陈伟, 姚金波, 朱守鸿, 袁黎, 张永山. 基于广泛靶向代谢组学的不同颜色棉花花瓣中类黄酮成分差异分析. 棉花学报, 2021, 33: 482-492.
doi: 10.11963/cs20210036
Li Q L, Li Y, Chen W, Yao J B, Zhu S H, Yuan L, Zhang Y S. Metabolomics reveals the variation of flavonoids content in petals of cotton with different colors. Cotton Sci, 2021, 33: 482-492 (in Chinese with English abstract).
doi: 10.11963/cs20210036
[34] Nakabayashi R, Yonekura-Sakakibara K, Urano K, Suzuki M, Yamada Y, Nishizawa T, Matsuda F, Kojima M, Sakakibara H, Shinozaki K, Michael A J, Tohge T, Yamazaki M, Saito K. Enhancement of oxidative and drought tolerance in Arabidopsis by overaccumulation of antioxidant flavonoids. Plant J, 2014, 77: 367-379.
[35] Gouot J C, Smith J P, Holzapfel B P, Walker A R, Barril C. Grape berry flavonoids: a review of their biochemical responses to high and extreme high temperatures. J Exp Bot, 2019, 70: 397-423.
doi: 10.1093/jxb/ery392 pmid: 30388247
[36] 潘俊倩, 佟曦然, 郭宝林. 光对植物黄酮类化合物的影响研究进展. 中国中药杂志, 2016, 41: 3897-3903.
Pan J Q, Tong X R, Guo B L. Progress of effects of light on plant flavonoids. China J Chin Mater Med, 2016, 41: 3897-3903 (in Chinese with English abstract).
[37] 葛诗蓓, 张学宁, 韩文炎, 李青云, 李鑫. 植物类黄酮的生物合成及其抗逆作用机制研究进展. 园艺学报, 2023, 50: 209-224.
doi: 10.16420/j.issn.0513-353x.2021-1186
Ge S B, Zhang X N, Han W Y, Li Q Y, Li X. Research progress on plant flavonoids biosynthesis and their anti-stress mechanism. Acta Hortic Sin, 2023, 50: 209-224 (in Chinese with English abstract).
doi: 10.16420/j.issn.0513-353x.2021-1186
[38] Chen Y Y, Lu H Q, Jiang K X, Wang Y R, Wang Y P, Jiang J J. The favonoid biosynthesis and regulation in Brassica napus: a review. Int J Mol Sci, 2022, 24: 357.
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