欢迎访问作物学报,今天是

作物学报 ›› 2022, Vol. 48 ›› Issue (7): 1645-1657.doi: 10.3724/SP.J.1006.2022.14107

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

基于WGCNA发掘谷子穗部类黄酮合成途径调控关键基因

韩尚玲1(), 霍轶琼1,2, 李辉1, 韩华蕊1, 侯思宇1,2,3, 孙朝霞1,2,3, 韩渊怀1,2,3, 李红英1,2,3,*()   

  1. 1山西农业大学农学院, 山西太谷 030801
    2山西农业大学农业生物工程研究所, 山西太谷 030801
    3杂粮种质创新与分子育种山西省重点实验室, 山西太谷 030801
  • 收稿日期:2021-06-22 接受日期:2021-10-19 出版日期:2022-07-12 网络出版日期:2021-11-01
  • 通讯作者: 李红英
  • 作者简介:E-mail: 1438989621@qq.com
  • 基金资助:
    国家自然科学基金项目(31771810);国家自然科学基金项目(32070366);国家重点研发计划项目(2018YFD1000705-2);山西省优秀博士来晋工作奖励资金科研项目(SXYBKY2019042);山西省研究生创新项目(2020SY209);山西省高等学校科学研究优秀成果培育项目(2019KJ020);山西农谷建设科研专项(SXNGJSKYZX201702);杂粮种质创新与分子育种山西省重点实验室资助

Identification of regulatory genes related to flavonoids synthesis by weighted gene correlation network analysis in the panicle of foxtail millet

HAN Shang-Ling1(), HUO Yi-Qiong1,2, LI Hui1, HAN Hua-Rui1, HOU Si-Yu1,2,3, SUN Zhao-Xia1,2,3, HAN Yuan-Huai1,2,3, LI Hong-Ying1,2,3,*()   

  1. 1College of Agriculture, Shanxi Agricultural University, Taigu 030801, Shanxi, China
    2Institute of Agricultural Bioengineer, Shanxi Agricultural University, Taigu 030801, Shanxi, China
    3Shanxi Key Laboratory of Germplasm Innovation and Molecular Breeding in Minor Crops, Taigu 030801, Shanxi, China
  • Received:2021-06-22 Accepted:2021-10-19 Published:2022-07-12 Published online:2021-11-01
  • Contact: LI Hong-Ying
  • Supported by:
    National Natural Science Foundation of China(31771810);National Natural Science Foundation of China(32070366);National Key Research and Development Project(2018YFD1000705-2);Scientific Research Project of Shanxi Province Outstanding Doctoral Work Award Fund(SXYBKY2019042);Shanxi Graduate Innovation Project(2020SY209);Cultivation Project of Excellent Scientific Research Achievements in Shanxi Universities(2019KJ020);Shanxi Agricultural Valley Construction Research Project(SXNGJSKYZX201702);and the Shanxi Key Laboratory of Minor Crop Germplasm Innovation and Molecular Breeding

摘要:

类黄酮是植物重要的次生代谢物质, 在植物生长发育中发挥着重要的作用, 此外, 类黄酮具有抗氧化活性, 对人体十分有益。谷子籽粒营养丰富全面, 是一种保健型杂粮, 深受我国人民喜爱。谷子作为C4模式植物, 正在受到越来越多的关注。目前谷子籽粒类黄酮代谢及调控机制研究较少。本研究利用高类黄酮品种晋谷21 (JG21)及低类黄酮品种牛毛白(NMB)谷穗为材料, 分析JG21与NMB小穗发育不同阶段类黄酮靶向代谢组及JG21小穗发育不同阶段转录组, 结合加权基因共表达网络分析挖掘可能参与调控类黄酮代谢的转录因子, 并在不同水平的类黄酮品种中进行表达分析初步验证。结果发现, 2个品种小穗中主要富集的类黄酮组分为芹菜素、牡荆素及柚皮素, 三者共占总类黄酮含量的79%以上。类黄酮代谢基因共表达网络中包含38,921个基因, 共划分为32个模块, 其中turquoise模块、green模块及magenta模块与类黄酮代谢显著相关。利用类黄酮代谢通路差异表达基因作为关键基因筛选出与类黄酮代谢调控相关的27个转录因子家族, 并通过启动子结合基序分析筛选获得11个转录因子。Pearson相关性分析表明, 11个转录因子中有7个候选转录因子可能参与类黄酮代谢, 分别为WRKY38、MYB4a、PI、WRKY15、WRKY62、MYB46、WRKY23。以上结果为研究谷子类黄酮代谢通路转录调控机制提供了新的候选基因, 为深入揭示类黄酮代谢调控机制奠定基础。

关键词: 谷子, 类黄酮, 权重基因共表达网络, 转录因子

Abstract:

Flavonoids are important secondary metabolites in plants and play significant roles in plant growth and development. They have antioxidant activity and are beneficial to human health. Foxtail millet is rich in nutrients, making it a healthy grain and popular among consumers. The crop is gaining more and more attention as a C4 model plant. However, there are few studies on the metabolic regulatory mechanism of flavonoids in foxtail millet. In this study, the panicles of flavonoid-rich variety JG21 and flavonoid-less variety NMB were analyzed on the flavonoid metabolomic profiles. Transcriptome sequencing was performed on the panicles of JG21 at different developmental stages. Transcription factors involved in regulating flavonoid metabolism were identified by weighted gene correlation network analysis (WGCNA). The expression patterns of these genes were verified by qRT-PCR. The results showed that the main flavonoid components enriched in the spikelets of foxtail millet were apigenin, vitexin, and naringenin, accounting for more than 79% of the total flavonoids. The flavonoid-related network of JG21 contained 38,921 genes, which were divided into 32 modules. Among them, the turquoise module, green module, and magenta module were significantly correlated with flavonoid metabolism. A total of 27 transcription factor families related to the regulation of flavonoid metabolism were identified by using differentially expressed genes related to flavonoid metabolism pathway as the hubs, and 11 transcription factors were obtained through promoter binding motif analysis. Pearson correlation analysis showed that 7 out of the 11 transcription factors might be involved in flavonoid metabolism, which were WRKY38, MYB4a, PI, WRKY15, WRKY62, MYB46, and WRKY23, respectively. The above results provide new candidate genes for studying the transcriptional regulation mechanism of flavonoids and lay a foundation for further investigation of the flavonoid metabolism regulation mechanism in foxtail millet.

Key words: foxtail millet, flavonoids, WGCNA, transcription factor

图1

代表性品种JG21穗发育时期(S1、S3和S5) S1外观呈鲜绿色, 内含物呈水乳状; S3外观呈黄绿色或浅绿色, 营养物质积累, 内含物固化, 胚与粉状内含物可分离; S5外观呈深黄色或灰白色, 稃壳干燥变脆, 籽粒成熟。"

附表1

本试验所用引物"

基因
Gene
上游引物
Forward primer (5'-3')
下游引物
Reverse primer (5'-3')
Seita.4G268200 ACCTCAAGGACGAACAGCAG TTCACGTTCAGGAGGTACGC
Seita.3G350800 CGGTGGATCAACTACCTCCG GCGATCTGAGACCACCTGTT
Seita.7G284800 CACCGAGGAAGAAGACGACC TTGATCTCGTTGTCCGTCCG
Seita.7G201000 GACCTGACGGGCATCAAGAA TTGGAGCACTTGTCGCACTT
Seita.3G236800 GAGCCTGAGTGCAGAGATCG ATCCTCGCCTTTCAGATGCC
Seita.6G239700 CAGAGGAGCACTCTGCTTCG AGGCCTCTGAAGTCGAGCAT
Seita.5G362000 AGGAGATCAACGGGCACAAG CTCCCCGTAGTAGGCGATCT
Seita.5G361900 AGCATCCCCAGAGAGCAAAC GTGGAAGCTGCACCTGTAGT
Seita.3G164900 TTCTGGACGACGGCTACAAG TCTTCACGTTGCACCCTTCC
Seita.7G203300 AGACGTGCACCGACAAATCT TGATGGCAAGAGTGCCACAT
Seita.1G154200 TCGACGATCTGATGAGCTGC CCATCATTTGCTGCCACGAC

图2

谷子穗发育不同时期类黄酮各组分含量 柱上不同小写字母表示在P < 0.05水平差异显著。"

表1

样品转录组测序情况统计"

样本名称
Sample name
总序列数量
Total reads
匹配序列数量
Mapped reads
匹配比例
Mapped ratio
(%)
GC含量
GC content (%)
Q30比例
Q30 ratio
(%)
基因间序列比例
Intergenic ratio
(%)
外显子序列比例
Exon ratio
(%)
内含子序列比例
Intron ratio
(%)
JG21-S1-1 47,381,498 43,109,022 90.98 53.30 93.50 9.95 86.55 3.50
JG21-S1-2 49,046,244 44,551,756 90.84 53.49 93.28 10.04 86.50 3.46
JG21-S1-3 46,450,810 41,656,468 89.68 53.54 94.01 10.22 86.35 3.43
JG21-S3-1 43,629,752 41,008,492 93.99 54.21 93.48 10.33 86.91 2.76
JG21-S3-2 51,156,392 48,064,045 93.96 54.11 93.70 10.31 86.91 2.78
JG21-S3-3 47,754,204 44,808,816 93.83 53.96 93.61 10.26 86.87 2.87
JG21-S5-1 45,693,728 38,155,584 83.50 53.90 93.63 11.09 85.30 3.61
JG21-S5-2 43,824,250 36,414,881 83.09 53.78 93.48 11.10 85.30 3.60
JG21-S5-3 46,573,564 38,830,068 83.37 53.93 93.52 11.13 85.32 3.55

图3

基于欧氏距离法的谷子转录组样本表达量层次聚类图"

图4

谷穗转录本聚类及模块识别 a: 基于拓扑相异矩阵构建的基因聚类树。b: 使用动态剪切算法得到的基因模块, 不同颜色代表不同模块。"

图5

类黄酮代谢相关模块鉴定 每行代表一个模块, 每列代表一种性状。矩形框里的数字代表模块与性状之间的相关系数及相应P值。"

附图1

类黄酮差异表达基因表达分析"

表2

类黄酮合成通路差异表达基因与3种类黄酮物质相关性"

基因
Gene
牡荆素
Vitexin
柚皮素
Naringenin
芹菜素
Apigenin
CHIL_Seita.7G301600 0.933** 0.992** -0.436
F3H2_Seita.9G561700 0.391 -0.033 0.858**
F3'H6_Seita.2G219600 0.944** 0.987** -0.398
F3'H8_Seita.3G327200 0.921** 0.994** -0.464
ANR2_Seita.7G249100 0.862** 0.994** -0.567
CHSC2_Seita.8G140200 0.954** 0.984** -0.368
4CL1_Seita.6G093400 -0.688* -0.314 -0.642
4CL5_Seita.6G167900 0.974** 0.965** -0.280
4CL2_Seita.1G283300 0.663 0.917** -0.797*
PAL5_Seita.1G240600 0.928** 0.992** -0.442
PAL3_Seita.1G240400 0.919** 0.946** -0.382
PAL4_Seita.1G240500 0.951** 0.984** -0.373
PAL2_Seita.1G240300 0.956** 0.981** -0.352
PAL1_Seita.1G240200 0.953** 0.983** -0.367
PAL7_Seita.6G181000 0.971** 0.969** -0.296

图6

3个模块类黄酮合成基因局部调控网络 红色圆圈表示存在差异表达的类黄酮合成基因, 蓝色方块表示与类黄酮合成基因存在互作的差异表达转录因子。A: turquoise模块; B: green模块; C: magenta模块。"

附表2

类黄酮代谢基因与候选转录因子结合基序分析"

转录因子
Transcription factor
结合基序
Motif ID
E
E-value
靶基因
Target gene
模板链
Strand
起始位置
Start
终止位置
End
p
p-value
q
q-value
匹配序列
Matched Sequence
Seita.4G268200 MA0940.1
(AP1)
3.23722E-30 Seita.7G301600_CHIL - 361 373 0.0000404 0.119 ATAAAAAAATAAA
Seita.7G301600_CHIL + 765 777 0.0000413 0.119 CTAAATAAGAAAA
Seita.7G301600_CHIL + 1004 1016 0.0000417 0.119 ATAAAAATATAAA
Seita.1G240300_PAL2 + 695 707 0.0000676 0.153 ACAGAAAAAAAAA
Seita.7G301600_CHIL - 367 379 0.0000686 0.153 ACTAAAATAAAAA
Seita.2G219600_F3'H6 + 307 319 0.0000880 0.156 ACGAAAAAGGGAA
Seita.3G350800 MA1040.1(MYB46) 3.80676E-67 Seita.7G301600_CHIL - 1790 1797 0.0000179 0.293 GTTAGGTA
Seita.7G301600_CHIL - 1685 1692 0.0000593 0.293 GGTAGGTG
Seita.8G140200_CHSC2 + 1015 1022 0.0000772 0.293 GTTTGGTA
Seita.7G284800 MA1039.1(MYB4a) 1.80221E-92 Seita.7G301600_CHIL - 1685 1692 0.0000121 0.096 GGTAGGTG
Seita.1G240300_PAL2 - 1435 1442 0.0000241 0.096 GGTTGGTG
Seita.1G240300_PAL2 + 93 100 0.0000241 0.096 GGTTGGTG
Seita.2G219600_F3'H6 + 682 689 0.0000241 0.096 GGTTGGTG
Seita.1G240300_PAL2 - 665 672 0.0000535 0.155 GGTTGGTA
Seita.2G219600_F3'H6 + 375 382 0.0000681 0.181 AGTAGGTG
Seita.1G240300_PAL2 + 905 912 0.0000975 0.183 AGTAGGTG
Seita.7G301600_CHIL + 1220 1227 0.0000975 0.183 AGTAGGTG
Seita.7G201000 MA0120.1(id1) 2.69525E-87 Seita.1G240300_PAL2 - 1350 1361 0.0000238 0.185 TGGTCCCTTCCG
Seita.7G301600_CHIL + 553 564 0.0000644 0.232 TTTCCCTTCTCT
Seita.1G240300_PAL2 - 490 501 0.0000684 0.232 TTTTCCCTCTCT
Seita.2G219600_F3'H6 - 308 319 0.0000694 0.232 TTCCCTTTTTCG
Seita.3G236800 MA0559.1(PI) 4.96687E-74 Seita.8G140200_CHSC2 + 1243 1256 0.00000786 0.123 ACAAAACAGGAAAA
Seita.7G301600_CHIL + 1630 1643 0.0000174 0.146 ACAAAACAGGAAAA
Seita.8G140200_CHSC2 + 1261 1274 0.0000234 0.146 ACAAAAATAGAATA
Seita.8G140200_CHSC2 + 499 512 0.0000354 0.172 CTAGAAGAAGAAGG
Seita.8G140200_CHSC2 + 1219 1232 0.0000809 0.172 AAGAATAAGGAAAG
Seita.8G140200_CHSC2 + 710 723 0.0000885 0.172 ACAGAACTAGAAAA
Seita.6G239700 MA1039.1(MYB4) 1.85497E-89 Seita.9G561700_F3H2 + 277 284 0.0000975 0.183 AGTTGGTG
Seita.5G362000 MA1084.1(WRKY38) 2.75933E-17 Seita.6G167900_4CL5 + 176 183 0.0000414 0.660 AGTTGACC
Seita.6G167900_4CL5 - 1533 1540 0.0000828 0.880 CATTGACC
Seita.5G361900 MA1091.1(WRKY62) 1.26504E-15 Seita.6G167900_4CL5 - 177 184 0.0000147 0.468 TGGTCAAC
Seita.3G164900 MA1080.1(WRKY23) 2.98528E-34 Seita.1G240500_PAL4 - 947 954 0.0000593 0.820 AGTCAAAG
Seita.7G203300 MA0990.1(EDT1) 0 Seita.6G167900_4CL5 + 662 671 0.0000346 0.366 AAATAAATGC
Seita.6G167900_4CL5 - 330 339 0.0000779 0.618 CTTTTAATGC
Seita.1G154200 MA1076.1(WRKY15) 3.76677E-45 Seita.1G240500_PAL4 - 955 964 0.0000855 0.907 GAGTCAACTC

表3

候选转录因子功能"

转录因子
Transcription factor
功能
Function
AP1 拟南芥: 参与花的形成[20-22]
Arabidopsis thaliana: participate in flower formation[20-22]
MYB46 拟南芥: 参与木质素生物合成[23-25]
Arabidopsis thaliana: participate in lignin biosynthesis[23-25]
MYB4a/b 拟南芥: 参与类黄酮生物合成[26]
Arabidopsis thaliana: participate in flavonoid biosynthesis[26]
id1 玉米: 参与开花过程[27-28]
Zea mays: participate in flowering process[27-28]
PI 拟南芥: 参与开花过程[29]
Arabidopsis thaliana: participate in flowering process[29]
WRKY38 拟南芥: 基础防御的负调节剂[30]
Arabidopsis thaliana: negative regulator of basal defense[30]
WRKY62 拟南芥: 基础防御的负调节剂; 参与水杨酸诱导的反应[30-31]
Arabidopsis thaliana: negative regulator of basal defense; participate in the response induced by salicylic acid[30-31]
WRKY23 拟南芥: 介导黄酮醇合成的局部调控, 调节生长素的转运[32]; 参与生长素介导的PIN蛋白的重排[33]
Arabidopsis thaliana: participate in local regulation of flavonol biosynthesis and auxin transport[32]; participate in auxin-mediated PIN polarity rearrangements[33]
EDT1 拟南芥: 增加陆地棉抗旱性和耐盐性[34-36]
Arabidopsis thaliana: increase drought and salt tolerance of upland cotton[34-36]
WRKY15 拟南芥: 调节植物的生长和盐/渗透胁迫反应[37]; 抑制木质部形成期间VND7上游的导管分子分化[38]
Arabidopsis thaliana: modulates plant growth and salt/osmotic stress responses[37]; suppresses tracheary element differentiation upstream of VND7 during xylem formation[38]

表4

11个转录因子与3种类黄酮物质相关性"

转录因子
Transcription factors
JG21 NMB
牡荆素
Vitexin
柚皮素
Naringenin
芹菜素
Apigenin
牡荆素
Vitexin
柚皮素
Naringenin
芹菜素
Apigenin
WRKY38 0.948** 0.984** -0.378 0.595 0.715 -0.975**
EDT1 0.976** 0.962** -0.275 -0.983** -0.887* 0.993**
AP1 -0.922** -0.975** 0.422 0.927** 0.995** -0.717
MYB4a 0.926** 0.975** -0.401 0.879* 0.811* -0.991**
PI 0.886** 0.997** -0.534 0.805* 0.919* -0.889*
MYB4b -0.051 -0.472 0.994** 0.939** 0.984** -0.936**
WRKY15 0.980** 0.917** -0.136 0.738 0.801* -0.755
id1 -0.969** -0.973** 0.304 0.998** 0.998** -0.976**
WRKY62 0.946** 0.988** -0.392 0.497 0.773 -0.834*
MYB46 0.840** 0.986** -0.605 0.911** 0.915** -0.944**
WRKY23 0.983** 0.944** -0.228 0.874* 0.890* -0.937**
[1] Williams C A, Grayer R J. Anthocyanins and other flavonoids. Nat Prod Rep, 2004, 21: 539-573.
doi: 10.1039/b311404j
[2] Buer C S, Imin N, Djordjevic M A. Flavonoids: new roles for old molecules. J Integr Plant Biol, 2010, 52: 98-111.
doi: 10.1111/j.1744-7909.2010.00905.x
[3] Kozłowska A, Szostak-Wegierek D. Flavonoids-food sources and health benefits. Rocz Panstw Zakl Hig, 2014, 65: 79-85.
[4] 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.
doi: 10.1111/tpj.12388
[5] 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
[6] 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.
[7] Xu W J, Dubos C, Lepiniec L. Transcriptional control of flavonoid biosynthesis by MYB-bHLH-WDR complexes. Trends Plant Sci, 2015, 20: 176-185.
doi: 10.1016/j.tplants.2014.12.001
[8] 刁现民.谷子种质资源的深度分析和研究利用. 见: 2017年中国作物学会学术年会摘要集, 保定: 中国作物学会, 2017. p 1.
Diao X M. In-depth analysis and research utilization of foxtail millet germplasm resources. In: Abstract ppub of the Academic Annual Meeting of Chinese Crop Society in 2017Baoding: The Crop Science Society of China, 2017. p 1. (in Chinese)
[9] 徐玖亮, 温馨, 刁现民, 张福锁, 李学贤. 我国主要谷类杂粮的营养价值及保健功能. 粮食与饲料工业, 2021, (1): 27-35.
Xu J L, Wen X, Diao X M, Zhang F S, Li X X. Nutrition values and health effects of coarse cereals in China. Cereal Feed Ind, 2021, (1): 27-35. (in Chinese with English abstract)
[10] 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.
doi: 10.3390/life11060578
[11] 鲜小华, 王嘉, 徐新福, 曲存民, 卢坤, 李加纳, 刘列钊. 整合GWAS和WGCNA分析挖掘甘蓝型油菜黄籽微效作用位点. 作物学报, 2018, 44: 1105-1113.
Xian X H, Wang J, Xu X F, Qu C M, Lu K, Li J N, Liu L Z. Mining yellow-seeded micro effect loci in B. napus by integrated GWAS and WGCNA analysis. Acta Agron Sin, 2018, 44: 1105-1113. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2018.01105
[12] 程旭.基于转录组和共表达网络分析的玫瑰类黄酮和萜类生物合成相关基因研究. 华中农业大学硕士学位论文,湖北武汉, 2016.
Cheng X. Research of Flavonoids and Terpenoids Biosynthesis Genes Based on Transcriptome and Co-expression Network Analysis. MS Thesis of Huazhong Agricultural University, Wuhan, Hubei, China, 2016. (in Chinese with English abstract)
[13] Yang Z R, Zhang H S, Li X K, Shen H M, Gao J H, Hou S Y, Zhang B, Mayes S, Bennett M, Ma J X, Wu C Y, Sui Y, Han Y H, Wang X C. A mini foxtail millet with an Arabidopsis-like life cycle as a C4 model system. Nat Plants, 2020, 6: 1167-1178.
doi: 10.1038/s41477-020-0747-7
[14] Andrews S. Babraham bioinformatics-FastQC a quality control tool for high throughput sequence data. Bioinformatics, 2010, 26: 774-798.
[15] Bolger A M, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics, 2014, 30: 2114-2120.
doi: 10.1093/bioinformatics/btu170
[16] Kim D, Langmead B, Salzberg S L. HISAT: a fast spliced aligner with low memory requirements. Nat Methods, 2015, 12: 357-360.
doi: 10.1038/NMETH.3317
[17] Pertea M, Pertea G M, Antonescu C M, Chang T C, Mendell J T, Salzberg S L. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol, 2015, 33: 290-295.
doi: 10.1038/nbt.3122
[18] Love M I, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol, 2014, 15: 550.
doi: 10.1186/s13059-014-0550-8
[19] Fornes O, Castro-Mondragon J A, Khan A, van der Lee R, Zhang X, Richmond P A, Modi B P, Correard S, Gheorghe M, Baranašić D, Santana-Garcia W, Tan G, Chèneby J, Ballester B, Parcy F, Sandelin A, Lenhard B, Wasserman W W, Mathelier A. JASPAR 2020: update of the open-access database of transcription factor binding profiles. Nucleic Acids Res, 2020, 48: D87-D92.
[20] Monniaux M, McKim S M, Cartolano M, Thévenon E, Parcy F, Tsiantis M, Hay A. Conservation vs divergence in LEAFY and APETALA1 functions between Arabidopsis thaliana and Cardamine hirsuta. New Phytol, 2017, 216: 549-561.
doi: 10.1111/nph.14419 pmid: 28098947
[21] Goslin K, Zheng B B, Serrano-Mislata A, Rae L, Ryan P T, Kwaśniewska K, Thomson B, Ó’Maoiléidigh D S, Madueño F, Wellmer F, Graciet E. Transcription factor interplay between LEAFY and APETALA1/CAULIFLOWER during floral initiation. Plant Physiol, 2017, 174: 1097-1109.
doi: 10.1104/pp.17.00098 pmid: 28385730
[22] Han Y Y, Zhang C, Yang H B, Jiao Y L. Cytokinin pathway mediates APETALA1 function in the establishment of determinate floral meristems in Arabidopsis. Proc Natl Acad Sci USA, 2014, 111: 6840-6845.
doi: 10.1073/pnas.1318532111
[23] Kim W C, Ko J H, Kim J Y, Kim J, Bae H J, Han K H. MYB 46directly regulates the gene expression of secondary wall- associated cellulose synthases in Arabidopsis. Plant J, 2013, 73: 26-36.
doi: 10.1111/j.1365-313x.2012.05124.x
[24] Kim W C, Kim J Y, Ko J H, Kim J, Han K H. Transcription factor MYB46 is an obligate component of the transcriptional regulatory complex for functional expression of secondary wall- associated cellulose synthases in Arabidopsis thaliana . J Plant Physiol, 2013, 170: 1374-1378.
doi: 10.1016/j.jplph.2013.04.012
[25] Zhong R, Ye Z H. MYB46 and MYB83 bind to the SMRE sites and directly activate a suite of transcription factors and secondary wall biosynthetic genes. Plant Cell Physiol, 2012, 53: 368-380.
doi: 10.1093/pcp/pcr185
[26] Wang X C, Wu J, Guan M L, Zhao C H, Geng P, Zhao Q. Arabidopsis MYB4 plays dual roles in flavonoid biosynthesis. Plant J, 2020, 101: 637-652.
doi: 10.1111/tpj.14570
[27] Lazakis C M, Coneva V, Colasanti J. ZCN8 encodes a potential orthologue of Arabidopsis FT florigen that integrates both endogenous and photoperiod flowering signals in maize. J Exp Bot, 2011, 62: 4833-4842.
doi: 10.1093/jxb/err129 pmid: 21730358
[28] Coneva V, Guevara D, Rothstein S J, Colasanti J. Transcript and metabolite signature of maize source leaves suggests a link between transitory starch to sucrose balance and the autonomous floral transition. J Exp Bot, 2012, 63: 5079-5092.
doi: 10.1093/jxb/ers158
[29] Mara C D, Huang T, Irish V F. The Arabidopsis floral homeotic proteins APETALA3 and PISTILLATA negatively regulate the BANQUO genes implicated in light signaling. Plant Cell, 2010, 22: 690-702.
doi: 10.1105/tpc.109.065946
[30] Kim K C, Lai Z, Fan B, Chen Z. Arabidopsis WRKY38 and WRKY62 transcription factors interact with histone deacetylase 19 in basal defense. Plant Cell, 2008, 20: 2357-2371.
doi: 10.1105/tpc.107.055566
[31] Mao P, Duan M R, Wei C H, Li Y. WRKY62 transcription factor acts downstream of cytosolic NPR1 and negatively regulates jasmonate-responsive gene expression. Plant Cell Physiol, 2007, 48: 833-842.
doi: 10.1093/pcp/pcm058
[32] Grunewald W, De Smet I, Lewis D R, Löfke C, Jansen L, Goeminne G, Vanden Bossche R, Karimi M, De Rybel B, Vanholme B, Teichmann T, Boerjan W, Van Montagu M C, Gheysen G, Muday G K, Friml J, Beeckman T. Transcription factor WRKY23 assists auxin distribution patterns during Arabidopsis root development through local control on flavonol biosynthesis. Proc Natl Acad Sci USA, 2012, 109: 1554-1559.
doi: 10.1073/pnas.1121134109
[33] Prát T, Hajný J, Grunewald W, Vasileva M, Molnár G, Tejos R, Schmid M, Sauer M, Friml J. WRKY23 is a component of the transcriptional network mediating auxin feedback on PIN polarity. PLoS Genet, 2018, 14: e1007177.
doi: 10.1371/journal.pgen.1007177
[34] Guo X Y, Wang Y, Zhao P X, Xu P, Yu G H, Zhang L Y, Xiong Y, Xiang C B. AtEDT1/HDG11 regulates stomatal density and water-use efficiency via ERECTA and E2Fa. New Phytol, 2019, 223: 1478-1488.
doi: 10.1111/nph.15861
[35] Cai X T, Xu P, Wang Y, Xiang C B. Activated expression of AtEDT1/HDG11 promotes lateral root formation in Arabidopsis mutant edt1 by upregulating jasmonate biosynthesis. J Integr Plant Biol, 2015, 57: 1017-1730.
doi: 10.1111/jipb.12347
[36] Yu L H, Wu S J, Peng Y S, Liu R N, Chen X, Zhao P, Xu P, Zhu J B, Jiao G L, Pei Y, Xiang C B. Arabidopsis EDT1/HDG11 improves drought and salt tolerance in cotton and poplar and increases cotton yield in the field. Plant Biotechnol J, 2016, 14: 72-84.
doi: 10.1111/pbi.12358
[37] Vanderauwera S, Vandenbroucke K, Inzé A, van de Cotte B, Mühlenbock P, De Rycke R, Naouar N, Van Gaever T, Van Montagu M C, Van Breusegem F. AtWRKY 15perturbation abolishes the mitochondrial stress response that steers osmotic stress tolerance in Arabidopsis. Proc Natl Acad Sci USA, 2012, 109: 20113-20118.
doi: 10.1073/pnas.1217516109
[38] Ge S T, Han X F, Xu X W, Shao Y M, Zhu Q K, Liu Y D, Du J, Xu J, Zhang S Q. WRKY15 suppresses tracheary element differentiation upstream of VND7 during xylem formation. Plant Cell, 2020, 32: 2307-2324.
doi: 10.1105/tpc.19.00689
[39] Gu Z Y, Men S Q, Zhu J, Hao Q, Tong N N, Liu Z A, Zhang H C, Shu Q Y, Wang L S. Chalcone synthase is ubiquitinated and degraded via interactions with a RING-H2 protein in petals of Paeonia‘he xie’. J Exp Bot, 2019, 70: 4749-4762.
doi: 10.1093/jxb/erz245
[40] 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)
[41] Gonzalez A, Zhao M Z, Leavitt J M, Lloyd A M. Regulation of the anthocyanin biosynthetic pathway by the TTG1/bHLH/Myb transcriptional complex in Arabidopsis seedlings. Plant J, 2008, 53: 814-827.
doi: 10.1111/j.1365-313X.2007.03373.x
[42] Mohamed H I, Latif H H. Improvement of drought tolerance of soybean plants by using methyl jasmonate. Physiol Mol Biol Plants, 2017, 23: 545-556.
doi: 10.1007/s12298-017-0451-x
[1] 王蓉, 陈小红, 王倩, 刘少雄, 陆平, 刁现民, 刘敏轩, 王瑞云. 中国谷子名米品种遗传多样性与亲缘关系研究[J]. 作物学报, 2022, 48(8): 1914-1925.
[2] 李佩婷, 赵振丽, 黄潮华, 黄国强, 徐良年, 邓祖湖, 张玉, 赵新旺. 基于转录组及WGCNA的甘蔗干旱响应调控网络分析[J]. 作物学报, 2022, 48(7): 1583-1600.
[3] 柯丹霞, 霍娅娅, 刘怡, 李锦颖, 刘晓雪. 大豆TGA转录因子基因GmTGA26在盐胁迫中的功能分析[J]. 作物学报, 2022, 48(7): 1697-1708.
[4] 郭楠楠, 刘天策, 史硕, 胡心亭, 牛亚丹, 李亮. 长链非编码RNA (LncRNA)在印度梨形孢促进大麦根部生长发育中的调控作用[J]. 作物学报, 2022, 48(7): 1625-1634.
[5] 朱峥, 王田幸子, 陈悦, 刘玉晴, 燕高伟, 徐珊, 马金姣, 窦世娟, 李莉云, 刘国振. 水稻转录因子WRKY68在Xa21介导的抗白叶枯病反应中发挥正调控作用[J]. 作物学报, 2022, 48(5): 1129-1140.
[6] 黄伟, 高国应, 吴金锋, 刘丽莉, 张大为, 周定港, 成洪涛, 张凯旋, 周美亮, 李莓, 严明理. 芥菜型油菜BjA09.TT8BjB08.TT8基因调节类黄酮的合成[J]. 作物学报, 2022, 48(5): 1169-1180.
[7] 陈悦, 孙明哲, 贾博为, 冷月, 孙晓丽. 水稻AP2/ERF转录因子参与逆境胁迫应答的分子机制研究进展[J]. 作物学报, 2022, 48(4): 781-790.
[8] 晋敏姗, 曲瑞芳, 李红英, 韩彦卿, 马芳芳, 韩渊怀, 邢国芳. 谷子糖转运蛋白基因SiSTPs的鉴定及其参与谷子抗逆胁迫响应的研究[J]. 作物学报, 2022, 48(4): 825-839.
[9] 杜晓芬, 王智兰, 韩康妮, 连世超, 李禹欣, 张林义, 王军. 谷子叶绿体基因RNA编辑位点的鉴定与分析[J]. 作物学报, 2022, 48(4): 873-885.
[10] 赵美丞, 刁现民. 谷子近缘野生种的亲缘关系及其利用研究[J]. 作物学报, 2022, 48(2): 267-279.
[11] 尹明, 杨大为, 唐慧娟, 潘根, 李德芳, 赵立宁, 黄思齐. 大麻GRAS转录因子家族的全基因组鉴定及镉胁迫下表达分析[J]. 作物学报, 2021, 47(6): 1054-1069.
[12] 葛敏, 王元琮, 宁丽华, 胡梦梅, 石习, 赵涵. 氮响应转录因子ZmNLP5影响玉米根系生长的功能研究[J]. 作物学报, 2021, 47(5): 807-813.
[13] 马贵芳, 满夏夏, 张益娟, 高豪, 孙朝霞, 李红英, 韩渊怀, 侯思宇. 谷子穗发育期转录组与叶酸代谢谱联合分析[J]. 作物学报, 2021, 47(5): 837-846.
[14] 贾小平, 李剑峰, 张博, 全建章, 王永芳, 赵渊, 张小梅, 王振山, 桑璐曼, 董志平. 谷子SiPRR37基因对光温、非生物胁迫的响应特点及其有利等位变异鉴定[J]. 作物学报, 2021, 47(4): 638-649.
[15] 邱红梅, 陈亮, 侯云龙, 王新风, 陈健, 马晓萍, 崔正果, 张玲, 胡金海, 王跃强, 邱丽娟. 大豆种子颜色遗传调控机制研究进展[J]. 作物学报, 2021, 47(12): 2299-2313.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 李绍清, 李阳生, 吴福顺, 廖江林, 李达模. 水稻孕穗期在淹涝胁迫下施肥的优化选择及其作用机理[J]. 作物学报, 2002, 28(01): 115 -120 .
[2] 王兰珍;米国华;陈范骏;张福锁. 不同产量结构小麦品种对缺磷反应的分析[J]. 作物学报, 2003, 29(06): 867 -870 .
[3] 杨建昌;张亚洁;张建华;王志琴;朱庆森. 水分胁迫下水稻剑叶中多胺含量的变化及其与抗旱性的关系[J]. 作物学报, 2004, 30(11): 1069 -1075 .
[4] 袁美;杨光圣;傅廷栋;严红艳. 甘蓝型油菜生态型细胞质雄性不育两用系的研究Ⅲ. 8-8112AB的温度敏感性及其遗传[J]. 作物学报, 2003, 29(03): 330 -335 .
[5] 王永胜;王景;段静雅;王金发;刘良式. 水稻极度分蘖突变体的分离和遗传学初步研究[J]. 作物学报, 2002, 28(02): 235 -239 .
[6] 王丽燕;赵可夫. 玉米幼苗对盐胁迫的生理响应[J]. 作物学报, 2005, 31(02): 264 -268 .
[7] 田孟良;黄玉碧;谭功燮;刘永建;荣廷昭. 西南糯玉米地方品种waxy基因序列多态性分析[J]. 作物学报, 2008, 34(05): 729 -736 .
[8] 胡希远;李建平;宋喜芳. 空间统计分析在作物育种品系选择中的效果[J]. 作物学报, 2008, 34(03): 412 -417 .
[9] 王艳;邱立明;谢文娟;黄薇;叶锋;张富春;马纪. 昆虫抗冻蛋白基因转化烟草的抗寒性[J]. 作物学报, 2008, 34(03): 397 -402 .
[10] 郑希;吴建国;楼向阳;徐海明;石春海. 不同环境条件下稻米组氨酸和精氨酸的胚乳和母体植株QTL分析[J]. 作物学报, 2008, 34(03): 369 -375 .