Welcome to Acta Agronomica Sinica，

Acta Agronomica Sinica ›› 2024, Vol. 50 ›› Issue (12): 2998-3012.doi: 10.3724/SP.J.1006.2024.42023

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Metabolome and transcriptome analysis reveal molecular response to drought stress in indica rice Fuxiangzhan

WANG Ying-Heng1,2(), CUI Li-Li1,2, CAI Qiu-Hua1,2, LIN Qiang1,2, WU Fang-Xi1,2, CHEN Fei-He1,2, XIE Hong-Guang1,2, ZHU Yong-Sheng1,2, CHEN Li-Ping1,2, XIE Hua-An1,2, ZHANG Jian-Fu1,2,*()   

  1. 1Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou 350019, Fujian, China
    2Key Laboratory of Germplasm Innovation and Molecular Breeding of Hybrid Rice for South China, Ministry of Agriculture and Rural Affairs / Fuzhou Branch, National Rice Improvement Center of China / Fujian Engineering Laboratory of Crop Molecular Breeding / Fujian Key Laboratory of Rice Molecular Breeding / Incubator of National Key Laboratory of Fujian Germplasm Innovation and Molecular Breeding Between Fujian and Ministry of Sciences & Technology / Base of South China, National Key Laboratory of Hybrid Rice / National Rice Engineering Laboratory of China, Fuzhou 350003, Fujian, China
  • Received:2024-05-08 Accepted:2024-08-15 Online:2024-12-12 Published:2024-09-02
  • Contact: *E-mail: jianfzhang@163.com
  • Supported by:
    Natural Science Foundation of Fujian Province(2022J01451);Collaborative Innovation Project “5511” of Fujian Provincial People’s Government and Chinese Academy of Agricultural Sciences(XTCXGC2021001);Science and Technology Innovation Team of Fujian Academy of Agricultural Sciences(CXTD2021001)

RichHTML431

29

PDF

452

Abstract:

Drought is one of the most significant factors affecting agricultural production. In this study, the physiological indexes, hormone metabolites, and gene expression regulation network of drought response were analyzed for the high grain quality fragrant rice Fuxiangzhan. After drought stress, Fuxiangzhan exhibited higher drought survival rates and antioxidant enzyme activity compared to restorer lines Minghui63, Minghui86, and the drought-sensitive line Lijiangxintuanheigu, while showing lower membrane iron leakage and less peroxide accumulation. Five hormone metabolites (IAA, ICA, ABA, cZ, and SA) increased, whereas 11 hormone metabolites, including tZ, DHZ, GA1, and JA, decreased. A total of 6118 differentially expressed genes (DEGs) were identified, including 2615 up-regulated and 3503 down-regulated genes, which are involved in biological processes such as photosynthesis, energy metabolism, transcriptional regulation, REDOX, and ion binding, as well as molecular functions related to amino acids, sugars, fatty acids, hormones, and other anabolic metabolism and plant hormone signal transduction. KEGG pathways involving plant hormone signal transduction, zein biosynthesis, carotenoid biosynthesis, and tryptophan metabolism were identified from hormone metabolites and transcriptome analysis. Differentially expressed gene regulatory networks of the four pathways were constructed. The expression levels of 28 drought response genes related to transcription factors, antioxidant enzymes, and osmotic regulation were all up-regulated after drought stress in Fuxiangzhan. Our conclusion is that the hormone levels in Fuxiangzhan change after drought stress. The expression of anti-stress genes, including transcription factors, antioxidant system genes, osmoregulation, and other drought tolerance genes, were up-regulated. These changes lead to alterations in the activity of antioxidant enzymes and other physiological indexes. These results are helpful for further exploration of drought-resistant genes and serve in rice drought resistance breeding.

Key words: Fuxiangzhan, drought resistance, physiological properties, hormone metabolome, regulatory network

Table S1

qRT-PCR primer sequence"

基因登录号
Gene ID		 基因符号
Gene symbol		 上游引物
Forward primer (5′-3′)		 下游引物
Reverse primer (5′-3′)
LOC_Os01g63770 OsAUX1 TGATGGTCGTCATGGCTTATAA GAGGAATCGCCGATTACAATTG
LOC_Os03g08850 OsAFB5 CTGATAAATAGCCAGCCTGAGA GACTCCAGCTATCTTACCTTCC
LOC_Os01g53880 OsIAA6 ACCTGATCTTAACTCCGTGTTT TTCTACACTCAACTTAGGCTGG
LOC_Os04g56850 OsARF11 CAGCCTGTCATTGATTCGATTT TACTGTTTTGCTCCGAAGTACT
LOC_Os01g69920 OsHk3 GTTTCATGGACATACAGATGCC ATAGCCATCCATTTCGCTTTTC
LOC_Os07g25710 OsPHR2 TCTTCAGTTTCAAGCAATGAGC CCAGCTGCAATAGAACTGTTTT
LOC_Os05g38290 OsPP2C49 CGTGATCCGCCATTATTATTGG ATCGCAGGAGTAAATTAGGAGG
LOC_Os05g49730 OsPP2C51 CGAAGTTGTAGTAGCCGGAG CTTCACCGACCGGATTCTCTTC
LOC_Os01g64970 OsSAPK4 GTTTGTGTGCAGCTATTGTGTA CGCCAAACAGAAGCAAATTTAC
LOC_Os07g25590 OsTDC2 ATTGTTTGCCCTTCGAGTATTG TCAAACGACCTAACCCACTAAA
LOC_Os11g43900 OsTCTP CGTTCAAGGAGCTATTGATGTG GTCACAAACTGCTTCTTGTCAA
LOC_Os07g25540 OsYUCCA6 CTCAAGGGAAGTGACTTCTTCA TTGTGAAGCCAACAGAGTAGAG
LOC_Os01g07500 OsTAR2 CTTCTGCAACTTCACCAAGGAG AATCCTCCACATCCTCCCTATC
LOC_Os04g31040 OsVDE GGTGAAACAGGACTTGATGAAC TTACTTGTTGCCTTGTACTTGC
LOC_Os07g05940 OsNCED4 GCGACAAGCTTAGCTCAAATTA GCTAAACTATTTCAACTCCCTAGC
LOC_Os02g47510 OsNCED1 AGCACCAATGATACAAACCAAC TGTGTGCACTTATACTACGTGT
LOC_Os12g42280 OsNCED5 TTTGCTTTGCTTGTACAGACAG CACTGCAACTATCCCTATCACT
LOC_Os06g39880 OsCYP734A4 GCTAGCTAGGAAAAGACAGGAA GTACCACTAGTCTGTTAGCGAG

Fig. 1

Effects of drought stress on four rice varieties A: plants morphology before drought stress and after rehydration; B: survival rate; C: leaf relative electrical conductivity; D: activities of superoxide dismutase; E: peroxidase; F: catalase; G: malondialdehyde concentration; H: hydrogen peroxide; I: NBT staining. FXZ: Fuxiangzhan; MH63: Minghui 63; MH86: Minghui 86; LTH: Lijiangxintuanheigu; CK: control; DS: drought treatment. Data are presented as mean ± standard deviation (n = 3), different lowercase letters indicate significant differences at the 0.05 probability level."

Fig. 2

Hormone metabolite analysis of Fuxiangzhan under drought stress and normal conditions A: OPLS-DA score chart (x axis represents the difference between groups, y axis represents the difference within groups, and the parameters of the model are marked below the chart); B: volcano map of differential metabolites (each point in the volcano map represents a metabolite, x axis represents the value of log2 for the multiple change of each substance in the group, and y axis represents the value of log10 for the P-value of t-test); C: differential metabolic clustering heat map (x axis is each sample, y axis is the quantitative value of metabolites standardized by Z-score after hierarchical clustering, and the color bar above distinguishes different groups); D: KEGG enrichment network diagram of differential metabolites (light yellow nodes are pathways, and the small nodes connected to them are specific metabolites annotated to this pathway, and the depth of color indicates the fold change value of log2, which shows five pathways); CK: control; DS: drought treatment."

Fig. 3

Transcriptome analysis of Fuxiangzhan under drought stress and normal conditions A: the heatmap of transcriptome; B: volcano plot of genes; C: the number of differentially expressed genes; D: GO enrichment of DEGs (the vertical axis represents go entries, the horizontal axis represents -log10 (Q-value), and numbers represents the number of enriched genes in the terms); E: KEGG enrichment of DEGs (the vertical axis represents the enriched KEGG pathway, the horizontal axis represents the ratio of enriched genes, the dot size represents the number of enriched genes in the pathway, and the color represents the Q-value); CK: control; DS: drought treatment."

Fig. 4

Correlation analysis of hormone metabolite and transcriptome A: nine-quadrant diagram illustrating the correlation of hormone metabolites and genes. B: venn diagram showing the number of hormone metabolite and transcriptome pathways significantly changed (followed by a list of the four pathways at both the metabolite and gene levels); CK: control; DS: drought treatment."

Fig. 5

Hormone biosynthesis and signal transduction regulatory of Fuxiangzhan in response to drought stress Red indicates up regulation and purple indicates down regulation. CK indicates untreated; DS indicates drought treated. The heat map shows up-regulated gene expression in red and down-regulated gene expression in purple. Small circles represent metabolites, red up-regulated, green down-regulated. The boxes represent gene products, with red representing up-regulation, green representing down-regulation, and blue representing both up-regulation and down-regulation. CK: control; DS: drought treatment; TAM: tryptamine; IAN: indole-3-acetonitrile; IAAld: indole acetaldehyde; IPyA: indole pyruvate; IAOX: indole acetaldehyde stain; IAM: indole acetamide; Trp: tryptophan."

Fig. 6

qRT-PCR verified of DEGs The black column represents the FPKM value of RNA-seq, and the red line represents the relative expression of qRT-PCR. The left vertical axis is the FPKM value of RNA-seq, and the right vertical axis is the relative expression of qRT-PCR. CK: control; DS: drought treatment. Data are presented as mean ± standard deviation (n = 4), different lowercase letters indicate significant differences at the 0.05 probability level."

Fig. 7

Changes of hormone-related metabolic pathway gene expression in Fuxiangzhan and Lijiangxintuanheigu before and after drought treatment FXZ: Fuxiangzhan; LTH: Lijiangxintuanheigu; CK: control, DS: drought treatment. Data are presented as mean ± standard deviation (n = 4), different lowercase letters indicate significant differences at the 0.05 probability level."

Fig. 8

Heatmap of the expression level of key genes in drought tolerance under drought stress CK: control; DS: drought treatment; log2(FC) indicates the fold change value of log2."

[1] Gupta A, Rico-Medina A, Caño-Delgado A I. The physiology of plant responses to drought. Science, 2020, 368: 266-269.
doi: 10.1126/science.aaz7614 pmid: 32299946
[2] Zhang C M, Shi S L, Liu Z, Yang F, Yin G L. Drought tolerance in alfalfa (Medicago sativa L.) varieties is associated with enhanced antioxidative protection and declined lipid peroxidation. J Plant Physiol, 2019, 232: 226-240.
[3] McAdam S A M, Brodribb T J. Mesophyll cells are the main site of abscisic acid biosynthesis in water-stressed leaves. Plant Physiol, 2018, 177: 911-917.
doi: 10.1104/pp.17.01829 pmid: 29735726
[4] Kuromori T, Seo M, Shinozaki K. ABA transport and plant water stress responses. Trends Plant Sci, 2018, 23: 513-522.
doi: S1360-1385(18)30085-2 pmid: 29731225
[5] Takahashi F, Suzuki T, Osakabe Y, Betsuyaku S, Kondo Y, Dohmae N, Fukuda H, Yamaguchi-Shinozaki K, Shinozaki K. A small peptide modulates stomatal control via abscisic acid in long-distance signalling. Nature, 2018, 556: 235-238.
[6] Mega R, Abe F, Kim J S, Tsuboi Y, Tanaka K, Kobayashi H, Sakata Y, Hanada K, Tsujimoto H, Kikuchi J, Cutler S R, Okamoto M. Tuning water-use efficiency and drought tolerance in wheat using abscisic acid receptors. Nat Plants, 2019, 5: 153-159.
doi: 10.1038/s41477-019-0361-8 pmid: 30737511
[7] Okamoto M, Peterson F C, Defries A, Park S Y, Endo A, Nambara E, Volkman B F, Cutler S R. Activation of dimeric ABA receptors elicits guard cell closure, ABA-regulated gene expression, and drought tolerance. Proc Natl Acad Sci USA, 2013, 110: 12132-12137.
doi: 10.1073/pnas.1305919110 pmid: 23818638
[8] Park S Y, Peterson F C, Mosquna A, Yao J, Volkman B F, Cutler S R. Agrochemical control of plant water use using engineered abscisic acid receptors. Nature, 2015, 520: 545-548.
[9] Chen J N, Yin Y H. WRKY transcription factors are involved in brassinosteroid signaling and mediate the crosstalk between plant growth and drought tolerance. Plant Signal Behav, 2017, 12: e1365212.
[10] Xie Z L, Nolan T, Jiang H, Tang B Y, Zhang M C, Li Z H, Yin Y. The AP2/ERF transcription factor TINY modulates brassinosteroid-regulated plant growth and drought responses in Arabidopsis. Plant Cell, 2019, 31: 1788-1806.
[11] Luo L J. Breeding for water-saving and drought-resistance rice (WDR) in China. J Exp Bot, 2010, 61: 3509-3517.
doi: 10.1093/jxb/erq185 pmid: 20603281
[12] Sun X, Xiong H, Jiang C, Zhang D, Yang Z, Huang Y, Zhu W, Ma S, Duan J, Wang X, Liu W, Guo H, Li G, Qi J, Liang C, Zhang Z, Li J, Zhang H, Han L, Zhou Y, Peng Y, Li Z. Natural variation of DROT1 confers drought adaptation in upland rice. Nat Commun, 2022, 13: 4265-4281.
[13] Zhang Q F. Strategies for developing Green Super Rice. Proc Natl Acad Sci USA, 2007, 104: 16402-16409.
doi: 10.1073/pnas.0708013104 pmid: 17923667
[14] 吴方喜, 罗翠琴, 王颖姮, 谢云杰, 罗曦, 朱永生, 谢鸿光, 蒋家焕, 蔡秋华, 谢华安, 张建福. 优质、抗病、耐储藏香稻新品种福香占的选育与应用. 福建农业学报, 2022, 37: 683-690.
Wu F X, Luo C Q, Wang Y H, Xie Y J, Luo X, Zhu Y S, Xie H G, Jiang J H, Cai Q H, Xie H A, Zhang J F. Breeding and application of high-quality, blast-resistant, long-shelf-life fragrant Fuxiangzhan rice. Fujian J Agric Sci, 2022, 37: 683-690 (in Chinese with English abstract).
[15] 丁红, 张智猛, 徐扬, 张冠初, 郭庆, 秦斐斐, 戴良香. 氮素缓解花生干旱胁迫的生理和转录调控机制. 作物学报, 2023, 49: 225-238.
doi: 10.3724/SP.J.1006.2023.24020
Ding H, Zhang Z M, Xu Y, Zhang G C, Guo Q, Qin F F, Dai L X. Physiological and transcriptional regulation mechanisms of nitrogen alleviating drought stress in peanut. Acta Agron Sin, 2023, 49: 225-238 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2023.24020
[16] 陈力, 王靖, 邱晓, 孙海莲, 张文浩, 王天佐. 不同耐旱性紫花苜蓿干旱胁迫下生理响应和转录调控的差异研究. 作物学报, 2022, 49: 2122-2132.
Chen L, Wang J, Qiu X, Sun H L, Zhang W H, Wang T Z. Differences of physiological responses and transcriptional regulation of alfalfa with different drought tolerances under drought stresses. Acta Agron Sin, 2022, 49: 2122-2132 (in Chinese with English abstract).
[17] Liu H H, Ma Y, Chen N, Guo S Y, Liu H L, Guo X Y, Chong K, Xu Y Y. Overexpression of stress-inducible OsBURP16, the β subunit of polygalacturonase 1, decreases pectin content and cell adhesion and increases abiotic stress sensitivity in rice. Plant Cell Environ, 2014, 37: 1144-1158.
[18] Šimura J, Antoniadi I, Široká J, Tarkowská D, Strnad M, Ljung K, Novák O. Plant hormonomics: multiple phytohormone profiling by targeted metabolomics. Plant Physiol, 2018, 177: 476-489.
doi: 10.1104/pp.18.00293 pmid: 29703867
[19] Kim D, Paggi J M, Park C, Bennett C, Salzberg S L. Graph-based genome alignment and genotyping with HISAT2 and HISAT- genotype. Nat Biotechnol, 2019, 37: 907-915.
[20] 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.
[21] Wu T, Hu E, Xu S, Chen M, Guo P, Dai Z, Feng T, Zhou L, Tang W, Zhan L, Fu X, Liu S, Bo X, Yu G. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation (Camb), 2021, 2: 100141.
[22] Xie C, Mao X Z, Huang J J, Ding Y, Wu J M, Dong S, Kong L, Gao G, Li C Y, Wei L P. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res, 2011, 39: W316-W322.
[23] Dinneny J R. Developmental responses to water and salinity in root systems. Annu Rev Cell Dev Biol, 2019, 35: 239-257.
doi: 10.1146/annurev-cellbio-100617-062949 pmid: 31382759
[24] Lu Y, Yang W, Qi Z, Gao R, Tong J, Gao T, Zhang Y, Sun A, Zhang S, Ge J. Gut microbe-derived metabolite indole-3-carboxaldehyde alleviates atherosclerosis. Signal Transduct Target Ther, 2023, 8: 378.
[25] Cao X, Yang H L, Shang C Q, Ma S, Liu L, Cheng J L. The roles of auxin biosynthesis YUCCA gene family in plants. Int J Mol Sci, 2019, 20: 6343.
[26] Domingo C, Andrés F, Tharreau D, Iglesias D J, Talón M. Constitutive expression of OsGH3.1 reduces auxin content and enhances defense response and resistance to a fungal pathogen in rice. Mol Plant Microbe Interact, 2009, 22: 201-210.
[27] Tschaplinski T J, Tuskan G A, Gebre G M, Todd D E. Drought resistance of two hybrid Populus clones grown in a large-scale plantation. Tree Physiol, 1998, 18: 653-658.
pmid: 12651414
[28] Chen K, Li G J, Bressan R A, Song C P, Zhu J K, Zhao Y. Abscisic acid dynamics, signaling, and functions in plants. J Integr Plant Biol, 2020, 62: 25-54.
doi: 10.1111/jipb.12899
[29] Joo J, Lee Y H, Song S I. Overexpression of the rice basic leucine zipper transcription factor OsbZIP12 confers drought tolerance to rice and makes seedlings hypersensitive to ABA. Plant Biotechnol Rep, 2014, 8: 431-441.
[30] Zhang C, Li C, Liu J, Lv Y, Yu C, Li H, Zhao T, Liu B. The OsABF1 transcription factor improves drought tolerance by activating the transcription of COR413-TM1 in rice. J Exp Bot, 2017, 68: 4695-4707.
[31] Hossain M A, Cho J I, Han M, Ahn C H, Jeon J S, An G, Park P B. The ABRE-binding bZIP transcription factor OsABF2 is a positive regulator of abiotic stress and ABA signaling in rice. J Plant Physiol, 2010, 167: 1512-1520.
[32] Mathan J, Singh A, Ranjan A. Sucrose transport in response to drought and salt stress involves ABA-mediated induction of OsSWEET13 and OsSWEET15 in rice. Physiol Plant, 2021, 171: 620-637.
[33] Tang N, Zhang H, Li X, Xiao J, Xiong L. Constitutive activation of transcription factor OsbZIP46 improves drought tolerance in rice. Plant Physiol, 2012, 158: 1755-1768.
[34] Xiang Y, Tang N, Du H, Ye H Y, Xiong L Z. Characterization of OsbZIP23 as a key player of the basic leucine zipper transcription factor family for conferring abscisic acid sensitivity and salinity and drought tolerance in rice. Plant Physiol, 2008, 148: 1938-1952.
doi: 10.1104/pp.108.128199 pmid: 18931143
[35] Yuan X, Wang H, Cai J, Bi Y, Li D, Song F. Rice NAC transcription factor ONAC066 functions as a positive regulator of drought and oxidative stress response. BMC Plant Biol, 2019, 19: 278.
doi: 10.1186/s12870-019-1883-y pmid: 31238869
[36] Lee D K, Chung P J, Jeong J S, Jang G, Bang S W, Jung H, Kim Y S, Ha S H, Choi Y D, Kim J K. The rice OsNAC6 transcription factor orchestrates multiple molecular mechanisms involving root structural adaptions and nicotianamine biosynthesis for drought tolerance. Plant Biotechnol J, 2017, 15: 754-764.
[37] Shen H, Liu C, Zhang Y, Meng X, Zhou X, Chu C, Wang X. OsWRKY30 is activated by MAP kinases to confer drought tolerance in rice. Plant Mol Biol, 2012, 80: 241-253.
[38] Jung H, Chung P J, Park S H, Redillas M C F R, Kim Y S, Suh J W, Kim J K. Overexpression of OsERF48 causes regulation of OsCML16, a calmodulin-like protein gene that enhances root growth and drought tolerance. Plant Biotechnol J, 2017, 15: 1295-1308.
[39] Tang Y, Bao X, Zhi Y, Wu Q, Guo Y, Yin X, Zeng L, Li J, Zhang J, He W, Liu W, Wang Q, Jia C, Li Z, Liu K. Overexpression of a MYB family gene, OsMYB6, increases drought and salinity stress tolerance in transgenic rice. Front Plant Sci, 2019, 10: 168.
[40] Ahmad I, Devonshire J, Mohamed R, Schultze M, Maathuis F J M. Overexpression of the potassium channel TPKb in small vacuoles confers osmotic and drought tolerance to rice. New Phytol, 2016, 209: 1040-1048.
doi: 10.1111/nph.13708 pmid: 26474307
[1] RONG Yu-Xuan, HUI Liu-Yang, WANG Pei-Qi, SUN Si-Min, ZHANG Xian-Long, YUAN Dao-Jun, YANG Xi-Yan. Identification of the CLE gene family in Gossypium hirsutum and functional analysis of the drought resistance of GhCLE13 [J]. Acta Agronomica Sinica, 2024, 50(12): 2925-2939.
[2] ZHU Xu-Dong, YANG Lan-Feng, CHEN Yuan-Yuan, HOU Ze-Hao, LUO Yi-Rou, XIONG Ze-Hao, FANG Zheng-Wu. Biological functional analysis of common buckwheat (Fagopyrum esculentum) FeSGT1 gene in enhancing drought stress resistance [J]. Acta Agronomica Sinica, 2023, 49(6): 1573-1583.
[3] MENG Yu, TIAN Wen-Zhong, WEN Peng-Fei, DING Zhi-Qiang, ZHANG Xue-Pin, HE Li, DUAN Jian-Zhao, LIU Wan-Dai, GUO Tian-Cai, FENG Wei. Comprehensive evaluation of drought resistance of wheat varieties based on synergy of different developmental stages [J]. Acta Agronomica Sinica, 2023, 49(2): 570-582.
[4] ZHOU Wen-Qi, QIANG Xiao-Xia, LI Si-Yu, WANG Sen, WEI Wan-Rong. Identification of a rolling leaf allelic mutant e202 and fine mapping of E202 gene in rice [J]. Acta Agronomica Sinica, 2023, 49(11): 3029-3041.
[5] WANG Yun-Qi, GAO Fu-Li, LI Ao, GUO Tong-Ji, QI Liu-Ran, ZENG Huan-Yu, ZHAO Jian-Yun, WANG Xiao-Ge, GAO Guo-Ying, YANG Jia-Peng, BAI Jin-Ze, MA Ya-Huan, LIANG Yue-Xin, ZHANG Rui. Variation of ear temperature after anthesis and its relationship with yield in wheat [J]. Acta Agronomica Sinica, 2022, 48(9): 2400-2408.
[6] LI Pei-Ting, ZHAO Zhen-Li, HUANG Chao-Hua, HUANG Guo-Qiang, XU Liang-Nian, DENG Zu-Hu, ZHANG Yu, ZHAO Xin-Wang. Analysis of drought responsive regulatory network in sugarcane based on transcriptome and WGCNA [J]. Acta Agronomica Sinica, 2022, 48(7): 1583-1600.
[7] JIAN Hong-Ju, ZHANG Mei-Hua, SHANG Li-Na, WANG Ji-Chun, HU Bai-Geng, Vadim Khassanov, LYU Dian-Qiu. Screening candidate genes involved in potato tuber development using WGCNA [J]. Acta Agronomica Sinica, 2022, 48(7): 1658-1668.
[8] WANG Xing-Rong, LI Yue, ZHANG Yan-Jun, LI Yong-Sheng, WANG Jun-Cheng, XU Yin-Ping, QI Xu-Sheng. Drought resistance identification and drought resistance indexes screening of Tibetan hulless barley resources at adult stage [J]. Acta Agronomica Sinica, 2022, 48(5): 1279-1287.
[9] ZHAO Jia-Jia, QIAO Ling, WU Bang-Bang, GE Chuan, QIAO Lin-Yi, ZHANG Shu-Wei, YAN Su-Xian, ZHENG Xing-Wei, ZHENG Jun. Seedling root characteristics and drought resistance of wheat in Shanxi province [J]. Acta Agronomica Sinica, 2021, 47(4): 714-727.
[10] HAN Bei, WANG Xu-Wen, LI Bao-Qi, YU Yu, TIAN Qin, YANG Xi-Yan. Association analysis of drought tolerance traits of upland cotton accessions (Gossypium hirsutum L.) [J]. Acta Agronomica Sinica, 2021, 47(3): 438-450.
[11] Yin-Ping XU, Yong-Dong PAN, Qiang-De LIU, Yuan-Hu YAO, Yan-Chun JIA, Cheng REN, Ke-Cang HUO, Wen-Qing CHEN, Feng ZHAO, Qi-Jun BAO, Hua-Yu ZHANG. Drought resistance identification and drought resistance indexes screening of barley resources at mature period [J]. Acta Agronomica Sinica, 2020, 46(3): 448-461.
[12] ZHANG Xiao-Xiao,PAN Ying-Hong,REN Fu-Li,PU Wei-Jun,WANG Dao-Ping,LI Yu-Bin,LU Ping,LI Gui-Ying,ZHU Li. Establishment of an accurate evaluation method for drought resistance based on multilevel phenotype analysis in sorghum [J]. Acta Agronomica Sinica, 2019, 45(11): 1735-1745.
[13] WANG Can,ZHOU Ling-Bo,ZHANG Guo-Bing,ZHANG Li-Yi,XU Yan,GAO Xu,JIANG Ne,SHAO Ming-Bo. Identification and Indices Screening of Drought Resistance at Adult Plant Stage in Job’s Tears Germplasm Resources [J]. Acta Agron Sin, 2017, 43(09): 1381-1394.
[14] DO Thanh-Trung, LI Jian, ZHANG Feng-Juan, YANG Li-Tao, LI Yang-Rui,XING Yong-Xiu. Analysis of Differential Proteome in Relation to Drought Resistance in Sugarcane [J]. Acta Agron Sin, 2017, 43(09): 1337-1346.
[15] XU Wen,SHEN Hao,GUO Jun,YU Xiao-Cong,LI Xiang,YANG Yan-Hui,MA Xiao,ZHAO Shi-Jie,SONG Jian-Min. Drought Resistance of Wheat NILs with Different Cuticular Wax Contents in Flag Leaf [J]. Acta Agron Sin, 2016, 42(11): 1700-1707.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] WANG Li-Yan;ZHAO Ke-Fu. Some Physiological Response of Zea mays under Salt-stress[J]. Acta Agron Sin, 2005, 31(02): 264 -268 .
[2] Qi Zhixiang;Yang Youming;Zhang Cunhua;Xu Chunian;Zhai Zhixi. Cloning and Analysis of cDNA Related to the Genes of Secondary Wall Thickening of Cotton (Gossypium hirsutum L.) Fiber[J]. Acta Agron Sin, 2003, 29(06): 860 -866 .
[3] NI Da-Hu;YI Cheng-Xin;LI Li;WANG Xiu-Feng;ZHANG Yi;ZHAO Kai-Jun;WANG Chun-Lian;ZHANG Qi;WANG Wen-Xiang;YANG Jian-Bo. Developing Rice Lines Resistant to Bacterial Blight and Blast with Molecular Marker-Assisted Selection[J]. Acta Agron Sin, 2008, 34(01): 100 -105 .
[4] DAI Xiao-Jun;LIANG Man-Zhong;CHEN Liang-Bi. Comparison of rDNA Internal Transcribed Spacer Sequences in Oryza sativa L.[J]. Acta Agron Sin, 2007, 33(11): 1874 -1878 .
[5] WANG Bao-Hua;WU Yao-Ting;HUANG Nai-Tai;GUO Wang-Zhen;ZHU Xie-Fei;ZHANG Tian-Zhen. QTL Analysis of Epistatic Effects on Yield and Yield Component Traits for Elite Hybrid Derived-RILs in Upland Cotton[J]. Acta Agron Sin, 2007, 33(11): 1755 -1762 .
[6] WANG Chun-Mei;FENG Yi-Gao;ZHUANG Li-Fang;CAO Ya-Ping;QI Zeng-Jun;BIE Tong-De;CAO Ai-Zhong;CHEN Pei-Du. Screening of Chromosome-Specific Markers for Chromosome 1R of Secale cereale, 1V of Haynaldia villosa and 1Rk#1 of Roegneria kamoji[J]. Acta Agron Sin, 2007, 33(11): 1741 -1747 .
[7] Zhao Qinghua;Huang Jianhua;Yan Changjing. A STUDY ON THE POLLEN GERMINATION OF BRASSICA NAPUS L.[J]. Acta Agron Sin, 1986, (01): 15 -20 .
[8] ZHOU Lu-Ying;LI Xiang-Dong;WANG Li-Li;TANG Xiao;LIN Ying-Jie. Effects of Different Ca Applications on Physiological Characteristics, Yield and Quality in Peanut[J]. Acta Agron Sin, 2008, 34(05): 879 -885 .
[9] WANG Li-Xin; LI Yun-Fu; CHANG Li-Fang; HUANG Lan ;; LI Hong-Bo ; GE Ling-Ling; Liu Li-Hua ;; YAO Ji ;; ZHAO Chang-Ping ;. Method of ID Constitution for Wheat Cultivars[J]. Acta Agron Sin, 2007, 33(10): 1738 -1740 .
[10] ZHENG Tian-Qing;XU Jian-Long;FU Bing-Ying;GAO Yong-Ming;Satish VERUKA;Renee LAFITTE;ZHAI Hu-Qu;WAN Jian-Min;ZHU Ling-Hua;LI Zhi-Kang. Preliminary Identification of Genetic Overlaps between Sheath Blight Resistance and Drought Tolerance in the Introgression Lines from Directional Selection[J]. Acta Agron Sin, 2007, 33(08): 1380 -1384 .
Add: No. 80 Xueyuan South Rd, Beijing 100081, P. R. China E-mail: zwxb301@caas.cn
Supported by Beijing Magtech Co.Ltd