Journal of Integrative Agriculture ›› 2021, Vol. 20 ›› Issue (8): 2043-2055.DOI: 10.1016/S2095-3119(20)63220-8

所属专题：玉米遗传育种合辑Maize Genetics · Breeding · Germplasm Resources

• 论文 • 上一篇下一篇

收稿日期:2020-02-05 出版日期:2021-08-01 发布日期:2021-07-20

Comparative transcriptome analysis of different nitrogen responses in low-nitrogen sensitive and tolerant maize genotypes

DU Qing-guo^{1, 2*}, YANG Juan^1*, Shah SYED MUHAMMAD SADIQ¹, YANG Rong-xin¹, YU Jing-juan², LI Wen-xue¹

¹ National Engineering Laboratory for Crop Molecular Breeding/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China
² State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, P.R.China

Received:2020-02-05 Online:2021-08-01 Published:2021-07-20
Contact: Correspondence LI Wen-xue, Tel: +86-10-82105799, E-mail: liwenxue@caas.cn
About author:DU Qing-guo, E-mail: duqingguo2011@163.com; YANG Juan, E-mail: 13051377865@126.com; * These authors contributed equally to this study.
Supported by:
This work was supported by grants from the Ministry of Agriculture of China for Transgenic Research (2018ZX0800916B), the National Natural Science Foundation of China (31861143004) and the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences.

摘要/Abstract

摘要：

尽管目前的研究极大地促进了我们对于植物适应低氮胁迫的认知，但是关于不同作物基因型适应低氮胁迫能力不同的机制仍需要进一步探讨。本文中，我们根据田间条件下304份玉米自交系对低氮胁迫的耐受性，从中选择了Ye478（低氮胁迫敏感材料）和Qi319（耐受低氮胁迫材料）进行进一步的研究。首先我们对Ye478和Qi319正常氮水培和低氮水培的地上部和根部构建了16个转录组文库，并进行高通量测序。结果分析发现Qi319根系中特异上调表达的基因主要富集在代谢能相关途径，包括三羧酸代谢过程和烟酰胺代谢过程。在低氮胁迫处理5天后，仅在Ye478中观察到老叶变黄的表型；与Qi319相比，在Ye478地上部特异下调表达的基因主要与类囊体、叶绿体、光合膜和叶绿体基质等有关。对转录因子进行分析，共有216个转录因子在Ye478和Qi319之间差异表达，表明氮胁迫响应路径中的转录调控在不同作物基因型适应低氮胁迫中起重要作用。此外，在Ye478和Qi319中还发现了15个差异表达的miRNAs。综上所述，我们的研究有助于了解玉米耐受低氮胁迫的遗传变异和分子基础。

Abstract:

Although previous researches have greatly increased our general knowledge on plant responses to nitrogen (N) stress, a comprehensive understanding of the different responses in crop genotypes is still needed. This study evaluated 304 maize accessions for low-N tolerance under field conditions, and selected the low-N sensitive Ye478 and low-N tolerant Qi319 for further investigations. After a 5-day low-N treatment, the typical N-deficient phenotype with yellowing older leaves was observed in Ye478 but not in Qi319. After the 5-day low-N stress, 16 RNA libraries from leaf and root of Ye478 and Qi319 were generated. The differentially expressed genes (DEGs) in the root of Qi319 up-regulated by special N deficiency were mainly enriched in energy-related metabolic pathways, including tricarboxylic acid metabolic process and nicotinamide metabolic process. Consistent with yellowing older leaves only observed in Ye478, the special N deficiency-responsive DEGs related to thylakoid, chloroplast, photosynthetic membrane, and chloroplast stroma pathways were repressed by low-N stress in Ye478. A total of 216 transcription factors (TFs), including ZmNLP5, were identified as special N deficiency-responsive TFs between Qi319 and Ye478, indicating the importance of transcriptional regulation of N stress-responsive pathway in different tolerance to low-N stress between crop genotypes. In addition, 15 miRNAs were identified as DEGs between Qi319 and Ye478. Taken together, this study contributes to the understanding of the genetic variations and molecular basis of low-N tolerance in maize.

Key words: maize , genotype , nitrogen , RNA-seq , differentially expressed genes

. [J]. Journal of Integrative Agriculture, 2021, 20(8): 2043-2055.

DU Qing-guo, YANG Juan, Shah SYED MUHAMMAD SADIQ, YANG Rong-xin, YU Jing-juan, LI Wen-xue. Comparative transcriptome analysis of different nitrogen responses in low-nitrogen sensitive and tolerant maize genotypes[J]. Journal of Integrative Agriculture, 2021, 20(8): 2043-2055.

参考文献

Anders S, Pyl P T, Huber W. 2015. HTSeq – A Python framework to work with high-throughput sequencing data. Bioinformatics, 31, 166–169.
Araya T, Kubo T, von Wirén N, Takahashi H. 2015. Statistical modeling of nitrogen-dependent modulation of root system architecture in Arabidopsis thaliana. Journal of Integrative Plant Biology, 58, 254–265.
Bi Y M, Meyer A, Downs G S, Shi X, El-Kereamy A, Lukens L, Rothstein S J. 2004. High throughput RNA sequencing of a hybrid maize and its parents shows different mechanisms responsive to nitrogen limitation. BMC Genomics, 15, 77.
Bi Y M, Zhang Y, Signorelli T, Zhao R, Zhu T, Rothstein S. 2005. Genetic analysis of Arabidopsis GATA transcription factor gene family reveals a nitrate-inducible member important for chlorophyll synthesis and glucose sensitivity. The Plant Journal, 44, 680–692.
Cheirsilp B, Torpee S. 2012. Enhanced growth and lipid production of microalgae under mixotrophic culture condition: Effect of light intensity, glucose concentration and fed-batch cultivation. Bioresource Technology, 110, 510–516.
Cui Z, Zhang H, Chen X, Zhang C, Ma W, Huang C, Zhang W, Mi G, Miao Y, Li X, Gao Q, Yang J, Wang Z, Ye Y, Guo S, Lu J, Huang J, Lv S, Sun Y, Liu Y, et al. 2018. Pursuing sustainable productivity with millions of smallholder farmers. Nature, 555, 363–366.
Du Q, Wang K, Xu C, Zou C, Xie C, Xu Y, Li W X. 2016. Strand-specific RNA-Seq transcriptome analysis of genotypes with and without low-phosphorus tolerance provides novel insights into phosphorus-use efficiency in maize. BMC Plant Biology, 16, 222.
FAO (Food and Agricultural Organization of the United Nations). 2000. Fertilizer Requirements in 2015 and 2030. Food and Agricultural Organization of the United Nations, Rome.
Gao K, Chen F, Yuan L, Zhang F, Mi G. 2015. A comprehensive analysis of root morphological changes and nitrogen allocation in maize in response to low nitrogen stress. Plant, Cell & Environment, 38, 740–750.
Gao Z, Wang Y, Chen G, Zhang A, Yang S, Shang L, Wang D, Ruan B, Liu C, Jiang H, Dong G, Zhu L, Hu J, Zhang G, Zeng D, Guo L, Xu G, Teng S, Harberd N P, Qian Q. 2019. The indica nitrate reductase gene OsNR2 allele enhances rice yield potential and nitrogen use efficiency. Nature Communication, 10, 5207.
Ge M, Wang Y, Liu Y, Jiang L, He B, Ning L, Du H, Lv Y, Zhou L, Lin F, Zhang T, Liang S, Lu H, Zhao H. 2019. The NIN-like protein 5 (ZmNLP5) transcription factor is involved in modulating the nitrogen response in maize. The Plant Journal, 102, 353–368.
Gojon A, Nacry P, Davidian J C. 2009. Root uptake regulation: A central process for NPS homeostasis in plants. Current Opinion in Plant Biology, 12, 328–338.
Gruber B D, Giehl R F H, Friedel S, von Wirén N. 2013. Plasticity of the Arabidopsis root system under nutrient deficiencies. Plant Physiology, 163, 161–179.
Guo J H, Liu X J, Zhang Y, Shen L J, Han W X, Zhang W F, Christie P, Goulding K W, Vitousek P M, Zhang F S. 2010. Significant acidification in major Chinese croplands. Science, 327, 1008–1010.
Gutiérrez R A, Lejay L, Dean A, Chiaromonte F, Shasha D E, Coruzzi G M. 2007. Qualitative network models and genome-wide expression data define carbon/nitrogen-responsive molecular machines in Arabidopsis. Genome Biology, 8, 1–13.
Gutiérrez R A, Stokes T L, Thum K, Xu X, Obertello M, Katari M S, Tanurdzic M, Dean A, Nero D C, McClung C R, Coruzzi G M. 2008. Systems approach identifies an organic nitrogen-responsive gene network that is regulated by the master clock control gene CCA1. Proceedings of the National Academy of Sciences of the United States of America, 105, 4939–4944.
Huppe H C, Turpin D H. 1994. Integration of carbon and nitrogen metabolism in plant and algal cells. Annual Review of Plant Physiology and Plant Molecular Biology, 45, 577–607.
Ju X T, Xing G X, Chen X P, Zhang S L, Zhang L J, Liu X J, Cui Z L, Yin B, Christie P, Zhu Z L, Zhang F S. 2009. Reducing environmental risk by improving N management in intensive Chinese agricultural systems. Proceedings of the National Academy of Sciences of the United States of America, 106, 3041–3046.
Kim D, Langmead B, Salzberg S L. 2015. HISAT: A fast spliced aligner with low memory requirements. Nature Methods, 12, 357.
Kraiser T, Gras D E, Gutiérrez A G, González B, Gutiérrez R A. 2011. A holistic view of nitrogen acquisition in plants. Journal of Experimental Botany, 62, 1455–1466.
Li G, Cheng Q, Li L, Lu D, Lu W. 2021a. N, P and K use efficiency and maize yield responses to fertilization modes and densities. Journal of Integrative Agriculture, 20, 78–86.
Li G, Cheng G, Lu W, Lu D. 2021b. Differences of yield and nitrogen use efficiency under different applications of slow release fertilizer in spring maize. Journal of Integrative Agriculture, 20, 554–564.
Liang G, He H, Yu D. 2012. Identification of nitrogen starvation-responsive microRNAs in Arabidopsis thaliana. PLoS ONE, 7, e48951.
Maresma Á, Ariza M, Martínez E, Lloveras J, Martínez-Casasnovas J. 2016. Analysis of vegetation indices to determine nitrogen application and yield prediction in maize (Zea mays L.) from a standard UAV service. Remote Sensing, 8, 973.
McLaren J S. 2005. Crop biotechnology provides an opportunity to develop a sustainable future. Trends in Biotechnology, 23, 339–342.
Miller A J, Fan X, Orsel M, Smith S J, Wells D M. 2007. Nitrate transport and signaling. Journal of Experimental Botany, 58, 2292–2306.
Mu X, Chen Q, Chen F, Yuan L, Mi G. 2017. A RNA-seq analysis of the response of photosynthetic system to low nitrogen supply in maize leaf. International Journal of Molecular Sciences, 18, 2624.
Neuffer M G, Sheridan W F. 1980. Defective kernel mutants of maize. I. Genetic and lethality studies. Genetics, 95, 929–944.
Noctor G, Foyer C H. 1998. Ascorbate and glutathione: Keeping active oxygen under control. Annual Review of Plant Physiology and Plant Molecular Biology, 49, 249–279.
Palenchar P M, Kouranov A, Lejay L V, Coruzzi G M. 2004. Genome-wide patterns of carbon and nitrogen regulation of gene expression validate the combined carbon and nitrogen (CN)-signaling hypothesis in plants. Genome Biology, 5, R91.
Peng B, Li Y, Wang Y, Liu C, Liu Z, Tan W, Zhang Y, Wang D, Shi Y, Sun B, Song Y, Wang T, Li Y. 2011. QTL analysis for yield components and kernel-related traits in maize across multi-environments. Theoretical and Applied Genetics, 122, 1305–1320.
Pertea M, Pertea G M, Antonescu C M, Chang T C, Mendell J T, Salzberg S L. 2015. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nature Biotechnology, 33, 290.
Robinson M D, McCarthy D J, Smyth G K. 2010. EdgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 26, 139–140.
Stitt M, Muller C, Matt P, Gibon Y, Carillo P, Morcuende R, Scheible W R, Krapp A. 2002. Steps towards an integrated view of nitrogen metabolism. Journal of Experimental Botany, 53, 959–970.
Sun Q, Liu X, Yang J, Liu W, Du Q, Wang H, Fu C, Li W X. 2018. MicroRNA528 affects lodging resistance of maize by regulating lignin biosynthesis under nitrogen-luxury conditions. Molecular Plant, 11, 806–814.
Sunkar R, Kapoor A, Zhu J K. 2006. Posttranscriptional induction of two Cu/Zn superoxide dismutase genes in Arabidopsis is mediated by downregulation of miR398 and important for oxidative stress tolerance. The Plant Cell, 18, 2051–2065.
Tang W, Ye J, Yao X, Zhao P, Xuan W, Tian Y, Zhang Y, Xu S, An H, Chen G, Yu J, Wu W, Ge Y, Liu X, Li J, Zhang H, Zhao Y, Yang B, Jiang X, Peng C, et al. 2019. Genome-wide associated study identifies NAC42-activated nitrate transporter conferring high nitrogen use efficiency in rice. Nature Communication, 10, 5279.
Tian T, Liu Y, Yan H, You Q, Yi X, Du Z, Xu W, Su Z. 2017. agriGO v2.0: A GO analysis toolkit for the agricultural community. Nucleic Acids Research, 45, W122–W129.
Vidal E, Gutiérrez R A. 2008. A systems view of nitrogen nutrient and metabolite responses in Arabidopsis. Current Opinion in Plant Biology, 11, 521–529.
Wang R, Okamoto M, Xing X, Crawford N M. 2003. Microarray analysis of the nitrate response in Arabidopsis roots and shoots reveals over 1 000 rapidly responding genes and new linkages to glucose, trehalose-6-phosphate, iron, and sulfate metabolism. Plant Physiology, 132, 556–567.
Wang R, Xing X, Crawford N. 2007. Nitrite acts as transcriptome signal at micromolar concentrations in Arabidopsis roots, Plant Physiology, 145, 1735–1745.
Wang X, Zhang Y, Xu X, Li H, Wu X, Zhang S, Li X. 2014. Evaluation of maize inbred lines currently used in Chinese breeding programs for resistance to six foliar diseases. The Crop Journal, 2, 213–222.
Wang Y, Mi G H, Chen F J, Zhang J H, Zhang F S. 2004. Response of root morphology to nitrate supply and its contribution to nitrogen accumulation in maize. Journal of Plant Nutrition, 27, 2189–2202.
Wu J, Lawit S J, Weers B, Sun J, Mongar N, Van Hemert J, Melo R, Meng X, Rupe M, Clapp J, Haug Collet K, Trecker L, Roesler K, Peddicord L, Thomas J, Hunt J, Zhou W, Hou Z, Wimmer M, Jantes J, et al. 2019. Overexpression of zmm28 increases maize grain yield in the field. Proceedings of the National Academy of Sciences of the United States of America, 116, 23850–23858.
Ye J, Zhang Y, Cui H, Liu J, Wu Y, Cheng Y, Xu H, Huang H, Li S, Zhou A, Zhang X, Bolund L, Chen Q, Wang J, Yang H, Fang L, Shi C. 2018. WEGO 2.0: a web tool for plotting GO annotation. Nucleic Acids Research, 46, W71–W75.
Zhang C, Zhou Z, Yong H, Zhang X, Hao Z, Zhang F, Li M, Zhang D, Li X, Wang Z, Weng J. 2017. Analysis of the genetic architecture of maize ear and grain morphological traits by combined linkage and association mapping. Theoretical and Applied Genetics, 130, 1011–1029.
Zhang H, Forde B G. 1998. An Arabidopsis MADS box gene that controls nutrient-induced changes in root architecture. Science, 279, 407–409.
Zhang X, Davidson E A, Mauzerall D L, Searchinger T D, Dumas P, Shen Y. 2015. Managing nitrogen for sustainable development. Nature, 528, 51–59.
Zhao M, Tai H, Sun S, Zhang F, Xu Y, Li W X. 2012. Cloning and characterization of maize miRNAs involved in responses to nitrogen deficiency. PLoS ONE, 7, e29669.

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