基于RNA-Seq筛选高粱低氮胁迫相关候选基因

doi:10.3724/SP.J.1006.2024.34055

作物学报 ›› 2024, Vol. 50 ›› Issue (3): 669-685.doi: 10.3724/SP.J.1006.2024.34055

• 作物遗传育种·种质资源·分子遗传学 • 上一篇下一篇

基于RNA-Seq筛选高粱低氮胁迫相关候选基因

王瑞¹(), 张福耀¹, 詹鹏杰¹, 楚建强¹, 晋敏姗², 赵威军¹, 程庆军¹^,^*()

¹山西农业大学高粱研究所 / 高粱遗传与种质创新山西省重点实验室, 山西晋中 030600
²西北农林科技大学农学院, 陕西杨凌 712100

收稿日期:2023-03-16 接受日期:2023-10-23 出版日期:2024-03-12 网络出版日期:2023-11-17
通讯作者: *程庆军, E-mail: chqj7002@163.com
作者简介:E-mail: wangrui989@163.com
基金资助:
国家自然科学基金项目(32272164);山西省回国留学人员科研资助项目(2020-161);“十四五”生物育种工程项目(YZGC058)

Identification of candidate genes implicated in low-nitrogen-stress tolerance based on RNA-Seq in sorghum

WANG Rui¹(), ZHANG Fu-Yao¹, ZHAN Peng-Jie¹, CHU Jian-Qiang¹, JIN Min-Shan², ZHAO Wei-Jun¹, CHENG Qing-Jun¹^,^*()

¹Institute of Sorghum, Shanxi Agricultural University / Key Laboratory of Genetic and Germplasm Innovation in Sorghum for Shanxi, Jinzhong 030600, Shanxi, China
²College of Agronomy, Northwest A&F University, Yangling 712100, Shaanxi, China

Received:2023-03-16 Accepted:2023-10-23 Published:2024-03-12 Published online:2023-11-17
Contact: *E-mail: chqj7002@163.com
Supported by:
National Natural Science Foundation of China(32272164);Shanxi Scholarship Council of China(2020-161);“14th Five-Year Plan” Biological Breeding Project(YZGC058)

摘要/Abstract

摘要：

研究低氮胁迫条件下不同高粱材料间的基因差异表达, 为耐低氮型高粱品种选育和耐低氮胁迫的分子机制探究提供参考。选取2个耐低氮型高粱(BSX44和BTx378)为试验材料, 设置正常和低氮胁迫2个处理, 利用RNA-Seq技术对高粱苗期、抽穗期和开花期的基因表达进行分析, 通过生物信息学对差异基因的生物学功能和代谢途径进行研究, 筛选可能参与低氮调控的基因, 了解氮高效基因型在氮素吸收利用过程中可能的分子途径。结果表明, 在正常和低氮胁迫下, BTx378和BSX44在苗期分别筛选出937个和787个差异表达基因, 抽穗期分别筛选出1305个和935个差异表达基因, 开花期分别筛选出1402个和963个差异表达基因。对3个时期的差异表达基因进行鉴定, 发现在苗期、抽穗期和开花期分别有246、371和306个基因在2个耐低氮高粱品种中共同差异表达, 有28个基因在2个耐低氮品种的不同生育时期均差异表达, 其中有5个基因上调表达, 23个基因下调表达; 对共同差异表达基因的KEGG相关代谢通路富集分析, 发现主要集中在氮代谢、丙氨酸, 天冬氨酸和谷氨酸代谢、甘油磷脂代谢、氨基酸的生物合成等途径, 表明耐低氮型高粱可能通过这些途径相关基因的表达影响其对低氮胁迫的耐受性。

关键词: 高粱, 转录组测序, 低氮胁迫, 差异表达基因(DEGs)

Abstract:

The objective of this study is to explore gene differential expression between different sorghum materials under low nitrogen stress conditions and to provide the references for probing into the breeding of low-nitrogen-tolerant sorghum varieties and the molecular mechanism of low-nitrogen-stress tolerance in sorghum. Two low-nitrogen-tolerant sorghum varieties (BSX44 and BTx378) were selected as experimental materials, and both of them were subjected to normal-growth treatment and low-nitrogen-stress treatment respectively before the gene expression of sorghum was detected at seedling stage, heading stage and flowering stage via RNA-Seq technology. The biological functions and metabolic pathways of the differentially expressed genes (DEGs) were analyzed by bioinformatics to screen genes that may be involved in the low-nitrogen regulation, and to understand the possible molecular pathways for nitrogen efficient materials in the process of nitrogen absorption and utilization. The results showed that: For BTx378 and BSX44, under normal-growth and low-nitrogen-stress treatments, 937 and 787 DEGs were detected at the seedling stage, 1305 and 935 at the heading stage, and 1402 and 963 at the flowering stage, for BTx378 and BSX44 respectively. Then the converged DEGs at the three stages were identified, and it was found that 246 genes were differentially expressed in the two low-nitrogen-tolerant sorghum varieties at the seedling stage, 371 at the heading stage, and 306 at the flowering stage. Furthermore, a total of 28 genes were consistently detected as DEGs at all three stages in the two low-nitrogen tolerant varieties, among which 5 genes were up-regulated and 23 genes were down-regulated. The KEGG analysis of the 28 common DEGs showed that they were mainly enriched in nitrogen metabolism, alanine, aspartic acid and glutamic acid metabolism, glycerophospholipid metabolism, and amino acid biosynthesis. This suggested that regulation of the genes in these pathways mainly affects the low nitrogen stress tolerance in sorghum.

Key words: sorghum, transcriptome sequencing, low nitrogen stress, differentially expressed genes (DEGs)

王瑞, 张福耀, 詹鹏杰, 楚建强, 晋敏姗, 赵威军, 程庆军. 基于RNA-Seq筛选高粱低氮胁迫相关候选基因[J]. 作物学报, 2024, 50(3): 669-685.

WANG Rui, ZHANG Fu-Yao, ZHAN Peng-Jie, CHU Jian-Qiang, JIN Min-Shan, ZHAO Wei-Jun, CHENG Qing-Jun. Identification of candidate genes implicated in low-nitrogen-stress tolerance based on RNA-Seq in sorghum[J]. Acta Agronomica Sinica, 2024, 50(3): 669-685.

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共同差异表达基因相关信息"

序号	基因编号	基因功能注释
Number	Gene ID	Gene function annotation
1	Sb01g006100↓	铁氧还蛋白——NADP还原酶, 根同工酶, 叶绿体 Ferredoxin—NADP reductase, root isozyme, chloroplastic
2	Sb01g007010↓	PAC2家族 PAC2 family
3	Sb01g015190↑	异天冬酰胺肽酶/L-天冬酰胺酶1亚基β Isoaspartyl peptidase/L-asparaginase 1 subunit beta
4	Sb01g023750↓	丙氨酸转氨酶2 Alanine aminotransferase 2
5	Sb01g029470↓	硝酸盐转运蛋白1.1 POT家族 Nitrate transporter 1.1 POT family
6	Sb01g032250↑	二酰基甘油激酶1 Diacylglycerol kinase 1
7	Sb02g006060↓	抗病蛋白RPM1 Disease resistance protein RPM1
8	Sb02g042310↓	磷脂酶A1-Igamma2, 叶绿体 Phospholipase A1-Igamma2, chloroplastic
9	Sb03g012720↓	磷脂酶D p1 Phospholipase D p1
10	Sb03g036210↓	紫色酸性磷酸酶2 Purple acid phosphatase 2
11	Sb03g045170↑	蛋白SRG1 Protein SRG1
12	Sb04g005740↓	细胞色素P450 71D10 Cytochrome P450 71D10
13	Sb04g006250↓	氯通道样蛋白CLC-g Putative chloride channel-like protein CLC-g
14	Sb04g006740↓	枯草杆菌蛋白酶Subtilisin-like protease
15	Sb04g021010↓	甘油磷酸二酯磷酸二酯酶家族 Glycerophosphoryl diester phosphodiesterase family
16	Sb04g032280↓	分歧的CRAL/TRIO域 Divergent CRAL/TRIO domain
17	Sb04g034160↓	铁氧还蛋白——亚硝酸盐还原酶, 叶绿体 Ferredoxin—nitrite reductase, chloroplastic
18	Sb04g035040↓	20 kD伴侣蛋白, 叶绿体20 kD chaperonin, chloroplastic
19	Sb05g016820↓	精氨酸/丝氨酸蛋白45 Arginine/serine-rich protein 45
20	Sb06g016540↓	脱落胁迫成熟蛋白2 Abscisic stress-ripening protein 2
21	Sb06g025950↑	含SPX结构域的膜蛋白 SPX domain-containing membrane protein
22	Sb06g031460↓	谷氨酰胺合成酶, 叶绿体Glutamine synthetase, chloroplastic
23	Sb07g008300↓	紫色酸性磷酸酶15 Purple acid phosphatase 15
24	Sb07g026000↓	营养细胞壁蛋白gp1 Vegetative cell wall protein gp1
25	Sb07g028630↑	含BTB/POZ结构域的蛋白 BTB/POZ domain-containing protein
26	Sb08g003180↓	转录因子GLK2 Probable transcription factor GLK2
27	Sb09g028090↓	营养细胞壁蛋白gp1 Vegetative cell wall protein gp1
28	Sorghum_bicolor_newGene_166↓	未知蛋白Unknown protein

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参考文献 53

[1]	Morris G P, Ramu P, Deshpande S P, Hash C T, Shah T, Upadhyaya H D, Riera-Lizarazu O, Brown P J, Acharya C B, Mitchell S E, Harriman J, Glaubitz J C, Buckler E S, Kresovich S. Population genomic and genome-wide association studies of agroclimatic traits in sorghum. Proc Natl Acad Sci USA, 2013, 110: 453-458. doi: 10.1073/pnas.1215985110 pmid: 23267105
[2]	李顺国, 刘猛, 刘斐, 邹剑秋, 陆晓春, 刁现民. 中国高粱产业和种业发展现状与未来展望. 中国农业科学, 2021, 54: 471-482. doi: 10.3864/j.issn.0578-1752.2021.03.002
	Li S G, Liu M, Liu F, Zou J Q, Lu X C, Diao X M. Current status and future prospective of sorghum production and seed industry in China. Sci Agric Sin, 2021, 54: 471-482 (in Chinese with English abstract). doi: 10.3864/j.issn.0578-1752.2021.03.002
[3]	邹剑秋, 王艳秋, 柯福来. 高粱产业发展现状及前景展望. 山西农业大学学报(自然科学版), 2020, 40(3): 2-8.
	Zou J Q, Wang Y Q, Ke F L. Developing situation and prospect forecast of sorghum industry in China. J Shanxi Agric Univ (Nat Sci Edn), 2020, 40(3): 2-8 (in Chinese with English abstract).
[4]	张福耀, 平俊爱, 赵威军. 中国酿造高粱品质遗传改良研究进展. 农学学报, 2019, 9(3): 21-25. doi: 10.11923/j.issn.2095-4050.cjas18030019
	Zhang F Y, Ping J A, Zhao W J. Genetic quality improvement of brewing sorghum in China: research progress. J Agric, 2019, 9(3): 21-25 (in Chinese with English abstract). doi: 10.11923/j.issn.2095-4050.cjas18030019
[5]	李嵩博, 唐朝臣, 陈峰, 谢光辉. 中国粒用高粱改良品种的产量和品质性状时空变化. 中国农业科学, 2018, 51: 246-256. doi: 10.3864/j.issn.0578-1752.2018.02.005
	Li S B, Tang C C, Chen F, Xie G H. Temporal and spatial changes in yield and quality with grain sorghum variety improvement in China. Sci Agric Sin, 2018, 51: 246-256 (in Chinese with English abstract). doi: 10.3864/j.issn.0578-1752.2018.02.005
[6]	Vogan P J, Sage R F. Water-use efficiency and nitrogen-use efficiency of C(3)-C(4) intermediate species of Flaveria juss. (Asteraceae). Plant Cell Environ, 2011, 34: 1415-1430. doi: 10.1111/pce.2011.34.issue-9
[7]	Liu X J, Zhang Y, Han W X, Tang A H, Shen J L, Cui Z L, Vitousek P, Erisman J W, Goulding K, Christie P, Fangmeier A, Zhang F S. Enhanced nitrogen deposition over China. Nature, 2013, 494: 459-462. doi: 10.1038/nature11917
[8]	Yang Y Y, Liu L, Zhang F, Zhang X Y, Xu W, Liu X J, Li Y, Wang Z, Xie Y W. Enhanced nitrous oxide emissions caused by atmospheric nitrogen deposition in agroecosystems over China. Environ Sci Pollut Res Int, 2021, 28: 15350-15360. doi: 10.1007/s11356-020-11591-5
[9]	米国华. 论作物养分效率及其遗传改良. 植物营养与肥料学报, 2017, 23: 1525-1535.
	Mi G H. Nutrient use efficiency in crops and its genetic improvement. J Plant Nutr Fert, 2017, 23: 1525-1535 (in Chinese with English abstract).
[10]	凌宏清, 袁力行. 我国作物养分高效研究的现状与未来发展趋势. 中国基础科学, 2016, 18(2): 54-60.
	Ling H Q, Yuan L X. Research status of crop nutrient efficiency and its future development in China. China Basic Sci, 2016, 18(2): 54-60 (in Chinese with English abstract).
[11]	Tantray A Y, Hazzazi Y, Ahmad A. Physiological, agronomical, and proteomic studies reveal crucial players in rice nitrogen use efficiency under low nitrogen supply. Int J Mol Sci, 2022, 23: 6410. doi: 10.3390/ijms23126410
[12]	Hou M M, Yu M, Li Z Q, Ai Z Y, Chen J G. Molecular regulatory networks for improving nitrogen use efficiency in rice. Int J Mol Sci, 2021, 22: 9040. doi: 10.3390/ijms22169040
[13]	Tang W J, Ye J, Yao X M, Zhao P Z, Xuan W, Tian Y L, Zhang Y Y, Xu S, An H Z, Chen G M, Yu J, Wu W, Ge Y W, Liu X L, Li J, Zhang H Z, Zhao Y Q, Yang B, Jiang X Z, Peng C, Zhou C, Terzaghi W, Wang C M, Wan J M. Genome-wide associated study identifies NAC42-activated nitrate transporter conferring high nitrogen use efficiency in rice. Nat Commun, 2019, 10: 5279. doi: 10.1038/s41467-019-13187-1 pmid: 31754193
[14]	Gao Z Y, Wang Y F, Chen G, Zhang A P, Yang S L, Shang L G, Wang D Y, Ruan B P, Liu C L, Jiang H Z, Dong G J, Zhu L, Hu J, Zhang G H, Zeng D L, Guo L B, Xu G H, Teng S, Harberd N P, Qian Q. The indica nitrate reductase gene OsNR2 allele enhances rice yield potential and nitrogen use efficiency. Nat Commun, 2019, 10: 5207. doi: 10.1038/s41467-019-13110-8 pmid: 31729387
[15]	Lupini A, Preiti G, Badagliacca G, Abenavoli M R, Sunseri F, Monti M, Bacchi M. Nitrogen use efficiency in durum wheat under different nitrogen and water regimes in the Mediterranean Basin. Front Plant Sci, 2021, 11: 607226. doi: 10.3389/fpls.2020.607226
[16]	Cormier F, Gouis J L, Dubreuil P, Lafarge S, Praud S. A genome-wide identification of chromosomal regions determining nitrogen use efficiency components in wheat (Triticum aestivum L.). Theor Appl Genet, 2014, 127: 2679-2693. doi: 10.1007/s00122-014-2407-7 pmid: 25326179
[17]	Sandhu N, Kaur A, Sethi M, Kaur S, Varinderpal-Singh, Sharma A, Bentley A R, Barsby T, Chhuneja P. Genetic dissection uncovers genome-Wide marker-trait associations for plant growth, yield, and yield-related traits under varying nitrogen levels in nested synthetic wheat introgression libraries. Front Plant Sci, 2021, 12: 738710. doi: 10.3389/fpls.2021.738710
[18]	Ciampitti I A, Lemaire G. From use efficiency to effective use of nitrogen: a dilemma for maize breeding improvement. Sci Total Environ, 2022, 826: 154125. doi: 10.1016/j.scitotenv.2022.154125
[19]	Simons M, Saha R, Guillard L, Clément G, Armengaud P, Cañas R, Maranas C D, Lea P J, Bertrand Hirel B. Nitrogen-use efficiency in maize (Zea mays L.): from ‘omics’ studies to metabolic modelling. J Exp Bot, 2014, 65: 5657-5671. doi: 10.1093/jxb/eru227
[20]	Gallais A, Hirel B. An approach to the genetics of nitrogen use efficiency in maize. J Exp Bot, 2004, 55: 295-306. doi: 10.1093/jxb/erh006 pmid: 14739258
[21]	刘鹏, 武爱莲, 王劲松, 南江宽, 董二伟, 焦晓燕, 平俊爱, 白文斌. 不同基因型高粱的氮效率及对低氮胁迫的生理响应. 中国农业科学, 2018, 51: 3074-3083. doi: 10.3864/j.issn.0578-1752.2018.16.004
	Liu P, Wu A L, Wang J S, Nan J K, Dong E W, Jiao X Y, Ping J A, Bai W B. Nitrogen use efficiency and physiological responses of different sorghum genotypes influenced by nitrogen deficiency. Sci Agric Sin, 2018, 51: 3074-3083 (in Chinese with English abstract). doi: 10.3864/j.issn.0578-1752.2018.16.004
[22]	Singh P, Kumar K, Jha A K, Yadava P, Pal M, Rakshit S, Singh I. Global gene expression profiling under nitrogen stress identifies key genes involved in nitrogen stress adaptation in maize (Zea mays L.). Sci Rep, 2022, 12: 4211. doi: 10.1038/s41598-022-07709-z
[23]	Ge L H, Dou Y N, Li M M, Qu P J, He Z, Liu Y, Xu Z S, Chen J, Chen M, Ma Y Z. SiMYB3 in foxtail millet (Setaria italica) confers tolerance to low-nitrogen stress by regulating root growth in transgenic plants. Int J Mol Sci, 2019, 20: 5741. doi: 10.3390/ijms20225741
[24]	Sultana N, Islam S, Juhasz A, Yang R C, She M Y, Alhabbar Z, Zhang J J, Ma W J. Transcriptomic study for identification of major nitrogen stress responsive genes in australian bread wheat cultivars. Front Genet, 2020, 11: 583785. doi: 10.3389/fgene.2020.583785
[25]	Ding Q Q, Wang X T, Hu L Q, Qi X, Ge L H, Xu W Y, Xu Z S, Zhou Y B, Jia G Q, Diao X M, Min D H, Ma Y Z, Chen M. MYB-like transcription factor SiMYB42 from foxtail millet (Setaria italica L.) enhances Arabidopsis tolerance to low-nitrogen stress. Hereditas, 2018, 40: 327-338.
[26]	Yan H S, Shi H W, Hu C M, Luo M Z, Xu C J, Wang S G, Li N, Tang W S, Zhou Y B, Wang C X, Xu Z S, Chen J, Ma Y Z, Sun D Z, Chen M. Transcriptome differences in response mechanisms to low-nitrogen stress in two wheat varieties. Int J Mol Sci, 2021, 22: 12278. doi: 10.3390/ijms222212278
[27]	Zhang C J, Hou Y Q, Hao Q N, Chen H F, Chen L M, Yuan S L, Shan Z H, Zhang X J, Yang Z L, Qiu D Z, Zhou X N, Huang W J. Genome-wide survey of the soybean GATA transcription factor gene family and expression analysis under low nitrogen stress. PLoS One, 2015, 10: e0125174. doi: 10.1371/journal.pone.0125174
[28]	Jagadhesan B, Sathee L, Meena H S, Jha S K, Chinnusamy V, Kumar A, Kumar S. Genome wide analysis of NLP transcription factors reveals their role in nitrogen stress tolerance of rice. Sci Rep, 2020, 10: 9368. doi: 10.1038/s41598-020-66338-6 pmid: 32523127
[29]	Gelli M, Duo Y C, Konda A R, Zhang C, Holding D, Dweikat I. Identification of differentially expressed genes between sorghum genotypes with contrasting nitrogen stress tolerance by genome-wide transcriptional profiling. BMC Genomics, 2014, 15: 179. doi: 10.1186/1471-2164-15-179 pmid: 24597475
[30]	Zhu Z X, Li D, Wang P, Li J H, Lu X C. Transcriptome and ionome analysis of nitrogen, phosphorus and potassium interactions in sorghum seedlings. Theor Exp Plant Physiol, 2020, 32: 271-285. doi: 10.1007/s40626-020-00183-w
[31]	Massel K, Campbell B C, Mace E S, Tai S S, Tao Y F, Worland B G, Jordan D R, Botella J R, Godwin I D. Whole genome sequencing reveals potential new targets for improving nitrogen uptake and utilization in Sorghum bicolor. Front Plant Sci, 2016, 7: 1544. pmid: 27826302
[32]	王瑞, 平俊爱, 张福耀, 詹鹏杰, 楚建强. 高粱育种资源耐瘠性鉴定及评价. 作物杂志, 2020, (6): 30-37.
	Wang R, Ping J A, Zhang F Y, Zhan P J, Chu J Q. Identification and evaluation of sorghum breeding resources for barren tolerance. Crops, 2020, (6): 30-37 (in Chinese with English abstract).
[33]	Chalmel F, Lardenois A, Thompson J D, Muller J, Sahel J-A, Léveillard T, Poch O. GOAnno: GO annotation based on multiple alignment. Bioinformatics, 2005, 21: 2095-2096. pmid: 15647299
[34]	Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res, 2000, 28: 27-30. doi: 10.1093/nar/28.1.27 pmid: 10592173
[35]	Kanehisa M, Araki M, Goto S, Hattor M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, Yamanishi Y. KEGG for linking genomes to life and the environment. Nucleic Acids Res, 2008, 36: D480-D484. doi: 10.1093/nar/gkm882 pmid: 18077471
[36]	Mao X Z, Cai T, Olyarchuk J G, Wei L P. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics, 2005, 21: 3787-3793. doi: 10.1093/bioinformatics/bti430 pmid: 15817693
[37]	Miyake K, Ito T, Senda M, Ishikawa R, Harada T, Niizeki M, Akada S. Isolation of a subfamily of genes for R2R3-MYB transcription factors showing up-regulated expression under nitrogen nutrient-limited conditions. Plant Mol Biol, 2003, 53: 237-245. pmid: 14756320
[38]	Lea U S, Slimestad R, Smedvig P, Lillo C. Nitrogen deficiency enhances expression of specific MYB and bHLH transcription factors and accumulation of end products in the flavonoid pathway. Planta, 2007, 225: 1245-1253. doi: 10.1007/s00425-006-0414-x pmid: 17053893
[39]	胡利斧. 谷子低氮胁迫转录组分析及SiMYB3基因特性与功能鉴定. 中国农业科学院硕士学位论文, 北京, 2015.
	Hu L F. Transcriptome Analysis of Foxtail millet (Setaria italic) under Low Nitrogen Stress and Characteristics and Functional Identification of SiMYB3. MS Thesis of Chinese Academy of Agricultural Sciences, Beijing, China, 2015 (in Chinese with English abstract).
[40]	张玉宁, 史宏志, 王景, 周炎, 杨惠娟. 高、低硝态氮营养条件下烟草根系基因表达谱及代谢途径的差异分析. 烟草科技, 2019, 52(4): 1-8.
	Zhang Y N, Shi H Z, Wang J, Zhou Y, Yang H J. Analysis of gene expression profile and metabolic pathway of tobacco root at high and low levels of nitrate nitrogen. Tobacco Sci Technol, 2019, 52(4): 1-8 (in Chinese with English abstract).
[41]	刘天奇, 高红秀, 谢威, 张雪晴, 陈娜娜, 梅雪锋, 邢佳妮, 徐振华, 张忠臣. 水稻分蘖期氮素应答的转录组动态分析. 华北农学报, 2021, 36(1): 44-53. doi: 10.7668/hbnxb.20191406
	Liu T Q, Gao H X, Xie W, Zhang X Q, Chen N N, Mei X F, Xing J N, Xu Z H, Zhang Z C. Dynamic transcriptome analysis of rice response to nitrogen treatment at tillering stage. Acta Agric Boreali-Sin, 2021, 36(1): 44-53 (in Chinese with English abstract). doi: 10.7668/hbnxb.20191406
[42]	Less H, Galili G. Principal transcriptional programs regulating plant amino acid metabolism in response to abiotic stresses. Plant Physiol, 2008, 147: 316-330. doi: 10.1104/pp.108.115733 pmid: 18375600
[43]	王娇, 李萍, 宗毓铮, 张东升, 史鑫蕊, 杨净, 郝兴宇. 大气CO₂浓度和气温升高对玉米灌浆期碳氮代谢的影响. 中国生态农业学报, 2023, 31: 325-335.
	Wang J, Li P, Zong Y Z, Zhang D S, Shi X R, Yang J, Hao X Y. Effects of increased atmospheric CO₂ concentration and temperature on carbon and nitrogen metabolism in maize at the grain filling stage. Chin J Eco-Agric, 2023, 31: 325-335 (in Chinese with English abstract).
[44]	师进霖, 陈恩波, 姜跃丽. PEG6000渗透胁迫对甜瓜幼苗叶片渗透调节物质及膜脂过氧化的影响. 西北农业学报, 2010, 19(1): 186-189.
	Shi J L, Chen E B, Jiang Y L. Effect of osmotic stress with PEG6000 on smolytes and lipid peroxidation in muskmelon seedling leaves. Acta Agric Boreali-occident Sin, 2010, 19(1): 182-185 (in Chinese with English abstract).
[45]	Warth B, Parich A, Bueschl C, Schoefbeck D, Neumann NKN, Kluger B, Schuster K, Krska R, Adam G, Lemmens M, Schuhmacher R. GC-MS based targeted metabolic profiling identifies changes in the wheat metabolome following deoxynivalenol treatment. Metabolomics, 2015, 11: 722-738. pmid: 25972772
[46]	Dhiman A, Nanda A, Ahmad S A. Quest for staunch effects of flavonoids: utopian protection against hepatic ailments. Arab J Chem, 2012, 12: 1702-1711.
[47]	Masclaux D C, Daniel V F, Dechorgnat J, Chardon F, Gaufichon L, Suzuki A. Nitrogen uptake, assimilation and remobilization in plants: challenges for sustainable and productive agriculture. Ann Bot, 2010, 105: 1141-1157. doi: 10.1093/aob/mcq028
[48]	Xu G, Fan X R, Miller A J. Plant nitrogen assimilation and use efficiency. Annu Rev Plant Biol, 2012, 63: 153-182. doi: 10.1146/annurev-arplant-042811-105532 pmid: 22224450
[49]	Krapp A. Plant nitrogen assimilation and its regulation: a complex puzzle with missing pieces. Curr Opin Plant Biol, 2015, 25: 115-122. doi: 10.1016/j.pbi.2015.05.010 pmid: 26037390
[50]	Ohashi M, Ishiyama K, Kojima S, Konishi N, Nakano K, Kanno K, Hayakawa T, Yamaya T. Asparagine synthetase1, but not asparagine synthetase2, is responsible for the biosynthesis of asparagine following the supply of ammonium to rice roots. Plant Cell Physiol, 2015, 56: 769-778. doi: 10.1093/pcp/pcv005 pmid: 25634963
[51]	王嘉文, 吴刚, 徐云敏. 谷氨酰胺合成酶在植物氮同化及再利用中的研究进展. 分子植物育种, 2019, 17: 1373-1377.
	Wang J W, Wu G, Xu Y M. Research progress of glutamine synthetase in plant nitrogen assimilation and recycling. Mol Plant Breed, 2019, 17: 1373-1377 (in Chinese with English abstract).
[52]	Zhong C, Cao X C, Hu J J, Zhu L F, Zhang J H, Huang J L, Jin Q Y. Nitrogen metabolism in adaptation of photosynthesis to water stress in rice grown under different nitrogen levels. Front Plant Sci, 2017, 8: 1079. doi: 10.3389/fpls.2017.01079 pmid: 28690622
[53]	姜苏育. 低氮营养对小麦幼苗根系生长与氮素吸收利用的影响及其生理机制. 南京农业大学博士学位论文, 江苏南京, 2018.
	Jiang S Y. Effects of N-deficiency Supply on Root Growth and Nitrogen Uptake in Wheat Seedlings and its Physiological Mechanism. PhD Dissertation of Nanjing Agricultural University, Nanjing, Jiangsu, China, 2018 (in Chinese with English abstract).

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品种 Variety	生育期 Growth stage	处理Treatment
品种 Variety	生育期 Growth stage	正常氮Normal nitrogen	低氮Low nitrogen
BTx378	苗期 Seedling stage	T1 (NN-R1-S1)	T4 (LN-R1-S1)
	抽穗期 Heading stage	T2 (NN-R1-S2)	T5 (LN-R1-S2)
	开花期 Flowering stage	T3 (NN-R1-S3)	T6 (LN-R1-S3)
BSX44	苗期 Seedling stage	T7 (NN-R2-S1)	T10 (LN-R2-S1)
	抽穗期 Heading stage	T8 (NN-R2-S2)	T11 (LN-R2-S2)
	开花期 Flowering stage	T9 (NN-R2-S3)	T12 (LN-R2-S3)

对比组 Compare group		对照组vs处理组 Control group vs Treatment group
A	1	T1 vs T4	NN-R1-S1 vs LN-R1-S1	正常氮-BTx378-苗期 vs低氮-BTx378-苗期 Normal nitrogen-BTx378-Seedling stage vs Low nitrogen-BTx378-Seedling stage
A	2	T7 vs T10	NN-R2-S1 vs LN-R2-S1	正常氮-BSX44-苗期 vs低氮-BSX44-苗期 Normal nitrogen-BSX44-Seedling stage vs Low nitrogen-BSX44-Seedling stage
B	3	T2 vs T5	NN-R1-S2 vs LN-R1-S2	正常氮-BTx378-抽穗期 vs低氮-BTx378-抽穗期 Normal nitrogen-BTx378-Heading stage vs Low nitrogen-BTx378-Heading stage
B	4	T8 vs T11	NN-R2-S2 vs LN-R2-S2	正常氮-BSX44-抽穗期 vs低氮-BSX44-抽穗期 Normal nitrogen-BSX44-Heading stage vs Low nitrogen-BSX44-Heading stage
C	5	T3 vs T6	NN-R1-S3 vs LN-R1-S3	正常氮-BTx378-开花期 vs低氮-BTx378-开花期 Normal nitrogen-BTx378-Flowering stage vs Low nitrogen-BTx378-Flowering stage
C	6	T9 vs T12	NN-R2-S3 vs LN-R2-S3	正常氮-BSX44-开花期 vs低氮-BSX44-开花期 Normal nitrogen-BSX44-Flowering stage vs Low nitrogen-BSX44-Flowering stage

引物名称 Primer ID	序列 Sequence (5′-3′)	产物大小 Product length (bp)
Sb01g006100-F	TTGTCTCGGTGGAGAGGCTA	104
Sb01g006100-R	ATAACTCTGGCCCTCCCAGT	104
Sb01g015190-F	CTGATAATGGGTCTGGCGGT	157
Sb01g015190-R	CTTTTCCGAACGGCGACAAC	157
Sb01g029470-F	TCTGACCCGGACTTGCTCTA	107
Sb01g029470-R	TGGTCGAGGAACCTGCATTC	107
Sb04g032280-F	TGTGGGCGCACATAGACAAG	127
Sb04g032280-R	TCATACATGCAGCGGCTCTC	127
Sb06g016540-F	CGAAGGTGGCTACAACGAGT	171
Sb06g016540-R	TCGTTGGTGCCCGATTTGTT	171
Sb06g031460-F	ATGATGGGTCAAGCACAGGG	99
Sb06g031460-R	TGTTGTTGCCACCTCGGAAT	99
SbActin-F	ATTCACGAGACTACCTACAAC	84
SbActin-R	ACCAGAGAGGACGATGTT	84

百迈客样品编号 BMK-ID	样品 Sample	过滤序列 Clean reads	过滤碱基 Clean bases	GC 含量 GC content (%)	Q30 (%)
T1	NN-R1-S1	16,868,217	4,978,049,154	55.45	92.73
T2	NN-R1-S2	19,294,220	5,706,447,154	56.06	92.41
T3	NN-R1-S3	19,051,651	5,623,880,026	57.58	92.19
T4	LN-R1-S1	16,490,988	4,854,433,778	56.78	91.65
T5	LN-R1-S2	15,070,044	4,433,027,812	56.47	92.03
T6	LN-R1-S3	15,956,808	4,691,702,406	56.77	92.72
T7	NN-R2-S1	14,343,423	4,221,379,930	57.01	92.55
T8	NN-R2-S2	15,743,754	4,605,121,084	56.21	92.98
T9	NN-R2-S3	13,847,707	4,095,501,214	56.07	92.13
T10	LN-R2-S1	14,905,380	4,407,032,326	56.80	91.53
T11	LN-R2-S2	13,986,375	4,119,603,114	56.65	92.66
T12	LN-R2-S3	17,798,466	5,262,344,634	56.17	91.74

对比组 Compare group		比对组 Compare group	上调基因 Up-regulated genes	下调基因 Down-regulated genes	差异表达基因数目 DEG number
A	1	NN-R1-S1 vs LN-R1-S1	464	473	937
A	2	NN-R2-S1 vs LN-R2-S1	264	523	787
B	3	NN-R1-S2 vs LN-R1-S2	637	668	1305
B	4	NN-R2-S2 vs LN-R2-S2	432	503	935
C	5	NN-R1-S3 vs LN-R1-S3	394	1008	1402
C	6	NN-R2-S3 vs LN-R2-S3	384	579	963

基于RNA-Seq筛选高粱低氮胁迫相关候选基因

Identification of candidate genes implicated in low-nitrogen-stress tolerance based on RNA-Seq in sorghum

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KO编号KO ID	KEGG通路 KEGG pathway	KEGG同源基因KEGG orthology	基因编号 Gene ID
ko00910	氮代谢Nitrogen metabolism	K00366+K01915	Sb04g034160; Sb06g031460
ko00250	丙氨酸、天冬氨酸和谷氨酸代谢 Alanine, aspartate and glutamate metabolism	K00814+K01915	Sb01g023750; Sb06g031460
ko00564	甘油磷脂代谢Glycerophospholipid metabolism	K00901+K01115	Sb01g032250; Sb03g012720
ko01230	氨基酸的生物合成Biosynthesis of amino acids	K00814+K01915	Sb01g023750; Sb06g031460
ko00565	醚脂代谢Ether lipid metabolism	K01115	Sb03g012720
ko01210	2-氧羧酸代谢2-Oxocarboxylic acid metabolism	K00814	Sb01g023750
ko00630	乙醛酸和二羧酸代谢Glyoxylate and dicarboxylate metabolism	K01915	Sb06g031460
ko04070	磷脂酰肌醇信号系统Phosphatidylinositol signaling system	K00901	Sb01g032250
ko00195	光合作用Photosynthesis	K02641	Sb01g006100
ko00561	甘油脂代谢Glycerolipid metabolism	K00901	Sb01g032250
ko00330	精氨酸和脯氨酸代谢Arginine and proline metabolism	K01915	Sb06g031460
ko00710	光合生物的碳固定 Carbon fixation in photosynthetic organisms	K00814	Sb01g023750
ko04144	内吞作用Endocytosis	K01115	Sb03g012720
ko01200	碳代谢Carbon metabolism	K00814	Sb01g023750

基因编号 Genome ID	功能 Function	同源基因 Orthologous genes		苗期 Seedling stage		抽穗期 Heading stage		开花期 Flowering stage
基因编号 Genome ID	功能 Function	玉米 Maize	水稻 Rice	T1 vs T4	T7 vs T10	T2 vs T5	T8 vs T11	T3 vs T6	T9 vs T12
Sb01g001970	铵转运蛋白 AMT2	GRMZM2G338809	Os03g62200	↑	↑	↑	↑	↑	↑
Sb01g010270	谷氨酰胺合成酶 GS	GRMZM2G024104	Os03g50490	↓	--			↓	--
Sb01g029470	低亲和硝酸盐转运蛋白 NRT1/PTR	GRMZM2G161459	Os10g40600			↓	↓
Sb02g025100	谷氨酰胺合成酶 GS	GRMZM2G036783	Os09g25610	--	↑			↑	--
Sb02g033100	谷氨酰胺合成酶 GS	GRMZM2G459854				↓	↓
Sb03g035270	低亲和硝酸盐转运蛋白 NRT1/PTR	GRMZM2G035790		↓	--	↓	--	↓	--
Sb03g039530	亚硝酸还原酶 NiR	GRMZM2G367668				↓	--
Sb03g041190	低亲和硝酸盐转运蛋白 NRT1/PTR	GRMZM2G470454	Os01g65100	↑	↓			↓	--
Sb03g043020	低亲和硝酸盐转运蛋白 NRT1/PTR	GRMZM2G419328				↑	--
Sb04g002810	谷草转氨酶 AST		Os02g04170					--	↓
Sb04g031320	硝酸盐转运蛋白 NRT1/PTR		Os02g46460	↑	--
Sb05g002760	亚硝酸还原酶 NiR			--	↓
Sb06g020180	高亲和硝酸盐转运蛋白 NRT3	GRMZM2G163494	Os04g40410			↓	--
Sb06g028990	谷氨酸合成酶 GOGAT	GRMZM2G076239	Os04g53210					↓	--
Sb10g026090	低亲和硝酸盐转运蛋白 NRT1/PTR			↓	↓	↓	↓	↓	↓

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