• Arabidopsis;
  • leaf senescence;
  • SAG;
  • phytohormone;
  • systems biology


  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and Discussion
  5. Conclusion and Perspectives
  6. Materials and Methods
  7. Acknowledgements
  8. References
  9. Supporting Information

Plant leaf senescence has been recognized as the last phase of plant development, a highly ordered process regulated by genes known as senescence associated genes (SAGs). However, the function of most of SAGs in regulating leaf senescence as well as regulators of those functionally known SAGs are still unclear. We have previously developed a curated database of genes potentially associated with leaf senescence, the Leaf Senescence Database (LSD). In this study, we built gene networks to identify common regulators of leaf senescence in Arabidopsis thaliana using promoting or delaying senescence genes in LSD. Our results demonstrated that plant hormones cytokinin, auxin, nitric oxide as well as small molecules, such as Ca2+, delay leaf senescence. By contrast, ethylene, ABA, SA and JA as well as small molecules, such as oxygen, promote leaf senescence, altogether supporting the idea that phytohormones play a critical role in regulating leaf senescence. Functional analysis of candidate SAGs in LSD revealed that a WRKY transcription factor WRKY75 and a Cys2/His2–type transcription factor AZF2 are positive regulators of leaf senescence and loss-of-function of WRKY75 or AZF2 delayed leaf senescence. We also found that silencing of a protein phosphatase, AtMKP2, promoted early senescence. Collectively, LSD can serve as a comprehensive resource for systematic study of the molecular mechanism of leaf senescence as well as offer candidate genes for functional analyses.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and Discussion
  5. Conclusion and Perspectives
  6. Materials and Methods
  7. Acknowledgements
  8. References
  9. Supporting Information

Leaf senescence is the final phase of leaf development, in which leaf cells undergo active degenerative processes, including the degradation of chlorophylls, proteins, and other macromolecules (Lim et al. 2007; Ren et al. 2010). The released nutrients are transferred to actively growing young leaves and developing fruits and seeds (Gan and Amasino 1997; Zhou et al. 2009; Li et al. 2012). Efficient senescence is essential to maximize viability in the next season or generation, but premature senescence, a protective mechanism employed when plants are stressed, results in reduced yield and quality of crop plants (Breeze et al. 2011).

Leaf senescence is a developmentally programmed cell death process that can be regulated by multiple environmental cues and endogenous signals, including age, developmental cues, and plant growth regulators (Gan and Amasino 1995, 1997; Yoshida 2003; Guo and Gan 2005). While no single gene can be credited as responsible for senescence, the mechanisms of senescence are clearly under genetic control (Nam 1997). The genetically identified regulatory factors include transcription regulators, receptors and signaling components for hormone and stress response, and regulators of metabolism. Many advances in the understanding of leaf senescence at the molecular level had been achieved through the identification and characterization of hundreds of SAGs and senescence-related mutants (Buchanan-Wollaston et al. 2003). Microarray expression profiling in Arabidopsis revealed that more than 200 transcription factors, including WRKY, NAC, MADS, MYB, bZIP and bHLH family members, are involved in the regulation of leaf senescence, indicating that leaf senescence is governed by complex transcriptional regulatory networks (Buchanan-Wollaston et al. 2003; Buchanan-Wollaston et al. 2005; Liu et al. 2011).

In recent years, studies of leaf senescence with genetic and microarray analysis led to the accumulation of a large volume of scattered information related to SAGs (Lim et al. 2007). The construction of a plant leaf senescence related database with wide-spread collection and systematic annotation of SAGs may provide a useful resource and a good starting point for the further study of the molecular aspects of leaf senescence. In this regard, we have developed a leaf senescence database (LSD) ( and SAGs were retrieved based on genetic, genomic, proteomic, physiological or other experimental evidence, and were classified into different categories according to their functions in leaf senescence or morphological phenotypes when mutated (Liu et al. 2011). Although thousands of SAGs have been identified by transcriptome analysis and hundreds of SAGs were found to affect leaf senescence process by genetic analysis, the function of most of candidate SAGs in regulating leaf senescence as well as common regulators of those functionally known SAGs are still unclear. In this study, we identified common regulators of SAGs by building gene network using Pathway Studio software. Our results demonstrated that plant hormones and small molecules play an important role in regulating leaf senescence. With large scale of screening of mutants with altered senescence phenotype (Figure 1), we found WRKY75 and AZF2 are positive regulators of leaf senescence and loss-of-function of WRKY75 or AZF2 exhibited delayed senescence. In addition, silencing AtMKP2, a protein phosphatase, promoted early senescence. Taken together, LSD can serve as a useful resource for the systemic study on leaf senescence as well as offer candidate genes for functional analyses.


Figure 1. The pipeline we used to collect, annotate and functional analysis of senescence-associated genes (SAGs).  SAGs with genetic, molecular, genomic, and/or proteomic evidence were collected into LSD and annotated by bioinformatics. SAGs with genetic evidence were used for network pathway analysis. Mutants or transgenic plants were generated for SAGs without genetic evidence and used for screening altered senescence phenotype mutants and functional analysis as well as gene network analysis.

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Results and Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and Discussion
  5. Conclusion and Perspectives
  6. Materials and Methods
  7. Acknowledgements
  8. References
  9. Supporting Information

Building networks to identify common regulators of SAGs

To date, genes with a role in leaf senescence have been identified either by forward genetic screens that isolated mutants with altered senescence rates followed by cloning of the corresponding genes, or by reverse genetic analysis of genes that show differential expression during senescence (Lim et al. 2007). Genes that appear to modulate leaf senescence, including genes that may promote (Table 1) or delay (Table 2) senescence with genetic evidence in plants, served as basis for our work. Detailed information about these genes is available online (, as previously published (Liu et al. 2011). In line with previous efforts, we grouped genes that are shown to affect senescence into functional clusters: chlorophyll biosynthesis or degradation, hormone response pathway, transcription regulation, signal transduction, protein degradation or modification, nucleic acid degradation, lipid or carbohydrate metabolism and nutrient recycling (Tables 1 and 2). We then attempted to construct senescence-related gene networks by focusing on specific groups and find the common regulators of these SAGs.

Table 1.  List of genes that promote leaf senescence collected in LSD
AGIAliasFunctionEffectReferences (PMID)
AT3G44880 PAO/ACD1 Chlorophyll degradationpromote14701922;16113212
AT4G11910 NYE2 Chlorophyll degradationpromote14617064
AT4G13250 NYC1 Chlorophyll degradationpromote14617064
AT4G22920 AtNYE1 Chlorophyll degradationpromote17468209;17204643
AT5G13800 PPH Chlorophyll degradationpromote19304936
AT5G15250 AtFtsH6 Chlorophyll degradationpromote16157880
AT5G42270 FTSH5 Chlorophyll degradationpromote15918877;16157880
AT5G04900 NOL Chlorophyll degradationpromote18431481;19403948
AT5G37060 AtCHX24 Cation/H(+) exchangerpromote22195591
AT1G32080 AtLrgB Cell deathpromote21916894;22180599
AT2G41060 UBA2b Defensepromote18705666
AT3G15010 UBA2c Defensepromote18705666
AT3G56860 UBA2a Defensepromote18705666
AT1G58340 BCD1 Drug transmembrane transportpromote22150160
AT4G29130 HXK1/GIN2 Glucose signal pathwaypromote12690200
AT2G40220 ABI4 Hormone response pathway: ABApromote15118859
AT5G13170 SAG29 Hormone response pathway: ABApromote14617064;20963606
AT5G59220 SAG113 Hormone response pathway: ABApromote22007837;22184656
AT1G19220 ARF19 Hormone response pathway: Auxinpromote16176952
AT1G59750 ARF1 Hormone response pathway: Auxinpromote16176952;15860015
AT5G62000 ARF2/ORE14 Hormone response pathway: Auxinpromote16176952;20164142
AT1G20330 SMT2/CVP1 Hormone response pathway: BRpromote21447789;12215504
AT2G38050 DET2/DWF6 Hormone response pathway: BRpromote9298904
AT4G39400 BRI Hormone response pathway: BRpromote9298904
AT1G01480 ACS2 Hormone response pathway: ETpromote15860015;21447789
AT1G04310 ERS2 Hormone response pathway: ETpromote21447789
AT1G66330 AAF Hormone response pathway: ETpromote21940719
AT3G20770 EIN3 Hormone response pathway: ETpromote9215635
AT5G03280 EIN2 Hormone response pathway: ETpromote19229035
AT1G72520 LOX4 Hormone response pathway: JApromote11891244
AT1G17420 LOX3 Hormone response pathway: JApromote11891244
AT1G55020 LOX1 Hormone response pathway: JApromote11891244
AT2G33150 PED1/KAT2 Hormone response pathway: JApromote18441338
AT2G44050 COS1 Hormone response pathway: JApromote15075400
AT3G45140 LOX2 Hormone response pathway: JApromote20190093;11891244
AT5G63110 HDA6 Hormone response pathway: JApromote18212027
AT5G48880 KAT5/PKT1 Hormone response pathway: JApromote11891244
AT1G64280 NPR1 Hormone response pathway: SApromote10972893
AT1G74710 SID2 Hormone response pathway: SApromote19188277;10972893
AT3G52430 PAD4 Hormone response pathway: SApromote10972893
AT4G24230 ACPB3 Hormone response pathway: SApromote20442372
AT5G14930 SAG101 Nutrient recyclingpromote11971136
AT2G32830 Pht1;5 Nutrient recyclingpromote21628630
AT4G15530 PPDK Nutrient recyclingpromote20202167;15860015
AT4G30520 AtSARK Protein degradation/modificationpromote22034630
AT5G05700 DLS1/ATE1 Protein degradation/modificationpromote12366806
AT2G42620 ORE9/MAX2 Protein degradation/modificationpromote11487692
AT1G69270 RPK1 Protein degradation/modificationpromote21382977
AT1G79850 ORE4/PRPS17 Protein biosynthesispromote12164812
AT2G21660 ATGRP7 RNA bindingpromote14617064;18573194
AT4G36730 GBF1 Signal transductionpromote20484024
AT4G34160 CYCD3-1 Signal transductionpromote16517759
AT5G17690 TFL2 Signal transductionpromote12826620;9611176
AT1G80350 BOT1 Signal transduction:promote11169190;20966154
AT1G73500 MKK9 Signal transductionpromote19251906;15860015
AT2G43790 MPK6 Signal transductionpromote19251906
AT2G45660 SOC1 Transcription regulation: MADSpromote21447789
AT4G28140 Rap2.4f Transcription regulation: ERF/AP2promote20953945
AT5G41410 BEL1 Transcription regulation: HBpromote7912435
AT2G31070 TCP10 Transcription regulation: TCPpromote18816164
AT3G15030 TCP4 Transcription regulation: TCPpromote18816164
AT4G18390 TCP2 Transcription regulation: TCPpromote18816164
AT1G49010 AtMYBL Transcription regulation: MYBpromote21097474
AT2G47190 ATMYB2 Transcription regulation: MYBpromote15860015;21543729
AT1G69490 NAP Transcription regulation: NACpromote16640597;15860015
AT3G10500 NTL4/NAC053 Transcription regulation: NACpromote22313226
AT3G29035 AtNAC3 Transcription regulation: NACpromote15860015;21303842
AT4G35580 NTL9 Transcription regulation: NACpromote18443413;15860015
AT5G39610 ORE1/NAC2 Transcription regulation: NACpromote19229035;20113437
AT4G27330 SPL Transcription regulation: NZZpromote19726570
AT4G23810 WRKY53 Transcription regulation: WRKYpromote17369373
AT1G13260 RAV1/EDF4 Transcription regulation: AP2/B3promote20826506
AT1G62300 WRKY6 Transcription regulation: WRKYpromote11722756;12000796
AT4G19890 AtS40-3 Unclearpromote20238146
Table 2.  List of genes that delay leaf senescence collected in LSD
AGIAliasFunctionEffectReferences (PMID)
AT1G44446 CAO Chlorophyll biosynthesisdelay22285931
AT4G37000 ACD2 Chlorophyll degradationdelay8187175;11149948
AT1G32230 RCD1 Cell deathdelay22150398
AT2G45760 BAP2/BON Cell deathdelay17631528
AT3G61190 BAP1 Cell deathdelay21447789;17631528
AT5G15410 DND1 Defensedelay20699402
AT5G09860 HPR1 Defensedelay22035198
AT2G42530 COR15B Environmental factorsdelay21673078
AT2G42540 COR15A Environmental factorsdelay21673078
AT5G52300 RD29B Environmental factorsdelay21673078
AT5G52310 RD29A Environmental factorsdelay21673078
AT1G52340 GIN1 Hormone response pathway: ABAdelay15118859
AT2G38120 AUX1 Hormone response pathway: Auxindelay22034630
AT5G25620 YUCAA6 Hormone response pathway: Auxindelay21511905
AT1G10470 ARR4 Hormone response pathway: CKdelay14973166;15860015
AT1G19050 ARR7 Hormone response pathway: CKdelay15860015
AT1G27320 AHK3/ORE12 Hormone response pathway: CKdelay16407152
AT1G59940 ARR3 Hormone response pathway: CKdelay14973166;15860015
AT2G01830 CRE1/AHK4 Hormone response pathway: CKdelay16361392
AT2G41310 ARR8 Hormone response pathway: CKdelay14973166;15860015
AT3G48100 ARR5 Hormone response pathway: CKdelay14973166;15860015
AT3G57040 ARR9 Hormone response pathway: CKdelay14973166;15860015
AT4G16110 ARR2 Hormone response pathway: CKdelay14973166;15860015
AT5G35750 AHK2 Hormone response pathway: CKdelay16361392
AT5G62920 ARR6 Hormone response pathway: CKdelay16326927; 14973166
AT1G66340 ETR1 Hormone response pathway: ETdelay8211181
AT3G23150 ETR2 Hormone response pathway: ETdelay21447789
AT1G11680 CYP51A2 Hormone response pathway: ETdelay19915013
AT1G54040 ESP/ESR Hormone response pathway: JAdelay17369373
AT3G47450 AtNOS1 Hormone response pathway: NOdelay16272429;15448272
AT5G64930 CPR5/OLD1 Hormone response pathway: SAdelay12366800;16172137
AT1G04010 PSAT1 Lipid/Carbohydrate metabolismdelay19923239
AT3G51970 ASAT1 Lipid/Carbohydrate metabolismdelay19923239
AT4G36400 D-2HGDH Lipid/Carbohydrate metabolismdelay21296880
AT1G67140 SWEETIE Lipid/Carbohydrate metabolismdelay18452589
AT1G76490 HMG1 Lipid/Carbohydrate metabolismdelay14871314
AT2G39770 VTC1 Lipid/Carbohydrate metabolismdelay15064386
AT4G34890 AtXDH1 Nucleic acid degradationdelay18266920;15860015
AT4G34900 AtXDH2 Nucleic acid degradationdelay18266920
AT1G26670 VTI12 Nutrient recyclingdelay19251905;17360696
AT5G39510 VTI11 Nutrient recyclingdelay19251905;17360696
AT1G54210 ATG12A Nutrient recycling: Autophagydelay12070171;12114572;
AT1G62040 ATG8C Nutrient recycling: autophagydelay16157655
AT2G05630 ATG8D Nutrient recycling: Autophagydelay16157655
AT2G31260 AtAPG9 Nutrient recycling: Autophagydelay12114572
AT2G45170 ATG8E Nutrient recycling: Autophagydelay16157655
AT3G06420 ATG8H Nutrient recycling: Autophagydelay16157655;15860015
AT3G07525 ATG10 Nutrient recycling: Autophagydelay18245858
AT3G15580 ATG8I Nutrient recycling: Autophagydelay16157655;14617064
AT3G19190 ATG2 Nutrient recycling: Autophagydelay19773385
AT3G60640 ATG8G Nutrient recycling: Autophagydelay16157655
AT3G61710 ATG6 Nutrient recycling: autophagydelay17339883
AT3G62770 ATG18A Nutrient recycling: Autophagydelay15860012
AT4G04620 ATG8B Nutrient recycling: Autophagydelay16157655
AT4G16520 ATG8F Nutrient recycling: Autophagydelay16157655
AT4G21980 ATG8A Nutrient recycling: Autophagydelay15860015;16157655
AT5G17290 ATG5 Nutrient recycling: Autophagydelay19773385
AT5G45900 APG7 Nutrient recycling: Autophagydelay12070171;15860015
AT2G44140 ATG4A Nutrient recycling: Autophagydelay19074627
AT3G59950 ATG4B Nutrient recycling: Autophagydelay19074627
AT1G08720 EDR1 Protein degradation/modificationdelay21447789;22035198
AT2G43400 ETFQO Protein degradation/modificationdelay20501910
AT3G45300 IVDH Protein degradation/modificationdelay20501910
AT4G14880 OLD3/OAS-A1 Protein degradation/modificationdelay12366800;20429919
AT5G09900 RPN5A Protein degradation/modificationdelay19252082
AT5G64760 RPN5B Protein degradation/modificationdelay19252082
AT4G38630 RPN10 Protein degradation /modificationdelay12671091
AT4G12570 UPR5 Protein degradation/modificationdelay20409006
AT1G02860 BAH1/NLA Protein degradation/modificationdelay18552353
AT1G20780 SAUL1 Protein degradation/modificationdelay19309463
AT4G09010 APX4 Redox regulationdelay16034597
AT1G70170 At2-MMP Signal transductiondelay11726650
AT1G20900 ORE7 Signal transductiondelay17971039
AT4G00650 FRI Signal transductiondelay19878465
AT5G10140 FLC Signal transductiondelay19878465
AT1G09570 PHYA Signal transductiondelay22171633
AT4G25470 CBF2 Transcription regulation: ERF/AP2delay19854800
AT2G47585 miR164A Transcription regulation: miRNAdelay19229035
AT5G01747 miR164B Transcription regulation: miRNAdelay19229035
AT5G27807 miR164C Transcription regulation: miRNAdelay19229035
AT4G23713 miR319 Transcription regulation: miRNAdelay18816164
AT5G13180 VIN2/NAC83 Transcription regulation: NACdelay21673078;15860015
AT2G40750 WRKY54 Transcription regulation: WRKYdelay22268143
AT3G56400 WRKY70 Transcription regulation: WRKYdelay22268143
AT5G13790 AGL15 Transcription regulation: MADSdelay12226488

To identify the common regulators, the genes that promote (Table 1) or delay (Table 2) senescence in Arabidopsis were input into Pathway Studio 5 software respectively. All networks are displayed in Figures 2 and 3, in which some genes with no links are not involved in the network analysis.We found that several small molecules, such as Ca2+, copper, iron, oxygen and glucose, are the regulators of this gene network. Previous studies demonstrated that Ca2+ is an essential component involved in plant senescence signaling cascades, delaying the senescence of detached leaves (Poovaiah and Leopold 1973; Ma et al. 2010) and leaf senescence induced by methyl jasmonate (Chou and Kao 1992). It is noteworthy that phytohormones, including ethylene, abscisic acid (ABA), cytokinin, auxin and salicylic acid (SA) as well as nitric oxide (NO), are the major regulators of this gene network (Figures 2 and 3), supporting the notion that the phytohormones play a critical role in leaf senescence (Buchanan-Wollaston et al. 2005). They might regulate leaf senescence by coordinating the responses to environmental cues with those induced by developmental signals (Guo and Gan 2012).


Figure 2. Common regulators (identified by Pathway Studio 5) associated with the dataset of SAGs that delay leaf senescence process.  Color regulation relations by effect: Green-positive; red-negative; grey and/or broken lines-unknown. Color coding of entities associated with gene network: circle-small molecules; ellipse-protein; hexagon-functional class.

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Figure 3. Common regulators (identified by Pathway Studio 5) associated with the dataset of SAGs that promote leaf senescence process.  Color regulation relations by effect: Green-positive; red-negative; grey and/or broken lines-unknown. Color coding of entities associated with gene network: circle-small molecules; ellipse-protein; hexagon-functional class.

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Cytokinins are considered to be senescence-delaying hormone and have the strongest effect among all types of hormones with a retardation effect of leaf senescence (Back and Richmond 1969; Gan and Amasino 1995; Zhang et al. 2010). Cytokinin signaling genes such as the type-A ARRs and biosynthesis genes show reduced transcription during leaf senescence (Buchanan-Wollaston et al. 2005). One of the three known cytokinin receptors, AHK3, has been demonstrated to function in the cytokinin-mediated delay of leaf senescence; and the phosphorelay of AHK3 to ARR2, a type B Arabidopsis cytokinin response regulator, is essential for controlling leaf longevity (Kim et al. 2006). Type-A ARRs act as negative regulators of cytokinin responses, and arr2arr4arr5arr6 mutant exhibits a higher rate of chlorophyll retention in the absence of exogenous cytokine in dark (To et al. 2004). Auxin or auxin signal pathway has also been implicated in the regulation of leaf senescence (Osborne, 1959). Mutation in ARF2, a repressor of auxin signaling, causes delayed senescence in Arabidopsis rosette leaves (Ellis et al. 2005; Lim et al. 2010). And two allelic mutations, ore14-1/arf2-10 and ore14-2/arf2-11, also cause significant delays in all senescence parameters in Arabidopsis (Lim et al. 2010). These data imply that auxin is involved in the negative regulation of leaf senescence (Ellis et al. 2005). Recently, nitric oxide (NO) has been demonstrated as a negative regulator during leaf senescence, and abolishing NO generation in either loss-of-function mutants (Guo and Crawford 2005) or transgenic Arabidopsis plants expressing NO degrading dioxygenase leads to an early senescence phenotype in these plants compared to the wild type (Mishina et al. 2007). By contrast, ethylene has long been seen as the key hormone in regulating the onset of leaf senescence (Burg 1968; Aharoni and Lieberman 1979). Ethylene-insensitive mutants, etr1-1 and ein2-1, display increased leaf longevity (John et al. 1997; Oh et al. 1997; Kim et al. 2009). Mutation in EIN3, a key transcription factor as a positive regulator of ethylene pathway, delayed dark induced senescence in detached leaves (Chao et al. 1997). More recently, emerging evidence implied that ethylene might not directly regulate the onset of leaf senescence but rather act to modulate the progression of leaf senescence (Jing et al. 2002). It has been demonstrated that JA positively regulated leaf senescence (He et al. 2002). Exogenous JA induces senescence in both attached and detached Arabidopsis leaves but not in the JA-insensitive mutant coi1, and that the endogenous JA levels increased in senescing leaves (He et al. 2002). Taken together, network analyses suggested that phytohormones are important regulators of plant leaf senescence and many of these altered senescence phenotypes occur as a result of altered hormone signaling.

Functional analysis of putative SAGs

In order to determine whether SAGs collected in LSD really affect leaf senescence process, T-DNA insertion lines were selected using the SIGnaL database ( and ordered from ABRC. If multiple insertions were available in the same genes, the selection was based on the position of the insertions that disrupt the gene function as much as possible, such as those insertions located within exon. Some RNAi lines were generated by ourselves or obtained from other laboratories for further study if there was no suitable insertion line available from the Salk collections.

First, senescence phenotype-known mutants or transgenic plants were used to test whether our experimental conditions are suitable for leaf senescence phenotype analysis. Plants with significant delayed or promoted senescence phenotype were used in this study. They were grown in soil under long-day (16 h light/8 h dark) conditions alongside wild-type controls and 5-week-old plants were used for phenotype analysis. In agreement with previous reports, wrky53 (Miao and Zentgraf 2007), npr1 (Buchanan-Wollaston et al. 2005), NahG (Buchanan-Wollaston et al. 2005), ore9 (Woo et al., 2001), jaw (Schommer et al., 2008) and ESROE (Miao and Zentgraf, 2007) plants exhibited significantly delayed senescence phenotype compared to wild type (Figure 4). By contrast, esr (Miao and Zentgraf 2007) and cpr5 (Yoshida et al. 2002; Jing et al. 2007; Jing and Dijkwel 2008; Jing et al. 2008) plants displayed accelerated senescence (Figure 4).


Figure 4. Senescence phenotype of several known mutants with altered senescence rates.  Symptoms of senescence were present in 5-week-old wrky53, esr, ESROE, npr1, NahG, cpr5, jaw, ore9 and wild-type plants. Plants were grown under long days (LDs; 16 h light/8 h dark) at 22 °C. Rosette leaves were cut and arranged according to their ages.

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Next, we utilized the approach described above for large-scale phenotype analysis (Figure 1), mainly focused on transcriptional factors (NAC, WRKY, bZIP and zinc finger gene families) as well as genes involving in signal transduction (e.g. protein phosphate or dephosphate). Not surprisingly, most of the mutants could not be distinguished from the wild type, probably due to functional redundancy or lack of effect on senescence (data not shown). Nonetheless, WRKY75RNAi and azf2 plants displayed significantly delayed senescence phenotype, whereas AtMKP2RNAi exhibited early senescence, which were used for further analysis.

WRKY75 is a positive regulator of leaf senescence

In Arabidopsis, microarray studies have suggested a role of WRKY transcription factors in drought, cold, or high salinity stress (Narusaka et al. 2004). Several WRKY transcription factors, such as WRKY4 (Lai et al. 2008), WRKY6 (Robatzek and Somssich 2002), WRKY22 (Zhou et al. 2011), WRKY53 (Miao and Zentgraf 2007; Zentgraf et al. 2010), WRKY54 (Besseau et al. 2012) and WRKY70 (Ulker et al. 2007; Besseau et al. 2012) of Arabidopsis have been shown to play a role in leaf senescence (Eulgem et al. 2000). The involvement of WRKY75 during senescence has also been suggested based on a microarray analysis and unpublished data (Guo et al. 2004). In this study, we further examined the role of WRKY75 in regulating leaf senescence. WRKY75 mRNA exhibited high expression in senescent leaves compared to young leaves in wild type Col-0 (Figure 5D), indicating that WRKY75 is one of senescence-associated genes (SAGs) that are typically up-regulated during senescence (Buchanan-Wollaston and Ainsworth 1997; Nam 1997). WRKY75 was effectively knock-down by RNA-silencing as demonstrated by RT-PCR analysis (Devaiah et al. 2007) (Figure 5D). The leaf senescence marker gene SAG12 was also used to indicate the status of senescence (Pontier et al. 1999) (Figure 5D). Following the molecular characterization of the RNAi plants, they were grown in soil under long-day (16 h light/8 h dark) conditions alongside wild-type controls. No difference in overall development, bolting, and flowering time could be observed (data no shown). However, if rosettes of 6.5-week-old plants were analyzed, we observed that WARKY75RNNAi plants show delayed leaf senescence phenotypes compared to wild-type plants (Figure 5A). Senescent yellowing leaves can be observed on wild-type plants of the same age as WARKY75RNNAi plants, which do not have any leaves undergoing senescence at this point (Figure 5B, C). In addition, we found a WRKY75 knockout line (SALK_048763) also exhibited delayed senescence phenotype (See supplemental Figure 1). Taken together, WRKY75 is a positive regulator of leaf senescence but the molecular mechanism underlying is still unclear.


Figure 5. Silencing WRKY75 gene expression by RNAi delays leaf senescence.  (A) Senescence-related phenotype of 6.5-week-old WRKY75RNAi and wild type Col-0 plants.  (B) Senescence-related phenotype of rosette leaves from 6.5-week-old WRKY75RNAi and wild type Col-0 plants.  (C) Rosette leaves were cut and arranged according to their ages.  (D) RT-PCR analysis of WRKY75 and SAG12 expression level in young (Y) and senescent (S) leaves of wild type Col-0 as well as in 4th leaves of 6.5-week-old Col-0 and WRKY75RNAi plants. ACT2 was used as loading control.

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Loss-of-function of AtMKP2 promoted early senescence

Another mutant is AtMKP2i which displayed significantly early senescence compared to wild type (Figure 6A). RT-PCR analysis demonstrated that AtMKP2 was efficiently silenced (Lee and Ellis 2007) (Figure 6B). No difference in bolting, and flowering time could be observed. However, if rosettes of 6-week-old plants were analyzed, we found that AtMKP2i plants displayed early senescence compared to wild type and AtMKP2 over-expressing lines (35S-AtMKP2), suggesting loss-of-function of AtMKP2 promoted leaf senescence process. However, over-expression of AtMKP2 didn't extend the plant longevity (Figure 6A). AtMKP2 was previously shown to display in vitro dephosphorylation activity against MPK3/MPK6 (Lee and Ellis 2007). In vivo, MKP2 positively regulates oxidative stress functions and AtMKP2-silenced plants (AtMKP2i) exhibit enhanced sensitivity to ozone stress (Lee and Ellis 2007). Free radicals are thought to play an essential role in senescence, especially those derived from oxygen. The critical balance between production and scavenging of reactive oxygen species (ROS), which normally is very tightly regulated, appears to be specifically disrupted during the progression of senescence in different cellular compartments either by depletion of antioxidants or excess production of ROS (Srivalli and Khanna-Chopra 2009). Thus, sensitivity to ROS may be one of the reasons leading to early senescence in AtMKP2i plants. Interestingly, a MAPK cascade involving MKK9-MPK6 is shown to play an important role in regulating leaf senescence in Arabidopsis (Zhou et al. 2009). Loss-of-function of MKK9 delayed leaf senescence, whereas constitutive or inducible overexpression of MKK9 causes premature senescence in leaves and in whole Arabidopsis plants (Zhou et al. 2009). Constitutive activation of MKK9 protein promotes the production of ROS and induced cell death in Arabidopsis, which can be partly blocked by knockout of MPK3/6 (Liu et al. 2008). Recently, it was reported that inducible over-expression of GmSARK, a SENESCENCE-ASSOCIATED RECEPTOR-LIKE KINASE (SARK) in soybean (Glycine max), or its homolog in Arabidopsis AtSARK, causes precocious senescence, whereas a T-DNA insertion mutant of AtSARK showed significantly delayed senescence (Xu et al. 2011). Above mentioned data imply that the coordinated activities of protein kinases and protein phosphatases regulate leaf senescence process.


Figure 6. Silencing AtMKP2 gene expression by RNAi accelerates leaf senescence.  (A) Senescence-related phenotype of 6-week-old AtMKP2i, 35S-AtMKP2 and wild type Col-0 plants.  (B) RT-PCR analysis of AtMKP2, RBCS, NAP, MKK9 andSAG12 expression level in AtMKP2i, 35S-AtMKP2 and wild type Col-0 plants. ACT2 was used as loading control. RNA was extracted from 4th leaves of 6-week-old plants.

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Loss-of-function of AZF2 delayed natural and dark induced leaf senescence

AZF2 encodes a Cys2/His2 type zinc finger protein and its mRNA level was up-regulated by ABA, high salt, and mild desiccation (Sakamoto et al. 2000; Drechsel et al. 2010; Kodaira et al. 2011). Microarray analysis revealed that gene expression of AZF2 increased in the senescent leaves compared to young leaves, suggesting that AZF2 is a senescence-associated gene (Breeze et al. 2011). To examine the effect of AZF2 on leaf senescence, we obtained a T-DNA insertion mutant of azf2 (SALK_132562) in Col-0 background. RT-PCR analysis confirmed that AZF2 expression was completely eliminated by the T-DNA insertion in the homozygous mutant (Breeze et al. 2011) (Figure 7C). After molecular characterization, azf2 mutants were grown in soil under long-day (16 h light/8 h dark) conditions alongside wild-type Col-0. Compared with the wild-type plants, 5-week-old azf2 mutants displayed significant delayed senescence phenotypes (Figure 7A). No leaves became yellow in azf2 mutants, while several leaves died in the wild type plants (Figure 7). The role of AZF2 in regulating leaf senescence was investigated by the classic, detached-leaf dark-induced senescence assay system (Buchanan-Wollaston et al. 2005). Fully grown 6th rosette leaves from the azf2 mutant and wild type Col-0 were detached and treated under dark conditions for 4 days. As shown in Figure 7B, leaves of azf2 mutant exhibited green compared to the yellowing leaves of control, suggesting that mutation in azf2 effectively delayed dark induced senescence. These data suggest that AZF2 regulated positively leaf senescence, and further investigation is required to understand the molecular mechanism involved.


Figure 7. Mutation in AZF2 delays natural and dark-induced leaf senescence.  (A) Natural senescence phenotype of azf2 mutant. Rosette leaves from 5-wk-old plants were cut and arranged according to their ages.  (B) Dark-induced senescence phenotype of azf2 mutant. 6th leaves from 5-wk-old plants were cut and treated with dark at 22°C for 4 days.  (C) RT-PCR analysis of the gene expression of AZF2 in azf2 and Col-0 wild-type (WT) plants. ACT2 was amplified as a control.

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Conclusion and Perspectives

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and Discussion
  5. Conclusion and Perspectives
  6. Materials and Methods
  7. Acknowledgements
  8. References
  9. Supporting Information

Using a system-biology approach to the study of plant leaf senescence, global network such as those presented herein provide a framework for researchers to investigate specific signaling and regulatory pathways involved in leaf senescence (Figure 1). Network-based studies integrating transcription, interaction and metabolic data have identified a set of biological processes related to leaf senescence. The integration of small molecular, glucose, lipids, plant hormones and their signaling transduction components in interaction networks could bring further insights into the leaf senescence process.

The Leaf Senescence Database provides information of senescence-associated genes and is the most comprehensive plant senescence-related database (Liu et al. 2011). We designed the databases and tools in LSD so that they can be useful to researchers working on the science of plant leaf senescence. Understanding leaf senescence is a collaborative effort. LSD will hopefully reflect that spirit and continue to improve not only due to our efforts but thanks to the feedback from the research community working on the science of plant leaf senescence. Given the large number of senescence-related changes and players involved in plant leaf senescence process, the insights provided by LSD are a first step towards understanding the molecular aspects of plant ageing (Liu et al. 2011). In the future, we hope to continually upgrade, update and expand the resources in LSD, as well as to develop new tools that can benefit the research community in plant ageing.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and Discussion
  5. Conclusion and Perspectives
  6. Materials and Methods
  7. Acknowledgements
  8. References
  9. Supporting Information

Materials and plant growth conditions

All of the transgenic lines and mutants in this study were derived from the wild-type Arabidopsis thaliana Columbia (Col-0) ecotype and cultivated in growth chambers under long days (LDs; 16 h light/8 h dark) at 22 °C under fluorescence illumination (100–150 μE m−2 s−1). Seeds were sterilized by liquid N2 for 15 min. The sterilized seeds were stratified in the dark at 4°C for 3d and germinated on Murashige and Skoog (MS) medium (pH 5.7) supplemented with 1% sucrose and 0.8% (w/v) agar. T-DNA insertion null allele for SAGs in LSD, as well as wrky53 (SALK_034157C), jaw (CS6948), npr1(CS3726), zaf2 (SALK_132562C) and cpr5 (CS3770) in the Col-0 background were obtained from the randomly mutagenized T-DNA lines (SALK collection) at The Arabidopsis Information Resource (Tair). Homozygous plants were identified from segregating T3 populations by genotyping with gene-specific primers. esr mutant and transgenic Arabidopsis ESROE line were kindly provided by Ulrike Zentgraf (ZMBP, Germy); ore9 was kindly provided by H.G. Nam (Pohang University of Science and Technology, Korea); WRKY75RNAi was kindly provided by Kashchandra G. Raghothama (Purdue University, Indiana); AtMKP2i and 35S-AtMKP2 were shared by Brian Ellis (University of British Columbia, Canada).

RNA Isolation and RT-PCR analysis

Total RNA was extracted by TRIzol reagent and DNase treatment of total RNA was performed using deoxyribonuclease I (Invitrogen). Reverse transcription was performed by using 1 μg of RNA at 70 °C by MMLV (Promega) reverse transcriptase according to the manufacturer's protocol. RT-PCR was performed with gene-specific primers (See Supplemental Table 1 online).

Assays for natural leaf senescence

For age-dependent leaf senescence, the third and fourth rosette leaves of individual plants were used for analyses of chlorophyll content and SAG12 gene expression. For dark-induced leaf senescence, the third and fourth rosette leaves from a 4-week-old Arabidopsis plant were excised and placed on moisturized filter papers in Petri dishes with adaxial side facing up. The plates were kept in dark at 23 °C for 4 days.

Construction of SAG gene networks

A set of genes that have been reported to be associated with promoted- or delayed-senescence phenotypes in Arabidopsis thaliana were generated. This set was derived from our Leaf Senescence Database ( Based on this set of senescence associated genes, the gene network was constructed by introducing names of genes (canonical names) from our compiled set into PATHWAY STUDIO 5 software (Ariadne Genomics, Rockville, MD) and selecting mode of common regulators or targets for network building. The software identified associations among the input genes by referencing a proprietary Arabidopsis database.

(Co-Editor: Hai-Chun Jing)


  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and Discussion
  5. Conclusion and Perspectives
  6. Materials and Methods
  7. Acknowledgements
  8. References
  9. Supporting Information

We thank members of Guo Lab for many helpful discussions and critical reading of the manuscript. We thank Xiaochuan Liu for his kind assistance in analyzing gene regulatory network. We also thank Ulrike Zentgraf (ZMBP, Germany) for kindly providing ESROE, WRKY53OE and esr mutants HG Nam (Pohang University of Science and Technology, Korea) for ore9 mutant, Kashchandra G. Raghothama (Purdue University, Indiana) for WRKY75RNAi mutant and Brian Ellis (University of British Columbia, Canada) for AtMKP2i and 35S-AtMKP2 mutants. This work was supported by grants from the Ministry of Science and Technology of China (2009CB119101) and the National Science Foundation of China (91017010) to H.G.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and Discussion
  5. Conclusion and Perspectives
  6. Materials and Methods
  7. Acknowledgements
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and Discussion
  5. Conclusion and Perspectives
  6. Materials and Methods
  7. Acknowledgements
  8. References
  9. Supporting Information

Figure S1. Knockout of WRKY75 delays leaf senescence. Senescence-related phenotype of 7.5-week-old wild type Col-0 and wrky75(SALK_048763) mutant.

Table S1. Primers used in this study.

JIPB_1136_sm_Suppmat.doc201KSupporting info item

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.