Nucleotide and RNA Metabolism Prime Translational ... (RNA metabolism and import components) precedes a later cascade of gene expression encoding the bioenergetic and metabolic functions

Nucleotide and RNA Metabolism Prime TranslationalInitiation in the Earliest Events of MitochondrialBiogenesis during Arabidopsis Germination1[W][OA]

Simon R. Law2, Reena Narsai2, Nicolas L. Taylor, Etienne Delannoy3, Chris Carrie, Estelle Giraud,A. Harvey Millar, Ian Small, and James Whelan*

Australian Research Council Centre of Excellence in Plant Energy Biology (S.R.L., R.N., N.L.T., E.D., C.C.,E.G., A.H.M., I.S., J.W.), Centre for Computational Systems Biology (R.N., I.S.), and Centre for ComparativeAnalysis of Biomolecular Networks (N.L.T., A.H.M.), University of Western Australia, Crawley 6009, WesternAustralia, Australia

Mitochondria play a crucial role in germination and early seedling growth in Arabidopsis (Arabidopsis thaliana). Morphologicalobservations of mitochondria revealed that mitochondrial numbers, typical size, and oval morphology were evident after 12 hof imbibition in continuous light (following 48 h of stratification). The transition from a dormant to an active metabolic statewas punctuated by an early molecular switch, characterized by a transient burst in the expression of genes encodingmitochondrial proteins. Factors involved in mitochondrial transcription and RNA processing were overrepresented amongthese early-expressed genes. This was closely followed by an increase in the transcript abundance of genes encoding proteinsinvolved in mitochondrial DNA replication and translation. This burst in the expression of factors implicated in mitochondrialRNA and DNA metabolism was accompanied by an increase in transcripts encoding components required for nucleotidebiosynthesis in the cytosol and increases in transcript abundance of specific members of the mitochondrial carrier proteinfamily that have previously been associated with nucleotide transport into mitochondria. Only after these genes peaked inexpression and largely declined were typical mitochondrial numbers and morphology observed. Subsequently, there was anincrease in transcript abundance for various bioenergetic and metabolic functions of mitochondria. The coordination ofnucleus- and organelle-encoded gene expression was also examined by quantitative reverse transcription-polymerase chainreaction, specifically for components of the mitochondrial electron transport chain and the chloroplastic photosyntheticmachinery. Analysis of protein abundance using western-blot analysis and mass spectrometry revealed that for many proteins,patterns of protein and transcript abundance changes displayed significant positive correlations. A model for mitochondrialbiogenesis during germination is proposed, in which an early increase in the abundance of transcripts encoding biogenesisfunctions (RNA metabolism and import components) precedes a later cascade of gene expression encoding the bioenergeticand metabolic functions of mitochondria.

A distinguishing feature in the life cycle of manyflowering plants is the production of seeds that arecapable of remaining dormant for several years. Yet,upon perception of appropriate signals, the dormantseed transitions from a quiescent state to a highlyactive metabolic state. This transition requires a rela-tively rapid reestablishment of the various biochemi-

cal activities localized to a number of distinct cellularstructures/organelles. These organelles can then uti-lize the stored reserves to establish the seedling beforephotosynthesis begins to support plant growth. Thisordered and timely reestablishment of metabolic func-tion is essential for successful seedling establishment,as the biochemical machinery required for autotrophicgrowth must be completed before seed reserves areexhausted (Bewley, 1997).

In dry seeds, mitochondria do not have the charac-teristic cristae structures, which represent infolding ofthe inner membrane that contains the ATP-producingrespiratory chain (Logan et al., 2001; Vartapetian et al.,2003; Howell et al., 2006). Rather, they appear as morecircular organelles where both membranes are close toeach other (Logan et al., 2001; Vartapetian et al., 2003;Howell et al., 2006). This structure, which has beentermed a promitochondrion structure (Logan et al.,2001), develops the more typical mitochondrial mor-phology in 12 to 24 h after imbibition (the passiveuptake of water by the seed) in maize (Zea mays) andrice (Oryza sativa; Logan et al., 2001; Howell et al.,

1 This work was supported by the Australian Research CouncilCentre of Excellence (grant no. CEO561495) and the Western Aus-tralian State Government Centres of Excellence scheme.

2 These authors contributed equally to the article.3 Present address: Functional Genomics of Arabidopsis, Unite de

Recherche en Genomique Vegetale, INRA, Evry 91057, France.* Corresponding author; e-mail [email protected] author responsible for distribution of materials integral to the

findings presented in this article in accordance with the policydescribed in the Instructions for Authors (www.plantphysiol.org) is:James Whelan ([email protected]).

[W] The online version of this article contains Web-only data.[OA] Open Access articles can be viewed online without a sub-

scription.www.plantphysiol.org/cgi/doi/10.1104/pp.111.192351

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2006). This structural change is accompanied by anincrease in metabolic activity. However, mitochondriado not arise de novo but rather from preexistingorganelles, and the details of the molecular mecha-nisms and signals that initiate this process are unclear.Mitochondrial biogenesis requires energy and variousbuilding blocks that are produced in the mitochondria;thus, some endogenous mitochondrial activity mustexist to prime subsequent mitochondrial biogenesis,which ultimately provides energy for a variety of cel-lular processes in the germinating tissues. The regula-tion and timing of mitochondrial biogenesis are ofcritical importance to the process of germination andearly seedling establishment.Studies on mitochondrial biogenesis during germi-

nation have been primarily carried out in starch-storing seeds, such as maize and rice. Initial studiesin maize revealed that transcripts and proteins of theATPase complex and cytochrome oxidase began toaccumulate after 6 h of imbibition (Ehrenshaft andBrambl, 1990). A notable exception was observed withthe mitochondrially encoded subunit 9 of the ATPsynthase complex, which was detected in dry embryosand increased further in imbibition. A later studyshowed that the transcript and protein for mitochon-drial HSP60 were present in dry embryos and in-creased upon imbibition (Prasad and Stewart, 1992). Adetailed study in maize built on these earlier studies topropose that different populations of mitochondriaexisted and that the “light” or promitochondrial frac-tion matured into cristae-containing mitochondriawith large increases in metabolic components (Loganet al., 2001). Studies in rice revealed that an orderedassembly of mitochondria occurs, that componentsrequired to build or import mitochondrial proteins arepresent in promitochondrial structures, and that theyare active almost immediately upon imbibition tofacilitate the rapid rate of mitochondrial biogenesisand associated increases in respiration observed in thefirst 24 h after imbibition (Howell et al., 2006, 2007).No direct studies have been carried out in the oil

seed Arabidopsis (Arabidopsis thaliana) to investigatemitochondrial biogenesis and determine how it pro-ceeds relative to the other energy organelles: chloro-plasts and peroxisomes. The importance of themitochondrion in providing energy for germinationand the interaction with photosynthesis position it as acritical organelle during germination and early seed-ling establishment (Nunes-Nesi et al., 2011). Previ-ously, we have carried out an in-depth transcriptomeanalysis of germination and defined greater than 700germination-specific genes (i.e. genes defined as dis-playing maximum expression during germinationcompared with all other development stages in Arab-idopsis; Narsai et al., 2011). Thus, to define the role ofmitochondria in germination and to study the earliestevents of mitochondrial biogenesis during germina-tion in Arabidopsis, we undertook a closer analysis ofthis germination transcriptome data set (GSE30223;Narsai et al., 2011) and combined it with a detailed

analysis of mitochondria- and plastid-encoded organ-ellar genes (using high-throughput quantitative re-verse transcription [qRT]-PCR). To link these data withcellular development, we visualized mitochondrialprofiles during germination using mitochondriallytargeted GFP and compared this with chloroplast-and peroxisome-targeted red fluorescent protein (RFP)and cyan fluorescent protein (CFP), respectively. Pro-tein abundance profiles during germination were alsoanalyzed in this study, using antibodies and peptidemass spectrometry to link the timing of transcriptionalchanges to protein accumulation changes. The resultsshow the status of mitochondria in fresh dry seeds andthe changes that occur over the course of seed matu-ration, stratification (moist chilling of the seeds indarkness to alleviate dormancy), germination (thetime from the start of water uptake to the point wherethe embryo emerges from the testa), and post germi-nation. These results show some of the earliest changesin mitochondria that occur during germination.

RESULTS

Temporal Examination of Organelle Biogenesis

The use of a stably transformed line of Arabidopsisseed containing different fluorophores targeted to themitochondria, plastid, and peroxisome facilitated an invivo temporal examination of biogenesis for the energyorganelles during germination (Fig. 1A). Throughoutthe germination time course, peroxisomes (cyan chan-nel) were observed to be present in high densities,with negligible changes to morphology and size(approximately 2 mm). This is consistent with thepivotal role of glyoxysomes and peroxisomes in me-tabolizing the energy stores present in oil seeds priorto the establishment of photoautotrophism (Graham,2008). In the red channel, small proplastids (1–2 mm)were observed at high densities in the first time point(dry seed; Fig. 1Ai). The plastids remain small until aslate as 12 h SL (i.e. 12 h into continuous light, following48 h of stratification at 4�C in the dark), after whichthey undergo a major increase in size (approximately4 mm) and exhibit a globular morphology by 48 h SL.This organellar expansion is symptomatic of the tran-sition from undifferentiated proplastid to etioplastsand chloroplasts, as photosynthesis is establishedin the greening cotyledons. In the green channel,mitochondria could not be visualized in dry seeds,and as the mitochondrial, peroxisomal, and plastidfluorescence-tagged proteins were all driven by the 35Scauliflower mosaic virus promoter, the lack of a mito-chondrial signal reflects mitochondrial mass or protein,not a lack of expression of the marker. However,following 48 h of stratification (Fig. 1Aii), GFP-contain-ing mitochondrial populations could be observed, withvariedmorphologies and sizes (0.5–2mm). After 12 h SLin continuous light (Fig. 1Aiii), the mitochondrial mor-phology took on a more uniform rod shape, accompa-

Mitochondrial Biogenesis in Arabidopsis during Seed Germination

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Figure 1. Developmental profiling of mitochondria, plastids, and peroxisomes in an Arabidopsis embryo/seedling over agermination time course. A, Seeds from a stably transformed line of Arabidopsis plants expressing mitochondria-targeted GFP,plastid-targeted RFP, and peroxisome-targeted CFP were examined at a number of time points during seed germination. i, Thecotyledon of an embryo dissected from a dry seed. Peroxisomes (cyan) and proplastids (red) are visible in high numbers. ii, Thecotyledon of an embryo dissected from a seed after 48 h of stratification (48 h S; prior to transfer to continuous light). Peroxisomes(cyan) and proplastids (red) are visible in high numbers; mitochondria (green) can begin to be identified, although these are not asdistinct as in later time points. iii, The cotyledon of an embryo dissected at 12 h in continuous light (12 h SL). All three organellesare clearly visible. iv, The cotyledon of an embryo dissected at 48 h in continuous light (48 h SL). All three organelles are moreclearly visible. The plastids (red) have quadrupled in size and are colocalizing with the peroxisomes. Bars = 15 mm. B, Totalprotein was extracted from Arabidopsis seeds collected during the germination time course and separated by SDS-PAGE (30 mg).Separated proteins were transferred to a polyvinylidene difluoride membrane and subjected to western-blot analysis. Followingquantitation of band intensities using ImageQuant TL software (GE Healthcare), values were normalized to the highest level ofintensity over the time course and graphed.

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nied by an increase in mitochondrial density. This isconsistent with studies using electron microscopy thatindicate that the cristae structure of mitochondria de-velop 12 to 24 h after imbibition (Logan et al., 2001;Howell et al., 2006). This increase in density and uni-form morphology remained consistent throughout theremainder of the time course. In the early time points(Fig. 1A, i–iii), peroxisomes and proplastids had aseemingly random distribution within cells and werenot observed to interact with each other. However, inthe final time point (48 h SL; Fig. 1Aiv), the peroxisomeswere observed to colocalize in clusters around thechloroplasts. Colocalization of this nature has beenobserved in adult leaf tissue previously (Mano et al.,2002) and suggests the establishment of photorespira-tion, a hallmark of the transition from glyoxysome toleaf peroxisome.Protein abundance changes for several organelle

proteins were analyzed across a time series fromfreshly harvested seeds (upon removal from siliques)as well as dry seeds after 15 d of ripening (0 h), across48 h of dark stratification (S), and then following 48 hof exposure to light (SL) at 22�C. Western-blot analysisusing antibodies raised to markers of different com-partments showed that the pattern of protein expres-sion over the time course differed substantially (Fig.1B). For some proteins, the protein abundance did notdramatically change in abundance over the timecourse, with less than a 50% change in abundanceseen from dry seeds to 48 h SL (Fig. 1B). This was truefor the cytosolic marker UGPase, which maintained arelatively consistent abundance, being highly abun-dant (70% or 0.7) in harvested and dry seed to max-imum abundance (100% or 1.0) at 48 h SL (Fig. 1B). Themitochondrial marker ATPb varied in abundancefrom 60% (0.6) at harvest and dry seed to maximumabundance at 48 h SL (Fig. 1B). Larger increases inprotein abundance were observed in mitochondrialvoltage-dependant anion channel (VDAC) and theperoxisomal 3-ketoacyl-CoA thiolase (Kat2; 40% [0.4]at harvest and dry seed to 100% [1.0] at 48 h SL). Thelargest increases in protein abundance were observedfor the two subunits of plastid Rubisco, denoted SSUand RbcL (30% [0.3] at harvest and dry seed and 100%[1.0] at 48 h SL), and the vacuole V-ATPase (20% [0.2]at harvest and dry seed to 100% [1.0] at 48 h SL;Fig. 1B).

Transcript and Protein Correlation in OrganelleBiogenesis during Germination

To study the process of organelle biogenesis duringgermination, transcript abundance changes were ana-lyzed using the previously published microarray data(GSE30223; Narsai et al., 2011), and protein abundancewas measured by shotgun mass spectrometry detec-tion of peptides. Of the 15,789 genes expressed in atleast one time point during the time course (Narsaiet al., 2011), quantitative data for 178 of the corre-sponding proteins were obtained by counting peptide

mass spectra (Ishihama et al., 2005; see “Materials andMethods”). For each of these, the corresponding tran-script abundance was normalized to maximum (forthe equivalent time points as the proteins) and visu-alized as a heat map in order of functional category(Fig. 2; Supplemental Table S1). In this way, it waspossible to identify any concordance between tran-script and protein levels during germination.

Examination of the heat map showing transcriptand protein abundance, and the corresponding corre-lation coefficient for each gene revealed a pattern ofconcordance relating to function, with 81 of the 178transcripts/proteins showing significant positivecorrelations of r . 0.62, while only 15 of the 178transcripts/proteins showed significant negative cor-relations (r , 20.62; Fig. 2). Notably, a number ofgenes encoding mitochondrial (green bars), plastid(red bars), and peroxisomal (blue bars) componentsfrom this overlapping set revealed strong correlations(Fig. 2). For example, for genes encoding translationfunctions, particularly ribosomal proteins, a strongconcordance was observed between transcript andprotein abundance, with positive correlations ob-served for all but two of the genes encoding translationfunctions (Fig. 2). Also, nine of the 14 mitochondrialproteins displayed significant positive correlations(r. 0.62); for example, two ADP/ATP carrier proteins(At3g08580 and At5g13490) that have a role in trans-port were seen to have significant positive correlations(Fig. 2; Supplemental Table S1). Additionally, 10 of the34 plastid proteins also showed strong positive corre-lations (r . 0.62; Fig. 2). The pattern of expression forthese organellar proteins (and transcripts), largelyencoding major metabolic components, showed anincrease over time, sometimes showing a lower/stableexpression by 48 h SL (Fig. 2). In contrast, embryodevelopment and other seed-related proteins, such asthe late embryogenesis abundance proteins (LEA) andtwo abscisic acid-responsive proteins, were mosthighly expressed in dry seed (0 h) and decreased inabundance in both transcript and protein to varyingdegrees upon imbibition. However, despite the differ-ence in expression pattern, these functions were alsoseen largely to show strong transcript and proteincorrelations. Thus, using microarray analysis of tran-script abundance and mass spectrometry-based quan-titation of proteins (Fig. 2), in a number of cases, it isclear that strong concordance is evident.

Comparative Analysis of Organelle Transcripts Reveals a

Transient Suite of Genes Unique to the Mitochondria

Of the 15,789 genes expressed in at least one timepoint during the germination time course, the genesencoding organelle-targeted proteins were analyzed tocompare transcriptomic profiles observed over thetime course of stratification and germination (Supple-mental Fig. S1; Supplemental Table S2). Using strictand consistent criteria of localization predication da-tabases and publications showing experimentally de-





termined localization (see “Materials and Methods”),genes were defined as encoding proteins localized tothe plastid (2,135), peroxisome (447), and mitochon-drion (980) in an equivalent manner (SupplementalFig. S1; Supplemental Table S2). By defining localiza-tions in this manner, bias for a single organelle wasreduced to a minimum, allowing maximum compara-bility between these gene lists (see “Materials andMethods”). For each gene set (e.g. the mitochondrialset; Fig. 3), expression values were hierarchically clus-tered, and four distinct clusters were observed: cluster1, transcripts that increased in abundance from 6 h SLand remained at high levels across the time course;cluster 2, highly expressed in dry seed and up to 12 h Sbefore decreasing over time; cluster 3, transientlyexpressed with low/absent expression levels in dryseed and up to 12 h S before increasing dramatically inabundance at 48 h S, but then decreasing after 6 to 12 hinto the light (SL); and cluster 4, largely unchanging inabundance over the time course. Upon examination ofthe genes encoding plastid-localized proteins, it wasevident that these were significantly overrepresentedin cluster 1 profiles (up-regulated after 6 h SL; 48%plastid versus 30% across the whole transcriptome;Supplemental Fig. S1Ai). This overrepresentation wasnot unexpected, given that the plastid proteins largelyfunction upon exposure to light. In contrast, genesencoding peroxisome proteins were not different inexpression pattern from that seen in the genome(Supplemental Fig. S1Aii). Interestingly, it was seenthat for the mitochondrial gene set, there was anoverrepresentation of transcripts showing transientexpression (cluster 3, 25% versus 15% across the wholetranscriptome; Fig. 3). The decrease seen in the abun-dance of transcripts in this transient cluster coincideswith the time point(s) when transcripts in cluster1 begin to increase (6–12 h SL) and also coincideswith the time point(s) when the morphological obser-vations reveal that mitochondria take on the typicalrod-shaped appearance (Fig. 1Aiii). Thus, the appear-ance of transcripts in cluster 3 correlates with a tran-sitional event from the dormant seed to activemitochondrial biogenesis. The correlation betweenmitochondrial function and this transitory burst inexpression led us to examine putative regulatory ele-ments in the promoters of these genes (Fig. 3).

In order to gain insight into the regulatory processesthat drive the observed changes in transcript abun-dance, the presence of cis-acting regulatory elementsor transcription factor-binding sites was analyzed.First, the promoter regions of genes in clusters 1 and3 were searched for 6-mers (six-nucleotide motifs) to

Figure 2. Concordance/discordance in transcript and protein abun-dance data during germination. Transcript and protein abundance data

were normalized to maximum and visualized as a heat map in order offunctional category. Pearson’s correlation coefficient was calculated foreach transcript/protein abundance pair. Correlation coefficients greaterthan 0.625 were considered statistically significant (P , 0.05) and areindicated by the gray line. Annotation and localization details for eachgene are shown in Supplemental Table S1, in accordance with thedisplayed order.

Law et al.




find significantly overrepresented motifs (Fig. 3, leftside). In addition, Pscan was used to search for motifsthat are known binding sites of specific transcriptionfactors (Zambelli et al., 2009), and their overrepresen-tation is shown with a variety of elements defined inclusters 1 and 3 compared with the genome represen-tation, and while there was some overlap (GATA, HeatShock Factor binding site, and Heat Shock Element),there were also distinct groups in each cluster (Fig. 3).Notably, the ABRE-like and DRE elements, which havebeen previously associated with germination, werepresent in cluster 1 but not in cluster 3 (Nakabayashiet al., 2005). Analysis of known transcription factor-binding sites may be more informative, as the regula-tors are known. Here, it was also observed that bothclusters 1 and 3 shared overrepresented binding sitesfor PIF3, ANT, FLC, ABI4, and CDC5, but cluster 3 wasalso unique in that it contained RAV1, DAG1, and

DAG2 binding sites, while cluster 1 contained bHLHbinding sites that were not enriched in cluster 3. Thebinding sites for all these transcription factors havebeen previously associated with germination, but withreference to the expression of plastid-encoded genes orproteins found in other locations (Peterson, 1977;Ikeda et al., 2009; Groszmann et al., 2010; Lau andDeng, 2010; Taylor et al., 2010; Rizza et al., 2011). Thus,it would appear that the regulation of genes encodingmitochondrial proteins during germination is likely tobe under these samemainstream regulatory pathways.Notably, the finding that genes encoding mitochon-drial proteins are overrepresented in this transientexpression pattern suggests that one of the earliesttargets of these previously characterized regulators ofgermination is in fact genes that encode mitochondrialproteins, which are activated very early during ger-mination.

Figure 3. Distribution of overrepre-sented motifs (left panel) and transcrip-tion factor (TF)-binding sites (rightpanel) and in the promoters of mito-chondrial genes (center panel). Alltranscripts for genes encoding mito-chondrial proteins called present at aminimum of one time point were nor-malized to the highest expressionvalue of each gene and hierarchicallyclustered. Cluster 3 of the mitochon-drial set was observed to be signifi-cantly enriched compared with theclustered distribution of the genome,indicated with an asterisk. On the left,putative regulator-binding motifs cal-culated to be overrepresented (byz-score analysis; P , 0.05) are indi-cated for clusters 1 and 3 (i.e. wheretranscripts were observed to increaseduring the time course of the experi-ment). On the right are listed knowntranscription factor-binding sites en-riched in clusters 1 (pink) and 3(green), as determined by Pscan (Zam-belli et al., 2009), with the expressionof the profile of the transcription fac-tors indicated according to cluster (e.g.the binding site for PIF3 is enriched ingenes present in clusters 1 and 3, andthe expression of PIF3 is assigned tocluster 1 by hierarchical clustering).





To gain a detailed insight into the mitochondrialfunctions activated as one of the primary events ofgermination, a functional analysis was carried out. Thefirst step involved further curation of the mitochon-drial gene list, which was generated largely uponcollation of localization data from 40 relevant publi-cations (Supplemental Table S2D; Supplemental Ma-terials and Methods S1). In this way, the expression ofa refined list of 945 genes encoding mitochondrialproteins was examined, and a custom pathway imagewas used to compare and contrast patterns of tran-script abundance for genes encoding mitochondrialproteins that were assigned to distinct functionalcategories (Fig. 4; Supplemental Fig. S1B). Stable andlow transcript abundance was observed in all func-tional categories at the first four time points (H, 0 h, 1 h

S, and 12 h S; Fig. 4), corresponding with the lack ofvisible mitochondria during this time (Fig. 1Ai). Thefirst suite of transcripts to undergo a discernible anddramatic increase in abundance were those encodingproteins belonging to the protein import apparatus ofthe outer mitochondrial membrane (TOMs, SAM, andmetaxin), which were seen to peak in expression at48 h S and 1 h SL (Fig. 4). The early increase in theabundance of these transcripts complies with previousfindings in rice that have also shown these genes to beamong the first to increase in transcript abundanceupon imbibition (Howell et al., 2006, 2009). Interest-ingly, however, this intensive examination of themitochondrial subset revealed that this distinct ex-pression pattern was also observed to a greater extentfor transcripts encoding proteins involved in the tran-

Figure 4. Transcript abundance profiles of genes encoding mitochondrial proteins during germination. Transcript abundancewas normalized to the maximum expression level during the time course, classified into nontrivial BINS, and displayed on acustom pathway image. A method of color-coding was utilized to distinguish subtle variations between the profiles. Three shadesof green were used to denote transcript abundance peaking at 48 h S/1 h SL (light green), 6 h SL (medium green), and 12 h SL(dark green). Two shades of red were used to denote transcript abundance increasing steadily, with maximal abundance in thefinal time point (dark red) and transcript abundance increasing steadily until 24 h SL, followed by a small decrease/stabilizationin abundance at 48 h SL (light red). For a number of transcripts, one or more proteins were quantitated. Purple asterisks have beenused to indicate when transcript and protein abundances peak at the same time point.

Law et al.




scription of mitochondria-encoded genes as well asRNA editing and splicing factors (Fig. 4, light greenshading). Notably, when the protein abundance forone of these factors (a mitochondrial pentatricopeptiderepeat [PPR; At5g46460]; Fig. 2) was quantitated, theprotein abundance also corresponded with the tran-sient expression seen for the respective transcript (Fig.4, purple asterisk; Supplemental Table S1). This tran-sient expression was also seen for RNA polymeraseand splicing factors as well as mitochondrial membersof the mitochondrial transcription termination factorfamily (Fig. 4), which have been shown to have a rolenot only in transcription termination but also in tran-scription initiation (Hyvarinen et al., 2010) and even inmodulating mitochondrial DNA replication (Hyvari-nen et al., 2007; Roberti et al., 2009). Interestingly, itwas seen that chloroplast RNA polymerase did notshow this transient expression pattern (data notshown) and instead peaked in expression at 48 h SL.Coincident with this early transient induction of genesinvolved in mitochondrial RNA metabolism was ananalogous increase in the abundance of transcriptsencoding proteins involved in cytosolic nucleotidesynthesis and a number of mitochondrial carrier pro-teins previously defined as nucleotide carriers (Pal-mieri et al., 2011; Fig. 4, nucleotide synthesis andnucleotide carriers).At 6 h SL, transcripts of genes encoding ribosomal

proteins, proteins involved in protein folding, and theinner membrane protein import machinery peaked, asdid a number of proteins associated with mitochon-drial DNA replication (Fig. 4, medium green shading).The final transient peak in transcript abundance wasobserved for genes encoding tRNAs and the proteinconstituents of the VDAC, which occurred at 12 h SL(Fig. 4, dark green shading; Supplemental Fig. S2, darkgreen shading). Quantitative western blotting alsorevealed that the protein abundance of VDAC accu-mulated in a similar way to the corresponding tran-script expression pattern from dry seed to 48 h S, andprotein abundance only peaked at the final time point(Supplemental Fig. S3).Transcripts encoding the metabolic functions of

mitochondria, such as components of the electrontransport chain, ascorbate glutathione metabolism,and photorespiration, all peaked later during germi-nation, at either 24 h SL or 48 h SL (Fig. 4, light red anddark red shading, respectively). Quantitative westernblotting for components of complex I, complex III, andcomplex V also revealed that these proteins peaked inabundance coincident with the respective transcriptabundances (Fig. 4; Supplemental Fig. S3). Interest-ingly, tricarboxylic acid (TCA) cycle components alsopeaked in transcript abundance at 24 h SL or 48 h SL(Fig. 4). It is possible that this late induction of the TCAcycle and glycolysis components reflects the change inenergy pathways, from the mobilization of storagelipids via b-oxidation and the glyoxylate cycle duringgermination (Bewley, 1997), which could provide theenergy for early RNA and protein metabolism, to the

use of newly fixed carbon through photosynthesisand the glycolytic degradation of sugars as seedlingestablishment occurs. Interestingly, genes encodingproteins of the glycolytic pathway, located in the cy-tosol but previously reported to be associated with theouter mitochondrial membrane (Graham et al., 2007),peaked in expression at the same time (48 h SL) as thetranscripts encoding mitochondrial metabolic func-tions (Fig. 4, glycolysis). Notably, these transcripts(encoding glycolytic functions) showed a very slowincrease in abundance during stratification and up to12 h SL (likely representing a minor response to im-bibition) before sharply increasing in transcript abun-dance at 24 h and 48 h SL, when the energy demandincreases with seedling establishment (Fig. 4, glycoly-sis).

The Mitochondrial Transcriptome, Nucleotide, and RNA

Metabolism during Germination

The changes in transcript abundance patterns de-scribed above suggest that mitochondrial RNA me-tabolism is activated very early during germination,just after imbibition. As ATH1 microarray GeneChipsuse polyadenylated mRNA to measure transcriptabundance, this is not a suitable platform to measurethe abundance of the nonpolyadenylated transcripts ofmitochondria-encoded genes. Thus, a qRT-PCR plat-form analyzing random-primed cDNAwas employedto measure transcript abundance for genes encoded inthe mitochondrial genome (de Longevialle et al., 2007).We used four time points to determine the pattern ofexpression for mitochondrial genes encoding proteinsfound in complexes I, III, IV, and Vand for three genes,ccmB, ccmC, and ccmF, that are required for cytochromec biogenesis (Giege et al., 2008). The profiles for thesemitochondrial transcripts were compared with thetranscriptomic profiles observed for the nucleus-encoded counterparts of these complexes at the sametime points: 0 h, 6 h SL, 24 h SL, and 48 h SL. The 0-hand 6-h SL time points reveal which mitochondrialtranscripts (indicated in gray) increased significantlyin abundance before the nucleus-encoded counterparttranscripts (indicated in red). The latter were seen tosignificantly increase in abundance only at or after 6 hSL (Fig. 5).

It was evident that the pattern of accumulation oftranscripts for mitochondrially encoded proteins dif-fered significantly compared with the accumulation oftranscripts for nucleus-encoded proteins in the samerespiratory complex (Fig. 5). While transcript abun-dance for both nuclear andmitochondrial genes was atits lowest at 0 h, several mitochondrial transcriptsincreased in abundance during stratification andpeaked in expression between 1 h SL and 12 h SL,while the nucleus-encoded counterparts increased inabundance later and peaked at 24 h SL (Fig. 5; Sup-plemental Table S3). Furthermore, the protein abun-dance for nucleus-encoded electron transport chaincomponents of complex I and complex III also peaked





at 24/48 h SL, as did their corresponding transcripts(Fig. 4; Supplemental Fig. S3). Thus, it appears that theearly increase in expression observed for nuclear genesencoding mitochondrial proteins associated with RNAtranscription, splicing, and editing has functional sig-nificance, as the transcript abundance of mitochondrialtranscripts increases in a similar manner and patternover the same time period. Interestingly, the proteinabundance of a mitochondrial PPR protein (At5g46460)also showed this transient expression, peaking inabundance at 48 h S before decreasing over time (Fig.2). Notably, the mitochondria-encoded transcripts gen-erally did not decrease in abundance, unlike thenucleus-encoded transcripts in cluster 3 (Figs. 3 and 5;Supplemental Table S3).

A corresponding survey of the chloroplast-encodedcomponents of the photosynthetic machinery andtheir nucleus-encoded counterparts was also carriedout for comparison (Supplemental Fig. S4). It wasobserved that the nuclear and plastid transcripts dif-fered in expression at 0 h, as the nuclear transcriptswere all lowly expressed or absent, while most of thechloroplast transcripts were moderately to highly ex-pressed (Supplemental Fig. S4). However, by 6 h SL,the abundance of plastid transcripts was reduced tolevels similar to those of their nuclear counterparts

and then proceeded to increase in abundance in a verysimilar manner to the nucleus-encoded components,with all transcripts peaking in expression at 48 h SL(Supplemental Fig. S4).

In order to further investigate the relationship be-tween the nucleus-encoded mitochondrial proteinsinvolved in RNA metabolism and their organelle-encoded targets, 261 PPR proteins known or predictedto be targeted to the mitochondria were compiled(Supplemental Table S4). Hierarchical clustering ofthese revealed that a significant percentage of this setof PPR proteins showed transient expression, peakingin expression between 48 h S and 6 h SL (62% versus15% in the genome; P , 0.01; Fig. 6A). A number ofstudies have characterized the interactions betweenspecific Arabidopsis PPR proteins and their organelle-encoded targets (Chateigner-Boutin et al., 2011;Hammani et al., 2011; Holzle et al., 2011; Jonietzet al., 2011; Verbitskiy et al., 2011; for review, seeDelannoy et al., 2007; Fujii and Small, 2011). Thesestudies were used as a basis to investigate specificregulatory events of mitochondrial RNA processingduring the germination time course (Fig. 6B). Whenthe transcript abundance for the PPR proteins andtheir targets were plotted together, it became clear thatthe PPR transcripts increased in abundance transiently

Figure 5. Coordination of nucleus- and organelle-encoded components of the mitochondrial electron transport chain.Expression values derived from microarray analysis of nucleus-encoded components of the mitochondrial electron transportchain were profiled in parallel to corresponding mitochondria-encoded components quantitated by qRT-PCR. For each genedisplayed, gene names, annotations, and abundance levels are detailed in Supplemental Table S3.

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before or coincident with their targets, but never after(Fig. 6B). Interestingly, the majority of PPR proteinsknown to bind just one transcript had a profile charac-terized by a single peak (e.g. MEF8, MEF22, andMEF18;Takenaka et al., 2010), while PPR proteins with multipleknown targets had profiles punctuated with multiplepeaks (e.g. MEF11 [Takenaka et al., 2010] and MEF1[Zehrmann et al., 2009]; Fig. 6B). These concordantprofiles were also observed when transcripts encodingchloroplastic PPR proteins were profiled alongside theirorganelle-encoded transcripts (Supplemental Fig. S5).Thus, it appears that the expression of nuclear genesencoding proteins implicated in RNA processing inmitochondria (and plastids) occurs just prior to, orcoincident with, changes in the target organelle tran-script abundance. This close correspondence may insome cases be due to a causative relationship: some PPRproteins have been shown to directly control RNAstability and accumulation (Prikryl et al., 2011).In addition to the genes encoding PPR proteins, it is

clear that a significant number of other nuclear genesencoding mitochondrial proteins display a transientexpression pattern, peaking in abundance at 48 h S

before decreasing in abundance after 6 h SL (cluster 3;Fig. 3; Supplemental Fig. S1B). Notably, this groupincluded the mitochondrial components of the purinebiosynthesis pathway, phosphoribosylaminoimida-zole synthase (At3g55010) and phosphoribosylformyl-glycinamidine amidotransferase (At1g74260), as wellas a series of mitochondrial carriers that were recentlypredicted to be nucleotide carriers based on sequenceconsensus analysis across organisms (Palmieri et al.,2011). This suggests a coordination of mitochondrialnucleotide synthesis and nucleotide transport withthis early RNA metabolism phase of mitochondrialbiogenesis initiation.

Considering the potential role of this transient phasein the development of functional mitochondria, wesought to gain an insight into the importance of theroles played by the 239 genes highlighted through asurvey of the genetic impact of their loss on Arabi-dopsis growth, development, and morphology (clus-ter 3; Supplemental Fig. S1B). To do this, a number ofdatabases and large-scale forward and reverse geneticstudies were queried, identifying phenotypes forknocked out/silenced genes. The databases included

Figure 6. Profiling mitochondria-targeted PPRs and their known organelle-encoded transcript targets. A, Hierarchical clusteringof the relative expression levels of 261 genes encoding PPR proteins targeted to the mitochondria. Of the four clusters identified,cluster 3, which is characterized by transient expression, was significantly (P, 0.001) enriched (62%) when compared with thetotal genome (15%). B, PPR proteins that have been characterized previously in the literature were normalized alongside qRT-PCR data showing expression of their known mitochondria-encoded RNA targets.





the SeedGenes database, which documents pheno-types for all genes showing embryo-lethal/defectivephenotypes (Meinke et al., 2008); the Chloroplast 2010Project, which reveals phenotypes for genes predictedto be localized to the chloroplast (Ajjawi et al., 2010);and the Agrikola database (Hilson et al., 2004). Fur-thermore, these were supplemented with individualgene searches in The Arabidopsis Information Re-source (TAIR; Swarbreck et al., 2008). Remarkably, ofthe 239 genes queried, one in three (78 genes) had apreviously observed (and published) altered phenotype(Fig. 7; Supplemental Table S5). Furthermore, thefinding that nearly 40% of these showed embryo-arrested/lethal phenotypes is a highly significantoverrepresentation (P , 0.01) in comparison with theexpected number in the genome (Berg et al., 2005;Bryant et al., 2011). The number of developmentallyimpaired phenotypes (specifically embryo lethal; Fig.7) suggests that the role of these proteins is highlysignificant for normal plant development. Taken to-gether with the observed synchronous expression seenfor these genes during germination, this suggests that

these genes not only carry out crucial mitochondrialfunctions but that their expression represents a crucialcontrol point during germination and seedling estab-lishment through the linkage of nucleotide synthesisand transport with RNA metabolism.

DISCUSSION

Mitochondrial populations in dormant dry seedsrepresent the minimum structure (promitochondria)required to produce mitochondria and are essentiallyin a state of synchronized dormancy with each other.The rapid development of mitochondria followingimbibition (the passive uptake of water by the seed)allows the synchronous maturation of mitochondria tobe investigated (Logan et al., 2001; Howell et al., 2006).Previous studies on mitochondrial biogenesis duringseed germination in maize have detailed the transitionfrom promitochondria to mature mitochondria thatcontain typical cristae morphology (Logan et al., 2001),but the regulatory and developmental processes thatdrive this maturation are unknown. In order to un-

Figure 7. Phenotypes observed in atransiently expressed set of genes en-coding mitochondrial proteins duringseed germination. Of the 239 tran-siently expressed genes (SupplementalFig. S1B; cluster 3), one in three (78genes) were observed to have a previ-ously published phenotype when si-lenced or knocked out (SupplementalTable S5). Of these, 37% presentedan embryo-arrested/lethal phenotype,which is three times greater than theexpected number of embryo-arrested/lethal phenotypes for the whole ge-nome. Other categories are as follows:leaf shape/development/amino acidcontent/fatty acid content/polysac-charide (AA/FA/PS) content, wholeplant affected, developmental, flowerdevelopment/timing/siliques, reduced/altered hypocotyl and/or root growth,and seed pigment/yield/amino acidcontent/fatty acid content (for details,see Supplemental Table S5). WT, Wildtype.

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cover the earliest events in mitochondrial activationduring germination, we carried out transcript andprotein profiling of Arabidopsis seeds from freshlyharvested seed (collected on the day from maturesiliques) through stratification (at 4�C in the dark onsolid Murashige and Skoog [MS] medium) and thenimbibition in light for 48 h. In parallel with this,tagging of organelles with fluorescent marker proteinswas used to monitor mitochondrial biogenesis. Or-ganelle transcript abundance changes were alsomonitored to investigate the coordination of geneexpression between the organelle and nuclear ge-nomes.Combining these investigations revealed that mito-

chondrial RNA and DNA metabolism, in terms of

transcription, translation, and replication, representthe earliest mitochondrial functions that are reestab-lished during the transition from promitochondria tometabolically active mitochondria during germination(Fig. 8). The activation of DNA and RNA functions issupported by the early peak in expression of factorsinvolved in cytosolic nucleotide metabolism and mi-tochondrial transporters that supply nucleotides to themitochondrial matrix (Fig. 8). There are two sources ofevidence that this peak in transcripts encoding mito-chondrial DNA- and RNA-related processes is func-tionally important. First, this peak precedes the rise inmitochondrial transcript abundance, which in turnprecedes the rise in transcripts for nucleus-encodedcomponents of mitochondrial metabolism (Figs. 4 and

Figure 8. A model for mitochondrial biogenesis during germination. Mitochondria in dry seeds lack cristae structures (Stasis).The earliest events that occur in mitochondrial biogenesis occur at the end of stratification and the first hour of transfer to lightand are associated with RNA transcription and translation, leading to an increase in the transcript abundance of mitochondria-encoded genes. The next stage, which occurs at 24 h after transfer to light, is the increase in the transcript abundance of genesencoding various metabolic components. For a number of transcripts, one or more proteins were quantitated. The stages at whichthe lowest/highest corresponding protein abundances are observed are indicated with black/green asterisks, respectively.





5). Second, mutational analysis of the genes that en-code these mitochondrial proteins shows that inacti-vation leads to either complete embryo arrest orslower development (Fig. 7; Meinke et al., 2008).Thus, this peak in transcript abundance for genesencoding mitochondrial proteins involved in DNAreplication and transcription is essential for normaldevelopment. Following this “biogenesis” state, themitochondria accumulate the apparatus necessary forenergy production and enter what we have termed a“metabolic” state (Fig. 8), which represents the maturemitochondria. Interestingly, the transcript abundanceprofiles of the components of the electron transportchain particularly displayed a high level of similaritywith the corresponding protein abundances (derivedfrom quantitative western-blot data and peptide massspectroscopy), with an accumulation of these compo-nents toward the final time points, peaking in abun-dance at 24 and 48 h SL (Fig. 8, green asterisk). Incontrast, mitochondrial import components were seento exhibit dissimilar patterns between transcript andprotein accumulation (Fig. 8); however, this was ex-pected, given that low correlations between transcriptand protein abundance for these components havebeen previously observed both in Arabidopsis (Listeret al., 2007) and rice (Howell et al., 2006).

The phasic nature of mitochondrial biogenesis out-lined in this study offers an intriguing insight into therole of the host over the endosymbiont. Being ofprokaryotic ancestry, it would not be surprising toobserve similarities in the transition from promito-chondrion to mature mitochondrion with that of thegermination of a bacterial endospore. Both structuresrepresent internalized bodies of a bacterial nature, andboth undergo a period of stasis prior to an “activationevent.” However, in contrast to promitochondria, thedormant endospore is in fact already replete with thenecessary apparatus required for germination, andactivation is a biophysical process without major mac-romolecular synthesis (Moir, 2006). This deviation inmolecular maturation serves to emphasize the crucialrole of the eukaryotic host cell.

Investigation of germination offers an excellent bi-ological system for studying the coordination of avariety of processes, given the rapid, wholesalechanges observed in a strict temporal progression. Inthis study, we have examined correlations betweennuclear and mitochondrial transcripts, correlationsbetween putative regulators of organelle gene expres-sion and their target transcripts, and correlations be-tween transcript and protein abundance. Analysis ofprotein abundance using western-blot analysis andmass spectrometry revealed a number of positivecorrelations between transcript and protein abun-dance (Fig. 2). In many cases where negative correla-tions were observed, it was simply due to a temporaldislocation (i.e. a period of lag between transcriptabundance and protein abundance). It has been pre-viously shown in other systems that the degree ofcorrelation between transcript and protein abundance

increases if time offsets are used (Irmler et al., 2008).Thus, the negative correlation observed for cruciferin(Fig. 2) is possibly due to the fact that while transcriptabundance has peaked at 48 h SL, the encoded proteinhas not yet accumulated. Similarly, for mitochondrialASP1 (At2g30970) and AAC2 (At5g13490), it was seenthat the transcript level increased from 48 h S to 6 h SLand then decreased/stabilized at 48 h SL, while thecorresponding proteins were still absent at 48 h S andonly increased in abundance from 6 h SL beforepeaking at 48 h SL (Fig. 2; Supplemental Table S1).Given the technical limitations of obtaining quantita-tive protein abundance, these data revealed (in thissystem at least) that when active cellular synthesis andgrowth are occurring, transcript abundance is likely tobe the primary level of control. A recent study inves-tigating the plastid-specific transcriptional program ofgermination found that during stratification and ger-mination, transcript and protein accumulation are notconcordant and postulated that plastid transcriptionwas more important for germination than translation(Demarsy et al., 2012). It should be noted that onlysemiquantitative macroarrays were used in that study,time points were much farther apart than in our work(dry seeds, imbibed seeds, and 2-, 4-, and 6-d-oldplantlets), and a 16-h-light/8-h-dark cycle was used,which imposes a daily modulation on top of thegermination process. Considering these differences,particularly the light/dark cycle, we would expect tosee differences between that study and ours. Interest-ingly, while it was noted that specific inhibition ofplastid translation with lincomycin did not preventgermination, it was seen that the inhibition of bothplastid and mitochondrial translation with chloram-phenicol completely prevents it (Demarsy et al., 2012),further emphasizing the integral role of mitochondrialbiogenesis during germination.

The analysis of nuclear and mitochondrial tran-scripts for proteins located in the same respiratorychain complex revealed that the peak in transcriptabundance occurs at different times. In fact, by 48 h S,mitochondria-encoded transcripts had peaked inabundance, whereas nucleus-encoded transcripts hadnot yet significantly changed in abundance comparedwith the harvested seeds (Fig. 5). Interestingly, even atthe protein level, nucleus-encoded proteins (complex Isubunit Ndufs4 [At5g67590] and cytochrome c subunit[At1g22840]) increased almost 10-fold in abundancefrom dry seed to 48 h SL, in contrast to the mitochond-rially encoded complex I protein NAD9 (AtMg00070),which only increased by more than 2-fold in abun-dance from dry seed to 48 h SL (data not shown). Thisapparent lack of coordination between mitochondrialand nuclear transcripts has been previously observedin mitochondrial biogenesis in Arabidopsis duringsugar starvation and refeeding (Giege et al., 2005).

This study has also allowed an investigation into thetime course of the accumulation of mitochondrialtranscripts compared with that of transcripts encodingproteins involved in processing these mitochondrial

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transcripts (Fig. 6). The expression of genes encodingPPR proteins during germination is strikingly en-riched in cluster 3, and it was revealed that thetranscript encoding a protein involved in transcriptmaturation, such as editing, always peaked in abun-dance prior to or coincident with the target transcriptfor those with known targets (Fig. 6). It was shown thatthe first hour of stratification represents a phase ofacute activity, where these genes are expressed andlikely active, which helps to explain the lethal orsevere growth phenotypes observed when these genesare inactivated (Fig. 7; Meinke et al., 2008). This rapidresponse is particularly intriguing in light of the seed’scapacity to cycle between different depths of dor-mancy for months or even years at a time in anticipa-tion of environmental conditions suitable for seedlingestablishment. As yet, the molecular regulation of dor-mancy cycling remains a mystery, although a numberof studies have identified a series of possible mecha-nisms (Cadman et al., 2006; Holdsworth et al., 2008;Footitt et al., 2011).The regulation of nuclear genes encoding mitochon-

drial proteins is often divided into anterograde andretrograde regulatory pathways (Millar et al., 2011).While retrograde pathways and signaling are inten-sively studied under stimulation via various stressesthat induce changes in transcript and protein abun-dance under stress (Wessel and Flugge, 1984), little isknown about the retrograde pathways that exist toregulate the expression of the majority of mitochon-drial proteins involved in carbon metabolism andrespiration during normal growth and development,or even if such pathways exist. One possibility is thatduring seed germination, no communication takesplace and that as soon as the conditions for germina-tion are satisfied, all events commence in essentially apreprogrammed manner limited only by biophysicalconstraints and the availability of substrates to achievegermination and seedling establishment. While thismodel could not account for temporal differences intranscript abundance observed between mitochon-dria- and nucleus-encoded transcripts, it is harder toexplain the temporal difference observed for nucleus-encoded transcripts that encode different functions.Another possibility is that retrograde signals are

sent from mitochondria to the nucleus to coordinategene expression that ensures that the germinationprocess only proceeds when different metabolic pre-conditions have been met in a series of checkpoints.While the existence and nature of such signals remainto be defined, it has been reported that perturbation ofboth mitochondrial and plastid translation by inacti-vation of the dual targeted, nucleus-encoded prolyl-tRNA synthetase 1 results in a retrograde response,with leaky mutants of this gene shown to result in thedifferential expression of genes encoding proteinsinvolved in photosynthetic functions (Pesaresi et al.,2006). Furthermore, plastidial gene expression repre-sents an important group of retrograde signaling fromplastids to the nucleus, indicating that organelle gene

expression can act as a retrograde signal (Pfannschmidt,2010). Thus, it is postulated in this study that the earlyburst in the transcript abundance of mitochondrialgenes uncovered here may be acting as a signal toprompt the expression of nuclear genes encoding pro-teins involved in various metabolic functions requiredfor germination and seedling establishment. However,intensive follow-up studies are necessary to validatethis hypothesis. Overall, it appears that while mito-chondrial functions appear to be under developmentalcontrol during the earliest stages of germination (i.e. theactivation of mitochondrial transcription and transla-tion), the next phase of gene expression may requiresignals from this preceding event before these re-sponses can occur and germination can progress toseedling establishment. Thus, it is proposed that nucle-otide synthesis and transport, and the concomitantmitochondrial transcription and translation, duringearly germination are essential steps to mediate thetransition frompromitochondria intomature mitochon-dria (Logan et al., 2001).

CONCLUSION

The transition of promitochondria to mature mito-chondria displaying high metabolic activity is charac-terized by a burst in the expression of genes encodingfunctions in nucleotide biosynthesis and transport aswell as in organelle RNA- and DNA-related functions.This switch occurs prior to the increase in mitochon-drial numbers, prior to the assumption of typical ovalmitochondrial morphology, and is probably essentialfor germination to occur. While this switch has notbeen identified in other plant species studies to date, itprovides a developmental target that may be used toensure that premature germination or sprouting doesnot occur in cereals, and it may also represent theearliest time points that putative signals potentiallyoriginating from the mitochondria could signal thenucleus to proceed with mitochondrial biogenesis.

MATERIALS AND METHODS

Transformation of Arabidopsis Ecotype Columbia with

Organelle-Targeted Fluorescent Proteins

A stably transformed line of Arabidopsis (Arabidopsis thaliana ecotype

Columbia [Col-0]) seed, expressing three distinct organelle-targeted fluores-

cent proteins, was generated via Agrobacterium tumefaciens-mediated transfor-

mation. The first construct consisted of the 42-amino-acid mitochondrial

targeting signal of alternative oxidase fused to GFP (Carrie et al., 2007) and

cloned into pCambia 1301 in place of GUS. The second construct consisted of

the full-length cDNA of the plastid-targeted small subunit of Rubisco

(Rubisco SSU) fused to RFP (Carrie et al., 2007) and cloned into the pGreenII

expression cassette (Hellens et al., 2000). The final construct consisted of the

peroxisomal targeting signal 1 fused to the C terminus of CFP in the binary

plasmid pFGC (Nelson et al., 2007). These constructs were stably transformed

by three consecutive rounds of Agrobacterium-mediated transformation uti-

lizing the floral dipping method outlined by Clough and Bent (1998). Follow-

ing the floral dipping, seeds were harvested and screened using antibiotic

selection, with hygromycin for the GFP construct, kanamycin for the RFP

construct, and glufosinate for the CFP construct.





Confocal Microscopy to Observe Organelle Biogenesis

during a Germination Time Course

The transformed seeds were surface sterilized by treatment with 0.05%

(v/v) Triton X-100 in 70% (v/v) ethanol followed by successive washes with

70% (v/v) ethanol and 100% (v/v) ethanol. The seeds were then plated on

Arabidopsis solid medium, containing 4.3 g of Gamborg’s B5 basal medium

(Austratec), 0.5 g of MES, and 30 g of Suc, made up to 1 L with double distilled

water. The seeds were then stratified for 48 h at 4�C in the dark, followed by an

additional 48 h in continuous light (100 mE m22 s21) at 23�C. Seeds were

collected throughout this time course, and the embryos were excised from the

surrounding endosperm and testa by submerging in water and applying

pressure with a coverslip. GFP, RFP, and CFP localization was monitored

using a Leica TCS SP2 multiphoton confocal microscope, with excitation

wavelengths of 410/440 nm (CFP), 460/480 nm (GFP), and 535/555 nm (RFP)

and emission wavelengths of 460/480 nm (CFP), 500 to 540 nm (GFP), and 570

to 625 nm (RFP). Images were analyzed using ImageJ image-processing

software (Abramoff et al., 2004).

Arabidopsis Tissue Collection for Transcript andProtein Analysis

Approximately 80 and 150 mg of Arabidopsis (Col-0) seeds was surface

sterilized as outlined above and sown on Arabidopsis solid MS medium (3%

Suc) for transcript and protein analysis, respectively. Sampling was carried

out at 10 time points: freshly harvested seed (H) on the day of collection from

plants, seeds following 15 d of dark, dry, ripening (0 h), seeds after 1 h of

stratification (imbibition of seeds on Arabidopsis MS medium at 4�C in the

dark; 1 h S), 12 h of stratification (12 h S), 48 h of stratification (48 h S), and on

plates transferred to continuous light and collected 1 h into the light (1 h SL), 6

h into the light (6 h SL), 12 h into the light (12 h SL), 24 h into the light (24 h SL),

and 48 h into the light (48 h SL; sampling as described by Narsai et al. [2011]).

Collections were repeated three times for three biological replicates.

RNA Isolation, qRT-PCR, and Microarray Analysis

The Ambion Plant RNA isolation aid and RNAqeous RNA isolation kit

were used for effective isolation of RNA from all samples collected. qRT-PCR

was carried out using the LightCycler 480 system (Roche). SYBR Green I was

the selected assay detection format, as carried out previously (Delannoy et al.,

2009). The primer sequences used in this study have been outlined (Delannoy

et al., 2009; Kuhn et al., 2009). For microarray experiments, 400 ng of total RNA

was used as the starting amount of RNA for the ATH1 Arabidopsis genome

expression array; for details, see Narsai et al. (2011). In order to view the

profiles of expression changes over the time course, all GC-robust multiarray

average was made relative to the maximum intensity over the time course. For

Supplemental Figure S1, these data were then hierarchically clustered using

average linkage clustering (based on Euclidean distance) in Partek Genomics

Suite version 6.5.

MapMan Analysis

To visualize the shifting patterns of the abundance of transcripts encoding

proteins targeted to the mitochondria, transcripts were mapped into a custom

mitochondrial MapMan pathway (Usadel et al., 2005), with 1,059 of the total

present set (15,789) being classified into nontrivial MapMan BINS. The

transcript abundance of each gene was scaled to range between 21 and 1,

and values were averaged across each BIN.

Compiling Lists of Organellar Proteins

To compare the changing patterns of transcript abundance between the

mitochondria, the chloroplast, and the peroxisome, it was necessary to

generate lists of transcripts encoding proteins targeted to these organelles.

To make these lists as comparable as possible, a consistent set of criteria was

employed, using SUBA (Heazlewood et al., 2007). Based on the output from

SUBA, next to each gene in each organelle list a source number is indicated,

where 1 refers to an experimentally determined localization by either mass

spectrometry or GFP analysis, 2 refers to a computationally predicted local-

ization based on protein sequence (however, for a gene to be denoted as 2, at

least five predictors needed to have predicted to the same localization), and 3

refers to a protein localization determined by both experimental analysis and

prediction. Given the limited experimental annotation for peroxisomal localiza-

tion and the limited number of peroxisomal predictors (PeroxP [Emanuelsson

et al., 2007] and WoLF PSORT [Horton et al., 2007]), the peroxisomal list was

augmented with genes from the AraPerox database (Reumann et al., 2004), and

these were denoted as 4. The predictor programs utilized were Predotar (Small

et al., 2004), TargetP (Emanuelsson et al., 2007),WoLF PSORT (Horton et al., 2007),

MitoProt2 (Claros and Vincens, 1996), SubLoc (Hua and Sun, 2001), iPSORT

(Bannai et al., 2002), MITOPRED (Guda et al., 2004) PeroxP (Emanuelsson et al.,

2003), MultiLoc (Hoglund et al., 2006), and LOCtree (Nair and Rost, 2005).

To produce a comprehensive list of genes encoding proteins targeted to the

mitochondria, a custom list of all currently defined genes encoding proteins

located in the mitochondria in Arabidopsis was manually compiled and

annotated based on a number of functional classifications: carrier proteins and

import components of the mitochondrial outer and inner membrane, constitu-

ents of the electron transport chain, prohibitins, generation enzymes, RNA

editing/splicing, RNA polymerase and organelle-encoded genes, transcription

factors, ribosomal proteins, translation factors, tRNAs, assembly, ascorbate/

glutathione, sulfur metabolism, heme, folate, and photorespiration. For defining

lists of mitochondrial proteins involved in amino acid metabolism, cytosolic

glycolysis, and the TCA cycle, annotations were based on MapMan ATH1

TAIR9 annotation BIN files with localization, as these functional categories

have been extensively defined previously. The annotated gene list for 945

mitochondria-located proteins was categorized into a BIN hierarchy for

display on the custom mitochondria MapMan image according to the BIN

structure shown in Supplemental Table S2. A full outline of the manual

curation of this list, including all references, can be found in Supplemental

Materials and Methods S1.

Phenotype Analysis of Transiently Expressed Genes

A subset of 239 transiently expressed genes encoding proteins targeted to the

mitochondria was cross-referenced against a number of large-scale forward and

reverse genetic studies, identifying phenotypes for knocked out/silenced genes.

Databases used were the SeedGenes database (Meinke et al., 2008), the Chlo-

roplast 2010 Project (Ajjawi et al., 2010), and the Agrikola database (Hilson et al.,

2004). Furthermore, these databases were supplemented with manual database

checking of TAIR (Swarbreck et al., 2008). Sources and full references for each

phenotype are shown in Supplemental Table S5.

Total Protein Extraction from Seed, and Protein

Quantification for SDS-PAGE and Western Blotting

Following collection, seeds were snap frozen with liquid nitrogen and

ground with a mortar and pestle. The extraction was carried out according to

the methodology outlined at http://www.seed-proteome.com. Total protein

was extracted in triplicate, at 2�C, in 2.2 mL of lysis buffer containing 7 M urea

(Bio-Rad), 2 M thiourea (AnalaR), 4% (w/v) CHAPS (Sigma-Aldrich), 18 mM

Tris-HCl (Amresco), and 0.2% (v/v) Triton X-100 (Sigma-Aldrich). Following a

10-min incubation at 4�C, 14 mM dithiothreitol was added. The protein

extracts were then stirred for 20 min at 4�C, followed by rounds of centrif-

ugation at 35,000g for 10 min at 4�C. Protein concentrations were then

measured in accordance with a methodology adapted from Schaffner and

Weissmann (1973). For each sample, 4 mL of protein extract was diluted with

25 mL of double distilled water, followed by the addition of 300 mL of Amido

black (taken from a stock solution containing 26mg of Amido black in 100mL of

acetic acid:MetOH [1:10]). This mixture was then mixed by vortexing and

incubated for 5 min at room temperature, followed by 4 min of centrifugation at

13,000 rpm at room temperature. Once the supernatant had been removed, the

pellet was washed with 500 mL of acetic acid:MetOH (1:10), followed by a

second round of centrifugation. Then, the dyed protein pellet was resuspended

in 1mL of 0.1 MNaOH and the absorbancewasmeasured at 615 nmon aUV-VIS

spectrophotometer (Shimadzu). A standard curve derived from eight dilutions

of a bovine serum albumin standard quantitated in the same manner was then

used to quantitate the samples.

SDS-PAGE and Western Blotting

SDS-PAGE was utilized to separate 30 mg of total protein extract from each

time point, alongside a purified mitochondrial sample (Supplemental Fig. S6),

which was then transferred to a supported polyvinylidene difluoride mem-

brane (Millipore) in Towbin buffer (Towbin et al., 1979), at 30 V for 16 h, using

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a Trans-Blot Plus Electrophoretic Transfer Cell (Bio-Rad). Probing of proteins

of interest was undertaken using an array of different antibodies that have

been described previously or purchased from Agrisera. The VDAC protein

was obtained from Dr. Tom Elthon (University of Nebraska). The antibody for

Kat2 has been described previously (Footitt et al., 2007). The antibodies for

ATP synthase, RbcS, RbcL, V-ATPase, and UGPase were purchased from

Agrisera. Blots were visualized by chemiluminescence (Roche Applied Sci-

ence) using an ImageQuant RT ECL Imager (GEHealthcare). The western-blot

band intensities were subsequently quantitated using ImageQuant TL soft-

ware (GE Healthcare).

Mass Spectrometry Identification of Proteins Expressedduring Germination

Following collection, seeds were snap frozen with liquid nitrogen and

ground to a powder in a Retsch ball mill. The extraction was carried out based

on Wessel and Flugge (1984) and carried out in triplicate. Briefly, the powder

was resuspended in SDS-Tris grinding buffer (500 mM Tris, pH 7.0, 7% [w/v]

SDS, and 10% [v/v] b-mercaptoethanol), and the solution was spun at 10,000g

for 5 min. To the supernatant were added 4 volumes of methanol, 1 volume of

chloroform, and 1 volume water; it was then vortexed and spun at 10,000g for

5 min. The protein interface was collected and washed in 500 mL of methanol,

and the pellet was air dried. The pellet was then resuspended in 20%

acetonitrile and 10 mMNH4HCO3 andmixed for 1 min at 30 Hz in a Retsch ball

mill at room temperature. The resulting solution was spun at 2,000g for 5 min,

and the resulting supernatant was collected. The protein content was deter-

mined by a modified Bradford assay using bovine serum albumin as a

standard (Peterson, 1977). A total of 250 mg was then digested and run on the

mass spectrometer as outlined previously (Taylor et al., 2010).

Output files from quantitative-time of flight data were conducted using the

Mascot search engine version 2.3.02 (Matrix Science) and the TAIR9 database

(June 19, 2009; 3,3621 sequences and 13,487,170 residues) utilizing error

tolerances of 6100 ppm for mass spectrometry and 6 0.5 D for tandem mass

spectrometry, Max Missed Cleavages set to 1, Oxidation (M) and Carbox-

ymethyl (C) variable modifications, the instrument set to ESI-Q-TOF, and

Peptide Charge set at 2+ and 3+. Output files for each triplicate treatment were

then aligned, including the protein MOWSE score, peptide matches, and the

Mascot-calculated exponentially modified protein abundance index values

based on Ishihama et al. (2005). Protein content was calculated using the

method of Ishihama et al. (2005) and shown as an average of triplicates with SE

(Supplemental Table S6.) Only proteins identified in two out of three biolog-

ical replicates in at least one time point were used for further analysis (Fig. 2).

In this way, 178 unique proteins were identified.

Supplemental Data

The following materials are available in the online version of this article.

Supplemental Figure S1. Hierarchical clustering of the transcript abun-

dance of transcripts targeted to the three energy organelles.

Supplemental Figure S2.MapMan visualization of transcripts involved in

mitochondrial processes during a germination time course.

Supplemental Figure S3. Protein abundance profiling of Arabidopsis seed

during a germination time course.

Supplemental Figure S4. Coordination of nucleus- and organelle-encoded

components of the chloroplast photosynthetic electron transport chain.

Supplemental Figure S5. Profiling of chloroplast-targeted PPRs and their

known organelle-encoded transcript targets.

Supplemental Figure S6. Confirmation quantitation of total proteins

extracted from Arabidopsis seeds during the germination time course.

Supplemental Table S1. Details of the 178 transcripts/proteins analyzed

in parallel, shown in accordance with the order presented in Figure 2.

Supplemental Table S2. Mitochondrial lists of genes generated using

SUBA through a combination of experimental evidence (mass spectros-

copy and GFP) and predictive tools.

Supplemental Table S3. Average transcript abundance of mitochondria-

encoded genes of the electron transport chain during germination, as

shown in Figure 5.

Supplemental Table S4. Lists of PPR proteins targeted to either the

mitochondria or the chloroplast.

Supplemental Table S5. Data for each gene that was found to have a

phenotype, details showing the number of genes showing known

phenotypes, and full references for these genes.

Supplemental Table S6. Abundance of 178 proteins calculated using the

exponentially modified protein abundance index during germination.

Supplemental Materials and Methods S1. A custom list of all currently

defined genes encoding proteins located in the mitochondria in Arabi-

dopsis that was manually compiled and annotated based on a number of

studies.

Received December 18, 2011; accepted February 13, 2012; published February

16, 2012.

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