Nucleotide and RNA Metabolism Prime Translational Initiation in the Earliest Events of Mitochondrial Biogenesis during Arabidopsis Germination

Temporal Examination of Organelle Biogenesis

The use of a stably transformed line of Arabidopsis seed containing different fluorophores targeted to the mitochondria, plastid, and peroxisome facilitated an in vivo temporal examination of biogenesis for the energy organelles during germination (Fig. 1A). Throughout the germination time course, peroxisomes (cyan channel) were observed to be present in high densities, with negligible changes to morphology and size (approximately 2 μm). This is consistent with the pivotal role of glyoxysomes and peroxisomes in metabolizing the energy stores present in oil seeds prior to the establishment of photoautotrophism (Graham, 2008). In the red channel, small proplastids (1–2 μm) were observed at high densities in the first time point (dry seed; Fig. 1Ai). The plastids remain small until as late as 12 h SL (i.e. 12 h into continuous light, following 48 h of stratification at 4°C in the dark), after which they undergo a major increase in size (approximately 4 μm) and exhibit a globular morphology by 48 h SL. This organellar expansion is symptomatic of the transition from undifferentiated proplastid to etioplasts and chloroplasts, as photosynthesis is established in the greening cotyledons. In the green channel, mitochondria could not be visualized in dry seeds, and as the mitochondrial, peroxisomal, and plastid fluorescence-tagged proteins were all driven by the 35S cauliflower mosaic virus promoter, the lack of a mitochondrial signal reflects mitochondrial mass or protein, not a lack of expression of the marker. However, following 48 h of stratification (Fig. 1Aii), GFP-containing mitochondrial populations could be observed, with varied morphologies and sizes (0.5–2 μm). After 12 h SL in continuous light (Fig. 1Aiii), the mitochondrial morphology took on a more uniform rod shape, accompanied by an increase in mitochondrial density. This is consistent with studies using electron microscopy that indicate that the cristae structure of mitochondria develop 12 to 24 h after imbibition (Logan et al., 2001; Howell et al., 2006). This increase in density and uniform morphology remained consistent throughout the remainder of the time course. In the early time points (Fig. 1A, i–iii), peroxisomes and proplastids had a seemingly random distribution within cells and were not observed to interact with each other. However, in the final time point (48 h SL; Fig. 1Aiv), the peroxisomes were observed to colocalize in clusters around the chloroplasts. Colocalization of this nature has been observed in adult leaf tissue previously (Mano et al., 2002) and suggests the establishment of photorespiration, a hallmark of the transition from glyoxysome to leaf peroxisome.

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Figure 1.

Developmental profiling of mitochondria, plastids, and peroxisomes in an Arabidopsis embryo/seedling over a germination 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, The cotyledon of an embryo dissected from a dry seed. Peroxisomes (cyan) and proplastids (red) are visible in high numbers. ii, The cotyledon 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 as distinct as in later time points. iii, The cotyledon of an embryo dissected at 12 h in continuous light (12 h SL). All three organelles are clearly visible. iv, The cotyledon of an embryo dissected at 48 h in continuous light (48 h SL). All three organelles are more clearly visible. The plastids (red) have quadrupled in size and are colocalizing with the peroxisomes. Bars = 15 μm. B, Total protein was extracted from Arabidopsis seeds collected during the germination time course and separated by SDS-PAGE (30 μg). Separated proteins were transferred to a polyvinylidene difluoride membrane and subjected to western-blot analysis. Following quantitation of band intensities using ImageQuant TL software (GE Healthcare), values were normalized to the highest level of intensity over the time course and graphed.

Protein abundance changes for several organelle proteins were analyzed across a time series from freshly harvested seeds (upon removal from siliques) as well as dry seeds after 15 d of ripening (0 h), across 48 h of dark stratification (S), and then following 48 h of exposure to light (SL) at 22°C. Western-blot analysis using antibodies raised to markers of different compartments showed that the pattern of protein expression over the time course differed substantially (Fig. 1B). For some proteins, the protein abundance did not dramatically change in abundance over the time course, with less than a 50% change in abundance seen from dry seeds to 48 h SL (Fig. 1B). This was true for the cytosolic marker UGPase, which maintained a relatively consistent abundance, being highly abundant (70% or 0.7) in harvested and dry seed to maximum abundance (100% or 1.0) at 48 h SL (Fig. 1B). The mitochondrial marker ATPβ varied in abundance from 60% (0.6) at harvest and dry seed to maximum abundance at 48 h SL (Fig. 1B). Larger increases in protein abundance were observed in mitochondrial voltage-dependant anion channel (VDAC) and the peroxisomal 3-ketoacyl-CoA thiolase (Kat2; 40% [0.4] at harvest and dry seed to 100% [1.0] at 48 h SL). The largest increases in protein abundance were observed for the two subunits of plastid Rubisco, denoted SSU and 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 Organelle Biogenesis during Germination

To study the process of organelle biogenesis during germination, transcript abundance changes were analyzed using the previously published microarray data (GSE30223; Narsai et al., 2011), and protein abundance was measured by shotgun mass spectrometry detection of peptides. Of the 15,789 genes expressed in at least one time point during the time course (Narsai et al., 2011), quantitative data for 178 of the corresponding proteins were obtained by counting peptide mass spectra (Ishihama et al., 2005; see “Materials and Methods”). For each of these, the corresponding transcript abundance was normalized to maximum (for the equivalent time points as the proteins) and visualized as a heat map in order of functional category (Fig. 2; Supplemental Table S1). In this way, it was possible to identify any concordance between transcript and protein levels during germination.

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Figure 2.

Concordance/discordance in transcript and protein abundance data during germination. Transcript and protein abundance data were normalized to maximum and visualized as a heat map in order of functional category. Pearson’s correlation coefficient was calculated for each transcript/protein abundance pair. Correlation coefficients greater than 0.625 were considered statistically significant (P < 0.05) and are indicated by the gray line. Annotation and localization details for each gene are shown in Supplemental Table S1, in accordance with the displayed order.

Examination of the heat map showing transcript and protein abundance, and the corresponding correlation coefficient for each gene revealed a pattern of concordance relating to function, with 81 of the 178 transcripts/proteins showing significant positive correlations of r > 0.62, while only 15 of the 178 transcripts/proteins showed significant negative correlations (r < −0.62; Fig. 2). Notably, a number of genes encoding mitochondrial (green bars), plastid (red bars), and peroxisomal (blue bars) components from this overlapping set revealed strong correlations (Fig. 2). For example, for genes encoding translation functions, particularly ribosomal proteins, a strong concordance was observed between transcript and protein abundance, with positive correlations observed for all but two of the genes encoding translation functions (Fig. 2). Also, nine of the 14 mitochondrial proteins displayed significant positive correlations (r > 0.62); for example, two ADP/ATP carrier proteins (At3g08580 and At5g13490) that have a role in transport were seen to have significant positive correlations (Fig. 2; Supplemental Table S1). Additionally, 10 of the 34 plastid proteins also showed strong positive correlations (r > 0.62; Fig. 2). The pattern of expression for these organellar proteins (and transcripts), largely encoding major metabolic components, showed an increase over time, sometimes showing a lower/stable expression by 48 h SL (Fig. 2). In contrast, embryo development and other seed-related proteins, such as the late embryogenesis abundance proteins (LEA) and two abscisic acid-responsive proteins, were most highly expressed in dry seed (0 h) and decreased in abundance in both transcript and protein to varying degrees upon imbibition. However, despite the difference in expression pattern, these functions were also seen largely to show strong transcript and protein correlations. Thus, using microarray analysis of transcript abundance and mass spectrometry-based quantitation of proteins (Fig. 2), in a number of cases, it is clear 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 time point during the germination time course, the genes encoding organelle-targeted proteins were analyzed to compare transcriptomic profiles observed over the time course of stratification and germination (Supplemental Fig. S1; Supplemental Table S2). Using strict and consistent criteria of localization predication databases and publications showing experimentally determined localization (see “Materials and Methods”), genes were defined as encoding proteins localized to the plastid (2,135), peroxisome (447), and mitochondrion (980) in an equivalent manner (Supplemental Fig. S1; Supplemental Table S2). By defining localizations in this manner, bias for a single organelle was reduced to a minimum, allowing maximum comparability between these gene lists (see “Materials and Methods”). For each gene set (e.g. the mitochondrial set; Fig. 3), expression values were hierarchically clustered, and four distinct clusters were observed: cluster 1, transcripts that increased in abundance from 6 h SL and remained at high levels across the time course; cluster 2, highly expressed in dry seed and up to 12 h S before decreasing over time; cluster 3, transiently expressed with low/absent expression levels in dry seed and up to 12 h S before increasing dramatically in abundance at 48 h S, but then decreasing after 6 to 12 h into the light (SL); and cluster 4, largely unchanging in abundance over the time course. Upon examination of the genes encoding plastid-localized proteins, it was evident that these were significantly overrepresented in cluster 1 profiles (up-regulated after 6 h SL; 48% plastid versus 30% across the whole transcriptome; Supplemental Fig. S1Ai). This overrepresentation was not unexpected, given that the plastid proteins largely function upon exposure to light. In contrast, genes encoding peroxisome proteins were not different in expression pattern from that seen in the genome (Supplemental Fig. S1Aii). Interestingly, it was seen that for the mitochondrial gene set, there was an overrepresentation of transcripts showing transient expression (cluster 3, 25% versus 15% across the whole transcriptome; Fig. 3). The decrease seen in the abundance of transcripts in this transient cluster coincides with the time point(s) when transcripts in cluster 1 begin to increase (6–12 h SL) and also coincides with the time point(s) when the morphological observations reveal that mitochondria take on the typical rod-shaped appearance (Fig. 1Aiii). Thus, the appearance of transcripts in cluster 3 correlates with a transitional event from the dormant seed to active mitochondrial biogenesis. The correlation between mitochondrial function and this transitory burst in expression led us to examine putative regulatory elements in the promoters of these genes (Fig. 3).

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Figure 3.

Distribution of overrepresented motifs (left panel) and transcription factor (TF)-binding sites (right panel) and in the promoters of mitochondrial genes (center panel). All transcripts for genes encoding mitochondrial proteins called present at a minimum of one time point were normalized to the highest expression value of each gene and hierarchically clustered. Cluster 3 of the mitochondrial set was observed to be significantly enriched compared with the clustered distribution of the genome, indicated with an asterisk. On the left, putative regulator-binding motifs calculated to be overrepresented (by z-score analysis; P < 0.05) are indicated for clusters 1 and 3 (i.e. where transcripts were observed to increase during the time course of the experiment). On the right are listed known transcription factor-binding sites enriched in clusters 1 (pink) and 3 (green), as determined by Pscan (Zambelli et al., 2009), with the expression of the profile of the transcription factors indicated according to cluster (e.g. the binding site for PIF3 is enriched in genes present in clusters 1 and 3, and the expression of PIF3 is assigned to cluster 1 by hierarchical clustering).

In order to gain insight into the regulatory processes that drive the observed changes in transcript abundance, the presence of cis-acting regulatory elements or transcription factor-binding sites was analyzed. First, the promoter regions of genes in clusters 1 and 3 were searched for 6-mers (six-nucleotide motifs) to find significantly overrepresented motifs (Fig. 3, left side). In addition, Pscan was used to search for motifs that are known binding sites of specific transcription factors (Zambelli et al., 2009), and their overrepresentation is shown with a variety of elements defined in clusters 1 and 3 compared with the genome representation, and while there was some overlap (GATA, Heat Shock 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 have been previously associated with germination, were present in cluster 1 but not in cluster 3 (Nakabayashi et al., 2005). Analysis of known transcription factor-binding sites may be more informative, as the regulators are known. Here, it was also observed that both clusters 1 and 3 shared overrepresented binding sites for PIF3, ANT, FLC, ABI4, and CDC5, but cluster 3 was also unique in that it contained RAV1, DAG1, and DAG2 binding sites, while cluster 1 contained bHLH binding sites that were not enriched in cluster 3. The binding sites for all these transcription factors have been previously associated with germination, but with reference to the expression of plastid-encoded genes or proteins found in other locations (Peterson, 1977; Ikeda et al., 2009; Groszmann et al., 2010; Lau and Deng, 2010; Taylor et al., 2010; Rizza et al., 2011). Thus, it would appear that the regulation of genes encoding mitochondrial proteins during germination is likely to be under these same mainstream regulatory pathways. Notably, the finding that genes encoding mitochondrial proteins are overrepresented in this transient expression pattern suggests that one of the earliest targets of these previously characterized regulators of germination is in fact genes that encode mitochondrial proteins, which are activated very early during germination.

To gain a detailed insight into the mitochondrial functions activated as one of the primary events of germination, a functional analysis was carried out. The first step involved further curation of the mitochondrial gene list, which was generated largely upon collation of localization data from 40 relevant publications (Supplemental Table S2D; Supplemental Materials and Methods S1). In this way, the expression of a refined list of 945 genes encoding mitochondrial proteins was examined, and a custom pathway image was used to compare and contrast patterns of transcript abundance for genes encoding mitochondrial proteins that were assigned to distinct functional categories (Fig. 4; Supplemental Fig. S1B). Stable and low transcript abundance was observed in all functional categories at the first four time points (H, 0 h, 1 h S, and 12 h S; Fig. 4), corresponding with the lack of visible mitochondria during this time (Fig. 1Ai). The first suite of transcripts to undergo a discernible and dramatic increase in abundance were those encoding proteins belonging to the protein import apparatus of the outer mitochondrial membrane (TOMs, SAM, and metaxin), which were seen to peak in expression at 48 h S and 1 h SL (Fig. 4). The early increase in the abundance of these transcripts complies with previous findings in rice that have also shown these genes to be among the first to increase in transcript abundance upon imbibition (Howell et al., 2006, 2009). Interestingly, however, this intensive examination of the mitochondrial subset revealed that this distinct expression pattern was also observed to a greater extent for transcripts encoding proteins involved in the transcription of mitochondria-encoded genes as well as RNA editing and splicing factors (Fig. 4, light green shading). Notably, when the protein abundance for one of these factors (a mitochondrial pentatricopeptide repeat [PPR; At5g46460]; Fig. 2) was quantitated, the protein abundance also corresponded with the transient expression seen for the respective transcript (Fig. 4, purple asterisk; Supplemental Table S1). This transient expression was also seen for RNA polymerase and splicing factors as well as mitochondrial members of the mitochondrial transcription termination factor family (Fig. 4), which have been shown to have a role not only in transcription termination but also in transcription initiation (Hyvärinen et al., 2010) and even in modulating mitochondrial DNA replication (Hyvärinen et al., 2007; Roberti et al., 2009). Interestingly, it was seen that chloroplast RNA polymerase did not show this transient expression pattern (data not shown) and instead peaked in expression at 48 h SL. Coincident with this early transient induction of genes involved in mitochondrial RNA metabolism was an analogous increase in the abundance of transcripts encoding proteins involved in cytosolic nucleotide synthesis and a number of mitochondrial carrier proteins previously defined as nucleotide carriers (Palmieri et al., 2011; Fig. 4, nucleotide synthesis and nucleotide carriers).

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Figure 4.

Transcript abundance profiles of genes encoding mitochondrial proteins during germination. Transcript abundance was normalized to the maximum expression level during the time course, classified into nontrivial BINS, and displayed on a custom pathway image. A method of color-coding was utilized to distinguish subtle variations between the profiles. Three shades of 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 the final time point (dark red) and transcript abundance increasing steadily until 24 h SL, followed by a small decrease/stabilization in abundance at 48 h SL (light red). For a number of transcripts, one or more proteins were quantitated. Purple asterisks have been used to indicate when transcript and protein abundances peak at the same time point.

At 6 h SL, transcripts of genes encoding ribosomal proteins, proteins involved in protein folding, and the inner membrane protein import machinery peaked, as did a number of proteins associated with mitochondrial DNA replication (Fig. 4, medium green shading). The final transient peak in transcript abundance was observed for genes encoding tRNAs and the protein constituents of the VDAC, which occurred at 12 h SL (Fig. 4, dark green shading; Supplemental Fig. S2, dark green shading). Quantitative western blotting also revealed that the protein abundance of VDAC accumulated in a similar way to the corresponding transcript expression pattern from dry seed to 48 h S, and protein abundance only peaked at the final time point (Supplemental Fig. S3).

Transcripts encoding the metabolic functions of mitochondria, such as components of the electron transport chain, ascorbate glutathione metabolism, and photorespiration, all peaked later during germination, at either 24 h SL or 48 h SL (Fig. 4, light red and dark red shading, respectively). Quantitative western blotting for components of complex I, complex III, and complex V also revealed that these proteins peaked in abundance coincident with the respective transcript abundances (Fig. 4; Supplemental Fig. S3). Interestingly, tricarboxylic acid (TCA) cycle components also peaked in transcript abundance at 24 h SL or 48 h SL (Fig. 4). It is possible that this late induction of the TCA cycle and glycolysis components reflects the change in energy pathways, from the mobilization of storage lipids via β-oxidation and the glyoxylate cycle during germination (Bewley, 1997), which could provide the energy for early RNA and protein metabolism, to the use of newly fixed carbon through photosynthesis and the glycolytic degradation of sugars as seedling establishment occurs. Interestingly, genes encoding proteins of the glycolytic pathway, located in the cytosol but previously reported to be associated with the outer mitochondrial membrane (Graham et al., 2007), peaked in expression at the same time (48 h SL) as the transcripts encoding mitochondrial metabolic functions (Fig. 4, glycolysis). Notably, these transcripts (encoding glycolytic functions) showed a very slow increase in abundance during stratification and up to 12 h SL (likely representing a minor response to imbibition) before sharply increasing in transcript abundance at 24 h and 48 h SL, when the energy demand increases with seedling establishment (Fig. 4, glycolysis).

The Mitochondrial Transcriptome, Nucleotide, and RNA Metabolism during Germination

The changes in transcript abundance patterns described above suggest that mitochondrial RNA metabolism is activated very early during germination, just after imbibition. As ATH1 microarray GeneChips use polyadenylated mRNA to measure transcript abundance, this is not a suitable platform to measure the abundance of the nonpolyadenylated transcripts of mitochondria-encoded genes. Thus, a qRT-PCR platform analyzing random-primed cDNA was employed to measure transcript abundance for genes encoded in the mitochondrial genome (de Longevialle et al., 2007). We used four time points to determine the pattern of expression for mitochondrial genes encoding proteins found in complexes I, III, IV, and V and for three genes, ccmB, ccmC, and ccmF, that are required for cytochrome c biogenesis (Giegé et al., 2008). The profiles for these mitochondrial transcripts were compared with the transcriptomic profiles observed for the nucleus-encoded counterparts of these complexes at the same time points: 0 h, 6 h SL, 24 h SL, and 48 h SL. The 0-h and 6-h SL time points reveal which mitochondrial transcripts (indicated in gray) increased significantly in abundance before the nucleus-encoded counterpart transcripts (indicated in red). The latter were seen to significantly increase in abundance only at or after 6 h SL (Fig. 5).

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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 transport chain were profiled in parallel to corresponding mitochondria-encoded components quantitated by qRT-PCR. For each gene displayed, gene names, annotations, and abundance levels are detailed in Supplemental Table S3.

It was evident that the pattern of accumulation of transcripts for mitochondrially encoded proteins differed significantly compared with the accumulation of transcripts for nucleus-encoded proteins in the same respiratory complex (Fig. 5). While transcript abundance for both nuclear and mitochondrial genes was at its lowest at 0 h, several mitochondrial transcripts increased in abundance during stratification and peaked in expression between 1 h SL and 12 h SL, while the nucleus-encoded counterparts increased in abundance later and peaked at 24 h SL (Fig. 5; Supplemental Table S3). Furthermore, the protein abundance for nucleus-encoded electron transport chain components 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 the early increase in expression observed for nuclear genes encoding mitochondrial proteins associated with RNA transcription, splicing, and editing has functional significance, as the transcript abundance of mitochondrial transcripts increases in a similar manner and pattern over the same time period. Interestingly, the protein abundance of a mitochondrial PPR protein (At5g46460) also showed this transient expression, peaking in abundance at 48 h S before decreasing over time (Fig. 2). Notably, the mitochondria-encoded transcripts generally did not decrease in abundance, unlike the nucleus-encoded transcripts in cluster 3 (Figs. 3 and 5; Supplemental Table S3).

A corresponding survey of the chloroplast-encoded components of the photosynthetic machinery and their nucleus-encoded counterparts was also carried out for comparison (Supplemental Fig. S4). It was observed that the nuclear and plastid transcripts differed in expression at 0 h, as the nuclear transcripts were all lowly expressed or absent, while most of the chloroplast transcripts were moderately to highly expressed (Supplemental Fig. S4). However, by 6 h SL, the abundance of plastid transcripts was reduced to levels similar to those of their nuclear counterparts and then proceeded to increase in abundance in a very similar 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 between the nucleus-encoded mitochondrial proteins involved in RNA metabolism and their organelle-encoded targets, 261 PPR proteins known or predicted to be targeted to the mitochondria were compiled (Supplemental Table S4). Hierarchical clustering of these revealed that a significant percentage of this set of PPR proteins showed transient expression, peaking in expression between 48 h S and 6 h SL (62% versus 15% in the genome; P < 0.01; Fig. 6A). A number of studies have characterized the interactions between specific Arabidopsis PPR proteins and their organelle-encoded targets (Chateigner-Boutin et al., 2011; Hammani et al., 2011; Hölzle et al., 2011; Jonietz et al., 2011; Verbitskiy et al., 2011; for review, see Delannoy et al., 2007; Fujii and Small, 2011). These studies were used as a basis to investigate specific regulatory events of mitochondrial RNA processing during the germination time course (Fig. 6B). When the transcript abundance for the PPR proteins and their targets were plotted together, it became clear that the PPR transcripts increased in abundance transiently before or coincident with their targets, but never after (Fig. 6B). Interestingly, the majority of PPR proteins known to bind just one transcript had a profile characterized by a single peak (e.g. MEF8, MEF22, and MEF18; Takenaka et al., 2010), while PPR proteins with multiple known targets had profiles punctuated with multiple peaks (e.g. MEF11 [Takenaka et al., 2010] and MEF1 [Zehrmann et al., 2009]; Fig. 6B). These concordant profiles were also observed when transcripts encoding chloroplastic PPR proteins were profiled alongside their organelle-encoded transcripts (Supplemental Fig. S5). Thus, it appears that the expression of nuclear genes encoding proteins implicated in RNA processing in mitochondria (and plastids) occurs just prior to, or coincident with, changes in the target organelle transcript abundance. This close correspondence may in some cases be due to a causative relationship: some PPR proteins have been shown to directly control RNA stability and accumulation (Prikryl et al., 2011).

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Figure 6.

Profiling mitochondria-targeted PPRs and their known organelle-encoded transcript targets. A, Hierarchical clustering of 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 the total 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.

In addition to the genes encoding PPR proteins, it is clear that a significant number of other nuclear genes encoding mitochondrial proteins display a transient expression 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 group included the mitochondrial components of the purine biosynthesis pathway, phosphoribosylaminoimidazole synthase (At3g55010) and phosphoribosylformylglycinamidine amidotransferase (At1g74260), as well as a series of mitochondrial carriers that were recently predicted to be nucleotide carriers based on sequence consensus analysis across organisms (Palmieri et al., 2011). This suggests a coordination of mitochondrial nucleotide synthesis and nucleotide transport with this early RNA metabolism phase of mitochondrial biogenesis initiation.

Considering the potential role of this transient phase in the development of functional mitochondria, we sought to gain an insight into the importance of the roles played by the 239 genes highlighted through a survey of the genetic impact of their loss on Arabidopsis growth, development, and morphology (cluster 3; Supplemental Fig. S1B). To do this, a number of databases and large-scale forward and reverse genetic studies were queried, identifying phenotypes for knocked out/silenced genes. The databases included the SeedGenes database, which documents phenotypes for all genes showing embryo-lethal/defective phenotypes (Meinke et al., 2008); the Chloroplast 2010 Project, which reveals phenotypes for genes predicted to be localized to the chloroplast (Ajjawi et al., 2010); and the Agrikola database (Hilson et al., 2004). Furthermore, these were supplemented with individual gene searches in The Arabidopsis Information Resource (TAIR; Swarbreck et al., 2008). Remarkably, of the 239 genes queried, one in three (78 genes) had a previously observed (and published) altered phenotype (Fig. 7; Supplemental Table S5). Furthermore, the finding that nearly 40% of these showed embryo-arrested/lethal phenotypes is a highly significant overrepresentation (P < 0.01) in comparison with the expected number in the genome (Berg et al., 2005; Bryant et al., 2011). The number of developmentally impaired phenotypes (specifically embryo lethal; Fig. 7) suggests that the role of these proteins is highly significant for normal plant development. Taken together with the observed synchronous expression seen for these genes during germination, this suggests that these genes not only carry out crucial mitochondrial functions but that their expression represents a crucial control point during germination and seedling establishment through the linkage of nucleotide synthesis and transport with RNA metabolism.

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Figure 7.

Phenotypes observed in a transiently expressed set of genes encoding mitochondrial proteins during seed germination. Of the 239 transiently expressed genes (Supplemental Fig. S1B; cluster 3), one in three (78 genes) were observed to have a previously published phenotype when silenced or knocked out (Supplemental Table S5). Of these, 37% presented an embryo-arrested/lethal phenotype, which is three times greater than the expected number of embryo-arrested/lethal phenotypes for the whole genome. Other categories are as follows: leaf shape/development/amino acid content/fatty acid content/polysaccharide (AA/FA/PS) content, whole plant affected, developmental, flower development/timing/siliques, reduced/altered hypocotyl and/or root growth, and seed pigment/yield/amino acid content/fatty acid content (for details, see Supplemental Table S5). WT, Wild type.