Chloroplast competition is controlled by lipid biosynthesis in evening primroses

Significance Plastids and mitochondria are usually uniparentally inherited, typically maternally. When the DNA-containing organelles are transmitted to the progeny by both parents, evolutionary theory predicts that the maternal and paternal organelles will compete in the hybrid. As their genomes do not undergo sexual recombination, one organelle will “try” to outcompete the other, thus favoring the evolution and spread of aggressive cytoplasms. The investigations described here in the evening primrose, a model species for biparental plastid transmission, have discovered that chloroplast competition is a metabolic phenotype. It is conferred by rapidly evolving genes that are encoded on the chloroplast genome and control lipid biosynthesis. Because of their high mutation rate, these loci can evolve and become fixed in a population very quickly.

Controlling for phylogenetic relatedness in the correlation mapping approach of the wild type plastomes Using the 13,912 1 kb windows of the wild type correlation mapping analyses (Materials and Methods), we determined whether the total count of nucleotide changes for every plastome in the aligned sequence window compared to the reference (total sequence divergence) significantly explained the inheritance strength of the plastomes, while controlling for shared patterns of nucleotide divergence between related lineages. To do this, we ran a phylogenetic generalized linear squares (PGLS) analysis using the nlme package in R v3.2.1 (9) in each genomic window. As underlying phylogeny, we used the maximum likelihood tree estimated from our manually curated plastome-wide ClustalW (10) multiple alignment (Dataset S2 and Materials and Methods; Fig. S1), obtained by employing Mega v7.02.6 (11) with its standard parameters and 300 bootstrap replications. Because our tree only encompasses 14 distinct lineages, we used the simplest model of phylogenetic correlation structure (12) to prevent overfitting by additional parameter estimation. In order to conform with the PGLS model assumptions, we repeated this analysis for our two continuous response variables -% of biparental inheritance from our biennis and blandina crosses (Table S7). After extracting p-values from the slope of each window-wise phylogenetically informed correlation, we controlled for an inflated false discovery rate by applying a Benjamini and Hochberg correction. Uncorrected p-values were plotted as a function of alignment position and p-values below the significance threshold of 0.05 were greyed out. Alignment windows whose corrected p-values still remained significant after correction were marked in red in the original Person/Spearman correlation mapping plot ( Fig. S1).

Chloroplast isolation
For isolation of chloroplasts, Oenothera leaf tissue was harvested 7-8 weeks after sowing and processed as described previously (2). However, minor modifications were applied to allow a rapid isolation of chloroplasts from six plant lines in parallel: 35 g of leaf material was homogenized in 500 ml BoutHomX buffer. The pellet from the first centrifugation step was re-suspended in 100 ml ChloroWash and, after one filtration, the volume was adjusted to 150 ml before the second filtration. After the second centrifugation step re-suspended chloroplasts were loaded on two Percoll step gradients (each: 7 ml 85% Percoll, 14 ml 45% Percoll). Subsequent to gradient centrifugation the recovered chloroplasts were washed with 30 ml ChloroWash, followed by three additional washing steps with smaller volumes and a final re-suspension of the chloroplasts in 300-500 µl ChloroWash for the following ACCase activity measurements.

Lipid extraction, mass spectrometry sample preparation and measurements
Metabolites were extracted according to published protocols (13) from 50 mg Oenothera seedlings harvested 6 DAS. In brief, frozen tissue was homogenized by a ball mixer mill and transferred to cooled 2.0 ml round bottom microcentrifuge tubes. Subsequently, each sample was resuspended in 1.0 ml of a -20°C methanol:methyl-tert butyl-ether [1:3 (v/v)] mixture, containing 0.5 μg of 1,2-diheptadecanoyl-sn-glycero-3-phosphocholine (Avanti Polar Lipids, Alabaster, AL, USA) as an internal standard. Samples were then immediately vortexed before incubation for 10 min at 4°C on an orbital shaker. This step was followed by ultra-sonication in an ice-cooled bath-type sonicator for an additional 10 min. To separate the organic from the aqueous phase, 650 μl of a H2O:methanol mix [3:1 (v/v)] was added to the homogenate, which was briefly vortexed before being centrifuged for 5 min at 14,000 g. Finally, 500 μl of the upper methyl-tert butyl-ether phase, containing the hydrophobic (lipid) compounds, was placed in a fresh 1.5 ml microcentifuge tube. This aliquot was either stored at -20°C for up to several weeks or immediately concentrated to complete dryness in a speed vacuum concentrator at room temperature. Prior to analysis the dried pellets were re-suspended in 400 μL acetonitrile:isopropanol [7:3 (v:v)], ultra-sonicated and centrifuged for 5 min at 14,000 g. The cleared supernatant was transferred to fresh glass vials and 2 μl of each sample was injected onto a C8 reverse phase column (100 mm x 2.1 mm x 1.7 μm particles) using a Acquity UPLC system (Waters, Manchester, UK). In addition to the individual samples, we prepared pooled samples, in which 10 µl aliquots of each sample from the whole sample collection were combined. These pooled samples were measured after every 20 th sample, to provide information on system performance including sensitivity, retention time consistency, sample reproducibility and compound stability.
The mobile phase for our chromatographic separation consisted of Buffer A (1% 1 M NH4-acetate and 0.1% acetic acid in UPLC MS grade water), while Buffer B contained 1% 1 M NH4-acetate and 0.1% acetic acid in acetonitrile/isopropanol [7:3 (v:v)] (BioSolve, Valkenswaard, Netherlands). The flow rate of the UPLC system was set to 400 μl/min with a Buffer A/Buffer B gradient of 1 min isocratic flow at 45% Buffer A (55% Buffer B), 3 min linear gradient from 45% to 25% Buffer A (55% to 75% Buffer B), 8 min linear gradient from 25% to 11% Buffer A (75% to 89% Buffer B), and 3 min linear gradient from 11% to 1% Buffer A (89% to 99% Buffer B). After cleaning the column for 4.5 min at 1% Buffer A/99% Buffer (B) the solution was set back to 45% Buffer A/55% Buffer (B) and the column was re-equilibrated for 4.5 min, resulting in a final run time of 24 min per sample.
Mass spectra were acquired with an Orbitrap-type mass spectrometer (Exactive; Thermo-Fisher, Bremen, Germany) and recorded in the full scan mode, covering a mass range from 100-1,500 m/z. The resolution was set to 60,000 with 2 scans per second, restricting the maximum loading time to 100 ms.
Samples were injected using the heated electrospray ionization source (HESI) at a capillary voltage of 3.5 kV in positive and negative ionization mode. A sheath gas flow value of 40 was used, with an auxiliary gas flow value at 20 and a capillary temperature of 200°C, while drying gas temperature in the heated electro spray source was 350°C. The skimmer voltage was set to 20 V with tube lens value at 140 V. The spectra were recorded from 0 to 20 min of the UPLC gradients.

Data processing and normalization of lipid data
Data analysis of the raw files (*.raw) was performed using QI for metabolomics v2.3 (Nonlinear Dynamics, Newcastle upon Tyne, UK) according to the vendor description. Data were normalized to the internal standard (1,2-diheptadecanoyl-sn-glycero-3-phosphocholine) and the exact fresh weight of each sample.

Determination of photosynthetic parameters
Gas exchange measurements were performed with a GFS-3000 open gas exchange system equipped with the LED array unit 3055-FL as actinic light source for simultaneous chlorophyll a fluorescence measurements (Heinz Walz GmbH, Effeltrich, Germany). Light response curves of CO2 assimilation were measured at 22°C cuvette temperature with 17,500 ppm humidity and a saturating CO2 concentration of 2,000 ppm, to fully repress photorespiration. Plants were dark-adapted for a minimum of 30 min. Then, the maximum quantum efficiency of photosystem II in the dark-adapted state (FV/FM) and leaf respiration were determined. Afterwards, the actinic light intensity was first set to the growth light intensity of 200 µE m -2 s -1 , followed by measurements at 500, 1,000, and finally 1,500 µE m -2 s -1 . At each light intensity, gas exchange was recorded until a steady state of transpiration and leaf assimilation was reached. Maximum leaf assimilation was corrected for the respiration measured in darkness. After the end of the gas exchange measurements, the chlorophyll content and chlorophyll a/b ratio of the measured leaf section were determined in 80% (v/v) acetone according to (16). Leaf absorptance was calculated from leaf transmittance and reflectance spectra as 100% minus transmittance (%) minus reflectance (%). Spectra were measured between 400 and 700 nm wavelength using an integrating sphere attached to a photometer (V650, Jasco Inc., Groß-Umstadt, Germany). The spectral bandwidth was set to 1 nm, and the scanning speed was 200 nm min -1 .
Fluorescence microscopy and differential interference contrast to analyze ptDNA nucleoids, chloroplast volume and number per cell We investigated leaf material from the central laminal region of the first true leaf 25 DAS. For this, four pieces of 5 mm 2 were excised from five individual plants per line and fixed. DAPI (4',6-diamidino-2phenylindole) stains of ptDNA nucleoids and fluorescence microscopy were conducted as previously described (17,18) with minor modifications: In brief, excised leaf fragments were fixed with 3% glutaraldehyde in 50 mM phosphate buffer (pH 7.2), washed in 1x PBS buffer (phosphate-buffered saline, 137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4, pH 7.2) and macerated in 1% (w/v) cellulase and 1% (w/v) pectinase solution (both Sigma-Aldrich, St. Louis, MO, USA) in the 1x PBS for 30 min at 37°C. Subsequently, explants were washed in 1x PBS and stored at 4°C until use. For microscopy, small tissue sectors were gently squeezed into a drop of the 1x PBS between a microscope slide and a cover glass. Then preparations were frozen in liquid nitrogen and, after removing the cover glasses, air dried and mounted in a drop of DAPI solution [5 µg/ml DAPI (Sigma-Aldrich, St. Louis, MO, USA) in 1x PBS buffer in 70% glycerol ("for fluorescence microscopy"; Merck, Darmstadt, Germany)]. DAPI as fluorochrome is considered to be sensitive enough to detect DNA of a single plastid genome copy (19). The preparations were sealed with Fixogum rubber cement (Marabu, Tamm, Germany) and examined with a Nikon Eclipse Ni-U upright epifluorescence microscope equipped with a cooled monochrome camera (Nikon, Chiyoda, Japan) under a 100x UV objective. For each investigated cell, five to seven picture frames were digitally captured, each at a different focal plane. The frames were stacked and combined using standard macro  (20). For statistical analysis of each experiment, for comparison of all lines, one-way ANOVA was performed. In addition, to test differences between the weak plastome I variants or IV-atroSt and the strong wild type I-johSt, a two-tailed homoscedastic t-test followed by adjustment of p-values according to Benjamini-Hochberg was performed. (Tables S15 and S16).

Generation of green variants with altered inheritance strength
For functional validation of loci predicted by correlation mapping in the wild types (see Main Text and below), mutagenesis of the strong chloroplast genome I-johSt was conducted using the Oenothera plastome mutator (see Materials and Methods for details). Inheritance strengths of the obtained green variants were determined in crosses to the white chloroplast mutants I-chi or IV-delta as pollen or seed parent, respectively (Materials and Methods for details, Fig. 2, Table S10, and Main Text).
The progeny of three seasons were analysed for the two crossing series. From these experiments it appeared that the lines VC1 and V3g (together with the weak wild type IV-atroSt) have very low assertiveness rates in the F1. As already judged by eye, they form a distinct class from all other variants in both crossing directions ( Fig. 2; Table S10). For the reciprocal cross, no significant differences from the strong wild type I-johSt were found for the variants V1c, V2f, and V3e, meaning that these variants had the same transmission efficiency as the wild type, although they underwent a mutagenesis approach and carry background mutations. This makes them a particularly valuable material to identify plastome mutatorinduced mutations that do not affect chloroplast inheritance. All other variant plastids showed a significantly decreased competitive ability from at least one parent when compared to the wild type chloroplast genome I-johSt. In general, the plastome I variants cannot be grouped easily into the classes of Schötz (strong, The results of the classical experimental set up in which bleached chloroplast mutants are used, could be confirmed in a MassARRAY® approach employed for the crosses of the plastome I variants with the strong wild type plastome I-hookdV as male parent or the weak wild type IV-atroSt as the female parent (see Materials and Methods for details). Due to the detection threshold of the method (5-10%) when I-hookdV was transmitted through the pollen, most variants showed the same or slightly decreased transmission efficiency as their wild type I-johSt, with the progeny having increased amounts of paternal plastid DNA (ptDNA). However, only for VC1 and V3g is the difference of the ratio of paternal and maternal ptDNA in the pool large enough to result in the detection of a significantly lower assertiveness rate (Fig. 2B). The lines behave similarly in the other crossing direction, where most variants seem to be of wild type competitive ability. Again VC1 and V3g can clearly be confirmed as weak lines, while V3c and V3f (which appear as weak to intermediate when contributed by the female), show a higher transmission efficiency than I-johSt. This is the same reciprocal difference that is observed in the classical experimental set up (Fig. 2). Altogether, especially due to the detection limit, the classical approach using bleached chloroplast mutants gives more reliable results and allows a much finer discrimination of transmission efficiencies. Moreover, there is no qualitative difference in the assertiveness rates between the green wild types I-hook/IV-atroSt and their corresponding bleached mutants I-chi/IV-delta. This is in agreement with the classical literature (24) and investigated in more detail below.
2. The green plastome I variants do not display impaired growth, altered chloroplast morphology, nor a photosynthetic phenotype To rule out the possibility that the observed differences in chloroplast inheritance strength result from secondary effects in the green variants we performed several controls: First, we monitored growth behavior of plants with the green chloroplasts of different inheritance strength in the common nuclear background of johansen Standard. Second, to access the physiological status of the material, we measured photosynthesis parameters. Third and last, we performed detailed microscopy to investigate chloroplast size, number per cell and morphology.

No growth, germination or macroscopic phenotypes are present in the plastome I variants
To ensure that the green variants are not impaired in development, cultures of johansen Standard plants harboring various variant chloroplasts were compared side-by-side to plants with their strong wild type chloroplast genome I-johSt and the weak one IV-atroSt. It appeared that seeds from all plant lines germinated at 100% within 3 days after sowing (DAS). After transfer to soil, no differences in growth were observed during whole plant development under standard greenhouse conditions. Also no macroscopic phenotype such as altered leaf coloration was observed (Fig. S7).

Photosynthetic parameters are unaltered in the plastome I variants
To gain insights into the physiological status of our materials, we determined several photosynthetic parameters and plotted them against competitive ability (Fig. S8). From these analyses it became clear that differences in photosynthesis capability, if present at all, cannot be interpreted as a function of inheritance strength: We could not detect significant differences between plants nor dependencies of inheritance strengths on chlorophyll content per leaf area or for chlorophyll a/b ratio. The latter reflects the ratio of the photosynthetic reaction centers (exclusively binding chlorophyll a) to the antenna proteins (which bind both chlorophyll a and b). Also FV/FM, the maximum quantum efficiency of photosystem II (PSII) in the darkadapted state, did not show any changes with inheritance strengths. All measured values were above 0.8 indicating that PSII was intact and that its antenna proteins were efficiently coupled to the reaction centre.
There was a minor tendency towards a decrease of leaf respiration in darkness with higher assertiveness rates. However, neither for leaf assimilation rates measured at the growth light intensity of 200 µE m -2 s -1 , nor for assimilation capacity measured under light-saturated conditions, were changes dependent on competitive ability observed. Similarly, for other photosynthetic parameters tested, including leaf absorptance, the chlorophyll a fluorescence parameters qN (non-photochemical quenching, a measure for the thermal dissipation of excess excitation energy in the antenna bed of PSII) and qL (a measure of the redox state of the PSII acceptor side), no clear differences dependent on competitive ability were found.

Chloroplast sizes, numbers or volumes per cell are unchanged in the plastome I variants
To test if differences in competitive ability are a side effect of a putative chloroplast division phenotype, our strong wild type I-johSt was compared to three lines with weak transmission efficiency (VC1, V3g and IV-atroSt). For this, we performed light microscopy using DIC optics at a developmental stage where the  (Table S15). Very similar results were obtained for the chloroplast volume, for which one-way ANOVA gave a value of 0.51 in the comparison of all four lines. Comparing I-johSt with the weak plastomes also did not uncover significant differences, as judged from multiple t-testing (Table S16) 3. Correlation mapping As described above, the green variants do not display any phenotype other than an altered inheritance of the chloroplast in crosses. Together with the wild type chloroplasts of different inheritance strengths, this makes them a valuable material to pinpoint molecular loci for chloroplast transmission encoded on the plastome. In contrast to algae or fungi, however, organelle genomes of higher plants or animals are not amendable to linkage mapping (25). Consequently, in these materials, identification of functionally relevant loci can only be based on correlation of a polymorphism within a given sequence interval to a phenotype in a mapping panel. To our best knowledge, this has been done only manually so far (26,27), which somewhat limits these analyses to a manageable number of organelle sequences, as well as to simple phenotypes, such as the presence or absence of sterility (28). We therefore developed a novel mapping approach that fills this methodological gap. Conceivably, this approach could be applied to map loci conferring cytoplasmic male sterility (28), mitochondrial diseases (29), cytonuclear incompatibility or to analyze adaptive cytoplasms (30)(31)(32).
The method is based on Spearman's rank and/or Pearson's correlation (Materials and Methods), with the latter capturing linear dependencies more directly. Since (i) presence or absence of linear dependencies in our data structure is a matter of speculation, and (ii) as a rank-based correlation metric, Spearman correlation yields more statistically robust results that are less influenced by outliers, we have used both approaches. For this, we calculated sequence divergence (total count of nucleotide changes, i.e. SNPs, insertions and deletions) in respect to a reference sequence (see below) for every sequence in an alignment at a given alignment window. The value thus obtained is then correlated with a phenotype. In our case, this is a class of inheritance strength or a percentage value expressing transmission efficiency of a given chloroplast genome (see above and Materials and Methods for details). For example, if the reference sequence represents a strong chloroplast genome and, relative to it, certain weak plastomes contain polymorphisms in the same alignment window, this window is identified as highly relevant for inheritance strength ( Fig. 1A; Fig. S17). Subsequently, individual polymorphisms or regions within this window are analyzed separately (Fig. 1B). Since full organelle genomes are analyzed, more than one relevant site can be identified. However, as for any other association mapping approach, the presence of two or more genetically independent loci that confer the same phenotype can complicate the conclusion. Perfect correlation coefficients of 1 or -1 might not be achievable at a single site.
Another common challenge of all genome wide association studies, a lack of resolution to identify functionally relevant loci due to linkage disequilibrium, is especially challenging in a non-recombining system such as an organelle genome. Here, linkage to phylogeny is extreme and even absolute correlation at a single site may be due to genetic hitchhiking via linkage disequilibrium, and not necessarily due to functional relevance. However, also the opposite is true. Non-independence from the phylogeny does not necessarily stand against functionality. Ideally, this problem can be partially circumvented, if phylogenetic independence of the correlation between a given trait (e.g. inheritance strength) and a sequences window can be shown. This indicates functionality, since trait and sequence windows must have evolved at least twice independently. Phylogenetic independent contrasts (PIC) or related methods such as phylogenetic generalized least squares (PGLS) test this null-hypothesis, which motivated us to implement a phylogenetic control in our correlation mapping approach (SI Materials and Methods). However, since a lack of sufficient independence from phylogeny does not stand against functionality (see above), in our context, these methods are only informative for the subset of cases where independent evolution indeed happened and cannot replace experimental verification of predictive loci.

Categorization of wild type and mutant plastomes into classes of inheritance strength
The datasets that measure inheritance strength of wild type chloroplasts or the green variants were either obtained from the literature or produced in this work. They represent percentage values of heteroplasmic seedlings in an F1 generation that reflect inheritance strength of a given chloroplast genome (Tables S7 and   S10; see above). The numbers can be directly applied to Spearman's/Pearson's correlation. If datasets of more than one crossing series are to be combined, clustering of the crossing data into classes is necessary.
For the wild type plastomes, we used the original data of Franz Schötz, where two sets of crosses "biennis white" and "blandina white" are available (33,34) (Table S13; Materials and Methods); inheritance strength of 25 wild type chloroplasts was determined using these previously described tester lines.
Clustering of the two datasets with the k-means algorithm using the optimal number of centers (k = 3) confirmed the original classifications suggested by Schötz, with the exception of the I-bauriSt and II-corSt plastomes ( Fig. S16A; for details see Materials and Methods). These plastomes were borderline genotypes in Schötz's classification system, and according to our data, they might be reassigned. Besides these minor discrepancies, clustering supports the presence of the three classes of inheritances strengths (strong, medium and weak) among the wild type plastomes of Oenothera, as previously described.
The clustering of the green variants is less clear. When data from the I-chi and IV-delta crossing experiments are combined, the pamk function identified k = 2 as the optimal number of clusters, clearly separating the weak from the stronger materials (Fig. S16B). However, finer clustering of the stronger variants leads to ambiguous class membership. This is likely due to the higher variation in the IV-delta crosses compared to the I-chi crosses ( Fig. 2

Selection of reference sequences for correlation mapping
For correlation mapping in the wild types the chloroplast genome of I-hookdV was chosen as a reference for two reasons: The plastome is the strongest one known (Table S13), but also the most derived one as judged from phylogenetic analyses (Fig. S1, SI Materials and Methods). Based on this it is a natural choice, since every polymorphism in respect to this reference should potentially make a chloroplast genome weaker.
A similar argument applies to the reference I-johSt in the correlation analysis of the green variants. This plastome is the progenitor of these lines.

Correlation mapping in the wild type plastomes
Pearson's correlation generally identified more windows than Spearman's, but both predict essentially the same regions relevant for inheritance strengths. Interestingly, there was no notable difference between the methods if either k-means classes or the "biennis/blandina white" crossing data were used for correlation ( Fig. 1A, Fig. S1, and Dataset S1). Largely based on theoretical considerations (presence of three clearly ranked classes in the wild types and stronger experimental base if the "biennis white" and "blandina white" crossing experiments are combined; see above), we discuss here Spearman's rank correlation to k-means classes in more detail. According to the latter, sequence windows in the ycf1 and ycf2 genes (between alignment positions 99011-100000 and 134641-135640) show nearly absolute correlation to inheritance strengths (rho = -0.99, p < 0.0005; Dataset S1). In both genes, the correlation oscillates from rho = 0.86 to -0.99 (p < 0.0005), and the positive and negative correlation should be interpreted as equally important.
Another nearly absolute correlation (rho = 0.98, p < 0.0005) was measured in alignment windows containing the promoter, 5'-UTR and 5'-end of accD (positions 63501-64760). A window further upstream containing the same features (positons 63391-64490) also correlates with rho = 0.96, p < 0.0005 (Fig. 1B). However, highly significant correlations of 0.96 were also found in intergenic regions of photosynthesis genes and/or tRNA genes, for example between ycf3 and psaA (encoding a photosystem I assembly factor and core subunit, respectively) (35). In addition, significant correlations were measured from the spacers of the photosystem II and cytochrome b6f subunit genes psbE and petL, and in a sequence interval contacting trnR-UCU and trnG-UCC. In contrast, no significant correlation was observed for oriA. For oriB, three sequence windows (partially) containing the oriB correlate with 0.90, 0.88 (both p < 0.0005) and 0.81 (p< 0.005). If Pearson's correlation to k-means classes is applied to the wild type data, the described pattern can be reproduced but more windows with significant correlation are identified ( Fig. 1 and see above). The highest observed Pearson correlation in the wild type dataset is r = 0.96 (p < 0.0005) in a sequence window again containing the promoter, 5'-UTR and the 5'-end of accD (Fig. 1B, Dataset S1).

Correlation mapping in the green variants
When correlation mapping results are compared between the wild type and the green variants, the most striking difference in the variants is the loss of significance after p-value adjustment for Spearman's but not for Pearson's correlation. Here, windows with significant correlations were obtained (cf. Fig. 1

vs. 3 and
Fig. S1 vs. S10, Dataset S1). This is probably because the rank-based Spearman correlation is less influenced by the VC1 and V3g data points. These two single genotypes, however, form the weak and, therefore, most predictive class, whereas the other variants do not differ noticeably from their wild type progenitor (cf. Fig.   2 and Fig. S16B; also discussed above). This leads to a relatively weak correlation to inheritance strengths which appears to be an under-estimation and a consequence of the multiple testing correction (> 13,000 tests). The weak correlations also contradict the genetic observations, which clearly indicate that the plastomes of the green variants must contain mutated loci for inheritance strength. A similar argument applies to correlation of the k-means classes in the variants. As discussed above, definition of these classes is less clear than in the wild type, which weakens their predictive power. We therefore think that the Pearson correlation of the I-chi crosses (which yield a better resolution than the reciprocal IV-delta crosses; Fig. 2 and above) represents the best approach to identify the relevant loci that alter inheritance strength in this material. Notably, this approach yields the most significant correlations, but all approaches (including Spearman) identify the same regions in the plastome with the highest correlation values (Fig. S10, Dataset S1).
In the variants, Pearson's correlation of the I-chi crosses predicts a sequence window in the 5'-end of accD as significantly correlated to inheritance strengths (r = 0.78 and p < 0.005). The strongest correlation for this dataset is observed for the 5'-UTR of ycf2 (r = 0.91, p < 0.0005). In addition, a highly repetitive region in the coding region of the same gene also shows good correlation values (r = 0.71; p < 0.05; Fig.   S10, Dataset S1). Two insertions/deletions (indels) in ycf1 are also significant (r = 0.61; p < 0.05). They represent a single insertion and a deletion in the weak variant VC1, located relatively close to each other (see below). The functional relevance of the two mutations for inheritance strength can be questioned, however. Since the second weakest variant of the dataset displays a wild type ycf1 sequence (

Correlation analysis at selected loci
When correlation mapping is applied to selected loci within the above identified alignment windows, the general observation is that correlation values drop to some extent (cf. Dataset S1). This is probably best explained by looking at the highly correlating sequence intervals spanning the promoter, 5'-UTR and 5'end of accD in the wild types (Fig. 1B). When analyzed as functional units (promoter/5'-UTR region and protein N-terminus; Fig. S4), correlation of the individual segments (promoter/5'-UTR region: r = 0.80 or rho = 0.74; p < 0.005 for both; full N-terminus: r = 0.78 or rho = 0.60; p < 0.005 or p < 0.05) is much lower than for the original sequence intervals (r = 0.94 or rho = 0.96 and r = 0.96 or rho = 0.98 with p < 0.005 for all), which led to the identification of these regions. As discussed below, experimental evidence is available that promoter/5'-UTR and N-terminus interact to affect the inheritance phenotype, while the individual regions display weaker correlations.
In spite of these complications, to get an impression of how well certain coding or promoter/5'-UTR regions, as well as segments of oriB correlate with inheritance strengths, we calculated correlation values for accD, ycf1, ycf2, and oriB for polymorphisms that are present in both wild type and the variants (Figs. S4-S6, Dataset S1). We also included two prominent sites in the ycf2 gene present in the wild type, for which we found no mutation in the variants. Please note that at three sites (AccD N-terminus, the AccD site 2 and the ycf2 promoter/5'-UTR region) in addition to Person's correlation, the Spearman's correlation analysis yields significant correlations in the variants. This is in contrast to the whole plastome approach described above, where p-value corrections due to multiple testing were applied.
The best correlating region in both sequence sets (wild type and variants) is site 2 of the AccD Nterminus (Fig. S4B). Its prediction is extremely robust in that significant Pearson's and Spearman's correlations were obtained for all crossing series and k-means classes (Fig. S4, Dataset S1). Less clear is the contribution of ycf2. In the wild types, the ycf2 site 1 and site 2, but not site 3 can be associated with inheritance strength, but in the green variants, site 3 exerts the most influence on the competitive ability of chloroplasts ( Fig. S5B and below).
In summary, the refined analyses at selected loci clearly confirm the contribution of accD on inheritance strengths and might have even identified the most important region. It also shows that ycf2 may contribute to the phenotype. Without chloroplast transformation in the evening primrose, a technology currently not available, the influence of the individual sites remains speculative.

Phylogenetic independence of the loci predicted by correlation mapping
To address the possible impact of phylogenetic non-independence on the association between total sequence divergence and inheritance strength, we implemented a phylogenetic control in our correlation mapping analysis. In principal, we expect loci for inheritance strength to be to some extent independent of the phylogeny, since plastome phylogeny in Oenothera is (((I,II) III) IV), whereas inheritance strengths follows the distribution (((I,III) II) IV) (Fig. S1).
For the wild type dataset det, for which it is easy to reconstruct a phylogeny, we performed this test using a phylogenetic generalize least squares model (PGLS), statistically equivalent to phylogenetic independent contrasts (PIC) but with a much more flexible implementation (36). This allowed for relatedness between each of our 14 lineages to be accounted for in the association between divergence and inheritance strength, however, both PIC and PGLS analyses rely on the assumption of a continuously distributed response variable (12,37). Unfortunately, our discrete k-means clustering approach that best reflects the joint inheritance strength of our two sets of crosses, "biennis white" and "blandina white" (see above) does not fit this assumption. Instead, we conducted the analysis with continuous measures of inheritance strength, % of variegated seedlings from the biennis and blandina crosses, despite these frequencies not always assigning the same rank order to our wild-type chloroplast lineages (Table S7).
Consequently, for the blandina crosses, this analysis was not informative. Before p-value correction, only some minor sequence variation around trnM-CAU and trnV-UAC, as well as the small single sequence (SSC) and the inverted repeat A (IRA) junction were found to be phylogenetically independent (Dataset S1).
The latter is displayed at the very end of the linear plastomes map in Fig. S1, highly divergent not only in evening primroses and likely depleted of functional sequences motifs (8). For the biennis crosses, the SSC/IRA junction and five new regions were identified, four of them again comprising minor sequence variation in intergenic regions, not being able to explain the inheritance phenotypes (Dataset S1 and S2).
The fourth region, however, is ycf2 and here two of the previously predicted sites (see above) were shown to be significant after phylogenetic correction (site 2 and site 3; p < 0.05 and p < 0.05, respectively; Fig. S1, Dataset S1). However, they did not survive statistical significance after false discovery rate correction, most likely because of a lack of power, i.e. with a small tree there are insufficient numbers of independent events along a relatively small phylogeny to detect the significant association [only one event, comparing phylogeny (((I,II) III) IV) to inheritance (((I,III) II) IV)]. In other words, the phylogenetically-controlled association analysis alone does not withstand statistical scrutiny.
Interestingly, accD is missing from the phylogenetic independent regions. This might support the view of at least two independent loci determining inheritance strengths, one of which (ycf2) is not linked to the phylogeny. In summary, we think that implementation of PGLS or related methods has the potential to significantly improve the correlation mapping method, although this needs to be explored with a much broader base.
4. Repeat structure, sequence evolution and divergence of accD, ycf1, ycf2, and oriB The four genes or loci partially span rapidly evolving regions of the Oenothera plastome that are characterized by large repetitive regions. Those can be of up to 1 kb in size as is the case for site 3 in the ycf2 gene. They are comprised mostly of tandem or direct repeats (and less pronounced palindromes or inverted repeats) as described earlier (8). Due to their repetitive nature, these regions are very prone to replication slippage (2,38) and sequence divergence at these regions substantially contributes to the overall sequence variation of the Oenothera chloroplast DNA . Fig. 3 therein) (8). The presence of repeats also makes them a preferred target of the plastome mutator allele (39,40). Sequence evolution is extremely fast at these repeats. In case of the repetitive regions of accD and ycf1 phenotypically neutral spontaneous mutations were isolated repeatedly at very similar sites (2).
Moreover, the oriB (which is essentially located in the rrn16 -trnI-GAU spacer) is used as a hypervariable marker allele that allows discrimination among a huge variety of Oenothera strains (3). The repeat structure of the oriB region was analysed earlier and is comprised of 7 direct repeat classes that can be divided into various subtypes (39, 41) (and below). In the accD gene mostly tandem or direct repeats span the promoter/5'-UTR and N-terminal region (Fig. 1); all three of these segments are considered to contribute to the regulation of the gene (42)(43)(44)(45)(46). In fact, sequence variation induced by theses repeats is so high that upstream of the accD start codon, a window of about 1.4 kb cannot be aligned between the weak plastome IV and the stronger plastomes I-III (Dataset S2). This is to some extent also observed for site 2 in the Nterminus of the wild type AccD. In plastome IV major portions of this site is missing and about half of the remaining sequence is polymorphic (Fig. S2A). In the ycf2 coding sequence, the most prominent repeats are present in sites 2 and 3. At the first site the number of PEKRKEKK tandem repeats can be correlated with inheritance strengths in the wild types, but not in the variants. The situation is reversed for site 3, in which tandem repeats exist as two subtypes 5'-GAGGAAGtAGAAGGGACAGAA-3' and 5'-GAGGAAGgAGAAGGGACAGAA-3' associated with a GAT linker, and correlate with inheritance strengths in the variants, but not in the wild types (Fig. S2).
5. Variation at the chloroplast origins of DNA replication is not responsible for differences in chloroplast competition As elaborated above, our correlation mapping already points to a connection of lipid biosynthesis and chloroplast competition. However, one might still argue that a priori differences in the origins of replication are the simplest mechanistic explanation for organelle competition. At least some evidence supporting this claim is available for yeast and Drosophila (47)(48)(49). The location and repetitive nature of oriB in evening primroses (see above) are reminiscent of the non-coding displacement loop (D-loop) of metazoan mitochondrial DNA (mtDNA). In many animal taxa the D-loop is the most variable sequence of mtDNA and is in the proximity of tRNA or rRNA genes (47, 50, 51).

Sequence variation in oriB cannot explain differences in inheritance strength
Previous work in the evening primrose did not support an involvement of the origins of replication in chloroplast competition. First, the number of D-loop initiation sites (i.e. oris) does not differ between weak and strong plastomes and their locations in the chloroplast genome is identical (52). Second, in a previous association mapping study that investigated the hypervariable repeat region of oriB, a short repeat series was identified as the sole determinant that could explain the difference between the strong and intermediate plastomes I, III and II on one side, and the weak plastome IV on the other side (41). The sequence (5'-ACGACACGACGATTAGATTAGCTCATTGGTAGGACGACGATTAGCTCATTGGTAGGACGACG -3') is 62 bp in size and is capable of forming of weak hairpins. Our study, analyzing a greater number of plastome sequences, confirms the absence of this sequence in the weak plastome IV. However, in none of the green plastome I variants with altered inheritance strength is the sequence partially or fully deleted.
Moreover, the very weak variants of plastome III (Main Text and see below) do not carry a single mutation in one of the two origins of replication (Dataset S2). We therefore do not think that a genetic determinant within the oriB of Oenothera is able to explain the huge differences observed in competitive behavior.
To substantiate this view, also on the level of DNA, we investigated the dynamics by which ptDNA increases during plant development in more detail. In addition, we analyzed chloroplast nucleoid structure and number per cell.

Changes in plastid DNA amounts during development do not correlate with inheritance strength
To investigate if differences in ptDNA increase during development and/or if changed ratios of plastid/nuclear DNA are able to explain chloroplast competition, we performed quantitative real-time PCR.
In general, plastid DNA amounts are not static during ontogenies (18,53). They increase as leaves grow, starting from 0.4% in meristematic tissue to more than 20% in mature leaves (17). If differences were observed in DNA abundance during development in different Oenothera lines harboring chloroplasts with different inheritance strengths, it might hint towards an aspect of DNA replication such as replication speed as an underlying mechanism for plastid competition. To monitor this process we analysed total DNA of the johansen Standard strain equipped with the strong and the weak wild type chloroplast I-johSt and IV-atroSt, respectively. In addition, we included selected lines of our plastome I variants: V1c, V2a, V2g, and V3e (all Depending on the plastome target region, at 5 DAS a small increase of ptDNA amounts was observed in the lines V1c, V3e, V3c, VC1 and V3g. These differences, however, are not significant. At 21 DAS the weaker variants V3c, V3g and VC1 showed an increase in relative ptDNA amounts compared to wild type I-johSt, but only for the target ndhI which was again not significant. In general, from 5 to 21 DAS only a minor or no increase of plastid DNA amount was observed for each particular line and each plastid target, while in the young rosette at 32 DAS the ptDNA amount doubled (Fig. S11). These results echo previous work in Arabidopsis and sugar beet (17,53). Since the same results were obtained for plant lines carrying strong and weak plastids, no developmental difference in ptDNA copy numbers correlates with differential transmission efficiencies.
In summary, all minor increases in ptDNA amount are not significant nor do they correlate with transmission efficiencies nor with the DNA variations described previously (Fig. S6B). Moreover, no differences can be detected in IV-atroSt compared to wild type I-johSt, although plastome IV is the weakest of all genotypes tested. Therefore, the ptDNA amounts in vegetative tissues do not indicate different replication speeds, suggesting that replication per se is not the underlying mechanism for different transmission efficiencies.

Nucleoid number and structure is identical in lines with different inheritance strength
Under the premise that ptDNA amounts are constant, there is still the possibility that strong and faster replicating plastomes have altered numbers of nucleoids, which could impact their ability to divide. To exclude this possibility we quantified nucleoids in the central laminal region of the first true leaf 25 DAS.
After staining with DAPI, nucleoids were clearly visible as small dots with their fluorescence sharply delimiting them from the dark cellular background, even when forming tight associations like clumps or threads (Figs. S12 and S13). One strong (I-johSt) and three weak lines (V3g, VC1, and IV-atroSt) were investigated. The mean number of nucleoids per chloroplast ranges between 17.7 and 18.1 with no significance differences between the lines. One-way ANOVA gave p = 0.53; multiple t-tests comparing I-johSt with each of the weaker plastomes did not point to significant differences as well ( Fig. S14 and Table   S14). Moreover, we did not observe any difference in nucleoid morphology between the lines.

Expression and transcript maturation of accD and ycf2
Since the polymorphisms in oriB cannot explain differences in competitive ability, we investigated the accumulation of accD and ycf2 transcripts. A probe specific for the conserved C-terminal part of accD detected the mature transcript at about 3 kb. No differences in transcript accumulation were observed between I-johSt and the plastome I variants. However, for IV-atroSt two additional bands running below the mature transcript were present. Moreover, the mature transcript clearly over-accumulated in this weak, but phylogenetically more distant plastome. This transcript over-accumulation appears to be a result of the high sequence variation observed in the accD promotor/5'-UTR that strongly correlates with inheritance strength (see Fig. 1, Fig. S4A and above). A similar analysis was conducted for ycf2, where again a probe specific for the C-terminal part of the gene detected the mature transcript at the expected size of about 9 kb. The very small differences in size between the lines perfectly mirrors the occurrence of in-frame deletions in the lines IV-atroSt, V3c, V3g, and VC1 (Dataset S2). In IV-atroSt as well as in the plastome I variants, no difference in accumulation of the mature transcript compared to I-johSt was found. However, transcript stability/processing seems to vary between the strong plastome I-johSt and the weak IV-atroSt. Interestingly, whereas the strong variants V1c, V3e and, to same, extent V2g showed exactly the same transcript pattern as the wild type, the weak variants showed a pattern more similar to IV-atroSt. This indicates a correlation between transmission efficiency of mutations in site 3 of ycf2 (cf. Fig. S3), which might result from altered mRNA degradation and/or processing.

ACCase activity in lines harboring chloroplasts of different inheritance strength
As the above described analysis indicates an involvement of accD and/or ycf2 in the inheritance phenotype, we decided to determine ACCase activity in our lines. From these measurements, it appeared that the strong variants (V1c, V3e, V2a, and V2g) display a similar or even lower ACCase activity than their wild type I-johSt. The same holds true for the strong to intermediate or intermediate genotypes (V3c and V3d). In the weak materials, a 2-3 fold increase of ACCase activity is observed for VC1 and IV-atroSt, although V3g shows wild type enzyme activity (Fig. 4A). Although there is no simple linear correlation between inheritance strengths and ACCase activity, the strong increase in VC1 and IV-atroSt is hard to ignore. In fact, both inheritance strength and ACCase activity seem to depend on the particular mutation pattern: (i) Mutations in ycf2 seem to influence ACCase activity, as judged from the variant V3e that is wild type for the accD segments but is mutated in ycf2 (Fig. 4A, yellow box). (ii) Larger mutations in the AccD Nterminus have higher ACCase activity, whereas the presence of a more diminutive AccD N-terminus correlates with lower activity (Fig. 4A, cf. blue boxes vs. the remaining pattern). (iii) There must be an influence of ycf2 on inheritance strength (cf. Fig. 4A, green boxes associated with the weaker materials).
Hence, if ACCase and/or Ycf2 result in altered levels of lipids, one would expect that lipid composition is predictive of inheritance strengths.

Predictability of inheritance strength based on lipid-levels
To test for predictability of inheritance strength from lipid level data, we analyzed 16 chloroplast genotypes of different inheritance strength in a LASSO regression model (Table S3; Materials and Methods). Since chloroplast inheritance strength is independent of photosynthetic competence (see below), we included pale lines. The aim was to enrich the lipid signal responsible for inheritance strength, i.e. to deplete for the structural lipids of the thylakoid membrane (54); also see Main Text. Namely, we used our bleached psaA mutants I-chi and IV-delta impaired in photosystem I assembly, as well as the pale green virescent genotypes III-lamS, III-V1 and III-V2 (Tables S3 and S9; Fig. S15). Such materials were previously shown to have perturbed thylakoid membrane formation (55)(56)(57)(58). Moreover, as elaborated in the following chapters, we could confirm the independence of a pale phenotype from inheritance strength with these plastomes.

Chloroplast inheritance strength is independent of bleaching
Intuitively one might expect that bleached chloroplast mutants would be less successful in crosses than their corresponding green wild types. However, previous analyses in evening primroses showed that differences in chloroplast inheritance strength are largely independent of the chloroplast mutant used for the analyses (59,60). At least for Oenothera, it is therefore generally accepted that mutations in a chloroplast genome that result in bleaching essentially do not affect chloroplast assertiveness rates (24) (also see Fig. 2A,C vs 2B,D and above). Due to technical limitations, however, this hypothesis was never tested directly. Since closure of this gap is of general relevance for this work, and to provide further evidence that chloroplast inheritance strength is largely independent of the photosynthetic status of the chloroplast, we directly compared the wild type chloroplast I-hookdV and its bleached derivative I-chi, as well as IV-atroSt and the corresponding mutant IV-delta. For this, we investigated appropriate F1 populations crossed to the chloroplast genomes I-johSt, VC1, and V3g with the MassARRAY® system ( Fig. S18; see Materials and Methods for details on the material). As expected, transmission efficiencies had the same range for nearly all six pairs of crosses under investigation. Only in one cross with VC1 as a mother, the bleached mutant Ichi actually behaved stronger than its corresponding green wild type.
Taken together, we could confirm that chloroplast assertiveness rates are independent of photosynthetic capability. Moreover, these results make it very unlikely that the differences in inheritance strengths observed for the mutated plastome I variants (all sharing a green phenotype), are due to a secondary effect.

The very weak variants III-V1 and III-V2
While the plastome I variants and their wild type I-johSt are native in and compatible with the nuclear background of the johansen Standard race, III-lamS and its plastome mutator variants III-V1 and III-V2 are foreign and incompatible in this background, meaning that tissues carrying them do not develop a normal green color (Materials and Methods, Fig. S15, Table S11). The wild type III-lamS plastome appears to be strong, as judged from crosses to I-johSt as pollen donor, its derivative variants III-V1 and III-V2 are weak (cf. Fig. 2A vs. Fig. S19; cf. Table S10, S11 and S13) (60). Although the fraction of plants showing biparental inheritance in the crosses of III-V1 and III-V2 to I-johSt as pollen donor are somewhat low (37.3% and 38.0%, respectively) for a combination of a weak and a strong plastome (Fig. 2, Table S10) (24), the striking difference of these crosses to all other crosses described is that some seedlings contain only paternal chloroplasts ( Fig. S19; Table S11). As mentioned previously, biparental inheritance in the evening primrose shows maternal dominance, in which progeny are either homoplasmic for the maternal chloroplast or heteroplasmic for the maternal and the paternal chloroplasts, but they are never homoplasmic for the paternal one. The appearance of homoplasmic offspring having the paternal chloroplast in the III-V1/III-V2 crosses to I-johSt is the only reported case in the evening primrose where an exception to maternal dominance occurs. This justifies the definition of a new inheritance class for these plastomes.

Classes of inheritance strength employed in the LASSO regression model
To predict chloroplast inheritance strength from lipid-level data, the genotypes of the plants needed to be ranked according to their inheritance strengths (Materials and Methods; Table S3). For the green variants (V1c, V2a, V2g, V3e, V3c, V3d, VC1, and V3g) and the wild types I-johSt and IV-atroSt, the existing kmeans classes 1 -4 already employed in our association mapping approach were used (see above). The remaining plastomes (I-chi, IV-delta, I-hookdV, III-lamS, III-V1 and III-V2) were rendered consistent with this framework based on the classification of Schötz and our own data. This adds the plastome I-chi, its wild type I-hookdV and III-lamS to the strong class 1. The mutant IV-delta was placed into the weak class 4. As  (Table S3)

Predictability of inheritance strength based on lipid-level data as explanatory variables
The rationale of the predictive approach is as follows: To test for predictability of inheritance strength based on lipid-level data, a linear model (LASSO) was trained and its performance tested in a cross-validation setting on two randomly selected genotypes with differing inheritance strength (see Materials and Methods).
If the proposed regression model has predictive power, the actual inheritance strength-values associated with the two test genotypes should be positively correlated with their predicted ones. Note that for each genotype repeated measurements were available. Thus, regression was performed over more than two points and correlation coefficients could assume absolute values differing from 1. Testing was done in a crossvalidation setting, i.e. the two test genotypes were not included in the model training. This procedure was repeated 100 times, with each run corresponding to two new randomly selected genotypes of differing inheritance strength and all others used for model training.
If, indeed, inheritance strengths can be predicted based on lipid levels, on average, a positive correlation (Pearson correlation coefficient, r) between actual and predicted inheritance strength-values of the two test set genotypes should be obtained. To test for this outcome, 100 Pearson correlation coefficients are classified as positive (success) or negative (failure). Then, they were compared to the null hypothesis of no predictive value, corresponding to a 50% chance of obtaining a positive correlation and significant deviations from this expected probability tested by performing a binomial test.

The lipid classes DGDG, PG, PC, and PE are enriched for predictive lipids
From the 100 cross-validation runs, using the combined dataset from three independent experimental series (Table S3) Individual lipids were ranked with regard to their predictive value based on the coefficients by which they entered the regression model ( Fig. 4C; Table S4). Averaged over all 100 cross-validation runs, 20 lipids/molecules were identified as predictive as judged by their average absolute weight. They were considered predictive if their absolute average weight was greater than one standard deviation (SD = 0.7) of the average weights of all 102 lipids/molecules. The individual predictive lipids belong to the membrane lipid classes MGDG, DGDG, PG, PC, and PE, as well as to the storage lipid class TAG. Among those, DGDG, PG, PC, and PE were found enriched (odds ratio > 1), albeit statistical significance could not be established (Table S3).
The classes MGDG and DGDG mostly represent plastid lipids located in both the thylakoid membrane and the envelope. PGs and PCs are found in plastid and extraplastidial membranes, although for the chloroplast, PCs are specific to the envelope. PEs are present in the plasma and mitochondrial membranes and, as the storage lipids TAG, essentially absent from chloroplasts (61).

A model for the predictability of inheritance strength based on lipid-levels
Taking into account the data above and of Fig. 4, we propose the following model to explain how certain changes in lipid abundance influence inheritance strengths: Increased activity of acetyl-CoA carboxylase in the chloroplast (Fig. 4A) S1. Correlation mapping and phylogenetic independence of predicted sites in the wild type chloroplast genomes using the "biennis/blandina white" crossing data. (A) Pearson's correlation, Spearman's correlation and PGLS. Relevant genes or loci with significant correlation are noted on the linear plastome maps above. Non-significant correlations before (PGLS) or after (Pearson's/Spearman's correlation) pvalue adjustment (p > 0.05) are displayed in grey. Alignment windows whose corrected p-values of the PGLS analyses still remained significant after correction are marked in red in the original Pearson/Spearman correlation mapping plot. For details see SI Text. (B) ML tree of the 14 wild type chloroplast genomes used for the analysis above and their inheritance strength relative to "biennis white" (cf. Table S5). Tree is drawn to scale, with branch lengths measured in the number of substitutions per site. Numbers at branch points represent bootstrap values.        Comparison between the lines. Note lack of statistically significant differences (Tables S15 and S16; SI Text for details). Scale bar = 10 µm               Fig S15 and S19, Tables S7, S8 and S11 and SI Text.
3) For details see Table S1and Dataset S2. 4) For details see Dataset S2. x = included in the experiment -= not included in the experiment 1) For details on the chloroplast genomes, their inheritance class, carried mutations and phenotype of the nuclear background of johansen Standard see Fig. 2, Figs. S15, S18 and S19, Tables S1, S2, S6-S11, and SI Text.    Renner (80) this line was originally "received from Amsterdam" by N. v. Gescher in 1907. The material is quite likely identical to that collected by D. T. MacDouglas in 1902/1903 as described in (66). Also see (84). Percentage of variegated seedlings, heteroplasmic due to the paternal transmission of the bleached chloroplast mutants "biennis white" or "blandina white" and the maternal transmission of the green wild chloroplast of the seed parent. Data accoding to Schötz (34). For details see therein, reviews in (24,68) and SI Text. 4) Class of inheritance strength as determined by F. Schötz. For reviews see (24,68,87). 5) For details on the definition of these classes see SI Text. 6) The chloroplast genomes of the two suaveolens stains are identical.  (24,68,87). 5) For details on the definition of these classes, see SI Text. 6) For details on the donor strains, see Table S6.   Table S8 for details on the wild type plastomes.
2) See Table S9 for details on the chloroplast mutants.
3) All crosses were performed in the nuclear genetic background of O. elata ssp. hookeri strain johansen Standard. For details on the crosses see Materials and Methods, on the line see Table S6. 4) Percentage of variegated seedlings, heteroplasmic due to the paternal transmission of the bleached chloroplast mutant I-chi and the maternal transmission of the green wild type or variant chloroplast of the seed parent. For details see SI Text and Fig. 2

5)
Percentage of variegated seedlings, heteroplasmic due to the paternal transmission of the green wild type or variant chloroplast and the maternal transmission of the bleached chloroplast mutant IV-delta of the seed parent. For details see SI Text and Fig. 2. 6) Classes of inheritance strength as determined by F. Schötz. For reviews see (24,68,87). 7) For details on the definition of the classes in the variants see SI Text. Table S11. Wild type chloroplast genome III-lamS and its very weak variants 1) created by the plastome mutator in crosses to I-johSt 1) as pollen donor 2) Variant/ plastome
2) All crosses were performed in the constant nuclear genetic background of O. elata ssp. hookeri strain johansen Standard. For details on the crosses see Materials and Methods, on the line see Table S6. 3) Percentage of variegated seedlings, heteroplasmic due to the paternal transmission of the green wild type chloroplast I-johSt and the maternal transmission of the virescent chloroplast of the seed parent. For details see SI Text and Fig. S19. 4) Percentage of homoplasmic green seedlings resulting from paternal inheritance of the green wild type chloroplast I-johSt that fully out-competed the virescent chloroplast of the seed parent. For details see SI Text and Fig. S19. 5) Classes of inheritance strength as determined by F. Schötz. For reviews see (24,68,87). 6) For details on the definition of the classes in the variants see SI Text.     Table S6.
2) For details on the wild type or variant plastomes see Table S10.
3) Means ± standard deviations are given. 4) p-values obtained with two-tailed homoscedastic t-test followed by multiple testing correction according to Benjamini-Hochberg.
2) For details on the wild type or variant plastomes see Table S10.
3) Means ± standard deviations are given. 4) p-values obtained with two-tailed homoscedastic t-test followed by multiple testing correction according to Benjamini-Hochberg.  Table S6.
2) For details on the wild type or variant plastomes see Table S10.
3) Means ± standard deviations are given. 4) p-values obtained with two-tailed homoscedastic t-test followed by multiple testing correction according to Benjamini-Hochberg. 5) Chloroplast volume index calculated according to (20).