Only the first two codon positions in the nucleotide alignment were included for phylogenetic analyses 29, positions. Gblocks with the least stringent settings was also applied to the protein alignment, reducing the alignment from 48, to 13, amino acid positions. Taxon and gene sampling for the nuclear rDNA alignment was based on Marin 18 and extended with species of Streptophyta, Rhodophyta and Glaucophyta for which near complete small 18S and large 28S subunit rRNA genes were available.
Both alignments and positions, respectively were concatenated, and poorly aligned positions removed using the Gblocks with the least stringent settings see above. Gblocks reduced the alignment from to positions. Plastid phylogenies were inferred from the amino acid and nucleotide datasets using Bayesian and ML analyses.
Bayesian analyses of both the amino acid and nucleotide datasets were conducted using MrBayes v. Two independent runs were performed using 1 million amino acid dataset or 3 million nucleotide dataset generations, each with one cold and three heated chains, and sampling every generations. A maxdiff of 1 was obtained in both analyses, indicating that at least one of the runs was stuck in a local maximum. We also addressed possible phylogenetic artefacts due to potential biases in amino acid composition resulting from the low GC content in the cpDNAs of Verdigellas and clade VI prasinophytes 27 , Five independent chains were run for 3, cycles and a consensus topology was calculated after a burn-in of cycles.
Because the root age of the Viridiplantae is highly uncertain, these results should be regarded as tentative. MrBayes analyses included two independent runs of 5 million generations each with four chains.
Sequence alignments and trees are available from TreeBase study ID How to cite this article : Leliaert, F. Chloroplast phylogenomic analyses reveal the deepest-branching lineage of the Chlorophyta, Palmophyllophyceae class. Leliaert, F. Phylogeny and molecular evolution of the green algae. Plant Sci. McCourt, R. Charophyte algae and land plant origins. Trends Ecol. Becker, B. Streptophyte algae and the origin of embryophytes. Analyses of charophyte chloroplast genomes help characterize the ancestral chloroplast genome of land plants.
Genome Biol. Wickett, N. Phylotranscriptomic analysis of the origin and early diversification of land plants. Natl Acad. USA , E—E Graham, L. The origin of plants: Body plan changes contributing to a major evolutionary radiation. USA 97 , — Melkonian, M. Phylum Chlorophyta. Class Prasinophyceae in Handbook of Protoctista. The structure, cultivation, habitats and life histories of the eukaryotic microorganisms and their descendants exclusive of animals, plants and fungi eds Margulis , L.
Sym, S. The class Prasinophyceae in Prog. Into the deep: New discoveries at the base of the green plant phylogeny. BioEssays 33 , — Fawley, M. Guillou, L. Diversity of picoplanktonic prasinophytes assessed by direct nuclear SSU rDNA sequencing of environmental samples and novel isolates retrieved from oceanic and coastal marine ecosystems. Protist , — Latasa, M.
Pigment suites and taxonomic groups in Prasinophyceae. Nakayama, T. The basal position of scaly green flagellates among the green algae Chlorophyta is revealed by analyses of nuclear-encoded SSU rRNA sequences. Marin, B. Molecular phylogeny and classification of the Mamiellophyceae class. Chlorophyta based on sequence comparisons of the nuclear- and plastid-encoded rRNA operons. Turmel, M.
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The chloroplast genomes of the green algae Pyramimonas , Monomastix , and Pycnococcus shed new light on the evolutionary history of prasinophytes and the origin of the secondary chloroplasts of euglenids. Lemieux, C. Six newly sequenced chloroplast genomes from prasinophyte green algae provide insights into the relationships among prasinophyte lineages and the diversity of streamlined genome architecture in picoplanktonic species. BMC Genomics 15 , Chloroplast phylogenomic analysis resolves deep-level relationships within the green algal class Trebouxiophyceae.
BMC Evol. Nested in the Chlorellales or independent class? Phylogeny and classification of the Pedinophyceae Viridiplantae revealed by molecular phylogenetic analyses of complete nuclear and plastid-encoded rRNA operons. The origin and early evolution of green plants in Evolution of primary producers in the sea eds Falkowski, P. Zechman, F.
An unrecognized ancient lineage of green plants persists in deep marine waters. Pueschel, C. Ultrastructure of Verdigellas peltata Palmellaceae, Chlorophyta , a deep-water, palmelloid alga with ferritin and trilaminar sheaths. Phycologia 36 , — Womersley, H. Part I. Government Printer, South Australia, Nelson, W. Palmophyllum umbracola sp. Chlorophyta from offshore islands of northern New Zealand. Phycologia 25 , — Ballantine, D. Verdigellas , a new deep-water genus Tetrasporales, Chlorophyta from the tropical western Atlantic.
A clade uniting the green algae Mesostigma viride and Chlorokybus atmophyticus represents the deepest branch of the Streptophyta in chloroplast genome-based phylogenies. BMC Biol. New phylogenetic hypotheses for the core Chlorophyta based on chloroplast sequence data. Sun, L. Chloroplast phylogenomic inference of green algae relationships. Ancestral chloroplast genome in Mesostigma viride reveals an early branch of green plant evolution. Nature , — Lang, B. Plastid genomes of algae in Genomics of chloroplasts and mitochondria Vol. The complete chloroplast DNA sequence of the green alga Nephroselmis olivacea : Insights into the architecture of ancestral chloroplast genomes.
USA 96 , — Worden, A. Green evolution and dynamic adaptations revealed by genomes of the marine picoeukaryotes Micromonas. Science , — Robbens, S. The complete chloroplast and mitochondrial DNA sequence of Ostreococcus tauri : organelle genomes of the smallest eukaryote are examples of compaction. The chloroplast genomes of Bryopsis plumosa and Tydemania expeditionis Bryopsidales, Chlorophyta : compact genomes and genes of bacterial origin.
BMC Genomics 16 , Melton, J. III , Leliaert, F. The complete chloroplast and mitochondrial genomes of the green macroalga Ulva sp. UNA Ulvophyceae, Chlorophyta. PLos One 10 , e Huang, J. Horizontal gene transfer in the evolution of photosynthetic eukaryotes. Dynamic evolution of the chloroplast genome in the green algal classes Pedinophyceae and Trebouxiophyceae.
Hasegawa, T. Prasinoderma coloniale gen. Phycologia 35 , — Miyashita, H. Prasinococcus capsulatus gen. Jouenne, F.
Prasinoderma singularis sp. Protist , 70—84 Umen, J. Green algae and the origins of multicellularity in the plant kingdom. Cold Spring Harb. Division of Palmoclathrus stipitatus Chlorophyta vegetative cells. Phycologia 27 , — Sieburth, J. Guillard, R. Pycnococcus provasolii gen. Lewis, L. Green algae and the origin of land plants. Chadefaud, M. Tome 1. McNeill, J. International Code of Nomenclature for algae, fungi, and plants Melbourne Code Zerbino, D. Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome Res.
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Lohse, M. Mesquite: a modular system for evolutionary analysis Version 3. Abstract Lang BF, Burger G and Bandlow W "Activity of reduced ubiquinone: cytochrome c oxidoreductase with various ubiquinol-isoprenologues as substrate and corresponding inhibitory effect of antimycin in yeast. Cruz-Reyes, MW. Marechal-Drouard, ed. Academic Press, Elsevier, Amsterdam. Bock, V. Knoop, eds , Springer-Verlag Heidelberg, Germany. Bullerwell, ed , Springer-Verlag Heidelberg, Germany, p. Parkinson, ed.
Lennarz, MD. Sankoff and J. Nadeau, eds. Volume II. Quagliariello et al. Bandlow et al. Rome, Italy, July Aug 2, Association des Producteurs de Canneberges du Quebec apcq. Quebec City, March , Poster : "Successful transformation of Diplonema papillatum - the type species of the most diverse marine protists diplonemids. Interdisciplinary Science Workshop.
Invited talk: "Underlying philosophy and challenges in designing trans-disciplinary training program. Example: bioinformatics. Gene Ontology Workshop. Montreal, QC, Canada, October 16, Talk: "Plant-microbe interactions at the molecular level. Benasque, Spain, July , Talk: "Spliceosomal introns in 'primitive' unicellular flagellates. Droushia, Cyprus, May June 01, Talk: "Eccentricities of mitochondrial genomes across diplonemids. Talk: "Comparative analysis of jakobid, malawimonad and ancyromonad nuclear genomes. Invited talk: "Le microbiome de la canneberge.
Montreal QC, Canada, Dec 15 Invited talk: "Decryption of hidden genes at the transcript level. Invited talk:"Tirer profit du microbiome du sol. Helsinki, Finland, Aug 14, Montreal, Canada, Jul , Poster: "The mitoribosome of a primitive eukaryote. Contributed talk: "Gene encryption in the mitochondrial genome of diplonemids. Titisee, Germany, Mar Apr, Plants were pooled for each biological replicate. The same batch of samples was used for transcriptomic, proteomic, and metabolomic studies.
Standard curves of 0—40 pmol authentic standard were freshly prepared on the day of measurement. The chromatograms and mass spectra were evaluated using TagFinder software Luedemann et al.
Metabolite identification was manually supervised using the mass spectral and retention index collection of the Golm Metabolome Database Kopka et al. Peak heights of the mass fragments were normalized on the basis of the fresh weight of the sample and the added amount of an internal standard ribitol.
Plants were collected and pooled together for RNA extraction. Each pooled RNA was considered as one biological replicate. To distinguish the homologous transcripts derived from nucleus and organelles, the clean reads were mapped to the Arabidopsis thaliana genome TAIR10 with nucleus-encoded CDS gene set, the mitochondria-encoded CDS gene set, and the chloroplast-encoded CDS gene set. The transcript abundance was estimated by RPKM Reads per kilobase transcript per million reads calculation for each gene in each compartment Mortazavi et al.
In order to filter the differentially expressed transcripts between sapmles, all reads were sequenced and p -value was calculated according to a strict algorithm Audic and Claverie, The reads from gene A is denoted as x , and when the expression of each given transcripts occupies only a small part of the library, x yields to the Poisson distribution:. Therefore, the probability of gene A expressed equally between the two compared samples can be calculated by:.
Besides the p -value calculation, correction for false positive type I errors and false negative type II errors were performed using FDR method Benjamini et al. The PageMan software package Usadel et al. After alkylation, the mixture was diluted with 4 mM CaCl 2 to reduce the concentration of urea to less than 2 M. Two biological replicates of each sample were used for iTRAQ labeling. Then the second biological replicate samples were labeled with , , , and , respectively. All labeled samples eight tubes were combined together and the labeled peptides were fractionated by SCX Zhao et al.
Two technical replicates were run. The raw data obtained from the machine were converted to. To qualify and quantify the protein abundance changes of the nucleus- and organelle-encoded genes under different conditions, we searched the protein IDs and peptides mapped by ProteinPilot software against the Arabidopsis nucleus-encoded protein database, mitochondria-encoded protein database, and chloroplast-encoded protein database from the TAIR website 2. Downstream analysis for the calculation of the protein expressed level for each gene from each compartment was conducted by a series of in-house perl scripts.
In all searches, trypsin was selected as the enzyme used for protein digestion and IAA was selected as the cysteine alkylation agent. Bias correction and background correction were also applied. For protein identifications, a minimal unused ProtScore of 1. Primer premier 5. Actin 2 At3g was used as the internal control. For every transcript, each cDNA sample was analyzed in triplicate, and relative transcript abundance was calculated by normalizing to the maximum level. FW, Fresh weight. In total, 29, expressed transcripts were detected in the RNA-seq data, including 29, transcripts encoded by the nuclear genome, transcripts encoded by the mitochondrial genome, and 96 transcripts encoded by the chloroplast genome Supplementary Tables S3—S5.
The 29, nuclear transcripts were encoded by a total of 23, genes, where the difference between these two numbers is due to the fact that some genes display alternative splicing. When transcripts were compared between the OE line and WT, there were more suppressed transcripts than up-regulated transcripts in the OE line in all three time points Figure 2A. Most of the differentially expressed genes were nuclear-encoded except one chloroplast-encoded transcript and a few transcripts encoded by the mitochondrial genome Supplementary Table S6.
Differentially expressed transcripts and proteins in overexpression OE line compared with WT. B Number of differentially expressed proteins 1. PageMan analysis Usadel et al. As would be anticipated, photosynthetic gene expression was up-regulated in the OE line in comparison to WT Figure 3.
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However, a significant decline in photosynthetic gene expression across the light period was observed. By contrast, genes associated to stress and redox responses were clearly down-regulated during light period in the OE line as compared to WT Figure 3 , although the expression pattern of the genotypes was more similar eight hours after the onset of illumination. Expression analysis in OE compared with WT.
A condensed PageMap display of altered pathways is shown. Gene expression data are presented as log 2 fold changes in comparison with the same time point of WT. The data were subjected to a Wilcoxon test in PageMan, and the results are displayed in false-color code. We additionally observed differential expression of transcripts involved in RNA processing and RNA transcription, which were up-regulated during end of night and beginning of light in OE line, but the transcription factor MADS box and WRKY families were down-regulated in the same time frame Figure 3.
It is also worth nothing that a strong down-regulation of transcripts involved in DNA synthesis and protein degradation were displayed in OE line during the light period while genes involved in the biosynthesis of ribosomal proteins were up regulated in the OE line Figure 3 , suggesting that the OE line may have a lower protein turnover rate, and the resources could be shifted to protein synthesis.
Spectrals, peptides, and proteins identifications were done by ProteinPilot software. Quality control measurements demonstrated that the protein data were confident for further study Supplementary Figure S2. In the dark, more proteins had lower abundances in OE line than in WT up vs. The significant differentially expressed transcripts were selected with both 1.
At the end of the night, the abundances of 17 transcripts from the chloroplast genome were increased in the OE line but no transcripts were statistically suppressed. Eleven out of 17 upregulated transcripts encode ribosomal proteins. The transcripts of TRNS. The abundances of nine proteins were increased in the OE line and all of them encode ribosomal proteins, while the abundances of eight proteins were decreased in the OE line, including five photosystem II components, two ATP synthase subunits and one NDH complex component Supplementary Table S4.
At 1 h after onset of illumination, only a few transcripts were up-regulated. By contrast, these ribosomal RNAs were up-regulated in the OE line after eight hours of illumination. Only four transcripts were suppressed, including two genes encoding PSII core proteins psbM and psbL , rpl20 , and clpP1 encoding the caseinolytic protease P1. For protein abundance, the abundances of seven ribosomal proteins were increased in the OE line, while the protein abudances of three PS II components, two cytochrome b6f complex subunits and two NDH complex subunits were lower in the OE line Supplementary Table S4.
By comparing the transcriptome and proteomic data between the end of the night and the middle of the day, the correlation of transcript and protein abundance is not high, except for a few ribosomal proteins Supplementary Table S4. In general the OE line had a higher abundance of ribosomal proteins than the WT at both time points, and a higher abundance of 16S and 23S ribosomal RNAs than WT at the middle of the day, implying a higher translation rate in the OE line under illumination.
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Interestingly, a number of proteins involved in the linear photosynthetic electron transport chain, including components of photosystem II, NDH complex and cytochrome b6f complex, were suppressed in the OE line during the day. While in dark, when ATP is mainly produced in the mitochondria rather than in the chloroplast, the protein abundance of two chloroplastidial ATP synthase subunits were suppressed in the OE line.
Our transcriptome data showed that the transcript abundances of the above genes were not significantly different between the two lines, except for rrn16 and rrn Hence, the transcription of these chloroplast genes by PEP and NEP is under complex regulatory control, and how availability of energy affects chloroplast genome regulation requires further studies. The transcript abundances were found to be significantly different between the OE and WT lines.
Hence, the transcription of the mitochondrial genome is greatly affected by the availability of energy. Comparing to WT, the transcript abundances of 5 genes cox1, ccb, nad9, rps2 , and orf were consistently higher in the OE line at all three time points. In contrast, the transcript abundances of seven genes atp and 6 orfs were consistently lower in the OE line at all three time points. At the end of the night, most upregulated transcripts in the OE line encode hypothetical proteins.
The transcripts of four NADH dehydrogenase components, two ATPase subunits, cytochrome c oxidase subunit 1, cytochrome c biogenesis of , and rpl2 were also up-regulated in the OE line. In addition to the transcript of atp , all other down-regulated transcripts encode hypothetical proteins. In the middle of day, the transcript abundances of nad9 , cox1 , rpl2 , and ccb were increased in OE line, while the transcript abundances of atp, ccb , and rps5 were downregulated.
RpoTm is the basic RpoT for the transcription of most mitochondrial genes and RpoTmp plays a special role in the transcription of cox1, ccmC, matR, nad1, nad2 , nad6 , and rps4 Kuhn et al. Our RNA-seq showed that the transcript abundances cox1 and nad6 are higher in the OE line, whereas the transcript abundances of matR, nad1, nad2 , and rps4 were indifferent. Our data indicates that the transcription of mitochondrial genes through RpoTm and RpoTmp is under complex regulation.
Comparing to transcript abundance, not many proteins had significant changes in abundance. In the middle of day, protein abundances of the 21 proteins were not significantly different between the OE and WT lines. Although mRNA levels of the core components of PSI and PSII, encoded by both the chloroplast and nuclear genomes, were not significantly changed during the dark to light transition in OE plants compared to WT, the transcription profiles of other components of the photosynthetic apparatus were significantly altered in the OE line Figure 4 ; Supplementary Table S Heatmap of transcription and translation profiles of photosystem compared WT with OE in days-old leaves of Arabidopsis.
Each value was calculated by log 2 ratio and colors were scaled per row with up-regulated in red and down-regulated in green. Transcriptions of psbM , Lhcb2. The abundances of many proteins were decreased in the OE line. We postulated that the mitochondria of OE line produce more ATP at the end of the night, which affects the transcription and translation profiles of plant cells. At the end of the dark period, the transcription of four genes involved in the Calvin—Benson cycle were up-regulated one FBPase, one aldolase, one rubisco activase, and one transaldolase and one was down-regulated ribosephosphate isomerase in the OE line, whereas the abundances of three proteins [a fructose-bisphosphate FBP aldolase, a phosphoglycerate kinase, and a triose-phosphate isomerase] were decreased in the OE line Supplementary Table S In carbohydrate metabolism, the transcript and protein abundances of several enzymes involved in starch metabolism, including -amylase, starch synthase, starch branching enzyme, and cytosolic starch phosphorylase were altered in the OE line Supplementary Table S13 , which suggests the energy status of plant affects starch metabolism significantly.
In glycolysis, the transcription of almost all genes was unaltered between the lines, except for the downregulation of PFK3 mRNA. In the TCA cycle, while only two genes were down-regulated in the OE line at transcriptional level, the protein abundances of an oxoglutarate dehydrogenase and a component of the succinate dehydrogenase SDH complex were increased. In carbohydrate metabolism, many enzymes involved in starch, sucrose and cell wall metabolism had higher protein abundances in the OE line Supplementary Table S For glycolysis, there was almost no change at the transcriptional level, but five enzymes had lower abundances in the OE line Supplementary Table S The lack of correlation between mRNA and protein levels suggests that enzymes in central carbon metabolism are dominated by post-transcriptional regulation.
In the respiratory electron transport chain in mitochondria, differential regulation of mRNA transcription was observed between the two lines at all three time points Supplementary Table S By contrast, the transcription of nad9 , coxI were consistently upregulated in the OE line at all three time points. Metabolomics analysis showed that the OE line contained significantly higher level of sugars Figure 5.
This finding is consistent with the findings of higher CO 2 assimilation rates in transgenic Camalina sativa Zhang et al. Metabolites were measured through gas chromatography—mass spectrometry GC—MS. Consistent with this study, there are a wide range of observations that adenylates play a central role in the regulation of plant physiology Geigenberger et al.
Indeed, it is widely recognized that plants have different energy homeostasis than microbes and mammals Saglio et al. Elevating the levels of adenylates via supply of adenine to potato tubers or adenosine to castor bean endosperm resulted in increases in starch biosynthesis and respiration and a general increase in anabolism, respectively Loef et al.
Similarly elevating the levels of adenylates by the repression of the plastidial adenylate kinase resulted in elevated starch biosynthesis in potato and enhanced growth in both potato and Arabidopsis Regierer et al. By contrast, a decrease in the adenylate energy state either by mutation of complex I of the respiratory chain in Arabidopsis resulted in suppression of germination and growth, and alteration in organic and amino acids Meyer et al.
Despite considerable research effort, few comprehensive systems-based approaches have been performed to evaluate the effect of altered adenylate pools in plants. AtPAP2 is dually targeted to the outer membranes of chloroplasts and mitochondria Sun et al. AtPAP2 selectively interacts with some components of the photosystems and plays a role in their import into chloroplasts Zhang et al. OE of AtPAP2 results in a change in the photosystem composition and thylakoid architecture, which could lead to a higher photosynthetic efficiency and sucrose supply in the OE line Zhang et al.
These phenotypes showed that AtPAP2 can alter the physiology of these two organelles by modulating protein import. Hence, when we interpret the proteomics data of these two organelles, cautions should be taken as the increases in protein abundances of some nuclear-encoded proteins could be directly due to the role of AtPAP2 in protein import.
By contrast, the changes in transcription and translation of these two organellar genomes are not directly linked to protein import, and a comparison of the OE line and WT at the end of the night reflects the impact of higher ATP output from mitochondria on chloroplasts and plant physiology. Also, comparison of the OE line and WT following illumination reflects the impact of higher energy output from chloroplasts on mitochondria and plant physiology. There are two major sources of ATP in plant cells: i linear electron flow LEF and cyclic electron flow CEF in chloroplast under light; ii the catabolism of assimilated carbon via glycolysis in the cytosol and the chloroplast, and quantitatively more importantly, by the TCA cycle and the respiratory electron transport chain in the mitochondria Cheung et al.
Carbon compounds used to generate ATP at night are produced from CO 2 fixation in chloroplast during the day, so ultimately the high-energy status of the OE line must be resulted from a higher photosynthetic efficiency.
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A recent study on diatoms showed that the mitochondrial electron transport chain could consume excess reductants channeled from chloroplasts to produce ATP, which in turn could be used for carbon fixation in the chloroplasts Bailleul et al. Our proteomics data shows that some components in CEF pathways are altered at 8 h following the onset of illumination Figure 4. Another possibility is that the mitochondria in the OE line might be more active in consuming reducing power from chloroplasts and produce extra ATP under illumination Bailleul et al. Under illumination, chloroplasts export 3C compounds to cytosol, which are mainly consumed for sucrose synthesis.
If there is a high ATP generation in the chloroplasts and the mitochondria of the illuminated leaf, the increase in ATP content in the OE line would be anticipated to result in a higher rate of carbon fixation and sucrose synthesis, which is supported by the higher sucrose phosphate synthase SPS activity in the OE line Zhang et al. This in turn could lead to faster growth rate and higher biomass accumulation in the OE line. In the dark, photosynthesis ceases and there is little ATP production from the chloroplast compared to the mitochondria.
The higher ATP level in the OE line may be produced from mitochondria where extra sucrose can be used to generate more ATP via sucrolysis and mitochondrial respiration.