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      Abiotic Stress Tolerance of Charophyte Green Algae: New Challenges for Omics Techniques

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          Abstract

          Charophyte green algae are a paraphyletic group of freshwater and terrestrial green algae, comprising the classes of Chlorokybophyceae, Coleochaetophyceae, Klebsormidiophyceae, Zygnematophyceae, Mesostigmatophyceae, and Charo- phyceae. Zygnematophyceae (Conjugating green algae) are considered to be closest algal relatives to land plants (Embryophyta). Therefore, they are ideal model organisms for studying stress tolerance mechanisms connected with transition to land, one of the most important events in plant evolution and the Earth’s history. In Zygnematophyceae, but also in Coleochaetophyceae, Chlorokybophyceae, and Klebsormidiophyceae terrestrial members are found which are frequently exposed to naturally occurring abiotic stress scenarios like desiccation, freezing and high photosynthetic active (PAR) as well as ultraviolet (UV) irradiation. Here, we summarize current knowledge about various stress tolerance mechanisms including insight provided by pioneer transcriptomic and proteomic studies. While formation of dormant spores is a typical strategy of freshwater classes, true terrestrial groups are stress tolerant in vegetative state. Aggregation of cells, flexible cell walls, mucilage production and accumulation of osmotically active compounds are the most common desiccation tolerance strategies. In addition, high photophysiological plasticity and accumulation of UV-screening compounds are important protective mechanisms in conditions with high irradiation. Now a shift from classical chemical analysis to next-generation genome sequencing, gene reconstruction and annotation, genome-scale molecular analysis using omics technologies followed by computer-assisted analysis will give new insights in a systems biology approach. For example, changes in transcriptome and role of phytohormone signaling in Klebsormidium during desiccation were recently described. Application of these modern approaches will deeply enhance our understanding of stress reactions in an unbiased non-targeted view in an evolutionary context.

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          Organic osmolytes as compatible, metabolic and counteracting cytoprotectants in high osmolarity and other stresses.

          P H Yancey (2005)
          Organic osmolytes are small solutes used by cells of numerous water-stressed organisms and tissues to maintain cell volume. Similar compounds are accumulated by some organisms in anhydrobiotic, thermal and possibly pressure stresses. These solutes are amino acids and derivatives, polyols and sugars, methylamines, methylsulfonium compounds and urea. Except for urea, they are often called ;compatible solutes', a term indicating lack of perturbing effects on cellular macromolecules and implying interchangeability. However, these features may not always exist, for three reasons. First, some of these solutes may have unique protective metabolic roles, such as acting as antioxidants (e.g. polyols, taurine, hypotaurine), providing redox balance (e.g. glycerol) and detoxifying sulfide (hypotaurine in animals at hydrothermal vents and seeps). Second, some of these solutes stabilize macromolecules and counteract perturbants in non-interchangeable ways. Methylamines [e.g. trimethylamine N-oxide (TMAO)] can enhance protein folding and ligand binding and counteract perturbations by urea (e.g. in elasmobranchs and mammalian kidney), inorganic ions, and hydrostatic pressure in deep-sea animals. Trehalose and proline in overwintering insects stabilize membranes at subzero temperatures. Trehalose in insects and yeast, and anionic polyols in microorganisms around hydrothermal vents, can protect proteins from denaturation by high temperatures. Third, stabilizing solutes appear to be used in nature only to counteract perturbants of macromolecules, perhaps because stabilization is detrimental in the absence of perturbation. Some of these solutes have applications in biotechnology, agriculture and medicine, including in vitro rescue of the misfolded protein of cystic fibrosis. However, caution is warranted if high levels cause overstabilization of proteins.
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            The origin and evolution of lignin biosynthesis.

            Lignin, a phenolic polymer derived mainly from hydroxycinnamyl alcohols, is ubiquitously present in tracheophytes. The development of lignin biosynthesis has been considered to be one of the key factors that allowed land plants to flourish in terrestrial ecosystems. Lignin provides structural rigidity for tracheophytes to stand upright, and strengthens the cell wall of their water-conducting tracheary elements to withstand the negative pressure generated during transpiration. In this review, we discuss a number of aspects regarding the origin and evolution of lignin biosynthesis during land plant evolution, including the establishment of its monomer biosynthetic scaffold, potential precursors to the lignin polymer, as well as the emergence of the polymerization machinery and regulatory system. The accumulated knowledge on the topic, as summarized here, provides us with an evolutionary view on how this complex metabolic system emerged and developed.
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              Klebsormidium flaccidum genome reveals primary factors for plant terrestrial adaptation

              The colonization of land by plants was a key event in the evolution of life, making the modern terrestrial environment habitable by supplying various nutrients1 and sufficient atmospheric oxygen2. It is generally accepted that the ancestor(s) of current terrestrial plants was closely related to present-day charophytes3 4 5. However, the fragmentary genome sequence data available for charophytes has frustrated efforts to find evidence consistent with the proposed transition of a charophyte(s) to the first land plants. The colonization of land by plants must have been preceded by the transition of aquatic algae to terrestrial algae. During this process, the transition species of aquatic algae must have acquired a range of adaptive mechanisms to cope with the harsh features of terrestrial environments, such as drought, high-intensity light and UV radiation6. In addition to making these adaptations, land plants needed to simultaneously enlarge their body sizes through cellular differentiation. The primary features that enabled primitive aquatic plants to colonize land have yet to be established. Given that these features must have a genetic basis and that the intermediate genomes of the relatives between aquatic algae and terrestrial plants must lead to clues to these crucial factors, comparative genomic analyses involving charophytic algae—which comprise streptophytes with embryophytes (land plants)—seem critical for elucidation of these features. The charophytic algae Klebsormidium usually consist of multicellular and non-branching filaments without differentiated or specialized cells. Klebsormidium species therefore have primitive body plans, and most species that have adapted to land also can survive in fresh water4 7. In fact, tolerance to typical terrestrial stresses like drought8 9 10 or freezing9 11 has been reported in some Klebsormidium species. These features suggest that an ancestor of modern-day members of Klebsormidiales acquired fundamental mechanisms that enable survival in severe land environments that differ substantially from the more stable conditions characteristic of aquatic environments. Here we sequence and analyse the genome of the K. flaccidum strain NIES-2285 (Fig. 1). Comparison of this genome sequence with available genome sequences of other algae and land plants suggests that K. flaccidum acquired many genes specific to land plants. These include genes essential for plant hormone action and cyclic electron flow (CEF) activity—biological systems that were probably critical for terrestrialization. Our analysis provides evidence that K. flaccidum has the fundamental machinery required for adaptation to survival in terrestrial environments. Results Genome sequencing and phylogenetic analysis Total genome size was estimated as 117.1±21.8 Mb (Supplementary Fig. 1), and the DNA and cDNA sequences were determined using both the Roche 454 GS FLX Titanium and Illumina GAIIx platforms (Supplementary Table 1). The sequenced DNA reads were assembled into 1,814 scaffolds covering the nuclear (104 Mb), plastidic (181 kb) and mitochondrial (106 kb) genomes (Supplementary Table 1). We identified and annotated 16,215 protein-coding genes in the nuclear and organellar genomes (Supplementary Table 1). To examine the phylogenetic similarity between K. flaccidum, land plants and other algae, we compared the sequences of 31 highly conserved proteins of 14 species and charophytes (K. flaccidum, 5 land plants, 7 charophytes algae and 9 other algae; Supplementary Data 1). The phylogenetic tree constructed based on the concatenated amino acid sequence alignment of 31 nuclear genes showed that K. flaccidum diverged after Chlorokybus atmophyticus (Fig. 2). This topology was the same as previous reports3 4 5. Comparative analyses for gene families and protein domains We classified all proteins from each of the 15 species whose genome sequences were determined (Fig. 3a and Supplementary Table 2), revealing that 1,238 proteins of K. flaccidum are shared by land plants, a number greater than that of other algae, although phylogenetic analysis showed that K. flaccidum is an early diverging lineage of charophytes. Hierarchical clustering (Fig. 3b) based on the presence or absence of homologous genes in individual organisms for 5,447 K. flaccidum gene groups commonly found in other species suggested that the K. flaccidum proteins resemble those of land plants more than those of other algae we analysed. The reciprocal best-hit analysis of conserved proteins of both algae and land plants also supported that K. flaccidum has genetic characters similar to those of land plants (Supplementary Fig. 2). Next, we inferred the history of gene acquisition that enabled terrestrial adaptation by assessing the diversity seen among gene families and protein domains in 15 representative algae and land plants. For this study, paralogues were defined as genes belonging to a gene family containing at least two genes, and singletons were defined as genes lacking any paralogue in each species. The number of gene families was defined as the sum of the gene families of paralogues and singletons (Supplementary Table 3). To represent the diversity within the gene complement of each species, we plotted the number of gene families against the total number of genes (Fig. 4a). For algae, the number of gene families increased proportionally with total gene number. This was not the case, however, for land plants owing to an apparent upper limit of the number of gene families. Compared with the algae analysed, the plants studied contained more paralogous genes in each gene family and fewer singletons (Supplementary Fig. 3). For K. flaccidum, we found that many paralogues for which the number in land plants was significantly greater were in fact singletons (Supplementary Fig. 4 and Supplementary Data 2). Notably, these counterpart genes are involved in processes such as cell wall biogenesis, signal transduction, plant hormone-related categories and environmental responses (Supplementary Data 2 and 3). In addition to gene families, we also analysed the number of domains and domain combinations, based on the Pfam database12, in proteins of the 15 species studied. For domain combinations, the numbers, positions and order of domains in each protein were ignored (Supplementary Table 4). For each species, the number of domains and domain combinations were plotted separately against the total number of genes (Fig. 4b). Although the number of domains in each of K. flaccidum, Physcomitrella patens (moss) and Selaginella moellendorffii (spike moss) was the maximal value, for angiosperms (flowering plants) the number of domain combinations continued to increase with increasing gene number. Comparison of the total number of Pfam domains in 15 species revealed that 90.7% (4,441/4,894) of the domains and 84.3% (2,360/2,801) of domain combinations that are commonly found in land plants are represented in the K. flaccidum genome (Fig. 4c and Supplementary Table 5). Thus, many archetypal genes typically found in modern land plants probably had already been acquired by the ancestor of K. flaccidum. During adaptation to the various challenges associated with terrestrial life, the numbers of these genes increased in land plants because additional paralogues were acquired, thereby providing new combinations of domains as a consequence of gene duplication and shuffling in land plants13. Streptophyta-specific genes and their roles We next conducted a comprehensive search for systems typically found in land plants that are essential for terrestrial life. The gene ontology categories of the 1,238 Streptophyta-specific genes in K. flaccidum (Fig. 3a and Supplementary Table 2) were assigned based on best hits with respect to Arabidopsis genes/gene families. Several genes are highly enriched in biological process categories such as regulation of transcription, signal transduction, response to various stress conditions, cell wall biogenesis and plant hormone-related functions (Supplementary Data 4). It is reasonable to expect that biological systems involved in these categories contributed to primary terrestrial adaptation. These analyses suggested that an ancestor of K. flaccidum had already acquired genes crucial for terrestrial life. In particular, plant hormone-mediated signal transduction pathways were likely essential for the evolution of responses to environmental stimuli in land plants. Many plant hormones have also been detected in both unicellular and multicellular algae14 15, but their functions in algae remain mostly unclear. Analysis of the K. flaccidum genome revealed candidates for most of the genes required for the biosynthesis of auxin, abscisic acid (ABA), and jasmonic acid (JA) (Supplementary Data 5). Moreover, detection of plant hormones with mass spectrometry unambiguously indicated the presence in K. flaccidum of the auxin indole-3-acetic acid, ABA, the cytokinin isopentenyladenine, JA, and salicylic acid (Supplementary Table 6). In addition, we identified genes predicted to encode counterparts of the plant hormone receptors ABP1 (auxin), GTG (ABA), CRE1 (cytokinin) and ETR (ethylene) (Fig. 5 and Supplementary Data 5). We also compared organellar genes found in other algae and land plants. A notable feature of the K. flaccidum plastid genome was the presence of 18 NADH oxidoreductase subunits that constitute the NADH dehydrogenase-like complex (NDH) (Fig. 6, Supplementary Data 6 and 7), which mediates CEF in photosystemI16 17 18. Several stresses, including high-intensity light and drought, can activate CEF. It is believed that CEF increases the proton gradient across the thylakoid membrane, which induces non-photochemical quenching (NPQ) and ATP synthesis16 19. These responses dissipate excess light energy and enable various adaptive responses to stress. Land plants have two CEF pathways, namely the PGR5 and NDH pathways19 20, but no genes encoding NDH have been found in algae except for members of Charophyta and some Prasinophyceae21. Here we identified seven genes in the K. flaccidum nuclear genome that encode NDH components and PGR5 (Supplementary Data 7). Although some NDH genes were not identified, the K. flaccidum genome harbours genes that encode major NDH components (Fig. 6 and Supplementary Data 7). A CEF activity mediated by the NDH pathway has been detected as a transient increase in chlorophyll fluorescence after turning off actinic light by pulse-amplitude-modulated fluorometry22. Our analysis clearly demonstrated that K. flaccidum has the CEF activity (Fig. 7a,b). Discussion We showed K. flaccidum produced several plant hormones. Moreover, we found some counterparts for key components in the hormone signalling pathways are encoded in the genome. Of special interest is the likely importance of ABA as a key factor for terrestrialization, because ABA is a central signalling molecule needed to adapt to abiotic stresses such as drought, salinity and freezing23. Although we identified counterparts of the hormone receptors ABP1, GTG, CRE1 and ETR for auxin, ABA, cytokinin and ethylene respectively, we did not detect putative genes for other known receptors, such as TIRs (auxin), PYR/PYL/RCAR (ABA), GID (gibberellin), COI1 (JA-isoleucine) and NPR (salicylic acid) (Fig. 5 and Supplementary Table 6). Among them, the TIRs, GID and COI1 are coupled with protein turnover mediated by the ubiquitin–proteasome system and enable crosstalk among plant hormone signalling pathways24 25. It is thus interesting that most of the plant hormone signalling machineries that are dependent on SCF (Skp, Cullin and F-box-containing protein) complexes are probably missing in K. flaccidum, although K. flaccidum encodes putative variants of functional receptors and transporters found in land plants, such as ABP1, PIN 26 and AUX, which are involved in auxin sensing and transport. PINs transport auxin between plants cells and thus have crucial roles in many developmental processes. Arabidopsis produces a novel type of PINs with a short hydrophilic loop in the central region, and these PINs localize to the endoplasmic reticulum26. KfPIN was intermediate in size between short- and long-type PINs in our gene models (Supplementary Figs 5 and 6). Further analysis will reveal whether KfPIN directly facilitates auxin transport between cells. Genomic evidence suggests that K. flaccidum has certain types of primitive land-plant signalling pathways for plant hormone responses. The primitive plant hormone responses like those found in K. flaccidum may have further evolved in land plants by coupling with more refined signalling networks such as those involving ubiquitin-mediated proteolysis. These primitive hormone signallings in K. flaccidum may facilitate various responses of this alga to harsh environmental stresses on land. In addition, these hormone systems may play important roles in cell–cell communication in this organism. We tried to find some gene families specific in multicellular organisms (Clathrus crispus, Ectocarpus siliculosus, Volvox carteri, K. flaccidum and land plants). However, we did not detect any increase in the number of genes that are characteristic of multicellular organisms (Supplementary Fig. 7). In these organisms, multicellularity has evolved independently, and thus comparison between unicellular and multicellular charophytic algae will be necessary to clarify the multicellularity of land plants similarly to study of Volvox27. However, genes related to multicellularity (WUSCHEL, AGAMOUS like MADS-box gene in land plants, GNOM, and several cell wall-related genes) exist in K. flaccidum (Supplementary Data 5). These results suggest that the ancestor of K. flaccidum probably had made a start toward organizing the current complex multicellular systems while it still had a simple body plan. We showed CEF activity in Photosystem I in this alga. Two different inducers of NPQ—PsbS and the Lhc-like polypeptide LHCSR—are known in algae and land plants (Supplementary Data 7). In land plants, NPQ relies mainly on PSBS28, whereas in green algae NPQ relies mainly on LHCSR29. PSBS and LHCSR work independently through different mechanisms. In P. patens, PSBS and LHCSR act additively to induce strong NPQ for efficient photoprotection30. In this regard, K. flaccidum likely relies on LHCSR, whereas PSBS function predominates in the late-diverging charophyta (Zygnematales, Coleochetales and Charales)30. Although we detected psbS mRNA in K. flaccidum, further work is necessary to clarify the role of PSBS in this alga. Our genome analysis of K. flaccidum reveals the presence and functionality of several important stress responses found in terrestrial plants. Although the protein sets encoded by these genes are primitive, they may be sufficient to guide a primitive body plan and direct the tissue differentiation needed to define a terrestrial alga. Future research on each genomic factor in this organism and further analyses of other charophyte genomes may assist our understanding of the events that enabled plants to colonize land. Methods Genome sequencing and annotation Genomic DNA and expressed mRNAs of K. flaccidum strain NIES-2285 were extracted (Supplementary Methods) and sequenced using the Roche 454 GS FLX Titanium and Illumina GAIIx platforms (Supplementary Methods). A total of 5.4 Gb (genomic DNA) and 570 Mb (transcriptome) were assembled using Newbler (Supplementary Methods). Chloroplast and mitochondrial genomes were assembled independently of the nuclear genome (Supplementary Methods). Sequencing and assembly of the nuclear genome was validated using bowtie2, SPALN, BLAST and MEGAN (Supplementary Methods). Organellar genes were predicted and annotated using Glimmer3, GeneMarkP, GeneMark (a heuristic approach for gene prediction), FGENESB, tRNAScan-SE, RNAmmer and BLAST with additional manual curation (Supplementary Methods). Assembled transcript sequences were mapped to scaffolds using SPALN. Nuclear genes were modelled and predicted by Augustus. These genes were annotated with blast2GO, BLASTP, interpro, Gclust, targetP, ipsort, KAAS, clustalW, MUSCLE, Gblocks and FastTree with additional manual curation (Supplementary Methods). The assembled scaffolds sequences have been deposited at DDBJ. The data also can be freely accessed through the project’s website http://www.plantmorphogenesis.bio.titech.ac.jp/~algae_genome_project/klebsormidium/index.html. A basic BLAST tool to search nucleotide and protein databases is accessible at http://genome.microbedb.jp/klebsormidium. Species used for comparative genome analyses K. flaccidum genes were compared with those of nine other algae (Chondrus crispus 31, Ectocarpus siliculosus 32, Phaeodactylum tricornutum 33, Cyanidioschyzon merolae 34, Micromonas strain RCC299 (ref. 35), Ostreococcus tauri 36, Chlorella variabilis NC64A37, Volvox carteri f. nagariensis30, and Chlamydomonas reinhardtii 38), eight charophyte ESTs5 (Mesostigma viride, Chlorokybus atmophyticus, Klebsormidium flaccidum, Nitella hyalina, Chaetosphaeridium globosum, Coleochaete sp., Spirogyra pratensis, Penium margaritaceum), and five land plants (Physcomitrella patens subsp. Patens6, Selaginella moellendorffii 39, Oryza sativa subsp. Japonica40, Populus trichocarpa 41 and Arabidopsis thaliana 42). Gene data in JGI43, Phytozome44 or the RefSeq45 release version 54 data set were used for all species except for three algal species—C. merolae, E. siliculosus and C. crispus. These data were used as two data sets: Data set 1 (mainly JGI data) and Data set 2 (mainly refseq data) (Supplementary Table 7). Each data set yielded the same conclusion (Supplementary Tables 2–5,Figs 3a,b and 4a–c and Supplementary Figs 3 and 8–12). Classification of genes All-against-all BLASTP46 analysis was applied to all genes of the 15 species analysed (e-value 50% of the query and database sequences were used for this analysis. After extracting the proteins with reciprocal best hits, homologous clusters were identified by clustering analysis using OrthoMCL47 with following parameters: inflation value=1.5, percentMatchCutoff=1 and evalueExponentCutoff=–3. These homologous clusters were classified into four categories: (1) clusters found only algae, (2) clusters found only in land plants, (3) clusters found in both algae and land plants and (4) no reciprocal best hit to other species (Fig. 3a, Supplementary Table 2 and Supplementary Fig. 8). For this analysis, K. flaccidum was not considered as the reference for both algae and land plants. We also classified homologous clusters into four categories: (1) clusters found only in unicellular organisms, (2) clusters found only in multicellular organisms, (3) clusters found in both unicellular and multicellular organisms and (4) no reciprocal best hit to other species (Supplementary Fig. 7). Heat maps for gene classification First, homologous groups produced by OrthoMCL that contained K. flaccidum genes were selected. As a result, 5,447 gene groups were extracted as non-unique groups shared by K. flaccidum and other organisms and used for subsequent analysis. Against each group, the presence or absence of genes in individual organisms was checked. Then, Pearson’s correlation coefficient between each gene was calculated as a distance matrix, and a gene cluster was constructed using the complete linkage method. Finally, a binary heat map profile with a dendrogram was created (Fig. 3b and Supplementary Fig. 9). All statistical analyses were performed with the R programme version 2.15.1 ( http://www.r-project.org/). Phylogenetic tree with Charophyta species A total of 160 ortholog data sets that contained amino acid sequences of Charophyta were obtained from previous research5. Sequences originating from Mesostigma were removed from the above data sets because only a few orthologue groups were contained in its EST sequence. BLASTP (e-value 740 nm). The transient increase of chlorophyll fluorescence in the presence or absence of far-red light was then compared (Fig. 7a,b). Other analysis Methods for organellar genomes assembly (Supplementary Fig. 74), nuclear genome validation (Supplementary Figs 75–77), organellar genes (Supplementary Fig. 78, Supplementary Tables 10 and 11), transposable elements prediction (Supplementary Tables 1 and 12), non-coding RNAs prediction (Supplementary Tables 1 and 12) and genome duplication (Supplementary Figs 79 and 80) are described in Supplementary Methods. Author contributions K. Hori prepared samples of K. flaccidum for each experiment. T. Moriyama and N.S. performed the pilot study for genome sequencing. K. Hori, T.T., N.Y., T.Y., H. Mori, N.T., J.U., K. Higashi, N.S. and K. Kurokawa performed in silico analysis. F.M., S.S., D.S. and S.T. performed genome sequencing. K. Hori, F.M. and K. Kurokawa assembled the genome sequence. T.F. and Y.N. constructed the genome sequence database. K. Hori, M. Seo, M. Ikeuchi, M.W., H.W., K. Kobayashi, M. Saito, T. Masuda, Y.S.-S., K.M., K.A., M. Shimojima, S.M., M. Iwai, T. Nobusawa, T. Narise, S.K., H.S., R.S., M.M., Y.I., Y.O.-Y., K.O., M. Satoh, K.S., M. Ishii, R.O., M.K.-S., R.H., D.M., H. Mochizuki, Y.K., N.S. and H.O. annotated the nuclear genes. K. Hori and N.T. annotated the organellar genes. M. Seo analysed plant hormone levels. K. Hori analysed cyclic electron flow. N.S., Y.N., K. Kurokawa and H.O. designed the experiments. K. Hori, T.T., N.Y., T.Y. and H.O. wrote the manuscript. S.I. and H.O. planned the project. Additional information Accession codes: The assembled nuclear, plastidic, and mitochondrial genome sequences of K. flaccidum, strain NIES-2285, have been deposited in DDBJ/EMBL/GenBank under the accession codes DF236950 to DF238763; BioProject ID PRJDB718. How to cite this article: Hori, K. et al. Klebsormidium flaccidum genome reveals primary factors for plant terrestrial adaptation. Nat. Commun. 5:3978 doi: 10.1038/ncomms4978 (2014). Supplementary Material Supplementary Figures, Tables, Methods and References Supplementary Figures 1-80, Supplementary Tables 1-12, Supplementary Methods and Supplementary References. Supplementary Data 1 Genes used for the construction of phylogenetic tree (Fig. 2). Supplementary Data 2 Gene families in K. flaccidum for which the numbers of genes were significantly increased in land plants (median land plant gene number / median algae gene number 10). Supplementary Data 3 Numbers of genes and families in the GO biological process categories (classified by Arabidopsis GO slim) that were significantly better represented among land plants than among algae (median land plants gene number / median algal gene number 10). Supplementary Data 4 Numbers of Streptophyta-specific genes and gene groups of K. flaccidum in GO biological process categories. Supplementary Data 5 Genes involved in plant hormone biosynthesis, plant hormone signalling and multicelluarity in K. flaccidum. Supplementary Data 6 Gene list for chloroplast Ndh. Supplementary Data 7 Gene list for the NDH complex and proteins involved in cyclic electron flow. Supplementary Data 8 Reciprocal BLASTP best-hit proteins for K. flaccidum with nine algae or five land plant proteins. Supplementary Data 9 The manually curated 309 gene models. Supplementary Data 10 Predicted tRNA. Supplementary Data 11 Predicted non-coding RNAs.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                20 May 2016
                2016
                : 7
                : 678
                Affiliations
                [1] 1Unit of Functional Plant Biology, Institute of Botany, University of Innsbruck, Innsbruck Austria
                [2] 2Department of Botany, Faculty of Science, Charles University in Prague, Prague Czech Republic
                Author notes

                Edited by: Zoë A. Popper, National University of Ireland, Ireland

                Reviewed by: John Moore, Stellenbosch University, South Africa; Sven B. Gould, Heinrich-Heine-Universität Düsseldorf, Germany

                *Correspondence: Andreas Holzinger, andreas.holzinger@ 123456uibk.ac.at

                This article was submitted to Plant Evolution and Development, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2016.00678
                4873514
                27242877
                8fa54cf0-fe40-4b80-b6fb-5b1e7cceed45
                Copyright © 2016 Holzinger and Pichrtová.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 24 March 2016
                : 02 May 2016
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 139, Pages: 17, Words: 0
                Funding
                Funded by: Austrian Science Fund 10.13039/501100002428
                Award ID: I 1951-B16, P 24242-B16
                Funded by: Grantová Agentura České Republiky 10.13039/501100001824
                Award ID: 15-34645 L
                Categories
                Plant Science
                Review

                Plant science & Botany
                transcriptomics,proteomics,metabolomics,uv irradiation,desiccation,phylogenomic analysis

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