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https://doi.org/10.37427/botcro-2020-026

De novo transcriptome analysis of high growth rate Pyropia yezoensis (Bangiales, Rhodophyta) mutant with high utilization of nitrogen

Seo-jeong Park ; Chonnam National University, Department of Biotechnology and Bioengineering, Interdisciplinary Program for Bioenergy and Biomaterials, Gwangju 61186, Republic of Korea
Jong-il Choi ; Chonnam National University, Department of Biotechnology and Bioengineering, Interdisciplinary Program for Bioenergy and Biomaterials, Gwangju 61186, Republic of Korea


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Sažetak

Pyropia yezoensis (Ueda) M.S.Hwang et H.G.Choi (Bangiales, Rhodophyta) has potentially high economic value. P. yezoensis has been used as food in East Asian countries for a long time, and, in addition to that its consumption is increasing worldwide owing to the growing interest in healthy seaweed food. A mutant (Py2K) with a high growth rate was developed using gamma rays to increase the production of P. yezoensis. De novo transcriptome analysis was performed to determine the mechanism underlying the high growth rate of this mutant. The transcriptomes from wild-type (PyWT) and mutant (Py2K) strains were assembled, and 167,165 genes were analyzed. A total of 15,979 genes were differentially expressed. Transcriptome analysis of nitrogen pathway revealed the increase in nitrogen availability through the upregulation of nitrate transporter gene (nrt) expression. Activation of nitrogen assimilation and re-assimilation and upregulation in alternative oxidase (aox) gene contributed to the increase in cellular nitrogen availability, thereby affecting the synthesis of phycobiliprotein. As a consequence, the efficiency of photosynthesis and the subsequent growth rate increased, which contributed to the color differences in thalli between PyWT and Py2K.

Ključne riječi

differentially expressed genes; high growth rate mutant; nitrogen availability Pyropia yezoensis; RNA-sequencing; transcriptome analysis

Hrčak ID:

240846

URI

https://hrcak.srce.hr/240846

Datum izdavanja:

1.10.2020.

Posjeta: 1.646 *




Introduction

Seaweeds have been used as food and for medicines in East Asian countries for at least 1500 years (Hwang et al. 2019). The rhodophyte genus Pyropia J.Agardh (Bangiales) is a well-known farmed seaweed in East Asian countries such as Korea, Japan, and China. Pyropia is rich in nutrients including polysaccharides, proteins, steroids, carotenoids, long-chain poly-unsaturated fatty acids (PUFAs), and vitamins (Lee et al. 2016). The growing interest in seaweed-based food for the sake of health and nutrition (Van Loo et al. 2017) has increased the market demand for Pyropia, giving it a high potential economic value (Jiang et al. 2018). In addition to Pyropia tenera (Kjellman) N.Kikuchi, M.Miyata, M.S.Hwang et H.G.Choi, P. seriata (Kjellman) N.Kikuchi et M.Miyata, and P. dentata (Kjellman) N.Kikuchi et M.Miyata, P. yezoensis (Ueda) M.S.Hwang et H.G.Choi is one of the most cultivated species in Korea (Hwang et al. 2005).

Many studies have been directed an increasing the production of Pyropia, particularly through the control of algal diseases and using different cultivation technologies (Park et al. 2006,Kim et al. 2014,Kim et al. 2017). Selection, hybridization, and mutation are the basic methods used to develop seaweed strains suitable for mass cultivation, and nine Pyropia strains have been developed using these three methods in Korea from 2012 to 2018 (Park and Hwang 2014,Lee and Choi 2018,Hwang et al. 2019). Physical and chemical mutagens induce genetic variabilities in plants, and enhanced-tolerant mutants have been generated over the past 50 years (Beyaz and Yildiz 2017,Lee and Choi 2018). Several studies have also used mutagens to induce mutations in seaweed (Guimarães et al. 2003,Zayadan et al. 2014,Lee and Choi 2018). Gamma radiation is a physical mutagen generally used to obtain mutants with desirable traits. In this study, a mutant with high growth rate was developed using gamma rays. However, the mechanisms underlying its high growth rate were difficult to understand owing to the limited genetic information. Although some studies have published the draft and plastid genomes of P. yezoensis, information on its genome remains inadequate (Nakamura et al. 2013,Wang et al. 2013).

Transcriptome analysis using high-throughput RNA-sequencing (RNA-seq) offers the opportunity to investigate the molecular components de novo. Several transcriptome-based studies have been performed for non-model organisms such as seaweeds (Bryant et al. 2017,Carvalho et al. 2018,Garcia-Jimenez et al. 2018,Nan et al. 2018). The analysis of expressed transcripts may reveal unknown metabolic pathways or improve our knowledge about specific regulatory mechanisms.

In the present study, we performed de novo RNA-seq analysis to evaluate the mechanism underlying the high growth rate of the mutant P. yezoensis. Computational analysis of the transcriptome analysis result was combined with experiments to reveal the differences between the mutant and wild-type strains. This study aimed to elucidate the metabolic changes in the mutant strain with a high growth rate. The results of this study could improve our understanding about the functions of Pyropia genes and assist in the development of other mutants or recombinant seaweeds. Furthermore, the isolated mutant Pyropia with high growth will be useful in seaweed-based industries.

Materials and methods

Algal culture and development of a mutant with high growth rate

Pyropia yezoensis specimens were obtained from the Seaweed Research Center (Mokpo, Republic of Korea). Gametophytes of PyWT and Py2K were cultured in filter-sterilized Provasoli Enriched Seawater (PES) medium (Provasoli 1963) at 10 °C. A growth chamber set with a 10 h light and 14 h dark cycle (80 μmol photons·m−2·s−1) and filter-sterilized air was used. The medium was replaced every week.

Mutant P. yezoensis with a high growth rate was isolated as previously described (Lee and Choi 2019). Blades (1-2 cm long) were cultured for 4 weeks and exposed to 60Co gamma rays at 2 kGy at a rate of 10 kGy h-1 (Nordion International, Ottawa, Ontario, Canada). The samples were allowed to recover at 10 °C for 24 h in the dark. The surviving cells were selected and cultivated under similar conditions for 30 days. The length and width of blades were measured every week, and blades longer and wider than wild-type blades were isolated. Isolated blades were cultured for 6 weeks under similar conditions. The selected mutant with high growth rate was termed as “Py2K.”

RNA sequencing and de novo transcriptome analysis

The gametophytes were harvested after 4 weeks of cultivation and frozen in liquid nitrogen. Total RNA was prepared and sequenced by Insilicogen Company (Yongin, Republic of Korea) (Baek et al. 2018). The Illumina NextSeq 500 platform was used for pair-end RNA-seq.

Clean reads generated by Trimmomatic (Bolger et al. 2014) were assembled using Trinity (Haas et al. 2013) in an in silico normalization and a de novo assembly mode. The published draft genome of P. yezoensis (Nakamura et al. 2013) was used as the reference indexed with BBsplit in BBtools (Bushnell et al. 2017) to separate more reliable reads as P. yezoensis from clean reads. Putative contaminants were distinguished and eliminated from unmapped clean reads of P. yezoensis draft genome. Putative contaminants were distinguished using Diamond blast (Buchfink et al. 2015) with the NCBI non-redundant (NCBI-nr) database (Pruitt et al. 2005). The most annotated bacterial species were considered as putative contaminants. Mapped reads from P. yezoensis draft genome and unmapped reads from P. yezoensis and filter reads were merged and then de novo assembled using Trinity. The assemblies were separately generated from PyWT and Py2K.

The open-reading frame was identified by TransDecoder (Haas et al. 2013), and duplicates were eliminated using CD-HIT-EST (Li and Godzik 2006) by clustering based on at least 90% similarity. A shared sequence file between PyWT and Py2K was generated by CD-HIT-EST-2D and BBsplit. Transcriptome assembly was qualified using BUSCO v3 with Eukaryota database (Waterhouse et al. 2018).

Functional annotation and differential expressed genes (DEGs) analysis

NCBI-nr, SWISS-PROT (Consortium 2018), Pfam (Sonnhammer et al. 1997), and Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa and Goto 2000) were used for annotation. TransDecoder was used to retrieve amino acid sequences, while BLASTp (Camacho et al. 2009) was employed to descript amino acid sequences from SWISS-PROT. DIAMOND (Buchfink et al. 2015) was used with NCBI-nr to annotate amino acid sequences, while conserved protein domains from Pfam were annotated with hmmscan (Finn et al. 2011). Functional annotation was processed with an e-value ≤ l × 10−5. GO terms were annotated using the top BLASTp matched with sequences in SWISS-PROT as per the Trinotate workflow.

Gene abundance in sequences from PyWT and Py2K was estimated using Salmon (Patro et al. 2017). We used DEseq2 (Love et al. 2014) to identify DEGs between PyWT and Py2K at a false discovery rate (FDR) significant at ≤ 0.05 and an absolute value of log2 ratio ≥ 1. WEGO v2 was used to analyze functional interpretation (Ye et al. 2018).

Real-time quantitative polymerase chain reaction (RT-qPCR) was performed to validate the findings of transcriptome analysis using TB GreenTM Premix Ex TaqTM (Tli RNaseH Plus, TaKaRa) on an Illumina Eco Real-Time system. All reactions were conducted in triplicate. PyGADPH was used as an internal control (Kong et al. 2015). The primer sets specific for selected unigenes were designed using Primer3 (Untergasser, et al. 2012) (On-line Suppl. Tab. 1).

Differential expression level was calculated by the 2(−∆∆Ct) method (Livak and Schmittgen 2001), while relative expression was described by log2 2(−∆∆Ct). All experiments were performed in triplicate.

Antioxidant activity and polyphenol content

The 1,1-diphenyl-2-picryl-hydrazyl (DPPH) assay was performed as described byJao and Ko (2002) andNguyen et al. (2018). Harvested algal samples were powdered in liquid nitrogen using a mortar. Each ground sample (100 mg) was mixed with 80% ethanol at a ratio of 1:10 (w/v) and shaken at 100 rpm at 75 °C for 1 day. The mixture was filtered and condensed, and condensed samples were diluted with dimethyl sulfoxide (DMSO) to 20 mg mL-1. Then, 100 μL DPPH (1.5 × 10-4 M) and a 100 μL sample (500 μg mL-1) were placed in a 96-well plate, mixed, and reacted at 25 °C for 30 min. Absorbance was measured at 517 nm wavelength using a microplate reader (Molecular Devices, CA, San Jose, USA). The ferric ion-reducing antioxidant potential (FRAP) assay was performed with a ferric-reducing antioxidant power (FRAP) assay kit (Sigma-Aldrich, St. Louis, MO, USA) following the manufacturer’s protocol.

Total polyphenolic content was measured as described byMaksimović et al. (2005). Ground algal samples and 80% acetone were mixed at a ratio of 1:100 (w/v) and incubated in a water bath at 20 °C for 6 h. The samples were centrifuged, and the supernatants obtained were incubated with Folin-Ciocalteu reagent (Sigma) at a ratio of 1:2 (v/v) at room temperature for 1 h. The absorbance of the reaction solution was measured at 750 nm wavelength using a microplate reader.

Determination of chlorophyll fluorescence and photosynthetic pigment content

The photochemical efficiency of the photosystem II (PSII; Fv/Fm) was determined for PyWT and Py2K using a microscopy pulse-amplitude modulation apparatus (Walz GmbH, Effeltrich, Germany) as previously described byKim et al. (2006).

Phycoerythrin (PE) and phycocyanin (PC) levels were quantitatively analyzed as per the method described bySampath-Wiley and Neefus (2007). Algal samples were ground in liquid nitrogen using a mortar, and 100 mg of powdered samples were incubated with 800 μL of 0.1 M phosphate buffer (pH 6.8) at 4 °C for 12 h. The incubated samples were centrifuged at 15,000 ×g for 10 min at 4 °C, and the supernatants obtained were mixed with 200 μL phosphate buffer by vortexing. Their absorbance was measured using a microplate reader at 564, 618, and 730 nm (Molecular Devices).

Chlorophyll a (Chl a) was extracted by incubating 100 mg powdered samples with 1.8 mL of 98% acetone for 2 h at 4 °C in the dark. The supernatants obtained after centrifugation at 5000 ×g for 10 min were used to determine spectrophotometrically the content of Chl a, as described byJeffrey and Humphrey (1975). The mean of triplicate ± standard deviation was presented, and the Student t-test was used to determine the significance of the difference between the wild type and the mutant.

Results

De novo assembly and functional annotation of mutant P. yezoensis transcriptome

After exposure to 2 kGy gamma irradiation, a mutant of P. yezoensis with long and wide blades was isolated (Fig. 1A, B). The blades of Py2K were six times longer and three times wider than those of PyWT after 6 weeks of cultivation under similar conditions (Fig. 1C, D). Random amplified polymorphic DNA (RAPD) analysis was conducted to compare genotypic differences between PyWT and Py2K (Al-Zahim et al. 1999). Seven primer sets revealed the different patterns of amplified bands (On-line Suppl. Fig. 1), indicating that the isolated mutant was genetically distinct from the wild-type strain.

Fig. 1 Pyropia yezoensis wild-type (PyWT) and high growth rate mutant (Py2K). A – phenotype of PyWT, B – phenotype of Py2K cultivated for 6 weeks, C – growth of PyWT, D – growth of Py2K during 6 weeks of cultivation. Values are means ± standard deviation (n = 10).
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RNA was prepared from six samples, and approximately 424 million reads (151 base pairs) were generated by RNA-seq (On-line Suppl. Tab. 2). Elimination of putative contaminating sequences from the transcriptome yielded 197,780 transcripts and 167,165 genes (Tab. 1); N50 contained 672 bp and N10 contained 1,629 bp. While N50 was not long, N10 had sufficient length. The GC content was 52.42%, which was lower than the known GC content of the P. yezoensis genome. The E90 transcript set, indicative of the top 90% expressed transcripts, was 15,299 and the E90N50 was 675 bp. Thus, the assembled transcriptome contained near-complete gene sequence information for 78.2% genes in Eukaryota database (C: 78.2% [S: 43.9%, D: 34.3%], F: 16.5%, M: 5.3%, n: 303; C, complete BUSCOs; S, complete and single-copy BUSCOs; D, complete and duplicated BUSCOs; F, fragmented BUSCOs; M, missing BUSCOs; n, total BUSCO groups searched).

Tab. 1 Statistics of the assembled transcriptome of Pyropia yezoensis wild-type (PyWT) and mutant variant (Py2K) before and after the removal of putative contaminant sequences using BBtools.
StatisticShared sequences (PyWT and Py2K)
Before After
Total trinity genes170,461167,165
Total trinity transcripts202,789197,780
GC (%)52.5852.42
Contig N101,6231,629
Contig N50675672
Median contig length495492
Average contig626.14624.81
Total assembled bases126,974,556123,574,254

Genes were mostly annotated in NCBI-nr (140,721 genes; 71.65%), followed by Pfam (103,827 genes; 52.86%), GO (98,361 genes; 50.07%), SWISS-PROT (94,390 genes; 48.06%), and KEGG (82,023 genes; 41.76%). In total, 146,654 genes (74.67%) were annotated from at least one database.

DEGs from the wild-type and mutant variants and GO enrichment

We confirmed the high similarity between the heatmaps of samples from each group using Pearson’s correlation coefficients (On-line Suppl. Fig. 2). In all, 15,979 genes were retained at an FDR ≤ 0.05 and absolute value of log2 ratio ≥ 1 (Fig. 2). In Py2K, 9,113 genes were upregulated and 6,866 genes were downregulated as compared to PyWT. A total of 14,658 DEGs (91.73%) were annotated in at least one database, and most DEGs were annotated in NCBI-nr (14,494 DEGs; 90.70%), followed by Pfam (10,703 DEGs; 66.98%), GO (9,531 DEGs; 59.65%), SWISS-PROT (9,251 DEGs; 57.89%), and KEGG (8,042 DEGs; 50.33%).

Fig. 2 Heatmap of differentially expressed genes (DEGs) between Pyropia yezoensis wild-type (PyWT) and mutant variants (Py2K). Each sample is on the x-axis and genes are on the y-axis. Purple and olive indicate downregulated and upregulated genes in the mutant, respectively.
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GO term enrichment analysis revealed the annotation of 17 GO terms (Fig. 3). Four of these GO terms were mostly annotated in cellular process (GO:0009987, Biological Process), catalytic activity (GO:0003824, Molecular Function), cell (GO:0005623, Cellular Component), and cell part (GO:0044464, Cellular Component).

Fig. 3 Distribution of genes ontology terms in differentially expressed genes in Pyropia yezoensis wild-type and mutant variant (Py2K).
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RT-qPCR was conducted to validate the results of transcriptome analysis with 10 randomly selected DEGs. Most genes showed similar expression patterns with DEGs (On-line Suppl. Fig. 3). Thus, RT-qPCR analysis confirmed the validity of the transcriptome analysis.

Upregulated transcripts in the mutant strain

The transcripts that were overexpressed in Py2K were related to antioxidant enzymes, shikimate pathway, nitrogen utilization, ribosome biogenesis, and energy generation. Antioxidant enzymes such as glutathione peroxidase, glutathione S-transferase, glutathione synthetase, peroxiredoxin, catalase, thioredoxin, and aldehyde dehydrogenase were found to be upregulated in the mutant strain (On-line Suppl. Tab. 3). The expression of some genes (chorismite synthase [cs], 3-dehydroquinate dehydratase [DHQase], shikimate kinase [sk], and shikimate dehydrogenase [sdh]), including those involved in the shikimate pathway related to phenol precursors, was upregulated in the mutant (On-line Suppl. Tab. 4, On-line Suppl. Fig. 4). Various transcripts related to the pathways utilizing nitrogen were overexpressed in Py2K (Fig. 4, On-line Suppl. Tab. 5). Moreover, the expression of various transcripts related to energy production such as the Calvin cycle, electron transport chain (ETC), and photosynthesis also increased in Py2K as follows: mitochondrial complex I, II, III, IV, V (genes encoding NADH-ubiquinone oxidoreductase, succinate dehydrogenase, CoQ-cytochrome c reductase, cytochrome c oxidase, and F1F0 ATP synthase, respectively), cytochrome c (Cyt c), isocitrate dehydrogenase (idh), and heme oxygenase (ho) (Fig. 4, On-line Suppl. Tab. 6).

Fig. 4 Description of differentially expressed genes (DEGs) related to the high growth rate of the Pyropia yezoensis mutant Py2K. Nitrogen assimilation pathway is shown as described byLillo (2004). The green and red arrows indicate upregulated and downregulated genes in Py2K– respectively. Abbreviations: NRT – nitrate transporter, NR – nitrate reductase, Nir – ferredoxin-nitrite reductase, GS – glutamine synthetase, GOGAT – glutamine oxoglutarate aminotransferase, XDH – xanthine dehydrogenase, ALN – allantoinase (allantoin amidohydrolase), AAH – allantoate amidohydrolase, UGlyAH – ureidoglycine aminohydrolase, UAH – ureidoglycolate amidohydrolase, ER – endoplasmic reticulum, CL – cardiolipin, mitochondrial complex: I – NADH dehydrogenase, complex II – succinate dehydrogenase, complex III – cytochrome c oxidase, complex IV – cytochrome c oxidase, UQ – ubiquinone, Cyt c – cytochrome c, Cyt cox – oxidized cytochrome c, Cyt cred – reduced cytochrome c, AOX – alternative oxidase, IDH – isocitrate dehydrogenase, APAF1 – apoptotic protease-activating factor 1.
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Increased antioxidant capacity and content of photosynthetic pigments in the mutant strain

DPPH and FRAP assays were performed to confirm the increase in the antioxidant capacity of Py2K (Fig. 5A, B). DPPH radical-scavenging activity of Py2K was higher (78.43%) than that of PyWT (69.80%), while FRAP assay revealed a higher level of Fe3+ in Py2K (408.80 nM) than in PyWT (237.06 nM). We analyzed total phenolic content and found that the phenol content of Py2K was higher than that of PyWT (Fig. 5C).

Fig. 5 Antioxidant capacity of Pyropia yezoensis wild-type (PyWT) and mutant variant (Py2K) determined using: A – 1,1-diphenyl-2-picryl-hydrazyl (DPPH) assay, B – ferric ion-reducing antioxidant potential (FRAP) assay, C – total phenolic content. Values are means ± standard deviation (n = 3). The Student t-test was conducted to define the difference between PyWT and Py2K. Asterisk means the significant difference between PyWT and Py2K by the Student t-test (*P < 0.05, **P < 0.001).
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The Fv/Tm value of Py2K was higher than that of PyWT, while Py2K contained more PE and PC than PyWT (Tab. 2). However, the content of Chl a slightly increased in Py2K over that in PyWT.

Tab. 2 The photochemical efficiency of the photosystem II (Fv/Fm values) and chlorophyll a (Chl a), phycoerythrin (PE), and phycocyanin (PC) content in Pyropia yezoensis wild-type (PyWT) and mutant variant (Py2K). Mean of triplicate ± standard deviation is presented. Asterisk means the significant difference between PyWT and Py2K by the Student t-test (*P < 0.05, **P < 0.001).
Photochemical efficiencyPyWTPy2K
Fv/Fm0.58 ± 0.070.62 ± 0.08
Chl a27.60 ± 0.5428.54 ± 0.61
PE175.12 ± 2.54180.33 ± 1.76*
PC180.33 ± 2.61241.48 ± 2.51**
PE/Chl a6.34 ± 1.436.33 ± 0.82
PC/Chl a6.53 ± 1.498.47 ± 1.35*
PE + PC/Chl a12.88 ± 1.1914.8 ± 0.96*

Discussion

In this study, a mutant P. yezoensis strain with high growth rate, Py2K, was obtained by gamma irradiation. Transcriptome analysis was performed de novo to elucidate differences in phenotypes between mutant Py2K and wild-type strains.

Transcriptome analysis revealed the upregulation in the expression of antioxidant enzymes in the mutant Py2K variant. Normal cellular metabolism generates reactive oxygen species (ROS) as a byproduct (Poljsak et al. 2013). High growth rate may induce the generation of excessive ROS as compared with normal growth conditions, owing to the activation of cellular metabolism. ROS could damage cells and, hence, antioxidants play an important role as scavengers of excessively produced ROS to limit ROS-induced damage. The increase in the antioxidant capacity of mutants developed with gamma rays is common and related to the mechanisms by which mutation is induced, involving generation of ROS or free radicals in cells (Beyaz and Yildiz 2017). The results of DPPH and FRAP assays show that Py2K had higher antioxidant capacity than did PyWT. The FRAP assay measures antioxidant capacity based on reducing power. Higher values in FRAP assay for mutant samples may indicate the additional components of Py2K as sources of reducing power. The content of total phenolic compounds, which act as reducing agents donating a single electron or hydrogen atom (Rabeta and Faraniza 2013), was higher in mutant Py2K than in the wild-type strain. Further, transcriptome analysis showed the activation of the biosynthesis pathway for phenol precursor, probably owing to the increase in the content of phenolics in the mutant strain. Therefore, high expression of antioxidant enzymes and increased levels of phenolic compounds could enhance the ROS-scavenging capacity of mutant Py2K.

The high growth of Py2K could be associated with the increased availability of nitrogen and energy regeneration system. Nitrogen is an essential nutrient and a limiting macro-nutrient in the ocean (Moore et al. 2013,Bristow et al. 2017). Nitrogen is assimilated in the following manner: NO3 uptake → NO3 → NO2 → NH4+ → glutamine → glutamate → amino acids (Lillo 2004). The gene nrt encodes a transporter that is located in the cell membrane and is involved in nitrate uptake. There are two forms of these genes, nrt1 and nrt2. In general, the members of the nrt1 family have low affinity for nitrate, while those of the nrt2 family exhibit high affinity for nitrate (Lillo 2004). In the transcriptome analysis, we failed to observe nrt1 as a DEG; however, nrt2 expression was upregulated in Py2K (On-line Suppl. Tab. 5). Assimilated NO3 is reduced to NH4+ by NR and NiR. The expression of nir is induced by nitrate, which is generated by NR. NH4+ is used to produce glutamine via glutamine synthetase (gs) in the chloroplast, and glutamine is converted to glutamate, which is used for amino acid synthesis. The expression of gs and the genes related to amino acid synthesis (those encoding D-amino-acid N-acetyltransferase, cystathionine gamma-lyase, and arginosuccinate synthase) was upregulated in Py2K. NO3 uptake could be enhanced following increased nrt expression, which resulted in increased synthesis of amino acids that were used as building blocks.

Nucleobases are rich stores of nitrogen in cells (Werner et al. 2013). Purine degradation results in the release of nitrogen, which is re-assimilated into amino acids. Purine ring catabolism via ureide-degrading reactions generates five NH3 molecules from one adenosine molecule. The purine ring catabolism pathway was constructed using ureide-degrading reactions with reference toWerner and Witte (2011),Hafez et al. (2017) and,Melino et al. (2018), although this pathway is controversial in plants. The genes aln and aah (encoding allantoate amidohydrolase) are important for purine ring catabolism, and Arabidopsis mutants deficient in aln and aah had accelerated senescence, rapid transition, and impairment in reproductive growth (Takagi et al. 2018) (Fig. 4). Upregulated expression of aln could contribute to the activation of purine ring catabolism, and activated nitrogen re-assimilation would allow mutant variants to grow at higher rates than the wild-type strain.

Ribosome biogenesis is an important process regulating plant growth and development (Hang et al. 2018). Repressed ribosome biogenesis results in defective vegetable growth and development (Beine-Golovchuk et al. 2018,Maekawa and Yanagisawa 2018, Palm et al. 2019). Repression of ribosome biogenesis is imperative under starvation conditions because it is one of the most energy consuming cellular processes (Kraft et al. 2008,Ohbayashi and Sugiyama 2018). However, transcripts related to ribosome biogenesis were upregulated in Py2K (On-line Suppl. Tab. 5), indicating that their high growth rate may induce the underutilization of cellular nitrogen as building blocks and mediate activation of nitrogen assimilation and re-assimilation; ribosome biogenesis replenished the cellular building blocks that were lacking.

Oxidative phosphorylation generates the bulk of ATP from mitochondria that is essential for the maintenance and growth of cells (Millar et al. 2011). In plants, the electron transport chain (ETC) comprises the mitochondrial complex I, II, III, IV, and V, ubiquinone (UQ), Cyt c, and alternative oxidase (AOX). Enhanced ETC leads to the generation of higher ATP levels, which subsequently support cell maintenance. Cyt c, a small heme protein and an essential component of the ETC in mitochondria, was found to be upregulated in Py2K (Virolainen et al. 2002,Ott et al. 2002,Reape et al. 2008,Matsuura et al. 2016). The presence of bax/bak in the outer membrane and peroxidation of cardiolipin (CL) stimulate the release of Cyt c. The expression of bax/bak is negatively regulated by the mitochondrial complex I (Kim et al. 2003,Westphal et al. 2011). Upregulated expression of mitochondrial complex I may result in the repression of the expression of bax/bak in the mutant variant. Further, CL peroxidation can be induced by ROS generated from oxidative phosphorylation to produce CL hydroperoxide (CL-OOH) and free Cyt c (Perier et al. 2005,de Paepe et al. 2014). Released Cyt c is immediately oxidized to Cyt cox, which activates caspase and combines with caspase-9 and apoptotic protease activating factor 1 (APAF1) to form a complex that promotes apoptosis (McMillin and Dowhan 2002,Vianello et al. 2007,Brown and Borutaite 2008).

Py2K showed upregulated expression of mitochondrial manganese-dependent superoxide dismutase (mnsod), which removes ROS generated from activated ETC (Vanlerberghe 2013) and prevents ROS-mediated CL peroxidation and the release of Cyt c. Cyt c reductants can reduce Cyt cox to Cyt cred (Brown and Borutaite 2008) and may include superoxide, ascorbate, reduced glutathione, cytochrome P450, cytochrome b5, NAD(P)H, and tetramethyl-p-phenylenediamine.

In general, plant mitochondria contain AOX in their ETC systems (Vanlerberghe 2013). AOX is located between mitochondrial complexes II and III, and electrons are distributed to AOX and complex III. AOX is a non-proton pumping oxidase that can reduce the production of ROS generated from complex I and III. In addition, the expression of aox gene is upregulated under abiotic/biotic stress conditions because increased AOX expression is beneficial for maintaining homeostasis and to increase resistance against stress. AOX contributes to redox homeostasis for nitrate assimilation by supplying high reducing power to reduce nitrate to NH4+ (Vanlerberghe 2013). Stress conditions such as deficient cellular nitrogen may upregulate the expression of aox and contribute to nitrate assimilation by supplying high reducing power.

The Calvin cycle provides organic acids, and the ETC oxidizes NADH. The increase in the expression of idh may result in the activation of the Calvin cycle in Py2K mutant and contribute to ETC activation. Therefore, these findings suggest the activation of oxidative phosphorylation in the high growth rate mutant. Upregulated Cyt c expression could induce apoptosis; however, the high level of cytochrome b5 in Py2K may be useful to reduce oxidized Cyt c; thus, Cyt c may not induce apoptosis. Furthermore, the increased expression of aox could provide high reducing power for nitrate assimilation and prevent excessive ROS production (Fig. 4, On-line Suppl. Tab. 6).

Photosynthesis is the process in which energy is derived from light and stored in the form of nutrients. P. yezoensis uses Chl a and phycobiliproteins to obtain light for photosynthesis. Photosynthesis efficiency determines the growth of P. yezoensis, and an increase in photosynthesis efficiency may enhance the growth of P. yezoensis (Gao et al. 1991). Although Chl a is a photosynthetic pigment in plants and algae, the high phycobiliprotein content and phycobiliprotein/Chl a ratio indicate enhanced energy efficiency and rapid growth (Zhang et al. 2014). The increased Fv/Tm value and PE + PC/Chl a ratio in Py2K suggest that the enhanced photosynthetic efficiency may contribute to the high growth rate of the mutant (Tab. 2).

In summary, DEGs analysis revealed the increase in nitrogen uptake owing to the upregulated expression of nrt and that the activation of nitrogen assimilation and re-assimilation may serve as reasons for the high growth rate of the mutant (Fig. 6). In addition, aox expression was upregulated in mitochondria and may have led to nitrogen assimilation by supplying NAD(P)H (Vanlerberghe 2013). Nitrogen availability might have increased and enhanced amino acid synthesis and ribosome biogenesis. Increased contents of amino acids as building blocks and high number of ribosomes could be useful during cell growth. Furthermore, increased nitrogen availability may regulate the synthesis of photosynthetic pigments and generate high levels of PE and PC in Py2K (Gao et al. 2019). The high expression of the genes related to the synthesis of phycobiliprotein precursor was evident in DEG analysis. High levels of PE and PC could enhance photosynthesis in the mutant, thereby increasing its growth rate (Zhang et al. 2014). Further, the differences in the levels of PE and PC between the mutant and PyWT may have led to variations in algal color (Fig. 1A, B). Increased nitrogen availability may activate cellular processes such as photosynthesis and induce the production of ROS. Some genes related to antioxidants were highly expressed in Py2K. Improved antioxidant capability may sufficiently scavenge ROS during the activation of cellular processes and prevent cell death.

Fig. 6 Transcriptomic analysis for Pyropia yezoensis mutant. The green arrows indicate activated pathways related to the high growth rate of the mutant. AOX – alternative oxidase, N – nitrogen, NRT – nitrate transporter, ER – endoplasmic reticulum.
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In this study, transcriptome analysis was performed to understand the metabolic changes in the newly isolated mutant Pyropia Py2K. Py2K has a high growth rate and would be useful in seaweed cultivation. Furthermore, the transcriptome analysis performed could be useful for an understanding of the expression pattern of genes and the development of new cultivars of seaweeds for which genetic information is missing.

Appendices

On line Supplementary materials

On-line Suppl. Tab. 1. Sequences of primer sets used for RT-qPCR to validate results of transcriptome analysis.

On-line Suppl. Tab. 2. Summary statistics of raw and clean reads in Pyropia yezoensis wild type (PyWT) and mutant (Py2K).On-line Suppl. Tab. 3. List of upregulated genes in mutant Pyropia yezoensis (Py2K) annotated as ‘antioxidant’.

On-line Suppl. Tab. 3. List of upregulated genes in mutant Pyropia yezoensis (Py2K) annotated as ‘antioxidant’.

On-line Suppl. Tab. 4. List of differentially expressed genes in Pyropia yezoensis mutant (Py2K) related to the Shikimate pathway.

On-line Suppl. Tab. 5. List of differentially expressed genes in Pyropia yezoensis mutant (Py2K) related to nitrogen assimilation and re-assimilation, ribosome biogenesis, and amino acid biosynthesis.

On-line Suppl. Tab. 6. List of differentially expressed genes in Pyropia yezoensis mutant (Py2K) related to the electron transport chain.

On-line Suppl. Fig. 1. Random amplified polymorphic DNA (RAPD) analysis of Pyropia yezoensis wild-type (PyWT) and mutant (Py2K). RAPD analysis was conducted to compare PyWT and Py2K using 20 RAPD primer sets (OPA 1-20 primer sets). Representative amplifications with OPA 4, 7, 11, 12, 15 17 and 20 are shown. Arrows indicate the bands that were different between PyWT and Py2K. Wt, wild-type; Mt, mutant.

On-line Suppl. Fig. 2. Relationship among samples based on log2-transformed count data between Pyropia yezoensis wild-type (PyWT) and mutant (Py2K) with hierarchically clustered heatmap using Pearson’s correlation coefficients.

On-line Suppl. Fig. 3. Reverse transcription quantitative PCR (RT-qPCR) results for verification of transcriptome analysis results. All experiments were performed in triplicate and error bar indicated standard deviation.

On-line Suppl. Fig. 4. Description of differentially expressed genes (DEGs) in the shikimate biosynthesis pathway related to phenol biosynthesis in Py2K. The shikimic acid pathway was described bySantos-Sánchez et al. (2019). The green arrows indicate upregulated genes in Py2K. PEP – phosphoenolpyruvic acid, D-erythores-4-P – D-erythores-4-phosphate, DAHP – 3-deoxy-D-arabion-heptulosonic acid 7-phosphate, DHQ – 3-dehydroquinic acid, DHS – 3-dehydroshikimic acid, S3P – shikimic acid 3-phosphate, EPSP – 5-enolpyruvylshikimic acid 3-phosphate, DAHPS – 3-deoxy-D-arabion-heptulosonic acid 7-phosphate synthase, DHQS – 3-dehydroquinic acid synthase, SDH – shikimate dehydrogenase, SK – shikimate kinase, EPSPS – 5-enolpyruvylshikimic acid 3-phosphate synthase, CS – chorismite sy

Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2018R1D1A1B07049359) and a Golden Seed Project Grant funded by Ministry of Oceans and Fisheries (213008-05-4-SB910).

References

 

Al-Zahim M, Ford-Lloyd B, Newbury H. Detection of somaclonal variation in garlic (Allium sativum L.) using RAPD and cytological analysis. Plant Cell Rep. 1999;6:473–7. https://doi.org/10.1007/s002990050606

 

Baek SJ, Chun JM, Kang TW, Seo YS, Kim SB, Seong B, et al. Identification of epigenetic mechanisms involved in the anti-asthmatic effects of Descurainia sophia seed extract based on a multi-omics approach. Molecules. 2018;23:2879. https://doi.org/10.3390/molecules23112879 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/30400597

 

Beine-Golovchuk O, Firmino AAP, Dąbrowska A, Schmidt S, Erban A, Walther D, et al. Plant temperature acclimation and growth rely on cytosolic ribosome biogenesis factor homologs. Plant Physiol. 2018;176:2251–76. https://doi.org/10.1104/pp.17.01448 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29382692

 

Beyaz R, Yildiz M. 2017: The use of gamma irradiation in plant mutation breeding. In: Jurić, S. (ed.) Plant Engineering, 34–46. IntechOpen, London.

 

Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20. https://doi.org/10.1093/bioinformatics/btu170 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/24695404

 

Bristow LA, Mohr W, Ahmerkamp S, Kuypers MM. Nutrients that limit growth in the ocean. Curr Biol. 2017;27:R474–8. https://doi.org/10.1016/j.cub.2017.03.030 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/28586682

 

Brown GC, Borutaite V. Regulation of apoptosis by the redox state of cytochrome c. Biochim Biophys Acta. 2008;1777:877–81. https://doi.org/10.1016/j.bbabio.2008.03.024 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/18439415

 

Bryant DM, Johnson K, DiTommaso T, Tickle T, Couger MB, Payzin-Dogru D, et al. A tissue-mapped axolotl de novo transcriptome enables identification of limb regeneration factors. Cell Rep. 2017;18:762–76. https://doi.org/10.1016/j.celrep.2016.12.063 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/28099853

 

Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015;12:59. https://doi.org/10.1038/nmeth.3176 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/25402007

 

Bushnell B, Rood J, Singer E. BBMerge–accurate paired shotgun read merging via overlap. PLoS One. 2017;12:e0185056. https://doi.org/10.1371/journal.pone.0185056 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29073143

 

Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10:421. https://doi.org/10.1186/1471-2105-10-421 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/20003500

 

Carvalho EL, Maciel LF, Macedo PE, Dezordi FZ, Abreu ME, Victória FC, et al. De novo assembly and annotation of the Antarctic alga Prasiola crispa transcriptome. Front Mol Biosci. 2018;4:89. https://doi.org/10.3389/fmolb.2017.00089 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29359133

 

Consortium U. UniProt: the universal protein knowledgebase. Nucleic Acids Res. 2018;46:2699. PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29425356

 

de Paepe R, Lemaire SD, Danon A. Cardiolipin at the heart of stress response across kingdoms. Plant Signal Behav. 2014;9:e29228. https://doi.org/10.4161/psb.29228 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/25763690

 

Finn RD, Clements J, Eddy SR. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 2011;39:W29–37. https://doi.org/10.1093/nar/gkr367 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/21593126

 

Gao G, Gao Q, Bao M, Xu J, Li X. Nitrogen availability modulates the effects of ocean acidification on biomass yield and food quality of a marine crop Pyropia yezoensis. Food Chem. 2019;271:623–9. https://doi.org/10.1016/j.foodchem.2018.07.090 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/30236725

 

Gao K, Aruga Y, Asada K, Ishihara T, Akano T, Kiyohara M. Enhanced growth of the red alga Porphyra yezoensis Ueda in high CO2 concentrations. J Appl Phycol. 1991;4:355–62. https://doi.org/10.1007/BF02392889

 

Garcia-Jimenez P, Llorens C, Roig FJ, Robaina RR. Analysis of the Transcriptome of the Red Seaweed Grateloupia imbricata with Emphasis on Reproductive Potential. Mar Drugs. 2018;16:490. https://doi.org/10.3390/md16120490 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/30544522

 

Guimarães M, Plastino EM, Destombe C. Green mutant frequency in natural populations of Gracilaria domingensis (Gracilariales, Rhodophyta) from Brazil. Eur J Phycol. 2003;2:165–9. https://doi.org/10.1080/0967026031000085878

 

Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc. 2013;8:1494. https://doi.org/10.1038/nprot.2013.084 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/23845962

 

Hafez RM, Abdel-Rahman TM, Naguib RM. Uric acid in plants and microorganisms: Biological Applications and Genetics-A review. J Adv Res. 2017;8:475–86. https://doi.org/10.1016/j.jare.2017.05.003 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/28748114

 

Hang R, Wang Z, Deng X, Liu C, Yan B, Yang C, et al. Ribosomal RNA Biogenesis and Its Response to Chilling Stress in Oryza sativa. Plant Physiol. 2018;177:381–97. https://doi.org/10.1104/pp.17.01714 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29555785

 

Hwang EK, Yotsukura N, Pang SJ, Su L, Shan TF. Seaweed breeding programs and progress in eastern Asian countries. Phycologia. 2019;5:484–95. https://doi.org/10.1080/00318884.2019.1639436

 

Hwang MS, Kim SM, Ha DS, Baek JM, Kim HS, Choi HG. DNA sequences and identification of Porphyra cultivated by natural seeding on the southwest coast of Korea. Algae. 2005;3:183–96. https://doi.org/10.4490/ALGAE.2005.20.3.183

 

Jao CL, Ko WC. 1, 1-Diphenyl-2-picrylhydrazyl (DPPH) radical scavenging by protein hydrolyzates from tuna cooking juice. Fish Sci. 2002;2:430–5. https://doi.org/10.1046/j.1444-2906.2002.00442.x

 

Jeffrey ST, Humphrey G. New spectrophotometric equations for determining chlorophylls a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochem Physiol Pflanz. 1975;2:191–4. https://doi.org/10.1016/S0015-3796(17)30778-3

 

Jiang H, Zou D, Lou W, Deng Y, Zeng X. Effects of seawater acidification and alkalization on the farmed seaweed, Pyropia haitanensis (Bangiales, Rhodophyta), grown under different irradiance conditions. Algal Res. 2018;31:413–20. https://doi.org/10.1016/j.algal.2018.02.033

 

Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28:27–30. https://doi.org/10.1093/nar/28.1.27 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/10592173

 

Kim GH, Moon KH, Kim JY, Shim J, Klochkova TA. A revaluation of algal diseases in Korean Pyropia (Porphyra) sea farms and their economic impact. Algae. 2014;4:249. https://doi.org/10.4490/algae.2014.29.4.249

 

Kim JK, Yarish C, Hwang EK, Park M, Kim Y. Seaweed aquaculture: cultivation technologies, challenges and its ecosystem services. Algae. 2017;1:1–13. https://doi.org/10.4490/algae.2017.32.3.3

 

Kim KY, Jeong HJ, Main HP, Garbary DJ. Fluorescence and photosynthetic competency in single eggs and embryos of Ascophyllum nodosum (Phaeophyceae). Phycologia. 2006;3:331–6. https://doi.org/10.2216/05-40.1

 

Kim M, Ahn JW, Jin UH, Choi D, Paek KH, Pai HS. Activation of the programmed cell death pathway by inhibition of proteasome function in plants. J Biol Chem. 2003;278:19406–15. https://doi.org/10.1074/jbc.M210539200 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/12637532

 

Kong F, Cao M, Sun P, Liu W, Mao Y. Selection of reference genes for gene expression normalization in Pyropia yezoensis using quantitative real-time PCR. J Appl Phycol. 2015;2:1003–10. https://doi.org/10.1007/s10811-014-0359-6

 

Kraft C, Deplazes A, Sohrmann M, Peter M. Mature ribosomes are selectively degraded upon starvation by an autophagy pathway requiring the Ubp3p/Bre5p ubiquitin protease. Nat Cell Biol. 2008;10:602. https://doi.org/10.1038/ncb1723 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/18391941

 

Lee HJ, Choi J. Isolation and characterization of a high-growth-rate strain in Pyropia yezoensis induced by ethyl methane sulfonate. J Appl Phycol. 2018;4:2513–22. https://doi.org/10.1007/s10811-018-1426-1

 

Lee JH, Kim HH, Ko JY, Jang JH, Kim GH, Lee JS, et al. Rapid preparation of functional polysaccharides from Pyropia yezoensis by microwave-assistant rapid enzyme digest system. Carbohydr Polym. 2016;153:512–7. https://doi.org/10.1016/j.carbpol.2016.07.122 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/27561523

 

Lee HJ, Choi J. Enhancing temperature tolerance of Pyropia tenera (Bangiales) by inducing mutation. Phycologia. 2019;5:496–503. https://doi.org/10.1080/00318884.2019.1623547

 

Li W, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22:1658–9. https://doi.org/10.1093/bioinformatics/btl158 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/16731699

 

Lillo C. 2004: Light regulation of nitrate uptake, assimilation and metabolism. In: Amâncio, S., Stulen, I. (eds.), Nitrogen acquisition and assimilation in higher plants, 149–184. Springer, Dordrecht.

 

Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2− ΔΔCT method. Methods. 2001;25:402–8. https://doi.org/10.1006/meth.2001.1262 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/11846609

 

Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. https://doi.org/10.1186/s13059-014-0550-8 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/25516281

 

Maekawa S, Yanagisawa S. Nucleolar stress and sugar response in plants. Plant Signal Behav. 2018;13:e1442975. https://doi.org/10.1080/15592324.2018.1442975 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29465318

 

Maksimović Z, Malenčić Đ, Kovačević N. Polyphenol contents and antioxidant activity of Maydis stigma extracts. Bioresour Technol. 2005;96:873–7. https://doi.org/10.1016/j.biortech.2004.09.006 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/15627557

 

Matsuura K, Canfield K, Feng W, Kurokawa M. Metabolic regulation of apoptosis in cancer. Int Rev Cell Mol Biol. 2016;327:43–87. https://doi.org/10.1016/bs.ircmb.2016.06.006 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/27692180

 

McMillin JB, Dowhan W. Cardiolipin and apoptosis. Biochim Biophys Acta. 2002;1585:97–107. https://doi.org/10.1016/S1388-1981(02)00329-3 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/12531542

 

Melino VJ, Casartelli A, George J, Rupasinghe T, Roessner U, Okamoto M, et al. RNA catabolites contribute to the nitrogen pool and support growth recovery of wheat. Front Plant Sci. 2018;9:1539. https://doi.org/10.3389/fpls.2018.01539 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/30455708

 

Millar, A.H., Whelan, J., Soole, K.L., Day, D.A., 2011: Organization and regulation of mitochondrial respiration in plants. Annual Review of pPant Biology 62, 79–104.

 

Moore C, Mills M, Arrigo K, Berman-Frank I, Bopp L, Boyd P, et al. Processes and patterns of oceanic nutrient limitation. Nat Geosci. 2013;9:701. https://doi.org/10.1038/ngeo1765

 

Nakamura Y, Sasaki N, Kobayashi M, Ojima N, Yasuike M, Shigenobu Y, et al. The first symbiont-free genome sequence of marine red alga, Susabi-nori (Pyropia yezoensis). PLoS One. 2013;8:e57122. https://doi.org/10.1371/journal.pone.0057122 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/23536760

 

Nan F, Feng J, Lv J, Liu Q, Xie S. Transcriptome analysis of the typical freshwater rhodophytes Sheathia arcuata grown under different light intensities. PLoS One. 2018;13:e0197729. https://doi.org/10.1371/journal.pone.0197729 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29813098

 

Nguyen TT, Choi YJ, Nguyen THP, Neri TA, Choi BD. Change in the antioxidant activity of roasted seasoned laver Pyropia yezoensis with heat processing and storage. Korean Journal of Fisheries and Aquatic Sciences. 2018;4:362–8.

 

Ohbayashi I, Sugiyama M. Plant nucleolar stress response, a new face in the NAC-dependent cellular stress responses. Front Plant Sci. 2018;99:2247. https://doi.org/10.3389/fpls.2017.02247 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29375613

 

Ott M, Robertson JD, Gogvadze V, Zhivotovsky B, Orrenius S. Cytochrome c release from mitochondria proceeds by a two-step process. Proc Natl Acad Sci USA. 2002;3:1259–63. https://doi.org/10.1073/pnas.241655498 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/11818574

 

Palm D, Streit D, Shanmugam T, Weis BL, Ruprecht M, Simm S, et al. Plant-specific ribosome biogenesis factors in Arabidopsis thaliana with essential function in rRNA processing. Nucleic Acids Res. 2019;47:1880–95. PubMed: http://www.ncbi.nlm.nih.gov/pubmed/30576513

 

Park CS, Hwang EK. Isolation and evaluation of a strain of Pyropia yezoensis (Bangiales, Rhodophyta) resistant to red rot disease. J Appl Phycol. 2014;2:811–7. https://doi.org/10.1007/s10811-013-0183-4

 

Park CS, Kakinuma M, Amano H. Forecasting infections of the red rot disease on Porphyra yezoensis Ueda (Rhodophyta) cultivation farms. J Appl Phycol. 2006;18:295–9. https://doi.org/10.1007/s10811-006-9031-0

 

Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14:417. https://doi.org/10.1038/nmeth.4197 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/28263959

 

Perier C, Tieu K, Guégan C, Caspersen C, Jackson-Lewis V, Carelli V, et al. Complex I deficiency primes Bax-dependent neuronal apoptosis through mitochondrial oxidative damage. Proc Natl Acad Sci USA. 2005;102:19126–31. https://doi.org/10.1073/pnas.0508215102 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/16365298

 

Poljsak B, Šuput D, Milisav I. Achieving the balance between ROS and antioxidants: when to use the synthetic antioxidants. Oxid Med Cell Longev. 2013;•••:956792. https://doi.org/10.1155/2013/956792 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/23738047

 

Provasoli L. Organic regulation of phytoplankton fertility. The Sea. 1963;2:165–219.

 

Pruitt KD, Tatusova T, Maglott DR. NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2005;33:D501–4. https://doi.org/10.1093/nar/gki025 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/15608248

 

Rabeta M, Faraniza RN. Total phenolic content and ferric reducing antioxidant power of the leaves and fruits of Garcinia atrovirdis and Cynometra cauliflora. Int Food Res J. 2013;20:1691–6.

 

Reape TJ, Molony EM, McCabe PF. Programmed cell death in plants: distinguishing between different modes. J Exp Bot. 2008;59:435–44. https://doi.org/10.1093/jxb/erm258 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/18256053

 

Sampath-Wiley P, Neefus CD. An improved method for estimating R-phycoerythrin and R-phycocyanin contents from crude aqueous extracts of Porphyra (Bangiales, Rhodophyta). J Appl Phycol. 2007;19:123–9. https://doi.org/10.1007/s10811-006-9118-7 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/19396349

 

Santos-Sánchez NF, Salas-Coronado R, Hernández-Carlos B, Villanueva-Cañongo C. 2019: Shikimic acid pathway in biosynthesis of phenolic compounds. In: Soto-Hernández, M. (ed.), Plant Physiological Aspects of Phenolic Compounds, IntechOpen, London.

 

Sonnhammer EL, Eddy SR, Durbin R. Pfam: a comprehensive database of protein domain families based on seed alignments. Proteins. 1997;28:405–20. https://doi.org/10.1002/(SICI)1097-0134(199707)28:3<405::AID-PROT10>3.0.CO;2-L PubMed: http://www.ncbi.nlm.nih.gov/pubmed/9223186

 

Takagi H, Watanabe S, Tanaka S, Matsuura T, Mori IC, Hirayama T, et al. Disruption of ureide degradation affects plant growth and development during and after transition from vegetative to reproductive stages. BMC Plant Biol. 2018;18:287. https://doi.org/10.1186/s12870-018-1491-2 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/30458716

 

Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, et al. Primer3 - new capabilities and interfaces. Nucleic Acids Res. 2012;40:e115–115. https://doi.org/10.1093/nar/gks596 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/22730293

 

Van Loo EJ, Hoefkens C, Verbeke W. Healthy, sustainable and plant-based eating: Perceived (mis) match and involvement-based consumer segments as targets for future policy. Food Policy. 2017;69:46–57. https://doi.org/10.1016/j.foodpol.2017.03.001

 

Vanlerberghe GC. Alternative oxidase: a mitochondrial respiratory pathway to maintain metabolic and signaling homeostasis during abiotic and biotic stress in plants. Int J Mol Sci. 2013;14:6805–47. https://doi.org/10.3390/ijms14046805 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/23531539

 

Vianello A, Zancani M, Peresson C, Petrussa E, Casolo V, Krajňáková J, et al. Plant mitochondrial pathway leading to programmed cell death. Physiol Plant. 2007;1:242–52. https://doi.org/10.1111/j.1399-3054.2006.00767.x

 

Virolainen E, Blokhina O, Fagerstedt K. Ca2+‐induced high amplitude swelling and cytochrome c release from wheat (Triticum aestivum L.) mitochondria under anoxic stress. Ann Bot (Lond). 2002;4:509–16. https://doi.org/10.1093/aob/mcf221

 

Wang L, Mao Y, Kong F, Li G, Ma F, Zhang B, et al. Complete sequence and analysis of plastid genomes of two economically important red algae: Pyropia haitanensis and Pyropia yezoensis. PLoS One. 2013;8:e65902. https://doi.org/10.1371/journal.pone.0065902 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/23734264

 

Waterhouse RM, Seppey M, Simão FA, Manni M, Ioannidis P, Klioutchnikov G, et al. BUSCO applications from quality assessments to gene prediction and phylogenomics. Mol Biol Evol. 2018;35:543–8. PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29220515

 

Werner AK, Witte CP. The biochemistry of nitrogen mobilization: purine ring catabolism. Trends Plant Sci. 2011;16:381–7. https://doi.org/10.1016/j.tplants.2011.03.012 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/21482173

 

Werner AK, Medina-Escobar N, Zulawski M, Sparkes IA, Cao FQ, Witte CP. The ureide-degrading reactions of purine ring catabolism employ three amidohydrolases and one aminohydrolase in Arabidopsis, soybean, and rice. Plant Physiol. 2013;163:672–81. https://doi.org/10.1104/pp.113.224261 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/23940254

 

Westphal D, Dewson G, Czabotar PE, Kluck RM. Molecular biology of Bax and Bak activation and action. Biochim Biophys Acta. 2011;1813:521–31. https://doi.org/10.1016/j.bbamcr.2010.12.019 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/21195116

 

Ye J, Zhang Y, Cui H, Liu J, Wu Y, Cheng Y, et al. WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update. Nucleic Acids Res. 2018;46:W71–5. https://doi.org/10.1093/nar/gky400 PubMed: http://www.ncbi.nlm.nih.gov/pubmed/29788377

 

Zayadan B, Purton S, Sadvakasova A, Userbaeva A, Bolatkhan K. Isolation, mutagenesis, and optimization of cultivation conditions of microalgal strains for biodiesel production. Russ J Plant Physiol. 2014;1:124–30. https://doi.org/10.1134/S102144371401018X

 

Zhang T, Li J, Ma F, Lu Q, Shen Z, Zhu J. Study of photosynthetic characteristics of the Pyropia yezoensis thallus during the cultivation process. J Appl Phycol. 2014;2:859–65. https://doi.org/10.1007/s10811-013-0157-6


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