Transcriptome Sequencing of Essential Marine Brown and Red

Home , Coccomyxaceae, Colpomenia sinuosa, Cryptomonadaceae, Cyanophora paradoxa, Desmarestiaceae, Desmarestia viridis

Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12 DOI: 10.1007/s13131-014-0435-4 http://www.hyxb.org.cn E-mail: [email protected]

Transcriptome sequencing of essential marine brown and red algal species in China and its significance in algal biology and phylogeny WU Shuangxiu1,3†, SUN Jing1,3,4†, CHI Shan2†, WANG Liang1,3,4†, WANG Xumin1,3, LIU Cui2, LI Xingang1,3, YIN Jinlong1, LIU Tao2*, YU Jun1,3* 1 CAS Key Laboratory of Genome Sciences and Information, Beijing Key Laboratory of Genome and Precision Medicine Technologies, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China 2 College of Marine Life Science, Ocean University of China, Qingdao 266003, China 3 Beijing Key Laboratory of Functional Genomics for Dao-di Herbs, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China 4 University of Chinese Academy of Sciences, Beijing 100049, China

Received 3 April 2013; accepted 26 July 2013

©The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg 2014

Abstract Most phaeophytes (brown algae) and rhodophytes (red algae) dwell exclusively in marine habitats and play important roles in marine ecology and biodiversity. Many of these brown and red algae are also important resources for industries such as food, medicine and materials due to their unique metabolisms and metabolites. However, many fundamental questions surrounding their origins, early diversification, taxonomy, and special metabolisms remain unsolved because of poor molecular bases in brown and red algal study. As part of the 1 000 Plant Project, the marine macroalgal transcriptomes of 19 Phaeophyceae species and 21 Rhodophyta species from China's coast were sequenced, covering a total of 2 phyla, 3 classes, 11 orders, and 19 families. An average of 2 Gb per sample and a total 87.3 Gb of RNA-seq raw data were generated. Approxi- mately 15 000 to 25 000 unigenes for each brown algal sample and 5 000 to 10 000 unigenes for each red algal sample were annotated and analyzed. The annotation results showed obvious differences in gene expression and genome characteristics between red algae and brown algae; these differences could even be seen between multicellular and unicellular red algae. The results elucidate some fundamental questions about the phylogenetic taxonomy within phaeophytes and rhodophytes, and also reveal many novel metabolic pathways. These pathways include algal CO2 fixation and particular carbohydrate metabolisms, and related gene/gene family characteristics and evolution in brown and red algae. These findings build on known algal genetic information and significantly improve our understanding of algal biology, biodiversity, evolution, and potential utilization of these marine algae. Key words: Phaeophyceae, brown algae, Rhodophyta, red algae, marine macroalgae, transcriptome sequencing, secondary generation sequencing Citation: Wu Shuangxiu, Sun Jing, Chi Shan, Wang Liang, Wang Xumin, Liu Cui, Li Xingang, Yin Jinlong, Liu Tao, Yu Jun. 2014. Tran- scriptome sequencing of essential marine brown and red algal species in China and its significance in algal biology and phylogeny. Acta Oceanologica Sinica, 33(2): 1–12, doi: 10.1007/s13131-014-0435-4

1 Introduction multicellular (Grosberg and Strathmann, 2007). Algae are a highly diverse group of organisms that live in Both brown and red algae exhibit a range of different hap- a range of aquatic and terrestrial environments (Grossman, loid-diploid life cycles, house a variety of novel metabolic path- 2007). Dwelling exclusively in particular marine habitats, in- ways, and synthesize various unique chemical compounds of cluding some harsh environments, are the phaeophytes, known both ecological and commercial importance (Grossman, 2007). as brown algae belonging to Class Phaeophyceae of Phylum These marine algae serve as major carbon-fixation producers Ochrophyta, and rhodophytes, known as red algae of Phylum and play essential roles in stabilizing different marine ecosys- Rhodophyta. These organisms are morphologically diverse, tems, forming submerged forests or creating niches for a broad varying from unicells about 1 µm in diameter, such as Cyanidi- range of other marine organisms (Cock et al., 2012). As a result, oschyzon merolae (Matsuzaki et al., 2004) and Galdieria sulphu- these environmental tolerance characteristics make brown and raria (Schönknecht et al., 2013), to complex multicellular forms red algae ideal candidates for mechanism study and novel gene reaching lengths of more than 30 m, such as Macrocystis Pyrif- discovery (Misumi et al., 2008). era (Tirichine and Bowler, 2011); though, most phaeophytes are In particular, special polysaccharides, such as alginates and

Foundation item: The National Natural Science Foundation of China under contract Nos 31140070, 31271397 and 41206116; the algal transcriptome sequencing was supported by 1KP Project (www.onekp.com). *Corresponding author, E-mail: [email protected], [email protected] †Contributed equally. 2 WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12

fucoids in brown algae and agars in red algae, as well as their chiangii, which was nominated as Prionitis divaricata previous- numerous and various derivatives, are valuable resources in the ly, and genera Grateloupia and Gracilaria (Wang et al., 2001). production of antitumours, anticoagulants, solid matrices in Algal evolution study is complicated and difficult given cur- medicines, and additives for foods and cosmetics (Berteau and rently available genome data because of multiple methods of Mulloy, 2003; Drury et al., 2003; Matsubara, 2004; Grossman, gene acquisition by algae. Nuclear genomes are mosaics of 2007). Recently, red and brown algae have also attracted grow- genes acquired over long periods of time, not only by vertical ing interest as potential resources for biofuel production due to descent but also by endosymbiotic gene transfer (EGT) and their huge biomass storages (Bartsch et al., 2008). Therefore, the horizontal gene transfer (HGT) during both the primary and corresponding novel carbohydrate metabolism pathways have the secondary endosymbiosis processes (Green, 2011; Tirich- become long-term areas of focus in research. In addition, there ine and Bowler, 2011). Algal evolution study is further compli- is a long-standing debate on the existence of a C4 photosyn- cated by the dearth of existing sequenced red and brown algal thetic pathway during CO2-fixation in marine phytoplankton genomes. Within red algae, C. merolae and G. sulphuraria are (Falkowski and Raven, 1997). However, so far only a few carbo- the only unicellular species that have been sequenced, and Py- hydrate metabolism genes, such as the genes encoding GDP- ropia yezoensis and Chondrus crispus are the only multicellular mannose dehydrogenase of Ectocarpus silicuiosus (Tenhaken et species that have been sequenced. For brown algae, a compre- al., 2011) and mannuronan C-5-epimerase of Laminaria digita- hensive view of genetic characteristics was not available until ta (Nyvall et al., 2003) in the alginate biosynthesis pathway, and 2010, when the complete genome sequence of E. silicilosus, a one gene encoding the first enzyme, mannitol-1-phosphate de- small multicellular brown alga from the order Ectocarpales, hydrogenase in the mannitol biosynthesis pathway (Rousvoal was published (Cock et al., 2010). In addition, expressed se- et al., 2011), have been characterized by molecular biological quence tag (EST) libraries of G. sulphuraria (Weber et al., 2004) experiments. and RNA-seq data of Pyropia yezoensis of Rhodophyta (Liang The origin and evolution of phaeophytes and rhodophytes et al., 2010), Saccharina japonica (Deng et al., 2012), S. latis- is also a research hotspot. Rhodophytes are believed to have sima (Heinrich et al., 2012) and E. siliculosus (Dittami et al., originated from a non-photosynthetic unicellular eukaryote 2009) of Phaeophyceae were the only molecular data available engulfing a photosynthetic cyanobacterium 1.5–1.8 billion for studies in brown algae and red algae until now. Therefore, years ago (Gould et al., 2008; Kutschera and Niklas, 2005; Parker more genome information on more species is needed to solve et al., 2008). Termed the primary endosymbiosis, this event these questions. gave rise to the extant Plantae (or Archaeplastida), consisting In November 2009, a NESCent/iPlant-sponsored 1 000 Plant of three photosynthetic lineages: Glaucophyta, Rhodophyta (1KP) Analysis Workshop was held in Phoenix to initiate the 1 000 (red algae), and a collective group of Chlorophyta (green algae) Plant Transcriptome Sequencing Project (1KP Project, www. and land plants, whose chloroplasts have double layered mem- onekp.com). The project aimed to resolve relationships across branes (Simon et al., 2009). After the primary endosymbiosis, the green plant phylogeny and elucidate processes contributing a second heterotrophic eukaryote engulfed a unicellular green to diversification and biological innovations, including origins or red photosynthetic eukaryote, resulting in a variety of sec- of multicellularity, colonization of land, the evolution of vascu- ondary-endosymbiosis photosynthetic eukaryotes. These sec- lar systems, and the origins of seeds and flowers. The 1KP Proj- ondary-endosymbiosis photosynthetic eukaryotes have three ect will generate unparalleled plant sequence databases for in- or four membraned chloroplasts and include cryptophytes, vestigating the evolution of gene families, regulatory networks haptophytes, heterokonts (also known as Stramenopiles), and and biosynthetic pathways. In this program, our group provided dinoflagellates (Delwiche and Palmer, 1996; Kutschera and 21 Rhodophyta species and 19 Phaeophyceae species, with the Niklas, 2005, 2008; Baldauf, 2008). Phaeophytes are believed genome size ranging from about 107 Mb to 782 Mb (http://data. to have arisen with diatoms and golden algae (all belonging to kew.org/cvalues/CvalServlet? querytype=6), covering a total of Ochrophyta), as well as Oomycetes via the secondary endosym- 2 phyla, 3 classes, 11 orders and 19 families. All of these algae are biotic event (Reyes-Prieto et al., 2007). These organisms all be- macroalgae and represent various unique and important bio- long to heterokonts, which are characterized by the occurrence logical characteristics and commercial values; most have never of cells with two unequal flagella in their life history (Ben Ali et been subjected to large-scale gene sequencing. For each sam- al., 2001). There continues to be heated debate over the origin of ple, an average of 2 Gb of raw RNA-seq data were generated on eukaryotic algae as monophyletic or polyphyletic. the Illumina sequencing platform HiSeq 2000. Paired-end data Even within Phaeophyceae and Rhodophyta, there exists were assembled by SOAPdenovo-trans to typically yield 10 000 controversy over the taxonomic classifications of some species. scaffolds with lengths of greater than 1 kb for each sample. The For example, for brown algae, there were arguments on whether results were released on password-protected repositories at Sargassum fusiforme, which was nominated as Hizikia fusifor- Westgrid (http://206.12.25.82/1kp-data) and TACC (http://web. mis before, belongs to genus Sargassum or Hizikia (Cho et al., corral.tacc.utexas.edu/OneKP). Using these data, we annotated 2006), whether Saccharina sculpera, which was nominated as genes, classified unigene functions, analyzed pathways, and Kjellmaniella crassifolia previously, belongs to genus Sacchari- compared differences between all brown and red algal samples. na or Kjellmaniella in taxonomy (Lane et al., 2006), and what is Coupled with public algal genomic and transcriptomic data, the exact molecular evidence on phylogenetic positions of Or- further analyses for determining the origins, early diversifica- ders Ishigeales and Dictyotales (Kawai et al., 2005; Silberfeld et tion, evolution, taxonomy, special metabolisms, and genes/ al., 2010). For red algae, there were the arguments on what is the gene families of brown algae and red algae will make significant relationship between Gracilariopsis lemaneiformis and Genus contributions to our understanding of algal gene characteris- Gracilaria, which are commonly cultured together (Zhang and tics, phylogenetic evolution, important biological processes, Xia, 1992), and what is the relationship between Grateloupia and algae-based biotechnologies. WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12 3

2 Material and methods 2.2 Total algal RNA extraction The algal samples were first immersed in liquid nitrogen and 2.1 Algal sample collection ground to a fine powder using a chilled mortar and pestle. Total Algal samples were collected from field conditions along the RNA was extracted using an improved CTAB method (Li et al., coast of China during October, 2010 to March, 2012 (Table 1). 2012; Johnson et al., 2012; Yao et al., 2009; Ghangal et al., 2009; Some of these samples were sterilized with KI-I2 buffer (con- Xu et al., 2010) for brown algal samples and using an improved taining 0.15% IK, 0.05% I2, weight/volume) for 3 s, washed with Trizol method (Li et al., 2012; Johnson et al., 2012) for red algal sterile seawater, and stored in liquid nitrogen immediately samples. The quality and quantity of extracted RNA were as- for total RNA extraction. Others were taken back and cultured sessed using a Nanodrop ND 1000 spectrophotometer (Labtech in the laboratory of the Culture Collection of Seaweed in the International Ltd, Lewes, UK) and Agilent 2100 bioanalyzer (Ag- Ocean University of China, in a modified seawater medium, ilent Biotechnolgies. Santa Clara, USA). supplemented with nutrients of 4 mg/L of NaNO3 and 0.4 mg/L −2 −1 of KH2PO4 under 10°C and 30 μmol photons m s of irradi- 2.3 Transcriptome sequencing ance. cDNA library construction and sequencing were performed

Table 1. Species information of 18 brown algae and 21 red algae for transcriptome sequencing Phylum Class Order Family Species Tissue Date Ochrophyta Phaeophyceae Desmarestiales Desmarestiaceae Desmarestia viridis branches/ leaves 2012-03-20 Dictyotales Dictyotaceae Dictyopteris undulata leaves 2012-03-20 Ishigeales Ishigeaceae Ishige okamurai branches 2012-02-29 Laminariales Laminariaceae Saccharina japonica leaves 2011-04-16 Saccharina sculpera leaves 2011-07-27 Alariaceae Undaria pinnatifida leaves 2012-03-07 Chordariaceae Punctaria latifolia leaves 2012-03-20 Ectocarpales Scytosiphonaceae Colpomenia sinuosa leaves 2012-02-28 Petalonia fascia leaves 2012-03-09 Scytosiphon lomentaria leaves 2012-02-28 Scytosiphon dotyi leaves 2012-03-09 Fucales Sargassaceae Sargassum fusiforme branches/ leaves 2011-04-02 Sargassum hemiphyllum var. branches/ leaves 2011-12-13 chinense Sargassum henslowianum branches/ leaves 2011-12-13 Sargassum horneri branches/ leaves 2011-05-07 Sargassum integerrimum branches/ leaves 2011-12-13 Sargassum muticum branches/ leaves 2012-03-07 Sargassum thunbergii branches/ leaves 2011-04-16 Sargassum vachellianum branches/ leaves 2011-02-22 Rhodophyta Bangiophyceae Bangiales Bangiaceae Pyropia yezoensis leaves 2011-04-16 Florideophyceae Ceramiales Ceramiaceae Ceramium kondoi branches 2012-02-28 Dasyaceae Heterosiphonia pulchra branches 2012-03-18 Rhodomelaceae Symphyocladia latiuscul branches/ leaves 2011-08-30 Neosiphonia japonica branches/ leaves 2011-04-16 Gigartinales Dumontiaceae Dumontia simplex leaves 2012-03-18 Endocladiaceae Gloiopeltis furcata branche/ leaves 2011-04-28 Gigartinaceae Mazzaella japonica leaves 2012-03-18 Chondrus crispus leaves 2011-04-16 Phyllophoraceae Ahnfeltiopsis flabelliformis branches/ leaves 2011-08-24 Solieriaceae Eucheuma denticulatum branches 2010-10-22 Betaphycus philippinensis branches 2012-02-20 Kappaphycus alvarezii branches 2011-03-24 Gracilariales Gracilariaceae Gracilaria vermiculophylla branches 2011-04-18 Gracilaria chouae branches 2011-04-28 Gracilaria blodgettii branches 2011-07-14 Gracilariopsis lemaneiformis branches 2011-05-20 Halymeniales Halymeniaceae Grateloupia livida leaves 2011-04-18 Grateloupia turuturu leaves 2011-04-28 Grateloupia catenata branches/ leaves 2011-08-23 Grateloupia chiangii branches/ leaves 2011-04-18 4 WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12

by the BGI (Shenzhen, China) on Illumina (San Diego, USA) (Zdobnov and Apweiler, 2001). The Clusters of Orthologous HiSeq instruments in accordance with the manufacturer's in- Groups (COG) classification was performed against the COG structions. Briefly, mRNA was isolated from total RNA with Se- database (http://www.ncbi.nlm.nih.gov/COG) using BLASTX ra-mag Magnetic Oligo (dT) Beads. The mRNA with fragment (E-value<10−5) (Tatusov et al., 2003). Pathway analysis was per- buffer was sheared into short fragments of about 200 bp. Us- formed using the Kyoto Encyclopedia of Genes and Genomes ing these mRNA fragments as templates, first-strand cDNAs (KEGG) annotation service KAAS (Moriya et al., 2007). were synthesized by random hexamers-primers and reverse transcriptase. The second-strand cDNA was synthesized using 3 Results and discussion DNA polymerase I, together with RNase H and dNTPs, and was purified by QiaQuick PCR purification kit (Qiagen). The double- 3.1 Sample collecting stranded cDNA was subjected to end-repair and phosphoryla- In order to discover more expressed gene information tion using T4 DNA polymerase, Klenow DNA polymerase, and on phylogenetic evolution, essential metabolism pathways, T4 PNK. PE adapter was added to the repaired cDNA fragments and relatively important biological characteristics in spe- by T4 DNA ligase. Fragment size selection was performed using cies of brown and red algae, we collected 19 species of brown agarose gel, from which fragments of 200–250 bp were extract- algae and 21 species of red algae during their growing season ed. The selected cDNA fragments were amplified by PCR. The (Table 1). These brown algal samples covered 6 orders, Des- constructed cDNA library was sequenced by Illumina HiSeq marestiales, Dictyotales, Ishigeales, Laminariales, Ectocarpales 2000. and Fucales, and 8 families. These red algal samples covered 5 orders, Bangiales, Ceramiales, Gigartinales, Gracilariales and 2.4 De novo assembly Halymeniales, and 11 families. These species not only repre- Strict reads filtering was performed before the assembly. sented major taxonomic and biodiversity units for comprehen- Pair-end reads with primer or adaptor sequences were re- sive phylogenetic study of brown and red algae but also stood moved. Reads with more than 10% of bases below Q20 quality for significant ecologically important or commercially valuable or more than 5% of bases as unknown nucleotides (Ns) were fil- species for marine resource utilization or protection. tered from total reads. De novo assembly was carried out using SOAPdenovo-Trans (Li et al., 2010) (http://soap.genomics.org. 3.2 Transcriptome sequencing and assembly cn/SOAPdenovo-Trans.html). Gapcloser was then used for gap We sequenced approximately 2 Gb per algal sample and to- filling of the scaffolds. tal 87.3 Gb of RNA-seq raw data using the Illumina Hiseq 2000 platform. After strict reads filtering, we generated a total of 514 2.5 Transcriptome analysis million 90 bp paired-end reads with high-quality because these To identify gene expression patterns in our target species, reads had a quality value more than 20 (error rate 0.01) and ac- the BLASTX homology search was conducted against the NCBI counted for more than 97.48% bases of the whole sequences. On non-redundant (nr) protein database (of July 2012, http://www. average about 10–16 millions paired-end reads were obtained ncbi.nlm.nih.gov) with E-value less than 10-5. Functional classi- for most algal libraries, except Gracilaria blodgettii, Gratelou- fication of the unigenes' Gene Orthology (GO) (http://www.ge- pia chiangii, Symphyocladia latiuscul and Ceramium kondoi, neontology.org/) was performed by the InterProScan program whose reads numbered less than 10 million (Fig. 1).

2.0 brown algae red algae

1.5 ) 7

1.0 Number of reads (10

0.5

0.0 l i i i s a a a a a e u x m m Petalonia fascia Ishige okamura Chondrus crispus Gracilaria choua Punctaria latifolia Grateloupia livida Pyropia yezoensis Ceramium kondoi Scytosiphon dotyi Dumontia simple Sargassum horneri Gloiopeltis furcat Mazzaella japonica Desmarestia viridi Undaria pinnatifid Saccharina sculper Saccharina japonica Gracilaria blodgettii Sargassum muticum Colpomenia sinuos Grateloupia turutur Grateloupia chiangi Grateloupia catenat Sargassum fusiforme Dictyopteris undulata Sargassum thunbergii Neosiphonia japonica Kappaphycus alvarezi Heterosiphonia pulchra Scytosiphon lomentaria Eucheuma denticulatum Symphyocladia latiuscu Sargassum hemiphyllu Sargassum vachellianum Sargassum integerrimu Sargassum henslowianum Betaphycus philippinensis Gracilaria vermiculophylla Ahnfeltiopsis flabelliformis Gracilariopsis lemaneiformis

Fig.1. Statistics of paired-end reads numbers of transcriptome sequencing data of all the red and brown algal libraries. WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12 5

These clean paired-end reads were assembled into scaffolds multicellular red algal species using SOAPdenovo-trans and Gapcloser (Li et al., 2010). For red algal samples, 10 000 to 50 000 scaffolds were obtained in each 3.4 Gene ontology (GO) classification library, and N50 of each library was between 2 000 bp and 3 000 To understand the function of the unigenes we found in bp mostly. For brown algal samples, 50 000 to 100 000 scaffolds brown and red algal samples, GO assignment was applied us- were obtained and the N50 of each library ranged from 756 bp ing the Interproscan program (Zdobnov and Apweiler, 2001). to 1 709 bp (Fig. 2). Approximately 50%–70% unigenes were assigned to at least one On the whole, the assembly quality of red algal samples was GO term among all the algal libraries. These unigenes were fur- much better than that of brown algal samples. This discrepancy ther classified into functional categories in Level 2 to Level 4. might be a result of poorer RNA quality of brown algal samples In GO Level 2 (Fig. 4), the GO classifications of all libraries were due to their high contents of viscous polysaccharides (data not mostly consistent with each other, and there was no distinct dif- shown); or, particular brown algal genome characteristics could ference between brown and red algae. Unigenes that classified have lead to difficult assembly. in GO Category “biological process” were divided into 12 subcategories, while Categories “cellular component” and “molec- 3.3 Gene annotation ular function” were divided into 9 and 12 subcategories respec- To understand the expressed genes in these red and brown tively, with the percentage of unigenes over 0.01%. “Cellular algae, we annotated the transcripts after assembly by sequence process” and “metabolic process” were the largest two subcat- alignment against the databases of nr, Swissprot, and GO using egories in the “biological process” group that comprised about BLASTX. For red algal samples, approximately 5 000 to 10 000 40% unigenes. Moreover, “cell part” and “binding” were the unigenes were annotated in each library while about 15 000 to largest subcategories in the “cellular component” and “molecu- 25 000 unigenes were annotated to each brown algal sample lar function” groups, comprising 12%–20% and 47%–55% of all (Fig. 3). unigenes, respectively. Based on GO results in level 3 and level 4, The annotated unigenes in brown algal samples numbered the largest category in the “biological process” group was “cel- far more than those in red algal samples. This discrepancy could lular macromolecule metabolic process,” which is a subgroup be attributed to an existing sequenced brown algae genome for of both “cellular process” and “metabolic process”; “intracellu- E. siliculosus, which allowed for the alignment of more than lar part” and “nucleotide binding” were the largest categories in 90% of unigenes in each library. In contrast, no sequenced mul- “cellular component” and “molecular function” groups. ticellular red algal genome existed at the time of our annotation In addition, unigenes assigned to categories of “develop- blast, leading to difficulties in the annotation of marine red al- mental process,” “signaling,” and “localization” in brown algal gae transcripts. The results proved that there are obvious dif- samples numbered more than those in red algal samples, in- ferences in gene and genome characteristics between multicel- dicating potential differences in function between brown and lular and unicellular red algae, as well as between red algae and red algae. However, these unigenes consisted of less than 0.01% brown algae. Therefore, to better understand red algal genetic of all unigenes, necessitating further investigation for related characteristics, it is necessary to carry out a genomic study on genes and their expression levels, and functional effects on algal

4 000 ab average length average length median length median length n50 n50

3 000

2 000 Length/bp

1 000

0 s s e a x u m Petalonia fascia Ishige okamurai Chondrus crispus Gracilaria choua Punctaria latifolia Grateloupia livida Pyropia yezoensis Ceramium kondoi Scytosiphon dotyi Dumontia simple Sargassum horneri Gloiopeltis furcata Mazzaella japonica Desmarestia viridi Undaria pinnatifida Saccharina sculpera Saccharina japonica Gracilaria blodgettii Sargassum muticum Colpomenia sinuosa Grateloupia chiangii Grateloupia turutur Grateloupia catenat Sargassum fusiforme Dictyopteris undulata Sargassum thunbergii Neosiphonia japonica Kappaphycus alvarezii Heterosiphonia pulchra Scytosiphon lomentaria Eucheuma denticulatum Symphyocladia latiuscul Sargassum hemiphyllum Sargassum vachellianum Sargassum integerrimu Sargassum henslowianum Betaphycus philippinensis Gracilaria vermiculophylla Ahnfeltiopsis flabelliformis Gracilariopsis lemaneiformi

Fig.2. Statistics of the assembly quality of transcriptome sequencing data of all the red algal (a) and brown algal (b) libraries. 6 WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12

30 000 brown algae red algae 25 000

20 000

15 000 Number

10 000

5 000

0 l i i s s a a a a a a a x m m gii gassum horneri Petalonia fascia Ishige okamura gassum muticum Chondrus crispus Gracilaria chouae Punctaria latifoli gassum fusiforme Grateloupia livida Pyropia yezoensi Ceramium kondoi Scytosiphon dotyi gassum thunber Dumontia simple Sar Gloiopeltis furcat Mazzaella japonica Desmarestia viridis Undaria pinnatifida Saccharina sculpera Saccharina japonic Gracilaria blodgetti Sar Colpomenia sinuos Grateloupia chiangii Grateloupia turuturu Grateloupia catenata Sar gassum hemiphyllum gassum vachellianuDictyopteris undulata Sar Neosiphonia japonica gassum integerrimu gassum henslowianum Kappaphycus alvarezii Heterosiphonia pulchr Scytosiphon lomentari Eucheuma denticulatum Symphyocladia latiuscu Sar Sar Sar Sar Betaphycus philippinensi Gracilaria vermiculophyll Ahnfeltiopsis flabelliformis Gracilariopsis lemaneiformis

Fig.3. Statistics of unigene number of all the red and brown algal libraries.

1 brown algae

s red algae

0.1

0.01

0.001 Ratio of unigenes to all unigene t t t t s s s s s n ganelle binding cell par signaling or virion par membrane localization ganelle par or membrane par cellular proces receptor activity catalytic activity ganismal proces metabolic proces transporter activity antioxidant activity extracellular region biological adhesion response to stimulus biological regulation developmental proces electron carrier activity ganization or biogenesis nutrient reservoir activity macromolecular complex enzyme regulator activity membrane enclosed lumen structural molecule activity estabiishment of localizatio molecular transducer activity regulation of biological proces multicellular or protein binding transcription factor activity cellular component or nucleic acid binding transcription factor activity

Biological process Cellular component Molecular function

Fig.4. GO classification in Level 2 for all the red and brown algal samples. biological process. against the COG database, which contains 112 920 proteins from 7 eukaryotic complete genomes. Among all 25 categories 3.5 Clusters of orthologous groups (COG) classification of COG classification (Fig. 5), “translation, ribosomal structure To further confirm the function role of the unigenes we and biogenesis” (J), “posttranslational modification, protein found, COG classification was applied by sequence alignment turnover, chaperones” (O) and “general function prediction WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12 7

A: RNA processing and modification 0.14 B: Chromatin structure and dynamics brown algae C: Energy production and conversion red algae D: Cell cycle control, cell division, chromosome partitioning 0.12 E: Amino acid transport and metabolism F: Nucleotide transport and metabolism G: Carbohydrate transport and metabolism s 0.10 H: Coenzyme transport and metabolism I: Lipid transport and metabolism J: Translation, ribosomal structure and biogenesis 0.08 K: Transcription L: Replication, recombination and repair M: Cell wall/membrane/envelope biogenesis 0.06 N: Cell motility O: Posttranslational modification, protein turnover, chaperones P: Inorganic ion transport and metabolism Q: Secondary metabolites biosynthesis, transport and catabolism

Ratio of unigenes to all unigene 0.04 R: General function prediction only S: Function unknown T: Signal transduction mechanisms 0.02 U: Intracellular trafficking, secretion, and vesicular transport V: Defense mechanisms W: Extracellular structures 0.00 Y: Nuclear structure Z: Cytoskeleton

Fig.5. COG classification for all the red and brown algal samples. only” (R) were the most abundant categories in all algal librar- metabolism pathways, indicated that the active physiological ies, comprising more than 10% of unigenes. For red algal sam- process was focusing on the metabolic process, especially on ples, Category J, “translation, ribosomal structure and biogen- the carbohydrate metabolism and relative processes both for esis,” included the most genes, while for brown algal samples, brown algae and red algae in the growth season when we col- Category R, “general function prediction only” included the lected them. most genes. This discrepancy indicated that there were differences in gene characteristics or expression profiles between red 4 Discussion algae and brown algae. The high proportion of unigenes in Categeory R, “general 4.1 Contribution to algal phylogenetic study function prediction only,” for both brown algal and red algal Phylogenetic studies, particularly on ancient events of the samples indicated unknown function for numerous genes de- different origins of extant Kingdoms Plantae (or Archaeplas- spite the available annotations based on the genomes of the tida) (Simon et al., 2009) and Chromista (Cavalier-Smith, 2010), brown alga, E. siliculosus (Cock et al., 2010), and the unicellular really depended on the development of molecular bases of red alga, C. merolae (Matsuzaki et al., 2004). Therefore, further representative species. With more and more complete-ge- physiological, biochemical and molecular studies are impor- nome sequencing and EST data of model algal species released tant to reveal these gene functions. (Table 2), many fundamental questions about origins of different algal lineages, origins of multicellularity, and occurrences 3.6 KEGG pathway analysis of primary and secondary endosymbiosis have become clearer. In order to understand the high-level functions and utilities Especially, the development of high-throughput sequencing of the transcripts in biological systems, scaffolds were searched technology and reduced sequencing cost has allowed for such on the KEGG database to reconstruct the metabolic pathways phylogenetic studies on diverse groups of algae. (Fig. 6). On average, approximately 577 unigenes of red algal The first algal genome sequencing on C. merolae, a unicellu- samples and 660 unigenes of brown algal samples were assigned lar red alga that lives in the high temperatures and strongly acid- to 287 KEGG pathways, respectively. Sequence comparisons re- ic habitat, supported the hypothesis of a single primary plastid vealed a similar distribution of genes among most categories endosymbiosis of red algae and green plants by analyzing the for both algal samples. Most genes, about 37.23% for red algae Calvin cycle enzymes (Matsuzaki et al., 2004). Genomic and and 36.41% for brown algae, were assigned to the function of cDNA sequence information of Chlamydomonas reinhardtii, “metabolism”, followed by the function of “genetic information a model species of unicellular green algae, helped to advance processing”, and the group relevant to “human diseases”. The our understanding of the last common ancestor of plants and highest two numbers of scaffolds were assigned to pathways animals (Merchant et al., 2007). Phylogenetic analyses on the of “translation” in Category “genetic information processing” draft genome and transcriptome data, as well as concatenated and “carbohydrate metabolism” in Category “metabolism”, fol- multi-proteins of plastid of Cyanophora paradoxa, a “living fos- lowed by two pathways on “amino acid metabolism in Category sil” glaucophyte, showed further evidence for a single origin of ‘metabolism’ and ‘folding, sorting and degradation’ in Category Plantae plastids and also placed glaucophytes very close to the ‘genetic information processing’”. The abundance of scaffolds divergence point of red and green algae (Price et al., 2012). assigned to metabolism pathways, especially to carbohydrate Cryptophytes and chlorarachniophytes are termed as sec- 8 WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12

350 red algae A: Metabolism B: Genetic Information Processing 300 brown algae C: Environmental Information Processing D: Cellular Processes 250 E: Organismal Systems s F: Human Diseases 200

150

Number of unigene 100

0 t m m m m m m m m m Cancers Translation Cell motility Transcription Development gy metabolis Sensory system Immune system Nervous system Immune diseases Digestive system Excretory system Lipid metabolis Endocrine system Circulatory system Signal transduction Ener Membrane transpor Cell communication Cell growth and death Replication and repair Substance dependence Nucleotide metabolis Cardiovascular diseases Amino acid metabolis Infectious diseases: viral Transport and catabolis Environmental adaptation Carbohydrate metabolis Neurodegenerative diseases Infectious diseases: parasitic Infectious diseases: bacterial Folding, sorting and degradation Metabolism of other amino acids Endocrine and metabolic diseases Signaling molecules and interaction Glycan biosynthesis and metabolis Glycan biosynthesis and metabolis Metabolism of cofactors and vitamins Metabolism of terpenoids and polyketides Biosynthesis of other secondary metabolites Xenobiotics biodegradation and metabolis

ABCD EF

Fig.6. Metabolic pathway analysis on the unigenes using KEGG for all the brown and red algal samples. ondary plastid-bearing eukaryotic algae, which distinctively and Saccharina sculpera of brown algae, as well as Gracilariop- own the endosymbiont nuclei (nucleomorphs) persisting in sis lemaneiformis and Grateloupia chiangii of red algae (Sun et the cytoplasm. The nuclear genomes of the cryptophyte Guil- al., 2014; Jia et al., 2014a, b). lardia theta and the chlorarachniophyte Bigelowiella natans Moreover, such a broad range of algal transcriptome infor- were recently sequenced to investigate the pattern and process mation enabled us to do phylogenetic analyses on many impor- of host–endosymbiont integration, and the reason for the per- tant genes and gene families related to the novel and unique sistence of nucleomorphs in cryptophytes (Curtis et al., 2012). metabolic pathways of brown and red algae, such as unique So far, the genome of E. silicilosus, a model organism of brown and complex carbohydrate metabolisms, light harvesting and algae, is the largest one (approximately 214 Mb) among all se- transporting systems, special amino acid/iodine metabolisms, quenced algae, and its sequencing analysis provided important and stress adaptation systems, among others. These phyloge- clues for the emergence of multicellularity in this group (Cock netic analyses helped to distinguish between host cells, engulf- et al., 2010). However, more gene information about muticel- ing cells, or horizontal gene transformation (HGT) as origins of lular brown and red algae is needed to prove the findings about genes or pathways, and elucidated the mosaic characteristics the origin and evolution in plant kingdom. of algal genome. All these analyses will be reported in separate In this study, we selected a broad range of 19 Phaeophyceae articles in this journal. species and 21 Rhodophyta species, covering a total of 3 classes, 11 orders and 19 families. These species typically represented 4.2 Contribution to algal genetic and biological study main taxonomic units for phylogenetic studies on marine Pha- All of our selected brown and red algal species in this study eophyceae and Rhodophyta. Each algal sample yielded 2 Gb were of great ecological or commercial importance and most raw data on average; approximately 10 000 to 50 000 scaffolds were studied for the first time in this transcriptome sequencing and 5 000 to 10 000 unigenes were obtained for red algae, and study. Therefore, these transcriptome data, especially for the about 50 000 to 100 000 scaffolds and 15 000 to 25 000 unigenes unigene annotation and functional analysis on GO, COG and were obtained for brown algae (Figs 3 and 4). Based on these KEGG, definitely provided valuable information not only to dis- transcripts' assembly and annotation results, we could see clear cover genome characteristics of these marine algae, but also to differences in brown and red algal genomes or gene expres- help reveal the unique characteristics and mechanisms of ma- sion characteristics. Further using these transcriptome data for rine algae in adapting to ocean environments. nuclear-oriented, mitochondrial-oriented and plastid-oriented For example, numerous marine macroalgae, including the genes, we not only addressed phylogenetic taxonomy of pha- Ishige species, Sargassum species, Saccharina species and eophytes and rhodophytes as a whole, but also confirmed that Gracilaria species, inhabit the harsh and extreme environments of taxonomy-contentious species, such as Sargassum fusiforme of upper intertidal zones. The transctiptome analysis on I. oka- WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12 9

Table 2. Update information of publicly available algal genome sequences Genome Phylum Order Family Species Strain Reference size/Mb Cercozoa Chlorarachniales Chlorarachniaceae Bigelowiella natans CCMP2755 91.4 Curtis et al. (2012) Chlorophyta Chlamydomonadales Chlamydomonadaceae Chlamydomonas reinhardtii CC-503 105.4 Merchant et al. (2007) Chlorellales Chlorellaceae Chlorella variabilis NC64A 42.2 Blanc et al. (2010) Chlorococcales Coccomyxaceae Coccomyxa subellipsoidea c-169 48.8 Blanc et al. (2012) Mamiellales Bathycoccaceae Ostreococcus lucimarinus CCE9901 13.2 Palenik et al. (2007) Ostreococcus tauri OTH95 12.6 Derelle et al. (2002) Bathycoccus prasinos RCC1105 15 Moreau et al. (2012) CCMP1545 21.8 Mamiellaceae Micromonas pusilla Worden et al. (2009) RCC 299 21 Volvocales Volvocaceae Volvox carteri UTEX2908 125.5 Prochnik et al. (2010) Cryptophyta Cryptomonadales Cryptomonadaceae Guillardia theta CCMP2712 83.5 Curtis et al. (2012) Glaucophyta Glaucocystales Glaucocystaceae Cyanophora paradoxa CCMP329 70 Price et al. (2012) Haptophyta Isochrysidales Noëlaerhabdaceae Emiliania huxleyi CCMP1516 167.7 Read et al. (2013) Ochrophyta Ectocarpales Ectocarpaceae Ectocarpus siliculosus Ec32 214 Cock et al. (2010) Radakovits et al. Eustigmatales Monodopsidaceae Nannochloropsis gaditana CCMP526 30.4 (2012) Nannochloropsis oceanica LAMB0001 27.6 Pan et al.(2011) Naviculales Phaeodactylaceae Phaeodactylum tricornutum CCP1055/1 27.5 Bowler et al. (2008)

Pelagomonadales Pelagomonadaceae Aureococcus anophagefferens CCMP1984 50.9 Gobler et al. (2011) Armbrust et al. Thalassiosirales Thalassiosiraceae Thalassiosira pseudonana CCMP1335 32.4 (2004) Thalassiosira oceanica CCMP1005 69.4 Lommer et al. (2012) Matsuzaki et al. Rhodophyta Cyanidiales Cyanidiaceae Cyanidioschyzon merolae 10D 16.6 (2004) Schönknecht et al. Galdieriaceae Galdieria sulphuraria 074W 13.7 (2013) Nakamura et al. Bangiales Bangiaceae Pyropia yezoensis U-51 43 (2013) Gigartinales Gigartinaceae Chondrus crispus 105 Collén et al. (2013)

murae found ample kinds of Rab proteins, which were thought ral sequence fragment about 335 kb in length was found in the to play an important role in adaptating to environmental stress genome of E. silicilosus (Cock et al., 2010). We screened endog- (Bolte et al., 2000; Agarwal et al., 2008). These Rab proteins pro- enous viral elements (EVEs), the host genomic fragments origi- vided clues about how algae cope with the highly variable en- nated from viral genomes, in all publicly available algal genome vironment of the intertidal zone. In addition, numerous genes sequences and transcriptome/EST data, including the tran- for trehalose metabolism were annotated in all these sequenced scriptome data of this study, and found EVEs existing univer- transcriptomes, showing this resistance-adaptation oligosac- sally in algal genomes. Their distribution and expression char- charide widely distributed in brown and red algae (Qu et al., acteristics in different algal species are also analyzed (Wang et 2014). The phylogenetic analysis on algal trehalose-metabolism al., 2014). genes has been done and will be reported in a separate article. The most unique biological characteristics of brown and red The analysis of the gene family of heat shock protein (HSP), an algae are their special carbohydrate metabolisms and products, adaptation protein, is also ongoing. such as alginates and fucoidins of brown algal cell wall (Drury Red algal species of genus Gracilaria not only play vital roles et al., 2003; Berteau and Mulloy, 2003), and agars in red algae in the recycling and maintenance of nitrogen and phosphorus (Matsubara, 2004). These carbohydrate products are valuable balance in seawater (Huovinen et al., 2006), but also are major resources for medicines, food and material industry. In particu- resources for phycobiloprotein production as coloring mate- lar, the Saccharina species, the famous seaweed food known as rials (Dufosséa et al., 2005), fluorescent probes (Glazer, 1997), kelps, are important algal resources for the production of io- and even anti-inflammatory and anti-hyperalgesic agents (Shih dine, alginate, mannitol and fucoids (Raj and Sharma, 2003). In et al., 2009). In this study we annotated all three types of phy- this study, we analyzed transcriptome data of S. japonica and cobiloproteins in Gracilaria species and all red algal species characterized the gene structure, duplication, and phylogenetic and constructed phylogenetic trees based on phycobiloprotein evolution of the gene family (algG), which encodes alginate-c5- sequences. These analyses verify the contentious taxonomic mannuronan-epimerase and is involved in algal alginate bio- classifications among red algae and also provide valuable gene synthesis. In addition, a large number of vanadium-dependent information for the study of phycobiloprotein biosynthetic haloperoxidases (vHPO) involved in iodine metabolism (Küp- pathways (Xu et al., 2014). per et al., 1998; Butler and Carter-Franklin, 2004) were predict- In the genome study of E. silicilosus, a large integrated vi- ed by using bioinformatics analysis, which enhanced the un- 10 WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12

derstanding of biological characteristics and economic value of ride. Glycobiology, 13(6): 29R–40R this organism (Wang et al., 2014). Blanc G, Agarkova I, Grimwood J, et al. 2012. The genome of the polar For red algae in Family Solieriaceae, Betaphycus gelatinus, eukaryotic microalga Coccomyxa subellipsoidea reveals traits of cold adaptation. Genome Biol, 13(5): R39 Kappaphycus alvarezii and Eucheuma denticulatum pro- Blanc G, Duncan G, Agarkova I, et al. 2010. The Chlorella variabilis duce carrgeenans, including beta (β)-, kappa (κ)- and iota (ι)- NC64A genome reveals adaptation to photosymbiosis, coevolu- carrageenans, that are important for their uses in food and tion with viruses, and cryptic sex. Plant Cell, 22(9): 2943–2955 medicine industry (Rudolph, 2000). However, the biosynthesis Bolte S, Schiene K, Dietz K, et al. 2000. Characterization of a small pathway of carrageenan is not clear. The comparative analy- GTP-binding protein of the rab5 family in Mesembryanthemum ses of transcriptomes of three species found 30 differentially- crystallium with increased level of expression during early salt expressed KEGG orthologs related to the carbohydrate me- stress. Plant Mol Biol, 42: 923–936 Bowler C, Allen A E, Badger J H, et al. 2008. The Phaeodactylum genome tabolism, including 21 orthologs in glycolysis/gluconeogenesis reveals the evolutionary history of diatom genomes. Nature, pathway, 16 orthologs in carbon fixation of photosynthetic or- 456(7219): 239–244 ganisms, 5 orthologs of galactose metabolism and 9 orthologs Butler A, Carter-Franklin J N. 2004. The role of vanadium bromoper- in fructose and mannose metabolism, and 8 orthologs in sulfur oxidase in the biosynthesis of halogenated marine natural prod- metabolism, giving clues on the biosynthesis pathways of dif- ucts. Nat Prod Rep, 21(1): 180–188 ferent types of carrgeenans of red algae (Song et al., 2014). Cavalier-Smith T. 2010. Kingdoms Protozoa and Chromista and the eo- In KEGG analysis, we for the first time annotated the entire zoan root of the eukaryotic tree. Biol Lett, 6(3): 342–345 Cho G Y, Rousseau F, de Reviers B, et al. 2006. Phylogenetic relation- C -pathway genes in this study's transcriptome data, includ- 4 ships within the Fucales (Phaeophyceae) assessed by the photo- ing ones encoding phosphoenolpyruvate carboxylase (PEPC), system I coding psaA sequences. Phycologia, 45: 512–519 pyruvate,orthophosphate dikinase (PPDK), alanine transami- Cock J M, Arun A, Godfroy O, et al. 2012. Genomics of brown algae: cur- nase (ALT), malate dehydrogenase (MDH), malic enzyme (ME), rent advances and future prospects. Genes & Genomics, 34(1): aspartate aminotransferase (ATT), and pyruvate kinase (PK). 1–5 We also for the first time verified these genes universally dis- Cock J M, Sterck L, Rouz P, et al. 2010. The Ectocarpus genome and the tributed among all algal lineages (unpublished data). More de- independent evolution of multicellularity in brown algae. Na- ture, 465(7298): 617–621 tailed analyses on CO fixation and carbohydrate metabolism 2 Collén J, Porcel B, Carr W, et al. 2013. Genome structure and metabolic and other essential metabolism pathways among brown and features in the red seaweed Chondrus crispus shed light on evo- red algae based on these transcriptomes and biological experi- lution of the Archaeplastida. Proc Natl Acad Sci U S A, 110(13): ments are ongoing in our laboratory. 5247–5252 Curtis B A, Tanifuji G, Burki F, et al. 2012. Algal genomes reveal evolu- 5 Conclusions tionary mosaicism and the fate of nucleomorphs. Nature, 492: The analyses of transcriptome sequencing results of such 59–65 broad range of marine brown and red algae for the first time Delwiche C F, Palmer J D. 1996. Rampant horizontal transfer and du- not only helped to verify the taxonomy-contentious species of plication of rubisco genes in eubacteria and plastids. Mol Biol Evol, 13: 873–882 Phaeophyceae and Rhodophyta, and elucidate genome and Deng Yunyan, Yao Jianting, Wang Xiuliang, et al. 2012. Transcriptome metabolism characteristics of marine brown and red algae, but sequencing and comparative analysis of Saccharina japonica also provided many new insights into marine algal adaptation (Laminariales, Phaeophyceae) under blue light induction. PLoS mechanisms to seashore environments, as well as the origins One, 7(6): e39704 and evolutions of eukaryotic and multicellular algae. With the Derelle E, Ferraz C, Lagoda P, et al. 2002. DNA libraries for sequenc- increasing impact of industrial development on the changing ing the genome of Ostreococcus tauri (chlorophyta, prasino- atmospheric, aquatic, and terrestrial ecosystems, more genetic phyceae): the smallest free-living eukaryotic cell. J Phycol, 38: 1150–1156 information needs to be deeply explored in marine algae in Dittami S M, Scornet D, Petit J L, et al. 2009. Global expression analysis order to protect and utilize the vast amount of marine biore- of the brown alga Ectocarpus siliculosus (Phaeophyceae) reveals sources. large-scale reprogramming of the transcriptome in response to abiotic stress. Genome Biol, 10(6): R66 Drury J L, Dennis R G, Mooney D J. 2003. The tensile properties of algi- References nate hydrogels. Biomaterials, 25(l6): 3187–3199 Agarwal P K, Agarwal P, Jain P, et al. 2008. Constitutive overexpression of Dufosséa L, Galaupa P, Yaronb A. 2005. Microorganisms and microal- a stress-inducible small GTP-binding protein PgRab7 from Pen- gae as sources of pigments for food use: a scientific oddity or an nisetum glaucum enhances abiotic stress tolerance in transe- industrial reality. Trends in Food Science and Technology, 16: gene tabacco. Plant Cell Rep, 27: 105–115 389–406 Armbrust E V, Berges J A, Bowler C, et al. 2004. The genome of the dia- Falkowski P G, Raven J A. 1997. Aquatic Photosynthesis. Malden, MA: tom Thalassiosira pseudonana: ecology, evolution, and metabo- Blackwell Science lism. Science, 306(5693): 79–86 Ghangal R, Raghuvanshi S, Chand Sharma P, et al. 2009. Isolation of Baldauf S L. 2008. An overview of the phylogeny and diversity of eu- good quality RNA from a medicinal plant seabuckthorn, rich in karyotes. Journal of Systematics and Evolution, 46: 263–273 secondary metabolites. Plant Physiology and Biochemistry, 47: Bartsch I, Wiencke C, Bischof K, et al. 2008. The genus Laminaria sensu 1113–1115 lato: recent insights and developments. Euro J of Phycol, 43: 1–86 Glazer A N. 1997. Phycobiliproteins: A family of valuable, widely used Ben Ali A, De Baere R, Van der Auwera G, et al. 2001. Phylogenetic re- fluorophores. Scanning, 19: 154–155 lationships among algae based on complete large-subunit rRNA Gobler C J, Berry D L, Dyhrman S T, et al. 2011. Niche of harmful alga sequences. International Journal of Systematic and Evolutionary Aureococcus anophagefferens revealed through ecogenomics. Microbiology, 51: 737–749 Proc Natl Acad Sci USA, 108(11): 4352–4357 Berteau O, Mulloy B. 2003. Sulfated fucans, fresh perspectives: Struc- Gould S B, Waller R F, McFadden G I. 2008. Plastid evolution. Annu Rev tures, functions, and biological properties of sulfated fucans and Plant Biol, 59: 491–517 an overview of enzymes active toward this class of polysaccha- Green B. 2011. After the primary endosymbiosis: an update on the WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12 11

chromalveolate hypothesis and the origins of algae with Chl c. R74 Photosynth Res, 107: 103–115 Moriya Y, Itoh M, Okuda S, et al. 2007. KAAS: an automatic genome an- Grosberg R K, Strathmann R R. 2007. The evolution of multicellularity: notation and pathway reconstruction server. Nuleic Acids Res, a minor major transition? Annual Review of Ecology, Evolution, 35: W182–W185 and Systematics, 38: 621–654 Nakamura Y, Sasaki N, Kobayashi M, et al. 2013. The First Symbiont- Grossman A R. 2007. In the grip of algal genomics. Adv Exp Med Biol, Free Genome Sequence of Marine Red Alga, Susabi-nori (Py- 616: 54–76 ropia yezoensis). PLoS ONE 8(3): e57122, doi:10.1371/journal. Heinrich S, Valentin K, Frickenhaus S, et al. 2012. Transcriptomic Anal- pone.0057122 ysis of Acclimation to Temperature and Light Stress in Saccha- Nyvall P, Corre E, Boisset C, et al. 2003. Characterization of mannuro- rina latissima (Phaeophyceae). PLoS ONE, 7: e44342 nan C-5-epimerase genes from the brown alga Laminaria digi- Huovinen P, Gomez I, Lovengreen C. 2006. A five-year study of solar tata. Plant Physiol, 133(2): 726–735. ultraviolet radiation in southern Chile (39 degrees S): potential Palenik B, Grimwood J, Aerts A, et al. 2007. The tiny eukaryote Ostreo- impact on physiology of coastal marine algae? Photochemistry coccus provides genomic insights into the paradox of plankton and Photobiology, 82(2): 515–522 speciation. Proc Natl Acad Sci USA, 104(18): 7705–7710 Jia Shangang, Wang Xumin, Li Tianyong, et al. 2014a. Phylogenomic Pan Kehou, Qin Junjie, Li Si, et al. 2011. Nuclear monoploidy and analysis of transcriptomic sequences of mitochondria and chlo- asexual propagation of Nannochloropsis oceanica (Eustigmato- roplasts of essential brown algae (Phaeophyceae) in China. Acta phyceae) as revealed by its genome sequence. J Phycol, 47(6): Oceanologica Sinica, 33(2): 94–101 1425–1432 Jia Shangang, Wang Xumin, Qian Hao, et al. 2014b. Phylogenomic anal- Parker M S, Mock T, Armbrust E V. 2008. Genomic insights into marine ysis of transcriptomic sequences of mitochondria and chloro- microalgae. Annu Rev Genet, 42: 619–645 plasts for marine red algae (Rhodophyta) in China. Acta Oceano- Price D C, Chan C X, Yoon H S, et al. 2012. Cyanophora paradoxa ge- logica Sinica, 33(2): 86–93 nome elucidates origin of photosynthesis in algae and plants. Johnson M T, Carpenter E J, Tian Z, et al. 2012. Evaluating methods for Science, 335(6070): 843–847 isolating total RNA and predicting the success of sequencing Prochnik S E, Umen J, Nedelcu A M, et al. 2010. Genomic analysis of phylogenetically diverse plant transcriptomes. PLoS One, 7(11): organismal complexity in the multicellular green alga Volvox e50226 carteri. Science, 329(5988): 223–226 Kawai H, Sasaki H, Maeba S, et al. 2005. Morphology and molecular Qu Jieqiong, Wang Xumin, Chi Shan, et al. 2014. Transcriptome charac- phylogeny of Phaeostrophion irregulare (Phaeophyceae) with terization of Ishige okamurae (Phaeophyceae) shows strong en- a proposal for Phaeostrophiaceae fam. nov., and a review of vironmental acclimation. Acta Oceanologica Sinica, 33(2): 20–26 Ishigeaceae. Phycologia, 44: 169–182 Radakovits R, Jinkerson R E, Fuerstenberg S I, et al. 2012. Draft genome Küpper F C, Schweigert N, Ar Gall E, et al. 1998. Iodine uptake in Lami- sequence and genetic transformation of the oleaginous alga nariales involves extracellular, haloperoxidase-mediated oxida- Nannochloropis gaditana. Nat Commun, 3: 686–695 tion of iodide. Planta, 207(2): 163–171 Raj N K, Sharma C P. 2003. Oral insulin—a perspective. J Biomater Appl, Kutschera U, Niklas K J. 2005. Endosymbiosis, cell evolution and spe- 17(3): 183–196 ciation. Theory Biosci, 124: 1–24 Read B A, Kegel J, Klute M J, et al. 2013. Pan genome of the phyto- Kutschera U, Niklas K J. 2008. Macroevolution via secondary endosym- plankton Emiliania underpins its global distribution. Nature, biosis: a Neo-Goldschmidtian view of unicellular hopeful mon- 499(7457): 209–213 sters and Darwin's primordial intermediate form. Theory Biosci, Reyes-Prieto A, Weber A P, Bhattacharya D. 2007. The origin and es- 127: 277–289 tablishment of the plastid in algae and plants. Annual Review of Lane C E, Mayes C, Druehl L D, et al. 2006. A multi-gene molecular in- Genetics, 41: 147–168 vestigation of the kelp (Laminariales, Phaeophyceae) supports Rousvoal S, Groisillier A, Dittami S M, et al. 2011. Mannitol-1-phos- substantial taxonomic re-organization. Journal of Phycology, 42: phate dehydrogenase activity in Ectocarpus siliculosus, a key 493–512 role for mannitol synthesis in brown algae. Planta, 233: 261–273 Li Tianyong, Ren Lei, Zhou Guan, et al. 2012. A suitable method for Rudolph B. 2000. Seaweed products: red algae of economic signifi- extracting total RNA from red algae. Transactions of Oceanology cance. In: Martin R E, Carter E P, Davis L M, et al., eds. Marine and Limnology (in Chinese), 4: 64–71 and Freshwater Products Handbook. Lancarster, UK: Technomic Li Ruiqiang, Zhu Hongmei, Ruan Jue, et al. 2010. De novo assembly of Publishing Co, 515–529 human genomes with massively parallel short read sequencing. Schönknecht G, Chen W H, Temes C M, et al. 2013. Gene transfer from Genome Research, 20: 265-272 bacteria and archaea facilitated evolution of an extremophilic Liang Chengwei, Zhang Xiaowen, Zou Jian, et al. 2010. Identification of eukaryote. Science, 339: 1207–1210 miRNA from Porphyra yezoensis by high-throughput sequencing Shih C M, Cheng S N, Wong C S, et al. 2009. Antiinflammatory and anti- and bioinformatics analysis. PLoS One, 5(5): e10698 hyperalgesic activity of C-phycocyanin. Anesthesia and Analge- Lommer M, Specht M, Roy A S, et al. 2012. Genome and low-iron re- sia, 108(4): 1303–1310 sponse of an oceanic diatom adapted to chronic iron limitation. Silberfeld T, Leigh J W, Verbruggen H, et al. 2010. A multi-locus time-cal- Genome Biol, 13(7): R66 ibrated phylogeny of the brown algae (Heterokonta, Ochrophy- Matsubara K. 2004. Recent advances in marine algal anticoagulants. ta, Phaeophyceae): Investigating the evolutionary nature of the Curr Med Chem Cardiovasc Hematol Agents, 2(1): 13–19 “brown algal crown radiation. Molecular Phylogenetics and Evo- Matsuzaki M, Misumi O, Shin-I T, et al. 2004. Genome sequence of the lution, 56: 659–674 ultrasmall unicellular red alga Cyanidioschyzon merolae 10D. Simon N, Cras A L, Foulon E, et al. 2009. Diversity and evolution of ma- Nature, 428(6983): 653–657 rine phytoplankton. C R Biol, 332: 159–170 Merchant S S, Prochnik S E, Vallon O, et al. 2007. The Chlamydomonas Song Lipu, Wu Shuangxiu, Sun Jing, et al., 2014. De novo sequencing genome reveals the evolution of key animal and plant functions. and comparative analysis of three red algal species of Family So- Science, 318: 245–250 lieriaceae to discover putative genes associated with carrageen- Misumi O, Yoshida Y, Nishida K, et al. 2008. Genome analysis and its an biosysthesis. Acta Oceanologica Sinica, 33(2): 45–53 significance in four unicellular algae, Cyanidioschyzon [correct- Sun Jing, Wang Liang, Wu Shuangxiu, et al. 2014. Transcriptome-wide ed] merolae, Ostreococcus tauri, Chlamydomonas reinhardtii, evolutionary analysis on essential brown algae (Phaeophyceae) and Thalassiosira pseudonana. J Plant Res, 121(1): 3–17 in China. Acta Oceanologica Sinica, 33(2): 13–19 Moreau H, Verhelst B, Couloux A, et al. 2012. Gene functionalities and Tatusov R L, Fedorova N D, Jackson J D, et al. 2003. The COG database: genome structure in Bathycoccus prasinos reflect cellular spe- an updated version includes eukaryotes. BMC Bioinformatics, 4: cializations at the base of the green lineage. Genome Biology, 13: 41 12 WU Shuangxiu et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 2, P. 1–12

Tenhaken R, Voglas E, Cock J M, et al. 2011. Characterization of GDP- bon export from rhodoplasts. Plant Mol Biol, 55: 17–32 mannose dehydrogenase from the brown alga Ectocarpus si- Worden A Z, Lee J H, Mock T, et al. 2009. Green evolution and dynamic liculosus providing the precursor for the alginate polymer. J Biol adaptations revealed by genomes of the marine picoeukaryotes Chem, 286(19): 16707–16715 Micromonas. Science, 324(5924): 268–272 Tirichine L, Bowler C. 2011. Decoding algal genomes: tracing back the Xu Jia, Aileni M, Abbagani S, et al. 2010. A reliable and efficient method history of photosynthetic life on Earth. Plant J, 66(1): 45–57 for total RNA isolation from various members of spurge family Wang Hongwei, Kawaguchi S, Horiguchi T, et al. 2001. A morphologi- (Euphorbiaceae). Phytochemical Analysis, 21: 395–398 cal and molecular assessment of the genus Prionitis J. Agardh Xu Jiayue, Sun Jing, Yin Jinlong, et al. 2014. Comparative analysis of (Halymeniaceae, Rhodophyta). Phycological Research, 49(3): four essential Gracilariaceae species in China based on whole 251–261 transcriptomic sequencing. Acta Oceanologica Sinica, 33(2): Wang Ren, Wang Xumin, Zhang Yalan, et al. 2014. Origin and evolution 54–62 of alginate-c5-mannuronan-epimerase gene based on transcrip- Yao Jianting, Fu Wandong, Wang Xiuliang. 2009. Improved RNA iso- tomic analysis of brown algae. Acta Oceanologica Sinica, 33(2): lation from Laminaria japonica Aresch (Laminariaceae, Pha- 73–85 eophyta). Appl Phycol, 21: 233–238 Wang Liang, Wu Shuangxiu, Liu Tao, et al. 2014 Endogenous Viral Ele- Zdobnov E M, Apweiler R. 2001. InterProScan—an integration platform ments in Algal Genomes. Acta Oceanologica Sinica, 33(2): 102– for the signature-recognition methods in InterPro. Bioinformat- 107 ics, 17(9): 847–848 Weber A P M, Oesterhelt C, Gross W, et al. 2004. EST-analysis of the Zhang Junfu, Xia Bangmei. 1992. Studies on two new Gracilaria from thermo-acidophilic red microalga Galdieria sulphuraria reveals South China and a summary of Gracilaria species in China. Tax- potential for lipid A biosynthesis and unveils the pathway of car- onomy of Economic Seaweeds, 3: 195–206