Introduction

Transcriptomics-assisted gene mining approaches have been widely used for understanding the physiological implications of how an organism responds to biotic and abiotic stress conditions. Next generation sequencing (NGS) based transcriptomics has not only accelerated but has also played a key role in the identification of new functional genes across diverse species, which has been leveraged to understand the genetic basis of ecological adaptation to their surrounding environment. The origin and evolution of aquatic plants has been previously re-visited1 and with the availability of increasing transcriptomics and genomic resources, it will be more apparent to hypothesize the origin and diversification of aquatic plants1. Phylogenetically, the origin of aquatic plants dates back to the Cretaceous era (145 MYA ago)2 and shows signatures of early divergence of aquatic and terrestrial plants1. Seagrasses belong to the order of Alismatales3,4, which represent a large order of monocotyledons comprising of 13 families and 165 genera widely represented by seagrasses and freshwater aquatic species5. Seagrasses have been described as paraphyletic hydrophilus angiosperms with genera belonging to the families Cymodoceaceae, Zosteraceae and Hydrocharitaceae1,3,4. The early evolutionary divergence of seagrasses from land plants highlights their suitability as models for identifying and capturing the genes and associated pathways, which can shed evidence on the functional divergence of these species, particularly within the angiosperm lineage1. Ancestrally acquired traits of evolutionary specialization includes aerenchyma, a dynamic carbonic–carbonate system and efficient photosynthetic systems allowing them to survive in light-limited environments6. In addition, they have also exhibit morphological and physiological specific changes such as leaf structure, carbon concentrating mechanisms (CCMs), adaptation to light limitation, submergence, tolerance to high salinity and resisting wave action and tidal currents thus making them an attractive model system to study in regards to their adaptation to marine environments4,6.

Recently, whole genome sequences of Zostera marina7 and Zostera muelleri8 have provided insight into the partial loss of the ethylene pathway. Additionally, salt tolerance and reproductive mechanisms have been reviewed and subsequently revisited in recent genome7,8 and previously described transcriptional reports using a plethora of next generation sequencing technologies9,10,11,12. Nonetheless, RNA Sequencing (RNA-Seq) has been widely used as the method of choice to understand the functional and phenotypic plasticity of non-model plants including seagrasses9,13, paving the way for dissecting species adaptation to the marine environment. Transcriptomics repositories such as PhytometaSync (http://www.phytometasyn.ca) and the 1KP project (onekp.com) have been buil and made publicly available for land plants, which enabled functional gene mining, exploration of phenotypic plasticity, metabolism genes and phylogenetic inferences in land plants. However, the only available transcriptome portal in-case of marine plants is Dr. Zompo database (http://drzompo.uni-muenster.de)14, providing transcriptomic resources for two seagrasses namely Zostera marina and Posidonia oceanica respectively14. It is worth to mention that these species only exist in the Northern hemisphere14, as such, this database is limited concerning the species coverage. The lack of such resources for other seagrasses and aquatic plants, specifically phylogenetically and ecologically relevant species prompted us to develop SeagrassDB, an open access portal to disseminate the expressed gene repertoire to the marine scientific community. To the best of our knowledge, this is the first resource portal which provides large scale access to 1,052,262 unigenes representing 34,455 transcription factors, 470,568 PFAM domains, 382,528 prosite models and 482,121 InterPro domains across 8 seagrass species and 1 freshwater aquatic plant species for functional gene mining and phylogenomic exploration. SeagrassDB will serve as a resource for mining functional genes, understanding and cataloguing stress-related functional changes, as well as performing comparative transcriptomics across aquatic and land plant species.

Material and Methods

Illumina sequencing, and assembly of seagrass and aquatic plant transcriptomes

Leaf samples from 6 seagrass species Cymodocea serrulata, Halodule uninervis, Halophila ovalis, Phyllospadix iwatensis, Syringodium isoetifolium, Zostera muelleri and one aquatic species Lemna minor were collected from all around Australia. RNA was extracted from leaf samples following manufacturer’s instructions and subsequent contamination of genomic DNA was removed using the column purification step as implemented in PureLink™ DNase (Life Technologies). Quality controls of the RNA samples was done using the RNA 6000 Nano Kit Agilent (Agilent 2100 Bioanalyzer, Australia). RNA quantification was further confirmed at AGRF sequencing facility, Melbourne, Australia and only high-quality RNA with RIN number greater than 7 were subsequently sequenced using Illumina Hiseq 2000 at AGRF, Melbourne, Australia. All the sequencing data from in this study has been deposited to EBI and can be accessed under the project code: PRJEB22311 (ERP103988). Quality checking of the raw reads was done using FASTQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Based on the FASTQC reports, quality cleaning of the raw reads was done using Trimmomatic version 3.215 using 2:30:10 SLIDINGWINDOW:4:5 LEADING:5 TRAILING:5 MINLEN:50 in PE mode. Quality cleaned reads were assembled using Trinity version 216,17 with Kmer = 25 and default K-min-cov = 1. Assembled transcripts were further clustered using CD-HIT-EST18 using a word size of 8 and an identity overlap of 0.95 and non-redundant transcripts were re-assembled using the overlap-layout consensus algorithm implemented in Contig Assembly Program (CAP3)19 to obtain unigenes with the following settings; identity cut-off threshold of 95%, overlap length cut-off of 50, specific clipping range of N > 50, specific gap penalty factor of 3 and a max number of word occurrences of 100020. In case of Zostera marina, raw sequencing reads were retrieved from a previously published study with the following NCBI SRA accession number SRP03548911 and were subsequently assembled using the parameters defined above using Trinity version 216,17. For Posidonia oceanica, assembled contigs were obtained from the recent transcriptome10 and are available from NCBI under the entry GEMD01000000. In-silico expression profiling of the assembled unigenes were done using RSEM21 . FPKM has been used as a measure of the unigene expression estimates21.

Transcriptome completeness, Domain completeness, single copy orthologs and functional annotations

Assembled non-redundant unigenes were functionally assessed for transcriptome completeness using two independent approaches: (1) BUSCO22, which uses the entire embryophyte dataset, which represents the evolutionary informed near-universal single copy orthologs from OrthoDB v9 in trans mode and (2) DOGMA23, which uses a set of PFAM modeled evolutionary conserved set of protein domains. Additionally, completeness of assembled transcriptomes was assessed using 3790 single copy conserved orthologs from Arabidopsis thaliana (available from: http://compgenomics.ucdavis.edu/compositae_reference.php) using reciprocal best blast (RBH) orthology approaches. Assembled unigenes were functionally annotated by performing BLASTx searches against NCBI (www.ncbi.nlm.nih.gov), UniProt/TrEMBL (www.uniprot.org) with an E-value cutoff of 1E-5, min-identity = 50% and functional annotations were retrieved from UniProt/TrEMBL flat files available from (www.uniprot.org). Coding regions were predicted using GeneMarkST24, which employs unsupervised learning models for identifying the coding regions24. For the identification of transcription factors, curated BLASTx searches against the plant transcription factor databases available from http://planttfdb.cbi.pku.edu.cn and http://plntfdb.bio.uni-potsdam.de/v3.0/ were performed. In addition, transcription factors were also identified using plant TFcat25. KEGG based representation of unigenes was done using KEGG Mapper and KEGG (www.genome.jp/kegg/).

Development of SeagrassDB

SeagrassDB has been developed using MySQL version: 14.04.01 Distribution 5.5.54 (http://www.mysql.com/), APACHE version: 2.4.7 (http://www.apache.org/) and PHP version: 5.5.9 (http://www.php.net/) with several of the built-in functionalities coded in PHP5 for fast interaction with the user-defined queries. The present version of the SeagrassDB supports a three-tiered architecture, where the middle tier representing MySQL is effectively interacting with query-based search patterns from the client-based PHP tier. The database is hosted on National eResearch Collaboration Tools and Resources (NeCTAR) on a 64-bit virtual machine running Ubuntu version 14.04.05 with 12GB of RAM. Linux architecture is supported by a LAMP server. The portal works well with CSS3 enabled browsers including Google Chrome, Safari and Mozilla Firefox.

Results and Discussion

Climate change associated with rapid increase in global CO2 emissions is a key challenge, which needs to be evaluated for conservation of seagrass meadows and associated rates of carbon sequestration26,27,28,29. In addition, light acclimation and adaptation of seagrass species to variations in light intensities have been widely studied, which has allowed biologists to understand light adaptation in marine plants30,31,32,33. Leveraging the recent advances in the high throughput sequencing approaches, attempts have been made to address the ecological and reproductive adaption of aquatic plants using genomics and transcriptomics approaches7,8,34,35. With the recently available genome sequences of Zostera marina7 and Zostera mulleri8, attempts have been made to identify key genes linked to aquatic adaptation and their possible applications to improve crop domestication, which will subsequently allow us to develop sustainable approaches for feeding the global population of ca. 9.5 billion people by 205036.

As compared to genome sequencing approaches, transcriptomics-assisted gene discovery and candidate gene validation approaches have been widely used to unravel the species specific genetic adaptation. Rapid development in comparative genomics and transcriptomics has enabled the identification of early onset markers for physiological stress and senescence29,33,34,35. Several research groups have addressed this issue by developing open-access transcriptomics portals for land plants; however, these attempts have been limited in marine and aquatic plants, which presents a bottleneck to develop forward genetic approaches to understand the ecological speciation and genetics of marine and aquatic plants. Another potential bottleneck is the availability of the transcriptomics data under a unified browsing portal with systematic annotations, which can enable the high throughput mining of genes for a diverse number of marine and aquatic species. Taking these considerations into account, we developed SeagrassDB, which represents a unified transcriptomics portal for seagrasses and aquatic plants and provides a comprehensive resource to explore the functional gene space in seagrasses and aquatic plants as well as to explore the phylogenomics perspective and evolutionary of ancestral characters in aquatic plants and seagrasses.

Transcriptome assessment in SeagrassDB

Transcriptomics has been widely applied to study several factors affecting the seagrass distribution, which involves phylogeographic differentiation37, tissue specific transcriptomics to address reproductive biology38 and to understand abiotic response to environmental conditions39. Table 1 and Fig. 1 presents the summary statistics of the transcriptome assembly present in SeagrassDB. The number of assembled unigenes varied from 51,707 in Phyllospadix iwatensis to 293,045 in Zostera muelleri. The assembled unigenes showed an N50 value of 1,836 bp in Phyllospadix iwatensis and an N50 value of 724 bp in Halophila ovalis. Overall the observed N50 is in line with previous reports for higher plants13 and previously reported N50 values in Posidonia oceanica10 and Zostera marina11, thus providing a good representation of the assembled transcriptomes. Functional annotation using BLASTx (E-value 1E-5) based searches revealed a cumulative percentage of transcriptome annotations for Cymodocea serrulata (49.46%), Halodule uninervis (62.93%), Halophila ovalis (55.85%), Lemna minor (38.01%), Phyllospadix iwatensis (62.93%), Syringodium isoetifolium (42.14%), Zostera muelleri (41.44%), Zostera marina (59.63%) and Posidonia oceanica (49.03%) respectively, thus providing further evidence of the high coverage of the assembled transcriptomes.

Table 1 Summary statistics of transcriptomics in SeagrassDB.
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Figure 1
figure 1

Contig binning across the assembled species in SeagrassDB.

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Transcriptome completeness has been evaluated using three independent measures, including 1) BUSCO22, which uses embryophyta specific lineage conserved single copy orthologs derived from OrthoDB v9, 2) DOGMA23, which is used to access the protein domain completeness based on the presence and absence of evolutionary conserved functional domains and 3) Arabidopsis thaliana single copy orthologs. Tables 2 and 3 represent the summary statistics of BUSCO and DOGMA based transcriptome completeness. It is worth highlighting that all the species sequenced in the present study showed a high degree of completeness using single-copy BUSCO (Table 2), which is analogous to the high representation of the identified completed proteins domains as revealed by DOGMA (Table 3). Orthology reassignments indicated a set of 2402 single copy conserved orthologs across seagrass and aquatic plant species present in SeagrassDB. Figure 2 represents nested and Edwards Venn diagram based representation of the shared single copy conserved orthologs across the phylogenetically profiled aquatic plant species.

Table 2 BUSCO assessment of transcriptome completeness in SeagrassDB.
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Table 3 DOGMA based assessment of transcriptome completeness in SeagrassDB.
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Figure 2
figure 2

(a) Venn diagram using VennPainter available from https://github.com/linguoliang/VennPainter shows the shared single copy orthologs across aquatic plant species; (b) showing the shared single copy orthologs across the Cymodoceaceae, Araceae and Hydrocharitaceae; and (c) showing the shared single copy orthologs across the Zosteracea, Posidoniceae and Araceae.

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SeagrassDB: a unified platform for browsing 9 aquatic plant species

Systematic approaches for storing and visualization of transcriptomics resources for marine and aquatic plant species has been previously addressed through the development of Dr. Zompo14, which provides information for only two species, Zostera marina11 and Posidonia oceanica10. Although Dr. Zompo14 represents the data in a unified framework, it does not include other seagrass species, which have evolved over time. Additional limitations of Dr. Zompo14 include the absence of expression estimates for the assembled unigenes. Transcriptomics assisted gene discovery with the available expression estimates helps identify candidate genes accurately, where multiple in-paralogs have been predicted using homology based approaches. Previously, it has been widely shown that FPKM values of 1 represent the abundance and expression of one transcript per cell40. SeagrassDB bridges all the gaps and provides a unified platform for accessing all the associated information within the transcript assemblies present in SeagrassDB.

SeagrassDB searching and browsing patterns are given in Fig. 3, which displays the hierarchal information stored in SeagrassDB. In addition to the hierarchically stored information in SeagrassDB, we also provide a species information page (Fig. 3a) that allows the user to browse through the morphological and physiological traits of these aquatic plants. The functional annotations page allows for species selection as a first curated step, which presents the unigenes associated with the selected species and respective information such as FPKM, BLASTx hit, E-value, family, GO annotations, Interpro, Prosite and associated PFAM domains for each unigene (Fig. 3b and c). SeagrassDB provides transcriptome completeness assessments as well as the binning of unigenes according to length and the orthology searches against the single copy conserved orthologous genes in Arabidopsis thaliana (Fig. 3). While the transcriptome assemblies report in-paralogs in addition to the orthologs, the display table only shows single copy orthologs across all the species. In addition to this, BLAST enabled searches and downloads of user enabled curated queries are present (Fig. 3d and e) for down-stream analysis.

Figure 3
figure 3

Browsing SeagrassDB.

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Transcription factors and KEGG representation in SeagrassDB

Transcription factors play an important role in regulating the gene expression of plants. Apart from regulating the gene expression, their roles and diversification have been widely addressed41. Recent studies in land plants have focussed on the development of activation domains by the fusion of the designed transcription factor with proteins of interest42. Given the importance of transcription factors, identifying transcription factors is crucial to the understanding of the regulatory roles of the transcripts as identified through high-throughput sequencing approaches. Although the regulatory roles of transcription factors have been widely studied across the land plants, limited information on the role of transcription factors and their subsequent role as gene regulators is present across the aquatic plants29,33,34,35.

Transcription factor classification revealed a total of Cymodocea serrulata (3652); Halodule uninervis (3161); Halophila ovalis (3500); Lemna minor (4444); Phyllospadix iwatensis (2722); Syringodium isoetifolium (3045); Zostera muelleri (8370); Zostera marina (2524) and Posidonia oceanica (3033) transcription factors respectively. Interestingly, among the identified transcription factors, WD-40 like and C2H2 were the most abundant transcription factors across all the species (Supplementary Table 1). It is worth highlighting that the WD-40 family represents a 40 amino acid motif ending in Trp-Asp, which has been shown to play key roles in light signalling and cell development43. Furthermore, the C2H2 family of transcription factors have been previously shown to play important roles in cell development and photomorphogenesis44,45. Abundance of these transcription factor families may indicate towards their role as regulatory genes in controlling abiotic stress mediated development. Nonetheless, the availability of these annotated transcription factors will allow for a deeper understanding the functional gene space and encourage mining for seagrasses and aquatic plants.

Evolution of genes and biochemical pathways has been a prime focus to understand the metabolic divergence of species in response to environmental constraints46. Recently, it has been speculated that the evolution of specialized metabolic pathways is related to lifestyle adaptations47. We performed KEGG based mapping of unigenes to classify them to the respective pathways, revealing a total of Cymodocea serrulata (7232); Halodule uninervis (7465); Halophila ovalis (6309); Lemna minor (6474); Phyllospadix iwatensis (6702); Syringodium isoetifolium (6703); Zostera muelleri (9508); Zostera marina (6307) and Posidonia oceanica (7345) KEGG orthology (KO) terms respectively. Using transcriptomics and proteomic approaches, arrays of genes and proteins have been shown to be differentially expressed across light, temperature and ocean acidification conditions29,30,31,32,33,34,35,47. It is also worthwhile mentioning that previous estimates of accelerated evolution of seagrass genes such as those involved in photosynthetic and metabolic pathways but also in translation pathways1 are all examples of convergent evolution in seagrasses.

Applications of SeagrassDB: Case example of a salt sensitive gene from sequence, structure and phylogenetic conservation

Proton pumps play an important role in adaptation of plants to salt tolerance. Physiological significance of protons pumps has been widely elucidated across land plants including the model plant Arabidopsis thaliana. However, physiological evidence of the proton pumps has been only established in Zostera marina48. In model land plants, proton pumps play an important role in the Na+ and K+ homeostasis and also maintain the cyclic transport of ions across the plasma membrane49. The lack of resources for seagrass species till now has limited the understanding of these proton pumps in such species except for a few previous studies in Zostera marina48,49.

To demonstrate the possible applications of SeagrassDB, we performed a case study by performing a BLASTx search of the H+-ATPase, which is a proton-pump and maintains the proton-motive force across the cell membrane49. Previously, H+-ATPase has been shown to be a decisive factor for hyperosmotic stress and has been demonstrated to confer the salt tolerant ATPase activity in Zostera marina49. To compare, we used the model plant Arabidopsis thaliana H+-ATPase as a query to perform BLASTx searches against diverse species present in SeagrassDB with an E-value cutoff of 1E-5 revealing the presence of H+-ATPase across all the species. Subsequently, protein alignments were done using MSAProbs50, revealing a high degree of conservation across the domains present in H+-ATPase (Fig. 4a). To understand whether the sequence based modifications are supported by the structural models, we downloaded the structure model of H+-ATPase from PDB (5KSD)51, and mapped the conservation scores to the H+-ATPase model, which revealed overall high conservation of the H+-ATPase gene (Fig. 4b). The backbone of this model supported high conservation of residues across the structural model as revealed by Chimera available from https://www.cgl.ucsf.edu/chimera/ (Fig. 4c).

Figure 4
figure 4

(a) Shows the protein alignment of H+-ATPase; (b) and (c) shows the structural conservation of H+-ATPases across the land and aquatic plants.

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To demonstrate the importance of SeagrassDB as a source of phylogenomics in seagrass and aquatic species, we further assessed the phylogenetic ancestral tree reconstruction using RAxML version 852. Figure 5 represents the evolutionary classification of the H+ ATPase gene across the land plants and aquatic plants using Chlamydomonas reinhardtii and Osterococcus tauri as the outgroup species. For phylogenetic characters based leaf sorting, all branches showing bootstrapped data of more than 50% were retained. Interestingly, the observed protein conservation across the proton pumps revealed reliable phylogenetic placement, with all the seagrass species representing a distinct clade (Fig. 5). This observation supports the exemplified usage of transcripts and proteins models present in SeagrassDB for construction of ancestral states and also to study the protein model evolution. Transcriptomics assisted phylogenetic profiling has recently gained importance due to the unavailability of complete genomes in several of the non-model species. Illustrative examples of application of SeagrassDB from sequence-based methods to phylogenetic placement will broaden the understanding of the evolution and phylogenetic placement of marine plants.

Figure 5
figure 5

Phylogenetic resolution of H+ ATPase across the evolutionary time scale.

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Conclusion

Although functional genomics is the forefront focus in land plant research, limited studies have been performed in seagrasses due to the lack of sequence resources. Identification of regulatory genes and pathways in marine plants will not only advance the understanding of marine physiological adaptations but will also play a key role in identifying the evolutionary forces that contribute to regulate these genes and pathways, in turn addressing the rapid radiation of aquatic plants during and after the Cretaceous era. SeagrassDB has been developed with the goal to accelerate functional genomics approaches in seagrasses and aquatic plants and to obtain further information through comparative transcriptomics to understand the genes, which could be functionally transferred for crop domestication.