Next Article in Journal
Culture Collections as Hidden Sources of Microbial Biomolecules and Biodiversity
Previous Article in Journal
Is the Distribution of Two Rare Orchis Sister Species Limited by Their Main Mycobiont?
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diversity
Volume 12
Issue 7
10.3390/d12070263
diversity-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Importance of Genomics for Deciphering the Invasion Success of the Seagrass Halophila stipulacea in the Changing Mediterranean Sea

by
Alexandros Tsakogiannis
1,
Tereza Manousaki
1,
Vasileia Anagnostopoulou
2,
Melanthia Stavroulaki
1 and
Eugenia T. Apostolaki
2,*
1
Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, PO Box 2214, 71003 Heraklion, Greece
2
Institute of Oceanography, Hellenic Centre for Marine Research, PO Box 2214, 71003 Heraklion, Greece
*
Author to whom correspondence should be addressed.
Diversity 2020, 12(7), 263; https://doi.org/10.3390/d12070263
Submission received: 27 April 2020 / Revised: 24 June 2020 / Accepted: 24 June 2020 / Published: 30 June 2020
(This article belongs to the Section Marine Diversity)
Browse Figures
Versions Notes

Abstract

:
The Mediterranean Sea is subject to pressures from biological invasion due to coastal anthropic activities and global warming, which potentially modify its biogeography. The Red Sea tropical seagrass Halophila stipulacea entered the Eastern Mediterranean over a century ago, and its occurrence is expanding towards the northwest. Here, we highlight the importance of genomics for deciphering the evolutionary and ecological procedures taking place during the invasion process of H. stipulacea and review the relatively sparse genetic information available for the species to date. We report the first draft whole-genome sequencing of a H. stipulacea individual from Greece, based on Illumina Sequencing technology. A comparison of the Internal Transcribed Spacer (ITS) regions revealed a high divergence of the herein sequenced individual compared to Mediterranean populations sequenced two decades ago, rendering further questions on the evolutionary processes taking place during H. stipulacea adaptation in the invaded Mediterranean Sea. Our work sets the baseline for a future analysis of the invasion genomic of the focal species.

1. Introduction

Biological invasion is a major force of altering marine ecosystems [1], as anthropic activity and climate change redistribute diversity outside their native biogeographical range [2]. The Mediterranean Sea has become a hot spot of non-indigenous species of tropical origin due to the Suez Canal opening, along with increased maritime traffic and aquaculture activities [3]. At the same time, the resemblance of the thermal conditions in the Mediterranean to the natural ranges of tropical species facilitates the expansion and establishment of tropical species in the region [4]. Furthermore, the Mediterranean Sea, particularly the Eastern part of the basin, are warming up, suggesting that the performance and competitive capacity of tropical species may be enhanced in the future Mediterranean Sea contrary to that of their native counterparts, which appear to be detrimentally affected by warming [5].
Halophila stipulacea (Forsskål) Ascherson 1867 is a tropical seagrass species (native to the Red Sea and Indian Ocean) that entered the Mediterranean Sea following the opening of the Suez Canal in 1869. At present, the species occupies the Eastern and Central Mediterranean, but preliminary estimations show that it will be able to expand throughout the Mediterranean during the next 100 years [6]. Species traits that facilitate the successful invasion of H. stipulacea include its ability to extend over a wide range of depth (0–50 m), salinity, and light intensity (35–400 μmol photons m−2 s−1) [7]. Additional factors that enhance the possibility of the establishment of H. stipulacea are that the species is characterized by rapid clonal growth [8], a high dispersal potential of vegetative fragments [9], and sexual reproduction outside its native range ([10,11,12] and Crete and Amorgos Islands, Greece; E. Apostolaki pers. obs.). H. stipulacea also exhibits a high tolerance [13] and resilience to perturbations [14], with a high capacity to recover [15], which enhance the species’ fitness. Lastly, recent experimentation revealed the displacement of the thermal niche of exotic populations towards the colder Mediterranean Sea regime [16], indicating that temperature, which is the main parameter that determines the geographical distribution of marine plants, particularly tropical species in the Mediterranean [17], does not seem to constitute a barrier for the species to expand towards the colder Western Mediterranean.
H. stipulacea in the Mediterranean usually occupies bare sediments void of native macrophytes, while it occasionally creates mixed meadows with the native seagrass Cymodocea nodosa and grows to the edges of the endemic Posidonia oceanica meadows or above dead P. oceanica mats. Although it entered the Eastern Mediterranean over a century ago (first record in 1894), there has not been any evidence of competition with the native seagrass until very recently [18]. However, the replacement of C. nodosa by H. stipulacea has been reported in Tunisia [19] and was attributed to the degradation of C. nodosa meadows as a result of eutrophication. In addition, its introduction to the Caribbean Sea resulted in H. stipulacea outcompeting the natives (Thalassia testudinum and Syringodium filiforme) when the nutrient availability was elevated [20,21]. As the invasion success is probably related to the vulnerability of the native recipient meadows, it is possible that the current regression of native seagrass in the Mediterranean basin [22] could facilitate the progression of H. stipulacea even further, raising concerns.
Understanding the mechanisms that govern the invasion success of H. stipulacea is crucial for addressing the change in seagrass biogeography of the Mediterranean. Genome-wide analysis could help reveal the traits that make H. stipulacea tolerant and resilient, allowing its rapid geographical dispersion. High throughput sequencing and bioinformatic technologies have transformed modern Biology, uncovering particular genetic responses to environmental factors. However, only with the unprecedented resolution offered by the developments of the ‘genomics era’ has this been realized [23]. Genome-wide analyses allow samples to be scanned for selectively important variation and evaluations of the adaptive potential of populations [24]. Invasion genomics have led to discoveries related to the cryptic diversity, route of invasion, and number of introductions [25]. Although implementing techniques that do not rely on the presence of a reference genome, such as genotyping-by-sequencing [26], RAD-Seq [27], reduced representation sequencing [28], amplicon sequencing [29], or transcriptome sequencing [30], can help answer a broad spectrum of questions, they present innumerable possibilities when utilized together with whole-genome data. It is well-established that the availability of a reference genome sets the ground for understanding the shared and unique biological traits of each species, allowing studies on genetics, evolution, ecology, and life history traits. A complete genome sequence is key to revealing recent population histories [31] and selection signatures [32].
The first complete genome sequence of a plant species was that of the model plant Arabidopsis (Arabidopsis thaliana) [33], followed two years later by the rice (Oryza sativa) genome [34]. Whole-genome sequencing of many species of plants has been carried out since then and only very recently attention has been paid to aquatic plant genome sequencing [35,36,37,38]. Whole-genome sequencing has been successfully applied to seagrass species, leading to the construction of important datasets, such as the sequencing and study of the Zostera marina [39] and Z. muelleri [40] genomes, which revealed how the gene content reflects the adaptation of seagrasses to the marine environment through gene gains and losses. More targeted studies have been applied at transcriptome, proteome, and metabolome levels in P. oceanica and C. nodosa [40,41,42,43,44,45,46]. These studies have laid the foundations for understanding the physiological and evolutionary processes of seagrass responses to global change. Nonetheless, and despite the expansion of H. stipulacea, to our knowledge, no relevant information on H. stipulacea genome is currently available.
Here, we aim to review the genetic information available for H. stipulacea and provide the first draft whole-genome assembly of the species, offering the seagrass community a tool that will enhance H. stipulacea research at the genomics level. Most importantly, it will offer the possibility to study the invasion genomics of the species through the application of further genomic tools (e.g., RAD-Seq technologies) which substantially benefit from the availability of reference genomes. Such experiments will unveil the population structure of invasive versus source populations and will allow researchers to search for candidate loci responsible for the invasion success and adaptation to the new environment.

2. Methods

2.1. Literature Survey

To get an overview of the research interest on the genetics of our focal species, we performed a literature review of studies related to seagrass genomics and/or genetics using the Web of Science search engine and the search terms “seagrass” AND “genetic” OR “genomic”. We took into account all relevant publications published until February 2020. The search produced a total of 347 results.

2.2. Genomic Analysis

2.2.1. Sampling

Divers collected H. stipulacea shoots by hand on 29/5/2019 at a depth of 20 m from Crete, Greece (Hersonissos, 35°18′53.74″N, 25°25′7.23″E). The shoots were transferred to the laboratory in seawater immediately after sampling and were gently cleaned to remove debris and epiphytes. A single fragment of H. stipulacea bearing five shoots that did not have any signs of degradation was selected for further preparation. Extra care was taken to only select green leaves and rhizomes (no roots). The tissues were immersed in RNAlaterTM Stabilization Solution, incubated for 48 h at 4 °C, and then stored at −80 °C until DNA extraction.

2.2.2. DNA Extraction, Library Preparation, and Sequencing

High molecular weight DNA was extracted using a modified protocol of the CTAB chloroform/isoamyl alcohol (24:1) isolation method, followed by post-extraction RNase treatment (Ambion® RNase Cocktail™, ThermoFisher Scientific, 27 Forge Parkway, Franklin, MA, USA) [39,47,48,49] and cleaning with ProNex-beads technology (ProNex® Size-Selective Purification System, Promega Corporation 2800 Woods Hollow Road Madison, WI, USA), allowing us to eliminate any RNA traces and enzyme traces, improve the purity, and size select for next generation whole-genome sequencing. The final elution was made with 50 μL EB Qiagen’s® buffer (Tris-EDTA pH = 8.5) providing 1980 μg of high molecular weight DNA with extra purity (39.6 ng/μL of DNA measured in s Qubit™ 4 Fluorometer (ThermoFisher Scientific, 27 Forge Parkway, Franklin, MA, USA) using the BR dsDNA kit and purity rates measured with Nanodrop: 260/280 = 1.82 and 260/230 = 2.13).
The DNA integrity was assessed by electrophoresis in 0.4% w/v megabase agarose gel. Template DNA for Illumina sequencing was sheared by ultrasonication by employing a Covaris instrument. A PCR-free library was prepared with the Kapa Hyper Prep DNA kit with TruSeq Unique Dual Indexing. Paired end 2 × 150 bp sequencing was performed at the Norwegian Sequencing Centre (NSC) on an Illumina Hiseq4000 platform.

2.2.3. Bioinformatic Analyses

All raw sequences have been uploaded to the NCBI SRA database (BioProject ID: PRJNA642709). The quality of the Illumina Sequencing reads was assessed using FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Then, to remove low-quality reads and adapters and trim low-quality read edges, we used fastp v0.19.10 (https://github.com/OpenGene/fastp) with the parameters ‘--detect_adapter_for_pe -w 20 -l 140 -q 25 -u 20 -y -c’. The high-quality reads that passed the filtering criteria were used for downstream analyses. To evaluate the level of contamination of the sequenced reads, we used kraken2 [50] against the precompiled database 16S_Silva138_20200326.
Prior to assembly, we estimated the H. stipulacea genome size using kmergenie (http://kmergenie.bx.psu.edu/). Then, we input the quality-filtered reads in Spades v3.13.0 [51] to build the genome assembly. The produced assembly was assessed in terms of contiguity using QUAST [52] and quality with BUSCO v3 [53] using the database odb10. BUSCO assesses the presence of key genes in a taxonomically-informed manner. For our focal species, we searched the produced assembly against the viridiplantae geneset. The resulting assembly has been uploaded in the NCBI (BioProject ID: PRJNA642712).
Finally, to see how the sequenced individual compared to other H. stipulacea individuals, we downloaded all available H. stipulacea ITS sequences from the NCBI (see Supplementary File 1 for the list). The complete sequences were kept and used for a blast search against the H. stipulacea genome, with the aim of identifying the homologous sequence. All the different queries returned one contig as the best hit, which included the ITS of the sequenced individual. The top hit contig was combined with all downloaded sequences and aligned with mafft (--auto) [54]. The aligned sequence was manually curated in Jalview2 [55] (see Supplementary File 2 for the alignment). Then, the alignment was used for phylogenetic analysis in RaxML (model GTRCAT) using 100 bootstraps for branch support [56].

3. Results and Discussion

3.1. Research Interest on H. stipulacea Genetics

Although the need for the application of genomic techniques to seagrasses was recognized early enough, it still lags behind compared to other taxa, as important challenges emerge at multiple levels during the application of such technologies, e.g., tissue sampling, the application of wet lab techniques, and bioinformatic analyses. For H. stipulacea in particular, research interest on molecular profiling is limited compared to other seagrass species (Figure 1). It appears that there is no information on H. stipulacea genome, and even any genetic information is extremely limited [57,58,59,60], despite the increase in the total research effort for this species shown above.
The existing studies mostly account for genetic diversification of the species using a single locus or a few multi-locus markers. Although undoubtedly important, such analyses cannot infer population genetic parameters at a deeper level, and cannot precisely address the origin of invasions or whether the introduction occurred once or multiple times. The comparison of ribosomal ITS regions between Red Sea and Mediterranean populations by [59] proposed that the studied invading populations originated from the Red Sea; a deduction based on the absence of differentiation among these populations for the ITS region, where as they underlined, phylogenetic analyses when using this ribosomal region, must be taken with caution. Moreover, results of the same study showed that there was a high degree of intra-individual variability for this DNA region, whilst [58] found no ITS intra-individual nucleotide diversity for an East-Aegean population. On the other hand, an analysis of the first extensive population recorded in the western part of the basin with randomly amplified polymorphic DNA (RAPD) markers showed a high genetic diversity and clear genetic difference between shallow and deep stands of the same population [57]. Using RAPD, [60] were able to confirm the molecular identity of El-Bardawil lake isolates of Halophila stipulacea and also verified the absence of intra-individual variability for the ITS region considered among the isolates from Turkey [58]. A recent comparative study on karyotypes across Halophila sp. [61] excludes the possibility of polyploidy being the factor for the observed intra-individual variability reported by [59], and revealed that our focal species has a relatively smaller 2C value (<10 pg) compared to other Halophila species [61]. These findings make the genome sequencing of H. stipulacea a much more feasible target compared to some other Halophila species (H. decipiens and H. spinulosa also have small genomes). The availability of the H. stipulacea genome is of extreme importance as it would enable scanning for genes related to H. stipulacea plasticity and invasiveness; assist with transcriptomic analyses; and also assist with the development of more polymorphic and reliable markers that span across the genome and thus with tracking, with a greater precision, the origin of invasions.

3.2. The First Draft Reference Genome of H. Stipulacea

Our sequencing effort yielded ~626 million reads in total, summing ~94.5 Gbases. Quality control led to the elimination of 77% of the raw dataset, maintaining 482 million high-quality reads summing up to ~72 Gb. The filtered dataset was used for the genome size estimation, which resulted in a kmer of 43 and a genome size of 3.4 Gb. Based on the genome size estimation, we also calculated that the genomic coverage of our sequencing effort was ~21X. Then, a draft genome assembly was built and assessed (see Table 1 for basic assembly statistics). The assembly covered 3.7 Gb overall, and scored 48.8% complete and 19.5% fragmented BUSCO genes, summing up to 68.3% discovered genes (294 genes out of 430 tested). A search for contaminants showed a low percentage of sequence contamination (0.71% overall), with top contaminant sequences coming from Archaeplastida (including green and red algae and terrestrial plants) and Cyanobacteria (see Supplementary File 3 for a complete list). Our genome assembly (3.4 Gb) is highly comparable to the estimated genome size (3.6 Gb) of the congeneric H. ovalis [62] (i.e., the same tool for genome estimation was used in both studies), which suggests a rather large genome for all Halophila species, but a slightly smaller genome size for H. stipulacea compared to H. ovalis, as also found in a karyotypic study [61]. The resulting draft genome assembly is close to our genome size estimation, confirming that H. stipulacea has a much larger genome compared to Z. marina, with a genome assembly of ~200 Mb and BUSCO results of 93.9% complete and 1.9% fragmented.
Based on the BUSCO results, it appears that we have captured at least ~70% of the H. stipulacea genome using solely short reads. This outcome is rather satisfying given the difficulties characterizing the Halophila genomes, which are mainly reflected by their genome size and organization; factors that are most probably correlated with the number of repetitive sequences [63,64], such as “low-complexity” sequences [65], and transposable elements [66]. These genomic elements are considered as key contributors to the eukaryotic genome structure and in many plants, their abundance can be up to 90% of their genome sequence [63,67]. Bioinformatic data analysis in seagrasses, like in many plants, is usually complicated and more time- and resource-consuming relative to animal genomic analysis. The major factors influencing the success of building a genomic reference for seagrasses and plants in general are the often larger genome size (e.g., the sugar pine Pinus lambertiana 31Gb genome [68]), the genomic complexity (e.g., the rice genome [69]), and the possibility for polyploidy (e.g., strawberry genome [70]). Efforts to sequence the genome of H. ovalis have taken place [62], but this remains the first successfully assembled genome for the genus of Halophila. However, the current assembly can be improved through two possible avenues: either by increasing the sequencing effort to reach the genomic coverage obtained by studies sequencing smaller seagrass genomes (e.g., the Z. marina genome was sequenced at a coverage of ~50x [39]) or by using the long reads provided by third-generation sequencing platforms, such as Oxford Nanopore and Pacific Biosciences. The latter option ensures the contiguity and quality of the assembly, as confirmed by other studies combining the two technologies from other species of interest (e.g., [71,72]), even though it has not yet been applied to seagrasses. However, we expect that with the future use of long reads, the contiguity and quality of the assembly will be improved, reaching the level of the first published seagrass genome, that of Z. marina.
To see how the sequenced individual relates to other H. stipulacea individuals, we compared the ITS sequence of the genome with complete sequences available in NCBI from the study of [59]. The resulting phylogenetic tree showed a remarkably high divergence of the sequenced individual compared to all other sequences from Greece, Italy, and Egypt (see Figure 2). Although the topology clustered the sequenced H. stipulacea individual with an individual from Egypt and another from Italy, the clustering was not supported by bootstrap values (all <10). The extreme divergence observed in the sequenced ITS region resembles the regions described as pseudogenes by [59], characterized by large branch lengths reflecting faster evolutionary rates of the duplicated ITS regions. Other such sequences with longer branches are included in Figure 2. The presence of duplicated ITS regions leads to the relaxation of selective pressures acting on the duplicated sequences, which then evolve at a faster rate. This hampers the phylogenetic positioning of species when using duplicated markers. Therefore, the conducted analysis could not resolve the relationship between the newly sequenced individual and other sequenced haplotypes. However, this divergence, including tandem duplications and possible pseudogenization [59], needs to be further studied by sampling multiple individuals from multiple populations and conducting a thorough population genomic analysis.
In this study, we managed to build the first draft assembly of H. stipulacea. The next step would be to predict the gene models using transcriptomic data and then compare the protein-coding sequences to those of other seagrasses and terrestrial plants. Such study will allow a comparison of the gene content among the sequenced seagrasses and will deepen our understanding of the pathways that have been secondarily lost during the transition to the sea (e.g., stomatal genes), as described in detail in [39] and further illustrated through including Z. muelleri, H. ovalis, and five non-marine plant species in the comparison [62]. Finally, it may lead to the identification of large-scale duplications that will inform us about past whole-genome duplication events (see the Ks-based age distributions analysis in [39]) and will highlight genes with a selective pressure and possible functions linked not only to the adaptation to seawater, but also to the response to climate change.

4. Closing Remarks

Although our literature search reflected the response of the seagrass community to the ‘genomics age’, only a few seagrass genomes have previously been sequenced. Inspired by the ecological importance of the focal invasive species, we managed to provide the first draft whole-genome assembly. Although all Halophila genomes are remarkably large, it is still feasible to sequence them using only short reads. However, the addition of third-generation sequencing long reads will assist in refining the assembly. Here, we have offered the backbone that will unleash multiple downstream genomic analyses needed not only for understanding the complex evolutionary and ecological procedures taking place during the invasion process of H. stipulacea, but also the genomic changes linked to climate change.

Supplementary Materials

The following are available online at https://www.mdpi.com/1424-2818/12/7/263/s1.

Author Contributions

T.M. and E.A. conceived the study. A.T., V.A., and M.S. performed the laboratory work. T.M. performed the bioinformatic analysis. A.T., T.M., and E.T.A. wrote the paper and all authors approved the final manuscript. E.T.A. acquired funding. All authors have read and agreed to the published version of the manuscript.

Funding

This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme ‘Human Resources Development, Education and Lifelong Learning 2014–2020’ in the context of the project ‘I-ADAPT’ (MIS 5006611).

Acknowledgments

We thank Giorgos Chatzigeorgiou and Theodoros Danis for helping in the field and lab and Costas Tsigenopoulos and Thanos Dailianis for providing expertise and stimulating discussions. We acknowledge constructive criticism from the reviewers.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Simberloff, D.; Martin, J.-L.; Genovesi, P.; Maris, V.; Wardle, D.A.; Aronson, J.; Courchamp, F.; Galil, B.; García-Berthou, E.; Pascal, M.; et al. Impacts of biological invasions: What’s what and the way forward. Trends Ecol. Evol. 2013, 28, 58–66. [Google Scholar] [CrossRef] [Green Version]
  2. Pecl, G.T.; Araújo, M.B.; Bell, J.D.; Blanchard, J.; Bonebrake, T.C.; Chen, I.-C.; Clark, T.D.; Colwell, R.K.; Danielsen, F.; Evengård, B.; et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science 2017, 355, eaai9214. [Google Scholar] [CrossRef] [PubMed]
  3. Zenetos, A.; Çinar, M.E.; Crocetta, F.; Golani, D.; Rosso, A.; Servello, G.; Shenkar, N.; Turon, X.; Verlaque, M. Uncertainties and validation of alien species catalogues: The Mediterranean as an example. Estuar. Coast. Shelf Sci. 2017, 191, 171–187. [Google Scholar] [CrossRef]
  4. Bates, A.E.; McKelvie, C.M.; Sorte, C.J.B.; Morley, S.A.; Jones, N.A.R.; Mondon, J.A.; Bird, T.J.; Quinn, G. Geographical range, heat tolerance and invasion success in aquatic species. PLoS ONE 2013, 280, 20131958. [Google Scholar] [CrossRef] [Green Version]
  5. Marbà, N.; Jordà, G.; Agustí, S.; Girard, C.; Duarte, C.M. Footprints of climate change on Mediterranean Sea biota. Front. Mar. Sci. 2015, 2, 56. [Google Scholar] [CrossRef]
  6. Georgiou, D.; Alexandre, A.; Luis, J.; Santos, R. Temperature is not a limiting factor for the expansion of Halophila stipulacea throughout the Mediterranean Sea. Mar. Ecol. Prog. Ser. 2016, 544, 159–167. [Google Scholar] [CrossRef]
  7. Sharon, Y.; Levitan, O.; Spungin, D.; Berman-Frank, I.; Beer, S. Photoacclimation of the seagrass Halophila stipulacea to the dim irradiance at its 48-meter depth limit. Limnol. Oceanogr. 2011, 56, 357–362. [Google Scholar] [CrossRef]
  8. Marbà, N.; Duarte, C.M. Rhizome elongation and seagrass clonal growth. Mar. Ecol. Prog. Ser. 1998, 174, 269–280. [Google Scholar] [CrossRef]
  9. Weatherall, E.J.; Jackson, E.L.; Hendry, R.A.; Campbell, M.L. Quantifying the dispersal potential of seagrass vegetative fragments: A comparison of multiple subtropical species. Estuar. Coast. Shelf Sci. 2016, 169, 207–215. [Google Scholar] [CrossRef]
  10. Nguyen, H.M.; Kleitou, P.; Kletou, D.; Sapir, Y.; Winters, G. Differences in flowering sex ratios between native and invasive populations of the seagrass Halophila stipulacea. Bot. Mar. 2018, 61, 337–342. [Google Scholar] [CrossRef]
  11. Gerakaris, V.; Tsiamis, K. Sexual reproduction of the Lessepsian seagrass Halophila stipulacea in the Mediterranean Sea. Bot. Mar. 2015, 58, 51–53. [Google Scholar] [CrossRef]
  12. Lipkin, Y. Halophila stipulacea in Cyprus and Rhodes, 1967–1970. Aquat. Bot. 1975, 1, 309–320. [Google Scholar] [CrossRef]
  13. Apostolaki, E.T.; Holmer, M.; Santinelli, V.; Karakassis, I. Species-specific response to sulfide intrusion in native and exotic Mediterranean seagrasses under stress. Mar. Environ. Res. 2018, 134, 85–95. [Google Scholar] [CrossRef] [PubMed]
  14. Hernández-Delgado, E.A.; Toledo-Hernández, C.; Ruíz-Díaz, C.P.; Gómez-Andújar, N.; Medina-Muñiz, J.L.; Canals-Silander, M.F.; Suleimán-Ramos, S.E. Hurricane Impacts and the Resilience of the Invasive Sea Vine, Halophila stipulacea: A Case Study from Puerto Rico. Estuaries Coasts 2020, 1–21. [Google Scholar] [CrossRef]
  15. O’Brien, K.R.; Waycott, M.; Maxwell, P.; Kendrick, G.A.; Udy, J.W.; Ferguson, A.J.P.; Kilminster, K.; Scanes, P.; McKenzie, L.J.; McMahon, K.; et al. Seagrass ecosystem trajectory depends on the relative timescales of resistance, recovery and disturbance. Mar. Pollut. Bull. 2018, 134, 166–176. [Google Scholar] [CrossRef] [Green Version]
  16. Wesselmann, M.; Anton, A.; Duarte, C.M.; Hendriks, I.E.; Agustí, S.; Savva, I.; Apostolaki, E.T.; Marbà, N. Tropical seagrass Halophila stipulacea shifts thermal tolerance during Mediterranean invasion. Proc. Royal Soc. B Biol. Sci. 2020, 287, 20193001. [Google Scholar] [CrossRef] [Green Version]
  17. Bianchi, C.N. Biodiversity issues for the forthcoming tropical Mediterranean Sea. Hydrobiologia 2007, 580, 7–21. [Google Scholar] [CrossRef]
  18. Boudouresque, C.F.; Bernard, G.; Pergent, G.; Shimabukuro, H.; Verlaque, M. Regression of Mediterranean seagrasses caused by natural processes and anthropogenic disturbances and stress: A critical review. Bot. Mar. 2009, 52, 395–418. [Google Scholar] [CrossRef]
  19. Sghaier, Y.R.; Zakhama-Sraieb, R.; Charfi-Cheikhrouha, F. Effects of the invasive seagrass Halophila stipulacea on the native seagrass Cymodocea nodosa. In Proceedings of the Fifth Mediterranean 281 Symposium on Marine Vegetation, Portoroz, Slovenia, 27–28 October 2014; RAC/SPA: Tunis, Tunisia, 2014; pp. 167–172. [Google Scholar]
  20. Willette, D.A.; Ambrose, R.F. Effects of the invasive seagrass Halophila stipulacea on the native seagrass, Syringodium filiforme, and associated fish and epibiota communities in the Eastern Caribbean. Aquat. Bot. 2012, 103, 74–82. [Google Scholar] [CrossRef]
  21. Van Tussenbroek, B.I.; Van Katwijk, M.M.; Bouma, T.J.; Van der Heide, T.; Govers, L.L.; Leuven, R.S.E.W. Non-native seagrass Halophila stipulacea forms dense mats under eutrophic conditions in the Caribbean. J. Sea Res. 2016, 115, 1–5. [Google Scholar] [CrossRef]
  22. Marbà, N.; Díaz-Almela, E.; Duarte, C.M. Mediterranean seagrass (Posidonia oceanica) loss between 1842 and 2009. Biol. Conserv. 2014, 176, 183–190. [Google Scholar] [CrossRef]
  23. Stapley, J.; Reger, J.; Feulner, P.G.D.; Smadja, C.; Galindo, J.; Ekblom, R.; Bennison, C.; Ball, A.D.; Beckerman, A.P.; Slate, J. Adaptation genomics: The next generation. Trends Ecol. Evol. 2010, 25, 705–712. [Google Scholar] [CrossRef] [PubMed]
  24. Primmer, C.R. From Conservation Genetics to Conservation Genomics. Ann. N.Y. Acad. Sci. 2009, 1162, 357–368. [Google Scholar] [CrossRef] [PubMed]
  25. Rius, M.; Turon, X.; Bernardi, G.; Volckaert, F.A.M.; Viard, F. Marine invasion genetics: From spatio-temporal patterns to evolutionary outcomes. Biol. Invasions 2015, 17, 869–885. [Google Scholar] [CrossRef] [Green Version]
  26. Ekblom, R.; Wolf, J.B.W. A field guide to whole-genome sequencing, assembly and annotation. Evol. Appl. 2014, 7, 1026–1042. [Google Scholar] [CrossRef]
  27. Baird, N.A.; Etter, P.D.; Atwood, T.S.; Currey, M.C.; Shiver, A.L.; Lewis, Z.A.; Selker, E.U.; Cresko, W.A.; Johnson, E.A. Rapid SNP Discovery and Genetic Mapping Using Sequenced RAD Markers. PLoS ONE 2008, 3, e3376. [Google Scholar] [CrossRef]
  28. Tassell, C.P.V.; Smith, T.P.L.; Matukumalli, L.K.; Taylor, J.F.; Schnabel, R.D.; Lawley, C.T.; Haudenschild, C.D.; Moore, S.S.; Warren, W.C.; Sonstegard, T.S. SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries. Nat. Methods 2008, 5, 247–252. [Google Scholar] [CrossRef]
  29. Zavodna, M.; Grueber, C.E.; Gemmell, N.J. Parallel Tagged Next-Generation Sequencing on Pooled Samples—A New Approach for Population Genetics in Ecology and Conservation. PLoS ONE 2013, 8, e61471. [Google Scholar] [CrossRef] [Green Version]
  30. Wang, Z.; Gerstein, M.; Snyder, M. RNA-Seq: A revolutionary tool for transcriptomics. Nat. Rev. Genet. 2009, 10, 57–63. [Google Scholar] [CrossRef]
  31. Li, H.; Durbin, R. Inference of human population history from individual whole-genome sequences. Nature 2011, 475, 493–496. [Google Scholar] [CrossRef] [Green Version]
  32. Hohenlohe, P.A.; Phillips, P.C.; Cresko, W.A. Using Population Genomics to Detect Selection in Natural Populations: Key Concepts and Methodological Considerations. Int. J. Plant Sci. 2010, 171, 1059–1071. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. The Arabidopsis Initiative. Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 2000, 408, 796–815. [Google Scholar] [CrossRef] [Green Version]
  34. Goff, S.A.; Ricke, D.; Lan, T.H.; Presting, G.; Wang, R.; Dunn, M.; Glazebrook, J.; Sessions, A.; Oeller, P.; Varma, H.; et al. A draft sequence of the rice genome (Oryza sativa L. ssp. japonica). Science 2002, 296, 92–100. [Google Scholar] [CrossRef] [Green Version]
  35. Wang, W.; Haberer, G.; Gundlach, H.; Gläßer, C.; Nussbaumer, T.; Luo, M.C.; Lomsadze, A.; Borodovsky, M.; Kerstetter, R.A.; Shanklin, J.; et al. The Spirodela polyrhiza genome reveals insights into its neotenous reduction fast growth and aquatic lifestyle. Nat. Commun. 2014, 5, 3311. [Google Scholar] [CrossRef] [PubMed]
  36. Hoeck, A.V.; Horemans, N.; Monsieurs, P.; Cao, H.X.; Vandenhove, H.; Blust, R. The first draft genome of the aquatic model plant Lemna minor opens the route for future stress physiology research and biotechnological applications. Biotechnol. Biofuels 2015, 8, 188. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Yang, Y.; Sun, P.; Lv, L.; Wang, D.; Ru, D.; Li, Y.; Ma, T.; Zhang, L.; Shen, X.; Meng, F.; et al. Prickly waterlily and rigid hornwort genomes shed light on early angiosperm evolution. Nat. Plants 2020, 6, 215–222. [Google Scholar] [CrossRef] [PubMed]
  38. An, D.; Zhou, Y.; Li, C.; Xiao, Q.; Wang, T.; Zhang, Y.; Wu, Y.; Li, Y.; Chao, D.-Y.; Messing, J.; et al. Plant evolution and environmental adaptation unveiled by long-read whole-genome sequencing of Spirodela. Proc. Natl. Acad. Sci. USA 2019, 116, 18893–18899. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Olsen, J.L.; Rouzé, P.; Verhelst, B.; Lin, Y.-C.; Bayer, T.; Collen, J.; Dattolo, E.; Paoli, E.D.; Dittami, S.; Maumus, F.; et al. The genome of the seagrass Zostera marina reveals angiosperm adaptation to the sea. Nature 2016, 530, 331–335. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Lee, H.; Golicz, A.A.; Bayer, P.E.; Jiao, Y.; Tang, H.; Paterson, A.H.; Sablok, G.; Krishnaraj, R.R.; Chan, C.-K.K.; Batley, J.; et al. The Genome of a Southern Hemisphere Seagrass Species (Zostera muelleri). Plant Physiol. 2016, 172, 272–283. [Google Scholar] [CrossRef] [Green Version]
  41. Marín-Guirao, L.; Ruiz, J.M.; Dattolo, E.; Garcia-Munoz, R.; Procaccini, G. Physiological and molecular evidence of differential short-term heat tolerance in Mediterranean seagrasses. Sci. Rep. 2016, 6, 28615. [Google Scholar] [CrossRef] [Green Version]
  42. Jueterbock, A.; Franssen, S.U.; Bergmann, N.; Gu, J.; Coyer, J.A.; Reusch, T.B.H.; Bornberg-Bauer, E.; Olsen, J.L. Phylogeographic differentiation versus transcriptomic adaptation to warm temperatures in Zostera marina, a globally important seagrass. Mol. Ecol. 2016, 25, 5396–5411. [Google Scholar] [CrossRef] [Green Version]
  43. Franssen, S.U.; Gua, J.; Bergmannb, N.; Wintersa, G.; Klostermeierc, U.C.; Rosenstielc, P.; Bornberg-Bauera, E.; Reuschb, T.B.H. Transcriptomic resilience to global warming in the seagrass Zostera marina, a marine foundation species. Proc. Natl. Acad. Sci. USA 2011, 108, 19276–19281. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. D’Esposito, D.; Orrù, L.; Dattolo, E.; Bernardo, L.; Lamontanara, A.; Orsini, L.; Serra, I.A.; Mazzuca, S.; Procaccini, G. Transcriptome characterisation and simple sequence repeat marker discovery in the seagrass Posidonia oceanica. Sci. Data 2016, 3, 160115. [Google Scholar] [CrossRef] [PubMed]
  45. De Kock, W.; Hasler-Sheetal, H.; Holmer, M.; Tsapakis, M.; Apostolaki, E.T. Metabolomics and traditional indicators unveil stress of a seagrass (Cymodocea nodosa) meadow at intermediate distance from a fish farm. Ecol. Indic. 2020, 109, 105765. [Google Scholar] [CrossRef]
  46. Malandrakis, E.; Dadali, O.; Kavouras, M.; Danis, T.; Panagiotaki, P.; Miliou, H.; Tsioli, S.; Orfanidis, S.; Küpper, F.C.; Exadactylos, A. Identification of the abiotic stress-related transcription in little Neptune grass Cymodocea nodosa with RNA-seq. Mar. Genom. 2017, 34, 47–56. [Google Scholar] [CrossRef] [PubMed]
  47. Barbier, F.F.; Chabikwa, T.G.; Ahsan, M.U.; Cook, S.E.; Powell, R.; Tanurdzic, M.; Beveridge, C.A. A phenol/chloroform-free method to extract nucleic acids from recalcitrant, woody tropical species for gene expression and sequencing. Plant Methods 2019, 15, 62. [Google Scholar] [CrossRef] [Green Version]
  48. Maltas, E.; Vural, H.C.; Yildiz, S. Extraction of genomic DNA from polysaccharide- and phenolics-rich Ginkgo biloba. J. Med. Plants Res. 2011, 5, 332–339. [Google Scholar]
  49. Doyle, J.J.; Doyle, L.J. Isolation of plant DNA from fresh tissue. Focus 1990, 12, 13–15. [Google Scholar]
  50. Wood, D.E.; Lu, J.; Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol. 2019, 20, 257. [Google Scholar] [CrossRef] [Green Version]
  51. Bankevich, A.; Nurk, S.; Antipov, D.; Gurevich, A.A.; Dvorkin, M.; Kulikov, A.S.; Lesin, V.M.; Nikolenko, S.I.; Pham, S.; Prjibelski, A.D.; et al. SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing. J. Comput. Biol. 2012, 19, 455–477. [Google Scholar] [CrossRef] [Green Version]
  52. Gurevich, A.; Saveliev, V.; Vyahhi, N.; Tesler, G. QUAST: Quality assessment tool for genome assemblies. Bioinformatics 2013, 29, 1072–1075. [Google Scholar] [CrossRef] [PubMed]
  53. Simão, F.A.; Waterhouse, R.M.; Ioannidis, P.; Kriventseva, E.V.; Zdobnov, E.M. BUSCO: Assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 2015, 31, 3210–3212. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Katoh, K.; Standley, D.M. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol. Biol. Evol. 2013, 30, 772–780. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Waterhouse, A.M.; Procter, J.B.; Martin, D.M.A.; Clamp, M.; Barton, G.J. Jalview Version 2—A multiple sequence alignment editor and analysis workbench. Bioinformatics 2009, 25, 1189–1191. [Google Scholar] [CrossRef] [Green Version]
  56. Stamatakis, A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014, 30, 1312–1313. [Google Scholar] [CrossRef]
  57. Procaccini, G.; Acunto, S.; Fama, P.; Maltagliati, F. Structural, morphological and genetic variability in Halophila stipulacea (Hydrocharitaceae) populations in the western Mediterranean. Mar. Biol. 1999, 135, 181–189. [Google Scholar] [CrossRef]
  58. Rindi, F.; Cavas, L.; Serrão, E.; Duarte, C.M.; Marrá, N. Molecular identification of the tropical seagrass Halophila stipulacea from Turkey. Cah. Biol. Mar. 2011, 52, 227–232. [Google Scholar]
  59. Ruggiero, M.V.; Procaccini, G. The rDNA ITS Region in the Lessepsian Marine Angiosperm Halophila stipulacea (Forssk.) Aschers. (Hydrocharitaceae): Intragenomic Variability and Putative Pseudogenic Sequences. J. Mol. Evol. 2004, 58, 115–121. [Google Scholar] [CrossRef]
  60. El-Hady, H.H.A.; Hamed, E.R.; Shehata, A.N. Molecular Identification, Antimicrobial and Antioxidant Activities of the Tropical Seagrass Halophila stipulacea Grown in El-Bardawil Lake, Egypt. Aust. J. Basic Appl. Sci. 2012, 6, 474–481. [Google Scholar]
  61. Gargiulo, G.M.; Vilardo, I.; Cambrea, G.; Gemelli, F.; Crosca, A. Karyomorphology and DNA quantification in the marine angiosperm Halophila stipulacea (Forsskål) Ascherson from Mediterranean and Red Seas. Aquat. Bot. 2018, 148, 1–9. [Google Scholar] [CrossRef]
  62. Lee, H.; Golicz, A.A.; Bayer, P.E.; Severn-Ellis, A.A.; Chan, C.-K.K.; Batley, J.; Kendrick, G.A.; Edwards, D. Genomic comparison of two independent seagrass lineages reveals habitat-driven convergent evolution. J. Exp. Bot. 2018, 69, 3689–3702. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Mehrotra, S.; Goyal, V. Repetitive Sequences in Plant Nuclear DNA: Types, Distribution, Evolution and Function. Genom. Proteom. Bioinform. 2014, 12, 164–171. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Jurka, J.; Kapitonov, V.V.; Kohany, O.; Jurka, M.V. Repetitive Sequences in Complex Genomes: Structure and Evolution. Annu. Rev. Genom. Hum. Genet. 2007, 8, 241–259. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Toll-Riera, M.; Radó-Trilla, N.; Martys, F.; Albà, M.M. Role of Low-Complexity Sequences in the Formation of Novel Protein Coding Sequences. Mol. Biol. Evol. 2012, 29, 883–886. [Google Scholar] [CrossRef] [Green Version]
  66. Feschotte, C.; Jiang, N.; Wessler, S.R. Plant transposable elements: Where genetics meets genomics. Nat. Rev. Genet. 2002, 3, 329–341. [Google Scholar] [CrossRef]
  67. Choulet, F.; Wicker, T.; Rustenholz, C.; Paux, E.; Salse, J.; Leroy, P.; Schlub, S.; Le Paslier, M.C.; Magdelenat, G.; Gonthier, C.; et al. Megabase Level Sequencing Reveals Contrasted Organization and Evolution Patterns of the Wheat Gene and Transposable Element Spaces. Plant Cell 2020, 22, 1686–1701. [Google Scholar] [CrossRef] [Green Version]
  68. Stevens, K.A.; Wegrzyn, J.L.; Zimin, A.; Puiu, D.; Crepeau, M.; Cardeno, C.; Paul, R.; Gonzalez-Ibeas, D.; Koriabine, M.; Holtz-Morris, A.E.; et al. Sequence of the Sugar Pine Megagenome. Genetics 2016, 204, 1613–1626. [Google Scholar] [CrossRef]
  69. Akakpo, R.; Carpentier, M.; Hsing, Y.I.; Panaud, O. The impact of transposable elements on the structure, evolution and function of the rice genome. New Phytol. 2020, 226, 44–49. [Google Scholar] [CrossRef] [Green Version]
  70. Edger, P.P.; Poorten, T.J.; VanBuren, R.; Hardigan, M.A.; Colle, M.; McKain, M.R.; Smith, R.D.; Teresi, S.J.; Nelson, A.D.L.; Wai, C.M.; et al. Origin and evolution of the octoploid strawberry genome. Nat. Genet. 2019, 51, 541–547. [Google Scholar] [CrossRef] [Green Version]
  71. Danis, T.; Tsakogiannis, A.; Kristoffersen, J.B.; Golani, D.; Tsaparis, D.; Kasapidis, P.; Kotoulas, G.; Magoulas, A.; Tsigenopoulos, C.S.; Manousaki, T. Building a high-quality reference genome assembly for the eastern Mediterranean Sea invasive sprinter Lagocephalus sceleratus (Tetraodontiformes, Tetraodontidae). bioRxiv 2020. [Google Scholar] [CrossRef]
  72. Jiang, S.; An, H.; Xu, F.; Zhang, X. Chromosome-level genome assembly and annotation of the loquat (Eriobotrya japonica) genome. Gigascience 2020, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Diversity 12 00263 g001 550
Figure 1. Publication effort in terms of genetics and genomics studies for all seagrass species and for Halophila stipulacea separately, reported in the Web of Science, as of February 2020.
Figure 1. Publication effort in terms of genetics and genomics studies for all seagrass species and for Halophila stipulacea separately, reported in the Web of Science, as of February 2020.
Diversity 12 00263 g001
Diversity 12 00263 g002 550
Figure 2. Maximum likelihood phylogenetic analysis of the ITS sequence from the sequenced individual (Crete) and individuals from [59] coming from Italy, Egypt, and Greece. Bootstrap values are all below 10 and omitted. The branch length scale represents the number of substitutions per site.
Figure 2. Maximum likelihood phylogenetic analysis of the ITS sequence from the sequenced individual (Crete) and individuals from [59] coming from Italy, Egypt, and Greece. Bootstrap values are all below 10 and omitted. The branch length scale represents the number of substitutions per site.
Diversity 12 00263 g002
Table
Table 1. Summary statistics of the assembled H. stipulacea genome.
Table 1. Summary statistics of the assembled H. stipulacea genome.
Assembly Statistics
Total length in bp3,705,345,858
Total number of contigs866,469
Contig N50 *7949
L50 **102,383
GC%41.97
Number of unknown bases (N’s) per 100 Kbp14.13
Note: * Given that all contigs are sorted in terms of their length, the N50 value refers to the length of the contig that divides the assembly into two equal parts in terms of bases; ** L50 is the number of contigs whose summed length is N50.

Share and Cite

MDPI and ACS Style

Tsakogiannis, A.; Manousaki, T.; Anagnostopoulou, V.; Stavroulaki, M.; Apostolaki, E.T. The Importance of Genomics for Deciphering the Invasion Success of the Seagrass Halophila stipulacea in the Changing Mediterranean Sea. Diversity 2020, 12, 263. https://doi.org/10.3390/d12070263

AMA Style

Tsakogiannis A, Manousaki T, Anagnostopoulou V, Stavroulaki M, Apostolaki ET. The Importance of Genomics for Deciphering the Invasion Success of the Seagrass Halophila stipulacea in the Changing Mediterranean Sea. Diversity. 2020; 12(7):263. https://doi.org/10.3390/d12070263

Chicago/Turabian Style

Tsakogiannis, Alexandros, Tereza Manousaki, Vasileia Anagnostopoulou, Melanthia Stavroulaki, and Eugenia T. Apostolaki. 2020. "The Importance of Genomics for Deciphering the Invasion Success of the Seagrass Halophila stipulacea in the Changing Mediterranean Sea" Diversity 12, no. 7: 263. https://doi.org/10.3390/d12070263

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop