Elsevier

Marine Genomics

Volume 31, February 2017, Pages 1-8
Marine Genomics

Review
Marine genomics: News and views

https://doi.org/10.1016/j.margen.2016.09.002Get rights and content

Abstract

Marine ecosystems occupy 71% of the surface of our planet, yet we know little about their diversity. Although the inventory of species is continually increasing, as registered by the Census of Marine Life program, only about 10% of the estimated two million marine species are known. This lag between observed and estimated diversity is in part due to the elusiveness of most aquatic species and the technical difficulties of exploring extreme environments, as for instance the abyssal plains and polar waters. In the last decade, the rapid development of affordable and flexible high-throughput sequencing approaches have been helping to improve our knowledge of marine biodiversity, from the rich microbial biota that forms the base of the tree of life to a wealth of plant and animal species. In this review, we present an overview of the applications of genomics to the study of marine life, from evolutionary biology of non-model organisms to species of commercial relevance for fishing, aquaculture and biomedicine. Instead of providing an exhaustive list of available genomic data, we rather set to present contextualized examples that best represent the current status of the field of marine genomics.

Introduction

Marine ecosystems, including coral reefs, deep-sea floor, hydrothermal vents, seagrass meadows, mangroves, the abyssal water column, sandy and rocky beaches, polar ice and saltmarshes, occupy a vast portion of Earth's surface and harbour the majority of its biomass. As sequencing the genome of any species is now technically feasible and increasingly affordable, marine scientists have been taking advantage of genomic technologies to address both new and long-standing questions in evolutionary biology, as well as to explore the richness of marine biodiversity for industrial purposes. Several international consortia have been established and are currently pooling efforts towards producing, curating and disseminating marine genomic data (see Box 1).

Assembling whole genomes can still be lengthy and non-trivial, especially for most eukaryotic species. Yet, they are essential to improve our understanding of species evolution. For example, the genome of the amphioxus Branchiostoma floridae allowed the reconstruction of the gene set of the last common chordate ancestor (Putnam et al., 2008), whereas the genome of the jawless fish sea lamprey Petromyzon marinus has shed light into the development of appendages and the origin of myelin-associated proteins (Smith et al., 2013). Venkatesh and colleagues revealed interesting immune system innovations in the genome of the elephant shark Callorhinchus milii (Venkatesh et al., 2014) whereas the hitherto assumed essential vertebrate immune gene, MHC class II, was shown to be missing completely from the Atlantic cod genome Gadus morhua (Star et al., 2011). Complete genomes of model fish species have also been shown to be important tools for studying general mechanisms of evolution in other species. The established model species zebra fish Danio rerio, and emerging model systems such as the spotted gar Lepisosteus oculatus (Braasch et al., 2016) are being increasingly used to study human genome evolution and to better understand human diseases at the genomic level.

Marine research has also taken advantage of methods that focus on subsets of the genome, which have a lower cost and therefore facilitate research on non-model organisms (da Fonseca et al., 2016). One such approach is the sequencing of RNA molecules (known as RNAseq), which targets the portion of the genome that is transcribed. RNAseq actually offers the advantage of detecting immediate molecular responses to stressors (e.g. climatic, pollution or even presence of predators or competitors), while DNA sequence data provides information regarding relatively long-term evolutionary adaptive changes. Transcriptomes can be produced from a specific tissue (Li et al., 2014), a whole individual (Rodriguez et al., 2012), a pool of individuals (Helm et al., 2013) or even a microbial community [i.e. metatranscriptomics (Alex and Antunes, 2015, Sun et al., 2014)]. The flexibility of RNAseq has allowed marine scientists to explore the basal non-bilaterian metazoan lineages (Fernandez-Valverde et al., 2015, Pooyaei Mehr et al., 2013, Stefanik et al., 2014, Wenger and Galliot, 2013), providing insight into the evolution of special developmental features such as head regeneration in Hydra magnipapillata (Krishna et al., 2013), or life cycle events as those happening with the scyphozoan jellyfish Aurelia aurita (Brekhman et al., 2015) and Porifera family members (Perez-Porro et al., 2013, Qiu et al., 2015). RNAseq has also been used to investigate mechanisms of evolutionary processes, such as the basis for the repeated evolution in independent populations of the copepods Tigriopus californicus (Pereira et al., 2016).

Other popular approaches targeting limited portions of the genome are restriction-site associated DNA sequencing (RADseq) and targeted sequencing. RADseq is a reduced-representation method where a restriction enzyme is used to digest the whole genome into small fragments that are then sequenced in both directions from enzyme cut sites (Baird et al., 2008, Etter et al., 2011). RADseq provides a cost-efficient way to simultaneously detect and genotype hundreds to thousands of SNPs in non-model species because does not require a reference genome (Andrews et al., 2016). Targeted sequence capture is the method of choice when the sequence of the regions of interest is known, and it implies the sequencing of the DNA that hybridizes with a set of probes (Grover et al., 2012). Capture probes are designed from anonymous, genic and/or ultra-conserved regions from a reference genome of the same or a closely-related species, depending on the required variation for the downstream analysis (da Fonseca et al., 2016).

Unlike for most multicellular organisms, genome size and complexity are not a limitation in microbial genomics. Microbial organisms have small genomes and hence it is no surprise that the first marine bacterial genome (thermophilic methanogenic archaean Methanococcus jannaschii, genome size: 1.7 Mb) was sequenced in 1996, five years prior to the human genome. Microbial genomics methods include sequencing of isolates and cultivation-independent techniques. The latter are of particular importance to sample the unknown marine diversity and encompass single-cell genomics [SCG; reviewed in (Gawad et al., 2016, Lasken and McLean, 2014)] and metagenomics [e.g. (Escobar-Zepeda et al., 2015)]. SCG recovers genomic information from single, uncultured cells. This enables, for example, the discovery of microbes that grow in nutritionally poor environments [oligotrophs; (Swan et al., 2013)], the identification of viral material in single cells and the study of the interactions between marine microorganisms (Labonté et al., 2015, Roux et al., 2014). Metagenomics implies a simpler laboratory setup than SCG, and has become a popular approach. Metagenomic data is mainly produced by two approaches: amplicon- and shotgun-sequencing [(Poretsky et al., 2014) and (Ranjan et al., 2015) for details about each approach] of DNA extracted using specific methods (Taberlet et al., 2007). The goals of marine metagenomic projects vary considerably: from characterizing community composition, mostly using the 16S ribosomal RNA sequences, to discovering the functional potential of genes found in genomes from a specific environment. Metagenomics provides insight into the whole genomic composition of an environment, as one obtains full or partial genomes of co-inhabiting microorganisms from an environmental sample, including microbial communities living within and on the body of a larger host organism. The collection of microbial genomes obtained from a single environmental sample is referred to as a ‘metagenome’, although originally this word was specifically used to describe ‘the collective genomes of soil microflora’ (Handelsman et al., 1998). Furthermore, metagenomics has also shed light on community function when backed-up with metatranscriptomic data (RNAseq of environmental samples), which can hold information regarding what is essential for microbial survival in particular conditions. This dual approach has revealed that some groups of Archaea, generally known as ammonia-oxidizers, have the physiological machinery to digest proteins, carbohydrates, and lipids (Li et al., 2015), prompting a complete re-thinking of the carbon-cycle in marine environments.

In the following sections, we provide examples on how genomic studies using the approaches described above (whole-genome sequencing, RNAseq, RADseq, target capture, metagenomics, SCG and metatranscriptomics), are helping to resolve the tree of life, contributing to a better understanding of marine biogeography, revealing adaptions to marine conditions and fostering the discovery of new bioactive compounds.

Section snippets

Biodiversity and biogeography

The vast majority of earth's microorganism diversity (sensu latum: Virus, Bacteria and Archea) is found in marine ecosystems. A big share of this diversity was uncovered by the use of SCG and metagenomics approaches, which revealed an expanded version of the tree of life as compared to the one recovered by using solely cultured isolates (Hug et al., 2016). Despite being a recent field, metagenomics has advanced our knowledge in a variety of marine biology domains. A new archaeal lineage

Adaptive evolution

Understanding how organisms adapt to changing conditions in their environment has been facilitated by the availability of the new genomic tools. By studying the transcriptome (Kong et al., 2014) and the genome sequencing of Zostera marina (Olsen et al., 2016), researchers revealed gene losses related to marine adaptation, such as stomatal genes (Benzecry and Brack-Hanes, 2016), ultraviolet resistance genes and genes associated with biosynthesis of the exine pollen layer (Cooper et al., 2000).

Effects of anthropogenic-induced changes in marine habitat

Several marine ecosystems are being severely affected by anthropogenic actions, from increasing water temperature, leading to recent bleaching of the Great Coral Reef in Australia, to the oil spills as the 2010 Gulf of Mexico event. RNAseq has been used extensively by marine researchers to assess the effect of permanent and transient changes in the environment (Todd et al., 2016), including bleaching in corals (Anderson et al., 2016) and exposure to heavy metals in cnidarian (Elran et al., 2014

Genome evolution

The analysis of microbial genome evolution, seemingly trivial because of the very small genome sizes involved, has become complex because of the technical and computational challenges of the aforementioned cultivation-independent methods (SCG and metagenomics). Often a combination of both methods is necessary for a comparative analysis (Mende et al., 2016). Metagenomic contigs need to be binned into putative species, a process that might result in chimeric bins (Sangwan et al., 2016).

Aquaculture and bioprospecting

Aquaculture has highly benefited from the development of genomic technologies. Genomic data has enabled the identification of gene variants associated with advantageous traits such as growth, health and disease resistance in species of commercial interest. For example, candidate genes that can be used for selective breeding have been identified in the Pacific oyster (Zhang et al., 2012) and the Mediterranean mussel Mytilus galloprovincialis (Murgarella et al., 2016). A mutation was also found

Concluding remarks

The study of marine biology has gained powerful allies with the genomics revolution. As shown in this review, a diverse array of methodological approaches has already been applied to several lines of research in marine biology. It has been explored by scientists interested in fundamental questions in biology and biomedical research, as well as by industrial engineers in search of biomaterials. The more we accumulate genomes and transcriptomes, the better we will be able to: i) uncover the full

Acknowledgments

The authors gratefully acknowledge the following for supporting their research: Young Investigator grant VKR023446 from Villum Fonden (RF), European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie grant agreement No 655150 (AMR), postdoctoral fellowship from the Carlsberg Foundation CF15-0721 (MTL), FPI graduate fellowship BES-2014-069575 (SA), Juan de la Cierva fellowship FPDI-2013-17503 (SR). We thank Rafael Zardoya for helpful comments.

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