| Literature DB >> 28655320 |
Daniel J Macqueen1, Craig R Primmer2, Ross D Houston3, Barbara F Nowak4, Louis Bernatchez5, Steinar Bergseth6, William S Davidson7, Cristian Gallardo-Escárate8, Tom Goldammer9, Yann Guiguen10, Patricia Iturra11, James W Kijas12, Ben F Koop13, Sigbjørn Lien14, Alejandro Maass15,16, Samuel A M Martin17, Philip McGinnity18, Martin Montecino19,20, Kerry A Naish21, Krista M Nichols22, Kristinn Ólafsson23, Stig W Omholt14,24, Yniv Palti25, Graham S Plastow26, Caird E Rexroad27, Matthew L Rise28, Rachael J Ritchie29, Simen R Sandve14, Patricia M Schulte30, Alfredo Tello31, Rodrigo Vidal32, Jon Olav Vik14, Anna Wargelius33, José Manuel Yáñez34.
Abstract
We describe an emerging initiative - the 'Functional Annotation of All Salmonid Genomes' (FAASG), which will leverage the extensive trait diversity that has evolved since a whole genome duplication event in the salmonid ancestor, to develop an integrative understanding of the functional genomic basis of phenotypic variation. The outcomes of FAASG will have diverse applications, ranging from improved understanding of genome evolution, to improving the efficiency and sustainability of aquaculture production, supporting the future of fundamental and applied research in an iconic fish lineage of major societal importance.Entities:
Keywords: Aquaculture; Comparative biology; Data sharing; Evolution; Functional annotation; Genome biology; Phenotyping; Salmonid fish; Standardized data and metadata; Whole genome duplication
Mesh:
Year: 2017 PMID: 28655320 PMCID: PMC5488370 DOI: 10.1186/s12864-017-3862-8
Source DB: PubMed Journal: BMC Genomics ISSN: 1471-2164 Impact factor: 3.969
Fig. 1The comparative-evolutionary framework of FAASG. Shown are the initial target species for functional annotation (see Table 1) and their evolutionary relationships (time-calibrated tree after [7]). The selected species come from all three salmonid subfamilies. The position of the salmonid-specific WGD is highlighted (after [7, 9, 10]), along with Latin names of genera. Additional salmonid species that are future potential targets for functional annotation are not shown. Two lineages where anadromous life-history is thought to have evolved independently are highlighted ‘A’ (after [47]). The status of genomics resources are shown to the right of the tree: squares and circles indicate genome and transcriptome assemblies, respectively (dark grey = resource either published or close to being published; light grey = resource under active development; ‘Ch’ = chromosome-anchored genome assembly)
Levels of genome-wide functional annotation within the FAASG framework
| Class of variation | Context | Origin of data | Goal |
|---|---|---|---|
| Genomic sequence | Phylogeny-wide | Comparative analysis | Define fixed substitutions across species including for WGD gene duplicates. Assign to different classes: exonic, intronic, regulatory, synonymous vs. non-synonymous; radical vs. conservative non-synonymous and divergent from ancestral state |
| Genomic sequence | Population-level | Genome-resequencing | Define SNPs and structural genome variation within species. Assign to different classes: as above |
| Epigenetic | Phylogeny-wide and population level | Assays described in Additional file | Generate DNA methylome maps and define their regulation across tissues, developmental stages and common-garden physiological manipulations |
| Epigenetic | Phylogeny-wide and population level | Assays described in Additional file | Define a range of histone marks and their regulation across tissues, developmental stages and common-garden physiological manipulations |
| Epigenetic | Phylogeny-wide and population level | Assays described in Additional file | Generate maps of DNA accessibility and define their regulation across tissues, developmental stages and common-garden physiological manipulations |
| RNA expression | Phylogeny-wide and population level | RNAseq - potentially stranded protocols (see Additional file | Define expression of miRNA, mRNA and non-coding RNA across adult tissues, developmental stages and common-garden physiological manipulations [ |
| Protein level | Phylogeny-wide and population level | Various possible mass spectrometer platforms – bottom up approach | Define proteome across tissues, developmental stages and common-garden physiological manipulations |
The role of functional genome annotation in addressing key challenges for salmonid research and its application. Below we list selected key questions, highlight their importance, and then briefly describe (in italics) how the FAASG initiative will help address them
| Aquaculture |
| What is the functional genetic basis of key performance traits for salmonid aquaculture? |
| Few causative variants underlying performance trait QTL have been identified. Knowledge of the precise functional variants underpinning QTL will inform the biology of these traits, and facilitate cost-effective selection for favorable alleles. |
| How can we optimize genomic selection for genetic improvement in aquaculture breeding programs? |
| Genomic selection can accelerate genetic gain for traits important to sustainable and profitable aquaculture, such as host resistance to infectious diseases. Predicting breeding values in distant relatives to the training population is challenging, thus necessitating frequent, expensive phenotypic tests. |
| What is the functional genetic basis of recent domestication in salmonid species? |
| Salmonids are excellent models to study the genomic basis of recent domestication, facilitating discovery of genetic variation of importance in adaptation to aquaculture environments. These outcomes can improve hatchery management, health and welfare of farmed fish, and have implications for interactions with wild populations. |
| How can genome editing technology contribute to improved aquaculture production? |
| Genome editing technology, notably CRISPR-Cas9 has potential to enhance aquaculture production directly by introducing favorable alleles into farmed populations, or indirectly, for example by providing a better understanding of the functional basis of production traits (e.g. using gene knockout). While regulatory and public acceptance is required, the potential is highlighted by several high profile successes in terrestrial livestock. |
| What is the long term impact of aquaculture escapees on wild populations? |
| Evaluating and understanding the impacts of aquaculture escapees on wild populations supports risk assessment for the use of native and non-native strains in culture. |
| How can measurement of salmonid health and welfare in aquaculture be improved? |
| Appropriate biomarkers of stress, health and growth status in salmonid aquaculture are currently difficult to define and far from comprehensive. |
| Ecology, evolution and physiology |
| What role did the whole genome duplication and subsequent rediploidization play in salmonid evolution? |
| This is a long-standing question of fundamental importance to our understanding of salmonid biology and the role of WGDs in evolution more generally. |
| How important is genetic vs. epigenetic variation in regulating trait variability? |
| Rapid phenotypic divergence and phenotypic plasticity are hallmarks of many salmonid species, yet remain poorly-characterized. An improved understanding of heritable epigenetic variation and its interaction with both genetic and environmental variation can be exploited in both conservation and aquaculture. |
| What is the genomic basis of response and adaptation to natural and anthropogenic stressors? |
| Human-induced environmental changes, including climate change, are already negatively affecting salmonid populations. Understanding the role of genetic and epigenetic variation in physiological response to these changes will be key to predicting, and potentially mitigating, these effects. |
| What role do ‘non-coding’ RNAs have in generating phenotypic variation? |
| The functions of non-coding RNAs are poorly understood in salmonids. The greater retention of miRNAs in comparison to duplicated genes after WGD suggests important functions in coping with a duplicated genome. Non-coding RNAs may regulate traits of interest to aquaculture and evolutionary biology. |
| How many salmonid species exist, and how can we distinguish them? |
| The actual number of salmonid species is unknown. Habitat-dependent phenotypes can suggest different species, but genomics and functional genomics methods are ultimately required to answer this question. |