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Zhang L, Li H, Shi M, Ren K, Zhang W, Cheng Y, Wang Y, Xia XQ. FishSNP: a high quality cross-species SNP database of fishes. Sci Data 2024; 11:286. [PMID: 38461307 PMCID: PMC10924876 DOI: 10.1038/s41597-024-03111-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 03/04/2024] [Indexed: 03/11/2024] Open
Abstract
The progress of aquaculture heavily depends on the efficient utilization of diverse genetic resources to enhance production efficiency and maximize profitability. Single nucleotide polymorphisms (SNPs) have been widely used in the study of aquaculture genomics, genetics, and breeding research since they are the most prevalent molecular markers on the genome. Currently, a large number of SNP markers from cultured fish species are scattered in individual studies, making querying complicated and data reuse problematic. We compiled relevant SNP data from literature and public databases to create a fish SNP database, FishSNP ( http://bioinfo.ihb.ac.cn/fishsnp ), and also used a unified analysis pipeline to process raw data that the author of the literature did not perform SNP calling on to obtain SNPs with high reliability. This database presently contains 45,690,243 (45 million) nonredundant SNP data for 13 fish species, with 30,288,958 (30 million) of those being high-quality SNPs. The main function of FishSNP is to search, browse, annotate and download SNPs, which provide researchers various and comprehensive associated information.
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Affiliation(s)
- Lei Zhang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Heng Li
- State Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Mijuan Shi
- State Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Keyi Ren
- State Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
- College of Fisheries and Life Science, Dalian Ocean University, Dalian, 116023, China
| | - Wanting Zhang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Yingyin Cheng
- State Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Yaping Wang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiao-Qin Xia
- State Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
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Beck SV, Räsänen K, Leblanc CA, Skúlason S, Jónsson ZO, Kristjánsson BK. Differences among families in craniofacial shape at early life-stages of Arctic charr (Salvelinus alpinus). BMC DEVELOPMENTAL BIOLOGY 2020; 20:21. [PMID: 33106153 PMCID: PMC7586659 DOI: 10.1186/s12861-020-00226-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Accepted: 10/15/2020] [Indexed: 11/10/2022]
Abstract
BACKGROUND Organismal fitness can be determined at early life-stages, but phenotypic variation at early life-stages is rarely considered in studies on evolutionary diversification. The trophic apparatus has been shown to contribute to sympatric resource-mediated divergence in several taxa. However, processes underlying diversification in trophic traits are poorly understood. Using phenotypically variable Icelandic Arctic charr (Salvelinus alpinus), we reared offspring from multiple families under standardized laboratory conditions and tested to what extent family (i.e. direct genetic and maternal effects) contributes to offspring morphology at hatching (H) and first feeding (FF). To understand the underlying mechanisms behind early life-stage variation in morphology, we examined how craniofacial shape varied according to family, offspring size, egg size and candidate gene expression. RESULTS Craniofacial shape (i.e. the Meckel's cartilage and hyoid arch) was more variable between families than within families both across and within developmental stages. Differences in craniofacial morphology between developmental stages correlated with offspring size, whilst within developmental stages only shape at FF correlated with offspring size, as well as female mean egg size. Larger offspring and offspring from females with larger eggs consistently had a wider hyoid arch and contracted Meckel's cartilage in comparison to smaller offspring. CONCLUSIONS This study provides evidence for family-level variation in early life-stage trophic morphology, indicating the potential for parental effects to facilitate resource polymorphism.
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Affiliation(s)
- Samantha V Beck
- Department of Aquaculture and Fish Biology, Hólar University, 551, Sauðárkrókur, Iceland. .,Institute of Life- and Environmental Sciences, University of Iceland, Reykjavík, Iceland. .,The Rivers and Lochs Institute, University of the Highlands and Islands, Inverness, UK.
| | - Katja Räsänen
- Department of Aquatic Ecology, Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.,Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland
| | - Camille A Leblanc
- Department of Aquaculture and Fish Biology, Hólar University, 551, Sauðárkrókur, Iceland
| | - Skúli Skúlason
- Department of Aquaculture and Fish Biology, Hólar University, 551, Sauðárkrókur, Iceland
| | - Zophonías O Jónsson
- Institute of Life- and Environmental Sciences, University of Iceland, Reykjavík, Iceland
| | - Bjarni K Kristjánsson
- Department of Aquaculture and Fish Biology, Hólar University, 551, Sauðárkrókur, Iceland
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3
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Tang M, Lu Y, Xiong Z, Chen M, Qin Y. The Grass Carp Genomic Visualization Database (GCGVD): an informational platform for genome biology of grass carp. Int J Biol Sci 2019; 15:2119-2127. [PMID: 31592084 PMCID: PMC6775296 DOI: 10.7150/ijbs.32860] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2019] [Accepted: 05/27/2019] [Indexed: 11/25/2022] Open
Abstract
With the release of the draft genome of the grass carp, researches on the grass carp from the genetic level and the further molecular mechanisms of economically valuable physiological behaviors have gained great attention. In this paper, we integrated a large number of genomic, genetic and some other data resources and established a web-based grass carp genomic visualization database (GCGVD). To view these data more effectively, we visualized grass carp and zebrafish gene collinearity and genetic linkage map using Scalable Vector Graphics (SVG) format in the browser, and genomic annotations by JBrowse. Furthermore, we carried out some preliminary study on a whole-genome alternative splicing (AS)of the grass carp. The RNA-seq reads of 15 samples were aligned to the reference genome of the grass carp by Bowtie2 software. RNA-seq reads of each sample and density map of reads were also exhibited in JBrowse. Additionally, we designed a universal grass carp genome annotation data model to improve the retrieval speed and scalability. Compared with the published database GCGD previously, we newly added the visualization of some more genomic annotations, conserved domain and RNA-seq reads aligned to the reference genome. GCGVD can be accessed at http://122.112.216.104.
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Affiliation(s)
- Min Tang
- College of Information Technology, Shanghai Ocean University, Shanghai, 201306, China.,Key Laboratory of Fisheries Information Ministry of Agriculture, Shanghai, 201306, China
| | - Ying Lu
- College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, 201306, China
| | - Zhongmin Xiong
- College of Information Technology, Shanghai Ocean University, Shanghai, 201306, China.,Key Laboratory of Fisheries Information Ministry of Agriculture, Shanghai, 201306, China
| | - Ming Chen
- College of Information Technology, Shanghai Ocean University, Shanghai, 201306, China.,Key Laboratory of Fisheries Information Ministry of Agriculture, Shanghai, 201306, China
| | - Yufang Qin
- College of Information Technology, Shanghai Ocean University, Shanghai, 201306, China.,Key Laboratory of Fisheries Information Ministry of Agriculture, Shanghai, 201306, China
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4
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Beck SV, Räsänen K, Ahi EP, Kristjánsson BK, Skúlason S, Jónsson ZO, Leblanc CA. Gene expression in the phenotypically plastic Arctic charr (Salvelinus alpinus): A focus on growth and ossification at early stages of development. Evol Dev 2018; 21:16-30. [PMID: 30474913 PMCID: PMC9285049 DOI: 10.1111/ede.12275] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Gene expression during development shapes the phenotypes of individuals. Although embryonic gene expression can have lasting effects on developmental trajectories, few studies consider the role of maternal effects, such as egg size, on gene expression. Using qPCR, we characterize relative expression of 14 growth and/or skeletal promoting genes across embryonic development in Arctic charr (Salvelinus alpinus). We test to what extent their relative expression is correlated with egg size and size at early life‐stages within the study population. We predict smaller individuals to have higher expression of growth and skeletal promoting genes, due to less maternal resources (i.e., yolk) and prioritization of energy toward ossification. We found expression levels to vary across developmental stages and only three genes (Mmp9, Star, and Sgk1) correlated with individual size at a given developmental stage. Contrary to our hypothesis, expression of Mmp9 and Star showed a non‐linear relationship with size (at post fertilization and hatching, respectively), whilst Sgk1 was higher in larger embryos at hatching. Interestingly, these genes are also associated with craniofacial divergence of Arctic charr morphs. Our results indicate that early life‐stage variation in gene expression, concomitant to maternal effects, can influence developmental plasticity and potentially the evolution of resource polymorphism in fishes.
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Affiliation(s)
- Samantha V Beck
- Department of Aquaculture and Fish Biology, Hólar University College, Háskólinn á Hólum, Sauðárkrókur, Iceland.,Institute of Life- and Environmental Sciences, University of Iceland, Reykjavík, Iceland
| | - Katja Räsänen
- Department of Aquatic Ecology, Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.,Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland
| | - Ehsan P Ahi
- Institute of Life- and Environmental Sciences, University of Iceland, Reykjavík, Iceland.,Institute of Zoology, University of Graz, Universitätsplatz 2, Graz, Austria
| | - Bjarni K Kristjánsson
- Department of Aquaculture and Fish Biology, Hólar University College, Háskólinn á Hólum, Sauðárkrókur, Iceland
| | - Skúli Skúlason
- Department of Aquaculture and Fish Biology, Hólar University College, Háskólinn á Hólum, Sauðárkrókur, Iceland
| | - Zophonías O Jónsson
- Institute of Life- and Environmental Sciences, University of Iceland, Reykjavík, Iceland
| | - Camille A Leblanc
- Department of Aquaculture and Fish Biology, Hólar University College, Háskólinn á Hólum, Sauðárkrókur, Iceland
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5
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Guðbrandsson J, Franzdóttir SR, Kristjánsson BK, Ahi EP, Maier VH, Kapralova KH, Snorrason SS, Jónsson ZO, Pálsson A. Differential gene expression during early development in recently evolved and sympatric Arctic charr morphs. PeerJ 2018; 6:e4345. [PMID: 29441236 PMCID: PMC5807978 DOI: 10.7717/peerj.4345] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Accepted: 01/19/2018] [Indexed: 02/06/2023] Open
Abstract
Phenotypic differences between closely related taxa or populations can arise through genetic variation or be environmentally induced, leading to altered transcription of genes during development. Comparative developmental studies of closely related species or variable populations within species can help to elucidate the molecular mechanisms related to evolutionary divergence and speciation. Studies of Arctic charr (Salvelinus alpinus) and related salmonids have revealed considerable phenotypic variation among populations and in Arctic charr many cases of extensive variation within lakes (resource polymorphism) have been recorded. One example is the four Arctic charr morphs in the ∼10,000 year old Lake Thingvallavatn, which differ in numerous morphological and life history traits. We set out to investigate the molecular and developmental roots of this polymorphism by studying gene expression in embryos of three of the morphs reared in a common garden set-up. We performed RNA-sequencing, de-novo transcriptome assembly and compared gene expression among morphs during an important timeframe in early development, i.e., preceding the formation of key trophic structures. Expectedly, developmental time was the predominant explanatory variable. As the data were affected by some form of RNA-degradation even though all samples passed quality control testing, an estimate of 3'-bias was the second most common explanatory variable. Importantly, morph, both as an independent variable and as interaction with developmental time, affected the expression of numerous transcripts. Transcripts with morph effect, separated the three morphs at the expression level, with the two benthic morphs being more similar. However, Gene Ontology analyses did not reveal clear functional enrichment of transcripts between groups. Verification via qPCR confirmed differential expression of several genes between the morphs, including regulatory genes such as AT-Rich Interaction Domain 4A (arid4a) and translin (tsn). The data are consistent with a scenario where genetic divergence has contributed to differential expression of multiple genes and systems during early development of these sympatric Arctic charr morphs.
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Affiliation(s)
- Jóhannes Guðbrandsson
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavík, Iceland
- Freshwater Division, Marine and Freshwater Research Institute, Reykjavík, Iceland
| | - Sigríður Rut Franzdóttir
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavík, Iceland
- Biomedical Center, University of Iceland, Reykjavík, Iceland
| | | | - Ehsan Pashay Ahi
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavík, Iceland
- Karl-Franzens-Universität, Graz, Austria
| | - Valerie Helene Maier
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavík, Iceland
- Biomedical Center, University of Iceland, Reykjavík, Iceland
| | | | | | - Zophonías Oddur Jónsson
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavík, Iceland
- Biomedical Center, University of Iceland, Reykjavík, Iceland
| | - Arnar Pálsson
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavík, Iceland
- Biomedical Center, University of Iceland, Reykjavík, Iceland
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6
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Chen Y, Shi M, Zhang W, Cheng Y, Wang Y, Xia XQ. The Grass Carp Genome Database (GCGD): an online platform for genome features and annotations. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2018; 2017:4049441. [PMID: 29220445 PMCID: PMC5532967 DOI: 10.1093/database/bax051] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Accepted: 06/20/2017] [Indexed: 12/15/2022]
Abstract
As one of the four major Chinese carps of important economic value, the grass carp (Ctenopharyngodon idellus) has attracted increasing attention from the scientific community. Recently, the draft genome has been released as a milestone in research of grass carp. In order to facilitate the utilization of these genome data, we developed the grass carp genome database (GCGD). GCGD provides visual presentation of the grass carp genome along with annotations and amino acid sequences of predicted protein-coding genes. Other related genetic and genomic data available in this database include the genetic linkage maps, microsatellite genetic markers (i.e. Short Sequence Repeats, SSRs), and some selected transcriptomic datasets. A series of tools have been integrated into GCGD for visualization, analysis and retrieval of data, e.g. JBrowse for navigation of genome annotations, BLAST for sequence alignment, EC2KEGG for comparison of metabolic pathways, IDConvert for conversion of terms across databases and ReadContigs for extraction of sequences from the grass carp genome. Database URL:http://bioinfo.ihb.ac.cn/gcgd
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Affiliation(s)
- Yaxin Chen
- Institute of Hydrobiology, The Chinese Academy of Sciences, Wuhan 430072, China and
- University of Chinese Academy of Sciences, Beijing, China
| | - Mijuan Shi
- Institute of Hydrobiology, The Chinese Academy of Sciences, Wuhan 430072, China and
| | - Wanting Zhang
- Institute of Hydrobiology, The Chinese Academy of Sciences, Wuhan 430072, China and
| | - Yingyin Cheng
- Institute of Hydrobiology, The Chinese Academy of Sciences, Wuhan 430072, China and
| | - Yaping Wang
- Institute of Hydrobiology, The Chinese Academy of Sciences, Wuhan 430072, China and
| | - Xiao-Qin Xia
- Institute of Hydrobiology, The Chinese Academy of Sciences, Wuhan 430072, China and
- Corresponding author: Tel/Fax: +86 27 68780915;
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7
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Carruthers M, Yurchenko AA, Augley JJ, Adams CE, Herzyk P, Elmer KR. De novo transcriptome assembly, annotation and comparison of four ecological and evolutionary model salmonid fish species. BMC Genomics 2018; 19:32. [PMID: 29310597 PMCID: PMC5759245 DOI: 10.1186/s12864-017-4379-x] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 12/11/2017] [Indexed: 12/21/2022] Open
Abstract
Background Salmonid fishes exhibit high levels of phenotypic and ecological variation and are thus ideal model systems for studying evolutionary processes of adaptive divergence and speciation. Furthermore, salmonids are of major interest in fisheries, aquaculture, and conservation research. Improving understanding of the genetic mechanisms underlying traits in these species would significantly progress research in these fields. Here we generate high quality de novo transcriptomes for four salmonid species: Atlantic salmon (Salmo salar), brown trout (Salmo trutta), Arctic charr (Salvelinus alpinus), and European whitefish (Coregonus lavaretus). All species except Atlantic salmon have no reference genome publicly available and few if any genomic studies to date. Results We used paired-end RNA-seq on Illumina to generate high coverage sequencing of multiple individuals, yielding between 180 and 210 M reads per species. After initial assembly, strict filtering was used to remove duplicated, redundant, and low confidence transcripts. The final assemblies consisted of 36,505 protein-coding transcripts for Atlantic salmon, 35,736 for brown trout, 33,126 for Arctic charr, and 33,697 for European whitefish and are made publicly available. Assembly completeness was assessed using three approaches, all of which supported high quality of the assemblies: 1) ~78% of Actinopterygian single-copy orthologs were successfully captured in our assemblies, 2) orthogroup inference identified high overlap in the protein sequences present across all four species (40% shared across all four and 84% shared by at least two), and 3) comparison with the published Atlantic salmon genome suggests that our assemblies represent well covered (~98%) protein-coding transcriptomes. Thorough comparison of the generated assemblies found that 84-90% of transcripts in each assembly were orthologous with at least one of the other three species. We also identified 34-37% of transcripts in each assembly as paralogs. We further compare completeness and annotation statistics of our new assemblies to available related species. Conclusion New, high-confidence protein-coding transcriptomes were generated for four ecologically and economically important species of salmonids. This offers a high quality pipeline for such complex genomes, represents a valuable contribution to the existing genomic resources for these species and provides robust tools for future investigation of gene expression and sequence evolution in these and other salmonid species. Electronic supplementary material The online version of this article (10.1186/s12864-017-4379-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Madeleine Carruthers
- Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, G12 8QQ, Glasgow, UK
| | - Andrey A Yurchenko
- Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, G12 8QQ, Glasgow, UK
| | - Julian J Augley
- Glasgow Polyomics, Wolfson Wohl Cancer Research Centre, University of Glasgow, G61 1QH, Glasgow, UK.,Present Address: Fios Genomics Ltd., Nine Edinburgh Bioquarter, 9 Little France Road, Edinburgh, EH16 4UX, UK
| | - Colin E Adams
- Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, G12 8QQ, Glasgow, UK.,Scottish Centre for Ecology and the Natural Environment, University of Glasgow, Rowardennan, G63 0AW, UK
| | - Pawel Herzyk
- Glasgow Polyomics, Wolfson Wohl Cancer Research Centre, University of Glasgow, G61 1QH, Glasgow, UK.,Institute of Molecular, Cell & Systems Biology, College of Medical, Veterinary & Life Sciences, University of Glasgow, G12 8QQ, Glasgow, UK
| | - Kathryn R Elmer
- Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, G12 8QQ, Glasgow, UK.
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8
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Sequeida A, Maisey K, Imarai M. Interleukin 4/13 receptors: An overview of genes, expression and functional role in teleost fish. Cytokine Growth Factor Rev 2017; 38:66-72. [PMID: 28988781 DOI: 10.1016/j.cytogfr.2017.09.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2017] [Revised: 09/26/2017] [Accepted: 09/26/2017] [Indexed: 12/11/2022]
Abstract
In superior vertebrates, Interleukin 4 (IL-4) and Interleukin 13 (IL-13) play key and diverse roles to support immune responses acting on cell surface receptors. When stimulated, receptors activate intracellular signalling cascades switching cell phenotypes according to stimuli. In teleost fish, Interleukin 4/13 (IL-4/13) is the ancestral family cytokine related to both IL-4 and IL-13. Every private and common receptor subunit for IL-4/13 have in fish at least two paralogues and, as in mammals, soluble forms are also part of the receptor system. Reports for findings of fish IL-4/13 receptors have covered comparative analysis, transcriptomic profiles and to a lesser extent, functional analysis regarding ligand-receptor interactions and their biological effects. This review addresses available information from fish IL-4/13 receptors and discusses overall implications on teleost immunity, summarized gene induction strategies and pathogen-induced gene modulation, which may be useful tools to enhance immune response. Additionally, we present novel coding sequences for Atlantic salmon (Salmo salar) common gamma chain receptor (γC), Interleukin 13 receptor alpha 1A chain (IL-13Rα1A) and Interleukin 13 receptor alpha 1B chain (IL-13Rα1B).
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Affiliation(s)
- A Sequeida
- Laboratory of Immunology, Center for Aquatic Biotechnology, Department of Biology, Faculty of Chemistry and Biology, University of Santiago of Chile, Av. Bernardo O'Higgins, 3363 Santiago, Chile
| | - K Maisey
- Laboratory of Immunology, Center for Aquatic Biotechnology, Department of Biology, Faculty of Chemistry and Biology, University of Santiago of Chile, Av. Bernardo O'Higgins, 3363 Santiago, Chile; Laboratory of Comparative Immunology, Center for Aquatic Biotechnology, Department of Biology, Faculty of Chemistry and Biology, University of Santiago of Chile,Av. Bernardo O'Higgins, 3363 Santiago, Chile
| | - M Imarai
- Laboratory of Immunology, Center for Aquatic Biotechnology, Department of Biology, Faculty of Chemistry and Biology, University of Santiago of Chile, Av. Bernardo O'Higgins, 3363 Santiago, Chile.
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9
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Correa K, Bangera R, Figueroa R, Lhorente JP, Yáñez JM. The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar). Genet Sel Evol 2017; 49:15. [PMID: 28143593 PMCID: PMC5282780 DOI: 10.1186/s12711-017-0291-8] [Citation(s) in RCA: 77] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2016] [Accepted: 01/18/2017] [Indexed: 01/12/2023] Open
Abstract
Sea lice infestations caused by Caligus rogercresseyi are a main concern to the salmon farming industry due to associated economic losses. Resistance to this parasite was shown to have low to moderate genetic variation and its genetic architecture was suggested to be polygenic. The aim of this study was to compare accuracies of breeding value predictions obtained with pedigree-based best linear unbiased prediction (P-BLUP) methodology against different genomic prediction approaches: genomic BLUP (G-BLUP), Bayesian Lasso, and Bayes C. To achieve this, 2404 individuals from 118 families were measured for C. rogercresseyi count after a challenge and genotyped using 37 K single nucleotide polymorphisms. Accuracies were assessed using fivefold cross-validation and SNP densities of 0.5, 1, 5, 10, 25 and 37 K. Accuracy of genomic predictions increased with increasing SNP density and was higher than pedigree-based BLUP predictions by up to 22%. Both Bayesian and G-BLUP methods can predict breeding values with higher accuracies than pedigree-based BLUP, however, G-BLUP may be the preferred method because of reduced computation time and ease of implementation. A relatively low marker density (i.e. 10 K) is sufficient for maximal increase in accuracy when using G-BLUP or Bayesian methods for genomic prediction of C. rogercresseyi resistance in Atlantic salmon.
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Affiliation(s)
- Katharina Correa
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Av Santa Rosa 11735, La Pintana, Chile.,Aquainnovo, Cardonal s/n Lote B, Puerto Montt, Chile
| | - Rama Bangera
- Aquainnovo, Cardonal s/n Lote B, Puerto Montt, Chile
| | - René Figueroa
- Aquainnovo, Cardonal s/n Lote B, Puerto Montt, Chile
| | | | - José M Yáñez
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Av Santa Rosa 11735, La Pintana, Chile. .,Aquainnovo, Cardonal s/n Lote B, Puerto Montt, Chile.
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10
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Magnanou E, Noirot C, Falcón J, Jørgensen EH. Sequencing and characterization of a multi-organ Arctic charr transcriptome: A toolbox for investigating polymorphism and seasonal life in a high Arctic fish. Mar Genomics 2016; 29:45-53. [PMID: 27118202 DOI: 10.1016/j.margen.2016.04.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 04/08/2016] [Accepted: 04/08/2016] [Indexed: 02/06/2023]
Abstract
The Arctic charr (Salvelinus alpinus L.) inhabits fresh water ecosystems of the high North. The species has developed a strong phenotypic plasticity and variability in life history characteristics which has made this species an attractive model for investigations on phenotype plasticity, morph formation and ecological speciation. Further, the extreme seasonal variations in environmental conditions (e.g. food availability) in the high North induce seasonal changes in phenotype, which require precise timing mechanisms and physiological preparations. Individual gating of life-history strategies (e.g. formation of resident and sea-migrating morphs) and transitions (e.g. maturation) depends on conditional traits (size/energy status) at specific assessment time windows, and complex neuroendocrine regulation, which so far is poorly understood. In the absence of a reference genome, and in order to facilitate the investigation of the complex biological mechanisms of this unique fish model, the present study reveals a reference transcriptome for the Arctic charr. Using Roche 454 GS FLX+, we targeted various organs being either at the crossroads of many key pathways (neuroendocrine, metabolic, behavioral), of different ontological origins or displaying complementary physiological functions. The assemblage yielded 34,690 contigs greater than 1000bp with an average length (1690bp) and annotation rate (52%) within the range, or even higher, than what has been previously obtained with other teleost de novo transcriptomes. We dramatically improve the publically available transcript data on this species that may indeed be useful for various disciplines, from basic research to applied aspects related to conservation issues and aquaculture.
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Affiliation(s)
- Elodie Magnanou
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, Biologie Intégrative des Organismes Marins (BIOM), Observatoire Océanologique, F-66650, Banyuls/Mer, France.
| | - Celine Noirot
- INRA, Plateforme bioinformatique Toulouse Midi-Pyrénées, UR875 Biométrie et Intelligence Artificielle, BP 52627, 31326 Castanet-Tolosan Cedex, France
| | - Jack Falcón
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, Biologie Intégrative des Organismes Marins (BIOM), Observatoire Océanologique, F-66650, Banyuls/Mer, France
| | - Even Hjalmar Jørgensen
- Faculty of Biosciences, Fisheries and Economy, Department of Arctic and Marine Biology, UiT the Arctic University of Norway, NO-9037 Tormsø, Norway.
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11
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Yáñez JM, Naswa S, López ME, Bassini L, Correa K, Gilbey J, Bernatchez L, Norris A, Neira R, Lhorente JP, Schnable PS, Newman S, Mileham A, Deeb N, Di Genova A, Maass A. Genomewide single nucleotide polymorphism discovery in Atlantic salmon (Salmo salar): validation in wild and farmed American and European populations. Mol Ecol Resour 2016; 16:1002-11. [PMID: 26849107 DOI: 10.1111/1755-0998.12503] [Citation(s) in RCA: 92] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2015] [Revised: 01/11/2016] [Accepted: 01/16/2016] [Indexed: 11/29/2022]
Abstract
A considerable number of single nucleotide polymorphisms (SNPs) are required to elucidate genotype-phenotype associations and determine the molecular basis of important traits. In this work, we carried out de novo SNP discovery accounting for both genome duplication and genetic variation from American and European salmon populations. A total of 9 736 473 nonredundant SNPs were identified across a set of 20 fish by whole-genome sequencing. After applying six bioinformatic filtering steps, 200 K SNPs were selected to develop an Affymetrix Axiom(®) myDesign Custom Array. This array was used to genotype 480 fish representing wild and farmed salmon from Europe, North America and Chile. A total of 159 099 (79.6%) SNPs were validated as high quality based on clustering properties. A total of 151 509 validated SNPs showed a unique position in the genome. When comparing these SNPs against 238 572 markers currently available in two other Atlantic salmon arrays, only 4.6% of the SNP overlapped with the panel developed in this study. This novel high-density SNP panel will be very useful for the dissection of economically and ecologically relevant traits, enhancing breeding programmes through genomic selection as well as supporting genetic studies in both wild and farmed populations of Atlantic salmon using high-resolution genomewide information.
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Affiliation(s)
- J M Yáñez
- Faculty of Veterinary and Animal Sciences, University of Chile, Av. Santa Rosa 11735, Santiago, Chile.,Aquainnovo, Talca 60, Puerto Montt, Chile
| | - S Naswa
- Genus plc, 100 Bluegrass Commons Blvd. Suite 2200, Hendersonville, TN 37075, USA
| | - M E López
- Aquainnovo, Talca 60, Puerto Montt, Chile.,Faculty of Agricultural Sciences, University of Chile, Av. Santa Rosa 11315, Santiago, Chile
| | - L Bassini
- Aquainnovo, Talca 60, Puerto Montt, Chile.,Faculty of Agricultural Sciences, University of Chile, Av. Santa Rosa 11315, Santiago, Chile
| | - K Correa
- Faculty of Veterinary and Animal Sciences, University of Chile, Av. Santa Rosa 11735, Santiago, Chile.,Aquainnovo, Talca 60, Puerto Montt, Chile
| | - J Gilbey
- Marine Scotland Science, Freshwater Fisheries Laboratory, Faskally, Pitlochry, PH16 5LB, Scotland, UK
| | - L Bernatchez
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC G1V 0A6, Canada
| | - A Norris
- Marine Harvest, Kindrum, Fanad, C. Donegal, Ireland
| | - R Neira
- Aquainnovo, Talca 60, Puerto Montt, Chile.,Faculty of Agricultural Sciences, University of Chile, Av. Santa Rosa 11315, Santiago, Chile
| | | | - P S Schnable
- Data2Bio LLC, Ames, IA 50011, USA.,Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - S Newman
- Genus plc, 100 Bluegrass Commons Blvd. Suite 2200, Hendersonville, TN 37075, USA
| | - A Mileham
- Genus plc, 1525 River Road, DeForest, WI 53532, USA
| | - N Deeb
- Genus plc, 100 Bluegrass Commons Blvd. Suite 2200, Hendersonville, TN 37075, USA
| | - A Di Genova
- Fondap Center for Genome Regulation, Av. Blanco Encalada 2085, 3rd floor, Santiago, Chile.,Mathomics Bioinformatics Laboratory, Center for Mathematical Modeling and Center for Genome Regulation, University of Chile, Av. Blanco Encalada 2120, 7th floor, Santiago, Chile
| | - A Maass
- Fondap Center for Genome Regulation, Av. Blanco Encalada 2085, 3rd floor, Santiago, Chile.,Mathomics Bioinformatics Laboratory, Center for Mathematical Modeling and Center for Genome Regulation, University of Chile, Av. Blanco Encalada 2120, 7th floor, Santiago, Chile.,Department of Mathematical Engineering, University of Chile, Av. Blanco Encalada 2120, 5th floor, Santiago, Chile
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12
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Correa K, Lhorente JP, López ME, Bassini L, Naswa S, Deeb N, Di Genova A, Maass A, Davidson WS, Yáñez JM. Genome-wide association analysis reveals loci associated with resistance against Piscirickettsia salmonis in two Atlantic salmon (Salmo salar L.) chromosomes. BMC Genomics 2015; 16:854. [PMID: 26499328 PMCID: PMC4619534 DOI: 10.1186/s12864-015-2038-7] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2015] [Accepted: 10/08/2015] [Indexed: 12/15/2022] Open
Abstract
Background Pisciricketssia salmonis is the causal agent of Salmon Rickettsial Syndrome (SRS), which affects salmon species and causes severe economic losses. Selective breeding for disease resistance represents one approach for controlling SRS in farmed Atlantic salmon. Knowledge concerning the architecture of the resistance trait is needed before deciding on the most appropriate approach to enhance artificial selection for P. salmonis resistance in Atlantic salmon. The purpose of the study was to dissect the genetic variation in the resistance to this pathogen in Atlantic salmon. Methods 2,601 Atlantic salmon smolts were experimentally challenged against P. salmonis by means of intra-peritoneal injection. These smolts were the progeny of 40 sires and 118 dams from a Chilean breeding population. Mortalities were recorded daily and the experiment ended at day 40 post-inoculation. Fish were genotyped using a 50K Affymetrix® Axiom® myDesignTM Single Nucleotide Polymorphism (SNP) Genotyping Array. A Genome Wide Association Analysis was performed on data from the challenged fish. Linear regression and logistic regression models were tested. Results Genome Wide Association Analysis indicated that resistance to P. salmonis is a moderately polygenic trait. There were five SNPs in chromosomes Ssa01 and Ssa17 significantly associated with the traits analysed. The proportion of the phenotypic variance explained by each marker is small, ranging from 0.007 to 0.045. Candidate genes including interleukin receptors and fucosyltransferase have been found to be physically linked with these genetic markers and may play an important role in the differential immune response against this pathogen. Conclusions Due to the small amount of variance explained by each significant marker we conclude that genetic resistance to this pathogen can be more efficiently improved with the implementation of genetic evaluations incorporating genotype information from a dense SNP array. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2038-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Katharina Correa
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Av Santa Rosa 11735, Santiago, Chile.
| | | | - María E López
- Facultad de Ciencias Agronómicas, Universidad de Chile, Av Santa Rosa 11315, Santiago, Chile.
| | - Liane Bassini
- Facultad de Ciencias Agronómicas, Universidad de Chile, Av Santa Rosa 11315, Santiago, Chile.
| | - Sudhir Naswa
- Genus plc, 100 Bluegrass Commons Blvd. Suite 2200, Hendersonville, TN, 37075, USA.
| | - Nader Deeb
- Genus plc, 100 Bluegrass Commons Blvd. Suite 2200, Hendersonville, TN, 37075, USA.
| | - Alex Di Genova
- Laboratory of Bioinformatics and Mathematics of the Genome, Center for Mathematical Modeling (UMI 2807 CNRS) and Center for Genome Regulation, Universidad de Chile, Beauchef 851, Santiago, Chile.
| | - Alejandro Maass
- Laboratory of Bioinformatics and Mathematics of the Genome, Center for Mathematical Modeling (UMI 2807 CNRS) and Center for Genome Regulation, Universidad de Chile, Beauchef 851, Santiago, Chile.
| | - William S Davidson
- Department of Molecular Biology and Biochemistry, Simon Fraser University, 8888 University Drive, Burnaby, BC, Canada.
| | - José M Yáñez
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Av Santa Rosa 11735, Santiago, Chile.
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13
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Ahi EP, Steinhäuser SS, Pálsson A, Franzdóttir SR, Snorrason SS, Maier VH, Jónsson ZO. Differential expression of the aryl hydrocarbon receptor pathway associates with craniofacial polymorphism in sympatric Arctic charr. EvoDevo 2015; 6:27. [PMID: 26388986 PMCID: PMC4574265 DOI: 10.1186/s13227-015-0022-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2015] [Accepted: 09/04/2015] [Indexed: 12/03/2022] Open
Abstract
Background The developmental basis of craniofacial morphology hinges on interactions of numerous signalling systems. Extensive craniofacial variation in the polymorphic Arctic charr, a member of the salmonid family, from Lake Thingvallavatn (Iceland), offers opportunities to find and study such signalling pathways and their key regulators, thereby shedding light on the developmental pathways, and the genetics of trophic divergence. Results To identify genes involved in the craniofacial differences between benthic and limnetic Arctic charr, we used transcriptome data from different morphs, spanning early development, together with data on craniofacial expression patterns and skeletogenesis in model vertebrate species. Out of 20 genes identified, 7 showed lower gene expression in benthic than in limnetic charr morphs. We had previously identified a conserved gene network involved in extracellular matrix (ECM) organization and skeletogenesis, showing higher expression in developing craniofacial elements of benthic than in limnetic Arctic charr morphs. The present study adds a second set of genes constituting an expanded gene network with strong, benthic–limnetic differential expression. To identify putative upstream regulators, we performed knowledge-based motif enrichment analyses on the regulatory sequences of the identified genes which yielded potential binding sites for a set of known transcription factors (TFs). Of the 8 TFs that we examined using qPCR, two (Ahr2b and Ap2) were found to be differentially expressed between benthic and limnetic charr. Expression analysis of several known AhR targets indicated higher activity of the AhR pathway during craniofacial development in benthic charr morphotypes. Conclusion These results suggest a key role of the aryl hydrocarbon receptor (AhR) pathway in the observed craniofacial differences between distinct charr morphotypes. Electronic supplementary material The online version of this article (doi:10.1186/s13227-015-0022-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ehsan Pashay Ahi
- Institute of Life and Environmental Sciences, University of Iceland, Sturlugata 7, 101 Reykjavik, Iceland
| | - Sophie S Steinhäuser
- Biomedical Center, University of Iceland, Vatnsmýrarvegur 16, 101 Reykjavik, Iceland
| | - Arnar Pálsson
- Institute of Life and Environmental Sciences, University of Iceland, Sturlugata 7, 101 Reykjavik, Iceland ; Biomedical Center, University of Iceland, Vatnsmýrarvegur 16, 101 Reykjavik, Iceland
| | - Sigrídur Rut Franzdóttir
- Institute of Life and Environmental Sciences, University of Iceland, Sturlugata 7, 101 Reykjavik, Iceland
| | - Sigurdur S Snorrason
- Institute of Life and Environmental Sciences, University of Iceland, Sturlugata 7, 101 Reykjavik, Iceland
| | - Valerie H Maier
- Institute of Life and Environmental Sciences, University of Iceland, Sturlugata 7, 101 Reykjavik, Iceland ; Biomedical Center, University of Iceland, Vatnsmýrarvegur 16, 101 Reykjavik, Iceland
| | - Zophonías O Jónsson
- Institute of Life and Environmental Sciences, University of Iceland, Sturlugata 7, 101 Reykjavik, Iceland ; Biomedical Center, University of Iceland, Vatnsmýrarvegur 16, 101 Reykjavik, Iceland
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14
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Gudbrandsson J, Ahi EP, Franzdottir SR, Kapralova KH, Kristjansson BK, Steinhaeuser SS, Maier VH, Johannesson IM, Snorrason SS, Jonsson ZO, Palsson A. The developmental transcriptome of contrasting Arctic charr (Salvelinus alpinus) morphs. F1000Res 2015; 4:136. [PMID: 27635217 PMCID: PMC5007756 DOI: 10.12688/f1000research.6402.1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/10/2024] Open
Abstract
Species and populations with parallel evolution of specific traits can help illuminate how predictable adaptations and divergence are at the molecular and developmental level. Following the last glacial period, dwarfism and specialized bottom feeding morphology evolved rapidly in several landlocked Arctic charrSalvelinus alpinuspopulations in Iceland. To study the genetic divergence between small benthic morphs and limnetic morphs, we conducted RNA-sequencing charr embryos at four stages in early development. We studied two stocks with contrasting morphologies: the small benthic (SB) charr from Lake Thingvallavatn and Holar aquaculture (AC) charr.The data reveal significant differences in expression of several biological pathways during charr development. There was also an expression difference between SB- and AC-charr in genes involved in energy metabolism and blood coagulation genes. We confirmed differing expression of five genes in whole embryos with qPCR, includinglysozymeandnatterin-likewhich was previously identified as a fish-toxin of a lectin family that may be a putative immunopeptide. We also verified differential expression of 7 genes in the developing head that associated consistently with benthic v.s.limnetic morphology (studied in 4 morphs). Comparison of single nucleotide polymorphism (SNP) frequencies reveals extensive genetic differentiation between the SB and AC-charr (~1300 with more than 50% frequency difference). Curiously, three derived alleles in the otherwise conserved 12s and 16s mitochondrial ribosomal RNA genes are found in benthic charr.The data implicate multiple genes and molecular pathways in divergence of small benthic charr and/or the response of aquaculture charr to domestication. Functional, genetic and population genetic studies on more freshwater and anadromous populations are needed to confirm the specific loci and mutations relating to specific ecological traits in Arctic charr.
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15
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Gudbrandsson J, Ahi EP, Franzdottir SR, Kapralova KH, Kristjansson BK, Steinhaeuser SS, Maier VH, Johannesson IM, Snorrason SS, Jonsson ZO, Palsson A. The developmental transcriptome of contrasting Arctic charr ( Salvelinus alpinus) morphs. F1000Res 2015; 4:136. [PMID: 27635217 PMCID: PMC5007756 DOI: 10.12688/f1000research.6402.2] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/05/2016] [Indexed: 12/23/2022] Open
Abstract
Species and populations with parallel evolution of specific traits can help illuminate how predictable adaptations and divergence are at the molecular and developmental level. Following the last glacial period, dwarfism and specialized bottom feeding morphology evolved rapidly in several landlocked Arctic charr
Salvelinus alpinus populations in Iceland. To study the genetic divergence between small benthic morphs and limnetic morphs, we conducted RNA-sequencing charr embryos at four stages in early development. We studied two stocks with contrasting morphologies: the small benthic (SB) charr from Lake Thingvallavatn and Holar aquaculture (AC) charr. The data reveal significant differences in expression of several biological pathways during charr development. There was also an expression difference between SB- and AC-charr in genes involved in energy metabolism and blood coagulation genes. We confirmed differing expression of five genes in whole embryos with qPCR, including
lysozyme and
natterin-like which was previously identified as a fish-toxin of a lectin family that may be a putative immunopeptide. We also verified differential expression of 7 genes in the developing head that associated consistently with benthic v.s.limnetic morphology (studied in 4 morphs). Comparison of single nucleotide polymorphism (SNP) frequencies reveals extensive genetic differentiation between the SB and AC-charr (~1300 with more than 50% frequency difference). Curiously, three derived alleles in the otherwise conserved 12s and 16s mitochondrial ribosomal RNA genes are found in benthic charr. The data implicate multiple genes and molecular pathways in divergence of small benthic charr and/or the response of aquaculture charr to domestication. Functional, genetic and population genetic studies on more freshwater and anadromous populations are needed to confirm the specific loci and mutations relating to specific ecological traits in Arctic charr.
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Affiliation(s)
- Johannes Gudbrandsson
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Ehsan P Ahi
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Sigridur R Franzdottir
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Kalina H Kapralova
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
| | | | - S Sophie Steinhaeuser
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Valerie H Maier
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Isak M Johannesson
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Sigurdur S Snorrason
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Zophonias O Jonsson
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Arnar Palsson
- Institute of Life and Environmental Sciences, University of Iceland, Reykjavik, 101, Iceland
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16
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Smedley D, Haider S, Durinck S, Pandini L, Provero P, Allen J, Arnaiz O, Awedh MH, Baldock R, Barbiera G, Bardou P, Beck T, Blake A, Bonierbale M, Brookes AJ, Bucci G, Buetti I, Burge S, Cabau C, Carlson JW, Chelala C, Chrysostomou C, Cittaro D, Collin O, Cordova R, Cutts RJ, Dassi E, Di Genova A, Djari A, Esposito A, Estrella H, Eyras E, Fernandez-Banet J, Forbes S, Free RC, Fujisawa T, Gadaleta E, Garcia-Manteiga JM, Goodstein D, Gray K, Guerra-Assunção JA, Haggarty B, Han DJ, Han BW, Harris T, Harshbarger J, Hastings RK, Hayes RD, Hoede C, Hu S, Hu ZL, Hutchins L, Kan Z, Kawaji H, Keliet A, Kerhornou A, Kim S, Kinsella R, Klopp C, Kong L, Lawson D, Lazarevic D, Lee JH, Letellier T, Li CY, Lio P, Liu CJ, Luo J, Maass A, Mariette J, Maurel T, Merella S, Mohamed AM, Moreews F, Nabihoudine I, Ndegwa N, Noirot C, Perez-Llamas C, Primig M, Quattrone A, Quesneville H, Rambaldi D, Reecy J, Riba M, Rosanoff S, Saddiq AA, Salas E, Sallou O, Shepherd R, Simon R, Sperling L, Spooner W, Staines DM, Steinbach D, Stone K, Stupka E, Teague JW, Dayem Ullah AZ, Wang J, Ware D, et alSmedley D, Haider S, Durinck S, Pandini L, Provero P, Allen J, Arnaiz O, Awedh MH, Baldock R, Barbiera G, Bardou P, Beck T, Blake A, Bonierbale M, Brookes AJ, Bucci G, Buetti I, Burge S, Cabau C, Carlson JW, Chelala C, Chrysostomou C, Cittaro D, Collin O, Cordova R, Cutts RJ, Dassi E, Di Genova A, Djari A, Esposito A, Estrella H, Eyras E, Fernandez-Banet J, Forbes S, Free RC, Fujisawa T, Gadaleta E, Garcia-Manteiga JM, Goodstein D, Gray K, Guerra-Assunção JA, Haggarty B, Han DJ, Han BW, Harris T, Harshbarger J, Hastings RK, Hayes RD, Hoede C, Hu S, Hu ZL, Hutchins L, Kan Z, Kawaji H, Keliet A, Kerhornou A, Kim S, Kinsella R, Klopp C, Kong L, Lawson D, Lazarevic D, Lee JH, Letellier T, Li CY, Lio P, Liu CJ, Luo J, Maass A, Mariette J, Maurel T, Merella S, Mohamed AM, Moreews F, Nabihoudine I, Ndegwa N, Noirot C, Perez-Llamas C, Primig M, Quattrone A, Quesneville H, Rambaldi D, Reecy J, Riba M, Rosanoff S, Saddiq AA, Salas E, Sallou O, Shepherd R, Simon R, Sperling L, Spooner W, Staines DM, Steinbach D, Stone K, Stupka E, Teague JW, Dayem Ullah AZ, Wang J, Ware D, Wong-Erasmus M, Youens-Clark K, Zadissa A, Zhang SJ, Kasprzyk A. The BioMart community portal: an innovative alternative to large, centralized data repositories. Nucleic Acids Res 2015; 43:W589-98. [PMID: 25897122 PMCID: PMC4489294 DOI: 10.1093/nar/gkv350] [Show More Authors] [Citation(s) in RCA: 526] [Impact Index Per Article: 52.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2015] [Accepted: 04/02/2015] [Indexed: 01/17/2023] Open
Abstract
The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.
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Affiliation(s)
- Damian Smedley
- Wellcome Trust Sanger Institute, Welcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Syed Haider
- The Weatherall Institute Of Molecular Medicine, University of Oxford, Oxford, OX3 9DS, UK
| | - Steffen Durinck
- Genentech, Inc. 1 DNA Way South San Francisco, CA 94080, USA
| | - Luca Pandini
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | - Paolo Provero
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy Dept of Molecular Biotechnology and Health Sciences University of Turin, Italy
| | - James Allen
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Olivier Arnaiz
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris Sud, 1 avenue de la terrasse, 91198 Gif sur Yvette, France
| | - Mohammad Hamza Awedh
- Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Richard Baldock
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Giulia Barbiera
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | | | - Tim Beck
- Department of Genetics, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - Andrew Blake
- MRC Harwell, Harwell Science and Innovation Campus, Oxfordshire, OX11 0RD, UK
| | | | - Anthony J Brookes
- Department of Genetics, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - Gabriele Bucci
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | - Iwan Buetti
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | - Sarah Burge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | | | | | - Claude Chelala
- Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | | | - Davide Cittaro
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | | | - Raul Cordova
- International Potato Center (CIP), Lima, 1558, Peru
| | - Rosalind J Cutts
- Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Erik Dassi
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, Italy
| | - Alex Di Genova
- Center for Mathematical Modeling and Center for Genome Regulation, University of Chile, Beauchef 851, 7th floor, Chile
| | - Anis Djari
- Plate-forme bio-informatique Genotoul, Mathématiques et Informatique Appliquées de Toulouse, INRA, Castanet-Tolosan, France
| | | | | | - Eduardo Eyras
- Catalan Institute for Research and Advanced Studies (ICREA), Passeig Lluis Companys 23, E-08010 Barcelona, Spain Universitat Pompeu Fabra, Dr Aiguader 88 E-08003 Barcelona, Spain
| | | | - Simon Forbes
- Wellcome Trust Sanger Institute, Welcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Robert C Free
- Department of Genetics, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | | | - Emanuela Gadaleta
- Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Jose M Garcia-Manteiga
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | - David Goodstein
- Department of Energy, Joint Genome Institute, Walnut Creek, USA
| | - Kristian Gray
- HUGO Gene Nomenclature Committee (HGNC), European Bioinformatics Institute (EMBL-EBI) Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - José Afonso Guerra-Assunção
- Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Bernard Haggarty
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Dong-Jin Han
- Medicinal Bioconvergence Research Center, College of Pharmacy, Seoul National University, Seoul 151-742, Republic of Korea Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul 151-742, Republic of Korea
| | - Byung Woo Han
- Research Institute of Pharmaceutical Sciences, College of Pharmacy, Seoul National University, Seoul 151-742, Republic of Korea Information Center for Bio-pharmacological Network, Seoul National University, Suwon 443-270, Republic of Korea
| | - Todd Harris
- Ontario Institute for Cancer Research, Toronto, M5G 0A3, Canada
| | - Jayson Harshbarger
- RIKEN Center for Life Science Technologies (CLST), Division of Genomic Technologies (DGT), Kanagawa, 230-0045, Japan
| | - Robert K Hastings
- Department of Genetics, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - Richard D Hayes
- Department of Energy, Joint Genome Institute, Walnut Creek, USA
| | - Claire Hoede
- Plate-forme bio-informatique Genotoul, Mathématiques et Informatique Appliquées de Toulouse, INRA, Castanet-Tolosan, France
| | - Shen Hu
- School of Dentistry and Dental Research Institute, University of California Los Angeles (UCLA), Los Angeles, CA 90095-1668, USA
| | | | - Lucie Hutchins
- Mouse Genomic Informatics Group, The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Zhengyan Kan
- Oncology Computational Biology, Pfizer, La Jolla, USA
| | - Hideya Kawaji
- RIKEN Center for Life Science Technologies (CLST), Division of Genomic Technologies (DGT), Kanagawa, 230-0045, Japan RIKEN Preventive Medicine and Diagnosis Innovation Program, Saitama 351-0198, Japan
| | - Aminah Keliet
- INRA URGI Centre de Versailles, bâtiment 18 Route de Saint Cyr 78026 Versailles, France
| | - Arnaud Kerhornou
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Sunghoon Kim
- Medicinal Bioconvergence Research Center, College of Pharmacy, Seoul National University, Seoul 151-742, Republic of Korea Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul 151-742, Republic of Korea
| | - Rhoda Kinsella
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Christophe Klopp
- Plate-forme bio-informatique Genotoul, Mathématiques et Informatique Appliquées de Toulouse, INRA, Castanet-Tolosan, France
| | - Lei Kong
- Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, 100871, P.R. China
| | - Daniel Lawson
- VectorBase, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Dejan Lazarevic
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | - Ji-Hyun Lee
- Medicinal Bioconvergence Research Center, College of Pharmacy, Seoul National University, Seoul 151-742, Republic of Korea Research Institute of Pharmaceutical Sciences, College of Pharmacy, Seoul National University, Seoul 151-742, Republic of Korea Information Center for Bio-pharmacological Network, Seoul National University, Suwon 443-270, Republic of Korea
| | - Thomas Letellier
- INRA URGI Centre de Versailles, bâtiment 18 Route de Saint Cyr 78026 Versailles, France
| | - Chuan-Yun Li
- Institute of Molecular Medicine, Peking University, Beijing, China
| | - Pietro Lio
- Computer Laboratory, University of Cambridge, Cambridge, CB3 0FD, UK
| | - Chu-Jun Liu
- Institute of Molecular Medicine, Peking University, Beijing, China
| | - Jie Luo
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Alejandro Maass
- Center for Mathematical Modeling and Center for Genome Regulation, University of Chile, Beauchef 851, 7th floor, Chile Department of Mathematical Engineering, University of Chile, Av. Beauchef 851, 5th floor, Santiago, Chile
| | - Jerome Mariette
- Plate-forme bio-informatique Genotoul, Mathématiques et Informatique Appliquées de Toulouse, INRA, Castanet-Tolosan, France
| | - Thomas Maurel
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Stefania Merella
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | - Azza Mostafa Mohamed
- Departament of Biochemistry, Faculty of Science for Girls, King Abdulaziz University, Jeddah, Saudi Arabia
| | | | - Ibounyamine Nabihoudine
- Plate-forme bio-informatique Genotoul, Mathématiques et Informatique Appliquées de Toulouse, INRA, Castanet-Tolosan, France
| | - Nelson Ndegwa
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, 17177 Stockholm, Sweden
| | - Céline Noirot
- Plate-forme bio-informatique Genotoul, Mathématiques et Informatique Appliquées de Toulouse, INRA, Castanet-Tolosan, France
| | | | - Michael Primig
- Inserm U1085 IRSET, University of Rennes 1, 35042 Rennes, France
| | - Alessandro Quattrone
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, Italy
| | - Hadi Quesneville
- INRA URGI Centre de Versailles, bâtiment 18 Route de Saint Cyr 78026 Versailles, France
| | - Davide Rambaldi
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | | | - Michela Riba
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | - Steven Rosanoff
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Amna Ali Saddiq
- Department of Biological Sciences, Faculty of Science for Girls, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Elisa Salas
- International Potato Center (CIP), Lima, 1558, Peru
| | | | - Rebecca Shepherd
- Wellcome Trust Sanger Institute, Welcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | | | - Linda Sperling
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris Sud, 1 avenue de la terrasse, 91198 Gif sur Yvette, France
| | - William Spooner
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA Eagle Genomics Ltd., Babraham Research Campus, Cambridge, CB22 3AT, UK
| | - Daniel M Staines
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Delphine Steinbach
- INRA URGI Centre de Versailles, bâtiment 18 Route de Saint Cyr 78026 Versailles, France
| | - Kevin Stone
- Mouse Genomic Informatics Group, The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Elia Stupka
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy
| | - Jon W Teague
- Wellcome Trust Sanger Institute, Welcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Abu Z Dayem Ullah
- Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Jun Wang
- Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, 100871, P.R. China
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Marie Wong-Erasmus
- Human Longevity, Inc. 10835 Road to the Cure 140 San Diego, CA 92121, USA
| | - Ken Youens-Clark
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Amonida Zadissa
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Shi-Jian Zhang
- Institute of Molecular Medicine, Peking University, Beijing, China
| | - Arek Kasprzyk
- Center for Translational Genomics and Bioinformatics San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
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17
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García K, Ramírez-Araya S, Díaz Á, Reyes-Cerpa S, Espejo RT, Higuera G, Romero J. Inactivated E. coli transformed with plasmids that produce dsRNA against infectious salmon anemia virus hemagglutinin show antiviral activity when added to infected ASK cells. Front Microbiol 2015; 6:300. [PMID: 25932022 PMCID: PMC4399331 DOI: 10.3389/fmicb.2015.00300] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2014] [Accepted: 03/26/2015] [Indexed: 12/12/2022] Open
Abstract
Infectious salmon anemia virus (ISAV) has caused great losses to the Chilean salmon industry, and the success of prevention and treatment strategies is uncertain. The use of RNA interference (RNAi) is a promising approach because during the replication cycle, the ISAV genome must be transcribed to mRNA in the cytoplasm. We explored the capacity of E. coli transformed with plasmids that produce double-stranded RNA (dsRNA) to induce antiviral activity when added to infected ASK cells. We transformed the non-pathogenic Escherichia coli HT115 (DE3) with plasmids that expressed highly conserved regions of the ISAV genes encoding the nucleoprotein (NP), fusion (F), hemagglutinin (HE), and matrix (M) proteins as dsRNA, which is the precursor of the RNAi mechanism. The inactivated transformed bacteria carrying dsRNA were tested for their capacity to silence the target ISAV genes, and the dsRNA that were able to inhibit gene expression were subsequently tested for their ability to attenuate the cytopathic effect (CPE) and reduce the viral load. Of the four target genes tested, inactivated E. coli transformed with plasmids producing dsRNA targeting HE showed antiviral activity when added to infected ASK cells.
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Affiliation(s)
- Katherine García
- Laboratorio de Biotecnología, Unidad de Alimentos, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile Santiago, Chile
| | - Sebastián Ramírez-Araya
- Laboratorio de Biotecnología, Unidad de Alimentos, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile Santiago, Chile
| | - Álvaro Díaz
- Laboratorio de Biotecnología, Unidad de Alimentos, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile Santiago, Chile
| | - Sebastián Reyes-Cerpa
- Facultad de Química y Biología, Centro de Biotecnología Acuícola, Universidad de Santiago de Chile Santiago, Chile
| | - Romilio T Espejo
- Laboratorio de Biotecnología, Unidad de Alimentos, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile Santiago, Chile ; Centro Nacional de Genómica y Bioinformática (Omics Solutions) Santiago, Chile
| | - Gastón Higuera
- Laboratorio de Biotecnología, Unidad de Alimentos, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile Santiago, Chile
| | - Jaime Romero
- Laboratorio de Biotecnología, Unidad de Alimentos, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile Santiago, Chile
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Grimholt U, Hauge H, Hauge AG, Leong J, Koop BF. Chemokine receptors in Atlantic salmon. DEVELOPMENTAL AND COMPARATIVE IMMUNOLOGY 2015; 49:79-95. [PMID: 25445904 DOI: 10.1016/j.dci.2014.11.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2014] [Revised: 11/09/2014] [Accepted: 11/10/2014] [Indexed: 06/04/2023]
Abstract
Teleost sequence data have revealed that many immune genes have evolved differently when compared to other vertebrates. Thus, each gene family needs functional studies to define the biological role of individual members within major species groups. Chemokine receptors, being excellent markers for various leukocyte subpopulations, are one such example where studies are needed to decipher individual gene function. The unique salmonid whole genome duplication that occurred approximately 95 million years ago has provided salmonids with many additional duplicates further adding to the complexity and diversity. Here we have performed a systematic study of these receptors in Atlantic salmon with particular focus on potential inflammatory receptors. Using the preliminary salmon genome data we identified 48 chemokine or chemokine-like receptors including orthologues to the ten receptors previously published in trout. We found expressed support for 40 of the bona fide salmon receptors. Eighteen of the chemokine receptors are duplicated, and when tested against a diploid sister group the majority were shown to be remnants of the 4R whole genome duplication with subsequent high sequence identity. The salmon chemokine receptor repertoire of 40 expressed bona fide genes is comparably larger than that found in humans with 23 receptors. Diversification has been a major driving force for these duplicate genes with the main variability residing in ligand binding and signalling domains.
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Affiliation(s)
| | - Helena Hauge
- Norwegian Veterinary Institute, P.O. Box 750 Sentrum, 0106 Oslo, Norway
| | | | - Jong Leong
- Centre for Biomedical Research, Department of Biology, University of Victoria, PO Box 3020 STN CSC, Victoria, Canada
| | - Ben F Koop
- Centre for Biomedical Research, Department of Biology, University of Victoria, PO Box 3020 STN CSC, Victoria, Canada
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19
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Kapralova KH, Franzdóttir SR, Jónsson H, Snorrason SS, Jónsson ZO. Patterns of miRNA expression in Arctic charr development. PLoS One 2014; 9:e106084. [PMID: 25170615 PMCID: PMC4149506 DOI: 10.1371/journal.pone.0106084] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2013] [Accepted: 08/01/2014] [Indexed: 11/18/2022] Open
Abstract
Micro-RNAs (miRNAs) are now recognized as a major class of developmental regulators. Sequences of many miRNAs are highly conserved, yet they often exhibit temporal and spatial heterogeneity in expression among species and have been proposed as an important reservoir for adaptive evolution and divergence. With this in mind we studied miRNA expression during embryonic development of offspring from two contrasting morphs of the highly polymorphic salmonid Arctic charr (Salvelinus alpinus), a small benthic morph from Lake Thingvallavatn (SB) and an aquaculture stock (AC). These morphs differ extensively in morphology and adult body size. We established offspring groups of the two morphs and sampled at several time points during development. Four time points (3 embryonic and one just before first feeding) were selected for high-throughput small-RNA sequencing. We identified a total of 326 conserved and 427 novel miRNA candidates in Arctic charr, of which 51 conserved and 6 novel miRNA candidates were differentially expressed among developmental stages. Furthermore, 53 known and 19 novel miRNAs showed significantly different levels of expression in the two contrasting morphs. Hierarchical clustering of the 53 conserved miRNAs revealed that the expression differences are confined to the embryonic stages, where miRNAs such as sal-miR-130, 30, 451, 133, 26 and 199a were highly expressed in AC, whereas sal-miR-146, 183, 206 and 196a were highly expressed in SB embryos. The majority of these miRNAs have previously been found to be involved in key developmental processes in other species such as development of brain and sensory epithelia, skeletogenesis and myogenesis. Four of the novel miRNA candidates were only detected in either AC or SB. miRNA candidates identified in this study will be combined with available mRNA expression data to identify potential targets and involvement in developmental regulation.
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Affiliation(s)
- Kalina H. Kapralova
- Institute of Life- and Environmental Sciences, University of Iceland, Reykjavík, Iceland
| | | | - Hákon Jónsson
- Institute of Life- and Environmental Sciences, University of Iceland, Reykjavík, Iceland
| | - Sigurður S. Snorrason
- Institute of Life- and Environmental Sciences, University of Iceland, Reykjavík, Iceland
| | - Zophonías O. Jónsson
- Institute of Life- and Environmental Sciences, University of Iceland, Reykjavík, Iceland
- * E-mail:
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20
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Angotzi AR, Stefansson SO, Nilsen TO, Rathore RM, Rønnestad I. Molecular cloning and genomic characterization of novel leptin-like genes in salmonids provide new insight into the evolution of the Leptin gene family. Gen Comp Endocrinol 2013; 187:48-59. [PMID: 23583470 DOI: 10.1016/j.ygcen.2013.03.022] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2013] [Revised: 03/04/2013] [Accepted: 03/08/2013] [Indexed: 11/29/2022]
Abstract
In the current study we describe the identification of novel leptin B homologous gene/s in the four salmonid species Atlantic salmon (Salmo salar), rainbow trout (Oncorhynchus mykiss), brown trout (Salmo trutta) and Arctic charr (Salvelinus alpinus). Homology modeling of Salmo salar (Ss) LepB1/B2 suggests that the protein satisfies parameters as long-chain four helical cytokine family and that the basic structural pattern of the protein follows that of human leptin (Zhang et al., 1997). Importantly, the docking studies suggested the SsLepB has binding affinity to the AA residues that identify the leptin binding and FNIII domains of the SsLep receptor (Rønnestad et al., 2010). Phylogenetic analyses support that LepB paralogs have most probably originated by 4R whole genome duplication (WGD) before speciation of the salmonid lineages. LepB1 and LepB2 genes are both present in the two closest relatives, the Atlantic salmon and the brown trout, while rainbow trout and charr have only preserved the long LepB1 variant in their genome. We have defined the sites of SsLepB mRNA expression at key life stages in Atlantic salmon and found that SsLepB1 and SsLepB2, although to different extent, were expressed in redundant and mostly complementary fashion in brain and gills throughout the lifecycle, suggesting that this pair of paralogs is likely undergoing early stages of subfunctionalization. Furthermore, we have quantified the expression profiles of SsLepB genes and of other two recently duplicated salmon leptins (SsLepA1, SsLepA2) during early development and show evidence that in fish, as in mammals and amphibians, leptin could play important roles in growth and development. This study provides an essential groundwork to further elucidate structural and functional evolution of this important hormone in salmonids as well as in other teleosts.
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Affiliation(s)
- Anna R Angotzi
- Department of Biology, University of Bergen, Thormolensgate 55, Bergen 5020, Norway.
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