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Moccetti C, Sperlich N, Saboret G, Ten Brink H, Brodersen J. Migratory-derived resources induce elongated food chains through middle-up food web effects. MOVEMENT ECOLOGY 2024; 12:56. [PMID: 39164695 PMCID: PMC11337878 DOI: 10.1186/s40462-024-00496-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 07/25/2024] [Indexed: 08/22/2024]
Abstract
BACKGROUND Seasonal movements of animals often result in the transfer of large amounts of energy and nutrients across ecosystem boundaries, which may have large consequences on local food webs through various pathways. While this is known for both terrestrial- and aquatic organisms, quantitative estimates on its effects on food web structure and identification of key pathways are scarce, due to the difficulty in obtaining replication on ecosystem level with negative control, i.e. comparable systems without migration. METHODS In this study, we estimate the impact of Arctic charr (Salvelinus alpinus) migration on riverine ecosystem structure, by comparing multiple streams with strictly resident populations above natural migration barriers with streams below those barriers harboring partially migratory populations. We compared density estimates and size structure between above and below populations. Diet differences were examined through the analysis of stomach contents, changes in trophic position were examined by using stable isotopes. To infer growth rate of resident individuals, back-growth calculation was performed using otoliths. RESULTS We find higher densities of small juveniles in partially migratory populations, where juvenile Arctic charr show initially lower growth, likely due to higher intraspecific competition. After reaching a size, where they can start feeding on eggs and smaller juveniles, which are both more frequent in partially migratory populations, growth surpasses that of resident populations. Cannibalism induced by high juvenile densities occurred almost exclusively in populations with migration and represents an altered energy pathway to the food web. The presence of large cannibalistic charr feeding on smaller ones that have a similar trophic level as charr from strictly resident populations (based on stomach content) coupled with steeper δ15N-size regression slopes illustrate the general increase of food chain length in systems with migration. CONCLUSIONS Our results thus suggest that the consumption of migration-derived resources may result in longer food chains through middle-up rather than bottom-up effects. Furthermore, by occupying the apex of the food chain and feeding on juvenile conspecifics, resident individuals experience reduced competition with their young counterparts, which potentially balances their fitness with migratory individuals.
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Affiliation(s)
- Coralie Moccetti
- Department of Fish Ecology and Evolution, Center for Ecology, Evolution & Biogeochemistry, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum, 6047, Switzerland.
- Division Aquatic Ecology & Evolution, Institute of Ecology and Evolution, University of Bern, Bern, 3012, Switzerland.
| | - Nicola Sperlich
- Department of Fish Ecology and Evolution, Center for Ecology, Evolution & Biogeochemistry, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum, 6047, Switzerland
| | - Grégoire Saboret
- Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, Universitätstrasse 16, Zürich, 8092, Switzerland
- Department of Surface Waters; Biogeochemistry, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum, 6047, Switzerland
| | - Hanna Ten Brink
- Department of Fish Ecology and Evolution, Center for Ecology, Evolution & Biogeochemistry, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum, 6047, Switzerland
- Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, PO Box 94240, Amsterdam, 1090 GE, The Netherlands
- Department of Coastal Systems, NIOZ Royal Netherlands Institute for Sea Research, PO Box 59, Den Burg Texel, 1790 AB, The Netherlands
| | - Jakob Brodersen
- Department of Fish Ecology and Evolution, Center for Ecology, Evolution & Biogeochemistry, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum, 6047, Switzerland
- Division Aquatic Ecology & Evolution, Institute of Ecology and Evolution, University of Bern, Bern, 3012, Switzerland
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2
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Effects of Early Thermal Environment on Growth, Age at Maturity, and Sexual Size Dimorphism in Arctic Charr. JOURNAL OF MARINE SCIENCE AND ENGINEERING 2022. [DOI: 10.3390/jmse10020167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
The effects of early thermal environment on growth, age at maturity, and sexual size dimorphism in Arctic charr (Salvelinus alpinus) are investigated. This study is a 654-day long rearing trial split into two sequential experimental phases termed EP1 and EP2 and lasting 315 and 339 days, respectively. EP1 started at the end of the yolk sac stage when the experimental fish were divided into three groups and reared at different target temperatures (7, 10 and 12 °C). During EP2, all groups were reared at the same temperature (7–8 °C) until harvest (~1300 g). Growth rates increased with temperature from 7 to 12 °C, and at the end of EP1 the 12C group had 49.0% and 19.2% higher mean weight than groups 7C and 10C, respectively. Elevated early rearing temperatures were, however, found to cause precocious sexual maturation and reduce the long-term growth performance. At the end of EP2, the 7C group had 3.6% and 14.1% higher mean weight than 10C and 12C, respectively. Elevated early rearing temperatures had a much stronger effect on the maturity incidence of females, and while male-biased sexual size dimorphism (SSD) was found in all groups, the magnitude of SSD was positively associated with temperature.
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Pappas F, Palaiokostas C. Genotyping Strategies Using ddRAD Sequencing in Farmed Arctic Charr ( Salvelinus alpinus). Animals (Basel) 2021; 11:899. [PMID: 33801139 PMCID: PMC8004150 DOI: 10.3390/ani11030899] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/13/2021] [Accepted: 03/16/2021] [Indexed: 12/17/2022] Open
Abstract
Incorporation of genomic technologies into fish breeding programs is a modern reality, promising substantial advances regarding the accuracy of selection, monitoring the genetic diversity and pedigree record verification. Single nucleotide polymorphism (SNP) arrays are the most commonly used genomic tool, but the investments required make them unsustainable for emerging species, such as Arctic charr (Salvelinus alpinus), where production volume is low. The requirement to genotype a large number of animals for breeding practices necessitates cost effective genotyping approaches. In the current study, we used double digest restriction site-associated DNA (ddRAD) sequencing of either high or low coverage to genotype Arctic charr from the Swedish national breeding program and performed analytical procedures to assess their utility in a range of tasks. SNPs were identified and used for deciphering the genetic structure of the studied population, estimating genomic relationships and implementing an association study for growth-related traits. Missing information and underestimation of heterozygosity in the low coverage set were limiting factors in genetic diversity and genomic relationship analyses, where high coverage performed notably better. On the other hand, the high coverage dataset proved to be valuable when it comes to identifying loci that are associated with phenotypic traits of interest. In general, both genotyping strategies offer sustainable alternatives to hybridization-based genotyping platforms and show potential for applications in aquaculture selective breeding.
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Affiliation(s)
| | - Christos Palaiokostas
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, P.O. Box 7090, 750 07 Uppsala, Sweden;
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4
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D'Ambrosio J, Morvezen R, Brard-Fudulea S, Bestin A, Acin Perez A, Guéméné D, Poncet C, Haffray P, Dupont-Nivet M, Phocas F. Genetic architecture and genomic selection of female reproduction traits in rainbow trout. BMC Genomics 2020; 21:558. [PMID: 32795250 PMCID: PMC7430828 DOI: 10.1186/s12864-020-06955-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Accepted: 07/27/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Rainbow trout is a significant fish farming species under temperate climates. Female reproduction traits play an important role in the economy of breeding companies with the sale of fertilized eggs. The objectives of this study are threefold: to estimate the genetic parameters of female reproduction traits, to determine the genetic architecture of these traits by the identification of quantitative trait loci (QTL), and to assess the expected efficiency of a pedigree-based selection (BLUP) or genomic selection for these traits. RESULTS A pedigreed population of 1343 trout were genotyped for 57,000 SNP markers and phenotyped for seven traits at 2 years of age: spawning date, female body weight before and after spawning, the spawn weight and the egg number of the spawn, the egg average weight and average diameter. Genetic parameters were estimated in multi-trait linear animal models. Heritability estimates were moderate, varying from 0.27 to 0.44. The female body weight was not genetically correlated to any of the reproduction traits. Spawn weight showed strong and favourable genetic correlation with the number of eggs in the spawn and individual egg size traits, but the egg number was uncorrelated to the egg size traits. The genome-wide association studies showed that all traits were very polygenic since less than 10% of the genetic variance was explained by the cumulative effects of the QTLs: for any trait, only 2 to 4 QTLs were detected that explained in-between 1 and 3% of the genetic variance. Genomic selection based on a reference population of only one thousand individuals related to candidates would improve the efficiency of BLUP selection from 16 to 37% depending on traits. CONCLUSIONS Our genetic parameter estimates made unlikely the hypothesis that selection for growth could induce any indirect improvement for female reproduction traits. It is thus important to consider direct selection for spawn weight for improving egg production traits in rainbow trout breeding programs. Due to the low proportion of genetic variance explained by the few QTLs detected for each reproduction traits, marker assisted selection cannot be effective. However genomic selection would allow significant gains of accuracy compared to pedigree-based selection.
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Affiliation(s)
- J D'Ambrosio
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
- SYSAAF, Station INRAE-LPGP, Campus de Beaulieu, 35042, Rennes cedex, France
| | - R Morvezen
- SYSAAF, Station INRAE-LPGP, Campus de Beaulieu, 35042, Rennes cedex, France
| | - S Brard-Fudulea
- SYSAAF, Section Avicole, Centre INRAE Val de Loire, 37380, Nouzilly, France
| | - A Bestin
- SYSAAF, Station INRAE-LPGP, Campus de Beaulieu, 35042, Rennes cedex, France
| | - A Acin Perez
- Viviers de Sarrance, Pisciculture Labedan, 64490, Sarrance, France
| | - D Guéméné
- SYSAAF, Section Avicole, Centre INRAE Val de Loire, 37380, Nouzilly, France
| | - C Poncet
- Université Clermont-Auvergne, INRAE, GDEC, 63039, Clermont-Ferrand, France
| | - P Haffray
- SYSAAF, Station INRAE-LPGP, Campus de Beaulieu, 35042, Rennes cedex, France
| | - M Dupont-Nivet
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - F Phocas
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
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Nugent CM, Leong JS, Christensen KA, Rondeau EB, Brachmann MK, Easton AA, Ouellet-Fagg CL, Crown MTT, Davidson WS, Koop BF, Danzmann RG, Ferguson MM. Design and characterization of an 87k SNP genotyping array for Arctic charr (Salvelinus alpinus). PLoS One 2019; 14:e0215008. [PMID: 30951561 PMCID: PMC6450613 DOI: 10.1371/journal.pone.0215008] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 03/25/2019] [Indexed: 11/21/2022] Open
Abstract
We have generated a high-density, high-throughput genotyping array for characterizing genome-wide variation in Arctic charr (Salvelinus alpinus). Novel single nucleotide polymorphisms (SNPs) were identified in charr from the Fraser, Nauyuk and Tree River aquaculture strains, which originated from northern Canada and fish from Iceland using high coverage sequencing, reduced representation sequencing and RNA-seq datasets. The array was designed to capture genome-wide variation from a diverse suite of Arctic charr populations. Cross validation of SNPs from various sources and comparison with previously published Arctic charr SNP data provided a set of candidate SNPs that generalize across populations. Further candidate SNPs were identified based on minor allele frequency, association with RNA transcripts, even spacing across intergenic regions and association with the sex determining (sdY) gene. The performance of the 86,503 SNP array was assessed by genotyping Fraser, Nauyuk and Tree River strain individuals, as well as wild Icelandic Arctic charr. Overall, 63,060 of the SNPs were polymorphic within at least one group and 36.8% were unique to one of the four groups, suggesting that the array design allows for characterization of both within and across population genetic diversity. The concordance between sdY markers and known phenotypic sex indicated that the array can accurately determine the sex of individuals based on genotype alone. The Salp87k genotyping array provides researchers and breeders the opportunity to analyze genetic variation in Arctic charr at a more detailed level than previously possible.
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Affiliation(s)
- Cameron M. Nugent
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
| | - Jong S. Leong
- University of Victoria, Department of Biology, Victoria, British Columbia, Canada
| | - Kris A. Christensen
- Fisheries and Oceans Canada, Centre for Aquaculture and Environmental Research, West Vancouver, British Columbia, Canada
| | - Eric B. Rondeau
- Fisheries and Oceans Canada, Centre for Aquaculture and Environmental Research, West Vancouver, British Columbia, Canada
| | - Matthew K. Brachmann
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
| | - Anne A. Easton
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
| | | | - Michelle T. T. Crown
- Simon Fraser University, Molecular Biology and Biochemistry, Burnaby, British Columbia, Canada
| | - William S. Davidson
- Simon Fraser University, Molecular Biology and Biochemistry, Burnaby, British Columbia, Canada
| | - Ben F. Koop
- University of Victoria, Department of Biology, Victoria, British Columbia, Canada
| | - Roy G. Danzmann
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
| | - Moira M. Ferguson
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
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6
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Zenger KR, Khatkar MS, Jones DB, Khalilisamani N, Jerry DR, Raadsma HW. Genomic Selection in Aquaculture: Application, Limitations and Opportunities With Special Reference to Marine Shrimp and Pearl Oysters. Front Genet 2019; 9:693. [PMID: 30728827 PMCID: PMC6351666 DOI: 10.3389/fgene.2018.00693] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 12/11/2018] [Indexed: 11/20/2022] Open
Abstract
Within aquaculture industries, selection based on genomic information (genomic selection) has the profound potential to change genetic improvement programs and production systems. Genomic selection exploits the use of realized genomic relationships among individuals and information from genome-wide markers in close linkage disequilibrium with genes of biological and economic importance. We discuss the technical advances, practical requirements, and commercial applications that have made genomic selection feasible in a range of aquaculture industries, with a particular focus on molluscs (pearl oysters, Pinctada maxima) and marine shrimp (Litopenaeus vannamei and Penaeus monodon). The use of low-cost genome sequencing has enabled cost-effective genotyping on a large scale and is of particular value for species without a reference genome or access to commercial genotyping arrays. We highlight the pitfalls and offer the solutions to the genotyping by sequencing approach and the building of appropriate genetic resources to undertake genomic selection from first-hand experience. We describe the potential to capture large-scale commercial phenotypes based on image analysis and artificial intelligence through machine learning, as inputs for calculation of genomic breeding values. The application of genomic selection over traditional aquatic breeding programs offers significant advantages through being able to accurately predict complex polygenic traits including disease resistance; increasing rates of genetic gain; minimizing inbreeding; and negating potential limiting effects of genotype by environment interactions. Further practical advantages of genomic selection through the use of large-scale communal mating and rearing systems are highlighted, as well as presenting rate-limiting steps that impact on attaining maximum benefits from adopting genomic selection. Genomic selection is now at the tipping point where commercial applications can be readily adopted and offer significant short- and long-term solutions to sustainable and profitable aquaculture industries.
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Affiliation(s)
- Kyall R Zenger
- Centre for Sustainable Tropical Fisheries and Aquaculture, College of Science and Engineering, James Cook University, Townsville, QLD, Australia.,ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia
| | - Mehar S Khatkar
- ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia.,Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, Australia
| | - David B Jones
- Centre for Sustainable Tropical Fisheries and Aquaculture, College of Science and Engineering, James Cook University, Townsville, QLD, Australia
| | - Nima Khalilisamani
- ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia.,Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, Australia
| | - Dean R Jerry
- Centre for Sustainable Tropical Fisheries and Aquaculture, College of Science and Engineering, James Cook University, Townsville, QLD, Australia.,ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia.,Tropical Futures Institute, James Cook University Singapore, Singapore, Singapore
| | - Herman W Raadsma
- ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia.,Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, Australia
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7
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Kodama M, Hard JJ, Naish KA. Mapping of quantitative trait loci for temporal growth and age at maturity in coho salmon: Evidence for genotype-by-sex interactions. Mar Genomics 2018; 38:33-44. [DOI: 10.1016/j.margen.2017.07.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 07/01/2017] [Accepted: 07/22/2017] [Indexed: 11/26/2022]
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8
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Pang M, Fu B, Yu X, Liu H, Wang X, Yin Z, Xie S, Tong J. Quantitative trait loci mapping for feed conversion efficiency in crucian carp (Carassius auratus). Sci Rep 2017; 7:16971. [PMID: 29209087 PMCID: PMC5717303 DOI: 10.1038/s41598-017-17269-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 11/21/2017] [Indexed: 11/29/2022] Open
Abstract
QTL is a chromosomal region including single gene or gene clusters that determine a quantitative trait. While feed efficiency is highly important in aquaculture fish, little genetic and genomic progresses have been made for this trait. In this study, we constructed a high-resolution genetic linkage map in a full-sib F1 family of crucian carp (Carassius auratus) consisting of 113 progenies with 8,460 SNP markers assigning onto 50 linkage groups (LGs). This genetic map spanned 4,047.824 cM (0.478 cM/marker) and covered 98.76% of the crucian carp genome. 35 chromosome-wide QTL affecting feed conversion efficiency (FCE, 8 QTL), relative growth rate (RGR, 9 QTL), average daily gain (ADG, 13 QTL) and average daily feed intake (ADFI, 5 QTL) were detected on 14 LGs, explaining 14.0–20.9% of the phenotypic variations. In LGs of LG16, LG25, LG36 and LG49, several QTL affecting different traits clustered together at the identical or close regions of the same linkage group. Seven candidate genes, whose biological functions may involve in the energy metabolism, digestion, biosynthesis and signal transduction, were identified from these QTL intervals by comparative genomics analysis. These results provide a basis for elucidating genetic mechanism of feed efficiency and potential marker-assisted selection in crucian carp.
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Affiliation(s)
- Meixia Pang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.,University of Chinese Academy of Sciences, Beijing, 100039, China
| | - Beide Fu
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Xiaomu Yu
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Haiyang Liu
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.,University of Chinese Academy of Sciences, Beijing, 100039, China
| | - Xinhua Wang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.,University of Chinese Academy of Sciences, Beijing, 100039, China
| | - Zhan Yin
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Shouqi Xie
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Jingou Tong
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.
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Abdelrahman H, ElHady M, Alcivar-Warren A, Allen S, Al-Tobasei R, Bao L, Beck B, Blackburn H, Bosworth B, Buchanan J, Chappell J, Daniels W, Dong S, Dunham R, Durland E, Elaswad A, Gomez-Chiarri M, Gosh K, Guo X, Hackett P, Hanson T, Hedgecock D, Howard T, Holland L, Jackson M, Jin Y, Khalil K, Kocher T, Leeds T, Li N, Lindsey L, Liu S, Liu Z, Martin K, Novriadi R, Odin R, Palti Y, Peatman E, Proestou D, Qin G, Reading B, Rexroad C, Roberts S, Salem M, Severin A, Shi H, Shoemaker C, Stiles S, Tan S, Tang KFJ, Thongda W, Tiersch T, Tomasso J, Prabowo WT, Vallejo R, van der Steen H, Vo K, Waldbieser G, Wang H, Wang X, Xiang J, Yang Y, Yant R, Yuan Z, Zeng Q, Zhou T. Aquaculture genomics, genetics and breeding in the United States: current status, challenges, and priorities for future research. BMC Genomics 2017; 18:191. [PMID: 28219347 PMCID: PMC5319170 DOI: 10.1186/s12864-017-3557-1] [Citation(s) in RCA: 83] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 02/06/2017] [Indexed: 12/31/2022] Open
Abstract
Advancing the production efficiency and profitability of aquaculture is dependent upon the ability to utilize a diverse array of genetic resources. The ultimate goals of aquaculture genomics, genetics and breeding research are to enhance aquaculture production efficiency, sustainability, product quality, and profitability in support of the commercial sector and for the benefit of consumers. In order to achieve these goals, it is important to understand the genomic structure and organization of aquaculture species, and their genomic and phenomic variations, as well as the genetic basis of traits and their interrelationships. In addition, it is also important to understand the mechanisms of regulation and evolutionary conservation at the levels of genome, transcriptome, proteome, epigenome, and systems biology. With genomic information and information between the genomes and phenomes, technologies for marker/causal mutation-assisted selection, genome selection, and genome editing can be developed for applications in aquaculture. A set of genomic tools and resources must be made available including reference genome sequences and their annotations (including coding and non-coding regulatory elements), genome-wide polymorphic markers, efficient genotyping platforms, high-density and high-resolution linkage maps, and transcriptome resources including non-coding transcripts. Genomic and genetic control of important performance and production traits, such as disease resistance, feed conversion efficiency, growth rate, processing yield, behaviour, reproductive characteristics, and tolerance to environmental stressors like low dissolved oxygen, high or low water temperature and salinity, must be understood. QTL need to be identified, validated across strains, lines and populations, and their mechanisms of control understood. Causal gene(s) need to be identified. Genetic and epigenetic regulation of important aquaculture traits need to be determined, and technologies for marker-assisted selection, causal gene/mutation-assisted selection, genome selection, and genome editing using CRISPR and other technologies must be developed, demonstrated with applicability, and application to aquaculture industries.Major progress has been made in aquaculture genomics for dozens of fish and shellfish species including the development of genetic linkage maps, physical maps, microarrays, single nucleotide polymorphism (SNP) arrays, transcriptome databases and various stages of genome reference sequences. This paper provides a general review of the current status, challenges and future research needs of aquaculture genomics, genetics, and breeding, with a focus on major aquaculture species in the United States: catfish, rainbow trout, Atlantic salmon, tilapia, striped bass, oysters, and shrimp. While the overall research priorities and the practical goals are similar across various aquaculture species, the current status in each species should dictate the next priority areas within the species. This paper is an output of the USDA Workshop for Aquaculture Genomics, Genetics, and Breeding held in late March 2016 in Auburn, Alabama, with participants from all parts of the United States.
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Affiliation(s)
- Hisham Abdelrahman
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Mohamed ElHady
- Department of Biological Sciences, Auburn University, Auburn, AL, 36849, USA
| | | | - Standish Allen
- Aquaculture Genetics & Breeding Technology Center, Virginia Institute of Marine Science, Gloucester Point, VA, 23062, USA
| | - Rafet Al-Tobasei
- Department of Biology, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
| | - Lisui Bao
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ben Beck
- Aquatic Animal Health Research Unit, USDA-ARS, 990 Wire Road, Auburn, AL, 36832, USA
| | - Harvey Blackburn
- USDA-ARS-NL Wheat & Corn Collections at a Glance GRP, National Animal Germplasm Program, 1111 S. Mason St., Fort Collins, CO, 80521-4500, USA
| | - Brian Bosworth
- USDA-ARS/CGRU, 141 Experimental Station Road, Stoneville, MS, 38701, USA
| | - John Buchanan
- Center for Aquaculture Technologies, 8395 Camino Santa Fe, Suite E, San Diego, CA, 92121, USA
| | - Jesse Chappell
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - William Daniels
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Sheng Dong
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Rex Dunham
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Evan Durland
- Department of Fisheries and Wildlife, Oregon State University, Corvallis, OR, 97331, USA
| | - Ahmed Elaswad
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Marta Gomez-Chiarri
- Department of Fisheries, Animal & Veterinary Science, 134 Woodward Hall, 9 East Alumni Avenue, Kingston, RI, 02881, USA
| | - Kamal Gosh
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ximing Guo
- Haskin Shellfish Research Laboratory, Department of Marine and Coastal Sciences, Rutgers University, 6959 Miller Avenue, Port Norris, NJ, 08349, USA
| | - Perry Hackett
- Department of Genetics, Cell Biology and Development, 5-108 MCB, 420 Washington Avenue SE, Minneapolis, MN, 55455, USA
| | - Terry Hanson
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Dennis Hedgecock
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089-0371, USA
| | - Tiffany Howard
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Leigh Holland
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Molly Jackson
- Taylor Shellfish Farms, 130 SE Lynch RD, Shelton, WA, 98584, USA
| | - Yulin Jin
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Karim Khalil
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Thomas Kocher
- Department of Biology, University of Maryland, 2132 Biosciences Research Building, College Park, MD, 20742, USA
| | - Tim Leeds
- National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, 25430, USA
| | - Ning Li
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Lauren Lindsey
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Shikai Liu
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zhanjiang Liu
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
| | - Kyle Martin
- Troutlodge, 27090 Us Highway 12, Naches, WA, 98937, USA
| | - Romi Novriadi
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ramjie Odin
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yniv Palti
- National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, 25430, USA
| | - Eric Peatman
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Dina Proestou
- USDA ARS NEA NCWMAC Shellfish Genetics at the University Rhode Island, 469 CBLS, 120 Flagg Road, Kingston, RI, 02881, USA
| | - Guyu Qin
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Benjamin Reading
- Department of Applied Ecology, North Carolina State University, Raleigh, NC, 27695-7617, USA
| | - Caird Rexroad
- USDA ARS Office of National Programs, George Washington Carver Center Room 4-2106, 5601 Sunnyside Avenue, Beltsville, MD, 20705, USA
| | - Steven Roberts
- School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, 98105, USA
| | - Mohamed Salem
- Department of Biology, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
| | - Andrew Severin
- Genome Informatics Facility, Office of Biotechnology, Iowa State University, Ames, IA, 50011, USA
| | - Huitong Shi
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Craig Shoemaker
- Aquatic Animal Health Research Unit, USDA-ARS, 990 Wire Road, Auburn, AL, 36832, USA
| | - Sheila Stiles
- USDOC/NOAA, National Marine Fisheries Service, NEFSC, Milford Laboratory, Milford, Connectcut, 06460, USA
| | - Suxu Tan
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Kathy F J Tang
- School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ, 85721, USA
| | - Wilawan Thongda
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Terrence Tiersch
- Aquatic Germplasm and Genetic Resources Center, School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA, 70820, USA
| | - Joseph Tomasso
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Wendy Tri Prabowo
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Roger Vallejo
- National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, 25430, USA
| | | | - Khoi Vo
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Geoff Waldbieser
- USDA-ARS/CGRU, 141 Experimental Station Road, Stoneville, MS, 38701, USA
| | - Hanping Wang
- Aquaculture Genetics and Breeding Laboratory, The Ohio State University South Centers, Piketon, OH, 45661, USA
| | - Xiaozhu Wang
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Jianhai Xiang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
| | - Yujia Yang
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Roger Yant
- Hybrid Catfish Company, 1233 Montgomery Drive, Inverness, MS, 38753, USA
| | - Zihao Yuan
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Qifan Zeng
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Tao Zhou
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
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Genome-Wide Mapping of Growth-Related Quantitative Trait Loci in Orange-Spotted Grouper (Epinephelus coioides) Using Double Digest Restriction-Site Associated DNA Sequencing (ddRADseq). Int J Mol Sci 2016; 17:501. [PMID: 27058532 PMCID: PMC4848957 DOI: 10.3390/ijms17040501] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Revised: 03/28/2016] [Accepted: 03/29/2016] [Indexed: 12/19/2022] Open
Abstract
Mapping of quantitative trait loci (QTL) is essential for the discovery of genetic structures that related to complex quantitative traits. In this study, we identified 264,072 raw SNPs (single-nucleotide polymorphisms) by double digest restriction site associated DNA sequencing (ddRADseq), and utilized 3029 of these SNPs to construct a genetic linkage map in orange-spotted grouper (Epinephelus coioides) using a regression mapping algorithm. The genetic map contained 24 linkage groups (LGs) spanning a total genetic distance of 1231.98 cM. Twenty-seven significant growth-related QTLs were identified. Furthermore, we identified 17 genes (fez2, alg3, ece2, arvcf, sla27a4, sgk223, camk2, prrc2b, mchr1, sardh, pappa, syk, tert, wdrcp91, ftz-f1, mate1 and notch1) including three (tert, ftz-f1 and notch1) that have been reported to be involved in fish growth. To summarize, we mapped growth-related QTLs in the orange-spotted grouper. These QTLs will be useful in marker-assisted selection (MAS) efforts to improve growth-related traits in this economically important fish.
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11
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Kocmarek AL, Ferguson MM, Danzmann RG. Co-localization of growth QTL with differentially expressed candidate genes in rainbow trout. Genome 2015; 58:393-403. [PMID: 26360524 DOI: 10.1139/gen-2015-0047] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
We tested whether genes differentially expressed between large and small rainbow trout co-localized with familial QTL regions for body size. Eleven chromosomes, known from previous work to house QTL for weight and length in rainbow trout, were examined for QTL in half-sibling families produced in September (1 XY male and 1 XX neomale) and December (1 XY male). In previous studies, we identified 108 candidate genes for growth expressed in the liver and white muscle in a subset of the fish used in this study. These gene sequences were BLASTN aligned against the rainbow trout and stickleback genomes to determine their location (rainbow trout) and inferred location based on synteny with the stickleback genome. Across the progeny of all three males used in the study, 63.9% of the genes with differential expression appear to co-localize with the QTL regions on 6 of the 11 chromosomes tested in these males. Genes that co-localized with QTL in the mixed-sex offspring of the two XY males primarily showed up-regulation in the muscle of large fish and were related to muscle growth, metabolism, and the stress response.
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Affiliation(s)
- Andrea L Kocmarek
- Department of Integrative Biology, 50 Stone Rd. East, University of Guelph, Guelph, ON N1G 2W1, Canada.,Department of Integrative Biology, 50 Stone Rd. East, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Moira M Ferguson
- Department of Integrative Biology, 50 Stone Rd. East, University of Guelph, Guelph, ON N1G 2W1, Canada.,Department of Integrative Biology, 50 Stone Rd. East, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Roy G Danzmann
- Department of Integrative Biology, 50 Stone Rd. East, University of Guelph, Guelph, ON N1G 2W1, Canada.,Department of Integrative Biology, 50 Stone Rd. East, University of Guelph, Guelph, ON N1G 2W1, Canada
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12
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Ulloa PE, Rincón G, Islas-Trejo A, Araneda C, Iturra P, Neira R, Medrano JF. RNA sequencing to study gene expression and SNP variations associated with growth in zebrafish fed a plant protein-based diet. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2015; 17:353-63. [PMID: 25702041 DOI: 10.1007/s10126-015-9624-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2014] [Accepted: 01/16/2015] [Indexed: 05/16/2023]
Abstract
The objectives of this study were to measure gene expression in zebrafish and then identify SNP to be used as potential markers in a growth association study. We developed an approach where muscle samples collected from low- and high-growth fish were analyzed using RNA-Sequencing (RNA-seq), and SNP were chosen from the genes that were differentially expressed between the low and high groups. A population of 24 families was fed a plant protein-based diet from the larval to adult stages. From a total of 440 males, 5 % of the fish from both tails of the weight gain distribution were selected. Total RNA was extracted from individual muscle of 8 low-growth and 8 high-growth fish. Two pooled RNA-Seq libraries were prepared for each phenotype using 4 fish per library. Libraries were sequenced using the Illumina GAII Sequencer and analyzed using the CLCBio genomic workbench software. One hundred and twenty-four genes were differentially expressed between phenotypes (p value < 0.05 and FDR < 0.2). From these genes, 164 SNP were selected and genotyped in 240 fish samples. Marker-trait analysis revealed 5 SNP associated with growth in key genes (Nars, Lmod2b, Cuzd1, Acta1b, and Plac8l1). These genes are good candidates for further growth studies in fish and to consider for identification of potential SNPs associated with different growth rates in response to a plant protein-based diet.
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Affiliation(s)
- Pilar E Ulloa
- Programa de Doctorado en Ciencias de Recursos Naturales, Universidad de La Frontera, Casilla 54-D, Temuco, Chile,
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Tsai HY, Hamilton A, Guy DR, Tinch AE, Bishop SC, Houston RD. The genetic architecture of growth and fillet traits in farmed Atlantic salmon (Salmo salar). BMC Genet 2015; 16:51. [PMID: 25985885 PMCID: PMC4436873 DOI: 10.1186/s12863-015-0215-y] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2015] [Accepted: 05/11/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Performance and quality traits such as harvest weight, fillet weight and flesh color are of economic importance to the Atlantic salmon aquaculture industry. The genetic factors underlying these traits are of scientific and commercial interest. However, such traits are typically polygenic in nature, with the number and size of QTL likely to vary between studies and populations. The aim of this study was to investigate the genetic basis of several growth and fillet traits measured at harvest in a large farmed salmon population by using SNP markers. Due to the marked heterochiasmy in salmonids, an efficient two-stage mapping approach was applied whereby QTL were detected using a sire-based linkage analysis, a sparse SNP marker map and exploiting low rates of recombination, while a subsequent dam-based analysis focused on the significant chromosomes with a denser map to confirm QTL and estimate their position. RESULTS The harvest traits all showed significant heritability, ranging from 0.05 for fillet yield up to 0.53 for the weight traits. In the sire-based analysis, 1695 offspring with trait records and their 20 sires were successfully genotyped for the SNPs on the sparse map. Chromosomes 13, 18, 19 and 20 were shown to harbor genome-wide significant QTL affecting several growth-related traits. The QTL on chr. 13, 18 and 20 were detected in the dam-based analysis using 512 offspring from 10 dams and explained approximately 6-7 % of the within-family variation in these traits. CONCLUSIONS We have detected several QTL affecting economically important complex traits in a commercial salmon population. Overall, the results suggest that the traits are relatively polygenic and that QTL tend to be pleiotropic (affecting the weight of several components of the harvested fish). Comparison of QTL regions across studies suggests that harvest trait QTL tend to be relatively population-specific. Therefore, the application of marker or genomic selection for improvement in these traits is likely to be most effective when the discovery population is closely related to the selection candidates (e.g. within-family genomic selection).
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Affiliation(s)
- Hsin Yuan Tsai
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG, UK.
| | - Alastair Hamilton
- Landcatch Natural Selection Ltd., 15 Beta Centre, Stirling University Innovation Park, Stirling, FK9 4NF, UK.
| | - Derrick R Guy
- Landcatch Natural Selection Ltd., 15 Beta Centre, Stirling University Innovation Park, Stirling, FK9 4NF, UK.
| | - Alan E Tinch
- Landcatch Natural Selection Ltd., 15 Beta Centre, Stirling University Innovation Park, Stirling, FK9 4NF, UK.
| | - Stephen C Bishop
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG, UK.
| | - Ross D Houston
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG, UK.
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Genome-wide association study (GWAS) for growth rate and age at sexual maturation in Atlantic salmon (Salmo salar). PLoS One 2015; 10:e0119730. [PMID: 25757012 PMCID: PMC4355585 DOI: 10.1371/journal.pone.0119730] [Citation(s) in RCA: 112] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Accepted: 01/25/2015] [Indexed: 11/26/2022] Open
Abstract
Early sexual maturation is considered a serious drawback for Atlantic salmon aquaculture as it retards growth, increases production times and affects flesh quality. Although both growth and sexual maturation are thought to be complex processes controlled by several genetic and environmental factors, selection for these traits has been continuously accomplished since the beginning of Atlantic salmon selective breeding programs. In this genome-wide association study (GWAS) we used a 6.5K single-nucleotide polymorphism (SNP) array to genotype ∼480 individuals from the Cermaq Canada broodstock program and search for SNPs associated with growth and age at sexual maturation. Using a mixed model approach we identified markers showing a significant association with growth, grilsing (early sexual maturation) and late sexual maturation. The most significant associations were found for grilsing, with markers located in Ssa10, Ssa02, Ssa13, Ssa25 and Ssa12, and for late maturation with markers located in Ssa28, Ssa01 and Ssa21. A lower level of association was detected with growth on Ssa13. Candidate genes, which were linked to these genetic markers, were identified and some of them show a direct relationship with developmental processes, especially for those in association with sexual maturation. However, the relatively low power to detect genetic markers associated with growth (days to 5 kg) in this GWAS indicates the need to use a higher density SNP array in order to overcome the low levels of linkage disequilibrium observed in Atlantic salmon before the information can be incorporated into a selective breeding program.
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Küttner E, Parsons KJ, Easton AA, Skúlason S, Danzmann RG, Ferguson MM. Hidden genetic variation evolves with ecological specialization: the genetic basis of phenotypic plasticity in Arctic charr ecomorphs. Evol Dev 2014; 16:247-57. [PMID: 24920458 DOI: 10.1111/ede.12087] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The genetic variance that determines phenotypic variation can change across environments through developmental plasticity and in turn play a strong role in evolution. Induced changes in genotype-phenotype relationships should strongly influence adaptation by exposing different sets of heritable variation to selection under some conditions, while also hiding variation. Therefore, the heritable variation exposed or hidden from selection is likely to differ among habitats. We used ecomorphs from two divergent populations of Arctic charr (Salvelinus alpinus) to test the prediction that genotype-phenotype relationships would change in relation to environment. If present over several generations this should lead to divergence in genotype-phenotype relationships under common conditions, and to changes in the amount and type of hidden genetic variance that can evolve. We performed a common garden experiment whereby two ecomorphs from each of two Icelandic lakes were reared under conditions that mimicked benthic and limnetic prey to induce responses in craniofacial traits. Using microsatellite based genetic maps, we subsequently detected QTL related to these craniofacial traits. We found substantial changes in the number and type of QTL between diet treatments and evidence that novel diet treatments can in some cases provide a higher number of QTL. These findings suggest that selection on phenotypic variation, which is both genetically and environmentally determined, has shaped the genetic architecture of adaptive divergence in Arctic charr. However, while adaptive changes are occurring in the genome there also appears to be an accumulation of hidden genetic variation for loci not expressed in the contemporary environment.
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Affiliation(s)
- Eva Küttner
- Department of Integrative Biology, University of Guelph, Guelph, 50 Stone Road West, ON, Canada, N1G 2W1
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Gutierrez AP, Lubieniecki KP, Fukui S, Withler RE, Swift B, Davidson WS. Detection of quantitative trait loci (QTL) related to grilsing and late sexual maturation in Atlantic salmon (Salmo salar). MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2014; 16:103-110. [PMID: 23912817 PMCID: PMC3896801 DOI: 10.1007/s10126-013-9530-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/11/2013] [Accepted: 07/15/2013] [Indexed: 06/02/2023]
Abstract
In Atlantic salmon aquaculture, early sexual maturation represents a major problem for producers. This is especially true for grilse, which mature after one sea winter before reaching a desirable harvest weight, rather than after two sea winters. Salmon maturing as grilse have a much lower market value than later maturing individuals. For this reason, most companies desire fish that grow fast and mature late. Marker-assisted selection has the potential to improve the efficiency of selection against early maturation and for late sexual maturation; however, studies identifying age of sexual maturation-related genetic markers are lacking for Atlantic salmon. Therefore, we used a 6.5K single-nucleotide polymorphism (SNP) array to genotype five families from the Mainstream Canada broodstock program and search for SNPs associated with early (grilsing) or late sexual maturation. There were 529 SNP loci that were variable across all five families, and this was the set that was used for quantitative trait loci (QTL) analysis. GridQTL identified two chromosomes, Ssa10 and Ssa21, containing QTL related to grilsing. In contrast, only one QTL, on Ssa18, was found linked to late maturation in Atlantic salmon. Our previous work on these five families did not identify genome-wide significant growth-related QTL on Ssa10, Ssa21, or Ssa18. Therefore, taken together, these results suggest that both grilsing and late sexual maturation are controlled independently of one another and also from growth-related traits. The identification of genomic regions associated with grilsing or late sexual maturation provide an opportunity to incorporate this information into selective breeding programs that will enhance Atlantic salmon farming.
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Affiliation(s)
- Alejandro P. Gutierrez
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia Canada V5A 1S6
| | - Krzysztof P. Lubieniecki
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia Canada V5A 1S6
| | - Steve Fukui
- Mainstream Canada, 203-919 Island Highway, Campbell River, British Columbia Canada V9W 2C2
| | - Ruth E. Withler
- Pacific Biological Station, 3190 Hammond Bay Road, Nanaimo, British Columbia Canada V9T 6N7
| | - Bruce Swift
- TRI-GEN Fish Improvement Ltd., 2244 Wilson Road, Agassiz, British Columbia Canada V0M 1A0
| | - William S. Davidson
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia Canada V5A 1S6
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Mapping quantitative trait loci (QTL) for body weight, length and condition factor traits in backcross (BC1) family of Common carp (Cyprinus carpio L.). Mol Biol Rep 2013; 41:721-31. [PMID: 24368591 DOI: 10.1007/s11033-013-2911-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Accepted: 12/16/2013] [Indexed: 01/24/2023]
Abstract
Body weight and length are economical important traits in aquaculture species influenced by quantitative trait loci (QTL) and environmental factors. In this study, a backcross (BC1) common carp family, with 86 progeny, was utilized to construct genetic map for preliminary QTL mapping. The genetic map was constructed with 366 markers, including 191 SNP from gene, coverage 50 linkage groups with an average marker distance of 18.5 cM. A total of fourteen QTLs associated with body weight (BW), body length (BL) and condition factor (K) were detected on ten linkage groups (LGs). Among these QTLs detected, three (qBW8, qBL8 and qK8) were associated with BW, BL and K respectively, were mapped on LG8. qBW8 and qK8 were identified on similar interval neared locus HLJ2394 explained 14.9 and 20.9 % of the phenotype variance, while qBL8 was identified on separate nearby locus HLJ571 with 30.8 % of phenotype variance. Two QTLs, qBW13 and qK13, related with BW and K separately, were found on LG13 at different locus with phenotype variance of 25.3 and 20.9 %. Other two QTLs, qBW19 and qBL19, associated to BW and BL were mapped on same region near SNP0626 on LG19, and explained 10.3 and 15.6 % of phenotype variance. While other seven QTLs related with BW and BL were located on different LGs. Confidential interval was ranged from 1.1 to 10 cM in the present study. These markers, with lower QTL interval, have great influence on the body weight and length. Therefore, these QTLs will be helpful to find out the genes related with specific trait.
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18
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Chiasson MA, Quinton CD, Danzmann RG, Ferguson MM. Comparative analysis of genetic parameters and quantitative trait loci for growth traits in Fraser strain Arctic charr (Salvelinus alpinus) reared in freshwater and brackish water environments. J Anim Sci 2013; 91:2047-56. [PMID: 23478828 DOI: 10.2527/jas.2012-5656] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
To determine the potential for genetic improvement in Fraser strain Arctic charr (AC, Salvelinus alpinus), we calculated genetic parameters for BW and condition factor (K) and tested if previously identified QTL for these traits were detectable across a commercial broodstock reared in both freshwater (FRW) and brackish water (BRW). Individuals from 30 full-sib families were reared up to 29 mo of age in FRW and BRW tanks at a commercial facility. Heritability for BW and K was moderate in FRW (0.29 to 0.38) but lower in BRW (0.14 to 0.17). Genetic correlations for BW across environments were positive and moderate (0.33 to 0.67); however, equivalent K correlations were very weak (0.24 to 0.37). We identified a single BW QTL with experimentwide effects on linkage group AC-8, 4 BW QTL (AC-4, -13, -14, and -19), and 3 K QTL (AC-4, -5, and -20) with chromosomewide effects across families. Notably, the QTL on AC-8 had significant effects with BW at 3 out of 4 sampling dates in FRW and had significant allelic phase disequilibrium with BW across families, suggesting a tight coupling of the marker region to the QTL in this population. Body weight QTL were identified on AC-4 in both FRW and BRW environments and AC-4 was the only linkage group with a detectable QTL for both K and BW. Modest consistency of some QTL effects as well as moderate heritability in both environments suggests that there is some potential for genetic improvement of growth in this species even though gene × environment interactions are high.
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Affiliation(s)
- M A Chiasson
- Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada.
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19
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Küttner E, Parsons KJ, Robinson BW, Skúlason S, Danzmann RG, Ferguson MM. Effects of population, family, and diet on craniofacial morphology of Icelandic Arctic charr (Salvelinus alpinus). Biol J Linn Soc Lond 2013. [DOI: 10.1111/j.1095-8312.2012.02038.x] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Eva Küttner
- Department of Integrative Biology; University of Guelph; 50 Stone Road West Guelph ON Canada N1G 2W1
| | - Kevin J. Parsons
- Department of Integrative Biology; University of Guelph; 50 Stone Road West Guelph ON Canada N1G 2W1
| | - Beren W. Robinson
- Department of Integrative Biology; University of Guelph; 50 Stone Road West Guelph ON Canada N1G 2W1
| | - Skúli Skúlason
- Hólar University College; Hólar, Hjaltadalur 551 Sauðarkrókur Iceland
| | - Roy G. Danzmann
- Department of Integrative Biology; University of Guelph; 50 Stone Road West Guelph ON Canada N1G 2W1
| | - Moira M. Ferguson
- Department of Integrative Biology; University of Guelph; 50 Stone Road West Guelph ON Canada N1G 2W1
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20
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Minegishi Y, Henkel CV, Dirks RP, van den Thillart GEEJM. Genomics in eels--towards aquaculture and biology. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2012; 14:583-590. [PMID: 22527267 PMCID: PMC3419832 DOI: 10.1007/s10126-012-9444-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2011] [Accepted: 03/23/2012] [Indexed: 05/31/2023]
Abstract
Freshwater eels (genus Anguilla), especially the species inhabiting the temperate areas such as the European, American and Japanese eels, are important aquaculture species. Although artificial reproduction has been attempted since the 1930s and large numbers of studies have been conducted, it has not yet fully succeeded. Problems in eel artificial breeding are highly diverse, for instance, lack of basic information about reproduction in nature, no appropriate food for larvae, high mortality, and high individual variation in adults in response to maturation induction. Over the last decade, genomic data have been obtained for a variety of aquatic organisms. Recent technological advances in sequencing and computation now enable the accumulation of genomic information even for non-model species. The draft genome of the European eel Anguilla anguilla has been recently determined using Illumina technology and transcriptomic data based on next generation sequencing have been emerging. Extensive genomic information will facilitate many aspects of the artificial reproduction of eels. Here, we review the progress in genome-wide studies of eels, including additional analysis of the European eel genome data, and discuss future directions and implications of genomic data for aquaculture.
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Affiliation(s)
- Yuki Minegishi
- Institute of Biology-Leiden, Leiden University, Leiden, The Netherlands.
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GILLINGHAM MARKAF, BECHET ARNAUD, GERACI JULIA, WATTIER REMI, DUBREUIL CHRISTINE, CEZILLY FRANK. Genetic polymorphism in dopamine receptor D4 is associated with early body condition in a large population of greater flamingos,Phoenicopterus roseus. Mol Ecol 2012; 21:4024-37. [DOI: 10.1111/j.1365-294x.2012.05669.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Coding Gene SNP Mapping Reveals QTL Linked to Growth and Stress Response in Brook Charr (Salvelinus fontinalis). G3-GENES GENOMES GENETICS 2012; 2:707-20. [PMID: 22690380 PMCID: PMC3362300 DOI: 10.1534/g3.112.001990] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2012] [Accepted: 04/16/2012] [Indexed: 11/27/2022]
Abstract
Growth performance and reduced stress response are traits of major interest in fish production. Growth and stress-related quantitative trait loci (QTL) have been already identified in several salmonid species, but little effort has been devoted to charrs (genus Salvelinus). Moreover, most QTL studies to date focused on one or very few traits, and little investigation has been devoted to QTL identification for gene expression. Here, our objective was to identify QTL for 27 phenotypes related to growth and stress responses in brook charr (Salvelinus fontinalis), which is one of the most economically important freshwater aquaculture species in Canada. Phenotypes included 12 growth parameters, six blood and plasma variables, three hepatic variables, and one plasma hormone level as well as the relative expression measurements of five genes of interest linked to growth regulation. QTL analysis relied on a linkage map recently built from S. fontinalis consisting of both single-nucleotide polymorphism (SNP, n = 266) and microsatellite (n =81) markers in an F2 interstrain hybrid population (n = 171). We identified 63 growth-related QTL and four stress-related QTL across 18 of the 40 linkage groups of the brook charr linkage map. Percent variance explained, confidence interval, and allelic QTL effects also were investigated to provide insight into the genetic architecture of growth- and stress-related QTL. QTL related to growth performance and stress response that were identified could be classified into two groups: (1) a group composed of the numerous, small-effect QTL associated with some traits related to growth (i.e., weight) that may be under the control of a large number of genes or pleiotropic genes, and (2) a group of less numerous QTL associated with growth (i.e., gene expression) and with stress-related QTL that display a larger effect, suggesting that these QTL are under the control of a limited number of genes of major effect. This study represents a first step toward the identification of genes potentially linked to phenotypic variation of growth and stress response in brook charr. The ultimate goal is to provide new tools for developing Molecular Assisted Selection for this species.
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