Literature DB >> 25883603

Genomics in aquaculture to better understand species biology and accelerate genetic progress.

José M Yáñez1, Scott Newman2, Ross D Houston3.   

Abstract

Entities:  

Keywords:  QTL; aquaculture; breeding programs; genome; next-generation sequencing; single nucleotide polymorphisms

Year:  2015        PMID: 25883603      PMCID: PMC4381651          DOI: 10.3389/fgene.2015.00128

Source DB:  PubMed          Journal:  Front Genet        ISSN: 1664-8021            Impact factor:   4.599


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The production of fish and shellfish through aquaculture is an increasingly important source of high-quality animal protein, with a worldwide production of 66.6 million tons in 2012 (FAO, 2014). Considering the continuously growing global human population and increasing demand for fish products, improvements in the scale, efficiency, and sustainability of aquaculture are essential. To achieve this, several challenges facing the culture of fish and shellfish species need to be overcome. These relate to the diverse biology of the cultured species and their interaction with environmental factors. Examples include outbreaks of infectious diseases, control of sexual maturation, sustainable feed for carnivorous species, and tolerance of diverse and changing environments. This “Frontiers in Livestock Genomics” Research Topic highlights the opportunities offered by recent developments in the field of genomics, and in particular high-throughput sequencing, to contribute to addressing these challenges, with a focus on selective breeding programmes. The use of selective breeding as a tool to improve the biological efficiency of production in aquaculture generally lags behind plant and farm animal industries, and less than 10% of aquaculture production is based on genetically-improved stocks (Gjedrem et al., 2012). Encouragingly, annual genetic gains reported for aquatic species are in general substantially higher than that of terrestrial farm animals (Gjedrem et al., 2012) and there is considerable scope for achieving significant positive economic impact via improved breeding schemes. However, the status of breeding programs and the level of technology used for aquatic species production are wide-ranging, from use of wild seed stocks through to family-based selection incorporating genomic tools. Family selection and genomic tools can be applied to improve traits that are expensive or difficult to measure on the selection candidates themselves including disease resistance (Yáñez et al., 2014; Ødegård et al., 2014), flesh color (Colihueque and Araneda, 2014; Ødegård et al., 2014) and other appearance traits such as body shape and skin pigmentation (Colihueque and Araneda, 2014) in finfish species. In contrast, despite the global importance of mollusc species for aquaculture, few selective breeding programmes exist and the state of genomic tools and knowledge for these species is typically lacking (Astorga, 2014). Genomics resources such as whole genome reference sequences, high-density SNP genotyping arrays and genotyping-by-sequencing are in development for several aquaculture species. Fuller characterisation of these resources is underway and is resulting in improved fundamental knowledge of the genome structure and biology, highlighted in this issue by the analysis of repeat elements in the Asian sea bass genome (Kuznetsova et al., 2014). These resources will provide powerful tools for the research community and will aid in the determination of the genetic factors involved in the regulation of complex traits. For example, high-throughput RNA sequencing can give a holistic view of the host response to infectious diseases, and help identify the important genes and pathways defining genetic resistance, as demonstrated in this issue for rainbow trout (Ali et al., 2014; Marancik et al., 2014) and panaeid shrimp (Santos et al., 2014). Sequencing technology has also facilitated the development of abundant genetic markers that have multi-faceted applications for selective breeding of aquatic species, including parentage assignment in mixed-family environments, providing greater control over family representation and inbreeding (Vandeputte and Haffray, 2014). Medium or high-density SNP arrays can be used to predict genomic breeding values for economically-important traits in well-developed breeding programmes, such as Atlantic salmon (Ødegård et al., 2014). For instance, based on simulations of a Pacific white shrimp breeding program, genetic progress of disease resistance traits is faster with genomic-enabled selection compared to conventional phenotype-based selection due to higher accuracy (Castillo-Juárez et al., 2015). Incorporation of genetic marker information can also be a useful asset to optimize genetic diversity and future genetic gain when establishing base populations for breeding programmes (Fernández et al., 2014). Furthermore, these genomic tools can be applied to investigate putative genomic signatures of selection during the domestication process of farmed fish species, thus potentially identifying genomic regions underlying variation in relevant phenotypes in wild and domestic fish populations (López et al., 2015). Aquaculture species typically have several common features, for example high fecundity and external fertilization, plus a short evolutionary distance from their wild ancestors. The reproductive features enable flexible mating structures to be used for breeding programmes, and can provide a powerful resource for genetic studies of complex traits, such as disease resistance (Yáñez et al., 2014). However, the diversity between these species is enormous and often necessitates the establishment of species-specific reproduction and breeding programmes. For example, there is a remarkable variety of sex-determination systems within aquatic farmed species, and the study of Martínez et al. (2014) highlights various methods of controlling sex ratio with aquaculture breeding programmes. This species diversity also presents an issue for choosing suitable model organisms to inform on the biology of the farmed species of interest. Model finfish species, such as zebrafish, have been well-characterized and Ulloa et al. (2014) highlight their utility for the evaluation of the response to alternative diets. However, due to the vast evolutionary distance between certain farmed aquatic and model species, it is clear that direct research on the species of interest can often be the most feasible and informative. The aquaculture industry has often been innovative and visionary in their application of new technologies to improve production. Genomics present another major opportunity, and the research published in this special issue provides several excellent examples of their potential or realized application. Using genomic tools to more effectively utilize genetic variation in economically-important traits via sustainable breeding programmes is paramount to the continued successful growth and stability of aquaculture production.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
  14 in total

1.  Genetic improvement of Pacific white shrimp [Penaeus (Litopenaeus) vannamei]: perspectives for genomic selection.

Authors:  Héctor Castillo-Juárez; Gabriel R Campos-Montes; Alejandra Caballero-Zamora; Hugo H Montaldo
Journal:  Front Genet       Date:  2015-03-24       Impact factor: 4.599

2.  Primary analysis of repeat elements of the Asian seabass (Lates calcarifer) transcriptome and genome.

Authors:  Inna S Kuznetsova; Natascha M Thevasagayam; Prakki S R Sridatta; Aleksey S Komissarov; Jolly M Saju; Si Y Ngoh; Junhui Jiang; Xueyan Shen; László Orbán
Journal:  Front Genet       Date:  2014-07-25       Impact factor: 4.599

3.  Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.

Authors:  Jesús Fernández; Miguel Á Toro; Anna K Sonesson; Beatriz Villanueva
Journal:  Front Genet       Date:  2014-11-25       Impact factor: 4.599

4.  Whole-body transcriptome of selectively bred, resistant-, control-, and susceptible-line rainbow trout following experimental challenge with Flavobacterium psychrophilum.

Authors:  David Marancik; Guangtu Gao; Bam Paneru; Hao Ma; Alvaro G Hernandez; Mohamed Salem; Jianbo Yao; Yniv Palti; Gregory D Wiens
Journal:  Front Genet       Date:  2015-01-08       Impact factor: 4.599

Review 5.  Appearance traits in fish farming: progress from classical genetics to genomics, providing insight into current and potential genetic improvement.

Authors:  Nelson Colihueque; Cristian Araneda
Journal:  Front Genet       Date:  2014-08-04       Impact factor: 4.599

Review 6.  Genetic considerations for mollusk production in aquaculture: current state of knowledge.

Authors:  Marcela P Astorga
Journal:  Front Genet       Date:  2014-12-10       Impact factor: 4.599

7.  Characterization of the rainbow trout spleen transcriptome and identification of immune-related genes.

Authors:  Ali Ali; Caird E Rexroad; Gary H Thorgaard; Jianbo Yao; Mohamed Salem
Journal:  Front Genet       Date:  2014-10-14       Impact factor: 4.599

8.  Genomic prediction in an admixed population of Atlantic salmon (Salmo salar).

Authors:  Jørgen Odegård; Thomas Moen; Nina Santi; Sven A Korsvoll; Sissel Kjøglum; Theo H E Meuwissen
Journal:  Front Genet       Date:  2014-11-21       Impact factor: 4.599

Review 9.  RNA-seq as a powerful tool for penaeid shrimp genetic progress.

Authors:  Camilla A Santos; Danielly V Blanck; Patrícia D de Freitas
Journal:  Front Genet       Date:  2014-08-28       Impact factor: 4.599

10.  Zebrafish as animal model for aquaculture nutrition research.

Authors:  Pilar E Ulloa; Juan F Medrano; Carmen G Feijoo
Journal:  Front Genet       Date:  2014-09-10       Impact factor: 4.599

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  25 in total

1.  Complete mitochondrial genome from South American catfish Pseudoplatystoma reticulatum (Eigenmann & Eigenmann) and its impact in Siluriformes phylogenetic tree.

Authors:  Luciana Cristine Vasques Villela; Anderson Luis Alves; Eduardo Sousa Varela; Michel Eduardo Beleza Yamagishi; Poliana Fernanda Giachetto; Naiara Milagres Augusto da Silva; Josi Margarete Ponzetto; Samuel Rezende Paiva; Alexandre Rodrigues Caetano
Journal:  Genetica       Date:  2017-02-03       Impact factor: 1.082

2.  Genomic Selection in Aquaculture Species.

Authors:  François Allal; Nguyen Hong Nguyen
Journal:  Methods Mol Biol       Date:  2022

3.  Identification of a Growth-Associated Single Nucleotide Polymorphism (SNP) in Cyclin C of the Giant Tiger Shrimp Penaeus monodon.

Authors:  Sirithorn Janpoom; Sirikan Prasertlux; Puttawan Rongmung; Piamsak Menasveta; Thanathip Lamkom; Panya Sae-Lim; Bavornlak Khamnamtong; Sirawut Klinbunga
Journal:  Biochem Genet       Date:  2020-08-11       Impact factor: 1.890

4.  Genomic prediction of host resistance to sea lice in farmed Atlantic salmon populations.

Authors:  Hsin-Yuan Tsai; Alastair Hamilton; Alan E Tinch; Derrick R Guy; James E Bron; John B Taggart; Karim Gharbi; Michael Stear; Oswald Matika; Ricardo Pong-Wong; Steve C Bishop; Ross D Houston
Journal:  Genet Sel Evol       Date:  2016-06-29       Impact factor: 4.297

5.  Genome-Wide Association Study for Identifying Loci that Affect Fillet Yield, Carcass, and Body Weight Traits in Rainbow Trout (Oncorhynchus mykiss).

Authors:  Dianelys Gonzalez-Pena; Guangtu Gao; Matthew Baranski; Thomas Moen; Beth M Cleveland; P Brett Kenney; Roger L Vallejo; Yniv Palti; Timothy D Leeds
Journal:  Front Genet       Date:  2016-11-22       Impact factor: 4.599

6.  The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar).

Authors:  Katharina Correa; Rama Bangera; René Figueroa; Jean P Lhorente; José M Yáñez
Journal:  Genet Sel Evol       Date:  2017-01-31       Impact factor: 4.297

7.  Genotype Imputation To Improve the Cost-Efficiency of Genomic Selection in Farmed Atlantic Salmon.

Authors:  Hsin-Yuan Tsai; Oswald Matika; Stefan McKinnon Edwards; Roberto Antolín-Sánchez; Alastair Hamilton; Derrick R Guy; Alan E Tinch; Karim Gharbi; Michael J Stear; John B Taggart; James E Bron; John M Hickey; Ross D Houston
Journal:  G3 (Bethesda)       Date:  2017-04-03       Impact factor: 3.154

8.  Construction and Annotation of a High Density SNP Linkage Map of the Atlantic Salmon (Salmo salar) Genome.

Authors:  Hsin Y Tsai; Diego Robledo; Natalie R Lowe; Michael Bekaert; John B Taggart; James E Bron; Ross D Houston
Journal:  G3 (Bethesda)       Date:  2016-07-07       Impact factor: 3.154

9.  Genome wide association and genomic prediction for growth traits in juvenile farmed Atlantic salmon using a high density SNP array.

Authors:  Hsin-Yuan Tsai; Alastair Hamilton; Alan E Tinch; Derrick R Guy; Karim Gharbi; Michael J Stear; Oswald Matika; Steve C Bishop; Ross D Houston
Journal:  BMC Genomics       Date:  2015-11-18       Impact factor: 3.969

10.  Verification of SNPs Associated with Growth Traits in Two Populations of Farmed Atlantic Salmon.

Authors:  Hsin Y Tsai; Alastair Hamilton; Derrick R Guy; Alan E Tinch; Steve C Bishop; Ross D Houston
Journal:  Int J Mol Sci       Date:  2015-12-22       Impact factor: 5.923

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