89, 630638. 4, (2016). doi: 10.2527/af.2011-0027. Cell 152, 11731183 (2013). The development of advanced image analysis software including artificial neural network (ANN) algorithms based on machine learning approaches has been an important step forward in the development of analysis systems for automated MVS phenotyping (e.g., Grys etal., 2017). Comput. Edvardsen, R. B., Leininger, S., Kleppe, L., Skaftnesmo, K. O. For easy to measure traits of moderate-to-high heritability, this is relatively easy to achieve; however, for most, if not all diseases, and complex multi-factorial traits, the development of adequate training data sets will remain a logistical challenge. (2017). 92, JVI.00415-18 (2018). These data are used to estimate genetic marker effects, which are then applied to predict breeding values for genotyped selection candidates. All of these MVSs are able to extract and analyze quantitative information from digital images and have the ability to improve the accuracy of the phenotype by electronically analyzing the data at a pixel level across spectral regions not always visible to the human eye. Zhang, X. et al. Principles of hyperspectral imaging technology. BMC. Animal improvement programs are based on using phenotypic information of individuals in conjunction with knowledge on genetic relationships and quantitative genetic principles. Lillehammer etal. Aquaculture 254, 203210 (2006). Proc. Genomics of the divergence continuum in an African plant biodiversity hotspot, I: drivers of population divergence in Restio capensis (Restionaceae). Smith, C. C. R., Snowberg, L. K., Gregory Caporaso, J., Knight, R. & Bolnick, D. I. Dietary input of microbes and host genetic variation shape among-population differences in stickleback gut microbiota. GWAS analysis of QTL for enteric septicemia of catfish and their involved genes suggest evolutionary conservation of a molecular mechanism of diseaseresistance. Microbiol. Houston, R.D., Bean, T.P., Macqueen, D.J. Estimation of shrimp (Pandalus borealis) carapace length by image analysis. Google Scholar. 47:24. doi: 10.1186/s12711-015-0100-1, Torkamaneh, D., Laroche, J., Bastien, M., Abed, A., and Belzile, F. (2017). AquaLeap project: Sel. Cornejo-Granados, F. et al. Number of contributing subpopulations and mating design in the base population when establishing a selective breeding program for fish. Genome-Wide Association and genomic selection for resistance to Amoebic Gill Disease in Atlantic Salmon. PLoS One 7:e37558. Genet. Genetics of resistance to photobacteriosis in gilthead sea bream (Sparus aurata) using 2b-RAD sequencing. G3 (Bethesda, Md.) doi: 10.1534/g3.117.040717, Uleberg, E., and Meuwissen, T. H. E. (2011). Genetics 158, 12031215 (2001). 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. Wang, Q., Yu, Y., Li, F., Zhang, X. 5:415. doi: 10.3389/fgene.2014.00415, Yez, J. M., Naswa, S., Lpez, M., Bassini, L., Correa, K., Gilbey, J., et al. doi: 10.1083/jcb.201610026, Guo, X., Li, Q., Wang, Q., and Kong, L. (2012). The greatest immediate value from genomic selection is realized where genomic breeding values can be targeted against traits that drive economic returns to commercial farmers. Finally, disease outbreaks are a major problem for the culture of aquatic species, and therefore, identifying disease resistant stock has been a major goal of breeding programs. 6, 127 (2015). Following on from GBLUP, a single-step GBLUP method (ssGBLUP) was developed (Legarra etal., 2009; Aguilar etal., 2010) to utilize all available information. 15, e2003790 (2017). 12:94. doi: 10.1186/1471-2148-12-94, Saberioon, M., Gholizadeh, A., Cisar, P., Pautsina, A., and Urban, J. 5, 2733. For aquaculture species that have been improved, such as Atlantic salmon (Salmo salar), Nile tilapia (Oreochromis niloticus), and the Pacific white shrimp (Litopenaeus vannamei), selection for growth has dramatically increased efficiencies helping establish these species as global commodities. Sci. Segregation of infectious pancreatic necrosis resistance QTL in the early life cycle of Atlantic Salmon (Salmo salar). The ability to maximize GBS data and generate accurate computational outcomes is especially important for aquaculture species that often have genetic resource limitations. 627, 95103 (2018). Rev. Mol. Visual quality detection of aquatic products using machine vision. Nevertheless, the levels of accuracies observed in these initial investigations demonstrate potentially for applying genomic selection in breeding schemes in aquaculture species. 42, 1717. A matrix containing the estimation of the proportion of total genomic DNA shared by any two individuals based on genome-wide genetic marker data. However, variation in inbreeding coefficients and genetic gain across studies has been seen as a result of interactions between mating design (Nirea etal., 2012a) and effective population size (Dupont-Nivet etal., 2006). 8, 369393 (2016). doi: 10.1111/1755-0998.12291, Mathiassen, J. R., Misimi, E., Toldnes, B., Bond, M., and stvik, S. O. Genet. (2014). A novel approach to estimating heterozygosity from low-coverage genome sequence. Amsterdam: Elsevier Science B.V. Gjedrem, T., Robinson, N., and Rye, M. (2012). Designing aquaculture mass selection programs to avoid high inbreeding rates. Of practical concern is also how best to use available information. Aquaculture 453, 6772. Determination of Quantitative Trait Loci (QTL) for early maturation in rainbow trout (Oncorhynchus mykiss). G3 10, 581590 (2020). Front. (2018) concluded that although QTL studies in L. vannamei and P. monodon provided a valuable insight into the architecture of disease survival and tolerance traits, they failed to provide the necessary information to apply findings through commercial MAS programs. Skaala, . et al. Yez, J. M. et al. GRM, even based on a smaller subset of markers, can provide an accurate estimate of the proportion of the genome shared by related individuals and hence provides higher accuracy of estimation of breeding values as compared to estimates based on pedigree information alone (Habier etal., 2007; Forni etal., 2011; Vallejo etal., 2017). (2006). doi: 10.1016/j.margen.2011.08.006. Dealing with paralogy in RADseq data: in silico detection and single nucleotide polymorphism validation in Robinia pseudoacacia L. Ecol. PDF Genetically Modified Organisms and Aquaculture (2009). Aquaculture is the farming of aquatic organisms and is the fastest growing animal protein production sector globally, supplying approximately 50% of seafood in 2015 (Fishery Statistics, FAO, 2017). 11:63. doi: 10.1186/1471-2156-11-63, Xu, J., Zhao, Z., Zhang, X., Zheng, X., Li, J., Jiang, Y., et al. A., and Meuwissen, T. H. E. (2012a). BMC Evol. QTL mapping for disease resistance has also been conducted in the eastern oyster Crassostrea virginica for MSX and Dermo (Yu and Guo, 2006), the European flat oyster Ostrea edulis for Bonamiosis (Lallias etal., 2009), and the Atlantic salmon for salmonid alphavirus (Gonen etal., 2015), ISAv (Moen etal., 2007), and Gyrodactylus salaris parasitic disease (Gilbey etal., 2006; for review, see Yez etal., 2014). Genet. (2015). (2017). Sustainable production and use of cleaner fish for the biological control of sea lice: recent advances and current challenges. doi: 10.1007/s10126-008-9098-5. Hindar, K., Fleming, I. doi: 10.1016/j.compag.2016.02.020, Sun, X., Fernando, R., and Dekkers, J. Comparison of accuracy of genome-wide and BLUP breeding value estimates in sib based aquaculture breeding schemes. Houston, R. D. Future directions in breeding for disease resistance in aquaculture species. Agric. Genomics 112, 20212027 (2020). Genet. The utilization of dominance and epistasis can potentially increase the power of genomic selection in cross-bred populations including family line crosses. ElMasry, G., and Sun, D.-W. (2010). Evol. Abstract. (2015). Sel. Fish Physiol. Evol. 17, 460. doi: 10.1186/s12864-016-2756-5, Dou, J., Li, X., Fu, Q., Jiao, W., Li, Y., Li, T., et al. Aquaculture genomics, genetics and breeding in the United States Within our own research programs (i.e., marine shrimp and pearl oyster), machine learning algorithms have allowed precise inexpensive phenotyping across diverse production traits. doi: 10.1016/j.aquaculture.2013.10.033, Snelling, W. M., Allan, M. F., Keele, J. W., Kuehn, L. A., Thallman, R. M., Bennett, G. L., et al. Joshi, R., Arnyasi, M., Lien, S., Gjen, H., Magnus, A., Tola, A., et al. Mating structures for genomic selection breeding programs in aquaculture. Tsai, H.-Y. Goddard, M. (2009). Evol. The DNA construct. Genomewide single nucleotide polymorphism discovery in Atlantic salmon (Salmo salar): validation in wild and farmed American and European populations. Genome sequence and genetic diversity of the common carp, Cyprinus carpio. However, subsequent analysis using higher number of loci (1,0005,000) in combination with greater population size (3060) increased the accuracy of selection and genetic gain over five generations (Sonesson and Meuwissen, 2009). Each of these aspects can have different challenges depending on the specific aquaculture species and production system. Nat. Furthermore, genomic selection can reduce rates of inbreeding by up to 81% when compared with traditional selection programs (Vandeputte and Haffray, 2014). Rev. (2018). & Urban, J. 50, 30 (2018). Most central nucleus breeding programs are pathogen free, and breeding decisions are based on family sib selection, but commercial grow-out environments are under constant disease challenge. Mar. doi: 10.1534/g3.115.019570, Hely, F. S., Amer, P. R., Walker, S. P., and Symonds, J. E. (2013). (2017). Sel. 9, 2972 (2018). doi: 10.1111/j.1095-8649.2010.02881.x, Eaton, D. A. R. (2014). doi: 10.1534/genetics.115.175406, Moghadam, H. K., Ferguson, M. M., and Danzmann, R. G. (2007). Sci. Eknath, A. E. & Acosta, B. O. Environ. Evol. Pattern recognition and machine learning. Why does the magnitude of genotype-by-environment interaction vary? B., Czard, T., Bekaert, M., Lowe, N. R., Downing, A., et al. J. Comparison of Minolta colorimeter and machine vision system in measuring colour of irradiated Atlantic salmon. Nature Reviews Genetics thanks L. Bernatchez, D. Jerry, N. H. Nguyen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. There are limited number of studies into imputation accuracy and its application to aquaculture breeding programs. Anim. Genet. PDF Applications of genetics in aquaculture - Fish Consulting Group Aquac. Through the application of mass selection, Bentsen and Olesen (2002) highlighted that increasing the number of breeders from 4 to 100in isolated lines can significantly reduce the rate of inbreeding across different heritabilities. Ross D. Houston. A., Moghadam, H. K., Danzmann, R. G., and Ferguson, M. M. (2011). Viruses 8, 23 (2016). The unclear genetic interactions between host and donor further complicate the application of genomic selection if such effects are significantly greater than zero. Aquaculture 350353, 117129 (2012). Ecol. PLoS Biol. (2007). Supported by continuous advances in sequencing and bioinformatics, genomics is increasingly being applied across the broad range of aquaculture species and at all stages of the domestication process to optimize selective breeding. Houston, R. D. et al. This approach, termed genomic selection, first proposed by Meuwissen etal. PLoS Genet. The use of microarray technology has been a feasible choice for large-scale SNP genotyping across terrestrial and crop production industries (Fan etal., 2010; Rasheed etal., 2017). Evol. In this approach, decisions on selecting breeding candidates are derived from genomic breeding values predicted from genome-wide loci (VanRaden, 2008). Provided by the Springer Nature SharedIt content-sharing initiative, Nature Reviews Genetics (Nat Rev Genet) This study highlights a potentially cost-efficient approach to genomic selection in aquaculture that could help democratize the use of the technology to smaller aquaculture sectors. Accurate genomic predictions for BCWD resistance in rainbow trout are achieved using low-density SNP panels: evidence that long-range LD is a major contributing factor. doi: 10.1186/1297-9686-43-1, Fuji, K., Kobayashi, K., Hasegawa, O., Coimbra, M. R. M., Sakamoto, T., and Okamoto, N. (2006). Increasing growth and body size has been a major goal of many aquaculture selective breeding programs due to its ease of measure and moderate-to-high heritability (Gjedrem, 2000; Gjedrem and Baranski, 2009). A comparative review on microbiota manipulation: lessons from fish, plants, livestock, and human research. Rev. Comput. Breeding for disease resistance of Penaeid shrimps. 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. However, very few examples of causative genes have been identified. GSE 42, 4141. Such imputed in silico genotypes can then be used for genomic selection and other genomic analyses. Yoshida, G. M. et al. Cell 154, 442451 (2013). Resour. Recent advances of genome mapping and marker-assisted selection in aquaculture. Methodology for genetic evaluation of disease resistance in aquaculture species: challenges and future prospects. doi: 10.1002/ece3.2466, Viazzi, S., Van Hoestenberghe, S., Goddeeris, B., and Berckmans, D. (2015). 18, 123146 (1993). Optimizing genomic prediction of host resistance to koi herpesvirus disease in carp. Genomic prediction accuracy for resistance against Piscirickettsia salmonis in farmed rainbow trout. Fishing for divergence in a sea of connectivity: the utility of ddRADseq genotyping in a marine invertebrate, the black-lip pearl oyster Pinctada margaritifera. (2011). Preprint at bioRxiv https://doi.org/10.1101/734442 (2019). Harland, J. GSE 41, 3737. Rev. Tsai, H.-Y. 16, 103110. (2011). Aquaculture is the fastest-growing farmed food sector and will soon become the primary source of fish and shellfish for human diets. 17, 893938 (2016). 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.
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how would genetic engineering help aquaculture be more effective?
