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dc.contributor.authorRoss Houston*
dc.contributor.authorJose Manuel Yanez*
dc.contributor.authorScott Newman*
dc.date.accessioned2021-02-11T14:25:59Z
dc.date.available2021-02-11T14:25:59Z
dc.date.issued2016*
dc.date.submitted2016-01-19 14:05:46*
dc.identifier18344*
dc.identifier.issn16648714*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/48419
dc.description.abstractFrom a global perspective aquaculture is an activity related to food production with large potential for growth. Considering a continuously growing population, the efficiency and sustainability of this activity will be crucial to meet the needs of protein for human consumption in the near future. However, for continuous enhancement of the culture of both fish and shellfish there are still challenges to overcome, mostly related to the biology of the cultured species and their interaction with (increasingly changing) environmental factors. Examples of these challenges include early sexual maturation, feed meal replacement, immune response to infectious diseases and parasites, and temperature and salinity tolerance. Moreover, it is estimated that less than 10% of the total aquaculture production in the world is based on populations genetically improved by means of artificial selection. Thus, there is considerable room for implementing breeding schemes aimed at improving productive traits having significant economic impact. By far the most economically relevant trait is growth rate, which can be efficiently improved by conventional genetic selection (i.e. based on breeding values of selection candidates). However, there are other important traits that cannot be measured directly on selection candidates, such as resistance against infectious and parasitic agents and carcass quality traits (e.g. fillet yield and meat color). However, these traits can be more efficiently improved using molecular tools to assist breeding programs by means of marker-assisted selection, using a few markers explaining a high proportion of the trait variation, or genomic selection, using thousands of markers to estimate genomic breeding values. The development and implementation of new technologies applied to molecular biology and genomics, such as next-generation sequencing methods and high-throughput genotyping platforms, are allowing the rapid increase of availability of genomic resources in aquaculture species. These resources will provide powerful tools to the research community and will aid in the determination of the genetic factors involved in several biological aspects of aquaculture species. In this regard, it is important to establish discussion in terms of which strategies will be more efficient to solve the primary challenges that are affecting aquaculture systems around the world. The main objective of this Research Topic is to provide a forum to communicate recent research and implementation strategies in the use of genomics in aquaculture species with emphasis on (1) a better understanding of fish and shellfish biological processes having considerable impact on aquaculture systems; and (2) the efficient incorporation of molecular information into breeding programs to accelerate genetic progress of economically relevant traits.*
dc.languageEnglish*
dc.relation.ispartofseriesFrontiers Research Topics*
dc.subjectQH426-470*
dc.subjectQ1-390*
dc.subject.classificationbic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical)en_US
dc.subject.othergenomic selection*
dc.subject.otherNext-generation sequencing*
dc.subject.otherFish breeding*
dc.subject.otherTranscription*
dc.subject.otherselection footprints*
dc.subject.otherhigh-throughput genotyping*
dc.subject.otherGenetic*
dc.subject.otherSingle nucleotide polymorphism*
dc.titleGenomics in Aquaculture to Better Understand Species Biology and Accelerate Genetic Progress*
dc.typebook
oapen.identifier.doi10.3389/978-2-88919-957-0*
oapen.relation.isPublishedBybf5ce210-e72e-4860-ba9b-c305640ff3ae*
oapen.relation.isbn9782889199570*
oapen.pages151*


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