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From FAANG to fork: application of highly annotated genomes to improve farmed animal production

Authors: Clark, Emily; Archibald, Alan; Daetwyler, Hans; Groenen, Martien; Harrison, Peter; Houston, Ross; Kühn, Christa; +7 Authors

From FAANG to fork: application of highly annotated genomes to improve farmed animal production

Abstract

The Food and Agriculture Organisation of the United Nations (FAO) reports that by the year 2050 the global human population is likely to reach 9.7 billion, rising to 11.2 billion by 2100 (https://population.un.org/wpp/Publications/Files/Key_Findings_WPP_2015.pdf). This population growth poses several challenges to the global food system, which will need to produce more healthy food using fewer natural resources, reducing the environmental impact, conserving biodiversity and flexibly adjusting to changing societal expectations. Meeting this demand requires environmentally sustainable improvements to farmed animal health and welfare, and of efficiency and diversification (e.g. to include a broader range of locally adapted species) [1]. The changes in breeding strategies and management practises required to meet these goals will need to build on an improved ability to accurately use genotype to predict phenotype in the world’s farmed animal species, both terrestrial and aquatic.

Countries
Netherlands, Norway, United Kingdom, France, United States, France
Keywords

570, [SDV.GEN.GA] Life Sciences [q-bio]/Genetics/Animal genetics, Review, 630, FAANG, genomics, Life Science, Animals, Selection, Genetic, farmed animal, Uncategorized, Gene Editing, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Genome, other, Genetic Variation, Agriculture, Genetics and Genomics, Molecular Sequence Annotation, genotype-to-phenotype, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics, Animal Sciences

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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