From FAANG to Fork: Application of Highly Annotated Genomes to Improve Farmed Animal Production

Emily Clark, Alan Archibald, Hans D. Daetwyler , Martien Am Groenen, Peter W. Harrison, Ross Houston, Christa Kuhn, Sigbjorn Lien, Dan Macqueen, James M. Reecy, Diego Robledo, Mick Watson, Christopher K Tuggle, Elisabetta Guiffra

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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 ( 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 (Figure 1).
Here we describe a set of research priorities to meet such present and future challenges that build on progress, successes and resources from the Functional Annotation of ANimal Genomes (FAANG) project [2]. The first stages of FAANG focused on foundational data generation to characterise expressed and regulatory genomic regions, curation and provision of annotated farmed animal genomes [2,3]. These were largely based on individual level, high depth approaches [3]. The primary challenge facing this community now is harnessing these resources to link genotype, phenotype and genetic merit in order to translate this research out of the laboratory and into industry application in the field. To achieve this effectively, we will need to generate functional genomic information for large populations of animals, rather than relying on a small number of deeply annotated individuals. Furthermore, to date, most of the datasets are from tissues consisting of heterogeneous cell populations, hindering the resolution of functional information and limiting our ability to understand the fundamental cellular and subcellular processes underlying phenotypes. Since the original FAANG white paper was published in 2015 [2], exciting new opportunities have arisen to tackle these challenges. We describe a set of research action priorities for FAANG for the next decade (Figure 2), in each of the sections below.
Original languageEnglish
JournalGenome Biology
Publication statusPublished - 24 Nov 2020


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