Completed Genetics & Molecular Biology Food & Agriculture

Establishing the infrastructure for functional annotation of farmed animal genomes

In plain English

AI plain-English summary

Farm animal genomes are missing large chunks of their instruction manuals. Current DNA blueprints for chickens, cattle, pigs, and salmon identify 70–90% of protein-coding genes but leave out most non-coding RNA genes and almost all regulatory sequences that control when and where genes switch on or off. This gap matters because without a complete functional map of the genome, researchers cannot reliably link an animal’s genetic makeup (genotype) to its observable traits (phenotype)—such as disease resistance, growth rate, or meat quality. The international FAANG consortium, launched after a 2014 workshop of over 100 scientists, aims to fill this gap by generating experimental data to annotate domesticated animal genomes comprehensively. This project builds the digital infrastructure to make that possible. It will create a Data Coordination Centre and Data Analysis Centres, plus standardised bioinformatics pipelines for processing ChIP-seq, RNA-seq, and Methyl-seq data. The hardware and software will sit at Roslin, TGAC, and EMBL-EBI. If successful, the infrastructure will enable researchers in animal breeding, veterinary medicine, and agriculture to pinpoint the functional elements that drive economically important traits—without each lab having to reinvent the analytical tools from scratch.

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Research on domesticated animals has important socio-economic impacts, including underpinning and accelerating improvements in agriculture, improving animal health and welfare, contributing to medical research and increasing our understanding of natural and wild animal populations. High quality annotated genome sequences ("sequence of DNA nucleotides that make up the genetic material of an organism") provide an important framework for the discovery of genetic variation ("genotype") in that sequence linked to variation in the characteristics ("phenotype") of an animal. Genome sequences are available for many domesticated animals, including poultry (chicken, turkey and duck), livestock (cattle, pig, goat and sheep), fish (cod, tilapia and salmon) and companion animals (dog and horse). Today technology to sequence DNA is both rapid and relatively cheap and allowed the development of a wide range of assays based on generating short or long sequences. High quality, annotated genomes are critical to the analysis of these assays, including RNA-seq analysis of a cells RNA ("read off the genome, encoding information to synthesise proteins or regulate gene expression"), Methyl-seq analysis of the location of covalent modifications (methyl-groups) to the genome or ChIP-seq analysis of proteins bound to the genome that activate or repress gene expression. Identifying the functional elements within the genome that code for proteins, non-coding RNAs or regulate gene expression is essential for understanding the phenotypic consequences encoded in the genome. Annotated genome sequences are freely available on-line through Ensembl, NCBI and UCSC. We have used the Ensembl system to establish high quality annotations of animal genomes based on mostly cDNA and comparative data from other species. Whilst 70-90% of protein coding elements can be identified, there is little information on non-coding RNA genes many of which are suspected to regulate gene expression. Comparing the number of annotated RNAs read from genes in the human, mouse and domesticated animal genomes shows that the complexity of RNAs in domesticated animals is underestimated. Even less is known of regulatory sequences, which is a significant barrier to understanding the link between genotype and phenotype. The importance of this challenge is recognised by the EU-US Animal Biotechnology Working Group, which is promoting the need for transnational coordinated functional annotation of animal genomes. Following a workshop of over 100 scientists in San Diego (2014) an international consortium the "Functional Annotation of ANimal Genomes or FAANG" was launched. The FAANG project aims to provide experimental data to comprehensively annotate domesticated animal genomes. We will establish the data infrastructure to support these goals. The infrastructure will comprise hardware and compute capacity at Roslin/TGAC/EMBL-EBI together with software to enable the functional annotation of animal genomes. The infrastructure will support a Data Coordination Centre (DCC) and Data Analysis Centres (DACs). DCC will store data and analyses from the FAANG consortium subject to quality control checks. DACs will seek to minimise redundant analysis of data. Standard bioinformatics pipelines for quality control of assay-by-sequence data (ChIP-Seq, RNA-Seq, and Methyl-seq), tools for validation of sample identity and a number of primary analysis pipelines (to map location of RNAs for protein coding/non-coding RNAs and regulatory features) will be developed. A high quality annotated genome is a key source of information and critical for contemporary research in the biological sciences. It is valuable not only to academic researchers, but also to scientists working in animal breeding, animal health and pharmaceutical industries. This project is concerned with the infrastructure for delivering high quality annotated reference genomes to enable research on economically important animals.

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Researchers

Alan Archibald (Principal Investigator)Andrew Law (Co-Investigator)David Burt (Co-Investigator)Federica Di Palma (Co-Investigator)Mario Caccamo (Co-Investigator)Michael Watson (Co-Investigator)Paul Flicek (Co-Investigator)Robert Davey (Co-Investigator)Timothy Stitt (Co-Investigator)

Related Research

Grants with similar aims, by meaning.

Ensembl and enabling genetics and genomics research in farmed animal species
Ensembl genome portal for farm and companion animals
Ensembl - adding value to animal genomes through high quality annotation
Ensembl in a new era - deep genome annotation of domesticated animal species and breeds
The Animal Functional Genomics Resource

Original classification

Research Grant

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