Award details

Developing next generation genetic improvement tools from next generation sequencing

Reference	BB/M009254/1
Principal Investigator / Supervisor	Dr John Hickey
Co-Investigators / Co-Supervisors
Institution	University of Edinburgh
Department	The Roslin Institute
Funding type	Research
Value (£)	341,731
Status	Completed
Type	Research Grant
Start date	16/06/2015
End date	15/06/2018
Duration	36 months

Abstract

The UK dairy research and industrial sectors, as well as RCUK, will invest heavily in sequence data in the coming years. This proposal will ensure that the infrastructure and strategy underpinning this investment is optimal. The platform generated will allow for the combination and analysis of both genotype and sequence information on the UK (dairy) cattle population, and will serve as a technology example for other livestock species. There are three components to this proposal. The first will develop a strategy for collecting sequence information across a whole population. The second will put in place the infrastructure required to handle, share, analyse, and utilise inter(national) shared sequence data within the UK dairy breeding and research communities. The third will evaluate the ability of sequence data to increase the accuracy of genomic selection and the power of genome wide association studies in national dairy cattle populations. Through these activities this project will develop the strategy, infrastructure, and expertise for sequence data required by the UK breeding sector and through this will help maintain world class standards in both the science and application of dairy production in the UK.

Summary

Phenotype and pedigree informed genetic improvement in livestock using techniques such as Best Linear Unbiased Prediction (BLUP) has seen rates of improvement of between 1% to 3% per annum in many livestock populations. Over the past 50 or so years we have seen that genetics research, including molecular and statistical developments, has been applied by many operational plant and livestock breeding programmes. The availability of reference sequences for many species has resulted in the discovery of very many thousands (and higher) of single-nucleotide polymorphisms (SNPs) leading to the on-going development of low-cost SNP arrays and being used around the globe in many livestock species - genomic selection. Through research and industry (nationally and internationally) the UK dairy industry implemented genomic selection for industry traits (milk production, fertility, longevity) in April 2012 using a pooled collaborative SNP genotype file (predominately bulls, now over 100,000 individuals). This will lead to an expected increase in the annual rate of genetic improvement of approximately 30-50%. The next horizon for research and its translation into genetic improvement tools is the inclusion of sequence data alongside the tools that the industry have already invested in. These developments provide exciting opportunities for the research community to explore the more readily available and vast amounts of genomic data to create new knowledge and drive innovation in the field, as we have seen historically in plant and livestock genetic research. Because the UK dairy industry and research sectors are collectively likely to invest heavily in sequence information in the coming years, a collaborative strategy to generate, store and process sequence information efficiently is needed to enable its effective used in animal breeding research and for use in next generation genetic improvement tools. The rate of change we are now experiencing in ready availability of genomic and sequence information means there a real need to take a community based approach to utilising these data, including the involvement of the end user as well as basic research. In the case of this proposal, the end-user focus is the animal breeding industry as well as the biosciences research community. A DNA sequence captures the complete genome of an individual. If available for sufficient individuals, it will provide a range of benefits 1) greater livestock improvement through more accurate and more persistent genomic selection, 2) the identification of targets for genome editing, 3) detection and breeding management of rare variants, including recent mutations, and 4) greater biological knowledge. More powerful biological discovery will be enabled because the causal nucleotides are contained within the sequence, unlike the case of markers such as single nucleotide polymorphism (SNP). Its exploitation in animal breeding programmes is expected to create a paradigm shift that will greatly enhance the production of food from farmed livestock through both increased output and reduced wastage. However, it is expensive to collect sequence data at the high read rates (essentially accuracy) needed generally for research and this has led to small islands of sequence data at research institutes. Commercial breeding companies are beginning to assimilate some sequence data but this is usually IP protected. Some have large genotype datasets that can be imputed to full sequence level. The aim of this project is to develop the methodology(s) to optimise the distribution of sequencing effort across, and in key populations within, the UK dairy cattle population. The hypothesis that will be studied is that the inclusion of optimal sequence data will improve the results for genome wide association studies for novel traits and genomic selection in the wider UK dairy cattle population compared to widespread SNP chips alone.

Impact Summary

The future sustainability of the UK dairy industry relies on farmers being able to respond to key market signals and future developments in genetic improvement tools are likely to be a key. The partners have successfully worked together to deliver R&D that drives the ongoing changes in the genetic and genomic improvement tools used by farmers. For example, SRUC has delivered information on, and produced, practical dairy selection tools, particularly the inclusion of fertility, health, welfare and survival traits. Adoption of new indexes have improved animal health and welfare and economic performance compared to continued use of previous selection practices, and has cumulatively reduced greenhouse gas emissions per breeding animal by 1.4%/yr. The overall annualised economic benefits of the genetic improvement that has taken place in the years 1980-2009 is worth £127 million/year to the UK dairy industry. Globally and within the UK dairy production is important both commercially and for research. Dairy genetics is particularly important for research because, due to its high commercial value, it serves as a model species for all other livestock. For example, dairy cattle breeding was the first to widely adopt genomic selection and was the sector that undertook many of the innovations in genetic and genomic evaluations. Sequence data is expensive and therefore requires a unified approach involving all stakeholders. In dairy this includes research organisations, farmers, private companies, levy boards, and research funding agencies. In this proposal we will bring these groups together by developing a unified strategy for the collection, handling, and utilisation of sequence information within the UK dairy industry. (i) The academic community. Sequence data is of great value for the prediction and understanding of quantitative traits. However, small islands of sequence data are of limited value on their own - to benefit from sequence huge quantities are needed - quantities that are far beyond the scope of a single researcher or a single research project. This proposal will put in place the strategy and infrastructure to generate the quantities of sequence data that is required by current and future researchers. (ii) Commercial sequence and genotype providers. Companies providing SNP or sequence data will be able to add value to the data that they generate. (iii) Society. All members of society who work to improve or depend upon the competitiveness and sustainability of agriculture will benefit from the downstream practical applications. The application of the research by breeding organisations will lead to faster and more sustainable genetic progress, leading to healthier food, and food production that is more resource efficient and affordable. Increased efficiencies in agriculture has direct societal benefits in greater food security with less environmental impact. (iv) UK science base. The proposed research will provide a platform for increased R&D capabilities in the UK, maintaining its scientific reputation and associated institutions, with increased capability for sustainable agricultural production. (v) Training. The proposed research will be embedded within training courses that the investigators are regularly invited to give, and the post-docs and programmer working on the project will have the opportunity to be trained in world leading livestock genetics community in a cutting edge area of research. Further, this project is aligned to delivery of already awarded projects (involving postdocs and PhD). This cohort of early career researchers will greatly benefit from the activity of the community. (vi) Funding agencies. Funding agencies will be required to fund sequence data in the coming year. This research will put in place the tools and ideas required to optimise this. investment and to maximise its complementarity to investments from other organisations (e.g. breeding companies).

Committee	Research Committee C (Genes, development and STEM approaches to biology)
Research Topics	Animal Health, Technology and Methods Development
Research Priority	X – Research Priority information not available
Research Initiative	X - not in an Initiative
Funding Scheme	Industrial Partnership Award (IPA)

Associated awards:

BB/M010635/1 Developing next generation genetic improvement tools from next generation sequencing

I accept the terms and conditions of use (opens in new window)

export PDF file

back to list new search