GplusE: Genomic selection and Environment modelling for next generation wheat breeding

Lead Research Organisation: National Inst of Agricultural Botany
Department Name: Centre for Research

Abstract

Despite its importance and growing demand within the UK, and globally, the rate of increase in wheat yields on UK farms have stagnated. To meet global future demand, annual wheat yield increases must grow to at least 1.4% and increasing the rate of genetic improvement using modern approaches is one way to do this. The ability to record vast quantities of genetic and phenotypic information cheaply (e.g. genetic markers and spectral images of field trials - termed in this proposal as Genomics and Phenomics) presents a new opportunity for increasing the rate of genetic improvement.
The rate of genetic improvement is affected by (1) the accuracy of selection, (2) breeding cycle time, (3) selection intensity, and (4) the amount of genetic diversity to be selected upon. In the medium to long term, concerns about genetic diversity are being addressed through national and international projects to introgress traits and alleles from landraces and progenitor species. However, the major barrier to the immediate increase in the rate of genetic improvement in wheat is the length of the breeding cycle time. Even at their fastest wheat breeding programs require at least four to six seasons to complete a cycle, principally due to the time required to reduce the number of individuals for selection to a subset that can be intensively phenotyped. Genomic selection (GS) is a new breeding tool that, amongst other advantages, can dramatically reduce breeding cycle time as selection can occur without the need to record phenotypes. In wheat this means breeding cycle time could be reduced to one season, dramatically increasing the rate of genetic improvement. In the extreme, using glasshouses to complete 2 cycles of selection per year, 10 cycles could be undertaken in the 5-year time frame currently taken for a single selection cycle.
GS uses a training population that is phenotyped and genotyped to construct a prediction equation. This equation is used to predict the breeding values of unphenotyped individuals, which, in wheat, would allow reduction of the breeding cycle to one season. GS assumes that saturating the genome of all individuals with molecular markers and estimating the effect of these markers (i.e. training the prediction equation) will allow capture of a large proportion of the genetic variation caused by the underlying quantitative trait loci. If the proportion of the captured genetic variation is large and well estimated the prediction equation will be able to make accurate predictions about breeding values. Similarly, in Phenomics the phenotype could be saturated with descriptors, which could lead to a better separation of its environmental and genetic components as well as generating more precise phenotypes.
Creation of training populations is a required investment for GS and strategic use of resources to achieve the required size is needed to optimize the cost and benefit of GS. Use of a genotyping and imputation strategy is paramount for reducing costs. Field trials are also costly. Use of novel high-dimensional approaches for capturing extra traits and variables (Phenomics) could enhance the value of field trials generally, as well as enabling more powerful GS.
This proposal will use field trials and simulation to design and evaluate Genomics and Phenomics strategies for increasing rates of genetic improvement in wheat. This will include GS training population designs and low cost collection of genotype data, assessment of the properties of high-dimensional environmental descriptors and quantification of their power, assessment of the properties of trait phenotypes collected by high-dimensional data recording devices and quantification of their relationships to standard traits. Results will be generalised to other species with breeding programs similar to those of wheat as well as to other type of experiments and field trials (e.g. National List evaluations).

Technical Summary

This proposal will develop and evaluate strategies for next generation wheat breeding based on the use of Genomic and Phenomic data, which can now be recorded in large quantities cheaply. It will bring "Big Data" to wheat breeding. Genomic selection (GS) could revolutionize wheat breeding: cycle times could be shortened; accuracy and intensity of selection maintained or increased; and more widespread selection for hard to measure traits could be undertaken. The key advantage of GS in comparison to traditional breeding is the ability to use high-dimension genetic marker information to make accurate predictions of genetic value for selection candidates without having to wait for phenotypes to be collected.
Analogous to GS, Phenomics uses instruments to record high dimensional phenotypic (e.g. spectral images) and environmental (e.g. soil electro-magnetic imaging) data. These may be determinants or indicators of complex trait phenotypes such as yield. More accurate modelling of environment and phenotype could enable faster genetic improvement in wheat, or increased efficiency of assessment in any field trial. Phenomics is highly valuable for wheat breeding. This project will scale that value to field level, enabling it to drive genetic improvement.
This project will use a large field trial combined with simulation to study the key factors in the application of GS to wheat breeding: training population design and genotyping strategy. It will integrate GS with Phenomics so that they empower each other.

Planned Impact

Genomic selection and Environment modelling for next generation wheat breeding (GplusE) links Phenomics and Genomics to deliver to the wheat breeding community a platform to greatly increase the rate of progress possible through breeding. Wheat is the UK's major crop and has the 3rd largest production of any cereal globally. This project has the potential to benefit individuals and organisations worldwide for whom improvement in wheat yields is important. This ranges from farmers in the developing world, through millers and bakers, to anyone buying bread in their local supermarket. The impact of the methods we develop will be seen first by the UK wheat breeders involved in this project, with delivery of improved varieties to market in the following few years.
More specifically:
The commercial breeding partners will benefit immediately by:
1. Initiation of propriety training populations of direct relevance to their breeding programs;
2. Protocols for cost reduction of genotyping by use of imputation and of phenotyping by remote capture of covariates;
3. Access to data generated in the project and to source code for programs required to implement GplusE.
Other breeders will benefit by publication of protocols for the application of GplusE within their own breeding programmes, including access to compiled versions of software developed within the project. This will be available following their publication.
Agronomists and field crop researchers will benefit from exemplars of the use of Phenomics and precision agriculture to improve the accuracy of treatment comparisons in field trials, for example in trials comparing agronomic inputs.
Suppliers of precision agriculture services and genotypes will benefit from new market opportunities in supplying services to field trials operators, including breeders.
The academic crop research community will benefit from improved techniques for field trials and demonstration of how novel physiological and other traits could be incorporated into breeding programmes within a quantitative genetics framework.
Longer term (>8 years) the linking of Phenomics and Genomics may result in development of varieties more adapted to specific environment conditions allowing, for example, automated switching of varieties during drilling to match micro-environmental conditions. This benefits the farmer in improving yield and the environment by reducing inputs currently required to compensate for variety weaknesses.
NIAB / RI will benefit from exposure to complementary expertise in each other's institutes. For NIAB this will result in improved application of big-data methods to their research interests in agricultural science and genetics. For RI, it will open opportunities for broader application of its quantitative genetics research and future funding and collaboration with both private and public sector crop and plant science communities.
The PDRAs funded by this project will benefit from contact with each other and with staff outside their host institutes. They will gain knowledge and expertise beyond the confines of their project areas.
This project will genotype, phenotype and analyse 3,000 lines. The size of the project and the disciplines involved, encompassing quantitative genetics, molecular genetics, plant physiology, Phenomics and agronomy will provide opportunities for training of scientific and technical staff in these fields. The research will also generate opportunities for field visits and workshops to stakeholders from outside RI and NIAB. NIAB Innovation Farm showcases innovation in agriculture, provides free support and assistance for small to medium businesses in the East of England and hosts national and international workshops. This infrastructure will be used to inform a wider public and scientific community.

Publications

10 25 50
 
Description Algorithms for genomic and phenomic prediction of yield have been developed, based on data collected across two sites and two years. Results showed that phenomic traits, mostly vegetation indices calculated from hyperspectral data collected using manned aircraft, were the most accurate predictors of genotypic performance. Combining phenomic predictors with genetic markers made small, additional improvements in prediction accuracy. Incorporating environmental covariates, such as apparent soil conductivity of the test sites, did not improve trial precision or prediction accuracies; this is may be because spatial differences in soil characteristics were not large enough to measureably affect yield.
Exploitation Route Outcomes have been made available to the commercial breeding companies that were partners in the project. Other companies and organisations not involved in the project have expressed interest in applying the findings to their own work. Published papers suggest ways these large trials and data sets can be statistically treated, and how genomic selection can be incorporated into ongoing breeding programmes.
Sectors Agriculture, Food and Drink

 
Description Ideas on how to incorporate genomic selection into breeding programmes have been considered by commercial seed companies. Algorithms for predicting yield performance of elite wheat crosses have been considered by commercial breeders. Methods for using airborne hyperspectral imagery for plant breeding have been learned by the company subcontracted to do the data capture.
First Year Of Impact 2018
Sector Agriculture, Food and Drink
Impact Types Economic

 
Description Workshop on implementation of genomic selection in the CGIAR breeding programmes
Geographic Reach Multiple continents/international 
Policy Influence Type Participation in a advisory committee
 
Description Workshop on implementation of genomic selection in the CGIAR breeding programmes
Geographic Reach Multiple continents/international 
Policy Influence Type Participation in a advisory committee
 
Title DiPR: Differentially Penalized Regression 
Description A simple method of independently weighting two or more sets of variables in ridge regression, while using standard ridge regression software. Useful in genomic prediction models with separate classes of genetic markers, and for incorporating different sets of predictors eg plant metabolites and genetic markers. 
Type Of Material Data analysis technique 
Year Produced 2015 
Provided To Others? Yes  
Impact Is being tested in various genomic selection projects. 
URL http://bmcgenet.biomedcentral.com/articles/10.1186/s12863-015-0169-0
 
Description Collaboration with Portugal 
Organisation National Institute of Agrarian and Veterinary Research
Country Portugal 
Sector Public 
PI Contribution I advise the Portuguese FASTBREED project: Implementation of a bread and durum wheat breeding program based on genomic selection using genomic selection. This is a project to introduce genomic selection into the state wheat breeding programmes. In 2016, at the kick off meetings, I gave two seminars; one to the breeders and one to molecular biologists and bioinformaticians to explain how genomic selection works. I also proposed a crossing and testing programme with their own breeding material to introduce genomic selection. This is now being put in place.
Collaborator Contribution Portuguese breeders and geneticists are running the breeding programme and carrying out all genotyping, analytical and other activities.
Impact None so far.
Start Year 2016
 
Title Diferentially Penalized Regression (DiPR) 
Description A simple method of using existing software for ridge regression to independently penalized two sets of predictors. THis is never less accurate than using either set alone or both sets pooled and treated as one. Applications are predicting traits from a combination of genetic markers and metabolites or predicting hybrid performance from co-dominant markers, fitting separate additive an dominance effects at each. Can be used in genomic selection and association mapping. 
Type Of Technology Software 
Year Produced 2014 
Open Source License? Yes  
Impact Prediction of wheat yields and other agronomic traits from seed metabolites and genetic markers. Combining known markers for QTL with background markers in genomic selection / prediction in an optimal manner. Used in two publications: Ward J, Rakszegi M, Bedo S, Shewry PR, Mackay I (2015) Differentially penalized regression to predict agronomic traits from metabolites and markers. BMC Genetics 16:19 Bentley AR, Scutari M, Gosman N, Faure S, Bedford F, Howell P, Cockram J, Rose GA, Barber T, Irigoyen J, Horsnell R, Pumfrey C, Winnie E, Schacht J, Beauchêne K, Praud S, Greenland A, Balding D, Mackay I J (2014) Applying association mapping and genomic selection to the dissection of key traits in elite European wheat. Theoretical and Applied Genetics, 127:2619-2633 
URL http://www.niab.com/pages/id/326/Resources
 
Title Selection of diverse subsets of lines 
Description An R script which uses genetic algorithms to select a subset of lines from a larger collection. The algorithm searches for the subset with either the greatest genetic diversity or which captures the greatest number of alleles. This is a replacement for similar functions previously available in the package PowerMarker. 
Type Of Technology Software 
Year Produced 2016 
Open Source License? Yes  
Impact The method was used to compare strategies for diversity capture in different multi-founder mapping population designs and is described in: Ladejobi, O., Elderfield, J., Gardner, K.A., Gaynor, R.C., Hickey, J., Hibberd, J.M., Mackay, I.J. and Bentley, A.R., 2016. Maximizing the potential of multi-parental crop populations. Applied & Translational Genomics, 11, pp.9-17. The software is a replacement for similar functions previously available in the package PowerMarker, which is no longer supported. 
URL http://www.niab.com/pages/id/326/Resources
 
Description BBRO workshop - genetics and remote sensing 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact BBRO decison makers and sugar beet growers attended NIAB to identify potential areas of collaboration. Advice was given on best remote sensing practice for sugar beet growing and research with remote sensing.
Year(s) Of Engagement Activity 2017
 
Description Camb. Plant Sci epidemiology groups 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Professional Practitioners
Results and Impact A seminar to the two epidemiology groups in the University of Cambridge Plant Sciences Department. To introduce to the methods and approaches of trait mapping and genomic selection in crops, highlighting some overlaps with epidemiological methodology.
Year(s) Of Engagement Activity 2016
 
Description Cereals 2015 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Interacted with visitors to cereals regarding remote sensing at NIAB
Year(s) Of Engagement Activity 2015
 
Description Cereals 2016 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Cereals 2016
Year(s) Of Engagement Activity 2016
URL http://www.cerealsevent.co.uk/
 
Description Croptech 2017 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact Industry event where I interacted with numerous potential remote sensing collaborators
Year(s) Of Engagement Activity 2017
URL http://www.croptecshow.com/
 
Description Drones for Farming 2015 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Presentation to practitioners of remote sensing on the developments in the remote sensing industry.
Year(s) Of Engagement Activity 2015
URL https://cdn.harper-adams.ac.uk/document/page/163_Presenter-Biographies.pdf
 
Description Drones in Farming 2016 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Presentation on remote sensing to industry providers and farmers. Resulted in collaboration with Harper Adams
Year(s) Of Engagement Activity 2016
URL http://www.harper-adams.ac.uk/initiatives/national-centre-precision-farming/drones-conference.cfm
 
Description Estonian farmers visit 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Visit to NIAB from Estonian farmers. Winners of their version of club hectare. Talk on GplusE approaches.
Year(s) Of Engagement Activity 2016
 
Description Farmers personal development group 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact Presentation on remote sensing to a collection of regional farmers on the benefit of remote sensing.
Year(s) Of Engagement Activity 2016
 
Description Farmers personal development meeting 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact Presentation to regional farmers on the benefits of remote sensing
Year(s) Of Engagement Activity 2015
 
Description IPPN talk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Talk given to academics and industry members at the International Plant Phenotyping Network workshop held at CIMMYT, Mexico, Dec. 2016. Examples were shown of phenotyping work done in project.
Year(s) Of Engagement Activity 2016
 
Description JHI offsite meeting 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact Gave talk to James Hutton Institute scientific staff at their annual off-site workshop in Dunkeld on genomic selection and how it can be implemented in small breeding programmes.
Year(s) Of Engagement Activity 2016
 
Description John Deere meeting 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact Meeting with John Deere representatives with regard to small grain production
Year(s) Of Engagement Activity 2016
 
Description Landmark article 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact NIAB publication - Landmark article on remote sensing
Year(s) Of Engagement Activity 2015
 
Description Landmark artucle on GS 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact I wrote an article on genomic selection "Genomic selection and the quantitative geneticists' revenge" for the NIAB members quarterly journal: LandMark Bulletin. This described the potential of genomic selection in plant breeding in lay terms.
Year(s) Of Engagement Activity 2016
 
Description Monogram 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Other audiences
Results and Impact Presented a poster at Monogram 2016, Cambridge
Year(s) Of Engagement Activity 2016
 
Description NIAB Open day 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Talk at NIAB open day on the potential benefits of GplusE.
Year(s) Of Engagement Activity 2015
 
Description NIAB open day 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact NIAB open day. Presented poster and plots on GplusE
Year(s) Of Engagement Activity 2016
 
Description QMPB 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact NIAB run a two week intensive course in Quantitative Methods for Plant Breeding, covering relevant aspects of statistics, quantitative genuetics and population genetics. There are 25 participants every year. To date, no-one has said they would not recommend the course to others. The course has also been put on in Australia, France, India (once at ICRISAT and once at the Punjab Agricultural University) and Malaysia. We update it every year to disseminate developments and methods resulting from out own research work in MAGIC, genomic selection, association mapping and plant breeding strategy. It has resulted in a global set of new contacts, some of which have resulted in successful collaborations.
Year(s) Of Engagement Activity 2008,2009,2010,2011,2012,2013,2014,2015,2016
URL http://www.niab.com/pages/id/360/quantitative_methods_in_plant_breeding
 
Description Talk to NPZ breeders 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Brief description of Remote sensing involved in GplusE project to Breeders from the UK and Germany.
Year(s) Of Engagement Activity 2017
 
Description Turkey Wheat Workshop 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Participation in one week workshop over multiple sites in Turkey to discuss UK - Turkish collaboration over wheat research, representing the NIAB Genetics and Breeding group on behalf of Dr Alison Bentley, the Director of Genetics and Breeding. Aside from questions and discussions at the time, it resulted in an agreement to sent some of our most resistant yellow rust lines to Turkey for screening, a novel approach to participatory plant breeding incorporating genomic selection and a collaborative grant application to the GCRF.
Year(s) Of Engagement Activity 2016
 
Description UCam ChemEng Lecture 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact Invited lecture given to 2nd year students in Chem Engineering. Talk focussed on use of sensors in agriculture, examples given from project work.
Year(s) Of Engagement Activity 2017
 
Description cereals 2015 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact Demonstration of NIAB outcomes and projects at Cereals 2016. Carried out every year, gets very large numbers of visitors and considerable coverage in the farming press.
Year(s) Of Engagement Activity 2015
 
Description multi-founder mapping populations in plants and animals 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact Workshop to discuss methods for creation and exploitation of MAGIC and MAGIC-like populations. A review paper will be written and submitted.

no actual impacts realised to date
Year(s) Of Engagement Activity 2013