Professor Ben Hayes
Professor

Ben Hayes

Email: 
Phone: 
+61 7 334 62173

Background

Professor Hayes has extensive research experience in genetic improvement of livestock, crop, pasture and aquaculture species, with a focus on integration of genomic information into breeding programs, including leading many large scale projects which have successfully implemented genomic technologies in livestock and cropping industries. Author of more than 300 journal papers, including in Nature Genetics, Nature Reviews Genetics, and Science, contributing to statistical methodology for genomic, microbiome and metagenomic profile predictions, quantitative genetics including knowledge of genetic mechanisms underlying complex traits, and development of bioinformatics pipelines for sequence analysis. Thomson Reuters highly cited researcher in 2015, 2016, 2017 and 2018.

Availability

Professor Ben Hayes is:
Available for supervision

Qualifications

  • Doctor of Philosophy, Central Queensland University
  • Certificate of Quantum Information, Computation and Communication, Massachusetts Institute of Technology

Research impacts

Genomic prediction, of which Ben Hayes was a co-inventor, and first described in the seminal publication [Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819-1829] is now being used very widely in livestock and crops to predict future trait outcomes. The technology is also being used increasingly in human disease research.

In dairy cattle, the technology has been actively used by the industry for the past five years, and increases in genetic gain for key economic traits can be demonstrated. Nearly every dairy bull worldwide chosen for widespread use in the industry is now selected on the basis of genomic predictions. Dr Hayes has been an invited speaker at numerous high profile conferences, including the Biology of Genomes conference at Cold Spring Harbor May 2015, and also has a number of youtube videos explaining complex trait prediction for a general audience, one of which has been viewed more than 5000 times (https://www.youtube.com/watch?v=RovnCsda-zQ).

Ben Hayes led the program on animal improvement of the Dairy Futures CRC, which concluded June 2016. The animal improvement program in the Dairy Futures CRC is a successful research and utilisation program which has a very high level of industry input and collaboration. The value of the program was recognised recently when it was awarded a Cooperative Research Centres Association (CRCA) Award for Excellence in Innovation. The Dairy Futures CRC under the leadership of Dr. Hayes successfully developed and implemented a genomic breeding value for feed efficiency, which has been widely adopted by the industry.

Dr. Hayes established the 1000 bull genomes project, a consortium of over 30 institutes across the globe, which has assembled whole genome sequences of 1682 cattle of 55 breeds. The consortium has published a widely cited paper in Nature Genetics (Daetwyler et al. 2014), and has already led to more than 50 companion papers.

Search Professor Ben Hayes’s works on UQ eSpace

399 works between 2000 and 2024
All (399) Journal Article (337) Book Chapter (9) Conference Publication (51) Other Outputs (2)

201 - 220 of 399 works

2016

Journal Article

Genomic selection improves heat tolerance in dairy cattle

Garner, J. B., Douglas, M. L., Williams, S. R. O., Wales, W. J., Marett, L. C., Nguyen, T. T. T., Reich, C. M. and Hayes, B. J. (2016). Genomic selection improves heat tolerance in dairy cattle. Scientific Reports, 6 (1) 34114, 34114. doi: 10.1038/srep34114

Genomic selection improves heat tolerance in dairy cattle

2016

Journal Article

Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture

Goddard, M. E., Kemper, K. E., MacLeod, I. M., Chamberlain, A. J. and Hayes, B. J. (2016). Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture. Proceedings of the Royal Society B: Biological Sciences, 283 (1835) 20160569, 20160569. doi: 10.1098/rspb.2016.0569

Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture

2016

Journal Article

Genomic selection for tolerance to heat stress in Australian dairy cattle

Nguyen, Thuy T. T., Bowman, Phil J., Haile-Mariam, Mekonnen, Pryce, Jennie E. and Hayes, Benjamin J. (2016). Genomic selection for tolerance to heat stress in Australian dairy cattle. Journal of Dairy Science, 99 (4), 2849-2862. doi: 10.3168/jds.2015-9685

Genomic selection for tolerance to heat stress in Australian dairy cattle

2016

Journal Article

Polyceraty (multi-horns) in Damara sheep maps to ovine chromosome 2

Greyvenstein, O. F. C., Reich, C. M., van Marle-Koster, E., Riley, D. G. and Hayes, B. J. (2016). Polyceraty (multi-horns) in Damara sheep maps to ovine chromosome 2. Animal Genetics, 47 (2), 263-266. doi: 10.1111/age.12411

Polyceraty (multi-horns) in Damara sheep maps to ovine chromosome 2

2016

Journal Article

Detailed phenotyping identifies genes with pleiotropic effects on body composition

Bolormaa, Sunduimijid, Hayes, Ben J., van der Werf, Julius H. J., Pethick, David, Goddard, Michael E. and Daetwyler, Hans D. (2016). Detailed phenotyping identifies genes with pleiotropic effects on body composition. BMC Genomics, 17 (224) 224, 1-21. doi: 10.1186/s12864-016-2538-0

Detailed phenotyping identifies genes with pleiotropic effects on body composition

2016

Journal Article

Genomic heritabilities and genomic estimated breeding values for methane traits in Angus cattle

Hayes, B. J., Donoghue, K. A., Reich, C. M., Mason, B. A., Bird-Gardiner, T., Herd, R. M. and Arthur, P. F. (2016). Genomic heritabilities and genomic estimated breeding values for methane traits in Angus cattle. Journal of Animal Science, 94 (3), 902-908. doi: 10.2527/jas2015-0078

Genomic heritabilities and genomic estimated breeding values for methane traits in Angus cattle

2016

Journal Article

Genetic gain and inbreeding from genomic selection in a simulated commercial breeding program for perennial ryegrass

Lin, Zibei, Cogan, Noel O. I., Pembleton, Luke W., Spangenberg, German C., Forster, John W., Hayes, Ben J. and Daetwyler, Hans D. (2016). Genetic gain and inbreeding from genomic selection in a simulated commercial breeding program for perennial ryegrass. Plant Genome, 9 (1), 876-883. doi: 10.3835/plantgenome2015.06.0046

Genetic gain and inbreeding from genomic selection in a simulated commercial breeding program for perennial ryegrass

2016

Journal Article

Technical note: equivalent genomic models with a residual polygenic effect

Liu, Z., Goddard, M. E., Hayes, B. J., Reinhardt, F. and Reents, R. (2016). Technical note: equivalent genomic models with a residual polygenic effect. Journal of Dairy Science, 99 (3), 2016-2025. doi: 10.3168/jds.2015-10394

Technical note: equivalent genomic models with a residual polygenic effect

2016

Journal Article

Targeted imputation of sequence variants and gene expression profiling identifies twelve candidate genes associated with lactation volume, composition and calving interval in dairy cattle

Raven, Lesley-Ann, Cocks, Benjamin G., Kemper, Kathryn E., Chamberlain, Amanda J., Vander Jagt, Christy J., Goddard, Michael E. and Hayes, Ben J. (2016). Targeted imputation of sequence variants and gene expression profiling identifies twelve candidate genes associated with lactation volume, composition and calving interval in dairy cattle. Mammalian Genome, 27 (1-2), 81-97. doi: 10.1007/s00335-015-9613-8

Targeted imputation of sequence variants and gene expression profiling identifies twelve candidate genes associated with lactation volume, composition and calving interval in dairy cattle

2016

Journal Article

Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits

MacLeod, I. M., Bowman, P. J., Vander Jagt, C. J., Haile-Mariam, M., Kemper, K. E., Chamberlain, A. J., Schrooten, C., Hayes, B. J. and Goddard, M. E. (2016). Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits. BMC Genomics, 17 (1) 144. doi: 10.1186/s12864-016-2443-6

Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits

2016

Journal Article

Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits

Aliloo, Hassan, Pryce, Jennie E., Gonzalez-Recio, Oscar, Cocks, Benjamin G. and Hayes, Ben J. (2016). Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits. Genetics Selection Evolution, 48 (1) 186, 8.1-8.11. doi: 10.1186/s12711-016-0186-0

Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits

2016

Journal Article

Reducing the carbon footprint of Australian milk production by mitigation of enteric methane emissions

Moate, Peter J., Deighton, Matthew H., Williams, S. Richard O., Pryce, Jennie E., Hayes, Ben J., Jacobs, Joe L., Eckard, Richard J., Hannah, Murray C. and Wales, William J. (2016). Reducing the carbon footprint of Australian milk production by mitigation of enteric methane emissions. Animal Production Science, 56 (7), 1017-1034. doi: 10.1071/AN15222

Reducing the carbon footprint of Australian milk production by mitigation of enteric methane emissions

2016

Journal Article

Accuracy and computational efficiency of genomic selection with high-density SNP and whole-genome sequence data

Wang, Tingting, Chen, Yi-Ping Phoebe and Hayes, Ben (2016). Accuracy and computational efficiency of genomic selection with high-density SNP and whole-genome sequence data. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 11 (034) 034, 1-18. doi: 10.1079/PAVSNNR201611034

Accuracy and computational efficiency of genomic selection with high-density SNP and whole-genome sequence data

2016

Conference Publication

Improving the selection efficiency in potato breeding

Slater, A. T., Cogan, N. O.I., Rodoni, B. C., Hayes, B. J. and Forster, J. W. (2016). Improving the selection efficiency in potato breeding. 29th International Horticultural Congress on Horticulture - Sustaining Lives, Livelihoods and Landscapes (IHC) / International Symposium on Plant Breeding in Horticulture, Brisbane, QLD, Australia, 17-22 August 2014. LEUVEN 1: International Society for Horticultural Science. doi: 10.17660/ActaHortic.2016.1127.37

Improving the selection efficiency in potato breeding

2016

Journal Article

Genomic selection: a paradigm shift in animal breeding

Meuwissen, Theo, Hayes, Ben and Goddard, Mike (2016). Genomic selection: a paradigm shift in animal breeding. Animal Frontiers, 6 (1), 6-14. doi: 10.2527/af.2016-0002

Genomic selection: a paradigm shift in animal breeding

2016

Journal Article

Differentially expressed genes in endometrium and corpus luteum of holstein cows selected for high and low fertility are enriched for sequence variants associated with fertility

Moore, Stephen G., Pryce, Jennie E., Hayes, Ben J., Chamberlain, Amanda J., Kemper, Kathryn E., Berry, Donagh P., McCabe, Matt, Cormican, Paul, Lonergan, Pat, Fair, Trudee and Butler, Stephen T. (2016). Differentially expressed genes in endometrium and corpus luteum of holstein cows selected for high and low fertility are enriched for sequence variants associated with fertility. Biology of Reproduction, 94 (1) 19. doi: 10.1095/biolreprod.115.132951

Differentially expressed genes in endometrium and corpus luteum of holstein cows selected for high and low fertility are enriched for sequence variants associated with fertility

2015

Journal Article

Accuracy of genotype imputation based on random and selected reference sets in purebred and crossbred sheep populations and its effect on accuracy of genomic prediction

Moghaddar, Nasir, Gore, Klint P., Daetwyler, Hans D., Hayes, Ben J. and van der Werf, Julius H. J. (2015). Accuracy of genotype imputation based on random and selected reference sets in purebred and crossbred sheep populations and its effect on accuracy of genomic prediction. Genetics Selection Evolution, 47 (1) 175. doi: 10.1186/s12711-015-0175-8

Accuracy of genotype imputation based on random and selected reference sets in purebred and crossbred sheep populations and its effect on accuracy of genomic prediction

2015

Journal Article

Rare variants in transcript and potential regulatory regions explain a small percentage of the missing heritability of complex traits in cattle

Gonzalez-Recio, Oscar, Daetwyler, Hans D., MacLeod, Iona M., Pryce, Jennie E., Bowman, Phil J., Hayes, Ben J. and Goddard, Michael E. (2015). Rare variants in transcript and potential regulatory regions explain a small percentage of the missing heritability of complex traits in cattle. PLoS One, 10 (12) e0143945, e0143945. doi: 10.1371/journal.pone.0143945

Rare variants in transcript and potential regulatory regions explain a small percentage of the missing heritability of complex traits in cattle

2015

Journal Article

Extensive variation between tissues in allele specific expression in an outbred mammal

Chamberlain, Amanda J., Vander Jagt, Christy J., Hayes, Benjamin J., Khansefid, Majid, Marett, Leah C., Millen, Catriona A., Nguyen, Thuy T. T. and Goddard, Michael E. (2015). Extensive variation between tissues in allele specific expression in an outbred mammal. BMC Genomics, 16 (1) 993. doi: 10.1186/s12864-015-2174-0

Extensive variation between tissues in allele specific expression in an outbred mammal

2015

Journal Article

Two-variance-component model improves genetic prediction in family datasets

Tucker, George, Loh, Po-Ru, MacLeod, Iona M., Hayes, Ben J., Goddard, Michael E., Berger, Bonnie and Price, Alkes L. (2015). Two-variance-component model improves genetic prediction in family datasets. American Journal of Human Genetics, 97 (5), 677-690. doi: 10.1016/j.ajhg.2015.10.002

Two-variance-component model improves genetic prediction in family datasets

Current funding

  • 2024 - 2029
    ARC Training Centre in Predictive Breeding for Agricultural Futures
    ARC Industrial Transformation Training Centres
    Open grant
  • 2024 - 2028
    Program 2 - Resistance Sources: Using 'FastStack' to develop effective durable net blotch resistance gene stacks
    Grains Research & Development Corporation
    Open grant
  • 2024 - 2029
    Achieving improved genetic gain for yield in chickpea, faba bean and lentil using genetic diversity (GRDC grant administered by Murdoch University)
    Murdoch University
    Open grant
  • 2024 - 2028
    Fast tracking deployment of chickpea heat tolerance
    GRDC - PROC-9176886 - Fast tracking deployment of chickpea heat tolerance to develop chickpea varieties with improved high temperature tolerance
    Open grant
  • 2023 - 2027
    RustHapSelect: Fast-tracking rust resistance haplotypes into high-yielding germplasm (GRDC grant administered by CSIRO)
    CSIRO
    Open grant
  • 2022 - 2025
    Northern Genomics commercialisation scoping study
    Meat & Livestock Australia
    Open grant
  • 2022 - 2027
    Reducing methane emissions and improving profitability in Northern Australian beef
    Meat & Livestock Australia
    Open grant
  • 2022 - 2026
    Scaling Genomic Selection Across the Indian Smallholder Dairy Sector (BMGF grant administered by BAIF Development Research Foundation)
    BAIF Development Research Foundation
    Open grant
  • 2022 - 2027
    Facilitating Innovations for Resilient Livestock Farming Systems (Re-Livestock) (Horizon Europe grant administered by the Spanish National Research Council)
    Spanish National Research Council (Agencia Estatal Consejo Superior de Investigaciones Científicas)
    Open grant
  • 2022 - 2026
    Balancing polled and profit: demonstration of breeding strategies to replace dehorning in a large integrated beef and cattle operation
    A. A. COMPANY PTY. LTD.
    Open grant
  • 2022 - 2026
    On-farm genomics: genomic solutions for Northern beef cattle management and breeding
    Meat & Livestock Australia
    Open grant
  • 2022 - 2026
    Digging deeper to improve yield stability
    ARC Linkage Projects
    Open grant
  • 2022 - 2026
    LESTR Low Emission Saliva Test for Ruminants
    Meat & Livestock Australia
    Open grant
  • 2021 - 2026
    ARC Research Hub for Supercharging Tropical Aquaculture Through Genetic Solutions - externally administered by James Cook University (JCU)
    James Cook University
    Open grant
  • 2021 - 2026
    NB2: Assessing practical interventions to reduce calf wastage and herd mortality in northern systems
    Meat & Livestock Australia
    Open grant

Past funding

  • 2023 - 2024
    Genomic prediction of ratoon yield robustness
    Sugar Research Australia Limited
    Open grant
  • 2022 - 2024
    Northern Beef Information Nucleus (Spyglass) Phase 4 Extension
    Australian Brahman Breeders' Association Limited
    Open grant
  • 2022 - 2024
    Development of genomic multi-breed eating quality trait estimates using shared global data (Meat & Livestock Australia project administered by University of New England)
    University of New England
    Open grant
  • 2021 - 2022
    DNA as the ultimate identifier in blockchain traceability systems
    Innovation Connections
    Open grant
  • 2020 - 2024
    Screening of diverse barley germplasm for rapid discovery and utilisation of novel disease resistance in barley using R-HapSelect : A haplotype-based toolkit
    Grains Research & Development Corporation
    Open grant
  • 2020 - 2023
    FY20 Postgraduate Scholarships - Harrison Lamb
    Meat & Livestock Australia
    Open grant
  • 2019 - 2021
    Bull fertility update: historical data, new cohort and advanced genomics (Meat & Livestock Australia grant administered by CSIRO)
    CSIRO
    Open grant
  • 2018 - 2023
    India Dairy Genetic Gain: Array designs for Indian Cattle and Buffalo
    Bill & Melinda Gates Foundation
    Open grant
  • 2018 - 2024
    National Tree Genomics Program - Genomics Toolbox
    Horticulture Innovation Australia Limited
    Open grant
  • 2018 - 2021
    Predicting age of livestock from DNA samples
    Meat & Livestock Australia
    Open grant
  • 2018 - 2023
    National Tree Genomics Program - Phenotype Prediction
    Horticulture Innovation Australia Limited
    Open grant
  • 2018 - 2023
    FastStack - evolutionary computing to stack desirable alleles in wheat
    ARC Linkage Projects
    Open grant
  • 2018 - 2021
    Female Reproduction Phenobank and Validation Herds
    Meat & Livestock Australia
    Open grant
  • 2017 - 2020
    Novel genomic technologies to improve fertility in Northern Beef Cattle
    ARC Linkage Projects
    Open grant
  • 2017 - 2024
    Improving fertility in northern cattle through host and pathogen molecular diagnosis
    Meat & Livestock Australia
    Open grant
  • 2017 - 2023
    Implementing and validating genomic selection in SRA breeding programs to accelerate improvements in yield, commercial cane sugar, and other key traits
    Sugar Research Australia Limited
    Open grant
  • 2017 - 2019
    Genetics R&D: Characterisation of the Brahman Genome
    Meat & Livestock Australia
    Open grant
  • 2017 - 2023
    Improving bovine respiratory disease control through the characterisation of pathogen genomics and host interactions
    Meat & Livestock Australia
    Open grant
  • 2017 - 2018
    Expression of genes and proteins related to meat quality in Bos indicus cattle
    UQ-FAPESP Strategic Research Fund SPRINT
    Open grant
  • 2017 - 2022
    Accelerating genetic gain for productivity and profitability in Northern beef cattle with genomic technologies
    Meat & Livestock Australia
    Open grant
  • 2017 - 2024
    Cattle tick and Buffalo fly host genetics, susceptibility to buffalo fly lesions and biomarkers for resistance
    Meat & Livestock Australia
    Open grant

Availability

Professor Ben Hayes is:
Available for supervision

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Supervision history

Current supervision

Completed supervision

Enquiries

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