[en] Phenotypes have been reviewed to select for lower-emitting animals in order to decrease the environmental footprint of dairy cattle products. This includes direct selection for breath measurements, as well as indirect selection via indicator traits such as feed intake, milk spectral data, and rumen microbial communities. Many of these traits are expensive or difficult to record, or both, but with genomic selection, inclusion of methane emission as a breeding goal trait is feasible, even with a limited number of registrations. At present, methane emission is not included among breeding goals for dairy cattle worldwide. There is no incentive to include enteric methane in breeding goals, although global warming and the release of greenhouse gases is a much-debated political topic. However, if selection for reduced methane emission became a reality, there would be limited consensus as to which phenotype to select for: methane in liters per day or grams per day, methane in liters per kilogram of energy-corrected milk or dry matter intake, or a residual methane phenotype, where methane production is corrected for milk production and the weight of the cow. We have reviewed the advantages and disadvantages of these traits, and discuss the methods for selection and consequences for these phenotypes.
Disciplines :
Genetics & genetic processes Animal production & animal husbandry
Author, co-author :
de Haas, Yvette; Wageningen UR Livestock Research
Pszczola, Marcin; Poznan University of Life Sciences
Soyeurt, Hélène ; Université de Liège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Modélisation et développement
Wall, Eilleen; Scotland's Rural College - SRUC
Lassen, Jan; Aarhus University
Language :
English
Title :
Invited review: Phenotypes to genetically reduce greenhouse gas emissions in dairying
Alternative titles :
Phénotypes pour réduire génétiquement les émissions de méthane des vaches laitières
Publication date :
2017
Journal title :
Journal of Dairy Science
ISSN :
0022-0302
eISSN :
1525-3198
Publisher :
American Dairy Science Association, Champaign, United States - Illinois
Volume :
100
Issue :
2
Pages :
855-870
Peer reviewed :
Peer Reviewed verified by ORBi
Name of the research project :
Methagene
Funders :
COST - European Cooperation in Science and Technology [BE]
Aguerre, M. J., M. A. Wattiaux, J. M. Powell, and G. A. Broderick. 2010. Effect of dietary forage to concentrate ratio on lactation performance and methane emission from dairy cows. In Proc. 4th Int. Conf. GHG Anim. Agric., Banff, Canada.
Aguerre, M.J., Wattiaux, M.A., Powell, J.M., Broderick, G.A., Arndt, C., Effect of forage-to-concentrate ratio in dairy cow diets on emission of methane, carbon dioxide, and ammonia, lactation performance, and manure excretion. J. Dairy Sci. 94 (2011), 3081–3093 21605777.
Aguilar, I., Misztal, I., Johnson, D.L., Legarra, A., Tsuruta, S., Lawlor, T.J., Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. J. Dairy Sci. 93 (2010), 743–752 20105546.
Attwood, G.T., Altermann, E., Kelly, W.J., Leahy, S.C., Zhang, L., Morrison, M., Exploring rumen methanogen genomes to identify targets for methane mitigation strategies. Anim. Feed Sci. Technol. 166–67 (2011), 65–75.
Axelsson, H.H., Fikse, W.F., Kargo, M., Sorensen, A.C., Johansson, K., Rydhmer, L., Genomic selection using indicator traits to reduce the environmental impact of milk production. J. Dairy Sci. 96 (2013), 5306–5314 23726422.
Banos, G., Coffey, M.P., Veerkamp, R.F., Berry, D.P., Wall, E., Merging and characterising phenotypic data on conventional and rare traits from dairy cattle experimental resources in three countries. Animal 6 (2012), 1040–1048 23031463.
Bell, M.J., Wall, E., Russell, G., Simm, G., Stott, A.W., The effect of improving cow productivity, fertility, and longevity on the global warming potential of dairy systems. J. Dairy Sci. 94 (2011), 3662–3678 21700056.
Benchaar, C., Greathead, H., Essential oils and opportunities to mitigate enteric methane emissions from ruminants. Anim. Feed Sci. Technol. 166–67 (2011), 338–355.
Benson, A.K., Kelly, S.A., Legge, R., Ma, F.R., Low, S.J., Kim, J., Zhang, M., Oh, P.L., Nehrenberg, D., Hua, K.J., Kachman, S.D., Moriyama, E.N., Walter, J., Peterson, D.A., Pomp, D., Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc. Natl. Acad. Sci. USA 107 (2010), 18933–18938 20937875.
Berry, D.P., Crowley, J.J., Cell biology symposium: Genetics of feed efficiency in dairy and beef cattle. J. Anim. Sci. 91 (2013), 1594–1613 23345557.
Berry, D.P., Lassen, J., de Haas, Y., Residual feed intake and breeding approached for enteric methane. Malik, P.K., Bhatta, R., Takahashi, J., Kohn, R.A., Prasad, C.S., (eds.) Livestock Production and Climate Change, 2015, CABI, Wallingford, UK, 273–291.
Boettcher, P.J., Pagnacco, G., Stella, A., A Monte Carlo approach for estimation of haplotype probabilities in half-sib families. J. Dairy Sci. 87 (2004), 4303–4310 15545394.
Boichard, D., Brochard, M., New phenotypes for new breeding goals in dairy cattle. Animal 6 (2012), 544–550 22436268.
Bouwman, A.C., Hickey, J., Calus, M., Veerkamp, R., Imputation of non-genotyped individuals based on genotyped relatives: Assessing the imputation accuracy of a real case scenario in dairy cattle. Genet. Sel. Evol., 46, 2014, 6 24490796.
Buch, L.H., Kargo, M., Berg, P., Lassen, J., Sørensen, A.C., The value of cows in reference populations for genomic selection of new functional traits. Animal, 6, 2012, 880 22558957.
Buch, L.H., Sorensen, M.K., Berg, P., Pedersen, L.D., Sorensen, A.C., Genomic selection strategies in dairy cattle: Strong positive interaction between use of genotypic information and intensive use of young bulls on genetic gain. J. Anim. Breed. Genet. 129 (2012), 138–151 22394236.
Buddle, B.M., Denis, M., Attwood, G.T., Altermann, E., Janssen, P.H., Ronimus, R.S., Pinares-Patino, C.S., Muetzel, S., Wedlock, D.N., Strategies to reduce methane emissions from farmed ruminants grazing on pasture. Vet. J. 188 (2011), 11–17 20347354.
Calus, M.P.L., De Haas, Y., Pszczola, M., Veerkamp, R.F., Predicted accuracy of and response to genomic selection for new traits in dairy cattle. Animal 7 (2013), 183–191 23031684.
Calus, M.P., de Haas, Y., Veerkamp, R.F., Combining cow and bull reference populations to increase accuracy of genomic prediction and genome-wide association studies. J. Dairy Sci. 96 (2013), 6703–6715.
Calus, M.P.L., Veerkamp, R.F., Accuracy of multi-trait genomic selection using different methods. Genet. Sel. Evol., 43, 2011, 26 21729282.
Calus, M.P.L., Veerkamp, R.F., Mulder, H.A., Imputation of missing single nucleotide polymorphism genotypes using a multivariate mixed model framework. J. Anim. Sci. 89 (2011), 2042–2049 21357451.
Capper, J.L., Cady, R.A., Bauman, D.E., The environmental impact of dairy production: 1944 compared with 2007. J. Anim. Sci. 87 (2009), 2160–2167 19286817.
Chagunda, M.G.G., Ross, D., Roberts, D.J., On the use of a laser methane detector in dairy cows. Comput. Electron. Agric. 68 (2009), 157–160.
Chagunda, M.G.G., Yan, T., Do methane measurements from a laser detector and an indirect open-circuit respiration calorimetric chamber agree sufficiently closely?. Anim. Feed Sci. Technol. 165 (2011), 8–14.
Chaudhry, A. S., and M. A. K. Khalil. 2010. Effect of various spices on in vitro degradability, methane and fermentation profiles of different ruminant feeds. In Proc. 4th Int. Conf. GHG Anim. Agric., Banff, Canada.
Chaudhry, A.S., Khan, M.M.H., Impacts of different spices on in vitro rumen dry matter disappearance, fermentation and methane of wheat or ryegrass hay based substrates. Livest. Sci. 146 (2012), 84–90.
Chilliard, Y., Martin, C., Rouel, J., Doreau, M., Milk fatty acids in dairy cows fed whole crude linseed, extruded linseed, or linseed oil, and their relationship with methane output. J. Dairy Sci. 92 (2009), 5199–5211 19762838.
Clark, S.A., Hickey, J., Daetwyler, H., van der Werf, J., The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes. Genet. Sel. Evol., 44, 2012, 4 22321529.
Colvin, H.W., Cupps, P.T., Cole, H.H., Dietary influences on eructation and related ruminal phenomena in cattle. J. Dairy Sci. 41 (1958), 1565–1579.
Connor, E.E., Hutchison, J.L., Olson, K.M., Norman, H.D., Triennial lactation symposium: Opportunities for improving milk production efficiency in dairy cattle. J. Anim. Sci. 90 (2012), 1687–1694 22038990.
Daetwyler, H.D., Villanueva, B., Woolliams, J.A., Accuracy of predicting the genetic risk of disease using a genome-wide approach. PLoS One, 3, 2008, e3395 18852893.
Daetwyler, H.D., Wiggans, G.R., Hayes, B.J., Woolliams, J.A., Goddard, M.E., Imputation of missing genotypes from sparse to high density using long-range phasing. Genetics 189 (2011), 317–327 21705746.
de Haas, Y., Calus, M.P.L., Veerkamp, R.F., Wall, E., Coffey, M.P., Daetwyler, H.D., Hayes, B.J., Pryce, J.E., Improved accuracy of genomic prediction for dry matter intake of dairy cattle from combined European and Australian data sets. J. Dairy Sci. 95 (2012), 6103–6112 22863091.
de Haas, Y., Windig, J.J., Calus, M.P.L., Dijkstra, J., de Haan, M., Bannink, A., Veerkamp, R.F., Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection. J. Dairy Sci. 94 (2011), 6122–6134 22118100.
de Roos, A.P.W., Genomic Selection in Dairy Cattle, 2011, Wageninen University, Wageningen, Netherlands.
Dehareng, F., Delfosse, C., Froidmont, E., Soyeurt, H., Martin, C., Gengler, N., Vanlierde, A., Dardenne, P., Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows. Animal 6 (2012), 1694–1701 23031566.
Demeyer, D.I., Van Nevel, C.J., Methanogenesis, an integrated part of carbohydrate fermentation and its control. McDonald, I.W., Warner, A.C.I., (eds.) Digestion and Metabolism in the Ruminant, 1975, University of New England Publishing Unit, Armidale, NSW, Australia, 366–382.
Désilets, E., Greenhouse gas mitigation program for Canadian agriculture. Final report for the Dairy Farmers of Canada. Accessed Oct. 29, 2016. http://www.dairyfarmers.ca/content/download/307/1692/version/1/file/Our_cows_our_air_final_report.pdf, 2006.
Dijkstra, J., van Zijderveld, S.M., Apajalahti, J.A., Bannink, A., Gerrits, W.J.J., Newbold, J.R., Perdok, H.B., Berends, H., Relationships between methane production and milk fatty acid profiles in dairy cattle. Anim. Feed Sci. Technol. 166–67 (2011), 590–595.
Donoghue, K.A., Herd, R.M., Bird, S.H., Arthur, P.F., Hegarty, R.S., Preliminary genetic parameters for methane production in Australian beef cattle. Pages 290–293 in 20th Proc. Assoc. Advmt. Anim. Breed. Genet., Napier, New Zealand. http://www.aaabg.org/aaabghome/proceedings20.php, 2013.
Dougherty, R.W., Cook, H.M., Routes of eructed gas expulsion in cattle—A quantitative study. Am. J. Vet. Res. 23 (1962), 997–1000 13887521.
Druet, T., Georges, M., A hidden Markov model combining linkage and linkage disequilibrium information for haplotype reconstruction and quantitative trait locus fine mapping. Genetics 184 (2010), 789–798 20008575.
Ellis, J.L., Dijkstra, J., Kebreab, E., Bannink, A., Odongo, N.E., McBride, B.W., France, J., Aspects of rumen microbiology central to mechanistic modelling of methane production in cattle. J. Agric. Sci. 146 (2008), 213–233.
Ferris, C.P., Gordon, F.J., Patterson, D.C., Porter, M.G., Yan, T., The effect of genetic merit and concentrate proportion in the diet on nutrient utilization by lactating dairy cows. J. Agric. Sci. 132 (1999), 483–490.
Garnsworthy, P.C., The environmental impact of fertility in dairy cows: A modelling approach to predict methane and ammonia emissions. Anim. Feed Sci. Technol. 112 (2004), 211–223.
Garnsworthy, P.C., Craigon, J., Hernandez-Medrano, J.H., Saunders, N., Variation among individual dairy cows in methane measurements made on farm during milking. J. Dairy Sci. 95 (2012), 3181–3189 22612953.
Gengler, N., Abras, S., Verkenne, C., Vanderick, S., Szydlowski, M., Renaville, R., Accuracy of prediction of gene content in large animal populations and its use for candidate gene detection and genetic evaluation. J. Dairy Sci. 91 (2008), 1652–1659 18349258.
Goddard, M., Genomic selection: Prediction of accuracy and maximisation of long term response. Genetica 136 (2009), 245–257 18704696.
Goddard, M.E., Hayes, B.J., Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nat. Rev. Genet. 10 (2009), 381–391 19448663.
Guan, L.L., Nkrumah, J.D., Basarab, J.A., Moore, S.S., Linkage of microbial ecology to phenotype: Correlation of rumen microbial ecology to cattle's feed efficiency. FEMS Microbiol. Lett. 288 (2008), 85–91 18785930.
Habier, D., Tetens, J., Seefried, F.-R., Lichtner, P., Thaller, G., The impact of genetic relationship information on genomic breeding values in German Holstein cattle. Genet. Sel. Evol. 42 (2010), 5–17 20170500.
Hansen Axelsson, H., Thomasen, J.R., Sørensen, A.C., Rydhmer, L., Kargo, M., Johansson, K., Fikse, W.F., Breakeven prices for recording of indicator traits to reduce the environmental impact of milk production. J. Anim. Breed. Genet. 132 (2015), 30–41 25134920.
Haque, M.N., Cornou, C., Madsen, J., Estimation of methane emission using the C02 method from dairy cows fed concentrate with different carbohydrate compositions in automatic milking system. Livest. Sci. 164 (2014), 57–66.
Hayes, B., Goddard, M., Genome-wide association and genomic selection in animal breeding. Genome 53 (2010), 876–883 21076503.
Hayes, B.J., Bowman, P.J., Chamberlain, A.J., Goddard, M.E., Invited review: Genomic selection in dairy cattle: Progress and challenges. J. Dairy Sci. 92 (2009), 433–443 19164653.
Hayes, B.J., Lewin, H.A., Goddard, M.E., The future of livestock breeding: genomic selection for efficiency, reduced emissions intensity, and adaptation. Trends Genet. 29 (2013), 206–214 23261029.
Hegarty, R.S., Genotype differences and their impact on digestive tract function of ruminants: A review. Aust. J. Exp. Agric. 44 (2004), 458–467.
Hegarty, R.S., Current and emerging technologies for decreasing enteric methane emission from individual ruminants. Rec. Adv. Anim. Nutr. 17 (2009), 81–88.
Hegarty, R.S., Applicability of short-term emission measurements for on-farm quantification of enteric methane. Animal 7 (2013), 401–408 23739481.
Hegarty, R.S., Goopy, J.P., Herd, R.M., McCorkell, B., Cattle selected for lower residual feed intake have reduced daily methane production. J. Anim. Sci. 85 (2007), 1479–1486 17296777.
Herd, R.M., Arthur, P.F., Bird, S.H., Donoghue, K.A., Hegarty, R.S., Genetic variation for methane traits in beef cattle. In Proc. 10th World Conference on Genetic Applied to Livestock Production, Vancouver, Canada. https://asas.org/meetings/previous-meetings/wcgalp, 2014.
Herd, R. M., P. F. Arthur, R. S. Hegarty, and J. A. Archer. 2002. Potential to reduce greenhouse gas emissions from beef production by selection for reduced residual feed intake. In Proc. 7th World Congress on Genetics Applied to Livestock Production, Montpellier, France.
Herd, R. M., S. H. Bird, K. A. Donoghue, P. F. Arthur, and R. S. Hegarty. 2013. Phenotypic associations between methane production traits, volatile fatty acids and animal breeding traits. Pages 286–289 in Proc. Proc. Assoc. Advmt. Anim. Breed. Genet., Napier, New Zealand.
Hickey, J.M., Kinghorn, B., Tier, B., van der Werf, J., Cleveland, M., A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation. Genet. Sel. Evol., 44, 2012, 9 22462519.
Howie, B.N., Donnelly, P., Marchini, J., A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet., 5, 2009, e1000529 19543373.
Hulshof, R.B.A., Berndt, A., Gerrits, W.J.J., Dijkstra, J., van Zijderveld, S.M., Newbold, J.R., Perdok, H.B., Dietary nitrate supplementation reduces methane emission in beef cattle fed sugarcane-based diets. J. Anim. Sci. 90 (2012), 2317–2323 22287674.
Hungate, R.E., Methane formation and cellulose digestion—Biochemical ecology and microbiology of the rumen ecosystem. Experientia 43 (1982), 117–120 6955186.
Hungate, R.E., Symposium on ‘Nutritional implications of microbial action in the nonruminal alimentary tract’. Microbes of nutritional importance in the alimentary tract. Proc. Nutr. Soc. 43 (1984), 1–11 6709632.
Jentsch, W., Schweigel, M., Weissbach, F., Scholze, H., Pitroff, W., Derno, M., Methane production in cattle calculated by the nutrient composition of the diet. Arch. Anim. Nutr. 61 (2007), 10–19 17361944.
Johannes, M., A. L. F. Hellwing, P. Lund, M. R. Weisbjerg, and T. Hvelplund. 2010. Different physical forms of rapeseed as fat source to reduce enteric methane emission from dairy cows. In Proc. Proc. 4th. Int. Conf. GHG Anim. Agric., Banff, Canada.
Johnson, D.E., Hill, T.M., Ward, G.M., Johnson, K.A., Branine, M.E., Carmean, B.R., Lodman, D.W., Ruminants and other animals. Khalil, M.A.K., (eds.) Atmospheric Methane: Sources, Sinks, and Role in Global Change, Vol. 13, 1993, Springer, Berlin, Germany, 199–229.
Johnson, K.A., Westberg, H.H., Lamb, B.K., Kincaid, R.L., The use of sulphur hexafluoride for measuring methane production by cattle. McCracken, K.J., Unsworth, E.F., Wylie, A.R.G., (eds.) Energy Metabolism of Farm Animals, 1998, CABI Publishing, Wallingford, UK, 189–192.
Kandel, P. B., S. Vanderick, M.-L. Vanrobays, A. Vanlierde, F. Dehareng, E. Froidmont, H. Soyeurt, and N. Gengler. 2014. Consequences of selection for environmental impact traits in dairy cows. In Proc. 10th World Conference on Genetic Applied to Livestock Production, Vancouver, Canada, August 17–22, 2014.
Kandel, P.B., Vanrobays, M.-L., Vanlierde, A., Dehareng, F., Froidmont, E., Dardenne, P., Lewis, E., Buckley, F., Deighton, M.H., McParland, S., Gengler, N., Soyeurt, H., Genetic parameters for methane emissions predicted from milk mid-infrared spectra in dairy cows. Adv. Anim. Biosci., 4, 2013, 279.
Knapp, J.R., Laur, G.L., Vadas, P.A., Weiss, W.P., Tricarico, J.M., Invited review: Enteric methane in dairy cattle production: Quantifying the opportunities and impact of reducing emissions. J. Dairy Sci. 97 (2014), 3231–3261 24746124.
Lassen, J., Lovendahl, P., Heritability for enteric methane emission from Danish Holstein cows using a non-invasive FTIR method. Adv. Anim. Biosci., 4, 2013, 280.
Lassen, J., Lovendahl, P., Heritability estimates for enteric methane emissions from Holstein cattle measured using noninvasive methods. J. Dairy Sci. 99 (2016), 1959–1967 26805978.
Lassen, J., Lovendahl, P., Madsen, J., Accuracy of noninvasive breath methane measurements using Fourier transform infrared methods on individual cows. J. Dairy Sci. 95 (2012), 890–898 22281353.
Legarra, A., Aguilar, I., Misztal, I., A relationship matrix including full pedigree and genomic information. J. Dairy Sci. 92 (2009), 4656–4663 19700729.
Leip, A., Weiss, F., Wassenaar, T., Perez, I., Fellmann, T., Loudjani, P., Tubiello, F., Grandgirard, D., Monni, S., Biala, K., Evaluation of the livestock sector's contribution to the EU greenhouse gas emissions (GGELS)—final report. Accessed Oct. 29, 2016. http://ec.europa.eu/agriculture/analysis/external/livestock-gas/full_text_en.pdf, 2010.
Li, R.W., Connor, E.E., Li, C.J., Baldwin, R.L., Sparks, M.E., Characterization of the rumen microbiota of pre-ruminant calves using metagenomic tools. Environ. Microbiol. 14 (2012), 129–139 21906219.
Li, Y., Abecasis, G.R., Mach 1.0: rapid haplotype reconstruction and missing genotype inference. Am. J. Hum. Genet., 79, 2006, 2290.
Lund, M.S., de Roos, A.P.W., de Vries, A.G., Druet, T., Ducrocq, V., Fritz, S., Guillaume, F., Guldbrandtsen, B., Liu, Z.T., Reents, R., Schrooten, C., Seefried, F., Su, G.S., A common reference population from four European Holstein populations increases reliability of genomic predictions. Genet. Sel. Evol., 43, 2011, 43 22152008.
Lund, M. S., A. P. W. de Roos, A. G. de Vries, T. Druet, V. Ducroq, S. Fritz, F. Guillaume, B. Guldbrandtsen, Z. Liu, R. Reents, C. Schrooten, M. Seefried, and G. Su. 2010. Improving genomic prediction by EuroGenomics collaboration. In Proc. 9th World Congress on Genetics Applied to Livestock Production, Leipzig, Germany.
Madsen, J., Bjerg, B.S., Hvelplund, T., Weisbjerg, M.R., Lund, P., Methane and carbon dioxide ratio in excreted air for quantification of the methane production from ruminants. Livest. Sci. 129 (2010), 223–227.
Manzanilla Pech, C.I.V., De Haas, Y., Hayes, B.J., Veerkamp, R.F., Khansefid, M., Donoghue, K.A., Arthur, P.F., Pryce, J.E., Genome-wide association study of methane emissions in Angus beef cattle with validation in dairy cattle. J. Anim. Sci. 94 (2016), 4151–4166.
Martin, C., Morgavi, D.P., Doreau, M., Methane mitigation in ruminants: From microbe to the farm scale. Animal 4 (2010), 351–365 22443940.
Martin, C., Rouel, J., Jouany, J.P., Doreau, M., Chilliard, Y., Methane output and diet digestibility in response to feeding dairy cows crude linseed, extruded linseed, or linseed oil. J. Anim. Sci. 86 (2008), 2642–2650 18469051.
McAllister, T.A., Okine, E.K., Mathison, G.W., Cheng, K.J., Dietary, environmental and microbiological aspects of methane production in ruminants. Can. J. Anim. Sci. 76 (1996), 231–243.
McCauley, E.H., Dziuk, H.E., Correlation of motility and gas collection from goat rumen. Am. J. Physiol., 209, 1965, 1152 5846916.
Meuwissen, T.H., Hayes, B., Goddard, M., Prediction of total genetic value using genome-wide dense marker maps. Genetics 157 (2001), 1819–1829 11290733.
Mohammed, R., McGinn, S.M., Beauchemin, K.A., Prediction of enteric methane output from milk fatty acid concentrations and rumen fermentation parameters in dairy cows fed sunflower, flax, or canola seeds. J. Dairy Sci. 94 (2011), 6057–6068 22118093.
Moss, A.R., Jouany, J.P., Newbold, J., Methane production by ruminants: Its contribution to global warming. Ann. Zootech. 49 (2000), 231–253.
Mulder, H.A., Calus, M.P.L., Druet, T., Schrooten, C., Imputation of genotypes with low-density chips and its effect on reliability of direct genomic values in Dutch Holstein cattle. J. Dairy Sci. 95 (2012), 876–889 22281352.
Munger, A., Kreuzer, M., Absence of persistent methane emission differences in three breeds of dairy cows. Aust. J. Exp. Agric. 48 (2008), 77–82.
Murray, R.M., Bryant, A.M., Leng, R.A., Rates of production of methane in rumen and large-intestine of sheep. Br. J. Nutr. 36 (1976), 1–14 949464.
Negussie, E., Liinamo, A.-E., Mantysaari, P., Mantysaari, E., Lidauer, M., Between and within-individual variation in methanee output measurements in dairy cows. Proc, 2012, European Association of Animal Production, Bratislava, Slovakia, 170.
Nielsen, H.M., Amer, P.R., An approach to derive economic weights in breeding objectives using partial profile choice experiments. Animal 1 (2007), 1254–1262 22444881.
Nkrumah, J.D., Okine, E.K., Mathison, G.W., Schmid, K., Li, C., Basarab, J.A., Price, M.A., Wang, Z., Moore, S.S., Relationships of feedlot feed efficiency, performance, and feeding behavior with metabolic rate, methane production, and energy partitioning in beef cattle. J. Anim. Sci. 84 (2006), 145–153 16361501.
Pickering, N.K., Oddy, V.H., Basarab, J.A., Cammack, K., Hayes, B.J., Hegarty, R.S., McEwan, J.C., Miller, S., Pinares, C., De Haas, Y., Invited review: Genetic possibilities to reduce enteric methane emissions from ruminants. Animal 9 (2015), 1431–1440 http://dx.doi.org/10.1017/S1751731115000968 26055577.
Pimentel, E.C., Wensch-Dorendorf, M., Konig, S., Swalve, H., Enlarging a training set for genomic selection by imputation of un-genotyped animals in populations of varying genetic architecture. Genet. Sel. Evol., 45, 2013, 12 23621897.
Pinares-Patiño, C.S., Hickey, S.M., Young, E.A., Dodds, K.G., MacLean, S., Molano, G., Sandoval, E., Kjestrup, H., Harland, R., Hunt, C., Pickering, N.K., McEwan, J.C., Heritability estimates of methane emissions from sheep. Animal 7 (2013), 316–321 23739473.
Pryce, J.E., Johnston, J., Hayes, B.J., Sahana, G., Weigel, K.A., McParland, S., Spurlock, D., Krattenmacher, N., Spelman, R.J., Wall, E., Calus, M.P.L., Imputation of genotypes from low density (50,000 markers) to high density (700,000 markers) of cows from research herds in Europe, North America, and Australasia using 2 reference populations. J. Dairy Sci. 97 (2014), 1799–1811 24472132.
Pszczola, M., Optimizing Genomic Selection for Scarcely Recorded Traits, 2013, Wageningen UR, Wageningen, Netherlands.
Pszczola, M., Mulder, H.A., Calus, M.P.L., Effect of enlarging the reference population with (un)genotyped animals on the accuracy of genomic selection in dairy cattle. J. Dairy Sci. 94 (2011), 431–441 21183054.
Pszczola, M., Strabel, T., Mulder, H.A., Calus, M.P.L., Reliability of genomic selection for animals with different relationships within and to the reference population. J. Dairy Sci. 95 (2012), 389–400 22192218.
Pszczola, M., Veerkamp, R.F., de Haas, Y., Wall, E., Strabel, T., Calus, M.P.L., Effect of predictor traits on accuracy of genomic breeding values for feed intake based on a limited cow reference population. Animal 7 (2013), 1759–1768 23915541.
Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K.S., Manichan, C., Nielsen, T., Pons, N., Levenez, F., Yamada, T., Mende, D.R., Li, J., Xu, J., Li, S., Li, D., Cao, J., Wang, B., Liang, H., Zheng, H., Xie, Y., Tap, J., Lepage, P., Bertalan, M., Batto, J.M., Hansen, T., le Paslier, D., Linneberg, A., Nielsen, H.B., Pelletier, E., Renault, P., Sicheritz-Ponten, T., Turner, K., Zhu, H., Yu, C., Li, S., Jian, M., Yan, Z., Li, Y., Zhang, X., Li, S., Qin, N., Yang, H., Wang, J., Brunak, S., Doré, J., Guarner, F., Kristiansen, K., Pedersen, O., Parkhill, J., Weissenbach, J., MetaHIT Consortium, Bork, P., Ehrlich, S.D., Wang, J., A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464 (2010), 59–65 20203603.
Robertson, L.J., Waghorn, G.C., Dairy industry perspectives on methane emissions and production from cattle fed pasture or total mixed rations in New Zealand. Pages 213–218 in Proc. New Zealand Soc. Animal Production, Palmerston North, New Zealand. http://www.nzsap.org/view/biblio/volume/62, 2002.
Robinson, D. L., J. P. Goopy, R. S. Hegarty, and P. Vercoe. 2010. Repeatability, animal and sire variation in 1-hr methane emissions and relationships with rumen volatile fatty acid concentrations. Page 712 in 9th World Congress on Genetics Applied to Livestock Production. Leipzig, Germany.
Rutten, M.J.M., Bovenhuis, H., Hettinga, K.A., van Valenberg, H.J.F., van Arendonk, J.A.M., Predicting bovine milk fat composition using infrared spectroscopy based on milk samples collected in winter and summer. J. Dairy Sci. 92 (2009), 6202–6209 19923625.
Sahana, G., Mailund, T., Lund, M.S., Guldbrandtsen, B., Local genealogies in a linear mixed model for genome-wide association mapping in complex pedigreed populations. PLoS One, 6, 2011, e27061 22073255.
Schäff, C., Borner, S., Hacke, S., Kautzsch, U., Albrecht, D., Hammon, H.M., Rontgen, M., Kuhla, B., Increased anaplerosis, TCA cycling, and oxidative phosphorylation in the liver of dairy cows with intensive body fat mobilization during early lactation. J. Proteome Res. 11 (2012), 5503–5514 23046364.
Scheet, P., Stephens, M., A fast and flexible statistical model for large-scale population genotype data: Applications to inferring missing genotypes and haplotypic phase. Am. J. Hum. Genet. 78 (2006), 629–644 16532393.
Soyeurt, H., Dardenne, P., Dehareng, F., Lognay, G., Veselko, D., Marlier, M., Bertozzi, C., Mayeres, P., Gengler, N., Estimating fatty acid content in cow milk using mid-infrared spectrometry. J. Dairy Sci. 89 (2006), 3690–3695 16899705.
Soyeurt, H., Dehareng, F., Gengler, N., McParland, S., Wall, E., Berry, D.P., Coffey, M., Dardenne, P., Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries. J. Dairy Sci. 94 (2011), 1657–1667 21426953.
Steinfeld, H., Gerber, P., Wassenaar, T., Castel, V., Rosales, M., de Haan, C., Livestock's Long Shadow: Environmental Issues and Options, 2006, Food and Agriculture Organization of the United Nations, Rome, Italy.
van Engelen, S., Bovenhuis, H., Dijkstra, J., van Arendonk, J.A.M., Visker, M., Short communication: Genetic study of methane production predicted from milk fat composition in dairy cows. J. Dairy Sci. 98 (2015), 8223–8226 26364110.
Van Grevenhof, E.M., Van Arendonk, J., Bijma, P., Response to genomic selection: The Bulmer effect and the potential of genomic selection when the number of phenotypic records is limiting. Genet. Sel. Evol., 44, 2012, 26 22862849.
van Lingen, H.J., Crompton, L.A., Hendriks, W.H., Reynolds, C.K., Dijkstra, J., Meta-analysis of relationships between enteric methane yield and milk fatty acid profile in dairy cattle. J. Dairy Sci. 97 (2014), 7115–7132 25218750.
van Middelaar, C.E., Berentsen, P.B.M., Dijkstra, J., van Arendonk, J.A.M., de Boer, I.J.M., Methods to determine the relative value of genetic traits in dairy cows to reduce greenhouse gas emissions along the chain. J. Dairy Sci. 97 (2014), 5191–5205 24881792.
Vanlierde, A., Dehareng, F., Froidmont, E., Dardenne, P., Kandel, P.B., Gengler, N., Deighton, M.H., Buckley, F., Lewis, E., McParland, S., Berry, D.P., Soyeurt, H., Prediction of the individual enteric methane emission of dairy cows from milk-mid-infrared spectra. Adv. Anim. Biosci., 4, 2013, 433.
Vanlierde, A., Vanrobays, M.L., Dehareng, F., Froidmont, E., Soyeurt, H., McParland, S., Lewis, E., Deighton, M.H., Grandl, F., Kreuzer, M., Gredler, B., Dardenne, P., Gengler, N., Hot topic: Innovative lactation-stage-dependent prediction of methane emissions from milk mid-infrared spectra. J. Dairy Sci. 98 (2015), 5740–5747 26026761.
Vanrobays, M.-L., Kandel, P.B., Soyeurt, H., Vanlierde, A., Dehareng, F., Froidmont, E., Gengler, N., Phenotypic and genetic variability of methane emissions and milk fatty acid contents of Walloon Holstein dairy cattle. Page 33 in Proc. 19th Natl. Symposium on Applied Biological Sciences, Gembloux, Belgium. http://www.events.gembloux.ulg.ac.be/nsabs2014/, 2013.
von Rohr, P., Hofer, A., Kunzi, N., Economic values for meat quality traits in pigs. J. Anim. Sci. 77 (1999), 2633–2640 10521022.
Waghorn, G.C., Reid, C.S.W., Rumen motility in sheep and cattle given different diets. N. Z. J. Agric. Res. 26 (1983), 289–295.
Wall, E. 2010. Broadening breeding goals in a changing world. In World Conf. Genet. Applied Livest. Prod., Leipzig, Germany.
Wall, E., Coffey, M.P., Amer, P.R., A theoretical framework for deriving direct economic values for body tissue mobilization traits in dairy cattle. J. Dairy Sci. 91 (2008), 343–353 18096957.
Wall, E., Coffey, M.P., Pollott, G.E., The effect of lactation length on greenhouse gas emissions from the national dairy herd. Animal 6 (2012), 1857–1867 23031357.
Wall, E., Simm, G., Moran, D., Developing breeding schemes to assist mitigation of greenhouse gas emissions. Animal 4 (2010), 366–376 22443941.
Weimer, P.J., Stevenson, D.M., Mantovani, H.C., Man, S.L.C., Host specificity of the ruminal bacterial community in the dairy cow following near-total exchange of ruminal contents. J. Dairy Sci. 93 (2010), 5902–5912 21094763.
Wientjes, Y.C.J., Veerkamp, R.F., Calus, M.P.L., The effect of linkage disequilibrium and family relationships on the reliability of genomic prediction. Genetics 193 (2013), 621–631 23267052.
Wolc, A., Arango, J., Settar, P., Fulton, J.E., O'Sullivan, N.P., Preisinger, R., Habier, D., Fernando, R., Garrick, D.J., Dekkers, J.C.M., Persistence of accuracy of genomic estimated breeding values over generations in layer chickens. Genet. Sel. Evol., 43, 2011, 23 21693035.
Wright, A.D.G., Klieve, A.V., Does the complexity of the rumen microbial ecology preclude methane mitigation?. Anim. Feed Sci. Technol. 166–67 (2011), 248–253.
Yin, T., Pinent, T., Brugemann, K., Simianer, H., Konig, S., Simulation, prediction, and genetic analyses of daily methane emissions in dairy cattle. J. Dairy Sci. 98 (2015), 5748–5762 26026753.
Yu, J., Pressoir, G., Briggs, W.H., Bi, I.V., Yamasaki, M., Doebley, J.F., McMullen, M.D., Gaut, B.S., Nielsen, D.M., Holland, J.B., Kresovich, S., Buckler, E.S., A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet. 38 (2006), 203–208 16380716.
Zebeli, Q., Aschenbach, J.R., Tafaj, M., Boguhn, J., Ametaj, B.N., Drochner, W., Invited review: Role of physically effective fiber and estimation of dietary fiber adequacy in high-producing dairy cattle. J. Dairy Sci. 95 (2012), 1041–1056 22365188.
