doi: 10.15389/agrobiology.2022.6.1055eng
UDC: 636.2.033:577.21:57.087
Acknowledgements:
Supported financially from the Ministry of Science and Higher Education of the Russian Federation, the State Order topic registration No. FGGN-2022-0011
BEEF CATTLE EVALUATION BY FEEDING EFFICIENCY AND GROWTH ENERGY INDICATORS BASED ON BIOINFORMATIC AND GENOMIC TECHNOLOGIES (review)
A.A. Belous✉, A.A. Sermyagin, N.A. Zinovieva
Ernst Federal Research Center for Animal Husbandry, 60, pos. Dubrovitsy, Podolsk District, Moscow Province, 142132 Russia, e-mail belousa663@gmail.com (✉ corresponding author), alex_sermyagin85@mail.ru, n_zinovieva@mail.ru
ORCID:
Belous A.A. orcid.org/0000-0001-7533-4281
Zinovieva N.A. orcid.org/0000-0003-4017-6863
Sermyagin A.A. orcid.org/0000-0002-1799-6014
Received October 10, 2022
Beef cattle breeding is characterized by significantly higher feed costs per unit of output compared to other livestock industries. For most species of farm animals, breeding to improve the efficiency of feed use has been difficult until recently due to the complexity of the individual assessment of this indicator. The improvement of the trait occurred indirectly, through selection for an increase in the intensity of growth and a decrease in the fat content in carcasses. In 1960-1980, Förster-Technik GmbH (Germany) developed automatic feeding stations for individual fattening to account for data on energy costs for the growth and development of animals, which made it possible to derive the feed conversion rate (FCR), which remains one of the main parameters of feed efficiency (K.R. Koots et al., 1994). FCR as a trait is not important for genetic selection due to moderate heritability (A.A. Sermyagin et al., 2020; D.N. Crews et al., 2005). In this regard, and thanks to data from feedlots, in 1963 a new alternative concept for the FCR indicator, the predicted residual feed intake (RFI), was developed. RFI is an individual characteristic of an animal, which is determined by the results of test fattening (duration from 70 to 84 days), taking into account daily feed intake and live weight gain (R.M. Koch et al., 1963). The advantage of using RFI as a measure of feed efficiency in conjunction with FCR is that selection for a negative RFI will allow for reduced feed intake without compromising growth. In addition, the predicted residual feed intake does not depend on productivity, growth and body size, making it a trait that has a clear breeding value (G. Acetoze et al., 2015; J.A. Archer et al., 2000; G.E. Carstens et al., 2002). It has been established that RFI correlates with FCR (genetic correlation coefficients vary from 0.45 to 0.85), but RFI does not depend on average daily gain (ADG) and metabolic body weight (MWT) (B.W. Kennedy et al., 1993; P.F. Artur et al., 2001). The assertion that individuals of the same body weight require different amounts of feed to achieve the same performance provides the scientific basis for assessing RFI in beef cattle. Due to the fact that RFI is hereditarily determined (heritability coefficients vary from 0.08 to 0.49), a directed search for quantitative trait loci (QTL) is conducted using the GWAS (genome-wide association study) methodology. Since the 2000s, methods have been developed and implemented for assessing the breeding value of farm animals using information on a large number of SNPs (single nucleotide polymorphism), based on the principle of linear modeling. Linear models, depending on the approach to data structuring, are divided into rrBLUP (estimation of the effect of each marker), GBLUP (estimation of breeding value based on genomic relationship), and one of the most common modern one-step estimation method ssGBLUP (genomic breeding value estimation model that takes into account genomic relationship along with pedigree). BayesA and BayesB are applicable non-linear Bayesian models. Scientific studies using genome-wide association analysis have allowed the development of genomic selection programs and the identification of a number of SNPs associated with indicators of feed efficiency. Thus, seven positional candidate genes were found which were previously associated with the efficiency of feed use and growth energy in different types of farm animals, and were recently identified in Angus cattle. The analysis of foreign studies allows us to recommend the use of the described methods both in research work and for production purposes with the prospect of including these parameters in the criteria for genomic evaluation of beef cattle of different breeds bred in Russia.
Keywords: feeding efficiency, feed conversion, predicted residual feed intake, genomic technologies, genome-wide association search, GWAS, beef cattle, pig breeding.
REFERENCES
- Lowe M., Gereffi G. A value chain analysis of the U.S. beef and dairy industries. Center on Globalization, Governance & Competitiveness, Duke University, Duke, NC, USA, 2009 CrossRef
- Archer J.A., Richardson E.C., Herd R.M., Arthur P.F. Potential for selection to improve efficiency of feed use in beef cattle: a review. Australian Journal of Agricultural Research, 1999, 50(2): 147-162 CrossRef
- Taylor J., Kerley M., Schnabel R., Pomp D., Garrick D., Hansen S., Loy D., Tait J. R., Weaber R., Seabury C., Beever J., Faulkner D., Shike D., Fahrenkrug S., Spangler M., Sonstegard T., Freetly H., Pollak J., Johnson K., Neibergs H. National program for the genetic improvement of feed efficiency in beef cattle. Faculty Papers and Publications in Animal Science, 2016: 907.
- Sermyagin A.A., Belous A.A., Trebunskikh E.A., Zinov’eva N.A. Feeding behavior as the new breeding traits in pigs. Sel'skokhozyaistvennaya biologiya [Agricultural Biology], 2020, 55(6): 1126-1138 CrossRef
- Oberschätzl-Kopp R., Peis R., Haidn B., Reiter K. Studies on dairy cow behaviour with automatic feeding in a herd milked by an AMS. LandTechnik, 71(2), 2016: 55-65 CrossRef
- Arthur P.F., Archer J.A., Johnston D.J., Herd R.M., Richardson E.C., Parnell P.F. Genetic and phenotypic variance and covariance components for feed intake, feed efficiency and other postweaning traits in Angus cattle. Journal of Animal Science, 2001, 79(11): 2805-2811 CrossRef
- Kennedy B.W., van der Werf J.H., Meuwissen T.H. Genetic and statistical properties of residual feed intake. Journal of Animal Science, 1993, 71(12): 3239-3250 CrossRef
- Deutscher G.H. Reducing calving difficulty by heifer and sire selection and management. Proc. The Range Beef Cow Symposium XIV. Gering, Nebraska, 1995: 183.
- Strohbehn D., Bryce S., Maxwell D., Anderson L., Wilson D. Influence of Angus sire birth weight EPD on performance of crossbred first-calf heifers: a progress report. In: Iowa State Beef Research Report. Iowa, 1993: 54-60.
- Nielsen M.K., MacNeil M.D., Dekkers J.C.M., Crews D.H., Rathje T.A., Enns R.M., Weaber R.L. Review: Life-cycle, total-industry genetic improvement of feed efficiency in beef cattle: Blueprint for the Beef Improvement Federation. Professional Animal Scientist, 2013, 29: 559-565 CrossRef
- Berry D.P., Crowley J.J. Cell biology symposium: genetics of feed efficiency in dairy and beef cattle. Journal of Animal Science, 2013, 91(4): 1594-1613 CrossRef
- Koots K.R., Gibson J.P., Wilton J.W. Analyses of published genetic parameter estimates for beef production traits. 2. Phenotypic and genetic correlations. Animal Breeding Abstracts, 1994, 62(11): 825-853.
- Crews D.H.Jr. Genetics of efficient feed utilization and national cattle evaluation: a review. Genet. Mol. Res., 2005, 4(2): 152-165.
- Koch R.M., Swiger L.A., Chambers D., Gregory K.E. Efficiency of feed use in beef cattle. Journal of Animal Science, 1963, 22(2): 486-494 CrossRef
- Savietto D. Berry D.P. Friggens N.C. Towards an improved estimation of the biological components of residual feed intake in growing cattle. Journal of Animal Science, 2014, 92(2): 467-476 CrossRef
- Archer J.A., Arthur P.F., Herd R.M., Richardson E.C. Genetic variation in feed efficiency and its component traits. Proc. 6th World Congress on Genetics Applied to Livestock Production. Armidale, NSW, Australia, 25: 81-84.
- Herd R.M., Bishop S.C. Genetic variation in residual feed intake and its association with other production traits in British Hereford cattle. Livestock Production Science, 2000, 63(2): 111-119 CrossRef
- Acetoze G., Weber K.L., Ramsey J.J., Rossow H.A. Relationship between liver mitochondrial respiration and proton leak in low and high RFI steers from two lineages of RFI Angus bulls. International Scholarly Research Notices, 2015: 194014 CrossRef
- Archer J.A., Bergh L. Duration of performance tests for growth rate, feed intake and feed efficiency in four biological types of beef cattle. Livestock Production Science, 2000, 65(1-2): 47-55 CrossRef
- Carstens G.E., Theis C.M., White M.B., Welsh T.H., Warrington B.G., Randel R.D., Forbes T.D.A., Lippke H., Greene L.W., Lunt D.K. Residual feed intake in beef steers: I. Correlation with performance traits and ultrasound measures of body composition. Proc. Western Section, American Society of Animal Science, 2002, 53: 552-555.
- Herd R.M., Arthur P.F. Physiological basis for variation in residual feed intake. Journal of Animal Science, 2009, 87(suppl_14): E64-E71 CrossRef
- Montanholi Y., Fontoura A., Swanson K., Coomber B., Yamashiro S., Miller S. Small intestine histomorphometry of beef cattle with divergent feed efficiency. Acta Veterinaria Scandinavica, 2013, 55(1): 9 CrossRef
- Lancaster P.A., Carstens G.E., Michal J.J., Brennan K.M., Johnson K.A., Davis M.E. Relationships between residual feed intake and hepatic mitochondrial function in growing beef cattle. Journal of Animal Science, 2014, 92(7): 3134-3141 CrossRef
- Perkins S.D., Key C.N., Garrett C.F., Foradori C.D., Bratcher C.L., Kriese-Anderson L.A., Brandebourg T.D. Residual feed intake studies in Angus-sired cattle reveal a potential role for hypothalamic gene expression in regulating feed efficiency. Journal of Animal Science, 2014, 92(2): 549-560 CrossRef
- Basarab J.A., McCartney D., Okine E.K., Baron V.S. Relationships between progeny residual feed intake and dam productivity traits. Canadian Journal of Animal Science, 2007, 87(4): 489-502 CrossRef
- Gilbert H., Billon Y., Brossard L., Faure J., Gatellier P., Gondret F., Labussière E., Lebret B., Lefaucheur L., Le Floch N., Louveau I., Merlot E., Meunier-Salaün M.-C., Montagne L., Mormede P., Renaudeau D., Riquet J., Rogel-Gaillard C., van Milgen J., Vincent A., Noblet J. Review: divergent selection for residual feed intake in the growing pig. Animal, 2017, 11(9): 1427-1439 CrossRef
- Fu L., Jiang Y., Wang C., Mei M., Zhou Z., Jiang Y., Song H., Ding X.A Genome-wide association study on feed efficiency related traits in landrace pigs. Front. Genet., 2020, 11: 692 CrossRef
- Liu M.F., Goonewardene L.A., Bailey D.R.C., Basarab J.A., Kemp R.A., Arthur P.F., Okine E.K., Makarechian M. A study on the variation of feed efficiency in station tested beef bulls. Canadian Journal of Animal Science, 2000, 80(3): 435-441 CrossRef
- Crowley J.J., McGee M., Kenny D.A., Crews D.H., Evans R.D., Berry D.P. Phenotypic and genetic parameters for different measures of feed efficiency in different breeds of Irish performance tested beef bulls. Journal of Animal Science, 2010, 88(3): 885-894 CrossRef
- Lu D., Miller S., Sargolzaei M., Kelly M., Vander Voort G., Caldwell T., Wang Z., Plastow G., Moore S. Genome-wide association analyses for growth and feed efficiency traits in beef cattle. Journal of Animal Science, 2013, 91(8): 3612-3633 CrossRef
- Saatchi M., Beever J.E., Decker J.E., Faulkner D.B., Freetly H.C., Hansen S.L., Helen Y., Kristen A.J., Stephen D.K., Monty S.K., JaeWoo K., Daniel D.L., Elisa M., Holly L.N., Pollak E.J., Shnabel R.D., Seabury C.M., Shike D.W., Snelling W.M., Spangler M.L., Weaber R.L., Garrick D.J., Taylor J.F. QTLs associated with dry matter intake, metabolic mid-test weight, growth and feed efficiency have little overlap across 4 beef cattle studies. BMC Genomics, 2014, 15: 1004 CrossRef
- Schenkel F.S., Miller S.P., Wilton J.W. Genetic parameters and breed differences for feed efficiency, growth, and body composition traits of young beef bulls. Canadian Journal of Animal Science, 2004, 84(2): 177-185 CrossRef
- Robinsonab D.L., Oddy V.H. Genetic parameters for feed efficiency, fatness, muscle area and feeding behaviour of feedlot finished beef cattle. Livestock Production Science, 2004, 90(2-3): 255-270 CrossRef
- Hoque M.A., Arthur P.F., Hiramoto K., Oikawa T. Genetic parameters for carcass traits of field progeny and their relationships with feed efficiency traits of their sire population for Japanese Black (Wagyu) cattle. Livestock Science, 2006, 100(2-3): 251-260 CrossRef
- Hoque M.A., Arthur P.F., Hiramoto K., Oikawa T. Genetic relationship between different measures of feed efficiency and its component traits in Japanese Black (Wagyu) bulls. Livestock Science, 2006, 99(2-3): 111-118 CrossRef
- Baker S.D., Szasz J.I., Klein T.A., Kuber P.S., Hunt C.W., Glaze J.B., Falk D., Richard J., Miller C., Battaglia R.A., Hill R.A. Residual feed intake of purebred Angus steers: Effects on meat quality and palatability. Journal of Animal Science, 2006, 84(4): 938-945 CrossRef
- Nkrumah J.D., Sherman E.L., Li C., Marques E., Crews Jr. D.H., Bartusiak R., Brenda M.M., Wang Z., Basarab J.A., Moore S.S. Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake and feed efficiency of beef cattle. Journal of Animal Science, 2007, 85(12): 3170-3181 CrossRef
- Van Der Westhuizen R.R., Westhuizen J., Schoeman S.J. Genetic variance components for residual feed intake and feed conversion ratio and their correlations with other production traits in beef bulls. South African Journal of Animal Science, 2004, 34(4): 257-264.
- Almeida R. Consumo e eficiência alimentar de bovinos em crescimento Tese (Doutorado). Piracicaba-SP, Piracicaba, 2005: 181 CrossRef
- Geldermann H. Investigations on inheritance of quantitative characters in animals by gene markers. I. Methods. Theoretical and Applied Genetics, 1975, 46: 319-330 CrossRef
- Hayes B., Goddard M.E. The distribution of the effects of genes affecting quantitative traits in livestock. Genet. Sel. Evol., 2008, 33: 209-229 CrossRef
- Meuwissen T.H.E., Hayes B.J., Goddard M.E. Prediction of total genetic value using genome-wide dense marker maps. Genetics, 2001, 157(4): 1819-1829 CrossRef
- Goddard M.E., Hayes B.J. Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Reviews Genetics, 2009, 10: 381-391 CrossRef
- Sermyagin A.A., Gladyr’ E.A., Kharitonov S.N., Ermilov A.N., Strekozov N.I., Brem G., Zinovieva N.A. Genome-wide association study for milk production and reproduction traits in Russian holstein cattle population. Agricultural Biology, 2016, 51(2): 182-193 CrossRef
- Van Eenennaam A.L., van der Werf J.H.J., Goddard M.E. The value of using DNA markers for beef bull selection in the seedstock sector. Journal of Animal Science, 2011, 89(2): 307-320 CrossRef
- Do D.N., Strathe A.B., Ostersen T., Pant S.D., Kadarmideen H.N. Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake. Front. Genet., 2014, 5: 307 CrossRef
- Sherman E.L., Nkrumah J.D., Li C., Bartusiak R., Murdoch B., Moore S.S. Fine mapping quantitative trait loci for feed intake and feed efficiency in beef cattle. Journal of Animal Science, 2009, 87(1): 37-45 CrossRef
- Chander D., Sharma V.K., Dudi K., Baban B.N., Sharma S.Ph., Negesse T., Kundu S.S., Dutta M.M., Gupta R., Singh D. Residual feed intake as a tool for selecting more efficient animals: a review. Indian Journal of Animal Nutrition, 2017, 34(3): 238-255 CrossRef
- Higgins M.G., Fitzsimons C., McClure M.C., McKenna C., Conroy S., Kenny D.A., McGee M., Waters S.M., Morris D.W. GWAS and eQTL analysis identifies a SNP associated with both residual feed intake and GFRA2 expression in beef cattle. Sci. Rep., 2018, 8: 14301 CrossRef
- Moore S.S., Mujibi F.D., Sherman E.L. Molecular basis for residual feed intake in beef. Journal of Animal Science,2009, 87(suppl_14) CrossRef
- Hu Z.-L., Park C.A., Reecy J.M. Bringing the animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services. Nucleic Acids Research, 2022, 50(D1): D956-D961 CrossRef
- Hu Z.-L., Park C.A., Reecy J.M. Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB. Nucleic Acids Research, 2019, 47(D1): D701-D710 CrossRef
- Hu Z.-L., Park C.A., Reecy J.M. Development of animal QTLdb and CorrDB: resynthesizing big data to improve meta-analysis of genetic and genomic information. The 11th World Congress on Genetics Applied to Livestock Production (WCGALP). New Zealand, 2018: 954.
- Serão N.V., González-Peña D., Beever J.E., Faulkner D.B., Southey B.R., Rodriguez-Zas S.L. Single nucleotide polymorphisms and haplotypes associated with feed efficiency in beef cattle. BMC Genet., 2013, 14: 94 CrossRef
- Snelling W.M., Allan M.F., Keele J.W., Kuehn L.A., McDaneld T., Smith T.P.L., Sonstegard T.S., Thallman R.M., Bennett G.L. Genome-wide association study of growth in crossbred beef cattle. Journal of Animal Science, 2010, 88(3): 837-848 CrossRef
- Bolormaa S., Pryce J.E., Kemper K., Savin K., Hayes B.J., Barendse W., Zhang Y., Reich C.M., Mason B.A., Bunch R.J., Harrison B.E., Reverter A., Herd R.M., Tier B., Graser H.U., Goddard M.E. Accuracy of prediction of genomic breeding values for residual feed intake and carcass and meat quality traits in Bos taurus, Bos indicus, and composite beef cattle. Journal of Animal Science, 2013, 91(7): 3088-3104 CrossRef
- Barendse W., Reverter A., Bunch R.J., Harrison B.E., Barris W., Thomas M.B. A validated whole-genome association study of efficient food conversion in cattle. Genetics, 2007, 176(3): 1893-1905 CrossRef
- Sherman E.L., Nkrumah J.D., Moore S.S. Whole genome single nucleotide polymorphism associations with feed intake and feed efficiency in beef cattle. Journal of Animal Science, 2010, 88(1): 16-22 CrossRef
- Seabury C.M., Oldeschulte D.L., Saatchi M., Beever J.E., Decker J.E., Halley Y.A., Bhattarai E.K., Molaei M., Freetly H.C., Hansen S.L., Yampara-Iquise H., Johnson K.A., Kerley M.S., Kim J., Loy D.D., Marques E., Neibergs H.L., Schnabel R.D., Shike D.W., Spangler M.L., Weaber R.L., Garrick D.J., Taylor J.F. Genome-wide association study for feed efficiency and growth traits in U.S. beef cattle. BMC Genomics, 2017, 18: 386 CrossRef
- Matukumalli L.K., Lawley C.T., Schnabel R.D., Taylor J.F., Allan M.F., Heaton M.P., O'Connell J., Moore S.S., Smith T.P.L., Sonstegard T.S., Van Tassell C.P. Development and characterization of a high-density SNP genotyping assay for cattle. PLoS ONE, 2009, 4(4): e5350 CrossRef
- Rincon G., Weber K.L., Van Eenennaam A.L., Golden B.L., Medrano J.F. Hot topic: performance of bovine high-density genotyping platforms in Holsteins and Jerseys. J. Dairy Sci., 2011, 94(12): 6116-6121 CrossRef
- Santana M.H.A., Utsunomiya Y.T., Neves H.H., Gomes R.C., Garcia J.F., Fukumasu H., Silva S.L., Junior G.A.O., Alexandre P.A., Leme P.R., Brassaloti R.A., Coutinho L.L., Lopes T.G., Meirelles F.V., Eler J.P., Ferraz J.B.S. Genome-wide association analysis of feed intake and residual feed intake in Nellore cattle. BMC Genet., 2014, 15: 21 CrossRef
- Connor E.E., Kahl S., Elsasser T.H., Parker J.S., Li R.W., Van Tassell C.P., Baldwin VI R.L., Barao S.M. Enhanced mitochondrial complex gene function and reduced liver size may mediate improved feed efficiency of beef cattle during compensatory growth. Functional & Integrative Genomics, 2010, 10: 39-51 CrossRef
- Ribeiro R., Monteiro C., Catalán V., Hu P., Cunha V., Rodríguez A., Gomez-Ambrosi J., Fraga A., Principe P., Lobato C., Lobo F., Morais A., Silva V., Sanches-Magalhaes J., Oliveira J., Pina F., Lopes C., Medeiros R., Frühbeck G. Obesity and prostate cancer: gene expression signature of human periprostatic adipose tissue. BMC Med., 2012, 10: 108 CrossRef
- Cabezas A., Costas M.J., Pinto R.M., Couto A., Cameselle J.C. Identification of human and rat FAD-AMP lyase (cyclic FMN forming) as ATP-dependent dihydroxyacetone kinases. Biochemical and Biophysical Research Communications, 2005, 338(4): 1682-1689 CrossRef
- Tang J., Wen Z.G., Guo Z.B., Huang W., Guo Y.M., Xie M., Hou S.S. Dietary riboflavin supplementation improve the growth performance and antioxidant status of starter white Pekin ducks fed a corn-soybean meal diet. Livestock Science, 2014, 170: 131-136 CrossRef
- Kong B.-W., Song J.J., Lee J.Y., Hargis B.M., Wing T., Lassiter K. Gene expression in breast muscle associated with feed efficiency in a single male broiler line using a chicken 44K oligo microarray. I. Top differentially expressed genes. Poultry Science, 2011, 90(11): 2535-2547 CrossRef
- Fontanesi L., Galimberti G., Calò D.G., Fronza R., Martelli P.L., Scotti E., Colombo M., Schiavo G., Casadio R., Buttazzoni L., Russo V. Identification and association analysis of several hundred single nucleotide polymorphisms within candidate genes for back fat thickness in Italian Large White pigs using a selective genotyping approach. Journal of Animal Science, 2012, 90(8): 2450-2464 CrossRef
- Powers H.J., Corfe B.M., Nakano E. Riboflavin in development and cell fate. In: Water soluble vitamins. Subcellular Biochemistry, vol. 56. O. Stanger (ed.). Springer, Dordrecht, 2012: 229-245 CrossRef
- Henriques B.J., Olsen R.K., Bross P., Gomes C.M. Emerging roles for riboflavin in functional rescue of mitochondrial β-oxidation flavoenzymes. Curr. Med. Chem., 2010, 17(32): 3842-3854 CrossRef
- Leung-Pineda V., Huh J., Piwnica-Worms H. DDB1 targets Chk1 to the Cul4 E3 Ligase complex in normal cycling cells and in cells experiencing replication stress. Cancer Research, 2009, 69(6): 2630-2637 CrossRef
- de las Heras-Saldana S., Clark S.A., Duijvesteijn N., Gondro C., van der Werf J.H.J., Chen Y. Combining information from genome-wide association and multi-tissue gene expression studies to elucidate factors underlying genetic variation for residual feed intake in Australian Angus cattle. BMC Genomics, 2019, 20(939) CrossRef
- Comuzzie A.G., Cole S.A., Laston S.L., Voruganti V.S., Haack K., Gibbs R.A., Butte N.F. Novel genetic loci identified for the pathophysiology of childhood obesity in the Hispanic population. PLoS ONE, 2012, 7(12): e51954 CrossRef
- Setoguchi K., Furuta M., Hirano T., Nagao T., Watanabe T., Sugimoto Y., Takasuga A. Cross-breed comparisons identified a critical 591-kb region for bovine carcass weight QTL (CW-2) on chromosome 6 and the Ile-442-met substitution in NCAPG as a positional candidate. BMC Genet., 2009, 10: 43 CrossRef
- Zhang F., Wang Y., Mukiibi R., Chen L., Vinsky M., Plastow G., Basarab J., Stothard P., Li C. Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: I: feed efficiency and component traits. BMC Genomics, 2020, 21: 36 CrossRef