Skip to main content Accessibility help

Invited review: Phenotyping strategies and quantitative-genetic background of resistance, tolerance and resilience associated traits in dairy cattle

  • S. König (a1) and K. May (a1) (a2)


In dairy cattle, resistance, tolerance and resilience refer to the adaptation ability to a broad range of environmental conditions, implying stable performances (e.g. production level, fertility status) independent from disease or infection pressure. All three mechanisms resistance, tolerance and resilience contribute to overall robustness, implying the evaluation of phenotyping and breeding strategies for improved robustness in dairy cattle populations. Classically, breeding approaches on improved robustness rely on simple production traits, in combination with detailed environmental descriptors and enhanced statistical modelling to infer possible genotype by environment interactions. In this regard, innovative environmental descriptors were heat stress indicators, and statistical modelling focussed on random regression or reaction norm methodology. A robust animal has high breeding values over a broad spectra of environmental levels. During the last years, direct health traits were included into selection indices, implying advances in genetic evaluations for traits being linked to resistance or tolerance against infectious and non-infectious diseases. Up to now, genetic evaluation for health traits is primarily based on subjectively measured producer-recorded data, with disease trait heritabilities in a low-to-moderate range. Thus, it is imperative to identify objectively measurable phenotypes as suitable biomarkers. New technologies (e.g. mid-infrared spectrometry) offer possibilities to determine potential biomarkers via laboratory analyses. Novel biomarkers include measurable physiological traits (e.g. serum metabolites, hormone levels) as indicators for a current infection, or the host’s reaction to environmental stressors. The rumen microbiome composition is proposed as a biomarker to detect interactions between host genotype and environmental effects. The understanding of host genetic variation in disease resistance and individual expression of robustness encourages analyses on the underlying immune response (IR) system. Recent advances have been made in order to infer the genetic background of IR traits and cows immunological competence in relation to functional and production traits. Thus, a last aspect of this review addresses the genetic background and current state of genetic control for resistance to economically relevant infectious and non-infectious dairy cattle diseases by considering immune-related factors.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Invited review: Phenotyping strategies and quantitative-genetic background of resistance, tolerance and resilience associated traits in dairy cattle
      Available formats

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Invited review: Phenotyping strategies and quantitative-genetic background of resistance, tolerance and resilience associated traits in dairy cattle
      Available formats

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Invited review: Phenotyping strategies and quantitative-genetic background of resistance, tolerance and resilience associated traits in dairy cattle
      Available formats


Corresponding author


Hide All
Abdel-Azim, GA, Freeman, AE, Kehrli, ME, Kelm, SC, Burton, JL, Kuck, AL and Schnell, S 2005. Genetic basis and risk factors for infectious and non-infectious diseases in US Holsteins. I. Estimation of genetic parameters for single diseases and general health. Journal of Dairy Science 88, 11991207.10.3168/jds.S0022-0302(05)72786-7
Al-Kanaan, A 2016. Heat stress response for physiological traits in dairy and dual purpose cattle populations on phenotypic and genetic scales. PhD thesis, Faculty of Organic Agriculture, University of Kassel, Kassel, Germany.
Bannerman, DD, Springer, HR, Paape, MJ, Kauf, ACW and Goff, JP 2008. Evaluation of breed-dependent differences in the innate immune responses of Holstein and Jersey cows to Staphylococcus aureus intramammary infection. Journal of Dairy Research 75, 291301.10.1017/S0022029908003427
Banos, G, Wall, E, Coffey, MP, Banall, A, Gillespie, S, Russell, GC and McNeilly, TN 2013. Identification of immune traits correlated with dairy cow health, reproduction and productivity. PloS One 8, e65766.10.1371/journal.pone.0065766
Bastin, C, Soyeurt, H and Gengler, N 2013. Genetic parameters of milk production traits and fatty acid contents in milk for Holstein cows in parity 1-3. Journal of Animal Breeding and Genetics 130, 118127.
Biomarkers Definitions Working Group 2001. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clinical Pharmacology & Therapeutics 69, 8995.10.1067/mcp.2001.113989
Bishop, SC 2012. A consideration of resistance and tolerance for ruminant nematode infections. Frontiers in Genetics 3, 168.10.3389/fgene.2012.00168
Boettcher, PJ, Fatehi, J and Schutz, MM 2003. Genotype x environment interactions in conventional versus pasture-based dairies in Canada. Journal of Dairy Science 86, 383389.
Brügemann, K, Gernand, E, von Borstel, UU and König, S 2013. Application of random regression models to infer the genetic background and phenotypic trajectory of binary conception rate by alterations of temperature x humidity indices. Livestock Science 15, 389396.10.1016/j.livsci.2013.08.009
Calus, MPL, Berry, DP, Banos, G, de Haas, Y and Veerkamp, RF 2013. Genomic selection: the option for new robustness traits? Advances in Animal Biosciences 4, 618625.10.1017/S2040470013000186
Calus, MPL and Veerkamp, RF 2003. Estimation of environmental sensitivity of genetic merit for milk production traits using random regression model. Journal of Dairy Science 86, 37563764.10.3168/jds.S0022-0302(03)73982-4
Carabaño, MJ, Ramón, M, Díaz, C, Molina, A, Pérez-Guzmán, MD and Serradilla, JM 2017. Breeding and genetics symposium: breeding for resilience to heat stress effects in dairy ruminants. A comprehensive review. Journal of Animal Science 95, 18131826.
Cardoso, FF and Tempelmann, RJ 2012. Linear reaction norm models for genetic merit prediction of Angus cattle under genotype by environment interaction. Journal of Animal Science 90, 21302141.10.2527/jas.2011-4333
Carlén, E, Strandberg, E and Roth, A 2004. Genetic parameters for clinical mastitis, somatic cell score, and production in the first three lactations of Swedish Holstein cows. Journal of Dairy Science 87, 30623070.10.3168/jds.S0022-0302(04)73439-6
Chagas, LM, Bass, JJ, Blache, D, Burke, CR, Kay, JK, Lindsay, DR, Lucy, MC, Martin, GB, Meier, S, Rhodes, FM, Roche, JR, Thatcher, WW and Webb, R 2007. Invited review: new perspectives on the roles of nutrition and metabolic priorities in the subfertility. Journal of Dairy Science 90, 40224032.10.3168/jds.2006-852
Colditz, IG and Hine, BC 2016. Resilience in farm animals: biology, management, breeding and implications for animal welfare. Animal Production Science 56, 19611983.10.1071/AN15297
Das, R, Sailo, L, Verma, N, Bharti, P, Saikia, J, Imtiwati, P and Kumar, R 2016. Impact of heat stress on health and performance of dairy animals: a review. Veterinary World 9, 260268.10.14202/vetworld.2016.260-268
De Jong, G and Bijma, P 2002. Selection and phenotypic plasticity in evolutionary biology and animal breeding. Livestock Production Science 78, 195214.10.1016/S0301-6226(02)00096-9
Detilleux, JC, Koehler, KJ, Freeman, AE, Kehrli, ME Jr. and Kelley, DH 1994. Immunological parameters of periparturient Holstein cattle: genetic variation. Journal of Dairy Science 77, 26402650.10.3168/jds.S0022-0302(94)77205-2
Egger-Danner, C, Cole, JB, Pryce, JE, Gengler, N, Heringstad, B, Bradley, A and Stock, KF 2015. Invited review: overview of new traits and phenotypin strategies in dairy cattle with a focus on functional traits. Animal 9, 191207.10.1017/S1751731114002614
Farnaud, S and Evans, RW 2003. Lactoferrin – a multifunctional protein with antimicrobial properties. Molecular Immunology 40, 395405.10.1016/S0161-5890(03)00152-4
Fikse, WF, Rekaya, R and Weigel, KA 2003. Assessment of environmental descriptors for studying genotype by environment interaction. Livestock Production Science 82, 223231.10.1016/S0301-6226(03)00009-5
Gause, GF 1947. Problems of evolution. Transactions of the Connecticut Academy of Arts and Sciences 37, 1768.
Grelet, C, Bastin, C, Gelé, M, Davière, JB, Johan, M, Werner, A, Reding, R, Fernandez Pierna, JA, Colinet, FG, Dardenne, P, Gengler, N, Soyeurt, H and Dehareng, F 2016. Development of Fourier transform mid-infrared calibrations to predict acetone, ß-hydroxybutyrate and citrate contents in bovine milk through a European dairy network. Journal of Dairy Science 99, 48164825.10.3168/jds.2015-10477
Haile-Mariam, D, Carrick, MJ and Goddard, ME 2008. Genotype by environment interaction for fertility, survival, and milk production traits in Australian dairy cattle. Journal of Dairy Science 91, 48404853.10.3168/jds.2008-1084
Hammami, H, Vandenplas, J, Vanrobays, ML, Rekik, B, Bastin, C and Gengler, N 2015. Genetic analysis of heat stress effects on yield traits, udder health, and fatty acids of Walloon Holstein cows. Journal of Dairy Science 98, 49564968.10.3168/jds.2014-9148
Heriazon, A, Quinton, M, Miglior, F, Leslie, KE, Sears, W and Mallard, BA 2013. Phenotypic and genetic parameters of antibody and dalyed-type hypersensitivity responses of lactating Holstein cows. Veterinary Immunology and Immunopathology 154, 8392.
Hernandez, A, Quinton, VM, Miglior, F and Mallard, BA 2006. Genetic parameters of dairy cattle immune response traits. In Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Brazil, Book of abstracts, pp. 1518.
Hernandez-Sanabria, E, Goonewardene, LA, Wang, Z, Mi, Z, Moore, SS and Guan, LL 2013. Influence of sire breed on the interplay among rumen microbial populations inhabiting the rumen liquid of the progeny in beef cattle. PloS One 8, e58461.
Jewell, KA, McCormick, CA, Odt, CL, Weimer, PJ and Suen, G 2015. Ruminal bacterial community composition in dairy cows is dynamic over the course of two lactations and correlates with feed efficiency. Applied and Environmental Microbiology 81, 46974710.10.1128/AEM.00720-15
Kelm, SC, Dettilleux, JC, Freeman, AE, Kehrli, ME, Dietz, AB, Fox, LK, Butler, JE, Kasckovics, I and Kelley, DH 1997. Genetic association between parameters of innate immunity and measures of mastitis in periparturient Holstein cattle. Journal of Dairy Science 80, 17671775.10.3168/jds.S0022-0302(97)76110-1
Klein, S, May, K, Scheper, C and König, S 2018. Phänotypische und genomweite Assoziationen für ß-Hydroxybutyrat und Aceton in der Milch als potentielle Indikatoren für Ketose in der Frühlaktation. National Animal Breeding Meeting of the German Society of Animal Science 12th and 13th September, Bonn, Germany, pp. 3738.
Koeck, A, Jamrozik, J, Schenkel, FS, Moore, RK, Lefebvre, DM, Kelton, DF and Miglior, F 2014. Genetic analysis of milk ß-hydroxybutyrate and its association with fat-to-protein ratio, body condition score, clinical ketosis, and displaced abomasums in early first lactation of Canadian Holsteins. Journal of Dairy Science 97, 72867292.10.3168/jds.2014-8405
König, S, Dietl, G, Raeder, I and Swalve, HH 2005. Genetic relationships between dairy performance under large-scale farm and family farm conditions. Journal of Dairy Science 88, 40874096.
Lie, O 1979. Genetic analysis of some immunological traits in young bulls. Acta Veterinaria Scandinavica 20, 372386.
Lin, C, Raskin, L and Stahl, DA 1997. Microbial community structure in gastrointestinal tracts of domestic animals: comparative analyses using rRNA targeted oligonucleotide probes. FEMS Microbiology Ecology 22, 281294.10.1111/j.1574-6941.1997.tb00380.x
Magombedze, G, Reddy, PBJ, Eda, S and Ganusov, VV 2013. Cellular and population plasticity of helper CD4(+) T cell responses. Frontiers in Physiology 4, 206.10.3389/fphys.2013.00206
Martin, P, Barkema, HW, Brito, LF, Narayana, SG and Miglior, F 2018. Symposium review: Novel strategies to genetically improve mastitis resistance in dairy cattle. Journal of Dairy Science 101, 27242736.10.3168/jds.2017-13554
May, K, Brügemann, K, König, S and Strube, C 2018. The impact of patent Fasciola hepatica infections on individual milk production and fertility parameters in dairy cows. In 28th Annual Meeting of the German Society for Parasitology, Berlin, Germany, pp. 176177.
May, K, Brügemann, K, Yin, T, Scheper, C, Strube, C and König, S 2017. Genetic line comparisons and genetic parameters for endoparasite infections and test-day milk production traits. Journal of Dairy Science 100, 73307344.10.3168/jds.2017-12901
Mazengera, KE, Kennedy, BW, Burnside, EB, Wilkie, BN and Burton, JH 1985. Genetic parameters of bovine serum immunoglobulins. Journal of Dairy Science 68, 23092314.10.3168/jds.S0022-0302(85)81104-8
Montaldo, HH, Pelcastre-Cruz, A, Castillo-Juárez, H, Ruiz-López, FJ and Miglior, F 2017. Genotype x environment interaction for fertility and milk yield traits in Canadian, Mexican and US Holstein cattle. Spanish Journal of Agricultural Research 15, e0402.
Morméde, P, Foury, A, Terenina, E and Knap, PW 2011. Breeding for robustness: the role of cortisol. Animal 5, 651657.10.1017/S1751731110002168
Nauta, WJ, Veerkamp, RF, Brascamp, EW and Bovenhuis, H 2006. Genotype by environment interaction for milk production traits between organic and conventional dairy cattle production in the Netherlands. Journal of Dairy Science 89, 27292737.
Neuenschwander, TF-O, Miglior, F, Jamrozik, J, Berke, O, Kelton, DF and Schaeffer, LR 2012. Genetic parameters for producer-recorded health data in Canadian Holstein cattle. Animal 6, 571578.10.1017/S1751731111002059
Norberg, E, Rogers, GW, Ødegård, J, Cooper, JB and Madsen, P 2006. Short communication: genetic correlation between test-day electrical conductivity of milk and mastitis. Journal of Dairy Science 89, 779781.10.3168/jds.S0022-0302(06)72139-7
Piechotta, M, Sander, AK, Kastelic, JP, Wilde, R, Heppelmann, M, Rudolph, B, Schuberth, HJ, Bollwein, H and Kaske, M 2012. Short communication: prepartum plasma insulin-like growth factor-I concentrations based on day of insemination are lower in cows developing postpartum diseases. Journal of Dairy Science 95, 13671370.10.3168/jds.2011-4622
Pieper, L, Staufenbiel, R, Christ, J, Panicke, L, Müller, U and Brockmann, GA 2016. Heritability of metabolic response to the intravenous glucose tolerance test in German Holstein Friesian bulls. Journal of Dairy Science 99, 72407246.10.3168/jds.2015-10672
Pryce, JE, Gaddis, KP, Koeck, A, Bastin, C, Adessayed, M, Gengler, N, Miglior, F, Heringstad, B, Egger-Danner, C and Stock, K 2016. Invited review: Opportunities for genetic improvement of metabolic diseases. Journal of Dairy Science 99, 68556873.10.3168/jds.2016-10854
Rauw, WM and Gomez-Raja, L 2015. Genotype by environment interaction and breeding for robustness in livestock. Frontiers in Genetics 6, 310.10.3389/fgene.2015.00310
Robertson, A 1959. The sampling variance of the genetic correlation coefficient. Biometrics 15, 469485.10.2307/2527750
Samoré, AB, Rizzi, R, Rossoni, A and Banato, A 2010. Genetic parameters for functional longevity, type traits, somatic cell scores, milk flow and production in the Italian Brown Swiss. Italian Journal of Animal Science 9, e28.10.4081/ijas.2010.e28
Sanders, AH, Shearer, JK and De Vries, A 2009. Seasonal incidence of lameness and risk factors associated with thin soles, white line disease, ulcers, and sole punctures in dairy cattle. Journal of Dairy Science 92, 31653174.10.3168/jds.2008-1799
Santos, LV, Brügemann, K, Ebinghaus, A and König, S 2018. Genetic parameters for longitudinal behaviour and health indicator traits generated in automatic milking systems. Archives Animal Breeding 61, 161171.10.5194/aab-61-161-2018
Sasson, G, Ben-Shabat, SK, Seroussi, E, Doron-Faigenboim, A, Shterzer, N, Yaacoby, S, Berg Miller, ME, White, BA, Halperin, E and Mizrahi, I 2017. Heritable bovine rumen bacteria are phylogenetically related and correlated with the cow’s capacity to harvest energy from its feed. mBio 8, e00703.
Schöpke, K, Gomez, A, Dunbar, KA, Swalve, HH and Döpfer, D 2015. Investigating the genetic background of bovine digital dermatitis using improved definitions of clinical status. Journal of Dairy Science 98, 81648174.10.3168/jds.2015-9485
Sorensen, LP, Mark, T, Madsen, P and Lund, MS 2009. Genetic correlations between pathogen-specific mastitis and somatic cell count in Danish Holsteins. Journal of Dairy Science 92, 34573471.10.3168/jds.2008-1870
Streit, M, Reinhardt, F, Thaller, G and Bennewitz, J 2012. Reaction norms and genotype-by-environment interaction in the German Holstein dairy cattle. Journal Animal Breeding Genetics 129, 380389.10.1111/j.1439-0388.2012.00999.x
Tajima, K, Nonaka, I, Higuchi, K, Takusari, N, Kurihara, M, Takenaka, A, Mitsumori, M, Kailkawa, H and Aminov, R 2007. Influence of high temperature and humidity on rumen bacterial diversity in Holstein heifers. Anaerobe 13, 5764.10.1016/j.anaerobe.2006.12.001
Tetens, J, Heuer, C, Heyer, I, Klein, MS, Gronwald, W, Junge, W, Oefner, PJ, Thaller, G and Krattenmacher, N 2015. Polymorphisms within the APOBR gene are highly associated with milk levels of prognostic ketosis biomarkers in dairy cattle. Physiological Genomics 47, 129137.
Thompson-Crispi, KA, Miglior, F and Mallard, BA 2013. Genetic parameters for natural antibodies and associations with specific antibody and mastitis in Canadian Holsteins. Journal of Dairy Science 96, 39653972.10.3168/jds.2012-5919
Thompson-Crispi, KA, Sewalem, A, Miglior, F and Mallard, BA 2012. Genetic parameters of adaptive immune response traits in Canadian Holsteins. Journal of Dairy Science 95, 401409.10.3168/jds.2011-4452
Twomey, AJ, Carroll, RI, Doherty, ML, Byrne, N, Graham, DA, Sayers, RG, Blom, A and Berry, DP 2018. Genetic correlations between endo-parasite phenotypes and economically important traits in dairy and beef cattle. Journal of Animal Science 96, 407421.
Twomey, AJ, Graham, DA, Doherty, ML, Blom, A and Berry, DP 2018. Little genetic variability in resilience among cattle exists for a range of performance traits across herds in Ireland differing in Fasciola hepatica prevalence. Journal of Animal Science 96, 20992112.10.1093/jas/sky108
Van Haelst, YNT, Beeckman, A, van Knegsel, ATM and Fievez, V 2008. Short communication: elevated concentrations of oleic acid and long-chain fatty acids in milk fat of multiparous subclinical ketotic cows. Journal of Dairy Science 91, 46834686.10.3168/jds.2008-1375
Wagter, LC, Mallard, BA, Wilkie, BN, Leslie, KE, Boettcher, PJ and Dekkers, JCM 2000. A quantitative approach to classifying Holstein cows based on antibody responsiveness and its relationship to peripartum mastitis occurrence. Journal of Dairy Science 83, 488498.10.3168/jds.S0022-0302(00)74908-3
Walther, S, Tietze, M, Czerny, CP, König, S and Diesterbeck, US 2016. Development of a bioinformatics framework for the detection of gene conversation and the analysis of combinatorial diversity in immunoglobulin heavy chains in four cattle breeds. PloS One 11, e0164567.10.1371/journal.pone.0164567
Weigel, KA and Rekaya, R 2000. A multiple-trait herd cluster model for international dairy sire evaluation. Journal of Dairy Science 83, 815821.
West, JW 2003. Effects of heat-stress on production in dairy cattle. Journal of Dairy Science 86, 21312144.10.3168/jds.S0022-0302(03)73803-X
Wheelock, JB, Rhoads, RP, VanBaale, MJ, Sanders, SR and Baumgard, LH 2010. Effects of heat stress on energetic metabolism in lactating Holstein cows. Journal of Dairy Science 93, 644655.10.3168/jds.2009-2295
Zwald, NR, Weigel, KA, Chang, YM, Welper, RD and Clay, JS 2004. Genetic selection for health traits using producer-recorded data I. Incidence rates, heritability estimates, and sire breeding values. Journal of Dairy Science 87, 42874294.10.3168/jds.S0022-0302(04)73573-0


Type Description Title
Supplementary materials

König and May supplementary material
König and May supplementary material 1

 Word (19 KB)
19 KB

Invited review: Phenotyping strategies and quantitative-genetic background of resistance, tolerance and resilience associated traits in dairy cattle

  • S. König (a1) and K. May (a1) (a2)


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed