Determining Heat Stress Effects of Multiple Genetic Traits in Tropical Dairy Cattle Using Single-Step Genomic BLUP
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data
2.2. Analyses and Computations
2.3. Accuracy of Breeding Value Predictions
3. Results
3.1. Effects of Heat Stress on Genetic Parameters
3.2. Genetic Correlation
3.3. Accuracy of Genetic Predictions
3.4. Rate of Decline in MY, SCS, and FPR Traits
4. Discussion
4.1. Genetic Parameter Estimation
4.2. Genetic Correlation
4.3. Accuracy
4.4. Rate of Decline of MY, SCS, and FPR
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Das, R.; Sailo, L.; Verma, N.; Bharti, P.; Saikia, J.; Imtiwati; Kumar, R. Impact of heat stress on health and performance of dairy animals: A review. Vet. World 2016, 9, 260–268. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yan, G.; Li, H.; Shi, Z. Evaluation of Thermal Indices as the Indicators of Heat Stress in Dairy Cows in a Temperate Climate. Animals 2021, 11, 2459. [Google Scholar] [CrossRef] [PubMed]
- Polsky, L.; von Keyserlingk, M.A.G. Invited review: Effects of heat stress on dairy cattle welfare. J. Dairy Sci. 2017, 100, 8645–8657. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Aguilar, I.; Misztal, I.; Tsuruta, S. Genetic components of heat stress for dairy cattle with multiple lactations. J. Dairy Sci. 2009, 92, 5702–5711. [Google Scholar] [CrossRef] [Green Version]
- Boonkum, W.; Misztal, I.; Duangjinda, M.; Pattarajinda, V.; Tumwasorn, S.; Sanpote, J. Genetic effects of heat stress on milk yield of Thai Holstein crossbreds. J. Dairy Sci. 2011, 94, 487–492. [Google Scholar] [CrossRef] [Green Version]
- Gernand, E.; König, S.; Kipp, C. Influence of on-farm measurements for heat stress indicators on dairy cow productivity, female fertility, and health. J. Dairy Sci. 2019, 102, 6660–6671. [Google Scholar] [CrossRef]
- Santana, M.L., Jr.; Bignardi, A.B.; Pereira, R.J.; Stefani, G.; El Faro, L. Genetics of heat tolerance for milk yield and quality in Holsteins. Animal 2017, 11, 4–14. [Google Scholar] [CrossRef] [Green Version]
- Nguyen, T.T.T.; Bowman, P.J.; Haile-Mariam, M.; Pryce, J.E.; Hayes, B.J. Genomic selection for tolerance to heat stress in Australian dairy cattle. J. Dairy Sci. 2016, 99, 2849–2862. [Google Scholar] [CrossRef] [Green Version]
- Dikmen, S.; Hansen, P.J. Is the temperature-humidity index the best indicator of heat stress in lactating dairy cows in a sub-tropical environment? J. Dairy Sci. 2009, 92, 109–116. [Google Scholar] [CrossRef] [Green Version]
- Ravagnolo, O.; Misztal, I.; Hoogenboom, G. Genetic Component of Heat Stress in Dairy Cattle, Development of Heat Index Function. J. Dairy Sci. 2000, 83, 2120–2125. [Google Scholar] [CrossRef]
- Reis, N.S.; Ferreira, I.C.; Mazocco, L.A.; Souza, A.C.B.; Pinho, G.A.S.; da Fonseca Neto, Á.M.; Malaquias, J.V.; Macena, F.A.; Muller, A.G.; Martins, C.F.; et al. Shade Modifies Behavioral and Physiological Responses of Low to Medium Production Dairy Cows at Pasture in an Integrated Crop-Livestock-Forest System. Animals 2021, 11, 2411. [Google Scholar] [CrossRef] [PubMed]
- West, J.W. Effects of Heat-Stress on Production in Dairy Cattle. J. Dairy Sci. 2003, 86, 2131–2144. [Google Scholar] [CrossRef]
- Thompson, J.A.; Magee, D.D.; Tomaszewski, M.A.; Wilks, D.L.; Fourdraine, R.H. Management of summer infertility in Texas Holstein dairy cattle. Theriogenology 1996, 46, 547–558. [Google Scholar] [CrossRef]
- de Rensis, F.; Scaramuzzi, R.J. Heat stress and seasonal effects on reproduction in the dairy cow—A review. Theriogenology 2003, 60, 1139–1151. [Google Scholar] [CrossRef]
- Roth, Z.; Arav, A.; Bor, A.; Zeron, Y.; Braw-Tal, R.; Wolfenson, D. Improvement of quality of oocytes collected in the autumn by enhanced removal of impaired follicles from previously heat-stressed cows. Reproduction 2001, 122, 737–744. [Google Scholar] [CrossRef]
- Schüller, L.K.; Burfeind, O.; Heuwieser, W. Impact of heat stress on conception rate of dairy cows in the moderate climate considering different temperature–humidity index thresholds, periods relative to breeding, and heat load indices. Theriogenology 2014, 81, 1050–1057. [Google Scholar] [CrossRef]
- Mader, T.L.; Holt, S.M.; Hahn, G.L.; Davis, M.S.; Spiers, D.E. Feeding strategies for managing heat load in feedlot cattle. J. Anim. Sci. 2002, 80, 2373–2382. [Google Scholar] [CrossRef] [Green Version]
- Madalena, F.E.; Teodoro, R.L.; Lemos, A.M.; Monteiro, J.B.N.; Barbosa, R.T. Evaluation of Strategies for Crossbreeding of Dairy Cattle in Brazil. J. Dairy Sci. 1990, 73, 1887–1901. [Google Scholar] [CrossRef]
- Berma, A. Increasing Heat Stress Relief Produced by Coupled Coat Wetting and Forced Ventilation. J. Dairy Sci. 2008, 91, 4571–4578. [Google Scholar] [CrossRef] [Green Version]
- Moore, C.E.; Kay, J.K.; Collier, R.J.; VanBaale, M.J.; Baumgard, L.H. Effect of Supplemental Conjugated Linoleic Acids on Heat-Stressed Brown Swiss and Holstein Cows. J. Dairy Sci. 2005, 88, 1732–1740. [Google Scholar] [CrossRef] [Green Version]
- Buaban, S.; Puangdee, S.; Duangjinda, M.; Boonkum, W. Estimation of genetic parameters and trends for production traits of dairy cattle in Thailand using a multiple-trait multiple-lactation test day model. Asian-Australas. J. Anim. Sci. 2020, 33, 1387–1399. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Reodecha, C. Genetic evaluation of dairy cattle in Thailand. In Proceedings of the 7th World Congress on Genetics Applied to Livestock Production, Montpellier, France, 19–23 August 2002. [Google Scholar]
- Chanvijit, K.; Duangjinda, M.; Pattarajinda, V.; Reodecha, C. Model comparison for genetic evaluation of milk yield in crossbred Holsteins in the tropics. J. Appl. Genet. 2005, 46, 387–393. [Google Scholar] [PubMed]
- Bohmanova, J.; Misztal, I.; Cole, J.B. Temperature-Humidity Indices as Indicators of Milk Production Losses due to Heat Stress. J. Dairy Sci. 2007, 90, 1947–1956. [Google Scholar] [CrossRef]
- Ravagnolo, O.; Misztal, I. Genetic Component of Heat Stress in Dairy Cattle, Parameter Estimation. J. Dairy Sci. 2000, 83, 2126–2130. [Google Scholar] [CrossRef]
- Buaban, S.; Lengnudum, K.; Boonkum, W.; Phakdeedindan, P. Genome-wide association study on milk production and somatic cell score for Thai dairy cattle using weighted single-step approach with random regression test-day model. J. Dairy Sci. 2022, 105, 468–494. [Google Scholar] [CrossRef] [PubMed]
- Schcolnik, T. Using milk fat-to-protein ratio to evaluate dairy cows energy balance status. J. Anim. Sci. 2016, 94, 54–55. [Google Scholar] [CrossRef] [Green Version]
- Meuwissen, T.H.E.; Hayes, B.J.; Goddard, M.E. Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps. Genetics 2001, 157, 1819–1829. [Google Scholar] [CrossRef] [PubMed]
- Hayes, B.J.; Visscher, P.M.; Goddard, M.E. Increased accuracy of artificial selection by using the realized relationship matrix. Genet. Res. 2009, 91, 47–60. [Google Scholar] [CrossRef] [Green Version]
- Wiggans, G.R.; Cole, J.B.; Hubbard, S.M.; Sonstegard, T.S. Genomic Selection in Dairy Cattle: The USDA Experience. Annu. Rev. Anim. Biosci. 2017, 5, 309–327. [Google Scholar] [CrossRef] [Green Version]
- Schaeffer, L.R. Strategy for applying genome-wide selection in dairy cattle. J. Anim. Breed. Genet. 2006, 123, 218–223. [Google Scholar] [CrossRef]
- Daetwyler, H.D.; Villanueva, B.; Bijma, P.; Woolliams, J.A. Inbreeding in genome-wide selection. J. Anim. Breed. Genet. 2007, 124, 369–376. [Google Scholar] [CrossRef] [PubMed]
- Pryce, J.E.; Haile-Mariam, M.; Goddard, M.E.; Hayes, B.J. Identification of genomic regions associated with inbreeding de-pression in Holstein and Jersey dairy cattle. Genet. Sel. Evol. 2014, 46, 71. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Misztal, I.; Legarra, A.; Aguilar, I. Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information. J. Dairy Sci. 2009, 92, 4648–4655. [Google Scholar] [CrossRef] [Green Version]
- Legarra, A.; Aguilar, I.; Misztal, I. A relationship matrix including full pedigree and genomic information. J. Dairy Sci. 2009, 92, 4656–4663. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Christensen, O.F.; Lund, M.S. Genomic prediction when some animals are not genotyped. Genet. Sel. Evol. 2010, 42, 2. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- 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. 2010, 93, 743–752. [Google Scholar] [CrossRef]
- Tsuruta, S.; Misztal, I.; Lawlor, T.J. Short communication: Genomic evaluations of final score for US Holsteins benefit from the inclusion of genotypes on cows. J. Dairy Sci. 2013, 96, 3332–3335. [Google Scholar] [CrossRef] [Green Version]
- Lourenco, D.A.L.; Fragomeni, B.O.; Tsuruta, S.; Aguilar, I.; Zumbach, B.; Hawken, R.J.; Legarra, A.; Misztal, I. Accuracy of estimated breeding values with genomic information on males, females, or both: An example on broiler chicken. Genet. Sel. Evol. 2015, 47, 1–9. [Google Scholar] [CrossRef] [Green Version]
- Legarra, A.; Reverter, A. Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method. Genet. Sel. Evol. 2018, 50, 1–18. [Google Scholar] [CrossRef] [Green Version]
- Hollifield, M.K.; Lourenco, D.; Bermann, M.; Howard, J.T.; Misztal, I. Determining the stability of genomic estimated breeding values in future generations in commercial pig populations. J. Anim. Sci. 2021, 99, 1–8. [Google Scholar] [CrossRef]
- Bermann, M.; Legarra, A.; Hollifield, M.K.; Masuda, Y.; Lourenco, D.; Misztal, I. Validation of single-step GBLUP genomic predictions from threshold models using the linear regression method: An application in chicken mortality. J. Anim. Breed. Genet. 2020, 138, 4–13. [Google Scholar] [CrossRef] [PubMed]
- National Oceanic and Atmospheric Administration. Livestock Hot Weather Stress; US Department Commerce, National Weather Service Central Region; Operations Manual Letter C–31–76; US Government Printing Office: Washington, DC, USA, 1976.
- Bohmanova, J.; Misztal, I.; Tsuruta, S.; Norman, H.D.; Lawlor, T.J. Short Communication: Genotype by environment interaction due to heat stress. J. Dairy Sci. 2008, 91, 840–846. [Google Scholar] [CrossRef] [PubMed]
- Sungkhapreecha, P.; Misztal, I.; Hidalgo, J.; Steyn, Y.; Buaban, S.; Duangjinda, M.; Boonkum, W. Changes in genetic parameters for milk yield and heat tolerance in the Thai Holstein crossbred dairy population under different heat stress levels and over time. J. Dairy Sci. 2021, 104, 12703–12712. [Google Scholar] [CrossRef]
- Misztal, I.; Tsuruta, S.; Lourenco, D.; Aguilar, I.; Legarra, A.; Vitezica, Z. Manual for BLUPF90 Family of Programs. Available online: https://nce.ads.uga.edu/wiki/lib/exe/fetch.php?media=blupf90all2.pdf (accessed on 9 August 2019).
- VanRaden, P.M. Efficient Methods to Compute Genomic Predictions. J. Dairy Sci. 2008, 91, 4414–4423. [Google Scholar] [CrossRef] [Green Version]
- Carabaño, M.J.; Logar, B.; Bormann, J.; Minet, J.; Vanrobays, M.-L.; Díaz, C.; Tychon, B.; Gengler, N.; Hammami, H. Modeling heat stress under different environmental conditions. J. Dairy Sci. 2016, 99, 3798–3814. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Berman, A. Invited review: Are adaptations present to support dairy cattle productivity in warm climates? J. Dairy Sci. 2011, 94, 2147–2158. [Google Scholar] [CrossRef] [PubMed]
- Hansen, P.J. Physiological and cellular adaptations of zebu cattle to thermal stress. Anim. Reprod. Sci. 2004, 82–83, 349–360. [Google Scholar] [CrossRef]
- Kumar, A.; Ashraf, S.; Goud, T.S.; Grewal, A.; Singh, S.V.; Yadav, B.R.; Upadhyay, R.C. Expression profiling of major heat shock protein genes during different seasons in cattle (Bos indicus) and buffalo (Bubalus bubalis) under tropical climatic condition. J. Therm. Biol. 2015, 51, 55–64. [Google Scholar] [CrossRef] [PubMed]
- Boonkum, W.; Duangjinda, M. Estimation of genetic parameters for heat stress, including dominance gene effects, on milk yield in Thai Holstein dairy cattle. Anim. Sci. J. 2014, 86, 245–250. [Google Scholar] [CrossRef]
- Bernabucci, U.; Biffani, S.; Buggiotti, L.; Vitali, A.; Lacetera, N.; Nardone, A. The effects of heat stress in Italian Holstein dairy cattle. J. Dairy Sci. 2014, 97, 471–486. [Google Scholar] [CrossRef]
- Rhoads, M.L.; Rhoads, R.P.; VanBaale, M.J.; Collier, R.J.; Sanders, S.R.; Weber, W.J.; Crooker, B.A.; Baumgard, L.H. Effects of heat stress and plane of nutrition on lactating Holstein cows: I. Production, metabolism, and aspects of circulating somatotropin. J. Dairy Sci. 2009, 92, 1986–1997. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- National Research Council. Nutrient Requirements of Dairy Cattle: 7th Revised Edition; National Academy Press: Washington, DC, USA, 2001. [Google Scholar]
- Hammami, H.; Bormann, J.; M’Hamdi, N.; Montaldo, H.H.; Gengler, N. Evaluation of heat stress effects on production traits and somatic cell score of Holsteins in a temperate environment. J. Dairy Sci. 2013, 96, 1844–1855. [Google Scholar] [CrossRef] [Green Version]
- Dohoo, I.R.; Meek, A.H. Somatic cell counts in bovine milk. Can. Vet. J. 1982, 23, 119–125. [Google Scholar]
- Hyder, I.; Reddy, P.R.K.; Raju, J.; Manjari, P.; Prasad, C.S.; Kumar, K.A.; Sejian, V. Alteration in Rumen Functions and Diet Digestibility During Heat Stress in Sheep. In Sheep Production Adapting to Climate Change; Springer: Singapore, 2017; pp. 235–265. [Google Scholar]
- Shearer, J.K. Rumen Acidosis, Heat Stress and Laminitis. In Proceedings of the 4th Annual Arizona Dairy Production Conference, Tempe, AZ, USA, 11 October 2005; pp. 25–32. [Google Scholar]
- Kadzere, C.T.; Murphy, M.R.; Silanikove, N.; Maltz, E. Heat stress in lactating dairy cows: A review. Livest. Prod. Sci. 2002, 77, 59–91. [Google Scholar] [CrossRef]
- Guarini, A.R.; Lourenco, D.A.L.; Brito, L.F.; Sargolzaei, M.; Baes, C.F.; Miglior, F.; Misztal, I.; Schenkel, F.S. Comparison of genomic predictions for lowly heritable traits using multi-step and single-step genomic best linear unbiased predictor in Hol-stein cattle. J. Dairy Sci. 2018, 101, 8076–8086. [Google Scholar] [CrossRef] [PubMed]
- Lourenco, D.A.L.; Legarra, A.; Tsuruta, S.; Masuda, Y.; Aguilar, I.; Misztal, I. Single-Step Genomic Evaluations from Theory to Practice: Using SNP Chips and Sequence Data in BLUPF90. Genes 2020, 11, 790. [Google Scholar] [CrossRef]
- Bauer, J.; Přibyl, J.; Vostrý, L. Short communication: Reliability of single-step genomic BLUP breeding values by multi-trait test-day model analysis. J. Dairy Sci. 2015, 98, 4999–5003. [Google Scholar] [CrossRef] [Green Version]
- Andonov, S.; Lourenco, D.A.L.; Fragomeni, B.O.; Masuda, Y.; Pocrnic, I.; Tsuruta, S.; Misztal, I. Accuracy of breeding values in small genotyped populations using different sources of external information—A simulation study. J. Dairy Sci. 2017, 100, 395–401. [Google Scholar] [CrossRef] [Green Version]
- Muir, W.M. Comparison of genomic and traditional BLUP-estimated breeding value accuracy and selection response under alternative trait and genomic parameters. J. Anim. Breed. Genet. 2007, 124, 342–355. [Google Scholar] [CrossRef]
- Bohlouli, M.; Shodja, J.; Alijani, S.; Eghbal, A. The relationship between temperature-humidity index and test-day milk yield of Iranian Holstein dairy cattle using random regression model. Livest. Sci. 2013, 157, 414–420. [Google Scholar] [CrossRef]
- Dunn, R.J.H.; Mead, N.E.; Willett, K.M.; Parker, D.E. Analysis of heat stress in UK dairy cattle and impact on milk yields. Environ. Res. Lett. 2014, 9, 064006. [Google Scholar] [CrossRef]
- Smith, D.L.; Smith, T.; Rude, B.J.; Ward, S.H. Short communication: Comparison of the effects of heat stress on milk and component yields and somatic cell score in Holstein and Jersey cows. J. Dairy Sci. 2013, 96, 3028–3033. [Google Scholar] [CrossRef] [PubMed]
- Brügemann, K.; Gernand, E.; von Borstel, U.K.; König, S. Defining and evaluating heat stress thresholds in different dairy cow production systems. Arch. Anim. Breed. 2012, 55, 13–24. [Google Scholar] [CrossRef]
- Sammad, A.; Wang, Y.J.; Umer, S.; Lirong, H.; Khan, I.; Khan, A.; Ahmad, B.; Wang, Y. Nutritional Physiology and Biochemistry of Dairy Cattle under the Influence of Heat Stress: Consequences and Opportunities. Animals 2020, 10, 793. [Google Scholar] [CrossRef]
- Puangdee, S.; Duangjinda, M.; Boonkum, W.; Katawatin, S.; Buaban, S.; Thepparat, M. Genetic associations between milk fat-to-protein ratio, milk production and fertility in the first two lactations of Thai Holsteins dairy cattle. Anim. Sci. J. 2017, 88, 723–730. [Google Scholar] [CrossRef]
- Gantner, V.; Bobic, T.; Gantner, R.; Gregic, M.; Kuterovac, K.; Novakovic, J.; Potocnik, K. Differences in response to heat stress due to production level and breed of dairy cows. Int. J. Biometeorol. 2017, 61, 1675–1685. [Google Scholar] [CrossRef]
- Hagiya, K.; Hayasaka, K.; Yamazaki, T.; Shirai, T.; Osawa, T.; Terawaki, Y.; Nagamine, Y.; Masuda, Y.; Suzuki, M. Effects of heat stress on production, somatic cell score and conception rate in Holsteins. Anim. Sci. J. 2016, 88, 3–10. [Google Scholar] [CrossRef] [Green Version]
- Igono, M.O.; Johnson, H.D.; Steevens, B.J.; Hainen, W.A.; Shanklin, M.D. Effect of season on milk temperature, milk growth hormone, prolactin, and somatic cell counts of lactating cattle. Int. J. Biometeorol. 1988, 32, 194–200. [Google Scholar] [CrossRef]
- Lambertz, C.; Sanker, C.; Gauly, M. Climatic effects on milk production traits and somatic cell score in lactating Holstein-Friesian cows in different housing systems. J. Dairy Sci. 2014, 97, 319–329. [Google Scholar] [CrossRef]
- Godden, S.; Rapnicki, P.; Stewart, S.; Fetrow, J.; Johnson, A.; Bey, R.; Farnsworth, R. Effectiveness of an Internal Teat Seal in the Prevention of New Intramammary Infections During the Dry and Early-Lactation Periods in Dairy Cows when used with a Dry Cow Intramammary Antibiotic. J. Dairy Sci. 2003, 86, 3899–3911. [Google Scholar] [CrossRef]
- Negri, R.; Daltro, D.D.S.; Cobuci, J.A. Heat stress effects on somatic cell score of Holstein cattle in tropical environment. Livest. Sci. 2021, 247, 104480. [Google Scholar] [CrossRef]
- Heuer, C.; Schukken, Y.H.; Dobbelaar, P. Postpartum Body Condition Score and Results from the First Test Day Milk as Predictors of Disease, Fertility, Yield, and Culling in Commercial Dairy Herds. J. Dairy Sci. 1999, 82, 295–304. [Google Scholar] [CrossRef]
- Haas, D.; Hofírek, B. The diagnostic importance of milk components for a human and cows’ health. In Proceedings of the Contributions: Milk Day 2004, CUA Prague, Czech, 10–11 June 2004; pp. 26–29. [Google Scholar]
- Richardt, W. Milk composition as an indicator of nutrition and health. Breeding 2004, 11, 26–27. [Google Scholar]
Item/Traits | MY | SCS | FPR |
---|---|---|---|
Number of herd x test-month x test-year | 24,928 | 24,928 | 24,928 |
Number of farm x calving season | 218 | 218 | 218 |
Number of breed group x months in milk group | 30 | 30 | 30 |
Classes of age at first calving | 7 | 7 | 7 |
Number of animals with records | 15,380 | 15,380 | 15,380 |
Number of animals in the pedigree | 33,231 | 33,231 | 33,231 |
Number of animals with genotypes | 882 | 882 | 882 |
Minimum | 5 | 0.01 | 0.23 |
Maximum | 45 | 10.00 | 3.58 |
Mean | 14.33 | 3.56 | 1.13 |
Standard deviation | 4.46 | 1.82 | 0.33 |
Methods | BLUP | ssGBLUP | ||||
---|---|---|---|---|---|---|
Parameters | MY | SCS | FPR | MY | SCS | FPR |
1.247 | 0.421 | 0.018 | 1.058 | 0.411 | 0.018 | |
(0.006) | (0.005) | (0.004) | (0.006) | (0.005) | (0.004) | |
5.753 | 0.152 | 0.007 | 5.650 | 0.204 | 0.007 | |
(0.066) | (0.010) | (0.010) | (0.063) | (0.007) | (0.009) | |
0.094 | 0.035 | 0.001 | 0.015 | 0.005 | 0.001 | |
(0.011) | (0.012) | (0.012) | (0.008) | (0.009) | (0.008) | |
−0.116 | 0.018 | −0.001 | −0.107 | 0.014 | −0.001 | |
(0.009) | (0.006) | (0.004) | (0.008) | (0.005) | (0.005) | |
6.208 | 0.707 | 0.023 | 6.481 | 0.754 | 0.025 | |
(0.051) | (0.005) | (0.008) | (0.058) | (0.004) | (0.009) | |
0.715 | 0.068 | 0.003 | 0.185 | 0.015 | 0.001 | |
(0.006) | (0.011) | (0.011) | (0.007) | (0.008) | (0.008) | |
−0.429 | 0.026 | −0.001 | −0.532 | 0.036 | −0.002 | |
(0.014) | (0.006) | (0.004) | (0.009) | (0.004) | (0.004) | |
3.350 | 1.762 | 0.050 | 3.086 | 1.736 | 0.049 | |
(0.008) | (0.003) | (0.003) | (0.008) | (0.003) | (0.003) | |
16.822 | 3.101 | 0.100 | 15.836 | 2.075 | 0.098 | |
(0.032) | (0.062) | (0.067) | (0.046) | (0.045) | (0.055) | |
0.334 | 0.049 | 0.060 | 0.344 | 0.087 | 0.061 | |
(0.003) | (0.004) | (0.006) | (0.003) | (0.003) | (0.004) | |
−0.158 | 0.247 | −0.378 | −0.368 | 0.438 | −0.378 | |
(0.008) | (0.009) | (0.008) | (0.005) | (0.009) | (0.008) | |
−0.204 | 0.119 | −0.120 | −0.486 | 0.339 | −0.400 | |
(0.010) | (0.008) | (0.009) | (0.009) | (0.009) | (0.008) |
Methods | BLUP | ssGBLUP | ||||
---|---|---|---|---|---|---|
Traits | MY | SCS | FPR | MY | SCS | FPR |
MY | − | 0.06 | −0.21 | − | 0.09 | −0.18 |
SCS | −0.10 | − | 0.06 | −0.13 | − | 0.01 |
FPR | 0.02 | −0.01 | − | 0.02 | 0.08 | − |
Methods | BLUP | ssGBLUP | ||||
---|---|---|---|---|---|---|
Traits | MY | SCS | FPR | MY | SCS | FPR |
Ratio of accuracies | 0.24 | 0.37 | 0.26 | 0.37 | 0.49 | 0.38 |
Accuracy | 0.20 | 0.20 | 0.25 | 0.36 | 0.33 | 0.40 |
Methods | BLUP | ssGBLUP | ||||
---|---|---|---|---|---|---|
Traits | MY (kg) | SCS (score) | FPR (%) | MY (kg) | SCS (score) | FPR (%) |
Percentage of Holstein genes (percentage of the number of animals) | ||||||
BG1: < 87.5% (22%) | 0.12 | 0.01 | −0.01 | 0.02 | 0.00 | 0.00 |
BG2: 87.5 to 93.6% (53%) | −0.01 | 0.02 | −0.01 | −0.03 | 0.04 | −0.01 |
BG3: >93.7% (25%) | −0.07 | 0.05 | −0.02 | −0.08 | 0.07 | −0.05 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Sungkhapreecha, P.; Chankitisakul, V.; Duangjinda, M.; Buaban, S.; Boonkum, W. Determining Heat Stress Effects of Multiple Genetic Traits in Tropical Dairy Cattle Using Single-Step Genomic BLUP. Vet. Sci. 2022, 9, 66. https://doi.org/10.3390/vetsci9020066
Sungkhapreecha P, Chankitisakul V, Duangjinda M, Buaban S, Boonkum W. Determining Heat Stress Effects of Multiple Genetic Traits in Tropical Dairy Cattle Using Single-Step Genomic BLUP. Veterinary Sciences. 2022; 9(2):66. https://doi.org/10.3390/vetsci9020066
Chicago/Turabian StyleSungkhapreecha, Piriyaporn, Vibuntita Chankitisakul, Monchai Duangjinda, Sayan Buaban, and Wuttigrai Boonkum. 2022. "Determining Heat Stress Effects of Multiple Genetic Traits in Tropical Dairy Cattle Using Single-Step Genomic BLUP" Veterinary Sciences 9, no. 2: 66. https://doi.org/10.3390/vetsci9020066