Abo-Ismail, M. K., Brito, L. F., Miller, S. P., Sargolzaei, M., Grossi, D. A., Moore, S. S., … Schenkel, F. S. (2017). Genome-wide association studies and genomic prediction of breeding values for calving performance and body conformation traits in Holstein cattle. Genetics Selection Evolution, 49(1), 82. https://doi.org/10.1186/s12711-017-0356-8
Aguilar, I., Misztal, I., Johnson, D., Legarra, A., Tsuruta, S., & Lawlor, T. (2010). Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. Journal of Dairy Science, 93(2), 743–752. https://doi.org/10.3168/jds.2009-2730
Aguilar, I., Misztal, I., Tsuruta, S., Legarra, A., & Wang, H. (2014). PREGSF90–POSTGSF90: computational tools for the implementation of single-step genomic selection and genome-wide association with ungenotyped individuals in BLUPF90 programs. Paper presented at the Proceedings of the 10th world congress of genetics applied to livestock production.
Ali, T., & Schaeffer, L. (1987). Accounting for covariances among test day milk yields in dairy cows. Canadian Journal of Animal Science, 67(3), 637–644. https://doi.org/10.4141/cjas87-067
Atashi, H., Zamiri, M., & Dadpasand, M. (2013). Association between dry period length and lactation performance, lactation curve, calf birth weight, and dystocia in Holstein dairy cows in Iran. Journal of Dairy Science, 96(6), 3632–3638. https://doi.org/10.3168/jds.2012-5943
Atashi, H., Zamiri, M. J., & Sayyadnejad, M. B. (2012). Effect of twinning and stillbirth on the shape of lactation curve in Holstein dairy cows of Iran. Archives Animal Breeding, 55(3), 226–233. https://doi.org/10.5194/aab-55-226-2012
Bagnato, A., Schiavini, F., Rossoni, A., Maltecca, C., Dolezal, M., Medugorac, I., … Lipkin, E. (2008). Quantitative trait loci affecting milk yield and protein percentage in a three-country Brown Swiss population. Journal of Dairy Science, 91(2), 767–783. https://doi.org/10.3168/jds.2007-0507
Bennewitz, J., Reinsch, N., Grohs, C., Levéziel, H., Malafosse, A., Thomsen, H., … Kalm, E. (2003). Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle. Genetics Selection Evolution, 35(3), 319. https://doi.org/10.1186/1297-9686-35-3-319
Bignardi, A. B., El Faro, L., Cardoso, V. L., Machado, P. F., & de Albuquerque, L. G. (2009). Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil. Livestock Science, 123(1), 1–7. https://doi.org/10.1016/j.livsci.2008.09.021
Boichard, D., Grohs, C., Bourgeois, F., Cerqueira, F., Faugeras, R., Neau, A., … Levéziel, H. (2003). Detection of genes influencing economic traits in three French dairy cattle breeds. Genetics Selection Evolution, 35(1), 77. https://doi.org/10.1186/1297-9686-35-1-77
Buitenhuis, B., Janss, L. L., Poulsen, N. A., Larsen, L. B., Larsen, M. K., & Sørensen, P. (2014). Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle. BMC Genomics, 15(1), 1112. https://doi.org/10.1186/1471-2164-15-1112
Chen, B., Sun, Y., Niu, J., Jarugumilli, G. K., & Wu, X. (2018). Protein lipidation in cell signaling and diseases: function, regulation, and therapeutic opportunities. Cell Chemical Biology, 25, 817–831.
Chen, H., Zhang, L., Li, X., Li, X., Sun, G., Yuan, X., … Liu, G. (2013). Adiponectin activates the AMPK signaling pathway to regulate lipid metabolism in bovine hepatocytes. Journal of Steroid Biochemistry and Molecular Biology, 138, 445–454. https://doi.org/10.1016/j.jsbmb.2013.08.013
Cole, J., Ehrlich, J., & Null, D. (2012). Projecting milk yield using best prediction and the MilkBot lactation model. Journal of Dairy Science, 95(7), 4041–4044.
Cole, J. B., Wiggans, G. R., Ma, L. I., Sonstegard, T. S., Lawlor, T. J., Crooker, B. A., … Da, Y. (2011). Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary US Holstein cows. BMC Genomics, 12(1), 408. https://doi.org/10.1186/1471-2164-12-408
Dekkers, J., Ten Hag, J., & Weersink, A. (1998). Economic aspects of persistency of lactation in dairy cattle. Livestock Production Science, 53(3), 237–252. https://doi.org/10.1016/S0301-6226(97)00124-3
Do, D., Bissonnette, N., Lacasse, P., Miglior, F., Sargolzaei, M., Zhao, X., & Ibeagha-Awemu, E. (2017). Genome-wide association analysis and pathways enrichment for lactation persistency in Canadian Holstein cattle. Journal of Dairy Science, 100(3), 1955–1970. https://doi.org/10.3168/jds.2016-11910
Ehrlich, J. (2011). Quantifying shape of lactation curves, and benchmark curves for common dairy breeds and parities. Bovine Practitioner, 45(1), 88.
El-Awady, H. (2013). Genetic aspects of lactation curve traits and persistency indices in Friesian cows. Archiva Zootechnica, 16(1), 15-29.
Erbe, M., Hayes, B. J., Matukumalli, L. K., Goswami, S., Bowman, P. J., Reich, C. M., … Goddard, M. E. (2012). Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. Journal of Dairy Science, 95(7), 4114–4129. https://doi.org/10.3168/jds.2011-5019
Gebreyohannes, G., Koonawootrittriron, S., Elzo, M. A., & Suwanasopee, T. (2013). Variance components and genetic parameters for milk production and lactation pattern in an Ethiopian multibreed dairy cattle population. Asian-Australasian Journal of Animal Sciences, 26(9), 1237. https://doi.org/10.5713/ajas.2013.13040
Hostens, M., Ehrlich, J., Van Ranst, B., & Opsomer, G. (2012). On-farm evaluation of the effect of metabolic diseases on the shape of the lactation curve in dairy cows through the MilkBot lactation model. Journal of Dairy Science, 95(6), 2988–3007. https://doi.org/10.3168/jds.2011-4791
Iso-Touru, T., Sahana, G., Guldbrandtsen, B., Lund, M., & Vilkki, J. (2016). Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants. BMC Genetics, 17(1), 55. https://doi.org/10.1186/s12863-016-0363-8
Jiang, H., Zhang, X., Chen, X., Aramsangtienchai, P., Tong, Z., & Lin, H. (2018). Protein lipidation: Occurrence, mechanisms, biological functions, and enabling technologies. Chemical Reviews, 118(3), 919–988. https://doi.org/10.1021/acs.chemrev.6b00750
Jiang, L., Liu, J., Sun, D., Ma, P., Ding, X., Yu, Y., & Zhang, Q. (2010). Genome wide association studies for milk production traits in Chinese Holstein population. PLoS ONE, 5(10), e13661. https://doi.org/10.1371/journal.pone.0013661
Khatkar, M. S., Nicholas, F. W., Collins, A. R., Zenger, K. R., Cavanagh, J. A. L., Barris, W., … Raadsma, H. W. (2008). Extent of genome-wide linkage disequilibrium in Australian Holstein-Friesian cattle based on a high-density SNP panel. BMC Genomics, 9(1), 187. https://doi.org/10.1186/1471-2164-9-187
Kolbehdari, D., Wang, Z., Grant, J. R., Murdoch, B., Prasad, A., Xiu, Z., … Moore, S. S. (2008). A whole-genome scan to map quantitative trait loci for conformation and functional traits in Canadian Holstein bulls. Journal of Dairy Science, 91(7), 2844–2856. https://doi.org/10.3168/jds.2007-0585
Kolbehdari, D., Wang, Z., Grant, J. R., Murdoch, B., Prasad, A., Xiu, Z., … Moore, S. S. (2009). A whole genome scan to map QTL for milk production traits and somatic cell score in Canadian Holstein bulls. Journal of Animal Breeding and Genetics, 126(3), 216–227. https://doi.org/10.1111/j.1439-0388.2008.00793.x
Kuleshov, M. V., Jones, M. R., Rouillard, A. D., Fernandez, N. F., Duan, Q., Wang, Z., … Ma'ayan, A. (2016). Enrichr: A comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Research, 44(W1), W90–W97. https://doi.org/10.1093/nar/gkw377
López, S., France, J., Odongo, N. E., McBride, R. A., Kebreab, E., AlZahal, O., … Dijkstra, J. (2015). On the analysis of Canadian Holstein dairy cow lactation curves using standard growth functions. Journal of Dairy Science, 98(4), 2701–2712. https://doi.org/10.3168/jds.2014-8132
Lund, M. S., Sorensen, P., Madsen, P., & Jaffrézic, F. (2008). Detection and modelling of time-dependent QTL in animal populations. Genetics Selection Evolution, 40(2), 177. https://doi.org/10.1186/1297-9686-40-2-177
McKay, S. D., Schnabel, R. D., Murdoch, B. M., Matukumalli, L. K., Aerts, J., Coppieters, W., … Moore, S. S. (2007). Whole genome linkage disequilibrium maps in cattle. BMC Genetics, 8(1), 74. https://doi.org/10.1186/1471-2156-8-74
Meredith, B. K., Kearney, F. J., Finlay, E. K., Bradley, D. G., Fahey, A. G., Berry, D. P., & Lynn, D. J. (2012). Genome-wide associations for milk production and somatic cell score in Holstein-Friesian cattle in Ireland. BMC Genetics, 13(1), 21. https://doi.org/10.1186/1471-2156-13-21
Misztal, I., Tsuruta, S., Strabel, T., Auvray, B., Druet, T., & Lee, D. (2002). BLUPF90 and related programs (BGF90). Paper presented at the Proceedings of the 7th world congress on genetics applied to livestock production.
Nayeri, S., Sargolzaei, M., Abo-Ismail, M. K., May, N., Miller, S. P., Schenkel, F., … Stothard, P. (2016). Genome-wide association for milk production and female fertility traits in Canadian dairy Holstein cattle. BMC Genetics, 17(1), 75. https://doi.org/10.1186/s12863-016-0386-1
Nayeri, S., Sargolzaei, M., Abo-Ismail, M., Miller, S., Schenkel, F., Moore, S., & Stothard, P. (2017). Genome-wide association study for lactation persistency, female fertility, longevity, and lifetime profit index traits in Holstein dairy cattle. Journal of Dairy Science, 100(2), 1246–1258. https://doi.org/10.3168/jds.2016-11770
Nayeri, S., & Stothard, P. (2016). Tissues, metabolic pathways and genes of key importance in lactating dairy cattle. Springer Science Reviews, 4(2), 49–77. https://doi.org/10.1007/s40362-016-0040-3
Ning, C., Kang, H., Zhou, L., Wang, D., Wang, H., Wang, A., … Liu, J. (2017). Performance gains in genome-wide association studies for longitudinal traits via modeling time-varied effects. Scientific Reports, 7(1), 590. https://doi.org/10.1038/s41598-017-00638-2
Ning, C., Wang, D., Zheng, X., Zhang, Q., Zhang, S., Mrode, R., & Liu, J.-F. (2018). Eigen decomposition expedites longitudinal genome-wide association studies for milk production traits in Chinese Holstein. Genetics Selection Evolution, 50(1), 12. https://doi.org/10.1186/s12711-018-0383-0
Rekaya, R., Carabano, M., & Toro, M. (2000). Bayesian analysis of lactation curves of Holstein-Friesian cattle using a nonlinear model. Journal of Dairy Science, 83(11), 2691–2701. https://doi.org/10.3168/jds.S0022-0302(00)75163-0
Rekik, B., Gara, A. B., Hamouda, M. B., & Hammami, H. (2003). Fitting lactation curves of dairy cattle in different types of herds in Tunisia. Livestock Production Science, 83(2–3), 309–315. https://doi.org/10.1016/S0301-6226(03)00028-9
Rodriguez-Zas, S., Southey, B., Heyen, D., & Lewin, H. (2002). Interval and composite interval mapping of somatic cell score, yield, and components of milk in dairy cattle. Journal of Dairy Science, 85(11), 3081–3091. https://doi.org/10.3168/jds.S0022-0302(02)74395-6
Rupp, R., & Boichard, D. (2003). Genetics of resistance to mastitis in dairy cattle. Veterinary Research, 34(5), 671–688. https://doi.org/10.1051/vetres:2003020
Saghanezhad, F., Atashi, H., Dadpasand, M., Zamiri, M., & Shokri-Sangari, F. (2017). Estimation of genetic parameters for lactation curve traits in Holstein Dairy Cows in Iran. Iranian Journal of Applied Animal Science, 7(4), 559-566.
Sargolzaei, M., Chesnais, J. P., & Schenkel, F. S. (2014). A new approach for efficient genotype imputation using information from relatives. BMC Genomics, 15(1), 478. https://doi.org/10.1186/1471-2164-15-478
Schaeffer, L. (2016). Random regression models. Retrieved from http://animalbiosciences.uoguelph.ca/~lrs/BOOKS/rrmbook.pdf
Shanks, R., Berger, P., Freeman, A., & Dickinson, F. (1981). Genetic aspects of lactation curves. Journal of Dairy Science, 64(9), 1852–1860. https://doi.org/10.3168/jds.S0022-0302(81)82775-0
Sherchand, L., McNew, R., Kellogg, D., & Johnson, Z. (1995). Selection of a mathematical model to generate lactation curves using daily milk yields of Holstein cows. Journal of Dairy Science, 78(11), 2507–2513. https://doi.org/10.3168/jds.S0022-0302(95)76880-1
Silvestre, A., Petim-Batista, F., & Colaco, J. (2006). The accuracy of seven mathematical functions in modeling dairy cattle lactation curves based on test-day records from varying sample schemes. Journal of Dairy Science, 89(5), 1813–1821. https://doi.org/10.3168/jds.S0022-0302(06)72250-0
Singh, A., Singh, A., Singh, M., Prakash, V., Ambhore, G., Sahoo, S., & Dash, S. (2016). Estimation of genetic parameters for first lactation monthly test-day milk yields using random regression test day model in Karan Fries cattle. Asian-Australasian Journal of Animal Sciences, 29(6), 775. https://doi.org/10.5713/ajas.15.0643
Strucken, E., Bortfeldt, R., De Koning, D., & Brockmann, G. (2012). Genome-wide associations for investigating time-dependent genetic effects for milk production traits in dairy cattle. Animal Genetics, 43(4), 375–382. https://doi.org/10.1111/j.1365-2052.2011.02278.x
Tekerli, M., Akinci, Z., Dogan, I., & Akcan, A. (2000). Factors affecting the shape of lactation curves of Holstein cows from the Balikesir province of Turkey. Journal of Dairy Science, 83(6), 1381–1386. https://doi.org/10.3168/jds.S0022-0302(00)75006-5
Triola, G. (2011). The protein lipidation and its analysis. Journal of Glycomics and Lipidomics, 2, 2153–0637.
VanRaden, P. M., Null, D. J., Sargolzaei, M., Wiggans, G. R., Tooker, M. E., Cole, J. B., … Doak, G. A. (2013). Genomic imputation and evaluation using high-density Holstein genotypes. Journal of Dairy Science, 96(1), 668–678. https://doi.org/10.3168/jds.2012-5702
VanRaden, P., Van Tassell, C., Wiggans, G., Sonstegard, T., Schnabel, R., Taylor, J., & Schenkel, F. (2009). Invited review: Reliability of genomic predictions for North American Holstein bulls. Journal of Dairy Science, 92(1), 16–24. https://doi.org/10.3168/jds.2008-1514
Verardo, L., Silva, F., Varona, L., Resende, M., Bastiaansen, J., Lopes, P., & Guimarães, S. (2015). Bayesian GWAS and network analysis revealed new candidate genes for number of teats in pigs. Journal of Applied Genetics, 56(1), 123–132. https://doi.org/10.1007/s13353-014-0240-y
Wang, D., Ning, C., Liu, J.-F., Zhang, Q., & Jiang, L. (2019). Replication of genome-wide association studies for milk production traits in Chinese Holstein by an efficient rotated linear mixed model. Journal of Dairy Science, 102(3), 2378–2383.
Wang, H., Misztal, I., Aguilar, I., Legarra, A., & Muir, W. (2012). Genome-wide association mapping including phenotypes from relatives without genotypes. Genetics Research, 94(2), 73–83. https://doi.org/10.1017/S0016672312000274
