Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows

Atashi, Hadi; Bastin, C.; Wilmot, Hélène; Vanderick, Sylvie; Hubin, X.; Gengler, Nicolas

doi:10.3168/jds.2022-21780

Download

Article (Scientific journals)

Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows

Atashi, Hadi; Bastin, C.; Wilmot, Hélène et al.

2022 • In Journal of Dairy Science

Peer Reviewed verified by ORBi

Permalink
https://hdl.handle.net/2268/295203

DOI
10.3168/jds.2022-21780

Files (1)Send to Details Statistics Bibliography Similar publications

Files

Full Text

1-s2.0-S0022030222005392-main.pdf

Publisher postprint (2.81 MB)

Download

All documents in ORBi are protected by a user license.

Send to

RIS BibTex APA Chicago Permalink X Linkedin

Details

Keywords :

genetic parameter; milk composition; mid-infrared spectroscopy; dual-purpose cattle

Abstract :

[en] This study aimed to estimate genetic parameters and identify genomic region(s) associated with selected cheese-making properties (CMP) in Dual-Purpose Belgian Blue (DPBB) cows. Edited data were 46,301 test-day records of milk yield, fat percentage, protein percentage, casein percentage, milk calcium content (CC), coagulation time (CT), curd firmness after 30 min from rennet addition (a30), and milk titratable acidity (MTA) collected from 2014 to 2020 on 4,077 first-parity (26,027 test-day records), and 3,258 secondparity DPBB cows (20,274 test-day records) distributed in 124 herds in the Walloon Region of Belgium. Data of 28,266 SNP, located on 29 Bos taurus autosomes (BTA) of 1,699 animals were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 25 consecutive SNPs (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Heritability estimates for the included CMP ranged from 0.19 (CC) to 0.50 (MTA), and 0.24 (CC) to 0.41 (MTA) in the first and second parity, respectively. The genetic correlation estimated between CT and a30 varied from −0.61 to −0.41 and from −0.55 to −0.38 in the first and second lactations, respectively. Negative genetic correlations were found between CT and milk yield and composition, while those estimated between curd firmness and milk composition were positive. Genome-wide association analyses results identified 4 genomic regions (BTA1, BTA3, BTA7, and BTA11) associated with the considered CMP. The identified genomic regions showed contrasting results between parities and among the different stages of each parity. It suggests that different sets of candidate genes underlie the phenotypic expression of the considered CMP between parities and lactation stages of each parity. The findings of this study can be used for future implementation and use of genomic evaluation to improve the cheese-making traits in DPBB cows.

Disciplines :

Animal production & animal husbandry

Author, co-author :

Atashi, Hadi ; Université de Liège - ULiège > Département GxABT > Ingénierie des productions animales et nutrition

Bastin, C.

Wilmot, Hélène ; Université de Liège - ULiège > TERRA Research Centre > Ingénierie des productions animales et nutrition

Vanderick, Sylvie ; Université de Liège - ULiège > TERRA Research Centre > Ingénierie des productions animales et nutrition

Hubin, X.

Gengler, Nicolas ; Université de Liège - ULiège > TERRA Research Centre > Ingénierie des productions animales et nutrition

Language :

English

Title :

Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows

Publication date :

September 2022

Journal title :

Journal of Dairy Science

ISSN :

0022-0302

eISSN :

1525-3198

Publisher :

American Dairy Science Association

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://api.elsevier.com/content/article/PII:S0022030222005392?httpAccept=text/xml

Funders :

F.R.S.-FNRS - Fonds de la Recherche Scientifique

Available on ORBi :

since 28 September 2022

Statistics

Number of views

72 (15 by ULiège)

Number of downloads

36 (8 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

OpenAlex citations

Bibliography

Abd El-Gawad, M.A., Ahmed, N.S., Cheese yield as affected by some parameters review. Acta Sci. Pol. Technol. Aliment. 10 (2011), 131–153.
Aguilar, I., Misztal, I., Johnson, D., Legarra, A., Tsuruta, S., Lawlor, T., 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 https://doi.org/10.3168/jds.2009-2730 20105546.
Aguilar, I., Misztal, I., Tsuruta, S., Legarra, A., Wang, H., PREGSF90–POSTGSF90: Computational tools for the implementation of single-step genomic selection and genome-wide association with ungenotyped individuals in BLUPF90 programs. Proc. 10th World Congr. Genet. Appl. Livest. Prod., Vancouver, BC, Canada, 2014, American Society of Animal Science, 1–3 https://doi.org/10.13140/2.1.4801.5045.
Aguilar, I., S. Tsuruta, Y. Masuda, D. Lourenco, A. Legarra, and I. Misztal. 2018. BLUPF90 suite of programs for animal breeding with focus on genomics. Paper presented at the Proceedings of the 11th World Congress on Genetics Applied to Livestock Production, Auckland, New Zealand.
Ashwell, M.S., Heyen, D.W., Sonstegard, T.S., Van Tassell, C.P., Da, Y., VanRaden, P.M., Ron, M., Weller, J.I., Lewin, H.A., Detection of quantitative trait loci affecting milk production, health, and reproductive traits in Holstein cattle. J. Dairy Sci. 87 (2004), 468–475 https://doi.org/10.3168/jds.S0022-0302(04)73186-0 14762090.
Atashi, H., Bastin, C., Soyeurt, H., Dehareng, F., Wilmot, H., Vanderick, S., Gengler, N., Genetic parameters of butter softness and spreadability as new traits in Dual Purpose Belgian Blue. Interbull Bull. 56 (2021), 167–171.
Atashi, H., Salavati, M., De Koster, J., Ehrlich, J., Crowe, M., Opsomer, G., E. Gplus. Consortium. Hostens, M., Genome-wide association for milk production and lactation curve parameters in Holstein dairy cows. J. Anim. Breed. Genet. 137 (2020), 292–304 https://doi.org/10.1111/jbg.12442.
Atashi, H., Wilmot, H., Gengler, N., The pattern of linkage disequilibrium in Dual-Purpose Belgian Blue cattle. J. Anim. Breed. Genet. 139 (2022), 320–329 https://doi.org/10.1111/jbg.12662 34859921.
Atashi, H., Wilmot, H., Vanderick, S., Hubin, X., Gengler, N., Genome-wide association study for milk production traits in Dual-Purpose Belgian Blue cows. Livest. Sci., 256, 2022, 104831 https://doi.org/10.1016/j.livsci.2022.104831.
Bagnicka, E., Kawecka-Grochocka, E., Pawlina-Tyszko, K., Zalewska, M., Kapusta, A., Kościuczuk, E., Marczak, S., Ząbek, T., MicroRNA expression profile in bovine mammary gland parenchyma infected by coagulase-positive or coagulase-negative staphylococci. Vet. Res., 52, 2021, 41 https://doi.org/10.1186/s13567-021-00912-2 33676576.
Bastin, C., Dehareng, F., Gengler, N., Sindic, M., Piraux, E., Soyeurt, H., Wilmot, H., Bertozzi, C., Leblois, J., Colinet, F., Advanced monitoring of milk quality to address the demand of added-value dairy products. Paper presented at the Proceedings of the 71st Annual Meeting of the European Federation of Animal Science. 2020, Wageningen Academic Publishers.
Benedet, A., Ho, P.N., Xiang, R., Bolormaa, S., De Marchi, M., Goddard, M.E., Pryce, J.E., The use of mid-infrared spectra to map genes affecting milk composition. J. Dairy Sci. 102 (2019), 7189–7203 https://doi.org/10.3168/jds.2018-15890 31178181.
Bittante, G., Modeling rennet coagulation time and curd firmness of milk. J. Dairy Sci. 94 (2011), 5821–5832 https://doi.org/10.3168/jds.2011-4514 22118072.
Bittante, G., Penasa, M., Cecchinato, A., Invited review: Genetics and modeling of milk coagulation properties. J. Dairy Sci. 95 (2012), 6843–6870 https://doi.org/10.3168/jds.2012-5507 23021752.
Buitenhuis, B., Poulsen, N.A., Larsen, L.B., Sehested, J., Estimation of genetic parameters and detection of quantitative trait loci for minerals in Danish Holstein and Danish Jersey milk. BMC Genet., 16, 2015, 52 https://doi.org/10.1186/s12863-015-0209-9 25989905.
Cai, Z., Guldbrandtsen, B., Lund, M.S., Sahana, G., Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle. BMC Genomics, 19, 2018, 656 https://doi.org/10.1186/s12864-018-5050-x 30189836.
Cassandro, M., Comin, A., Ojala, M., Dal Zotto, R., De Marchi, M., Gallo, L., Carnier, P., Bittante, G., Genetic parameters of milk coagulation properties and their relationships with milk yield and quality traits in Italian Holstein cows. J. Dairy Sci. 91 (2008), 371–376 https://doi.org/10.3168/jds.2007-0308 18096961.
Cecchinato, A., Penasa, M., De Marchi, M., Gallo, L., Bittante, G., Carnier, P., Genetic parameters of coagulation properties, milk yield, quality, and acidity estimated using coagulating and noncoagulating milk information in Brown Swiss and Holstein-Friesian cows. J. Dairy Sci. 94 (2011), 4205–4213 https://doi.org/10.3168/jds.2010-3913 21787956.
Chen, H., Zhang, L., Li, X., Li, X., Sun, G., Yuan, X., Lei, L., Liu, J., Yin, L., Deng, Q., Wang, J., Liu, Z., Yang, W., Wang, Z., Zhang, H., Liu, G., Adiponectin activates the AMPK signaling pathway to regulate lipid metabolism in bovine hepatocytes. J. Steroid Biochem. Mol. Biol. 138 (2013), 445–454 https://doi.org/10.1016/j.jsbmb.2013.08.013 23994141.
Cole, J.B., Wiggans, G.R., Ma, L., Sonstegard, T.S., Lawlor, T.J. Jr., Crooker, B.A., Van Tassell, C.P., Yang, J., Wang, S., Matukumalli, L.K., Da, Y., Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary US Holstein cows. BMC Genomics, 12, 2011, 408 https://doi.org/10.1186/1471-2164-12-408 21831322.
Colinet, F., The Dual Purpose Belgian Blue. 2010, Gembloux Agro-Biol. Tech, University of Liège.
Colinet, F., Soyeurt, H., Anceau, C., Vanlierde, A., Keyen, N., Dardenne, P., Gengler, N., Sindic, M., Potential estimation of titratable acidity in cow milk using mid-infrared spectrometry. Proceedings of ICAR 37th Annual Meeting. http://www.icar.org/Documents/Riga_2010/ppt/Colinet.pdf, 2010. (Accessed 16 January 2013)
Colinet, F., Troch, T., Baeten, V., Dehareng, F., Dardenne, P., Sindic, M., Gengler, N., Genetic variability of MIR predicted milk technological properties in Walloon dairy cattle. Paper presented at the Proceedings of the 66th Annual Meeting of the European Federation of Animal Science. 2015, Wageningen Academic Publishers.
Dadousis, C., Biffani, S., Cipolat-Gotet, C., Nicolazzi, E., Rossoni, A., Santus, E., Bittante, G., Cecchinato, A., Genome-wide association of coagulation properties, curd firmness modeling, protein percentage, and acidity in milk from Brown Swiss cows. J. Dairy Sci. 99 (2016), 3654–3666 https://doi.org/10.3168/jds.2015-10078 26947304.
De Marchi, M., Fagan, C.C., O'Donnell, C.P., Cecchinato, A., Dal Zotto, R., Cassandro, M., Penasa, M., Bittante, G., Prediction of coagulation properties, titratable acidity, and pH of bovine milk using mid-infrared spectroscopy. J. Dairy Sci. 92 (2009), 423–432 https://doi.org/10.3168/jds.2008-1163 19109300.
Durán Aguilar, M., Román Ponce, S., Ruiz López, F., González Padilla, E., Vásquez Peláez, C., Bagnato, A., Strillacci, M.G., Genome-wide association study for milk somatic cell score in Holstein cattle using copy number variation as markers. J. Anim. Breed. Genet. 134 (2017), 49–59 https://doi.org/10.1111/jbg.12238 27578198.
Guinee, T.P., O'Kennedy, B.T., Kelly, P.M., Effect of milk protein standardization using different methods on the composition and yields of Cheddar cheese. J. Dairy Sci. 89 (2006), 468–482 https://doi.org/10.3168/jds.S0022-0302(06)72110-5 16428616.
Hayes, H.C., Petit, E.J., Mapping of the β-lactoglobulin gene and of an immunoglobulin M heavy chain-like sequence to homoeologous cattle, sheep, and goat chromosomes. Mamm. Genome 4 (1993), 207–210 https://doi.org/10.1007/BF00417564 8499654.
Ibeagha-Awemu, E.M., Peters, S.O., Akwanji, K.A., Imumorin, I.G., Zhao, X., High density genome wide genotyping-by-sequencing and association identifies common and low frequency SNPs, and novel candidate genes influencing cow milk traits. Sci. Rep., 6, 2016, 31109 https://doi.org/10.1038/srep31109 27506634.
Ikonen, T., Ahlfors, K., Kempe, R., Ojala, M., Ruottinen, O., Genetic parameters for the milk coagulation properties and prevalence of noncoagulating milk in Finnish dairy cows. J. Dairy Sci. 82 (1999), 205–214 https://doi.org/10.3168/jds.S0022-0302(99)75225-2 10022022.
Ikonen, T., Morri, S., Tyrisevä, A.-M., Ruottinen, O., Ojala, M., Genetic and phenotypic correlations between milk coagulation properties, milk production traits, somatic cell count, casein content, and pH of milk. J. Dairy Sci. 87 (2004), 458–467 https://doi.org/10.3168/jds.S0022-0302(04)73185-9 14762089.
Iung, L.H.S., Petrini, J., Ramírez-Díaz, J., Salvian, M., Rovadoscki, G.A., Pilonetto, F., Dauria, B.D., Machado, P.F., Coutinho, L.L., Wiggans, G.R., Mourão, G.B., Genome-wide association study for milk production traits in a Brazilian Holstein population. J. Dairy Sci. 102 (2019), 5305–5314 https://doi.org/10.3168/jds.2018-14811 30904307.
Jamrozik, J., Schaeffer, L.R., Estimates of genetic parameters for a test day model with random regressions for yield traits of first lactation Holsteins. J. Dairy Sci. 80 (1997), 762–770 https://doi.org/10.3168/jds.S0022-0302(97)75996-4 9149971.
Jiang, J., Ma, L., Prakapenka, D., VanRaden, P.M., Cole, J.B., Da, Y., A large-scale genome-wide association study in US Holstein cattle. Front. Genet., 10, 2019, 412 https://doi.org/10.3389/fgene.2019.00412 31139206.
Kemper, K.E., Bowman, P.J., Hayes, B.J., Visscher, P.M., Goddard, M.E., A multi-trait Bayesian method for mapping QTL and genomic prediction. Genet. Sel. Evol., 50, 2018, 10 https://doi.org/10.1186/s12711-018-0377-y 29571285.
Kemper, K.E., Reich, C.M., Bowman, P.J., Vander Jagt, C.J., Chamberlain, A.J., Mason, B.A., Hayes, B.J., Goddard, M.E., Improved precision of QTL mapping using a nonlinear Bayesian method in a multi-breed population leads to greater accuracy of across-breed genomic predictions. Genet. Sel. Evol., 47, 2015, 29 https://doi.org/10.1186/s12711-014-0074-4 25887988.
Kolbehdari, D., Wang, Z., Grant, J., Murdoch, B., Prasad, A., Xiu, Z., Marques, E., Stothard, P., Moore, S., A whole-genome scan to map quantitative trait loci for conformation and functional traits in Canadian Holstein bulls. J. Dairy Sci. 91 (2008), 2844–2856 https://doi.org/10.3168/jds.2007-0585 18565942.
Kuleshov, M.V., Jones, M.R., Rouillard, A.D., Fernandez, N.F., Duan, Q., Wang, Z., Koplev, S., Jenkins, S.L., Jagodnik, K.M., Lachmann, A., McDermott, M.G., Monteiro, C.D., Gundersen, G.W., Ma'ayan, A., Enrichr: A comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44:W1 (2016), W90–W97 https://doi.org/10.1093/nar/gkw377 27141961.
Maxa, J., Neuditschko, M., Russ, I., Förster, M., Medugorac, I., Genome-wide association mapping of milk production traits in Braunvieh cattle. J. Dairy Sci. 95 (2012), 5357–5364 https://doi.org/10.3168/jds.2011-4673 22916942.
Meredith, B.K., Kearney, F.J., Finlay, E.K., Bradley, D.G., Fahey, A.G., Berry, D.P., Lynn, D.J., Genome-wide associations for milk production and somatic cell score in Holstein-Friesian cattle in Ireland. BMC Genet., 13, 2012, 21 https://doi.org/10.1186/1471-2156-13-21 22449276.
Misztal, I., S. Tsuruta, T. Strabel, B. Auvray, T. Druet, and D. Lee. 2002. BLUPF90 and related programs (BGF90). Paper presented at the proceeding of the 7th World Congress on Genetics Applied to Livestock Production, Montpellier, France.
Mohan, G., Kumar, A., Khan, S.H., Kumar, N.A., Kapila, S., Lathwal, S., Sodhi, M., Niranjan, S., Casein (CSN) gene variants and parity affect the milk protein traits in crossbred (Bos taurus x Bos indicus) cows in sub-tropical climate. Trop. Anim. Health Prod., 53, 2021, 289 https://doi.org/10.1007/s11250-021-02736-w 33905007.
Mota, R.R., Mayeres, P., Bastin, C., Glorieux, G., Bertozzi, C., Vanderick, S., Hammami, H., Colinet, F.G., Gengler, N., Genetic evaluation for birth and conformation traits in dual-purpose Belgian Blue cattle using a mixed inheritance model. J. Anim. Sci. 95 (2017), 4288–4299 https://doi.org/10.2527/jas2017.1748 29108034.
Oliveira, H.R., Cant, J.P., Brito, L.F., Feitosa, F.L.B., Chud, T.C.S., Fonseca, P.A.S., Jamrozik, J., Silva, F.F., Lourenco, D.A.L., Schenkel, F.S., Genome-wide association for milk production traits and somatic cell score in different lactation stages of Ayrshire, Holstein, and Jersey dairy cattle. J. Dairy Sci. 102 (2019), 8159–8174 https://doi.org/10.3168/jds.2019-16451 31301836.
Pan, C.-J., Chen, S.-Y., Jun, H.S., Lin, S.R., Mansfield, B.C., Chou, J.Y., SLC37A1 and SLC37A2 are phosphate-linked, glucose-6-phosphate antiporters. PLoS One, 6, 2011, e23157 https://doi.org/10.1371/journal.pone.0023157 21949678.
Panthi, R.R., Jordan, K.N., Kelly, A.L., Sheehan, J.D., Selection and treatment of milk for cheesemaking. Cheese, 4th ed., 2017, Academic Press, 23–50 https://doi.org/10.1016/B978-0-12-417012-4.00002-8.
Pausch, H., Emmerling, R., Gredler-Grandl, B., Fries, R., Daetwyler, H.D., Goddard, M.E., Meta-analysis of sequence-based association studies across three cattle breeds reveals 25 QTL for fat and protein percentages in milk at nucleotide resolution. BMC Genomics, 18, 2017, 853 https://doi.org/10.1186/s12864-017-4263-8 29121857.
Pegolo, S., Cecchinato, A., Mele, M., Conte, G., Schiavon, S., Bittante, G., Effects of candidate gene polymorphisms on the detailed fatty acids profile determined by gas chromatography in bovine milk. J. Dairy Sci. 99 (2016), 4558–4573 https://doi.org/10.3168/jds.2015-10420 26995140.
Penasa, M., Toffanin, V., Cologna, N., Cassandro, M., De Marchi, M., Effects of dairy factory, milk casein content and titratable acidity on coagulation properties in Trentingrana dairy industry. J. Dairy Res. 83 (2016), 242–248 https://doi.org/10.1017/S0022029916000212 27210496.
PM Food & Dairy Consulting, World Cheese Market 2000-2020. http://www.pmfood.dk/upl/9735/WCMINFORMATION.pdf, 2014. (Accessed 6 February 2018)
Popescu, C.P., Long, S., Riggs, P., Womack, J., Schmutz, S., Fries, R., Gallagher, D., Standardization of cattle karyotype nomenclature: Report of the committee for the standardization of the cattle karyotype. Cytogenet. Cell Genet. 74 (1996), 259–261 https://doi.org/10.1159/000134429 8976379.
Poulsen, N.A., Rybicka, I., Larsen, L.B., Buitenhuis, A.J., Larsen, M.K., Genetic variation of riboflavin content in bovine milk. J. Dairy Sci. 98 (2015), 3496–3501 https://doi.org/10.3168/jds.2014-8829 25771056.
Pretto, D., De Marchi, M., Penasa, M., Cassandro, M., Effect of milk composition and coagulation traits on Grana Padano cheese yield under field conditions. J. Dairy Res. 80 (2013), 1–5 https://doi.org/10.1017/S0022029912000453 22998758.
Raven, L.-A., Cocks, B.G., Hayes, B.J., Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle. BMC Genomics, 15, 2014, 62 https://doi.org/10.1186/1471-2164-15-62 24456127.
Raven, L.-A., Cocks, B.G., Kemper, K.E., Chamberlain, A.J., Vander Jagt, C.J., Goddard, M.E., Hayes, B.J., Targeted imputation of sequence variants and gene expression profiling identifies twelve candidate genes associated with lactation volume, composition and calving interval in dairy cattle. Mamm. Genome 27 (2016), 81–97 https://doi.org/10.1007/s00335-015-9613-8 26613780.
Saharinen, J., Hyytiäinen, M., Taipale, J., Keski-Oja, J., Latent transforming growth factor-β binding proteins (LTBPs)—structural extracellular matrix proteins for targeting TGF-β action. Cytokine Growth Factor Rev. 10 (1999), 99–117 https://doi.org/10.1016/S1359-6101(99)00010-6 10743502.
Sanchez, M.-P., Govignon-Gion, A., Croiseau, P., Fritz, S., Hozé, C., Miranda, G., Martin, P., Barbat-Leterrier, A., Letaïef, R., Rocha, D., Brochard, M., Boussaha, M., Boichard, D., Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle. Genet. Sel. Evol., 49, 2017, 68 https://doi.org/10.1186/s12711-017-0344-z 28923017.
Sanchez, M.-P., Ramayo-Caldas, Y., Wolf, V., Laithier, C., El Jabri, M., Michenet, A., Boussaha, M., Taussat, S., Fritz, S., Delacroix-Buchet, A., Brochard, M., Boichard, D., Sequence-based GWAS, network and pathway analyses reveal genes co-associated with milk cheese-making properties and milk composition in Montbéliarde cows. Genet. Sel. Evol., 51, 2019, 34 https://doi.org/10.1186/s12711-019-0473-7 31262251.
Santos, B.N.C., Silva, C.C.C.V., Domingues, J.R., Cortez, M.A.S., Freitas, D.D.G.C., Chiappini, C.C.J., Araújo, K.G.L., Effect of calcium addition and pH on yield and texture of Minas cured cheese. Arq. Bras. Med. Vet. Zootec. 65 (2013), 601–609 https://doi.org/10.1590/S0102-09352013000200042.
Schopen, G.C.B., Koks, P.D., Van Arendonk, J.A.M., Bovenhuis, H., Visker, M.H.P.W., Whole genome scan to detect quantitative trait loci for bovine milk protein composition. Anim. Genet. 40 (2009), 524–537 https://doi.org/10.1111/j.1365-2052.2009.01880.x 19397519.
Schulman, N.F., Sahana, G., Iso-Touru, T., Lund, M., Andersson-Eklund, L., Viitala, S.M., Värv, S., Viinalass, H., Vilkki, J.H., Fine mapping of quantitative trait loci for mastitis resistance on bovine chromosome 11. Anim. Genet. 40 (2009), 509–515 https://doi.org/10.1111/j.1365-2052.2009.01872.x 19397517.
Soyeurt, H., Bruwier, D., Romnee, J.-M., Gengler, N., Bertozzi, C., Veselko, D., Dardenne, P., Potential estimation of major mineral contents in cow milk using mid-infrared spectrometry. J. Dairy Sci. 92 (2009), 2444–2454 https://doi.org/10.3168/jds.2008-1734 19447976.
Threadgill, D.W., Womack, J.E., Genomic analysis of the major bovine milk protein genes. Nucleic Acids Res. 18 (1990), 6935–6942 https://doi.org/10.1093/nar/18.23.6935 1979856.
Tiezzi, F., Pretto, D., De Marchi, M., Penasa, M., Cassandro, M., Heritability and repeatability of milk coagulation properties predicted by mid-infrared spectroscopy during routine data recording, and their relationships with milk yield and quality traits. Animal 7 (2013), 1592–1599 https://doi.org/10.1017/S1751731113001195 23816365.
Tiezzi, F., Valente, B.D., Cassandro, M., Maltecca, C., Causal relationships between milk quality and coagulation properties in Italian Holstein-Friesian dairy cattle. Genet. Sel. Evol., 47, 2015, 45 https://doi.org/10.1186/s12711-015-0123-7 25968045.
Troch, T., Lefébure, É., Baeten, V., Colinet, F., Gengler, N., Sindic, M., Cow milk coagulation: Process description, variation factors and evaluation methodologies. A review. Biotechnol. Agron. Soc. Environ. 21 (2017), 276–287 https://doi.org/10.25518/1780-4507.13692.
Vallas, M., Bovenhuis, H., Kaart, T., Pärna, K., Kiiman, H., Pärna, E., Genetic parameters for milk coagulation properties in Estonian Holstein cows. J. Dairy Sci. 93 (2010), 3789–3796 https://doi.org/10.3168/jds.2009-2435 20655449.
VanRaden, P.M., Efficient methods to compute genomic predictions. J. Dairy Sci. 91 (2008), 4414–4423 https://doi.org/10.3168/jds.2007-0980 18946147.
Wang, X., Ma, P., Liu, J., Zhang, Q., Zhang, Y., Ding, X., Jiang, L., Wang, Y., Zhang, Y., Sun, D., Zhang, S., Su, G., Yu, Y., Genome-wide association study in Chinese Holstein cows reveal two candidate genes for somatic cell score as an indicator for mastitis susceptibility. BMC Genet., 16, 2015, 111 https://doi.org/10.1186/s12863-015-0263-3 26370837.
Wedholm, A., Larsen, L.B., Lindmark-Månsson, H., Karlsson, A.H., Andrén, A., Effect of protein composition on the cheese-making properties of milk from individual dairy cows. J. Dairy Sci. 89 (2006), 3296–3305 https://doi.org/10.3168/jds.S0022-0302(06)72366-9 16899662.
Wiggans, G.R., Sonstegard, T.S., VanRaden, P.M., Matukumalli, L.K., Schnabel, R.D., Taylor, J.F., Schenkel, F.S., Van Tassell, C.P., Selection of single-nucleotide polymorphisms and quality of genotypes used in genomic evaluation of dairy cattle in the United States and Canada. J. Dairy Sci. 92 (2009), 3431–3436 https://doi.org/10.3168/jds.2008-1758 19528621.
Wilmot, H., Bormann, J., Soyeurt, H., Hubin, X., Glorieux, G., Mayeres, P., Bertozzi, C., Gengler, N., Development of a genomic tool for breed assignment by comparison of different classification models: Application to three local cattle breeds. J. Anim. Breed. Genet. 139 (2022), 40–61 https://doi.org/10.1111/jbg.12643 34427366.
Xu, L., Cole, J.B., Bickhart, D.M., Hou, Y., Song, J., VanRaden, P.M., Sonstegard, T.S., Van Tassell, C.P., Liu, G.E., Genome wide CNV analysis reveals additional variants associated with milk production traits in Holsteins. BMC Genomics, 15, 2014, 683 https://doi.org/10.1186/1471-2164-15-683 25128478.
Yang, S.-H., Bi, X.-J., Xie, Y., Li, C., Zhang, S.-L., Zhang, Q., Sun, D.-X., Validation of PDE9A gene identified in GWAS showing strong association with milk production traits in Chinese Holstein. Int. J. Mol. Sci. 16 (2015), 26530–26542 https://doi.org/10.3390/ijms161125976 26556348.
Yegin, S., Dekker, P., Progress in the field of aspartic proteinases in cheese manufacturing: structures, functions, catalytic mechanism, inhibition, and engineering. Dairy Sci. Technol. 93 (2013), 565–594 https://doi.org/10.1007/s13594-013-0137-2.
Zhou, C., Li, C., Cai, W., Liu, S., Yin, H., Shi, S., Zhang, Q., Zhang, S., Genome-wide association study for milk protein composition traits in a Chinese Holstein population using a single-step approach. Front. Genet., 10, 2019, 72 https://doi.org/10.3389/fgene.2019.00072 30838020.