Hostname: page-component-76fb5796d-dfsvx Total loading time: 0 Render date: 2024-04-25T17:11:56.842Z Has data issue: false hasContentIssue false
  • English
  • Français

Comparative selection signature analyses identify genomic footprints in Reggiana cattle, the traditional breed of the Parmigiano-Reggiano cheese production system

Published online by Cambridge University Press:  13 January 2020

F. Bertolini ,
G. Schiavo ,
S. Bovo ,
M. T. Sardina ,
S. Mastrangelo ,
S. Dall’Olio ,
B. Portolano  and
L. Fontanesi Open the ORCID record for L. Fontanesi [Opens in a new window]
F. Bertolini
Affiliation:
National Institute of Aquatic Resources, Technical University of Denmark, Kemitorvet, Building 202, 2800Kongens Lyngby, Denmark
G. Schiavo
Affiliation:
Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, 40127Bologna, Italy
S. Bovo
Affiliation:
Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, 40127Bologna, Italy
M. T. Sardina
Affiliation:
Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Viale delle Scienze, Ed. 4, 90128Palermo, Italy
S. Mastrangelo
Affiliation:
Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Viale delle Scienze, Ed. 4, 90128Palermo, Italy
S. Dall’Olio
Affiliation:
Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, 40127Bologna, Italy
B. Portolano
Affiliation:
Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Viale delle Scienze, Ed. 4, 90128Palermo, Italy
L. Fontanesi*
Affiliation:
Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, 40127Bologna, Italy
*
†E-mail: luca.fontanesi@unibo.it
Get access

Abstract

Reggiana is an autochthonous cattle breed reared mainly in the province of Reggio Emilia, located in the North of Italy. Reggiana cattle (originally a triple-purpose population largely diffused in the North of Italy) are characterised by a typical solid red coat colour. About 2500 cows of this breed are currently registered to its herd book. Reggiana is now considered a dual-purpose breed even if it is almost completely dedicated to the production of a mono-breed branded Protected Designation of Origin Parmigiano-Reggiano cheese, which is the main driver of the sustainable conservation of this local genetic resource. In this study, we provided the first overview of genomic footprints that characterise Reggiana and define the diversity of this local cattle breed. A total of 168 Reggiana sires (all bulls born over 35 years for which semen was available) and other 3321 sires from 3 cosmopolitan breeds (Brown, Holstein and Simmental) were genotyped with the Illumina BovineSNP50 panel. ADMIXTURE analysis suggested that Reggiana breed might have been influenced, at least in part, by the other three breeds included in this study. Selection signatures in the Reggiana genome were identified using three statistical approaches based on allele frequency differences among populations or on properties of haplotypes segregating in the populations (fixation index (FST); integrated haplotype score; cross-population extended haplotype homozygosity). We identified several regions under peculiar selection in the Reggiana breed, particularly on bovine chromosome (BTA) 6 in the KIT gene region, that is known to be involved in coat colour pattern distribution, and within the region of the LAP3, NCAPG and LCORL genes, that are associated with stature, conformation and carcass traits. Another already known region that includes the PLAG1 gene (BTA14), associated with conformation traits, showed a selection signature in the Reggiana cattle. On BTA18, a signal of selection included the MC1R gene that causes the red coat colour in cattle. Other selection sweeps were in regions, with high density of quantitative trait loci for milk production traits (on BTA20) and in several other large regions that might have contributed to shape and define the Reggiana genome (on BTA17 and BTA29). All these results, overall, indicate that the Reggiana genome might still contain several signs of its multipurpose and non-specialised utilisation, as already described for other local cattle populations, in addition to footprints derived by its ancestral origin and by its adaptation to the specialised Parmigiano-Reggiano cheese production system.

Keywords

autochthonous breedBos taurusgenomeselection signatureselection sweep
Type
Research Article
Information
animal , Volume 14 , Issue 5 , May 2020 , pp. 921 - 932
Copyright
© The Animal Consortium 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alexander, DH, Novembre, J and Lange, K 2009. Fast model-based estimation of ancestry in unrelated individuals. Genome Research 19, 1655–6164.CrossRefGoogle ScholarPubMed
Associazione Nazionale Allevatori Bovini di Razza Reggiana (ANABORARE) 2019. Retrieved on 1 June 2019 from https://www.razzareggiana.it/.Google Scholar
Bertolini, F, Galimberti, G, Calò, DG, Schiavo, G, Matassino, D and Fontanesi, L 2015. Combined use of principal component analysis and random forests identify population-informative single nucleotide polymorphisms: application in cattle breeds. Journal of Animal Breeding and Genetics 132, 346–356.CrossRefGoogle ScholarPubMed
Bertolini, F, Galimberti, G, Schiavo, G, Mastrangelo, S, Di Gerlando, R, Strillacci, MG, Bagnato, A, Portolano, B and Fontanesi, L 2018. Preselection statistics and Random Forest classification identify population informative single nucleotide polymorphisms in cosmopolitan and autochthonous cattle breeds. Animal 12, 12–19.10.1017/S1751731117001355CrossRefGoogle ScholarPubMed
Browning, BL and Browning, SR 2009. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. American Journal of Human Genetics 84, 210–223.10.1016/j.ajhg.2009.01.005CrossRefGoogle ScholarPubMed
Caroli, A, Chessa, S, Bolla, P, Budelli, E and Gandini, GC 2004. Genetic structure of milk protein polymorphisms and effects on milk production traits in a local dairy cattle. Journal of Animal Breeding and Genetics 121, 119–127.CrossRefGoogle Scholar
Chang, CC, Chow, CC, Tellier, LC, Vattikuti, S, Purcell, SM and Lee, JJ 2015. Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience 4, 7.CrossRefGoogle ScholarPubMed
Chen, EY, Tan, CM, Kou, Y, Duan, Q, Wang, Z, Meirelles, GV, Clark, NR and Ma’ayan, A 2013. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 128, 14.Google Scholar
Flori, L, Fritz, S, Jaffrezic, F, Boussaha, M, Gut, I, Heath, S, Foulley, JL and Gautier, M 2009. The genome response to artificial selection: a case study in dairy cattle. PLoS One 4, e6595.CrossRefGoogle ScholarPubMed
Fontanesi, L, Scotti, E and Russo, V 2010a. Analysis of SNPs in the KIT gene of cattle with different coat colour patterns and perspectives for using these markers for breed traceability and authentication of beef and dairy products. Italian Journal of Animal Science 9, e42.CrossRefGoogle Scholar
Fontanesi, L, Scotti, E and Russo, V 2012. Haplotype variability in the bovine MITF gene and association with piebaldism in Holstein and Simmental cattle breeds. Animal Genetics 43, 250–256.CrossRefGoogle ScholarPubMed
Fontanesi, L, Scotti, E, Samorè, AB, Bagnato, A and Russo, V 2015. Association of 20 candidate gene markers with milk production and composition traits in sires of Reggiana breed, a local dairy cattle population. Livestock Science 176, 14–21.CrossRefGoogle Scholar
Fontanesi, L, Tazzoli, M, Russo, V and Beever, J 2010b. Genetic heterogeneity at the bovine KIT gene in cattle breeds carrying different putative alleles at the spotting locus. Animal Genetics 41, 295–303.CrossRefGoogle ScholarPubMed
Gandini, G, Maltecca, C, Pizzi, F, Bagnato, A and Rizzi, R 2007. Comparing local and commercial breeds on functional traits and profitability: the case of Reggiana dairy cattle. Journal of Dairy Science 90, 2004–2011.CrossRefGoogle ScholarPubMed
Gautier, M, Klassmann, A and Vitalis, R 2017. rehh 2.0: a reimplementation of the R package rehh to detect positive selection from haplotype structure. Molecular Ecology Resources 17, 78–90.CrossRefGoogle Scholar
Gautier, M and Naves, M 2011. Footprints of selection in the ancestral admixture of a New World Creole cattle breed. Molecular Ecology 20, 3128–3143.10.1111/j.1365-294X.2011.05163.xCrossRefGoogle ScholarPubMed
González-Rodríguez, A, Munilla, S, Mouresan, EF, Cañas-Álvarez, JJ, Díaz, C, Piedrafita, J, Altarriba, J, Baro, JÁ, Molina, A and Varona, L 2016. On the performance of tests for the detection of signatures of selection: a case study with the Spanish autochthonous beef cattle populations. Genetics Selection Evolution 48, 81.CrossRefGoogle ScholarPubMed
Gutiérrez-Gil, B, Arranz, JJ and Wiener, P 2015. An interpretive review of selective sweep studies in Bos taurus cattle populations: identification of unique and shared selection signals across breeds. Frontiers in Genetics 6, 167.Google ScholarPubMed
Hu, Z-L, Park, CA and Reecy, JM 2019. Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB. Nucleic Acids Research 47, D701–D710.CrossRefGoogle ScholarPubMed
Macciotta, NPP, Biffani, S, Bernabucci, U, Lacetera, N, Vitali, A, Ajmone-Marsan, P and Nardone, A 2017. Derivation and genome-wide association study of a principal component-based measure of heat tolerance in dairy cattle. Journal of Dairy Science 100, 4683–4697.CrossRefGoogle ScholarPubMed
Mariani, P and Russo, V 1971. Distribuzione delle varianti genetiche delle caseine e della b-lattoglobulina nelle vacche di razza Reggiana. Rivista di Zootecnia 44, 310–322.Google Scholar
Marras, G, Gaspa, G, Sorbolini, S, Dimauro, C, Ajmone-Marsan, P, Valentini, A, Williams, JL and Macciotta, NP 2015. Analysis of runs of homozygosity and their relationship with inbreeding in five cattle breeds farmed in Italy. Animal Genetics 46, 110–121.10.1111/age.12259CrossRefGoogle ScholarPubMed
Mastrangelo, S, Ciani, E, Ajmone-Marsan, P, Bagnato, A, Battaglini, L, Bozzi, R, Carta, A, Catillo, G, Cassandro, M, Casu, S, Ciampolini, R, Crepaldi, P, D’Andrea, M, Di Gerlando, R, Fontanesi, L, Longeri, M, Macciotta, NPP, Mantovani, R, Marletta, D, Matassino, D, Mele, M, Pagnacco, G, Pieramati, C, Portolano, B, Sarti, MF, Tolone, M and Pilla, F 2018a. Conservation status and historical relatedness of Italian cattle breeds. Genetics Selection Evolution 50, 35.CrossRefGoogle ScholarPubMed
Mastrangelo, S, Sardina, MT, Tolone, M, Di Gerlando, R, Sutera, AM, Fontanesi, L and Portolano, B 2018b. Genome-wide identification of runs of homozygosity islands and associated genes in local dairy cattle breeds. Animal 12, 2480–2488.10.1017/S1751731118000629CrossRefGoogle ScholarPubMed
Mastrangelo, S, Tolone, M, Di Gerlando, R, Fontanesi, L, Sardina, MT and Portolano, B 2016. Genomic inbreeding estimation in small populations: evaluation of runs of homozygosity in three local dairy cattle breeds. Animal 10, 746–754.CrossRefGoogle ScholarPubMed
Rocha, D, Billerey, C, Samson, F, Boichard, D and Boussaha, M 2014. Identification of the putative ancestral allele of bovine single-nucleotide polymorphisms. Journal of Animal Breeding and Genetics 131, 483–486.CrossRefGoogle ScholarPubMed
Rothammer, S, Seichter, D, Förster, M and Medugorac, I 2013. A genome-wide scan for signatures of differential artificial selection in ten cattle breeds. BMC Genomics 14, 908.CrossRefGoogle ScholarPubMed
Russo, V, Fontanesi, L, Scotti, E, Tazzoli, M, Dall’Olio, S and Davoli, R 2007. Analysis of melanocortin 1 receptor (MC1R) gene polymorphisms in some cattle breeds: their usefulness and application for breed traceability and authentication of Parmigiano Reggiano cheese. Italian Journal of Animal Science 6, 257–272.CrossRefGoogle Scholar
Sabeti, PC, Varilly, P, Fry, B, Lohmueller, J, Hostetter, E, Cotsapas, C, Xie, X, Byrne, EH, McCarroll, SA, Gaudet, R, Schaffner, SF, Lander, ES; International HapMap Consortium, Frazer, KA, Ballinger, DG, Cox, DR, Hinds, DA, Stuve, LL, Gibbs, RA, Belmont, JW, Boudreau, A, Hardenbol, P, Leal, SM, Pasternak, S, Wheeler, DA, Willis, TD, Yu, F, Yang, H, Zeng, C, Gao, Y, Hu, H, Hu, W, Li, C, Lin, W, Liu, S, Pan, H, Tang, X, Wang, J, Wang, W, Yu, J, Zhang, B, Zhang, Q, Zhao, H, Zhao, H, Zhou, J, Gabriel, SB, Barry, R, Blumenstiel, B, Camargo, A, Defelice, M, Faggart, M, Goyette, M, Gupta, S, Moore, J, Nguyen, H, Onofrio, RC, Parkin, M, Roy, J, Stahl, E, Winchester, E, Ziaugra, L, Altshuler, D, Shen, Y, Yao, Z, Huang, W, Chu, X, He, Y, Jin, L, Liu, Y, Shen, Y, Sun, W, Wang, H, Wang, Y, Wang, Y, Xiong, X, Xu, L, Waye, MM, Tsui, SK, Xue, H, Wong, JT, Galver, LM, Fan, JB, Gunderson, K, Murray, SS, Oliphant, AR, Chee, MS, Montpetit, A, Chagnon, F, Ferretti, V, Leboeuf, M, Olivier, JF, Phillips, MS, Roumy, S, Sallée, C, Verner, A, Hudson, TJ, Kwok, PY, Cai, D, Koboldt, DC, Miller, RD, Pawlikowska, L, Taillon-Miller, P, Xiao, M, Tsui, LC, Mak, W, Song, YQ, Tam, PK, Nakamura, Y, Kawaguchi, T, Kitamoto, T, Morizono, T, Nagashima, A, Ohnishi, Y, Sekine, A, Tanaka, T, Tsunoda, T, Deloukas, P, Bird, CP, Delgado, M, Dermitzakis, ET, Gwilliam, R, Hunt, S, Morrison, J, Powell, D, Stranger, BE, Whittaker, P, Bentley, DR, Daly, MJ, de Bakker, PI, Barrett, J, Chretien, YR, Maller, J, McCarroll, S, Patterson, N, Pe’er, I, Price, A, Purcell, S, Richter, DJ, Sabeti, P, Saxena, R, Schaffner, SF, Sham, PC, Varilly, P, Altshuler, D, Stein, LD, Krishnan, L, Smith, AV, Tello-Ruiz, MK, Thorisson, GA, Chakravarti, A, Chen, PE, Cutler, DJ, Kashuk, CS, Lin, S, Abecasis, GR, Guan, W, Li, Y, Munro, HM, Qin, ZS, Thomas, DJ, McVean, G, Auton, A, Bottolo, L, Cardin, N, Eyheramendy, S, Freeman, C, Marchini, J, Myers, S, Spencer, C, Stephens, M, Donnelly, P, Cardon, LR, Clarke, G, Evans, DM, Morris, AP, Weir, BS, Tsunoda, T, Johnson, TA, Mullikin, JC, Sherry, ST, Feolo, M, Skol, A, Zhang, H, Zeng, C, Zhao, H, Matsuda, I, Fukushima, Y, Macer, DR, Suda, E, Rotimi, CN, Adebamowo, CA, Ajayi, I, Aniagwu, T, Marshall, PA, Nkwodimmah, C, Royal, CD, Leppert, MF, Dixon, M, Peiffer, A, Qiu, R, Kent, A, Kato, K, Niikawa, N, Adewole, IF, Knoppers, BM, Foster, MW, Clayton, EW, Watkin, J, Gibbs, RA, Belmont, JW, Muzny, D, Nazareth, L, Sodergren, E, Weinstock, GM, Wheeler, DA, Yakub, I, Gabriel, SB, Onofrio, RC, Richter, DJ, Ziaugra, L, Birren, BW, Daly, MJ, Altshuler, D, Wilson, RK, Fulton, LL, Rogers, J, Burton, J, Carter, NP, Clee, CM, Griffiths, M, Jones, MC, McLay, K, Plumb, RW, Ross, MT, Sims, SK, Willey, DL, Chen, Z, Han, H, Kang, L, Godbout, M, Wallenburg, JC, L’Archevêque, P, Bellemare, G, Saeki, K, Wang, H, An, D, Fu, H, Li, Q, Wang, Z, Wang, R, Holden, AL, Brooks, LD, McEwen, JE, Guyer, MS, Wang, VO, Peterson, JL, Shi, M, Spiegel, J, Sung, LM, Zacharia, LF, Collins, FS, Kennedy, K, Jamieson, R and Stewart, J. 2007. Genome-wide detection and characterization of positive selection in human populations. Nature 449, 913–918.CrossRefGoogle ScholarPubMed
Scheet, P and Stephens, M 2006. A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. American Journal of Human Genetics 78, 629–644.CrossRefGoogle ScholarPubMed
Takasuga, A 2016. PLAG1 and NCAPG-LCORL in livestock. Animal Science Journal 87, 159–167.CrossRefGoogle ScholarPubMed
Utsunomiya, YT, Milanesi, M, Utsunomiya, ATH, Torrecilha, RBP, Kim, ES, Costa, MS, Aguiar, TS, Schroeder, S, do Carmo, AS, Carvalheiro, R, Neves, HHR, Padula, RCM, Sussai, TS, Zavarez, LB, Cipriano, RS, Caminhas, MMT, Hambrecht, G, Colli, L, Eufemi, E, Ajmone-Marsan, P, Cesana, D, Sannazaro, M, Buora, M, Morgante, M, Liu, G, Bickhart, D, Van Tassell, CP, Sölkner, J, Sonstegard, TS and Garcia, JF 2017. A PLAG1 mutation contributed to stature recovery in modern cattle. Scientific Reports 7, 17140.CrossRefGoogle ScholarPubMed
Voight, BF, Kudaravalli, S, Wen, X and Pritchard, JK 2006. A map of recent positive selection in the human genome. PLoS Biology 4, e72.CrossRefGoogle ScholarPubMed
Wright, S 1951. The genetical structure of populations. Annals of Eugenetics 15, 323–354.CrossRefGoogle ScholarPubMed
Zhao, F, McParland, S, Kearney, F, Du, L and Berry, DP 2015. Detection of selection signatures in dairy and beef cattle using high-density genomic information. Genetics Selection Evolution 47, 49.CrossRefGoogle ScholarPubMed
Supplementary material: File

Bertolini et al. supplementary material

Figures S1-S2 and Tables S1-S5

Download Bertolini et al. supplementary material(File)
File 289.3 KB