Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-16T09:24:18.321Z Has data issue: false hasContentIssue false

Genome-wide identification of runs of homozygosity islands and associated genes in local dairy cattle breeds

Published online by Cambridge University Press:  26 March 2018

S. Mastrangelo*
Affiliation:
Dipartimento Scienze Agrarie, Alimentari e Forestali, Università degli Studi di Palermo, 90128 Palermo, Italy
M. T. Sardina
Affiliation:
Dipartimento Scienze Agrarie, Alimentari e Forestali, Università degli Studi di Palermo, 90128 Palermo, Italy
M. Tolone
Affiliation:
Dipartimento Scienze Agrarie, Alimentari e Forestali, Università degli Studi di Palermo, 90128 Palermo, Italy
R. Di Gerlando
Affiliation:
Dipartimento Scienze Agrarie, Alimentari e Forestali, Università degli Studi di Palermo, 90128 Palermo, Italy
A. M. Sutera
Affiliation:
Dipartimento Scienze Agrarie, Alimentari e Forestali, Università degli Studi di Palermo, 90128 Palermo, Italy
L. Fontanesi
Affiliation:
Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, 40127 Bologna, Italy
B. Portolano
Affiliation:
Dipartimento Scienze Agrarie, Alimentari e Forestali, Università degli Studi di Palermo, 90128 Palermo, Italy
*
Get access

Abstract

Runs of homozygosity (ROH) are widely used as predictors of whole-genome inbreeding levels in cattle. They identify regions that have an unfavorable effect on a phenotype when homozygous, but also identify the genes associated with traits of economic interest present in these regions. Here, the distribution of ROH islands and enriched genes within these regions in four dairy cattle breeds were investigated. Cinisara (71), Modicana (72), Reggiana (168) and Italian Holstein (96) individuals were genotyped using the 50K v2 Illumina BeadChip. The genomic regions most commonly associated with ROHs were identified by selecting the top 1% of the single nucleotide polymorphisms (SNPs) most commonly observed in the ROH of each breed. In total, 11 genomic regions were identified in Cinisara and Italian Holstein, and eight in Modicana and Reggiana, indicating an increased ROH frequency level. Generally, ROH islands differed between breeds. The most homozygous region (>45% of individuals with ROH) was found in Modicana on chromosome 6 within a quantitative trail locus affecting milk fat and protein concentrations. We identified between 126 and 347 genes within ROH islands, which are involved in multiple signaling and signal transduction pathways in a wide variety of biological processes. The gene ontology enrichment provided information on possible molecular functions, biological processes and cellular components under selection related to milk production, reproduction, immune response and resistance/susceptibility to infection and diseases. Thus, scanning the genome for ROH could be an alternative strategy to detect genomic regions and genes related to important economic traits.

Type
Research Article
Copyright
© The Animal Consortium 2018 

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

Barrett, JC, Fry, B, Maller, J and Daly, MJ 2005. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263265.Google Scholar
Cheng, HC, Zhang, FW, Deng, CY, Jiang, CD, Xiong, YZ, Li, FE and Lei, MG 2007. NNAT and DIRAS3 genes are paternally expressed in pigs. Genetics Selection Evolution 39, 599607.Google Scholar
Cohen, M, Reichenstein, M, Everts-van der Wind, A, Heon-Lee, J, Shani, M, Lewin, HA, Weller, JI, Ron, M and Seroussi, E 2014. Cloning and characterization of FAM13A1-a gene near a milk protein QTL on BTA6: evidence for population-wide linkage disequilibrium in Israeli Holsteins. Genomics 84, 374383.Google Scholar
Connor, EE, Sonstegard, TS, Kahl, S, Bennett, GL and Snelling, WM 2003. The bovine type I iodothyronine deiodinase (DIO1) gene maps to chromosome 3. Animal Genetics 34, 233234.Google Scholar
Ferenčaković, M, Hamzić, E, Gredler, B, Solberg, TR, Klemetsdal, G, Curik, I and Sölkner, J 2013a. Estimates of autozygosity derived from runs of homozygosity: empirical evidence from selected cattle populations. Journal of Animal Breeding and Genetics 130, 286293.Google Scholar
Ferenčaković, M, Solkner, J and Curik, I 2013b. Estimating autozygosity from high-throughput information: effects of SNP density and genotyping errors. Genetics Selection Evolution 45, 42.Google Scholar
Flori, L, Fritz, S, Jaffrézic, 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.Google Scholar
Gaspa, G, Marras, G, Sorbolini, S, Ajmone-Marsan, P, Williams, JL, Valentini, A, Dimauro, C and Macciotta, NNP 2014. Genome-wide homozygosity in Italian Holstein cattle using HD panel. In Proceedings of the 10th World Congress of Genetics Applied to Livestock Production, 17 to 22 August, Vancouver, BC, Canada.Google Scholar
Gibson, J, Morton, N and Collins, A 2006. Extended tracts of homozygosity in outbred human populations. Human Molecular Genetics 15, 789795.Google Scholar
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 Scholar
Huang, W, Peñagaricano, F, Ahmad, KR, Lucey, JA, Weigel, KA and Khatib, H 2012. Association between milk protein gene variants and protein composition traits in dairy cattle. Journal of Dairy Science 95, 440449.Google Scholar
Kim, ES, Cole, JB, Huson, H, Wiggans, GR, Van Tassell, CP, Crooker, BA, Liu, G, Da, Y and Sonstegard, TS 2013. Effect of artificial selection on runs of homozygosity in U.S. Holstein cattle. PLoS One 8, e80813.Google Scholar
Kommadath, A, Woelders, H, Beerda, B, Mulder, HA, de Wit, AA, Veerkamp, RF, te Pas, MF and Smits, MA 2011. Gene expression patterns in four brain areas associate with quantitative measure of estrous behavior in dairy cows. BMC Genomics 12, 200.Google Scholar
Kukučková, V, Moravčíková, N, Ferenčaković, M, Simčič, M, Mészáros, G, Sölkner, S, Trakovická, A, Kadlečík, O, Curik, I and Kasarda, R 2017. Genomic characterization of Pinzgau cattle: genetic conservation and breeding perspectives. Conservation Genetics. 18, 893910.Google Scholar
Li, H, Wang, Z, Moore, SS, Schenkel, FS and Stothard, P 2010. Genome-wide scan for positional and functional candidate genes affecting milk production traits in Canadian Holstein Cattle. In Proceedings of the 9th World Congress of Genetics Applied to Livestock Production, 1 to 6 August, Leipzig, Germany.Google Scholar
Li, D, Xie, X, Wang, J, Bian, Y, Li, Q, Gao, X and Wang, C 2015. MiR-486 regulates lactation and targets the PTEN gene in cow mammary glands. PLoS One 10, e0118284.Google Scholar
Ma, L, O’Connell, JR, VanRaden, PM, Shen, B, Padhi, A, Sun, C, Bickhart, DM, Cole, JB, Null, DJ, Liu, GE, Da, Y and Wiggans, GR 2015. Cattle sex-specific recombination and genetic control from a large pedigree analysis. PLoS Genetics 11, e1005387.Google Scholar
Mastrangelo, S, Saura, M, Tolone, M, Salces-Ortiz, J, Di Gerlando, R, Bertolini, F, Fontanesi, L, Sardina, MT, Serrano, M and Portolano, B 2014. The genome-wide structure of two economically important indigenous Sicilian cattle breeds. Journal of Animal Science 92, 48334842.Google Scholar
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, 746754.Google Scholar
Mastrangelo, S, Tolone, M, Sardina, MT, Sottile, G, Sutera, AM, Di Gerlando, R and Portolano, B 2017. Genome-wide scan for runs of homozygosity identifies potential candidate genes associated with local adaptation in Valle del Belice sheep. Genetics Selection Evolution 49, 84.Google Scholar
Mészáros, G, Boison, SA, Pérez O’Brien, AM, Ferenčaković, M, Curik, I, Da Silva, MV, Utsunomiya, YT, Garcia, JF and Sölkner, J 2015. Genomic analysis for managing small and endangered populations: a case study in Tyrol Grey cattle. Frontiers in Genetics 6, 173.Google Scholar
Metzger, J, Karwath, M, Tonda, R, Beltran, S, Águeda, L, Gut, M, Gut, IG and Distl, O 2015. Runs of homozygosity reveal signatures of positive selection for reproduction traits in breed and non-breed horses. BMC Genomics 16, 764.Google Scholar
Mi, H, Muruganujan, A and Thomas, PD 2013. PANTHER in: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees. Nucleic Acids Research 41, D377D386.Google Scholar
Moore, SG, Pryce, JE, Hayes, BJ, Chamberlain, AJ, Kemper, KE, Berry, DP, McCabe, M, Cormican, P, Lonergan, P, Fair, T and Butler, ST 2016. Differentially expressed genes in endometrium and corpus luteum of Holstein cows selected for high and low fertility are enriched for sequence variants associated with fertility. Biology of Reproduction 94, 19.Google Scholar
Nayeri, S, Sargolzaei, M, Abo-Ismail, MK, Miller, S, Schenkel, F, Moore, SS and Stothard, P 2016. Genome-wide association study for lactation persistency, female fertility, longevity, and lifetime profit index traits in Holstein dairy cattle. Journal of Dairy Science 100, 12461258.Google Scholar
Nothnagel, M, Lu, T, Kayser, M and Krawczak, M 2009. Genomic and geographic distribution of SNP-defined runs of homozygosity in Europeans. Human Molecular Genetics 19, 29272935.Google Scholar
Ogorevc, J, Kunej, T, Razpet, A and Dovc, P 2009. Database of cattle candidate genes and genetic markers for milk production and mastitis. Animal Genetics 40, 832851.Google Scholar
Olsen, HG, Meuwissen, THE, Nilsen, H, Svendsen, M and Lien, S 2008. Fine mapping of quantitative trait loci on bovine chromosome 6 affecting calving difficulty. Journal of Dairy Science 91, 43124322.Google Scholar
Peripolli, E, Munari, DP, Silva, MVGB, Lima, ALF, Irgang, R and Baldi, F 2016. Runs of homozygosity: current knowledge and applications in livestock. Animal Genetics 48, 255271.Google Scholar
Pimentel, ECG, Bauersachs, S, Tietze, M, Simianer, H, Tetens, J, Thaller, G, Reinhardt, F, Wolf, E and König, S 2011. Exploration of relationships between production and fertility traits in dairy cattle via association studies of SNPs within candidate genes derived by expression profiling. Animal Genetics 42, 251262.Google Scholar
Purcell, S, Neale, B, Todd-Brown, K, Thomas, L, Ferreira, MA, Bender, D, Maller, J, Sklar, P, de Bakker, PI, Daly, MJ and Sham, PC 2007. PLINK: a tool set for whole genome association and population-based linkage analyses. The American Journal of Human Genetics 81, 559575.Google Scholar
Purfield, DC, Berry, DP, McParland, S and Bradley, DG 2012. Runs of homozygosity and population history in cattle. BMC Genetics 13, 70.Google Scholar
Purfield, DC, McParland, S, Wall, E and Berry, DP 2017. The distribution of runs of homozygosity and selection signatures in six commercial meat sheep breeds. PLoS One 12, e0176780.Google Scholar
Qanbari, S, Gianola, D, Hayes, B, Schenkel, F, Miller, S, Moore, S, Thaller, G and Simianer, H 2011. Application of site and haplotype-frequency based approaches for detecting selection signatures in cattle. BMC Genomics 12, 318.Google Scholar
Qanbari, S, Pausch, H, Jansen, S, Somel, M, Strom, TM, Fries, R, Nielsen, R and Simianer, H 2014. Classic selective sweeps revealed by massive sequencing in cattle. PLoS Genetics 10, e1004148.Google Scholar
Qanbari, S, Pimentel, ECG, Tetens, J, Thaller, G, Lichtner, P, Sharifi, AR and Simianer, H 2010. A genome-wide scan for signatures of recent selection in Holstein cattle. Animal Genetics 41, 377389.Google Scholar
Ramey, H, Decker, J, McKay, S, Rolf, M, Schnabel, R and Taylor, J 2013. Detection of selective sweeps in cattle using genome-wide SNP data. BMC Genomics 14, 382.Google Scholar
Rincon, G, Islas-Trejo, A, Castillo, AR, Bauman, DE, German, BJ and Medrano, JF 2012. Polymorphisms in genes in the SREBP1 signalling pathway and SCD are associated with milk fatty acid composition in Holstein cattle. Journal of Dairy Research 79, 6675.Google Scholar
Sahana, G, Guldbrandtsen, B, Thomsen, B and Lund, MS 2013. Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle. Animal Genetics 44, 620626.Google Scholar
Sölkner, J, Ferenčaković, M, Karimi, Z, Perez O’Brien, AM, Mészáros, G, Eaglen, S, Boison, SA and Curik, I 2014. Extremely non-uniform: patterns of runs of homozygosity in bovine Populations. In Proceedings, 10th World Congress of Genetics Applied to Livestock Production, 17 to 22 August, Vancouver, BC, Canada.Google Scholar
Szmatola, T, Gurgul, A, Ropka-Molik, K, Jasielczuck, I, Zabek, T and Bugno-Poniewierska, M 2016. Charateristics of runs of homozygosity in selected cattle breeds maintained in Poland. Livestock Science 188, 7280.Google Scholar
Weikard, R, Widmann, P, Buitkamp, J, Emmerling, R and Kuehn, C 2012. Revisiting the quantitative trait loci for milk production traits on BTA6. Animal Genetics 43, 318323.Google Scholar
Zhang, Q, Boichard, D, Hoeschele, I, Ernst, C, Eggen, A, Murkve, B, Pfister-Genskow, M, Witte, LA, Grignola, FE, Uimari, P, Thaller, G and Bishop, MD 1998. Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree. Genetics 149, 19591973.Google Scholar
Zhang, Q, Calus, MP, Guldbrandtsen, B, Lund, MS and Sahana, G 2015a. Estimation of inbreeding using pedigree, 50k SNP chip genotypes and full sequence data in three cattle breeds. BMC Genetics 16, 88.Google Scholar
Zhang, Q, Guldbrandtsen, B, Bosse, M, Lund, MS and Sahana, G 2015b. Runs of homozygosity and distribution of functional variants in the cattle genome. BMC Genomics 16, 542.Google Scholar
Zheng, X, Ju, Z, Wang, J, Li, Q, Huang, J, Zhang, A, Zhong, J and Wang, C 2011. Single nucleotide polymorphisms, haplotypes and combined genotypes of LAP3 gene in bovine and their association with milk production traits. Molecular Biology Reports 38, 40534061.Google Scholar
Supplementary material: File

Mastrangelo et al. supplementary material

Mastrangelo et al. supplementary material 1

Download Mastrangelo et al. supplementary material(File)
File 19.7 KB
Supplementary material: File

Mastrangelo et al. supplementary material

Mastrangelo et al. supplementary material 2

Download Mastrangelo et al. supplementary material(File)
File 78.5 KB