آمار
| تعداد نشریات | 26 |
| تعداد شمارهها | 447 |
| تعداد مقالات | 4,557 |
| تعداد مشاهده مقاله | 5,380,005 |
| تعداد دریافت فایل اصل مقاله | 3,580,078 |
Investigation of selection signatures provides key insights into genetic differences between Holstein and Sarabi dairy cattle breeds | ||
| Journal of Livestock Science and Technologies | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 22 تیر 1404 | ||
| نوع مقاله: Research Article (Regular Paper) | ||
| شناسه دیجیتال (DOI): 10.22103/jlst.2025.25072.1617 | ||
| نویسندگان | ||
| Parisa Biabani1؛ Hassan Mehrabani Yeganeh1؛ Hossein Moradi Shahrbabak* 1؛ Mahdi Mokhber* 2 | ||
| 1Department of Animal Science, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Karaj, 7787131587, Iran | ||
| 2Assistant Professor, Department of Animal Science, Faculty of Agricultural Science, Urmia university, Urmia, Iran | ||
| چکیده | ||
| Abstract Selection increases the frequency of beneficial alleles in subpopulations, leaving genomic signatures associated with genes and QTLs controlling economic traits. Genomic data from 60 Holstein and 72 Sarabi cattle were analyzed to identify these selection signatures. Quality control and data filtering were performed using PLINK_1.9 software. The genetic group was identified using three complementary methods: principal component analysis (PCA) with PLINK 1.9, discriminant analysis of principal components (DAPC) implemented in the adegenet package in R, and Admixture analysis conducted with Admixture version 1.23. Subsequently, FST, XP-EHH, and Rsb statistics were used to identify selection signatures. The chromosomal positions of the selected regions were aligned with the bovine genome data (ARS-UCD1.2 Bos Taurus) from the Ensembl Biomart database. Genetic analyses revealed the presence of two distinct genetic groups with different origins. In this study, 16 genomic regions were identified using the FST method, and 18 regions were determined using XP-EHH and Rsb methods, covering approximately 17.5 and 24 Mbp of the bovine genome, respectively. Based on gene ontology analyses, these regions contained coding genes related to key biological processes such as immune response, muscle growth, reproduction, and milk production. Several genes, including MYO1A, STAT6, and PRKAA1, were associated with traits such as carcass quality, fertility, and metabolic processes. The analysis of identified QTLs confirmed the presence of economically important traits, such as growth rate, disease resistance, meat quality, and milk composition. Regions on Bos taurus autosome (BTA) 6 and 10 were identified as key areas for immune-related genes, while milk production traits were observed on regions of BTA 5, 7, and 20. Overall, these findings provide valuable insights into the genetic basis of important economic traits in cattle and can contribute to future breeding programs aimed at improving productivity and disease resistance. | ||
| کلیدواژهها | ||
| dairy cattle؛ selection sweep؛ genomic array؛ population differentiation index | ||
| مراجع | ||
|
Alexander, D.H., Novembre, J., Lange, K., 2009. Fast model-based estimation of ancestry in unrelated individuals. Genome Research 19, 1655-1664.
Almeida, O.A.C., Moreira, G.C.M., Rezende, F.M., Boschiero, C., de Oliveira Peixoto, J., Ibelli, A.M.G., Ledur, M.C., de Novais, F.J., Coutinho, L.L., 2019. Identification of selection signatures involved in performance traits in a paternal broiler line. BMC Genomics 20, 1-20.
Álvarez, I., Fernández, I., Traoré, A., Pérez-Pardal, L., Menéndez-Arias, N.A., Goyache, F., 2020. Genomic scan of selective sweeps in Djallonké (West African Dwarf. sheep shed light on adaptation to harsh environments. Scientific Reports 10(1), 2824: 1-13.
Azizi, P., Moradi Shahrbabak, M., Moradi Shahrbabak, H., Mokhber, M., 2024. Identification of genomic regions related to litter size with divergent selection between Iranian indigenous sheep breeds and Romanov high reproductive sheep breed. Iranian Journal of Animal Science. doi: 10.22059/ijas.2024.369473.653982.
Bahbahani, H., Musa, H.H., Wragg, D., Shuiep, E.S., Almathen, F., Hanotte, O., 2019. Genome diversity and signatures of selection for production and performance traits in dromedary camels. Frontiers in Genetics 10, 893 (1-14).
Bertolini, F., Servin, B., Talenti, A., Rochat, E., Kim, E.S., Oget, C., Palhière, I., Crisà, A., Catillo, G., Steri, R., 2018. Signatures of selection and environmental adaptation across the goat genome post-domestication. Genetics Selection Evolution 50, 1-24.
Biabani, P., Yeganeh, H.M., Shahrbabak, H.M., Mokhber, M., 2022. Detection of genetic differences between Holstein and Iranian north-west indigenous hybrid cattles using genomic data. Research on Animal Production 13(37): 175-186.
Browning, S.R., Browning, B.L., 2007. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. The American Journal of Human Genetics 81, 1084-1097.
Chen, N., Cai, Y., Chen, Q., Li, R., Wang, K., Huang, Y., Hu, S., Huang, S., Zhang, H., Zheng, Z., 2018. Whole-genome resequencing reveals world-wide ancestry and adaptive introgression events of domesticated cattle in East Asia. Nature Cmmunications 9, 2337: 1-13.
Cole, J.B., Wiggans, G.R., Ma, L., Sonstegard, T.S., Lawlor, T.J., Crooker, B.A., Van Tassell, C.P., Yang, J., Wang, S., Matukumalli, L.K., 2011. Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary US Holstein cows. BMC Genomics 12, 1-17.
Consortium, B.H., Gibbs, R.A., Taylor, J.F., Van Tassell, C.P., Barendse, W., Eversole, K.A., Gill, C.A., Green, R.D., Hamernik, D.L., Kappes, S.M., 2009. Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds. Science 324, 528-32.
Cui, H.-X., Liu, R.-R., Zhao, G.-P., Zheng, M.-Q., Chen, J.-L., Wen, J., 2012. Identification of differentially expressed genes and pathways for intramuscular fat deposition in pectoralis major tissues of fast-and slow-growing chickens. BMC Genomics 13, 1-12.
Dadpasand, M., Zamani, P., Mirhoseini, S.Z., 2013. Genetic diversity among Sarabi, Holstein, and Simmental cattle breeds using microsatellite markers. Iranian Journal of Applied Animal Science 3(3), 559-564.
FAO. 2015. The Second Report on the State of the World’s Animal Genetic Resources for Food and Agriculture. Food and Agriculture Organization of the United Nations. http://www.fao.org/3/a-i4787e/index.html
García-Ruiz, A., Cole, J.B., VanRaden, P.M., Wiggans, G.R., Ruiz-López, F.J., Van Tassell, C.P., 2016. Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection. Proceedings of the National Academy of Sciences 113(28): E3995-E4004. https://doi.org/10.1073/pnas.1519061113
Gautier, M., Laloë D., Moazami-Goudarzi, K., 2010. Insights into the genetic history of French cattle from dense SNP data on 47 worldwide breeds. PloS One 5, e13038.
Gautier, M., Vitalis, R., 2012. rehh: an R package to detect footprints of selection in genome-wide SNP data from haplotype structure. Bioinformatics 28, 1176-7.
Grilz-Seger, G., Neuditschko, M., Ricard, A., Velie, B., Lindgren, G., Mesarič, M., Cotman, M., Horna, M., Dobretsberger, M., Brem, G., 2019. Genome-wide homozygosity patterns and evidence for selection in a set of European and near eastern horse breeds. Genes 10, 491, 1-23.
Groeneveld, L., Lenstra, J., Eding, H., Toro, M., Scherf, B., Pilling, D., Negrini, R., Finlay, E., Jianlin, H., Groeneveld, E., 2010. Genetic diversity in farm animals–a review. Animal Genetics 41, 6-31.
Gutiérrez-Gil, B., Arranz, J.J., 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), 1-20.
Jombart, T., Ahmed, I., 2011. adegenet 1.3-1: New tools for the analysis of genome-wide SNP data. Bioinformatics 27(21), 3070–3071. https://doi.org/10.1093/bioinformatics/btr521.
Jombart, T., 2008. Adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24(11), 1403-1405.
Kijas, J.W., Ortiz, J.S., McCulloch, R., James, A., Brice, B., Swain, B., Tosser‐Klopp, G., Consortium, I.G.G., 2013. Genetic diversity and investigation of polledness in divergent goat populations using 52 088 SNPs. Animal Genetics 44, 325-35.
Kukučková, V., Moravčíková, N., Ferenčaković, M., Simčič, M., Mészáros, G., Sölkner, J., Trakovická, A., Kadlečík, O., Curik, I., Kasarda, R., 2017. Genomic characterization of Pinzgau cattle: genetic conservation and breeding perspectives. Conservation Genetics 18, 893-910.
Leal-Gutierrez, J.D., Rezende, F.M., Elzo, M.A., Johnson, D., Penagaricano, F., Mateescu, R.G., 2018. Structural equation modeling and whole-genome scans uncover chromosome regions and enriched pathways for carcass and meat quality in beef. Frontiers in Genetics 9, 532.
Li, C., Sun, D., Zhang, S., Wang, S., Wu, X., Zhang, Q., Liu, L., Li, Y., Qiao L., 2014. Genome wide association study identifies 20 novel promising genes associated with milk fatty acid traits in Chinese Holstein. PloS One 9, e96186.
Maiorano, A.M., Lourenco, D.L., Tsuruta, S., Ospina, A.M.T., Stafuzza, N.B., Masuda, Y., Filho, A.E.V., Cyrillo, J.N.d.S.G., Curi, R.A., Silva, J.A.I.d.V., 2018. Assessing genetic architecture and signatures of selection of dual purpose Gir cattle populations using genomic information. PloS One 13, e0200694.
Medugorac, I., Medugorac, A., Russ I., Veit-Kensch, C.E., Taberlet, P., Luntz, B., Mix, H.M., Förster, M., 2009. Genetic diversity of European cattle breeds highlights the conservation value of traditional unselected breeds with high effective population size. Molecular Ecology 18, 3394-410.
Mirzaee, M., Ghavi Hossein-Zadeh, N., Shadparvar, A.A., Shahrbabak, H.M., 2019. Genetic diversity in Sarabi cattle: An ancestral Iranian breed. Journal of Livestock Science and Technologies 7(1), 59-66. https://doi.org/10.22103/jlst.2019.12322.1231
Mokhber, M., Moradi Shahrbabak. M., Sadeghi, M., Moradi Shahrbabak, H., Williams, J., 2015. Genome-wide survey of signature of positive selection in Khuzestani and Mazandrani buffalo breeds. Iranian Journal of Animal Science 46, 119-31.
Mokhber, M., Moradi-Shahrbabak, M., Sadeghi, M., Moradi-Shahrbabak, H., Stella, A., Nicolzzi, E., Rahmaninia, J., Williams, J.L., 2018. A genome-wide scan for signatures of selection in Azeri and Khuzestani buffalo breeds. BMC Genomics 19, 1-9.
Moradi, M.H., Nejati-Javaremi, A., Moradi-Shahrbabak, M., Dodds, K.G., McEwan, J.C., 2012. Genomic scan of selective sweeps in thin and fat tail sheep breeds for identifying of candidate regions associated with fat deposition. BMC Genetics 13, 1-15.
Moravčikova, N., Trakovicka, A., Kadlečik, O., Kasarda, R., 2019. Genomic signatures of selection in cattle through variation of allele frequencies and linkage disequilibrium. Journal of Central European Agriculture 20, 576-80.
Nolte, W., Thaller, G., Kuehn, C., 2019. Selection signatures in four German warmblood horse breeds: Tracing breeding history in the modern sport horse. PloS One 14, e0215913.
Peters, S., Kizilkaya, K., Garrick, D., Fernando, R., Reecy, J., Weaber, R., Silver, G., Thomas, M., 2012. Bayesian genome-wide association analysis of growth and yearling ultrasound measures of carcass traits in Brangus heifers. Journal of Animal Science 90, 3398-3409.
Price, A.L., Patterson, N.J., Plenge, R.M., Weinblatt, M.E., Shadick, N.A., Reich, D., 2006. Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics 38, 904-909.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A., Bender, D., Maller, J., Sklar, P., De Bakker, P.I., Daly, M.J., 2007. PLINK: a tool set for whole-genome association and population-based linkage analyses. The American Journal of Human Genetics 81, 559-575.
Qanbari, S., Pimentel, E., Tetens, J., Thaller, G., Lichtner, P., Sharifi, A.R., Simianer, H., 2010. A genome‐wide scan for signatures of recent selection in Holstein cattle. Animal Genetics 41, 377-389.
Qanbari, S., Simianer, H., 2014. Mapping signatures of positive selection in the genome of livestock. Livestock science 166, 133-143.
Qanbari, S., Strom, T.M., Haberer, G., Weigend, S., Gheyas, A.A., Turner, F., Burt, D.W., Preisinger, R., Gianola, D., Simianer, H., 2012. A high resolution genome-wide scan for significant selective sweeps: an application to pooled sequence data in laying chickens. PloS One 7, e49525.
Rincon, G., Farber, E., Farber, C., Nkrumah, J., Medrano, J., 2009. Polymorphisms in the STAT6 gene and their association with carcass traits in feedlot cattle. Animal Genetics 40, 878-882.
Ripley, B.D., 2001. The R project in statistical computing. MSOR connections. The Newsletter of the LTSN Maths, Stats & OR Network 1, 23-25.
Saatchi, M., Beever, J.E., Decker, J.E., Faulkner, D.B., Freetly, H.C., Hansen, S.L., Yampara-Iquise, H., Johnson, K.A., Kachman, S.D., Kerley M.S., 2014. QTLs associated with dry matter intake, metabolic mid-test weight, growth and feed efficiency have little overlap across 4 beef cattle studies. BMC Genomics 15, 1-14.
Sabeti, P.C., Varilly, P., Fry, B., Lohmueller, J., Hostetter, E., Cotsapas, C., Xie, X.H., Byrne, E.H., McCarroll, S.A., Gaudet, R., et al., 2007. Genome-wide detection and characterization of positive selection in human populations. Nature 449(7164), U912-U913.
Salehi, R., Javanmard, A., Mokhber, M., Alijani, S., 2023. Genomic Selection Signatures in Two French and Swedish Holstein Cattle Breeds Provide Evidence for Several Potential Candidate Genes Linked to Economic Traits. Iranian Journal of Applied Animal Science 13, 677-684.
Sempéré, G., Moazami-Goudarzi, K., Eggen, A., Laloë, D., Gautier, M., Flori, L., 2015. WIDDE: a Web-Interfaced next generation database for genetic diversity exploration, with a first application in cattle. BMC Genomics 16, 1-8.
Sherman, B.T., Hao, M., Qiu, J., Jiao, X., Baseler, M.W., Lane, H.C., Imamichi, T., Chang, W., 2022. DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Research 50, 216-221.
Signer-Hasler, H., Burren, A., Neuditschko, M., Frischknecht, M., Garrick, D., Stricker, C., Gredler, B., Bapst, B., Flury, C., 2017. Population structure and genomic inbreeding in nine Swiss dairy cattle populations. Genetics Selection Evolution 49, 1-13.
Simianer, H., Ma, Y., Qanbari, S., 2014. Statistical problems in livestock population genomics. In: Proceedings of the 10th World Congress on Genetics Applied to Livestock Production, pp. 17-22.
Smad, G., 2020. GeneCards—The human gene database https://www. genecards. org/cgi-bin/carddisp. pl? gene= SMAD6&keywords= smad6. Accessed.
Stella, A., Ajmone-Marsan, P., Lazzari, B., Boettcher, P., 2010. Identification of selection signatures in cattle breeds selected for dairy production. Genetics 185, 1451-61.
Sun, T., Huang, G., Wang, Z., Teng, S.-h., Cao, Y., Sun, J., Hanif, Q., Chen, N., Lei, C., Liao Y., 2020. Selection signatures of Fuzhong Buffalo based on whole-genome sequences. BMC Genomics 21, 1-10.
Tang, K., Thornton, K.R., Stoneking, M., 2007. A new approach for using genome scans to detect recent positive selection in the human genome. PLoS Biology 5, 1587–1602.
Uzzaman, M.R., Edea, Z., Bhuiyan, M.S.A., Walker, J., Bhuiyan, A., Kim K.S., 2014. Genome-wide single nucleotide polymorphism analyses reveal genetic diversity and structure of wild and domestic cattle in Bangladesh. Asian-Australasian journal of Animal Sciences 27(10), 1381-1386.
Wang, X., Ran, X., Niu, X., Huang, S., Li, S., Wang, J., 2022. Whole-genome sequence analysis reveals selection signatures for important economic traits in Xiang pigs. Scientific Reports 12, 11823, 1-17.
Weir, B.S., Cockerham, C.C., 1984. Estimating F-statistics for the analysis of population structure. Evolution 38(6), 1358-1370.
Yurchenko, A.A., Daetwyler, H.D., Yudin, N., Schnabel, R.D., Vander Jagt, C.J., Soloshenko, V., Lhasaranov, B., Popov, R., Taylor, J.F., Larkin, D.M., 2018. Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation. Scientific Reports 8 (Article No.12984), 1-16.
Zhang, J., Haider, S., Baran, J., Cros, A., Guberman, J.M., Hsu, J., Liang, Y., Yao, L., Kasprzyk, A., 2011. BioMart: a data federation framework for large collaborative projects. Database 2011, bar038.
Zhang, W., Yang, M., Zhou, M., Wang, Y., Wu, X., Zhang, X., Ding, Y., Zhao, G., Yin, Z., Wang, C., 2020. Identification of signatures of selection by whole-genome resequencing of a Chinese native pig. Frontiers in Genetics 11, 566255: 1-11. | ||
|
آمار تعداد مشاهده مقاله: 21 |
||