ردیابی نشانه های انتخاب مثبت مرتبط با صفات مهم اقتصادی در نژادهای گوسفند ایرانی (زندی) و مصری (بارکی و راهمنی) با استفاده از روش hapFLK

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، گروه علوم دامی، دانشکده کشاورزی و محیط زیست، دانشگاه اراک

2 استادیار، گروه علوم دامی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران

3 دانشیار، گروه علوم دامی، دانشکده کشاورزی و محیط زیست، دانشگاه اراک

چکیده

انتخاب طبیعی و مصنوعی در جهت افزایش فراوانی جهش­های جدیدی که در برخی از جمعیت­ها مفید هستند باعث بر جای گذاشتن نشانه­هایی در سطح ژنوم می­شود. هدف از پژوهش حاضر، شناسایی نشانه­های انتخاب بین نژادهای گوسفند بومی ایران با نژادهای مصری بود. بدین منظور از اطلاعات 96 رأس گوسفند زندی و 107 رأس گوسفند مصری (59 رأس بارکی و 48 رأس راهمنی) استفاده شد. پس از اجرای مراحل مختلف کنترل کیفیت داده­ها، برای شناسایی نشانه­های انتخاب از روش آماری hapFLK به ­وسیله نرم­افزارhapFLK  نسخه 4/1 استفاده شد. ژن­های کاندیدا با استفاده از چندشکلی­های تک نوکئوتیدی (SNP­) که در بازه­ 1/0 درصد بالای ارزش hapFLK، واقع شده بودند با استفاده از برنامه BioMart شناسایی شدند. سپس عملکرد زیستی ژن­ها با استفاده از پایگاه اطلاعاتی PANTHER بررسی شده و برای تفسیر عملکرد ژن­های کاندیدا از پایگاه­های برخط GeneCards و UniProtKB استفاده شد. نتایج حاصل از hapFLK نشان داد که در مقایسه­ جمعیت گوسفند بومی زندی با نژادهای مصر،ی هفت ناحیه ژنومی روی کروموزوم­های یک، دو (سه منطقه)، 10، 25 و 26 شناسایی شدند. بررسی ژن­های گزارش شده در این مناطق نشان داد که در داخل یا مجاورت این نواحی، ژن­های DNAJB4، FNDC3B، GULP1، ACVR1 و FGF9 قرار داشتند. ژن­های موجود در این مناطق با سیستم ایمنی، سازگاری، تعداد بره متولد شده و رشد عضلات مرتبط هستند. نتایج این تحقیق می­تواند منبع اطلاعاتی ارزشمندی در زمینه شناسایی مناطق ژنومی مرتبط با صفات در نژادهای مختلف گوسفند فراهم آورد. به هر حال، جهت شناسایی دقیق این ژن­ها و جایگاه­های کنترل کننده صفات کمّی یا QTLها لازم است مطالعات پیوستگی و عملکردی بیشتری انجام شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Genomic scan for positive selection signatures associated with economically important traits in Iranian (Zandi) and Egyptian (Barki and Rahmani) sheep breeds using hapFLK method

نویسندگان [English]

  • H. Mohammadi 1
  • H. Moradi Shahrebabak 2
  • A. H. Khaltabadi Farahani 3
1 Assistant Professor, Department of Animal Science, Faculty of Agriculture and Environmental Sciences, University of Arak, Arak, Iran
2 Assistant Professor, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
3 Associate Professor, Department of Animal Science, Faculty of Agriculture and Environmental Sciences, Arak University, Arak, Iran
چکیده [English]

Introduction: Artificial and natural selection not only increases the frequency of new-useful mutations but also remains some signals throughout the genome. Since these regions often control economically important traits, identifying and tracking these regions is the most important subject in animal genetics. Also, natural and artificial selection related to adaptation and economic traits, such as litter size, results in changes at the genomic level which leads to the appearance of selection signatures. Several tests including the linkage disequilibrium-based approach, site frequency spectrum, and population differentiation-based approach have been developed to explore the footprints of selection in the genome. Domestication and selection have significantly changed the behavioral and phenotypic traits in modern domestic animals. The selection of animals by humans left detectable signatures on the genome of modern sheep. The identification of these signals can help us to improve the genetic characteristics of economically important traits in sheep. Over the last decade, interest in the detection of genes or genomic regions that are targeted by selection has been growing. Identifying signatures of selection can provide valuable insights about the genes or genomic regions that are or have been under selection pressure, which in turn leads to a better understanding of genotype-phenotype relationships. One of the best ways to understand physiological processes is to analyze gene regulation networks. Identification of genes involved in economic traits as molecular markers in breeding is of special importance. Gene regulation networks enable the researcher to study all of the genes together. This study aimed to identify selection signature regions and candidate genes related to adaptation and the number of lambs born.
Materials and methods: To identify the signatures of selection in Iranian native sheep and Egyptian breeds, genomic information of 96 native sheep (including 96 Zandi) and 107 Egyptian sheep (including 59 Barki and 48 Rahmani) were used. The genomic information of foreign breeds was extracted from the Dryad database (https://dryad.com/articles/dataset). To determine the genotype of the samples, Illumina Bead Chip 50K was used. Quality control was conducted using the Plink software. The markers or individuals were excluded from the further study based on the following criteria: unknown chromosomal or physical location, call rate <0.95, missing genotype frequency >0.05, minor allele frequency (MAF) < 0.05, and a P-value for Hardy–Weinberg equilibrium test less than 10-6. After the quality control of the data, the hapFLK statistical method, with hapFLK v1.4 software, was used to identify selection signatures. The genomic version of the Oar_v4.0 database in NCBI was used for detecting the genomic position of single nucleotide polymorphisms (SNPs) in the sheep genome. Candidate genes were identified by SNPs located at 0.1% upper range of hapFLK using BioMart software in ensemble 109. Then, using the PANTHER database, the general biological function of the genes was checked. At this stage, it is assumed that genes that belong to a functional class can be considered as a group of genes that have some specific and common characteristics, and the QTLs in the selected region were extracted using the Animal Genome database, and the genes were compared with other research. GeneCards (http://www.genecards.org) and UniProtKB (http://www.uniprot.org) databases were also used to interpret the function of the obtained genes.
Results and discussion: Based on the results of hapFLK, by comparing the Zandi population with Egyptian breeds (Barki and Rahmani), seven genomic regions on chromosomes 1, 2 (three regions), 10, 25, and 26 were identified. Candidate genes of DNAJB4, FNDC3B, GULP1, ACVR1, and FGF9 were in these regions. Further investigation using bioinformatics tools showed these genomic regions overlapped with the immune system, adaptation, litter size, and lipid and muscle metabolism.
Conclusions: The results of this study may provide an important source to facilitate the identification of genomic regions and then, the genes affecting economically important traits in the sheep industry. However, it will be necessary to carry out more association and functional studies to demonstrate the implications of these genes. Therefore, in subsequent studies with more samples and more breeds of domestic and wild sheep in Iran, a better understanding of candidate genes for important economic traits in domestic and wild species would be achieved.

کلیدواژه‌ها [English]

  • Selection
  • Genome scan
  • Litter size
  • Adaptation
  • Sheep
Asadollahpour Nanaei, H., Kharrati-Koopaee, H., & Esmailizadeh A. (2022). Genetic diversity and signatures of selection for heat tolerance and immune response in Iranian native chickens. BMC Genomics, 23(1): 224. doi: 10.1186/s12864-022-08434-7
Azizpour, N., Khaltabadi Farahani, A. H., Moradi, M., & Mohammadi, H. (2020). Genome-wide association study based on gene-set enrichment analysis associated with milk yield in Holstein cattle. Journal of Animal Science Research, 30(1), 79-92. doi: 10.22034/AS.2021.46637.1621 [In Persian]
Bonhomme, M., Chevalet, C., Servin, B., Boitard, S., Abdallah, J., Blott, S., & SanCristobal M. (2010). Detecting selection in population trees: the Lewontin and Krakauer test extended. Genetics, 186(1), 241-262. doi: 10.1534/genetics.104.117275
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015). Second-Generation PLINK: Rising to the challenge of larger and richer datasets. Gigascience, 4, 7. doi: 10.1186/s13742-015-0047-8
Chen, Q., Wang, Z., Sun, J., Huang, Y., Hanif, Q., Liao, Y., & Lei, C. (2020). Identification of genomic characteristics and selective signals in a Du'an goat flock. Animals (Basel), 10(6), 994. doi: 10.3390/ani10060994
El-Halawany, N., Zhou, X., Al-Tohamy, A. F., El-Sayd, Y. A., Shawky, A. E., Michal, J. J., & Jiang, Z. (2016). Genome-wide screening of candidate genes for improving fertility in Egyptian native Rahmani sheep. Animal Genetics, 47(4), 513. doi: 10.1111/age.12437
Fariello, M. I., Boitard, S., Naya, H., SanCristobal, M., & Servin, B. (2013). Detecting signatures of selection through haplotype differentiation among hierarchically structured populations. Genetics, 193(3), 929-941. doi: 10.1534/genetics.112.147231.
Giacopelli, F., Cappato, S., Tonachini, L., Mura, M., Di Lascio, S., Fornasari, D., Ravazzolo, R., & Bocciardi, R. (2013). Identification and characterization of regulatory elements in the promoter of ACVR1, the gene mutated in Fibrodysplasia Ossificans Progressiva. Orphanet Journal of Rare Diseases, 8, 145. doi: 10.1186/1750-1172-8-145
Gutiérrez-Gil, B., Pérez, J., Alvarez, L., Martínez-Valladares, M., de la Fuente, L. F., Bayón, Y., Meana, A., San Primitivo, F., Rojo-Vázquez, F. A., & Arranz, J. J. (2009). Quantitative trait loci for resistance to trichostrongylid infection in Spanish Churra sheep. Genetics Selection Evolution, 41(1), 46. doi: 10.1186/1297-9686-41-46
Han, B., Wang, H., Zhang, J., & Tian, J. (2020). FNDC3B is associated with ER stress and poor prognosis in cervical cancer. Oncology Letters, 19(1), 406-414. doi: 10.3892/ol.2019.11098
Isabelle, C. M., & Picard, B. (2016). Expression marker-based strategy to improve beef quality. The Scientific World Journal, 3, 1-11. doi: 10.1155/2016/2185323
Khalifa, E. I., Ahmed, M. E., Hafez, Y. H., El-Zolaky, O. A., Bahera, K. M., & Abido, A. A. (2013). Age at puberty and fertility of Rahmani sheep fed on biological inoculated corn silage. Annals of Agricultural Sciences, 58(2), 163-172.  doi.org/10.1016/j.aoas.2013.07.003
Khaltabadi Farahani, A. H., Mohammadi, H., & Moradi, H. (2020). Gene set enrichment analysis using genome-wide association study to identify genes and pathways associated with litter size in various sheep breeds. Animal Production, 22(3), 325-335. doi:10.22059/jap.2020.292715.623468 [In Persian]
Kijas, J. W., Lenstra, J. A., Hayes, B., Boitard, S., Porto Neto, L. R., San Cristobal, M., Servin, B., McCulloch, R., Whan, V., McEwan, J., & Dalrymple, B. (2012). International Sheep Genomics Consortium Members. Genome-wide analysis of the world's sheep breeds reveals high levels of historic mixture and strong recent selection. PLoS Biology, 10(2), e1001258. doi: 10.1371/journal.pbio.1001258
Leroy, G., Baumung, R., Boettcher, P., Besbes, B., From, T., & Hoffmann, I. (2018). Animal genetic resources diversity and ecosystem services. Global Food Security, 17, 84-91. doi: 10.1002/ecy.3745
McBride, D., Carré, W., Sontakke, S. D., Hogg, C. O., & Law, A. (2012). Identification of miRNAs associated with the follicular-luteal transition in the ruminant ovary. Reproduction, 144, 221-233. doi: 10.1530/REP-12-0025
Mohammadi, H., Khaltabadi Farahani, H. K., Moradi, M. H., Mastrangelo, S., Di Gerlando, R., Sardina, M. T., Scatassa, M. L., Portolano, B., & Tolone, M. (2022). Weighted single-step genome-wide association study uncovers known and novel candidate genomic regions for milk production traits and somatic cell score in Valle del Belice dairy sheep. Animals (Basel), 12(9), 1155. doi: 10.3390/ani12091155
Patiabadi, Z., Razmkabir, M., Esmailizadeh Koshkoiyeh, A., Moradi, M. H., & Rashidi, A. (2023). Genomic scanning of selection signature in Iranian skin and wool sheep using FST unbiased estimator and hapFLK methods. Animal Production Research12(2), 85-103. doi: 10.22124/ar.2023.22903.1721 [In Persian]
Rostamzadeh Mahdabi, E., Esmailizadeh, A., Ayatollahi Mehrgardi, A., & Asadi Fozi, M. (2021). A genome-wide scan to identify signatures of selection in two Iranian indigenous chicken ecotypes. Genetics Selection Evolution, 53(1), 72. doi: 10.1186/s12711-021-00664-9
Sabeti, P. C., Schaffner, S. F., Fry, B., Lohmueller, J., Varilly, P., Shamovsky, O., & Lander, E. (2006). Positive natural selection in the human lineage. Science, 312(5780), 1614-1620. doi: 10.1126/science.1124309
Saravanan, K. A., Panigrahi, M., Kumar, H., Parida, S., Bhushan, B., Gaur, G. K., Dutt, T., Mishra, B. P., & Singh, R. K. (2021). Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds. Genomics, 113(3), 955-963. doi: 10.1016/j.ygeno.2021.02.009
Shimizu, T., Jayawardana, B. C., Nishimoto, H., Kaneko, E., Tetsuka, M., & Miyamoto, A. (2006). Involvement of the bone morphogenetic protein/receptor system during follicle development in the bovine ovary: hormonal regulation of the expression of bone morphogenetic protein 7 (BMP-7) and its receptors (ACTRI and ALK-2). Molecular and Cellular Endocrinology, 249, 78-83. doi: 10.1016/j.mce.2006.01.015
Tenghe, A. M. M., Bouwman, A. C., Berglund, B., Strandberg, E., de Koning, D. J., & Veerkamp, R. F. (2016). Genome wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle. Journal of Dairy Science, 99(7), 5470-5485. doi: 10.3168/jds.2015-10533
Wang, X., Liu, J., Zhou, G., Guo, J., Yan, H., Niu, Y., Li, Y., Yuan, C., Geng, R., Lan, X., An, X., Tian, X., Zhou, H., Song, J., Jiang, Y., & Chen, Y. (2016). Whole-genome sequencing of eight goat populations for the detection of selection signatures underlying production and adaptive traits. Scientific Reports, 6, 38932. doi: 10.1038/srep38932
Waineina, R. W., Okeno, T. O., Ilatsia, E. D., & Ngeno, K. (2022). Selection signature analyses revealed genes associated with adaptation, production, and reproduction in selected goat breeds in Kenya. Frontiers in Genetics, 13, 858923. doi: 10.3389/fgene.2022.858923
Wang, P., Li, X., Zhu, Y., Wei, J., Zhang, C., Kong, Q., Nie, X., Zhang, Q., & Wang, Z. (2022). Genome-wide association analysis of milk production, somatic cell score, and body conformation traits in Holstein cows. Frontiers in Veterinary Science, 9, 932034. doi: 10.3389/fvets.2022.932034
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(1), 12984. doi: 10.1038/s41598-018-31304-w
Zhang, Y. E. (2017). Non-Smad signaling pathways of the TGF- family. Cold Spring Harbor Perspectives in Biology, 9, 56-71. doi: 10.1101/cshperspect.a02212
Zhang, Z., Sui, Z., Zhang, J., Li, Q., Zhang, Y., Wang, C., Li, X., & Xing, F. (2022). Identification of signatures of selection for litter size and pubertal initiation in two sheep populations. Animals (Basel), 12(19), 2520. doi: 10.3390/ani12192520
Zhao, F., Deng, T., Shi, L., Wang, W., Zhang, Q., Du, L., & Wang, L. (2020). Genomic scan for selection signature reveals fat deposition in Chinese indigenous sheep with extreme tail types. Animals (Basel), 10(5), 773. doi: 10.3390/ani10050773