تجزیه و تحلیل غنی سازی مجموعه های ژنی جهت شناسایی مناطق ژنومی مرتبط با سازگاری محیطی در برخی از نژادهای گوسفندان ایرانی

نوع مقاله : مقاله پژوهشی

نویسندگان

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

2 گروه علوم دامی، دانشکدگان کشاورزی و منابع طبیعی، دانشگاه تهران

3 گروه علوم دامی، دانشکده کشاورزی و منابع طبیعی، دانشگاه شهید باهنر کرمان

چکیده

پژوهش حاضر با هدف مطالعه ارتباط ژنومی (GWAS) بر اساس تجزیه و تحلیل غنی­سازی مجموعه‌­های ژنی جهت شناسایی جایگاه­‌های ژنی مؤثر بر صفات سازگاری با شرایط محیطی با استفاده از اطلاعات آرایه­‌های ژنومیOvine high-density 600K  Illumina انجام شد. به­این منظور از اطلاعات ژنوتیپی 139 رأس گوسفندان بومی ایرانی شامل نژادهای کرمانی (15 رأس)، سنجابی (14 رأس)، لری­بختیاری (15 رأس)، قزل (15 رأس)، قره­گل (15 رأس)، سیاه­کبود (15 رأس)، کبوده شیراز (9 راس)، افشاری (14 رأس)، شال (15 رأس) و بلوچی (12 رأس) استفاده شد. ابتدا، تجزیه GWAS برای صفات مورد مطالعه در برنامه PLINK انجام شد. سپس، ژن­های معنی­داری که در داخل و یا 50 کیلوباز بالا و پایین­دست نشانگرهای معنی­دار قرار داشتند، شناسایی شدند. در نهایت، تفسیر مجموعه ژنی با هدف شناسایی عملکرد زیستی ژن­‌های نزدیک به مناطق انتخابی از مسیر پایگاه‌­های بیوانفورماتیکی مختلف انجام شد. نتایج نشان داد که به­ترتیب 2431،  2244 و 2145 نشانگر SNP با صفات سازگاری با شرایط محیطی گرمسیری-سردسیری، پراکنش در مناطق با ارتفاع بالا-پایین از سطح دریا و پوشش بدنی پشمی-پوستی در گوسفندان بومی ایران مرتبط هستند (05/0>P). با تجزیه و تحلیل غنی­سازی مجموعه­های ژنی، مسیرهای زیستی (و ژن­های کاندیدای) مربوط به پاسخ دفاعی به عفونت­های باکتریایی (HSPA4L، DNAJB4 و MSRB3)، تنظیم پاسخ ایمنی به­واسطه ایمونوگلوبولین­ها (IL27A، TRAF3IP2 و LY96)، تنظیم فرآیند سیستم رشد و اتصالات سلولی (BMP2، THBS1 و MYH10)، تنظیم اندازه ساختار آناتومی (FGF2 و ACTR3)، تنظیم استخوان­سازی و توسعه اندام (PTBP1 و TMEM117)، و رشد اپیدرم پوست و پشم (KRT71، KR27 و KR25) شناسایی شدند. در مجموع، نتایج تحقیق حاضر می­توانند دیدگاه جدیدی در رابطه با معماری ژنتیکی صفات سازگاری در برنامه­های اصلاح­نژادی گوسفندان کشور فراهم آورند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Gene-set enrichment analysis to identify genomic regions associated with environmental adaptation in some Iranian sheep breeds

نویسندگان [English]

  • A. Noroozi 1
  • M. H. Moradi 1 2
  • H. Mohammadi 1
  • A. H. Khaltabadi Farahani 1
  • A. K. Esmailizadeh 3
1 Department of Animal Science, Faculty of Agriculture and Environmental Sciences, Arak University, Arak, Iran
2 Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
3 Department of Animal Science, Faculty of Agriculture and Natural Resources, Shahid Bahonar University of Kerman, Kerman, Iran
چکیده [English]

Introduction: Environmental adaptations that allow different breeds to thrive in different ecological conditions are significant in sheep breeding. Understanding the genetic basis for such adaptations can greatly enhance breeding programs aimed at improving resilience and productivity. Various indigenous sheep breeds exhibit unique traits suited for their respective habitats in Iran. This study aimed to identify genomic loci associated with environmental adaptation through genome-wide association studies (GWAS) based on gene-set enrichment (GSE) analysis. By leveraging high-density single-nucleotide polymorphism (SNP) arrays, we explored the genetic mechanisms underlying thermotolerance, altitude adaptation, and coat type differentiation, which are critical for sustaining sheep production under Iran’s heterogeneous climates. These adaptations are particularly relevant given Iran’s diverse topography, where temperatures range from -20°C in mountainous regions to +50°C in deserts, creating strong selective pressures on local breeds.
Materials and methods: The Illumina HD ovine SNP600K BeadChip genomic arrays were utilized to analyze 139 animals from nine Iranian sheep breeds, namely Kermani (n=15), Sanjabi (n=14), Lori-Bakhtiari (n=15), Qezel (n=15), Gharagol (n=15), SiahKabod (n=15), GrayShiraz (n=9), Afshari (n=14), Shal (n=15), and Baluchi (n=12). Animals were grouped based on three adaptive traits: (1) tropical vs. cold climate resilience, (2) high vs. low altitude distribution, and (3) wool vs. skin coat type. Quality control filters included minor allele frequency (MAF) > 0.05, SNP call rate > 95%, and removal of markers with unknown genomic positions. To assess the relationship between specific traits and SNP variations across the genome, GWAS was conducted based on logistic regression models using PLINK software (v 1.9), with principal component analysis (PCA) to correct for population stratification. SNPs were assigned to respective genes based on their locations within the genomic sequence or a flanking region of 50 kb upstream and downstream of each significant SNP. Following this analysis, we employed various bioinformatics databases to interpret gene sets and ascertain their biological functions related to selected genomic regions.
Results and discussion: The results of the GWAS showed that 2431, 2244, and 2145 SNP markers were associated with adaptation to tropical-cold environmental conditions, distribution in areas with high-low height of sea level, and wool-skin body covering in Iranian indigenous sheep, respectively (P<0.05). Gene-set enrichment analysis identified the biological pathways (and candidate genes) of defense response to gram-positive bacterium (HSPA4L, DNAJB4, MSRB3), regulation of immunoglobulin mediated immune response (IL27A, TRAF3IP2, LY96), regulation of muscle system process and cell junction (BMP2, THBS1, MYH10), regulation of anatomical structure size (FGF2, ACTR3), regulation of ossification and organ growth (TMEM117, PTBP1), and skin epidermis development (KR25, KR27, KRT71). The pathways identified in the current study for adaptation traits in indigenous breeds played an important role in the regulation of the immune system, muscle structure development, osteoclast differentiation, body size, and regulation of wool growth. The insights gained from this study greatly extend our understanding of how specific genetic determinants contribute toward functional adaptations in Iranian sheep breeds under diverse environments. For example, the identification of HSPA4L in thermotolerance aligns with its known role in heat shock response, while novel candidates like TMEM117 may represent breed-specific adaptations. Some genes have also not been well-established in their biological function, and there may be potential mutual effects that are not yet understood in this context. Therefore, to determine the precise role of these genes, it is essential to conduct further comprehensive functional studies and biological system analyses.
Conclusions: In general, our findings provide valuable knowledge on genomic regions linked with vital adaptation traits among indigenous Iranian sheep breeds. The integration of GWAS and pathway analysis revealed not only expected candidates (e.g., KRT genes for wool) but also novel genes (e.g., LY96 for immunity) that broaden our understanding of genomic adaptability. These results may serve future research endeavors focused on dissecting genetic architectures underlying adaptability, particularly for marker-assisted selection in breeding programs. However, the study’s limitations, including sample size and the need for functional validation of candidate genes, highlight opportunities for future work. A pivotal component influencing successful breeding strategies aimed at improving these animals' resilience while considering changing global climates.

کلیدواژه‌ها [English]

  • Pathway analysis
  • Candidate gene
  • Iranian sheep
  • Genome-wide association analysis
Abdalla, E., Byrem, T., Weigel, K., & Rosa, G. (2016). Genome‐wide association mapping and pathway analysis of leukosis incidence in a US holstein cattle population. Animal Genetics, 47(4), 395-407. doi: 10.1111/age.12438
Abdoli, R., Mirhoseini, S. Z., Hossein-Zadeh, N. G., Zamani, P., Ferdosi, M. H., & Gondro, C. (2019a). Genome-wide association study of four composite reproductive traits in Iranian fat-tailed sheep. Reproduction, Fertility and Development31(6), 1127-1133. doi: 10.1071/RD18282
Abdoli, R., Mirhoseini, S. Z., Ghavi Hossein-Zadeh, N., Zamani, P., Moradi, M. H., Ferdosi, M. H., & Gondro, C. (2019b). Genome-wide association study of first lambing age and lambing interval in sheep. Small Ruminant Research, 178, 43-45. doi: 10.1016/J.SMALLRUMRES.2019.07.014
Amiri Roudbar, M., Mohammadabadi, M., Ayatollahi Mehrgardi, A., & Abdollahi Arpanahi, R. (2017). Estimates of variance components due to parent-of-origin effects for body weight in Iran-Black sheep. Small Ruminant Research, 141, 1-5. doi: 10.1016/j.smallrumres
An, B., Xu, L., Xia, J., Wang, X., Miao, J., Chang, T., Song, M., Ni, J., Xu, L., Zhang, L., Li, J., & Gao, H. (2020). Multiple association analysis of loci and candidate genes that regulate body size at three growth stages in Simmental beef cattle. BMC Genetics, 21(1), 32. doi: 10.1186/s12863-020-0837-6
Arora, R., Kaur, M., Kumar, A., Chhabra, P., Mir, M. A., Ahlawat, S., Singh, M. K., Sharma, R., & Gera, R. (2024). Skeletal muscle transcriptomics of sheep acclimated to cold desert and tropical regions identifies genes and pathways accentuating their diversity. International Journal of Biometeorology, 68(9), 1811-1821. doi: 10.1007/s00484-024-02708-3
Arzik, Y., Kizilaslan, M., Behrem, S., White, S. N., Piel, L. M., & Cinar, M. U. (2023). Genome-wide scan of wool production traits in akkaraman sheep. Genes14(3), 713. doi: 10.3390/genes14030713
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., Harris, M. A., Hill, D. P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J. C., Richardson, J. E., Ringwald, M., Rubin, G. M., & Sherlock, G. (2000). Gene ontology: Tool for the unification of biology. Nature Genetics, 25, 25-29. doi: 10.1038/75556
Chen, Z. H., Xu, Y. X., Xie, X. L., Wang, D. F., Aguilar-Gómez, D., Liu, G. J., Li, X., Esmailizadeh, A., Rezaei, V., Kantanen, J., Ammosov, I., Nosrati, M., Periasamy, K., Coltman, D. W., Lenstra, J. A., Nielsen, R., & Li, M. H. (2021). Whole-genome sequence analysis unveils different origins of European and Asiatic mouflon and domestication-related genes in sheep. Commun Biology, 4(1), 1307. doi: 10.1038/s42003-021-02817-4
Clancey, E., Kiser, J. N., & Moraes, J. G. N. (2019). Genome-wide association analysis and gene set enrichment analysis with SNP data identify genes associated with 305-day milk yield in Holstein dairy cows. Animal Genetics, 50, 254-258. doi: 10.1111/age.12792
Connell, P., Ballinger, C. A., Jiang, J., Wu, Y., Thompson, L. J., Hohfeld, J., & Patterson, C. (2001). The cochaperone CHIP regulates protein triagedecisions mediated by heat -shock proteins. Nature Cell Biology, 3, 93 -96. doi: 10.1038/35050618
Dadousis, C., Pegolo, S., Rosa, G., Gianola, D., Bittante, G., & Cecchinato, A. (2017). Pathway-based genome-wide association analysis of milk coagulation properties, curd firmness, cheese yield, and curd nutrient recovery in dairy cattle. Journal of Dairy Science, 100(2), 1223-1231. doi: 10.3168/jds.2016-11587
Dadousis, C., Pegolo, S., Rosa, G. J. M., Gianola, D., Bittante, G., & Cecchinato, A. (2017). Pathway-based genomewide association analysis of milk coagulation properties, curd firmness, cheese yield, and curd nutrient recovery in dairy cattle. Journal of Dairy Science, 100, 1223-1231. doi: 10.3168/jds.2016-11587
Devlin, B., & Roeder, K. (1999). Genomic control for association studies. Biometrics, 55, 997-1004. doi: 10.1111/j.0006-341x
Duan, X., An, B., Du, L., Chang, T., Liang, M., Yang, B. G., Xu, L., Zhang, L., Li, J. E. G., & Gao, H. (2021). Genome-wide association analysis of growth curve parameters in chinese simmental beef cattle. Animals, 11(1), 192. doi: 10.3390/ani11010192
Edea, Z., Dadi, H., Dessie, T., & Kim, K. S. (2019). Genomic signatures of high-altitude adaptation in Ethiopian sheep populations. Genes & Genomics41, 973-981. doi: 10.1007/s13258-019-00820-y
Esmaeilifard, S. M., Gholizadeh, M., Hafezian, S. H., & Abdollahi-Arpanahi, R. (2021). Genes and pathways affecting sheep productivity traits: genetic parameters, genome-wide association mapping, and pathway enrichment analysis. Frontiers in Genetics, 12, 710613. doi: 10.3389/fgene.2021.710613
Esmaeilifard, S. M., Hafezian, S. H., Gholizadeh, M., & Abdolahi-Arpanahi, R. (2019). Gene set enrichment analysis using genome-wide association study to identify genes and biological pathways associated with twinning in Baluchi sheep. Animal Production Research8(2), 63-80. doi: 10.22124/AR.2019.11948.1365 [In Persian]
Freitas, P. H., Wang, Y., Yan, P., Oliveira, H. R., Schenkel, F. S., Zhang, Y., Xu, Q., & Brito, L. F. (2021). Genetic diversity and signatures of selection for thermal stress in cattle and other two Bos species adapted to divergent climatic conditions. Frontiers in Genetics12, 604823. doi: 10.3389/fgene.2021.604823
Gaspar, D., Ginja, C., Carolino, N., Leão, C., Monteiro, H., Tábuas, L., Branco, S., Padre, L., Caetano, P., Romão, R., & Matos, C. (2024). Genome-wide association study identifies genetic variants underlying footrot in Portuguese Merino sheep. BMC Genomics25(1), 100.
Ghavi Hossein-Zadeh, N. (2024). An overview of recent technological developments in bovine genomics. Veterinary and Animal Science, 25, 100382. doi: 10.1016/J.VAS.2024.100382
Gholizadeh, M., Rahimi-Mianji, G., Nejati-Javaremi, A., De Koning, D. J., & Jonas, E. (2014). Genome wide association study to detect QTL for twinning rate in Baluchi sheep. Journal of Genetics93, 489-493. doi: 10.1186/s12864-024-10130-7
Gootwine, E. (2020). Invited review: Opportunities for genetic improvement toward higher prolificacy in sheep. Small Ruminant Research186, 106090. doi: 10.1016/j.smallrumres.2020.106090
Guo, T., Zhao, H., Yuan, C., Huang, S., Zhou, S., Lu, Z., Niu, C. E., Liu, J., Zhu, S., Yue, Y., & Yang, Y. (2021). Selective sweeps uncovering the genetic basis of horn and adaptability traits on fine-wool sheep in China. Frontiers in Genetics12, 604235. doi: 10.3389/fgene.2021.604235
Habimana, R., Ngeno, K., Okeno, T. O., Hirwa, C. A., Keambou Tiambo, C., & Yao, N. K. (2021). Genome-wide association study of growth performance and immune response to newcastle disease virus of indigenous chicken in Rwanda. Frontiers in Genetics, 12, 723980. doi: 10.3389/fgene.2021.723980
Han, Y., & Peñagaricano, F. (2016). Unravelling the genomic architecture of bull fertility in Holstein cattle. BMC Genetics, 17(1), 143. doi: 10.1186/s12863-016-0454-6
Huang, D.W., Sherman, B.T., & Lempicki, R.A. (2009). Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protocols, 4(1), 44-57. doi: 10.1038/nprot.2008.211
Igoshin, A., Yudin, N., Aitnazarov, R., Yurchenko, A. A., & Larkin, D. M. (2021). Whole-genome resequencing points to candidate DNA loci affecting body temperature under cold stress in Siberian cattle populations. Life11(9), 959. doi: 10.3390/life11090959
Jafarymanesh, A. R., Khaltabadi Farahani, A. H., Moradi, M. H., & Mohammadi, H. (2020). Gene-set enrichment analysis to identify genes and biological pathways associated with egg weight in the whole laying period. Journal of Agricultural Biotechnology, 12(3), 91-116. doi: 10.22103/JAB.2020.15255.1197 [In Persian]
Jombart, T., & Ahmed, I. (2011). New tools for the analysis of genome-wide SNP data. Bioinformatics, 27, 3070-3071. doi: 10.1093/bioinformatics/btr521
Jin, M., Lu, J., Fei, X., Lu, Z., Quan, K., Liu, Y., Chu, M., Di, R., Wei, C., & Wang, H. (2020). Selection signatures analysis reveals genes associated with high-altitude adaptation in Tibetan goats from Nagqu, Tibet. Animals10(9), 1599. doi: 10.3390/ani10091599
Jin, M., Wang, H., Liu, G., Lu, J., Yuan, Z., Li, T., Liu, E., Lu, Z., Du, L., & Wei, C. (2024). Whole-genome resequencing of Chinese indigenous sheep provides insight into the genetic basis underlying climate adaptation. Genetics Selection Evolution56(1), 26. doi: 10.1186/s12711-024-00880-z
Karimi, K., Farid, A. H., Myles, S., & Miar, Y. (2021). Detection of selection signatures for response to Aleutian mink disease virus infection in American mink. Scientific Reports11(1), 2944. doi: 10.1038/s41598-021-82522-8
Kaseja, K., Mucha, S., Yates, J., Smith, E., Banos, G., & Conington, J. (2023). Genome-wide association study of health and production traits in meat sheep. Animal17(10), 100968. doi: 10.1016/j.animal.2023.100968
Khalatabadi-Farahani, A. H., Mohammadi, H., & Moradi, M. H. (2020). Gene set enrichment analysis using genome-wide association study to identify genes and pathways associated with litter size in various sheep breeds. Journal of animal production, 22(3), 325-335. doi: 10.22059/jap.2020.292715.623468 [In Persian]
Khanzadeh, H., Ghavi Hossein-Zadeh, N., & Ghovvati, S. (2022). The statistical power of genome-wide association studies for threshold traits with different frequencies of causal variants. Genetica150(1), 51-57. doi: 10.1007/s10709-021-00140-8
Khare, S., Lawhon, S. D., Drake, K. L., Nunes, J. E. S., Figueiredo, J. F., Rossetti, C. A., Gull, T., Everts, R. E., Lewin, H. A., & Galindo, C. L. (2012). Systems biology analysis of gene expression during in vivo Mycobacterium avium paratuberculosis enteric colonization reveals role for immune tolerance. PLoS One, 8, e42127. doi: 10.1371/journal.pone.0042127
Kijas, J. W., Lenstra, B., Hayes, S., Boitard, L. R., & Porto, N. (2012). Genome wide analysis of the world’s sheep breeds reveals high levels of historic mixture and strong recent selection. PLoS Biology, 10, 1001258. doi: 10.1371/journal.pbio.1001258
Li, H., Wu, X. L., Tait, J. R. G., Bauck, S., Thomas, D. L., Murphy, T. W., & Rosa, G. J. M. (2020). Genome‐wide association study of milk production traits in a crossbred dairy sheep population using three statistical models. Animal Genetics51(4), 624-628. doi: 10.1111/age.12956
Li, X., Yuan, L., Wang, W., Zhang, D., Zhao, Y., Chen, J., Xu, D., Zhao, L., Li, F., & Zhang, X. (2022). Whole genome re-sequencing reveals artificial and natural selection for milk traits in East Friesian sheep. Frontiers in Veterinary Science9, 1034211. doi: 10.3389/fvets.2022.1034211
Liang, C. S., Kobiyama, A., Shimizu, A., Sasaki, T., Asakawa, S., Shimizu, N., & Watabe, S. (2007). Fast skeletal muscle myosin heavy chain gene cluster of medaka Oryzias latipes enrolled in temperature adaptation. Physiological Genomics29(2), 201-214. doi: 10.1152/physiolgenomics.00078.2006
Mastrangelo, S., Bahbahani, H., Moioli, B., Ahbara, A., Abri, M. A., & Almathen, F. (2019). Novel and known signals of selection for fat deposition in domestic sheep breeds from Africa and Eurasia. PloS ONE, 14, 0209632. doi: 10.1371/journal.pone.0209632
McLaren, R. J., Rogers, G. R., Davies, K. P., Maddox, J. F., & Montgomery, G. W. (1997). Linkage mapping of wool keratin and keratin-associated protein genes in sheep. Mammalian Genome, 8(12), 938–940. doi: 10.1007/s003359900616
Mi, H., & Thomas, P. (2009). PANTHER Pathway: an ontology-based pathway database coupled with data analysis tools. Methods in Molecular Biology, 563, 123-140. doi: 10.1007/978-1-60761-175-2_7
Mohammadi, H., Khalatabadi Farahani, A. H., Moradi, M. H., & Hajkhodadadi, I. (2022). Genome wide association study based on gene-set enrichment analysis of growth traits in a Chicken advanced intercross line. Journal of Animal Science Research, 31(3), 99-111. doi: 10.22034/AS.2021.46637.1621 [In Persian]
Mohammadi, H., Khaltabadi Farahani, A. H, & Moradi, M. H. (2023). Genome-wide association study based on gene-set enrichment analysis of economically important traits in Japanese quail. Animal Production Research12(1), 65-78. doi: 10.22124/AR.2023.20946.1657 [In Persian]
Mohammadi, H., Moradi, M. H., & Farahani, A. H. K. (2022). Genome-wide association study and pathway analysis for identifying the genes associated with coat color in Lori-Bakhtiari sheep breed. Iranian Journal of Animal Science, 53(3), 153-160. doi: 10.22059/IJAS.2022.329848.653846 [In Persian]
Mohammadi, H., & Sadeghi, M. (2010). Estimation of genetic parameters for growth and reproduction traits and genetic trends of growth traits in Zel sheep breed under rural production system. Iranian Journal of Animal Science, 41(3), 231-241. doi: 20.1001.1.20084773.1389.41.3.6.9 [In Persian]
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 Genomics19, 1-9. doi: 10.1186/s12864-018-4759-x
Mooney, M. A., & Wilmot, B. (2015). Gene Set Analysis: a step-by-step guide. American Journal of Medical Genetics, 168(7), 517-527. doi: 10.1002/ajmg.b.32328
Moradi, M. H., Nejati-Javaremi, A., Moradi-Shahrbabak, M., Dodds, K. G., Brauning, R., & McEwan, J. C. (2021). Hitchhiking mapping of candidate regions associated with fat deposition in iranian thin and fat tail sheep breeds suggests new insights into molecular aspects of fat tail selection. Animals, 12, 1423. doi: 10.3390/ani12111423
Moradi, M. H., Farahani, A. H., & Nejati-Javaremi, A. (2017). Genome-wide evaluation of effective population size in some Iranian sheep breeds using linkage disequilibrium information. Iranian Journal Animal Science, 48, 39-49. doi: 10.22059/IJAS.2017.213736.653464 [In Persian]
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, 10. doi: 10.1186/1471-2156-13-10
Pacheco, A., Banos, G., Lambe, N., McLaren, A., McNeilly, T. N., & Conington, J. (2024). Genome-wide association studies of parasite resistance, productivity and immunology traits in Scottish Blackface sheep. Animal18(2), 101069. doi: 10.1016/j.animal.2023.101069
Parsons, Y. M., Piper, L. R., & Cooper, D. W. (1994). Linkage relationships between keratin-associated protein (KRTAP) genes and growth hormone in sheep. Genomics, 20(3), 500-502. doi: 10.1006/geno.1994.1209
Pasandideh, M., Gholizadeh, M., & Rahimi‐Mianji, G. (2020). A genome‐wide association study revealed five SNPs affecting 8‐month weight in sheep. Animal Genetics, 51(6), 973-976. doi: 10.1111/age.12996
Patiabadi, Z., Razmkabir, M., EsmailizadehKoshkoiyeh, A., Moradi, M. H., Rashidi, A., & Mahmoudi, P. (2024). Whole-genome scan for selection signature associated with temperature adaptation in Iranian sheep breeds. PLoS ONE, 19(8), e0309023. doi: 10.1371/journal.pone.0309023
Pham, K., Frost, S., Parikh, K., Puvvula, N., Oeung, B., & Heinrich, E. C. (2022). Inflammatory gene expression during acute high‐altitude exposure. The Journal of Physiology600(18), 4169-4186. doi: 10.1113/JP282772
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., & Bender, D. (2007). PLINK: a toolset for whole-genome association and population-based linkage analysis. The American Journal of Human Genetics, 81, 559-575. doi: 10.1086/519795
Rastifar, M., Nejati-Javaremi, A., Moradi, M. H., & Abdollahi-Arpanahi, R. (2015). Identification of genomic regions associated with wool diameter in Iranian sheep breeds. Iranian Journal of Animal Science46(1), 65-72. doi: 10.22059/IJAS.2015.54592 [In Persian]
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. Genomics113(3), 955-963. doi: 10.1016/j.ygeno.2021.02.009
Senczuk, G., Criscione, A., Mastrangelo, S., Biscarini, F., Marletta, D., Pilla, F., Laloë, D., & Ciampolini, R. (2022). How geography and climate shaped the genomic diversity of Italian local cattle and sheep breeds. Animals, 12, 2198. doi: 10.3390/ani12172198
Tian, D., Han, B., Li, X., Liu, D., Zhou, B., Zhao, C., Zhang, N., Wang, L., Pei, Q., & Zhao, K. (2023). Genetic diversity and selection of Tibetan sheep breeds revealed by whole-genome resequencing. Animal Bioscience36(7), 991. doi: 10.5713/ab.22.0432
Vasu, M., Ahlawat, S., Chhabra, P., Sharm, U., Arora, R., Sharma, R., Mir, M. A., & Singh, M. K. (2024). Genetic insights into fiber quality, coat color and adaptation in Changthangi and Muzzafarnagri sheep: A comparative skin transcriptome analysis. Gene891, 147826. doi: 10.1016/j.gene.2023.147826
Veerkamp, R. F., Coffey, M. P., Berry, D. P., de Haas, Y., Strandberg, E., Bovenhuis, H., Calus, M. P. L., & Wall, E. (2012). Genome-wide associations for feed utilization complex in primiparous Holstein-Friesian dairy cows from experimental research herds in four European countries. Animal, 6, 1738–1749. doi: 10.1017/S1751731112001152
Wang, S., Dvorkin, D., & Da, Y. (2012). SNPEVG: a graphical tool for GWAS graphing with mouse clicks. BMC Bioinformatics13, 1-6. doi: 10.1186/1471-2105-13-319
Wang, S., Yi, X., Wu, M., Zhao, H., Liu, S., Pan, Y., Li, Q., Tang, X., Zhu, Y., & Sun, X. (2019). Detection of key gene InDels in TGF-β pathway and its relationship with growth traits in four sheep breeds. Animal Biotechnology, 32(2), 194-204. doi: 10.1080/10495398.2019.1675682
Wei, C., Wang, H., Liu, G., Zhao, F., Kijas, J. W., Ma, Y., Lu, J., Zhang, L. I., Cao, J., Wu, M., & Wang, G. (2016). Genome-wide analysis reveals adaptation to high altitudes in Tibetan sheep. Scientific Reports6(1), 26770. doi: 10.1038/srep26770
Wiener, P., Robert, C., Ahbara, A., Salavati, M., Abebe, A., Kebede, A., Wragg, D., Friedrich, J., Vasoya, D., Hume, D. A., & Djikeng, A. (2021). Whole-genome sequence data suggest environmental adaptation of Ethiopian sheep populations. Genome Biology and Evolution13(3), 014. doi: 10.1093/gbe/evab014
Yang, J. I., Li, W. R., Lv, F. H., He, S. G., Tian, S. L., Peng, W. F., Sun, Y. W., Zhao, Y. X., Tu, X. L., Zhang, M., & Xie, X. L. (2016). Whole-genome sequencing of native sheep provides insights into rapid adaptations to extreme environments. Molecular Biology and Evolution33(10), 2576-2592. doi: 10.1093/molbev/msw129
Young, M. D., Wakefield, M. J., Smyth, G. K., & Oshlack, A. (2010). Method gene ontology analysis for RNA-seq: Accounting for selection bias. Genome Biology, 11, 14-23. doi: 10.1186/gb-2010-11-2-r14
Yudin, N., & Larkin, D. M. (2019). Shared signatures of selection related to adaptation and acclimation in local cattle and sheep breeds from Russia. Russian Journal of Genetics55, 1008-1014. doi: 10.1134/S1022795419070159.
Zamani, P., Akhondi, M., & Mohammadabadi, M. (2015). Associations of inter-simple sequence repeat loci with predicted breeding values of body weight in sheep. Small Ruminant Research132, 123-127. doi:10.1016/j.smallrumres.2015.10.018
Zhang, H., Wang, Z., Wang, S., & Li, H. (2012). Progress of genome wide association study in domestic animals. Journal of Animal Science and Biotechnology, 3(1), 26. doi: 10.1186/2049-1891-3-26
Zhang, H., Zhuang, Z., Yang, M., Ding, R., Quan, J., Zhou, S., Gu, T., Xu, Z., Zheng, E., Cai, G., Yang, J., & Wu, Z. (2021). Genome-wide detection of genetic loci and candidate genes for body conformation traits in Duroc × Landrace × Yorkshire crossbred pigs. Frontiers in Genetics, 12, 664343. doi: 10.3389/fgene.2021.664343
Zhang, L., Liu, J., Zhao, F., Ren, H., Xu, L., Lu, J., Zhang, S., Zhang, X., Wei, C., Lu, G., & Zheng, Y. (2013). Genome-wide association studies for growth and meat production traits in sheep. PloS ONE8(6), e66569. doi: 10.1371/journal.pone.0066569
Zhuang, Z., Xu, L., Yang, J., Gao, H., Zhang, L., Gao, X., Li, J., & Zhu, B. (2020). Weighted single-step genome-wide association study for growth traits in chinese simmental beef cattle. Genes, 11(2), 189. doi: 10.3390/genes11020189