Identification of genomic regions related to litter size involving divergent selection in Iranian indigenous and high reproductive Romanov sheep breeds

Document Type : Research Paper

Authors

1 Department of Animal Science, Faculty of Agriculture, Universityof Tehran, Karaj. Iran.

2 Department of Animal Science, Faculty of Agriculture, University of Tehran. Karaj. Iran

3 Department of Animal Science, Faculty of Agriculture, Urmia University, Urmia. Iran.

Abstract

In order to identify genes related to reproductive performance under divergent selection in Iranian indigenous and high reproductive performance Romanov sheep breeds, the genomic data of 233 sheep were used. The genomeic data of Romanov sheep were obtained from the iSheep database and the genomic data of Iranian sheep was achieved from the database at https://disk.yandex.ru/d/3N2wEv0-9_NL0w. Data filtering and quality control, genetic differentiation index analysis (FST) and principal component analysis (PCA) were performed to determine genetic groups using PLINK 1.9 software. Following the final filtering, the genomic information of 488,752 common SNPs from autosomal chromosomes of 79 Romanov heads compared to 120 heads of nine Iranian indigenous sheep breeds to screening signature of selection. The ubiased FST (θ) estimator and XPEHH statistic were used to explore the signs of selection. The genes related to selected genomic regions were extracted using the BIOMART online database corresponding to areas in the sheep genome assembly (Oar 3.1). A total of 489 genes associated with the selected genomic regions (consisting of 0.1% of the studied markers) were identified. Investigation of the genomic regions under selection showed that out of all the identified genes related to the difference between the two studied groups, 7 genes were involved in biological pathways related to steroid synthesis and ovarian steroidogenesis that may be associated with litter size. Identifying this pathway and other complementary studies about genes involved in reproduction could be effective in designing breeding programs to improve reproductive performance.

Keywords

Main Subjects


Extended Abstract

Introduction

Around 12,000 BP, sheep (Ovis aries) were among the first animals domesticated by humans during the Neolithic Revolution. Iran has a good genetic diversity by having more than 30 breeds of sheep. Heep production plays a significant role in providing animal protein. These breeds are bred for meat and to a limited extent milk with thick wool, but are hardy and resilient in harsh environments. By development of molecular genetics, identification of selection signatures which reflects natural or artificial selection has become possible, and numerous methods have been developed in this regards. Using selection signature methods, we aimed to uncover adaptive selection signals, profile production types, and elucidate gene functions within selection patterns related to reproduction and litter size in sheep.

 

Materials and Methods

In order to identify genes related to reproductive performance with divergent selection between Iranian indigenous sheep breeds and high reproductive performance Romanov sheep breed, the genomic data of 233 sheep were used. The genomic data of Romanov sheep were obtained from the iSheep database and the genome of Iranian sheep was retrieved from the database at https://disk.yandex.ru/d/3N2wEv0-9_NL0w. Data filtering and quality control, genetic differentiation index analysis (FST) and principal component analysis (PCA) were performed to determine genetic groups using PLINK 1.9 software. . Following the final filtering, the genomic information of 488,752 common SNPs from autosomal chromosomes of 79 Romanov heads compared to 120 heads of nine Iranian indigenous sheep breeds to screening signature of selection. The unbiased FST (θ) estimator and XPEHH statistic were used to explore the signs of selection. The genes related to the selected genomic regions were extracted using the BIOMART online database corresponding to areas in the sheep genome assembly (Oar 3.1).

 

Results and discussion

A total of 489 genes associated with the selected genomic regions (consisting of 0.1% of studied markers) were identified. Investigation of the genomic regions under selection showed that out of all identified genes related to the difference between the two studied groups, 7 genes were involved in biological pathways related to steroid synthesis and ovarian steroidogenesis that may be associated with litter size.

 

Conclusion

 Identifying this pathway and other complementary studies about genes involved in reproduction could be effective in designing breeding programs to improve reproductive performance.

 

Author Contributions

Parviz Azizi: Investigation, Preparation, Writing original draft of the Manuscript,

Methodology Data curation, Software and Analysis.

Mohammad Moradi Shahrbabak: Conceptualization, Validation, Review and Editing the

manuscript, Project administration and Supervision.

Hossain Moradi Shahrbabak: Conceptualization, Validation, Review and Editing the

manuscript, Project administration and Supervision.

Mehdi Mokhber: Validation, Review and Editing the

Manuscript,

All authors contributed equally to the conceptualization of the article and writing of the

original and subsequent drafts.

 

Data Availability Statement

Data were obtained from iSheep data base

 

Acknowledgements

The authors would like to thank all participants of the present study.

 

Ethical considerations

The study was approved by the Ethics Committee of the University of Tehran (Ethical code:

IR.7108004/6/52). The authors avoided data fabrication, falsification, plagiarism, and

misconduct.

 

 

REFERENCES

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.‏
Barnett, R., Westbury, M. V., Sandoval-Velasco, M., Vieira, F. G., Jeon, S., Zazula, G., ... & Gilbert, M. T. P. (2020). Genomic adaptations and evolutionary history of the extinct scimitar-toothed cat, Homotherium latidens. Current Biology, 30(24), 5018-5025.‏
Biabani, P., Mehrbani Yeganeh, H., & 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.‏ (In Persian)
Biswas, S. & Akey, J. M. (2006). Genomic insights into positive Selection. Trends in Genetics, 22(8), 437-436.
Bovo, S., Ribani, A., Muñoz, M., Alves, E., Araujo, J. P., Bozzi, R., ... & Fontanesi, L. (2020). Whole-genome sequencing of European autochthonous and commercial pig breeds allows the detection of signatures of selection for adaptation of genetic resources to different breeding and production systems. Genetics Selection Evolution, 52(1), 1-19.‏
Bowles, D., Carson, A., & Isaac, P. (2014). Genetic distinctiveness of the Herdwick sheep breed and two other locally adapted hill breeds of the UK. PLoS One, 9(1), e87823.‏
Browning, B. L., Tian, X., Zhou, Y., & Browning, S. R. (2021). Fast two-stage phasing of large-scale sequence data. The American Journal of Human Genetics, 108(10), 1880-1890.
Browning, S.R. and B.L. Browning. 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(5): 1084-1097.
Buxadera, A. M., Alexandre, G., & Mandonnet, N. (2004). Discussion on the importance, definition and genetic components of the number of animals born in the litter with particular emphasis on small ruminants in tropical conditions. Small Ruminant Research, 54(1-2), 1-11.‏
Byrne, T. J., Ludemann, C. I., Amer, P. R., & Young, M. J. (2012). Broadening breeding objectives for maternal and terminal sheep. Livestock Science, 144(1-2), 20-36.‏
Chu, M. X., Liu, Z. H., Jiao, C. L., He, Y. Q., Fang, L., Ye, S. C., ... & Wang, J. Y. (2007). Mutations in BMPR-IB and BMP-15 genes are associated with litter size in Small Tailed Han sheep (Ovis aries). Journal of Animal Science, 85(3), 598-603.‏
Crepaldi, P., Bionda, A., Cortellari, M., Lopreiato, V., & Liotta, L. (2023). Selection signatures in Italian hunting dogs. Italian Journal of Animal Science, 22(s1), 91-92.‏
Demars, J., Fabre, S., Sarry, J., Rossetti, R., Gilbert, H., Persani, L., ... & Bodin, L. (2013). Genome-wide association studies identify two novel BMP15 mutations responsible for an atypical hyperprolificacy phenotype in sheep. PLoS Genetics, 9(4), e1003482.‏
Deniskova, T., Esmailizadeh, A., Dotsev, A., Koshkina, O., Farahvashi, M. A., Mokhtari, M., ... & Zinovieva, N. (2022). A Search for Eurasian Sheep Relationships: Genomic Assessment of the Autochthonous Sheep Breeds in Russia and the Persian Plateau. Diversity, 14(6), 445.‏
Diao, S., Huang, S., Chen, Z., Teng, J., Ma, Y., Yuan, X., ... & Zhang, Z. (2019). Genome-wide signatures of selection detection in three South China indigenous pigs. Genes, 10(5), 346.‏
Ensembl BioMart: Ensembl online genome database BioMart Tool. http://www.ensembl.org/biomart/martview/.
EntrezGene: NCBI Resources EntrezGene. http://www.ncbi.nlm.nih.gov/.
Esmaeili-Fard, 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.
Fariello, M. I., Servin, B., Tosser-Klopp, G., Rupp, R., Moreno, C., International Sheep Genomics Consortium, ... & Boitard, S. (2014). Selection signatures in worldwide sheep populations. PloS one, 9(8), e103813.‏
Garel, M., Cugnasse, J. M., Gaillard, J. M., Loison, A., Gibert, P., Douvre, P., & Dubray, D. (2005). Reproductive output of female mouflon (Ovis gmelini musimon× Ovis sp.): a comparative analysis. Journal of Zoology, 266(1), 65-71.‏
Gautier, M. and R. Vitalis. 2012. rehh: an R package to detect footprints of selection in genome-wide SNP data from haplotype structure. Bioinformatics, 28(8): 1176-1177.
Gholizadeh, M., & Esmaeili-Fard, S. M. (2022). Multi-population joint genome-wide association study to detect genomic regions associated with litter size in sheep. Animal Production Research, 11(3), 15-26.‏
Gootwine, E. (2020). Invited review: Opportunities for genetic improvement toward higher prolificacy in sheep. Small Ruminant Research, 186, 106090.‏
Gootwine, E. (2020). Invited review: Opportunities for genetic improvement toward higher prolificacy in sheep. Small Ruminant Research, 186, 106090.‏
Hanrahan, J. P., Gregan, S. M., Mulsant, P., Mullen, M., Davis, G. H., Powell, R., & Galloway, S. M. (2004). Mutations in the genes for oocyte-derived growth factors GDF9 and BMP15 are associated with both increased ovulation rate and sterility in Cambridge and Belclare sheep (Ovis aries). Biology of reproduction, 70(4), 900-909.‏
Hider, J. L., Gittelman, R. M., Shah, T., Edwards, M., Rosenbloom, A., Akey, J. M. & Parra, E. J. (2013). Exploring signatures of positive selection in pigmentation candidate genes in populations of East Asian ancestry. BMC Evolutionary Biology, 13, 150-160.
Jiang, Y., Xie, M., Chen, W., Talbot, R., Maddox, J. F., Faraut, T., ... & Dalrymple, B. P. (2014). The sheep genome illuminates biology of the rumen and lipid metabolism. Science, 344(6188), 1168-1173.
Khalkhali-Evrigh, R., Hedayat, N., Ming, L., & JIRANmutu. (2022). Identification of selection signatures in Iranian dromedary and Bactrian camels using whole genome sequencing data. Scientific reports, 12(1), 9653.‏
Kijas, J. W., Lenstra, J. A., Hayes, B., Boitard, S., Porto Neto, L. R. & et al. (2012). 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.
Kimura, M. (1985). The neutral theory of molecular evolution. Cambridge University Press, New York.
Li, L., Shi, X., Shi, Y., & Wang, Z. (2021). The signaling pathways involved in ovarian follicle development. Frontiers in Physiology, 12, 730196.‏
Lv, F. H., Agha, S., Kantanen, J., Colli, L., Stucki, S., Kijas, J. W., ... & Ajmone Marsan, P. (2014). Adaptations to climate-mediated selective pressures in sheep. Molecular biology and evolution, 31(12), 3324-3343.‏
Manzari, Z., Mehrabani Yeghaneh, H., Najati-Javaremi, A., Moradi, M. H., & Gholizadeh, M. (2016). Detection of loci under positive selection in Iranian Baluchi and Zel sheep breeds. Iranian Journal of animal Science, 47(3), 389-398.‏
Mohammadi, H., Moradi, M. H., & Khaltabadi Farahani, A. H. (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.‏ (In Persian)
Mohammadi, H., Rafat, S. A., Moradi Shahrbabak, H., Shoja, J., & Moradi, M. H. (2018). Genome-wide analysis for detection of loci under positive selection in Zandi sheep breed. Iranian Journal of animal Science, 48(4), 533-548.‏ (In Persian)
Mokhber, M., Moradi, M., Sadegi, M., Moradi, H. & Williams, J. (2015). Genome-Wide Survey of signature of positive selection in Khuzestani and Mazandrani buffalo breeds. Iranian Journal of Animal Science, 46(2), 119-131. (In Persian)
Mokhber, M., Moradi-Shahrbabak, M., Sadeghi, M., Moradi-Shahrbabak, H., Stella, A., Nicolzzi, E., ... & Williams, J. L. (2018). A genome-wide scan for signatures of selection in Azeri and Khuzestani buffalo breeds. BMC genomics, 19(1), 1-9.‏
Mokhber, M., Moradi Shahre Babak, M., Sadeghi, M., Moradi Shahrbabak, H., & Rahmani-Nia, J. (2019). Estimation of effective population size of Iranian water buffalo by genomic data. Iranian Journal of animal Science, 50(3), 197-205.‏ (In Persian)
Moradi Shahrebabak, H., Biabani, P., Mehrbani Yeganeh, H., & Mokhber, M. (2023). Investigating the genetic diversity of Iranian native and Holstein cattle breeds using genomic data. Animal Sciences Journal, 36(138), 87-98. (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.
Nicolazzi EL, Caprera A, Nazzicari N, Cozzi P, Strozzi F, Lawley C, et al. SNPchiMp v. 3: integrating and standardizing single nucleotide polymorphism data for livestock species. BMC Genomics. 2015;16:283.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P .I. W., Daly, M. J. & Sham, P. C. (2007). PLINK: a toolset for whole-genome association and population-based linkage analysis. The American Journal of Human Genetics, 81, 559–575.
Qanbari, S., Pausch, H., Jansen, S., Somel, M., Strom, T. M. & et al. (2014). Classic Selective Sweeps Revealed by Massive Sequencing in Cattle. PLoS Genetics, 10(2), e1004148. doi:10.1371/journal.pgen.1004148
Qanbari, S., Strom, T. M., Haberer, G., Weigend, S., Gheyas, A. A. & et al. (2012) A High Resolution Genome-Wide Scan for Significant Selective Sweeps: An Application to Pooled Sequence Data in Laying Chickens. PLoS ONE, 7(11), e49525. doi:10.1371/journal.pone.0049525.
R version 4.1.3  [computer software]. (2013). http:// www.r-project.org/.
Rahimmadar, S., Ghaffari, M., Mokhber, M., & Williams, J. L. (2021). Linkage disequilibrium and effective population size of buffalo populations of Iran, Turkey, Pakistan, and Egypt using a medium density SNP array. Frontiers in Genetics, 12, 608186.‏
Sabeti, P. C., Reich, D. E., Higgins, J. M., Levine, H. Z. P., Richter, D. J., Schaffner, S. F., Gabriel, S. B., Platko, J. V., Patterson, N. J., McDonald, G. J. & et al. (2002). Detecting recent positive selection in the human genome from Haplotype structure. Nature, 419, 832-837.
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(4), 677-684.‏
Shi, S., Shao, D., Yang, L., Liang, Q., Han, W., Xue, Q., ... & Tong, H. (2023). Whole genome analyses reveal novel genes associated with chicken adaptation to tropical and frigid environments. Journal of Advanced Research, 47, 13-25.‏
Simianer, H., Ma, Y. & Qanbari, S. (2014). Statistical problems in livestock population genomics. Proccedings 10th Congress of Genetics Applied to Livestock Production, 17-22 August., Vancouver, BC, Canada.
Strillacci, M. G., Moradi-Shahrbabak, H., Davoudi, P., Ghoreishifar, S. M., Mokhber, M., Masroure, A. J., & Bagnato, A. (2021). A genome-wide scan of copy number variants in three Iranian indigenous river buffaloes. BMC genomics, 22(1), 1-14.‏
Teo, Y. Y., Fry, A. E., Clark, T. G., Tai, E. S. & Seielstad, M. (2007). On the usage of HWE for identifying genotyping errors. Annals of Human Genetics, 71, 701-703.
Turner, S.D. 2014. QQman: An R package for visualizing GWAS results using Q-Q and manhattan plots. bioRxiv, 5165.
Wang, G., Wang, F., Pei, H., Li, M., Bai, F., Lei, C., & Dang, R. (2022). Genome-wide analysis reveals selection signatures for body size and drought adaptation in Liangzhou donkey. Genomics, 114(6), 110476.‏
Wang, Z. H., Zhu, Q. H., Li, X., Zhu, J. W., Tian, D. M., Zhang, S. S., ... & Li, M. H. (2021). iSheep: an integrated resource for sheep genome, variant and phenotype. Frontiers in Genetics, 12, 714852.‏
Weir, B. S. & Cockerham, C. C. 1984. Estimating F-statistics for the analysis of population structure. International Journal of Evolution, 38: 1358–1370.
Wolfová, M., Wolf, J., Krupová, Z., & Margetín, M. (2009). Estimation of economic values for traits of dairy sheep: II. Model application to a production system with one lambing per year. Journal of dairy science92(5), 2195-2203.‏
Xu, S. S., Gao, L., Xie, X. L., Ren, Y. L., Shen, Z. Q., Wang, F., ... & Li, M. H. (2018). Genome-wide association analyses highlight the potential for different genetic mechanisms for litter size among sheep breeds. Frontiers in genetics, 9, 118.‏
Yang, S., Li, X., Li, K., Fan, B. & Tang, Z. (2014). A genome-wide scan for signatures of selection in Chinese indigenous and commercial pig breeds. BMC Genetics, 15(7), 9. from http://www.biomedcentral.com/1471-2156/15/7.
Yazawa, T., Imamichi, Y., Sekiguchi, T., Miyamoto, K., Uwada, J., Khan, M. R. I., ... & Taniguchi, T. (2019). Transcriptional regulation of ovarian steroidogenic genes: recent findings obtained from stem cell-derived steroidogenic cells. BioMed Research International, 2019.‏
Zandi, M. B., Salek Ardestani, S., Vahedi, S. M., Mahboudi, H., Mahboudi, F., & Meskoob, A. (2022). Detection of Common Copy Number of Variants Underlying Selection Pressure in Middle Eastern Horse Breeds Using Whole-Genome Sequence Data. Journal of Heredity, 113(4), 421-430.‏
Zhao, F.P., Wei, C.H., Zhang, L., Liu, J.S., Wang, G.K., Tao, Z.E.N.G. and Du, L.X. (2016). A genome scan of recent positive selection signatures in three sheep populations. Journal of Integrative Agriculture, 15(1): 162-174.