Document Type : Research Paper

Authors

1 Departement of Animal Science, Arak University

2 department of Animal Science, Faculty of Agriculture, Arak University

Abstract

Nowadays, new studies are being conducted based on the results of GWAS studies and the mapping of gene regulation networks based on the use of AWM matrix algorithms. In the present study, to map gene networks using AWM-PCIT matrix algorithms and and the association of SNPs with sheep milk production phenotypes and compositions was used. For this purpose, data on milk production traits in Valle del Belice sheep were used. After data quality control, 469 ewes and 37228 SNPs were used for final analysis. Phenotypic data were retained for analysis and contained 5586 Test day records for six milk production traits. and their gene regulation network was plotted using the cytoscape program. The results showed that using AWM-PCIT matrix algorithms, among the candidate genes that are directly and indirectly related to milk production traits were identified GENES OSBPL3, ERBB4, VGLL4, BAZ1A, DDX25, CDH23, ITSN2, DPY30, FAT3 and CAPN10. The present study and other studies have shown that the complex process of milk production and composition is important under the influence of the gene regulation network of more than 10 genes and is associated with many other genes.In total, this study supported previous results from GWAS of milk production and composition traits, also revealed additional regions in the sheep genome associated with these economically important traits. Using these findings could potentially be useful for genetic selection in the breeding programs.

Keywords

Main Subjects

Bader, G. D., and Hogue, C. W. (2003). An automated method for finding molecular complexes in large protein interaction networks. BMC bioinformatics, 4(1), 1-27.‏
Caraux, G., and Pinloche, S. (2005). PermutMatrix: a graphical environment to arrange gene expression profiles in optimal linear order. Bioinformatics, 21(7), 1280-1281.‏
Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., and Lempicki, R. A. (2003). DAVID: database for annotation, visualization, and integrated discovery. Genome biology, 4(9), 1-11.‏
Du, X., Turner, N., and Yang, H. (2018). The role of oxysterol-binding protein and its related proteins in cancer. In Seminars in cell and developmental biology (Vol. 81, pp. 149-153). Academic Press.‏
Evans, J. C., Frayling, T. M., Cassell, P. G., Saker, P. J., Hitman, G. A., Walker, M., and Hattersley, A. T. (2001). Studies of association between the gene for calpain-10 and type 2 diabetes mellitus in the United Kingdom. The American Journal of Human Genetics, 69(3), 544-552.‏
Fortes, M. R., Reverter, A., Zhang, Y., Collis, E., Nagaraj, S. H., Jonsson, N. N., and Hawken, R. J. (2010). Association weight matrix for the genetic dissection of puberty in beef cattle. Proceedings of the National Academy of Sciences, 107(31), 13642-13647.‏
Haile, A., Hilali, M., Hassen, H., Lobo, R. N. B., and Rischkowsky, B. (2019). Estimates of genetic parameters and genetic trends for growth, reproduction, milk production and milk composition traits of Awassi sheep. animal, 13(2), 240-247.‏
Kang, Y. Y., Liu, Y., Wang, M. L., Guo, M., Wang, Y., and Cheng, Z. F. (2017). Construction and analyses of the microRNA-target gene differential regulatory network in thyroid carcinoma. PloS one, 12(6), e0178331.‏
Li, C., Sun, D., Zhang, S., Liu, L., Alim, M. A., and Zhang, Q. (2016). A post‐GWAS confirming the SCD gene associated with milk medium‐and long‐chain unsaturated fatty acids in Chinese Holstein population. Animal genetics, 47(4), 483-490.‏
Li, C., Wang, M., Cai, W., Liu, S., Zhou, C., Yin, H.,  and Zhang, S. (2018). Genetic analyses confirm SNPs in HSPA8 and ERBB2 are associated with milk protein concentration in Chinese Holstein cattle. Genes, 10(2), 104.‏
Li, R., Ma, Y., and Jiang, L. (2022). Research Progress of Dairy Sheep Milk Genes. Agriculture, 12(2), 169.‏
Okajima, T., Gu, Y., Teruya, R. I., Yano, S., Taketomi, T., Sato, B.,  and Tsuruta, F. (2020). Atypical cadherin FAT3 is a novel mediator for morphological changes of microglia. eneuro, 7(6).‏
Pucharcos, C., Estivill, X., and de la Luna, S. (2000). Intersectin 2, a new multimodular protein involved in clathrin-mediated endocytosis. FEBS letters, 478(1-2), 43-51.‏
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A., Bender, D.,  and Sham, P. C. (2007). PLINK: a tool set for whole-genome association and population-based linkage analyses. The American journal of human genetics, 81(3), 559-575.‏
Ramzan, K., Al-Numair, N. S., Al-Ageel, S., Elbaik, L., Sakati, N., Al-Hazzaa, S. A.,  and Imtiaz, F. (2020). Identification of novel CDH23 variants causing moderate to profound progressive nonsyndromic hearing loss. Genes, 11(12), 1474.‏
Raynal-Ljutovac, K., Lagriffoul, G., Paccard, P., Guillet, I., and Chilliard, Y. (2008). Composition of goat and sheep milk products: An update. Small ruminant research, 79(1), 57-72.‏
Reverter, A., and Chan, E. K. (2008). Combining partial correlation and an information theory approach to the reversed engineering of gene co-expression networks. Bioinformatics, 24(21), 2491-2497.‏
Reverter, A., and Fortes, M. R. (2013). Association weight matrix: a network-based approach towards functional genome-wide association studies. In Genome-Wide Association Studies and Genomic Prediction (pp. 437-447). Humana Press, Totowa, NJ.‏
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D.,  and Ideker, T. (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome research, 13(11), 2498-2504.‏
Simboeck, E., Gutierrez, A., Cozzuto, L., Beringer, M., Caizzi, L., M Keyes, W., and Di Croce, L. (2013). DPY30 regulates pathways in cellular senescence through ID protein expression. The EMBO journal, 32(16), 2217-2230.‏
Sutera, A. M., Portolano, B., Di Gerlando, R., Sardina, M. T., Mastrangelo, S., and Tolone, M. (2018). Determination of milk production losses and variations of fat and protein percentages according to different levels of somatic cell count in Valle del Belice dairy sheep. Small Ruminant Research, 162, 39-42.‏
Sutera, A. M., Riggio, V., Mastrangelo, S., Di Gerlando, R., Sardina, M. T., Pong‐Wong, R.,  and Portolano, B. (2019). Genome‐wide association studies for milk production traits in Valle del Belice sheep using repeated measures. Animal genetics, 50(3), 311-314.‏
Suthar, M. K., Purva, M., Maherchandani, S., and Kashyap, S. K. (2016). Identification and in silico analysis of cattle DExH/D box RNA helicases. Springerplus, 5(1), 1-13.‏
Williams, M. M., Vaught, D. B., Joly, M. M., Hicks, D. J., Sanchez, V., Owens, P.,  and Cook, R. S. (2017). ErbB3 drives mammary epithelial survival and differentiation during pregnancy and lactation. Breast Cancer Research, 19(1), 1-14.‏
Yang, Z., Shah, K., Khodadadi-Jamayran, A., and Jiang, H. (2016). Dpy30 is critical for maintaining the identity and function of adult hematopoietic stem cells. Journal of Experimental Medicine, 213(11), 2349-2364.‏
Zaghlool, A., Halvardson, J., Zhao, J. J., Etemadikhah, M., Kalushkova, A., Konska, K.,  and Feuk, L. (2016). A role for the chromatin‐remodeling factor BAZ1A in neurodevelopment. Human mutation, 37(9), 964-975.‏