Investigation of the Functional Proteins Related to Fertility in Cattle’s Endometrium by Protein-Protein Interactions Networks
محورهای موضوعی : Camel
F. Bahri Binabaj
1
(Department of Animal Science, College of Agriculture and Natural Resources, Gonbad Kavous University, Gonbad Kavous, Iran)
S.H. Farhangfar
2
(Department of Animal Science, Faculty of Agriculture, University of Birjand, Birjand, Iran)
E. Behdani
3
(Department of Animal Science, Faculty of Animal and Food Science, Ramin Agricultural and Natural Resources University, Mollasani, Ahvaz, Iran)
کلید واژه: Gene expression, major genes, molecular pathways, pregnancy loss,
چکیده مقاله :
Pregnancy loss is an important economic loss in cattle industry. This study was conducted to identify pre- and / or post-implantation genes and cellular algorithms. For this purpose, transcriptome data of endometrium tissue were analyzed. These data refer to three heifer categories: high fertile (HF), sub-fertile (SF) and infertile (IF). After gene detection, genes were divided into two groups: Up-expressed genes, which were up-regulated in every comparison of either favorable fertility cases or unfavorable fertility cases (HF vs. SF, HF vs. IF, and SF vs. IF), and down-expressed genes, which were down-regulated in the mentioned comparisons. String database was applied to construct protein-protein interaction (PPI) networks and clusterone plugin was used to determine the significant sub-network. Enrichment analysis, which involves the gene ontology and functional pathway, was performed to enrich the results. Our results suggested that over-expression of SHCBP1, NOP14, PGM5, and DHX58 genes may have positive effect on the outcome of pregnancy, and down-expression of IMP3, ATP5O, and RPL7 genes could help the reproductive efficiency. The results of the present study showed that the genes in up-regulated clusters could manipulate epithelial differentiation, fundamental biological role, glucose metabolism, and immune response, which led to reduced pregnancy loss. Also the genes in down-regulated clusters may participate in the improvement of pregnancy outcome by inducing anti-apoptotic processes. This study proposes the pregnancy-associated key genes and pathways to improve pregnancy success in cattle and other domestic animals.
Anders S., Pyl P.T. and Huber W. (2015). HTSeq-a python framework to work with high-throughput sequencing data. Bioinformatics. 31(2), 166-169.
Ansoleaga B., Garcia-Esparcia P., Llorens F., Hernández-Ortega K., Carmona M., Antonio del Rio J., Zerr I. and Ferrer I. (2016). Altered mitochondria, protein synthesis machinery, and purine metabolism are molecular contributors to the pathogenesis of creutzfeldt–jakob disease. J. Neuropathpl. Exp. Neurol. 75(8), 755-769.
Behdani E. and Bakhtiarizadeh M.R. (2017). Construction of an integrated gene regulatory network link to stress-related immune system in cattle. Genetica. 145(4), 441-454.
Binelli M., Scolari S.C., Pugliesi G., Van Hoeck V., Gonella-Diaza A.M., Andrade S.C., Gasparin G.R. and Coutinho L.L. (2015). The transcriptome signature of the receptive bovine uterus determined at early gestation. PLoS One. 10(4), e0122874.
Bolger A.M., Lohse M. and Usadel B. (2014). Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics. 30(15), 2114-2120.
Brüggemann M., Gromes A., Poss M., Schmidt D., Klümper N., Tolkach Y., Dietrich D., Kristiansen G., Müller S.C. and Ellinger J. (2017). Systematic analysis of the expression of the mitochondrial ATP synthase (Complex V) subunits in clear cell renal cell carcinoma. Transl. Oncol. 10(4), 661-668.
Buckley M.W., Arandjelovic S., Trampont P.C., Kim T.S., Braciale T.J. and Ravichandran K.S. (2014). Unexpected phenotype of mice lacking Shcbp1, a protein induced during T cell proliferation. PLoS One. 9(8), e105576.
Burns C.E., Galloway J.L., Smith A.C., Keefe M.D., Cashman T.J., Paik E.J., Mayhall E.A., Amsterdam A.H. and Zon L.I. (2009). A genetic screen in zebrafish defines a hierarchical network of pathways required for hematopoietic stem cell emergence. Blood. 113(23), 5776-5782.
Cerri R., Thompson I., Kim I., Ealy A., Hansen P., Staples C.R., Li J.L., Santos P. and Thatcher W. (2012). Effects of lactation and pregnancy on gene expression of endometrium of Holstein cows at day 17 of the estrous cycle or pregnancy. J. Dairy Sci. 95(10), 5657-5675.
Chakraborty D. (2013). Natural killer cells, hypoxia, and epigenetic regulation of hemochorial placentation. Ph D. Thesis. University of Kansas, Kansas, USA.
Ching Y.H., Munroe R.J., Moran J.L., Barker A.K., Mauceli E., Fennell T., Lindblad-Toh K., Abcunas L.M., Gilmour J.F. and Harris T.P. (2010). High resolution mapping and positional cloning of ENU-induced mutations in the Rw region of mouse chromosome 5. BMC Genet. 11(1), 106-113.
Chitwood J.L., Rincon G., Kaiser G.G., Medrano J.F. and Ross P.J. (2013). RNA-seq analysis of single bovine blastocysts. BMC Genom. 14(1), 350-361.
Degrauwe N., Suvà M.L., Janiszewska M., Riggi N. and Stamenkovic I. (2016). IMPs: An RNA-binding protein family that provides a link between stem cell maintenance in normal development and cancer. Gene Dev. 30(22), 2459-2474.
Dehmer M., Mueller L.A. and Emmert-Streib, F. (2013). Quantitative network measures as biomarkers for classifying prostate cancer disease states: a systems approach to diagnostic biomarkers. PLoS One. 8(11), e77602.
Dickinson S.E., Griffin B.A., Elmore M.F., Kriese-Anderson L., Elmore J.B., Dyce P.W., Rodnig S.P. and Biase F.H. (2018). Transcriptome profiles in peripheral white blood cells at the time of artificial insemination discriminate beef heifers with different fertility potential. BMC Genom. 19(1), 129-135.
Ding Y.B., He J.L., Chen X.M., Liu X.Q. and Wang Y.X. (2013). Novel differential transcript expression identified by LongSAGE in the mouse endometrium during the implantation window. Mol. Biol. Rep. 40(1), 651-663.
Djordjevic B., Westin S. and Broaddus R.R. (2012). Application of immune-histochemistry and molecular diagnostics to clinically relevant problems in endometrial cancer. Surg Pathol Clin. 5(4), 859-878.
Egashira M. and Hirota Y. (2013). Uterine receptivity and embryo-uterine interactions in embryo implantation: Lessons from mice. Reprod. Med. Biol. 12(4), 127-132.
Fruzangohar M., Ebrahimie E., Ogunniyi A.D., Mahdi L.K., Paton J.C. and Adelson D.L. (2013). Comparative GO: A web application for comparative gene ontology and gene ontology-based gene selection in bacteria. PLoS One. 8(3), e58759.
Gad A., Besenfelder U., Rings F., Ghanem N., Salilew-Wondim D., Hossain M., Tesfaye D., Lonergan P., Becker A. and Cinar U. (2011). Effect of reproductive tract environment following controlled ovarian hyperstimulation treatment on embryo development and global transcriptome profile of blastocysts: implications for animal breeding and human assisted reproduction. Hum. Reprod. 26(7), 1693-1707.
Geary T.W., Burns G.W., Moraes J.G., Moss J.I., Denicol A.C., Dobbs K.B., Ortega M.S., Hansen P.J., Wehrman M.E. and Neibergs H. (2016). Identification of beef heifers with superior uterine capacity for pregnancy. Biol. Reprod. 95(2), 1-12.
Glaab E., Baudot A., Krasnogor N., Schneider R. and Valencia A. (2012). EnrichNet: network-based gene set enrichment analysis. Bioinformatics. 28(18), 451-457.
Grewal R., Stepczynski J., Kelln R., Erickson T., Darrow R., Barsalou L., Patterson M., Organisciak D.T. and Wong P. (2004). Coordinated changes in classes of ribosomal protein gene expression is associated with light-induced retinal degeneration. Invest. Ophthalmol. Vis. Sci. 45(11), 3885-3895.
Gutierrez A., Tschumper R.C., Wu X., Shanafelt T.D., Eckel-Passow J., Huddleston P.M., Slager S.L., Kay N.E. and Jelinek D.F. (2010). LEF-1 is a prosurvival factor in chronic lymphocytic leukemia and is expressed in the preleukemic state of monoclonal B cell lymphocytosis. Blood. 116(16), 2975-2983.
He Y., Reichow S., Ramamoorthy S., Ding X., Lathigra R., Craig J.C., Sobral B.W., Schurig G.G., Sriranganathan N. and Boyle S.M. (2006). Brucella melitensis triggers time-dependent modulation of apoptosis and down- egulation of mitochondrion-associated gene expression in mouse macrophages. Infect Immun. 74(9), 5035-5046.
Hemmerich P., Mikecz A.V., Neumann F., Sözeri O., Wolff-Vorbeck G., Zoebelein R. and Krawinkel U. (1993). Structural and functional properties of ribosomal protein L7 from humans and rodents. Nucleic Acids Res. 21(2), 223-231.
Hong E.J., Park S.H., Choi K.C., Leung P.C. and Jeung E.B. (2006). Identification of estrogen-regulated genes by microarray analysis of the uterus of immature rats exposed to endocrine disrupting chemicals. Reprod. Biol. Endocrinnol. 4(1), 49-59.
Hu Y., Matkovich S.J., Hecker P.A., Zhang Y., Edwards J.R. and Dorn G.W. (2012). Epitranscriptional orchestration of genetic reprogramming is an emergent property of stress-regulated cardiac microRNAs. Proc. Natl. Acad. Sci. 109(48), 19864-19869.
Huang J.K., Carlin D.E., Yu M.K., Zhang W., Kreisberg J.F., Tamayo P. and Ideker T. (2018a). Systematic evaluation of molecular networks for discovery of disease genes. Cell Syst. 6(4), 484-495. e485.
Huang M.Y., Zhang W.Q., Zhao M., Zhu C., He J.P. and Liu J.L. (2018b). Assessment of embryo-induced transcriptomic changes in hamster uterus using RNA-Seq. Cell Physiol. Biochem. 46(5), 1868-1878.
Labaj P.P., Leparc G.G., Linggi B.E., Markillie L.M., Wiley H.S. and Kreil D.P. (2011). Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling. Bioinformatics. 27(13), 383-391.
Li Q., Zhang M., Kumar S., Zhu L.J., Chen D., Bagchi M.K. and Bagchi I.C. (2001). Identification and implantation stage-specific expression of an interferon-α-regulated gene in human and rat endometrium. Endocrinology. 142(6), 2390-2400.
Liu M., Shi X., Bi Y., Qi L., Guo X., Wang L., Zhou Z. and Sha J. (2014). SHCBP1L, a conserved protein in mammals, is predominantly expressed in male germ cells and maintains spindle stability during meiosis in testis. Mol. Hum. Reprod. 20(6), 463-475.
Liu P.C. and Thiele D.J. (2001). Novel stress-responsive genes EMG1 and NOP14 encode conserved, interacting proteins required for 40S ribosome biogenesis. Mol. Biol. Cell. 12(11), 3644-3657.
Luizon M.R., Palei A.C., Cavalli R.C. and Sandrim V.C. (2017). Pharmacogenetics in the treatment of pre-eclampsia: current findings, challenges and perspectives. Pharmacogenomics. 18(6), 571-583.
Maraziotis I.A., Dimitrakopoulou K. and Bezerianos A. (2008). An in silico method for detecting overlapping functional modules from composite biological networks. BMC Syst. Biol. 2(1), 93-103.
Montembault E., Zhang W., Przewloka M.R., Archambault V., Sevin E.W., Laue E.D., Glover D.M. and D'Avino P.P. (2010). Nessun Dorma, a novel centralspindlin partner, is required for cytokinesis in Drosophila spermatocytes. J. Cell Biol. 191(7), 1351-1365.
Mori H., Sakakibara S.I., Imai T., Nakamura Y., Iijima T., Suzuki A., Yuasa Y., Takeda M. and Okano H. (2001). Expression of mouse IGF2 mRNA binding protein 3 and its implications for the developing central nervous system. J. Neurosci. Res. 64(2), 132-143.
Neupane M., Geary T.W., Kiser J.N., Burns G.W., Hansen P.J., Spencer T.E. and Neibergs H.L. (2017). Loci and pathways associated with uterine capacity for pregnancy and fertility in beef cattle. PLoS One. 12(12), e0188997.
Pavličev M., Wagner G.P., Chavan A.R., Owens K., Maziarz J., Dunn-Fletcher C., Kallapur S.G., Muglia L. and Jones H. (2017). Single-cell transcriptomics of the human placenta: inferring the cell communication network of the maternal-fetal interface. Genome Res. 27(3), 349-361.
Peng C., Zhao H., Song Y., Chen W., Wang X., Liu X., Zhang C., Zhao J., Li J. and Cheng G. (2017). SHCBP1 promotes synovial sarcoma cell metastasis via targeting TGF-β1/Smad signaling pathway and is associated with poor prognosis. J. Exp. Clin. Cancer Res. 36(1), 141-149.
Pollpeter D., Komuro A., Barber G.N. and Horvath C.M. (2011). Impaired cellular responses to cytosolic DNA or infection with Listeria monocytogenes and vaccinia virus in the absence of the murine LGP2 protein. PLoS One. 6(4), e18842.
Red-Horse K., Drake P.M. and Fisher S.J. (2004). Human pregnancy: the role of chemokine networks at the fetal–maternal interface. Exp. Rev. Mol. Med. 6(11), 1-14.
Ren C.E., Zhu X., Li J., Lyle C., Dowdy S., Podratz K.C., Byck D., Chen H.B. and Jiang S.W. (2015). Microarray analysis on gene regulation by estrogen, progesterone and tamoxifen in human endometrial stromal cells. Int. J. Mol. Sci. 16(3), 5864-5885.
Robb A.O., Mills N.L., Newby D.E. and Denison F.C. (2007). Endothelial progenitor cells in pregnancy. Reproduction. 133(1), 1-9.
Robinson M.D., McCarthy D.J. and Smyth G.K. (2010). edgeR: A bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 26(1), 139-140.
Sahrawat T.R. and Bhalla S. (2013). Identification of critical target protein for cystic fibrosis using systems biology network approach. Int. J. Bioautomation. 17, 227-240.
Satoh T., Kato, H., Kumagai Y., Yoneyama M., Sato S., Matsushita K., Tsujimura T., Fujita T., Akira S. and Takeuchi O. (2010). LGP2 is a positive regulator of RIG-I–and MDA5-mediated antiviral responses. Proc. Natl. Acad. Sci. 107(4), 1512-151.
Saxena M. (2015). Pain related genes in endometriosis: A meta-analysis. MS Thesis. University of Sydney, Australia.
Shao-Jun C. (2015). Drug-target networks for Tanshinone IIA identified by data mining. Chinese J. Nat. Med. 13(10), 751-759.
Sheikhlou M.R., Badere S., Bahri Binabaj F. and Safari R. (2018). Inbreeding Trend and Inbreeding Depression on Birth and Weaning Weights of Iranian Baluchi Sheep. Pp. 78-81 in Proc. 18th Asian Australasian Anim. Prod. Congr. Kuching, Malaysia.
Shen C. and Liu Z.P. (2017). Identifying module biomarkers of hepatocellular carcinoma from gene expression data. 5404-5407 in Proc. Chinese Automation Congr, Jinan, China.
Smits K., De Coninck D.I., Van Nieuwerburgh F., Govaere J., Van Poucke M., Peelman L., Deforce D. and Van Soom A. (2016). The equine embryo influences immune-related gene expression in the oviduct. Biol. Reprod. 94(2), 31-38.
Spencer T.E., Sandra O. and Wolf E. (2008). Genes involved in conceptus–endometrial interactions in ruminants: Insights from reductionism and thoughts on holistic approaches. Reproduction. 135(2), 165-179.
Suzuki T., Behnam M., Ronasian F., Salehi M., Shiina M., Koshimizu E., Fujita A., Sekiguchi F., Miyatake S. and Mizuguchi T. (2018). A homozygous NOP14 variant is likely to cause recurrent pregnancy loss. J. Hum. Genet. 63(4), 425-431.
Szklarczyk D., Franceschini A., Wyder S., Forslund K., Heller D., Huerta-Cepas J., Simonovic M., Roth A., Santos A. and Tsafou, K.P. (2014). STRING v10: Protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 43, 447-452.
Takabatake K., Fujiwara H., Goto Y., Nakayama T., Higuchi T., Fujita J., Maeda M. and Mori T. (1997). Splenocytes in early pregnancy promote embryo implantation by regulating endometrial differentiation in mice. Hum. Reprod. 12(10), 2102-2107.
Tian Z., Guo M., Wang C., Liu X. and Wang S. (2017). Refine gene functional similarity network based on interaction networks. BMC Bioinformatics. 18(16), 550-559.
Tranguch S., Cheung-Flynn J., Daikoku T., Prapapanich V., Cox M.B., Xie H., Wang H., Das S.K., Smith D.F., Dey S.K. and Roberts S.K. (2005). Cochaperone immunophilin FKBP52 is critical to uterine receptivity for embryo implantation. Proc. Natl. Acad. Sci. 102(40), 14326-14331.
Trapnell C., Pachter L. and Salzberg S.L. (2009). TopHat: Discovering splice junctions with RNA-Seq. Bioinformatics. 25(9), 1105-1111.
Wadhwa R., Ryu J., Ahn H.M., Saxena N., Chaudhary A., Yun C.O. and Kaul S.C. (2015). Functional significance of point mutations in stress chaperone mortalin and their relevance to Parkinson disease. J. Biol. Chem. 290(13), 8447-8456.
Walker C.G., Meier S., Mitchell M.D., Roche J.R. and Littlejohn M. (2009). Evaluation of real-time PCR endogenous control genes for analysis of gene expression in bovine endometrium. BMC Mol. Biol. 10(1), 100-107.
Walsh S., Williams E. and Evans A. (2011). A review of the causes of poor fertility in high milk producing dairy cows. Anim. Reprod. Sci. 123(3), 127-138.
Zheng W., Yi X., Fadare O., Liang S.X., Martel M., Schwartz P.E. and Jiang Z. (2008). The oncofetal protein IMP3: A novel biomarker for endometrial serous carcinoma. Am. J. Surg. Pathol. 32(2), 304-315.
Zhu Z., Zhang X., Wang G. and Zheng H. (2014). The laboratory of genetics and physiology 2: Emerging insights into the controversial functions of this RIG-I-like receptor. BioMed Res. Int. 2014, 960190-960197.
Zucchini C., Rocchi A., Manara M.C., De Sanctis P., Capanni C., Bianchini M., Carinci P., Scotlandi K. and Valvassori L. (2008). Apoptotic genes as potential markers of metastatic phenotype in human osteosarcoma cell lines. Int. J. Oncol. 32(1), 17-31.
