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Paradigm of Time-sequence Development of the Intestine of Suckling Piglets with Microarray

  • Sun, Yunzi (School of Life Science, Guizhou Normal University) ;
  • Yu, Bing (Animal Nutrition Institute, Sichuan Agricultural University) ;
  • Zhang, Keying (Animal Nutrition Institute, Sichuan Agricultural University) ;
  • Chen, Xijian (Genminix Informatics Ltd. Co.) ;
  • Chen, Daiwen (Animal Nutrition Institute, Sichuan Agricultural University)
  • Received : 2011.12.26
  • Accepted : 2012.04.15
  • Published : 2012.10.01

Abstract

The interaction of the genes involved in intestinal development is the molecular basis of the regulatory mechanisms of intestinal development. The objective of this study was to identify the significant pathways and key genes that regulate intestinal development in Landrace piglets, and elucidate their rules of operation. The differential expression of genes related to intestinal development during suckling time was investigated using a porcine genome array. Time sequence profiles were analyzed for the differentially expressed genes to obtain significant expression profiles. Subsequently, the most significant profiles were assayed using Gene Ontology categories, pathway analysis, network analysis, and analysis of gene co-expression to unveil the main biological processes, the significant pathways, and the effective genes, respectively. In addition, quantitative real-time PCR was carried out to verify the reliability of the results of the analysis of the array. The results showed that more than 8000 differential expression transcripts were identified using microarray technology. Among the 30 significant obtained model profiles, profiles 66 and 13 were the most significant. Analysis of profiles 66 and 13 indicated that they were mainly involved in immunity, metabolism, and cell division or proliferation. Among the most effective genes in these two profiles, CN161469, which is similar to methylcrotonoyl-Coenzyme A carboxylase 2 (beta), and U89949.1, which encodes a folate binding protein, had a crucial influence on the co-expression network.

Keywords

References

  1. Altaf-Ul-Amin, M., Y. Shinbo, K. Mihara, K. Kurokawa and S. Kanaya. 2006. Development and implementation of an algorithm for detection of protein complexes in large interaction networks. BMC Bioinformatics 7:207. https://doi.org/10.1186/1471-2105-7-207
  2. Ashburner, M., C. A. Ball, J. A. Blake, D. Botstein, H. Butler, J. M. Cherry, A. P. Davis, K. Dolinski, S. S. Dwight and J. T. Eppig et al. 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25:25-29. https://doi.org/10.1038/75556
  3. Barabasi, A. L. and Z. N. Oltvai. 2004. Network biology: understanding the cell's functional organization. Nat. Rev. Genet. 5:101-113. https://doi.org/10.1038/nrg1272
  4. Buddington, R. K. 1994. Nutrition and ontogenetic development of the intestine. Can. J. Physiol. Pharmacol. 72:251-259. https://doi.org/10.1139/y94-039
  5. Butler, J. E. and M. Sinkora. 2007. The isolator piglet: a model for studying the development of adaptive immunity. Immunol. Res. 39:33-51. https://doi.org/10.1007/s12026-007-0062-7
  6. Caicedo, R. A., R. J. Schanler, N. Li and J. Neu. 2005. The developing intestinal ecosystem: implications for the neonate. Pediatr. Res. 58:625-628. https://doi.org/10.1203/01.PDR.0000180533.09295.84
  7. Carlson, M. R., B. Zhang, Z. Fang, P. S. Mischel, S. Horvath and S. F. Nelson. 2006. Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks. BMC Genomics 7:40. https://doi.org/10.1186/1471-2164-7-40
  8. Commare, C. E. and K. A. Tappenden. 2007. Development of the infant intestine: implications for nutrition support. Nutr. Clin. Pract. 22:159-173. https://doi.org/10.1177/0115426507022002159
  9. Covington, M. F., J. N. Maloof, M. Straume, S. A. Kay and S. L. Harmer. 2008. Global transcriptome analysis reveals circadian regulation of key pathways in plant growth and development. Genome Biol. 9:R130. https://doi.org/10.1186/gb-2008-9-8-r130
  10. Davidson, E. H., J. P. Rast, P. Oliveri, A. Ransick, C. Calestani, C. H. Yuh, T. Minokawa, G. Amore, V. Hinman, C. Arenas-Mena, O. Otim, C. T. Brown, C. B. Livi, P. Y. Lee, R. Revilla, A. G. Rust, Z. Pan, M. J. Schilstra, P. J. Clarke, M. I. Arnone, L. Rowen, R. A. Cameron, D. R. McClay, L. Hood and H. Bolouri. 2002. A genomic regulatory network for development. Science 295:1669-1678. https://doi.org/10.1126/science.1069883
  11. Donovan, S. M. 2006. Role of human milk components in gastrointestinal development: Current knowledge and future NEEDS. J. Pediatr. 149:13.
  12. Ernst, J., G. J. Nau and Z. Bar-Joseph. 2005. Clustering short time series gene expression data. Bioinformatics 21(Suppl 1):159-168. https://doi.org/10.1093/bioinformatics/bti1022
  13. Gilbert, D. and D. Lloyd. 2000. The living cell: a complex autodynamic multi-oscillator system? Cell Biol. Int. 24:569-580. https://doi.org/10.1006/cbir.2000.0571
  14. Gracey, A. Y., E. J. Fraser, W. Li, Y. Fang, R. R. Taylor, J. Rogers, A. Brass and A. R. Cossins. 2004. Coping with cold: An integrative, multitissue analysis of the transcriptome of apoikilothermic vertebrate. Proc. Natl. Acad. Sci. USA. 101: 16970-16975. https://doi.org/10.1073/pnas.0403627101
  15. Hall, G. A. and T. F. Byrne. 1989. Effects of age and diet on small intestinal structure and function in gnotobiotic piglets. Res. Vet. Sci. 47:387-392.
  16. Han, J. D. 2008. Understanding biological functions through molecular networks. Cell Res. 18:224-237. https://doi.org/10.1038/cr.2008.16
  17. Huber, W., V. J. Carey, L. Long, S. Falcon and R. Gentleman. 2007. Graphs in molecular biology. BMC Bioinformatics 8(Suppl 6): S8. https://doi.org/10.1186/1471-2105-8-S6-S8
  18. Jiang, Y. and M. K. Deyholos. 2006. Comprehensive transcriptional profiling of NaCl-stressed Arabidopsis roots reveals novel classes of responsive genes. BMC Plant Biol. 6: 25. https://doi.org/10.1186/1471-2229-6-25
  19. Kanehisa, M. and S. Goto. 2000. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28:27-30. https://doi.org/10.1093/nar/28.1.27
  20. Kim, J. G. and J. L. Vallet. 2004. Secreted and placental membrane forms of folate-binding protein occur sequentially during pregnancy in swine. Biol. Reprod. 71:1214-1219. https://doi.org/10.1095/biolreprod.104.031088
  21. Kitano, H. 2002. Systems biology: a brief overview. Science 295: 1662-1664. https://doi.org/10.1126/science.1069492
  22. Zhang, J., X. K. Teng, L. Z. Si, P. T. Zhou, X. Y. Kong and L. D. Hu. 2008. New evidence for the involvement of the EGF receptor pathway in hair follicle morphogenesis in uncv mice. Genes Genomics 30:347-353.
  23. Lee, J. M., E. P. Gianchandani, J. A. Eddy and J. A. Papin. 2008. Dynamic analysis of integrated signaling, metabolic, and regulatory networks. PLoS Comput Biol 4, e1000086. https://doi.org/10.1371/journal.pcbi.1000086
  24. Lunney, J. K. 2007. Advances in swine biomedical model genomics. Int. J. Biol. Sci. 3:179-184. https://doi.org/10.3923/ijb.2007.179.187
  25. Nikiforova, V. J. and L. Willmitzer. 2007. Network visualization and network analysis. EXS 97:245-275.
  26. Ojeda, N. B., D. Grigore and B. T. Alexander. 2008. Developmental programming of hypertension: insight from animal models of nutritional manipulation. Hypertension 52: 44-50. https://doi.org/10.1161/HYPERTENSIONAHA.107.092890
  27. Oltvai, Z. N. and A. L. Barabasi. 2002. Systems biology. Life's complexity pyramid. Science 298:763-764. https://doi.org/10.1126/science.1078563
  28. Pacha, J. 2000. Development of intestinal transport function in mammals. Physiol. Rev. 80:1633-1667.
  29. Pan, L., M. Deng, X. Xie and L. Gan. 2008. ISL1 and BRN3B co-regulate the differentiation of murine retinal ganglion cells. Development 135:1981-1990. https://doi.org/10.1242/dev.010751
  30. Ravasz, E., A. L. Somera, D. A. Mongru, Z. N. Oltvai and A. L. Barabasi. 2002. Hierarchical organization of modularity in metabolic networks. Science 297:1551-1555. https://doi.org/10.1126/science.1073374
  31. Rawat, A., G. J. Seifert and Y. Deng. 2008. Novel implementation of conditional co-regulation by graph theory to derive co-expressed genes from microarray data. BMC Bioinformatics 9 (Suppl 9):S7. https://doi.org/10.1186/1471-2105-9-S9-S7
  32. Sarkar, S. A., S. Kobberup, R. Wong, A. D. Lopez, N. Quayum, T. Still, A. Kutchma, J. N. Jensen, R. Gianani, G. M. Beattie, J. Jensen, A. Hayek and J. C. Hutton. 2008. Global gene expression profiling and histochemical analysis of the developing human fetal pancreas. Diabetologia 51:285-297. https://doi.org/10.1007/s00125-007-0880-0
  33. Schlitt, T., K. Palin, J. Rung, S. Dietmann, M. Lappe, E. Ukkonen and A. Brazma. 2003. From gene networks to gene function. Genome Res. 13:2568-2576. https://doi.org/10.1101/gr.1111403
  34. Schweikl, H., K. A. Hiller, A. Eckhardt, C. Bolay, G. Spagnuolo, T. Stempfl and G. Schmalz. 2008. Differential gene expression involved in oxidative stress response caused by triethylene glycol dimethacrylate. Biomaterials 29:1377-1387. https://doi.org/10.1016/j.biomaterials.2007.11.049
  35. Shalgi, R., D. Lieber, M. Oren and Y. Pilpel. 2007. Global and local architecture of the mammalian microRNA-transcription factor regulatory network. PLoS Comput. Biol. 3:e131. https://doi.org/10.1371/journal.pcbi.0030131
  36. Smidtas, S., A. Yartseva, V. Schachter and F. Kepes. 2006. Model of interactions in biology and application to heterogeneous network in yeast. C. R. Biol. 329:945-952. https://doi.org/10.1016/j.crvi.2006.06.010
  37. Stears, R. L., T. Martinsky and M. Schena. 2003. Trends in microarray analysis. Nat. Med. 9:140-145. https://doi.org/10.1038/nm0103-140
  38. Thaler, J. P. and D. E. Cummings. 2008. Metabolism: food alert. Nature 452:941-942. https://doi.org/10.1038/452941a
  39. Thompson, C. L., B. Wang and A. J. Holmes. 2008. The immediate environment during postnatal development has long-term impact on gut community structure in pigs. ISME J. 2:739-748. https://doi.org/10.1038/ismej.2008.29
  40. Tomita, M., K. Hashimoto, K. Takahashi, T. S. Shimizu, Y. Matsuzaki, F. Miyoshi, K. Saito, S. Tanida, K. Yugi, J. C. Venter and C. A. Hutchison. 3rd, 1999. E-CELL:software environment for whole-cell simulation. Bioinformatics 15:72-84. https://doi.org/10.1093/bioinformatics/15.1.72
  41. Vallet, J. L., T. P. Smith, T. S. Sonstegard, M. Heaton and S. C. Fahrenkrug. 2001. Structure of the genes for porcine endometrial secreted and membrane folate binding proteins. Domest. Anim. Endocrinol. 21:55-72. https://doi.org/10.1016/S0739-7240(01)00100-X
  42. Weaver, L. T., S. Austin and T. J. Cole. 1991. Small intestinal length: a factor essential for gut adaptation. Gut 32:1321-1323. https://doi.org/10.1136/gut.32.11.1321
  43. Wechter, W. P., A. Levi, K. R. Harris, A. R. Davis, Z. Fei, N. Katzir, J. J. Giovannoni, A. Salman-Minkov, A. Hernandez, J. Thimmapuram, Y. Tadmor, V. Portnoy and T. Trebitsh. 2008. Gene expression in developing watermelon fruit. BMC Genomics 9:275. https://doi.org/10.1186/1471-2164-9-275
  44. Young, R. A. 2000. Biomedical discovery with DNA arrays. Cell 102:9-15. https://doi.org/10.1016/S0092-8674(00)00005-2
  45. Yu, H., N. M. Luscombe, J. Qian and M. Gerstein. 2003. Genomic analysis of gene expression relationships in transcriptional regulatory networks. Trends Genet. 19:422-427. https://doi.org/10.1016/S0168-9525(03)00175-6

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