نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناس ارشد، گروه علوم دام و طیور، پردیس ابوریحان، دانشگاه تهران، پاکدشت، ایران

2 استادیار، گروه علوم دام و طیور، پردیس ابوریحان، دانشگاه تهران، پاکدشت، ایران

چکیده

این تحقیق به‌منظور درک بهتر سازوکارهای تنظیمی بیان ژن‏های مربوط به تعادل منفی انرژی انجام شد. ژن‏های با بیان بالا در تعادل منفی انرژی با استفاده از داده‏های ریزآرایه و RNA-seq شناسایی و توالی‏های پروموتری آنها برای شناسایی فاکتورهای رونویسی جدید در ارتباط با این مراحل تجزیه و تحلیل شدند. افزون بر این، از پایگاه اطلاعاتی STRING برای ترسیم شبکۀ ژنی مرتبط با فاکتورهای رونویسی شناسایی‌شده در تعادل منفی انرژی استفاده شد. نتایج تجزیه و تحلیل بیان ژن‏ها نشان داد که هشت ژن بیان بالا و معنادار در مقایسه تعادل منفی انرژی شدید نسبت به خفیف دارند (05/0< P). درنتیجۀ تجزیه و تحلیل پروموتری این ژن‏ها، 19 فاکتور رونویسی شناسایی شد. این مجموعه مشتمل بر یک فاکتور رونویسی (NF-κB) با نقش تأییدشده در تعادل منفی انرژی و فاکتورهای رونویسی جدید همچون SP1، ZBP89، NFI، Zf9، MYC، ZBTB7A، FOXF2، و KLF6، که نقش تنظیمی آنها در تعادل منفی انرژی گزارش نشده، است. براساس نتایج، 18 فاکتور رونویسی کاندید جدید معرفی‌شده در این مطالعه می‏توانند اطلاعات جدیدی را در درک بهتر شبکۀ تنظیمی مؤثر در تعادل منفی انرژی فراهم کنند.

کلیدواژه‌ها

عنوان مقاله [English]

Promoter analysis of effective genes in negative energy balance in dairy cows

نویسندگان [English]

  • Zohreh Mozduri 1
  • Mohammad Reza Bakhtiarizadeh 2

1 M.Sc. Student, Department of Animal and Poultry Sciences, College of Aboureihan, University of Tehran, Tehran, Iran

2 Assistant Professor, Department of Animal and Poultry Sciences, College of Aboureihan, University of Tehran, Tehran, Iran

چکیده [English]

This study was done to gain insights into transcriptional regulation of negative energy balance (NEB) assoctiated genes. Overexpressed genes in NEB were identified using microarray and RNA-seq data and promoter analysis of these overexpressed genes was applied to identify novel transcription factors. Moreever, STRING database was used to construct a regulatory network of identified transcription factors. The results of the gene expression analysis revealed that eight genes in severe NEB are more frequent and significant (P<0.05) in comparison to the mild NEB. Promoter analysis showed that promoters of overexpressed genes are enriched in putative binding sites for 19 transcription factors. This group included known NEB-associated transcription factor (NF-κB), and a number of transcription factors (such as SP1, ZBP89, NFI, Zf9, MYC, ZBTB7A, FOXF2 and KLF6) that had not been previously reported to be associated with NEB. Based on the present results, 18 new effective candidate trsnacription factors introduced in this study can provide new information to gain a better understanding of the regulatory network involved in NEB.

کلیدواژه‌ها [English]

  • gene expression
  • gene network
  • Microarray
  • RNA-Seq
  • transcription factors
1 . Wathes DC, Cheng Z, Chowdhury W, Fenwick MA, Fitzpatrick R, Morris DG, Patton J and Murphy JJ (2009) Negative energy balance alters global gene expression and immune responses in the uterus of postpartum dairy cows. Physiological Genomics. 39(1): 1-13.
2 . Fatima A, Lynn DJ, Padraic O, Seoighe C and Morris D (2014) The miRNAome of the postpartum dairy cow liver in negative energy balance. BMC Genomics. 15(1): 279-286.
3 . McCabe M, Waters S, Morris D, Kenny D, Lynn D and Creevey C (2012) RNA-seq analysis of differential gene expression in liver from lactating dairy cows divergent in negative energy balance. BMC Genomics. 13(1): 193-204.
4 . McCarthy SD, Waters SM, Kenny DA, Diskin MG, Fitzpatrick R, Patton J, Wathes DC and Morris DG (2010) Negative energy balance and hepatic gene expression patterns in high-yielding dairy cows during the early postpartum period: a global approach. Physiological Genomics. 42(3): 188-199.
5 . Bakhtiarizadeh MR, Moradi-Shahrbabak M and Ebrahimie E (2014) Transcriptional regulatory network analysis of the over-expressed genes in adipose tissue. Genes and Genomics. 36(1): 105-117.
6 . Hosseinpour B, Bakhtiarizadeh MR, Khosravi P and Ebrahimie E (2013) Predicting distinct organization of transcription factor binding sites on the promoter regions: a new genome-based approach to expand human embryonic stem cell regulatory network. Gene. 531(2): 212-219.
7 . Da Wei Huang BTS and Lempicki RA (2008) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols. 4(1): 44-57.
8 . Cartharius K, Frech K, Grote K, Klocke B, Haltmeier M, Klingenhoff A, Frisch M, Bayerlein M and Werner T (2005) MatInspector and beyond: promoter analysis based on transcription factor binding sites. Bioinformatics. 21(13): 2933-2942.
9 . Kelly EE, Giordano F, Horgan CP, Jollivet F, Raposo G and McCaffrey MW (2012) Rab30 is required for the morphological integrity of the Golgi apparatus. Biology of the Cell. 104(2): 84-101.
10 . Hato T, Tabata M and Oike Y (2008) The role of angiopoietin-like proteins in angiogenesis and metabolism. Trends in Cardiovascular Medicine. 18(1): 6-14.
11 . Omori Y, Imai J, Watanabe M, Komatsu T, Suzuki Y, Kataoka K, Watanabe S, Tanigami A and Sugano S (2001) CREB-H: a novel mammalian transcription factor belonging to the CREB/ATF family and functioning via the box-B element with a liver-specific expression. Nucleic Acids Resarch. 29(10): 2154-2162.
12 . Grasfeder LL, Gaillard S, Hammes SR, Ilkayeva O, Newgard CB, Hochberg RB, Dwyer MA, Chang C-y and McDonnell DP (2009) Fasting-induced hepatic production of DHEA is regulated by PGC-1α, ERRα, and HNF4α. Molecular Endocrinology. 23(8): 1171-1182.
13 . Chiba M, Murata S, Myronovych A, Kohno K, Hiraiwa N, Nishibori M, Yasue H and Ohkohchi N (2011) Elevation and characteristics of Rab30 and S100a8/S100a9 expression in an early phase of liver regeneration in the mouse. International Journal of Molecular Medicine. 27(4): 567-574.
14 . Fatima A (2014) Analysis of hepatic microRNA expression in postpartum dairy cows in negative energy balance: National University of Ireland, Galway.
15 . Arner P (2003) The adipocyte in insulin resistance: key molecules and the impact of the thiazolidinediones. Trends in Endocrinology and Metabolism. 14(3): 137-145.
16 . Gao H, Mejhert N, Fretz JA, Arner E, Lorente-Cebrián S, Ehrlund A, Dahlman-Wright K, Gong X, Strömblad S and Douagi I (2014) Early B Cell Factor 1 Regulates Adipocyte Morphology and Lipolysis in White Adipose Tissue. Cell Metabolism. 19(6): 981-992.
17 . Dang CV (2013) MYC, metabolism, cell growth, and tumorigenesis. Cold Spring Harbor Perspectives in Medicine. 3(8): a014217.
18 . Fretz JA, Nelson T, Xi Y, Adams DJ, Rosen CJ and Horowitz MC (2010) Altered metabolism and lipodystrophy in the early B-cell factor 1-deficient mouse. Endocrinology. 151(4): 1611-1621.
19 . Haldar SM, Jeyaraj D, Anand P, Zhu H, Lu Y, Prosdocimo DA, Eapen B, Kawanami D, Okutsu M and Brotto L (2012) Kruppel-like factor 15 regulates skeletal muscle lipid flux and exercise adaptation. Proceedings of the National Academy of Sciences. 109(17): 6739-6744.
20 . Bechmann LP, Vetter D, Ishida J, Hannivoort RA, Lang UE, Kocabayoglu P, Fiel MI, Muñoz U, Patman GL and Ge F (2013) Post-transcriptional activation of PPAR alpha by KLF6 in hepatic steatosis. Journal of hepatology. 58(5): 1000-1006.
21 . Yang X, Zu X, Tang J, Xiong W, Zhang Y, Liu F and Jiang Y (2012) Zbtb7 suppresses the expression of CDK2 and E2F4 in liver cancer cells: Implications for the role of Zbtb7 in cell cycle regulation. Molecular Medicine Reports. 5(6): 1475-1480.
22 . Graves R, Tontonoz P, Ross S and Spiegelman B (1991) Identification of a potent adipocyte-specific enhancer: involvement of an NF-1-like factor. Genes and Development. 5(3): 428-437.
23 . Mukesh M, Bionaz M, Graugnard D, Drackley J and Loor J (2010) Adipose tissue depots of Holstein cows are immune responsive: inflammatory gene expression in vitro. Domestic Animal Endocrinology. 38(3): 168-178.
24 . Zhang F and Du G (2012) Dysregulated lipid metabolism in cancer. World Journal of Biological Chemistry. 3(8): 167.
25 . Heldin C-H, Miyazono K and Ten Dijke P (1997) TGF-β signalling from cell membrane to nucleus through SMAD proteins. Nature. 390(6659): 465-471.
26 . Derdak Z, Villegas KA, Harb R, Wu AM, Sousa A and Wands JR (2013) Inhibition of p53 attenuates steatosis and liver injury in a mouse model of non-alcoholic fatty liver disease. Journal of Hepatology. 58(4): 785-791.
27 . Go G-w and Mani A (2012) Low-density lipoprotein receptor (LDLR) family orchestrates cholesterol homeostasis. The Yale Journal of Biology and Medicine. 85(1): 19-28.
28 . Kaur K, Pandey AK, Srivastava S, Srivastava AK and Datta M (2011) Comprehensive miRNome and in silico analyses identify the Wnt signaling pathway to be altered in the diabetic liver. Molecular BioSystems. 7(12): 3234-3244.
29 . Barthel A, Schmoll D and Unterman TG (2005) FoxO proteins in insulin action and metabolism. Trends in Endocrinology and Metabolism. 16(4): 183-189.