نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه علوم دامی، دانشگاه علوم کشاورزی و منابع طبیعی خوزستان، اهواز، ایران
2 دانشیار دانشکدۀ علوم دامی و صنایع غذایی، دانشگاه کشاورزی و منابع طبیعی رامین خوزستان
3 استاد،دانشگاه علوم کشاورزی و منابع طبیعی رامین، تخصص: ژنتیک و اصلاح نژاد دام و طیور
4 دانشگاه علوم کشاورزی و منابع طبیعی خوزستان، تخصص: تغذیه نشخوارکنندگان/گاو شیری/ گوسفند/گاومیش/ روشهای آزمایشگاهی/ کشت پیوسته دو
5 دانشیار،پردیس ابوریحان، تخصص: ژنتیک و اصلاح نژاد دام/ ژنتیک مولکولی/ بیوانفورماتیک
چکیده
هدف این پژوهش شناسایی lncRNAهای دخیل در کنترل فعالیت مسیرهای بیولوژیکی مؤثر در بروز اسیدوز بود. به این منظور دو گروه گوساله شامل گروه شاهد (3 گوساله نر سالم) و گروه بیمار (3 گوساله نر مبتلا به اسیدوز) به‌صورت مقایسهای مورد مطالعه قرار گرفتند. توالی‌یابی جفتی با استفاده از پلاتفرم illumine Hiseq2500 انجام شد. از نرم‌افزار Hisat2 برای هم‌ترازی خوانشها با ژنوم مرجع گاو و بسته نرم‌افزاری StringTie جهت سرهمبندی رونوشتها استفاده شد. با استفاده از توالی‌یابی نسل بعد، 1636 ژن متعلق به lncRNAهای شناخته‌شده بین ژنی شناسایی شد که تغییرات بیان 56 ژن معنیدار بود (05/0P≤). ژنهای همجوار lncRNAهای شناخته‌شده بین ژنی روی ژنوم گاو هلشتاین تعیین شدند. نتایج نشان داد با سطح احتمال 05/0P≤، پنج مسیر بیولوژیکی Apelin signaling pathway، Gap junction، Glucagon signaling pathway، Renin secretion وAGE-RAGE signaling pathway in diabetic complications غنی میشوند. آنالیز عملکرد مولکولی این ژنها نشان داد دو عملکرد مولکولی شامل gap junction channel activity و phosphatidylinositol phospholipase C activity به‌طور معنیدار غنی میشوند. برخی lncRNAها در نمونههای سالم و اسیدوزی بیان متفاوتی داشتند و کاهش pH به‌عنوان محرکی برای فعال‌شدن برخی مسیرهای بیولوژیکی ترارسانی پیام عمل کرد. براساس نتایج حاصل، lncRNAهایی که تفاوت بیان معنیدار در گروه کنترل و اسیدوز دارند با مسیرهای مرتبط با سوخت‌وساز انرژی شکمبه و ترارسانی پیام همراه می‌باشند. از lncRNAها میتوان به‌عنوان عامل پیش‌آگاهی‌دهنده اسیدوز و بیومارکر در اصلاح دام استفاده نمود.
کلیدواژه‌ها
عنوان مقاله [English]
Biological pathways related to known intergenic lncRNAs in calf ruminal samples affected with acidosis
نویسندگان [English]
- Bizhan Mahmoudi 1
- Hedayatollah Roshanfekr 3
- Mohsen Sari 4
- Mohammad Reza Bakhtiarizadeh 5
1 Department of Animal science, Agricultural Sciences and Natural Resources University of Khuzestan, Ahvaz, Iran
3 Department of Animal science, Agricultural Sciences and Natural Resources University of Khuzestan, Ahvaz, Iran
4 Animal Science Department, Agricultural Sciences and Natural Resources University of Khuzestan, Ahvaz, Iran.
5 Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, Tehran, Iran
چکیده [English]
The objective of this study was to identify known intergenic lncRNAs related to biological pathways of acidosis in Holstein calves using ruminal
tissue. Two groups of healthy calves (N=3) and affected by acidosis (N=3) were compared. Paired-end sequencing method was performed using the
Hiseq2500 illumine platform. Hisat2 software was used to align reads to the bovine reference genome and StringTie software package was used to
assemble read files into transcripts. Using next generation sequencing, 1636 genes belonging to known intergenic lncRNAs were identified, of which
56 genes showed significant differential expression (P≤0.05). Neighbor genes of known intergenic lncRNAs were determined on bovine genome.
Analysis of biological pathways and molecular function showed that five biological pathways were significantly (P≤0.05) enriched. These pathways
were Apelin signaling pathway, Gap junction, Glucagon signaling pathway, Renin secretion, and AGE-RAGE signaling pathway. Moreover, two
molecular functions including gap junction channel activity, and phosphatidyl inositol phospholipase C activity were significantly (P≤0.05) enriched.
Some lncRNAs have different expression in healthy and acidosis samples, and the decreased pH acts as a stimulus to activate some biological
signaling pathways. In conclusion, it was indicated that lncRNAs with differential expression between the control group and the group affected by
acidosis are associated with pathways related to rumen energy metabolism and signaling. Identified differentially expressed lncRNAs could be used as
prognostic in acidosis and biomarkers or promising candidates in animal breeding.
کلیدواژه‌ها [English]
- Gene expression pattern
- Illumine
- LncRNA
- Sequencing
- Signaling
2. Bakhtiarizadeh MR and Salami SA (2019) Identification and expression analysis of long noncoding RNAs in fat-tail of sheep breeds. G3: Genes, Genomes, Genetics 9 (4): 1263-1276.
3. Bakhtiarizadeh MR, Hosseinpour B, Arefnezhad B, Shamabadi N and Salami SA (2016) In silico prediction of long intergenic non-coding RNAs in sheep. Genome 59 (4): 263-275.
5. Chapman NA, Dupré DJ and Rainey JK (2014) Theapelin receptor: physiology, pathology, cell signalling, and ligand modulation of a peptide-activated class A GPCR. Biochemistry and cell biology 92 (6): 431-440.
6. Cocco L, FolloMY, Manzoli L and Suh PG (2015) Phosphoinositide-specific phospholipase C in health and disease. Journal of lipid research 56 (10): 1853-1860.
7. Galsgaard KD, Pedersen J, Knop FK, Holst JJ and Albrechtsen NJW (2019) Glucagon Receptor Signaling and Lipid Metabolism. Frontiers in physiology 10:413.
8. Giepmans BN (2006) Role of connexin43- interacting proteins at gap junctions, in Cardiovascular Gap Junctions. Karger Publishers. p. 41-56.
9. Hangauer MJ, Vaughn IW and McManus MT (2013) Pervasive transcription of the human genome produces thousands of previously unidentified long intergenic noncoding RNAs. PLoS genetics 9 (6): e1003569 .
10. Ibeagha-Awemu EM and Zhao X (2015) Epigenetic marks: regulators of livestock phenotypes and conceivable sources of missing variation in livestock improvement programs.Frontiers in genetics 6 302.
11. Kawakami T and Xiao W (2013) Phospholipase C-β in immune cells. Advances in biological regulation 53 (3): 249-257.
12. Kay AM, Simpson CL and Stewart JA (2016) The role of AGE/RAGE signaling in diabetesmediated vascular calcification. Journal of diabetes research 2016: 1-8.
13. Kong L, Zhang Y, Ye ZQ, Lio XQ, Zhao SQ, Wei L and Gao G (2007) CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic acids research 35 (suppl_2): W345- W349.
14. Kudla G, Lipinski L, Caffin F, Helwak A and Zylicz M (2006) High guanine and cytosine content increases mRNA levels in mammalian cells. PLoS biology 4 (6): e180.
15. Leblanc S (2010) Monitoring metabolic health of dairy cattle in the transition period. Journal of reproduction and Development. 56(S): S29-S35.
16. Li A, Zhang J, and Zhou Z (2014) PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme. BMC bioinformatics 15 (1): 311.
17. Li T, Wang S, Wu R, Zhou X, Zhu D and Zhang Y (2012) Identification of long nonprotein coding RNAs in chicken skeletal muscle using next generation sequencing. Genomics 99 (5): 292-298.
18. Mackey E (2013) Effects of ruminal acidosis on rumen papillae transcriptome. University of Delaware, Newark, Delaware, thesis.
19. Mohanty I, Parija SC, Suklabaidya S and Rattan S (2018) Acidosis potentiates endothelium-dependent vasorelaxation and gap junction communication in the superior mesenteric artery. European journal of pharmacology 827: 22-31.
20. Quinn JJ and Chang HY (2016) Unique features of long non-coding RNA biogenesis and function. Nature Reviews Genetics 17 (1): 47.
21. Ransohoff JD, Wei Y and Khavari PA (2018) The functions and unique features of long intergenic non-coding RNA. Nature reviews Molecular cell biology 19 (3): 143.
22. Rao YS, Chai XW, Wang ZF, Nie QH and Zhang XQ (2013) Impact of GC content on gene expression pattern in chicken. Genetics Selection Evolution 45 (1): 9.
23. Sun L, Luo H, Bu D, Zhao C, Liu Y, Chen R and Zhao Y (2013) Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts. Nucleic acids research 41 (17): e166.
24. Sun YY, Cheng M, Xu M, Song LW, Gao M and Hu HL (2018) The effects of subacute ruminal acidosis on rumen epithelium barrier function in dairy goats. Small ruminant research 169: 1-7.
25. Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL and Pachter L (2013) Differential analysis of gene regulation at transcript resolution with RNA-seq. Nature biotechnology 31: 46-53.
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