Predicting CpG Islands and Their Relationship with Genomic Feature in Cattle by Hidden Markov Model Algorithm
محورهای موضوعی : Camel
A. برازنده
1
(
Department of Animal Science, Shahid Bahonar University of Kerman, Kerman, Iran|Department of Animal Science, University of Jiroft, Jiroft, Iran
)
م.ر. محمدآبادی
2
(
Department of Animal Science, Shahid Bahonar University of Kerman, Kerman, Iran
)
م. قادری
3
(
Department of Animal Science, University of Yasouj, Yasouj, Iran
)
ح. نظام آبادی پور
4
(
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
)
کلید واژه: cattle, genome, CpG islands, epigenomic, HMM,
چکیده مقاله :
Cattle supply an important source of nutrition for humans in the world. CpG islands (CGIs) are very important and useful, as they carry functionally relevant epigenetic loci for whole genome studies. As a matter of fact, there have been no formal analyses of CGIs at the DNA sequence level in cattle genomes and therefore this study was carried out to fill the gap. We used hidden markov model algorithm to detect CGIs. The total number of predicted CGIs for cattle was 90668. The number of detected CGIs and CGI densities downwardly varied across chromosomes. Chromosome 25 had the largest number of CGIs (4556) and the highest CGI density (106.20 CGIs/Mb).A significant positive correlation observed among CGI densities with guanine-cytosine (GC) content, ObsCpG/ExpCpG, recombination rate and gene density. When the size of chromosomes increased, the CGI densities decreased and a trend of higher CGI densities in the telomeric regions observed. This feature may be the reason of a positive correlation between CGI density and recombination rate. To detect information on CGI density differences between cattle and other vertebrate genomes, CGI density was also scanned in eleven vertebrate genomes. The CGI densities varied greatly among genomes. These discoveries may contribute to a better understanding of epigenomic role of CGIs and their molecular evolution in the cattle.
گاو یکی از مهمترین تأمین کنندههای مواد غذایی و مغذی بشر در جهان است. جزایر CpG نواحی مهم و مفیدی هستند که دارای ارتباط عملکردی با رویدادهای مهم اپی ژنتیکی در سطح ژنوم میباشند. با توجه به اینکه تاکنون جزایر CpG در سطح ژنوم گاو بررسی نشدهاند هدف از این مطالعه بررسی این جزایر در ژنوم گاو با استفاده از مدلهای محفی مارکوف است. تعداد 90668 جزیره CpG در ژنوم گاو پیشبینی گردید. تغییرات تعداد و تراکم جزایر CpG در طول کروموزومها بسیار کم بود. کروموزوم 25 دارای بیشترین تعداد (4556) و تراکم (CGIs/Mb 106٫20) جزایر CpG بود. همبستگی مثبت و معنیدار بین تراکم جزایر CpG با محتوی GC، نسبت مشاهده شده به مورد انتظار CpG، نرخ نوترکیبی و تراکم ژن مشاهده گردید. با افزایش سایز کروموزمها تراکم جزایر CpG کاهش یافت و همچنین تراکم جزایر CpG در نواحی تلومری کروموزمها بیشتر از سایر قسمتها مشاهده گردید که میتواند علت همبستگی مثبت بین نرخ نوترکیبی و تراکم جزایر CpG باشد. جهت یافتن تفاوتهای جزایر CpG بین ژنوم گاو و سایر مهرهداران جزایر CpG در یازده مهرهدار دیگر بررسی گردید. تغییرات تراکم جزایر CpG در بین حیوانات مورد مطالعه بسیار متفاوت بود. یافتههای این مطالعه میتواند در درک بهتر نقش اپی ژنتیکی و نقش تکامل مولکولی جزایر CpG در ژنوم گاو مؤثر باشد.
Amiri Roudbar M., Mohammadabadi M.R. and Salmani V. (2015). Epigenetics: a new challenge in animal breeding. Genet. Third Mel. 12(4), 3736-3751.
Archibald A.L., Cockett N.E., Dalrymple B.P., Faraut T., Kijas J.W., Maddox J.F., McEwan J.C., Hutton Oddy V., Raadsma H.W. and Wade C. (2010). The sheep genome reference sequence: a work in progress. Anim. Genet. 41, 449-453.
Chuang L.Y., Huang H.C., Lin M.C. and Yang C.H. (2011). Particle swarm optimization with reinforcement learning for the prediction of CpG islands in the human genome. PLoS One. 6, 21-36.
Chuang L.Y., Yang C.H. and Lin M.C. (2012). CpGPAP: CpG island predictor analysis platform. BMC Genet. 13, 13.
Deaton A. and Bird A. (2011). CpG islands and the regulation of transcription. Gen. Dev. 25, 1010-1022.
Dong Y., Xie M., Jiang Y., Xiao N., Du X., Zhang W., Tosser-Klopp G., Wang J., Yang S. and Liang J. (2013). Sequencing and automated whole-genome optical mapping of the genome of a domestic goat (Capra hircus). Nat. Biotechnol. 31, 135-141.
Elsik C.G., Tellam R.L., Worley K.C., Gibbs R.A., Muzny D.M., Weinstock G.M., Adelson D.L., Eichler E.E., Elnitski L. and Guigó R. (2009). The genome sequence of taurine cattle: a window to ruminant biology and evolution. Science. 324, 522-528.
Gardiner-Garden M. and Frommer M. (1987). CpG islands in vertebrate genomes. J. Mol. Biol. 196, 261-282.
Glass J.L., Thompson R.F., Khulan B., FigueroaM.E., Olivier E. N., Oakley E.J., Zant G. Van Bouhassira E.E., Melnick A. and Golden A. (2007). CG dinucleotide clustering is a species-specific property of the genome. Nucleic Acids. Res. 35, 6798-6807.
Hackenberg M., Previti C., Luque-Escamilla P.L., Carpena P., Martinez-Aroza J. and Oliver J.L. (2006). CpGcluster: a distance-based algorithm for CpG island detection. BMC Bioinformatics. 7, 446.
Hackenberg M., Barturen G., Carpena P., Luque-Escamilla P.L., Previti C. and Oliver J.L. (2010). Prediction of CpG island function: CpG clustering vs. sliding window methods. BMC Genom. 11, 327.
Han L., Su B., Li W.H. and Zhao Z. (2008). CpG island density and its correlations with genomic features in mammalian genomes. Genome. Biol. 9(5), 1-12.
Han L. and Zhao Z. (2008). Comparative analysis of CpG islands in four fish genomes. Comp. Funct. Genomics. 2008, 565631.
Han L. and Zhao Z. (2009). Contrast features of CpG islands in the promoter and other regions in the dog genome. Genomics. 94, 117-124.
Hillier L.W., Miller W., Birney E., Warren W., Hardison R.C., Ponting C.P., Bork P., Burt D.W., Groenen M.A.M. and DelanyM.E. (2004). Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature. 432, 695-716.
Irizarry R.A., Wu H. and Feinberg A.P. (2009). A species-generalized probabilistic model-based definition of CpG islands. Mamm. Genome. 20, 674-680.
Jensen-Seaman M.I., Furey T.S., Payseur B.A., Lu Y., Roskin K.M., Chen C., Thomas M.A., Haussler D. and Jacob H.J. (2004). Comparative recombination rates in the rat, mouse, and human Genomes. Genome. Res. 14, 528-538.
Jirimutu Wang Z., Ding G., Chen G., Sun Y., Sun Z., Zhang H., Wang L., Hasi S. and Zhang Y. (2012). Genome sequences of wild and domestic bactrian camels. Nat. Commun. 3, 1202-1212.
McQueen H.A., Fantes J., Cross S.H., Clark V.H., Archibald A.L. and Bird A.P. (1996). CpG islands of chicken are concentrated on microchromosomes. Nat. Genet. 12, 321-324.
Medvedeva Y.A., Fridman M.V, Oparina N.J., Malko D.B., Ermakova E.O., Kulakovskiy I.V, Heinzel A. and Makeev V.J. (2010). Intergenic, gene terminal and intragenic CpG islands in the human genome. BMC Genomics. 11, 48.
Poissant J., Hogg J.T., Davis C.S., Miller J.M., Maddox J.F. and Coltman D.W. (2010). Genetic linkage map of a wild genome: genomic structure, recombination and sexual dimorphism in bighorn sheep. BMC Genomics. 11, 524.
Quinlan A.R. and Hall I.M. (2010). BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 26, 841-842.
Rabiner L.R. (1989). Tutorial on hmm and applications. IEEE J. 77, 257-286.
Rao Y.S., Chai X.W., Wang Z.F., Nie Q.H. and Zhang X.Q. (2013). Impact of GC content on gene expression pattern in chicken. Genet. Sel. Evol. 45, 9.
Rice P., Longden I. and Bleasby A. (2000). EMBOSS: the European molecular biology open software suite. Trends. Genet. 16, 276-277.
Saito Y., Nagae G., Motoi N., Miyauchi E., Ninomiya H., Uehara H., Mun M., Okumura S., Ohyanagi F. and Nishio M. (2016). Prognostic significance of CpG island methylator phenotype in surgically resected small cell lung carcinoma. Cancer Sci. 107(3), 320-325.
Su J., Zhang Y., Lv J., Liu H., Tang X., Wang F., Qi Y., Feng Y., and Li X. (2010). CpG_MI: a novel approach for identifying functional CpG islands in mammalian genomes. Nucleic Acids. Res. 38, 6.
Takai D. and Jones P.A. (2002). Comprehensive analysis of CpG islands in human chromosomes 21 and 22. Proc. Natl. Acad. Sci. USA. 99, 3740-3745.
Tan B., Yin Y., Liu Z., Tang W., Xu H., Kong X., Li X., Yao K., Gu W. and Smith S.B. (2011). Dietary L-arginine supplementation differentially regulates expression of lipid-metabolic genes in porcine adipose tissue and skeletal muscle. J. Nutr. Biochem. 22, 441-445.
Tortereau F., Servin B., Frantz L., Megens H.J., Milan D., Rohrer G., Wiedmann R., Beever J., Archibald A.L. and Schook L.B. (2012). A high density recombination map of the pig reveals a correlation between sex-specific recombination and GC content. BMC Genomics. 13, 586.
Vercelli D. (2016). Does epigenetics play a role in human asthma? Allergol. Int. 65, 123-126.
Wang Y. and Leung F.C.C. (2004). An evaluation of new criteria for CpG islands in the human genome as gene markers. Bioinformatics. 20, 1170-1177.
Weng Z.Q., Saatchi M., Schnabel R.D., Taylor J.F. and Garrick D.J. (2014). Recombination locations and rates in beef cattle assessed from parent-offspring pairs. Genet. Sel. Evol. 46, 34-41.
Willham R.L. (1986). From husbandry to science: a highly significant facet of our livestock heritage. J. Anim. Sci. 62, 1742-1758.
Wu H., Caffo B., Jaffee H.A., Irizarry R.A. and Feinberg A.P. (2010). Redefining CpG islands using hidden Markov models. Biostatistics. 11, 499-514.
Wu H., Guang X., Al-Fageeh M.B., Cao J., Pan S., Zhou H., Zhang L., Abutarboush M.H., Xing Y. and Xie Z. (2014). Camelid genomes reveal evolution and adaptation to desert environments. Nat. Commun. 5, 5188-5197.
Yang C.H., Lin Y.D., Chiang Y.C. and Chuang L.Y. (2016). A hybrid approach for CpG island detection in the human genome. PLoS One. 11, 23-36.
