基于“天河二号”的水产病原生物信息分析平台构建及其在水产病原分析中的应用

doi:10.16288/j.yczz.15-038

[an error occurred while processing this directive]

HEREDITAS(Beijing) ›› 2015, Vol. 37 ›› Issue (7): 702-710.doi: 10.16288/j.yczz.15-038

• Research Articles • Previous Articles Next Articles

Construction and application of bioinformatic analysis platform for aquatic pathogen based on the MilkyWay-2 supercomputer

Xiang Fang, Ningqiu Li, Xiaozhe Fu, Kaibin Li, Qiang Lin, Lihui Liu, Cunbin Shi, Shuqin Wu

Key Laboratory of Aquatic Animal Immune Technology of Guangdong Province,Key Laboratory of Fishery Drug Development of Ministry of Agriculture, Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510380, China

Received:2015-01-16 Revised:2015-04-01 Online:2015-07-20 Published:2015-07-20

Abstract

Abstract: As a key component of life science, bioinformatics has been widely applied in genomics, transcriptomics, and proteomics. However, the requirement of high-performance computers rather than common personal computers for constructing a bioinformatics platform significantly limited the application of bioinformatics in aquatic science. In this study, we constructed a bioinformatic analysis platform for aquatic pathogen based on the MilkyWay-2 supercomputer. The platform consisted of three functional modules, including genomic and transcriptomic sequencing data analysis, protein structure prediction, and molecular dynamics simulations. To validate the practicability of the platform, we performed bioinformatic analysis on aquatic pathogenic organisms. For example, genes of Flavobacterium johnsoniae M168 were identified and annotated via Blast searches, GO and InterPro annotations. Protein structural models for five small segments of grass carp reovirus HZ-08 were constructed by homology modeling. Molecular dynamics simulations were performed on out membrane protein A of Aeromonas hydrophila, and the changes of system temperature, total energy, root mean square deviation and conformation of the loops during equilibration were also observed. These results showed that the bioinformatic analysis platform for aquatic pathogen has been successfully built on the MilkyWay-2 supercomputer. This study will provide insights into the construction of bioinformatic analysis platform for other subjects.

Key words: bioinformatics, MilkyWay-2, aquatic pathogen

Xiang Fang, Ningqiu Li, Xiaozhe Fu, Kaibin Li, Qiang Lin, Lihui Liu, Cunbin Shi, Shuqin Wu. Construction and application of bioinformatic analysis platform for aquatic pathogen based on the MilkyWay-2 supercomputer[J]. HEREDITAS(Beijing), 2015, 37(7): 702-710.

References

[1] Dolled-Filhart MP, Lee M, Jr., Ouyang CW, Haraksingh RR, Lin JC. Computational and bioinformatics frameworks for next-generation whole exome and genome sequencing. ScientificWorldJournal , 2013, 2013: Article ID 730210.
[2] Bishop ÖT, Adebiyi EF, Alzohairy AM, Everett D, Ghedira K, Ghouila A, Kumuthini J, Mulder NJ, Panji S, Patterton HG. Bioinformatics education-perspectives and challenges out of Africa. Brief Bioinform , 2015, 16(2): 355-364.
[3] Good BM, Su AI. Crowdsourcing for bioinformatics. Bioinformatics , 2013, 29(16): 1925-1933.
[4] Hamada M. Fighting against uncertainty: an essential issue in bioinformatics. Brief Bioinform , 2014: 15(5): 748-767.
[5] Cheng LP, Zhu J, Hui WH, Zhang XK, Honig B, Fang Q, Zhou ZH. Backbone model of an aquareovirus virion by cryo-electron microscopy and bioinformatics. J Mol Biol , 2010, 397(3): 852-863.
[6] Verma AK, Gupta S, Verma S, Mishra A, Nagpure NS, Singh SP, Pathak AK, Sarkar UK, Singh M, Seth PK. Interaction between shrimp and white spot syndrome virus through PmRab7-VP28 complex: an insight using simulation and docking studies. J Mol Model , 2013, 19(3): 1285-1294.
[7] Mu YN, Li MY, Ding F, Ding Y, Ao JQ, Hu SN, Chen XH. De novo characterization of the spleen transcriptome of the large yellow croaker ( Pseudosciaena crocea ) and analysis of the immune relevant genes and pathways involved in the antiviral response. PLoS One , 2014, 9(5): e97471.
[8] Wiens GD, LaPatra SE, Welch TJ, Rexroad C, III, Call DR, Cain KD, LaFrentz BR, Vaisvil B, Schmitt DP, Kapatral V. Complete genome sequence of Flavobacterium psychrophilum strain CSF259-93, used to select rainbow trout for increased genetic resistance against bacterial cold water disease. Genome Announc , 2014, 2(5): e00889-14.
[9] Khemiri A, Lecheheb SA, Chi Song PC, Jouenne T, Cosette P. Proteomic regulation during Legionella pneumophila biofilm development: decrease of virulence factors and enhancement of response to oxidative stress. J Water Health , 2014, 12(2): 242-253.
[10] Liao XK. MilkyWay-2: back to the world Top 1. Front Comput Sci , 2014, 8(3): 343-344.
[11] Liao XK, Xiao LQ, Yang CQ, Lu YT. MilkyWay-2 supercomputer: system and application. Front Comput Sci , 2014, 8(3): 345-356.
[12] Pang ZB, Xie M, Zhang J, Zheng Y, Wang GB, Dong DZ, Suo G. The TH Express high performance interconnect networks. Front Comput Sci , 2014, 8(3): 357-366.
[13] Xu WX, Lu YT, Li Q, Zhou EQ, Song ZL, Dong Y, Zhang W, Wei DP, Zhang XM, Chen HT, Xing JY, Yuan Y. Hybrid hierarchy storage system in MilkyWay-2 supercomputer. Front Comput Sci , 2014, 8(3): 367-377.
[14] Conesa A, Gotz S. Blast2GO: A comprehensive suite for functional analysis in plant genomics. Int J Plant Genomics , 2008, 2008: 619832.
[15] Jones P, Binns D, Chang HY, Fraser M, Li WZ, McAnulla C, McWilliam H, Maslen J, Mitchell A, Nuka G, Pesseat S, Quinn AF, Sangrador-Vegas A, Scheremetjew M, Yong SY, Lopez R, Hunter S. InterProScan 5: genome-scale protein function classification. Bioinformatics , 2014, 30(9): 1236-1240.
[16] Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res , 2008, 18(5): 821-829.
[17] Luo RB, Liu BH, Xie YL, Li ZY, Huang WH, Yuan JY, He GZ, Chen YX, Pan Q, Liu YJ, Tang JB, Wu GX, Zhang H, Shi YJ, Liu Y, Yu C, Wang B, Lu Y, Han CL, Cheung DW, Yiu SM, Peng SL, Zhu XQ, Liu GM, Liao XK, Li YR, Yang HM, Wang J, Lam TW, Wang J. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. GigaScience , 2012, 1: 18.
[18] Besemer J, Lomsadze A, Borodovsky M. GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res , 2001, 29(12): 2607-2618.
[19] Stanke M, Morgenstern B. AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints. Nucleic Acids Res , 2005, 33(Supp

Metrics

Comments

www.chinagene.cn
备案号：京ICP备09063187号

Construction and application of bioinformatic analysis platform for aquatic pathogen based on the MilkyWay-2 supercomputer

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	Shanshan Wang, Wanyi Zhao, Huixiao Wu, Meng Shu, Jiaxin Yuan, Li Fang, Chao Xu. Research on the variants of FGFR1 and CEP290 genes in idiopathic hypogonadotropin hypogonadism [J]. Hereditas(Beijing), 2022, 44(10): 937-949.
[2]	Hong Xiang, Xiaohu Yang, Liangxia Ai, Yanping Pan, Yong Hu. Bioinformatics analysis of differentially expressed genes on alopecia [J]. Hereditas(Beijing), 2020, 42(2): 172-182.
[3]	Hongqiang Lyu, Lele Hao, Erhu Liu, Zhifang Wu, Jiuqiang Han, Yuan Liu. Current status and future perspectives in bioinformatical analysis of Hi-C data [J]. Hereditas(Beijing), 2020, 42(1): 87-99.
[4]	Chao He,Wenlong Shen,Ping Li,Yan Zhang,Jing Zeng,Zuoming Yin,Zhihu Zhao. Bioinformatics analysis of Alu components at the level of genome 3D structure [J]. Hereditas(Beijing), 2019, 41(3): 254-261.
[5]	Yuansheng Zhang,Lin Xia,Jian Sang,Man Li,Lin Liu,Mengwei Li,Guangyi Niu,Jiabao Cao,Xufei Teng,Qing Zhou,Zhang Zhang. The BIG Data Center’s database resources [J]. Hereditas(Beijing), 2018, 40(11): 1039-1043.
[6]	Xiaohua Xiang, Xinru Wu, Jiangtao Chao, Minglei Yang, Fan Yang, Guo Chen, Guanshan Liu, Yuanying Wang. Genome-wide identification and expression analysis of the WRKY gene family in common tobacco (Nicotiana tabacum L.) [J]. Hereditas(Beijing), 2016, 38(9): 840-856.
[7]	Xiaoxu Li, Cheng Liu, Wei Li, Zenglin Zhang, Xiaoming Gao, Hui Zhou, Yongfeng Guo. Genome-wide identification, phylogenetic analysis and expression profiling of the WOX family genes in Solanum lycopersicum [J]. HEREDITAS(Beijing), 2016, 38(5): 444-460.
[8]	Xue Zhou, Yilan Du, Ping Jin, Fei Ma. Bioinformatic analysis of cancer-related microRNAs and their target genes [J]. HEREDITAS(Beijing), 2015, 37(9): 855-864.
[9]	Hongmei Qiu, Wenyuan Hao, Shuqin Gao, Xiaoping Ma, Yuhong Zheng, Fanfan Meng, Xuhong Fan, Yang Wang, Yueqiang Wang, Shuming Wang. Gene mining of sulfur-containing amino acid metabolic enzymes in soybean [J]. HEREDITAS(Beijing), 2014, 36(9): 934-942.
[10]	Yang Shi, Xiao Xu, Haoyang Li, Qian Xu, Jichen Xu. Bioinformatics analysis of the expansin gene family in rice [J]. HEREDITAS(Beijing), 2014, 36(8): 809-820.
[11]	Lu Qi, Yanqing Ding. Involvement of the CREB5 regulatory network in colorectal cancer metastasis [J]. HEREDITAS(Beijing), 2014, 36(7): 679-684.
[12]	Xianzhi Chen, Yan Wang, Jianlei Shi, Longjing Zhu, Kelei Wang, Jian Xu. Genome-wide identification, sequence characteristic and expression analysis of heat shock factors (HSFs) in cucumber [J]. HEREDITAS, 2014, 36(4): 376-386.
[13]	Yan Cheng, Lin Chen, Xin Cao, Siqimeige Ha, Xiaodong Xie. Expression profiling and functional analysis of hsa-miR-125b and its target genes in drug-resistant cell line of human gastric cancer [J]. HEREDITAS, 2014, 36(2): 119-128.
[14]	Anming Ding, Ling Li, Xu Qu, Tingting Sun, Yaqiong Chen, Peng Zong, Zunqiang Li, Daping Gong, Yuhe Sun. Genome-wide identification and bioinformatic analysis of PPR gene family in tomato [J]. HEREDITAS, 2014, 36(1): 77-84.
[15]	Guangxin Sun, Yushi Luan, Juanjuan Cui. Mining and characterization of miRNAs closely associated with the pathogenicity in tomato [J]. HEREDITAS, 2014, 36(1): 69-76.