期刊论文详细信息
BMC Medical Genomics
PD_NGSAtlas: a reference database combining next-generation sequencing epigenomic and transcriptomic data for psychiatric disorders
Xia Li3  Chun Xu1  Juan Xu3  Zishan Wang3  Juan Chen3  Peter M Thompson2  Jianping Lu3  Hong Chen3  Yongsheng Li3  Zheng Zhao3 
[1] Department of Pediatrics, Paul L. Foster School of Medicine, Texas Tech University Health Science Center, El Paso, TX, USA;Southwest Brain Bank, Department of Psychiatry, UTHSCSA, San Antonio, TX, USA;College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
关键词: Blood;    Brain;    Epigenomic and transcriptomic data;    Next-generation sequencing;    Bipolar disorder;    Schizophrenia;   
Others  :  1090039
DOI  :  10.1186/s12920-014-0071-z
 received in 2014-09-22, accepted in 2014-12-11,  发布年份 2014
【 摘 要 】

Background

Psychiatric disorders such as schizophrenia (SZ) and bipolar disorder (BP) are projected to lead the global disease burden within the next decade. Several lines of evidence suggest that epigenetic- or genetic-mediated dysfunction is frequently present in these disorders. To date, the inheritance patterns have been complicated by the problem of integrating epigenomic and transcriptomic factors that have yet to be elucidated. Therefore, there is a need to build a comprehensive database for storing epigenomic and transcriptomic data relating to psychiatric disorders.

Description

We have developed the PD_NGSAtlas, which focuses on the efficient storage of epigenomic and transcriptomic data based on next-generation sequencing and on the quantitative analyses of epigenetic and transcriptional alterations involved in psychiatric disorders. The current release of the PD_NGSAtlas contains 43 DNA methylation profiles and 37 transcription profiles detected by MeDIP-Seq and RNA-Seq, respectively, in two distinct brain regions and peripheral blood of SZ, BP and non-psychiatric controls. In addition to these data that were generated in-house, we have included, and will continue to include, published DNA methylation and gene expression data from other research groups, with a focus on psychiatric disorders. A flexible query engine has been developed for the acquisition of methylation profiles and transcription profiles for special genes or genomic regions of interest of the selected samples. Furthermore, the PD_NGSAtlas offers online tools for identifying aberrantly methylated and expressed events involved in psychiatric disorders. A genome browser has been developed to provide integrative and detailed views of multidimensional data in a given genomic context, which can help researchers understand molecular mechanisms from epigenetic and transcriptional perspectives. Moreover, users can download the methylation and transcription data for further analyses.

Conclusions

The PD_NGSAtlas aims to provide storage of epigenomic and transcriptomic data as well as quantitative analyses of epigenetic and transcriptional alterations involved in psychiatric disorders. The PD_NGSAtlas will be a valuable data resource and will enable researchers to investigate the pathophysiology and aetiology of disease in detail. The database is available at http://bioinfo.hrbmu.edu.cn/pd_ngsatlas/ webcite.

【 授权许可】

   
2014 Zhao et al.; licensee BioMed Central.

附件列表
Files Size Format View
Figure 2. 61KB Image download
Figure 4. 113KB Image download
Figure 3. 144KB Image download
Figure 2. 82KB Image download
Figure 1. 90KB Image download
【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 2.

【 参考文献 】
  • [1]Patel V, Prince M: Global mental health: a new global health field comes of age. JAMA 2010, 303(19):1976-1977.
  • [2]Burmeister M, McInnis MG, Zollner S: Psychiatric genetics: progress amid controversy. Nat Rev Genet 2008, 9(7):527-540.
  • [3]Karlsgodt KH, Sun D, Jimenez AM, Lutkenhoff ES, Willhite R, van Erp TG, Cannon TD: Developmental disruptions in neural connectivity in the pathophysiology of schizophrenia. Dev Psychopathol 2008, 20(4):1297-1327.
  • [4]Lewis DA, Levitt P: Schizophrenia as a disorder of neurodevelopment. Annu Rev Neurosci 2002, 25:409-432.
  • [5]Craddock N, O'Donovan MC, Owen MJ: The genetics of schizophrenia and bipolar disorder: dissecting psychosis. J Med Genet 2005, 42(3):193-204.
  • [6]Kushima I, Aleksic B, Ito Y, Nakamura Y, Nakamura K, Mori N, Kikuchi M, Inada T, Kunugi H, Nanko S, Kato T, Yoshikawa T, Ujike H, Suzuki M, Iwata N, Ozaki N: Association study of ubiquitin-specific peptidase 46 (USP46) with bipolar disorder and schizophrenia in a Japanese population. J Hum Genet 2010, 55(3):133-136.
  • [7]Pidsley R, Mill J: Epigenetic studies of psychosis: current findings, methodological approaches, and implications for postmortem research. Biol Psychiatry 2011, 69(2):146-156.
  • [8]Bird A: DNA methylation patterns and epigenetic memory. Genes Dev 2002, 16(1):6-21.
  • [9]Nan X, Ng HH, Johnson CA, Laherty CD, Turner BM, Eisenman RN, Bird A: Transcriptional repression by the methyl-CpG-binding protein MeCP2 involves a histone deacetylase complex. Nature 1998, 393(6683):386-389.
  • [10]Suzuki MM, Bird A: DNA methylation landscapes: provocative insights from epigenomics. Nat Rev Genet 2008, 9(6):465-476.
  • [11]Li E, Bestor TH, Jaenisch R: Targeted mutation of the DNA methyltransferase gene results in embryonic lethality. Cell 1992, 69(6):915-926.
  • [12]Guo JU, Ma DK, Mo H, Ball MP, Jang MH, Bonaguidi MA, Balazer JA, Eaves HL, Xie B, Ford E, Zhang K, Ming GL, Gao Y, Song H: Neuronal activity modifies the DNA methylation landscape in the adult brain. Nat Neurosci 2011, 14(10):1345-1351.
  • [13]Pidsley R, Dempster EL, Mill J: Brain weight in males is correlated with DNA methylation at IGF2. Mol Psychiatry 2010, 15(9):880-881.
  • [14]Lubin FD, Roth TL, Sweatt JD: Epigenetic regulation of BDNF gene transcription in the consolidation of fear memory. J Neurosci 2008, 28(42):10576-10586.
  • [15]Isles AR, Davies W, Wilkinson LS: Genomic imprinting and the social brain. Philos Trans R Soc Lond B Biol Sci 2006, 361(1476):2229-2237.
  • [16]Connor CM, Akbarian S: DNA methylation changes in schizophrenia and bipolar disorder. Epigenetics 2008, 3(2):55-58.
  • [17]Chen WG, Chang Q, Lin Y, Meissner A, West AE, Griffith EC, Jaenisch R, Greenberg ME: Derepression of BDNF transcription involves calcium-dependent phosphorylation of MeCP2. Science 2003, 302(5646):885-889.
  • [18]Martinowich K, Hattori D, Wu H, Fouse S, He F, Hu Y, Fan G, Sun YE: DNA methylation-related chromatin remodeling in activity-dependent BDNF gene regulation. Science 2003, 302(5646):890-893.
  • [19]Mill J, Tang T, Kaminsky Z, Khare T, Yazdanpanah S, Bouchard L, Jia P, Assadzadeh A, Flanagan J, Schumacher A, Wang SC, Petronis A: Epigenomic profiling reveals DNA-methylation changes associated with major psychosis. Am J Hum Genet 2008, 82(3):696-711.
  • [20]Grayson DR, Jia X, Chen Y, Sharma RP, Mitchell CP, Guidotti A, Costa E: Reelin promoter hypermethylation in schizophrenia. Proc Natl Acad Sci U S A 2005, 102(26):9341-9346.
  • [21]Iwamoto K, Bundo M, Yamada K, Takao H, Iwayama-Shigeno Y, Yoshikawa T, Kato T: DNA methylation status of SOX10 correlates with its downregulation and oligodendrocyte dysfunction in schizophrenia. J Neurosci 2005, 25(22):5376-5381.
  • [22]Xiao Y, Camarillo C, Ping Y, Arana TB, Zhao H, Thompson PM, Xu C, Su BB, Fan H, Ordonez J, Wang L, Mao C, Zhang Y, Cruz D, Escamilla MA, Li X: The DNA methylome and transcriptome of different brain regions in schizophrenia and bipolar disorder. PLoS One 2014, 9(4):e95875.
  • [23]Y Li, Camarillo C, J Xu, TB Arana, Y Xiao, Z Zhao, H Chen, M Ramirez, J Zavala, MA Escamilla, R Armas, R Mendoza, A Ontiveros, H Nicolini, A Jerez, LP. Rubin, X Li, C Xu: Genome-wide methylome analyses reveal novel epigenetic regulation patterns in schizophrenia and bipolar disorder.Biomed Res Int 2014, http://www.hindawi.com/journals/bmri/aa/201587/.
  • [24]Hackenberg M, Barturen G, Oliver JL: NGSmethDB: a database for next-generation sequencing single-cytosine-resolution DNA methylation data. Nucleic Acids Res 2011, 39(Database issue):D75-79.
  • [25]Zou D, Sun S, Li R, Liu J, Zhang J, Zhang Z: MethBank: a database integrating next-generation sequencing single-base-resolution DNA methylation programming data.Nucleic Acids Res 2014, doi:10.1093/nar/gku920.
  • [26]Lv J, Liu H, Su J, Wu X, Liu H, Li B, Xiao X, Wang F, Wu Q, Zhang Y: DiseaseMeth: a human disease methylation database. Nucleic Acids Res 2012, 40(Database issue):D1030-1035.
  • [27]Gu F, Doderer MS, Huang YW, Roa JC, Goodfellow PJ, Kizer EL, Huang TH, Chen Y: CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers. PLoS One 2013, 8(4):e60980.
  • [28]Xin Y, Chanrion B, O'Donnell AH, Milekic M, Costa R, Ge Y, Haghighi FG: MethylomeDB: a database of DNA methylation profiles of the brain. Nucleic Acids Res 2012, 40(Database issue):D1245-1249.
  • [29]Rajkowska G, Goldman-Rakic PS: Cytoarchitectonic definition of prefrontal areas in the normal human cortex: II. Variability in locations of areas 9 and 46 and relationship to the Talairach Coordinate System. Cerebral cortex 1995, 5(4):323-337.
  • [30]Karolchik D, Hinrichs AS, Furey TS, Roskin KM, Sugnet CW, Haussler D, Kent WJ: The UCSC Table Browser data retrieval tool. Nucleic Acids Res 2004, 32(Database issue):D493-496.
  • [31]Bernstein BE, Birney E, Dunham I, Green ED, Gunter C, Snyder M: An integrated encyclopedia of DNA elements in the human genome. Nature 2012, 489(7414):57-74.
  • [32]Li R, Yu C, Li Y, Lam TW, Yiu SM, Kristiansen K, Wang J: SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 2009, 25(15):1966-1967.
  • [33]Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS: Model-based analysis of ChIP-Seq (MACS). Genome Biol 2008, 9(9):R137. BioMed Central Full Text
  • [34]Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B: Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 2008, 5(7):621-628.
  • [35]Robinson MD, McCarthy DJ, Smyth GK: edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26(1):139-140.
  • [36]Wang L, Feng Z, Wang X, Wang X, Zhang X: DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 2010, 26(1):136-138.
  • [37]Benjamini Y, Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing.J Roy Stat Soc 1995, 57(1):289–300.
  • [38]Skinner ME, Uzilov AV, Stein LD, Mungall CJ, Holmes IH: JBrowse: a next-generation genome browser. Genome Res 2009, 19(9):1630-1638.
  • [39]Sainz J, Mata I, Barrera J, Perez-Iglesias R, Varela I, Arranz MJ, Rodriguez MC, Crespo-Facorro B: Inflammatory and immune response genes have significantly altered expression in schizophrenia. Mol Psychiatry 2013, 18(10):1056-1057.
  • [40]Schultz CC, Nenadic I, Riley B, Vladimirov VI, Wagner G, Koch K, Schachtzabel C, Muhleisen TW, Basmanav B, Nothen MM, Deufel T, Kiehntopf M, Rietschel M, Reichenbach JR, Cichon S, Schlosser RG, Sauer H: ZNF804A and cortical structure in schizophrenia: in vivo and postmortem studies. Schizophr Bull 2014, 40(3):532-541.
  • [41]Hayashi-Takagi A, Vawter MP, Iwamoto K: Peripheral biomarkers revisited: integrative profiling of peripheral samples for psychiatric research. Biol Psychiatry 2014, 75(12):920-928.
  • [42]Sullivan PF, Daly MJ, O'Donovan M: Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat Rev Genet 2012, 13(8):537-551.
  • [43]Sullivan PF, Fan C, Perou CM: Evaluating the comparability of gene expression in blood and brain. Am J Med Genet B Neuropsychiatr Genet 2006, 141B(3):261-268.
  • [44]Rollins B, Martin MV, Morgan L, Vawter MP: Analysis of whole genome biomarker expression in blood and brain. Am J Med Genet B Neuropsychiatr Genet 2010, 153B(4):919-936.
  • [45]Davies MN, Volta M, Pidsley R, Lunnon K, Dixit A, Lovestone S, Coarfa C, Harris RA, Milosavljevic A, Troakes C, Al-Sarraj S, Dobson R, Schalkwyk LC, Mill J: Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood. Genome Biol 2012, 13(6):R43. BioMed Central Full Text
  • [46]Bell JT, Tsai PC, Yang TP, Pidsley R, Nisbet J, Glass D, Mangino M, Zhai G, Zhang F, Valdes A, Shin SY, Dempster EL, Murray RM, Grundberg E, Hedman AK, Nica A, Small KS, Dermitzakis ET, McCarthy MI, Mill J, Spector TD, Deloukas P: Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLoS genetics 2012, 8(4):e1002629.
  • [47]Davies MN, Krause L, Bell JT, Gao F, Ward KJ, Wu H, Lu H, Liu Y, Tsai PC, Collier DA, Murphy T, Dempster E, Mill J, Battle A, Mostafavi S, Zhu X, Henders A, Byrne E, Wray NR, Martin NG, Spector TD, Wang J: Hypermethylation in the ZBTB20 gene is associated with major depressive disorder. Genome Biol 2014, 15(4):R56. BioMed Central Full Text
  文献评价指标  
  下载次数:20次 浏览次数:6次