Additional annotation enhances potential for biologically-relevant analysis of the Illumina Infinium HumanMethylation450 BeadChip array

Epigenetics & Chromatin

Michael S Kobor²  Wendy P Robinson¹  Carolyn J Brown¹  Eldon Emberly³  Pau Farré³  Lucia L Lam²  Allison M Cotton¹  E Magda Price¹ 

[1] Department of Medical Genetics, University of British Columbia, 2329 West Mall, Vancouver, BC, V6T 1Z3, Canada;Centre for Molecular Medicine and Therapeutics, 950 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada;Department of Physics, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada

关键词: 450 k;    Repetitive elements;    Tissue-specific DNA methylation;    CpG enrichment;    Annotation;    CpG islands;    Polymorphic probes;    non-specific probes;    DNA methylation;    Infinium HumanMethylation450 BeadChip array;   

Others  :  811593
DOI  :  10.1186/1756-8935-6-4

 received in 2012-11-17, accepted in 2013-02-13,  发布年份 2013

【 摘 要 】

Background

Measurement of genome-wide DNA methylation (DNAm) has become an important avenue for investigating potential physiologically-relevant epigenetic changes. Illumina Infinium (Illumina, San Diego, CA, USA) is a commercially available microarray suite used to measure DNAm at many sites throughout the genome. However, it has been suggested that a subset of array probes may give misleading results due to issues related to probe design. To facilitate biologically significant data interpretation, we set out to enhance probe annotation of the newest Infinium array, the HumanMethylation450 BeadChip (450 k), with >485,000 probes covering 99% of Reference Sequence (RefSeq) genes (National Center for Biotechnology Information (NCBI), Bethesda, MD, USA). Annotation that was added or expanded on includes: 1) documented SNPs in the probe target, 2) probe binding specificity, 3) CpG classification of target sites and 4) gene feature classification of target sites.

Results

Probes with documented SNPs at the target CpG (4.3% of probes) were associated with increased within-tissue variation in DNAm. An example of a probe with a SNP at the target CpG demonstrated how sample genotype can confound the measurement of DNAm. Additionally, 8.6% of probes mapped to multiple locations in silico. Measurements from these non-specific probes likely represent a combination of DNAm from multiple genomic sites. The expanded biological annotation demonstrated that based on DNAm, grouping probes by an alternative high-density and intermediate-density CpG island classification provided a distinctive pattern of DNAm. Finally, variable enrichment for differentially methylated probes was noted across CpG classes and gene feature groups, dependant on the tissues that were compared.

Conclusion

DNAm arrays offer a high-throughput approach for which careful consideration of probe content should be utilized to better understand the biological processes affected. Probes containing SNPs and non-specific probes may affect the assessment of DNAm using the 450 k array. Additionally, probe classification by CpG enrichment classes and to a lesser extent gene feature groups resulted in distinct patterns of DNAm. Thus, we recommend that compromised probes be removed from analyses and that the genomic context of DNAm is considered in studies deciphering the biological meaning of Illumina 450 k array data.

【 授权许可】

   
2013 Price et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

【 参考文献 】

• [1]Dempster EL, Pidsley R, Schalkwyk LC, Owens S, Georgiades A, Kane F, Kalidindi S, Picchioni M, Kravariti E, Toulopoulou T, Murray RM, Mill J: Disease-associated epigenetic changes in monozygotic twins discordant for schizophrenia and bipolar disorder. Hum Mol Genet 2011, 20(24):4786-4796.
• [2]Hansen KD, Timp W, Bravo HC, Sabunciyan S, Langmead B, McDonald OG, Wen B, Wu H, Liu Y, Diep D, Briem E, Zhang K, Irizarry RA, Feinberg AP: Increased methylation variation in epigenetic domains across cancer types. Nat Genet 2011, 43(8):768-775.
• [3]Aston KI, Punj V, Liu L, Carrell DT: Genome-wide sperm deoxyribonucleic acid methylation is altered in some men with abnormal chromatin packaging or poor in vitro fertilization embryogenesis. Fertil Steril 2012, 97(2):285-292.
• [4]Rakyan VK, Down TA, Balding DJ, Beck S: Epigenome-wide association studies for common human diseases. Nat Rev Genet 2011, 12(8):529-541.
• [5]Heijmans BT, Mill J: Commentary: The seven plagues of epigenetic epidemiology. Int J Epidemiol 2012, 41(1):74-78.
• [6]Foley DL, Craig JM, Morley R, Olsson CA, Dwyer T, Smith K, Saffery R: Prospects for epigenetic epidemiology. Am J Epidemiol 2009, 169(4):389-400.
• [7]Lam LL, Emberly E, Fraser HB, Neumann SM, Chen E, Miller GE, Kobor MS: Factors underlying variable DNA methylation in a human community cohort. Proc Natl Acad Sci U S A 2012, 109(Suppl 2):17253-17260.
• [8]Dedeurwaerder S, Defrance M, Calonne E, Denis H, Sotiriou C, Fuks F: Evaluation of the Infinium Methylation 450 K technology. Epigenomics 2011, 3(6):771-784.
• [9]Sandoval J, Heyn H, Moran S, Serra-Musach J, Pujana MA, Bibikova M, Esteller M: Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics 2011, 6(6):692-702.
• [10]Chen YA, Choufani S, Ferreira JC, Grafodatskaya D, Butcher DT, Weksberg R: Sequence overlap between autosomal and sex-linked probes on the Illumina HumanMethylation27 microarray. Genomics 2011, 97(4):214-222.
• [11]Zhang X, Mu W, Zhang W: On the analysis of the illumina 450 k array data: probes ambiguously mapped to the human genome. Front Genet 2012, 3:73.
• [12]Morris T, Lowe R: Report on the Infinium 450 k methylation array analysis workshop: April 20, 2012 UCL, London, UK. Epigenetics 2012, 7(8):961-962.
• [13]Ioshikhes IP, Zhang MQ: Large-scale human promoter mapping using CpG islands. Nat Genet 2000, 26(1):61-63.
• [14]Saxonov S, Berg P, Brutlag DL: A genome-wide analysis of CpG dinucleotides in the human genome distinguishes two distinct classes of promoters. Proc Natl Acad Sci U S A 2006, 103(5):1412-1417.
• [15]Hsieh CL: Dependence of transcriptional repression on CpG methylation density. Mol Cell Biol 1994, 14(8):5487-5494.
• [16]Weber M, Hellmann I, Stadler MB, Ramos L, Paabo S, Rebhan M, Schubeler D: Distribution, silencing potential and evolutionary impact of promoter DNA methylation in the human genome. Nat Genet 2007, 39(4):457-466.
• [17]Gardiner-Garden M, Frommer M: CpG islands in vertebrate genomes. J Mol Biol 1987, 196(2):261-282.
• [18]Cotton AM, Lam L, Affleck JG, Wilson IM, Penaherrera MS, McFadden DE, Kobor MS, Lam WL, Robinson WP, Brown CJ: Chromosome-wide DNA methylation analysis predicts human tissue-specific X inactivation. Hum Genet 2011, 130(2):187-201.
• [19]Irizarry RA, Ladd-Acosta C, Wen B, Wu Z, Montano C, Onyango P, Cui H, Gabo K, Rongione M, Webster M, Ji H, Potash JB, Sabunciyan S, Feinberg AP: The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores. Nat Genet 2009, 41(2):178-186.
• [20]Doi A, Park IH, Wen B, Murakami P, Aryee MJ, Irizarry R, Herb B, Ladd-Acosta C, Rho J, Loewer S, Miller J, Schlaeger T, Daley GQ, Feinberg AP: Differential methylation of tissue- and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts. Nat Genet 2009, 41(12):1350-1353.
• [21]Zhang D, Cheng L, Badner JA, Chen C, Chen Q, Luo W, Craig DW, Redman M, Gershon ES, Liu C: Genetic control of individual differences in gene-specific methylation in human brain. Am J Hum Genet 2010, 86(3):411-419.
• [22]Ji H, Ehrlich LI, Seita J, Murakami P, Doi A, Lindau P, Lee H, Aryee MJ, Irizarry RA, Kim K, Rossi DJ, Inlay MA, Serwold T, Karsunky H, Ho L, Daley GQ, Weissman IL, Feinberg AP: Comprehensive methylome map of lineage commitment from haematopoietic progenitors. Nature 2010, 467(7313):338-342.
• [23]Jjingo D, Conley AB, Yi SV, Lunyak VV, Jordan IK: On the presence and role of human gene-body DNA methylation. Oncotarget 2012, 3(4):462-474.
• [24]Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, Klotzle B, Bibikova M, Fan JB, Gao Y, Deconde R, Chen M, Rajapakse I, Friend S, Ideker T, Zhang K: Genome-wide Methylation Profiles Reveal Quantitative Views of Human Aging Rates. Mol Cell 2013, 49(2):359-367.
• [25]Barbosa-Morais NL, Dunning MJ, Samarajiwa SA, Darot JF, Ritchie ME, Lynch AG, Tavare S: A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data. Nucleic Acids Res 2010, 38(3):e17.
• [26]Benovoy D, Kwan T, Majewski J: Effect of polymorphisms within probe-target sequences on olignonucleotide microarray experiments. Nucleic Acids Res 2008, 36(13):4417-4423.
• [27]Fraser HB, Lam LL, Neumann SM, Kobor MS: Population-specificity of human DNA methylation. Genome Biol 2012, 13(2):R8. BioMed Central Full Text
• [28]Bell JT, Pai AA, Pickrell JK, Gaffney DJ, Pique-Regi R, Degner JF, Gilad Y, Pritchard JK: DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol 2011, 12(1):R10. BioMed Central Full Text
• [29]Blair JD, Price EM: Illuminating Potential Technical Artifacts of DNA-Methylation Array Probes. Am J Hum Genet 2012, 91(4):760-762.
• [30]Kent WJ: BLAT–the BLAST-like alignment tool. Genome Res 2002, 12(4):656-664.
• [31]Baccarelli A, Wright RO, Bollati V, Tarantini L, Litonjua AA, Suh HH, Zanobetti A, Sparrow D, Vokonas PS, Schwartz J: Rapid DNA Methylation Changes after Exposure to Traffic Particles. Am J Respir Crit Care Med 2009, 179(7):572-578.
• [32]Rusiecki JA, Baccarelli A, Bollati V, Tarantini L, Moore LE, Bonefeld-Jorgensen EC: Global DNA hypomethylation is associated with high serum-persistent organic pollutants in Greenlandic Inuit. Environ Health Perspect 2008, 116(11):1547-1552.
• [33]Eckhardt F, Lewin J, Cortese R, Rakyan VK, Attwood J, Burger M, Burton J, Cox TV, Davies R, Down TA, Haefliger C, Horton R, Howe K, Jackson DK, Kunde J, Koenig C, Liddle J, Niblett D, Otto T, Pettett R, Seemann S, Thompson C, West T, Rogers J, Olek A, Berlin K, Beck S: DNA methylation profiling of human chromosomes 6, 20 and 22. Nat Genet 2006, 38(12):1378-1385.
• [34]Smith ZD, Chan MM, Mikkelsen TS, Gu H, Gnirke A, Regev A, Meissner A: A unique regulatory phase of DNA methylation in the early mammalian embryo. Nature 2012, 484(7394):339-344.
• [35]Brenet F, Moh M, Funk P, Feierstein E, Viale AJ, Socci ND, Scandura JM: DNA methylation of the first exon is tightly linked to transcriptional silencing. PLoS One 2011, 6(1):e14524.
• [36]Laird PW: Principles and challenges of genomewide DNA methylation analysis. Nat Rev Genet 2010, 11(3):191-203.
• [37]Beyan H, Down TA, Ramagopalan SV, Uvebrant K, Nilsson A, Holland ML, Gemma C, Giovannoni G, Boehm BO, Ebers GC, Lernmark A, Cilio CM, Leslie RD, Rakyan VK: Guthrie card methylomics identifies temporally stable epialleles that are present at birth in humans. Genome Res 2012, 22(11):2138-2145.
• [38]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-D496.
• [39]Wang Y, Leung FC: An evaluation of new criteria for CpG islands in the human genome as gene markers. Bioinformatics 2004, 20(7):1170-1177.
• [40]Aboyoun P, Pages H, Lawrence M: GenomicRanges: Representation and manipulation of genomic intervals. R package version 1.6.7.    ,  : .
• [41]Yuen RK, Penaherrera MS, von Dadelszen P, McFadden DE, Robinson WP: DNA methylation profiling of human placentas reveals promoter hypomethylation of multiple genes in early-onset preeclampsia. Eur J Hum Genet 2010, 18(9):1006-1012.
• [42]Du P, Zhang X, Huang CC, Jafari N, Kibbe WA, Hou L, Lin SM: Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics 2010, 11:587. BioMed Central Full Text
• [43]Du P, Kibbe WA, Lin SM: lumi: a pipeline for processing Illumina microarray. Bioinformatics 2008, 24(13):1547-1548.
• [44]Maksimovic J, Gordon L, Oshlack A: SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips. Genome Biol 2012, 13(6):R44. BioMed Central Full Text
• [45]Holger S: siggenes: Multiple testing using SAM and Efron's empirical Bayes approaches. R package version 1.28.0.   2011,  : .