Controlling for conservation in genome-wide DNA methylation studies

BMC Genomics

Lior Pachter²  Meromit Singer¹ 

[1]Current address: Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, 02142, MA, USA

[2]Department of Molecular and Cell Biology, University of California at Berkeley, Berkeley, 94720, CA, USA

关键词: Coding;    Exon;    Intron;    Junctions;    DNA methylation;    Missing data;    Comparative analysis;    Conservation;    Averaging;   

Others  :  1208959
DOI  :  10.1186/s12864-015-1604-3

 received in 2015-04-15, accepted in 2015-05-01,  发布年份 2015

【 摘 要 】

Background

A commonplace analysis in high-throughput DNA methylation studies is the comparison of methylation extent between different functional regions, computed by averaging methylation states within region types and then comparing averages between regions. For example, it has been reported that methylation is more prevalent in coding regions as compared to their neighboring introns or UTRs, leading to hypotheses about novel forms of epigenetic regulation.

Results

We have identified and characterized a bias present in these seemingly straightforward comparisons that results in the false detection of differences in methylation intensities across region types. This bias arises due to differences in conservation rates, rather than methylation rates, and is broadly present in the published literature. When controlling for conservation at coding start sites the differences in DNA methylation rates disappear. Moreover, a re-evaluation of methylation rates at intronexon junctions reveals that the magnitude of previously reported differences is greatly exaggerated. We introduce two correction methods to address this bias, an inferencebased matrix completion algorithm and an averaging approach, tailored to address different underlying biological questions. We evaluate how analysis using these corrections affects the detection of differences in DNA methylation across functional boundaries.

Conclusions

We report here on a bias in DNA methylation comparative studies that originates in conservation rate differences and manifests itself in the false discovery of differences in DNA methylation intensities and their extents. We have characterized this bias and its broad implications, and show how to control for it so as to enable the study of a variety of biological questions.

【 授权许可】

   
2015 Singer and Pachter; licensee BioMed Central.

【 图 表 】

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

Fig. 5.

【 参考文献 】

• [1]Chinwalla AT, Cook LL, Delehaunty KD, Fewell GA, Fulton LA, Fulton RS, Graves TA, Hillier LW, Mardis ER, McPherson JD, Miner TL, Nash WE, Nelson JO, Nhan MN, Pepin KH, Pohl CS, Ponce TC, Schultz B, Thompson J, Trevaskis E, Waterston RH, Wendl MC, Wilson RK, Yang S-P, An P, Berry E, Birren B, Bloom T, Brown DG, Butler J et al.. Initial sequencing and comparative analysis of the mouse genome. Nature. 2002; 420:520-62.
• [2]Doolittle WF, Fraser P, Gerstein MB, Graveley BR, Henikoff S, Huttenhower C, Oshlack A. Sixty years of genome biology. Genome Biol. 2013; 14:113. BioMed Central Full Text
• [3]Guo H, Zhu P, Yan L, Li R, Hu B, Lian Y, Yan J, Ren X, Lin S, Li J, Jin X, Shi X, Liu P, Wang X, Wang W, Wei Y, Li X, Guo F, Wu X, Fan X, Yong J, Wen L, Xie SX, Tang F, Qiao J. The DNA methylation landscape of human early embryos. Nature. 2014; 511:606-10.
• [4]Su J, Wang Y, Xing X, Liu J, Zhang Y. Genome-wide analysis of DNA methylation in bovine placentas. BMC Genomics. 2014; 15:12. BioMed Central Full Text
• [5]Liang D, Zhang Z, Wu H, Huang C, Shuai P, Ye C-Y, Tang S, Wang Y, Yang L, Wang J, Yin W, Xia X. Single-base-resolution methylomes of populus trichocarpa reveal the association between DNA methylation and drought stress. BMC Genet. 2014; 15 Suppl 1:S9. BioMed Central Full Text
• [6]Zhong S, Fei Z, Chen Y-R, Zheng Y, Huang M, Vrebalov J, McQuinn R, Gapper N, Liu B, Xiang J, Shao Y, Giovannoni JJ. Single-base resolution methylomes of tomato fruit development reveal epigenome modifications associated with ripening. Nat Biotechnol. 2013; 31:154-9.
• [7]Gao F, Liu X, Wu X-P, Wang X-L, Gong D, Lu H, Xia Y, Song Y, Wang J, Du J, Liu S, Han X, Tang Y, Yang H, Jin Q, Zhang X, Liu M. Differential DNA methylation in discrete developmental stages of the parasitic nematode Trichinella spiralis. Genome Biol. 2012; 13:R100. BioMed Central Full Text
• [8]Zemach A, McDaniel IE, Silva P, Zilberman D. Genome-wide evolutionary analysis of eukaryotic DNA methylation. Science. 2010; 328:916-9.
• [9]Sati S, Tanwar VS, Kumar KA, Patowary A, Jain V, Ghosh S, Ahmad S, Singh M, Reddy SU, Chandak GR, Raghunath M, Sivasubbu S, Chakraborty K, Scaria V, Sengupta S. High resolution methylome map of rat indicates role of intragenic DNA methylation in identification of coding region. PLoS One. 2012; 7: Article ID e31621
• [10]Gent JI, Ellis NA, Guo L, Harkess AE, Yao Y, Zhang X, Dawe RK. CHH islands: de novo DNA methylation in near-gene chromatin regulation in maize. Genome Res. 2013; 23:628-37.
• [11]Hsieh T-F, Ibarra CA, Silva P, Zemach A, Eshed-Williams L, Fischer RL, Zilberman D. Genome-wide demethylation of arabidopsis endosperm. Science. 2009; 324:1451-4.
• [12]Lister R, O’Malley RC, Tonti-Filippini J, Gregory BD, Berry CC, Millar AH, Ecker JR. Highly integrated single-base resolution maps of the epigenome in arabidopsis. Cell. 2008; 133:523-36.
• [13]Feng S, Cokus SJ, Zhang X, Chen P-Y, Bostick M, Goll MG, Hetzel J, Jain J, Strauss SH, Halpern ME, Ukomadu C, Sadler KC, Pradhan S, Pellegrini M, Jacobsen SE. Conservation and divergence of methylation patterning in plants and animals. Proc Natl Acad Sci. 2010; 107:8689-94.
• [14]Lister R, Pelizzola M, Dowen RH, Hawkins RD, Hon G, Tonti-Filippini J, Nery JR, Lee L, Ye Z, Ngo Q-M, Edsall L, Antosiewicz-Bourget J, Stewart R, Ruotti V, Millar AH, Thomson JA, Ren B, Ecker JR. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature. 2009; 462:315-22.
• [15]Wang X, Wheeler D, Avery A, Rago A, Choi J-H, Colbourne JK, Clark AG, Werren JH. Function and evolution of DNA methylation in nasonia vitripennis. PLoS Genet. 2013; 9: Article ID e1003872
• [16]Zilberman D, Gehring M, Tran RK, Ballinger T, Henikoff S. Genome-wide analysis of Arabidopsis thaliana DNA methylation uncovers an interdependence between methylation and transcription. Nat Genet. 2007; 39:61-9.
• [17]Ball MP, Li JB, Gao Y, Lee J-H, LeProust EM, Park I-H, Xie B, Daley GQ, Church GM. Targeted and genome-scale strategies reveal gene-body methylation signatures in human cells. Nat Biotechnol. 2009; 27:361-8.
• [18]Zhang X, Yazaki J, Sundaresan A, Cokus S, Chan SW-L, Chen H, Henderson IR, Shinn P, Pellegrini M, Jacobsen SE, Ecker JR. Genome-wide high-resolution mapping and functional analysis of DNA methylation in arabidopsis. Cell. 2006; 126:1189-201.
• [19]Laurent L, Wong E, Li G, Huynh T, Tsirigos A, Ong CT, Low HM, Sung KWK, Rigoutsos I, Loring J, Wei C-L. Dynamic changes in the human methylome during differentiation. Genome Res. 2010; 20:320-31.
• [20]Hackett JA, Sengupta R, Zylicz JJ, Murakami K, Lee C, Down TA, Surani MA. Germline DNA demethylation dynamics and imprint erasure through 5-hydroxymethylcytosine. Science. 2013; 339:448-52.
• [21]Flores KB, Amdam GV. Deciphering a methylome: what can we read into patterns of DNA methylation? J Exp Biol. 2011; 214:3155-63.
• [22]Chen P-Y, Feng S, Joo JW, Jacobsen SE, Pellegrini M. A comparative analysis of DNA methylation across human embryonic stem cell lines. Genome Biol. 2011; 12:R62. BioMed Central Full Text
• [23]Khare T, Pai S, Koncevicius K, Pal M, Kriukiene E, Liutkeviciute Z, Irimia M, Jia P, Ptak C, Xia M, Tice R, Tochigi M, Moréra S, Nazarians A, Belsham D, Wong AHC, Blencowe BJ, Wang SC, Kapranov P, Kustra R, Labrie V, Klimasauskas S, Petronis A. 5-hmC in the brain is abundant in synaptic genes and shows differences at the exon-intron boundary. Nat Struct Mol Biol. 2012; 19:1037-43.
• [24]Gelfman S, Cohen N, Yearim A, Ast G. DNA-methylation effect on co-transcriptional splicing is dependent on GC-architecture of the exon-intron structure. Genome Res. 2013; 23(5):789-99.
• [25]Huang Y, Chavez L, Chang X, Wang X, Pastor WA, Kang J, Zepeda-Martínez JA, Pape UJ, Jacobsen SE, Peters B, Rao A. Distinct roles of the methylcytosine oxidases Tet1 and Tet2 in mouse embryonic stem cells. Proc Natl Acad Sci. 2014; 111:1361-6.
• [26]Choi JK. Contrasting chromatin organization of CpG islands and exons in the human genome. Genome Biol. 2010; 11:R70. BioMed Central Full Text
• [27]Flores K, Wolschin F, Corneveaux JJ, Allen AN, Huentelman MJ, Amdam GV. Genome-wide association between DNA methylation and alternative splicing in an invertebrate. BMC Genomics. 2012; 13:480. BioMed Central Full Text
• [28]Choi JK, Bae J-B, Lyu J, Kim T-Y, Kim Y-J. Nucleosome deposition and DNA methylation at coding region boundaries. Genome Biol. 2009; 10:R89. BioMed Central Full Text
• [29]Regulski M, Lu Z, Kendall J, Donoghue MTA, Reinders J, Llaca V, Deschamps S, Smith A, Levy D, McCombie WR, Tingey S, Rafalski A, Hicks J, Ware D, Martienssen RA. The maize methylome influences mRNA splice sites and reveals widespread paramutation-like switches guided by small RNA. Genome Res. 2013; 23:1651-62.
• [30]Deaton AM, Bird A. CpG islands and the regulation of transcription. Genes Dev. 2011; 25:1010-22.
• [31]Blyth CR. On Simpson’s paradox and the sure-thing principle. J Am Stat Assoc. 1972; 67:364-6.
• [32]Good IJ, Mittal Y. The amalgamation and geometry of two-by-two contingency tables. Ann Stat. 1987; 15:694-711.
• [33]Simpson EH. The interpretation of interaction in contingency tables. J R Stat Soc Ser B Methodol. 1951;238–241.
• [34]Yule GU. Notes on the Theory of Association of Attributes in Statistics. Biometrika. 1903; 2:121-34.
• [35]Pearl J. Simpson’s paradox: an anatomy. Causality: models, reasoning and inference. 1999.
• [36]Bickel PJ, Hammel EA, O’Connell JW et al.. Sex bias in graduate admissions: data from berkeley. Science. 1975; 187:398-404.
• [37]Chi EC, Zhou H, Chen GK, Vecchyo DOD, Lange K. Genotype imputation via matrix completion. Genome Res. 2013; 23:509-18.
• [38]Zhang M, Xie S, Dong X, Zhao X, Zeng B, Chen J, Li H, Yang W, Zhao H, Wang G, Chen Z, Sun S, Hauck A, Jin W, Lai J. Genome-wide high resolution parental-specific DNA and histone methylation maps uncover patterns of imprinting regulation in maize. Genome Res. 2014; 24:167-76.
• [39]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:R10. BioMed Central Full Text
• [40]Chodavarapu RK, Feng S, Bernatavichute YV, Chen P-Y, Stroud H, Yu Y, Hetzel JA, Kuo F, Kim J, Cokus SJ, Casero D, Bernal M, Huijser P, Clark AT, Krämer U, Merchant SS, Zhang X, Jacobsen SE, Pellegrini M. Relationship between nucleosome positioning and DNA methylation. Nature. 2010; 466:388-92.
• [41]Feldmann A, Ivanek R, Murr R, Gaidatzis D, Burger L, Schübeler D. Transcription factor occupancy can mediate active turnover of DNA methylation at regulatory regions. PLoS Genet. 2013; 9:e1003994.
• [42]Kobayashi H, Sakurai T, Miura F, Imai M, Mochiduki K, Yanagisawa E et al.. High-resolution DNA methylome analysis of primordial germ cells identifies gender-specific reprogramming in mice. Genome Res. 2013; 23(4):616-27.
• [43]Molaro A, Hodges E, Fang F, Song Q, McCombie WR, Hannon GJ, Smith AD. Sperm methylation profiles reveal features of epigenetic inheritance and evolution in primates. Cell. 2011; 146:1029-41.
• [44]Akalin A, Garrett-Bakelman FE, Kormaksson M, Busuttil J, Zhang L, Khrebtukova I, Milne TA, Huang Y, Biswas D, Hess JL, Allis CD, Roeder RG, Valk PJM, Löwenberg B, Delwel R, Fernandez HF, Paietta E, Tallman MS, Schroth GP, Mason CE, Melnick A, Figueroa ME. Base-pair resolution DNA methylation sequencing reveals profoundly divergent epigenetic landscapes in acute myeloid leukemia. PLoS Genet. 2012; 8: Article ID e1002781
• [45]Cokus SJ, Feng S, Zhang X, Chen Z, Merriman B, Haudenschild CD, Pradhan S, Nelson SF, Pellegrini M, Jacobsen SE. Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning. Nature. 2008; 452:215-9.
• [46]Wang X, Duan C-G, Tang K, Wang B, Zhang H, Lei M, Lu K, Mangrauthia SK, Wang P, Zhu G, Zhao Y, Zhu J-K. RNA-binding protein regulates plant DNA methylation by controlling mRNA processing at the intronic heterochromatin-containing gene IBM1. Proc Natl Acad Sci. 2013; 110:15467-72.
• [47]Zemach A, Kim MY, Hsieh P-H, Coleman-Derr D, Eshed-Williams L, Thao K, Harmer SL, Zilberman D. The Arabidopsis nucleosome remodeler DDM1 allows DNA methyltransferases to access H1-containing heterochromatin. Cell. 2013; 153:193-205.
• [48]Ehrlich M. DNA methylation in cancer: too much, but also too little. Oncogene. 2002; 21:5400-13.
• [49]Simmons MP, Ochoterena H. Gaps as characters in sequence-based phylogenetic analyses. Syst Biol. 2000; 49:369-81.
• [50]Tian D, Wang Q, Zhang P, Araki H, Yang S, Kreitman M, Nagylaki T, Hudson R, Bergelson J, Chen J-Q. Single-nucleotide mutation rate increases close to insertions/deletions in eukaryotes. Nature. 2008; 455:105-8.
• [51]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(suppl 1):D493-6.
• [52]Ernst J, Kellis M. ChromHMM: automating chromatin-state discovery and characterization. Nat Methods. 2012; 9:215-6.
• [53]Daily K, Patel VR, Rigor P, Xie X, Baldi P. MotifMap: integrative genome-wide maps of regulatory motif sites for model species. BMC Bioinformatics. 2011; 12:495. BioMed Central Full Text
• [54]Bishop CM. Pattern recognition and machine learning. Volume 1. Springer, New York; 2006.