{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T11:12:28Z","timestamp":1726139548647},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"S3","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2012,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>DNA methylation is essential for normal development and differentiation and plays a crucial role in the development of nearly all types of cancer. Aberrant DNA methylation patterns, including genome-wide hypomethylation and region-specific hypermethylation, are frequently observed and contribute to the malignant phenotype. A number of studies have recently identified distinct features of genomic sequences that can be used for modeling specific DNA sequences that may be susceptible to aberrant CpG methylation in both cancer and normal cells. Although it is now possible, using next generation sequencing technologies, to assess human methylomes at base resolution, no reports currently exist on modeling cell type-specific DNA methylation susceptibility. Thus, we conducted a comprehensive modeling study of cell type-specific DNA methylation susceptibility at three different resolutions: CpG dinucleotides, CpG segments, and individual gene promoter regions.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Using a k-mer mixture logistic regression model, we effectively modeled DNA methylation susceptibility across five different cell types. Further, at the segment level, we achieved up to 0.75 in AUC prediction accuracy in a 10-fold cross validation study using a mixture of k-mers.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>The significance of these results is three fold: 1) this is the first report to indicate that CpG methylation susceptible \"segments\" exist; 2) our model demonstrates the significance of certain k-mers for the mixture model, potentially highlighting DNA sequence features (k-mers) of differentially methylated, promoter CpG island sequences across different tissue types; 3) as only 3 or 4 bp patterns had previously been used for modeling DNA methylation susceptibility, ours is the first demonstration that 6-mer modeling can be performed without loss of accuracy.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-13-s3-s15","type":"journal-article","created":{"date-parts":[[2012,3,22]],"date-time":"2012-03-22T20:48:58Z","timestamp":1332449338000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A novel k-mer mixture logistic regression for methylation susceptibility modeling of CpG dinucleotides in human gene promoters"],"prefix":"10.1186","volume":"13","author":[{"given":"Youngik","family":"Yang","sequence":"first","affiliation":[]},{"given":"Kenneth","family":"Nephew","sequence":"additional","affiliation":[]},{"given":"Sun","family":"Kim","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2012,3,21]]},"reference":[{"key":"5093_CR1","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1101\/gad.947102","volume":"16","author":"A Bird","year":"2002","unstructured":"Bird A: DNA methylation patterns and epigenetic memory. Genes Dev. 2002, 16: 6-21. 10.1101\/gad.947102.","journal-title":"Genes Dev"},{"issue":"2","key":"5093_CR2","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1038\/5947","volume":"21","author":"PA Jones","year":"1999","unstructured":"Jones PA, Laird PW: Cancer-epigenetics comes of age. Nat Genet. 1999, 21 (2): 163-167. 10.1038\/5947.","journal-title":"Nat Genet"},{"issue":"23","key":"5093_CR3","doi-asserted-by":"publisher","first-page":"3215","DOI":"10.1101\/gad.1464906","volume":"20","author":"AH Ting","year":"2006","unstructured":"Ting AH, McGarvey KM, Baylin SB: The cancer epigenome-components and functional correlates. Genes Dev. 2006, 20 (23): 3215-3231. 10.1101\/gad.1464906.","journal-title":"Genes Dev"},{"issue":"21","key":"5093_CR4","doi-asserted-by":"publisher","first-page":"2042","DOI":"10.1056\/NEJMra023075","volume":"349","author":"JG Herman","year":"2003","unstructured":"Herman JG, Baylin SB: Gene silencing in cancer in association with promoter hypermethylation. N Engl J Med. 2003, 349 (21): 2042-2054. 10.1056\/NEJMra023075.","journal-title":"N Engl J Med"},{"issue":"2","key":"5093_CR5","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1038\/72785","volume":"24","author":"JF Costello","year":"2000","unstructured":"Costello JF, Fr\u00fchwald MC, Smiraglia DJ, Rush LJ, Robertson GP, Gao X, Wright FA, Feramisco JD, Peltom\u00e4ki P, Lang JC, Schuller DE, Yu L, Bloomfield CD, Caligiuri MA, Yates A, Nishikawa R, Su Huang H, Petrelli NJ, Zhang X, O'Dorisio MS, Held WA, Cavenee WK, Plass C: Aberrant CpG-island methylation has non-random and tumour-type-specific patterns. Nat Genet. 2000, 24 (2): 132-138. 10.1038\/72785.","journal-title":"Nat Genet"},{"issue":"3","key":"5093_CR6","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1038\/nrg2732","volume":"11","author":"PW Laird","year":"2010","unstructured":"Laird PW: Principles and challenges of genome-wide DNA methylation analysis. Nat Rev Genet. 2010, 11 (3): 191-203.","journal-title":"Nat Rev Genet"},{"issue":"21","key":"5093_CR7","doi-asserted-by":"publisher","first-page":"12253","DOI":"10.1073\/pnas.2037852100","volume":"100","author":"FA Feltus","year":"2003","unstructured":"Feltus FA, Lee EK, Costello JF, Plass C, Vertino PM: Predicting aberrant CpG island methylation. Proc Natl Acad Sci USA. 2003, 100 (21): 12253-12258. 10.1073\/pnas.2037852100.","journal-title":"Proc Natl Acad Sci USA"},{"issue":"13","key":"5093_CR8","doi-asserted-by":"publisher","first-page":"1530","DOI":"10.1093\/bioinformatics\/btn223","volume":"24","author":"K Pr\u00fcfer","year":"2008","unstructured":"Pr\u00fcfer K, Stenzel U, Dannemann M, Green RE, Lachmann M, Kelso J: PatMaN: rapid alignment of short sequences to large databases. Bioinformatics. 2008, 24 (13): 1530-1531. 10.1093\/bioinformatics\/btn223.","journal-title":"Bioinformatics"},{"key":"5093_CR9","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1158\/0008-5472.CAN-08-3274","volume":"69","author":"MT McCabe","year":"2009","unstructured":"McCabe MT, Lee EK, Vertino PM: A multifactorial signature of DNA sequence and polycomb binding predicts aberrant CpG island methylation. Cancer Res. 2009, 69: 282-291. 10.1158\/0008-5472.CAN-08-3274.","journal-title":"Cancer Res"},{"issue":"5","key":"5093_CR10","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1016\/j.ygeno.2005.12.016","volume":"87","author":"FA Feltus","year":"2006","unstructured":"Feltus FA, Lee EK, Costello JF, Plass C, Vertino PM: DNA motifs associated with aberrant CpG island methylation. Genomics. 2006, 87 (5): 572-579. 10.1016\/j.ygeno.2005.12.016.","journal-title":"Genomics"},{"issue":"2","key":"5093_CR11","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1038\/ng1719","volume":"38","author":"I Keshet","year":"2006","unstructured":"Keshet I, Schlesinger Y, Farkash S, Rand E, Hecht M, Segal E, Pikarski E, Young RA, Niveleau A, Cedar H, Simon I: Evidence for an instructive mechanism of de novo methylation in cancer cells. Nat Genet. 2006, 38 (2): 149-153. 10.1038\/ng1719.","journal-title":"Nat Genet"},{"issue":"3","key":"5093_CR12","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1093\/bioinformatics\/btl620","volume":"23","author":"L Goh","year":"2007","unstructured":"Goh L, Murphy SK, Muhkerjee S, Furey TS: Genomic sweeping for hypermethylated genes. Bioinformatics. 2007, 23 (3): 281-288. 10.1093\/bioinformatics\/btl620.","journal-title":"Bioinformatics"},{"issue":"18","key":"5093_CR13","doi-asserted-by":"publisher","first-page":"2204","DOI":"10.1093\/bioinformatics\/btl377","volume":"22","author":"F Fang","year":"2006","unstructured":"Fang F, Fan S, Zhang X, Zhang MQ: Predicting methylation status of CpG islands in the human brain. Bioinformatics. 2006, 22 (18): 2204-2209. 10.1093\/bioinformatics\/btl377.","journal-title":"Bioinformatics"},{"issue":"3","key":"5093_CR14","doi-asserted-by":"publisher","first-page":"e26","DOI":"10.1371\/journal.pgen.0020026","volume":"2","author":"C Bock","year":"2006","unstructured":"Bock C, Paulsen M, Tierling S, Mikeska T, Lengauer T, Walter J: CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure. PLoS Genet. 2006, 2 (3): e26-10.1371\/journal.pgen.0020026.","journal-title":"PLoS Genet"},{"issue":"5","key":"5093_CR15","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1016\/j.jmb.2005.02.044","volume":"348","author":"V Handa","year":"2005","unstructured":"Handa V, Jeltsch A: Profound flanking sequence preference of Dnmt3a and Dnmt3b mammalian DNA methyltransferases shape the human epigenome. J Mol Biol. 2005, 348 (5): 1103-1112. 10.1016\/j.jmb.2005.02.044.","journal-title":"J Mol Biol"},{"issue":"3","key":"5093_CR16","doi-asserted-by":"publisher","first-page":"e1000438","DOI":"10.1371\/journal.pgen.1000438","volume":"5","author":"Y Zhang","year":"2009","unstructured":"Zhang Y, Rohde C, Tierling S, Jurkowski TP, Bock C, Santacruz D, Ragozin S, Reinhardt R, Groth M, Walter J, Jeltsch A: DNA methylation analysis of chromosome 21 gene promoters at single base pair and single allele resolution. PLoS Genet. 2009, 5 (3): e1000438-10.1371\/journal.pgen.1000438.","journal-title":"PLoS Genet"},{"issue":"6","key":"5093_CR17","doi-asserted-by":"publisher","first-page":"1044","DOI":"10.1101\/gr.088773.108","volume":"19","author":"AL Brunner","year":"2009","unstructured":"Brunner AL, Johnson DS, Kim SW, Valouev A, Reddy TE, Neff NF, Anton E, Medina C, Nguyen L, Chiao E, Oyolu CB, Schroth GP, Absher DM, Baker JC, Myers RM: Distinct DNA methylation patterns characterize differentiated human embryonic stem cells and developing human fetal liver. Genome Res. 2009, 19 (6): 1044-1056. 10.1101\/gr.088773.108.","journal-title":"Genome Res"},{"issue":"7271","key":"5093_CR18","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1038\/nature08514","volume":"462","author":"R Lister","year":"2009","unstructured":"Lister R, Pelizzola M, Dowen RH, Hawkins RD, Hon G, Tonti-Filippini J, Nery JR, Lee L, Ye Z, Ngo QM, 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 (7271): 315-322. 10.1038\/nature08514.","journal-title":"Nature"},{"issue":"18","key":"5093_CR19","doi-asserted-by":"publisher","first-page":"8511","DOI":"10.1158\/0008-5472.CAN-07-1016","volume":"67","author":"KH Taylor","year":"2007","unstructured":"Taylor KH, Kramer RS, Davis WJ, Guo J, Duff DJ, Xu D, Caldwell CW, Shi H: Ultradeep bisulfite sequencing analysis of DNA methylation patterns in multiple gene promoters by 454 sequencing. Cancer Res. 2007, 67 (18): 8511-8518. 10.1158\/0008-5472.CAN-07-1016.","journal-title":"Cancer Res"},{"key":"5093_CR20","first-page":"315","volume-title":"Pac Symp Biocomput","author":"S Kim","year":"2008","unstructured":"Kim S, Li M, Paik H, Nephew K, Shi H, Kramer R, Xu D, Huang TH: Predicting DNA methylation susceptibility using CpG flanking sequences. Pac Symp Biocomput. 2008, 315-326."},{"key":"5093_CR21","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1186\/1471-2105-10-116","volume":"10","author":"C Previti","year":"2009","unstructured":"Previti C, Harari O, Zwir I, Val CD: Profile analysis and prediction of tissue-specific CpG island methylation classes. BMC Bioinformatics. 2009, 10: 116-10.1186\/1471-2105-10-116.","journal-title":"BMC Bioinformatics"},{"key":"5093_CR22","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L: Random forests. Machine Learning. 2001, 45: 5-32. 10.1023\/A:1010933404324.","journal-title":"Machine Learning"},{"key":"5093_CR23","volume-title":"Feature selection challenge","author":"NIPS","year":"2003","unstructured":"NIPS: Feature selection challenge. 2003, [http:\/\/www.nipsfsc.ecs.soton.ac.uk]"},{"key":"5093_CR24","volume-title":"Introduction to Algorithms","author":"TH Cormen","year":"2003","unstructured":"Cormen TH, Leiserson CE, Rivest RL, Stein C: Introduction to Algorithms. 2003, McGraw-Hill Science\/Engineering\/Math, [http:\/\/www.amazon.com\/exec\/obidos\/redirect?tag=citeulike07-20\\&path=ASIN\/0072970545]2","edition":"2"},{"key":"5093_CR25","volume-title":"amplicon 193 @ONLINE","author":"Y Zhang","year":"2010","unstructured":"Zhang Y, Rohde C, Tierling S, Jurkowski TP, Bock C, Santacruz D, Ragozin S, Reinhardt R, Groth M, Walter J, Jeltsch A: amplicon 193 @ONLINE. 2010, [http:\/\/biochem.jacobs-university.de\/name21\/presentation\/amplicon_summaries\/193_amplicon_summary.html]"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-13-S3-S15.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T18:44:50Z","timestamp":1630521890000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-13-S3-S15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,3,21]]},"references-count":25,"journal-issue":{"issue":"S3","published-print":{"date-parts":[[2012,12]]}},"alternative-id":["5093"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-13-s3-s15","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,3,21]]},"assertion":[{"value":"21 March 2012","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"S15"}}