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DOI10.1371/journal.pone.0142274
Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach
Haque, M. Muksitul1,2; Holder, Lawrence B.2; Skinner, Michael K.1
通讯作者Skinner, Michael K.
来源期刊PLOS ONE
ISSN1932-6203
出版年2015
卷号10期号:11
英文摘要

Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp) termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set of potential epimutations that can be used to facilitate identification of epigenetic diagnostics for ancestral environmental exposures and disease susceptibility.


类型Article
语种英语
国家USA
收录类别SCI-E
WOS记录号WOS:000365070700027
WOS关键词SPERM EPIMUTATIONS ; PRENATAL EXPOSURE ; DNA METHYLATION ; NONCODING RNAS ; DUTCH FAMINE ; REGIONS ; TRANSCRIPTION ; RESTRICTION ; CLASSIFIERS ; ALGORITHMS
WOS类目Multidisciplinary Sciences
WOS研究方向Science & Technology - Other Topics
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/189863
作者单位1.Washington State Univ, Ctr Reprod Biol, Sch Biol Sci, Pullman, WA 99164 USA;
2.Washington State Univ, Sch Elect Engn & Comp Sci, Pullman, WA 99164 USA
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Haque, M. Muksitul,Holder, Lawrence B.,Skinner, Michael K.. Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach[J],2015,10(11).
APA Haque, M. Muksitul,Holder, Lawrence B.,&Skinner, Michael K..(2015).Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.PLOS ONE,10(11).
MLA Haque, M. Muksitul,et al."Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach".PLOS ONE 10.11(2015).
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