TY - JOUR
T1 - Genome-wide methylation data mirror ancestry information
AU - Rahmani, Elior
AU - Shenhav, Liat
AU - Schweiger, Regev
AU - Yousefi, Paul
AU - Huen, Karen
AU - Eskenazi, Brenda
AU - Eng, Celeste
AU - Huntsman, Scott
AU - Hu, Donglei
AU - Galanter, Joshua
AU - Oh, Sam S.
AU - Waldenberger, Melanie
AU - Strauch, Konstantin
AU - Grallert, Harald
AU - Meitinger, Thomas
AU - Gieger, Christian
AU - Holland, Nina
AU - Burchard, Esteban G.
AU - Zaitlen, Noah
AU - Halperin, Eran
N1 - Publisher Copyright:
© 2017 The Author(s).
PY - 2017/1/3
Y1 - 2017/1/3
N2 - Background: Genetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data. Results: We demonstrate, using three large-cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with cis-located SNPs. Based on these insights, we propose a method, EPISTRUCTURE, for the inference of ancestry from methylation data, without the need for genotype data. Conclusions: EPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io.
AB - Background: Genetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data. Results: We demonstrate, using three large-cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with cis-located SNPs. Based on these insights, we propose a method, EPISTRUCTURE, for the inference of ancestry from methylation data, without the need for genotype data. Conclusions: EPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io.
KW - Ancestry
KW - DNA methylation
KW - Epigenetics
KW - Epigenome-wide association study (EWAS)
KW - Illumina 450K
KW - Population structure
UR - http://www.scopus.com/inward/record.url?scp=85010825671&partnerID=8YFLogxK
U2 - 10.1186/s13072-016-0108-y
DO - 10.1186/s13072-016-0108-y
M3 - מאמר
AN - SCOPUS:85010825671
VL - 10
JO - Epigenetics and Chromatin
JF - Epigenetics and Chromatin
SN - 1756-8935
IS - 1
M1 - 1
ER -