RT Journal Article
SR Electronic
T1 Genome-wide methylation data mirror ancestry information
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 066340
DO 10.1101/066340
A1 Elior Rahmani
A1 Liat Shenhav
A1 Regev Schweiger
A1 Paul Yousefi
A1 Karen Huen
A1 Brenda Eskenazi
A1 Celeste Eng
A1 Scott Huntsman
A1 Donglei Hu
A1 Joshua Galanter
A1 Sam Oh
A1 Melanie Waldenberger
A1 Konstantin Strauch
A1 Harald Grallert
A1 Thomas Meitinger
A1 Christian Gieger
A1 Nina Holland
A1 Esteban Burchard
A1 Noah Zaitlen
A1 Eran Halperin
YR 2016
UL http://biorxiv.org/content/early/2016/12/10/066340.abstract
AB 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. 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. 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.