Quantifying polymorphism and divergence from epigenetic data

A framework for inferring the action of selection

Shivani Mahajan, Jessica Crisci, Alex Wong, Schahram Akbarian, Matthieu Foll, Jeffrey Jensen

Research output: Contribution to journalArticle

Abstract

Epigenetic modifications are alterations that regulate gene expression without modifying the underlying DNA sequence. DNA methylation and histone modifications, for example, are capable of spatial and temporal regulation of expression-with several studies demonstrating that these epigenetic marks are heritable. Thus, like DNA sequence, epigenetic marks are capable of storing information and passing it from one generation to the next. Because the epigenome is dynamic and epigenetic modifications can respond to external environmental stimuli, such changes may play an important role in adaptive evolution. While recent studies provide strong evidence for species-specific signatures of epigenetic marks, little is known about the mechanisms by which such modifications evolve. In order to address this question, we analyze the genome wide distribution of an epigenetic histone mark (H3K4me3) in prefrontal cortex neurons of humans, chimps and rhesus macaques. We develop a novel statistical framework to quantify within- and between-species variation in histone methylation patterns, using an ANOVA-based method and defining an FST -like measure for epigenetics (termed epi- FST), in order to develop a deeper understanding of the evolutionary pressures acting on epigenetic variation. Results demonstrate that genes with high epigenetic FST values are indeed significantly overrepresented among genes that are differentially expressed between species, and we observe only a weak correlation with SNP density.

Original languageEnglish (US)
Article number190
JournalFrontiers in Genetics
Volume6
Issue numberMAY
DOIs
StatePublished - 2015
Externally publishedYes

Fingerprint

Epigenomics
Histone Code
DNA Methylation
Prefrontal Cortex
Macaca mulatta
Histones
Methylation
Genes
Single Nucleotide Polymorphism
Analysis of Variance
Genome
Gene Expression
Neurons
Pressure

Keywords

  • Adaptation
  • ANEVA
  • Epi-F<inf>ST</inf>
  • Epigenetics

ASJC Scopus subject areas

  • Genetics
  • Molecular Medicine
  • Genetics(clinical)

Cite this

Quantifying polymorphism and divergence from epigenetic data : A framework for inferring the action of selection. / Mahajan, Shivani; Crisci, Jessica; Wong, Alex; Akbarian, Schahram; Foll, Matthieu; Jensen, Jeffrey.

In: Frontiers in Genetics, Vol. 6, No. MAY, 190, 2015.

Research output: Contribution to journalArticle

Mahajan, Shivani ; Crisci, Jessica ; Wong, Alex ; Akbarian, Schahram ; Foll, Matthieu ; Jensen, Jeffrey. / Quantifying polymorphism and divergence from epigenetic data : A framework for inferring the action of selection. In: Frontiers in Genetics. 2015 ; Vol. 6, No. MAY.
@article{975c8674676741dfb42689df7714953f,
title = "Quantifying polymorphism and divergence from epigenetic data: A framework for inferring the action of selection",
abstract = "Epigenetic modifications are alterations that regulate gene expression without modifying the underlying DNA sequence. DNA methylation and histone modifications, for example, are capable of spatial and temporal regulation of expression-with several studies demonstrating that these epigenetic marks are heritable. Thus, like DNA sequence, epigenetic marks are capable of storing information and passing it from one generation to the next. Because the epigenome is dynamic and epigenetic modifications can respond to external environmental stimuli, such changes may play an important role in adaptive evolution. While recent studies provide strong evidence for species-specific signatures of epigenetic marks, little is known about the mechanisms by which such modifications evolve. In order to address this question, we analyze the genome wide distribution of an epigenetic histone mark (H3K4me3) in prefrontal cortex neurons of humans, chimps and rhesus macaques. We develop a novel statistical framework to quantify within- and between-species variation in histone methylation patterns, using an ANOVA-based method and defining an FST -like measure for epigenetics (termed epi- FST), in order to develop a deeper understanding of the evolutionary pressures acting on epigenetic variation. Results demonstrate that genes with high epigenetic FST values are indeed significantly overrepresented among genes that are differentially expressed between species, and we observe only a weak correlation with SNP density.",
keywords = "Adaptation, ANEVA, Epi-F<inf>ST</inf>, Epigenetics",
author = "Shivani Mahajan and Jessica Crisci and Alex Wong and Schahram Akbarian and Matthieu Foll and Jeffrey Jensen",
year = "2015",
doi = "10.3389/fgene.2015.00190",
language = "English (US)",
volume = "6",
journal = "Frontiers in Genetics",
issn = "1664-8021",
publisher = "Frontiers Media S. A.",
number = "MAY",

}

TY - JOUR

T1 - Quantifying polymorphism and divergence from epigenetic data

T2 - A framework for inferring the action of selection

AU - Mahajan, Shivani

AU - Crisci, Jessica

AU - Wong, Alex

AU - Akbarian, Schahram

AU - Foll, Matthieu

AU - Jensen, Jeffrey

PY - 2015

Y1 - 2015

N2 - Epigenetic modifications are alterations that regulate gene expression without modifying the underlying DNA sequence. DNA methylation and histone modifications, for example, are capable of spatial and temporal regulation of expression-with several studies demonstrating that these epigenetic marks are heritable. Thus, like DNA sequence, epigenetic marks are capable of storing information and passing it from one generation to the next. Because the epigenome is dynamic and epigenetic modifications can respond to external environmental stimuli, such changes may play an important role in adaptive evolution. While recent studies provide strong evidence for species-specific signatures of epigenetic marks, little is known about the mechanisms by which such modifications evolve. In order to address this question, we analyze the genome wide distribution of an epigenetic histone mark (H3K4me3) in prefrontal cortex neurons of humans, chimps and rhesus macaques. We develop a novel statistical framework to quantify within- and between-species variation in histone methylation patterns, using an ANOVA-based method and defining an FST -like measure for epigenetics (termed epi- FST), in order to develop a deeper understanding of the evolutionary pressures acting on epigenetic variation. Results demonstrate that genes with high epigenetic FST values are indeed significantly overrepresented among genes that are differentially expressed between species, and we observe only a weak correlation with SNP density.

AB - Epigenetic modifications are alterations that regulate gene expression without modifying the underlying DNA sequence. DNA methylation and histone modifications, for example, are capable of spatial and temporal regulation of expression-with several studies demonstrating that these epigenetic marks are heritable. Thus, like DNA sequence, epigenetic marks are capable of storing information and passing it from one generation to the next. Because the epigenome is dynamic and epigenetic modifications can respond to external environmental stimuli, such changes may play an important role in adaptive evolution. While recent studies provide strong evidence for species-specific signatures of epigenetic marks, little is known about the mechanisms by which such modifications evolve. In order to address this question, we analyze the genome wide distribution of an epigenetic histone mark (H3K4me3) in prefrontal cortex neurons of humans, chimps and rhesus macaques. We develop a novel statistical framework to quantify within- and between-species variation in histone methylation patterns, using an ANOVA-based method and defining an FST -like measure for epigenetics (termed epi- FST), in order to develop a deeper understanding of the evolutionary pressures acting on epigenetic variation. Results demonstrate that genes with high epigenetic FST values are indeed significantly overrepresented among genes that are differentially expressed between species, and we observe only a weak correlation with SNP density.

KW - Adaptation

KW - ANEVA

KW - Epi-F<inf>ST</inf>

KW - Epigenetics

UR - http://www.scopus.com/inward/record.url?scp=84940100701&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84940100701&partnerID=8YFLogxK

U2 - 10.3389/fgene.2015.00190

DO - 10.3389/fgene.2015.00190

M3 - Article

VL - 6

JO - Frontiers in Genetics

JF - Frontiers in Genetics

SN - 1664-8021

IS - MAY

M1 - 190

ER -