Epigenetic modifications are associated with inter-species gene expression variation in primates

Zhou, Xiang; Cain, Carolyn E.; Myrthil, Marsha; Lewellen, Noah; Michelini, Katelyn; Stephens, Matthew; Pritchard, Jonathan K.; Gilad, Yoav

doi:10.1186/preaccept-2025469919139083

Cited by 26 publications

(36 citation statements)

References 98 publications

(156 reference statements)

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“…Supplementary Figure S13A versus Figure 3). Further, neither edgeR nor DESeq2 perform well, consistent with the recent move from these methods towards linear models in differential expression analysis (3,7,45–47,106). This result is not contingent on having large sample sizes.…”

Section: Resultsmentioning

confidence: 58%

Differential expression analysis for RNAseq using Poisson mixed models

Sun

Hood

Scott

et al. 2017

Nucleic Acids Research

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Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html.

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Section: Resultsmentioning

confidence: 58%

Differential expression analysis for RNAseq using Poisson mixed models

Sun

Hood

Scott

et al. 2017

Nucleic Acids Research

Self Cite

View full text Add to dashboard Cite

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“…Previous efforts have relied heavily on computational approaches to pinpoint conserved non-coding elements that were either deleted or had undergone accelerated change specifically in the human lineage (McLean et al, 2011; Pollard et al, 2006; Prabhakar et al, 2006). Functional epigenomic comparisons between humans and other primates have been largely limited to lymphoblastoid cell lines (Cain et al, 2011; Shibata et al, 2012; Zhou et al, 2014;) or to profiling whole organs from more distantly related species (Cotney et al, 2013; Villar et al, 2015). …”

Section: Introductionmentioning

confidence: 99%

Enhancer Divergence and cis-Regulatory Evolution in the Human and Chimp Neural Crest

Prescott

Srinivasan

Marchetto

et al. 2015

Cell

324

418

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Summary Cis-regulatory changes play a central role in morphological divergence, yet the regulatory principles underlying emergence of human traits remain poorly understood. Here we use epigenomic profiling from human and chimpanzee cranial neural crest cells to systematically and quantitatively annotate divergence of craniofacial cis-regulatory landscapes. Epigenomic divergence is attributable to genetic variation within TF motifs at orthologous enhancers, with a novel motif being most predictive of activity biases. We explore properties of this cis-regulatory change, revealing the role of particular retroelements, uncovering broad clusters of species-biased enhancers near genes associated with human facial variation, and demonstrating that cis-regulatory divergence is linked to quantitative expression differences of crucial neural crest regulators. Our work provides a wealth of candidates for future evolutionary studies and demonstrates the value of ‘cellular anthropology’, a strategy of using in vitro-derived embryonic cell types to elucidate both fundamental and evolving mechanisms underlying morphological variation in higher primates.

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“…In addition, transcriptional activity is correlated with various epigenomic and structural features, including post-translational modifications to core histones, the locations of architectural proteins such as CTCF, and the organization of topological associated domains. Like TFBSs, these features display general conservation across species, yet do exhibit some variation, which correlates with differences in gene expression 12,20,23–25 .…”

Section: Introductionmentioning

confidence: 99%

Dynamic evolution of regulatory element ensembles in primate CD4+ T cells

et al. 2018

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How evolutionary changes at enhancers affect the transcription of target genes remains an important open question. Previous comparative studies of gene expression have largely measured the abundance of mRNA, which is affected by post-transcriptional regulatory processes, hence limiting inferences about the mechanisms underlying expression differences. Here we directly measured nascent transcription in primate species, allowing us to separate transcription from post-transcriptional regulation. We used PRO-seq to map RNA polymerases in resting and activated CD4+ T-cells in multiple human, chimpanzee, and rhesus macaque individuals, with rodents as outgroups. We observed general conservation in coding and non-coding transcription, punctuated by numerous differences between species, particularly at distal enhancers and non-coding RNAs. Genes regulated by larger numbers of enhancers are more frequently transcribed at evolutionarily stable levels, despite reduced conservation at individual enhancers. Adaptive nucleotide substitutions are associated with lineage-specific transcription, and at one locus, SGPP2, we predict and experimentally validate that multiple substitutions contribute to human-specific transcription. Collectively, our findings suggest a pervasive role for evolutionary compensation across ensembles of enhancers that jointly regulate target genes.

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Epigenetic modifications are associated with inter-species gene expression variation in primates

Cited by 26 publications

References 98 publications

Differential expression analysis for RNAseq using Poisson mixed models

Differential expression analysis for RNAseq using Poisson mixed models

Enhancer Divergence and cis-Regulatory Evolution in the Human and Chimp Neural Crest

Dynamic evolution of regulatory element ensembles in primate CD4+ T cells

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