Five vertebrate ChIP-seq reveals the evolutionary dynamics of transcription factor binding

By D. Schmidt, M. Wilson, B. Ballester, P. Schwalie, Gordon D Brown, Aileen Marshall, C. Kutter, S. Watt, C. P. Martinez-Jimenez, Sarah Mackay and 3 more. Science, 2010

758 citations recorded by the source corpus.

Subtle Variation Despite vast phenotypic differences, vertebrates have many readily recognizable specific cell types, like liver hepatocytes. The gene expression that defines specific cells depends on evolutionarily conserved orthologous transcription factors. Schmidt et al. (p. 1036, published online 8 April) studied the conservation and divergence in the genome-wide binding of two such transcription factors, CEBPA and HNF4A, in livers from human, dog, mouse, short-tailed opossum, and chicken. Although the sequence bound by orthologous transcription factors was similar, the vast majority of binding events were unique to each species. Binding of two liver-specific transcription factors in several vertebrate species reveals complex regulatory evolution. Transcription factors (TFs) direct gene expression by binding to DNA regulatory regions. To explore the evolution of gene regulation, we used chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) to determine experimentally the genome-wide occupancy of two TFs, CCAAT/enhancer-binding protein alpha and hepatocyte nuclear factor 4 alpha, in the livers of five vertebrates. Although each TF displays highly conserved DNA binding preferences, most binding is species-specific, and aligned binding events present in all five species are rare. Regions near genes with expression levels that are dependent on a TF are often bound by the TF in multiple species yet show no enhanced DNA sequence constraint. Binding divergence between species can be largely explained by sequence changes to the bound motifs. Among the binding events lost in one lineage, only half are recovered by another binding event within 10 kilobases. Our results reveal large interspecies differences in transcriptional regulation and provide insight into regulatory evolution.

Subfields: Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/8421a301213f4f8dd0d0388d883795e76b8be64b

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Citations in the corpus

ChIPBase: a database for decoding the transcriptional regulation of long non-coding RNA and microRNA genes from ChIP-Seq data (2012, neutral): “The results page summarizes all of the query results: (i) there are five ChIP-Seq experiments for these three TFs (Supplementary Figure S8A and B); (ii) there are HNF4A ChIP-Seq data from three different experiments; and (iii) HNF4A and HNF3B/FoxA2 have multiple binding sites in the regulatory domai”
Systematic discovery and characterization of regulatory motifs in ENCODE TF binding experiments (2013, background): “Because changes in the underlying motif matches are largely responsible for changes in binding across species (98), evolutionary-based approaches on the motif instances may be a means to deal with the high rate of non-functional binding (99–101).”
Enhancer Evolution across 20 Mammalian Species (2015, methodology): “Exploiting this computational infrastructure (and related resources in Drosophila ; Kim et al., 2009), recent studies have dissected how transcription factor (TF) binding has evolved (He et al., 2011; Paris et al., 2013; Schmidt et al., 2010; Stefﬂova et al., 2013).”
Massively parallel functional dissection of mammalian enhancers in vivo (2012, background): “However, recent studies have shown that many enhancers are evolving rapidly and that mammalian genomes contain large numbers of evolutionarily young, sometimes species-specific, enhancer”
Repetitive DNA and next-generation sequencing: computational challenges and solutions (2011, neutral): “, chromatin immunoprecipitation followed by sequencing (ChIP–seq”
A promoter-level mammalian expression atlas (2014, background): “Regulatory regions such as transcription factor binding sites are often, but not always, located in conserved and orthologous regions 19 .”
Comparative Hi-C Reveals that CTCF Underlies Evolution of Chromosomal Domain Architecture (2015, positive): “Studies that have tracked the evolution of different transcription factor (TF) binding patterns have shown that sequence evolution alone is incapable of fully explaining the evolutionary dynamics of TF binding landscapes (Dermitzakis and Clark, 2001; Birney et al., 2007; Borneman et al., 2007; Schmi”
Insights into hominid evolution from the gorilla genome sequence (2012, result): “Consistent with previous results reporting strong CTCF binding conservation 38 , and in contrast to the rapid turnover of some other transcription factor binding sites 39 , we found that approximately 70% of”
A computational pipeline for comparative ChIP-seq analyses (2011, methodology): “The focus of many current ChIP-seq studies is the comparison of transcription factor binding profiles across different conditions such as different developmental time points 5,6 , cell types (e.g., within one cell lineage 7,8 ) or closely related species 9,10 .”
Functional and mechanistic diversity of distal transcription enhancers (2011, neutral): “A subsequent study examined genomewide binding of the liver-specific transcription factors CEBPA and HNF4a in multiple species (Schmidt et al., 2010).”
oPOSSUM-3: Advanced Analysis of Regulatory Motif Over-Representation Across Genes or ChIP-Seq Datasets (2012, background): “Third, widespread application of ChIP-Seq profiling has resulted in an explosion of the number of potential regulatory sequences to be analyzed (Johnson et al. 2007; Malhotra et al. 2010; Schmidt et al. 2010).”
Differential network biology (2012, background): “Cross-species analysis of a handful of transcription factors in both yeast (Borneman et al , 2007; Tuch et al , 2008) and mammalian cells (Schmidt et al , 2010) has revealed that protein–DNA interactions evolve quite rapidly over evolutionary time.”