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Title: Tracing the Evolution of Lineage-Specific Transcription Factor Binding Sites in a Birth-Death Framework}
Article:
Abstract:
Changes in cis-regulatory element composition that result in novel patterns of gene expression are thought to be a major contributor to the evolution of lineage-specific traits. Although transcription factor binding events show substantial variation across species, most computational approaches to study regulatory elements focus primarily upon highly conserved sites, and rely heavily upon multiple sequence alignments. However, sequence conservation based approaches have limited ability to detect lineage-specific elements that could contribute to species-specific traits. In this paper, we describe a novel framework that utilizes a birth-death model to trace the evolution of lineage-specific binding sites without relying on detailed base-by-base cross-species alignments. Our model was applied to analyze the evolution of binding sites based on the ChIP-seq data for six transcription factors( GATA1, SOX2, CTCF, MYC, MAX, ETS1) along the lineage toward human after human-mouse common ancestor. We estimate that a substantial fraction of binding sites( ∼58–79% for each factor) in humans have origins since the divergence with mouse. Over 15% of all binding sites are unique to hominids. Such elements are often enriched near genes associated with specific pathways, and harbor more common SNPs than older binding sites in the human genome. These results support the ability of our method to identify lineage-specific regulatory elements and help understand their roles in shaping variation in gene regulation across species.
Introduction:
Changes in gene regulation play a key role in the evolution of morphological traits[1]–[3]. At the level of transcription, gene expression is controlled via transcription factor( TF) proteins that selectively bind to cis-regulatory elements in a sequence-specific manner[2],[4]. Utilizing chromatin immunoprecipitation of specific TFs followed by high-throughput sequencing( ChIP-seq), recent studies showed that the evolution of these transcription factor binding sites( TFBS) is highly dynamic, with sites differing a great deal even within mammals[5]–[9]. Despite substantial experimental evidence for rapid divergence of regulatory protein-binding events across species, computational models designed to analyze regulatory elements using cross-species comparisons have focused primarily upon ‘phylogenetic footprinting’ approaches, in which putatively functional regulatory elements are identified according to sequence conservation[10]–[15]. Previous computational studies have inferred the evolution of regulatory elements using, for example, the emergence of new conserved elements specific to a particular clade in the phylogeny[16] or lineage-specific alterations leading to a loss-of-function phenotype[17],[18]. Although such approaches have been helpful in understanding lineage-specific regulatory element evolution, all inherently rely upon fixed cross-species alignments, which are frequently of low quality within non-coding regions in the genome[19]–[21]. Previous studies have estimated that more than 15% of aligned bases within human-mouse whole-genome alignments are incorrect[22] and the error rate increases when more species are involved[19]. Ancestral reconstruction, which is sensitive to details of the multiple alignment, is a particularly challenging problem for non-coding regions[23],[24]. As a consequence, cross-species comparisons of non-coding sequences are limited in their ability to study regulatory sequence evolution, particularly in cases where the elements are selected for novelty or newly-derived. Such newly-derived regulatory elements are not rare; indeed, analyses using human population variation data from the 1000 Genomes Project[25] have shown that human genomic locations under selection undergo considerable turnover and frequently lie outside mammalian-conserved regions[26]. Yet, systematic identification of binding sites for specific TFs and assessment of their conservation and prevalence using cross-species comparisons remains a challenging problem. In this work, we introduce a novel evolutionary framework through which lineage-specific TFBSs can be inferred on a genome-wide scale. In contrast to conservation-based approaches[13],[16],[27], we utilize a birth-death model to infer ancestral states of a given motif without the use of the base-by-base alignment details in the underlying cross-species sequence alignment. Gains and losses of TFBS have been explicitly used both to improve cross-species sequence comparisons and to detect cis-regulatory modules, although such models are usually framed within the context of an alignment[21],[28]. A more similar alignment-free model was previously used to measure the overall rate of TFBS creation along different lineages[29]. In this work, we instead applied our framework to infer lineage-specific TFBS, estimating the branch of origin of each individual TFBS for six TFs. We then studied patterns for TFBS with different branches of origin, including target genes of the newly-derived sites, relationship with within-human variation, overlap with transposable elements, and cell-type specificity of TF-binding. Our results provide strong support that this novel method can help identify lineage-specific regulatory elements, a first step towards understanding the role of regulatory element evolution in shaping the variation of gene regulation across species.
Discussion:
The approach presented here represents an initial step towards understanding regulatory element evolution using in silico methods without relying on accurate cross-species alignments. Studies regarding the evolution of TFBSs are largely separable into those that emphasize cross-species conservation of regulatory elements[13],[27],[55]–[57] and studies highlighting the substantial divergence of transcription factor-binding events across species[5]–[7],[58]–[60]. To some extent, this dichotomy may largely reflect differences between analyses conducted in silico and experiment-based studies. Although computational approaches have had some success in identifying cis-regulatory alterations responsible for changes in phenotype[16],[17], the study of regulatory sequence evolution is limited by reliance upon multiple sequence alignments[20],[21]. Reconstructing the ancestral states of regulatory sequences is a particularly challenging problem; comparative studies of regulatory elements generally categorize sites as ‘conserved’ and ‘non-conserved’ in terms of their presence across species[34],[39],[61]. ‘Non-conserved’ sites are thus often assumed to be under a weaker amount of purifying selection, indicating a relative lack of function[62]. However, any interpretation of the results is obscured by the fact that no distinction can be made between ancestral sites that have later been lost, versus sites of recent origins. Newly-derived functional elements, which are also ‘non-conserved’ by the common definition, may induce a gain-of-function trait, harboring the potential for lineage-specific adaptation or positive selection. It has long been argued that alterations in regulatory function are responsible for many, if not most, species-specific traits[1]–[3], and it is indeed these elements that are likely to contribute to phenotypic adaptation and the variation seen across species. In this context, the high fraction of TFBSs that have recent origins after human-mouse divergence is particularly notable. For all six factors analyzed, the majority of human TFBSs bound in vivo were originally absent in human-mouse common ancestor, which is consistent with previous cross-species comparisons noting substantial divergence in ChIP-seq protein-binding events across the two species[5],[6] and similar comparisons presented here( Table 1), and is also comparable to detailed analyses conducted in Drosophila using alternative approaches[57]. This does not appear to simply be a consequence of the specific selection of TFs, since binding motifs for several factors analyzed( CTCF, ETS1, MYC, MAX) have been previously documented as ‘highly conserved’ compared to motifs of other factors[27],[39]. In particular, a comprehensive scan for conserved motifs identified the binding motifs of MYC and ETS1 as the second and third-highest ranking motifs across all motifs in terms of conservation score across human, mouse, rat, and dog( where the ETS1 binding motif was denoted as the ELK1 motif)[27]. It is important to note that ‘phylogenetic footprinting’ approaches usually measure motif conservation relative to neutrally evolving elements in non-coding regions. The fact that such motifs are substantially more conserved compared to a neutral proxy does not mean that the majority of binding sites are conserved, nor does it imply that protein-bound sites considered collectively across the genome are more conserved than coding sequences under relatively weak selection. Since some of the most ‘highly conserved’ regulatory motifs are largely comprised by sites with recent origins, it is unlikely that this birth of new binding sites is simply a special property of a handful of TFs, but instead is likely to apply across many other factors. Nevertheless, some analysis challenges remain. For example, it is acknowledged that not all computationally predicted TFBSs within ChIP-seq peaks were actively bound by the TF and many ChIP-seq peaks may correspond to experimental noise. While researchers have continuously improved TFBS identification, high-throughput experimental approaches would be necessary to systematically validate binding site predictions, especially for lineage-specific ones. Among TFBSs in humans, a considerable amount of them are unique to hominids and are even human-specific. Since there are an estimated ∼1700–1900 TFs in the human genome[63], if even a small fraction of these sites harbor important regulatory potential, the total number of human-specific functional binding sites genome-wide is quite large. Although not all TFBSs with recent origins will be responsible for lineage-specific traits, these results nonetheless offer the potential to understand adaptive evolution of gene regulation via the creation of new TFBSs, not only alone, but also in combination. In addition, a number of recent studies have highlighted differences in transcription factor binding within humans[9],[64], and our results suggest that sequence-level variation of TFBSs within the population may be more common among more recently-derived binding sites. The functional categories of genes close to recently derived binding sites may serve to shed new light upon adaptive traits obtained along the lineage leading to human. It is interesting that, despite substantial differences in the biological functions generally associated with the six TFs analyzed, genes near binding sites with recent origins are enriched for several sensory and neural related pathways and processes. We note that since the ChIP-seq data we used in this study were not derived from neuronal cells, further study is needed to more comprehensively understand the roles of hominid-specific sites in specific cell types. Nevertheless, identifying such lineage-specific regulatory elements not only provides potential insight on human biology, but may also provide new knowledge on the molecular mechanisms of human diseases. A natural future direction for this work would be to determine the specific regulatory effects of the recently derived TFBSs identified using this method. For instance, enrichment for within-species variation among recently derived binding sites raises the intriguing possibility that recently derived TFBSs most responsible for phenotypic differences across species are also the elements responsible for within-species variation. Future work will be necessary to demonstrate whether this is the case and the differences in traits brought about by this variation. Also, our current model needs to be integrated with gene expression data to understand the interplay between cis-regulatory element evolution( e. g., binding site turnover and lineage-specific sites) and gene expression differences across different species[65]–[68]. The extent to which newly derived TFBSs operate primarily as cell-type specific elements with cell-specific regulatory function also remains an open question. The mechanisms that contribute to cell-type specific TF binding, whether through the presence or absence of other protein factors, accessibility of DNA within the chromatin structure, or by other means, are also possible future directions that can be more fully understood using a combination of different types of data that are becoming available.
Recent experimental studies showed that the evolution of transcription factor binding sites ( TFBS ) is highly dynamic , with sites differing a great deal even between closely related mammalian species . Despite the substantial experimental evidence for rapid divergence of regulatory protein-binding events across species , computational methods designed to analyze regulatory elements evolution have focused primarily on phylogenetic footprinting approaches , in which putative functional regulatory elements are identified according to strong sequence conservation . Cross-species comparisons of non-coding sequences are limited in their ability to fully understand the evolution of regulatory sequences , particularly in cases where the elements are selected for novelty or species-specific . We have developed a novel framework to reconstruct the history of lineage-specific TFBS and showed that large amount of TFBS in human were born after human-mouse divergence . These elements also have distinct biological implications as compared to more ancient ones . This method can help understand the roles of lineage-specific TFBS in shaping gene regulation across different species .