The enhancer landscape during early neocortical development reveals patterns of dense regulation and co-option.

Genetic studies have identified a core set of transcription factors and target genes that control the development of the neocortex, the region of the human brain responsible for higher cognition. The specific regulatory interactions between these factors, many key upstream and downstream genes, and the enhancers that mediate all these interactions remain mostly uncharacterized. We perform p300 ChIP-seq to identify over 6,600 candidate enhancers active in the dorsal cerebral wall of embryonic day 14.5 (E14.5) mice. Over 95% of the peaks we measure are conserved to human. Eight of ten (80%) candidates tested using mouse transgenesis drive activity in restricted laminar patterns within the neocortex. GREAT based computational analysis reveals highly significant correlation with genes expressed at E14.5 in key areas for neocortex development, and allows the grouping of enhancers by known biological functions and pathways for further studies. We find that multiple genes are flanked by dozens of candidate enhancers each, including well-known key neocortical genes as well as suspected and novel genes. Nearly a quarter of our candidate enhancers are conserved well beyond mammals. Human and zebrafish regions orthologous to our candidate enhancers are shown to most often function in other aspects of central nervous system development. Finally, we find strong evidence that specific interspersed repeat families have contributed potentially key developmental enhancers via co-option. Our analysis expands the methodologies available for extracting the richness of information found in genome-wide functional maps.

Automated discovery of tissue-targeting enhancers and transcription factors from binding motif and gene function data.

Identifying enhancers regulating gene expression remains an important and challenging task. While recent sequencing-based methods provide epigenomic characteristics that correlate well with enhancer activity, it remains onerous to comprehensively identify all enhancers across development. Here we introduce a computational framework to identify tissue-specific enhancers evolving under purifying selection. First, we incorporate high-confidence binding site predictions with target gene functional enrichment analysis to identify transcription factors (TFs) likely functioning in a particular context. We then search the genome for clusters of binding sites for these TFs, overcoming previous constraints associated with biased manual curation of TFs or enhancers. Applying our method to the placenta, we find 33 known and implicate 17 novel TFs in placental function, and discover 2,216 putative placenta enhancers. Using luciferase reporter assays, 31/36 (86%) tested candidates drive activity in placental cells. Our predictions agree well with recent epigenomic data in human and mouse, yet over half our loci, including 7/8 (87%) tested regions, are novel. Finally, we establish that our method is generalizable by applying it to 5 additional tissues: heart, pancreas, blood vessel, bone marrow, and liver.

Sample matching by inferred agonal stress in gene expression analyses of the brain.

BACKGROUND: Gene expression patterns in the brain are strongly influenced by the severity and duration of physiological stress at the time of death. This agonal effect, if not well controlled, can lead to spurious findings and diminished statistical power in case-control comparisons. While some recent studies match samples by tissue pH and clinically recorded agonal conditions, we found that these indicators were sometimes at odds with observed stress-related gene expression patterns, and that matching by these criteria still sometimes results in identifying case-control differences that are primarily driven by residual agonal effects. This problem is analogous to the one encountered in genetic association studies, where self-reported race and ethnicity are often imprecise proxies for an individual's actual genetic ancestry. RESULTS: We developed an Agonal Stress Rating (ASR) system that evaluates each sample's degree of stress based on gene expression data, and used ASRs in post hoc sample matching or covariate analysis. While gene expression patterns are generally correlated across different brain regions, we found strong region-region differences in empirical ASRs in many subjects that likely reflect inter-individual variabilities in local structure or function, resulting in region-specific vulnerability to agonal stress. CONCLUSION: Variation of agonal stress across different brain regions differs between individuals, revealing a new level of complexity for gene expression studies of brain tissues. The Agonal Stress Ratings quantitatively assess each sample's extent of regulatory response to agonal stress, and allow a strong control of this important confounder.

Changes in the enhancer landscape during early placental development uncover a trophoblast invasion gene-enhancer network.

INTRODUCTION: Trophoblast invasion establishes adequate blood flow between mother and fetus in early placental development. However, little is known about the cis-regulatory mechanisms underlying this important process. We aimed to identify enhancer elements that are active during trophoblast invasion, and build a trophoblast invasion gene-enhancer network. METHODS: We carried out ChIP-Seq for an enhancer-associated mark (H3k27Ac) at two time points during early placental development in mouse. One time point when invasion is at its peak (e7.5) and another time point shortly afterwards (e9.5). We use computational analysis to identify putative enhancers, as well as the transcription factor binding sites within them, that are specific to the time point of trophoblast invasion. RESULTS: We compared read profiles at e7.5 and e9.5 to identify 1,977 e7.5-specific enhancers. Within a subset of e7.5-specific enhancers, we discovered a cell migration associated regulatory code, consisting of three transcription factor motifs: AP1, Ets, and Tcfap2. To validate differential expression of the transcription factors that bind these motifs, we performed RNA-Seq in the same context. Finally, we integrated these data with publicly available protein-protein interaction data and constructed a trophoblast invasion gene-enhancer network. DISCUSSION: The data we generated and analysis we carried out improves our understanding of the regulatory mechanisms of trophoblast invasion, by suggesting a transcriptional code exists in the enhancers of cell migration genes. Furthermore, the network we constructed highlights novel candidate genes that may be critical for trophoblast invasion.

A family of transposable elements co-opted into developmental enhancers in the mouse neocortex.

The neocortex is a mammalian-specific structure that is responsible for higher functions such as cognition, emotion and perception. To gain insight into its evolution and the gene regulatory codes that pattern it, we studied the overlap of its active developmental enhancers with transposable element (TE) families and compared this overlap to uniformly shuffled enhancers. Here we show a striking enrichment of the MER130 repeat family among active enhancers in the mouse dorsal cerebral wall, which gives rise to the neocortex, at embryonic day 14.5. We show that MER130 instances preserve a common code of transcriptional regulatory logic, function as enhancers and are adjacent to critical neocortical genes. MER130, a nonautonomous interspersed TE, originates in the tetrapod or possibly Sarcopterygii ancestor, which far predates the appearance of the neocortex. Our results show that MER130 elements were recruited, likely through their common regulatory logic, as neocortical enhancers.

Systematic changes in gene expression in postmortem human brains associated with tissue pH and terminal medical conditions.

Studies of gene expression abnormalities in psychiatric or neurological disorders often involve the use of postmortem brain tissue. Compared with single-cell organisms or clonal cell lines, the biological environment and medical history of human subjects cannot be controlled, and are often difficult to document fully. The chance of finding significant and replicable changes depends on the nature and magnitude of the observed variations among the studied subjects. During an analysis of gene expression changes in mood disorders, we observed a remarkable degree of natural variation among 120 samples, which represented three brain regions in 40 subjects. Most of such diversity can be accounted for by two distinct expression patterns, which in turn are strongly correlated with tissue pH. Individuals who suffered prolonged agonal states, such as with respiratory arrest, multi-organ failure or coma, tended to have lower pH in the brain; whereas those who experienced brief deaths, associated with accidents, cardiac events or asphyxia, generally had normal pH. The lower pH samples exhibited a systematic decrease in expression of genes involved in energy metabolism and proteolytic activities, and a consistent increase of genes encoding stress-response proteins and transcription factors. This functional specificity of changed genes suggests that the difference is not merely due to random RNA degradation in low pH samples; rather it reflects a broad and actively coordinated biological response in living cells. These findings shed light on critical molecular mechanisms that are engaged during different forms of terminal stress, and may suggest clinical targets of protection or restoration.