Allelic expression mapping across cellular lineages to establish impact of non-coding SNPs

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Chromatin accessibility reveals insights into androgen receptor activation and transcriptional specificity

BACKGROUND: Epigenetic mechanisms such as chromatin accessibility impact transcription factor binding to DNA and transcriptional specificity. The androgen receptor (AR), a master regulator of the male phenotype and prostate cancer pathogenesis, acts primarily through ligand-activated transcription of target genes. Although several determinants of AR transcriptional specificity have been elucidated, our understanding of the interplay between chromatin accessibility and AR function remains incomplete. RESULTS: We used deep sequencing to assess chromatin structure via DNase I hypersensitivity and mRNA abundance, and paired these datasets with three independent AR ChIP-seq datasets. Our analysis revealed qualitative and quantitative differences in chromatin accessibility that corresponded to both AR binding and an enrichment of motifs for potential collaborating factors, one of which was identified as SP1. These quantitative differences were significantly associated with AR-regulated mRNA transcription across the genome. Base-pair resolution of the DNase I cleavage profile revealed three distinct footprinting patterns associated with the AR-DNA interaction, suggesting multiple modes of AR interaction with the genome. CONCLUSIONS: In contrast with other DNA-binding factors, AR binding to the genome does not only target regions that are accessible to DNase I cleavage prior to hormone induction. AR binding is invariably associated with an increase in chromatin accessibility and, consequently, changes in gene expression. Furthermore, we present the first in vivo evidence that a significant fraction of AR binds only to half of the full AR DNA motif. These findings indicate a dynamic quantitative relationship between chromatin structure and AR-DNA binding that impacts AR transcriptional specificity

Molecular architecture of transcription factor hotspots in early adipogenesis

SummaryTranscription factors have recently been shown to colocalize in hotspot regions of the genome, which are further clustered into super-enhancers. However, the detailed molecular organization of transcription factors at hotspot regions is poorly defined. Here, we have used digital genomic footprinting to precisely define factor localization at a genome-wide level during the early phase of 3T3-L1 adipocyte differentiation, which allows us to obtain detailed molecular insight into how transcription factors target hotspots. We demonstrate the formation of ATF-C/EBP heterodimers at a composite motif on chromatin, and we suggest that this may be a general mechanism for integrating external signals on chromatin. Furthermore, we find evidence of extensive recruitment of transcription factors to hotspots through alternative mechanisms not involving their known motifs and demonstrate that these alternative binding events are functionally important for hotspot formation and activity. Taken together, these findings provide a framework for understanding transcription factor cooperativity in hotspots

Analysis of optimized DNase-seq reveals intrinsic bias in transcription factor footprint identification

DNase-seq is a powerful technique for identifying cis-regulatory elements across the genome. We studied the key experimental parameters to optimize the performance of DNase-seq. We found that sequencing short 50-100bp fragments that accumulate in long inter-nucleosome linker regions is more efficient for identifying transcription factor binding sites than using longer fragments. We also assessed the potential of DNase-seq to predict transcription factor occupancy through the generation of nucleotide-resolution transcription factor footprints. In modeling the sequence-specific DNaseI cutting bias we found a surprisingly strong effect that varied over more than two orders of magnitude. This confounds DNaseI footprint analysis to the extent that the nucleotide resolution cleavage patterns at most transcription factor binding sites are derived from intrinsic DNaseI cleavage bias rather than from specific protein-DNA interactions. In contrast, quantitative comparison of DNaseI hypersensitivity between states can predict transcription factor occupancy associated with particular biological perturbations

Genome-Wide Transcription Factor Binding in Leaves from C3 and C4 Grasses.

The majority of plants use C3 photosynthesis, but over 60 independent lineages of angiosperms have evolved the C4 pathway. In most C4 species, photosynthesis gene expression is compartmented between mesophyll and bundle-sheath cells. We performed DNaseI sequencing to identify genome-wide profiles of transcription factor binding in leaves of the C4 grasses Zea mays, Sorghum bicolor, and Setaria italica as well as C3 Brachypodium distachyon In C4 species, while bundle-sheath strands and whole leaves shared similarity in the broad regions of DNA accessible to transcription factors, the short sequences bound varied. Transcription factor binding was prevalent in gene bodies as well as promoters, and many of these sites could represent duons that influence gene regulation in addition to amino acid sequence. Although globally there was little correlation between any individual DNaseI footprint and cell-specific gene expression, within individual species transcription factor binding to the same motifs in multiple genes provided evidence for shared mechanisms governing C4 photosynthesis gene expression. Furthermore, interspecific comparisons identified a small number of highly conserved transcription factor binding sites associated with leaves from species that diverged around 60 million years ago. These data therefore provide insight into the architecture associated with C4 photosynthesis gene expression in particular and characteristics of transcription factor binding in cereal crops in general.BBSRC ERC CONACy

Transcriptional and translational regulation of sex-specific genes in mouse liver

With the advent of high-throughput sequencing technology, modeling molecular mechanisms for gene regulatory networks has expanded to include the epigenome. Using diverse high-throughput DNA sequencing platforms, previous studies have revealed such mechanisms for sex-differential gene regulation in mouse liver. This thesis describes the contribution of transcription factor (TF) HNF6 to these models. Further, the utility of digital genomic footprinting (DGF) using the DNase-I hypersensitive sites sequencing (DNase-Seq) assay or the Assay for Transposase Accessible Chromatin (ATAC-Seq) is demonstrated. Finally, this thesis characterizes the extent of post-translational control of genes active in mouse liver using the ribosome profiling assay (Ribo-Seq), by way of translational efficiency (TE), and uses Ribo-Seq to interrogate open reading frames from previously characterized untranslated regions of protein-coding genes and in a set of liver-expressed long non-coding RNA genes for evidence of translation. First, mouse liver binding sites for HNF6 are integrated for overlap with sex-biased DNase-I hypersensitivity sites, male-biased STAT5, and female-specific CUX2 binding sites. This analysis showed how epigenetic markers, together with HNF6, target specific sets of sex-biased genes, revealing specific mechanisms involving HNF6 that contribute to the sex-specificity of gene expression in mouse liver. Next, the limited utility of the DGF technique to predict TF-DNA interactions was demonstrated using publicly available datasets for 21 TFs using DNase-seq and ATAC-seq datasets and sequencing libraries prepared using chromatin as well as purified DNA. Additionally, a simple model is proposed that benchmarks performance of DNase-seq vs. ATAC-seq for the same set of 21 TFs. Finally, the extent to which liver-expressed genes are regulated by sex-differential TE was investigated using Ribo-Seq. Limited sex-differential TE was found. Further, this assay predicted novel peptides found in previously characterized non-coding open reading frames within untranslated regions of genes that may regulate TE of upstream genes, and in a set of liver-expressed long non-coding RNAs.2021-02-20T00:00:00

Transcriptional regulatory logic of the diurnal cycle in the mouse liver.

Many organisms exhibit temporal rhythms in gene expression that propel diurnal cycles in physiology. In the liver of mammals, these rhythms are controlled by transcription-translation feedback loops of the core circadian clock and by feeding-fasting cycles. To better understand the regulatory interplay between the circadian clock and feeding rhythms, we mapped DNase I hypersensitive sites (DHSs) in the mouse liver during a diurnal cycle. The intensity of DNase I cleavages cycled at a substantial fraction of all DHSs, suggesting that DHSs harbor regulatory elements that control rhythmic transcription. Using chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq), we found that hypersensitivity cycled in phase with RNA polymerase II (Pol II) loading and H3K27ac histone marks. We then combined the DHSs with temporal Pol II profiles in wild-type (WT) and Bmal1-/- livers to computationally identify transcription factors through which the core clock and feeding-fasting cycles control diurnal rhythms in transcription. While a similar number of mRNAs accumulated rhythmically in Bmal1-/- compared to WT livers, the amplitudes in Bmal1-/- were generally lower. The residual rhythms in Bmal1-/- reflected transcriptional regulators mediating feeding-fasting responses as well as responses to rhythmic systemic signals. Finally, the analysis of DNase I cuts at nucleotide resolution showed dynamically changing footprints consistent with dynamic binding of CLOCK:BMAL1 complexes. Structural modeling suggested that these footprints are driven by a transient heterotetramer binding configuration at peak activity. Together, our temporal DNase I mappings allowed us to decipher the global regulation of diurnal transcription rhythms in the mouse liver

Genome Biol.

With genome analysis expanding from the study of genes to the study of gene regulation, 'regulatory genomics' utilizes sequence information, evolution and functional genomics measurements to unravel how regulatory information is encoded in the genome