Introduction Various sequencing based approaches are used to identify and characterize the activities of cis -regulatory elements in a genome-wide fashion. Some of these techniques rely on indirect markers such as histone modifications (ChIP-seq with histone antibodies) or chromatin accessibility (ATAC-seq, DNase-seq, FAIRE-seq), while other techniques use direct measures such as episomal assays measuring the enhancer properties of DNA sequences (STARR-seq) and direct measurement of the binding of transcription factors (ChIP-seq with transcription factor-specific antibodies). The activities of cis -regulatory elements such as enhancers, promoters, and repressors are determined by their sequence and secondary processes such as chromatin accessibility, DNA methylation, and bound histone markers. Methods Here, machine learning models are employed to evaluate the accuracy with which cis -regulatory elements identified by various commonly used sequencing techniques can be predicted by their underlying sequence alone to distinguish between cis -regulatory activity that is reflective of sequence content versus secondary processes. Results and discussion Models trained and evaluated on D. melanogaster sequences identified through DNase-seq and STARR-seq are significantly more accurate than models trained on sequences identified by H3K4me1, H3K4me3, and H3K27ac ChIP-seq, FAIRE-seq, and ATAC-seq. These results suggest that the activity detected by DNase-seq and STARR-seq can be largely explained by underlying DNA sequence, independent of secondary processes. Experimentally, a subset of DNase-seq and H3K4me1 ChIP-seq sequences were tested for enhancer activity using luciferase assays and compared with previous tests performed on STARR-seq sequences. The experimental data indicated that STARR-seq sequences are substantially enriched for enhancer-specific activity, while the DNase-seq and H3K4me1 ChIP-seq sequences are not. Taken together, these results indicate that the DNase-seq approach identifies a broad class of regulatory elements of which enhancers are a subset and the associated data are appropriate for training models for detecting regulatory activity from sequence alone, STARR-seq data are best for training enhancer-specific sequence models, and H3K4me1 ChIP-seq data are not well suited for training and evaluating sequence-based models for cis -regulatory element prediction.
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Intrinsic bias estimation for improved analysis of bulk and single-cell chromatin accessibility profiles using SELMA
Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. However, enzymatic DNA cleavage exhibits intrinsic sequence biases that confound chromatin accessibility profiling data analysis. Existing computational tools are limited in their ability to account for such intrinsic biases and not designed for analyzing single-cell data. Here, we present Simplex Encoded Linear Model for Accessible Chromatin (SELMA), a computational method for systematic estimation of intrinsic cleavage biases from genomic chromatin accessibility profiling data. We demonstrate that SELMA yields accurate and robust bias estimation from both bulk and single-cell DNase-seq and ATAC-seq data. SELMA can utilize internal mitochondrial DNA data to improve bias estimation. We show that transcription factor binding inference from DNase footprints can be improved by incorporating estimated biases using SELMA. Furthermore, we show strong effects of intrinsic biases in single-cell ATAC-seq data, and develop the first single-cell ATAC-seq intrinsic bias correction model to improve cell clustering. SELMA can enhance the performance of existing bioinformatics tools and improve the analysis of both bulk and single-cell chromatin accessibility sequencing data.
more » « less- Award ID(s):
- 2048991
- NSF-PAR ID:
- 10371987
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Nature Communications
- Volume:
- 13
- Issue:
- 1
- ISSN:
- 2041-1723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)Characterizing genome-wide binding profiles of transcription factors (TFs) is essential for understanding biological processes. Although techniques have been developed to assess binding profiles within a population of cells, determining them at a single-cell level remains elusive. Here, we report scFAN (single-cell factor analysis network), a deep learning model that predicts genome-wide TF binding profiles in individual cells. scFAN is pretrained on genome-wide bulk assay for transposase-accessible chromatin sequencing (ATAC-seq), DNA sequence, and chromatin immunoprecipitation sequencing (ChIP-seq) data and uses single-cell ATAC-seq to predict TF binding in individual cells. We demonstrate the efficacy of scFAN by both studying sequence motifs enriched within predicted binding peaks and using predicted TFs for discovering cell types. We develop a new metric “TF activity score” to characterize each cell and show that activity scores can reliably capture cell identities. scFAN allows us to discover and study cellular identities and heterogeneity based on chromatin accessibility profiles.more » « less
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Summary Cell differentiation is driven by changes in the activity of transcription factors (
TF s) and subsequent alterations in transcription. To study this process, differences inTF binding between cell types can be deduced by probing chromatin accessibility. We used cell type‐specific nuclear purification followed by the assay for transposase‐accessible chromatin (ATAC ‐seq) to delineate differences in chromatin accessibility andTF regulatory networks between stem cells of the shoot apical meristem (SAM ) and differentiated leaf mesophyll cells inArabidopsis thaliana . Chromatin accessibility profiles ofSAM stem cells and leaf mesophyll cells were very similar at a qualitative level, yet thousands of regions having quantitatively different chromatin accessibility were also identified. Analysis of the genomic regions preferentially accessible in each cell type identified hundreds of overrepresentedTF ‐binding motifs, highlighting sets ofTF s that are probably important for each cell type. Within these sets, we found evidence for extensive co‐regulation of target genes by multipleTF s that are preferentially expressed in each cell type. Interestingly, theTF s within each of these cell type‐enriched sets also showed evidence of extensively co‐regulating each other. We further found that preferentially accessible chromatin regions in mesophyll cells tended to also be substantially accessible in the stem cells, whereas the converse was not true. This observation suggests that the generally higher accessibility of regulatory elements in stem cells might contribute to their developmental plasticity. This work demonstrates the utility of cell type‐specific chromatin accessibility profiling for the rapid development of testable models of regulatory control differences between cell types. -
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Somatic cell transcription factors are critical to maintaining cellular identity and constitute a barrier to human somatic cell reprogramming; yet a comprehensive understanding of the mechanism of action is lacking. To gain insight, we examined epigenome remodeling at the onset of human nuclear reprogramming by profiling human fibroblasts after fusion with murine embryonic stem cells (ESCs). By assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and chromatin immunoprecipitation sequencing we identified enrichment for the activator protein 1 (AP-1) transcription factor c-Jun at regions of early transient accessibility at fibroblast-specific enhancers. Expression of a dominant negative AP-1 mutant (dnAP-1) reduced accessibility and expression of fibroblast genes, overcoming the barrier to reprogramming. Remarkably, efficient reprogramming of human fibroblasts to induced pluripotent stem cells was achieved by transduction with vectors expressing SOX2, KLF4, and inducible dnAP-1, demonstrating that dnAP-1 can substitute for exogenous human OCT4. Mechanistically, we show that the AP-1 component c-Jun has two unexpected temporally distinct functions in human reprogramming: 1) to potentiate fibroblast enhancer accessibility and fibroblast-specific gene expression, and 2) to bind to and repress
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Abstract Background The genetic information contained in the genome of an organism is organized in genes and regulatory elements that control gene expression. The genomes of multiple plants species have already been sequenced and the gene repertory have been annotated, however,
cis -regulatory elements remain less characterized, limiting our understanding of genome functionality. These elements act as open platforms for recruiting both positive- and negative-acting transcription factors, and as such, chromatin accessibility is an important signature for their identification.Results In this work we developed a transgenic INTACT [isolation of nuclei tagged in specific cell types] system in tetraploid wheat for nuclei purifications. Then, we combined the INTACT system together with the assay for transposase-accessible chromatin with sequencing [ATAC-seq] to identify open chromatin regions in wheat root tip samples. Our ATAC-seq results showed a large enrichment of open chromatin regions in intergenic and promoter regions, which is expected for regulatory elements and that is similar to ATAC-seq results obtained in other plant species. In addition, root ATAC-seq peaks showed a significant overlap with a previously published ATAC-seq data from wheat leaf protoplast, indicating a high reproducibility between the two experiments and a large overlap between open chromatin regions in root and leaf tissues. Importantly, we observed overlap between ATAC-seq peaks and
cis -regulatory elements that have been functionally validated in wheat, and a good correlation between normalized accessibility and gene expression levels.Conclusions We have developed and validated an INTACT system in tetraploid wheat that allows rapid and high-quality nuclei purification from root tips. Those nuclei were successfully used to performed ATAC-seq experiments that revealed open chromatin regions in the wheat genome that will be useful to identify cis-regulatory elements. The INTACT system presented here will facilitate the development of ATAC-seq datasets in other tissues, growth stages, and under different growing conditions to generate a more complete landscape of the accessible DNA regions in the wheat genome.
