Characterization of cis-regulatory elements via open chromatin profiling

Cis-regulatorische Elemente wie Promotoren und Enhancer, die die Regulation der Transkription von Genen steuern, befinden sich in Regionen des dekondensierten Chromatins. DNase-seq und ATAC-seq sind weit verbreitete Verfahren, um solche offenen Chromatinregionen genomweit zu untersuchen. Die einzel-Nukleotid-Auflösung von DNase-seq wurde des Weiteren genutzt, um Transkriptionsfaktor-Bindungsstellen (TFBS) in regulatorischen Regionen durch TF-Footprinting zu bestimmen. Kürzlich durchgeführte Studien haben jedoch gezeigt, dass DNase I einen Sequenzbias aufweist, welcher nachteilige Auswirkungen auf die Footprinting-Effizienz hat. Auch wurden das Footprinting und die Auswirkungen des Sequenzbias auf ATAC-seq noch nicht umfassend untersucht. In dieser Arbeit nehme ich einen systematischen Vergleich der beiden Methoden vor und zeige, dass die beiden Methoden unterschiedliche Sequenzbiases haben und korrigiere diese protokollspezifischen Biases beim Footprinting. Der Einfluss von Bias-Korrekturen der Footprinting Ergebnisse ist für DNase-seq größer als für ATAC-seq, und Footprinting mit DNase-seq führt zu besseren Ergebnissen in unserer Datensätze. Trotz dieser Unterschiede zeige ich, dass die Integration replizierter Experimente die Ableitung von qualitativ hochwertigen Footprints ermöglicht, wobei die beiden Techniken weitgehend übereinstimmen. Diese Techniken werden ferner eingesetzt, um die cis-regulatorischen Elemente zu charakterisieren, die die Embryogenese der Fruchtfliege Drosophila melanogaster bestimmen. Durch die Verwendung von Embryonen die sich im richtigen Entwicklungsstadium befinden, sowie gewebespezifischer Kernsortierung mit offenem Chromatin-Profiling können zeitlich und gewebespezifisch aufgelöste vermeintliche cis-regulatorische Elemente definiert werden. Zusammengenommen demonstrieren diese Analysen die Fähigkeit der offenen Chromatin-Profilierung und der Computeranalyse zur Aufklärung der Mechanismen der Genregulation.Cis-regulatory elements such as promoters and enhancers, that govern transcriptional gene regulation, reside in regions of open chromatin. DNase-seq and ATAC-seq are broadly used methods to assay open chromatin regions genome-wide. The single nucleotide resolution of DNase-seq has been further exploited to infer transcription factor binding sites (TFBS) in regulatory regions through TF footprinting. However, recent studies have demonstrated the sequence bias of DNase I and its adverse effects on footprinting efficiency. Furthermore, footprinting and the impact of sequence bias have not been extensively studied for ATAC-seq. In this thesis, I undertake a systematic comparison of the two methods and demonstrate that the two methods have distinct sequence biases and correct for these protocol-specific biases when performing footprinting. The impact of bias correction on footprinting performance is greater for DNase-seq than for ATAC-seq, and footprinting with DNase-seq leads to better performance in our datasets. Despite these differences, I show that integrating replicate experiments allows the inference of high-quality footprints, with substantial agreement between the two techniques. These techniques are further employed to characterize the cis-regulatory elements governing the embryogenesis of a complex organism, the fruit fly Drosophila melanogaster. Combining tight staging of embryos and tissue-specific nuclear sorting with open chromatin profiling, enables the definition of temporally and tissue-specifically resolved putative cis-regulatory elements. Taken together, these analyses demonstrate the power of open chromatin profiling and computational analysis in elucidating the mechanisms of transcriptional gene regulation

FootprintPipeline

This is a pipeline to find transcription factor footprints in DNase-seq or ATAC-seq datasets

McEnhancer: predicting gene expression via semi-supervised assignment of enhancers to target genes

Abstract Transcriptional enhancers regulate spatio-temporal gene expression. While genomic assays can identify putative enhancers en masse, assigning target genes is a complex challenge. We devised a machine learning approach, McEnhancer, which links target genes to putative enhancers via a semi-supervised learning algorithm that predicts gene expression patterns based on enriched sequence features. Predicted expression patterns were 73–98% accurate, predicted assignments showed strong Hi-C interaction enrichment, enhancer-associated histone modifications were evident, and known functional motifs were recovered. Our model provides a general framework to link globally identified enhancers to targets and contributes to deciphering the regulatory genome

Determinants of promoter and enhancer transcription directionality in metazoans

Divergent transcription from promoters and enhancers occurs in many species, but it is unclear if it is a general feature of all eukaryotic cis regulatory elements. Here the authors define cis regulatory elements in worms, flies, and human; and identify several differences in regulatory architecture among metazoans

Additional file 1 of McEnhancer: predicting gene expression via semi-supervised assignment of enhancers to target genes

Supplementary figures. (PDF 9185 kb

Additional file 3 of McEnhancer: predicting gene expression via semi-supervised assignment of enhancers to target genes

McEnhancer predicted DHSs for each cluster. This table shows the predicted DHSs for each cluster, along with its associated gene. Columns represent DHS coordinates (chr, start, end), DHS ID linked to its associated gene, and number of times each DHS was selected in the model’s pairwise comparisons against other clusters. (TXT 778 kb

Tumor-intrinsic expression of the autophagy gene Atg16l1 suppresses anti-tumor immunity in colorectal cancer

Abstract Microsatellite-stable colorectal cancer (MSS-CRC) is highly refractory to immunotherapy. Understanding tumor-intrinsic determinants of immunotherapy resistance is critical to improve MSS-CRC patient outcomes. Here, we demonstrate that high tumor expression of the core autophagy gene ATG16L1 is associated with poor clinical response to anti-PD-L1 therapy in KRAS-mutant tumors from IMblaze370 (NCT02788279), a large phase III clinical trial of atezolizumab (anti-PD-L1) in advanced metastatic MSS-CRC. Deletion of Atg16l1 in engineered murine colon cancer organoids inhibits tumor growth in primary (colon) and metastatic (liver and lung) niches in syngeneic female hosts, primarily due to increased sensitivity to IFN-γ-mediated immune pressure. ATG16L1 deficiency enhances programmed cell death of colon cancer organoids induced by IFN-γ and TNF, thus increasing their sensitivity to host immunity. In parallel, ATG16L1 deficiency reduces tumor stem-like populations in vivo independently of adaptive immune pressure. This work reveals autophagy as a clinically relevant mechanism of immune evasion and tumor fitness in MSS-CRC and provides a rationale for autophagy inhibition to boost immunotherapy responses in the clinic