Seq2science: an end-to-end workflow for functional genomics analysis.

Sequencing databases contain enormous amounts of functional genomics data, making them an extensive resource for genome-scale analysis. Reanalyzing publicly available data, and integrating it with new, project-specific data sets, can be invaluable. With current technologies, genomic experiments have become feasible for virtually any species of interest. However, using and integrating this data comes with its challenges, such as standardized and reproducible analysis. Seq2science is a multi-purpose workflow that covers preprocessing, quality control, visualization, and analysis of functional genomics sequencing data. It facilitates the downloading of sequencing data from all major databases, including NCBI SRA, EBI ENA, DDBJ, GSA, and ENCODE. Furthermore, it automates the retrieval of any genome assembly available from Ensembl, NCBI, and UCSC. It has been tested on a variety of species, and includes diverse workflows such as ATAC-, RNA-, and ChIP-seq. It consists of both generic as well as advanced steps, such as differential gene expression or peak accessibility analysis and differential motif analysis. Seq2science is built on the Snakemake workflow language and thus can be run on a range of computing infrastructures. It is available at https://github.com/vanheeringen-lab/seq2science.

genomepy: genes and genomes at your fingertips.

MOTIVATION: Analyzing a functional genomics experiment, such as ATAC-, ChIP-, or RNA-sequencing, requires genomic resources such as a reference genome assembly and gene annotation. These data can generally be retrieved from different organizations and in different versions. Most bioinformatic workflows require the user to supply this genomic data manually, which can be a tedious and error-prone process. RESULTS: Here, we present genomepy, which can search, download, and preprocess the right genomic data for your analysis. Genomepy can search genomic data on NCBI, Ensembl, UCSC, and GENCODE, and inspect available gene annotations to enable an informed decision. The selected genome and gene annotation can be downloaded and preprocessed with sensible, yet controllable, defaults. Additional supporting data can be automatically generated or downloaded, such as aligner indexes, genome metadata, and blacklists. AVAILABILITY AND IMPLEMENTATION: Genomepy is freely available at https://github.com/vanheeringen-lab/genomepy under the MIT license and can be installed through pip or Bioconda.

Computational approaches to understand transcription regulation in development.

Gene regulatory networks (GRNs) serve as useful abstractions to understand transcriptional dynamics in developmental systems. Computational prediction of GRNs has been successfully applied to genome-wide gene expression measurements with the advent of microarrays and RNA-sequencing. However, these inferred networks are inaccurate and mostly based on correlative rather than causative interactions. In this review, we highlight three approaches that significantly impact GRN inference: (1) moving from one genome-wide functional modality, gene expression, to multi-omics, (2) single cell sequencing, to measure cell type-specific signals and predict context-specific GRNs, and (3) neural networks as flexible models. Together, these experimental and computational developments have the potential to significantly impact the quality of inferred GRNs. Ultimately, accurately modeling the regulatory interactions between transcription factors and their target genes will be essential to understand the role of transcription factors in driving developmental gene expression programs and to derive testable hypotheses for validation.

Retinoic acid signaling drives differentiation toward the absorptive lineage in colorectal cancer.

Retinoic acid (RA) signaling is an important and conserved pathway that regulates cellular proliferation and differentiation. Furthermore, perturbed RA signaling is implicated in cancer initiation and progression. However, the mechanisms by which RA signaling contributes to homeostasis, malignant transformation, and disease progression in the intestine remain incompletely understood. Here, we report, in agreement with previous findings, that activation of the Retinoic Acid Receptor and the Retinoid X Receptor results in enhanced transcription of enterocyte-specific genes in mouse small intestinal organoids. Conversely, inhibition of this pathway results in reduced expression of genes associated with the absorptive lineage. Strikingly, this latter effect is conserved in a human organoid model for colorectal cancer (CRC) progression. We further show that RXR motif accessibility depends on progression state of CRC organoids. Finally, we show that reduced RXR target gene expression correlates with worse CRC prognosis, implying RA signaling as a putative therapeutic target in CRC.

ANANSE: an enhancer network-based computational approach for predicting key transcription factors in cell fate determination.

Proper cell fate determination is largely orchestrated by complex gene regulatory networks centered around transcription factors. However, experimental elucidation of key transcription factors that drive cellular identity is currently often intractable. Here, we present ANANSE (ANalysis Algorithm for Networks Specified by Enhancers), a network-based method that exploits enhancer-encoded regulatory information to identify the key transcription factors in cell fate determination. As cell type-specific transcription factors predominantly bind to enhancers, we use regulatory networks based on enhancer properties to prioritize transcription factors. First, we predict genome-wide binding profiles of transcription factors in various cell types using enhancer activity and transcription factor binding motifs. Subsequently, applying these inferred binding profiles, we construct cell type-specific gene regulatory networks, and then predict key transcription factors controlling cell fate transitions using differential networks between cell types. This method outperforms existing approaches in correctly predicting major transcription factors previously identified to be sufficient for trans-differentiation. Finally, we apply ANANSE to define an atlas of key transcription factors in 18 normal human tissues. In conclusion, we present a ready-to-implement computational tool for efficient prediction of transcription factors in cell fate determination and to study transcription factor-mediated regulatory mechanisms. ANANSE is freely available at https://github.com/vanheeringen-lab/ANANSE.

Stronger induction of trained immunity by mucosal BCG or MTBVAC vaccination compared to standard intradermal vaccination.

BCG vaccination can strengthen protection against pathogens through the induction of epigenetic and metabolic reprogramming of innate immune cells, a process called trained immunity. We and others recently demonstrated that mucosal or intravenous BCG better protects rhesus macaques from Mycobacterium tuberculosis infection and TB disease than standard intradermal vaccination, correlating with local adaptive immune signatures. In line with prior mouse data, here, we show in rhesus macaques that intravenous BCG enhances innate cytokine production associated with changes in H3K27 acetylation typical of trained immunity. Alternative delivery of BCG does not alter the cytokine production of unfractionated bronchial lavage cells. However, mucosal but not intradermal vaccination, either with BCG or the M. tuberculosis-derived candidate MTBVAC, enhances innate cytokine production by blood- and bone marrow-derived monocytes associated with metabolic rewiring, typical of trained immunity. These results provide support to strategies for improving TB vaccination and, more broadly, modulating innate immunity via mucosal surfaces.

Combinatorial transcription factor activities on open chromatin induce embryonic heterogeneity in vertebrates.

During vertebrate gastrulation, mesoderm is induced in pluripotent cells, concomitant with dorsal-ventral patterning and establishing of the dorsal axis. We applied single-cell chromatin accessibility and transcriptome analyses to explore the emergence of cellular heterogeneity during gastrulation in Xenopus tropicalis. Transcriptionally inactive lineage-restricted genes exhibit relatively open chromatin in animal caps, whereas chromatin accessibility in dorsal marginal zone cells more closely reflects transcriptional activity. We characterized single-cell trajectories and identified head and trunk organizer cell clusters in early gastrulae. By integrating chromatin accessibility and transcriptome data, we inferred the activity of transcription factors in single-cell clusters and tested the activity of organizer-expressed transcription factors in animal caps, alone or in combination. The expression profile induced by a combination of Foxb1 and Eomes most closely resembles that observed in the head organizer. Genes induced by Eomes, Otx2, or the Irx3-Otx2 combination are enriched for maternally regulated H3K4me3 modifications, whereas Lhx8-induced genes are marked more frequently by zygotically controlled H3K4me3. Taken together, our results show that transcription factors cooperate in a combinatorial fashion in generally open chromatin to orchestrate zygotic gene expression.

A cell-based boundary model of gastrulation by unipolar ingression in the hydrozoan cnidarian Clytia hemisphaerica.

In Cnidaria, modes of gastrulation to produce the two body layers vary greatly between species. In the hydrozoan species Clytia hemisphaerica gastrulation involves unipolar ingression of presumptive endoderm cells from an oral domain of the blastula, followed by migration of these cells to fill the blastocoel with concomitant narrowing of the gastrula and elongation along the oral-aboral axis. We developed a 2D computational boundary model capable of simulating the morphogenetic changes during embryonic development from early blastula stage to the end of gastrulation. Cells are modeled as polygons with elastic membranes and cytoplasm, colliding and adhering to other cells, and capable of forming filopodia. With this model we could simulate compaction of the embryo preceding gastrulation, bottle cell formation, ingression, and intercalation between cells of the ingressing presumptive endoderm. We show that embryo elongation is dependent on the number of endodermal cells, low endodermal cell-cell adhesion, and planar cell polarity (PCP). When the strength of PCP is reduced in our model, resultant embryo morphologies closely resemble those reported previously following morpholino-mediated knockdown of the core PCP proteins Strabismus and Frizzled. Based on our results, we postulate that cellular processes of apical constriction, compaction, ingression, and then reduced cell-cell adhesion and mediolateral intercalation in the presumptive endoderm, are required and when combined, sufficient for Clytia gastrulation.