Modeling gene expression cascades during cell state transitions.

During cellular processes such as differentiation or response to external stimuli, cells exhibit dynamic changes in their gene expression profiles. Single-cell RNA sequencing (scRNA-seq) can be used to investigate these dynamic changes. To this end, cells are typically ordered along a pseudotemporal trajectory which recapitulates the progression of cells as they transition from one cell state to another. We infer transcriptional dynamics by modeling the gene expression profiles in pseudotemporally ordered cells using a Bayesian inference approach. This enables ordering genes along transcriptional cascades, estimating differences in the timing of gene expression dynamics, and deducing regulatory gene interactions. Here, we apply this approach to scRNA-seq datasets derived from mouse embryonic forebrain and pancreas samples. This analysis demonstrates the utility of the method to derive the ordering of gene dynamics and regulatory relationships critical for proper cellular differentiation and maturation across a variety of developmental contexts.

FOXO1-mediated lipid metabolism maintains mammalian embryos in dormancy.

Mammalian developmental timing is adjustable in vivo by preserving pre-implantation embryos in a dormant state called diapause. Inhibition of the growth regulator mTOR (mTORi) pauses mouse development in vitro, yet how embryonic dormancy is maintained is not known. Here we show that mouse embryos in diapause are sustained by using lipids as primary energy source. In vitro, supplementation of embryos with the metabolite L-carnitine balances lipid consumption, puts the embryos in deeper dormancy and boosts embryo longevity. We identify FOXO1 as an essential regulator of the energy balance in dormant embryos and propose, through meta-analyses of dormant cell signatures, that it may be a common regulator of dormancy across adult tissues. Our results lift a constraint on in vitro embryo survival and suggest that lipid metabolism may be a critical metabolic transition relevant for longevity and stem cell function across tissues.

Haplotype-based phylogenetic analysis and population genomics uncover the origin and domestication of sweetpotato.

The hexaploid sweetpotato (Ipomoea batatas) is one of the most important root crops worldwide. However, its genetic origin remains controversial, and its domestication history remains unknown. In this study, we used a range of genetic evidence and a newly developed haplotype-based phylogenetic analysis to identify two probable progenitors of sweetpotato. The diploid progenitor was likely closely related to Ipomoea aequatoriensis and contributed the B1 subgenome, IbT-DNA2, and the lineage 1 type of chloroplast genome to sweetpotato. The tetraploid progenitor of sweetpotato was most likely I. batatas 4x, which donated the B2 subgenome, IbT-DNA1, and the lineage 2 type of chloroplast genome. Sweetpotato most likely originated from reciprocal crosses between the diploid and tetraploid progenitors, followed by a subsequent whole-genome duplication. In addition, we detected biased gene exchanges between the subgenomes; the rate of B1 to B2 subgenome conversions was nearly three times higher than that of B2 to B1 subgenome conversions. Our analyses revealed that genes involved in storage root formation, maintenance of genome stability, biotic resistance, sugar transport, and potassium uptake were selected during the speciation and domestication of sweetpotato. This study sheds light on the evolution of sweetpotato and paves the way for improvement of this crop.

CENTRE: a gradient boosting algorithm for Cell-type-specific ENhancer-Target pREdiction.

MOTIVATION: Identifying target promoters of active enhancers is a crucial step for realizing gene regulation and deciphering phenotypes and diseases. Up to now, several computational methods were developed to predict enhancer gene interactions, but they require either many epigenomic and transcriptomic experimental assays to generate cell-type (CT)-specific predictions or a single experiment applied to a large cohort of CTs to extract correlations between activities of regulatory elements. Thus, inferring CT-specific enhancer gene interactions in unstudied or poorly annotated CTs becomes a laborious and costly task. RESULTS: Here, we aim to infer CT-specific enhancer target interactions, using minimal experimental input. We introduce Cell-specific ENhancer Target pREdiction (CENTRE), a machine learning framework that predicts enhancer target interactions in a CT-specific manner, using only gene expression and ChIP-seq data for three histone modifications for the CT of interest. CENTRE exploits the wealth of available datasets and extracts cell-type agnostic statistics to complement the CT-specific information. CENTRE is thoroughly tested across many datasets and CTs and achieves equivalent or superior performance than existing algorithms that require massive experimental data. AVAILABILITY AND IMPLEMENTATION: CENTRE's open-source code is available at GitHub via https://github.com/slrvv/CENTRE.

Fluid shear stress-modulated chromatin accessibility reveals the mechano-dependency of endothelial SMAD1/5-mediated gene transcription.

Bone morphogenetic protein (BMP) signaling and fluid shear stress (FSS) mediate complementary functions in vascular homeostasis and disease development. It remains to be shown whether altered chromatin accessibility downstream of BMP and FSS offers a crosstalk level to explain changes in SMAD-dependent transcription. Here, we employed ATAC-seq to analyze arterial endothelial cells stimulated with BMP9 and/or FSS. We found that BMP9-sensitive regions harbor non-palindromic GC-rich SMAD-binding elements (GGCTCC) and 69.7% of these regions become BMP-insensitive in the presence of FSS. While GATA and KLF transcription factor (TF) motifs are unique to BMP9- and FSS-sensitive regions, respectively, SOX motifs are common to both. Finally, we show that both SOX(13/18) and GATA(2/3/6) family members are directly upregulated by SMAD1/5. These findings highlight the mechano-dependency of SMAD-signaling by a sequential mechanism of first elevated pioneer TF expression, allowing subsequent chromatin opening to eventually providing accessibility to novel SMAD binding sites.

Induction of kidney-related gene programs through co-option of SALL1 in mole ovotestes.

Changes in gene expression represent an important source of phenotypic innovation. Yet how such changes emerge and impact the evolution of traits remains elusive. Here, we explore the molecular mechanisms associated with the development of masculinizing ovotestes in female moles. By performing integrative analyses of epigenetic and transcriptional data in mole and mouse, we identified the co-option of SALL1 expression in mole ovotestes formation. Chromosome conformation capture analyses highlight a striking conservation of the 3D organization at the SALL1 locus, but an evolutionary divergence of enhancer activity. Interspecies reporter assays support the capability of mole-specific enhancers to activate transcription in urogenital tissues. Through overexpression experiments in transgenic mice, we further demonstrate the capability of SALL1 to induce kidney-related gene programs, which are a signature of mole ovotestes. Our results highlight the co-option of gene expression, through changes in enhancer activity, as a plausible mechanism for the evolution of traits.

IsoTools: a flexible workflow for long-read transcriptome sequencing analysis.

MOTIVATION: Long-read transcriptome sequencing (LRTS) has the potential to enhance our understanding of alternative splicing and the complexity of this process requires the use of versatile computational tools, with the ability to accommodate various stages of the workflow with maximum flexibility. RESULTS: We introduce IsoTools, a Python-based LRTS analysis framework that offers a wide range of functionality for transcriptome reconstruction and quantification of transcripts. Furthermore, we integrate a graph-based method for identifying alternative splicing events and a statistical approach based on the beta-binomial distribution for detecting differential events. To demonstrate the effectiveness of our methods, we applied IsoTools to PacBio LRTS data of human hepatocytes treated with the histone deacetylase inhibitor valproic acid. Our results indicate that LRTS can provide valuable insights into alternative splicing, particularly in terms of complex and differential splicing patterns, in comparison to short-read RNA-seq. AVAILABILITY AND IMPLEMENTATION: IsoTools is available on GitHub and PyPI, and its documentation, including tutorials, CLI, and API references, can be found at https://isotools.readthedocs.io/.

Hierarchical Interleaved Bloom Filter: enabling ultrafast, approximate sequence queries.

We present a novel data structure for searching sequences in large databases: the Hierarchical Interleaved Bloom Filter (HIBF). It is extremely fast and space efficient, yet so general that it could serve as the underlying engine for many applications. We show that the HIBF is superior in build time, index size, and search time while achieving a comparable or better accuracy compared to other state-of-the-art tools. The HIBF builds an index up to 211 times faster, using up to 14 times less space, and can answer approximate membership queries faster by a factor of up to 129.

Prediction of protein-protein interactions using sequences of intrinsically disordered regions.

Protein-protein interactions (PPIs) play a crucial role in numerous molecular processes. Despite many efforts, mechanisms governing molecular recognition between interacting proteins remain poorly understood and it is particularly challenging to predict from sequence whether two proteins can interact. Here we present a new method to tackle this challenge using intrinsically disordered regions (IDRs). IDRs are protein segments that are functional despite lacking a single invariant three-dimensional structure. The prevalence of IDRs in eukaryotic proteins suggests that IDRs are critical for interactions. To test this hypothesis, we predicted PPIs using IDR sequences in candidate proteins in humans. Moreover, we divide the PPI prediction problem into two specific subproblems and adapt appropriate training and test strategies based on problem type. Our findings underline the importance of defining clearly the problem type and show that sequences encoding IDRs can aid in predicting specific features of the protein interaction network of intrinsically disordered proteins. Our findings further suggest that accounting for IDRs in future analyses should accelerate efforts to elucidate the eukaryotic PPI network.

Integration of Hi-C with short and long-read genome sequencing reveals the structure of germline rearranged genomes.

Structural variants are a common cause of disease and contribute to a large extent to inter-individual variability, but their detection and interpretation remain a challenge. Here, we investigate 11 individuals with complex genomic rearrangements including germline chromothripsis by combining short- and long-read genome sequencing (GS) with Hi-C. Large-scale genomic rearrangements are identified in Hi-C interaction maps, allowing for an independent assessment of breakpoint calls derived from the GS methods, resulting in >300 genomic junctions. Based on a comprehensive breakpoint detection and Hi-C, we achieve a reconstruction of whole rearranged chromosomes. Integrating information on the three-dimensional organization of chromatin, we observe that breakpoints occur more frequently than expected in lamina-associated domains (LADs) and that a majority reshuffle topologically associating domains (TADs). By applying phased RNA-seq, we observe an enrichment of genes showing allelic imbalanced expression (AIG) within 100 kb around the breakpoints. Interestingly, the AIGs hit by a breakpoint (19/22) display both up- and downregulation, thereby suggesting different mechanisms at play, such as gene disruption and rearrangements of regulatory information. However, the majority of interpretable genes located 200 kb around a breakpoint do not show significant expression changes. Thus, there is an overall robustness in the genome towards large-scale chromosome rearrangements.

Repression and 3D-restructuring resolves regulatory conflicts in evolutionarily rearranged genomes.

Regulatory landscapes drive complex developmental gene expression, but it remains unclear how their integrity is maintained when incorporating novel genes and functions during evolution. Here, we investigated how a placental mammal-specific gene, Zfp42, emerged in an ancient vertebrate topologically associated domain (TAD) without adopting or disrupting the conserved expression of its gene, Fat1. In ESCs, physical TAD partitioning separates Zfp42 and Fat1 with distinct local enhancers that drive their independent expression. This separation is driven by chromatin activity and not CTCF/cohesin. In contrast, in embryonic limbs, inactive Zfp42 shares Fat1's intact TAD without responding to active Fat1 enhancers. However, neither Fat1 enhancer-incompatibility nor nuclear envelope-attachment account for Zfp42's unresponsiveness. Rather, Zfp42's promoter is rendered inert to enhancers by context-dependent DNA methylation. Thus, diverse mechanisms enabled the integration of independent Zfp42 regulation in the Fat1 locus. Critically, such regulatory complexity appears common in evolution as, genome wide, most TADs contain multiple independently expressed genes.

Multiomic atlas with functional stratification and developmental dynamics of zebrafish cis-regulatory elements.

Zebrafish, a popular organism for studying embryonic development and for modeling human diseases, has so far lacked a systematic functional annotation program akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created a central repository to store and process zebrafish developmental functional genomic data. Our data coordination center ( https://danio-code.zfin.org ) combines a total of 1,802 sets of unpublished and re-analyzed published genomic data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements throughout development, including classes with distinct features dependent on their activity in time and space. We delineated the distinct distance topology and chromatin features between regulatory elements active during zygotic genome activation and those active during organogenesis. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predicted functional relationships between them beyond sequence similarity, thus extending the utility of zebrafish developmental genomics to mammals.

Enhanced cortical neural stem cell identity through short SMAD and WNT inhibition in human cerebral organoids facilitates emergence of outer radial glial cells.

Cerebral organoids exhibit broad regional heterogeneity accompanied by limited cortical cellular diversity despite the tremendous upsurge in derivation methods, suggesting inadequate patterning of early neural stem cells (NSCs). Here we show that a short and early Dual SMAD and WNT inhibition course is necessary and sufficient to establish robust and lasting cortical organoid NSC identity, efficiently suppressing non-cortical NSC fates, while other widely used methods are inconsistent in their cortical NSC-specification capacity. Accordingly, this method selectively enriches for outer radial glia NSCs, which cyto-architecturally demarcate well-defined outer sub-ventricular-like regions propagating from superiorly radially organized, apical cortical rosette NSCs. Finally, this method culminates in the emergence of molecularly distinct deep and upper cortical layer neurons, and reliably uncovers cortex-specific microcephaly defects. Thus, a short SMAD and WNT inhibition is critical for establishing a rich cortical cell repertoire that enables mirroring of fundamental molecular and cyto-architectural features of cortical development and meaningful disease modelling.