Translational potential of mouse models of human metabolic disease.

Obesity causes significant morbidity and mortality globally. Research in the last three decades has delivered a step-change in our understanding of the fundamental mechanisms that regulate energy homeostasis, building on foundational discoveries in mouse models of metabolic disease. However, not all findings made in rodents have translated to humans, hampering drug discovery in this field. Here, we review how studies in mice and humans have informed our current framework for understanding energy homeostasis, discuss their challenges and limitations, and offer a perspective on how human studies may play an increasingly important role in the discovery of disease mechanisms and identification of therapeutic targets in the future.

A Prion Epigenetic Switch Establishes an Active Chromatin State.

Covalent modifications to histones are essential for development, establishing distinct and functional chromatin domains from a common genetic sequence. Whereas repressed chromatin is robustly inherited, no mechanism that facilitates inheritance of an activated domain has been described. Here, we report that the Set3C histone deacetylase scaffold Snt1 can act as a prion that drives the emergence and transgenerational inheritance of an activated chromatin state. This prion, which we term [ESI+] for expressed sub-telomeric information, is triggered by transient Snt1 phosphorylation upon cell cycle arrest. Once engaged, the prion reshapes the activity of Snt1 and the Set3C complex, recruiting RNA pol II and interfering with Rap1 binding to activate genes in otherwise repressed sub-telomeric domains. This transcriptional state confers broad resistance to environmental stress, including antifungal drugs. Altogether, our results establish a robust means by which a prion can facilitate inheritance of an activated chromatin state to provide adaptive benefit.

Crystal Structure of the COMPASS H3K4 Methyltransferase Catalytic Module.

The SET1/MLL family of histone methyltransferases is conserved in eukaryotes and regulates transcription by catalyzing histone H3K4 mono-, di-, and tri-methylation. These enzymes form a common five-subunit catalytic core whose assembly is critical for their basal and regulated enzymatic activities through unknown mechanisms. Here, we present the crystal structure of the intact yeast COMPASS histone methyltransferase catalytic module consisting of Swd1, Swd3, Bre2, Sdc1, and Set1. The complex is organized by Swd1, whose conserved C-terminal tail not only nucleates Swd3 and a Bre2-Sdc1 subcomplex, but also joins Set1 to construct a regulatory pocket next to the catalytic site. This inter-subunit pocket is targeted by a previously unrecognized enzyme-modulating motif in Swd3 and features a doorstop-style mechanism dictating substrate selectivity among SET1/MLL family members. By spatially mapping the functional components of COMPASS, our results provide a structural framework for understanding the multifaceted functions and regulation of the H3K4 methyltransferase family.

Keeping Your Brain in Balance: Homeostatic Regulation of Network Function.

To perform computations with the efficiency necessary for animal survival, neocortical microcircuits must be capable of reconfiguring in response to experience, while carefully regulating excitatory and inhibitory connectivity to maintain stable function. This dynamic fine-tuning is accomplished through a rich array of cellular homeostatic plasticity mechanisms that stabilize important cellular and network features such as firing rates, information flow, and sensory tuning properties. Further, these functional network properties can be stabilized by different forms of homeostatic plasticity, including mechanisms that target excitatory or inhibitory synapses, or that regulate intrinsic neuronal excitability. Here we discuss which aspects of neocortical circuit function are under homeostatic control, how this homeostasis is realized on the cellular and molecular levels, and the pathological consequences when circuit homeostasis is impaired. A remaining challenge is to elucidate how these diverse homeostatic mechanisms cooperate within complex circuits to enable them to be both flexible and stable.

Drosophila melanogaster Set8 and L(3)mbt function in gene expression independently of histone H4 lysine 20 methylation.

Monomethylation of lysine 20 of histone H4 (H4K20me1) is catalyzed by Set8 and thought to play important roles in many aspects of genome function that are mediated by H4K20me binding proteins. We interrogated this model in a developing animal by comparing in parallel the transcriptomes of Set8 null , H4 K20R/A , and l(3)mbt mutant Drosophila melanogaster We found that the gene expression profiles of H4 K20A and H4 K20R larvae are markedly different than Set8 null larvae despite similar reductions in H4K20me1. Set8 null mutant cells have a severely disrupted transcriptome and fail to proliferate in vivo, but these phenotypes are not recapitulated by mutation of H4 K20 , indicating that the developmental defects of Set8 null animals are largely due to H4K20me1-independent effects on gene expression. Furthermore, the H4K20me1 binding protein L(3)mbt is recruited to the transcription start sites of most genes independently of H4K20me even though genes bound by L(3)mbt have high levels of H4K20me1. Moreover, both Set8 and L(3)mbt bind to purified H4K20R nucleosomes in vitro. We conclude that gene expression changes in Set8 null and H4 K20 mutants cannot be explained by loss of H4K20me1 or L(3)mbt binding to chromatin and therefore that H4K20me1 does not play a large role in gene expression.

Beyond histones: the elusive substrates of chromatin regulators.

Gene transcription is intimately linked to chromatin state and histone modifications. However, the enzymes mediating these post-translational modifications have many additional, nonhistone substrates, making it difficult to ascribe the most relevant modification. In this issue of Genes & Development, Crain and colleagues (doi:10.1101/gad.351698.124) have combined a powerful histone replacement system with mutational analysis of a chromatin regulator and a chromatin reader in Drosophila melanogaster Importantly, they discovered that genes controlled by the histone 4 lysine 20 (H4K20) methyltransferase Set8 and the protein recognizing H4K20 monomethylation, L(3)mbt, differ substantially from those affected by mutation of H4K20 itself. This demonstrates that H4K20 is not the key substrate for Set8 but that methylation of other, unidentified proteins mediates its effects on transcription.

Structural basis for product specificities of MLL family methyltransferases.

Human mixed-lineage leukemia (MLL) family methyltransferases methylate histone H3 lysine 4 to different methylation states (me1/me2/me3) with distinct functional outputs, but the mechanism underlying the different product specificities of MLL proteins remains unclear. Here, we develop methodologies to quantitatively measure the methylation rate difference between mono-, di-, and tri-methylation steps and demonstrate that MLL proteins possess distinct product specificities in the context of the minimum MLL-RBBP5-ASH2L complex. Comparative structural analyses of MLL complexes by X-ray crystal structures, fluorine-19 nuclear magnetic resonance, and molecular dynamics simulations reveal that the dynamics of two conserved tyrosine residues at the "F/Y (phenylalanine/tyrosine) switch" positions fine-tune the product specificity. The variation in the intramolecular interaction between SET-N and SET-C affects the F/Y switch dynamics, thus determining the product specificities of MLL proteins. These results indicate a modified F/Y switch rule applicable for most SET domain methyltransferases and implicate the functional divergence of MLL proteins.

Methylation of histone H3 at lysine 37 by Set1 and Set2 prevents spurious DNA replication.

DNA replication initiates at genomic locations known as origins of replication, which, in S. cerevisiae, share a common DNA consensus motif. Despite being virtually nucleosome-free, origins of replication are greatly influenced by the surrounding chromatin state. Here, we show that histone H3 lysine 37 mono-methylation (H3K37me1) is catalyzed by Set1p and Set2p and that it regulates replication origin licensing. H3K37me1 is uniformly distributed throughout most of the genome, but it is scarce at replication origins, where it increases according to the timing of their firing. We find that H3K37me1 hinders Mcm2 interaction with chromatin, maintaining low levels of MCM outside of conventional replication origins. Lack of H3K37me1 results in defective DNA replication from canonical origins while promoting replication events at inefficient and non-canonical sites. Collectively, our results indicate that H3K37me1 ensures correct execution of the DNA replication program by protecting the genome from inappropriate origin licensing and spurious DNA replication.

Argonaute NRDE-3 and MBT domain protein LIN-61 redundantly recruit an H3K9me3 HMT to prevent embryonic lethality and transposon expression.

The establishment and maintenance of chromatin domains shape the epigenetic memory of a cell, with the methylation of histone H3 lysine 9 (H3K9me) defining transcriptionally silent heterochromatin. We show here that the C. elegans SET-25 (SUV39/G9a) histone methyltransferase (HMT), which catalyzes H3K9me1, me2 and me3, can establish repressed chromatin domains de novo, unlike the SETDB1 homolog MET-2. Thus, SET-25 is needed to silence novel insertions of RNA or DNA transposons, and repress tissue-specific genes de novo during development. We identify two partially redundant pathways that recruit SET-25 to its targets. One pathway requires LIN-61 (L3MBTL2), which uses its four MBT domains to bind the H3K9me2 deposited by MET-2. The second pathway functions independently of MET-2 and involves the somatic Argonaute NRDE-3 and small RNAs. This pathway targets primarily highly conserved RNA and DNA transposons. These redundant SET-25 targeting pathways (MET-2-LIN-61-SET-25 and NRDE-3-SET-25) ensure repression of intact transposons and de novo insertions, while MET-2 can act alone to repress simple and satellite repeats. Removal of both pathways in the met-2;nrde-3 double mutant leads to the loss of somatic H3K9me2 and me3 and the synergistic derepression of transposons in embryos, strongly elevating embryonic lethality.

MRX Increases Chromatin Accessibility at Stalled Replication Forks to Promote Nascent DNA Resection and Cohesin Loading.

The recovery of stalled replication forks depends on the controlled resection of nascent DNA and on the loading of cohesin. These processes operate in the context of nascent chromatin, but the impact of nucleosome structure on a fork restart remains poorly understood. Here, we show that the Mre11-Rad50-Xrs2 (MRX) complex acts together with the chromatin modifiers Gcn5 and Set1 and the histone remodelers RSC, Chd1, and Isw1 to promote chromatin remodeling at stalled forks. Increased chromatin accessibility facilitates the resection of nascent DNA by the Exo1 nuclease and the Sgs1 and Chl1 DNA helicases. Importantly, increased ssDNA promotes the recruitment of cohesin to arrested forks in a Scc2-Scc4-dependent manner. Altogether, these results indicate that MRX cooperates with chromatin modifiers to orchestrate the action of remodelers, nucleases, and DNA helicases, promoting the resection of nascent DNA and the loading of cohesin, two key processes involved in the recovery of arrested forks.

Set1/COMPASS repels heterochromatin invasion at euchromatic sites by disrupting Suv39/Clr4 activity and nucleosome stability.

Protection of euchromatin from invasion by gene-repressive heterochromatin is critical for cellular health and viability. In addition to constitutive loci such as pericentromeres and subtelomeres, heterochromatin can be found interspersed in gene-rich euchromatin, where it regulates gene expression pertinent to cell fate. While heterochromatin and euchromatin are globally poised for mutual antagonism, the mechanisms underlying precise spatial encoding of heterochromatin containment within euchromatic sites remain opaque. We investigated ectopic heterochromatin invasion by manipulating the fission yeast mating type locus boundary using a single-cell spreading reporter system. We found that heterochromatin repulsion is locally encoded by Set1/COMPASS on certain actively transcribed genes and that this protective role is most prominent at heterochromatin islands, small domains interspersed in euchromatin that regulate cell fate specifiers. Sensitivity to invasion by heterochromatin, surprisingly, is not dependent on Set1 altering overall gene expression levels. Rather, the gene-protective effect is strictly dependent on Set1's catalytic activity. H3K4 methylation, the Set1 product, antagonizes spreading in two ways: directly inhibiting catalysis by Suv39/Clr4 and locally disrupting nucleosome stability. Taken together, these results describe a mechanism for spatial encoding of euchromatic signals that repel heterochromatin invasion.

A Bayesian fine-mapping model using a continuous global-local shrinkage prior with applications in prostate cancer analysis.

The aim of fine mapping is to identify genetic variants causally contributing to complex traits or diseases. Existing fine-mapping methods employ Bayesian discrete mixture priors and depend on a pre-specified maximum number of causal variants, which may lead to sub-optimal solutions. In this work, we propose a Bayesian fine-mapping method called h2-D2, utilizing a continuous global-local shrinkage prior. We also present an approach to define credible sets of causal variants in continuous prior settings. Simulation studies demonstrate that h2-D2 outperforms current state-of-the-art fine-mapping methods such as SuSiE and FINEMAP in accurately identifying causal variants and estimating their effect sizes. We further applied h2-D2 to prostate cancer analysis and discovered some previously unknown causal variants. In addition, we inferred 369 target genes associated with the detected causal variants and several pathways that were significantly over-represented by these genes, shedding light on their potential roles in prostate cancer development and progression.

Historic obstacles and emerging opportunities in the field of developmental metabolism - lessons from Heidelberg.

The field of developmental metabolism is experiencing a technological revolution that is opening entirely new fields of inquiry. Advances in metabolomics, small-molecule sensors, single-cell RNA sequencing and computational modeling present new opportunities for exploring cell-specific and tissue-specific metabolic networks, interorgan metabolic communication, and gene-by-metabolite interactions in time and space. Together, these advances not only present a means by which developmental biologists can tackle questions that have challenged the field for centuries, but also present young scientists with opportunities to define new areas of inquiry. These emerging frontiers of developmental metabolism were at the center of a highly interactive 2023 EMBO workshop 'Developmental metabolism: flows of energy, matter, and information'. Here, we summarize key discussions from this forum, emphasizing modern developmental biology's challenges and opportunities.

mBAT-combo: A more powerful test to detect gene-trait associations from GWAS data.

Gene-based association tests aggregate multiple SNP-trait associations into sets defined by gene boundaries and are widely used in post-GWAS analysis. A common approach for gene-based tests is to combine SNPs associations by computing the sum of χ2 statistics. However, this strategy ignores the directions of SNP effects, which could result in a loss of power for SNPs with masking effects, e.g., when the product of two SNP effects and the linkage disequilibrium (LD) correlation is negative. Here, we introduce "mBAT-combo," a set-based test that is better powered than other methods to detect multi-SNP associations in the context of masking effects. We validate the method through simulations and applications to real data. We find that of 35 blood and urine biomarker traits in the UK Biobank, 34 traits show evidence for masking effects in a total of 4,273 gene-trait pairs, indicating that masking effects is common in complex traits. We further validate the improved power of our method in height, body mass index, and schizophrenia with different GWAS sample sizes and show that on average 95.7% of the genes detected only by mBAT-combo with smaller sample sizes can be identified by the single-SNP approach with a 1.7-fold increase in sample sizes. Eleven genes significant only in mBAT-combo for schizophrenia are confirmed by functionally informed fine-mapping or Mendelian randomization integrating gene expression data. The framework of mBAT-combo can be applied to any set of SNPs to refine trait-association signals hidden in genomic regions with complex LD structures.

Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets.

This article provides an in-depth review of computational methods for predicting transcriptional regulators (TRs) with query gene sets. Identification of TRs is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement.

Detecting novel cell type in single-cell chromatin accessibility data via open-set domain adaptation.

Recent advances in single-cell technologies enable the rapid growth of multi-omics data. Cell type annotation is one common task in analyzing single-cell data. It is a challenge that some cell types in the testing set are not present in the training set (i.e. unknown cell types). Most scATAC-seq cell type annotation methods generally assign each cell in the testing set to one known type in the training set but neglect unknown cell types. Here, we present OVAAnno, an automatic cell types annotation method which utilizes open-set domain adaptation to detect unknown cell types in scATAC-seq data. Comprehensive experiments show that OVAAnno successfully identifies known and unknown cell types. Further experiments demonstrate that OVAAnno also performs well on scRNA-seq data. Our codes are available online at https://github.com/lisaber/OVAAnno/tree/master.

Fuzzy kernel evidence Random Forest for identifying pseudouridine sites.

Pseudouridine is an RNA modification that is widely distributed in both prokaryotes and eukaryotes, and plays a critical role in numerous biological activities. Despite its importance, the precise identification of pseudouridine sites through experimental approaches poses significant challenges, requiring substantial time and resources.Therefore, there is a growing need for computational techniques that can reliably and quickly identify pseudouridine sites from vast amounts of RNA sequencing data. In this study, we propose fuzzy kernel evidence Random Forest (FKeERF) to identify pseudouridine sites. This method is called PseU-FKeERF, which demonstrates high accuracy in identifying pseudouridine sites from RNA sequencing data. The PseU-FKeERF model selected four RNA feature coding schemes with relatively good performance for feature combination, and then input them into the newly proposed FKeERF method for category prediction. FKeERF not only uses fuzzy logic to expand the original feature space, but also combines kernel methods that are easy to interpret in general for category prediction. Both cross-validation tests and independent tests on benchmark datasets have shown that PseU-FKeERF has better predictive performance than several state-of-the-art methods. This new method not only improves the accuracy of pseudouridine site identification, but also provides a certain reference for disease control and related drug development in the future.

irGSEA: the integration of single-cell rank-based gene set enrichment analysis.

irGSEA is an R package designed to assess the outcomes of various gene set scoring methods when applied to single-cell RNA sequencing data. This package incorporates six distinct scoring methods that rely on the expression ranks of genes, emphasizing relative expression levels over absolute values. The implemented methods include AUCell, UCell, singscore, ssGSEA, JASMINE and Viper. Previous studies have demonstrated the robustness of these methods to variations in dataset size and composition, generating enrichment scores based solely on the relative gene expression of individual cells. By employing the robust rank aggregation algorithm, irGSEA amalgamates results from all six methods to ascertain the statistical significance of target gene sets across diverse scoring methods. The package prioritizes user-friendliness, allowing direct input of expression matrices or seamless interaction with Seurat objects. Furthermore, it facilitates a comprehensive visualization of results. The irGSEA package and its accompanying documentation are accessible on GitHub (https://github.com/chuiqin/irGSEA).

Benchmarking enrichment analysis methods with the disease pathway network.

Enrichment analysis (EA) is a common approach to gain functional insights from genome-scale experiments. As a consequence, a large number of EA methods have been developed, yet it is unclear from previous studies which method is the best for a given dataset. The main issues with previous benchmarks include the complexity of correctly assigning true pathways to a test dataset, and lack of generality of the evaluation metrics, for which the rank of a single target pathway is commonly used. We here provide a generalized EA benchmark and apply it to the most widely used EA methods, representing all four categories of current approaches. The benchmark employs a new set of 82 curated gene expression datasets from DNA microarray and RNA-Seq experiments for 26 diseases, of which only 13 are cancers. In order to address the shortcomings of the single target pathway approach and to enhance the sensitivity evaluation, we present the Disease Pathway Network, in which related Kyoto Encyclopedia of Genes and Genomes pathways are linked. We introduce a novel approach to evaluate pathway EA by combining sensitivity and specificity to provide a balanced evaluation of EA methods. This approach identifies Network Enrichment Analysis methods as the overall top performers compared with overlap-based methods. By using randomized gene expression datasets, we explore the null hypothesis bias of each method, revealing that most of them produce skewed P-values.

The SET oncoprotein promotes estrogen-induced transcription by facilitating establishment of active chromatin.

SET is a multifunctional histone-binding oncoprotein that regulates transcription by an unclear mechanism. Here we show that SET enhances estrogen-dependent transcription. SET knockdown abrogates transcription of estrogen-responsive genes and their enhancer RNAs. In response to 17ß-estradiol (E2), SET binds to the estrogen receptor α (ERα) and is recruited to ERα-bound enhancers and promoters at estrogen response elements (EREs). SET functions as a histone H2 chaperone that dynamically associates with H2A.Z via its acidic C-terminal domain and promotes H2A.Z incorporation, ERα, MLL1, and KDM3A loading and modulates histone methylation at EREs. SET depletion diminishes recruitment of condensin complexes to EREs and impairs E2-dependent enhancer-promoter looping. Thus, SET boosts E2-induced gene expression by establishing an active chromatin structure at ERα-bound enhancers and promoters, which is essential for transcriptional activation.