The location of nucleosomes in the human genome determines the primary chromatin structure and regulates access to regulatory regions. However, genome-wide information on deregulated nucleosome occupancy and its implications in primary cancer cells is scarce. Here, we conducted a genome-wide comparison of high-resolution nucleosome maps in peripheral-blood B cells from patients with chronic lymphocytic leukaemia (CLL) and healthy individuals at single base pair resolution. Our investigation uncovered significant changes of nucleosome positioning in CLL. Globally, the spacing between nucleosomes - the nucleosome repeat length (NRL) - was shortened in CLL. This effect was stronger in the more aggressive IGHV-unmutated than in the IGHV-mutated CLL subtype. Changes in nucleosome occupancy at specific sites were linked to active chromatin remodelling and reduced DNA methylation. Nucleosomes lost or gained in CLL marked differential binding of 3D chromatin organisers such as CTCF as well as immune response-related transcription factors and delineated mechanisms of epigenetic deregulation. The principal component analysis of nucleosome occupancy in cancer-specific regions allowed classification of samples between cancer subtypes and normal controls. Furthermore, patients could be better assigned to CLL subtypes according to differential nucleosome occupancy than based on DNA methylation or gene expression. Thus, nucleosome positioning constitutes a novel readout to dissect molecular mechanisms of disease progression and to stratify patients. Furthermore, we anticipate that the global nucleosome repositioning detected in our study, such as changes in the NRL, can be exploited for liquid biopsy applications based on cell-free DNA to stratify patients and monitor disease progression.

Three-dimensional (3D) chromatin structure has been shown to play a role in regulating gene transcription during biological transitions. Although our understanding of loop formation and maintenance is rapidly improving, much less is known about the mechanisms driving changes in looping and the impact of differential looping on gene transcription. One limitation has been a lack of well-powered differential looping data sets. To address this, we conducted a deeply sequenced Hi-C time course of megakaryocyte development comprising four biological replicates and 6 billion reads per time point. Statistical analysis revealed 1503 differential loops. Gained loop anchors were enriched for AP-1 occupancy and were characterized by large increases in histone H3K27ac (over 11-fold) but relatively small increases in CTCF and RAD21 binding (1.26- and 1.23-fold, respectively). Linear modeling revealed that changes in histone H3K27ac, chromatin accessibility, and JUN binding were better correlated with changes in looping than RAD21 and almost as well correlated as CTCF. Changes to epigenetic features between-rather than at-boundaries were highly predictive of changes in looping. Together these data suggest that although CTCF and RAD21 may be the core machinery dictating where loops form, other features (both at the anchors and within the loop boundaries) may play a larger role than previously anticipated in determining the relative loop strength across cell types and conditions.

Accurately measuring biological age is crucial for improving healthcare for the elderly population. However, the complexity of aging biology poses challenges in how to robustly estimate aging and in how to interpret the biological significance of the traits used for estimation. Here we present SCALE, a statistical pipeline that quantifies biological aging in different tissues using explainable features learned from literature and single-cell transcriptomic data. Applying SCALE to the "Mouse Aging Cell Atlas" (Tabula Muris Senis) data, we identified tissue-level transcriptomic aging programs for over 20 murine tissues and created a multi-tissue resource of mouse quantitative aging-associated genes. We observe that SCALE correlates well with other age indicators, such as the accumulation of somatic mutations, and can distinguish subtle differences in aging even in cells of the same chronological age. We further compared SCALE with other transcriptomic and methylation 'clocks' in data of aging muscle stem cells, Alzheimer's disease, and heterochronic parabiosis. Our results confirm that SCALE is more generalizable and reliable in assessing biological aging in aging-related diseases and rejuvenating interventions. Overall, SCALE represents a valuable advancement in our ability to measure aging accurately, robustly, and interpretably in single cells.

The interactome networks at the DNA, RNA, and protein levels are crucial for cellular functions, and the diverse variations of these networks are heavily involved in the establishment of different cell states. We have developed a diffusion-based method, Hi-C to geometry (CTG), to obtain reliable geometric information on the chromatin from Hi-C data. CTG produces a consistent and reproducible framework for the 3D genomic structure and provides a reliable and quantitative understanding of the alterations of genomic structures under different cellular conditions. The genomic structure yielded by CTG serves as an architectural blueprint of the dynamic gene regulatory network, based on which cell-specific correspondence between gene-gene and corresponding protein-protein physical interactions, as well as transcription correlation, is revealed. We also find that gene fusion events are significantly enriched between genes of short CTG distances and are thus close in 3D space. These findings indicate that 3D chromatin structure is at least partially correlated with downstream processes such as transcription, gene regulation, and even regulatory networking through affecting protein-protein interactions.

Comparative analysis of genome-scale metabolic networks (GSMNs) may yield important information on the biology, evolution, and adaptation of species. However, it is impeded by the high heterogeneity of the quality and completeness of structural and functional genome annotations, which may bias the results of such comparisons. To address this issue, we developed AuCoMe, a pipeline to automatically reconstruct homogeneous GSMNs from a heterogeneous set of annotated genomes without discarding available manual annotations. We tested AuCoMe with three data sets, one bacterial, one fungal, and one algal, and showed that it successfully reduces technical biases while capturing the metabolic specificities of each organism. Our results also point out shared and divergent metabolic traits among evolutionarily distant algae, underlining the potential of AuCoMe to accelerate the broad exploration of metabolic evolution across the tree of life.

Paleogenomics continues to yield valuable insights into the evolution, population dynamics, and ecology of our ancestors and other extinct species. However, DNA sequencing cannot reveal tissue-specific gene expression, cellular identity, or gene regulation, which are only attainable at the transcriptional level. Pioneering studies have shown that useful RNA can be extracted from ancient specimens preserved in permafrost and historical skins from extant canids, but no attempts have been made so far on extinct species. We extract, sequence, and analyze historical RNA from muscle and skin tissue of a ∼130-year-old Tasmanian tiger (Thylacinus cynocephalus) preserved in desiccation at room temperature in a museum collection. The transcriptional profiles closely resemble those of extant species, revealing specific anatomical features such as slow muscle fibers or blood infiltration. Metatranscriptomic analysis, RNA damage, tissue-specific RNA profiles, and expression hotspots genome-wide further confirm the thylacine origin of the sequences. RNA sequences are used to improve protein-coding and noncoding annotations, evidencing missing exonic loci and the location of ribosomal RNA genes while increasing the number of annotated thylacine microRNAs from 62 to 325. We discover a thylacine-specific microRNA isoform that could not have been confirmed without RNA evidence. Finally, we detect traces of RNA viruses, suggesting the possibility of profiling viral evolution. Our results represent the first successful attempt to obtain transcriptional profiles from an extinct animal species, providing thought-to-be-lost information on gene expression dynamics. These findings hold promising implications for the study of RNA molecules across the vast collections of natural history museums and from well-preserved permafrost remains.

A weak palindromic nucleotide motif is the hallmark of retroviral integration site alignments. Given that the majority of target sequences are not palindromic, the current model explains the symmetry by an overlap of the nonpalindromic motif present on one of the half-sites of the sequences. Here, we show that the implementation of multicomponent mixture models allows for different interpretations consistent with the existence of both palindromic and nonpalindromic submotifs in the sets of integration site sequences. We further show that the weak palindromic motifs result from freely combined site-specific submotifs restricted to only a few positions proximal to the site of integration. The submotifs are formed by either palindrome-forming nucleotide preference or nucleotide exclusion. Using the mixture models, we also identify HIV-1-favored palindromic sequences in Alu repeats serving as local hotspots for integration. The application of the novel statistical approach provides deeper insight into the selection of retroviral integration sites and may prove to be a valuable tool in the analysis of any type of DNA motifs.

A primary function of DNA methylation in mammalian genomes is to repress transposable elements (TEs). The widespread methylation loss that is commonly observed in cancer cells results in the loss of epigenetic repression of TEs. The aging process is similarly characterized by changes to the methylome. However, the impact of these epigenomic alterations on TE silencing and the functional consequences of this have remained unclear. To assess the epigenetic regulation of TEs in aging, we profiled DNA methylation in human mammary luminal epithelial cells (LEps)-a key cell lineage implicated in age-related breast cancers-from younger and older women. We report here that several TE subfamilies function as regulatory elements in normal LEps, and a subset of these display consistent methylation changes with age. Methylation changes at these TEs occurred at lineage-specific transcription factor binding sites, consistent with loss of lineage specificity. Whereas TEs mainly showed methylation loss, CpG islands (CGIs) that are targets of the Polycomb repressive complex 2 (PRC2) show a gain of methylation in aging cells. Many TEs with methylation loss in aging LEps have evidence of regulatory activity in breast cancer samples. We furthermore show that methylation changes at TEs impact the regulation of genes associated with luminal breast cancers. These results indicate that aging leads to DNA methylation changes at TEs that undermine the maintenance of lineage specificity, potentially increasing susceptibility to breast cancer.

Contacts between enhancers and promoters are thought to relate to their ability to activate transcription. Investigating factors that contribute to such chromatin interactions is therefore important for understanding gene regulation. Here, we have determined contact frequencies between millions of pairs of cis-regulatory elements from chromosome conformation capture data sets and analyzed a collection of hundreds of DNA-binding factors for binding at regions of enriched contacts. This analysis revealed enriched contacts at sites bound by many factors associated with active transcription. We show that active regulatory elements, independent of cohesin and polycomb, interact with each other across distances of tens of megabases in vertebrate and invertebrate genomes and that interactions correlate and change with activity. However, these ultra-long-range interactions are not dependent on RNA polymerase II transcription or individual transcription cofactors. Using simulations, we show that a model of chromatin and multivalent binding factors can give rise to long-range interactions via bridging-induced clustering. We propose that long-range interactions between cis-regulatory elements are driven by at least three distinct processes: cohesin-mediated loop extrusion, polycomb contacts, and clustering of active regions.

The rate of germline mutation is fundamental to evolutionary processes, as it generates the variation upon which selection acts. The guppy, Poecilia reticulata, is a model of rapid adaptation, however the relative contribution of standing genetic variation versus de novo mutation (DNM) to evolution in this species remains unclear. Here, we use pedigree-based approaches to quantify and characterize germline DNMs in three large guppy families. Our results suggest germline mutation rate in the guppy varies substantially across individuals and families. Most DNMs are shared across multiple siblings, suggesting they arose during early embryonic development. DNMs are randomly distributed throughout the genome, and male-biased mutation rate is low, as would be expected from the short guppy generation time. Overall, our study shows remarkable variation in germline mutation rate and provides insights into rapid evolution of guppies.

The true benefits of large datasets of the single-cell transcriptome and epigenome profiles can be availed only with their inclusion and search for annotating individual cells. Matching a single-cell epigenome profile to a large pool of reference cells remains a major challenge. Here, we present scEpiSearch, which enables searching, comparison and independent classification of single-cell open-chromatin profiles against a large reference of single-cell expression and open-chromatin datasets. Across performance benchmarks, scEpiSearch outperformed multiple methods in accuracy of search and low-dimensional coembedding of single-cell profiles, irrespective of platforms and species. Here, we also demonstrate the unconventional utilities of scEpiSearch by applying it on single-cell epigenome profiles of K562 cells and samples from patients with acute leukaemia to reveal different aspects of their heterogeneity, multipotent behavior and dedifferentiated states. Applying scEpiSearch on our single-cell open-chromatin profiles from embryonic stem cells (ESCs), we identified ESC subpopulations with more activity and poising for endoplasmic reticulum stress and unfolded protein response. Thus, scEpiSearch solves the nontrivial problem of amalgamating information from a large pool of single cells to identify and study the regulatory states of cells using their single-cell epigenomes.

Pediatric pineoblastomas (PBs) are rare and aggressive tumors of grade IV histology. Although some oncogenic drivers are characterized, including germline mutations in RB1 and DICER1, the role of epigenetic deregulation and cis-regulatory regions in PB pathogenesis and progression is largely unknown. Here, we generated genome-wide gene expression, chromatin accessibility, and H3K27ac profiles covering key time-points of PB initiation and progression from pineal tissues of a mouse model of Ccnd1-driven pineoblastoma. We identified PB-specific enhancers and super-enhancers and found that, in some cases, the accessible genome dynamic precedes the transcriptome, a characteristic that is underexplored in tumor progression. During progression of PB, newly acquired open chromatin regions lacking H3K27ac signal become enriched for repressive state elements and harbor motifs of repressor transcription factors like HINFP, GLI2, and YY1. Copy number variant analysis identified deletion events specific to the tumorigenic stage, affecting among others the histone genes cluster and Gas1, the growth arrest specific gene. Gene set enrichment analysis and gene expression signatures positioned the model used here close to human PB samples demonstrating the potential of our findings for exploring new avenues in PB management and therapy. Overall, this study reports the first temporal and in vivo cis-regulatory, expression, and accessibility maps in PB.

The epithelial and interstitial stem cells of the freshwater polyp Hydra are the best characterized stem cell systems in any cnidarian, providing valuable insight into cell type evolution and the origin of stemness in animals. However, little is known about the transcriptional regulatory mechanisms that determine how these stem cells are maintained and how they give rise to their diverse differentiated progeny. To address such questions, a thorough understanding of transcriptional regulation in Hydra is needed. To this end, we generated extensive new resources for characterizing transcriptional regulation in Hydra, including new genome assemblies for Hydra oligactis and the AEP strain of Hydra vulgaris, an updated whole-animal single-cell RNA-seq atlas, and genome-wide maps of chromatin interactions, chromatin accessibility, sequence conservation, and histone modifications. These data revealed the existence of large kilobase-scale chromatin interaction domains in the Hydra genome that contain transcriptionally co-regulated genes. We also uncovered the transcriptomic profiles of two previously molecularly uncharacterized cell types, isorhiza-containing nematocytes and somatic gonad ectoderm. Finally, we identified novel candidate regulators of cell-type-specific transcription, several of which have likely been conserved at least since the divergence of Hydra and the jellyfish Clytia hemisphaerica over 400 million years ago.

Low-level DNA N6-methyldeoxyadenosine (DNA-m6A) has recently been reported across various eukaryotes. Although anti-m6A antibody-based approaches are commonly used to measure DNA-m6A levels, this approach is known to be confounded by DNA secondary structures, RNA contamination, and bacterial contamination. To evaluate for these confounding features, we introduce an approach for systematically validating the selectivity of antibody-based DNA-m6A methods and use a highly selective anti-DNA-m6A antibody to reexamine patterns of DNA-m6A in C. reinhardtii, A. thaliana, and D. melanogaster Our findings raise caution about the use of antibody-based methods for endogenous m6A quantification and mapping in eukaryotes.

Copy number variants (CNVs), duplications and deletions of genomic sequences, contribute to evolutionary adaptation but can also confer deleterious effects and cause disease. Whereas the effects of amplifying individual genes or whole chromosomes (i.e., aneuploidy) have been studied extensively, much less is known about the genetic and functional effects of CNVs of differing sizes and structures. Here, we investigated Saccharomyces cerevisiae (yeast) strains that acquired adaptive CNVs of variable structures and copy numbers following experimental evolution in glutamine-limited chemostats. Although beneficial in the selective environment, CNVs result in decreased fitness compared with the euploid ancestor in rich media. We used transposon mutagenesis to investigate mutational tolerance and genome-wide genetic interactions in CNV strains. We find that CNVs increase mutational target size, confer increased mutational tolerance in amplified essential genes, and result in novel genetic interactions with unlinked genes. We validated a novel genetic interaction between different CNVs and BMH1 that was common to multiple strains. We also analyzed global gene expression and found that transcriptional dosage compensation does not affect most genes amplified by CNVs, although gene-specific transcriptional dosage compensation does occur for ∼12% of amplified genes. Furthermore, we find that CNV strains do not show previously described transcriptional signatures of aneuploidy. Our study reveals the extent to which local and global mutational tolerance is modified by CNVs with implications for genome evolution and CNV-associated diseases, such as cancer.

Changes in gene regulation are thought to underlie most phenotypic differences between species. For subterranean rodents such as the naked mole-rat, proposed phenotypic adaptations include hypoxia tolerance, metabolic changes and cancer resistance. However, it is largely unknown what regulatory changes may associate with these phenotypic traits, and whether these are unique to the naked mole-rat, the mole-rat clade or also present in other mammals. Here, we investigate regulatory evolution in heart and liver from two African mole-rat species and two rodent outgroups using genome-wide epigenomic profiling. First, we adapted and applied a phylogenetic modeling approach to quantitatively compare epigenomic signals at orthologous regulatory elements, and identified thousands of promoter and enhancer regions with differential epigenomic activity in mole-rats. These elements associate with known mole-rat adaptation in metabolic and functional pathways, and suggest candidate genetic loci that may underlie mole-rat innovations. Second, we evaluated ancestral and species-specific regulatory changes in the study phylogeny, and report several candidate pathways experiencing stepwise remodeling during the evolution of mole-rats, such as the insulin and hypoxia response pathways. Third, we report nonorthologous regulatory elements overlap with lineage-specific repetitive elements and appear to modify metabolic pathways by rewiring of HNF4 and RAR/RXR transcription factor binding sites in mole-rats. These comparative analyses reveal how mole-rat regulatory evolution informs previously reported phenotypic adaptations. Moreover, the phylogenetic modeling framework we propose here improves upon the state-of-the-art by addressing known limitations of inter-species comparisons of epigenomic profiles, and has broad implications in the field of comparative functional genomics.

Principal Component Analysis (PCA) is widely utilized in statistics, machine learning, and genomics for dimensionality reduction and uncovering low-dimensional latent structure. To address the challenges posed by ever-growing data size, fast and memory-efficient PCA methods have gained prominence. In this paper, we propose a novel Randomized Singular Value Decomposition (RSVD) algorithm implemented in PCAone, featuring a window-based optimization scheme that enables accelerated convergence while improving the accuracy. Additionally, PCAone incorporates out-of-core and multithreaded implementations for the existing Implicitly Restarted Arnoldi Method (IRAM) and RSVD. Through comprehensive evaluations using multiple large-scale real-world datasets in different fields, we demonstrate the advantage of PCAone over existing methods. The new algorithm achieves significantly faster computation time while maintaining accuracy comparable to the slower IRAM method. Notably, our analyses of UK Biobank, comprising around 0.5 million individuals and 6.1 million common SNPs, demonstrate that PCAone accurately computes the top 40 principal components within 9 hours. This analysis effectively captures population structure, signals of selection, structural variants, and low recombination regions, utilizing less than 20 GB of memory and 20 CPU threads. Furthermore, when applied to single-cell RNA sequencing data featuring 1.3 million cells, PCAone, accurately capturing the top 40 principal components in 49 minutes. This performance represents a 10-fold improvement over state-of-the-art tools.

Bacterial genomes differ in both gene content and sequence mutations, which underlies extensive phenotypic diversity, including variation in susceptibility to antimicrobials or vaccine-induced immunity. To identify and quantify important variants, all genes within a population must be predicted, functionally annotated and clustered, representing the pangenome. Despite the volume of genome data available, gene prediction and annotation are currently conducted in isolation on individual genomes, which is computationally inefficient and frequently inconsistent across genomes. Here, we introduce the open-source software graph-gene-caller (ggCaller). ggCaller combines gene prediction, functional annotation, and clustering into a single workflow using population-wide de Bruijn Graphs, removing redundancy in gene annotation, and resulting in more accurate gene predictions and orthologue clustering. We applied ggCaller to simulated and real-world bacterial datasets containing hundreds or thousands of genomes, comparing it to current state-of-the-art tools. ggCaller has considerable speed-ups with equivalent or greater accuracy, particularly with datasets containing complex sources of error, such as assembly contamination or fragmentation. ggCaller is also an important extension to bacterial genome-wide association studies, enabling querying of annotated graphs for functional analyses. We highlight this application by functionally annotating DNA sequences with significant associations to tetracycline and macrolide resistance in Streptococcus pneumoniae, identifying key resistance determinants that were missed when using only a single reference genome. ggCaller is a novel bacterial genome analysis tool with applications in bacterial evolution and epidemiology.

The cytidine deaminases APOBEC3A (A3A) and APOBEC3B (A3B) are prominent mutators of human cancer genomes. However, tumor-specific genetic modulators of APOBEC-induced mutagenesis are poorly defined. Here, we utilized a screen to identify 61 gene deletions that increase A3B-induced mutations in yeast. We also determined whether each deletion was epistatic with Ung1 loss, which indicated whether the encoded factors participate in the HR-dependent bypass of A3B/Ung1-dependent abasic sites or suppress A3B-catalyzed deamination by protecting against aberrant formation of single stranded DNA (ssDNA). We found that the mutation spectra of A3B-induced mutations revealed genotype-specific patterns of strand-specific ssDNA formation and nucleotide incorporation across APOBEC-induced lesions. Combining these three metrics, we were able to establish a multifactorial signature of APOBEC-induced mutations specific to (1) failure to remove H3K56 acetylation, (2) defective CTF18-RFC complex function, and (3) defective HR-mediated bypass of APOBEC-induced lesions. We extended these results by analyzing mutation data for human tumors and found BRCA1/2-deficient breast cancers display 3- to 4-fold more APOBEC-induced mutations. Mirroring our results in yeast, Rev1-mediated C-to-G substitutions are mainly responsible for increased APOBEC-signature mutations in BRCA1/2-deficient tumors, and these mutations associate with lagging strand synthesis during replication. These results identify important factors that influence DNA replication-dynamics and likely the abundance of APOBEC-induced mutation during tumor progression. They also highlight a novel role for BRCA1/2 during HR-dependent lesion bypass of APOBEC-induced lesions during cancer cell replication.

MicroRNAs (miRNAs) pair to sites in mRNAs to direct the degradation of these RNA transcripts. Conversely, certain RNA transcripts can direct the degradation of particular miRNAs. This target-directed miRNA degradation (TDMD) requires the ZSWIM8 E3 ubiquitin ligase. Here, we report the function of ZSWIM8 in the mouse embryo. Zswim8 -/- embryos were smaller than their littermates and died near the time of birth. This highly penetrant perinatal lethality was apparently caused by a lung sacculation defect attributed to failed maturation of alveolar epithelial cells. Some mutant individuals also had heart ventricular septal defects. These developmental abnormalities were accompanied by aberrant accumulation of more than 50 miRNAs observed across 12 tissues, which often led to enhanced repression of their mRNA targets. These ZSWIM8-sensitive miRNAs were preferentially produced from genomic miRNA clusters, and in some cases, ZSWIM8 caused a switch in the dominant strand or isoform that accumulated from a miRNA hairpin-observations suggesting that TDMD provides a mechanism to uncouple coproduced miRNAs from each other. Overall, our findings indicate that the regulatory influence of ZSWIM8, and presumably TDMD, in mammalian biology is widespread and consequential, and posit the existence of many yet-unidentified transcripts that trigger miRNA degradation.