BACKGROUND: Four-stranded G-quadruplexes (G4s) are DNA secondary structures in the human genome that are primarily found in active promoters associated with elevated transcription. Here, we explore the relationship between the folding of promoter G4s, transcription and chromatin state. RESULTS: Transcriptional inhibition by DRB or by triptolide reveals that promoter G4 formation, as assessed by G4 ChIP-seq, does not depend on transcriptional activity. We then show that chromatin compaction can lead to loss of promoter G4s and is accompanied by a corresponding loss of RNA polymerase II (Pol II), thus establishing a link between G4 formation and chromatin accessibility. Furthermore, pre-treatment of cells with a G4-stabilising ligand mitigates the loss of Pol II at promoters induced by chromatin compaction. CONCLUSIONS: Overall, our findings show that G4 folding is coupled to the establishment of accessible chromatin and does not require active transcription.

Identifying single nucleotide variants has become common practice for droplet-based single-cell RNA-seq experiments; however, presently, a pipeline does not exist to maximize variant calling accuracy. Furthermore, molecular duplicates generated in these experiments have not been utilized to optimally detect variant co-expression. Herein, we introduce scSNV designed from the ground up to "collapse" molecular duplicates and accurately identify variants and their co-expression. We demonstrate that scSNV is fast, with a reduced false-positive variant call rate, and enables the co-detection of genetic variants and A>G RNA edits across twenty-two samples.

Trans-acting expression quantitative trait loci (trans-eQTLs) account for ≥70% expression heritability and could therefore facilitate uncovering mechanisms underlying the origination of complex diseases. Identifying trans-eQTLs is challenging because of small effect sizes, tissue specificity, and a severe multiple-testing burden. Tejaas predicts trans-eQTLs by performing L2-regularized "reverse" multiple regression of each SNP on all genes, aggregating evidence from many small trans-effects while being unaffected by the strong expression correlations. Combined with a novel unsupervised k-nearest neighbor method to remove confounders, Tejaas predicts 18851 unique trans-eQTLs across 49 tissues from GTEx. They are enriched in open chromatin, enhancers, and other regulatory regions. Many overlap with disease-associated SNPs, pointing to tissue-specific transcriptional regulation mechanisms.

Haplotype phase represents the collective genetic variation between homologous chromosomes and is an essential feature of non-haploid genomes. Here we describe a computational strategy to reliably determine complete whole-chromosome haplotypes using a combination of bulk long-range sequencing and Hi-C sequencing. We demonstrate that this strategy can resolve the haplotypes of parental chromosomes in diploid human genomes with high precision (>99%) and completeness (>98%) and assemble the syntenic structure of rearranged chromosomes in aneuploid cancer genomes at base pair level resolution. Our work enables direct interrogation of chromosome-specific alterations and chromatin reorganization using bulk DNA sequencing.

BACKGROUND: Selection has dramatically shaped genetic and phenotypic variation in bread wheat. We can assess the genomic basis of historical phenotypic changes, and the potential for future improvement, using experimental populations that attempt to undo selection through the randomizing effects of recombination. RESULTS: We bred the NIAB Diverse MAGIC multi-parent population comprising over 500 recombinant inbred lines, descended from sixteen historical UK bread wheat varieties released between 1935 and 2004. We sequence the founders' genes and promoters by capture, and the MAGIC population by low-coverage whole-genome sequencing. We impute 1.1 M high-quality SNPs that are over 99% concordant with array genotypes. Imputation accuracy only marginally improves when including the founders' genomes as a haplotype reference panel. Despite capturing 73% of global wheat genetic polymorphism, 83% of genes cluster into no more than three haplotypes. We phenotype 47 agronomic traits over 2 years and map 136 genome-wide significant associations, concentrated at 42 genetic loci with large and often pleiotropic effects. Around half of these overlap known quantitative trait loci. Most traits exhibit extensive polygenicity, as revealed by multi-locus shrinkage modelling. CONCLUSIONS: Our results are consistent with a gene pool of low haplotypic diversity, containing few novel loci of large effect. Most past, and projected future, phenotypic changes arising from existing variation involve fine-scale shuffling of a few haplotypes to recombine dozens of polygenic alleles of small effect. Moreover, extensive pleiotropy means selection on one trait will have unintended consequences, exemplified by the negative trade-off between yield and protein content, unless selection and recombination can break unfavorable trait-trait associations.

BACKGROUND: How species can adapt to abrupt environmental changes, particularly in the absence of standing genetic variation, is poorly understood and a pressing question in the face of ongoing climate change. Here we leverage publicly available multi-omic and bio-climatic data for more than 1000 wild Arabidopsis thaliana accessions to determine the rate of transposable element (TE) mobilization and its potential to create adaptive variation in natural settings. RESULTS: We demonstrate that TE insertions arise at almost the same rate as base substitutions. Mobilization activity of individual TE families varies greatly between accessions, in association with genetic and environmental factors as well as through complex gene-environment interactions. Although the distribution of TE insertions across the genome is ultimately shaped by purifying selection, reflecting their typically strong deleterious effects when located near or within genes, numerous recent TE-containing alleles show signatures of positive selection. Moreover, high rates of transposition appear positively selected at the edge of the species' ecological niche. Based on these findings, we predict through mathematical modeling higher transposition activity in Mediterranean regions within the next decades in response to global warming, which in turn should accelerate the creation of large-effect alleles. CONCLUSIONS: Our study reveals that TE mobilization is a major generator of genetic variation in A. thaliana that is finely modulated by genetic and environmental factors. These findings and modeling indicate that TEs may be essential genomic players in the demise or rescue of native populations in times of climate crises.

BACKGROUND: Hybridization of plants that differ in number of chromosome sets (ploidy) frequently causes endosperm failure and seed arrest, a phenomenon referred to as triploid block. In Arabidopsis, loss of function of NRPD1, encoding the largest subunit of the plant-specific RNA polymerase IV (Pol IV), can suppress the triploid block. Pol IV generates short RNAs required to guide de novo methylation in the RNA-directed DNA methylation (RdDM) pathway. Recent work suggests that suppression of the triploid block by mutants in RdDM components differs, depending on whether the diploid pollen is derived from tetraploid plants or from the omission in second division 1 (osd1) mutant. This study aims to understand this difference. RESULTS: In this study, we find that the ability of mutants in the RdDM pathway to suppress the triploid block depends on their degree of inbreeding. While first homozygous generation mutants in RdDM components NRPD1, RDR2, NRPE1, and DRM2 have weak or no ability to rescue the triploid block, they are able to suppress the triploid block with successive generations of inbreeding. Inbreeding of nrpd1 was connected with a transgenerational loss of non-CG DNA methylation on sites jointly regulated by CHROMOMETHYLASES 2 and 3. CONCLUSIONS: Our data reveal that loss of RdDM function differs in its effect in early and late generations, which has important implications when interpreting the effect of RdDM mutants.

BACKGROUND: RNA-directed DNA methylation (RdDM) initiates cytosine methylation in all contexts and maintains asymmetric CHH methylation. Mature plant embryos show one of the highest levels of CHH methylation, and it has been suggested that RdDM is responsible for this hypermethylation. Because loss of RdDM in Brassica rapa causes seed abortion, embryo methylation might play a role in seed development. RdDM is required in the maternal sporophyte, suggesting that small RNAs from the maternal sporophyte might translocate to the developing embryo, triggering DNA methylation that prevents seed abortion. This raises the question of whether embryo hypermethylation is autonomously regulated by the embryo itself or influenced by the maternal sporophyte. RESULTS: Here, we demonstrate that B. rapa embryos are hypermethylated in both euchromatin and heterochromatin and that this process requires RdDM. Contrary to the current models, B. rapa embryo hypermethylation is not correlated with demethylation of the endosperm. We also show that maternal somatic RdDM is not sufficient for global embryo hypermethylation, and we find no compelling evidence for maternal somatic influence over embryo methylation at any locus. Decoupling of maternal and zygotic RdDM leads to successful seed development despite the loss of embryo CHH hypermethylation. CONCLUSIONS: We conclude that embryo CHH hypermethylation is conserved, autonomously controlled, and not required for embryo development. Furthermore, maternal somatic RdDM, while required for seed development, does not directly influence embryo methylation patterns.

BACKGROUND: Eukaryotic genomes undergo pervasive transcription, leading to the production of many types of stable and unstable RNAs. Transcription is not restricted to regions with annotated gene features but includes almost any genomic context. Currently, the source and function of most RNAs originating from intergenic regions in the human genome remain unclear. RESULTS: We hypothesize that many intergenic RNAs can be ascribed to the presence of as-yet unannotated genes or the "fuzzy" transcription of known genes that extends beyond the annotated boundaries. To elucidate the contributions of these two sources, we assemble a dataset of more than 2.5 billion publicly available RNA-seq reads across 5 human cell lines and multiple cellular compartments to annotate transcriptional units in the human genome. About 80% of transcripts from unannotated intergenic regions can be attributed to the fuzzy transcription of existing genes; the remaining transcripts originate mainly from putative long non-coding RNA loci that are rarely spliced. We validate the transcriptional activity of these intergenic RNAs using independent measurements, including transcriptional start sites, chromatin signatures, and genomic occupancies of RNA polymerase II in various phosphorylation states. We also analyze the nuclear localization and sensitivities of intergenic transcripts to nucleases to illustrate that they tend to be rapidly degraded either on-chromatin by XRN2 or off-chromatin by the exosome. CONCLUSIONS: We provide a curated atlas of intergenic RNAs that distinguishes between alternative processing of well-annotated genes from independent transcriptional units based on the combined analysis of chromatin signatures, nuclear RNA localization, and degradation pathways.

Researchers must be able to generate experimentally testable hypotheses from sequencing-based observational microbiome experiments to discover the mechanisms underlying the influence of gut microbes on human health. We describe geneshot, a novel bioinformatics tool for identifying testable hypotheses based on gene-level metagenomic analysis of WGS microbiome data. By applying geneshot to two independent previously published cohorts, we identify microbial genomic islands consistently associated with response to immune checkpoint inhibitor (ICI)-based cancer treatment in culturable type strains. The identified genomic islands are within operons involved in type II secretion, TonB-dependent transport, and bacteriophage growth.

BACKGROUND: The evolution of multicellularity is a critical event that remains incompletely understood. We use the social amoeba, Dictyostelium discoideum, one of the rare organisms that readily transits back and forth between both unicellular and multicellular stages, to examine the role of epigenetics in regulating multicellularity. RESULTS: While transitioning to multicellular states, patterns of H3K4 methylation and H3K27 acetylation significantly change. By combining transcriptomics, epigenomics, chromatin accessibility, and orthologous gene analyses with other unicellular and multicellular organisms, we identify 52 conserved genes, which are specifically accessible and expressed during multicellular states. We validated that four of these genes, including the H3K27 deacetylase hdaD, are necessary and that an SMC-like gene, smcl1, is sufficient for multicellularity in Dictyostelium. CONCLUSIONS: These results highlight the importance of epigenetics in reorganizing chromatin architecture to facilitate multicellularity in Dictyostelium discoideum and raise exciting possibilities about the role of epigenetics in the evolution of multicellularity more broadly.

BACKGROUND: Despite the prevalence and recurrence of polyploidization in the speciation of flowering plants, its impacts on crop intraspecific genome diversification are largely unknown. Brassica rapa is a mesopolyploid species that is domesticated into many subspecies with distinctive morphotypes. RESULTS: Herein, we report the consequences of the whole-genome triplication (WGT) on intraspecific diversification using a pan-genome analysis of 16 de novo assembled and two reported genomes. Among the genes that derive from WGT, 13.42% of polyploidy-derived genes accumulate more transposable elements and non-synonymous mutations than other genes during individual genome evolution. We denote such genes as being "flexible." We construct the Brassica rapa ancestral genome and observe the continuing influence of the dominant subgenome on intraspecific diversification in B. rapa. The gene flexibility is biased to the more fractionated subgenomes (MFs), in contrast to the more intact gene content of the dominant LF (least fractionated) subgenome. Furthermore, polyploidy-derived flexible syntenic genes are implicated in the response to stimulus and the phytohormone auxin; this may reflect adaptation to the environment. Using an integrated graph-based genome, we investigate the structural variation (SV) landscapes in 524 B. rapa genomes. We observe that SVs track morphotype domestication. Four out of 266 candidate genes for Chinese cabbage domestication are speculated to be involved in the leafy head formation. CONCLUSIONS: This pan-genome uncovers the possible contributions of allopolyploidization on intraspecific diversification and the possible and underexplored role of SVs in favorable trait domestication. Collectively, our work serves as a rich resource for genome-based B. rapa improvement.

A complete understanding of biological processes requires synthesizing information across heterogeneous modalities, such as age, disease status, or gene expression. Technological advances in single-cell profiling have enabled researchers to assay multiple modalities simultaneously. We present Schema, which uses a principled metric learning strategy that identifies informative features in a modality to synthesize disparate modalities into a single coherent interpretation. We use Schema to infer cell types by integrating gene expression and chromatin accessibility data; demonstrate informative data visualizations that synthesize multiple modalities; perform differential gene expression analysis in the context of spatial variability; and estimate evolutionary pressure on peptide sequences.

BACKGROUND: Alternative splicing, which generates multiple mRNA isoforms from single genes, is crucial for the regulation of eukaryotic gene expression. The flux through competing splicing pathways cannot be determined by traditional RNA-Seq, however, because different mRNA isoforms can have widely differing decay rates. Indeed, some mRNA isoforms with extremely short half-lives, such as those subject to translation-dependent nonsense-mediated decay (AS-NMD), may be completely overlooked in even the most extensive RNA-Seq analyses. RESULTS: RNA immunoprecipitation in tandem (RIPiT) of exon junction complex components allows for purification of post-splicing mRNA-protein particles (mRNPs) not yet subject to translation (pre-translational mRNPs) and, therefore, translation-dependent mRNA decay. Here we compare exon junction complex RIPiT-Seq to whole cell RNA-Seq data from HEK293 cells. Consistent with expectation, the flux through known AS-NMD pathways is substantially higher than that captured by RNA-Seq. Our RIPiT-Seq also definitively demonstrates that the splicing machinery itself has no ability to detect reading frame. We identify thousands of previously unannotated splicing events; while many can be attributed to splicing noise, others are evolutionarily conserved events that produce new AS-NMD isoforms likely involved in maintenance of protein homeostasis. Several of these occur in genes whose overexpression has been linked to poor cancer prognosis. CONCLUSIONS: Deep sequencing of RNAs in post-splicing, pre-translational mRNPs provides a means to identify and quantify splicing events without the confounding influence of differential mRNA decay. For many known AS-NMD targets, the nonsense-mediated decay-linked alternative splicing pathway predominates. Exon junction complex RIPiT-Seq also revealed numerous conserved but previously unannotated AS-NMD events.

Emerging single-cell technologies profile multiple types of molecules within individual cells. A fundamental step in the analysis of the produced high-dimensional data is their visualization using dimensionality reduction techniques such as t-SNE and UMAP. We introduce j-SNE and j-UMAP as their natural generalizations to the joint visualization of multimodal omics data. Our approach automatically learns the relative contribution of each modality to a concise representation of cellular identity that promotes discriminative features but suppresses noise. On eight datasets, j-SNE and j-UMAP produce unified embeddings that better agree with known cell types and that harmonize RNA and protein velocity landscapes.

BACKGROUND: Cancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. Entire classes of regulatory elements are affected by local variations in mutation frequency. However, the underlying mechanisms with functional and genetic determinants remain poorly understood. RESULTS: We characterise the mutational landscape of 1.3 million gene-regulatory and chromatin architectural elements in 2419 whole cancer genomes with transcriptional and pathway activity, functional conservation and recurrent driver events. We develop RM2, a statistical model that quantifies mutational enrichment or depletion in classes of genomic elements through genetic, trinucleotide and megabase-scale effects. We report a map of localised mutational processes affecting CTCF binding sites, transcription start sites (TSS) and tissue-specific open-chromatin regions. Increased mutation frequency in TSSs associates with mRNA abundance in most cancer types, while open-chromatin regions are generally enriched in mutations. We identify ~ 10,000 CTCF binding sites with core DNA motifs and constitutive binding in 66 cell types that represent focal points of mutagenesis. We detect site-specific mutational signature enrichments, such as SBS40 in open-chromatin regions in prostate cancer and SBS17b in CTCF binding sites in gastrointestinal cancers. Candidate drivers of localised mutagenesis are also apparent: BRAF mutations associate with mutational enrichments at CTCF binding sites in melanoma, and ARID1A mutations with TSS-specific mutagenesis in pancreatic cancer. CONCLUSIONS: Our method and catalogue of localised mutational processes provide novel perspectives to cancer genome evolution, mutagenesis, DNA repair and driver gene discovery. The functional and genetic correlates of mutational processes suggest mechanistic hypotheses for future studies.

Advancing RNA structural probing techniques with next-generation sequencing has generated demands for complementary computational tools to robustly extract RNA structural information amidst sampling noise and variability. We present diffBUM-HMM, a noise-aware model that enables accurate detection of RNA flexibility and conformational changes from high-throughput RNA structure-probing data. diffBUM-HMM is widely compatible, accounting for sampling variation and sequence coverage biases, and displays higher sensitivity than existing methods while robust against false positives. Our analyses of datasets generated with a variety of RNA probing chemistries demonstrate the value of diffBUM-HMM for quantitatively detecting RNA structural changes and RNA-binding protein binding sites.

BACKGROUND: Elevated temperatures can cause physiological, biochemical, and molecular responses in plants that can greatly affect their growth and development. Mutations are the most fundamental force driving biological evolution. However, how long-term elevations in temperature influence the accumulation of mutations in plants remains unknown. RESULTS: Multigenerational exposure of Arabidopsis MA (mutation accumulation) lines and MA populations to extreme heat and moderate warming results in significantly increased mutation rates in single-nucleotide variants (SNVs) and small indels. We observe distinctive mutational spectra under extreme and moderately elevated temperatures, with significant increases in transition and transversion frequencies. Mutation occurs more frequently in intergenic regions, coding regions, and transposable elements in plants grown under elevated temperatures. At elevated temperatures, more mutations accumulate in genes associated with defense responses, DNA repair, and signaling. Notably, the distribution patterns of mutations among all progeny differ between MA populations and MA lines, suggesting that stronger selection effects occurred in populations. Methylation is observed more frequently at mutation sites, indicating its contribution to the mutation process at elevated temperatures. Mutations occurring within the same genome under elevated temperatures are significantly biased toward low gene density regions, special trinucleotides, tandem repeats, and adjacent simple repeats. Additionally, mutations found in all progeny overlap significantly with genetic variations reported in 1001 Genomes, suggesting non-uniform distribution of de novo mutations through the genome. CONCLUSION: Collectively, our results suggest that elevated temperatures can accelerate the accumulation, and alter the molecular profiles, of DNA mutations in plants, thus providing significant insight into how environmental temperatures fuel plant evolution.

High-throughput chromosome conformation capture assays, such as Hi-C, have shown that the genome is organized into organizational units such as topologically associating domains (TADs), which can impact gene regulatory processes. The sparsity of Hi-C matrices poses a challenge for reliable detection of these units. We present GRiNCH, a constrained matrix-factorization-based approach for simultaneous smoothing and discovery of TADs from sparse contact count matrices. GRiNCH shows superior performance against seven TAD-calling methods and three smoothing methods. GRiNCH is applicable to multiple platforms including SPRITE and HiChIP and can predict novel boundary factors with potential roles in genome organization.

BACKGROUND: Structural variation (SV) acts as an essential mutational force shaping the evolution and function of the human genome. However, few studies have examined the role of SVs in high-altitude adaptation and little is known of adaptive introgressed SVs in Tibetans so far. RESULTS: Here, we generate a comprehensive catalog of SVs in a Chinese Tibetan (n = 15) and Han (n = 10) population using nanopore sequencing technology. Among a total of 38,216 unique SVs in the catalog, 27% are sequence-resolved for the first time. We systematically assess the distribution of these SVs across repeat sequences and functional genomic regions. Through genotyping in additional 276 genomes, we identify 69 Tibetan-Han stratified SVs and 80 candidate adaptive genes. We also discover a few adaptive introgressed SV candidates and provide evidence for a deletion of 335 base pairs at 1p36.32. CONCLUSIONS: Overall, our results highlight the important role of SVs in the evolutionary processes of Tibetans' adaptation to the Qinghai-Tibet Plateau and provide a valuable resource for future high-altitude adaptation studies.

Visual validation is an important step to minimize false-positive predictions from structural variant (SV) detection. We present Samplot, a tool for creating images that display the read depth and sequence alignments necessary to adjudicate purported SVs across samples and sequencing technologies. These images can be rapidly reviewed to curate large SV call sets. Samplot is applicable to many biological problems such as SV prioritization in disease studies, analysis of inherited variation, or de novo SV review. Samplot includes a machine learning package that dramatically decreases the number of false positives without human review. Samplot is available at https://github.com/ryanlayer/samplot .

Erratum in Genome Biol. 2021 Jun 9;22(1):177.

Deep generative models such as variational autoencoders (VAEs) and generative adversarial networks (GANs) generate and manipulate high-dimensional images. We systematically assess the complementary strengths and weaknesses of these models on single-cell gene expression data. We also develop MichiGAN, a novel neural network that combines the strengths of VAEs and GANs to sample from disentangled representations without sacrificing data generation quality. We learn disentangled representations of three large single-cell RNA-seq datasets and use MichiGAN to sample from these representations. MichiGAN allows us to manipulate semantically distinct aspects of cellular identity and predict single-cell gene expression response to drug treatment.

treeclimbR is for analyzing hierarchical trees of entities, such as phylogenies or cell types, at different resolutions. It proposes multiple candidates that capture the latent signal and pinpoints branches or leaves that contain features of interest, in a data-driven way. It outperforms currently available methods on synthetic data, and we highlight the approach on various applications, including microbiome and microRNA surveys as well as single-cell cytometry and RNA-seq datasets. With the emergence of various multi-resolution genomic datasets, treeclimbR provides a thorough inspection on entities across resolutions and gives additional flexibility to uncover biological associations.

BACKGROUND: Lung adenocarcinoma (LUAD) is a highly malignant and heterogeneous tumor that involves various oncogenic genetic alterations. Epigenetic processes play important roles in lung cancer development. However, the variation in enhancer and super-enhancer landscapes of LUAD patients remains largely unknown. To provide an in-depth understanding of the epigenomic heterogeneity of LUAD, we investigate the H3K27ac histone modification profiles of tumors and adjacent normal lung tissues from 42 LUAD patients and explore the role of epigenetic alterations in LUAD progression. RESULTS: A high intertumoral epigenetic heterogeneity is observed across the LUAD H3K27ac profiles. We quantitatively model the intertumoral variability of H3K27ac levels at proximal gene promoters and distal enhancers and propose a new epigenetic classification of LUAD patients. Our classification defines two LUAD subgroups which are highly related to histological subtypes. Group II patients have significantly worse prognosis than group I, which is further confirmed in the public TCGA-LUAD cohort. Differential RNA-seq analysis between group I and group II groups reveals that those genes upregulated in group II group tend to promote cell proliferation and induce cell de-differentiation. We construct the gene co-expression networks and identify group-specific core regulators. Most of these core regulators are linked with group-specific regulatory elements, such as super-enhancers. We further show that CLU is regulated by 3 group I-specific core regulators and works as a novel tumor suppressor in LUAD. CONCLUSIONS: Our study systematically characterizes the epigenetic alterations during LUAD progression and provides a new classification model that is helpful for predicting patient prognosis.

Nascent RNA profiling is growing in popularity; however, there is no standard analysis pipeline to uniformly process the data and assess quality. Here, we introduce PEPPRO, a comprehensive, scalable workflow for GRO-seq, PRO-seq, and ChRO-seq data. PEPPRO produces uniformly processed output files for downstream analysis and assesses adapter abundance, RNA integrity, library complexity, nascent RNA purity, and run-on efficiency. PEPPRO is restartable and fault-tolerant, records copious logs, and provides a web-based project report. PEPPRO can be run locally or using a cluster, providing a portable first step for genomic nascent RNA analysis.

BACKGROUND: The majority of pancreatic ductal adenocarcinomas (PDAC) are diagnosed at the metastatic stage, and standard therapies have limited activity with a dismal 5-year survival rate of only 8%. The liver and lung are the most common sites of PDAC metastasis, and each have been differentially associated with prognoses and responses to systemic therapies. A deeper understanding of the molecular and cellular landscape within the tumor microenvironment (TME) metastasis at these different sites is critical to informing future therapeutic strategies against metastatic PDAC. RESULTS: By leveraging combined mass cytometry, immunohistochemistry, and RNA sequencing, we identify key regulatory pathways that distinguish the liver and lung TMEs in a preclinical mouse model of metastatic PDAC. We demonstrate that the lung TME generally exhibits higher levels of immune infiltration, immune activation, and pro-immune signaling pathways, whereas multiple immune-suppressive pathways are emphasized in the liver TME. We then perform further validation of these preclinical findings in paired human lung and liver metastatic samples using immunohistochemistry from PDAC rapid autopsy specimens. Finally, in silico validation with transfer learning between our mouse model and TCGA datasets further demonstrates that many of the site-associated features are detectable even in the context of different primary tumors. CONCLUSIONS: Determining the distinctive immune-suppressive features in multiple liver and lung TME datasets provides further insight into the tissue specificity of molecular and cellular pathways, suggesting a potential mechanism underlying the discordant clinical responses that are often observed in metastatic diseases.

BACKGROUND: Androgen receptor (AR) is critical to the initiation, growth, and progression of prostate cancer. Once activated, the AR binds to cis-regulatory enhancer elements on DNA that drive gene expression. Yet, there are 10-100× more binding sites than differentially expressed genes. It is unclear how or if these excess binding sites impact gene transcription. RESULTS: To characterize the regulatory logic of AR-mediated transcription, we generated a locus-specific map of enhancer activity by functionally testing all common clinical AR binding sites with Self-Transcribing Active Regulatory Regions sequencing (STARRseq). Only 7% of AR binding sites displayed androgen-dependent enhancer activity. Instead, the vast majority of AR binding sites were either inactive or constitutively active enhancers. These annotations strongly correlated with enhancer-associated features of both in vitro cell lines and clinical prostate cancer samples. Evaluating the effect of each enhancer class on transcription, we found that AR-regulated enhancers frequently interact with promoters and form central chromosomal loops that are required for transcription. Somatic mutations of these critical AR-regulated enhancers often impact enhancer activity. CONCLUSIONS: Using a functional map of AR enhancer activity, we demonstrated that AR-regulated enhancers act as a regulatory hub that increases interactions with other AR binding sites and gene promoters.

Most research articles presenting new data analysis methods claim that "the new method performs better than existing methods," but the veracity of such statements is questionable. Our manuscript discusses and illustrates consequences of the optimistic bias occurring during the evaluation of novel data analysis methods, that is, all biases resulting from, for example, selection of datasets or competing methods, better ability to fix bugs in a preferred method, and selective reporting of method variants. We quantitatively investigate this bias using an example from epigenetic analysis: normalization methods for data generated by the Illumina HumanMethylation450K BeadChip microarray.

BACKGROUND: The 3D organization of the chromatin fiber in cell nuclei plays a key role in the regulation of gene expression. Genome-wide techniques to score DNA-DNA contacts, such as Hi-C, reveal the partitioning of chromosomes into epigenetically defined active and repressed compartments and smaller "topologically associated" domains. These domains are often associated with chromatin loops, which largely disappear upon removal of cohesin. Because most Hi-C implementations average contact frequencies over millions of cells and do not provide direct spatial information, it remains unclear whether and how frequently chromatin domains and loops exist in single cells. RESULTS: We combine 3D single-molecule localization microscopy with a low-cost fluorescence labeling strategy that does not denature the DNA, to visualize large portions of single human chromosomes in situ at high resolution. In parallel, we develop multi-scale, whole nucleus polymer simulations, that predict chromatin structures at scales ranging from 5 kb up to entire chromosomes. We image chromosomes in G1 and M phase and examine the effect of cohesin on interphase chromatin structure. Depletion of cohesin leads to increased prevalence of loose chromatin stretches, increased gyration radii, and reduced smoothness of imaged chromatin regions. By comparison to model predictions, we estimate that 6-25 or more purely cohesin-dependent chromatin loops coexist per megabase of DNA in single cells, suggesting that the vast majority of the genome is enclosed in loops. CONCLUSION: Our results provide new constraints on chromatin structure and showcase an affordable non-invasive approach to study genome organization in single cells.

BACKGROUND: The developmental gradient in monocot leaves has been exploited to uncover leaf developmental gene expression programs and chloroplast biogenesis processes. However, the relationship between the two is barely understood, which limits the value of transcriptome data to understand the process of chloroplast development. RESULTS: Taking advantage of the developmental gradient in the bread wheat leaf, we provide a simultaneous quantitative analysis for the development of mesophyll cells and of chloroplasts as a cellular compartment. This allows us to generate the first biologically-informed gene expression map of this leaf, with the entire developmental gradient from meristematic to fully differentiated cells captured. We show that the first phase of plastid development begins with organelle proliferation, which extends well beyond cell proliferation, and continues with the establishment and then the build-up of the plastid genetic machinery. The second phase is marked by the development of photosynthetic chloroplasts which occupy the available cellular space. Using a network reconstruction algorithm, we predict that known chloroplast gene expression regulators are differentially involved across those developmental stages. CONCLUSIONS: Our analysis generates both the first wheat leaf transcriptional map and one of the most comprehensive descriptions to date of the developmental history of chloroplasts in higher plants. It reveals functionally distinct plastid and chloroplast development stages, identifies processes occurring in each of them, and highlights our very limited knowledge of the earliest drivers of plastid biogenesis, while providing a basis for their future identification.

Endogenous retroviruses (ERVs) are emerging as promising therapeutic targets in cancer. As remnants of ancient retroviral infections, ERV-derived regulatory elements coordinate expression from gene networks, including those underpinning embryogenesis and immune cell function. ERV activation can promote an interferon response, a phenomenon termed viral mimicry. Although ERV expression is associated with cancer, and provisionally with autoimmune and neurodegenerative diseases, ERV-mediated inflammation is being explored as a way to sensitize tumors to immunotherapy. Here we review ERV co-option in development and innate immunity, the aberrant contribution of ERVs to tumorigenesis, and the wider biomedical potential of therapies directed at ERVs.

BACKGROUND: In maize hybrid breeding, complementary pools of parental lines with reshuffled genetic variants are established for superior hybrid performance. To comprehensively decipher the genetics of heterosis, we present a new design of multiple linked F1 populations with 42,840 F1 maize hybrids, generated by crossing a synthetic population of 1428 maternal lines with 30 elite testers from diverse genetic backgrounds and phenotyped for agronomic traits. RESULTS: We show that, although yield heterosis is correlated with the widespread, minor-effect epistatic QTLs, it may be resulted from a few major-effect additive and dominant QTLs in early developmental stages. Floral transition is probably one critical stage for heterosis formation, in which epistatic QTLs are activated by paternal contributions of alleles that counteract the recessive, deleterious maternal alleles. These deleterious alleles, while rare, epistatically repress other favorable QTLs. We demonstrate this with one example, showing that Brachytic2 represses the Ubiquitin3 locus in the maternal lines; in hybrids, the paternal allele alleviates this repression, which in turn recovers the height of the plant and enhances the weight of the ear. Finally, we propose a molecular design breeding by manipulating key genes underlying the transition from vegetative-to-reproductive growth. CONCLUSION: The new population design is used to dissect the genetic basis of heterosis which accelerates maize molecular design breeding by diminishing deleterious epistatic interactions.

Recent development of spatial transcriptomic technologies has made it possible to characterize cellular heterogeneity with spatial information. However, the technology often does not have sufficient resolution to distinguish neighboring cell types. Here, we present spatialDWLS, to quantitatively estimate the cell-type composition at each spatial location. We benchmark the performance of spatialDWLS by comparing it with a number of existing deconvolution methods and find that spatialDWLS outperforms the other methods in terms of accuracy and speed. By applying spatialDWLS to a human developmental heart dataset, we observe striking spatial temporal changes of cell-type composition during development.

Pseudogenes are gene copies presumed to mainly be functionless relics of evolution due to acquired deleterious mutations or transcriptional silencing. Using deep full-length PacBio cDNA sequencing of normal human tissues and cancer cell lines, we identify here hundreds of novel transcribed pseudogenes expressed in tissue-specific patterns. Some pseudogene transcripts have intact open reading frames and are translated in cultured cells, representing unannotated protein-coding genes. To assess the biological impact of noncoding pseudogenes, we CRISPR-Cas9 delete the nucleus-enriched pseudogene PDCL3P4 and observe hundreds of perturbed genes. This study highlights pseudogenes as a complex and dynamic component of the human transcriptional landscape.

BACKGROUND: Cellular senescence is a permanent state of replicative arrest defined by a specific pattern of gene expression. The epigenome in senescent cells is sculptured in order to sustain the new transcriptional requirements, particularly at enhancers and super-enhancers. How these distal regulatory elements are dynamically modulated is not completely defined. RESULTS: Enhancer regions are defined by the presence of H3K27 acetylation marks, which can be modulated by class IIa HDACs, as part of multi-protein complexes. Here, we explore the regulation of class IIa HDACs in different models of senescence. We find that HDAC4 is polyubiquitylated and degraded during all types of senescence and it selectively binds and monitors H3K27ac levels at specific enhancers and super-enhancers that supervise the senescent transcriptome. Frequently, these HDAC4-modulated elements are also monitored by AP-1/p300. The deletion of HDAC4 in transformed cells which have bypassed oncogene-induced senescence is coupled to the re-appearance of senescence and the execution of the AP-1/p300 epigenetic program. CONCLUSIONS: Overall, our manuscript highlights a role of HDAC4 as an epigenetic reader and controller of enhancers and super-enhancers that supervise the senescence program. More generally, we unveil an epigenetic checkpoint that has important consequences in aging and cancer.