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Intragenic translational heterogeneity describes the variation in translation at the level of transcripts for an individual gene. A factor that contributes to this source of variation is the mRNA structure. Both the composition of the thermodynamic ensemble, i.e., the stationary distribution of mRNA structures, and the switching dynamics between those play a role. The effect of the switching dynamics on intragenic translational heterogeneity remains poorly understood. We present a stochastic translation model that accounts for mRNA structure switching and is derived from a Markov model via approximate stochastic filtering. We assess the approximation on various timescales and provide a method to quantify how mRNA structure dynamics contributes to translational heterogeneity. With our approach, we allow quantitative information on mRNA switching from biophysical experiments or coarse-grain molecular dynamics simulations of mRNA structures to be included in gene regulatory chemical reaction network models without an increase in the number of species. Thereby, our model bridges a gap between mRNA structure kinetics and gene expression models, which we hope will further improve our understanding of gene regulatory networks and facilitate genetic circuit design. [ABSTRACT FROM AUTHOR]

In this study, we obtain an exact time-dependent solution of the chemical master equation (CME) of an extension of the two-state telegraph model describing bursty or non-bursty protein expression in the presence of positive or negative autoregulation. Using the method of spectral decomposition, we show that the eigenfunctions of the generating function solution of the CME are Heun functions, while the eigenvalues can be determined by solving a continued fraction equation. Our solution generalizes and corrects a previous time-dependent solution for the CME of a gene circuit describing non-bursty protein expression in the presence of negative autoregulation [Ramos et al., Phys. Rev. E 83, 062902 (2011)]. In particular, we clarify that the eigenvalues are generally not real as previously claimed. We also investigate the relationship between different types of dynamic behavior and the type of feedback, the protein burst size, and the gene switching rate. [ABSTRACT FROM AUTHOR]

Within the confines of a densely populated cell nucleus, chromatin undergoes intricate folding, forming loops, domains, and compartments under the governance of topological constraints and phase separation. This coordinated process inevitably introduces interference between different folding strategies. In this study, we model interphase chromatins as block copolymers with hetero-hierarchical loops within a confined system. Employing dissipative particle dynamics simulations and scaling analysis, we aim to explain how the structure and distribution of loop domains modulate the microphase separation of chromatins. Our results highlight the correlation between the microphase separation of the copolymer and the length, heterogeneity, and hierarchically nested levels of the loop domains. This correlation arises from steric repulsion intrinsic to loop domains. The steric repulsion induces variations in chain stiffness (including local orientation correlations and the persistence length), thereby influencing the degree of phase separation. Through simulations of block copolymers with distinct groups of hetero-hierarchical loop anchors, we successfully reproduce changes in phase separation across diverse cell lines, under fixed interaction parameters. These findings, in qualitative alignment with Hi-C data, suggest that the variations of loop constraints alone possess the capacity to regulate higher-order structures and the gene expressions of interphase chromatins. [ABSTRACT FROM AUTHOR]

The classical three-stage model of stochastic gene expression predicts the statistics of single cell mRNA and protein number fluctuations as a function of the rates of promoter switching, transcription, translation, degradation and dilution. While this model is easily simulated, its analytical solution remains an unsolved problem. Here we modify this model to explicitly include cell-cycle dynamics and then derive an exact solution for the time-dependent joint distribution of mRNA and protein numbers. We show large differences between this model and the classical model which captures cell-cycle effects implicitly via effective first-order dilution reactions. In particular we find that the Fano factor of protein numbers calculated from a population snapshot measurement are underestimated by the classical model whereas the correlation between mRNA and protein can be either over- or underestimated, depending on the timescales of mRNA degradation and promoter switching relative to the mean cell-cycle duration time. [ABSTRACT FROM AUTHOR]

A new in vitro system called Rec-Seq sheds light on how mRNA molecules compete for the machinery that translates their genetic sequence into proteins.

In some patients with myeloproliferative neoplasms (MPN), two genetic mutations are often found: JAK2 V617F and one in the TET2 gene. Whether one mutation is present influences how the other subsequent mutation will affect the regulation of gene expression. In other words, when a patient carries both mutations, the order of when they first arose has been shown to influence disease progression and prognosis. We propose a nonlinear ordinary differential equation, the Moran process, and Markov chain models to explain the non-additive and non-commutative mutation effects on recent clinical observations of gene expression patterns, proportions of cells with different mutations, and ages at diagnosis of MPN. Combined, these observations are used to shape our modeling framework. Our key proposal is that bistability in gene expression provides a natural explanation for many observed order-of-mutation effects. We also propose potential experimental measurements that can be used to confirm or refute predictions of our models.

A self-cleaving ribozyme that maps to an intron of the cytoplasmic polyadenylation element-binding protein 3 (Cpeb3) gene is thought to play a role in human episodic memory, but the underlying mechanisms mediating this effect are not known. We tested the activity of the murine sequence and found that the ribozymes self-scission half-life matches the time it takes an RNA polymerase to reach the immediate downstream exon, suggesting that the ribozyme-dependent intron cleavage is tuned to co-transcriptional splicing of the Cpeb3 mRNA. Our studies also reveal that the murine ribozyme modulates maturation of its harboring mRNA in both cultured cortical neurons and the hippocampus: inhibition of the ribozyme using an antisense oligonucleotide leads to increased CPEB3 protein expression, which enhances polyadenylation and translation of localized plasticity-related target mRNAs, and subsequently strengthens hippocampal-dependent long-term memory. These findings reveal a previously unknown role for self-cleaving ribozyme activity in regulating experience-induced co-transcriptional and local translational processes required for learning and memory.

Generalist microbes have adapted to a multitude of environmental stresses through their integrated stress response system. Individual stress responses have been quantified by E. coli metabolism and expression (ME) models under thermal, oxidative and acid stress, respectively. However, the systematic quantification of cross-stress & cross-talk among these stress responses remains lacking. Here, we present StressME: the unified stress response model of E. coli combining thermal (FoldME), oxidative (OxidizeME) and acid (AcidifyME) stress responses. StressME is the most up to date ME model for E. coli and it reproduces all published single-stress ME models. Additionally, it includes refined rate constants to improve prediction accuracy for wild-type and stress-evolved strains. StressME revealed certain optimal proteome allocation strategies associated with cross-stress and cross-talk responses. These stress-optimal proteomes were shaped by trade-offs between protective vs. metabolic enzymes; cytoplasmic vs. periplasmic chaperones; and expression of stress-specific proteins. As StressME is tuned to compute metabolic and gene expression responses under mild acid, oxidative, and thermal stresses, it is useful for engineering and health applications. The modular design of our open-source package also facilitates model expansion (e.g., to new stress mechanisms) by the computational biology community.

BACKGROUND: How novel phenotypes originate from conserved genes, processes, and tissues remains a major question in biology. Research that sets out to answer this question often focuses on the conserved genes and processes involved, an approach that explicitly excludes the impact of genetic elements that may be classified as clade-specific, even though many of these genes are known to be important for many novel, or clade-restricted, phenotypes. This is especially true for understudied phyla such as mollusks, where limited genomic and functional biology resources for members of this phylum have long hindered assessments of genetic homology and function. To address this gap, we constructed a chromosome-level genome for the gastropod Berghia stephanieae (Valdés, 2005) to investigate the expression of clade-specific genes across both novel and conserved tissue types in this species. RESULTS: The final assembled and filtered Berghia genome is comparable to other high-quality mollusk genomes in terms of size (1.05 Gb) and number of predicted genes (24,960 genes) and is highly contiguous. The proportion of upregulated, clade-specific genes varied across tissues, but with no clear trend between the proportion of clade-specific genes and the novelty of the tissue. However, more complex tissue like the brain had the highest total number of upregulated, clade-specific genes, though the ratio of upregulated clade-specific genes to the total number of upregulated genes was low. CONCLUSIONS: Our results, when combined with previous research on the impact of novel genes on phenotypic evolution, highlight the fact that the complexity of the novel tissue or behavior, the type of novelty, and the developmental timing of evolutionary modifications will all influence how novel and conserved genes interact to generate diversity.

The ability to independently control gene expression in two different tissues in the same animal is emerging as a major need, especially in the context of inter-organ communication studies. This type of study is made possible by technologies combining the GAL4/UAS and a second binary expression system such as the LexA system or QF system. Here, we describe a resource of reagents that facilitate combined use of the GAL4/UAS and a second binary system in various Drosophila tissues. Focusing on genes with well-characterized GAL4 expression patterns, we generated a set of more than 40 LexA-GAD and QF2 insertions by CRISPR knock-in and verified their tissue specificity in larvae. We also built constructs that encode QF2 and LexA-GAD transcription factors in a single vector. Following successful integration of this construct into the fly genome, FLP/FRT recombination is used to isolate fly lines that express only QF2 or LexA-GAD. Finally, using new compatible shRNA vectors, we evaluated both LexA and QF systems for in vivo gene knockdown and are generating a library of such RNAi fly lines as a community resource. Together, these LexA and QF system vectors and fly lines will provide a new set of tools for researchers who need to activate or repress two different genes in an orthogonal manner in the same animal.

BackgroundGene expression may be regulated by the DNA methylation of regulatory elements in cis, distal, and trans regions. One method to evaluate the relationship between DNA methylation and gene expression is the mapping of expression quantitative trait methylation (eQTM) loci (also called expression associated CpG loci, eCpG). However, no open-source tools are available to provide eQTM mapping. In addition, eQTM mapping can involve a large number of comparisons which may prevent the analyses due to limitations of computational resources. Here, we describe Torch-eCpG, an open-source tool to perform eQTM mapping that includes an optimized implementation that can use the graphical processing unit (GPU) to reduce runtime.ResultsWe demonstrate the analyses using the tool are reproducible, up to 18 × faster using the GPU, and scale linearly with increasing methylation loci.ConclusionsTorch-eCpG is a fast, reliable, and scalable tool to perform eQTM mapping. Source code for Torch-eCpG is available at https://github.com/kordk/torch-ecpg .

Aging and cellular senescence are increasingly recognized as key contributors to pulmonary fibrosis. However, our understanding in the context of scleroderma-associated interstitial lung disease (SSc-ILD) is limited. To investigate, we leveraged previously established lung aging- and cell-specific senescence signatures to determine their presence and potential relevance to SSc-ILD. We performed a gene expression meta-analysis of lung tissues from 38 SSc-ILD and 18 healthy controls and found that markers (GDF15, COMP, and CDKN2A) and pathways (p53) of senescence were significantly increased in SSc-ILD. When probing the established aging and cellular senescence signatures, we found that epithelial and fibroblast senescence signatures had a 3.6- and 3.7-fold enrichment, respectively, in the lung tissue of SSc-ILD and that lung aging genes (CDKN2A, FRZB, PDE1A, and NAPI12) were increased in SSc-ILD. These signatures were also enriched in SSc skin and associated with degree of skin involvement (limited vs. diffuse cutaneous). To further support these findings, we examined telomere length (TL), a surrogate for aging, in the lung tissue and found that, independent of age, SSc-ILD had significantly shorter telomeres than controls in type II alveolar cells in the lung. TL in SSc-ILD was comparable to idiopathic pulmonary fibrosis, a disease of known aberrant aging. Taken together, this study provides novel insight into the possible mechanistic effects of accelerated aging and aberrant cellular senescence in SSc-ILD pathogenesis.

Aging-related memory impairment and pathological memory disorders such as Alzheimers disease differ between males and females, and yet little is known about how aging-related changes in the transcriptome and chromatin environment differ between sexes in the hippocampus. To investigate this question, we compared the chromatin accessibility landscape and gene expression/alternative splicing pattern of young adult and aged mouse hippocampus in both males and females using ATAC-seq and RNA-seq. We detected significant aging-dependent changes in the expression of genes involved in immune response and synaptic function and aging-dependent changes in the alternative splicing of myelin sheath genes. We found significant sex-bias in the expression and alternative splicing of hundreds of genes, including aging-dependent female-biased expression of myelin sheath genes and aging-dependent male-biased expression of genes involved in synaptic function. Aging was associated with increased chromatin accessibility in both male and female hippocampus, especially in repetitive elements, and with an increase in LINE-1 transcription. We detected significant sex-bias in chromatin accessibility in both autosomes and the X chromosome, with male-biased accessibility enriched at promoters and CpG-rich regions. Sex differences in gene expression and chromatin accessibility were amplified with aging, findings that may shed light on sex differences in aging-related and pathological memory loss.

BackgroundCost-effective production of biofuels from lignocellulose requires the fermentation of D-xylose. Many yeast species within and closely related to the genera Spathaspora and Scheffersomyces (both of the order Serinales) natively assimilate and ferment xylose. Other species consume xylose inefficiently, leading to extracellular accumulation of xylitol. Xylitol excretion is thought to be due to the different cofactor requirements of the first two steps of xylose metabolism. Xylose reductase (XR) generally uses NADPH to reduce xylose to xylitol, while xylitol dehydrogenase (XDH) generally uses NAD+ to oxidize xylitol to xylulose, creating an imbalanced redox pathway. This imbalance is thought to be particularly consequential in hypoxic or anoxic environments.ResultsWe screened the growth of xylose-fermenting yeast species in high and moderate aeration and identified both ethanol producers and xylitol producers. Selected species were further characterized for their XR and XDH cofactor preferences by enzyme assays and gene expression patterns by RNA-Seq. Our data revealed that xylose metabolism is more redox balanced in some species, but it is strongly affected by oxygen levels. Under high aeration, most species switched from ethanol production to xylitol accumulation, despite the availability of ample oxygen to accept electrons from NADH. This switch was followed by decreases in enzyme activity and the expression of genes related to xylose metabolism, suggesting that bottlenecks in xylose fermentation are not always due to cofactor preferences. Finally, we expressed XYL genes from multiple Scheffersomyces species in a strain of Saccharomyces cerevisiae. Recombinant S. cerevisiae expressing XYL1 from Scheffersomyces xylosifermentans, which encodes an XR without a cofactor preference, showed improved anaerobic growth on xylose as the primary carbon source compared to S. cerevisiae strain expressing XYL genes from Scheffersomyces stipitis.ConclusionCollectively, our data do not support the hypothesis that xylitol accumulation occurs primarily due to differences in cofactor preferences between xylose reductase and xylitol dehydrogenase; instead, gene expression plays a major role in response to oxygen levels. We have also identified the yeast Sc. xylosifermentans as a potential source for genes that can be engineered into S. cerevisiae to improve xylose fermentation and biofuel production.

BACKGROUND: Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles. METHODS: The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses. RESULTS: Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires. CONCLUSIONS: Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.

Endogenous retroviruses (ERVs) are remnants of ancient parasitic infections and comprise sizable portions of most genomes. Although epigenetic mechanisms silence most ERVs by generating a repressive environment that prevents their expression (heterochromatin), little is known about mechanisms silencing ERVs residing in open regions of the genome (euchromatin). This is particularly important during embryonic development, where induction and repression of distinct classes of ERVs occur in short temporal windows. Here, we demonstrate that transcription-associated RNA degradation by the nuclear RNA exosome and Integrator is a regulatory mechanism that controls the productive transcription of most genes and many ERVs involved in preimplantation development. Disrupting nuclear RNA catabolism promotes dedifferentiation to a totipotent-like state characterized by defects in RNAPII elongation and decreased expression of long genes (gene-length asymmetry). Our results indicate that RNA catabolism is a core regulatory module of gene networks that safeguards RNAPII activity, ERV expression, cell identity, and developmental potency.

Anxiety disorders are among the most prevalent psychiatric disorders, causing significant suffering and disability. Relative to other psychiatric disorders, anxiety disorders tend to emerge early in life, supporting the importance of developmental mechanisms in their emergence and maintenance. Behavioral inhibition (BI) is a temperament that emerges early in life and, when stable and extreme, is linked to an increased risk for the later development of anxiety disorders and other stress-related psychopathology. Understanding the neural systems and molecular mechanisms underlying this dispositional risk could provide insight into treatment targets for anxiety disorders. Nonhuman primates (NHPs) have an anxiety-related temperament, called anxious temperament (AT), that is remarkably similar to BI in humans, facilitating the design of highly translational models for studying the early risk for stress-related psychopathology. Because of the recent evolutionary divergence between humans and NHPs, many of the anxiety-related brain regions that contribute to psychopathology are highly similar in terms of their structure and function, particularly with respect to the prefrontal cortex. The orbitofrontal cortex plays a critical role in the flexible encoding and regulation of threat responses, in part through connections with subcortical structures like the amygdala. Here, we explore individual differences in the transcriptional profile of cells within the region, using laser capture microdissection and single nuclear sequencing, providing insight into the molecules underlying individual differences in AT-related function of the pOFC, with a particular focus on previously implicated cellular systems, including neurotrophins and glucocorticoid signaling.

IntroductionThe regeneration of pulp tissue is crucial for true regenerative endodontic treatment, which requires a reduction in osteogenic differentiation. Garcinol, a histone acetyltransferase inhibitor, is a natural regulator that is known to suppress the osteogenic differentiation of dental pulp stem cells. In this study, the inhibitory effect of garcinol on the osteogenic differentiation of human dental pulp stem cells (hDPSCs) was evaluated using three-dimensional culture under in vitro and in vivo conditions.MethodshDPSCs were obtained from caries-free third molars and cultured with 10 μM garcinol for 7 days in an ultra-low attachment plate. The cell stemness and expression of osteogenic differentiation-related genes were analyzed using reverse transcription-polymerase chain reaction and single-cell analysis. A transplantation experiment was performed in mice to investigate whether garcinol-treated hDPSCs showed restrained osteogenic differentiation.ResultshDPSCs cultured in the U-shaped ultra-low attachment plate showed the highest expression of stemness-related genes. Garcinol-treated hDPSCs demonstrated downregulation of osteogenic differentiation, with lower expression of bone sialoprotein, which is related to bone formation, and higher expression of dentin sialophosphoprotein, which is related to dentin formation. However, the garcinol-treated hDPSCs did not show any alterations in their stemness. Consistent results were observed in the transplantation experiment in mice.ConclusionsGarcinol reduced the osteogenic differentiation of hDPSCs, which can contribute to true regenerative endodontic treatment.

Caenorhabditis elegans is a valuable model to study organ, tissue, and cell-type responses to external cues. However, the nematode comprises multiple syncytial tissues with spatial coordinates corresponding to distinct nuclear transcriptomes. Here, we present a single-nucleus RNA sequencing (snRNA-seq) protocol that aims to overcome difficulties encountered with single-cell RNA sequencing in C. elegans. We describe steps for isolating C. elegans nuclei for downstream applications including snRNA-seq applied to the context of alcohol exposure. For complete details on the use and execution of this protocol, please refer to Truong et al. (2023).1.

DNA deformability and differential hydration are crucial determinants of biological processes ranging from genetic material packaging to gene expression; their associative details, however, remain inadequately understood. Herein, we report investigations of the dynamic and thermodynamic responses of the local hydration of a variety of base pair sequences. Leveraging in silico sampling and our in-house analyses, we first report the local conformational propensity of sequences that are either predisposed toward the canonical A- or B-conformations or are restrained to potential transitory pathways. It is observed that the transition from the unrestrained A-form to the B-form leads to lengthwise structural deformation. The insertion of intermittent -(CG)- base pairs in otherwise homogeneous -(AT)- sequences bears dynamical consequences for the vicinal hydration layer. Calculation of the excess (pair) entropy suggests substantially higher values of hydration water surrounding A conformations over the B- conformations. Applying the Rosenfeld approximation, we project that the diffusivity of water molecules proximal to canonical B conformation is least for the minor groove of the canonical B-conformation. We determine that structure, composition, and conformation specific groove dimension together influence the local hydration characteristics and, therefore, are expected to be important determinants of biological processes. [ABSTRACT FROM AUTHOR]

The conserved family of Transcription Intermediary Factors (TIF1) proteins consists of key transcriptional regulators that control transcription of target genes by modulating chromatin state. Unlike mammals that have four TIF1 members, Drosophila only encodes one member of the family, Bonus. Bonus has been implicated in embryonic development and organogenesis and shown to regulate several signaling pathways, however, its targets and mechanism of action remained poorly understood. We found that knockdown of Bonus in early oogenesis results in severe defects in ovarian development and in ectopic expression of genes that are normally repressed in the germline, demonstrating its essential function in the ovary. Recruitment of Bonus to chromatin leads to silencing associated with accumulation of the repressive H3K9me3 mark. We show that Bonus associates with the histone methyltransferase SetDB1 and the chromatin remodeler NuRD and depletion of either component releases Bonus-induced repression. We further established that Bonus is SUMOylated at a single site at its N-terminus that is conserved among insects and this modification is indispensable for Bonuss repressive activity. SUMOylation influences Bonuss subnuclear localization, its association with chromatin and interaction with SetDB1. Finally, we showed that Bonus SUMOylation is mediated by the SUMO E3-ligase Su(var)2-10, revealing that although SUMOylation of TIF1 proteins is conserved between insects and mammals, both the mechanism and specific site of modification is different in the two taxa. Together, our work identified Bonus as a regulator of tissue-specific gene expression and revealed the importance of SUMOylation as a regulator of complex formation in the context of transcriptional repression.

Osteogenesis imperfecta (OI), or brittle bone disease, is a disorder characterized by bone fragility and increased fracture incidence. All forms of OI also feature short stature, implying an effect on endochondral ossification. Using the Aga2+/- mouse, which has a mutation in type I collagen, we show an affected growth plate primarily due to a shortened proliferative zone. We used single-cell RNA-Seq analysis of tibial and femoral growth plate tissues to understand transcriptional consequences on growth plate cell types. We show that perichondrial cells, which express abundant type I procollagen, and growth plate chondrocytes, which were found to express low amounts of type I procollagen, had ER stress and dysregulation of the same unfolded protein response pathway as previously demonstrated in osteoblasts. Aga2+/- proliferating chondrocytes showed increased FGF and MAPK signaling, findings consistent with accelerated differentiation. There was also increased Sox9 expression throughout the growth plate, which is expected to accelerate early chondrocyte differentiation but reduce late hypertrophic differentiation. These data reveal that mutant type I collagen expression in OI has an impact on the cartilage growth plate. These effects on endochondral ossification indicate that OI is a biologically complex phenotype going beyond its known impacts on bone to negatively affect linear growth.

β-arrestins play a key role in G protein-coupled receptor (GPCR) internalization, trafficking, and signaling. Whether β-arrestins act independently of G protein-mediated signaling has not been fully elucidated. Studies using genome-editing approaches revealed that whereas G proteins are essential for mitogen-activated protein kinase activation by GPCRs., β-arrestins play a more prominent role in signal compartmentalization. However, in the absence of G proteins, GPCRs may not activate β-arrestins, thereby limiting the ability to distinguish G protein from β-arrestin-mediated signaling events. We used β2-adrenergic receptor (β2AR) and its β2AR-C tail mutant expressed in human embryonic kidney 293 cells wildtype or CRISPR-Cas9 gene edited for Gαs, β-arrestin1/2, or GPCR kinases 2/3/5/6 in combination with arrestin conformational sensors to elucidate the interplay between Gαs and β-arrestins in controlling gene expression. We found that Gαs is not required for β2AR and β-arrestin conformational changes, β-arrestin recruitment, and receptor internalization, but that Gαs dictates the GPCR kinase isoforms involved in β-arrestin recruitment. By RNA-Seq analysis, we found that protein kinase A and mitogen-activated protein kinase gene signatures were activated by stimulation of β2AR in wildtype and β-arrestin1/2-KO cells but absent in Gαs-KO cells. These results were validated by re-expressing Gαs in the corresponding KO cells and silencing β-arrestins in wildtype cells. These findings were extended to cellular systems expressing endogenous levels of β2AR. Overall, our results support that Gs is essential for β2AR-promoted protein kinase A and mitogen-activated protein kinase gene expression signatures, whereas β-arrestins initiate signaling events modulating Gαs-driven nuclear transcriptional activity.

To address the ongoing global tuberculosis crisis, there is a need for shorter, more effective treatments. A major reason why tuberculosis requires prolonged treatment is that, following a short initial phase of rapid killing, the residual Mycobacterium tuberculosis withstands drug killing. Because existing methods lack sensitivity to quantify low-abundance mycobacterial RNA in drug-treated animals, cellular adaptations of drug-exposed bacterial phenotypes in vivo remain poorly understood. Here, we used a novel RNA-seq method called SEARCH-TB to elucidate the Mycobacterium tuberculosis transcriptome in mice treated for up to 28 days with standard doses of isoniazid, rifampin, pyrazinamide, and ethambutol. We compared murine results with in vitro SEARCH-TB results during exposure to the same regimen. Treatment suppressed genes associated with growth, transcription, translation, synthesis of rRNA proteins, and immunogenic secretory peptides. Bacteria that survived prolonged treatment appeared to transition from ATP-maximizing respiration toward lower-efficiency pathways and showed modification and recycling of cell wall components, large-scale regulatory reprogramming, and reconfiguration of efflux pump expression. Although the pre-treatment in vivo and in vitro transcriptomes differed profoundly, genes differentially expressed following treatment in vivo and in vitro were similar, with differences likely attributable to immunity and drug pharmacokinetics in mice. These results reveal cellular adaptations of Mycobacterium tuberculosis that withstand prolonged drug exposure in vivo, demonstrating proof of concept that SEARCH-TB is a highly granular pharmacodynamic readout. The surprising finding that differential expression is concordant in vivo and in vitro suggests that insights from transcriptional analyses in vitro may translate to the mouse. IMPORTANCE A major reason that curing tuberculosis requires prolonged treatment is that drug exposure changes bacterial phenotypes. The physiologic adaptations of Mycobacterium tuberculosis that survive drug exposure in vivo have been obscure due to low sensitivity of existing methods in drug-treated animals. Using the novel SEARCH-TB RNA-seq platform, we elucidated Mycobacterium tuberculosis phenotypes in mice treated for with the global standard 4-drug regimen and compared them with the effect of the same regimen in vitro. This first view of the transcriptome of the minority Mycobacterium tuberculosis population that withstands treatment in vivo reveals adaptation of a broad range of cellular processes, including a shift in metabolism and cell wall modification. Surprisingly, the change in gene expression induced by treatment in vivo and in vitro was largely similar. This apparent portability from in vitro to the mouse provides important new context for in vitro transcriptional analyses that may support early preclinical drug evaluation.

ImportanceIn this study, we developed a correlative approach that combined DNA immunoprecipitation-seq and RNA-seq analyses to define the regulon of the Chlamydia trachomatis transcription factor Euo. We confirmed the proposed role of Euo as a transcriptional repressor of late chlamydial genes but also showed that Euo activates transcription of a subset of midcycle genes and autoregulates its own expression via negative feedback. This study validates and expands the role of Euo as an important developmental regulator in C. trachomatis. In addition, this genome-wide correlative approach can be applied to study transcription factors in other pathogenic bacteria.

Understanding the genetic basis of novel adaptations in new species is a fundamental question in biology. Here we demonstrate a new role for galr2 in vertebrate craniofacial development using an adaptive radiation of trophic specialist pupfishes endemic to San Salvador Island, Bahamas. We confirmed the loss of a putative Sry transcription factor binding site upstream of galr2 in scale-eating pupfish and found significant spatial differences in galr2 expression among pupfish species in Meckel's cartilage using in situ hybridization chain reaction (HCR). We then experimentally demonstrated a novel role for Galr2 in craniofacial development by exposing embryos to Garl2-inhibiting drugs. Galr2-inhibition reduced Meckel's cartilage length and increased chondrocyte density in both trophic specialists but not in the generalist genetic background. We propose a mechanism for jaw elongation in scale-eaters based on the reduced expression of galr2 due to the loss of a putative Sry binding site. Fewer Galr2 receptors in the scale-eater Meckel's cartilage may result in their enlarged jaw lengths as adults by limiting opportunities for a circulating Galr2 agonist to bind to these receptors during development. Our findings illustrate the growing utility of linking candidate adaptive SNPs in non-model systems with highly divergent phenotypes to novel vertebrate gene functions.

Small open reading frame (smORF)-encoded microproteins, proteins containing less than 100-150 amino acids, are an emerging class of functional biomolecules. Here, we present a protocol for identifying translated smORFs in mammalian systems genome wide. We describe steps for generation of ribosome profiling (Ribo-seq) data, in silico translation of a transcriptome assembly to create an ORF database, and computational analysis of Ribo-seq to score individual smORFs for translation. Identification of translated smORFs is the first step to studying the functions of microproteins. For complete details on the use and execution of this protocol, please refer to Martinez et al.1.

Assessment of genomic conservation between humans and pigs at the functional level can improve the potential of pigs as a human biomedical model. To address this, we developed a deep learning-based approach to learn the genomic conservation at the functional level (DeepGCF) between species by integrating 386 and 374 functional profiles from humans and pigs, respectively. DeepGCF demonstrated better prediction performance compared with the previous method. In addition, the resulting DeepGCF score captures the functional conservation between humans and pigs by examining chromatin states, sequence ontologies, and regulatory variants. We identified a core set of genomic regions as functionally conserved that plays key roles in gene regulation and is enriched for the heritability of complex traits and diseases in humans. Our results highlight the importance of cross-species functional comparison in illustrating the genetic and evolutionary basis of complex phenotypes.

BACKGROUND: Despite major improvements in treatment of HER2-positive metastatic breast cancer (MBC), only few patients achieve complete remission and remain progression free for a prolonged time. The tumor immune microenvironment plays an important role in the response to treatment in HER2-positive breast cancer and could contain valuable prognostic information. Detailed information on the cancer-immune cell interactions in HER2-positive MBC is however still lacking. By characterizing the tumor immune microenvironment in patients with HER2-positive MBC, we aimed to get a better understanding why overall survival (OS) differs so widely and which alternative treatment approaches may improve outcome. METHODS: We included all patients with HER2-positive MBC who were treated with trastuzumab-based palliative therapy in the Netherlands Cancer Institute between 2000 and 2014 and for whom pre-treatment tissue from the primary tumor or from metastases was available. Infiltrating immune cells and their spatial relationships to one another and to tumor cells were characterized by immunohistochemistry and multiplex immunofluorescence. We also evaluated immune signatures and other key pathways using next-generation RNA-sequencing data. With nine years median follow-up from initial diagnosis of MBC, we investigated the association between tumor and immune characteristics and outcome. RESULTS: A total of 124 patients with 147 samples were included and evaluated. The different technologies showed high correlations between each other. T-cells were less prevalent in metastases compared to primary tumors, whereas B-cells and regulatory T-cells (Tregs) were comparable between primary tumors and metastases. Stromal tumor-infiltrating lymphocytes in general were not associated with OS. The infiltration of B-cells and Tregs in the primary tumor was associated with unfavorable OS. Four signatures classifying the extracellular matrix of primary tumors showed differential survival in the population as a whole. CONCLUSIONS: In a real-world cohort of 124 patients with HER2-positive MBC, B-cells, and Tregs in primary tumors are associated with unfavorable survival. With this paper, we provide a comprehensive insight in the tumor immune microenvironment that could guide further research into development of novel immunomodulatory strategies.

The nuclear receptor co-repressor (NCoR) complex mediates transcriptional repression dependent on histone deacetylation by histone deacetylase 3 (HDAC3) as a component of the complex. Unexpectedly, we found that signaling by the receptor activator of nuclear factor κB (RANK) converts the NCoR/HDAC3 co-repressor complex to a co-activator of AP-1 and NF-κB target genes that are required for mouse osteoclast differentiation. Accordingly, the dominant function of NCoR/HDAC3 complexes in response to RANK signaling is to activate, rather than repress, gene expression. Mechanistically, RANK signaling promotes RNA-dependent interaction of the transcriptional co-activator PGC1β with the NCoR/HDAC3 complex, resulting in the activation of PGC1β and inhibition of HDAC3 activity for acetylated histone H3. Non-coding RNAs Dancr and Rnu12, which are associated with altered human bone homeostasis, promote NCoR/HDAC3 complex assembly and are necessary for RANKL-induced osteoclast differentiation in vitro. These findings may be prototypic for signal-dependent functions of NCoR in other biological contexts.

Interactions between plant roots and rhizosphere bacteria modulate nitrogen (N)-cycling processes and create habitats rich in low molecular weight compounds (exudates) and complex organic molecules (decaying root litter) compared to those of bulk soil. Microbial N-cycling is regulated by edaphic conditions and genes from many interconnected metabolic pathways, but most studies of soil N-cycling gene expression have focused on single pathways. Currently, we lack a comprehensive understanding of the interplay between soil N-cycling gene regulation, spatial habitat, and time. We present results from a replicated time series of soil metatranscriptomes; we followed gene expression of multiple N transformations in four soil habitats (rhizosphere, detritusphere, rhizo-detritusphere, and bulk soil) during active root growth for the annual grass, Avena fatua. The presence of root litter and living roots significantly altered the trajectories of N-cycling gene expression. Upregulation of assimilatory nitrate reduction in the rhizosphere suggests that rhizosphere bacteria were actively competing with roots for nitrate. Simultaneously, ammonium assimilatory pathways were upregulated in both rhizosphere and detritusphere soil, which could have limited N availability to plants. The detritusphere supported dissimilatory processes DNRA and denitrification. Expression of nitrification genes was dominated by three phylotypes of Thaumarchaeota and was upregulated in bulk soil. Unidirectional ammonium assimilation and its regulatory genes (GS/GOGAT) were upregulated near relatively young roots and highly decayed root litter, suggesting N may have been limiting in these habitats (GS/GOGAT is typically activated under N limitation). Our comprehensive analysis indicates that differences in carbon and inorganic N availability control contemporaneous transcription of N-cycling pathways in soil habitats. IMPORTANCE Plant roots modulate microbial nitrogen (N) cycling by regulating the supply of root-derived carbon and nitrogen uptake. These differences in resource availability cause distinct micro-habitats to develop: soil near living roots, decaying roots, near both, or outside the direct influence of roots. While many environmental factors and genes control the microbial processes involved in the nitrogen cycle, most research has focused on single genes and pathways, neglecting the interactive effects these pathways have on each other. The processes controlled by these pathways determine consumption and production of N by soil microorganisms. We followed the expression of N-cycling genes in four soil microhabitats over a period of active root growth for an annual grass. We found that the presence of root litter and living roots significantly altered gene expression involved in multiple nitrogen pathways, as well as tradeoffs between pathways, which ultimately regulate N availability to plants.

The advent of single-cell RNA sequencing (scRNA-seq) technologies has enabled gene expression profiling at the single-cell resolution, thereby enabling the quantification and comparison of transcriptional variability among individual cells. Although alterations in transcriptional variability have been observed in various biological states, statistical methods for quantifying and testing differential variability between groups of cells are still lacking. To identify the best practices in differential variability analysis of single-cell gene expression data, we propose and compare 12 statistical pipelines using different combinations of methods for normalization, feature selection, dimensionality reduction and variability calculation. Using high-quality synthetic scRNA-seq datasets, we benchmarked the proposed pipelines and found that the most powerful and accurate pipeline performs simple library size normalization, retains all genes in analysis and uses denSNE-based distances to cluster medoids as the variability measure. By applying this pipeline to scRNA-seq datasets of COVID-19 and autism patients, we have identified cellular variability changes between patients with different severity status or between patients and healthy controls.

The innate immune system is the body's first line of defense against infection. Natural killer (NK) cells, a vital part of the innate immune system, help to control infection and eliminate cancer. Studies have identified a vast array of receptors that NK cells use to discriminate between healthy and unhealthy cells. However, at present, it is difficult to explain how NK cells will respond to novel stimuli in different environments. In addition, the expression of different receptors on individual NK cells is highly stochastic, but the reason for these variegated expression patterns is unclear. Here, we studied the recognition of unhealthy target cells as an inference problem, where NK cells must distinguish between healthy targets with normal variability in ligand expression and ones that are clear "outliers." Our mathematical model fits well with experimental data, including NK cells' adaptation to changing environments and responses to different target cells. Furthermore, we find that stochastic, "sparse" receptor expression profiles are best able to detect a variety of possible threats, in agreement with experimental studies of the NK cell repertoire. While our study was specifically motivated by NK cells, our model is general and could also apply more broadly to explain principles of target recognition for other immune cell types.

Wheat is an important contributor to global food security, and further improvements are required to feed a growing human population. Functional genetics and genomics tools can help us to understand the function of different genes and to engineer beneficial changes. In this study, we used a promoter capture assay to sequence 2-kb regions upstream of all high-confidence annotated genes from 1,513 mutagenized plants from the tetraploid wheat variety Kronos. We identified 4.3 million induced mutations with an accuracy of 99.8%, resulting in a mutation density of 41.9 mutations per kb. We also remapped Kronos exome capture reads to Chinese Spring RefSeq v1.1, identified 4.7 million mutations, and predicted their effects on annotated genes. Using these predictions, we identified 59% more nonsynonymous substitutions and 49% more truncation mutations than in the original study. To show the biological value of the promoter dataset, we selected two mutations within the promoter of the VRN-A1 vernalization gene. Both mutations, located within transcription factor binding sites, significantly altered VRN-A1 expression, and one reduced the number of spikelets per spike. These publicly available sequenced mutant datasets provide rapid and inexpensive access to induced variation in the promoters and coding regions of most wheat genes. These mutations can be used to understand and modulate gene expression and phenotypes for both basic and commercial applications, where limited governmental regulations can facilitate deployment. These mutant collections, together with gene editing, provide valuable tools to accelerate functional genetic studies in this economically important crop.

PURPOSE: We previously reported differential gene expression of the bone morphogenetic protein 2 (Bmp2) in guinea pig retinal pigment epithelium (RPE) after 1 day of hyperopic defocus, imposed with a negative contact lens (CLs). The study reported here sought to obtain insights into the temporal profiles of gene expression changes in Bmp2, as well as those of two closely related genes, the inhibitor of DNA binding 3 (Id3) and Noggin (Nog), both during myopia induction and when the CL treatment was terminated to allow recovery from induced myopia. METHODS: To induce myopia, 2-week-old pigmented guinea pigs (New Zealand strain, n = 8) wore monocular -10 diopter (D) rigid gas-permeable (RGP) CLs for one week, while the other eye served as a control. Ocular measurements were made at baseline, 3 days, and 7 days after the initiation of CL wear, with treatment then being terminated and additional measurements being made after a further 3 days, 1 week, and 2 weeks. Spherical equivalent refractive errors (SERs), axial length (AL), choroidal thickness (ChT), and scleral thickness (ScT) data were collected using retinoscopy, optical biometry (Lenstar), and spectral domain optical coherence tomography (SD-OCT), respectively. RPE samples were collected from both eyes of the guinea pigs after either 1 day or 1 week of CL wear or 1 day or 2 weeks after its termination, and RNA was subsequently isolated and subjected to quantitative real-time PCR (qRT-PCR) analyses, targeting the Bmp2, Id3, and Nog genes. RESULTS: Mean interocular differences (treated-control) in AL and SER were significantly different from baseline after 3 and 7 days of CL wear, consistent with induced myopia (p < 0.001 for all cases). Termination of CL wear resulted in the normalization (i.e., recovery) of the ALs and SERs of the treated eyes within 7 days, and the earlier significant ChT thinning with CL wear (p = 0004, day 7) was replaced by rapid thickening, which remained significant on day 7 (p = 0.009) but had normalized by day 14. The ChT changes were much smaller in magnitude than the AL changes in both phases. Interocular differences in the ScT showed no significant changes. The Bmp2 and Id3 genes were both significantly downregulated with CL wear, after 1 day (p = 0.012 and 0.016) and 7 days (p = 0.002 and 0.005), while Bmp2 gene expression increased and Nog gene expression decreased after the termination of CL wear, albeit transiently, which was significant on 1 day (p = 0.004 and 0.04) but not 2 weeks later. No change in Id3 gene expression was observed over the latter period. Conclusions: The above patterns of myopia induction and recovery validate this negative RGP-CL model as an alternative to traditional spectacle lens models for guinea pigs. The defocus-driven, sign-dependent changes in the expression of the Bmp2 gene in guinea pig RPE are consistent with observations in chicks and demonstrate the important role of BMP2 in eye growth regulation.

MOTIVATION: Since the development of single-cell RNA sequencing (scRNA-seq) technologies, clustering analysis of single-cell gene expression data has been an essential tool for distinguishing cell types and identifying novel cell types. Even though many methods have been available for scRNA-seq clustering analysis, the majority of them are constrained by the requirement on predetermined cluster numbers or the dependence on selected initial cluster assignment. RESULTS: In this article, we propose an adaptive embedding and clustering method named scAce, which constructs a variational autoencoder to simultaneously learn cell embeddings and cluster assignments. In the scAce method, we develop an adaptive cluster merging approach which achieves improved clustering results without the need to estimate the number of clusters in advance. In addition, scAce provides an option to perform clustering enhancement, which can update and enhance cluster assignments based on previous clustering results from other methods. Based on computational analysis of both simulated and real datasets, we demonstrate that scAce outperforms state-of-the-art clustering methods for scRNA-seq data, and achieves better clustering accuracy and robustness. AVAILABILITY AND IMPLEMENTATION: The scAce package is implemented in python 3.8 and is freely available from https://github.com/sldyns/scAce.

In many organisms, interactions among genes lead to multiple functional states, and changes to interactions can lead to transitions into new states. These transitions can be related to bifurcations (or critical points) in dynamical systems theory. Characterizing these collective transitions is a major challenge for systems biology. Here, we develop a statistical method for identifying bistability near a continuous transition directly from high-dimensional gene expression data. We apply the method to data from honey bees, where a known developmental transition occurs between bees performing tasks in the nest and leaving the nest to forage. Our method, which makes use of the expected shape of the distribution of gene expression levels near a transition, successfully identifies the emergence of bistability and links it to genes that are known to be involved in the behavioral transition. This proof of concept demonstrates that going beyond correlative analysis to infer the shape of gene expression distributions might be used more generally to identify collective transitions from gene expression data.

Dispatching rules are one of the most widely applied methods for solving Dynamic Job Shop Scheduling problems (DJSSP) in real-world manufacturing systems. Hence, the automated design of effective rules has been an important subject in the scheduling literature for the past several years. High computational requirements and difficulty in interpreting generated rules are limitations of literature methods. Also, feature selection approaches in the field of automated design of scheduling policies have been developed for the tree-based GP approach only. Therefore, the aim of this study is to propose a feature selection approach for the Gene Expression Programming (GEP) algorithm to evolve high-quality rules in simple structures with an affordable computational budget. This integration speeds up the search process by restricting the GP search space using the linear representation of the GEP algorithm and creates concise rules with only meaningful features using the feature selection approach. The proposed algorithm is compared with five algorithms and 30 rules from the literature under different processing conditions. Three performance measures are considered including total weighted tardiness, mean tardiness, and mean flow time. The results show that the proposed algorithm can generate smaller rules with high interpretability in a much shorter training time. [ABSTRACT FROM AUTHOR]

Mechanosensitive mechanisms are often used to sense damage to tissue structure, stimulating matrix synthesis and repair. While this kind of mechanoregulatory process is well recognized in eukaryotic systems, it is not known whether such a process occurs in bacteria. In Vibrio cholerae, antibiotic-induced damage to the load-bearing cell wall promotes increased signaling by the two-component system VxrAB, which stimulates cell wall synthesis. Here we show that changes in mechanical stress within the cell envelope are sufficient to stimulate VxrAB signaling in the absence of antibiotics. We applied mechanical forces to individual bacteria using three distinct loading modalities: extrusion loading within a microfluidic device, direct compression and hydrostatic pressure. In all cases, VxrAB signaling, as indicated by a fluorescent protein reporter, was increased in cells submitted to greater magnitudes of mechanical loading, hence diverse forms of mechanical stimuli activate VxrAB signaling. Reduction in cell envelope stiffness following removal of the endopeptidase ShyA led to large increases in cell envelope deformation and substantially increased VxrAB response, further supporting the responsiveness of VxrAB. Our findings demonstrate a mechanosensitive gene regulatory system in bacteria and suggest that mechanical signals may contribute to the regulation of cell wall homeostasis.

Future breeding is likely to involve the detection and removal of deleterious alleles, which are mutations that negatively affect crop fitness. However, little is known about the prevalence of such mutations and their effects on phenotypic traits in the context of modern crop breeding. To address this, we examined the number and frequency of deleterious mutations in 350 elite maize inbred lines developed over the past few decades in China and the United States. Our findings reveal an accumulation of weakly deleterious mutations and a decrease in strongly deleterious mutations, indicating the dominant effects of genetic drift and purifying selection for the two types of mutations, respectively. We also discovered that slightly deleterious mutations, when at lower frequencies, were more likely to be heterozygous in the developed hybrids. This is consistent with complementation as a potential explanation for heterosis. Subsequently, we found that deleterious mutations accounted for more of the variation in phenotypic traits than nondeleterious mutations with matched minor allele frequencies, especially for traits related to leaf angle and flowering time. Moreover, we detected fewer deleterious mutations in the promoter and gene body regions of differentially expressed genes across breeding eras than in nondifferentially expressed genes. Overall, our results provide a comprehensive assessment of the prevalence and impact of deleterious mutations in modern maize breeding and establish a useful baseline for future maize improvement efforts.

Late life insomnia may increase risk for accelerated biological aging. Intervening to treat insomnia may provide protection from biological aging by reducing the prevalence of senescent cells in the immune system, as indicated by gene expression of a marker of cellular senescence, p16INK4a. In the present study, we determine whether treatment of insomnia in older adults with cognitive behavioral therapy for insomnia (CBT-I) would reduce p16INK4a gene expression in peripheral blood mononuclear cells (PBMC), compared to a sleep education therapy (SET), an active comparator condition. Secondly, we investigate the relationship between sustained insomnia remission and reduced expression of p16INK4a. Participants 60 + years old with insomnia were enrolled in a randomized controlled trial and assigned to CBT-I or SET. Analyses of 231 older adults (CBT-I = 119; SET = 112) examine baseline, post (2 months), and 24 months gene expression of p16INK4a. Compared to baseline, expression of p16INK4a increased in the SET group over 24 months (P = 0.03), but showed no change in the CBT-I group. Those who received CBT-I and experienced sustained remission of insomnia had a significant decline in p16INK4a expression by 24 months compared to baseline (P = 0.02). Individuals not sustaining remission of insomnia exhibited overall increase expression of p16INK4a by 24 months (P = 0.03). In older adults with insomnia, p16INK4a increases over 24 months, while CBT-I treatment of insomnia mitigates the increase in p16INK4a. Further, sustained remission of insomnia using CBT-I leads to a decrease in p16INK4a. These results suggest that behavioral interventions that are effective at treating insomnia might reduce the population of senescent cells in circulating blood.

BackgroundProstate cancer (PCa) is a clinically heterogeneous disease. The creation of an expression-based subtyping model based on prostate-specific biological processes was sought.MethodsUnsupervised machine learning of gene expression profiles from prospectively collected primary prostate tumors (training, n = 32,000; evaluation, n = 68,547) was used to create a prostate subtyping classifier (PSC) based on basal versus luminal cell expression patterns and other gene signatures relevant to PCa biology. Subtype molecular pathways and clinical characteristics were explored in five other clinical cohorts.ResultsClustering derived four subtypes: luminal differentiated (LD), luminal proliferating (LP), basal immune (BI), and basal neuroendocrine (BN). LP and LD tumors both had higher androgen receptor activity. LP tumors also had a higher expression of cell proliferation genes, MYC activity, and characteristics of homologous recombination deficiency. BI tumors possessed significant interferon γactivity and immune infiltration on immunohistochemistry. BN tumors were characterized by lower androgen receptor activity expression, lower immune infiltration, and enrichment with neuroendocrine expression patterns. Patients with LD tumors had less aggressive tumor characteristics and the longest time to metastasis after surgery. Only patients with BI tumors derived benefit from radiotherapy after surgery in terms of time to metastasis (hazard ratio [HR], 0.09; 95% CI, 0.01-0.71; n = 855). In a phase 3 trial that randomized patients with metastatic PCa to androgen deprivation with or without docetaxel (n = 108), only patients with LP tumors derived survival benefit from docetaxel (HR, 0.21; 95% CI, 0.09-0.51).ConclusionsWith the use of expression profiles from over 100,000 tumors, a PSC was developed that identified four subtypes with distinct biological and clinical features.Plain language summaryProstate cancer can behave in an indolent or aggressive manner and vary in how it responds to certain treatments. To differentiate prostate cancer on the basis of biological features, we developed a novel RNA signature by using data from over 100,000 prostate tumors-the largest data set of its kind. This signature can inform patients and physicians on tumor aggressiveness and susceptibilities to treatments to help personalize cancer management.

During emergency hematopoiesis, hematopoietic stem cells (HSCs) rapidly proliferate to produce myeloid and lymphoid effector cells, a response that is critical against infection or tissue injury. If unresolved, this process leads to sustained inflammation, which can cause life-threatening diseases and cancer. Here, we identify a role of double PHD fingers 2 (DPF2) in modulating inflammation. DPF2 is a defining subunit of the hematopoiesis-specific BAF (SWI/SNF) chromatin-remodeling complex, and it is mutated in multiple cancers and neurological disorders. We uncovered that hematopoiesis-specific Dpf2-KO mice developed leukopenia, severe anemia, and lethal systemic inflammation characterized by histiocytic and fibrotic tissue infiltration resembling a clinical hyperinflammatory state. Dpf2 loss impaired the polarization of macrophages responsible for tissue repair, induced the unrestrained activation of Th cells, and generated an emergency-like state of HSC hyperproliferation and myeloid cell-biased differentiation. Mechanistically, Dpf2 deficiency resulted in the loss of the BAF catalytic subunit BRG1 from nuclear factor erythroid 2-like 2-controlled (NRF2-controlled) enhancers, impairing the antioxidant and antiinflammatory transcriptional response needed to modulate inflammation. Finally, pharmacological reactivation of NRF2 suppressed the inflammation-mediated phenotypes and lethality of Dpf2Δ/Δ mice. Our work establishes an essential role of the DPF2-BAF complex in licensing NRF2-dependent gene expression in HSCs and immune effector cells to prevent chronic inflammation.