Dynamic regulation of genome-wide pre-mRNA splicing and stress tolerance by the Sm-like protein LSm5 in Arabidopsis

Genetic analyses and dispersal patterns unveil the Amazonian origin of guava domestication

Guava (Psidium guajava L.) is a semi-domesticated fruit tree of moderate importance in the Neotropics, utilized for millennia due to its nutritional and medicinal benefits, but its origin of domestication remains unknown. In this study, we examine genetic diversity and population structure in 215 plants from 11 countries in Mesoamerica, the Andes, and Amazonia using 25 nuclear microsatellite loci to propose an origin of domestication. Genetic analyses reveal one gene pool in Mesoamerica (Mexico) and four in South America (Brazilian Amazonia, Peruvian Amazonia and Andes, and Colombia), indicating greater differentiation among localities, possibly due to isolation between guava populations, particularly in the Amazonian and Andean regions. Moreover, Mesoamerican populations show high genetic diversity, with moderate genetic structure due to gene flow from northern South American populations. Dispersal scenarios suggest that Brazilian Amazonia is the probable origin of guava domestication, spreading from there to the Peruvian Andes, northern South America, Central America, and Mexico. These findings present the first evidence of guava domestication in the Americas, contributing to a deeper understanding of its evolutionary history.

Quantifying compositional variability in microbial communities with FAVA

Microbial communities vary across space, time, and individual hosts, presenting new challenges for the development of statistics measuring the variability of community composition. To understand differences across microbiome samples from different host individuals, sampling times, spatial locations, or experimental replicates, we present FAVA, a new normalized measure for characterizing compositional variability across multiple microbiome samples. FAVA quantifies variability across many samples of taxonomic or functional relative abundances in a single index ranging between 0 and 1, equaling 0 when all samples are identical and equaling 1 when each sample is entirely comprised of a single taxon. Its definition relies on the population-genetic statistic F ST , with samples playing the role of "populations" and taxa playing the role of "alleles." Its convenient mathematical properties allow users to compare disparate data sets. For example, FAVA values are commensurable across different numbers of taxonomic categories and different numbers of samples considered. We introduce extensions that incorporate phylogenetic similarity among taxa and spatial or temporal distances between samples. We illustrate how FAVA can be used to describe across-individual taxonomic variability in ruminant microbiomes at different regions along the gastrointestinal tract. In a second example, a longitudinal analysis of gut microbiomes of healthy human adults taking an antibiotic, we use FAVA to quantify the increase in temporal variability of microbiomes following the antibiotic course and to measure the duration of the antibiotic's influence on microbial variability. We have implemented this tool in an R package, FAVA , which can fit easily into existing pipelines for the analysis of microbial relative abundances.

Significance statement

Studies of microbial community composition across time, space, or biological replicates often rely on summary statistics that analyze just one or two samples at a time. Although these statistics effectively summarize the diversity of one sample or the compositional dissimilarity between two samples, they are ill-suited for measuring variability across many samples at once. Measuring compositional variability among many samples is key to understanding the temporal stability of a community across multiple time points, or the heterogeneity of microbiome composition across multiple experimental replicates or host individuals. Our proposed measure, FAVA, meets the need for a statistic summarizing compositional variability across many microbiome samples all at once.

Transcriptome-wide characterization of genetic perturbations

Single cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are often noisy due to cost and technical constraints, limiting power to detect true effects with conventional differential expression analyses. Here, we introduce TRanscriptome-wide Analysis of Differential Expression (TRADE), a statistical framework which estimates the transcriptome-wide distribution of true differential expression effects from noisy gene-level measurements. Within TRADE, we derive multiple novel, interpretable statistical metrics, including the "transcriptome-wide impact", an estimator of the overall transcriptional effect of a perturbation which is stable across sampling depths. We analyze new and published large-scale Perturb-seq datasets to show that many true transcriptional effects are not statistically significant, but detectable in aggregate with TRADE. In a genome-scale Perturb-seq screen, we find that a typical gene perturbation affects an estimated 45 genes, whereas a typical essential gene perturbation affects over 500 genes. An advantage of our approach is its ability to compare the transcriptomic effects of genetic perturbations across contexts and dosages despite differences in power. We use this ability to identify perturbations with cell-type dependent effects and to find examples of perturbations where transcriptional responses are not only larger in magnitude, but also qualitatively different, as a function of dosage. Lastly, we expand our analysis to case/control comparison of gene expression for neuropsychiatric conditions, finding that transcriptomic effect correlations are greater than genetic correlations for these diagnoses. TRADE lays an analytic foundation for the systematic comparison of genetic perturbation atlases, as well as differential expression experiments more broadly.

Gene body DNA hydroxymethylation restricts the magnitude of transcriptional changes during aging

DNA hydroxymethylation (5hmC), the most abundant oxidative derivative of DNA methylation, is typically enriched at enhancers and gene bodies of transcriptionally active and tissue-specific genes. Although aberrant genomic 5hmC has been implicated in age-related diseases, its functional role in aging remains unknown. Here, using mouse liver and cerebellum as model organs, we show that 5hmC accumulates in gene bodies associated with tissue-specific function and restricts the magnitude of gene expression changes with age. Mechanistically, 5hmC decreases the binding of splicing associated factors and correlates with age-related alternative splicing events. We found that various age-related contexts, such as prolonged quiescence and senescence, drive the accumulation of 5hmC with age. We provide evidence that this age-related transcriptionally restrictive function is conserved in mouse and human tissues. Our findings reveal that 5hmC regulates tissue-specific function and may play a role in longevity.

EstroGene2.0: A multi-omic database of response to estrogens, ER-modulators, and resistance to endocrine therapies in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ ESR1 ) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Understanding the molecular mechanisms is thus key to optimize the existing drugs and to develop new ER-modulators. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities ( https://estrogeneii.web.app/ ). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed substantial diversity in response to different classes of ER-modulators including SERMs, SERDs, SERCA and LDD/PROTAC. Notably, endocrine resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signaling, which is recapitulated clinically. Furthermore, dissecting multiple ESR1 -mutant cell models revealed the different clinical relevance of genome-edited versus ectopic overexpression model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer's response to endocrine therapies and explore resistance mechanisms.

An alternative 3' splice site of PeuHKT1;3 improves the response to salt stress through enhancing affinity to K+ in Populus

Alternative splicing (AS) serves as a crucial post-transcriptional regulator in plants that contributes to the resistance to salt stress. However, the underlying mechanism is largely unknown. In this research, we identified an important AS transcript in Populus euphratica, PeuHKT1:3a, generated by alternative 3' splice site splicing mode that resulted in the removal of 252 bases at the 5' end of the first exon in PeuHKT1:3. Protein sequence comparison showed that the site of AS occurred in PeuHKT1:3 is located at a crucial Ser residue within the first pore-loop domain, which leads to inefficient K+ transport in HKT I-type transporters. Expressing PeuHKT1;3a in an axt3 mutant yeast strain can effectively compensate for the lack of intracellular K+, whereas the expression of PeuHKT1;3 cannot yield the effect. Furthermore, in transgenic Arabidopsis and poplar plants, it was observed that lines expressing PeuHKT1;3a exhibited greater salt tolerance compared to those expressing the PeuHKT1;3 strain. Analysis of ion content and flux demonstrated that the transgenic PeuHKT1;3a line exhibited significantly higher K+ content compared to the PeuHKT1;3 line, while there was no significant difference in Na+ content. In conclusion, our findings revealed that AS can give rise to novel variants of HKT I-type proteins in P. euphratica with modified K+ selectivity to keep a higher K+/Na+ ratio to enhanced salt tolerance.

Cerebellar granular neuron progenitors exit their germinative niche via BarH-like1 activity mediated partly by inhibition of T-cell factor

Cerebellar granule neuron progenitors (GNPs) originate from the upper rhombic lip (URL), a germinative niche in which developmental defects produce human diseases. T-cell factor (TCF) responsiveness and Notch dependence are hallmarks of self-renewal in neural stem cells. TCF activity, together with transcripts encoding proneural gene repressors hairy and enhancer of split (Hes/Hey), are detected in the URL; however, their functions and regulatory modes are undeciphered. Here, we established amphibian as a pertinent model for studying vertebrate URL development. The amphibian long-lived URL is TCF active, whereas the external granular layer (EGL) is non-proliferative and expresses hes4 and hes5 genes. Using functional and transcriptomic approaches, we show that TCF activity is necessary for URL emergence and maintenance. We establish that the transcription factor Barhl1 controls GNP exit from the URL, acting partly through direct TCF inhibition. Identification of Barhl1 target genes suggests that, besides TCF, Barhl1 inhibits transcription of hes5 genes independently of Notch signaling. Observations in amniotes suggest a conserved role for Barhl in maintenance of the URL and/or EGL via co-regulation of TCF, Hes and Hey genes.

CRISPR Screening Uncovers a Long-Range Enhancer for ONECUT1 in Pancreatic Differentiation and Links a Diabetes Risk Variant

Functional enhancer annotation is a valuable first step for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants for investigation. However, unbiased enhancer discovery in physiologically relevant contexts remains a major challenge. To discover regulatory elements pertinent to diabetes, we conducted a CRISPR interference screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers uncovered, we focused on a long-range enhancer ∼664 kb from the ONECUT1 promoter, since coding mutations in ONECUT1 cause pancreatic hypoplasia and neonatal diabetes. Homozygous enhancer deletion in hPSCs was associated with a near-complete loss of ONECUT1 gene expression and compromised pancreatic differentiation. This enhancer contains a confidently fine-mapped type 2 diabetes associated variant (rs528350911) which disrupts a GATA motif. Introduction of the risk variant into hPSCs revealed substantially reduced binding of key pancreatic transcription factors (GATA4, GATA6 and FOXA2) on the edited allele, accompanied by a slight reduction of ONECUT1 transcription, supporting a causal role for this risk variant in metabolic disease. This work expands our knowledge about transcriptional regulation in pancreatic development through the characterization of a long-range enhancer and highlights the utility of enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.

Spinal motor neuron development and metabolism are transcriptionally regulated by Nuclear Factor IA

Neural circuits governing all motor behaviors in vertebrates rely on the proper development of motor neurons and their precise targeting of limb muscles. Transcription factors are essential for motor neuron development, regulating their specification, migration, and axonal targeting. While transcriptional regulation of the early stages of motor neuron specification is well-established, much less is known about the role of transcription factors in the later stages of maturation and terminal arborization. Defining the molecular mechanisms of these later stages is critical for elucidating how motor circuits are constructed. Here, we demonstrate that the transcription factor Nuclear Factor-IA (NFIA) is required for motor neuron positioning, axonal branching, and neuromuscular junction formation. Moreover, we find that NFIA is required for proper mitochondrial function and ATP production, providing a new and important link between transcription factors and metabolism during motor neuron development. Together, these findings underscore the critical role of NFIA in instructing the assembly of spinal circuits for movement.

Automated single-cell omics end-to-end framework with data-driven batch inference

To facilitate single-cell multi-omics analysis and improve reproducibility, we present SPEEDI (Single-cell Pipeline for End to End Data Integration), a fully automated end-to-end framework for batch inference, data integration, and cell type labeling. SPEEDI introduces data-driven batch inference and transforms the often heterogeneous data matrices obtained from different samples into a uniformly annotated and integrated dataset. Without requiring user input, it automatically selects parameters and executes pre-processing, sample integration, and cell type mapping. It can also perform downstream analyses of differential signals between treatment conditions and gene functional modules. SPEEDI's data-driven batch inference method works with widely used integration and cell-typing tools. By developing data-driven batch inference, providing full end-to-end automation, and eliminating parameter selection, SPEEDI improves reproducibility and lowers the barrier to obtaining biological insight from these valuable single-cell datasets. The SPEEDI interactive web application can be accessed at https://speedi.princeton.edu/.

A model for accurate quantification of CRISPR effects in pooled FACS screens

CRISPR screens are powerful tools to identify key genes that underlie biological processes. One important type of screen uses fluorescence activated cell sorting (FACS) to sort perturbed cells into bins based on the expression level of marker genes, followed by guide RNA (gRNA) sequencing. Analysis of these data presents several statistical challenges due to multiple factors including the discrete nature of the bins and typically small numbers of replicate experiments. To address these challenges, we developed a robust and powerful Bayesian random effects model and software package called Waterbear. Furthermore, we used Waterbear to explore how various experimental design parameters affect statistical power to establish principled guidelines for future screens. Finally, we experimentally validated our experimental design model findings that, when using Waterbear for analysis, high power is maintained even at low cell coverage and a high multiplicity of infection. We anticipate that Waterbear will be of broad utility for analyzing FACS-based CRISPR screens.

Early life exposure to queen mandibular pheromone mediates persistent transcriptional changes in the brain of honey bee foragers

Behavioural regulation in insect societies remains a fundamental question in sociobiology. In hymenopteran societies, the queen plays a crucial role in regulating group behaviour by affecting individual behaviour and physiology through modulation of worker gene expression. Honey bee (Apis mellifera) queens signal their presence via queen mandibular pheromone (QMP). While QMP has been shown to influence behaviour and gene expression of young workers, we know little about how these changes translate in older workers. The effects of the queen pheromone could have prolonged molecular impacts on workers that depend on an early sensitive period. We demonstrate that removal of QMP impacts long-term gene expression in the brain and antennae in foragers that were treated early in life (1 day post emergence), but not when treated later in life. Genes important for division of labour, learning, chemosensory perception and ageing were among those differentially expressed in the antennae and brain tissues, suggesting that QMP influences diverse physiological and behavioural processes in workers. Surprisingly, removal of QMP did not have an impact on foraging behaviour. Overall, our study suggests a sensitive period early in the life of workers, where the presence or absence of a queen has potentially life-long effects on transcriptional activity.

Heat-stress-responsive HvHSFA2e gene regulates the heat and drought tolerance in barley through modulation of phytohormone and secondary metabolic pathways

KEY MESSAGE

The heat stress transcription factor HSFA2e regulates both temperature and drought response via hormonal and secondary metabolism alterations. High temperature and drought are the primary yield-limiting environmental constraints for staple food crops. Heat shock transcription factors (HSF) terminally regulate the plant abiotic stress responses to maintain growth and development under extreme environmental conditions. HSF genes of subclass A2 predominantly express under heat stress (HS) and activate the transcriptional cascade of defense-related genes. In this study, a highly heat-inducible HSF, HvHSFA2e was constitutively expressed in barley (Hordeum vulgare L.) to investigate its role in abiotic stress response and plant development. Transgenic barley plants displayed enhanced heat and drought tolerance in terms of increased chlorophyll content, improved membrane stability, reduced lipid peroxidation, and less accumulation of ROS in comparison to wild-type (WT) plants. Transcriptome analysis revealed that HvHSFA2e positively regulates the expression of abiotic stress-related genes encoding HSFs, HSPs, and enzymatic antioxidants, contributing to improved stress tolerance in transgenic plants. The major genes of ABA biosynthesis pathway, flavonoid, and terpene metabolism were also upregulated in transgenics. Our findings show that HvHSFA2e-mediated upregulation of heat-responsive genes, modulation in ABA and flavonoid biosynthesis pathways enhance drought and heat stress tolerance.

Sex-biased gene expression precedes sexual dimorphism in the agonadal annelid Platynereis dumerilii

Gametogenesis is the process by which germ cells differentiate into mature sperm and oocytes, cells essential for sexual reproduction. The sex-specific molecular programs that drive spermatogenesis and oogenesis can also serve as sex identification markers. Platynereis dumerilii is a research organism that has been studied in many areas of developmental biology. However investigations often disregard sex, as P. dumerilii juveniles lack sexual dimorphism. The molecular mechanisms of gametogenesis in the segmented worm P. dumerilii are also largely unknown. In this study, we used RNA sequencing to investigate the transcriptomic profiles of gametogenesis in P. dumerilii juveniles. Our analysis revealed that sex-biased gene expression becomes increasingly pronounced during the advanced developmental stages, particularly during the meiotic phases of gametogenesis. We identified conserved genes associated with spermatogenesis, such as dmrt1, and a novel gene psmt, that is associated with oogenesis. Additionally, putative long non-coding RNAs were upregulated in both male and female gametogenic programs. This study provides a foundational resource for germ cell research in P. dumerilii, markers for sex identification, and offers comparative data to enhance our understanding of the evolution of gametogenesis mechanisms across species.

ADBP-1 regulates ADR-2 nuclear localization to control editing substrate selection

Adenosine-to-inosine (A-to-I) RNA editing, catalyzed by ADAR enzymes, is a prevalent and conserved RNA modification. While A-to-I RNA editing is essential in mammals, in Caenorhabditis elegans , it is not, making them invaluable for RNA editing research. In C. elegans , ADR-2 is the sole catalytic A-to-I editing enzyme, and ADR-1 is an RNA editing regulator. ADAR localization is well-studied in humans but not well-established in C. elegans . In this study, we examine the cellular and tissue-specific localization of ADR-2. We show that while ADR-2 is present in most cells in the embryo, at later developmental stages, its expression is both tissue- and cell-type-specific. Additionally, both ADARs are mainly in the nucleus. ADR-2 is adjacent to the chromosomes during the cell cycle. We show that the nuclear localization of endogenous ADR-2 depends on ADBP-1, not ADR-1. In adbp-1 mutant worms, ADR-2 is mislocalized, while ADR-1 is not, leading to decreased editing levels and de-novo editing, mostly in exons, suggesting that ADR-2 is also functional in the cytoplasm. Besides, mutated ADBP-1 affects gene expression. Furthermore, we show that ADR-2 targets adenosines with different surrounding nucleotides in exons and introns. Our findings indicate that ADR-2 cellular localization is highly regulated and affects its function.

Maternal-fetal interfaces transcriptome changes associated with placental insufficiency and a novel gene therapy intervention

The etiology of fetal growth restriction (FGR) is multifactorial, although many cases often involve placental insufficiency. Placental insufficiency is associated with inadequate trophoblast invasion resulting in high resistance to blood flow, decreased availability of nutrients, and increased hypoxia. We have developed a non-viral, polymer-based nanoparticle that facilitates delivery and transient gene expression of human insulin-like 1 growth factor ( hIGF1 ) in placental trophoblast for the treatment of placenta insufficiency and FGR. Using the established guinea pig maternal nutrient restriction (MNR) model of placental insufficiency and FGR, the aim of the study was to identify novel pathways in the sub-placenta/decidua that provide insight into the underlying mechanism driving placental insufficiency, and may be corrected with hIGF1 nanoparticle treatment. Pregnant guinea pigs underwent ultrasound-guided sham or hIGF1 nanoparticle treatment at mid-pregnancy, and sub-placenta/decidua tissue was collected 5 days later. Transcriptome analysis was performed using RNA Sequencing on the Illumina platform. The MNR sub-placenta/decidua demonstrated fewer maternal spiral arteries lined by trophoblast, shallower trophoblast invasion and downregulation of genelists involved in the regulation of cell migration. hIGF1 nanoparticle treatment resulted in marked changes to transporter activity in the MNR + hIGF1 sub-placenta/decidua when compared to sham MNR. Under normal growth conditions however, hIGF1 nanoparticle treatment decreased genelists enriched for kinase signaling pathways and increased genelists enriched for proteolysis indicative of homeostasis. Overall, this study identified changes to the sub-placenta/decidua transcriptome that likely result in inadequate trophoblast invasion and increases our understanding of pathways that hIGF1 nanoparticle treatment acts on in order to restore or maintain appropriate placenta function.

A Regularized Bayesian Dirichlet-multinomial Regression Model for Integrating Single-cell-level Omics and Patient-level Clinical Study Data

The abundance of various cell types can vary significantly among patients with varying phenotypes and even those with the same phenotype. Recent scientific advancements provide mounting evidence that other clinical variables, such as age, gender, and lifestyle habits, can also influence the abundance of certain cell types. However, current methods for integrating single-cell-level omics data with clinical variables are inadequate. In this study, we propose a regularized Bayesian Dirichlet-multinomial regression framework to investigate the relationship between single-cell RNA sequencing data and patient-level clinical data. Additionally, the model employs a novel hierarchical tree structure to identify such relationships at different cell-type levels. Our model successfully uncovers significant associations between specific cell types and clinical variables across three distinct diseases: pulmonary fibrosis, COVID-19, and non-small cell lung cancer. This integrative analysis provides biological insights and could potentially inform clinical interventions for various diseases.

Structure-guided discovery of highly efficient cytidine deaminases with sequence-context independence

The applicability of cytosine base editors is hindered by their dependence on sequence context and by off-target effects. Here, by using AlphaFold2 to predict the three-dimensional structure of 1,483 cytidine deaminases and by experimentally characterizing representative deaminases (selected from each structural cluster after categorizing them via partitional clustering), we report the discovery of a few deaminases with high editing efficiencies, diverse editing windows and increased ratios of on-target to off-target effects. Specifically, several deaminases induced C-to-T conversions with comparable efficiency at AC/TC/CC/GC sites, the deaminases could introduce stop codons in single-copy and multi-copy genes in mammalian cells without double-strand breaks, and some residue conversions at predicted DNA-interacting sites reduced off-target effects. Structure-based generative machine learning could be further leveraged to expand the applicability of base editors in gene therapies.

The curses of performing differential expression analysis using single-cell data

Differential expression analysis is pivotal in single-cell transcriptomics for unraveling cell-type- specific responses to stimuli. While numerous methods are available to identify differentially expressed genes in single-cell data, recent evaluations of both single-cell-specific methods and methods adapted from bulk studies have revealed significant shortcomings in performance. In this paper, we dissect the four major challenges in single-cell DE analysis: normalization, excessive zeros, donor effects, and cumulative biases. These "curses" underscore the limitations and conceptual pitfalls in existing workflows. In response, we introduce a novel paradigm addressing several of these issues.

AKT2 modulates astrocytic nicotine responses in vivo

A better understanding of nicotine neurobiology is needed to reduce or prevent chronic addiction, ameliorate the detrimental effects of nicotine withdrawal, and increase successful cessation of use. Nicotine binds and activates two astrocyte-expressed nicotinic acetylcholine receptors (nAChRs), α4β2 and α7. We recently found that Protein kinase B-β (Pkb-β or Akt2) expression is restricted to astrocytes in mice and humans. To determine if AKT2 plays a role in astrocytic nicotinic responses, we generated astrocyte-specific Akt2 conditional knockout (cKO) and full Akt2 KO mice for in vivo and in vitro experiments. For in vivo studies, we examined mice exposed to chronic nicotine for two weeks in drinking water (200 μg/mL) and following acute nicotine challenge (0.09, 0.2 mg/kg) after 24 hrs. Our in vitro studies used cultured mouse astrocytes to measure nicotine-dependent astrocytic responses. We validated our approaches using lipopolysaccharide (LPS) exposure inducing astrogliosis. Sholl analysis was used to measure glial fibrillary acidic protein responses in astrocytes. Our data show that wild-type (WT) mice exhibit increased astrocyte morphological complexity during acute nicotine exposure, with decreasing complexity during chronic nicotine use, whereas Akt2 cKO mice showed increased astrocyte morphology complexity. In culture, we found that 100μM nicotine was sufficient for morphological changes and blocking α7 or α4β2 nAChRs prevented observed morphologic changes. Finally, we performed conditioned place preference (CPP) in Akt2 cKO mice and found that astrocytic AKT2 deficiency reduced nicotine preference compared to controls. These findings show the importance of nAChRs and Akt2 signaling in the astrocytic response to nicotine.

The Transpeptidase Sortase A Binds Nucleic Acids and Mediates Mammalian Cell Labeling

Wild-type sortase A is an important virulence factor displaying a diverse array of proteins on the surface of bacteria. This protein display relies on the transpeptidase activity of sortase A, which is widely engineered to allow protein ligation and protein engineering based on the interaction between sortase A and peptides. Here an unknown interaction is found between sortase A from Staphylococcus aureus and nucleic acids, in which exogenously expressed engineered sortase A binds oligonucleotides in vitro and is independent of its canonical transpeptidase activity. When incubated with mammalian cells, engineered sortase A further mediates oligonucleotide labeling to the cell surface, where sortase A attaches itself and is part of the labeled moiety. The labeling reaction can also be mediated by many classes of wild-type sortases as well. Cell surface GAG appears involved in sortase-mediated oligonucleotide cell labeling, as demonstrated by CRISPR screening. This interaction property is utilized to develop a technique called CellID to facilitate sample multiplexing for scRNA-seq and shows the potential of using sortases to label cells with diverse oligonucleotides. Together, the binding between sortase A and nucleic acids opens a new avenue to understanding the virulence of wild-type sortases and exploring the application of sortases in biotechnology.

Dysregulated alveolar epithelial cell progenitor function and identity in Hermansky-Pudlak syndrome pulmonary fibrosis

Hermansky-Pudlak syndrome (HPS) is a genetic disorder of endosomal protein trafficking associated with pulmonary fibrosis in specific subtypes, including HPS-1 and HPS-2. Single mutant HPS1 and HPS2 mice display increased fibrotic sensitivity while double mutant HPS1/2 mice exhibit spontaneous fibrosis with aging, which has been attributed to HPS mutations in alveolar epithelial type II (AT2) cells. We utilized HPS mouse models and human lung tissue to investigate mechanisms of AT2 cell dysfunction driving fibrotic remodeling in HPS. Starting at 8 weeks of age, HPS mice exhibited progressive loss of AT2 cell numbers. HPS AT2 cell was impaired ex vivo and in vivo. Incorporating AT2 cell lineage tracing in HPS mice, we observed aberrant differentiation with increased AT2-derived alveolar epithelial type I cells. Transcriptomic analysis of HPS AT2 cells revealed elevated expression of genes associated with aberrant differentiation and p53 activation. Lineage tracing and modeling studies demonstrated that HPS AT2 cells were primed to persist in a Krt8+ reprogrammed transitional state, mediated by p53 activity. Intrinsic AT2 progenitor cell dysfunction and p53 pathway dysregulation are novel mechanisms of disease in HPS-related pulmonary fibrosis, with the potential for early targeted intervention before the onset of fibrotic lung disease.

Cliffy: robust 16S rRNA classification based on a compressed LCA index

Taxonomic sequence classification is a computational problem central to the study of metagenomics and evolution. Advances in compressed indexing with the r -index enable full-text pattern matching against large sequence collections. But the data structures that link pattern sequences to their clades of origin still do not scale well to large collections. Previous work proposed the document array profiles, which use 𝒪 ( rd ) words of space where r is the number of maximal-equal letter runs in the Burrows-Wheeler transform and d is the number of distinct genomes. The linear dependence on d is limiting, since real taxonomies can easily contain 10,000s of leaves or more. We propose a method called cliff compression that reduces this size by a large factor, over 250x when indexing the SILVA 16S rRNA gene database. This method uses Θ( r log d ) words of space in expectation under a random model we propose here. We implemented these ideas in an open source tool called Cliffy that performs efficient taxonomic classification of sequencing reads with respect to a compressed taxonomic index. When applied to simulated 16S rRNA reads, Cliffy's read-level accuracy is higher than Kraken2's by 11-18%. Clade abundances are also more accurately predicted by Cliffy compared to Kraken2 and Bracken. Overall, Cliffy is a fast and space-economical extension to compressed full-text indexes, enabling them to perform fast and accurate taxonomic classification queries.

2012 ACM Subject Classification

Applied computing → Computational genomics.

Arginine methylation of SM-LIKE PROTEIN 4 antagonistically affects alternative splicing during Arabidopsis stress responses

Arabidopsis (Arabidopsis thaliana) PROTEIN ARGININE METHYLTRANSFERASE5 (PRMT5) post-translationally modifies RNA-binding proteins by arginine (R) methylation. However, the impact of this modification on the regulation of RNA processing is largely unknown. We used the spliceosome component, SM-LIKE PROTEIN 4 (LSM4), as a paradigm to study the role of R-methylation in RNA processing. We found that LSM4 regulates alternative splicing (AS) of a suite of its in vivo targets identified here. The lsm4 and prmt5 mutants show a considerable overlap of genes with altered AS raising the possibility that splicing of those genes could be regulated by PRMT5-dependent LSM4 methylation. Indeed, LSM4 methylation impacts AS, particularly of genes linked with stress response. Wild-type LSM4 and an unmethylable version complement the lsm4-1 mutant, suggesting that methylation is not critical for growth in normal environments. However, LSM4 methylation increases with abscisic acid and is necessary for plants to grow under abiotic stress. Conversely, bacterial infection reduces LSM4 methylation, and plants that express unmethylable-LSM4 are more resistant to Pseudomonas than those expressing wild-type LSM4. This tolerance correlates with decreased intron retention of immune-response genes upon infection. Taken together, this provides direct evidence that R-methylation adjusts LSM4 function on pre-mRNA splicing in an antagonistic manner in response to biotic and abiotic stress.

Regeneration in the absence of canonical neoblasts in an early branching flatworm

The remarkable regenerative abilities of flatworms are closely linked to neoblasts - adult pluripotent stem cells that are the only division-competent cell type outside of the reproductive system. Although the presence of neoblast-like cells and whole-body regeneration in other animals has led to the idea that these features may represent the ancestral metazoan state, the evolutionary origin of both remains unclear. Here we show that the catenulid Stenostomum brevipharyngium, a member of the earliest-branching flatworm lineage, lacks conventional neoblasts despite being capable of whole-body regeneration and asexual reproduction. Using a combination of single-nuclei transcriptomics, in situ gene expression analysis, and functional experiments, we find that cell divisions are not restricted to a single cell type and are associated with multiple fully differentiated somatic tissues. Furthermore, the cohort of germline multipotency genes, which are considered canonical neoblast markers, are not expressed in dividing cells, but in the germline instead, and we experimentally show that they are neither necessary for proliferation nor regeneration. Overall, our results challenge the notion that canonical neoblasts are necessary for flatworm regeneration and open up the possibility that neoblast-like cells may have evolved convergently in different animals, independent of their regenerative capacity.

Causal network perturbation analysis identifies known and novel type-2 diabetes driver genes

The molecular pathogenesis of diabetes is multifactorial, involving genetic predisposition and environmental factors that are not yet fully understood. However, pancreatic β-cell failure remains among the primary reasons underlying the progression of type-2 diabetes (T2D) making targeting β-cell dysfunction an attractive pathway for diabetes treatment. To identify genetic contributors to β-cell dysfunction, we investigated single-cell gene expression changes in β-cells from healthy (C57BL/6J) and diabetic (NZO/HlLtJ) mice fed with normal or high-fat, high-sugar diet (HFHS). Our study presents an innovative integration of the causal network perturbation assessment (ssNPA) framework with meta-cell transcriptome analysis to explore the genetic underpinnings of type-2 diabetes (T2D). By generating a reference causal network and in silico perturbation, we identified novel genes implicated in T2D and validated our candidates using the Knockout Mouse Phenotyping (KOMP) Project database.

The E3 ubiquitin-protein ligase UHRF1 promotes adipogenesis and limits fibrosis by suppressing GPNMB-mediated TGF-β signaling

The E3 ubiquitin-ligase UHRF1 is an epigenetic regulator coordinating DNA methylation and histone modifications. However, little is known about how it regulates adipogenesis or metabolism. In this study, we discovered that UHRF1 is a key regulatory factor for adipogenesis, and we identified the altered molecular pathways that UHRF1 targets. Using CRISPR/Cas9-based knockout strategies, we discovered the whole transcriptomic changes upon UHRF1 deletion. Bioinformatics analyses revealed that key adipogenesis regulators such PPAR-γ and C/EBP-α were suppressed, whereas TGF-β signaling and fibrosis markers were upregulated in UHRF1-depleted differentiating adipocytes. Furthermore, UHRF1-depleted cells showed upregulated expression and secretion of TGF-β1, as well as the glycoprotein GPNMB. Treating differentiating preadipocytes with recombinant GPNMB led to an increase in TGF-β protein and secretion levels, which was accompanied by an increase in secretion of fibrosis markers such as MMP13 and a reduction in adipogenic conversion potential. Conversely, UHRF1 overexpression studies in human cells demonstrated downregulated levels of GPNMB and TGF-β, and enhanced adipogenic potential. In conclusion, our data show that UHRF1 positively regulates 3T3-L1 adipogenesis and limits fibrosis by suppressing GPNMB and TGF-β signaling cascade, highlighting the potential relevance of UHRF1 and its targets to the clinical management of obesity and linked metabolic disorders.

Loss of dihydroceramide desaturase drives neurodegeneration by disrupting endoplasmic reticulum and lipid droplet homeostasis in glial cells

Dihydroceramide desaturases convert dihydroceramides to ceramides, the precursors of all complex sphingolipids. Reduction of DEGS1 dihydroceramide desaturase function causes pediatric neurodegenerative disorder hypomyelinating leukodystrophy-18 (HLD-18). We discovered that infertile crescent (ifc), the Drosophila DEGS1 homolog, is expressed primarily in glial cells to promote CNS development by guarding against neurodegeneration. Loss of ifc causes massive dihydroceramide accumulation and severe morphological defects in cortex glia, including endoplasmic reticulum (ER) expansion, failure of neuronal ensheathment, and lipid droplet depletion. RNAi knockdown of the upstream ceramide synthase schlank in glia of ifc mutants rescues ER expansion, suggesting dihydroceramide accumulation in the ER drives this phenotype. RNAi knockdown of ifc in glia but not neurons drives neuronal cell death, suggesting that ifc function in glia promotes neuronal survival. Our work identifies glia as the primary site of disease progression in HLD-18 and may inform on juvenile forms of ALS, which also feature elevated dihydroceramide levels.

Analyzing RNA-Seq Data from Chlamydia with Super Broad Transcriptomic Activation: Challenges, Solutions, and Implications for Other Systems

Motivation

RNA sequencing (RNA-Seq) offers profound insights into the complex transcriptomes of diverse biological systems. However, standard differential expression analysis pipelines based on DESeq2 and edgeR encounter challenges when applied to the immediate early transcriptomes of Chlamydia spp., obligate intracellular bacteria. These challenges arise from their reliance on assumptions that do not hold in scenarios characterized by extensive transcriptomic activation and limited repression. Standard analyses using unique chlamydial RNA-Seq reads alone identify nearly 300 upregulated and about 300 downregulated genes, significantly deviating from actual RNA-Seq read trends.

Results

By incorporating both chlamydial and host reads or adjusting for total sequencing depth, the revised normalization methods each detected over 700 upregulated genes and 30 or fewer downregulated genes, closely aligned with observed RNA-Seq data. Further validation through qRT-PCR analysis confirmed the effectiveness of these adjusted approaches in capturing the true extent of transcriptomic activation during the immediate early phase of chlamydial infection. While the strategies employed are developed in the context of Chlamydia, the principles of flexible and context-aware normalization may inform adjustments in other systems with unbalanced gene expression dynamics, such as bacterial spore germination.

Availability and implementation

The code for reproducing the presented bioinformatic analysis is available at https://zenodo.org/records/11201379.

H2A.Z chaperones converge on E2F target genes for melanoma cell proliferation

High levels of H2A.Z promote melanoma cell proliferation and correlate with poor prognosis. However, the role of the two distinct H2A.Z histone chaperone complexes SRCAP and P400-TIP60 in melanoma remains unclear. Here, we show that individual subunit depletion of SRCAP, P400, and VPS72 (YL1) results in not only the loss of H2A.Z deposition into chromatin but also a reduction of H4 acetylation in melanoma cells. This loss of H4 acetylation is particularly found at the promoters of cell cycle genes directly bound by H2A.Z and its chaperones, suggesting a coordinated regulation between H2A.Z deposition and H4 acetylation to promote their expression. Knockdown of each of the three subunits downregulates E2F1 and its targets, resulting in a cell cycle arrest akin to H2A.Z depletion. However, unlike H2A.Z deficiency, loss of the shared H2A.Z chaperone subunit YL1 induces apoptosis. Furthermore, YL1 is overexpressed in melanoma tissues, and its upregulation is associated with poor patient outcome. Together, these findings provide a rationale for future targeting of H2A.Z chaperones as an epigenetic strategy for melanoma treatment.

Strategies for effectively modelling promoter-driven gene expression using transfer learning

The ability to deliver genetic cargo to human cells is enabling rapid progress in molecular medicine, but designing this cargo for precise expression in specific cell types is a major challenge. Expression is driven by regulatory DNA sequences within short synthetic promoters, but relatively few of these promoters are cell-type-specific. The ability to design cell-type-specific promoters using model-based optimization would be impactful for research and therapeutic applications. However, models of expression from short synthetic promoters (promoter-driven expression) are lacking for most cell types due to insufficient training data in those cell types. Although there are many large datasets of both endogenous expression and promoter-driven expression in other cell types, which provide information that could be used for transfer learning, transfer strategies remain largely unexplored for predicting promoter-driven expression. Here, we propose a variety of pretraining tasks, transfer strategies, and model architectures for modelling promoter-driven expression. To thoroughly evaluate various methods, we propose two benchmarks that reflect data-constrained and large dataset settings. In the data-constrained setting, we find that pretraining followed by transfer learning is highly effective, improving performance by 24-27%. In the large dataset setting, transfer learning leads to more modest gains, improving performance by up to 2%. We also propose the best architecture to model promoter-driven expression when training from scratch. The methods we identify are broadly applicable for modelling promoter-driven expression in understudied cell types, and our findings will guide the choice of models that are best suited to designing promoters for gene delivery applications using model-based optimization. Our code and data are available at https://github.com/anikethjr/promoter_models.

H3F3A K27M Mutations Drives a Repressive Transcriptome by Modulating Chromatin Accessibility, Independent of H3K27me3 in Diffuse Midline Glioma

Background

Heterozygous histone H3.3K27M mutation is a primary oncogenic driver of Diffuse Midline Glioma (DMG). H3.3K27M inhibits the Polycomb Repressive Complex 2 (PRC2) methyltransferase complex, leading to a global reduction and redistributing of the repressive H3 lysine 27 tri-methylation. This rewiring of the epigenome is thought to promote gliomagenesis.

Methods

We established novel, isogenic DMG patient-derived cell lines that have been CRISPR-Cas9 edited to H3.3 WT or H3.3K27M alone and in combination with EZH2 and EZH1 co-deletion, inactivating PRC2 methyltransferase activity of PRC2 and eliminating H3K27me3.

Results

RNA-seq and ATAC-seq analysis of these cells revealed that K27M has a novel epigenetic effect that appears entirely independent of its effects on PRC2 function. While the loss of the PRC2 complex led to a systemic induction of gene expression (including HOX gene clusters) and upregulation of biological pathways, K27M led to a balanced gene deregulation but having an overall repressive effect on the biological pathways. Importantly, the genes uniquely deregulated by the K27M mutation, independent of methylation loss, are closely associated with changes in chromatin accessibility, with upregulated genes becoming more accessible. Notably, the PRC2- independent function of K27M appears necessary for tumorigenesis as xenografts of our H3.3K27M/EZH1/2 WT cells developed into tumors, while H3.3/EZH1/2 KO cells did not.

Conclusion

We demonstrate that K27M mutation alters chromatin accessibility and uniquely deregulates genes, independent of K27 methylation. We further show the mutation's role in altering biological pathways and its necessity for tumor development.

Key Points

We revealed genes regulated by H3.3K27M mutation and PRC2 in DMG.H3.3K27M mutation alters chromosome accessibility independent of H3K27me3.PRC2-independent effects of K27M mutation are crucial for tumor development.

Importance of the Study

This study is the first to demonstrate that H3F3A K27M mutations drive a repressive transcriptome by modulating chromatin accessibility independently of H3K27 trimethylation in Diffuse Midline Glioma (DMG). By isolating the effects of H3.3 K27me3 loss from those of the K27M mutation, we identified common and unique genes and pathways affected by each. We found that genes uniquely deregulated by K27M showed increased chromatin accessibility and upregulated gene expression, unlike other gene subsets affected by PRC2 knockout. Importantly, we determined the PRC2-independent function of K27M is also essential for tumorigenesis, as xenografts of H3.3 K27M/PRC2 WT cell lines formed tumors, while H3.3WT/PRC2 WT and K27M/PRC2 knockout cells did not. This research builds upon and advances prior studies, such as those identifying EZH2 as a therapeutic target in H3.3K27M DMGs, by revealing critical new pathways for gliomagenesis. The translational significance lies in identifying novel therapeutic targets against this aggressive pediatric cancer.

Cell type-specific gene expression dynamics during human brain maturation

The human brain undergoes protracted post-natal maturation, guided by dynamic changes in gene expression. Most studies exploring these processes have used bulk tissue analyses, which mask cell type-specific gene expression dynamics. Here, using single nucleus (sn)RNA-seq on temporal lobe tissue, including samples of African ancestry, we build a joint paediatric and adult atlas of 75 cell subtypes, which we verify with spatial transcriptomics. We explore the differences between paediatric and adult cell types, revealing the genes and pathways that change during brain maturation. Our results highlight excitatory neuron subtypes, including the LTK and FREM subtypes, that show elevated expression of genes associated with cognition and synaptic plasticity in paediatric tissue. The new resources we present here improve our understanding of the brain during its development and contribute to global efforts to build an inclusive brain cell map.

ZNF143 binds DNA and stimulates transcripstion initiation to activate and repress direct target genes

Transcription factors bind to sequence motifs and act as activators or repressors. Transcription factors interface with a constellation of accessory cofactors to regulate distinct mechanistic steps to regulate transcription. We rapidly degraded the essential and ubiquitously expressed transcription factor ZNF143 to determine its function in the transcription cycle. ZNF143 facilitates RNA Polymerase initiation and activates gene expression. ZNF143 binds the promoter of nearly all its activated target genes. ZNF143 also binds near the site of genic transcription initiation to directly repress a subset of genes. Although ZNF143 stimulates initiation at ZNF143-repressed genes (i.e. those that increase expression upon ZNF143 depletion), the molecular context of binding leads to cis repression. ZNF143 competes with other more efficient activators for promoter access, physically occludes transcription initiation sites and promoter-proximal sequence elements, and acts as a molecular roadblock to RNA Polymerases during early elongation. The term context specific is often invoked to describe transcription factors that have both activation and repression functions. We define the context and molecular mechanisms of ZNF143-mediated cis activation and repression.

Design, synthesis and cellular characterization of a new class of IPMK kinase inhibitors

Many genetic studies have established the kinase activity of inositol phosphate multikinase (IPMK) is required for the synthesis of higher-order inositol phosphate signaling molecules, the regulation of gene expression and control of the cell cycle. These genetic studies await orthogonal validation by specific IPMK inhibitors, but no such inhibitors have been synthesized. Here, we report complete chemical synthesis, cellular characterization, structure-activity relationships and rodent pharmacokinetics of a novel series of highly potent IPMK inhibitors. The first-generation compound 1 (UNC7437) decreased cellular proliferation and tritiated inositol phosphate levels in metabolically labeled human U251-MG glioblastoma cells. Compound 1 also regulated the transcriptome of these cells, selectively regulating genes that are enriched in cancer, inflammatory and viral infection pathways. Further optimization of compound 1 eventually led to compound 15 (UNC9750), which showed improved potency and pharmacokinetics in rodents. Compound 15 specifically inhibited cellular accumulation of InsP 5 , a direct product of IPMK kinase activity, while having no effect on InsP 6 levels, revealing a novel metabolic signature detected for the first time by rapid chemical attenuation of cellular IPMK activity. These studies designed, optimized and synthesized a new series of IPMK inhibitors, which reduces glioblastoma cell growth, induces a novel InsP 5 metabolic signature, and reveals novel aspects inositol phosphate cellular metabolism and signaling.

Impact of tRNA-induced proline-to-serine mistranslation on the transcriptome of Drosophila melanogaster

Mistranslation is the misincorporation of an amino acid into a polypeptide. Mistranslation has diverse effects on multicellular eukaryotes and is implicated in several human diseases. In Drosophila melanogaster, a serine transfer RNA (tRNA) that misincorporates serine at proline codons (P→S) affects male and female flies differently. The mechanisms behind this discrepancy are currently unknown. Here, we compare the transcriptional response of male and female flies to P→S mistranslation to identify genes and cellular processes that underlie sex-specific differences. Both males and females downregulate genes associated with various metabolic processes in response to P→S mistranslation. Males downregulate genes associated with extracellular matrix organization and response to negative stimuli such as wounding, whereas females downregulate aerobic respiration and ATP synthesis genes. Both sexes upregulate genes associated with gametogenesis, but females also upregulate cell cycle and DNA repair genes. These observed differences in the transcriptional response of male and female flies to P→S mistranslation have important implications for the sex-specific impact of mistranslation on disease and tRNA therapeutics.

Integrated de novo transcriptome of Culex pipiens mosquito larvae as a resource for genetic control strategies

We present a de novo transcriptome of the mosquito vector Culex pipiens, assembled by sequences of susceptible and insecticide resistant larvae. The high quality of the assembly was confirmed by TransRate and BUSCO. A mapping percentage until 94.8% was obtained by aligning contigs to Nr, SwissProt, and TrEMBL, with 27,281 sequences that simultaneously mapped on the three databases. A total of 14,966 ORFs were also functionally annotated by using the eggNOG database. Among them, we identified ORF sequences of the main gene families involved in insecticide resistance. Therefore, this resource stands as a valuable reference for further studies of differential gene expression as well as to identify genes of interest for genetic-based control tools.

The DNA loop release factor WAPL suppresses Epstein-Barr virus latent membrane protein expression to maintain the highly restricted latency I program

Epstein-Barr virus (EBV) uses latency programs to colonize the memory B-cell reservoir, and each program is associated with human malignancies. However, knowledge remains incomplete of epigenetic mechanisms that maintain the highly restricted latency I program, present in memory and Burkitt lymphoma cells, in which EBNA1 is the only EBV-encoded protein expressed. Given increasing appreciation that higher order chromatin architecture is an important determinant of viral and host gene expression, we investigated roles of Wings Apart-Like Protein Homolog (WAPL), a host factor that unloads cohesins to control DNA loop size and that was discovered as an EBNA2-associated protein. WAPL knockout (KO) in Burkitt cells de-repressed LMP1 and LMP2A expression but not other EBV oncogenes to yield a viral program reminiscent of EBV latency II, which is rarely observed in B-cells. WAPL KO also increased LMP1/2A levels in latency III lymphoblastoid cells. WAPL KO altered EBV genome architecture, triggering formation of DNA loops between the LMP promoter region and the EBV origins of lytic replication (oriLyt). Hi-C analysis further demonstrated that WAPL KO reprograms EBV genomic DNA looping. LMP1 and LMP2A de-repression correlated with decreased histone repressive marks at their promoters. We propose that EBV coopts WAPL to negatively regulate latent membrane protein expression to maintain Burkitt latency I.

Author Summary

EBV is a highly prevalent herpesvirus etiologically linked to multiple lymphomas, gastric and nasopharyngeal carcinomas, and multiple sclerosis. EBV persists in the human host in B-cells that express a series of latency programs, each of which is observed in a distinct type of human lymphoma. The most restricted form of EBV latency, called latency I, is observed in memory cells and in most Burkitt lymphomas. In this state, EBNA1 is the only EBV-encoded protein expressed to facilitate infected cell immunoevasion. However, epigenetic mechanisms that repress expression of the other eight EBV-encoded latency proteins remain to be fully elucidated. We hypothesized that the host factor WAPL might have a role in restriction of EBV genes, as it is a major regulator of long-range DNA interactions by negatively regulating cohesin proteins that stabilize DNA loops, and WAPL was found in a yeast 2-hybrid screen for EBNA2-interacting host factors. Using CRISPR together with Hi-ChIP and Hi-C DNA architecture analyses, we uncovered WAPL roles in suppressing expression of LMP1 and LMP2A, which mimic signaling by CD40 and B-cell immunoglobulin receptors, respectively. These proteins are expressed together with EBNA1 in the latency II program. We demonstrate that WAPL KO changes EBV genomic architecture, including allowing the formation of DNA loops between the oriLyt enhancers and the LMP promoter regions. Collectively, our study suggests that WAPL reinforces Burkitt latency I by preventing the formation of DNA loops that may instead support the latency II program.

Genome-wide characterization and comparison of endogenous retroviruses among 3 duck reference genomes

Endogenous retroviruses (ERV) are viral genomes integrated into the host genome and can be stably inherited. Although ERV sequences have been reported in some avian species' genome, the duck endogenous retroviruses (DERV) genome has yet to be quantified. This study aimed to identify ERV sequences and characterize genes near ERVs in the duck genome by utilizing LTRhavest and LTRdigest tools to forecast the duck genome and analyze the distribution of ERV copies. The results revealed 1,607, 2,031, and 1,908 full-length ERV copies in the Pekin duck (ZJU1.0), Mallard (CAU_wild_1.0), and Shaoxing duck (CAU_laying_1.0) genomes, respectively, with average lengths of 7,046, 7,027, and 6,945 bp. ERVs are mainly distributed on the 1, 2, and sex chromosomes. Phylogenetic analysis demonstrated the presence of Betaretrovirus in 3 duck genomes, whereas Alpharetrovirus was exclusively identified in the Shaoxing duck genome. Through screening, 596, 315, and 343 genes adjacent to ERV were identified in 3 duck genomes, respectively, and their functions of ERV neighboring genes were predicted. Functional enrichment analysis of ERV-adjacent genes revealed enrichment for Focal adhesion, Calcium signaling pathway, and Adherens junction in 3 duck genomes. The overlapped genes were highly expressed in 8 tissues (brain, fat, heart, kidney, liver, lung, skin, and spleen) of 8-wk-old Mallard, revealing their important expression in different tissues. Our study provides a new perspective for understanding the quantity and function of DERVs, and may also provide important clues for regulating nearby genes and affecting the traits of organisms.

The impact of exercise on gene regulation in association with complex trait genetics

Endurance exercise training is known to reduce risk for a range of complex diseases. However, the molecular basis of this effect has been challenging to study and largely restricted to analyses of either few or easily biopsied tissues. Extensive transcriptome data collected across 15 tissues during exercise training in rats as part of the Molecular Transducers of Physical Activity Consortium has provided a unique opportunity to clarify how exercise can affect tissue-specific gene expression and further suggest how exercise adaptation may impact complex disease-associated genes. To build this map, we integrate this multi-tissue atlas of gene expression changes with gene-disease targets, genetic regulation of expression, and trait relationship data in humans. Consensus from multiple approaches prioritizes specific tissues and genes where endurance exercise impacts disease-relevant gene expression. Specifically, we identify a total of 5523 trait-tissue-gene triplets to serve as a valuable starting point for future investigations [Exercise; Transcription; Human Phenotypic Variation].

IPMK regulates HDAC3 activity and histone H4 acetylation in human cells

Histone deacetylases (HDACs) repress transcription by catalyzing the removal of acetyl groups from histones. Class 1 HDACs are activated by inositol phosphate signaling molecules in vitro , but it is unclear if this regulation occurs in human cells. Inositol Polyphosphate Multikinase (IPMK) is required for production of inositol hexakisphosphate (IP6), pentakisphosphate (IP5) and certain tetrakisphosphate (IP4) species, all known activators of Class 1 HDACs in vitro . Here, we generated IPMK knockout (IKO) human U251 glioblastoma cells, which decreased cellular inositol phosphate levels and increased histone H4-acetylation by mass spectrometry. ChIP-seq showed IKO increased H4-acetylation at IKO-upregulated genes, but H4-acetylation was unchanged at IKO-downregulated genes, suggesting gene-specific responses to IPMK knockout. HDAC deacetylase enzyme activity was decreased in HDAC3 immunoprecipitates from IKO vs . wild-type cells, while deacetylase activity of other Class 1 HDACs had no detectable changes in activity. Wild-type IPMK expression in IKO cells fully rescued HDAC3 deacetylase activity, while kinase-dead IPMK expression had no effect. Further, the deficiency in HDAC3 activity in immunoprecipitates from IKO cells could be fully rescued by addition of synthesized IP4 (Ins(1,4,5,6)P4) to the enzyme assay, while control inositol had no effect. These data suggest that cellular IPMK-dependent inositol phosphates are required for full HDAC3 enzyme activity and proper histone H4-acetylation. Implications for targeting IPMK in HDAC3-dependent diseases are discussed.

An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs

Neuroblastoma is a common pediatric cancer, where preclinical studies suggest that a mesenchymal-like gene expression program contributes to chemotherapy resistance. However, clinical outcomes remain poor, implying we need a better understanding of the relationship between patient tumor heterogeneity and preclinical models. Here, we generated single-cell RNA-seq maps of neuroblastoma cell lines, patient-derived xenograft models (PDX), and a genetically engineered mouse model (GEMM). We developed an unsupervised machine learning approach ('automatic consensus nonnegative matrix factorization' (acNMF)) to compare the gene expression programs found in preclinical models to a large cohort of patient tumors. We confirmed a weakly expressed, mesenchymal-like program in otherwise adrenergic cancer cells in some pre-treated high-risk patient tumors, but this appears distinct from the presumptive drug-resistance mesenchymal programs evident in cell lines. Surprisingly however, this weak-mesenchymal-like program was maintained in PDX and could be chemotherapy-induced in our GEMM after only 24 hours, suggesting an uncharacterized therapy-escape mechanism. Collectively, our findings improve the understanding of how neuroblastoma patient tumor heterogeneity is reflected in preclinical models, provides a comprehensive integrated resource, and a generalizable set of computational methodologies for the joint analysis of clinical and pre-clinical single-cell RNA-seq datasets.

Preclinical Multi-Omic Assessment of Pioglitazone in Skeletal Muscles of Mice Implanted with Human HER2/neu Overexpressing Breast Cancer Xenografts

Breast cancer (BC) is the most prevalent cancer worldwide and is accompanied by fatigue during both active disease and remission in the majority of cases. Our lab has measured fatigue in isolated muscles from treatment-naive BC patient-derived orthotopic xenograft (BC-PDOX) mice. Here, we conducted a preclinical trial of pioglitazone in BC-PDOX mice to determine its efficacy in ameliorating BC-induced muscle fatigue, as well as its effects on transcriptomic, metabolomic, and lipidomic profiles in skeletal muscle.

Methods

The pioglitazone and vehicle groups were treated orally for 4 weeks upon reaching a tumor volume of 600 mm3. Whole-animal indirect calorimetry was used to evaluate systemic metabolic states. The transcriptome was profiled using short-read bulk RNA sequencing (RNA-seq). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to profile the metabolome and lipidome. Fast and slow skeletal muscle function were evaluated using isolated ex vivo testing.

Results

Pioglitazone was associated with a significant overall decrease in metabolic rate, with no changes in substrate utilization. RNA-seq supported the downstream effects of pioglitazone on target genes and displayed considerable upregulation of mitochondrial bioenergetic pathways. Skeletal muscle metabolomic and lipidomic profiles exhibited dysregulation in response to BC, which was partially restored in pioglitazone-treated mice compared to vehicle-treated BC-PDOX mice. Despite molecular support for pioglitazone's efficacy, isolated muscle function was not affected by pioglitazone treatment.

Conclusions

BC induces multi-omic dysregulation in skeletal muscle, which pioglitazone partially ameliorates. Future research should focus on profiling systemic metabolic dysfunction, identifying molecular biomarkers of fatigue, and testing alternative pioglitazone treatment regimens.

Stochastic modelling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones

Cancer progression is an evolutionary process driven by the selection of cells adapted to gain growth advantage. We present the first formal study on the adaptation of gene expression in subclonal evolution. We model evolutionary changes in gene expression as stochastic Ornstein-Uhlenbeck processes, jointly leveraging the evolutionary history of subclones and single-cell expression data. Applying our model to sublines derived from single cells of a mouse melanoma revealed that sublines with distinct phenotypes are underlined by different patterns of gene expression adaptation, indicating non-genetic mechanisms of cancer evolution. Interestingly, sublines previously observed to be resistant to anti-CTLA-4 treatment showed adaptive expression of genes related to invasion and non-canonical Wnt signaling, whereas sublines that responded to treatment showed adaptive expression of genes related to proliferation and canonical Wnt signaling. Our results suggest that clonal phenotypes emerge as the result of specific adaptivity patterns of gene expression.

A Membrane Lipid Signature Unravels the Dynamic Landscape of Group 1 ILCs

In an era where the established lines between cell identities are blurred by intra-lineage plasticity, distinguishing between stable and transitional states becomes imperative. This challenge is particularly pronounced within the Group 1 ILC lineage, where the similarity and plasticity between NK cells and ILC1s obscure their classification and the assignment of their unique contributions to immune regulation. This study exploits the unique property of Asialo-GM1 (AsGM1)-a membrane lipid associated with cytotoxic attributes absent in ILC1s-as a definitive criterion to distinguish between these cells. By prioritizing cytotoxic potential as the cardinal differentiator, our strategic use of the AsGM1 signature achieved precise delineation of NK cells and ILC1s across tissues, validated by RNA-seq analysis. This capability extends beyond steady-state classifications, adeptly capturing the binary classification of NK cells and ILC1s during acute liver injury. By leveraging two established models of NK-to-ILC1 plasticity driven by TGFβ and Toxoplasma gondii , we demonstrate the stability of the AsGM1 signature, which sharply contrasts with the loss of Eomes. This signature identified a spectrum of known and novel NK cell derivatives-ILC1-like entities that bridge traditional binary classifications in aging and infection. The early detection of the AsGM1 signature at the immature NK (iNK) stage, preceding Eomes, and its stability, unaffected by transcriptional reprogramming that typically alters Eomes, position AsGM1 as a unique, site-agnostic marker for fate mapping NK-to-ILC1 plasticity. This provides a powerful tool to explore the expanding heterogeneity within the Group 1 ILC landscape, effectively transcending the ambiguity inherent to the NK-to-ILC1 continuum.

Computational analysis of peripheral blood RNA sequencing data unravels disrupted immune patterns in Alzheimer's disease

The central nervous system (CNS) and the immune system collectively coordinate cellular functionalities, sharing common developmental mechanisms. Immunity-related molecules exert an influence on brain development, challenging the conventional view of the brain as immune-privileged. Chronic inflammation emerges as a key player in the pathophysiology of Alzheimer's disease (AD), with increased stress contributing to the disease progression and potentially exacerbating existing symptoms. In this study, the most significant gene signatures from selected RNA-sequencing (RNA-seq) data from AD patients and healthy individuals were obtained and a functional analysis and biological interpretation was conducted, including network and pathway enrichment analysis. Important evidence was reported, such as enrichment in immune system responses and antigen processes, as well as positive regulation of T-cell mediated cytotoxicity and endogenous and exogenous peptide antigen, thus indicating neuroinflammation and immune response participation in disease progression. These findings suggest a disturbance in the immune infiltration of the peripheral immune environment, providing new challenges to explore key biological processes from a molecular perspective that strongly participate in AD development.

Multiple factors and features dictate the selective production of ct-siRNA in Arabidopsis

Coding transcript-derived siRNAs (ct-siRNAs) produced from specific endogenous loci can suppress the translation of their source genes to balance plant growth and stress response. In this study, we generated Arabidopsis mutants with deficiencies in RNA decay and/or post-transcriptional gene silencing (PTGS) pathways and performed comparative sRNA-seq analysis, revealing that multiple RNA decay and PTGS factors impede the ct-siRNA selective production. Genes that produce ct-siRNAs often show increased or unchanged expression and typically have higher GC content in sequence composition. The growth and development of plants can perturb the dynamic accumulation of ct-siRNAs from different gene loci. Two nitrate reductase genes, NIA1 and NIA2, produce massive amounts of 22-nt ct-siRNAs and are highly expressed in a subtype of mesophyll cells where DCL2 exhibits higher expression relative to DCL4, suggesting a potential role of cell-specific expression of ct-siRNAs. Overall, our findings unveil the multifaceted factors and features involved in the selective production and regulation of ct-siRNAs and enrich our understanding of gene silencing process in plants.

Robust differential expression testing for single-cell CRISPR screens at low multiplicity of infection

Single-cell CRISPR screens (perturb-seq) link genetic perturbations to phenotypic changes in individual cells. The most fundamental task in perturb-seq analysis is to test for association between a perturbation and a count outcome, such as gene expression. We conduct the first-ever comprehensive benchmarking study of association testing methods for low multiplicity-of-infection (MOI) perturb-seq data, finding that existing methods produce excess false positives. We conduct an extensive empirical investigation of the data, identifying three core analysis challenges: sparsity, confounding, and model misspecification. Finally, we develop an association testing method - SCEPTRE low-MOI - that resolves these analysis challenges and demonstrates improved calibration and power.

AutoGDC: A Python Package for DNA Methylation and Transcription Meta-Analyses

Motivation

0.1The Genomic Data Commons is a powerful resource which facilitates the exploration of molecular alterations across various diseases. However, utilizing this resource for meta-analysis requires many different tools to query, download, organize, and analyze the data. In order to facilitate a more rapid, simple means of analyzing DNA methylation and RNA sequencing datasets from the GDC we developed autogdc, a python package that integrates data curation and preprocessing with meta-analysis functionality into one simplified bioinformatic pipeline.

Availability and Implementation

0.2The autogdc python package is available under the GPLv3 license at along with several examples of typical use-case scenarios in the form of a jupyter notebook. The data is all originally provided by the GDC, and is therefore available under the NIH Genomic Data Sharing (GDS) and NCI GDS policies.

Spatial Coding Dysfunction and Network Instability in the Aging Medial Entorhinal Cortex

Across species, spatial memory declines with age, possibly reflecting altered hippocampal and medial entorhinal cortex (MEC) function. However, the integrity of cellular and network-level spatial coding in aged MEC is unknown. Here, we leveraged in vivo electrophysiology to assess MEC function in young, middle-aged, and aged mice navigating virtual environments. In aged grid cells, we observed impaired stabilization of context-specific spatial firing, correlated with spatial memory deficits. Additionally, aged grid networks shifted firing patterns often but with poor alignment to context changes. Aged spatial firing was also unstable in an unchanging environment. In these same mice, we identified 458 genes differentially expressed with age in MEC, 61 of which had expression correlated with spatial firing stability. These genes were enriched among interneurons and related to synaptic transmission. Together, these findings identify coordinated transcriptomic, cellular, and network changes in MEC implicated in impaired spatial memory in aging.