Ensembl 2020

Prediction of protein subcellular localization in single cells

The subcellular localization of a protein is important for its function, and its mislocalization is linked to numerous diseases. Existing datasets capture limited pairs of proteins and cell lines, and existing protein localization prediction models either miss cell-type specificity or cannot generalize to unseen proteins. Here we present a method for Prediction of Unseen Proteins' Subcellular localization (PUPS). PUPS combines a protein language model and an image inpainting model to utilize both protein sequence and cellular images. We demonstrate that the protein sequence input enables generalization to unseen proteins, and the cellular image input captures single-cell variability, enabling cell-type-specific predictions. Experimental validation shows that PUPS can predict protein localization in newly performed experiments outside the Human Protein Atlas used for training. Collectively, PUPS provides a framework for predicting differential protein localization across cell lines and single cells within a cell line, including changes in protein localization driven by mutations.

Mitochondrial calcium signaling regulates branched-chain amino acid catabolism in fibrolamellar carcinoma

Metabolic adaptations are essential for survival. The mitochondrial calcium uniporter plays a key role in coordinating metabolic homeostasis by regulating mitochondrial metabolic pathways and calcium signaling. However, a comprehensive analysis of uniporter-regulated mitochondrial pathways has remained unexplored. Here, we investigate consequences of uniporter loss and gain of function using uniporter knockout cells and fibrolamellar carcinoma (FLC), which we demonstrate to have elevated mitochondrial calcium levels. We find that branched-chain amino acid (BCAA) catabolism and the urea cycle are uniporter-regulated pathways. Reduced uniporter function boosts expression of BCAA catabolism genes and the urea cycle enzyme ornithine transcarbamylase. In contrast, high uniporter activity in FLC suppresses their expression. This suppression is mediated by the transcription factor KLF15, a master regulator of liver metabolism. Thus, the uniporter plays a central role in FLC-associated metabolic changes, including hyperammonemia. Our study identifies an important role for the uniporter in metabolic adaptation through transcriptional regulation of metabolism and elucidates its importance for BCAA and ammonia metabolism.

Transcriptome-Wide Analysis of Brain Cancer Initiated by Polarity Disruption in Drosophila Type II Neuroblasts

Brain tumors, in particular gliomas and glioblastoma multiforme (GBM), are thought to originate from different cells facing specific founding insults, a feature that partly justifies the complexity and heterogeneity of these severe forms of cancer. However, gliomas and GBM are usually reproduced in animal models by inducing molecular alterations in mature glial cells, which, though being part of the puzzle, do not represent the whole picture. To fill this conceptual gap, we previously developed a neurogenic model of brain cancer in Drosophila, demonstrating that the loss of cell polarity in neural stem cells (called neuroblasts in the fruit fly) is sufficient to promote the formation of malignant masses that continue to grow in the adult, displaying several phenotypic traits typical of human GBM. Here, we expand on previous work by restricting polarity disruption to Drosophila type II neuroblasts, whose self-renewal is comparable to that of mammalian neural progenitors, with the aim to capture the molecular signature of the resulting cancers in a specific and reproducible context. A comparison of the most deregulated transcripts with those found in human primary GBMs confirmed that our model can be proficiently used to delve into the roots of human brain tumorigenesis.

The effect of visfatin on the transcriptomic profile of porcine anterior pituitary cells during periimplantation period

Females' reproductive capacity is closely related to the actual metabolic status of the organism. The pituitary, an element of the regulatory hypothalamic-pituitary-ovarian axis, is one of the most important endocrine glands regulating reproductive system activity. Undisturbed functioning of pituitary ensures the regular course of pregnancy through, among others, the modulation of steroid hormones production, which is critical in the early stages of gestation. Visfatin, a hormone belonging to the adipokines family, may belong to a group of factors regulating the reproductive functions in response to the female's metabolic status. Herein we verified the hypothesis assuming a modulatory effect of visfatin on the porcine anterior pituitary transcriptome on days 15 to 16 of gestation (beginning of implantation). RNA-seq analysis of the porcine anterior pituitary cells revealed changes in the expression of 203 genes (121 up-regulated and 82 down-regulated, when compared to the non-treated controls), assigned to 325 gene ontology terms. The presence of visfatin affected the frequency of alternative splicing events (194 cases), as well as long noncoding RNA expression (64 cases). Visfatin expression and the occurrence of alternative splicing events of genes that are responsible, directly or indirectly, for regulation of the secretory functions of the pituitary, including those critical for reproductive functions suggests that the adipokine may be a key agent in ensuring the appropriate hormonal milieu during the peri-implantation period.

Genomic and transcriptomic landscapes of metastatic neuroendocrine neoplasms from distinct primary sites and their clinical implications

Neuroendocrine neoplasms (NENs) encompass a highly heterogeneous group of neoplasms with varying prognoses and molecular alterations. Molecular profiling studies have furthered our understanding of NENs, but the majority of previous studies have focused on primary tumors and on mutational landscapes using DNA sequencing data. Here, we describe the genomic and transcriptomic landscapes of 28 metastatic NENs across different primary anatomical sites (PASs) and their potential clinical implications. Although our cohort is small, our analyses provide further insights on the molecular commonalities and distinctions between metastatic NENs of different PASs. Comparison to several reference transcriptome data sets revealed that despite considerable whole genome and transcriptome variability in NENs, the metastatic NENs are still more like each other than other cancer types. Our study also highlights the potential utility of NEN transcriptome data for molecular classification and clinical decision making.

Pilot study using a discrete mathematical approach for topological analysis and ssGSEA of gene expression in autosomal recessive polycystic kidney disease

Autosomal recessive polycystic kidney disease (ARPKD) is a severe genetic disorder characterized by renal cystogenesis and hepatic fibrosis, primarily associated with PKHD1 mutations. While differential expression analysis (DEG) has identified key genes involved in ARPKD, their network-level interactions remain unclear. Recent studies have implicated WNT signaling in ARPKD pathogenesis, but a topological framework may provide additional insights into gene community structures. This study applied a network-based approach integrating single-sample gene set enrichment analysis (ssGSEA) and topological centrality analysis to investigate gene communities in ARPKD. We identified three key communities: Community 2, centered on IFT22, exhibited stable activation in both ARPKD and healthy samples, suggesting its role in ciliary function. Community 5, predominantly activated in ARPKD, included genes linked to tissue repair and immune regulation. In contrast, Community 3 was suppressed in ARPKD, indicating potential structural instability. Notably, PKHD1 was mathematically isolated, suggesting limited direct involvement in ARPKD-specific transcriptional networks, while the absence of WNT5A, CDH1, and FZD10 from defined communities in ARPKD may indicate potential alterations in their network associations compared to healthy individuals. These findings highlight the advantages of network topology over conventional DEG analysis in elucidating ARPKD pathophysiology. By identifying gene communities and regulatory hubs, this approach offers novel insights into disease mechanisms and potential therapeutic targets.

EHMT2 as a Candidate Gene for an Autosomal Recessive Neurodevelopmental Syndrome

Neurodevelopmental disorders (NDD) comprise clinical conditions with high genetic heterogeneity and a notable enrichment of genes involved in regulating chromatin structure and function. The EHMT1/2 epigenetic complex plays a crucial role in repression of gene transcription in a highly tissue- and temporal-specific manner. Mutations resulting in heterozygous loss-of-function (LoF) of EHMT1 are implicated in Kleefstra syndrome 1 (KS1). EHMT2 is a gene acting in epigenetic regulation; however, the involvement of mutations in this gene in the etiology of NDDs has not been established thus far. A homozygous EHMT2 LoF variant [(NM_006709.5):c.328 + 2 T > G] was identified by exome sequencing in an adult female patient with a phenotype resembling KS1, presenting with intellectual disability, aggressive behavior, facial dysmorphisms, fused C2-C3 vertebrae, ventricular septal defect, supernumerary nipple, umbilical hernia, and fingers and toes abnormalities. The absence of homozygous LoF EHMT2 variants in population databases underscores the significant negative selection pressure exerted on these variants. In silico evaluation of the effect of the EHMT2(NM_006709.5):c.328 + 2 T > G variant predicted the abolishment of intron 3 splice donor site. However, manual inspection revealed potential cryptic donor splice sites at this EHMT2 region. To directly access the impact of this splice site variant, RNAseq analysis was employed and disclosed the usage of two cryptic donor sites within exon 3 in the patient's blood, which are predicted to result in either an out-of-frame or in-frame effect on the protein. Methylation analysis was conducted on DNA from blood samples using the clinically validated EpiSign assay, which revealed that the patient with the homozygous EHMT2(NM_006709.5):c.328 + 2 T > G splice site variant is conclusively positive for the KS1 episignature. Taken together, clinical, genetic, and epigenetic data pointed to a LoF mechanism for the EHMT2 splice variant and support this gene as a novel candidate for an autosomal recessive Kleefstra-like syndrome. The identification of additional cases with deleterious EHMT2 variants, alongside further functional validation studies, is required to substantiate EHMT2 as a novel NDD gene.

Olfactory ensheathing cells from adult female rats are hybrid glia that promote neural repair

Olfactory ensheathing cells (OECs) are unique glial cells found in both central and peripheral nervous systems where they support continuous axonal outgrowth of olfactory sensory neurons to their targets. Previously, we reported that following severe spinal cord injury, OECs transplanted near the injury site modify the inhibitory glial scar and facilitate axon regeneration past the scar border and into the lesion. To better understand the mechanisms underlying the reparative properties of OECs, we used single-cell RNA-sequencing of OECs from adult rats to study their gene expression programs. Our analyses revealed five diverse OEC subtypes, each expressing novel marker genes and pathways indicative of progenitor, axonal regeneration, secreted molecules, or microglia-like functions. We found substantial overlap of OEC genes with those of Schwann cells, but also with microglia, astrocytes, and oligodendrocytes. We confirmed established markers on cultured OECs, and localized select top genes of OEC subtypes in olfactory bulb tissue. We also show that OECs secrete Reelin and Connective tissue growth factor, extracellular matrix molecules which are important for neural repair and axonal outgrowth. Our results support that OECs are a unique hybrid glia, some with progenitor characteristics, and that their gene expression patterns indicate functions related to wound healing, injury repair, and axonal regeneration.

Maximum lifespan and brain size in mammals are associated with gene family size expansion related to immune system functions

Mammals exhibit an unusual variation in their maximum lifespan potential, measured as the longest recorded longevity of any individual in a species. Evidence suggests that lifespan increases follow expansion in brain size relative to body mass. Here, we found significant gene family size expansions associated with maximum lifespan potential and relative brain size but not in gestation time, age of sexual maturity, and body mass in 46 mammalian species. Extended lifespan is associated with expanding gene families enriched in immune system functions. Our results suggest an association between gene duplication in immune-related gene families and the evolution of longer lifespans in mammals. These findings explore the genomic features linked with the evolution of lifespan in mammals and its association with life story and morphological traits.

BaCoN (Balanced Correlation Network) improves prediction of gene buffering

Buffering between genes, where one gene can compensate for the loss of another gene, is fundamental for robust cellular functions. While experimentally testing all possible gene pairs is infeasible, gene buffering can be predicted genome-wide under the assumption that a gene's buffering capacity depends on its expression level and its absence primes a severe fitness phenotype of the buffered gene. We developed BaCoN (Balanced Correlation Network), a post hoc unsupervised correction method that amplifies specific signals in expression-vs-fitness correlation networks. We quantified 147 million potential buffering relationships by associating CRISPR-Cas9-screening fitness effects with transcriptomic data across 1019 Cancer Dependency Map (DepMap) cell lines. BaCoN outperformed state-of-the-art methods, including multiple linear regression based on our compiled gene buffering prediction metrics. Combining BaCoN with batch correction or Cholesky data whitening further boosts predictive performance. We characterized 808 high-confidence buffering predictions and found that in contrast to buffering gene pairs overall, buffering paralogs were on different chromosomes. BaCoN performance increases with more screens and genes considered, making it a valuable tool for gene buffering predictions from the growing DepMap.

Fragile X messenger ribonucleoprotein 1 (FMRP) regulates glycolytic gene expression under chronic hypoxia in HCT116 cells

Oxygen shortage, known as hypoxia, occurs commonly in both physiological and pathological conditions. Transcriptional regulation by hypoxia-inducible factors is a dominant regulatory mechanism controlling hypoxia-responsive genes during acute hypoxia; however, recent studies suggest that post-transcriptional regulation, including RNA degradation, also involves hypoxia-induced gene expression during the chronic hypoxia. In this study, we developed a method to quantify the contributions of RNA synthesis and degradation to differential gene expression, and identified 102 genes mainly regulated via RNA degradation under chronic hypoxia in HCT116 cells. Bioinformatics analysis showed that the genes mainly regulated by RNA degradation were involved in glycolysis. We examined changes in the RNA-binding ability of RNA-binding proteins by RNA interactome capture and statistical analysis using public databases. We identified fragile X messenger ribonucleoprotein 1 (FMRP) as an RNA-binding protein involved in the chronic hypoxia-induced increase in mRNAs encoding rate-limiting enzymes. This study emphasizes the importance of post-transcriptional gene regulation under chronic hypoxia in HCT116 cells.

Astrocytic RNA editing regulates the host immune response to alpha-synuclein

RNA editing is a posttranscriptional mechanism that targets changes in RNA transcripts to modulate innate immune responses. We report the role of astrocyte-specific, ADAR1-mediated RNA editing in neuroinflammation in Parkinson's disease (PD). We generated human induced pluripotent stem cell-derived astrocytes, neurons and cocultures and exposed them to small soluble alpha-synuclein aggregates. Oligomeric alpha-synuclein triggered an inflammatory glial state associated with Toll-like receptor activation, viral responses, and cytokine secretion. This reactive state resulted in loss of neurosupportive functions and the induction of neuronal toxicity. Notably, interferon response pathways were activated leading to up-regulation and isoform switching of the RNA deaminase enzyme, ADAR1. ADAR1 mediates A-to-I RNA editing, and increases in RNA editing were observed in inflammatory pathways in cells, as well as in postmortem human PD brain. Aberrant, or dysregulated, ADAR1 responses and RNA editing may lead to sustained inflammatory reactive states in astrocytes triggered by alpha-synuclein aggregation, and this may drive the neuroinflammatory cascade in Parkinson's.

A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines

The human genome contains instructions to transcribe more than 200,000 RNAs. However, many RNA transcripts are generated from the same gene, resulting in alternative isoforms that are highly similar and that remain difficult to quantify. To evaluate the ability to study RNA transcript expression, we profiled seven human cell lines with five different RNA-sequencing protocols, including short-read cDNA, Nanopore long-read direct RNA, amplification-free direct cDNA and PCR-amplified cDNA sequencing, and PacBio IsoSeq, with multiple spike-in controls, and additional transcriptome-wide N6-methyladenosine profiling data. We describe differences in read length, coverage, throughput and transcript expression, reporting that long-read RNA sequencing more robustly identifies major isoforms. We illustrate the value of the SG-NEx data to identify alternative isoforms, novel transcripts, fusion transcripts and N6-methyladenosine RNA modifications. Together, the SG-NEx data provide a comprehensive resource enabling the development and benchmarking of computational methods for profiling complex transcriptional events at isoform-level resolution.

Survey of gene, lncRNA and transposon transcription patterns in four mouse organs highlights shared and organ-specific sex-biased regulation

BACKGROUND

Sex-biased gene regulation is the basis of sexual dimorphism in phenotypes and has been studied across different cell types and different developmental stages. However, sex-biased expression of transposable elements (TEs), which represent nearly half of the mammalian genome and have the potential of influencing genome integrity and regulation, remains underexplored.

RESULTS

We report a survey of gene, lncRNA, and TE expression in four organs from mice with different combinations of gonadal and genetic sex. The data show remarkable variability among organs with respect to the impact of gonadal sex on transcription with the strongest effects observed in the liver. In contrast, the X-chromosome dosage alone had a modest influence on sex-biased transcription across organs, albeit interaction between X-dosage and gonadal sex cannot be ruled out. The presence of the Y-chromosome influences TE, but not gene or lncRNA, expression in the liver. Notably, 90% of sex-biased TEs (sDETEs) reside in clusters. Moreover, 54% of these clusters overlap or reside less than 100 kb from sex-biased genes or lncRNAs, share the same sex bias, and also have higher expression levels than sDETE clusters that do not co-localize with other types of sex-biased transcripts. We test the heterochromatic sink hypothesis that predicts higher expression of TEs in XX individuals finding no evidence to support it.

CONCLUSIONS

Our data show that sex-biased expression of TEs varies among organs with the highest numbers of sDETEs found in the liver following trends observed for genes and lncRNAs. It is enhanced by proximity to other types of sex-biased transcripts.

Endogenous viral elements constitute a complementary source of antigens for personalized cancer vaccines

Personalized cancer vaccines (PCVs) largely leverage neoantigens arising from somatic mutations, limiting their application to patients with relatively high tumor mutational burden (TMB). This underscores the need for alternative antigens to design PCVs for low TMB cancers. To this end, we substantiate endogenous retroviral elements (EVEs) as tumor antigens through large-scale genomic analyses of healthy tissues and solid cancers. These analyses revealed that the breadth of EVE expression in tumors stratify checkpoint inhibitor-treated melanoma patients into groups with differential overall and progression-free survival. To enable the design of PCVs containing EVE-derived epitopes with therapeutic potential, we developed a computational pipeline, ObsERV. We show that EVE-derived peptides are presented as epitopes on tumors and can be predicted by ObsERV. Preclinical testing of ObsERV demonstrates induction of sustained poly-functional CD4+ and CD8+ T-cell responses as well as long-term tumor protection. As such, EVEs may facilitate and improve PCVs, especially for low-TMB patients.

Protein codes promote selective subcellular compartmentalization

Cells have evolved mechanisms to distribute ~10 billion protein molecules to subcellular compartments where diverse proteins involved in shared functions must assemble. In this study, we demonstrate that proteins with shared functions share amino acid sequence codes that guide them to compartment destinations. We developed a protein language model, ProtGPS, that predicts with high performance the compartment localization of human proteins excluded from the training set. ProtGPS successfully guided generation of novel protein sequences that selectively assemble in the nucleolus. ProtGPS identified pathological mutations that change this code and lead to altered subcellular localization of proteins. Our results indicate that protein sequences contain not only a folding code but also a previously unrecognized code governing their distribution to diverse subcellular compartments.

Distinct gene regulatory dynamics drive skeletogenic cell fate convergence during vertebrate embryogenesis

Cell type repertoires have expanded extensively in metazoan animals, with some clade-specific cells being crucial to evolutionary success. A prime example are the skeletogenic cells of vertebrates. Depending on anatomical location, these cells originate from three different precursor lineages, yet they converge developmentally towards similar cellular phenotypes. Furthermore, their 'skeletogenic competency' arose at distinct evolutionary timepoints, thus questioning to what extent different skeletal body parts rely on truly homologous cell types. Here, we investigate how lineage-specific molecular properties are integrated at the gene regulatory level, to allow for skeletogenic cell fate convergence. Using single-cell functional genomics, we find that distinct transcription factor profiles are inherited from the three precursor states and incorporated at lineage-specific enhancer elements. This lineage-specific regulatory logic suggests that these regionalized skeletogenic cells are distinct cell types, rendering them amenable to individualized selection, to define adaptive morphologies and biomaterial properties in different parts of the vertebrate skeleton.

A comprehensive spatio-cellular map of the human hypothalamus

The hypothalamus is a brain region that plays a key role in coordinating fundamental biological functions1. However, our understanding of the underlying cellular components and neurocircuitries have, until recently, emerged primarily from rodent studies2,3. Here we combine single-nucleus sequencing of 433,369 human hypothalamic cells with spatial transcriptomics, generating a comprehensive spatio-cellular transcriptional map of the hypothalamus, the 'HYPOMAP'. Although conservation of neuronal cell types between humans and mice, as based on transcriptomic identity, is generally high, there are notable exceptions. Specifically, there are significant disparities in the identity of pro-opiomelanocortin neurons and in the expression levels of G-protein-coupled receptors between the two species that carry direct implications for currently approved obesity treatments. Out of the 452 hypothalamic cell types, we find that 291 neuronal clusters are significantly enriched for expression of body mass index (BMI) genome-wide association study genes. This enrichment is driven by 426 'effector' genes. Rare deleterious variants in six of these (MC4R, PCSK1, POMC, CALCR, BSN and CORO1A) associate with BMI at population level, and CORO1A has not been linked previously to BMI. Thus, HYPOMAP provides a detailed atlas of the human hypothalamus in a spatial context and serves as an important resource to identify new druggable targets for treating a wide range of conditions, including reproductive, circadian and metabolic disorders.

Human-correlated genetic models identify precision therapy for liver cancer

Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, is a leading cause of cancer-related mortality worldwide1,2. HCC occurs typically from a background of chronic liver disease, caused by a spectrum of predisposing conditions. Tumour development is driven by the expansion of clones that accumulate progressive driver mutations3, with hepatocytes the most likely cell of origin2. However, the landscape of driver mutations in HCC is broadly independent of the underlying aetiologies4. Despite an increasing range of systemic treatment options for advanced HCC, outcomes remain heterogeneous and typically poor. Emerging data suggest that drug efficacies depend on disease aetiology and genetic alterations5,6. Exploring subtypes in preclinical models with human relevance will therefore be essential to advance precision medicine in HCC7. Here we generated a suite of genetically driven immunocompetent in vivo and matched in vitro HCC models. Our models represent multiple features of human HCC, including clonal origin, histopathological appearance and metastasis. We integrated transcriptomic data from the mouse models with human HCC data and identified four common human-mouse subtype clusters. The subtype clusters had distinct transcriptomic characteristics that aligned with the human histopathology. In a proof-of-principle analysis, we verified response to standard-of-care treatment and used a linked in vitro-in vivo pipeline to identify a promising therapeutic candidate, cladribine, that has not previously been linked to HCC treatment. Cladribine acts in a highly effective subtype-specific manner in combination with standard-of-care therapy.

Unveiling conserved HIV-1 open reading frames encoding T cell antigens using ribosome profiling

The development of ribosomal profiling (Riboseq) revealed the immense coding capacity of human and viral genomes. Here, we used Riboseq to delineate the translatome of HIV-1 in infected CD4+ T cells. In addition to canonical viral protein coding sequences (CDSs), we identify 98 alternative open reading frames (ARFs), corresponding to small Open Reading Frames (sORFs) that are distributed across the HIV genome including the UTR regions. Using a database of HIV genomes, we observe that most ARF amino-acid sequences are likely conserved among clade B and C of HIV-1, with 8 ARF-encoded amino-acid sequences being more conserved than the overlapping CDSs. Using T cell-based assays and mass spectrometry-based immunopeptidomics, we demonstrate that ARFs encode viral polypeptides. In the blood of people living with HIV, ARF-derived peptides elicit potent poly-functional T cell responses mediated by both CD4+ and CD8+ T cells. Our discovery expands the list of conserved viral polypeptides that are targets for vaccination strategies and might reveal the existence of viral microproteins or pseudogenes.

The role of FTO in m6A RNA methylation and immune regulation in Staphylococcus aureus infection-related osteomyelitis

Background

Regulators of n6-methyladenosine (m6A) RNA modification play important roles in many diseases; however, their involvement in Staphylococcus aureus (S. aureus)-related osteomyelitis remains inadequately explored. Therefore, this study aims to investigate the role of m6A in S. aureus infection-related osteomyelitis and elucidate its underlying mechanisms.

Methods

We downloaded the S. aureus infection-related osteomyelitis infection dataset GSE30119 from the Gene Expression Omnibus database. Initially, we constructed a diagnostic model based on m6A genes and predicted the hub node miRNAs and transcription factors by constructing a protein-protein interaction network. Subsequently, a prognostic model was built using LASSO regression, the receiver operating characteristic curve of the model was plotted, and the predictive performance of the diagnostic model was validated. Further, unsupervised clustering analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were employed to assess immune cell infiltration. Additionally, we validated the expression of fat mass and obesity-associated protein (FTO) in S. aureus-infected Raw264.7 macrophages using qPCR and western blotting. Moreover, we conducted si-FTO experiments on mouse Raw264.7 macrophages to investigate the anti-inflammatory regulatory role of si-FTO during S. aureus infection.

Results

We identified 19 co-expressed genes closely related to FTO were identified, along with 206 related transcription factor regulatory genes and 589 miRNAs. Enrichment analyses suggested that these genes were involved in pathways related to the proliferation and oxidation of various immune cells, cellular senescence, and various tumors and immune cells, as well as cell cycle-related functions. GSEA revealed that PD-1, TH1, TH2, CTLA4, and other pathways were significantly enriched in patients with high FTO expression. GSVA indicated that the differentially enriched pathways were related to included amino acid metabolism, immunity, and infection. Correlation analysis of immune infiltration revealed that monocytes, M2 macrophages, resting mast cells, and neutrophils were present in normal and diseased samples. Differences in expression were observed between the groups. The western blotting and qPCR analyses confirmed that the protein expression of FTO was reduced in macrophages after infection with S. aureus, consistent with the observed changes in mRNA expression. Furthermore, we validated that FTO may influence the regulation of inflammation through the FoxO1/NF-kB pathway.

Conclusion

The m6A RNA methylation regulator FTO may serve as a potential diagnostic marker and therapeutic target, involved in the pathogenesis of S. aureus infection-related osteomyelitis. This finding provides new insights into the relationship between FTO-mediated m6A RNA methylation and osteomyelitis.

Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR

The revolutionary CRISPR-Cas9 system leverages a programmable guide RNA (gRNA) and Cas9 proteins to precisely cleave problematic regions within DNA sequences. This groundbreaking technology holds immense potential for the development of targeted therapies for a wide range of diseases, including cancers, genetic disorders, and hereditary diseases. CRISPR-Cas9 based genome editing is a multi-step process such as designing a precise gRNA, selecting the appropriate Cas protein, and thoroughly evaluating both on-target and off-target activity of the Cas9-gRNA complex. To ensure the accuracy and effectiveness of CRISPR-Cas9 system, after the targeted DNA cleavage, the process requires careful analysis of the resultant outcomes such as indels and deletions. Following the success of artificial intelligence (AI) in various fields, researchers are now leveraging AI algorithms to catalyze and optimize the multi-step process of CRISPR-Cas9 system. To achieve this goal AI-driven applications are being integrated into each step, but existing AI predictors have limited performance and many steps still rely on expensive and time-consuming wet-lab experiments. The primary reason behind low performance of AI predictors is the gap between CRISPR and AI fields. Effective integration of AI into multi-step CRISPR-Cas9 system demands comprehensive knowledge of both domains. This paper bridges the knowledge gap between AI and CRISPR-Cas9 research. It offers a unique platform for AI researchers to grasp deep understanding of the biological foundations behind each step in the CRISPR-Cas9 multi-step process. Furthermore, it provides details of 80 available CRISPR-Cas9 system-related datasets that can be utilized to develop AI-driven applications. Within the landscape of AI predictors in CRISPR-Cas9 multi-step process, it provides insights of representation learning methods, machine and deep learning methods trends, and performance values of existing 50 predictive pipelines. In the context of representation learning methods and classifiers/regressors, a thorough analysis of existing predictive pipelines is utilized for recommendations to develop more robust and precise predictive pipelines.

Transcriptomic Data Reveal Divergent Paths of Chitinase Evolution Underlying Dietary Convergence in Anteaters and Pangolins

Ant-eating mammals represent a textbook example of convergent evolution. Among them, anteaters and pangolins exhibit the most extreme convergent phenotypes with complete tooth loss, elongated skulls, protruding tongues, and hypertrophied salivary glands producing large amounts of saliva. However, comparative genomic analyses have shown that anteaters and pangolins differ in their chitinase acidic gene (CHIA) repertoires, which potentially degrade the chitinous exoskeletons of ingested ants and termites. While the southern tamandua (Tamandua tetradactyla) harbors four functional CHIA paralogs (CHIA1-4), Asian pangolins (Manis spp.) have only one functional paralog (CHIA5). Here, we performed a comparative transcriptomic analysis of salivary glands in 33 placental species, including 16 novel transcriptomes from ant-eating species and close relatives. Our results suggest that salivary glands play an important role in adaptation to an insect-based diet, as expression of different CHIA paralogs is observed in insectivorous species. Furthermore, convergently evolved pangolins and anteaters express different chitinases in their digestive tracts. In the Malayan pangolin, CHIA5 is overexpressed in all major digestive organs, whereas in the southern tamandua, all four functional paralogs are expressed, at very high levels for CHIA1 and CHIA2 in the pancreas and for CHIA3 and CHIA4 in the salivary glands, stomach, liver, and pancreas. Overall, our results demonstrate that divergent molecular mechanisms within the chitinase acidic gene family underlie convergent adaptation to the ant-eating diet in pangolins and anteaters. This study highlights the role of historical contingency and molecular tinkering of the chitin digestive enzyme toolkit in this classic example of convergent evolution.

Prioritizing effector genes at trait-associated loci using multimodal evidence

Genome-wide association studies (GWAS) yield large numbers of genetic loci associated with traits and diseases. Predicting the effector genes that mediate these locus-trait associations remains challenging. Here we present the FLAMES (fine-mapped locus assessment model of effector genes) framework, which predicts the most likely effector gene in a locus. FLAMES creates machine learning predictions from biological data linking single-nucleotide polymorphisms to genes, and then evaluates these scores together with gene-centric evidence of convergence of the GWAS signal in functional networks. We benchmark FLAMES on gene-locus pairs derived by expert curation, rare variant implication and domain knowledge of molecular traits. We demonstrate that combining single-nucleotide-polymorphism-based and convergence-based modalities outperforms prioritization strategies using a single line of evidence. Applying FLAMES, we resolve the FSHB locus in the GWAS for dizygotic twinning and further leverage this framework to find schizophrenia risk genes that converge with rare coding evidence and are relevant in different stages of life.

RNA sequence analysis landscape: A comprehensive review of task types, databases, datasets, word embedding methods, and language models

Deciphering information of RNA sequences reveals their diverse roles in living organisms, including gene regulation and protein synthesis. Aberrations in RNA sequence such as dysregulation and mutations can drive a diverse spectrum of diseases including cancers, genetic disorders, and neurodegenerative conditions. Furthermore, researchers are harnessing RNA's therapeutic potential for transforming traditional treatment paradigms into personalized therapies through the development of RNA-based drugs and gene therapies. To gain insights of biological functions and to detect diseases at early stages and develop potent therapeutics, researchers are performing diverse types RNA sequence analysis tasks. RNA sequence analysis through conventional wet-lab methods is expensive, time-consuming and error prone. To enable large-scale RNA sequence analysis, empowerment of wet-lab experimental methods with Artificial Intelligence (AI) applications necessitates scientists to have a comprehensive knowledge of both DNA and AI fields. While molecular biologists encounter challenges in understanding AI methods, computer scientists often lack basic foundations of RNA sequence analysis tasks. Considering the absence of a comprehensive literature that bridges this research gap and promotes the development of AI-driven RNA sequence analysis applications, the contributions of this manuscript are manifold: It equips AI researchers with biological foundations of 47 distinct RNA sequence analysis tasks. It sets a stage for development of benchmark datasets related to 47 distinct RNA sequence analysis tasks by facilitating cruxes of 64 different biological databases. It presents word embeddings and language models applications across 47 distinct RNA sequence analysis tasks. It streamlines the development of new predictors by providing a comprehensive survey of 58 word embeddings and 70 language models based predictive pipelines performance values as well as top performing traditional sequence encoding based predictors and their performances across 47 RNA sequence analysis tasks.

Olfactory ensheathing cells from adult female rats are hybrid glia that promote neural repair

Olfactory ensheathing cells (OECs) are unique glial cells found in both central and peripheral nervous systems where they support continuous axonal outgrowth of olfactory sensory neurons to their targets. Previously we reported that following severe spinal cord injury, OECs transplanted near the injury site modify the inhibitory glial scar and facilitate axon regeneration past the scar border and into the lesion. To better understand the mechanisms underlying the reparative properties of OECs, we used single-cell RNA-sequencing of OECs from adult rats to study their gene expression programs. Our analyses revealed five diverse OEC subtypes, each expressing novel marker genes and pathways indicative of progenitor, axonal regeneration, secreted molecules, or microglia-like functions. We found substantial overlap of OEC genes with those of Schwann cells, but also with microglia, astrocytes, and oligodendrocytes. We confirmed established markers on cultured OECs, and localized select top genes of OEC subtypes in olfactory bulb tissue. We also show that OECs secrete Reelin and Connective tissue growth factor, extracellular matrix molecules which are important for neural repair and axonal outgrowth. Our results support that OECs are a unique hybrid glia, some with progenitor characteristics, and that their gene expression patterns indicate functions related to wound healing, injury repair and axonal regeneration.

Potential Adaptive Introgression From Dogs in Iberian Grey Wolves (Canis lupus)

Invading species along with increased anthropogenization may lead to hybridization events between wild species and closely related domesticates. As a consequence, wild species may carry introgressed alleles from domestic species, which is generally assumed to yield adverse effects in wild populations. The opposite evolutionary consequence, adaptive introgression, where introgressed genes are positively selected in the wild species, is possible but has rarely been documented. Grey wolves (Canis lupus) are widely distributed across the Holarctic and frequently coexist with their close relative, the domestic dog (C. familiaris). Despite ample opportunity, hybridization rarely occurs in most populations. Here we studied the geographically isolated grey wolves of the Iberian Peninsula, who have coexisted with a large population of loosely controlled dogs for thousands of years in a human-modified landscape. We assessed the extent and impact of dog introgression on the current Iberian grey wolf population by analysing 150 whole genomes of Iberian and other Eurasian grey wolves as well as dogs originating from across Europe and western Siberia. We identified almost no recent introgression and a small (< 5%) overall ancient dog ancestry. Using a combination of single scan statistics and ancestry enrichment estimates, we identified positive selection on six genes (DAPP1, NSMCE4A, MPPED2, PCDH9, MBTPS1, and CDH13) for which wild Iberian wolves carry alleles introgressed from dogs. The genes with introgressed and positively selected alleles include functions in immune response and brain functions, which may explain some of the unique behavioural phenotypes in Iberian wolves such as their reduced dispersal compared to other wolf populations.

An organotypic atlas of human vascular cells

The human vascular system, comprising endothelial cells (ECs) and mural cells, covers a vast surface area in the body, providing a critical interface between blood and tissue environments. Functional differences exist across specific vascular beds, but their molecular determinants across tissues remain largely unknown. In this study, we integrated single-cell transcriptomics data from 19 human organs and tissues and defined 42 vascular cell states from approximately 67,000 cells (62 donors), including angiotypic transitional signatures along the arterial endothelial axis from large to small caliber vessels. We also characterized organotypic populations, including splenic littoral and blood-brain barrier ECs, thus clarifying the molecular profiles of these important cell states. Interrogating endothelial-mural cell molecular crosstalk revealed angiotypic and organotypic communication pathways related to Notch, Wnt, retinoic acid, prostaglandin and cell adhesion signaling. Transcription factor network analysis revealed differential regulation of downstream target genes in tissue-specific modules, such as those of FOXF1 across multiple lung vascular subpopulations. Additionally, we make mechanistic inferences of vascular drug targets within different vascular beds. This open-access resource enhances our understanding of angiodiversity and organotypic molecular signatures in human vascular cells, and has therapeutic implications for vascular diseases across tissues.

Macropinocytosis mediates resistance to loss of glutamine transport in triple-negative breast cancer

Triple-negative breast cancer (TNBC) metabolism and cell growth uniquely rely on glutamine uptake by the transporter ASCT2. Despite previous data reporting cell growth inhibition after ASCT2 knockdown, we here show that ASCT2 CRISPR knockout is tolerated by TNBC cell lines. Despite the loss of a glutamine transporter and low rate of glutamine uptake, intracellular glutamine steady-state levels were increased in ASCT2 knockout compared to control cells. Proteomics analysis revealed upregulation of macropinocytosis, reduction in glutamine efflux and increased glutamine synthesis in ASCT2 knockout cells. Deletion of ASCT2 in the TNBC cell line HCC1806 induced a strong increase in macropinocytosis across five ASCT2 knockout clones, compared to a modest increase in ASCT2 knockdown. In contrast, ASCT2 knockout impaired cell proliferation in the non-macropinocytic HCC1569 breast cancer cells. These data identify macropinocytosis as a critical secondary glutamine acquisition pathway in TNBC and a novel resistance mechanism to strategies targeting glutamine uptake alone. Despite this adaptation, TNBC cells continue to rely on glutamine metabolism for their growth, providing a rationale for targeting of more downstream glutamine metabolism components.

Mitochondrial Calcium Signaling Regulates Branched-Chain Amino Acid Catabolism in Fibrolamellar Carcinoma

Metabolic adaptations in response to changes in energy supply and demand are essential for survival. The mitochondrial calcium uniporter plays a key role in coordinating metabolic homeostasis by regulating TCA cycle activation, mitochondrial fatty acid oxidation, and cellular calcium signaling. However, a comprehensive analysis of uniporter-regulated mitochondrial pathways has remained unexplored. Here, we investigate metabolic consequences of uniporter loss- and gain-of-function using uniporter knockout cells and the liver cancer fibrolamellar carcinoma (FLC), which we demonstrate to have elevated mitochondrial calcium levels. Our results reveal that branched-chain amino acid (BCAA) catabolism and the urea cycle are uniporter-regulated metabolic pathways. Reduced uniporter function boosts expression of BCAA catabolism genes, and the urea cycle enzyme ornithine transcarbamylase (OTC). In contrast, high uniporter activity in FLC suppresses their expression. This suppression is mediated by reduced expression of the transcription factor KLF15, a master regulator of liver metabolism. Thus, uniporter responsive calcium signaling plays a central role in FLC-associated metabolic changes, including hyperammonemia. Our study identifies an important role for mitochondrial calcium signaling in metabolic adaptation through transcriptional regulation of metabolism and elucidates its importance for BCAA and ammonia metabolism in FLC.

Spatially aligned graph transfer learning for characterizing spatial regulatory heterogeneity

Spatially resolved transcriptomics (SRT) technologies facilitate the exploration of cell fates or states within tissue microenvironments. Despite these advances, the field has not adequately addressed the regulatory heterogeneity influenced by microenvironmental factors. Here, we propose a novel Spatially Aligned Graph Transfer Learning (SpaGTL), pretrained on a large-scale multi-modal SRT data of about 100 million cells/spots to enable inference of context-specific spatial gene regulatory networks across multiple scales in data-limited settings. As a novel cross-dimensional transfer learning architecture, SpaGTL aligns spatial graph representations across gene-level graph transformers and cell/spot-level manifold-dominated variational autoencoder. This alignment facilitates the exploration of microenvironmental variations in cell types and functional domains from a molecular regulatory perspective, all within a self-supervised framework. We verified SpaGTL's precision, robustness, and speed over existing state-of-the-art algorithms and show SpaGTL's potential that facilitates the discovery of novel regulatory programs that exhibit strong associations with tissue functional regions and cell types. Importantly, SpaGTL could be extended to process multi-slice SRT data and map molecular regulatory landscape associated with three-dimensional spatial-temporal changes during development.

A patient stratification signature mirrors the immunogenic potential of high grade serous ovarian cancers

BACKGROUND

While high-grade serous ovarian cancer (HGSC) has proven largely resistant to immunotherapy, sporadic incidents of partial and complete response have been observed in clinical trials and case reports. These observations suggest that a molecular basis for effective immunity may exist within a subpopulation of HGSC. Herein, we developed an algorithm, CONSTRU (Computing Prognostic Marker Dependencies by Successive Testing of Gene-Stratified Subgroups), to facilitate the discovery and characterization of molecular backgrounds of HGSC that confer resistance or susceptibility to protective anti-tumor immunity.

METHODS

We used CONSTRU to identify genes from tumor expression profiles that influence the prognostic power of an established immune cytolytic activity signature (CYTscore). From the identified genes, we developed a stratification signature (STRATsig) that partitioned patient populations into tertiles that varied markedly by CYTscore prognostic power. The tertile groups were then analyzed for distinguishing biological, clinical and immunological properties using integrative bioinformatics approaches.

RESULTS

Patient survival and molecular measures of immune suppression, evasion and dysfunction varied significantly across STRATsig tertiles in validation cohorts. Tumors comprising STRATsig tertile 1 (S-T1) showed no immune-survival benefit and displayed a hyper-immune suppressed state marked by activation of TGF-β, Wnt/β-catenin and adenosine-mediated immunosuppressive pathways, with concurrent T cell dysfunction, reduced potential for antigen presentation, and enrichment of cancer-associated fibroblasts. By contrast, S-T3 tumors exhibited diminished immunosuppressive signaling, heightened antigen presentation machinery, lowered T cell dysfunction, and a significant CYTscore-survival benefit that correlated with mutational burden in a manner consistent with anti-tumor immunoediting. These tumors also showed elevated activity of DNA damage/repair, cell cycle/proliferation and oxidative phosphorylation, and displayed greater proportions of Th1 CD4 + T cells. In these patients, but not those of S-T1 or S-T2, validated predictors of immunotherapy response were prognostic of longer patient survival. Further analyses showed that STRATsig tertile properties were not explained by known HGSC molecular or clinical subtypes or singular immune mechanisms.

CONCLUSIONS

STRATsig is a composite of parallel immunoregulatory pathways that mirrors tumor immunogenic potential. Approximately one-third of HGSC cases classify as S-T3 and display a hypo-immunosuppressed and antigenic molecular composition that favors immunologic tumor control. These patients may show heightened responsiveness to current immunotherapies.

Evidence for a role of human blood-borne factors in mediating age-associated changes in molecular circadian rhythms

Aging is associated with a number of physiologic changes including perturbed circadian rhythms; however, mechanisms by which rhythms are altered remain unknown. To test the idea that circulating factors mediate age-dependent changes in peripheral rhythms, we compared the ability of human serum from young and old individuals to synchronize circadian rhythms in culture. We collected blood from apparently healthy young (age 25-30) and old (age 70-76) individuals at 14:00 and used the serum to synchronize cultured fibroblasts. We found that young and old sera are equally competent at initiating robust ~24 hr oscillations of a luciferase reporter driven by clock gene promoter. However, cyclic gene expression is affected, such that young and old sera promote cycling of different sets of genes. Genes that lose rhythmicity with old serum entrainment are associated with oxidative phosphorylation and Alzheimer's Disease as identified by STRING and IPA analyses. Conversely, the expression of cycling genes associated with cholesterol biosynthesis increased in the cells entrained with old serum. Genes involved in the cell cycle and transcription/translation remain rhythmic in both conditions. We did not observe a global difference in the distribution of phase between groups, but found that peak expression of several clock-controlled genes (PER3, NR1D1, NR1D2, CRY1, CRY2, and TEF) lagged in the cells synchronized ex vivo with old serum. Taken together, these findings demonstrate that age-dependent blood-borne factors affect circadian rhythms in peripheral cells and have the potential to impact health and disease via maintaining or disrupting rhythms respectively.

Identifying the HIV-Resistance-Related Factors and Regulatory Network via Multi-Omics Analyses

For research on HIV/AIDS, it is important to elucidate the complex viral-host interaction, host dependency factors (HDFs), and restriction factors. However, the regulatory network of HIV-resistance-related factors remains not well understood. Therefore, we integrated four publicly available HIV-related transcriptome datasets, along with three datasets on HIV-infection-related DNA methylation, miRNA, and ChIP-seq, to predict the factors influencing HIV resistance and infection. Our approach involved differential analysis, functional annotation, and protein-protein interaction network analysis. Through comprehensive analyses, we identified 25 potential HIV-resistance-related genes (including shared EGF) and 24 HIV-infection-related hub genes (including shared JUN). Additionally, we pinpointed five key differentially methylated genes, five crucial differentially expressed microRNAs, and five significant pathways associated with HIV resistance. We mapped the potential regulatory pathways involving these HIV-resistance-related factors. Among the predicted factors, RHOA, RAD51, GATA1, IRF4, and CXCL8 have been validated as HDFs or restriction factors. The identified factors, such as JUN, EGF, and PLEK, are potential HDFs or restriction factors. This study uncovers the gene signatures and regulatory networks associated with HIV-1 resistance, suggesting potential targets for the development of new therapies against HIV/AIDS.

Repeat-Rich Regions Cause False-Positive Detection of NUMTs: A Case Study in Amphibians Using an Improved Cane Toad Reference Genome

Mitochondrial DNA (mtDNA) has been widely used in genetics research for decades. Contamination from nuclear DNA of mitochondrial origin (NUMTs) can confound studies of phylogenetic relationships and mtDNA heteroplasmy. Homology searches with mtDNA are widely used to detect NUMTs in the nuclear genome. Nevertheless, false-positive detection of NUMTs is common when handling repeat-rich sequences, while fragmented genomes might result in missing true NUMTs. In this study, we investigated different NUMT detection methods and how the quality of the genome assembly affects them. We presented an improved nuclear genome assembly (aRhiMar1.3) of the invasive cane toad (Rhinella marina) with additional long-read Nanopore and 10× linked-read sequencing. The final assembly was 3.47 Gb in length with 91.3% of tetrapod universal single-copy orthologs (n = 5,310), indicating the gene-containing regions were well assembled. We used 3 complementary methods (NUMTFinder, dinumt, and PALMER) to study the NUMT landscape of the cane toad genome. All 3 methods yielded consistent results, showing very few NUMTs in the cane toad genome. Furthermore, we expanded NUMT detection analyses to other amphibians and confirmed a weak relationship between genome size and the number of NUMTs present in the nuclear genome. Amphibians are repeat-rich, and we show that the number of NUMTs found in highly repetitive genomes is prone to inflation when using homology-based detection without filters. Together, this study provides an exemplar of how to robustly identify NUMTs in complex genomes when confounding effects on mtDNA analyses are a concern.

Amyotrophic lateral sclerosis diagnosis using machine learning and multi-omic data integration

Amyotrophic Lateral Sclerosis (ALS) is a complex and rare neurodegenerative disorder characterized by significant genetic, molecular, and clinical heterogeneity. Despite numerous endeavors to discover the genetic factors underlying ALS, a significant number of these factors remain unknown. This knowledge gap highlights the necessity for personalized medicine approaches that can provide more comprehensive information for the purposes of diagnosis, prognosis, and treatment of ALS. This work utilizes an innovative approach by employing a machine learning-facilitated, multi-omic model to develop a more comprehensive knowledge of ALS. Through unsupervised clustering on gene expression profiles, 9,847 genes associated with ALS pathways are isolated and integrated with 7,699 genes containing rare, presumed pathogenic genomic variants, leading to a comprehensive amalgamation of 17,546 genes. Subsequently, a Variational Autoencoder is applied to distil complex biomedical information from these genes, culminating in the creation of the proposed Multi-Omics for ALS (MOALS) model, which has been designed to expose intricate genotype-phenotype interconnections within the dataset. Our meticulous investigation elucidates several pivotal ALS signaling pathways and demonstrates that MOALS is a superior model, outclassing other machine learning models based on single omic approaches such as SNV and RNA expression, enhancing accuracy by 1.7 percent and 6.2 percent, respectively. The findings of this study suggest that analyzing the relationships within biological systems can provide heuristic insights into the biological mechanisms that help to make highly accurate ALS diagnosis tools and achieve more interpretable results.

Copy-number dosage regulates telomere maintenance and disease-associated pathways in neuroblastoma

Telomere maintenance in neuroblastoma is linked to poor outcome and caused by either telomerase reverse transcriptase (TERT) activation or through alternative lengthening of telomeres (ALT). In contrast to TERT activation, commonly caused by genomic rearrangements or MYCN amplification, ALT is less well understood. Alterations at the ATRX locus are key drivers of ALT but only present in ∼50% of ALT tumors. To identify potential new pathways to telomere maintenance, we investigate allele-specific gene dosage effects from whole genomes and transcriptomes in 115 primary neuroblastomas. We show that copy-number dosage deregulates telomere maintenance, genomic stability, and neuronal pathways and identify upregulation of variants of histone H3 and H2A as a potential alternative pathway to ALT. We investigate the interplay between TERT activation, overexpression and copy-number dosage and reveal loss of imprinting at the RTL1 gene associated with poor clinical outcome. These results highlight the importance of gene dosage in key oncogenic mechanisms in neuroblastoma.

Systematic perturbations of SETD2, NSD1, NSD2, NSD3, and ASH1L reveal their distinct contributions to H3K36 methylation

BACKGROUND

Methylation of histone 3 lysine 36 (H3K36me) has emerged as an essential epigenetic component for the faithful regulation of gene expression. Despite its importance in development and disease, how the molecular agents collectively shape the H3K36me landscape is unclear.

RESULTS

We use mouse mesenchymal stem cells to perturb the H3K36me methyltransferases (K36MTs) and infer the activities of the five most prominent enzymes: SETD2, NSD1, NSD2, NSD3, and ASH1L. We find that H3K36me2 is the most abundant of the three methylation states and is predominantly deposited at intergenic regions by NSD1, and partly by NSD2. In contrast, H3K36me1/3 are most abundant within exons and are positively correlated with gene expression. We demonstrate that while SETD2 deposits most H3K36me3, it may also deposit H3K36me2 within transcribed genes. Additionally, loss of SETD2 results in an increase of exonic H3K36me1, suggesting other (K36MTs) prime gene bodies with lower methylation states ahead of transcription. While NSD1/2 establish broad intergenic H3K36me2 domains, NSD3 deposits H3K36me2 peaks on active promoters and enhancers. Meanwhile, the activity of ASH1L is restricted to the regulatory elements of developmentally relevant genes, and our analyses implicate PBX2 as a potential recruitment factor.

CONCLUSIONS

Within genes, SETD2 primarily deposits H3K36me3, while the other K36MTs deposit H3K36me1/2 independently of SETD2 activity. For the deposition of H3K36me1/2, we find a hierarchy of K36MT activities where NSD1 > NSD2 > NSD3 > ASH1L. While NSD1 and NSD2 are responsible for most genome-wide propagation of H3K36me2, the activities of NSD3 and ASH1L are confined to active regulatory elements.

Human lens epithelial cells induce the inflammatory response when placed into the lens capsular bag model of posterior capsular opacification

Purpose

Cataracts are typically treated by phacoemulsification followed by intraocular lens implantation. Studies of mouse models of cataract surgery have revealed that lens epithelial cells rapidly remodel their transcriptome to express proinflammatory cytokines after lens fiber cell removal, but it is currently unknown whether this response is conserved in human lenses. This study seeks to fill this knowledge gap.

Methods

Human cadaver eyes from 70 to 89 year old individuals were prepared for the human capsular bag model of cataract surgery. The central epithelium was preserved in RNAlater during culture preparation, then the equatorial epithelium was either immediately preserved in RNAlater after the culture was created, or 24 h later. Gene expression profiles were generated by bulk sequencing of RNA isolated from these tissue samples. The transcriptomic response of human cadaver-derived lens epithelial cells to culture in this "capsular bag" model was characterized by bioinformatic analysis. The human response was directly compared to that of 24-month-old mouse lens epithelial cells subjected to fiber cell removal surgery.

Results

Human lens epithelial cells remodel approximately a third of their transcriptome by 24 h after surgery, and like mice, this response consists of induction of proinflammatory cytokine genes, upregulation of fibrotic markers and downregulation of genes controlling the lens epithelial phenotype.

Conclusions

These observations demonstrate that humans and mice have similar responses to cataract surgery and support the use of mice to study the response of lens epithelial cells to cataract surgery, suggesting that identified injury response mechanisms can be leveraged to elucidate new approaches to improve the outcomes of cataract surgery.

Comprehensive Annotation and Expression Profiling of C2H2 Zinc Finger Transcription Factors across Chicken Tissues

As the most abundant class of transcription factors in eukaryotes, C2H2-type zinc finger proteins (C2H2-ZFPs) play critical roles in various biological processes. Despite being extensively studied in mammals, C2H2-ZFPs remain poorly characterized in birds. Recent accumulation of multi-omics data for chicken enables the genome-wide investigation of C2H2-ZFPs in birds. The purpose of this study is to reveal the genomic occurrence and evolutionary signature of chicken C2H2-ZFPs, and further depict their expression profiles across diverse chicken tissues. Here, we annotated 301 C2H2-ZFPs in chicken genome, which are associated with different effector domains, including KRAB, BTB, HOMEO, PHD, SCAN, and SET. Among them, most KRAB-ZFPs lack orthologues in mammals and tend to form clusters by duplication, supporting their fast evolution in chicken. We also annotated a unique and previously unidentified SCAN-ZFP, which is lineage-specific and highly expressed in ovary and testis. By integrating 101 RNA-seq datasets for 32 tissues, we found that most C2H2-ZFPs have tissue-specific expression. Particularly, 74 C2H2-ZFPs-including 27 KRAB-ZFPs-show blastoderm-enriched expression, indicating their association with early embryo development. Overall, this study performs comprehensive annotation and expression profiling of C2H2 ZFPs in diverse chicken tissues, which gives new insights into the evolution and potential function of C2H2-ZFPs in avian species.

NMDtxDB: data-driven identification and annotation of human NMD target transcripts

The nonsense-mediated RNA decay (NMD) pathway is a crucial mechanism of mRNA quality control. Current annotations of NMD substrate RNAs are rarely data-driven, but use generally established rules. We present a data set with four cell lines and combinations for SMG5, SMG6, and SMG7 knockdowns or SMG7 knockout. Based on this data set, we implemented a workflow that combines Nanopore and Illumina sequencing to assemble a transcriptome, which is enriched for NMD target transcripts. Moreover, we use coding sequence information (CDS) from Ensembl, Gencode consensus Ribo-seq ORFs, and OpenProt to enhance the CDS annotation of novel transcript isoforms. In summary, 302,889 transcripts were obtained from the transcriptome assembly process, out of which 24% are absent from Ensembl database annotations, 48,213 contain a premature stop codon, and 6433 are significantly upregulated in three or more comparisons of NMD active versus deficient cell lines. We present an in-depth view of these results through the NMDtxDB database, which is available at https://shiny.dieterichlab.org/app/NMDtxDB, and supports the study of NMD-sensitive transcripts. We open sourced our implementation of the respective web-application and analysis workflow at https://github.com/dieterich-lab/NMDtxDB and https://github.com/dieterich-lab/nmd-wf.

Participation of ventricular trabeculae in neonatal cardiac regeneration leads to ectopic recruitment of Purkinje-like cells

Unlike adult mammals, newborn mice can regenerate a functional heart after myocardial infarction; however, the precise origin of the newly formed cardiomyocytes and whether the distal part of the conduction system (the Purkinje fiber (PF) network) is properly formed in regenerated hearts remains unclear. PFs, as well as subendocardial contractile cardiomyocytes, are derived from trabeculae, transient myocardial ridges on the inner ventricular surface. Here, using connexin 40-driven genetic tracing, we uncover a substantial participation of the trabecular lineage in myocardial regeneration through dedifferentiation and proliferation. Concomitantly, regeneration disrupted PF network maturation, resulting in permanent PF hyperplasia and impaired ventricular conduction. Proliferation assays, genetic impairment of PF recruitment, lineage tracing and clonal analysis revealed that PF network hyperplasia results from excessive recruitment of PFs due to increased trabecular fate plasticity. These data indicate that PF network hyperplasia is a consequence of trabeculae participation in myocardial regeneration.

Dissecting the regulatory logic of specification and differentiation during vertebrate embryogenesis

The interplay between transcription factors and chromatin accessibility regulates cell type diversification during vertebrate embryogenesis. To systematically decipher the gene regulatory logic guiding this process, we generated a single-cell multi-omics atlas of RNA expression and chromatin accessibility during early zebrafish embryogenesis. We developed a deep learning model to predict chromatin accessibility based on DNA sequence and found that a small number of transcription factors underlie cell-type-specific chromatin landscapes. While Nanog is well-established in promoting pluripotency, we discovered a new function in priming the enhancer accessibility of mesendodermal genes. In addition to the classical stepwise mode of differentiation, we describe instant differentiation, where pluripotent cells skip intermediate fate transitions and terminally differentiate. Reconstruction of gene regulatory interactions reveals that this process is driven by a shallow network in which maternally deposited regulators activate a small set of transcription factors that co-regulate hundreds of differentiation genes. Notably, misexpression of these transcription factors in pluripotent cells is sufficient to ectopically activate their targets. This study provides a rich resource for analyzing embryonic gene regulation and reveals the regulatory logic of instant differentiation.

Long-read de novo assembly of the red-legged partridge (Alectoris rufa) genome

The red-legged partridge (Alectoris rufa) is a popular game bird species that is in decline in several regions of southwestern Europe. The introduction of farm-reared individuals of a distinct genetic make-up in hunting reserves can result in genetic swamping of wild populations. Here we present a de novo genome assembly for the red-legged partridge based on long-read sequencing technology. The assembled genome size is 1.14 Gb, with scaffold N50 of 37.6 Mb and contig N50 of 29.5 Mb. Our genome is highly contiguous and contains 97.06% of complete avian core genes. Overall, the quality of this genome assembly is equivalent to those available for other close relatives such as the Japanese quail or the chicken. This genome assembly will contribute to the understanding of genetic dynamics of wild populations of red-legged partridges with releases of farm-reared reinforcements and to appropriate management decisions of such populations.

MOCHA's advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human cohorts

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is being increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. In response, MOCHA (Model-based single cell Open CHromatin Analysis) presents major advances over existing analysis tools, including: 1) improving identification of sample-specific open chromatin, 2) statistical modeling of technical drop-out with zero-inflated methods, 3) mitigation of false positives in single cell analysis, 4) identification of alternative transcription-starting-site regulation, and 5) modules for inferring temporal gene regulatory networks from longitudinal data. These advances, in addition to open chromatin analyses, provide a robust framework after quality control and cell labeling to study gene regulatory programs in human disease. We benchmark MOCHA with four state-of-the-art tools to demonstrate its advances. We also construct cross-sectional and longitudinal gene regulatory networks, identifying potential mechanisms of COVID-19 response. MOCHA provides researchers with a robust analytical tool for functional genomic inference from scATAC-seq data.

Maturation of germinal center B cells after influenza virus vaccination in humans

Germinal centers (GC) are microanatomical lymphoid structures where affinity-matured memory B cells and long-lived bone marrow plasma cells are primarily generated. It is unclear how the maturation of B cells within the GC impacts the breadth and durability of B cell responses to influenza vaccination in humans. We used fine needle aspiration of draining lymph nodes to longitudinally track antigen-specific GC B cell responses to seasonal influenza vaccination. Antigen-specific GC B cells persisted for at least 13 wk after vaccination in two out of seven individuals. Monoclonal antibodies (mAbs) derived from persisting GC B cell clones exhibit enhanced binding affinity and breadth to influenza hemagglutinin (HA) antigens compared with related GC clonotypes isolated earlier in the response. Structural studies of early and late GC-derived mAbs from one clonal lineage in complex with H1 and H5 HAs revealed an altered binding footprint. Our study shows that inducing sustained GC reactions after influenza vaccination in humans supports the maturation of responding B cells.

Single-housing-induced islet epigenomic changes are related to polymorphisms in diabetic KK mice

A lack of social relationships is increasingly recognized as a type 2 diabetes (T2D) risk. To investigate the underlying mechanism, we used male KK mice, an inbred strain with spontaneous diabetes. Given the association between living alone and T2D risk in humans, we divided the non-diabetic mice into singly housed (KK-SH) and group-housed control mice. Around the onset of diabetes in KK-SH mice, we compared H3K27ac ChIP-Seq with RNA-Seq using pancreatic islets derived from each experimental group, revealing a positive correlation between single-housing-induced changes in H3K27ac and gene expression levels. In particular, single-housing-induced H3K27ac decreases revealed a significant association with islet cell functions and GWAS loci for T2D and related diseases, with significant enrichment of binding motifs for transcription factors representative of human diabetes. Although these H3K27ac regions were preferentially localized to a polymorphic genomic background, SNVs and indels did not cause sequence disruption of enriched transcription factor motifs in most of these elements. These results suggest alternative roles of genetic variants in environment-dependent epigenomic changes and provide insights into the complex mode of disease inheritance.

The rate of W chromosome degeneration across multiple avian neo-sex chromosomes

When sex chromosomes evolve recombination suppression, the sex-limited chromosome (Y/W) commonly degenerate by losing functional genes. The rate of Y/W degeneration is believed to slow down over time as the most essential genes are maintained by purifying selection, but supporting data are scarce especially for ZW systems. Here, we study W degeneration in Sylvioidea songbirds where multiple autosomal translocations to the sex chromosomes, and multiple recombination suppression events causing separate evolutionary strata, have occurred during the last ~ 28.1-4.5 million years (Myr). We show that the translocated regions have maintained 68.3-97.7% of their original gene content, compared to only 4.2% on the much older ancestral W chromosome. By mapping W gene losses onto a dated phylogeny, we estimate an average gene loss rate of 1.0% per Myr, with only moderate variation between four independent lineages. Consistent with previous studies, evolutionarily constrained and haploinsufficient genes were preferentially maintained on W. However, the gene loss rate did not show any consistent association with strata age or with the number of W genes at strata formation. Our study provides a unique account on the pace of W gene loss and reinforces the significance of purifying selection in maintaining essential genes on sex chromosomes.

Visfatin (NAMPT) affects global gene expression in porcine anterior pituitary cells during the mid-luteal phase of the oestrous cycle

BACKGROUND

The pituitary belongs to the most important endocrine glands involved in regulating reproductive functions. The proper functioning of this gland ensures the undisturbed course of the oestrous cycle and affects the female's reproductive potential. It is believed that visfatin, a hormone belonging to the adipokine family, may regulate reproductive functions in response to the female's metabolic state. Herein we verified the hypothesis that suggests a modulatory effect of visfatin on the anterior pituitary transcriptome during the mid-luteal phase of the oestrous cycle.

RESULTS

RNA-seq analysis of the porcine anterior pituitary cells revealed changes in the expression of 202 genes (95 up-regulated and 107 down-regulated in the presence of visfatin, when compared to the non-treated controls), assigned to 318 gene ontology terms. We revealed changes in the frequency of alternative splicing events (235 cases), as well as long noncoding RNA expression (79 cases) in the presence of the adipokine. The identified genes were associated, among others, with reproductive system development, epithelial cell proliferation, positive regulation of cell development, gland morphogenesis and cell chemotaxis.

CONCLUSIONS

The obtained results indicate a modulatory influence of visfatin on the regulation of the porcine transcriptome and, in consequence, pituitary physiology during the mid-luteal phase of the oestrous cycle.

Transposase-assisted tagmentation: an economical and scalable strategy for single-worm whole-genome sequencing

AlphaMissense identifies 23 million human missense variants as likely pathogenic, but only 0.1% have been clinically classified. To experimentally validate these predictions, chemical mutagenesis presents a rapid, cost-effective method to produce billions of mutations in model organisms. However, the prohibitive costs and limitations in the throughput of whole-genome sequencing (WGS) technologies, crucial for variant identification, constrain its widespread application. Here, we introduce a Tn5 transposase-assisted tagmentation technique for conducting WGS in Caenorhabditis elegans, Escherichia coli, Saccharomyces cerevisiae, and Chlamydomonas reinhardtii. This method, demands merely 20 min of hands-on time for a single-worm or single-cell clones and incurs a cost below 10 US dollars. It effectively pinpoints causal mutations in mutants defective in cilia or neurotransmitter secretion and in mutants synthetically sterile with a variant analogous to the B-Raf Proto-oncogene, Serine/Threonine Kinase (BRAF) V600E mutation. Integrated with chemical mutagenesis, our approach can generate and identify missense variants economically and efficiently, facilitating experimental investigations of missense variants in diverse species.