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Maternal care effects on the hippocampal transcriptome and anxiety-mediated behaviors in the offspring that are reversible in adulthood.

Early-life experience has long-term consequences on behavior and stress responsivity of the adult. We previously proposed that early-life experience results in stable epigenetic programming of glucocorticoid receptor gene expression in the hippocampus. The aim of this study was to examine the global effect of early-life experience on the hippocampal transcriptome and the development of stress-mediated behaviors in the offspring and whether such effects were reversible in adulthood. Adult offspring were centrally infused with saline vehicle, the histone deacetylase inhibitor trichostatin A (TSA), or the essential amino acid l-methionine. The animals were assessed in an unfamiliar open-field arena, and the hippocampal transcriptome of each animal was evaluated by microarray analysis. Here we report that TSA and methionine treatment reversed the effect of maternal care on open-field behavior. We identified >900 genes stably regulated by maternal care. A fraction of these differences in gene expression is reversible by either the histone deacetylase inhibitor TSA or the methyl donor l-methionine. These results suggest that early-life experience has a stable and broad effect on the hippocampal transcriptome and anxiety-mediated behavior, which is potentially reversible in adulthood.

Aging↗

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on characterizing oocytes and ovarian tissue composition, as well as understanding the molecular mechanisms that guide ovarian function throughout its lifecycle. High-throughput omics technologies have enabled the characterization of different molecular layers, leading to substantial advances in our understanding of their complex dynamics. However, not all molecular aspects are studied equally, and studies examining the same modalities often show inconsistencies, underscoring the need for data standardization and highlighting the potential for using transformative artificial intelligence and machine-learning (AI/ML) methods for ovary studies. OBJECTIVE AND RATIONALE: This study aims to evaluate how multi-omic studies have advanced our understanding of the ovarian lifecycle from fetal development to postmenopause. We systematically reviewed published studies that have investigated molecular/omic layers, including the genome, methylome, transcriptome, and proteome throughout ovarian development and aging. Our analysis identified key molecular and cellular patterns, highlighted inconsistencies across studies and addressed gaps in data analysis, interpretation, and reproducibility to guide future research. SEARCH METHODS: We conducted a systematic literature search of Medline (PubMed), Embase (Ovid), and Web of Science Core Collection (Clarivate) using a combination of controlled and free text terms for human ovary, oogenesis, folliculogenesis, ovary development and (epi)genome, transcriptome, proteome, and multi-omic mechanisms to find relevant articles published before August 2025. To focus the scope of the current review, studies of domesticated and farm animals, rodents and other model organisms, non-human primates, as well as those examining various human ovarian pathologies were excluded. OUTCOMES: The search identified 23 546 studies for screening, of which 637 full-text studies were assessed for eligibility. Subsequently, we extracted data from 121 studies. Most studies analyzed the transcriptome of oocytes, granulosa cells, and ovarian tissue from reproductive-age individuals (n = 91), with fewer studies examining samples from individuals of advanced reproductive age (n = 45) and fetal (n = 16) samples. Transcriptome analyses were most common (n = 103, 85%), followed by proteome (n = 19, 16%) and epigenome (n = 14, 12%) studies. We found substantial variation in how studies defined and reported participants' groups as well as in their sequencing technologies and data analysis methods, with a lack of standardized reporting of background clinical information, data analysis methods, and pipeline details. The key findings underscore the prevailing consensus on genes defining major ovarian cell types and their roles throughout the ovarian lifespan, from prenatal development to postmenopausal transformation. This review highlighted the underrepresentation of certain patient groups, particularly prepubertal and peri-/postmenopausal individuals, among researched populations, due to obvious clinical and ethical reasons. WIDER IMPLICATIONS: This scoping review offers a comprehensive overview and benchmark of the current state of high-throughput omics-based research on ovarian cellular composition and molecular dynamics. To address these shortcomings, we propose general recommendations for multi-omics ovary studies and emphasize the necessity for more thorough multi-omic data integration by effectively applying novel AI/ML approaches. They can potentially improve the quality of multi-omics analyses at both single-cell and tissue levels despite limited sample sizes and enable integration of molecular profiling data with clinical and radiology datasets, enabling a more comprehensive understanding of ovarian biology. Such advancements can enhance reproducibility of research findings and guide future research to deepen our understanding of ovarian biology and ultimately support the development of medical technologies for better preserving fertility and alleviating infertility. REGISTRATION NUMBER: A protocol was published a priori on the Open Science Framework (https://osf.io/z38gb/).

Female↗

Pseudo-messenger RNA: phantoms of the transcriptome.

The mammalian transcriptome harbours shadowy entities that resist classification and analysis. In analogy with pseudogenes, we define pseudo-messenger RNA to be RNA molecules that resemble protein-coding mRNA, but cannot encode full-length proteins owing to disruptions of the reading frame. Using a rigorous computational pipeline, which rules out sequencing errors, we identify 10,679 pseudo-messenger RNAs (approximately half of which are transposon-associated) among the 102,801 FANTOM3 mouse cDNAs: just over 10% of the FANTOM3 transcriptome. These comprise not only transcribed pseudogenes, but also disrupted splice variants of otherwise protein-coding genes. Some may encode truncated proteins, only a minority of which appear subject to nonsense-mediated decay. The presence of an excess of transcripts whose only disruptions are opal stop codons suggests that there are more selenoproteins than currently estimated. We also describe compensatory frameshifts, where a segment of the gene has changed frame but remains translatable. In summary, we survey a large class of non-standard but potentially functional transcripts that are likely to encode genetic information and effect biological processes in novel ways. Many of these transcripts do not correspond cleanly to any identifiable object in the genome, implying fundamental limits to the goal of annotating all functional elements at the genome sequence level.

Animals↗

A novel transcriptome subtraction method for the detection of differentially expressed genes in highly complex eukaryotes.

We have designed a novel transcriptome subtraction method for the genome-scale analysis of differential gene expression in highly complex eukaryotes, in which suppression subtractive hybridization (SSH) is performed first to enrich the target and, after exchange of adapters, negative subtraction chain (NSC) is then used to eliminate the remaining background. NSC evolved from differential subtraction chain (DSC). We designed novel adapters which make the subtraction system more robust. SSH and NSC were then combined to successfully detect differentially expressed genes in Solanum. The combined technique improves qualitatively upon SSH, the only commercially available transcriptome subtraction system, by detecting target genes in the middle abundance class, to which most differentially expressed genes in highly complex eukaryotes are expected to belong. The main advantage of the combined technique with SSH/NSC is its ability to isolate differentially expressed genes quickly and cost-efficiently from non-standard models, for those microarrays are unavailable.

Gene Expression Profiling↗

PUNS: transcriptomic- and genomic-in silico PCR for enhanced primer design.

UNLABELLED: We developed a CGI/Perl-based web server to perform in silico polymerase chain reaction (PCR) on PCR primer sequences. The PUNS (Primer-UniGene Selectivity) server simulates PCR reactions by running BLASTN analysis on user-entered primer pairs against both the transcriptome and the genome to assess primer specificity. PUNS is particularly suited for the identification of highly selective primers for quantitative microarray validation. AVAILABILITY: Both system access and source-code are freely available at http://okeylabimac.med.utoronto.ca/PUNS.

Algorithms↗

Diving Deeper Into Mechanisms of Acrylamide-Induced Toxicity: RNA Sequencing Reveals Transcriptomic Alteration and Retrotransposon Expression in Drosophila melanogaster.

Given the inevitability of human and animal exposure to acrylamide, there is increasing concern regarding its potential health risks. While a number of molecular mechanisms have been proposed, the complexity of acrylamide toxicological pathways and interactions remains incompletely characterized. In this study, we employed a transcriptomic approach to investigate the transcriptional responses of Drosophila melanogaster following exposure to acrylamide (100 mg/kg). Our analysis identified 634 differentially expressed genes (DEGs), with 362 upregulated and 272 downregulated. Functional analysis revealed these DEGs are enriched in pathways related to reproduction, detoxification, cellular and metabolic processes, signaling, synaptic formation and organization. Notably, acrylamide exposure upregulated the expression of tau and beta-amyloid protein precursor-like genes, both implicated in Alzheimer's disease pathology. An aversive memory test further demonstrated that acrylamide impaired the short-term memory of treated flies. Additionally, acrylamide-induced toxicity altered the expression of nine long terminal repeat retrotransposons, belonging to the gypsy and pao superfamilies. By exploring the potential role of transposable element activity in acrylamide-mediated toxicity, this study provides novel insights into the molecular mechanisms underlying its effects. Collectively, these findings offer a more comprehensive understanding of the mechanisms and pathways associated with the toxic action and detoxification of acrylamide in D. melanogaster.

Animals↗

Transcriptomal profiling of the cellular transformation induced by Rho subfamily GTPases.

We have used microarray technology to identify the transcriptional targets of Rho subfamily guanosine 5'-triphosphate (GTP)ases in NIH3T3 cells. This analysis indicated that murine fibroblasts transformed by these proteins show similar transcriptomal profiles. Functional annotation of the regulated genes indicate that Rho subfamily GTPases target a wide spectrum of functions, although loci encoding proteins linked to proliferation and DNA synthesis/transcription are upregulated preferentially. Rho proteins promote four main networks of interacting proteins nucleated around E2F, c-Jun, c-Myc and p53. Of those, E2F, c-Jun and c-Myc are essential for the maintenance of cell transformation. Inhibition of Rock, one of the main Rho GTPase targets, leads to small changes in the transcriptome of Rho-transformed cells. Rock inhibition decreases c-myc gene expression without affecting the E2F and c-Jun pathways. Loss-of-function studies demonstrate that c-Myc is important for the blockage of cell-contact inhibition rather than for promoting the proliferation of Rho-transformed cells. However, c-Myc overexpression does not bypass the inhibition of cell transformation induced by Rock blockage, indicating that c-Myc is essential, but not sufficient, for Rock-dependent transformation. These results reveal the complexity of the genetic program orchestrated by the Rho subfamily and pinpoint protein networks that mediate different aspects of the malignant phenotype of Rho-transformed cells.

Amino Acid Substitution↗

Genomic characterization and phylogenetic placement of Matryoshka RNA virus 1 associated with Plasmodium vivax malaria in Africa.

Plasmodium vivax is a major cause of human malaria. It harbours Matryoshka RNA virus 1 (MaRNAV-1), a bi-segmented positive-sense RNA virus. MaRNAV-1 was first described in P. vivax and is now recognized as part of a wider group of Matryoshka viruses. These viruses also infect other haemosporidian parasites such as Leucocytozoon and Haemoproteus. The presence of MaRNAV-1 in African-origin human P. vivax, however, has not been clearly established. This study investigated whether MaRNAV-1 is present in public African-origin P. vivax transcriptomic datasets. Any viral sequences recovered were characterized using comparative genomic and phylogenetic analyses. A secondary in silico analysis targeted African-origin P. vivax RNA-seq runs from public repositories. Although the search covered Africa, only Ethiopian datasets could be confidently identified, retrieved and compiled at the time. After quality control and screening for MaRNAV-1 RNA-dependent RNA polymerase (RdRp) signals, three high-confidence runs were selected for further analysis. Reference-guided reconstruction, ORF prediction, blast-based validation and RdRp phylogenetic analysis were performed. MaRNAV-1 was identified in three Ethiopian P. vivax malaria transcriptomes. This was supported by strong segment-level mapping, near-complete coverage, high mean depth and minimal low-depth masking. The recovered genomes showed the expected bisegmented organization of MaRNAV-1. Segment I was highly conserved and encoded the canonical RdRp in all three consensus sequences. Segment II showed the conserved organization of two overlapping hypothetical ORFs in all three consensus sequences. Blast analyses confirmed close similarity to MaRNAV-1 reference sequences. Phylogenetic inference grouped the Ethiopian sequences within the broader P. vivax-associated MaRNAV-1 lineage, alongside other recognized MaRNAV lineages distinct from more divergent narna-like viruses. These findings provide genomic evidence for MaRNAV-1 in publicly available African-origin P. vivax transcriptomic datasets and add to the emerging evidence for the virus in the African malaria context.

MaRNAV↗

Estrone disrupts early reproductive development in juvenile male Siniperca chuatsi and is associated with brain and gonadal responses.

Whether estrone (E1)-associated disruption of early reproductive development in fish is accompanied by brain responses in addition to direct gonadal effects remains unclear. Here, juvenile Siniperca chuatsi, a non-model but economically important freshwater species, were exposed for 60 d to 0, 0.01, 0.1, and 1.0 μg/L E1, spanning environmentally reported and elevated concentrations. By integrating waterborne concentration monitoring, histopathology, transcriptomics, and quantitative real-time PCR (qPCR) validation, we evaluated E1-associated changes in brain and gonadal tissues during early reproductive development. Waterborne E1 concentrations remained generally stable throughout the exposure period. At the highest tested concentration (1.0 μg/L), E1 caused neuronal vacuolation and pyknosis in the hypothalamic region and induced distinct ovarian-like structures in the gonads of genetic males. In the brain, cyp19a1, crhr1, and adcy2a were significantly upregulated, whereas egr1 was significantly downregulated, indicating transcriptional changes in genes associated with local estrogen conversion, stress-response/cAMP signaling, and neuronal activity-related regulation within a broader injury/stress-response background. In the gonad, RNA-seq analysis showed significant downregulation of star2, hsd3b1, cyp17a1, and cyp11b and significant upregulation of hsd17b1, suggesting alterations in steroidogenesis-related gene expression at the transcriptomic level. qPCR analysis of selected gonadal candidate genes showed expression directions generally consistent with the RNA-seq results, and these molecular patterns were consistent with the feminized histological phenotype. Together, these results indicate that E1 can disrupt early reproductive development in juvenile S. chuatsi and support a cautious working model in which E1 exposure is accompanied by concurrent brain and gonadal responses. This study provides new evidence for understanding the toxic effects and ecological risk implications of natural estrogen E1 during early fish development.

Animals↗

Cardiomyocyte-Specific Plakophilin-2 Loss Is Sufficient to Induce Aging and Senescence of Nonmyocytes: Relevance to Arrhythmogenic Cardiomyopathy.

BACKGROUND: Pathogenic variants in PKP2 are the most common cause of familial arrhythmogenic right ventricular cardiomyopathy. This study tests whether plakophilin-2 (PKP2) deficiency only in cardiomyocytes is sufficient to provoke premature aging and proinflammatory senescence in nonmyocyte, cardiac resident cells. METHODS: We studied mice with cardiomyocyte-specific, tamoxifen-activated loss of PKP2 (cardiomyocyte-specific conditional knockout of plakophilin-2) using conventional and multiplex imaging, cytokine arrays, epigenetic clocks, spatial transcriptomics, expansion and structured illumination microscopy, and correlative data analysis. We examined nonmyocytes and cardiomyocytes for premature aging and senescence. RESULTS: We observed senescence-associated heterochromatin foci in nonmyocytes, predominantly in cells positive for α-smooth muscle actin staining. Cytokines in media of nonmyocyte cells were consistent with senescence-associated secretory phenotype. Epigenetic clocks identified premature aging. Multiplex immunohistochemistry showed nonmyocyte cells in niches, intermingled with cardiomyocytes. Spatial transcriptomics showed overrepresentation of senescence-associated secretory phenotype-related transcripts, predominantly in myocyte-rich areas of the left ventricle. Senescence-associated heterochromatin foci and increased epigenetic age were not found in cardiomyocytes from cardiomyocyte-specific conditional knockout of plakophilin-2 hearts, although we observed structural features associated with premature aging. Cross-reference analysis showed correlation between the cardiomyocyte-specific conditional knockout of plakophilin-2 cardiac proteome and that of mice 5 or 6 times their chronological age, as well as transcriptional signatures of neurodegenerative diseases. CONCLUSIONS: Loss of PKP2 expression only in adult cardiac myocytes is sufficient to induce proinflammatory senescence in nonmyocytes, and overall premature cardiac aging. This is the first study to intersect cellular senescence and premature aging with desmosomal arrhythmogenic cardiomyopathies. We speculate that cell-agnostic molecular signatures, biomarkers, and pharmacology of senescence and of neurodegenerative diseases may be relevant to diagnose or treat PKP2 arrhythmogenic right ventricular cardiomyopathy.

Animals↗

Identification of transcriptome SNPs between Xiphophorus lines and species for assessing allele specific gene expression within F₁ interspecies hybrids.

Variations in gene expression are essential for the evolution of novel phenotypes and for speciation. Studying allelic specific gene expression (ASGE) within interspecies hybrids provides a unique opportunity to reveal underlying mechanisms of genetic variation. Using Xiphophorus interspecies hybrid fishes and high-throughput next generation sequencing technology, we were able to assess variations between two closely related vertebrate species, Xiphophorus maculatus and Xiphophorus couchianus, and their F(1) interspecies hybrids. We constructed transcriptome-wide SNP polymorphism sets between two highly inbred X. maculatus lines (JP 163 A and B), and between X. maculatus and a second species, X. couchianus. The X. maculatus JP 163 A and B parental lines have been separated in the laboratory for ≈70 years and we were able to identify SNPs at a resolution of 1 SNP per 49 kb of transcriptome. In contrast, SNP polymorphisms between X. couchianus and X. maculatus species, which diverged ≈5-10 million years ago, were identified about every 700 bp. Using 6524 transcripts with identified SNPs between the two parental species (X. maculatus and X. couchianus), we mapped RNA-seq reads to determine ASGE within F(1) interspecies hybrids. We developed an in silico X. couchianus transcriptome by replacing 90,788 SNP bases for X. maculatus transcriptome with the consensus X. couchianus SNP bases and provide evidence that this procedure overcomes read mapping biases. Employment of the in silico reference transcriptome and tolerating 5 mismatches during read mapping allow direct assessment of ASGE in the F(1) interspecies hybrids. Overall, these results show that Xiphophorus is a tractable vertebrate experimental model to investigate how genetic variations that occur during speciation may affect gene interactions and the regulation of gene expression.

Alleles↗

Sequencing and analysis of 10,967 full-length cDNA clones from Xenopus laevis and Xenopus tropicalis reveals post-tetraploidization transcriptome remodeling.

Sequencing of full-insert clones from full-length cDNA libraries from both Xenopus laevis and Xenopus tropicalis has been ongoing as part of the Xenopus Gene Collection Initiative. Here we present 10,967 full ORF verified cDNA clones (8049 from X. laevis and 2918 from X. tropicalis) as a community resource. Because the genome of X. laevis, but not X. tropicalis, has undergone allotetraploidization, comparison of coding sequences from these two clawed (pipid) frogs provides a unique angle for exploring the molecular evolution of duplicate genes. Within our clone set, we have identified 445 gene trios, each comprised of an allotetraploidization-derived X. laevis gene pair and their shared X. tropicalis ortholog. Pairwise dN/dS, comparisons within trios show strong evidence for purifying selection acting on all three members. However, dN/dS ratios between X. laevis gene pairs are elevated relative to their X. tropicalis ortholog. This difference is highly significant and indicates an overall relaxation of selective pressures on duplicated gene pairs. We have found that the paralogs that have been lost since the tetraploidization event are enriched for several molecular functions, but have found no such enrichment in the extant paralogs. Approximately 14% of the paralogous pairs analyzed here also show differential expression indicative of subfunctionalization.

Animals↗

Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression.

Molecular profiling of cancer at the transcript level has become routine. Large-scale analysis of proteomic alterations during cancer progression has been a more daunting task. Here, we employed high-throughput immunoblotting in order to interrogate tissue extracts derived from prostate cancer. We identified 64 proteins that were altered in prostate cancer relative to benign prostate and 156 additional proteins that were altered in metastatic disease. An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed, revealing only 48%-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors.

Disease Progression↗

Monocyte chemotactic protein-1 expression is increased in human gestational tissues during term and preterm labor.

OBJECTIVE: Microarray analysis was used to characterize the labor-selective transcriptome of the human myometrium during labor. One highly up-regulated transcript, monocyte chemotactic protein-1 (MCP-1), was further characterized. METHODS: Expression of MCP-1 was evaluated in the myometrium, the placenta, the gestational membranes (GM) and the amniotic fluid (AF) by real time RT-PCR, Northern blot analysis and ELISA. The level of immunoreactive (IR) MCP-1 content of primary myometrial cultures treated with inflammatory cytokines was quantified by ELISA. RESULTS: Up-regulation of the myometrial MCP-1 transcript in term laboring patients was demonstrated by microarray and confirmed by real time (RT)-PCR and Northern blot analysis. Increased MCP-1 transcripts were demonstrated in GM during term labor. The IR content of myometrial MCP-1 was increased during term labor and in the AF from patients experiencing preterm delivery. Levels of IR MCP-1 increased in myometrial cultures in response to interleukin 1-beta. CONCLUSION: The expression of myometrial MCP-1 was significantly increased during term labor and was similarly increased in vitro in response to interleukin 1-beta, a pro-inflammatory substance known to play a role in preterm birth. The increased IR content of MCP-1 within the AF preceding preterm delivery may render this protein a useful predictor of preterm birth.

Adult↗

The next wave in metabolome analysis.

The metabolome of a cell represents the amplification and integration of signals from other functional genomic levels, such as the transcriptome and the proteome. Although this makes metabolomics a useful tool for the high-throughput analysis of phenotypes, the lack of a direct connection to the genome makes it difficult to interpret metabolomic data. Nevertheless, functional genomics has produced examples of the use of metabolomics to elucidate the phenotypes of otherwise silent mutations. Despite several successes, we believe that future metabolomic studies must focus on the accurate measurement of the concentrations of unambiguously identified metabolites. The research community must develop databases of metabolite concentrations in cells that are grown in several well-defined conditions if metabolomic data are to be integrated meaningfully with data from the other levels of functional-genomic analysis and to make a significant contribution to systems biology.

Animals↗

Systematic Analysis of Tumor Microenvironment Using IOBR.

The Immuno-Oncology Biological Research (IOBR) package is an R-based analysis tool for exploring the tumor microenvironment (TME) and its influence on anti-tumor immunity. Built for high-throughput data-spanning both transcriptomic and genomic profiles-IOBR integrates six analytical modules, including transcriptomic data preprocessing, TME profiling, TME pattern identification, ligand-receptor interaction analysis, genome-TME interaction assessment, and visualization. In this chapter, we walk through a multi-omics workflow using example datasets, illustrating data preparation, distribution analyses, result interpretation, and graphical output. IOBR is open source and is available at https://github.com/IOBR/IOBR and a detailed GitBook ( https://iobr.github.io/book/ ) offers a complete manual and analysis guide for each function.

Tumor Microenvironment↗

Post-genome-wide association study dissects genetic vulnerability and risk gene expression of Sjögren's disease for cardiovascular disease.

OBJECTIVES: This study aims to clarify the genetic associations between Sjögren's Disease (SD) and cardiovascular disease (CVD) outcomes, and to conduct an in-depth exploration of specific pleiotropic susceptibility genes. METHODS: We performed two-sample and multivariable Mendelian randomization (MR) analysis to investigate the association between SD and the risk of ischemic heart disease (IHD) and stroke. Linkage disequilibrium score regression (LDSC) and Bayesian co-localization analyses were employed to assess the genetic associations between traits. Cross-phenotype analyses were employed to identify shared variants and genes, followed by a Transcriptome-Wide Association Study (TWAS) and Multi-marker Analysis of Genomic Annotation (MAGMA) based on Multi-Trait Analysis of GWAS (MTAG) results. To validate the pleiotropic genes, we further analyzed tissue-specific differentially expressed genes (DEGs) related to SD using RNA sequencing data. RESULTS: The two-sample and multivariable MR analyses revealed that SD confers a genetic vulnerability to IHD and stroke. LDSC and co-localization analyses indicated a strong genetic linkage between SD and CVDs. Cross-phenotype analyses identified 38 and 37 pleiotropic single nucleotide polymorphisms (SNPs) for SD-Stroke and SD-IHD, respectively, primarily located within the MHC class region on 6p21.32:33 loci. Additionally, TWAS and MAGMA analyses identified pleiotropic genes located outside the MHC regions-seven associated with stroke (UHRF1BP1, SNRPC, BLK, FAM167A, ARHGAP27, C8orf12, and PLEKHM1) and two associated with IHD (UHRF1BP1 and SNRPC). Proxy variants within these genes in SD suggested an increased causal risk for stroke or IHD. Co-localization analysis further reinforced that SD and stroke share significant SNPs within the loci of FAM167A, BLK, C8orf12, SNRPC, and UHRF1BP1. DEG analysis revealed a significant up-regulation of the identified genes in SD-specific tissues. CONCLUSIONS: SD appears genetically predisposed to an increased risk of CVDs. Moreover, this research not only identified pleiotropic genes shared between SD and CVDs, but also, for the first time, detected key gene expressions that elevate CVD risk in SD patients-findings that may offer promising therapeutic targets for patient management.

Humans↗

Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution.

We present Tahoe-100M, a giga-scale single-cell perturbation atlas comprising 100 million transcriptomes from 50 diverse cancer cell lines treated with 1,100 drug-dose conditions. This parallel profiling of thousands of perturbations at single-cell resolution with minimal batch effects is enabled by the Mosaic platform, which multiplexes genetically distinct cell models into balanced "cell villages." Beyond cataloging transcriptomic shifts, Tahoe-100M systematically quantifies cellular phenotypes, including proliferation, cytotoxicity, lineage-specific vulnerabilities, and cell-cycle changes. It captures population-level transcriptomic heterogeneity, characterizing whether drug responses drive cells toward divergent fates or convergent states. Pathway-based signatures define drug-induced expression programs, classify mechanisms of action, reveal off-target activities, and expose adaptive stress responses associated with resistance. By unifying cellular and molecular readouts, this broadly applicable perturbation atlas advances our ability to model gene regulation, drug response, and network dynamics. Its public release enables the training of AI frameworks to advance predictive models of cell behavior.

Humans↗