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PubMed2003

GénoPlante-Info (GPI): a collection of databases and bioinformatics resources for plant genomics.

Génoplante is a partnership program between public French institutes (INRA, CIRAD, IRD and CNRS) and private companies (Biogemma, Bayer CropScience and Bioplante) that aims at developing genome analysis programs for crop species (corn, wheat, rapeseed, sunflower and pea) and model plants (Arabidopsis and rice). The outputs of these programs form a wealth of information (genomic sequence, transcriptome, proteome, allelic variability, mapping and synteny, and mutation data) and tools (databases, interfaces, analysis software), that are being integrated and made public at the public bioinformatics resource centre of Génoplante: GénoPlante-Info (GPI). This continuous flood of data and tools is regularly updated and will grow continuously during the coming two years. Access to the GPI databases and tools is available at http://genoplante-info.infobiogen.fr/.

Alleles↗

PubMed2006

From genomes to systems: the path with yeast.

Metabolic Control Analysis (MCA) is a conceptual and mathematical formalism that models the relative contributions of individual effectors in a pathway to both the flux through the pathway and the concentrations of individual intermediates within it. To exploit MCA in an initial Systems Biology analysis of the eukaryotic cell, two categories of experiments are required. In category 1 experiments, flux is changed and the impact on the levels of the direct and indirect products of gene action is measured. We have measured the impact of changing the flux on the transcriptome, proteome and metabolome of Saccharomyces cerevisiae. In this whole-cell analysis, flux equates to growth rate. In category 2 experiments, the levels of individual gene products are altered, and the impact on the flux is measured. We have used competition analyses between the complete set of heterozygous yeast deletion mutants to reveal genes encoding proteins with high flux control coefficients. These genes may be exploited, in a top-down analysis, to build a coarse-grained model of the eukaryotic cell, as exemplified by yeast. More detailed modelling requires that 'natural' biological systems be identified. The combination of flux balance analysis with both genetics and metabolomics in the definition of metabolic systems is discussed.

Computational Biology↗

PubMed2026

IL1RAP Is Associated With an Inflammation-Immunity-Related State in Skin Cutaneous Melanoma: Integrative Evidence From Pan-Cancer Data and Melanoma Immunotherapy Cohorts.

BACKGROUND: The crosstalk between inflammation and immunity plays a central role in tumor progression, immune evasion, and therapeutic response. Interleukin-1 receptor accessory protein (IL1RAP) is a key adaptor in inflammatory signaling, yet its immunological relevance and clinical implications in skin cutaneous melanoma (SKCM) remain largely unexplored. METHODS: We performed an integrative analysis combining pan-cancer and melanoma-focused datasets. Bulk transcriptomic, single-cell, spatial transcriptomic, genomic alteration, pharmacogenomic, and clinical survival data were obtained from TCGA, GTEx, GEO, ENA, and other public resources. IL1RAP expression was evaluated across cancer types in relation to diagnostic performance, immune subtypes, survival outcomes, functional pathway activity, immune-genomic states, somatic alterations, and drug-response metrics. Melanoma-focused analyses examined immune infiltration, methylation-derived tumor-infiltrating lymphocyte (MeTIL) scores, and exploratory survival associations in five treatment cohorts; the survival groups were defined using cohort-specific optimal cutoffs rather than median splits. RESULTS: IL1RAP expression differed between tumor and normal tissues in multiple cancers, although the direction and magnitude varied by cancer type. Pan-cancer survival associations were likewise context dependent. Single-cell and spatial transcriptomic resources indicated cell-type and spatial heterogeneity of IL1RAP expression within tumor microenvironments. Pathway, immune-genomic, and pharmacogenomic analyses identified exploratory associations with functional states, genomic features, and drug-response metrics. In SKCM, IL1RAP expression was associated with several immune-infiltration estimates and higher MeTIL scores. Across five melanoma immunotherapy cohorts, the direction and magnitude of the overall survival associations varied substantially. CONCLUSIONS: This retrospective integrative analysis suggests that IL1RAP may mark an inflammation-immunity-related state in SKCM. The heterogeneous associations across cancers and melanoma treatment cohorts support further validation but do not establish IL1RAP as a causal regulator, a treatment-response predictor, or a therapeutic target.

IL1RAP↗

PubMed2007

Serial analysis of gene expression in sugarcane (Saccharum spp.) leaves revealed alternative C4 metabolism and putative antisense transcripts.

Sugarcane (Saccharum spp.) is a highly efficient biomass and sugar producing crop. Leaf reactions have been considered as potential rate-limiting step for sucrose accumulation in sugarcane stalks. To characterize the sugarcane leaf transcriptome, field-grown mature leaves from cultivar "SP80-3280" were analyzed using Serial Analysis of Gene Expression (SAGE). From 480 sequenced clones, 9,482 valid tags were extracted, with 5,227 unique sequences, from which 3,659 (70%) matched at least a sugarcane assembled sequence (SAS) with putative function; while 872 tags (16.7%) matched SAS with unknown function; 523 (10%) matched SAS without a putative annotation; and only 173 (3.3%) did not match any sugarcane ESTs. Based on gene ontology (GO), photosystem (PS) I reaction center was identified as the most frequent gene product location, followed by the remaining sites of PS I, PS II and thylakoid complexes. For metabolic processes, photosynthesis light harvesting complexes; carbon fixation; and chlorophyll biosynthesis were the most enriched GO-terms. Considering the alternative photosynthetic C(4) cycles, tag frequencies related to phosphoenolpyruvate carboxykinase (PEPCK) and aspartate aminotransferase compared to those for NADP(+)-malic enzyme (NADP-ME) and NADP-malate dehydrogenase, suggested that PEPCK-type decarboxylation appeared to predominate over NADP-ME in mature leaves, although both may occur, opposite to currently assumed in sugarcane. From the unique tag set, 894 tags (17.1%) were assigned as potentially derived from antisense transcripts, while 73 tags (1.4%) were assigned to more than one SAS, suggesting the occurrence of alternative processing. The occurrence of antisense was validated by quantitative reverse transcription amplification. Sugarcane leaf transcriptome provided new insights for functional studies associated with sucrose synthesis and accumulation.

Carbohydrate Metabolism↗

PubMed2026

The molecular similarity landscape of preclinical cancer models to patient tumors.

Selecting appropriate preclinical models is fundamental for translational oncology, yet a large-scale, multi-omic quantitative comparison of their similarity to primary human tumors is lacking. To address this, we integrated transcriptomic, proteomic, and genomic profiles from over 10,000 primary tumors from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), alongside 4,000 preclinical models. Using a robust computational framework, we revealed a clear hierarchy of transcriptomic and proteomic similarity to patient tumors: with patient-dervied xenografts (PDXs) having greater transcriptomic and proteomic similarity to patient tumors (>) compared with patient-derived organoids (PDOs), which are equal in hierarchy to that of PDX-dervied organoids (PDXOs) > cell lines. We also quantified high molecular conservation (Pearson correlation coefficient = 0.96) across paired in vitro to in vivo platform (organoids to PDX) transitions. Furthermore, genomic analysis demonstrated that whole-exome sequencing (WES) outperforms RNA-seq in detecting DNA variants, and it identified a clonal complexity hierarchy (cell lines > PDXOs > PDXs > PDOs) reflecting the effect of passaging history on intratumor heterogeneity. Ultimately, this study delivers a comprehensive quantitative benchmark, establishing a population-level hierarchy of molecular similarity between preclinical models and primary tumors and providing a data-driven reference for model selection. These findings offer a data-driven framework for selecting models that balance biological representativeness with experimental practicality.

Humans↗

PubMed2025

EucaMOD: a comprehensive multi-omics database for functional genomics research and molecular breeding of fast-growing eucalyptus trees.

Eucalyptus, one of the most widely planted plantation tree species globally, is primarily found in tropical and subtropical regions and contributes significantly to economic and social benefits. With advances in sequencing technologies, there is an increasing demand for the systematic analysis of multi-omics data among Eucalyptus species to enhance genetic breeding efforts. Although several early genomic databases have been established for eucalyptus, they have not been updated in a timely manner and lack recent multi-omics data, rendering them insufficient for current research needs. To address this gap, we developed the eucalyptus multi-omics database (EucaMOD, http://eucalyptusggd.net/eucamod), a comprehensive resource for cross-omics studies. In this study, we functionally annotated 45 eucalyptus genomes and structurally annotated 15, conducting comparative genomics and pan-proteomics analyses across all genomes. Additionally, we analyzed eucalyptus transcriptome, epigenome, and variome data through standardized workflows, enabling the in-depth mining and reanalysis of multi-omics datasets. EucaMOD is the most comprehensive multi-omics database for eucalyptus to date and includes data from 45 genomes (39 species), 870 mRNA-seq samples, 17 miRNA-seq samples, 52 epigenomic datasets (histone modifications and transcription factor binding), and genetic variation data from 1219 samples. To support functional genomics and molecular breeding research, the database is organized into the following 11 modules: Home, Species, Genomics, Comparative genomics, Pan-proteomics, Transcriptomics, Epigenetics, Variomics, Tools, Download, and Help. EucaMOD also offers online analysis tools for data mining, providing free public services to aid eucalyptus gene function and genetic engineering studies.

Eucalyptus↗

PubMed2006

Genome-wide location analysis: insights on transcriptional regulation.

Gene expression analysis of microarray data can provide a global view of the transcriptome of a cell or specific tissue type, revealing important information about the kinds of signaling pathways, genes and protein classifications that are active. However, transcript profiles alone do not reveal how expression levels are controlled or which transcription factors (TFs) are responsible. Establishing transcriptional regulatory networks requires knowledge of TFs bound to promoter, enhancer and repressor elements. Accessibility of these sites and an additional level of control are mediated by chromatin and DNA modifications. Genome-wide location analysis is a tool for identifying protein-DNA interaction sites on a genomic scale. Applications of this tool are proving invaluable in determining in vivo target genes of TFs, epigenetic marks and cis-regulatory elements. Here, we will discuss how advances have been made in each of these categories and how this has helped to elucidate regulatory networks and control mechanisms.

Animals↗

PubMed2026

A single-cell meta-analysis evidences transposable element dysregulation in sex-based differences in Parkinson's disease.

Transposable elements (TEs) (mobile genetic elements comprising ∼45% of the human genome) have recently emerged as potential contributors to Parkinson's disease (PD); however their role and sex-specific impact remain poorly understood. Here, we present the first integrative meta-analysis of TE expression across 4 substantia nigra single-nucleus RNA-seq datasets, comprising a total of 66 donors, generating a cell-type-resolved atlas of TE dysregulation in PD. We identified widespread TE activation across major brain cell types (i.e. neurons, astrocytes, oligodendrocytes and microglia), with marked upregulation of L1s in neurons and HERVs in oligodendrocytes. Sex-stratified analyses revealed distinct male- and female-biased TE signatures, indicating regulatory programs uniquely affected in each sex, including MIR elements in microglia and Alu subfamilies in neurons. Correlation and genomic proximity analyses also uncovered TE-gene associations linked to important PD pathways such as neuroinflammation or myelination. Collectively, our study positions TEs as potential sex-modulated contributors to PD pathology and also provides a public web resource (PATOSS) to explore PD-associated TE transcriptional deregulation.

Parkinson's disease↗

PubMed2026

Single-nucleus transcriptomics reveals cell type-specific remodeling and epilepsy-associated microglia.

Temporal lobe epilepsy (TLE) is the most common acquired epilepsy, causing refractory seizures and cognitive deficits. We performed single-nucleus RNA sequencing on hippocampal tissue from mice 3 and 6 weeks following pilocarpine-induced status epilepticus, a robust model of TLE. Epilepsy samples showed reductions in Cck and Lamp5-Lhx6 interneuron subclusters, alongside increases in Cajal-Retzius cells, dentate granule (DG) cell precursors, and a mature DG cell subcluster. Among glia, an astrocyte subcluster and a markedly expanded microglia sublcuster were increased. We term this microglia population epilepsy-associated microglia (EAM). The transcriptomic profile of EAM overlaps with microglia described in models of Alzheimer's disease and traumatic brain injury, including enrichment of Myo1e and Igf1. EAM display amoeboid morphology, can be found in clumps around pyramidal and granule cell body layers, and exhibit enlarged vesicles and mitochondria. Cell-cell interaction analysis predicts DG cells as their primary interaction partners. This dataset defines transcriptomic programs underlying key cellular alterations in TLE, enabling mechanistic dissection of epileptogenesis.

TLE↗

PubMed2026

Multistage Genetic, Transcriptomic, and Single-Cell Evidence Prioritizes MAP1LC3A among Ferroptosis-Related Genes in Glioblastoma.

Glioblastoma (GBM) remains a highly aggressive malignancy, and the contribution of ferroptosis-related genes to disease susceptibility remains incompletely understood. A genetically anchored, multistage framework was applied to prioritize ferroptosis-related genes associated with GBM. Among 483 genes curated from FerrDb V2, 315 had candidate cis-expression quantitative trait loci (cis-eQTLs) in eQTLGen, 250 retained at least three independent instruments after linkage disequilibrium clumping, and 226 yielded valid inverse-variance weighted (IVW) Mendelian randomization estimates using a GBM genome-wide association study comprising 6,183 cases and 18,169 controls. Thirty-four genes met the exploratory discovery criteria of P < 0.05 and a Benjamini-Hochberg false discovery rate (BH-FDR) < 0.20, with directionally concordant Bayesian weighted Mendelian randomization (BWMR) estimates. Replication-stage Mendelian randomization using GTEx V10 whole-blood cis-eQTLs supported four genes: ATG7, RPTOR, MAP1LC3A, and CHMP6. Evaluation across three independent tumor-control transcriptomic cohorts demonstrated that MAP1LC3A was consistently downregulated in tumor tissue and showed a significant random-effects pooled estimate (log₂ fold change, -1.273; 95% confidence interval, -1.625 to -0.920; false discovery rate = 0.016), whereas the other three genes lacked comparable cross-cohort statistical support. Single-cell virtual knockout analysis was subsequently performed in a patient-balanced subset of 2,400 malignant cells selected from 4,916 eligible cells across 20 adult IDH-wild-type GBM tumors. Across five independently seeded runs, 3, 15, 4, and 7 robust downstream genes were identified for ATG7, RPTOR, MAP1LC3A, and CHMP6, respectively. The resulting consensus sets comprised 17 unique genes, with RND3 shared across all four targets. Gene Ontology analysis indicated enrichment of cell-adhesion and cell-surface processes, whereas no KEGG or Reactome pathways remained significant after multiple-testing correction. Collectively, these findings prioritize MAP1LC3A for future experimental investigation while distinguishing genetic association, tumor-expression concordance, and computational perturbation from definitive evidence of causality or mechanism.

Humans↗

PubMed2005

A comparison of the aging and apoptotic transcriptome of Saccharomyces cerevisiae.

In this paper, we present the results of global transcript analysis by the microarray technique of senescent and apoptotic yeast cells. We compared young daughter and old mother cells isolated by elutriation centrifugation, and non-apoptotic and apoptotic cells induced either by a temperature shift of the cdc48(S565G) temperature-sensitive mutant or of the orc2-1 temperature-sensitive mutant. The majority of all genes found to be differentially regulated in these three physiological situations was upregulated, indicating that a cellular death process was initiated rather than an unspecific shut-down of gene expression due to immediate killing. The functional classes of genes upregulated in all three conditions were largely the same, although individual genes were in many cases not identical. The largest group of genes involved were nuclear genes coding for mitochondrial components or functions, which is understandable given the fact that apoptosis can be triggered by mitochondrially generated oxygen radicals and that mitochondria play an important role in the execution of apoptosis. Other functional classes consisted of genes involved in DNA damage response, in cell cycle regulation and checkpoints, in DNA repair, and in membrane lipid and cell wall synthesis. These functional classes represent the response of the cell to the known cellular insults, which occur during aging and apoptosis. As we have shown previously, final-stage senescent yeast mother cells (of the wild-type) are apoptotic.

Apoptosis↗

PubMed2001

Genomic expression analysis implicates Wnt signaling pathway and extracellular matrix alterations in hepatic specification and differentiation of murine hepatic stem cells.

HBC-3 hepatic stem cells maintained in the undifferentiated state can be induced to differentiate along the hepatocyte lineage in response to DMSO (Rogler, 1997). In order to understand the complex transcriptional regulatory mechanisms associated with the differentiation of these somatic stem cells and to identify novel candidate stem cell and differentiation associated genes, we have begun to characterize the transcriptome of HBC-3 cells during a 7-day differentiation protocol. This analysis showed that differentiating HBC-3 cells undergo biphasic bursts of gene regulation peaking at 3 hours and 120 hours of DMSO treatment. In the undifferentiated state, HBC-3 cells express muscle, neuron, myeloid, and lymphoid specific genes that are rapidly downregulated during hepatocytic differentiation. Cluster analysis has revealed large groups of genes with different temporal regulation profiles demonstrating complex and widespread transcriptional changes. Specifically, we discovered a multifaceted downregulation of the Wnt/beta-catenin pathway accompanied by the repression of TCF target genes during HBC-3 differentiation. In addition, there is downregulation of cellular receptors for fibronectin and laminin and other extracellular matrix molecules indicative of widespread cell surface alterations. DMSO induces cell cycle arrest, and this is reflected in upregulation of growth inhibitory proteins such as cyclin I and p18 and downregulation of cyclins B1 and D. Genes needed for hepatocytic functions, such as apolipoprotein C-IV, phosphoenolpyruvate carboxykinase, alcohol dehydrogenase, and asialoglycoprotein receptor were upregulated. Finally, transcriptional regulators including Twist, Snail, HNF1a, and GATA6 were upregulated during differentiation of HBC-3 cells. The significance of these findings is that our genome-based approach has allowed the parallel identification of multiple regulatory pathways that is needed to begin to fully understand the complex differentiation process.

Animals↗

PubMed2006

Identification of regulators of germ layer morphogenesis using proteomics in zebrafish.

During vertebrate gastrulation, a well-orchestrated series of morphogenetic changes leads to the formation of the three germ layers: the ectoderm, mesoderm and endoderm. The analysis of gene expression patterns during gastrulation has been central to the identification of genes involved in germ layer formation. However, many proteins are regulated on a translational or post-translational level and are thus undetectable by gene expression analysis. Therefore, we developed a 2D-gel-based comparative proteomic approach to target proteins involved in germ layer morphogenesis during zebrafish gastrulation. Proteomes of ectodermal and mesendodermal progenitor cells were compared and 35 significantly regulated proteins were identified by mass spectrometry, including several proteins with predicted functions in cytoskeletal organization. A comparison of our proteomic results with data obtained in an accompanying microarray-based gene expression analysis revealed no significant overlap, confirming the complementary nature of proteomics and transcriptomics. The regulation of ezrin2, which was identified based on a reduction in spot intensity in mesendodermal cells, was independently validated. Furthermore, we show that ezrin2 is activated by phosphorylation in mesendodermal cells and is required for proper germ layer morphogenesis. We demonstrate the feasibility of proteomics in zebrafish, concluding that proteomics is a valuable tool for analysis of early development.

Animals↗

PubMedDate not supplied

From the messenger RNA saga to the transcriptome era.

This review attempts to provide an overview of the evolution of the ideas and techniques that prevailed at the beginning of research on ribonucleic acids, until the contemporary era of cellular transcript analysis using DNA biochips and microarrays. Certain applications derived from the use of microarrays and the corresponding analyses of transcriptomes are discussed, particularly concerning diagnosis and prevision of evolution of certain cancers.

Cloning, Molecular↗

PubMed2006

A method for similarity search of genomic positional expression using CAGE.

With the advancement of genome research, it is becoming clear that genes are not distributed on the genome in random order. Clusters of genes distributed at localized genome positions have been reported in several eukaryotes. Various correlations have been observed between the expressions of genes in adjacent or nearby positions along the chromosomes depending on tissue type and developmental stage. Moreover, in several cases, their transcripts, which control epigenetic transcription via processes such as transcriptional interference and genomic imprinting, occur in clusters. It is reasonable that genomic regions that have similar mechanisms show similar expression patterns and that the characteristics of expression in the same genomic regions differ depending on tissue type and developmental stage. In this study, we analyzed gene expression patterns using the cap analysis gene expression (CAGE) method for exploring systematic views of the mouse transcriptome. Counting the number of mapped CAGE tags for fixed-length regions allowed us to determine genomic expression levels. These expression levels were normalized, quantified, and converted into four types of descriptors, allowing the expression patterns along the genome to be represented by character strings. We analyzed them using dynamic programming in the same manner as for sequence analysis. We have developed a novel algorithm that provides a novel view of the genome from the perspective of genomic positional expression. In a similarity search of expression patterns across chromosomes and tissues, we found regions that had clusters of genes that showed expression patterns similar to each other depending on tissue type. Our results suggest the possibility that the regions that have sense-antisense transcription show similar expression patterns between forward and reverse strands.

Algorithms↗

PubMed2026

Pan-Cancer Quantification of Driver Alteration Transmission Across Molecular Layers Reveals Limited Propagation to Protein Abundance.

Precision oncology relies primarily on DNA-level alterations for therapeutic decisions, but the extent to which driver mutations propagate to protein abundance has not been systematically evaluated. Here, I developed a regression-based transmission score (TS_R 2) to quantify driver alteration signal propagation across DNA, mRNA, and protein layers. Applying this framework to matched genomic, transcriptomic, proteomic, and phosphoproteomic data from 754 Clinical Proteomic Tumor Analysis Consortium (CPTAC) tumors across seven cancer types, I analyzed 86 driver gene-cancer type pairs, of which 83 were evaluable for the full two-layer transmission score. I employed covariate-adjusted regression for each molecular transition, assessing significance via permutation testing (n = 1000). Mixed-effects modeling then partitioned gene-intrinsic from cancer-type-dependent effects. Only 5 of 83 evaluable pairs (6%) demonstrated high transmission (TS_R 2 > 0.05), with receptor tyrosine kinases (EGFR, FGFR2) exemplifying this class. The primary bottleneck occurred at the mutation-mRNA transition, not mRNA-protein translation. Gene identity accounted for 49% of transmission efficiency variance, nearly double the contribution of cancer type (29%). Copy number alterations transmitted signals 13.8-fold more efficiently than point mutations, and truncating mutations showed higher transmission than missense variants (Wilcoxon p = 0.005). Microsatellite instability attenuated mRNA-protein transmission in UCEC and COAD. These findings demonstrate that many driver alterations show limited propagation to protein abundance. This challenges DNA-only interpretations in precision oncology and provides a framework for integrated functional driver prioritization.

Humans↗

PubMed2006

Staying alive in adversity: transcriptome dynamics in the stress-resistant dauer larva.

In response to food depletion and overcrowding, the soil nematode Caenorhabditis elegans can arrest development and form an alternate third larval stage called the dauer. Though nonfeeding, the dauer larva is long lived and stress resistant. Metabolic and transcription rates are lowered but the transcriptome of the dauer is complex. In this study, distribution analysis of transcript profiles generated by Serial Analysis of Gene Expression (SAGE) in dauer larvae and in mixed developmental stages is presented. An inverse relationship was observed between frequency and abundance/copy number of SAGE tag types (transcripts) in both profiles. In the dauer profile, a relatively greater proportion of highly abundant transcripts was counterbalanced by a smaller fraction of low to moderately abundant transcripts. Comparisons of abundant tag counts between the two profiles revealed relative enrichment in the dauer profile of transcripts with predicted or known involvement in ribosome biogenesis and protein synthesis, membrane transport, and immune responses. Translation-coupled mRNA decay is proposed as part of an immune-like stress response in the dauer larva. An influence of genomic region on transcript level may reflect the coordination of transcription and mRNA turnover.

Acclimatization↗

PubMed2024

Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome.

Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here, we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Modeling of perturbation-induced heterogeneity connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state. A record of this paper's transparent peer review process is included in the supplemental information.

Humans↗