Transcriptional Variation Research Articles

Functional Genes and Transcripts Indicate the Existent and Active Microbial Mercury-Methylating Community in Mangrove Intertidal Sediments of an Urbanized Bay.

Mercury (Hg) methylation in mangrove sediments can result in the accumulation of neurotoxic methylmercury (MeHg). Identification of Hg methyltransferase gene hgcA provides the means to directly characterize the microbial Hg-methylating consortia in environments. Hitherto, the microbial Hg-methylating community in mangrove sediments was scarcely investigated. An effort to assess the diversity and abundance of hgcA genes and transcripts and link them to Hg and MeHg contents was made in the mangrove intertidal sediments along the urbanized Shenzhen Bay, China. The hgcA genes and transcripts associated with Thermodesulfobacteria [mainly Geobacteraceae, Syntrophorhabdaceae, Desulfobacterales, and Desulfarculales (these four lineages were previously classified into the Deltaproteobacteria taxon)], as well as Euryarchaeota (mainly Methanomicrobia and Theionarchaea) dominated the hgcA-harboring communities, while Chloroflexota, Nitrospirota, Planctomycetota, and Lentisphaerota-like hgcA sequences accounted for a small proportion. The hgcA genes appeared in greater abundance and diversity than their transcript counterparts in each sampling site. Correlation analysis demonstrated that the MeHg content rather than Hg content significantly correlated with the structure of the existent/active hgcA-harboring community and the abundance of hgcA genes/transcripts. These findings provide better insights into the microbial Hg methylation drivers in mangrove sediments, which could be helpful for understanding the MeHg biotransformation therein.

HGG-29. INTEGRATED MOLECULAR PROFILING OF >2000 PAEDIATRIC-TYPE DIFFUSE HIGH-GRADE GLIOMA TUMOURS AND >100 PATIENT-DERIVED MODELS

Abstract BACKGROUND Paediatric-type diffuse high-grade glioma (PDHGG) is recognised in the WHO2021 CNS Tumour Classification as biologically distinct from ‘adult-types’, and comprises four major categories based on distinct biology and clinical presentation, though sub-types within these are less well-defined. METHODS Published and unpublished genome/exome/targeted sequencing from n=1593 cases were integrated with n=2027 cases with methylation array profiling, with an overlap of n=761. These were supplemented with varying availability of bulk/single-cell RNAseq, ChIP-seq and ATAC-seq, and analysed alongside data from ~100 patient-derived models representing 16 PDHGG sub-types. RESULTS Around half of cases were diffuse midline glioma with H3K27 alterations (DMG-H3K27), which can be split into sub-types based upon either the specific histone alteration (DMG-H3.3K27M/-H3.1K27M/-EZHIP) or co-segregating pathway activating mutations (DMG-EGFR/-MAPK/-ACVR1). These showed distinct copy number, transcriptomic and epigenetic signatures depending on the anatomical location, replicated in ~50 models established as 2D/3D cultures and CDX/PDX. By contrast, diffuse hemispheric glioma with H3G34 mutations (DHG-H3G34) presented a homogenous genomic landscape (TP53/ATRX/PDGFRA) but with a higher degree of transcriptional diversity in both tumours and models. In high-grade glioma, H3/IDH-wild-type (HGG-WT) samples, receptor tyrosine kinase (RTK) subtypes are split by the presence or absence of co-segregating mutations (BCOR/SETD2/NF1) and copy number changes. Across methylation-based subtypes, genetic drivers are associated with distinct phenotypes or drug responses independent of location. EGFR mutations are largely confined to the highly infiltrative pedHGG_RTK2 hemispheric (enriched in gliomatosis cerebri) and DMG-EGFR (bithalamic glioma) subtypes, whilst PDGFRAmutations span DMG-H3.3K27M, DHG-H3G34, and pedHGG-RTK1, and exhibit a differential drug response to targeted therapies depending on the nature of the alteration. Hypermutant tumours are split between pedHGG-RTK1A and the emerging ‘HGG-E’ subtype. CONCLUSIONS These data aim to catalogue the diversity of PDHGG subtypes in order to identify biologically rational targets, and credential patient-derived models which can be exploited for mechanistic/preclinical studies.

Correction: Reduced protein-coding transcript diversity in severe dengue emphasises the role of alternative splicing.

Correction: Reduced protein-coding transcript diversity in severe dengue emphasises the role of alternative splicing.

TAD hierarchy restricts poised LTR activation and loss of TAD hierarchy promotes LTR co-option in cancer.

Transposable elements (TEs) are abundant in the human genome, and they provide the sources for genetic and functional diversity. The regulation of TEs expression and their functional consequences in physiological conditions and cancer development remain to be fully elucidated. Previous studies suggested TEs are repressed by DNA methylation and chromatin modifications. The effect of 3D chromatin topology on TE regulation remains elusive. Here, by integrating transcriptome and 3D genome architecture studies, we showed that haploinsufficient loss of NIPBL selectively activates alternative promoters at the long terminal repeats (LTRs) of the TE subclasses. This activation occurs through the reorganization of topologically associating domain (TAD) hierarchical structures and recruitment of proximal enhancers. These observations indicate that TAD hierarchy restricts transcriptional activation of LTRs that already possess open chromatin features. In cancer, perturbation of the hierarchical chromatin topology can lead to co-option of LTRs as functional alternative promoters in a context-dependent manner and drive aberrant transcriptional activation of novel oncogenes and other divergent transcripts. These data uncovered a new layer of regulatory mechanism of TE expression beyond DNA and chromatin modification in human genome. They also posit the TAD hierarchy dysregulation as a novel mechanism for alternative promoter-mediated oncogene activation and transcriptional diversity in cancer, which may be exploited therapeutically.

Transcription factor binding site divergence across maize inbred lines drives transcriptional and phenotypic variation.

Regulatory elements are important constituents of plant genomes that have shaped ancient and modern crops. Their identification, function, and diversity in crop genomes however are poorly characterized, thus limiting our ability to harness their power for further agricultural advances using induced or natural variation. Here, we use DNA affinity purification-sequencing (DAP-seq) to map transcription factor (TF) binding events for 200 maize TFs belonging to 30 distinct families and heterodimer pairs in two distinct inbred lines historically used for maize hybrid plant production, providing empirical binding site annotation for 5.3% of the maize genome. TF binding site comparison in B73 and Mo17 inbreds reveals widespread differences, driven largely by structural variation, that correlate with gene expression changes. TF binding site presence-absence variation helps clarify complex QTL such as vgt1, an important determinant of maize flowering time, and DICE, a distal enhancer involved in herbivore resistance. Modification of TF binding regions via CRISPR-Cas9 mediated editing alters target gene expression and phenotype. Our functional catalog of maize TF binding events enables collective and comparative TF binding analysis, and highlights its value for agricultural improvement.

Enhancing Clinical Documentation with Synthetic Data: Leveraging Generative Models for Improved Accuracy

Accurate and comprehensive clinical documentation is crucial for delivering high-quality healthcare, facilitating effective communication among providers, and ensuring compliance with regulatory requirements. However, manual transcription and data entry processes can be time-consuming, error-prone, and susceptible to inconsistencies, leading to incomplete or inaccurate medical records. This paper proposes a novel approach to augment clinical documentation by leveraging synthetic data generation techniques to generate realistic and diverse clinical transcripts. We present a methodology that combines state-of- the-art generative models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), with real-world clinical transcript and other forms of clinical data to generate synthetic transcripts. These synthetic transcripts can then be used to supplement existing documentation workflows, providing additional training data for natural language processing models and enabling more accurate and efficient transcription processes. Through extensive experiments on a large dataset of anonymized clinical transcripts, we demonstrate the effectiveness of our approach in generating high- quality synthetic transcripts that closely resemble real- world data. Quantitative evaluation metrics, including perplexity scores and BLEU scores, as well as qualitative assessments by domain experts, validate the fidelity and utility of the generated synthetic transcripts. Our findings highlight synthetic data generation's potential to address clinical documentation challenges, improving patient care, reducing administrative burdens, and enhancing healthcare system efficiency.

Reduced protein-coding transcript diversity in severe dengue emphasises the role of alternative splicing.

Dengue fever, a neglected tropical arboviral disease, has emerged as a global health concern in the past decade. Necessitating a nuanced comprehension of the intricate dynamics of host-virus interactions influencing disease severity, we analysed transcriptomic patterns using bulk RNA-seq from 112 age- and gender-matched NS1 antigen-confirmed hospital-admitted dengue patients with varying severity. Severe cases exhibited reduced platelet count, increased lymphocytosis, and neutropenia, indicating a dysregulated immune response. Using bulk RNA-seq, our analysis revealed a minimal overlap between the differentially expressed gene and transcript isoform, with a distinct expression pattern across the disease severity. Severe patients showed enrichment in retained intron and nonsense-mediated decay transcript biotypes, suggesting altered splicing efficiency. Furthermore, an up-regulated programmed cell death, a haemolytic response, and an impaired interferon and antiviral response at the transcript level were observed. We also identified the potential involvement of the RBM39 gene among others in the innate immune response during dengue viral pathogenesis, warranting further investigation. These findings provide valuable insights into potential therapeutic targets, underscoring the importance of exploring transcriptomic landscapes between different disease sub-phenotypes in infectious diseases.

Shiba: A unified computational method for robust identification of differential RNA splicing across platforms.

Alternative pre-mRNA splicing (AS) is a fundamental regulatory process that generates transcript diversity and cell type variation. We developed Shiba, a robust method integrating transcript assembly, splicing event identification, read counting, and statistical analysis, to efficiently quantify exon splicing levels across various types of RNA-seq datasets. Compared to existing pipelines, Shiba excels in capturing both annotated and unannotated or cryptic differential splicing events with superior accuracy, sensitivity, and reproducibility. Furthermore, Shiba's unique consideration of junction read imbalance and exon-body read coverage reduces false positives, essential for downstream functional analyses. We have further developed scShiba for single-cell/nucleus (sc/sn) RNA-seq data, enabling the exploration of splicing variations in heterogeneous cell populations. Both simulated and real data demonstrate Shiba's robustness across multiple sample sizes, including n=1 datasets and individual cell clusters from scRNA-seq. Application of Shiba on single replicates of RNA-seq identified new AS-NMD targets, and scShiba on snRNA-seq revealed intricate temporal AS regulation in dopaminergic neurons. Both Shiba and scShiba are provided in Docker/Singularity containers and Snakemake pipeline, enhancing accessibility and reproducibility. The comprehensive capabilities of Shiba and scShiba allow systematic and robust quantification of alternative splicing events, laying a solid foundation for mechanistic exploration of functional complexity in RNA splicing.

Nascent transcription reveals regulatory changes in extremophile fishes inhabiting hydrogen sulfide-rich environments.

Regulating transcription allows organisms to respond to their environment, both within a single generation (plasticity) and across generations (adaptation). We examined transcriptional differences in gill tissues of fishes in the Poecilia mexicana species complex (family Poeciliidae), which have colonized toxic springs rich in hydrogen sulfide (H2S) in southern Mexico. There are gene expression differences between sulfidic and non-sulfidic populations, yet regulatory mechanisms mediating this gene expression variation remain poorly studied. We combined capped-small RNA sequencing (csRNA-seq), which captures actively transcribed (i.e. nascent) transcripts, and messenger RNA sequencing (mRNA-seq) to examine how variation in transcription, enhancer activity, and associated transcription factor binding sites may facilitate adaptation to extreme environments. csRNA-seq revealed thousands of differentially initiated transcripts between sulfidic and non-sulfidic populations, many of which are involved in H2S detoxification and response. Analyses of transcription factor binding sites in promoter and putative enhancer csRNA-seq peaks identified a suite of transcription factors likely involved in regulating H2S-specific shifts in gene expression, including several key transcription factors known to respond to hypoxia. Our findings uncover a complex interplay of regulatory processes that reflect the divergence of extremophile populations of P. mexicana from their non-sulfidic ancestors and suggest shared responses among evolutionarily independent lineages.

Single-cell analysis reveals cellular and molecular factors counteracting HPV-positive oropharyngeal cancer immunotherapy outcomes

BackgroundOropharyngeal squamous cell carcinoma (OPSCC) induced by human papillomavirus (HPV-positive) is associated with better clinical outcomes than HPV-negative OPSCC. However, the clinical benefits of immunotherapy in patients with HPV-positive OPSCC...

Genetic architecture and correlations between the gut microbiome and gut gene transcription in Chinook salmon (Oncorhynchus tshawytscha).

Population divergence through selection can drive local adaptation in natural populations which has implications for the effective restoration of declining and extirpated populations. However, adaptation to local environmental conditions is complicated when both the host and its associated microbiomes must respond via co-evolutionary change. Nevertheless, for adaptation to occur through selection, variation in both host and microbiome traits should include additive genetic effects. Here we focus on host immune function and quantify factors affecting variation in gut immune gene transcription and gut bacterial community composition in early life-stage Chinook salmon (Oncorhynchus tshawytscha). Specifically, we utilized a replicated factorial breeding design to determine the genetic architecture (sire, dam and sire-by-dam interaction) of gut immune gene transcription and microbiome composition. Furthermore, we explored correlations between host gut gene transcription and microbiota composition. Gene transcription was quantified using nanofluidic qPCR arrays (22 target genes) and microbiota composition using 16 S rRNA gene (V5-V6) amplicon sequencing. We discovered limited but significant genetic architecture in gut microbiota composition and transcriptional profiles. We also identified significant correlations between gut gene transcription and microbiota composition, highlighting potential mechanisms for functional interactions between the two. Overall, this study provides support for the co-evolution of host immune function and their gut microbiota in Chinook salmon, a species recognized as locally adapted. Thus, the inclusion of immune gene transcription profile and gut microbiome composition as factors in the development of conservation and commercial rearing practices may provide new and more effective approaches to captive rearing.

H3.3-G34W in giant cell tumor of bone functionally aligns with the exon choice repressor hnRNPA1L2

RNA processing is an essential post-transcriptional phenomenon that provides the necessary complexity of transcript diversity prior to translation. Aberrations in this process could contribute to tumourigenesis, and we have previously reported increased splicing alterations in giant cell tumor of bone (GCTB), which carries mutations in the histone variant H3.3 encoding glycine 34 substituted for tryptophan (H3.3-G34W). G34W interacts with several splicing factors, most notably the trans-acting splicing factor hnRNPA1L2. To gain a deeper understanding of RNA processing in GCTB and isogenic HeLa cells with H3.3-G34W, we generated RNA-immunoprecipitation sequencing data from hnRNPA1L2 and H3.3-G34W associated RNAs, which showed that 80% overlapped across genic regions and were frequently annotated as E2F transcription factor binding sites. Splicing aberrations in both GCTB and HeLa cells with H3.3-G34W were significantly enriched for known hnRNPA1L2 binding motifs (p value < 0.01). This splicing aberration differed from hnRNPA1L2 knockouts, which showed alterations independent of H3.3-G34W. Of functional significance, hnRNPA1L2 was redistributed to closely match the H3.3 pattern, likely driven by G34W, and to loci not occupied in normal parental cells. Taken together, our data reveal a functional overlap between hnRNPA1L2 and H3.3-G34W with likely significant consequences for RNA processing during GCTB pathogenesis. This provides novel opportunities for therapeutic intervention in future modus operandi.

Nociceptor-immune interactomes reveal insult-specific immune signatures of pain

Inflammatory pain results from the heightened sensitivity and reduced threshold of nociceptor sensory neurons due to exposure to inflammatory mediators. However, the cellular and transcriptional diversity of immune cell and sensory neuron types makes it challenging to decipher the immune mechanisms underlying pain. Here we used single-cell transcriptomics to determine the immune gene signatures associated with pain development in three skin inflammatory pain models in mice: zymosan injection, skin incision and ultraviolet burn. We found that macrophage and neutrophil recruitment closely mirrored the kinetics of pain development and identified cell-type-specific transcriptional programs associated with pain and its resolution. Using a comprehensive list of potential interactions mediated by receptors, ligands, ion channels and metabolites to generate injury-specific neuroimmune interactomes, we also uncovered that thrombospondin-1 upregulated by immune cells upon injury inhibited nociceptor sensitization. This study lays the groundwork for identifying the neuroimmune axes that modulate pain in diverse disease contexts.

Establishing an optimized ATAC-seq protocol for the maize.

The advent of next-generation sequencing in crop improvement offers unprecedented insights into the chromatin landscape closely linked to gene activity governing key traits in plant development and adaptation. Particularly in maize, its dynamic chromatin structure is found to collaborate with massive transcriptional variations across tissues and developmental stages, implying intricate regulatory mechanisms, which highlights the importance of integrating chromatin information into breeding strategies for precise gene controls. The depiction of maize chromatin architecture using Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) provides great opportunities to investigate cis-regulatory elements, which is crucial for crop improvement. In this context, we developed an easy-to-implement ATAC-seq protocol for maize with fewer nuclei and simple equipment. We demonstrate a streamlined ATAC-seq protocol with four key steps for maize in which nuclei purification can be achieved without cell sorting and using only a standard bench-top centrifuge. Our protocol, coupled with the bioinformatic analysis, including validation by read length periodicity, key metrics, and correlation with transcript abundance, provides a precise and efficient assessment of the maize chromatin landscape. Beyond its application to maize, our testing design holds the potential to be applied to other crops or other tissues, especially for those with limited size and amount, establishing a robust foundation for chromatin structure studies in diverse crop species.

Transcriptome analysis reveals molecular targets of erythrocyte invasion phenotype diversity in natural Plasmodium falciparum isolates from Cameroon

Further understanding of the molecular mediators of alternative RBC invasion phenotypes in endemic malaria parasites will support malaria blood-stage vaccine or drug development. This study investigated the prevalence of sialic acid (SA)-dependent and SA-independent RBC invasion pathways in endemic Plasmodium falciparum parasites from Cameroon and compared the schizont stage transcriptomes in these two groups to uncover the wider repertoire of transcriptional variation associated with the use of alternative RBC invasion pathway phenotypes. A two-color flow cytometry-based invasion-inhibition assay against RBCs treated with neuraminidase, trypsin, and chymotrypsin and deep RNA sequencing of schizont stages harvested in the first ex vivo replication cycle in culture were employed in this investigation. RBC invasion phenotypes were determined for 63 isolates from asymptomatic children with uncomplicated malaria. Approximately 80% of the isolates invaded neuraminidase-treated but not chymotrypsin-treated RBCs, representing SA-independent pathways of RBC invasion. The schizont transcriptome profiles of 16 isolates with invasion phenotypes revealed a total of 5,136 gene transcripts, with 85% of isolates predicted at schizont stages. Two distinct transcriptome profile clusters belonging to SA-dependent and SA-independent parasites were obtained by data reduction with principal component analysis. Differential analysis of gene expression between the two clusters implicated, in addition to the well-characterized adhesins, the upregulation of genes encoding proteins mediating merozoite organelle discharges as well as several conserved, virulent, merozoite-associated, and exported proteins. The latter majority have been shown to have structural and physiological relevance to RBC surface remodeling and immune evasion in malaria and thus have potential as anti-invasion targets.

Comprehensive data mining reveals RTK/RAS signaling pathway as a promoter of prostate cancer lineage plasticity through transcription factors and CNV

Prostate cancer lineage plasticity is a key driver in the transition to neuroendocrine prostate cancer (NEPC), and the RTK/RAS signaling pathway is a well-established cancer pathway. Nevertheless, the comprehensive link between the RTK/RAS signaling pathway and lineage plasticity has received limited investigation. In particular, the intricate regulatory network governing the interplay between RTK/RAS and lineage plasticity remains largely unexplored. The multi-omics data were clustered with the coefficient of argument and neighbor joining algorithm. Subsequently, the clustered results were analyzed utilizing the GSEA, gene sets related to stemness, multi-lineage state datasets, and canonical cancer pathway gene sets. Finally, a comprehensive exploration of the data based on the ssGSEA, WGCNA, GSEA, VIPER, prostate cancer scRNA-seq data, and the GPSAdb database was conducted. Among the six modules in the clustering results, there are 300 overlapping genes, including 3 previously unreported prostate cancer genes that were validated to be upregulated in prostate cancer through RT-qPCR. Function Module 6 shows a positive correlation with prostate cancer cell stemness, multi-lineage states, and the RTK/RAS signaling pathway. Additionally, the 19 leading-edge genes of the RTK/RAS signaling pathway promote prostate cancer lineage plasticity through a complex network of transcriptional regulation and copy number variations. In the transcriptional regulation network, TP63 and FOXO1 act as suppressors of prostate cancer lineage plasticity, whereas RORC exerts a promoting effect. This study provides a comprehensive perspective on the role of the RTK/RAS pathway in prostate cancer lineage plasticity and offers new clues for the treatment of NEPC.

Diversity of transcripts of toll-like receptors in hemocytes of Planorbarius corneus mollusсs (Gastropoda, Pulmonata) uninfected and infected with Bilharziella polonica trematodes

Transcriptome of hemocytes from uninfected Planorbarius corneus snails and snails naturally infected with Bilharziella polonica (Schistosomatidae) was obtained and analyzed. Transcripts encoding all groups of immune factors previously described for other gastropods were found. Pathogen recognition molecules are the most diverse group of transcripts encoding immunity factors. Toll-like receptors of 11 types were identified. No differences in the set of toll-like receptors between infected and uninfected mollusсs were found. The data obtained expand our knowledge on immune reactions of snails to trematode invasion and make it possible to consider Planorbarius corneus as a new model for studying molluscs immune reactions.

Comprehensive analysis of KLF family reveals KLF6 as a promising prognostic and immune biomarker in pancreatic ductal adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma (PDAC) is one of the deadliest tumors worldwide, with extremely aggressive and complicated biology. Krüppel-like factors (KLFs) encode a series of transcriptional regulatory proteins and play crucial roles in a variety of processes, including tumor cell differentiation and proliferation. However, the potential biological functions and possible pathways of KLFs in the progression of PDAC remain elusive.MethodsWe systematically evaluated the transcriptional variations and expression patterns of KLFs in pancreatic cancer from the UCSC Xena. Based on difference analysis, the non-negative matrix factorization (NMF) algorithm was utilized to identify the immune characteristics and clinical significance of two different subtypes. The multivariate Cox regression was used to construct the risk model and then explore the differences in tumor immune microenvironment (TIME) and drug sensitivity between high and low groups. Through single-cell RNA sequencing (scRNA-seq) analysis, we screened KLF6 and further investigated its biological functions in pancreatic cancer and pan-cancer.ResultsThe KLFs exhibited differential expression and mutations in the transcriptomic profile of PDAC. According to the expression of KLFs, patients were classified into two distinct subtypes, each exhibiting significant differences in prognosis and TIME. Moreover, the KLF signature was developed using univariate Cox and Lasso regression, which proved to be a reliable and effective prognostic model. Furthermore, the KLF_Score was closely associated with immune infiltration, response to immunotherapy, and drug sensitivity and we screened small molecule compounds targeting prognostic genes separately. Through scRNA-seq analysis, KLF6 was selected to further demonstrate its role in the malignance of PC in vitro. Finally, pan-cancer analysis emphasized the biological significance of KLF6 in multiple types of tumors and its clinical utility in assessing cancer prognosis.ConclusionThis study elucidated the pivotal role of KLF family genes in the malignant development of PC through comprehensive analysis and revealed that KLF6 would be a novel diagnostic biomolecule marker and potential therapeutic target for PDAC.

ChIP-Atlas 3.0: a data-mining suite to explore chromosome architecture together with large-scale regulome data.

ChIP-Atlas (https://chip-atlas.org/) presents a suite of data-mining tools for analyzing epigenomic landscapes, powered by the comprehensive integration of over 376000 public ChIP-seq, ATAC-seq, DNase-seqand Bisulfite-seq experiments from six representative model organisms. To unravel the intricacies of chromatin architecture that mediates the regulome-initiated generation of transcriptional and phenotypic diversity within cells, we report ChIP-Atlas 3.0 that enhances clarity by incorporating additional tracks for genomic and epigenomic features within a newly consolidated 'annotation track' section. The tracks include chromosomal conformation (Hi-C and eQTL datasets), transcriptional regulatory elements (ChromHMM and FANTOM5 enhancers), and genomic variants associated with diseases and phenotypes (GWAS SNPs and ClinVar variants). These annotation tracks are easily accessible alongside other experimental tracks, facilitating better elucidation of chromatin architecture underlying the diversification of transcriptional and phenotypic traits. Furthermore, 'Diff Analysis,' a new online tool, compares the query epigenome data to identify differentially bound, accessible, and methylated regions using ChIP-seq, ATAC-seq and DNase-seq, and Bisulfite-seq datasets, respectively. The integration of annotation tracks and the Diff Analysis tool, coupled with continuous data expansion, renders ChIP-Atlas 3.0 a robust resource for mining the landscape of transcriptional regulatory mechanisms, thereby offering valuable perspectives, particularly for genetic disease research and drug discovery.

SCTC: inference of developmental potential from single-cell transcriptional complexity.

Inferring the developmental potential of single cells from scRNA-Seq data and reconstructing the pseudo-temporal path of cell development are fundamental but challenging tasks in single-cell analysis. Although single-cell transcriptional diversity (SCTD) measured by the number of expressed genes per cell has been widely used as a hallmark of developmental potential, it may lead to incorrect estimation of differentiation states in some cases where gene expression does not decrease monotonously during the development process. In this study, we propose a novel metric called single-cell transcriptional complexity (SCTC), which draws on insights from the economic complexity theory and takes into account the sophisticated structure information of scRNA-Seq count matrix. We show that SCTC characterizes developmental potential more accurately than SCTD, especially in the early stages of development where cells typically have lower diversity but higher complexity than those in the later stages. Based on the SCTC, we provide an unsupervised method for accurate, robust, and transferable inference of single-cell pseudotime. Our findings suggest that the complexity emerging from the interplay between cells and genes determines the developmental potential, providing new insights into the understanding of biological development from the perspective of complexity theory.