Comprehensive Annotation Research Articles

Mettannotator: a comprehensive and scalable Nextflow annotation pipeline for prokaryotic assemblies.

In recent years there has been a surge in prokaryotic genome assemblies, coming from both isolated organisms and environmental samples. These assemblies often include novel species that are poorly represented in reference databases creating a need for a tool that can annotate both well-described and novel taxa, and can run at scale. Here, we present mettannotator-a comprehensive, scalable Nextflow pipeline for prokaryotic genome annotation that identifies coding and non-coding regions, predicts protein functions, including antimicrobial resistance, and delineates gene clusters. The pipeline summarises the results of these tools in a GFF (General Feature Format) file that can be easily utilised in downstream analysis or visualised using common genome browsers. Here, we show how it works on 200 genomes from 29 prokaryotic phyla, including isolate genomes and known and novel metagenome-assembled genomes, and present metrics on its performance in comparison to other tools. The pipeline is written in Nextflow and Python and published under an open source Apache 2.0 licence. Instructions and source code can be accessed at https://github.com/EBI-Metagenomics/mettannotator. The pipeline is also available on WorkflowHub: https://workflowhub.eu/workflows/1069. Supplementary data are available at Bioinformatics online.

SUMMER: an integrated nanopore sequencing pipeline for variants detection and clinical annotation on the human genome

Long-read sequencing has emerged as a transformative technology in recent years, offering significant potential for the molecular diagnosis of unresolved genetic disorders. Despite its promise, the comprehensive detection and clinical annotation of genomic variants remain intricate and technically demanding. We present SUMMER, an integrated and structured workflow specifically designed to process raw Nanopore sequencing reads. SUMMER facilitates an in-depth analysis of multiple variant types, including SNV, SV, short tandem repeat and mobile element insertion. For clinical applications, SUMMER employs SvAnna to prioritize SV candidates based on phenotype relevance and utilizes Straglr to provide reference distributions of non-pathogenic unit counts for 55 known pathogenic short tandem repeats. By addressing critical challenges in variant detection and annotation, SUMMER seeks to advance the clinical utility of long-read sequencing in diagnostic genomics. SUMMER is available on the web at https://github.com/carolhuaxia/summer.

Comprehensive genome annotation of Trilocha varians, a new model species of Lepidopteran insects

Trilocha varians is a member of the bombycid moths. Since T. varians has a considerably shorter generation period than the prevailing model species, Bombyx mori, this species would be a novel model insect in Lepidoptera. To facilitate further use of T. varians, we developed genome annotation information on the chromosome-scale assembly of T. varians previously published by our group. 9 RNA-seq datasets and 2 Iso-seq datasets were submitted for transcriptome-based gene prediction. As a result, 16,266 protein-coding genes were predicted on the latest genome assembly, and 98.6% of BUSCO sequences were present in our gene models. ATAC-seq was also conducted to determine chromatin accessibility across the genome. Finally, piRNA-targeted small RNA-seq revealed T. varians genome harbours 517 piRNA clusters (piCs). This information will encourage and facilitate potential users who plan to use this species.

Whole genome sequence-based association analysis of African American individuals with bipolar disorder and schizophrenia.

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study). We increased power by incorporating 14,812 jointly called psychiatrically unscreened ancestry-matched controls from the Trans-Omics for Precision Medicine (TOPMed) Program for a total of 17,463 controls. To identify variants and sets of variants associated with BD and/or SZ, we performed single-variant tests, gene-based tests for singleton protein truncating variants, and rare and low-frequency variant annotation-based tests with conservation and universal chromatin states and sliding windows. We found suggestive evidence of BD association with single-variants on chromosome 18 and of lower BD risk associated with rare and low-frequency variants on chromosome 11 in a region with multiple BD GWAS loci, using a sliding window approach. We also found that chromatin and conservation state tests can be used to detect differential calling of variants in controls sequenced at different centers and to assess the effectiveness of sequencing metric covariate adjustments. Our findings reinforce the need for continued whole genome sequencing in additional samples of African American individuals and more comprehensive functional annotation of non-coding variants.

Understanding the triacylglycerol-based carbon anabolic differentiation in Cyperus esculentus and Cyperus rotundus developing tubers via transcriptomic and metabolomic approaches

BackgroundYellow nutsedge (Cyperus esculentus, known as ‘YouShaDou’ in China, YSD) and purple nutsedge (Cyperus rotundus, known as ‘XiangFuZi’ in China, XFZ), closely related Cyperaceae species, exhibit significant differences in triacylglycerol (TAG) accumulation within their tubers, a key factor in carbon flux repartitioning that highly impact the total lipid, carbohydrate and protein metabolisms. Previous studies have attempted to elucidate the carbon anabolic discrepancies between these two species, however, a lack of comprehensive genome-wide annotation has hindered a detailed understanding of the underlying molecular mechanisms.ResultsThis study utilizes transcriptomic analyses, supported by a comprehensive YSD reference genome, and metabolomic profiling to uncover the mechanisms underlying the major carbon perturbations between the developing tubers of YSD and XFZ germplasms harvested in Yunnan province, China, where the plant biodiveristy is renowned worldwide and may contain more genetic variations relative to their counterparts in other places. Our findings indicate distinct expression patterns of key regulatory genes involved in TAG biosynthesis and lipid droplet formation, including transcriptional factors and structural genes such as ABI3 transcriptional factor, rate-limiting enzymes GPAT3/6/9 and DGAT2/3, and oleosin and caleosin homologs. Furthermore, our omics data suggest that these differences in gene expression are not the sole contributors to the diverse tuber compositions. Instead, complex interactions among highly regulated catalytic reactions, governing carbohydrate, protein, and species-specific metabolite metabolisms, such as starch and sucrose metabolic pathways, flavonoid and amino acids biosynthetic pathways, collectively contribute to the pronounced carbon anabolic differentiation primarily evident in TAG accumulation, as well as the starch properties in mature tubers.ConclusionThis study offers new metabolic insights into the high-value underground non-photosynthetic tissues of Cyperaceae species, which harbors not only high biomass productivity but also abundant nutrients as favorable food or industrial sources in the modern agriculture. The detailed omics analyses aim to deepen our understanding of the Cyperaceae species, which may potentially broaden their application values and facilitate the molecular breeding of better varieties to ameliorate the food safety problem.

TRNA gene content, structure, and organization in the flowering plant lineage

Transfer RNAs (tRNAs) are noncoding RNAs involved in protein biosynthesis and have noncanonical roles in cellular metabolism, such as RNA silencing and the generation of transposable elements. Extensive tRNA gene duplications, modifications to mature tRNAs, and complex secondary and tertiary structures impede tRNA sequencing. As such, a comparative genomic analysis of complete tRNA sets is an alternative to understanding the evolutionary processes that gave rise to the extant tRNA sets. Although the tRNA gene (tDNA) structure and distribution in prokaryotes and eukaryotes, specifically in vertebrates, yeasts, and flies, are well understood, there is little information regarding plants. A detailed and comprehensive analysis and annotation of tDNAs from the genomes of 44 eudicots, 20 monocots, and five other non-eudicot and non-monocot species belonging to the Ceratophyllaceae and the ANA (Amborellales, Nymphaeales, and Austrobaileyales) clade will provide a global picture of plant tDNA structure and organization. Plant genomes exhibit varying numbers of nuclear tDNAs, with only the monocots showing a strong correlation between nuclear tDNA numbers and genome sizes. In contrast, organellar tDNA numbers varied little among the different lineages. A high degree of tDNA duplication in eudicots was detected, whereby most eudicot nuclear genomes (91%) and only a modest percentage of monocot (65%) and ANA nuclear genomes (25%) contained at least one tDNA cluster. Clusters of tRNATyr–tRNASer and tRNAIle genes were found in eudicot and monocot genomes, respectively, while both eudicot and monocot genomes showed clusters of tRNAPro genes. All plant genomes had intron-containing tRNAeMet and tRNATyr genes with modest sequence conservation and a strictly conserved tRNAAla-AGC species. Regulatory elements found upstream (TATA-box and CAA motifs) and downstream (poly(T) signals) of the tDNAs were present in only a fraction of the detected tDNAs. A and B boxes within the tDNA coding region show varying consensus sequences depending on the tRNA isotype and lineage. The chloroplast genomes, but not the mitogenomes, possess relatively conserved tRNA gene organization. These findings reveal differences and patterns acquired by plant genomes throughout evolution and can serve as a foundation for further studies on plant tRNA gene function and regulation.

Streamlining segmentation of cryo-electron tomography datasets with Ais.

Segmentation is a critical data processing step in many applications of cryo-electron tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation results, and are thus critically dependent on the availability of open-source software for accurate as well as high-throughput tomogram segmentation. There is a need for more user-friendly, flexible, and comprehensive segmentation software that offers an insightful overview of all steps involved in preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation package that is geared towards both high performance and accessibility, available on GitHub. In this report, we demonstrate two common processing steps that can be greatly accelerated with Ais: particle picking for subtomogram averaging, and generating many-feature segmentations of cellular architecture based on in situ tomography data. Featuring comprehensive annotation, segmentation, and rendering functionality, as well as an open repository for trained models at aiscryoet.org, we hope that Ais will help accelerate research and dissemination of data involving cryoET.

Comprehensive annotation of mutations in hallmark genes insights into structural and functional implications.

Understanding the multifaceted role of hallmark gene mutations in cancer progression is critical for developing targeted therapies. This study comprehensively analyses 344 hallmark gene mutations by mapping them to their three-dimensional protein structures using PDB data and AlphaFold models. Mutations were classified based on their locations, such as protein interfaces, ligand-binding sites, dimer interfaces, protein-DNA interfaces, and core regions. The results reveal that highly frequent mutations are located on the ligand-binding site and protein interface, highlighting their significant impact on protein function and interactions. This holistic approach bridges gaps in existing research, offering insights into the structural impacts of genetic alterations in hallmark genes, thereby informing more effective therapeutic strategies.

CNVizard—a lightweight streamlit application for an interactive analysis of copy number variants

BackgroundMethods to call, analyze and visualize copy number variations (CNVs) from massive parallel sequencing data have been widely adopted in clinical practice and genetic research. To enable a streamlined analysis of CNV data, comprehensive annotations and good visualizations are indispensable. The ability to detect single exon CNVs is another important feature for genetic testing. Nonetheless, most available open-source tools come with limitations in at least one of these areas. One additional drawback is that available tools deliver data in an unstructured and static format which requires subsequent visualization and formatting efforts.ResultsHere we present CNVizard, an interactive Streamlit app allowing a comprehensive visualization of CNVkit data. Furthermore, combining CNVizard with the CNVand pipeline allows the annotation and visualization of CNV or SV VCF files from any CNV caller.ConclusionCNVizard, in combination with CNVand, enables the comprehensive and streamlined analysis of short- and long-read sequencing data and provide an intuitive webapp-like experience enabling an interactive visualization of CNV data.

Sequence Analysis of microRNAs Encoded by Simian Lymphocryptoviruses.

Lymphocryptoviruses (LCVs) are ubiquitous gamma-herpesviruses that establish life-long infections in both humans and non-human primates (NHPs). In immunocompromised hosts, LCV infections are commonly associated with B cell disorders and malignancies such as lymphoma. In this study, we evaluated simian LCV-encoded small microRNAs (miRNAs) present in lymphoblastoid cell lines (LCLs) derived from a Mauritian cynomolgus macaque (Macaca fascicularis) with cyLCV-associated post-transplant lymphoproliferative disease (PTLD) as well as the viral miRNAs expressed in a baboon (Papio hamadryas) LCL that harbors CeHV12. Via sequence comparisons, we further predicted viral miRNAs encoded by LCVs that infect two additional NHP species: stump-tailed macaques (Macaca arctoides) and bonobos (Pan paniscus). Together, these species represent two arms of the primate phylogeny: Hominoids (Pan) and Old-World monkeys (Macaca, Papio). Through our analysis, we defined sequences for >95 viral miRNAs encoded by these four NHP LCVs. Our study provides the most comprehensive annotation of NHP LCV miRNAs to date, yielding a resource for developing sequence-specific reagents to detect these molecules. Importantly, we further demonstrate that cyLCV miRNAs can be detected in circulation in vivo and have biomarker potential for LCV-related PTLD.

Comprehensive genome annotation of the model ciliate Tetrahymena thermophila by in-depth epigenetic and transcriptomic profiling.

The ciliate Tetrahymena thermophila is a well-established unicellular model eukaryote, contributing significantly to foundational biological discoveries. Despite its acknowledged importance, current studies on Tetrahymena biology face challenges due to gene annotation inaccuracy, particularly the notable absence of untranslated regions (UTRs). To comprehensively annotate the Tetrahymena macronuclear genome, we collected extensive transcriptomic data spanning various cell stages. To ascertain transcript orientation and transcription start/end sites, we incorporated data on epigenetic marks displaying enrichment towards the 5' end of gene bodies, including H3 lysine 4 tri-methylation (H3K4me3), histone variant H2A.Z, nucleosome positioning and N6-methyldeoxyadenine (6mA). Cap-seq data was subsequently applied to validate the accuracy of identified transcription start sites. Additionally, we integrated Nanopore direct RNA sequencing (DRS), strand-specific RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) data. Using a newly developed bioinformatic pipeline, coupled with manual curation and experimental validation, our work yielded substantial improvements to the current gene models, including the addition of 2,481 new genes, updates to 23,936 existing genes, and the incorporation of 8,339 alternatively spliced isoforms. Furthermore, novel UTR information was annotated for 26,687 high-confidence genes. Intriguingly, 20% of protein-coding genes were identified to have natural antisense transcripts characterized by high diversity in alternative splicing, thus offering insights into understanding transcriptional regulation. Our work will enhance the utility of Tetrahymena as a robust genetic toolkit for advancing biological research, and provides a promising framework for genome annotation in other eukaryotes.

BioDolphin as a comprehensive database of lipid–protein binding interactions

Lipid-protein interactions are crucial for virtually all biological processes in living cells. However, existing structural databases focusing on these interactions are limited to integral membrane proteins. A systematic understanding of diverse lipid-protein interactions also encompassing lipid-anchored, peripheral membrane and soluble lipid binding proteins remains to be elucidated. To address this gap and facilitate the research of universal lipid-protein assemblies, we developed BioDolphin - a curated database with over 127,000 lipid-protein interactions. BioDolphin provides comprehensive annotations, including protein functions, protein families, lipid classifications, lipid-protein binding affinities, membrane association type, and atomic structures. Accessible via a publicly available web server (www.biodolphin.chemistry.gatech.edu), users can efficiently search for lipid-protein interactions using a wide range of options and download datasets of interest. Additionally, BioDolphin features interactive 3D visualization of each lipid-protein complex, facilitating the exploration of structure-function relationships. BioDolphin also includes detailed information on atomic-level intermolecular interactions between lipids and proteins that enable large scale analysis of both paired complexes and larger assemblies. As an open-source resource, BioDolphin enables global analysis of lipid-protein interactions and supports data-driven approaches for developing predictive machine learning algorithms for lipid-protein binding affinity and structures.

Mass Spectrometry-Based Molecular Networks Applied to Study the Molecular Interaction Between Two Endophytic Fungi Isolated From Tibouchina granulosa (Vell.) Cogn (Melastomataceae).

Establishing a microorganism as an endophyte involves complex molecular interactions with its host plant and a broader microbial community. Precise detection methods and comprehensive metabolite annotation are essential to study these interactions. This study focused on characterizing the chemical composition of metabolites produced by two endophytic fungi, Colletotrichum siamense and Xylaria berteroi, isolated from Tibouchina granulosa leaves in axenic conditions and coculture. We examined the fungal metabolites using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HR-MS/MS) and analysis tools like Cytoscape and Global Natural Products Social Molecular Networking. Co-cultivation revealed unique compounds not produced in isolation, including N-acetyltryptamine. A total of 32 compounds were identified, many with biotechnological potential due to their bioactivities. The untargeted metabolomics approach demonstrated that interactions among these T. granulosa endophytes can activate inactive metabolic pathways under axenic conditions, potentially producing novel bioactive molecules. This study is the first study of the chemical profile and interaction between endophytes isolated from T. granulosa.

An unmanned aerial vehicle captured dataset for railroad segmentation and obstacle detection

Safety is crucial in the railway industry because railways transport millions of passengers and employees daily, making it paramount to prevent injuries and fatalities. In order to guarantee passenger safety, computer vision, unmanned aerial vehicles (UAV), and artificial intelligence will be essential tools in the near future for routinely evaluating the railway environment. An unmanned aerial vehicle captured dataset for railroad segmentation and obstacle detection (UAV-RSOD) comprises high-resolution images captured by UAVs over various obstacles within railroad scenes, enabling automatic railroad extraction and obstacle detection. The dataset includes 315 raw images, along with 630 labeled and 630 masked images for railroad semantic segmentation. The dataset consists of 315 original images captured by the UAV for object detection and obstacle detection. To increase dataset diversity for training purposes, we applied data augmentation techniques, which expanded the dataset to 2002 augmented and annotated images for obstacle detection cover six different classes of obstacles on railroad lines. Additionally, we provide the original 315 images along with a script for augmentation, allowing users to generate their own augmented data as needed, offering a more sustainable and customizable option. Each image in the dataset is accurately annotated with bounding boxes and labeled under six categories, including person, boulder, barrel, branch, jerry can, and iron rod. This comprehensive classification and detailed annotation make the dataset an essential tool for researchers and developers working on computer vision applications in the railroad domain.

A novel human protein-coding locus identified using a targeted RNA enrichment technique.

Accurate and comprehensive genomic annotation, including the full list of protein-coding genes, is vital for understanding the molecular mechanisms of human biology. We have previously shown that the genome contains a multitude of yet hidden functional exons and transcripts, some of which might represent novel mRNAs. These results resonate with those from other groups and strongly argue that two decades after the completion of the first draft of the human genome sequence, the current annotation of human genes and transcripts remains far from being complete. Using a targeted RNA enrichment technique, we showed that one of the novel functional exons previously discovered by us and currently annotated as part of a long non-coding RNA, is actually a part of a novel protein-coding gene, InSETG-4, which encodes a novel human protein with no known homologs or motifs. We found that InSETG-4 is induced by various DNA-damaging agents across multiple cell types and therefore might represent a novel component of DNA damage response. Despite its low abundance in bulk cell populations, InSETG-4 exhibited expression restricted to a small fraction of cells, as demonstrated by the amplification-based single-molecule fluorescence in situ hybridization (asmFISH) analysis. This study argues that yet undiscovered human protein-coding genes exist and provides an example of how targeted RNA enrichment techniques can help to fill this major gap in our knowledge of the information encoded in the human genome.

Global identification of mammalian host and nested gene pairs reveal tissue-specific transcriptional interplay.

Nucleotide sequences along a gene provide instructions to transcriptional and cotranscriptional machinery allowing genome expansion into the transcriptome. Nucleotide sequence can often be shared between two genes and in some occurrences, a gene is located completely within a different gene; these are known as host/nested gene pairs. In these instances, if both genes are transcribed, overlap can result in a transcriptional crosstalk where genes regulate each other. Despite this, a comprehensive annotation of where such genes are located and their expression patterns is lacking. To address this, we provide an up-to-date catalog of host/nested gene pairs in mouse and human, showing that over a tenth of all genes contain a nested gene. We discovered that transcriptional co-occurrence is often tissue specific. This coexpression was especially prevalent within the transcriptionally permissive tissue, testis. We use this developmental system and scRNA-seq analysis to demonstrate that the coexpression of pairs can occur in single cells and transcription in the same place at the same time can enhance the transcript diversity of the host gene. In agreement, host genes are more transcript-diverse than the rest of the transcriptome. Host/nested gene configurations are common in both human and mouse, suggesting that interplay between gene pairs is a feature of the mammalian genome. This highlights the relevance of transcriptional crosstalk between genes which share nucleic acid sequence. The results and analysis are available on an Rshiny application (https://hngeneviewer.sites.er.kcl.ac.uk/hn_viewer/).

De Novo Transcriptome Assembly of Anoectochilus roxburghii for Morphological Diversity Assessment and Potential Marker Development.

Anoectochilus roxburghii is a rare and precious medicinal and ornamental plant of Orchidaceae. Abundant morphological characteristics have been observed among cultivated accessions. Our understanding of the genetic basis of morphological diversity is limited due to a lack of sequence data and candidate genes. In this study, a high-quality de novo transcriptome assembly of A.roxburghii was generated. A total of 138,385 unigenes were obtained, and a BUSCO (Benchmarking Universal Single-Copy Orthologs) analysis showed an assembly completeness of 98.8%. Multiple databases were used to obtain a comprehensive annotation, and the unigenes were functionally categorized using the GO (Gene Ontology), KOG (Eukaryotic Orthologous Groups), KEGG (Kyoto Encyclopedia of Genes and Genomes), and Nr databases. After comparing the phenotypic characteristics of five representative cultivars, a set of cultivar-specific, highly expressed unigenes was identified based on a comparative transcriptome analysis. Then, a WGCNA (Weighted Gene Co-expression Network Analysis) was performed to generate gene regulatory modules related to chlorophyll content (red) and sucrose synthase activity (black). In addition, the expression of six and four GO enrichment genes in the red and black modules, respectively, was analyzed using qRT-PCR to determine their putative functional roles in the leaves of the five cultivars. Finally, in silico SSR (Simple Sequence Repeat) mining of the assembled transcriptome identified 44,045 SSRs. Mononucleotide was the most dominant class of SSRs, followed by complex SSRs. In summary, this study reports on the phenomic and genomic resources of A. roxburghii, combining SSR marker development and validation. This report aids in morphological diversity assessments of Anoectochilus roxburghii.

GENCODE 2025: reference gene annotation for human and mouse.

GENCODE produces comprehensive reference gene annotation for human and mouse. Entering its twentieth year, the project remains highly active as new technologies and methodologies allow us to catalog the genome at ever-increasing granularity. In particular, long-read transcriptome sequencing enables us to identify large numbers of missing transcripts and to substantially improve existing models, and our long non-coding RNA catalogs have undergone a dramatic expansion and reconfiguration as a result. Meanwhile, we are incorporating data from state-of-the-art proteomics and Ribo-seq experiments to fine-tune our annotation of translated sequences, while further insights into function can be gained from multi-genome alignments that grow richer as more species' genomes are sequenced. Such methodologies are combined into a fully integrated annotation workflow. However, the increasing complexity of our resources can present usability challenges, and we are resolving these with the creation of filtered genesets such as MANE Select and GENCODE Primary. The next challenge is to propagate annotations throughout multiple human and mouse genomes, as we enter the pangenome era. Our resources are freely available at our web portal www.gencodegenes.org, and via the Ensembl and UCSC genome browsers.

Sc2GWAS: a comprehensive platform linking single cell and GWAS traits of human.

Identifying cell populations associated with risk variants is essential for uncovering cell-specific mechanisms that drive disease development and progression. Integrating genome-wide association studies (GWAS) with single-cell RNA sequencing (scRNA-seq) has become an effective strategy for detecting trait-cell relationships. The accumulation of trait-related single cell data has led to an urgent need for its comprehensively processing. To address this, we developed sc2GWAS (https://bio.liclab.net/sc2GWAS/), which aims to document large-scale GWAS trait-cell regulatory pairs at single-cell resolution and provide comprehensive annotations and enrichment analyses for these related pairs. The current version of sc2GWAS curates a total of 15078310 candidate trait-cell pairs from>6300000 individual cells, offering a valuable resource for exploring complex regulatory relationships between traits and cells. We applied strict quality control measures on both scRNA-seq data and GWAS data, ensuring the reliability and accuracy of the datasets for the identification of trait-relevant cells and genes. In addition, sc2GWAS provides ranked lists of trait-relevant genes and extensive (epi) genetic annotations, making it a valuable resource for downstream analyses. We demonstrate the utility of the platform by investigating Alzheimer's disease, where we identified significant associations between the disease and microglial cells, with the APOE gene emerging as particularly significant. This platform facilitates detailed research into complex trait-celland trait-gene interactions, we anticipate that sc2GWAS will become a comprehensive and valuable platform for exploring GWAS trait-cell regulatory mechanisms.

High-quality sika deer omics data and integrative analysis reveal genic and cellular regulation of antler regeneration.

Antler is the only organ that can fully regenerate annually in mammals. However, the regulatory pattern and mechanism of gene expression and cell differentiation during this process remain largely unknown. Here, we obtain comprehensive assembly and gene annotation of the sika deer (Cervus nippon) genome. Together with large-scale chromatin accessibility and gene expression data, we construct gene regulatory networks involved in antler regeneration, identifying four transcription factors, MYC, KLF4, NFE2L2, and JDP2 with high regulatory activity across whole regeneration process. Comparative studies and luciferase reporter assay suggest the MYC expression driven by a cervid-specific regulatory element might be important for antler regenerative ability. We further develop a model called cTOP which integrates single-cell data with bulk regulatory networks and find PRDM1, FOSL1, BACH1, and NFATC1 as potential pivotal factors in antler stem cell activation and osteogenic differentiation. Additionally, we uncover interactions within and between cell programs and pathways during the regeneration process. These findings provide insights into the gene and cell regulatory mechanisms of antler regeneration, particularly in stem cell activation and differentiation.