BMC Biology最新文献

{"title":"Elevated EGR1 binding at enhancers in excitatory neurons correlates with neuronal subtype-specific epigenetic regulation.","authors":"Liduo Yin, Xiguang Xu, Benjamin Conacher, Yu Lin, Gabriela L Carrillo, Yupeng Cun, Michael A Fox, Xuemei Lu, Hehuang Xie","doi":"10.1186/s12915-025-02357-x","DOIUrl":"10.1186/s12915-025-02357-x","url":null,"abstract":"<p><strong>Background: </strong>Brain development and neuronal cell specification are accompanied by epigenetic changes that enable the regulation of diverse gene expression patterns. During these processes, transcription factors interact with cell-type-specific epigenetic marks, binding to unique sets of cis-regulatory elements in different cell types. However, the detailed mechanisms through which cell-type-specific gene regulation is established in neurons remain to be explored.</p><p><strong>Results: </strong>In this study, we conducted a comparative histone modification analysis between excitatory and inhibitory neurons. Our results revealed that neuronal cell-type-specific histone modifications are enriched in super enhancer regions that contain abundant EGR1 motifs. Further CUT&RUN assay confirmed that excitatory neurons exhibit more EGR1 binding sites, primarily located in enhancers. Integrative analysis demonstrated that EGR1 binding is strongly correlated with various epigenetic markers of open chromatin regions and is linked to distinct gene pathways specific to neuronal subtypes. In inhibitory neurons, most genomic regions containing EGR1 binding sites become accessible during early embryonic stages, whereas super enhancers in excitatory neurons, which also host EGR1 binding sites, gain accessibility during postnatal stages.</p><p><strong>Conclusions: </strong>This study highlights the crucial role of transcription factor binding, such as EGR1, to enhancer regions, which may be key to establishing cell-type-specific gene regulation in neurons.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"251"},"PeriodicalIF":4.5,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12337459/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144815768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environmental adaptations in metagenomes revealed by deep learning.","authors":"Johanna C Winder, Simon Poulton, Taoyang Wu, Thomas Mock, Cock van Oosterhout","doi":"10.1186/s12915-025-02361-1","DOIUrl":"10.1186/s12915-025-02361-1","url":null,"abstract":"<p><strong>Background: </strong>Deep learning has emerged as a powerful tool in the analysis of biological data, including the analysis of large metagenome data. However, its application remains limited due to high computational costs, model complexity, and difficulty extracting biological insights from these artificial neural networks (ANNs). In this study, we applied a transfer learning approach using the ESM-2 protein structure prediction model and our own smaller ANN to classify proteins containing the domain of unknown function 3494 (DUF3494) by their source environments. DUF3494 is found in a diverse group of putative ice-binding and substrate-binding proteins across a range of environments in prokaryotic and eukaryotic microorganisms. They present a compelling test case for exploring the balance between prediction accuracy and interpretability in sequence classification.</p><p><strong>Results: </strong>Our ANN analysed 50,669 DUF3494 sequences from publicly available metagenomes, and successfully classified a large proportion of sequences by source environment (polar marine, glacier ice, frozen sediment, rock, subsurface). We identified environment-specific features that appear to drive classification. Our best-performing ANN was able to classify between 75.9 and 97.8% of sequences correctly. To enhance biological interpretability of these predictions, we compared this model with a genetic algorithm (GA), which, although it had lower predictive ability, provided transparent classification rules and predictors. Further in silico mutagenesis of key residues uncovered a vertically aligned column of amino acids on the b-face of the protein which was important for environmental differentiation, suggesting that both methods captured distinct evolutionary and ecological aspects of the sequences. Feature importance analysis identified that steric and electronic properties of the protein were associated with predictive ability.</p><p><strong>Conclusions: </strong>Our findings highlight the utility of deep learning for classification of diverse biological sequences and provide a framework for combining methods to improve model interpretability and ecological insights.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"252"},"PeriodicalIF":4.5,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12337378/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144815769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MESM: integrating multi-source data for high-accuracy protein-protein interactions prediction through multimodal language models.","authors":"Feng Wang, Jinming Chu, Liyan Shen, Shan Chang","doi":"10.1186/s12915-025-02356-y","DOIUrl":"10.1186/s12915-025-02356-y","url":null,"abstract":"<p><strong>Background: </strong>Protein-protein interactions (PPIs) play a critical role in essential biological processes such as signal transduction, enzyme activity regulation, cytoskeletal structure, immune responses, and gene regulation. However, current methods mainly focus on extracting features from protein sequences and using graph neural network (GNN) to acquire interaction information from the PPI network graph. This limits the model's ability to learn richer and more effective interaction information, thereby affecting prediction performance.</p><p><strong>Results: </strong>In this study, we propose a novel deep learning method, MESM, for effectively predicting PPI. The datasets used for the PPI prediction task were primarily constructed from the STRING database, including two Homo sapiens PPI datasets, SHS27k and SHS148k, and two Saccharomyces cerevisiae PPI datasets, SYS30k and SYS60k. MESM consists of three key modules, as follows: First, MESM extracts multimodal representations from protein sequence information, protein structure information, and point cloud features through Sequence Variational Autoencoder (SVAE), Variational Graph Autoencoder (VGAE), and PointNet Autoencoder (PAE). Then, Fusion Autoencoder (FAE) is used to integrate these multimodal features, generating rich and balanced protein representations. Next, MESM leverages GraphGPS to learn structural information from the PPI network graph structure and combines Graph Attention Network (GAT) to further capture protein interaction information. Finally, MESM uses Graph Convolutional Network (GCN) and SubgraphGCN to extract global and local features from the perspective of the overall graph and subgraphs. Moreover, we build seven independent graphs from the overall PPI network graph to specifically learn the features of each PPI type, thereby enhancing the model's learning ability for different types of interactions.</p><p><strong>Conclusions: </strong>Compared to the state-of-the-art methods, MESM achieved improvements of 8.77%, 4.98%, 7.48%, and 6.08% on SHS27k, SHS148k, SYS30k, and SYS60k, respectively. The experimental results demonstrate that MESM exhibits significant improvements in PPI prediction performance.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"253"},"PeriodicalIF":4.5,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12337455/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144815770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative evaluation of DNA and RNA probes for capture-based mitochondrial DNA next-generation sequencing.","authors":"Tianlei Sun, Shengjing Li, Yang Liu, Kaixiang Zhou, Jiamin Wang, Zhangwen Lei, Xu Guo, Jinliang Xing, Wenjie Guo","doi":"10.1186/s12915-025-02365-x","DOIUrl":"10.1186/s12915-025-02365-x","url":null,"abstract":"<p><strong>Background: </strong>Probe-based liquid-phase hybridization capture is a powerful and commonly used approach for next-generation sequencing (NGS) of mitochondrial DNA (mtDNA). However, the performance difference between DNA and RNA probe-based capture strategies for mtDNA NGS remains to be determined, leading to the irrational interchangeable use in numerous studies.</p><p><strong>Results: </strong>We custom-designed DNA and RNA probes targeting the double-stranded mtDNA and optimized their hybridization conditions for capture-based mtDNA NGS in fresh tissue and plasma samples. Under optimal conditions, we systematically compared the performance of DNA and RNA probes in mtDNA detection. RNA probes demonstrated superior mtDNA enrichment efficiency, characterized by higher mtDNA mapping rates and greater average mtDNA depth per gigabyte of sequencing data. However, DNA probes were more effective at reducing artifacts caused by nuclear mitochondrial DNA segments (NUMTs) in mtDNA mutation detection at both the read and mutation levels. Additionally, RNA probes captured a broader fragment size distribution and higher prevalence of longer fragments in plasma cell-free mtDNA.</p><p><strong>Conclusions: </strong>The systematic evaluation of DNA and RNA probes in capture-based mtDNA NGS provides valuable insights into their performance differences. These findings advocate for informed probe selection tailored to the specific experimental and clinical needs, ultimately advancing the field of mtDNA characterization and its applications in genomics and diagnostics.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"248"},"PeriodicalIF":4.5,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12333292/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144803665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of human pathogenic start loss variants based on self-supervised contrastive learning.","authors":"Jie Liu, Henghui Fan, Na Cheng, Yansen Su, Junfeng Xia","doi":"10.1186/s12915-025-02348-y","DOIUrl":"10.1186/s12915-025-02348-y","url":null,"abstract":"<p><strong>Background: </strong>Start loss variants are a class of genetic variants that affect the bases of the start codon, disrupting the normal translation initiation process and leading to protein deletions or the production of different proteins. Accurate assessment of the pathogenicity of these variants is crucial for deciphering disease mechanisms and integrating genomics into clinical practice. However, among the tens of thousands of start loss variants in the human genome, only about 1% have been classified as pathogenic or benign. Computational methods that rely solely on small amounts of labeled data often lack sufficient generalization capabilities, restricting their effectiveness in predicting the impact of start loss variants.</p><p><strong>Results: </strong>Here, we introduce StartCLR, a novel prediction method specifically designed for identifying pathogenic start loss variants. StartCLR captures variant context information from different dimensions by integrating embedding features from diverse DNA language models. Moreover, it employs self-supervised pre-training combined with supervised fine-tuning, enabling the effective utilization of both a large amount of unlabeled data and a small amount of labeled data to enhance prediction accuracy. Our experimental results show that StartCLR exhibits strong generalization and superior prediction performance across different test sets. Notably, when trained exclusively on high-confidence labeled data, StartCLR retains or even improves the prediction accuracy despite the reduced amount of labeled data.</p><p><strong>Conclusions: </strong>Collectively, these findings highlight the potential of integrating self-supervised contrastive learning with unlabeled data to mitigate the challenge posed by the scarcity of labeled start loss variants.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"250"},"PeriodicalIF":4.5,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12333246/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144803667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pharmacomodulation of G-quadruplexes in long non-coding RNAs dysregulated in colorectal cancer.","authors":"Shubham Sharma, Jérémie Mitteaux, Angélique Pipier, Marc Pirrotta, Marie-José Penouilh, David Monchaud, Bhaskar Datta","doi":"10.1186/s12915-025-02322-8","DOIUrl":"10.1186/s12915-025-02322-8","url":null,"abstract":"<p><strong>Background: </strong>Non-coding RNAs (ncRNAs) in human cells constitute a substantial portion of the transcriptome but do not lead to protein synthesis. Among them, long non-coding RNAs (lncRNAs, > 200 nucleotides long) are fascinating in their ability to orchestrate critical cellular functions that govern cell development, differentiation, and metabolism. Therefore, the dysregulation of lncRNAs has been linked with several diseases, chiefly cancers.</p><p><strong>Results: </strong>We focused here on colorectal cancer (CRC), the second-highest cause of mortalities related to cancer worldwide, and more particularly on three lncRNAs, i.e., LINC01589, MELTF-AS1, and UXT-AS1, known to be dysregulated in CRC. We identified a vulnerability in these lncRNAs that could be exploited from a therapeutic point of view: a part of their sequence folds into a secondary structure referred to as G-quadruplex (G4), which is suspected to play active roles in the lncRNA functions. We demonstrate here that these sequences do fold into G4s both in vitro and in CRC cells, and that these G4s can be modulated using PhpC, a prototype molecule for destabilizing G4s.</p><p><strong>Conclusion: </strong>We describe an innovative anticancer strategy that fully abides by the rules of chemical biology. We indeed modulate the formation of G4s in cells using ad hoc molecular tools in the aim of disturbing the homeostasis and inner functioning of lncRNAs. By exploiting cellular outcomes, we infer how this pharmacomodulation affects CRC biology and, beyond this, the fate of CRC cells owing to the flawed repertoire of correction and/or compensatory mechanisms in cancer cells.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"249"},"PeriodicalIF":4.5,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12333089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144803666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transcriptional patterns of cancer-related genes in primary and metastatic tumours revealed by machine learning.","authors":"Faeze Keshavarz-Rahaghi, Erin Pleasance, Steven J M Jones","doi":"10.1186/s12915-025-02339-z","DOIUrl":"10.1186/s12915-025-02339-z","url":null,"abstract":"<p><strong>Background: </strong>A key to understanding cancer is to determine the impact on the cellular pathways caused by the repertoire of DNA changes accrued in a cancer cell. Exploring the interactions between genomic aberrations and the expressed transcriptome can not only improve our understanding of the disease but also identify potential therapeutic approaches.</p><p><strong>Results: </strong>Using random forest models, we successfully identified transcriptional patterns associated with the loss of wild-type activity in cancer-related genes across various tumour types. While genes like TP53 and CDKN2A exhibited unique pan-cancer transcriptional patterns, others like ATRX, BRAF, and NRAS showed tumour-type-specific expression patterns. We also observed that genes like AR and ERBB4 did not lead to strong detectable patterns in the transcriptome when disrupted. Our investigation has also led to the identification of genes highly associated with transcriptional patterns. For instance, DRG2 emerged as the top contributor in classification of ATRX alterations in lower-grade gliomas and was significantly downregulated in ATRX mutant tumours. Additionally, transcriptional features important in classification of PTEN aberrations, such as CDCA8, AURKA, and CDC20, were found to be closely related to PTEN function.</p><p><strong>Conclusions: </strong>Our findings demonstrate the utility of machine learning in interpretation of cancer genomic data and provide new avenues for development of targeted therapies tailored to individual patients with cancer. Our analysis on the transcriptome revealed genes with expression levels strongly correlated with alterations in cancer-related genes. Additionally, we identified AURKA inhibitors as potential therapeutic option for tumours with alterations in tumour suppressors like FBXW7 or NSD1.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"246"},"PeriodicalIF":4.5,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12329921/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144798214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CRL2^LRRC41-Mediated DDX5 Ubiquitination Enhances Interaction with ELAVL1 Preventing NOG mRNA Degradation and Sustaining Proliferation and Migration of Human Spermatogonial Stem Cell-Like Cell Line.","authors":"Bing Jiang, Kehan Wang, Haoyue Hu, Wenxin Gao, Cong Shen, Xia Chen, Xiaoyan Huang, Jun Yu, Yibo Wu, Bo Zheng","doi":"10.1186/s12915-025-02363-z","DOIUrl":"10.1186/s12915-025-02363-z","url":null,"abstract":"<p><strong>Background: </strong>Human spermatogonial stem cells (SSCs) exhibit a remarkable capacity for proliferation, crucial for sustaining spermatogenesis throughout life. While the Cullin-RING E3 ubiquitin ligase 2 (CRL2) complex is known to regulate various cellular functions, its precise role in human SSCs has not been fully elucidated. This study aimed to investigate a novel variant of the CRL2 complex, termed CRL2^LRRC41, and its role in SSC function.</p><p><strong>Methods: </strong>We utilized molecular biology techniques, including gene knockdown and functional assays, to assess the effects of CRL2^LRRC41 on the proliferative and migratory abilities of human spermatogonial stem cell-like cell (SSCLC) line. Additionally, we employed proteomics and biochemical approaches to identify potential substrates of CRL2^LRRC41. We specifically focused on ATP-dependent RNA helicase DDX5, a known regulator of spermatogenesis, to explore its interaction with CRL2^LRRC41 and the downstream molecular mechanisms involved.</p><p><strong>Results: </strong>Our findings revealed that the disruption or dysfunction of CRL2^LRRC41 led to reduced proliferative and migratory abilities in human SSCLCs. Through our investigation, we identified DDX5 as a ubiquitination substrate of CRL2^LRRC41. Notably, the ubiquitination of DDX5 fosters its interaction with the RNA-binding protein ELAVL1, without directing DDX5 towards degradation via the ubiquitin-proteasome system (UPS). This interaction enhances the stability of the downstream transcript, Noggin (NOG), thereby supporting human SSCLC proliferation and migration.</p><p><strong>Conclusions: </strong>This study provides the first identification of the CRL2^LRRC41 complex in human SSCLCs and elucidates the molecular mechanisms by which CRL2^LRRC41 facilitates SSCLC function via ubiquitination-mediated protein interactions. These findings offer novel insights into the molecular underpinnings of male infertility.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"247"},"PeriodicalIF":4.5,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12329934/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144798213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic landscape uncovers remodeling of T cell immunity affected by fatty acid desaturase in Parkinson's disease at single-cell resolution.","authors":"Shi Yan, Xue Zhao, Yao Si, Xinyu Zhang, Di Wang, Lifen Yao, Linlin Sun","doi":"10.1186/s12915-025-02358-w","DOIUrl":"10.1186/s12915-025-02358-w","url":null,"abstract":"<p><strong>Background: </strong>Peripheral activated T cells cross the blood-brain barrier, partake in neuroinflammation, and induce dopaminergic neuron degeneration through characteristics such as cell adhesion and immune response in Parkinson's disease (PD). Metabolic activity, which can regulate and be regulated by cellular signaling pathways, has a profound impact on the differentiation and function of T cells. However, a characterization of T-cell metabolic heterogeneity at single-cell resolution in PD is still lacking. Here, combining metabolic gene expression profiling and pathway activity algorithm, we studied the metabolic programs in PD-associated T cells.</p><p><strong>Results: </strong>Cytotoxic T cells (CTLs) with adhesive properties dominated the proportion in PD patients based on the distribution of T cell types at single-cell resolution. The unsaturated fatty acid (UFA) biosynthetic process was found to be the pivotal contributor to CTLs' metabolic features distinct from other cell types. Meanwhile, the upregulation of UFA biosynthetic process strongly correlated with immunologic activity in CTLs. Additionally, we revealed that fatty acid desaturases became the critical factor in determining CTLs' metabolic heterogeneity according to the differentiation of T cell lineage and the high expression of metabolic genes in PD. Subsequent fatty acid desaturases adjustments mediated crosstalk with CTLs' immunity, suggesting a potential target for regulating neuroinflammation in PD condition.</p><p><strong>Conclusions: </strong>This analysis decoded the activation of T cells from another perspective, where PD-associated CTLs were metabolically reprogrammed to interact with the immune system, for in-depth insights into the immune characteristics of PD.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"245"},"PeriodicalIF":4.5,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330092/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144793546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic analyses support locally derived crown-of-thorns seastar outbreaks in the Pacific.","authors":"Carlos Leiva, Marta Martín-Huete, Sarah Lemer","doi":"10.1186/s12915-025-02350-4","DOIUrl":"10.1186/s12915-025-02350-4","url":null,"abstract":"<p><strong>Background: </strong>Crown-of-thorns seastars (COTS, Acanthaster spp.) are the most notorious coral predators, whose devastating outbreaks cause recurrent and extensive coral depletion across Indo-Pacific reefs. However, the spread potential of COTS outbreaks and the anthropogenic role in their initiation have remained a subject of intense debate for over five decades.</p><p><strong>Results: </strong>Here, using low-coverage whole-genome sequences of 247 COTS, we show that Pacific COTS populations are highly structured, indicating that outbreaks do not spread through open ocean, but instead are locally derived. Pacific COTS populations are grouped in three main lineages geographically restricted to Hawai'i, French Polynesia, and the West Pacific, with the latter showing further significant genetic substructure. Phylogenomic analyses indicated that the Hawai'i COTS lineage likely represents a different undescribed species and challenged the species status of both A. cf. solaris and the Eastern Pacific COTS species (A. ellisii), as the latter appeared as the sister group of the French Polynesia COTS lineage. Additionally, we show that current COTS populations present the highest effective sizes of the last million years, suggesting that human and/or climate change may influence COTS population sizes.</p><p><strong>Conclusions: </strong>Overall, our study highlights the improvements brought by low-coverage whole-genome sequencing approaches in resolving the phylogeny and connectivity patterns of a keystone species in understudied regions of the Pacific Ocean.</p>","PeriodicalId":9339,"journal":{"name":"BMC Biology","volume":"23 1","pages":"244"},"PeriodicalIF":4.5,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330192/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144793545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}