Current Genomics最新文献

{"title":"Inhibition of METTL9 Suppresses Migration and Proliferation of Melanoma in Cellular and Animal Models","authors":"Ren-Min Zhang, Hui Jia, Jia-Xing Sun, Lei Zhang, Ying Hou, Zhe-Sheng Chen, Xian-Feng Cheng, Yu-Fei Liu","doi":"10.1016/j.curgen.2026.06.005","DOIUrl":"https://doi.org/10.1016/j.curgen.2026.06.005","url":null,"abstract":"","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148394359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Novel Lysosomal Gene-based Prognostic Panel and Uncovering EIF4EBP1 as a Biomarker for Breast Cancer.","authors":"Bingkun Wang, Nianjin Wei, Meiyu He, Guocai Zhong, Shujun Zhang","doi":"10.2174/0113892029357021250626210819","DOIUrl":"10.2174/0113892029357021250626210819","url":null,"abstract":"<p><strong>Background: </strong>Lysosomal dysfunction is significantly associated with tumor progression. This study aimed to identify and develop a new predictive panel for breast cancer (BRCA) and examine its relationship with the immune environment and therapeutical status.</p><p><strong>Methods: </strong>We developed a prognostic panel employing lysosomal genes from The Cancer Genome Atlas Program (TCGA) and then validated and assessed it externally in the Gene Expression Omnibus (GEO). Furthermore, the disparities were identified between high and low-risk subgroups by examining the infiltration of microenvironment cells, gene expression of immune checkpoints, and small molecular compounds. Ultimately, the cancerous function and potential pathway of core LRG were verified using a series of <i>in vitro</i> tests.</p><p><strong>Results and discussion: </strong>First, the predictive panel of lysosome-related genes (LRGs) was generated <i>via</i> the least absolute shrinkage and selection operator. High-risk populations showed the shortest survival times. Meanwhile, the area under the curves (AUC) for predicting 1-, 3-, and 5-year survival rates indicated good predictive performance across all cohorts. Subsequent extensive investigations revealed a strong correlation between the risk score and the pathological stage, drug sensitivity, and tumor mutation burden (TMB). Then, we discovered that the levels of GPLD1, PLA2G5, and STX7 were reduced in BRCA tissues, whereas the expressions of PLA2G10, LAMP3, EIF4EBP1, and LPCAT1 were elevated in BRCA tissues compared to paracancerous tissues. Patients exhibiting high EIF4EBP1 expression experienced a more unfavorable outcome compared to those with low expression. EIF4EBP1 disruption dramatically impeded BRCA cell growth and invasive capacity, as demonstrated by CCK8, wound healing, and transwell assays. Moreover, EIF4EBP1 silencing in BRCA cells significantly restricted the TGF-β pathway.</p><p><strong>Conclusion: </strong>Our 9-LRG panel is a promising classifier for assessing the prognosis of BRCA. Notably, targeting EIF4EBP1 could potentially serve as a theoretical foundation for enhancing the prognosis of BRCA patients.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 5","pages":"368-388"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12728594/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145833256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Endoplasmic Reticulum Stress-Associated Proteins As Prognostic Markers In Breast Cancer.","authors":"Smriti Shreya, Shweta Pandey, Debasish Kumar Ghosh, Puneet, Shyam Babu Prasad, Christophe F Grosset, Buddhi Prakash Jain","doi":"10.2174/0113892029374158251030064845","DOIUrl":"10.2174/0113892029374158251030064845","url":null,"abstract":"<p><strong>Introduction: </strong>Breast cancer is a complex, heterogeneous disease that poses a significant global health risk. Both internal and external cellular stresses contribute to breast cancer progression. Endoplasmic reticulum (ER) stress is one such cellular stress response that activates intricate intracellular signaling pathways collectively known as the unfolded protein response (UPR). Maintaining protein homeostasis and regulating these pathways is essential in breast cancer progression.</p><p><strong>Methods: </strong>Using STRING and Harmonizome Reactome pathway datasets, we identified a list of UPR-associated genes. The Human Protein Atlas and UALCAN databases were used to analyze these genes as potential prognostic markers in breast cancer.</p><p><strong>Results: </strong>Three prognostic markers were identified in patients with breast cancer: FK506 binding protein 14 (FKBP14), S-phase kinase-associated protein 1 (SKP1), and Baculoviral IAP repeat containing 3 (BIRC3).</p><p><strong>Discussion: </strong>Expression levels of FKBP14, SKP1, and BIRC3 were compared to TCGA normal and GTEx data using the GEPIA2 database. Our analysis indicates that higher SKP1 expression is associated with poor overall survival and prognosis, whereas higher BIRC3 expression correlates with better prognosis and overall survival. BIRC3 protein levels are elevated in tumor tissue and increase as the tumor progresses through various stages. Additionally, the expression of these markers varies according to sex, age, ethnicity, breast cancer subtype, nodal metastasis, and menopause status.</p><p><strong>Conclusion: </strong>Overall, our study identifies that the genes involved in ER stress that are associated with breast cancer can serve as prognostic markers.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 6","pages":"621-632"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154239/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anomaly Detection with Graph Embedding in Bioinformatics: A Survey.","authors":"Tong Wang, Zhi-Ping Liu","doi":"10.2174/0113892029378251251210215239","DOIUrl":"10.2174/0113892029378251251210215239","url":null,"abstract":"<p><p>With the rapid development of network and data sciences, graph anomaly detection has emerged as a key research direction across multiple domains, and its application has been widely recognized in bioinformatics. Biomolecular networks, including gene regulatory networks, protein-protein interaction networks, and drug-molecule interaction networks, form the foundation of complex biological processes within organisms. Abnormal patterns within these networks are often closely associated with the onset and progression of diseases, making graph anomaly detection critically important for revealing disease mechanisms, facilitating disease diagnosis, and advancing drug development. In this paper, we review the current status of graph embedding-based anomaly detection algorithms in bioinformatics, with a particular focus on key literature and the development of dynamic graph anomaly detection algorithms. We explore how graph embedding techniques learn high-dimensional features of biomolecular networks and represent them in a low-dimensional space. Furthermore, we investigate the dynamic nature of biomolecular networks and how graph embedding algorithms can capture these changes to improve detection accuracy and efficiency. The challenges of current methods are summarized, and future directions are proposed to support key applications such as disease diagnosis, gene function annotation, and drug discovery. Through this review, we aim to provide theoretical foundations and methodological support for network anomaly detection in high-throughput omics data.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 6","pages":"434-446"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovative Applications and Challenges of Isothermal Amplification Technology in miRNA Detection.","authors":"Xuebo Li, Zhonglin Zhang, Jian Zhu, Yi Zhang, Yongcan Guo","doi":"10.2174/0113892029436961260112093518","DOIUrl":"10.2174/0113892029436961260112093518","url":null,"abstract":"<p><p>A class of endogenous non-coding RNAs with a length of roughly 18-25 nucleotides is known as microRNAs (miRNAs). They have been established as the best biomarkers for early cancer diagnosis, molecular subtyping, and prognostic evaluation. They also play important roles in important biological processes like cell proliferation, differentiation, apoptosis, and tumorigenesis through post-transcriptional regulatory networks. Traditional detection technologies (such as quantitative Polymerase Chain Reaction (qPCR), Northern blot, and microarrays) exhibit high sensitivity, yet they rely on expensive thermocycling equipment, involve cumbersome procedures, and are time-consuming, making it difficult to meet the demands of clinical point-of-care testing. In recent years, isothermal amplification technologies, represented by loop-mediated isothermal amplification (LAMP), Rolling Circle Amplification (RCA), Strand Displacement Amplification (SDA), and Exponential Amplification Reaction (EXPAR), have emerged as a research frontier in the field of miRNA detection, by virtue of their advantages including elimination of thermal cycling requirements, fast reaction kinetics, high sensitivity, and simple operation. This study aims to systematically organize the core principles, latest advancements, and integrated innovation patterns of isothermal amplification-based miRNA detection technologies, and provide support for the development of miRNA detection platforms suitable for clinical point-of-care testing.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 6","pages":"581-598"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154243/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomics-Driven Immunotherapy: Advancing Cancer Treatment through Personalized Approaches.","authors":"Aditi A Kate, Sharav A Desai, Siddhi P Sapkal, Madhulika M More, Vipul P Patel","doi":"10.2174/0113892029403241260416110923","DOIUrl":"10.2174/0113892029403241260416110923","url":null,"abstract":"<p><p>Cancer is a complex disease involving the abnormal growth and dissemination of cells. The traditional treatments of cancer suffer from challenges like drug resistance and non-specificity. However, immunotherapy has become a promising alternative, leveraging the body's immune system to attack cancer cells. However, the variability in patients' responses to immunotherapy underscores the significance of personalized treatment strategies. Genomics is key to understanding how genetic changes drive tumor development and response to immunotherapy. Genomic profiling techniques, such as NGS, enable the identification of molecular biomarkers, such as Tumor Mutational Burden (TMB) and Microsatellite Instability (MSI), that predict response to immunotherapy. Furthermore, the Tumor Microenvironment (TME), consisting of different cells and molecules surrounding the tumor, plays an important role in cancer progression and treatment outcomes. In this review, we highlight how genomics-driven approaches are accelerating cancer immunotherapy. It presents how genomics can be used to personalize immunotherapy for cancer and discusses challenges such as tumor heterogeneity and resistance to therapy, which require innovative technologies such as single-cell RNA sequencing, AI, and machine learning in immunogenomics, and liquid biopsies to refine treatment strategies. In the future, the incorporation of CRISPR-based gene editing, personalized neoantigen vaccines, and combination therapies holds great promise for transforming cancer treatment.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 7","pages":"771-801"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154235/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>DNMT3A</i> Deficiency Reduces <i>DNMT3B</i> Gene Methylation and Contributes to Whole-genome Transcription Alterations in HEK293 Cells.","authors":"Mengxiao Zhang, Jiaxian Wang, Gen Qi, Lanfeng Xie, Qiuxiang Tian, Hui Yang, Lei Feng, Nan Zhu, Xingchen Pan, Jianwei Zhu, Jianjun Hu, Peng Chen, Huili Lu","doi":"10.2174/0113892029351729250217113313","DOIUrl":"10.2174/0113892029351729250217113313","url":null,"abstract":"<p><strong>Introduction: </strong>DNA methylation is an important epigenetic modification associated with transcriptional repression and plays key roles in normal cell growth as well as oncogenesis. Among the three main DNA methyltransferases (DNMT1, DNMT3A, and DNMT3B), DNMT3A mediates <i>de novo</i> DNA methylation. However, the general effect of DNMT3A on cell proliferation, metabolism, and downstream gene regulation is still to be unveiled.</p><p><strong>Methods: </strong>In this study, we successfully created <i>DNMT3A</i>-deficient HEK293 cells with frameshift mutations in the catalytic domain using CRISPR/Cas9 technology. The <i>DNMT3A</i> deficient cells showed a 21.5% reduction in global DNA methylation levels, leading to impaired cell proliferation as well as a blockage of MAPK and PI3K-Akt pathways in comparison with wild-type cells.</p><p><strong>Results and discussion: </strong>RNA-seq analysis demonstrated that <i>DNMT3A</i> knockout resulted in the up-regulation of genes and pathways related to cell metabolism but down-regulation of those involved in ribosome function, potentially explaining the growth and signaling pathways inhibition. Furthermore, DNMT3A ablation reduced <i>DNMT3B</i> gene methylation, explaining the down-regulated profiles of genes.</p><p><strong>Conclusion: </strong>Our findings suggest a complex epigenetic regulatory role for <i>DNMT3A</i>, and the compensatory upregulation of <i>DNMT3B</i> in response to <i>DNMT3A</i> deficiency warrants further investigation to be validated in future studies.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 5","pages":"389-399"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12728590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145833291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization and Genomic Analysis of <i>Arthrobacter</i> sp. SF27: A Promising Dibutyl Phthalate-degrading Strain.","authors":"Ekaterina Korsakova, Yulia Nechaeva, Elena Plotnikova, Olga Yastrebova","doi":"10.2174/0113892029343036250210044540","DOIUrl":"10.2174/0113892029343036250210044540","url":null,"abstract":"<p><strong>Background: </strong>Phthalic acid esters (PAEs) are widely used chemical compounds in various industries. However, PAEs are also a major source of pollution in soil and aquatic ecosystems, posing a significant environmental threat. Microbial degradation is a very effective way to remove phthalic acid esters from a polluted environment.</p><p><strong>Objectives: </strong>The aims of this study were to investigate the ability of the strain <i>Arthrobacter</i> sp. SF27 (=VKM Ac-2063) to degrade PAEs (specifically, dibutyl phthalate (DBF)); to annotate the complete genome of the strain SF27 (GenBank accession number GCA_012952295); to identify genes (gene clusters) potentially involved in the degradation of DBF and its major degradation product, phthalic acid (PA).</p><p><strong>Methods: </strong>The ability of the strain SF27 to use DBP as the only source of carbon and energy was determined by cultivating it on a mineral medium containing 0.5-4 g/L DBP. The evaluation of the bacterial decomposition of DBP was carried out by GC-MS. The genome was annotated using the JGI Microbial Genome Annotation Pipeline (MGAP) (https://jgi.doe.gov/). Functional annotation was performed using various databases: KEGG, COG, NCBI, and GO. The Mauve program was used to compare the strain SF27 genome and the genomes of the closest DBP-degrading strains.</p><p><strong>Results: </strong>The strain <i>Arthrobacter</i> sp. SF27 is capable of growing on DBP as the sole source of carbon and energy at high concentrations (up to 4 g/L). The strain was able to degrade 60% of DBP (initial concentration of 1 g/L) and 20% of DBP (initial concentration of 3 g/L) within 72 hours. The genome analysis of the strain SF27 (GenBank accession number GCA_012952295) identified genes encoding hydrolases potentially involved in the initial stages of DBP degradation, leading to the formation of PA. Additionally, a cluster of <i>pht</i> genes encoding enzymes that are responsible for the transformation of PA into protocatechuic acid (PCA) has been identified and described in the genome. Based on genome analysis and cultural experiments, a complete pathway for the degradation of PA by the strain <i>Arthrobacter</i> sp. SF27 into basal metabolic compounds of the cell has been proposed.</p><p><strong>Conclusion: </strong>Based on the conducted research, it can be stated that the strain <i>Arthrobacter</i> sp. SF27 is an efficient <i>degrader</i> of <i>DBP</i>, promising for the development of biotechnologies aimed at the restoration of ecosystems contaminated with DBP.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 5","pages":"359-367"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12728591/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145833217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rank Aggregation Methods and Tools in Genomic Data Analysis.","authors":"Wenping Zou, Savannah Mwesigwa, Sayed-Rzgar Hosseini, Zhongming Zhao","doi":"10.2174/0113892029320249240830060611","DOIUrl":"10.2174/0113892029320249240830060611","url":null,"abstract":"<p><p>Rank aggregation (RA) is the process of consolidating disparate rankings into a single unified ranking. It holds immense potential in the field of genomics. RA has applications in diverse research areas, such as gene expression analysis, meta-analysis, gene prioritization, and biomarker discovery. However, there are many challenges in the application of the RA approach to biological data, such as dealing with heterogeneous data sources, rankings of mixed quality, and evaluating the consolidated rankings. In this review, we present an overview of the existing RA methods with an emphasis on those that have been tailored to the complexities of genomics research. These encompass a broad range of approaches, from distributional and heuristic methods to Bayesian and stochastic optimization algorithms. By examining these techniques, we aim to equip researchers with the background knowledge needed to navigate the intricacies of RA in genomics data integration effectively. We review the practical applications to highlight the relevance and impact of RA methods in advancing genomics research. As the field continues to evolve, we identify open problems and suggest future directions to enhance the effectiveness of rank aggregation in genomics, by addressing the challenges related to data heterogeneity, single-cell omics and spatial transcriptomics data, and the development of clear and consistent evaluation methods. In summary, RA stands as a powerful tool in genomics research, which can offer deeper insights and more comprehensive data integration solutions.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 5","pages":"329-340"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12728592/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145833243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the Evolutionary Adaptations and the Associated Functional Dynamics of Diatom <i>Cyclotella Cryptica</i>: A Chloroplast Genome-wide Comparative Study.","authors":"Pankaj Kumar Singh, Baskaran Srinivasan, M Arockia Babu, Nisha Bansal, Thakur Gurjeet Singh, Yogita Tyagi, Roshan Kumar","doi":"10.2174/0113892029458363260416055201","DOIUrl":"https://doi.org/10.2174/0113892029458363260416055201","url":null,"abstract":"<p><strong>Introduction: </strong><i>Cyclotella cryptica</i> is a marine diatom recognized as a promising biofuel resource and a model organism for studying diatom physiology and biotechnology. Since lipid biosynthesis in microalgae initiates in plastids, understanding chloroplast genome organization is crucial for advancing biofuel-related research.</p><p><strong>Objective: </strong>The work is focused on sequencing and analyzing the chloroplast genome of C. cryptica and performing a phylogenomic comparative analysis.</p><p><strong>Methods: </strong>The sequencing and annotation of the chloroplast genome of <i>C. cryptica</i> were performed. Comparative phylogenomic analysis was conducted using 27 diatom chloroplast genomes to investigate evolutionary relationships.</p><p><strong>Results: </strong>The chloroplast genome was 129,273 bp in length and contained 132 predicted gene biotypes, including 57 protein-coding genes, 67 tRNA genes, and 8 rRNA genes. Phylogenomic analysis revealed that centric diatoms clustered into a single clade, whereas pennate diatoms formed two distinct clades.</p><p><strong>Discussion: </strong>The conserved clustering of centric diatoms and the clear separation from pennate diatoms reflect established evolutionary patterns within diatoms and highlight the conserved nature of chloroplast genomes in Cyclotella species.</p><p><strong>Conclusion: </strong>These findings enhance understanding of chloroplast genome organization and evolution in Cyclotella and other diatoms and provide valuable genomic insights that may support future research aimed at improving biofuel production.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 7","pages":"833-842"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154245/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}