Current Genomics - Current Issue
Volume 26, Issue 5, 2025
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Rank Aggregation Methods and Tools in Genomic Data Analysis
More LessAuthors: Wenping Zou, Savannah Mwesigwa, Sayed-Rzgar Hosseini and Zhongming ZhaoRank 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.
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An Assessment of the Degradation Potential and Genomic Insights Towards Hydroxylated Biphenyls by Rhodococcus opacus Strain KT112-7
More LessAuthors: Darya Egorova, Bjorn Olsson, Tatyana Kir’yanova and Elena PlotnikovaBackgroundHydroxylated biphenyls are currently recognized as secondary pollutants that are hazardous to animals and humans. Bacterial degradation is the most effective method for the degradation of hydroxylated biphenyls. Several strains capable of degrading polychlorinated biphenyls have been described, which also degrade hydroxylated biphenyls.
Objectives1) To study the biodegradative properties of the Rhodococcus opacus strain KT112-7 towards mono-hydroxylated biphenyls. 2) To analyze the genome of the Rhodococcus opacus strain KT112-7. 3) To identify the genetic basis for the unique biodegradative potential of the Rhodococcus opacus strain KT112-7.
MethodsA genome analysis of the strain KT112-7 was conducted based on whole-genome sequencing using various programs and databases (Velvet, CONTIGuator, RAST, KEGG) for annotation and identification of protein-coding sequences. The strain KT112-7 was cultivated in a K1 mineral medium supplemented with mono-hydroxy biphenyls or mono-hydroxybenzoic acids as the carbon source. For the growth test mono-hydroxybiphenyls or mono-hydroxybenzoic acids were dosed at concentrations of 0.5 g/L and 1.0 g/L correspondently, and the bacterial growth was monitored by the optical density. For the biodegradative activity test, mono-hydroxybiphenyls were dosed at a concentration of 0.1 g/L in vials, inoculated with late exponential phase bacteria previously acclimated on biphenyl. Compound analysis was performed using GC-MS, HPLC, and spectrophotometry.
ResultsIt was found that the genome of strain KT112-7 consists of a chromosome and 2 plasmids. Biphenyl degradation genes (bph genes) were identified on plasmid PRHWK1 and the chromosome, as well as hydroxybenzoic acid degradation genes on the chromosome. The strain KT112-7 was shown to degrade mono-hydroxylated biphenyls to basal metabolic compounds of the cell, with the highest destructive activity observed towards 3- and 4-hydroxylated biphenyls (98%).
DiscussionAnalysis of the translated sequences of the bph genes from strain KT112-7 revealed that the amino acid sequences of the bph operon, located on plasmid pRHWK1, exhibit high similarity to homologous enzymes of the "upper" pathway for biphenyl degradation in Rhodococcus jostii RHA1, whose bph genes are also plasmid-borne. The deduced amino acid sequences encoded by the bphA1A2B genes, located on the chromosome of strain KT112-7, show a high degree of similarity to enzymes from Rhodococcus strains that mediate naphthalene degradation. The genes of the "lower" biphenyl pathway in strain KT112-7 are located on the chromosome and share a high level of similarity with the bph genes of Acidovorax sp. KKS102. Analysis of the deduced sequences of the pcaGHBCDF, pcaIJfadA, and catABC genes, along with the metabolites identified during the cultivation of strain KT112-7 on hydroxylated biphenyls, suggests the presence of both classical and unique metabolic pathways for hydroxylated benzoic acids in strain KT112-7.
ConclusionThe Rhodococcus opacus strain KT112-7 is characterized by genetic systems that contribute to its high biodegradative potential towards mono-hydroxylated biphenyls and their metabolites. Thus, the strain KT112-7 is promising for use in hydroxybiphenyl degradation technologies.
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Characterization and Genomic Analysis of Arthrobacter sp. SF27: A Promising Dibutyl Phthalate-degrading Strain
More LessAuthors: Ekaterina Korsakova, Yulia Nechaeva, Elena Plotnikova and Olga YastrebovaBackgroundPhthalic 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.
ObjectivesThe aims of this study were to investigate the ability of the strain Arthrobacter 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).
MethodsThe 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.
ResultsThe strain Arthrobacter 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 pht 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 Arthrobacter sp. SF27 into basal metabolic compounds of the cell has been proposed.
ConclusionBased on the conducted research, it can be stated that the strain Arthrobacter sp. SF27 is an efficient degrader of DBP, promising for the development of biotechnologies aimed at the restoration of ecosystems contaminated with DBP.
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Development of a Novel Lysosomal Gene-based Prognostic Panel and Uncovering EIF4EBP1 as a Biomarker for Breast Cancer
More LessAuthors: Bingkun Wang, Nianjin Wei, Meiyu He, Guocai Zhong and Shujun ZhangBackgroundLysosomal 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.
MethodsWe 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 in vitro tests.
Results and DiscussionFirst, the predictive panel of lysosome-related genes (LRGs) was generated via 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.
ConclusionOur 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.
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DNMT3A Deficiency Reduces DNMT3B Gene Methylation and Contributes to Whole-genome Transcription Alterations in HEK293 Cells
More LessAuthors: Mengxiao Zhang, Jiaxian Wang, Gen Qi, Lanfeng Xie, Qiuxiang Tian, Hui Yang, Lei Feng, Nan Zhu, Xingchen Pan, Jianwei Zhu, Jianjun Hu, Peng Chen and Huili LuIntroductionDNA 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 de novo DNA methylation. However, the general effect of DNMT3A on cell proliferation, metabolism, and downstream gene regulation is still to be unveiled.
MethodsIn this study, we successfully created DNMT3A-deficient HEK293 cells with frameshift mutations in the catalytic domain using CRISPR/Cas9 technology. The DNMT3A 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.
Results and DiscussionRNA-seq analysis demonstrated that DNMT3A 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 DNMT3B gene methylation, explaining the down-regulated profiles of genes.
ConclusionOur findings suggest a complex epigenetic regulatory role for DNMT3A, and the compensatory upregulation of DNMT3B in response to DNMT3A deficiency warrants further investigation to be validated in future studies.
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Integrated Multi-omics Analysis of Hub Genes and miRNA Interactions in Hypertrophic Cardiomyopathy
More LessAuthors: Huanhuan Hu, Ziheng Yu, Kongjie Lu, Hui Hu and Lang DengBackgroundHypertrophic Cardiomyopathy (HCM) is a complex cardiac disorder marked by the thickening of the heart muscle.
MethodsHCM and normal control cell lines were cultured in DMEM with 12.5% FBS and 1% penicillin-streptomycin at 37°C and 5% CO2. Differentially expressed genes (DEGs) were identified from GSE32453, GSE53408, and GSE113439 datasets using the limma package in R. Hub genes were determined through protein-protein interaction (PPI) network and Cytoscape analysis and validated via Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) and Western blot analysis. Gene enrichment, miRNA predictions, drug prediction, and molecular docking analyses were conducted for functional enrichment and to explore hub gene-associated drugs.
ResultsTo identify DEGs and hub genes implicated in HCM, we analyzed three Gene Expression Omnibus (GEO) datasets (GSE32453, GSE53404, and GSE1134439), extracting the top 1000 DEGs. Venn analysis revealed 21 common down-regulated genes. PPI analysis identified these six as key hub genes, including Iron Response Element Binding Protein 2 (IREB2), Protein Tyrosine Phosphatase, Non-Receptor Type 11 (PTPN11), IQ Motif Containing GTPase Activating Protein 1 (IQGAP1), Phosphoglucomutase 2 (PGM2), DIS3 RNA Exonuclease 3' to 5' (DIS3), Glutamine-Fructose-6-Phosphate Transaminase 1 (GFPT1) in HCM patients. Gene enrichment analysis highlighted the involvement of these genes in cellular functions such as energy metabolism and growth factor signaling, suggesting their role in the disease's progression. Validation using an additional dataset (GSE36961) confirmed significant down-regulation of all hub genes in HCM samples, supported by Receiver Operating Characteristic (ROC) curve analysis that demonstrated their diagnostic potential. Furthermore, miRNA analysis identified six up-regulated miRNAs (miR-124, miR-29b, miR-330, miR-34a, miR-375, and miR-451) that likely contribute to the dysregulation of these hub genes. Drug prediction analysis identified various potential therapeutic compounds targeting these hub genes. Molecular docking revealed favorable binding affinities, supporting the therapeutic potential of these drugs in modulating hub gene activity.
DiscussionThese findings demonstrate that HCM progression involves coordinated downregulation of hub genes and miRNA-mediated dysregulation of metabolic and signaling pathways. The integration of bioinformatics, validation assays, and drug docking suggests a strong translational potential for biomarker discovery and targeted therapy.
ConclusionOur findings suggest that IREB2, PTPN11, IQGAP1, PGM2, DIS3, and GFPT1 hub genes and their associated regulatory pathways may serve as biomarkers and therapeutic targets for HCM, potentially improving diagnosis and treatment strategies.
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Volumes & issues
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Volume 26 (2025)
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Volume 25 (2024)
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Volume 24 (2023)
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Volume 23 (2022)
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Volume 22 (2021)
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Volume 21 (2020)
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Volume 20 (2019)
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Volume 19 (2018)
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Volume 18 (2017)
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Volume 17 (2016)
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Volume 16 (2015)
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Volume 15 (2014)
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Volume 14 (2013)
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Volume 13 (2012)
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Volume 12 (2011)
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Volume 11 (2010)
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Volume 10 (2009)
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Volume 9 (2008)
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Volume 8 (2007)
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Volume 7 (2006)
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Volume 6 (2005)
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Volume 5 (2004)
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Volume 4 (2003)
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Volume 3 (2002)
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Volume 2 (2001)
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Volume 1 (2000)
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