Genomics, proteomics & bioinformatics最新文献_第2页

DeOri 10.0: An Updated Database of Experimentally Identified Eukaryotic Replication Origins. DeOri 10.0：经实验鉴定的真核生物复制起源的最新数据库。

Genomics, proteomics & bioinformatics Pub Date : 2024-10-15 DOI: 10.1093/gpbjnl/qzae076

Yu-Hao Zeng, Zhen-Ning Yin, Hao Luo, Feng Gao

{"title":"DeOri 10.0: An Updated Database of Experimentally Identified Eukaryotic Replication Origins.","authors":"Yu-Hao Zeng, Zhen-Ning Yin, Hao Luo, Feng Gao","doi":"10.1093/gpbjnl/qzae076","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzae076","url":null,"abstract":"DNA replication is a complex and crucial biological process in eukaryotes. To facilitate the study of eukaryotic replication events, we present a database of eukaryotic DNA replication origins (DeOri), which collects scattered data and integrates extensive sequencing data on eukaryotic DNA replication origins. With continuous updates of DeOri, the number of datasets in the new release increased from 10 to 151 and the number of sequences increased from 16,145 to 9,742,396. Besides nucleotide sequences and bed files, corresponding annotation files, such as coding sequences (CDS), mRNA, and other biological elements within replication origins, are also provided. The experimental techniques used for each dataset, as well as other statistical data, are also presented on web page. Differences in experimental methods, cell lines, and sequencing technologies have resulted in distinct replication origins, making it challenging to differentiate between cell-specific and non-specific replication. We combined multiple replication origins at the species level, scored them, and screened them. The screened regions were considered as species-conservative origins. They are integrated and presented as reference replication origins (rORIs), including Homo sapiens, Gallus gallus, Mus musculus, Drosophila melanogaster, and Caenorhabditis elegans. Additionally, we analyzed the distribution of relevant genomic elements associated with replication origins at the genome level, such as CpG island (CGI), transcription start site (TSS), and G-quadruplex (G4). These analysis results allow users to select the desired data based on it. DeOri is available at http://tubic.tju.edu.cn/deori/.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Aberrant Somatic Hypermutation at Super-enhancer Drives B Cell Lymphoma Transformation. 超级突变的异常体细胞高突变驱动 B 细胞淋巴瘤转化

Genomics, proteomics & bioinformatics Pub Date : 2024-10-15 DOI: 10.1093/gpbjnl/qzae015

Xueshuai Han, Zhaoqi Liu

引用次数: 0

TCRosetta: An Integrated Analysis and Annotation Platform for T-cell Receptor Sequences. TCRosetta：T 细胞受体序列的综合分析和注释平台。

Genomics, proteomics & bioinformatics Pub Date : 2024-10-15 DOI: 10.1093/gpbjnl/qzae013

Tao Yue, Si-Yi Chen, Wen-Kang Shen, Zhan-Ye Zhang, Liming Cheng, An-Yuan Guo

{"title":"TCRosetta: An Integrated Analysis and Annotation Platform for T-cell Receptor Sequences.","authors":"Tao Yue, Si-Yi Chen, Wen-Kang Shen, Zhan-Ye Zhang, Liming Cheng, An-Yuan Guo","doi":"10.1093/gpbjnl/qzae013","DOIUrl":"10.1093/gpbjnl/qzae013","url":null,"abstract":"T cells and T-cell receptors (TCRs) are essential components of the adaptive immune system. Characterization of the TCR repertoire offers a promising and highly informative source for understanding the functions of T cells in the immune response and immunotherapy. Although TCR repertoire studies have attracted much attention, there are few online servers available for TCR repertoire analysis, especially for TCR sequence annotation or advanced analyses. Therefore, we developed TCRosetta, a comprehensive online server that integrates analytical methods for TCR repertoire analysis and visualization. TCRosetta combines general feature analysis, large-scale sequence clustering, network construction, peptide-TCR binding prediction, generation probability calculation, and k-mer motif analysis for TCR sequences, making TCR data analysis as simple as possible. The TCRosetta server accepts multiple input data formats and can analyze ∼ 20,000 TCR sequences in less than 3 min. TCRosetta is the most comprehensive web server available for TCR repertoire analysis and is freely available at https://guolab.wchscu.cn/TCRosetta/.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types. 泛癌症分析揭示不同癌症类型中的 m6A 变异和细胞特异性调控网络

Genomics, proteomics & bioinformatics Pub Date : 2024-10-15 DOI: 10.1093/gpbjnl/qzae052

Yao Lin, Jingyi Li, Shuaiyi Liang, Yaxin Chen, Yueqi Li, Yixian Cun, Lei Tian, Yuanli Zhou, Yitong Chen, Jiemei Chu, Hubin Chen, Qiang Luo, Ruili Zheng, Gang Wang, Hao Liang, Ping Cui, Sanqi An

{"title":"Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types.","authors":"Yao Lin, Jingyi Li, Shuaiyi Liang, Yaxin Chen, Yueqi Li, Yixian Cun, Lei Tian, Yuanli Zhou, Yitong Chen, Jiemei Chu, Hubin Chen, Qiang Luo, Ruili Zheng, Gang Wang, Hao Liang, Ping Cui, Sanqi An","doi":"10.1093/gpbjnl/qzae052","DOIUrl":"10.1093/gpbjnl/qzae052","url":null,"abstract":"As the most abundant messenger RNA (mRNA) modification, N6-methyladenosine (m6A) plays a crucial role in RNA fate, impacting cellular and physiological processes in various tumor types. However, our understanding of the role of the m6A methylome in tumor heterogeneity remains limited. Herein, we collected and analyzed m6A methylomes across nine human tissues from 97 m6A sequencing (m6A-seq) and RNA sequencing (RNA-seq) samples. Our findings demonstrate that m6A exhibits different heterogeneity in most tumor tissues compared to normal tissues, which contributes to the diverse clinical outcomes in different cancer types. We also found that the cancer type-specific m6A level regulated the expression of different cancer-related genes in distinct cancer types. Utilizing a novel and reliable method called \"m6A-express\", we predicted m6A-regulated genes and revealed that cancer type-specific m6A-regulated genes contributed to the prognosis, tumor origin, and infiltration level of immune cells in diverse patient populations. Furthermore, we identified cell-specific m6A regulators that regulate cancer-specific m6A and constructed a regulatory network. Experimental validation was performed, confirming that the cell-specific m6A regulator CAPRIN1 controls the m6A level of TP53. Overall, our work reveals the clinical relevance of m6A in various tumor tissues and explains how such heterogeneity is established. These results further suggest the potential of m6A in cancer precision medicine for patients with different cancer types.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11514823/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141545653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

eRNA-IDO: A One-stop Platform for Identification, Interactome Discovery, and Functional Annotation of Enhancer RNAs. eRNA-IDO: Enhancer RNAs 鉴定、交互组发现和功能注释的一站式平台。

Genomics, proteomics & bioinformatics Pub Date : 2024-10-15 DOI: 10.1093/gpbjnl/qzae059

Yuwei Zhang, Lihai Gong, Ruofan Ding, Wenyan Chen, Hao Rong, Yanguo Li, Fawziya Shameem, Korakkandan Arshad Ali, Lei Li, Qi Liao

{"title":"eRNA-IDO: A One-stop Platform for Identification, Interactome Discovery, and Functional Annotation of Enhancer RNAs.","authors":"Yuwei Zhang, Lihai Gong, Ruofan Ding, Wenyan Chen, Hao Rong, Yanguo Li, Fawziya Shameem, Korakkandan Arshad Ali, Lei Li, Qi Liao","doi":"10.1093/gpbjnl/qzae059","DOIUrl":"10.1093/gpbjnl/qzae059","url":null,"abstract":"Growing evidence supports the transcription of enhancer RNAs (eRNAs) and their important roles in gene regulation. However, their interactions with other biomolecules and their corresponding functionality remain poorly understood. In an attempt to facilitate mechanistic research, this study presents eRNA-IDO, the first integrative computational platform for the identification, interactome discovery, and functional annotation of human eRNAs. eRNA-IDO comprises two modules: eRNA-ID and eRNA-Anno. Functionally, eRNA-ID can identify eRNAs from de novo assembled transcriptomes. eRNA-ID includes eight kinds of enhancer makers, enabling users to customize enhancer regions flexibly and conveniently. In addition, eRNA-Anno provides cell-/tissue-specific functional annotation for both new and known eRNAs by analyzing the eRNA interactome from prebuilt or user-defined networks between eRNAs and protein-coding genes. The prebuilt networks include the Genotype-Tissue Expression (GTEx)-based co-expression networks in normal tissues, The Cancer Genome Atlas (TCGA)-based co-expression networks in cancer tissues, and omics-based eRNA-centric regulatory networks. eRNA-IDO can facilitate research on the biogenesis and functions of eRNAs. The eRNA-IDO server is freely available at http://bioinfo.szbl.ac.cn/eRNA_IDO/.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11514848/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142044264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cancer Stemness Online: A Resource for Investigating Cancer Stemness and Associations with Immune Response. 癌症干细胞在线：研究癌症干性及其与免疫反应关系的资源。

Genomics, proteomics & bioinformatics Pub Date : 2024-10-15 DOI: 10.1093/gpbjnl/qzae058

Weiwei Zhou, Minghai Su, Tiantongfei Jiang, Yunjin Xie, Jingyi Shi, Yingying Ma, Kang Xu, Gang Xu, Yongsheng Li, Juan Xu

{"title":"Cancer Stemness Online: A Resource for Investigating Cancer Stemness and Associations with Immune Response.","authors":"Weiwei Zhou, Minghai Su, Tiantongfei Jiang, Yunjin Xie, Jingyi Shi, Yingying Ma, Kang Xu, Gang Xu, Yongsheng Li, Juan Xu","doi":"10.1093/gpbjnl/qzae058","DOIUrl":"10.1093/gpbjnl/qzae058","url":null,"abstract":"Cancer progression involves the gradual loss of a differentiated phenotype and the acquisition of progenitor and stem cell-like features, which are potential culprits of immunotherapy resistance. Although the state-of-the-art predictive computational methods have facilitated the prediction of cancer stemness, there remains a lack of efficient resources to accommodate various usage requirements. Here, we present the Cancer Stemness Online, an integrated resource for efficiently scoring cancer stemness potential at both bulk and single-cell levels. This resource integrates eight robust predictive algorithms as well as 27 signature gene sets associated with cancer stemness for predicting stemness scores. Downstream analyses were performed from five distinct aspects: identifying the signature genes of cancer stemness; exploring the associations with cancer hallmarks and cellular states; exploring the associations with immune response and the communications with immune cells; investigating the contributions to patient survival; and performing a robustness analysis of cancer stemness among different methods. Moreover, the pre-calculated cancer stemness atlas for more than 40 cancer types can be accessed by users. Both the tables and diverse visualizations of the analytical results are available for download. Together, Cancer Stemness Online is a powerful resource for scoring cancer stemness and expanding downstream functional interpretation, including immune response and cancer hallmarks. Cancer Stemness Online is freely accessible at http://bio-bigdata.hrbmu.edu.cn/CancerStemnessOnline.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11522875/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141984186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Laws of Genome Nucleotide Composition. 基因组核苷酸组成规律

Genomics, proteomics & bioinformatics Pub Date : 2024-10-15 DOI: 10.1093/gpbjnl/qzae061

Zhang Zhang

引用次数: 0

Global Invasion History and Genomic Signatures of Adaptation of the Highly Invasive Sycamore Lace Bug. 高入侵性梧桐花边蝽的全球入侵历史和适应性基因组特征

Genomics, proteomics & bioinformatics Pub Date : 2024-10-14 DOI: 10.1093/gpbjnl/qzae074

Zhenyong Du, Xuan Wang, Yuange Duan, Shanlin Liu, Li Tian, Fan Song, Wanzhi Cai, Hu Li

{"title":"Global Invasion History and Genomic Signatures of Adaptation of the Highly Invasive Sycamore Lace Bug.","authors":"Zhenyong Du, Xuan Wang, Yuange Duan, Shanlin Liu, Li Tian, Fan Song, Wanzhi Cai, Hu Li","doi":"10.1093/gpbjnl/qzae074","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzae074","url":null,"abstract":"Invasive species cause massive economic and ecological damage. Climate change has resulted in an unprecedented increase in the number and impact of invasive species; however, the mechanisms underlying these invasions are unclear. The sycamore lace bug, Corythucha ciliata, is a highly invasive species originating from North America and has expanded across the Northern Hemisphere since the 1960s. In this study, we assembled the C. ciliata genome using high-coverage Pacific Biosciences (PacBio), Illumina, and high-throughput chromosome conformation capture (Hi-C) sequencing. A total of 15,278 protein-coding genes were identified, and expansions of gene families with oxidoreductase and metabolic activities were observed. In-depth resequencing of 402 samples from native and nine invaded countries across three continents revealed 2.74 million single nucleotide polymorphisms. Two major invasion routes of C. ciliata were identified from North America to Europe and Japan, with a contact zone forming in East Asia. Genomic signatures of selection associated with invasion and long-term balancing selection in native ranges were identified. These genomic signatures overlapped with expanded genes, suggesting improvements in the oxidative stress and thermal tolerance of C. ciliata. These findings offer valuable insights into the genomic architecture and adaptive evolution underlying the invasive capabilities of species during rapid environmental changes.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RAG-seq: A NSR Primed and Transposase Tagmentation Mediated Strand-specific Total RNA Sequencing in Single Cell. RAG-seq：NSR引物和转座酶标记介导的单细胞链特异性总RNA测序。

Genomics, proteomics & bioinformatics Pub Date : 2024-10-10 DOI: 10.1093/gpbjnl/qzae072

Ping Xu, Zhiheng Yuan, Xiaohua Lu, Peng Zhou, Ding Qiu, Zhenghao Qiao, Zhongcheng Zhou, Li Guan, Yongkang Jia, Xuan He, Ling Sun, Youzhong Wan, Ming Wang, Yang Yu

{"title":"RAG-seq: A NSR Primed and Transposase Tagmentation Mediated Strand-specific Total RNA Sequencing in Single Cell.","authors":"Ping Xu, Zhiheng Yuan, Xiaohua Lu, Peng Zhou, Ding Qiu, Zhenghao Qiao, Zhongcheng Zhou, Li Guan, Yongkang Jia, Xuan He, Ling Sun, Youzhong Wan, Ming Wang, Yang Yu","doi":"10.1093/gpbjnl/qzae072","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzae072","url":null,"abstract":"Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of cellular diversity with unprecedented resolution. However, many current methods are limited in capturing full-length transcripts and discerning strand orientation. We present RAG-seq, an innovative strand-specific total RNA sequencing technique that combines not-so-random (NSR) primers with Tn5 transposase-mediated tagmentation. RAG-seq overcomes previous limitations by delivering comprehensive transcript coverage and maintaining strand orientation, which is essential for accurate quantification of overlapping genes and detection of antisense transcripts. Through optimized reverse transcription with oligo dT primers, rRNA depletion via Depletion of Abundant Sequences by Hybridization (DASH), and linear amplification, RAG-seq enhances sensitivity and reproducibility, especially for low-input samples and single cells. Application to mouse oocytes and early embryos highlights RAG-seq's superior performance in identifying stage-specific antisense transcripts, shedding light on their regulatory roles during early development. This advancement represents a significant leap in transcriptome analysis within complex biological contexts.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

GP-Plotter: Flexible Spectral Visualization for Proteomics Data with Emphasis on Glycoproteomics Analysis. GP-Plotter：灵活的蛋白质组学数据光谱可视化，重点是糖蛋白组学分析。

Genomics, proteomics & bioinformatics Pub Date : 2024-10-08 DOI: 10.1093/gpbjnl/qzae069

Zheng Fang, Mingming Dong, Hongqiang Qin, Mingliang Ye

{"title":"GP-Plotter: Flexible Spectral Visualization for Proteomics Data with Emphasis on Glycoproteomics Analysis.","authors":"Zheng Fang, Mingming Dong, Hongqiang Qin, Mingliang Ye","doi":"10.1093/gpbjnl/qzae069","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzae069","url":null,"abstract":"Identification evaluation and result dissemination are essential components in mass spectrometry-based proteomics analysis. The visualization of fragment ions in mass spectrum provides strong evidence for peptide identification and modification localization. Here, we present an easy-to-use tool, named GP-Plotter, for ion annotation of tandem mass spectra and corresponding image output. Identification result files of common searching tools in the community and user-customized files are supported as input of GP-Plotter. Multiple display modes and parameter customization can be achieved in GP-Plotter to present annotated spectra of interest. Different image formats, especially vector graphic formats, are available for image generation which is favorable for data publication. Notably, GP-Plotter is also well-suited for the visualization and evaluation of glycopeptide spectrum assignments with comprehensive annotation of glycan fragment ions. With a user-friendly graphical interface, GP-Plotter is expected to be a universal visualization tool for the community. GP-Plotter has been implemented in the latest version of Glyco-Decipher (v1.0.4) and the standalone GP-Plotter software is also freely available at https://github.com/DICP-1809.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142396283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0