Genomics, proteomics & bioinformatics最新文献_第3页

Reprogramming of RNA m6A Modification Is Required for Acute Myeloid Leukemia Development. 急性髓性白血病的发展需要对 RNA m6A 修饰进行重编程。

Genomics, proteomics & bioinformatics Pub Date : 2024-06-24 DOI: 10.1093/gpbjnl/qzae049

Weidong Liu, Yuhua Wang, Shuxin Yao, Guoqiang Han, Jin Hu, Rong Yin, Fuling Zhou, Ying Cheng, Haojian Zhang

{"title":"Reprogramming of RNA m6A Modification Is Required for Acute Myeloid Leukemia Development.","authors":"Weidong Liu, Yuhua Wang, Shuxin Yao, Guoqiang Han, Jin Hu, Rong Yin, Fuling Zhou, Ying Cheng, Haojian Zhang","doi":"10.1093/gpbjnl/qzae049","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzae049","url":null,"abstract":"Hematopoietic homeostasis is maintained by hematopoietic stem cells (HSCs), and it is tightly controlled at multiple levels to sustain the self-renewal capacity and differentiation potential of HSCs. Dysregulation of self-renewal and differentiation of HSCs leads to the development of hematologic diseases, including acute myeloid leukemia (AML). Thus, understanding the underlying mechanisms of HSC maintenance and the development of hematologic malignancies is one of the fundamental scientific endeavors in stem cell biology. N 6-methyladenosine (m6A) is a common modification in mammalian messenger RNAs (mRNAs) and plays important roles in various biological processes. In this study, we performed a comparative analysis of the dynamics of the RNA m6A methylome of hematopoietic stem and progenitor cells (HSPCs) and leukemia-initiating cells (LICs) in AML. We found that RNA m6A modification regulates the transformation of long-term HSCs into short-term HSCs and determines the lineage commitment of HSCs. Interestingly, m6A modification leads to reprogramming that promotes cellular transformation during AML development, and LIC-specific m6A targets are recognized by different m6A readers. Moreover, the very long chain fatty acid transporter ATP-binding cassette subfamily D member 2 (ABCD2) is a key factor that promotes AML development, and deletion of ABCD2 damages clonogenic ability, inhibits proliferation, and promotes apoptosis of human leukemia cells. This study provides a comprehensive understanding of the role of m6A in regulating cell state transition in normal hematopoiesis and leukemogenesis, and identifies ABCD2 as a key factor in AML development.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141447874","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

The Bioinformatic Applications of Hi-C and Linked Reads. Hi-C 和关联读数的生物信息学应用

Genomics, proteomics & bioinformatics Pub Date : 2024-06-21 DOI: 10.1093/gpbjnl/qzae048

Libo Jiang, Michael A Quail, Jack Fraser-Govi, Haipeng Wang, Xuequn Shi, Karen Oliver, Esther Mellado Gomez, Fengtang Yang, Zemin Ning

{"title":"The Bioinformatic Applications of Hi-C and Linked Reads.","authors":"Libo Jiang, Michael A Quail, Jack Fraser-Govi, Haipeng Wang, Xuequn Shi, Karen Oliver, Esther Mellado Gomez, Fengtang Yang, Zemin Ning","doi":"10.1093/gpbjnl/qzae048","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzae048","url":null,"abstract":"Long-range sequencing grants insight into additional genetic information beyond that which can be accessed by both short reads and modern long-read technology. Several new sequencing technologies are available for long-range datasets such as \"Hi-C\" and \"Linked Reads\" with high-throughput and high-resolution genome analysis, and are rapidly advancing the field of genome assembly, genome scaffolding, and more comprehensive variant identification. In this article, we focused on five major long-range sequencing technologies: high-throughput chromosome conformation capture (Hi-C), 10x Genomics Linked Reads, haplotagging, transposase enzyme linked long-read sequencing (TELL-seq), and single tube long fragment read (stLFR). We detailed the mechanisms and data products of the five platforms, introduced several of the most important applications, evaluated the quality of sequencing data from different platforms, and discussed the currently available bioinformatics tools. We hope this work will benefit the selection of appropriate long-range technology for specific biological studies.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141437947","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

Deep Amplicon Sequencing Reveals Culture Selection of Mycobacterium Tuberculosis by Clinical Samples. 深度扩增子测序揭示了临床样本对结核分枝杆菌培养的选择。

Genomics, proteomics & bioinformatics Pub Date : 2024-06-13 DOI: 10.1093/gpbjnl/qzae046

Jiuxin Qu, Wanfei Liu, Shuyan Chen, Chi Wu, Wenjie Lai, Rui Qin, Feidi Ye, Yuanchun Li, Liang Fu, Guofang Deng, Lei Liu, Qiang Lin, Peng Cui

{"title":"Deep Amplicon Sequencing Reveals Culture Selection of Mycobacterium Tuberculosis by Clinical Samples.","authors":"Jiuxin Qu, Wanfei Liu, Shuyan Chen, Chi Wu, Wenjie Lai, Rui Qin, Feidi Ye, Yuanchun Li, Liang Fu, Guofang Deng, Lei Liu, Qiang Lin, Peng Cui","doi":"10.1093/gpbjnl/qzae046","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzae046","url":null,"abstract":"The commonly-used drug susceptibility testing (DST) relies on bacterial culture and faces shortcomings such as long turnaround time and clone/subclone selection. We developed a targeted deep amplification sequencing (DAS) method directly applied to clinical specimens. In this DAS panel, we examined 941 drug-resistant mutations associated with 20 anti-tuberculosis drugs with an initial amount of 4 pg DNA and reduced clinical testing time from 20 days to two days. A prospective study was conducted using 115 clinical specimens mainly with Xpert® Mycobacterium tuberculosis/rifampicin (Xpert MTB/RIF) assay positive to evaluate drug-resistant mutation detection. DAS was performed on culture-free specimens, while culture-dependent isolates were used for phenotypic DST, DAS, and whole-genome sequencing (WGS). For in silico molecular DST, our result based on DAS panel revealed the similar accuracy to three published reports based on WGS. For 82 isolates, application of DAS showed better sensitivity (93.03% vs. 92.16%), specificity (96.10% vs. 95.02%), and accuracy (91.33% vs. 90.62%) than Mykrobe software using WGS. Compared to culture-dependent WGS, culture-free DAS provides a full picture of sequence variation at population level, exhibiting in detail the gain-and-loss variants caused by bacterial culture. Our study performs a systematic verification of the advantages of DAS in clinical applications and comprehensively illustrates the discrepancy in Mycobacterium tuberculosis before and after culture.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319301","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

CBioProfiler: A Web and Standalone Pipeline for Cancer Biomarker and Subtype Characterization. CBioProfiler：用于癌症生物标记物和亚型特征描述的网络和独立管道。

Genomics, proteomics & bioinformatics Pub Date : 2024-06-12 DOI: 10.1093/gpbjnl/qzae045

Xiaoping Liu, Zisong Wang, Hongjie Shi, Sheng Li, Xinghuan Wang

{"title":"CBioProfiler: A Web and Standalone Pipeline for Cancer Biomarker and Subtype Characterization.","authors":"Xiaoping Liu, Zisong Wang, Hongjie Shi, Sheng Li, Xinghuan Wang","doi":"10.1093/gpbjnl/qzae045","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzae045","url":null,"abstract":"Cancer is a leading cause of death worldwide, and the identification of biomarkers and subtypes that can predict the long-term survival of cancer patients is essential for their risk stratification, treatment, and prognosis. However, there are currently no standardized tools for exploring cancer biomarkers or subtypes. In this study, we introduced Cancer Biomarker and Subtype Profiler (CBioProfiler), a web server and standalone application that includes two pipelines for analyzing cancer biomarkers and subtypes. The cancer biomarker pipeline consists of five modules for identifying and annotating cancer survival-related biomarkers using multiple survival-related machine learning algorithms. The cancer subtype pipeline includes three modules for data preprocessing, subtype identification using multiple unsupervised machine learning methods, as well as subtype evaluation and validation. CBioProfiler also includes CuratedCancerPrognosisData, a novel R package that integrates reviewed and curated gene expression and clinical data from 268 studies. These studies cover 43 common blood and solid tumors and draw upon 47,686 clinical samples. The web server is available at https://www.cbioprofiler.com/ and https://cbioprofiler.znhospital.cn/CBioProfiler/, and the standalone app and source code can be found at https://github.com/liuxiaoping2020/CBioProfiler.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141312596","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

Acknowledgments to Reviewers 2023. 鸣谢审稿人 2023.

Genomics, proteomics & bioinformatics Pub Date : 2024-05-09 DOI: 10.1093/gpbjnl/qzae038

引用次数: 0

RNase P: Beyond Precursor tRNA Processing. RNase P：超越前体 tRNA 处理。

Genomics, proteomics & bioinformatics Pub Date : 2024-05-09 DOI: 10.1093/gpbjnl/qzae016

Peipei Wang, Juntao Lin, Xiangyang Zheng, Xingzhi Xu

引用次数: 0

KoNA: Korean Nucleotide Archive as A New Data Repository for Nucleotide Sequence Data. KoNA：作为核苷酸序列数据新数据储存库的韩国核苷酸档案。

Genomics, proteomics & bioinformatics Pub Date : 2024-05-09 DOI: 10.1093/gpbjnl/qzae017

Gunhwan Ko, Jae Ho Lee, Young Mi Sim, Wangho Song, Byung-Ha Yoon, Iksu Byeon, Bang Hyuck Lee, Sang-Ok Kim, Jinhyuk Choi, Insoo Jang, Hyerin Kim, Jin Ok Yang, Kiwon Jang, Sora Kim, Jong-Hwan Kim, Jongbum Jeon, Jaeeun Jung, Seungwoo Hwang, Ji-Hwan Park, Pan-Gyu Kim, Seon-Young Kim, Byungwook Lee

{"title":"KoNA: Korean Nucleotide Archive as A New Data Repository for Nucleotide Sequence Data.","authors":"Gunhwan Ko, Jae Ho Lee, Young Mi Sim, Wangho Song, Byung-Ha Yoon, Iksu Byeon, Bang Hyuck Lee, Sang-Ok Kim, Jinhyuk Choi, Insoo Jang, Hyerin Kim, Jin Ok Yang, Kiwon Jang, Sora Kim, Jong-Hwan Kim, Jongbum Jeon, Jaeeun Jung, Seungwoo Hwang, Ji-Hwan Park, Pan-Gyu Kim, Seon-Young Kim, Byungwook Lee","doi":"10.1093/gpbjnl/qzae017","DOIUrl":"10.1093/gpbjnl/qzae017","url":null,"abstract":"During the last decade, the generation and accumulation of petabase-scale high-throughput sequencing data have resulted in great challenges, including access to human data, as well as transfer, storage, and sharing of enormous amounts of data. To promote data-driven biological research, the Korean government announced that all biological data generated from government-funded research projects should be deposited at the Korea BioData Station (K-BDS), which consists of multiple databases for individual data types. Here, we introduce the Korean Nucleotide Archive (KoNA), a repository of nucleotide sequence data. As of July 2022, the Korean Read Archive in KoNA has collected over 477 TB of raw next-generation sequencing data from national genome projects. To ensure data quality and prepare for international alignment, a standard operating procedure was adopted, which is similar to that of the International Nucleotide Sequence Database Collaboration. The standard operating procedure includes quality control processes for submitted data and metadata using an automated pipeline, followed by manual examination. To ensure fast and stable data transfer, a high-speed transmission system called GBox is used in KoNA. Furthermore, the data uploaded to or downloaded from KoNA through GBox can be readily processed using a cloud computing service called Bio-Express. This seamless coupling of KoNA, GBox, and Bio-Express enhances the data experience, including submission, access, and analysis of raw nucleotide sequences. KoNA not only satisfies the unmet needs for a national sequence repository in Korea but also provides datasets to researchers globally and contributes to advances in genomics. The KoNA is available at https://www.kobic.re.kr/kona/.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141307671","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

Correction to: dbDEMC 3.0: Functional Exploration of Differentially Expressed miRNAs in Cancers of Human and Model Organisms. 更正为：dbDEMC 3.0：人类和模式生物癌症中差异表达 miRNA 的功能探索。

Genomics, proteomics & bioinformatics Pub Date : 2024-05-09 DOI: 10.1093/gpbjnl/qzae037

引用次数: 0

T2T-YAO, T2T-SHUN, and more. T2T-YAO、T2T-SHUN等。

Genomics, proteomics & bioinformatics Pub Date : 2023-12-01 Epub Date: 2023-09-22 DOI: 10.1016/j.gpb.2023.09.002

Jingfa Xiao, Jun Yu

引用次数: 0

T2T-YAO Reference Genome of Han Chinese - New Step in Advancing Precision Medicine in China. 汉族T2T-YAO参考基因组-中国精准医学发展的新步伐。

Genomics, proteomics & bioinformatics Pub Date : 2023-12-01 Epub Date: 2023-09-22 DOI: 10.1016/j.gpb.2023.09.001

Xue Zhang

引用次数: 0