NAR Genomics and Bioinformatics最新文献_第7页

Intronic RNA secondary structural information captured for the human MYC pre-mRNA. 捕捉到的人类 MYC 前核糖核酸内部二级结构信息。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-24 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae143

Taylor O Eich, Collin A O'Leary, Walter N Moss

{"title":"Intronic RNA secondary structural information captured for the human MYC pre-mRNA.","authors":"Taylor O Eich, Collin A O'Leary, Walter N Moss","doi":"10.1093/nargab/lqae143","DOIUrl":"10.1093/nargab/lqae143","url":null,"abstract":"To address the lack of intronic reads in secondary structure probing data for the human MYC pre-mRNA, we developed a method that combines spliceosomal inhibition with RNA probing and sequencing. Here, the SIRP-seq method was applied to study the secondary structure of human MYC RNAs by chemically probing HeLa cells with dimethyl sulfate in the presence of the small molecule spliceosome inhibitor pladienolide B. Pladienolide B binds to the SF3B complex of the spliceosome to inhibit intron removal during splicing, resulting in retained intronic sequences. This method was used to increase the read coverage over intronic regions of MYC. The purpose for increasing coverage across introns was to generate complete reactivity profiles for intronic sequences via the DMS-MaPseq approach. Notably, depth was sufficient for analysis by the program DRACO, which was able to deduce distinct reactivity profiles and predict multiple secondary structural conformations as well as their suggested stoichiometric abundances. The results presented here provide a new method for intronic RNA secondary structural analyses, as well as specific structural insights relevant to MYC RNA splicing regulation and therapeutic targeting.","PeriodicalId":33994,"journal":{"name":"NAR Genomics and Bioinformatics","volume":"6 4","pages":"lqae143"},"PeriodicalIF":4.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11500451/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509478","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

The next-generation sequencing-chess problem. 下一代测序-国际象棋问题。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-24 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae144

Leo Zeitler, Arach Goldar, Cyril Denby Wilkes, Julie Soutourina

引用次数: 0

Graphite: painting genomes using a colored de Bruijn graph. 石墨：使用彩色德布鲁因图绘制基因组。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-23 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae142

Rick Beeloo, Aldert L Zomer, Sebastian Deorowicz, Bas E Dutilh

引用次数: 0

MoNETA: MultiOmics Network Embedding for SubType Analysis. MoNETA：用于子类型分析的多声学网络嵌入。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-16 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae141

Giovanni Scala, Luigi Ferraro, Aurora Brandi, Yan Guo, Barbara Majello, Michele Ceccarelli

引用次数: 0

bcRflow: a Nextflow pipeline for characterizing B cell receptor repertoires from non-targeted transcriptomic data. bcRflow：从非靶向转录组数据表征 B 细胞受体谱系的 Nextflow 管道。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-15 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae137

Brent T Schlegel, Michael Morikone, Fangping Mu, Wan-Yee Tang, Gary Kohanbash, Dhivyaa Rajasundaram

{"title":"bcRflow: a Nextflow pipeline for characterizing B cell receptor repertoires from non-targeted transcriptomic data.","authors":"Brent T Schlegel, Michael Morikone, Fangping Mu, Wan-Yee Tang, Gary Kohanbash, Dhivyaa Rajasundaram","doi":"10.1093/nargab/lqae137","DOIUrl":"10.1093/nargab/lqae137","url":null,"abstract":"B cells play a critical role in the adaptive recognition of foreign antigens through diverse receptor generation. While targeted immune sequencing methods are commonly used to profile B cell receptors (BCRs), they have limitations in cost and tissue availability. Analyzing B cell receptor profiling from non-targeted transcriptomics data is a promising alternative, but a systematic pipeline integrating tools for accurate immune repertoire extraction is lacking. Here, we present bcRflow, a Nextflow pipeline designed to characterize BCR repertoires from non-targeted transcriptomics data, with functional modules for alignment, processing, and visualization. bcRflow is a comprehensive, reproducible, and scalable pipeline that can run on high-performance computing clusters, cloud-based computing resources like Amazon Web Services (AWS), the Open OnDemand framework, or even local desktops. bcRflow utilizes institutional configurations provided by nf-core to ensure maximum portability and accessibility. To demonstrate the functionality of the bcRflow pipeline, we analyzed a public dataset of bulk transcriptomic samples from COVID-19 patients and healthy controls. We have shown that bcRflow streamlines the analysis of BCR repertoires from non-targeted transcriptomics data, providing valuable insights into the B cell immune response for biological and clinical research. bcRflow is available at https://github.com/Bioinformatics-Core-at-Childrens/bcRflow.","PeriodicalId":33994,"journal":{"name":"NAR Genomics and Bioinformatics","volume":"6 4","pages":"lqae137"},"PeriodicalIF":4.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11474772/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142476445","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

Dynamic configuration and data security for bioinformatics cloud services with the Laniakea Dashboard. 利用 Laniakea Dashboard 实现生物信息学云服务的动态配置和数据安全。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-10 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae140

Marco Antonio Tangaro, Marica Antonacci, Giacinto Donvito, Nadina Foggetti, Pietro Mandreoli, Daniele Colombo, Graziano Pesole, Federico Zambelli

{"title":"Dynamic configuration and data security for bioinformatics cloud services with the Laniakea Dashboard.","authors":"Marco Antonio Tangaro, Marica Antonacci, Giacinto Donvito, Nadina Foggetti, Pietro Mandreoli, Daniele Colombo, Graziano Pesole, Federico Zambelli","doi":"10.1093/nargab/lqae140","DOIUrl":"10.1093/nargab/lqae140","url":null,"abstract":"Technological advances in high-throughput technologies improve our ability to explore the molecular mechanisms of life. Computational infrastructures for scientific applications fulfil a critical role in harnessing this potential. However, there is an ongoing need to improve accessibility and implement robust data security technologies to allow the processing of sensitive data, particularly human genetic data. Scientific clouds have emerged as a promising solution to meet these needs. We present three components of the Laniakea software stack, initially developed to support the provision of private on-demand Galaxy instances. These components can be adopted by providers of scientific cloud services built on the INDIGO PaaS layer. The Dashboard translates configuration template files into user-friendly web interfaces, enabling the easy configuration and launch of on-demand applications. The secret management and the encryption components, integrated within the Dashboard, support the secure handling of passphrases and credentials and the deployment of block-level encrypted storage volumes for managing sensitive data in the cloud environment. By adopting these software components, scientific cloud providers can develop convenient, secure and efficient on-demand services for their users.","PeriodicalId":33994,"journal":{"name":"NAR Genomics and Bioinformatics","volume":"6 4","pages":"lqae140"},"PeriodicalIF":4.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11464921/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142401507","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

scATAcat: cell-type annotation for scATAC-seq data. scATAcat：用于 scATAC-seq 数据的细胞类型注释。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-08 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae135

Aybuge Altay, Martin Vingron

引用次数: 0

TrajectoryGeometry suggests cell fate decisions can involve branches rather than bifurcations. 轨迹几何表明，细胞命运的决定可能涉及分支而非分叉。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-08 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae139

Anna Laddach, Vassilis Pachnis, Michael Shapiro

{"title":"TrajectoryGeometry suggests cell fate decisions can involve branches rather than bifurcations.","authors":"Anna Laddach, Vassilis Pachnis, Michael Shapiro","doi":"10.1093/nargab/lqae139","DOIUrl":"10.1093/nargab/lqae139","url":null,"abstract":"Differentiation of multipotential progenitor cells is a key process in the development of any multi-cellular organism and often continues throughout its life. It is often assumed that a bi-potential progenitor develops along a (relatively) straight trajectory until it reaches a decision point where the trajectory bifurcates. At this point one of two directions is chosen, each direction representing the unfolding of a new transcriptional programme. However, we have lacked quantitative means for testing this model. Accordingly, we have developed the R package TrajectoryGeometry. Applying this to published data we find several examples where, rather than bifurcate, developmental pathways branch. That is, the bipotential progenitor develops along a relatively straight trajectory leading to one of its potential fates. A second relatively straight trajectory branches off from this towards the other potential fate. In this sense only cells that branch off to follow the second trajectory make a 'decision'. Our methods give precise descriptions of the genes and cellular pathways involved in these trajectories. We speculate that branching may be the more common behaviour and may have advantages from a control-theoretic viewpoint.","PeriodicalId":33994,"journal":{"name":"NAR Genomics and Bioinformatics","volume":"6 4","pages":"lqae139"},"PeriodicalIF":4.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11459380/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142393890","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

Genome wide clustering on integrated chromatin states and Micro-C contacts reveals chromatin interaction signatures. 整合染色质状态和 Micro-C 接触的全基因组聚类揭示了染色质相互作用特征。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-03 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae136

Corinne E Sexton, Sylvia Victor Paul, Dylan Barth, Mira V Han

引用次数: 0

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package. 利用 Signifinder Bioconductor 软件包探索大量、单细胞和空间转录组学数据中的公共癌症基因表达特征。

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NAR Genomics and Bioinformatics Pub Date : 2024-10-03 eCollection Date: 2024-09-01 DOI: 10.1093/nargab/lqae138

Stefania Pirrotta, Laura Masatti, Anna Bortolato, Anna Corrà, Fabiola Pedrini, Martina Aere, Giovanni Esposito, Paolo Martini, Davide Risso, Chiara Romualdi, Enrica Calura

{"title":"Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package.","authors":"Stefania Pirrotta, Laura Masatti, Anna Bortolato, Anna Corrà, Fabiola Pedrini, Martina Aere, Giovanni Esposito, Paolo Martini, Davide Risso, Chiara Romualdi, Enrica Calura","doi":"10.1093/nargab/lqae138","DOIUrl":"10.1093/nargab/lqae138","url":null,"abstract":"Understanding cancer mechanisms, defining subtypes, predicting prognosis and assessing therapy efficacy are crucial aspects of cancer research. Gene-expression signatures derived from bulk gene expression data have played a significant role in these endeavors over the past decade. However, recent advancements in high-resolution transcriptomic technologies, such as single-cell RNA sequencing and spatial transcriptomics, have revealed the complex cellular heterogeneity within tumors, necessitating the development of computational tools to characterize tumor mass heterogeneity accurately. Thus we implemented signifinder, a novel R Bioconductor package designed to streamline the collection and use of cancer transcriptional signatures across bulk, single-cell, and spatial transcriptomics data. Leveraging publicly available signatures curated by signifinder, users can assess a wide range of tumor characteristics, including hallmark processes, therapy responses, and tumor microenvironment peculiarities. Through three case studies, we demonstrate the utility of transcriptional signatures in bulk, single-cell, and spatial transcriptomic data analyses, providing insights into cell-resolution transcriptional signatures in oncology. Signifinder represents a significant advancement in cancer transcriptomic data analysis, offering a comprehensive framework for interpreting high-resolution data and addressing tumor complexity.","PeriodicalId":33994,"journal":{"name":"NAR Genomics and Bioinformatics","volume":"6 4","pages":"lqae138"},"PeriodicalIF":4.0,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11447528/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373105","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