Periodic Reporting for period 1 - LongTREC (Long-TREC: The Long-Reads Transcriptomics European Consortium. The next generation transcriptome biology revealed by single molecule sequencing technologies)
Période du rapport: 2022-10-01 au 2024-09-30
Long-reads RNA sequencing (lrRNA-seq) is the near future of the transcriptomics field. It will improve the knowledge in very different areas such as biomedicine, agriculture or biodiversity among others, which will impact the society by improving, for example, disease diagnosis for patients, develop targeted treatments or vaccines, and identify genes for drought resistance, higher yield or plan disease resistance or ecosystem monitoring. Although some of these applications can be undertaken by short-reads, information is missed by the main limitation of short-read sequencing, the lack of reads spanning full isoforms. This limitation can be addressed by long-reads.
LongTREC researchers are working together to improve the methodology associated with lrRNA-seq. New bioinformatics tools are being developed to help analyze RNA sequences more efficiently, detect modifications in RNA, understand gene regulation, and even classify cancer patients more accurately; these tools are useful in studying various organisms and diseases. Advanced methods, including artificial intelligence, are helping LongTREC researchers detect changes in genes linked to diseases like cancer. Another exciting development is the use of RNA sequencing to study marine ecosystems, revealing new insights into ocean life. LongTREC members are expanding their work into multiomics looking at how different molecular processes work together. Some of these techniques are being fine-tuned to ensure they work across different species. Lastly, the team is dedicated to making these tools more user-friendly and widely available to scientists with non-bioinformatics knowledge. We are integrating our work into existing software platforms and creating easy-to-use workflows that help non-computational scientists analyze their data more effectively. Finally, LongTREC team is also developing a central resource for documentation, making it easier for others to learn and use these methods.
LongTREC researchers are working together to improve the methodology associated with lrRNA-seq. New bioinformatics tools are being developed to help analyze RNA sequences more efficiently, detect modifications in RNA, understand gene regulation, and even classify cancer patients more accurately; these tools are useful in studying various organisms and diseases. Advanced methods, including artificial intelligence, are helping LongTREC researchers detect changes in genes linked to diseases like cancer. Another exciting development is the use of RNA sequencing to study marine ecosystems, revealing new insights into ocean life. LongTREC members are expanding their work into multiomics looking at how different molecular processes work together. Some of these techniques are being fine-tuned to ensure they work across different species. Lastly, the team is dedicated to making these tools more user-friendly and widely available to scientists with non-bioinformatics knowledge. We are integrating our work into existing software platforms and creating easy-to-use workflows that help non-computational scientists analyze their data more effectively. Finally, LongTREC team is also developing a central resource for documentation, making it easier for others to learn and use these methods.
The LongTREC consortium has made significant contributions to the field of long-read transcriptomics, with several publications advancing the understanding of gene expression, regulation, and sequencing technologies. Dr. Ralf Herwig co-authored a paper focusing on methods for accurately characterizing full-length isoforms using long-read sequencing technologies like PacBio and Oxford Nanopore. These methods enhance the ability to capture alternative splicing, gene fusion events, and transcript diversity, improving the overall accuracy and efficiency of transcriptomic studies. Additionally, Dr. Herwig and LongTREC student Yalan Bi published a study introducing Isotools 2.0 a computational tool designed to efficiently process and analyze long-read sequencing data. This tool facilitates isoform identification, quantification, and quality assessment, addressing key challenges in transcriptome analysis and improving the scalability of long-read workflows. Another contribution from the LongTREC team includes the development of Icarust, a simulation tool created by Dr. Matthew Loose and LongTREC student Satrio Wibowo at the University of Nottingham. Icarust enhances adaptive sampling in Oxford Nanopore sequencing, enabling selective sequencing of specific transcripts in real-time to improve efficiency and reduce costs. Dr. Kristina Gruden, Dr. Marko Petek, and LongTREC student Nadja Nolte, from the National Institute of Biology in Slovenia, have published a work using long-read RNA sequencing to refine gene models in potato. This research improves transcriptomic accuracy by identifying full-length isoforms and alternative splicing events, supporting more precise genomic research and breeding efforts.
Two review articles have also expanded the understanding of long-read sequencing. First by Dr. Ana Conesa and LongTREC student Tianyuan Liu explores how long-read sequencing is transforming epigenomic studies, enabling direct detection of DNA methylation and RNA modifications. The second review by Dr. Eva Novoa and LongTREC student Xanthi-Lida Katopodi examines the potential of nanopore RNA sequencing in clinical applications, highlighting its ability to capture full-length transcripts and isoform diversity, offering promise for personalized medicine and diagnostics.
In summary, the LongTREC consortium’s work is advancing long-read sequencing technologies, with applications spanning from plant genomics to epigenomics and clinical diagnostics, ultimately improving the understanding of gene expression and regulatory mechanisms across various fields.
Two review articles have also expanded the understanding of long-read sequencing. First by Dr. Ana Conesa and LongTREC student Tianyuan Liu explores how long-read sequencing is transforming epigenomic studies, enabling direct detection of DNA methylation and RNA modifications. The second review by Dr. Eva Novoa and LongTREC student Xanthi-Lida Katopodi examines the potential of nanopore RNA sequencing in clinical applications, highlighting its ability to capture full-length transcripts and isoform diversity, offering promise for personalized medicine and diagnostics.
In summary, the LongTREC consortium’s work is advancing long-read sequencing technologies, with applications spanning from plant genomics to epigenomics and clinical diagnostics, ultimately improving the understanding of gene expression and regulatory mechanisms across various fields.
The LongTREC project is at the forefront of developing cutting-edge software for the analysis of third-generation sequencing data. LongTREC is dedicated to developing innovative methods for high-quality biological sample processing, ensuring that the resulting sequencing data is accurate and reliable. Beyond data generation, the project is committed to creating bioinformatics software that facilitates the exploration of RNA diversity in various fields. These include studying the role of RNA in inflammatory diseases and cancer, improving crop resilience and agricultural biotechnology, analyzing ecosystem diversity, and enhancing biodiversity annotation. A key aspect of LongTREC is the creation of an integrated ecosystem of bioinformatics tools, designed to work seamlessly together to perform sophisticated RNA analyses using third-generation sequencing. This interconnected suite of software will empower researchers to extract meaningful biological insights from complex RNA datasets with greater precision and efficiency than ever before.
LongTREC represents a significant step forward in RNA research, bridging computational biology with real-world applications in medicine, agriculture, and environmental sciences. Through its pioneering software solutions and commitment to scientific education, LongTREC is paving the way for a deeper understanding of RNA’s role in shaping life’s complexity.
LongTREC represents a significant step forward in RNA research, bridging computational biology with real-world applications in medicine, agriculture, and environmental sciences. Through its pioneering software solutions and commitment to scientific education, LongTREC is paving the way for a deeper understanding of RNA’s role in shaping life’s complexity.