Challenges in identifying mRNA transcript starts and ends from long-read sequencing data

Genome Research, Journal Year: 2024, Volume and Issue: 34(11), P. 1719 - 1734

Published: Nov. 1, 2024

Long-read sequencing (LRS) technologies have the potential to revolutionize scientific discoveries in RNA biology through comprehensive identification and quantification of full-length mRNA isoforms. Despite great promise, challenges remain widespread implementation LRS for RNA-based applications, including concerns about low coverage, high error, robust computational pipelines. Although much focus has been placed on defining exon composition structure with data, less careful characterization done ability assess terminal ends isoforms, specifically, transcription start end sites. Such is crucial completely delineating full molecules regulatory consequences. However, there are substantial inconsistencies both coordinates reads spanning a gene, such that often fail accurately recapitulate annotated or empirically derived molecules. Here, we describe specific identifying quantifying how these issues influence biological interpretations data. We then review recent experimental advances designed alleviate problems, ideal use cases each approach. Finally, outline anticipated developments necessary improvements from

Language: Английский

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Transcriptomics in the era of long-read sequencing

Nature Reviews Genetics, Journal Year: 2025, Volume and Issue: unknown

Published: March 28, 2025

Language: Английский

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Enhancing novel isoform discovery: leveraging nanopore long-read sequencing and machine learning approaches

Briefings in Functional Genomics, Journal Year: 2024, Volume and Issue: 23(6), P. 683 - 694

Published: Aug. 19, 2024

Long-read sequencing technologies can capture entire RNA transcripts in a single read, reducing the ambiguity constructing and quantifying transcript models comparison to more common earlier methods, such as short-read sequencing. Recent improvements accuracy of long-read have expanded scope for novel splice isoform detection also enabled far accurate reconstruction complex splicing patterns transcriptomes. Additionally, incorporation advancements machine learning deep algorithms bioinformatic software significantly improved reliability transcriptomic studies. However, there is lack consensus on what tools pipelines produce most precise consistent results. Thus, this review aims discuss compare performance available methods discovery with technologies, 25 being presented. Furthermore, intends demonstrate need developing standard analytical pipelines, tools, model conventions

Language: Английский

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TKSM: highly modular, user-customizable, and scalable transcriptomic sequencing long-read simulator

Bioinformatics, Journal Year: 2024, Volume and Issue: 40(2)

Published: Jan. 25, 2024

Transcriptomic long-read (LR) sequencing is an increasingly cost-effective technology for probing various RNA features. Numerous tools have been developed to tackle transcriptomic tasks (e.g. isoform and gene fusion detection). However, the lack of abundant gold-standard datasets hinders benchmarking such tools. Therefore, simulation LR important practical alternative. While existing simulators aim imitate machine noise target specific library protocols, they some preparation steps PCR) are difficult modify new changing techniques single-cell LRs).

Language: Английский

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SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark

Genome biology, Journal Year: 2023, Volume and Issue: 24(1)

Published: Dec. 11, 2023

Long-read RNA sequencing has emerged as a powerful tool for transcript discovery, even in well-annotated organisms. However, assessing the accuracy of different methods identifying annotated and novel transcripts remains challenge. Here, we present SQANTI-SIM, versatile that wraps around popular long-read simulators to allow precise management novelty based on structural categories defined by SQANTI3. By selectively excluding specific from reference dataset, SQANTI-SIM effectively emulates scenarios involving unannotated transcripts. Furthermore, provides customizable features supports simulation additional types data, representing first multi-omics lrRNA-seq field.

Language: Английский

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Transcriptome Responses to Different Salinity Conditions in Litoditis marina, Revealed by Long-Read Sequencing

Genes, Journal Year: 2024, Volume and Issue: 15(3), P. 317 - 317

Published: Feb. 28, 2024

The marine nematode Litoditis marina is widely distributed in intertidal zones around the globe, yet mechanisms underlying its broad adaptation to salinity remain elusive. In this study, we applied ONT long-read sequencing technology unravel transcriptome responses different conditions L. marina. Through under 3‰, 30‰ and 60‰ environments, obtained 131.78 G clean data 26,647 non-redundant transcripts, including 6464 novel transcripts. DEGs from current lrRNA-seq were highly correlated with those identified our previously reported Illumina short-read RNA data. When compared 3‰ condition, found that GO terms such as oxidoreductase activity, cation transmembrane transport ion shared between Similarly, extracellular space, structural constituents of cuticle, substrate-specific channel transporter activity salinity. addition, 79 genes significantly increased, while 119 decreased, increased. Furthermore, through enrichment analysis 214 containing DAS, salinity, cellular component assembly coenzyme biosynthetic process enriched. Additionally, observed also enriched Moreover, 86, 125, 81 contained DAS DEGs, comparisons 30‰, respectively. demonstrated landscape alternative polyadenylation This report provides several insights for further study by which euryhalinity formed evolved, it might contribute investigation dynamics induced global climate change.

Language: Английский

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