Trans-NanoSim characterizes and simulates nanopore RNA-sequencing data

Hafezqorani, Saber; Yang, Chen; Lo, Theodora; Nip, Ka Ming; Warren, René L.; Birol, İnanç

doi:10.1093/gigascience/giaa061

Cited by 22 publications

(17 citation statements)

References 19 publications

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“…We conducted a simulation study to evaluate the performance of LIQA and compared it with other state-of-the-art algorithms for isoform expression estimation and DAS detection based on GENCODE v24 annotation. To simulate a realistic dataset with known ground truth, we used NanoSim[34] to generate the ONT RNA-seq data. NanoSim is a fast and scalable read simulator that captures the technology-specific features of ONT data, and allows for adjustment upon improvement of Nanopore sequencing technology.…”

Section: Resultsmentioning

confidence: 99%

LIQA: Long-read Isoform Quantification and Analysis

Chen

et al. 2020

Preprint

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Long-read RNA sequencing (RNA-seq) technologies have made it possible to sequence full-length transcripts, facilitating the exploration of isoform-specific gene expression over conventional short-read RNA-seq. However, long-read RNA-seq suffers from high per-base error rate, presence of chimeric reads and alternative alignments, and other biases, which require different analysis methods than short-read RNA-seq. Here we present LIQA (Long-read Isoform Quantification and Analysis), an Expectation-Maximization based statistical method to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read RNA-seq data. Rather than summarizing isoform-specific read counts directly as done in short-read methods, LIQA incorporates base-pair quality score and isoform-specific read length information to assign different weights across reads, which reflects alignment confidence. Moreover, given isoform usage estimates, LIQA can detect DAS events between conditions. We evaluated LIQA's performance on simulated data and demonstrated that it outperforms other approaches in rare isoform characterization and in detecting DAS events between two groups. We also generated one direct mRNA sequencing dataset and one cDNA sequencing dataset using the Oxford Nanopore long-read platform, both with paired short-read RNA-seq data and qPCR data on selected genes, and we demonstrated that LIQA performs well in isoform discovery and quantification. Finally, we evaluated LIQA on a PacBio dataset on esophageal squamous epithelial cells, and demonstrated that LIQA recovered DAS events on FGFR3 that failed to be detected in short-read data. In summary, LIQA leverages the power of long-read RNA-seq and achieves higher accuracy in estimating isoform abundance than existing approaches, especially for isoforms with low coverage and biased read distribution.

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Section: Resultsmentioning

confidence: 99%

LIQA: Long-read Isoform Quantification and Analysis

Chen

et al. 2020

Preprint

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“…S2C,D). Based on an Illumina data set published by [20], we simulated a comparable scenario employing NanoSim [21] (Fig. S3).…”

Section: Mt-clipping Enables Detection and Analysis Of Cardiac Specific Genesmentioning

confidence: 99%

Improved nanopore direct RNA sequencing of cardiac myocyte samples by selective mt-RNA depletion

Vries

Eschenbach

Dieterich

2022

Journal of Molecular and Cellular Cardiology

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RNA sequencing is a powerful tool to analyze gene expression transcriptome wide. However, RNA sequencing in general and especially the recently developed methods of long read RNA sequencing are still low-throughput and cost-intensive. Here, one important design choice is to concentrate the sequencing capacity on specific parts of the transcriptome. Especially, abundant transcripts as ribosomal RNAs may dominate the available sequencing space, if not removed prior to sequencing. Several methods exist to reduce ribosomal RNA read numbers: either based on enrichment of the relevant fraction (polyA + RNA) or depletion, respectively degradation of ribosomal RNAs. Furthermore, commercial kits are available to deplete globin transcripts from blood samples. However, so far, no solution exists to deal with other tissue-specific highly abundant transcripts. This is especially of interest in the heart and other muscle derived samples, where reads originating from mitochondrial RNAs make up to 30% of reads in polyA + selected libraries and around 70% in single cell sequencing experiments. We present a simple method to diminish sequencing of mitochondrial RNAs in Oxford Nanopore direct RNA sequencing libraries by RNase H based clipping of the polyA tail. We show that mt-clipping enables enhanced detection of cytoplasmic mRNAs, among them genes involved in heart development and pathogenesis. Mt-clipping may be applied as well to other sequencing protocols that are based on oligo(dT) priming and can be easily adapted to other tissue-specific high-abundant transcripts.

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“…This algorithm works with aligned reads and is capable of restoring (i) skipped short exons and (ii) incorrectly detected splice sites (Methods). To evaluate how the designed algorithm affects transcript discovery we simulated Nanopore reads with NanoSim (Hafezqorani et al 2020), since for the real data the ground truth is unknown. Although one could use PacBio reads from the same RT event read pair for verification, the fraction of ONT reads having an RT pair is comparably low and is not suitable for transcript model construction.…”

Section: Splice Site Correction Improves Transcript Discovery Precisionmentioning

confidence: 99%

Sequencing of individual barcoded cDNAs on Pacific Biosciences and Oxford Nanopore reveals platform-specific error patterns

Mikheenko

Prjibelski

Joglekar

et al. 2022

Preprint

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Long-read transcriptomics requires understanding error sources inherent to technologies. Current approaches cannot compare methods for an individual RNA molecule. Here, we present a novel platform comparison method that combined barcoding strategies and long-read sequencing to sequence cDNA copies representing an individual RNA molecule on both Pacific Biosciences and Oxford Nanopore. We compared these long reads pairs in terms of sequence content and splicing structure. Although individual read pairs show high similarity, we found differences in (i) aligned length, (ii) TSS and (iii) polyA-site assignment, and (iv) exon-intron structures. Overall 25% of read pairs disagreed on either TSS, polyA-site, or a splice site. Intron-chain disagreement typically arises from alignment errors of microexons and complicated splice sites. Our single-molecule technology comparison revealed that inconsistencies are often caused by sequencing-error induced inaccurate ONT alignments, especially to downstream GTNNGT donor motifs. However, annotation-disagreeing upstream shifts in NAGNAG acceptors in ONT are often confirmed by PacBio and thus likely real. In both barcoded and non-barcoded ONT reads, we found that intron number and proximity of other GT/AGs better predict inconsistency with the annotation than read quality alone. We summarized these findings in an annotation-based algorithm for spliced alignment correction that improves subsequent transcript construction with ONT reads.

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Trans-NanoSim characterizes and simulates nanopore RNA-sequencing data

Cited by 22 publications

References 19 publications

LIQA: Long-read Isoform Quantification and Analysis

LIQA: Long-read Isoform Quantification and Analysis

Improved nanopore direct RNA sequencing of cardiac myocyte samples by selective mt-RNA depletion

Sequencing of individual barcoded cDNAs on Pacific Biosciences and Oxford Nanopore reveals platform-specific error patterns

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