Distinct 5′ and 3′ Coverage Biases Shape Transcriptome Interpretation in Nanopore Direct RNA versus PCR-cDNA Sequencing
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PROVIDER: PRJNA1309722 | ENA |
REPOSITORIES: ENA
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Project description:Long-read RNA sequencing enables isoform-resolved transcriptomics, but library preparation introduces systematic biases that shape biological interpretation. We benchmarked Oxford Nanopore’s two protocols—PCR-cDNA and direct RNA—using SKMM2 myeloma cells stimulated with interleukin-6 (IL-6) and ERCC synthetic spike-ins. Direct RNA produced longer, higher-quality reads and more high-confidence isoforms, but showed pronounced 5′ coverage loss. PCR-cDNA yielded shorter fragments with 3′ underrepresentation, detecting more low-abundance transcripts at reduced confidence. Protocol-specific biases had major consequences: differential expression analysis revealed limited overlap in IL-6–responsive genes, and pathway enrichment was broader in direct RNA. At the isoform level, differential transcript usage was almost entirely protocol-specific, with case studies (e.g. RPL22L1, GRB2, RNF220) illustrating concordance and divergence. ERCC controls confirmed these biases as technical rather than biological. Together, our results show that while both methods provide accurate gene-level quantification, transcript-level conclusions depend critically on protocol choice, highlighting the need for careful selection in long-read transcriptomics.
2025-08-27 | GSE306225 | GEO
Project description:Background RNA sequencing (RNA-seq) is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value. Results Here we present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of > 1000 in vitro transcribed (IVT) RNAs from a full-length human cDNA library and sequenced them with poly-A and total RNA-seq, the most common protocols. Because each cDNA is full length and we show IVT is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find ~50% of transcripts have > 2-fold and ~10% have > 10-fold differences in within-transcript sequence coverage. Strikingly, we also find > 6% of transcripts have regions of high, unpredictable sequencing coverage, where the same transcript varies dramatically in coverage between samples, confounding accurate determination of their expression. To get at causal factors, we used a combination of experimental and computational approaches to show that rRNA depletion is responsible for the most significant variability in coverage and that several sequence determinants also strongly influence representation. Conclusions In sum, these results show the utility of IVT-seq in promoting better understanding of bias introduced by RNA-seq and suggest caution in its interpretation. Furthermore, we find that rRNA-depletion is responsible for substantial, unappreciated biases in coverage. Perhaps most importantly, these coverage biases introduced during library preparation suggest exon level expression analysis may be inadvisable. 5 rRNA-depleted samples with duplicates, 1 polyA selected, 1 total RNA, and 1 plasmid library all without replicates.
2014-05-21 | E-GEOD-50445 | biostudies-arrayexpress
Project description:The chromatin interaction assays, particularly Hi-C, enabled detailed studies of chromatin architecture in multiple organisms and model systems, resulting in a deeper understanding of gene expression regulation mediated by epigenetics mechanisms. However, the analysis and interpretation of Hi-C data remain challenging due to technical biases, limiting direct comparisons of datasets obtained in different experiments and laboratories. As a result, removing biases from Hi-C-generated chromatin contact matrices is a critical data analysis step. Our novel approach HiConfidence eliminates biases from the Hi-C data by weighing chromatin contacts according to their consistency between replicates so that low-quality replicates do not influence the result. The algorithm is effective for the analysis of global changes in chromatin structures such as compartments and TADs. We apply the HiConfidence approach to several Hi-C datasets with significant technical biases that could not be analyzed effectively using existing methods, and obtain meaningful biological conclusions. In particular, HiConfidence aids in the study of how changes in the histone acetylation pattern affect chromatin organization in Drosophila cells.
2023-02-05 | GSE200078 | GEO
Project description:Long-read nanopore PCR-cDNA sequencing of pea stipules
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2024-11-10 | GSE281264 | GEO
Project description:Background: RNA-seq is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value. Results: We present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of over 1,000 in vitro transcribed RNAs from a full-length human cDNA library and sequenced them with polyA and total RNA-seq, the most common protocols. Because each cDNA is full length, and we show in vitro transcription is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find 50% of transcripts have more than two-fold and 10% have more than 10-fold differences in within-transcript sequence coverage. We also find greater than 6% of transcripts have regions of dramatically unpredictable sequencing coverage between samples, confounding accurate determination of their expression. We use a combination of experimental and computational approaches to show rRNA depletion is responsible for the most significant variability in coverage, and several sequence determinants also strongly influence representation. Conclusions: These results show the utility of IVT-seq for promoting better understanding of bias introduced by RNA-seq. We find rRNA depletion is responsible for substantial, unappreciated biases in coverage introduced during library preparation. These biases suggest exon-level expression analysis may be inadvisable, and we recommend caution when interpreting RNA-seq results.
2014-05-21 | GSE50445 | GEO
Project description:cDNA microarrays have become the technology of choice for profiling the expression of thousands of genes simultaneously in a single sample. However, cross-hybridization between targets and probes that do not correspond must be considered carefully during the design, analysis, and interpretation of these experiments. Here, we examined this potentially confounding issue by competitively hybridizing fragments with similar sequence obtained from two paralogous genes to a custom cDNA microarray that contains probes for only one of these two genes. We found that although a large contiguous portion of these two fragments was 84% identical and only one target was represented on the array, there was very little cross-hybridization of the non-represented target to either the paralogous probes or other (non-similar) features. We conclude that cDNA microarrays are indeed very specific and that promiscuous paralog hybridization adds little noise to the data. More generally, the absence of specific probes for any given gene does not increase the chance for cross-hybridization between non-specific probes and targets, even if sequence similarity is relatively high.
2009-07-03 | GSE16939 | GEO
Project description:Nanopore PCR-free direct cDNA sequencing of human kidney tissue
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Project description:blueberry transcriptome cDNA sequencing
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