5’XP sRNA-seq: Efficient Identification of Transcripts With and Without 5’ Phosphorylation Reveals Evolutionary Conserved Small RNA

Kugelberg, Unn; Nätt, Daniel; Skog, Signe; Kutter, Claudia; Öst, Anita

doi:10.1101/2020.08.21.261412

Cited by 3 publications

(5 citation statements)

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“…For the Peak and Peak rRNA fragments we have previously observed similar fragments in human sperm (8), and similar fragments located to the 5' ends of the 5.8S and 28S subunits in fruit fly embryos (44). This is also true for the 3' fragments of the 28S subunit (Peak 4), even though we never have observed such expression levels as we see in the HeLa cells.…”

Section: Seqpac Example 2: Novel Rrna-derived Srna Affected By Anticasupporting

confidence: 82%

“…Blasting this sequence showed that it was identical to the complete 2S rRNA subunit. This was expected since Kang et al did not to report of any method that depletes 2S rRNA prior to library construction, which is commonly done in fruit fly experiments (43, 44). The human proportion of the dataset was instead enriched with miRNA with the expected size of 22 nt (Figure 4B).…”

Section: Results and Descriptionmentioning

confidence: 99%

“…This map object along with the original PAC object can then be fed to the PAC_covplot function to generate coverage plots across the fasta reference, as exemplified in Figure 8. As we have illustrated before, such coverage plots are well suited for characterizing tRNA and rRNA fragmentation (8,44,48), as well as mitochondrial RNA (48).…”

Section: Results and Descriptionmentioning

confidence: 99%

“…We and others have consistently shown that these two popular kits perform differently with regard to sRNA coverage (48,63–65). Thus, future studies targeting this rRF must consider the choice of chemistry, and maybe even apply advanced protocols for better coverage (44, 66).…”

Section: Discussionmentioning

confidence: 99%

“…. As we have illustrated before, such coverage plots are well suited for characterizing tRNA and rRNA fragmentation(8,44,48), as well as mitochondrial RNA(48).Lastly, using the map object the map_rangetype function can generate more advanced classifications such as 5', i' and 3' tRFs or tRNA halves, previously best demonstrated in MINTbase and MINTmap(11). Nonetheless, the MINTmap/MINTbase suite is only readily available for human tRNA classification.Seqpac's PAC_mapper and map_rangetype functions fills this gap and expands the possibility for discovering novel tRNA fragment classes in any species.…”

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confidence: 99%

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Seqpac: A New Framework for small RNA analysis in R using Sequence-Based Counts

Skog

Örkenby

Kugelberg

et al. 2021

Preprint

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Small RNA sequencing (sRNA-seq) has become important for studying regulatory mechanisms in many cellular processes. Data analysis remains challenging, mainly because each class of sRNA--such as miRNA, piRNA, tRNA- and rRNA- derived fragments (tRFs/rRFs)--needs special considerations. Analysis therefore involves complex workflows across multiple programming languages, which can produce research bottlenecks and transparency issues. To make analysis of sRNA more accessible and transparent we present seqpac: a tool for advanced group-based analysis of sRNA completely integrated in R. This opens advanced sRNA analysis for Windows users--from adaptor trimming to visualization. Seqpac provides a framework of functions for analyzing a PAC object, which contains 3 standardized tables: sample phenotypic information (P), sequence annotations (A), and a counts table with unique sequences across the experiment (C). By applying a sequence-based counting strategy that maintains the integrity of the fastq sequence, seqpac increases flexibility and transparency compared to other workflows. It also contains an innovative targeting system allowing sequence counts to be summarized and visualized across sample groups and sequence classifications. Reanalyzing published data, we show that seqpac's fastq trimming performs equal to standard software outside R and demonstrate how sequence-based counting detects previously unreported bias. Applying seqpac to new experimental data, we discovered a novel rRF that was down-regulated by RNA pol I inhibition (anticancer treatment), and up-regulated in previously published data from tumor positive patients. Seqpac is available on github (https://github.com/Danis102/seqpac), runs on multiple platforms (Windows/Linux/Mac), and is provided with a step-by-step vignette on how to analyze sRNA-seq data.

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Section: Seqpac Example 2: Novel Rrna-derived Srna Affected By Anticasupporting

confidence: 82%

Section: Results and Descriptionmentioning

confidence: 99%

Section: Results and Descriptionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Seqpac: A New Framework for small RNA analysis in R using Sequence-Based Counts

Skog

Örkenby

Kugelberg

et al. 2021

Preprint

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Analysis at single-cell resolution identifies a stable mammalian tRNA-mRNA interface and increased translation efficiency in neurons

Gao

Kutter

2021

Preprint

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The correlation between codon and anticodon pools influences the efficiency of translation, but whether differences exist in these pools across individual cells is unknown. We determined that codon usage and amino acid demand are highly stable across different cell types using single-cell RNA-sequencing atlases of adult mouse and fetal human. After demonstrating the robustness of ATAC-sequencing for analysis of tRNA gene usage, we quantified anticodon usage and amino acid supply in adult mouse and fetal human single-cell ATAC-seq atlases. We found that tRNA gene usage is overall coordinated across cell types, except in neurons which clustered separately from other cell types. Integration of these datasets revealed a strong and statistically significant correlation between amino acid supply and demand across almost all cell types. Neurons have an enhanced translation efficiency over other cell types, driven by an increased supply of Ala-AGC anticodons. This results in faster decoding of the Ala-GCC codon, as determined by cell-type specific ribosome profiling, and a reduction of Ala-AGC anticodon pools may be implicated in neurological pathologies. This study, the first such examination of codon usage, anticodon usage, and translation efficiency at single-cell resolution, identifies conserved features of translation elongation across mammalian cellular diversity and evolution.

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Small RNA-Sequencing: Approaches and Considerations for miRNA Analysis

2021

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MicroRNAs (miRNAs) are a class of small RNA molecules that have an important regulatory role in multiple physiological and pathological processes. Their disease-specific profiles and presence in biofluids are properties that enable miRNAs to be employed as non-invasive biomarkers. In the past decades, several methods have been developed for miRNA analysis, including small RNA sequencing (RNA-seq). Small RNA-seq enables genome-wide profiling and analysis of known, as well as novel, miRNA variants. Moreover, its high sensitivity allows for profiling of low input samples such as liquid biopsies, which have now found applications in diagnostics and prognostics. Still, due to technical bias and the limited ability to capture the true miRNA representation, its potential remains unfulfilled. The introduction of many new small RNA-seq approaches that tried to minimize this bias, has led to the existence of the many small RNA-seq protocols seen today. Here, we review all current approaches to cDNA library construction used during the small RNA-seq workflow, with particular focus on their implementation in commercially available protocols. We provide an overview of each protocol and discuss their applicability. We also review recent benchmarking studies comparing each protocol’s performance and summarize the major conclusions that can be gathered from their usage. The result documents variable performance of the protocols and highlights their different applications in miRNA research. Taken together, our review provides a comprehensive overview of all the current small RNA-seq approaches, summarizes their strengths and weaknesses, and provides guidelines for their applications in miRNA research.

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5’XP sRNA-seq: Efficient Identification of Transcripts With and Without 5’ Phosphorylation Reveals Evolutionary Conserved Small RNA

Cited by 3 publications

References 40 publications

Seqpac: A New Framework for small RNA analysis in R using Sequence-Based Counts

Seqpac: A New Framework for small RNA analysis in R using Sequence-Based Counts

Analysis at single-cell resolution identifies a stable mammalian tRNA-mRNA interface and increased translation efficiency in neurons

Small RNA-Sequencing: Approaches and Considerations for miRNA Analysis

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