QuantSeq 3′ mRNA sequencing for RNA quantification

Moll, Pamela Renate; Ante, Michael; Seitz, Alexander; Reda, Torsten

doi:10.1038/nmeth.f.376

Cited by 240 publications

(218 citation statements)

References 3 publications

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“…Since we targeted the 3 0 untranslated region containing only a few splice junctions, the analysis workflow was straight-forward by mapping to the modified papaya reference sequences with extended ends. We achieved 47.0% of mapping reads which is lower than that of obtained in technical note (Moll et al 2014) perhaps due to limitations in the draft papaya genome annotation (Ming et al 2008) compared to other model organisms.…”

Section: Pecentage To Reference (%)mentioning

confidence: 61%

“…0 mRNA sequencing Total RNA samples (500 ng) were cleaned using DNAse I kit according to the Rapid out removal DNA kit instruction (Thermoscientific) and converted into cDNA by using QuantSeq 3 0 mRNA-seq reverse (REV) Library Prep Kit (Lexogen) according to manufacturer's instruction (Moll et al 2014) to generate compatible library for Illumina sequencing. Briefly, library generation was initiated by oligodT priming for first strand cDNA which generated one fragment per transcript.…”

Section: Library Construction and Quantseqmentioning

confidence: 99%

“…We applied QuantSeq 3 0 mRNA sequencing approach using Illumina sequencing technology. The approach generated one fragment per transcript at the 3 0 end with high strand specificity ([99.9%), allowing more precise and unambiguous gene expression quantification at much lower read number requirement compared to conventional mRNA-seq (Moll et al 2014). Since we targeted the 3 0 untranslated region containing only a few splice junctions, the analysis workflow was straight-forward by mapping to the modified papaya reference sequences with extended ends.…”

Section: Pecentage To Reference (%)mentioning

confidence: 99%

“…This reflects the high sensitivity of 3 0 mRNA sequencing approach in detecting rare transcripts compared with the conventional RNA-seq approaches, which produce multiple fragments from a single transcript (Moll et al 2014). Therefore, it is estimated that only around 41% of annotated genes (CPM [ 5) were functionally active in 4-weekold papaya embryogenic calli.…”

Section: Pecentage To Reference (%)mentioning

confidence: 99%

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Genome-wide transcriptome profiling of Carica papaya L. embryogenic callus

Jamaluddin

Noor

Goh

2017

Physiol Mol Biol Plants

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Genome-wide transcriptome profiling is a powerful tool to study global gene expression patterns in plant development. We report the first transcriptome profile analysis of papaya embryogenic callus to improve our understanding on genes associated with somatic embryogenesis. By using 3 0 mRNA-sequencing, we generated 6,190,687 processed reads and 47.0% were aligned to papaya genome reference, in which 21,170 (75.4%) of 27,082 annotated genes were found to be expressed but only 41% was expressed at functionally high levels. The top 10% of genes with high transcript abundance were significantly enriched in biological processes related to cell proliferation, stress response, and metabolism. Genes functioning in somatic embryogenesis such as SERK and LEA, hormone-related genes, stress-related genes, and genes involved in secondary metabolite biosynthesis pathways were highly expressed. Transcription factors such as NAC, WRKY, MYB, WUSCHEL, Agamous-like MADS-box protein and bHLH important in somatic embryos of other plants species were found to be expressed in papaya embryogenic callus. Abundant expression of enolase and ADH is consistent with proteome study of papaya somatic embryo. Our study highlights that some genes related to secondary metabolite biosynthesis, especially phenylpropanoid biosynthesis, were highly expressed in papaya embryogenic callus, which might have implication for cell factory applications. The discovery of all genes expressed in papaya embryogenic callus provides an important information into early biological processes during the induction of embryogenesis and useful for future research in other plant species.

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Section: Pecentage To Reference (%)mentioning

confidence: 61%

Section: Library Construction and Quantseqmentioning

confidence: 99%

Section: Pecentage To Reference (%)mentioning

confidence: 99%

Section: Pecentage To Reference (%)mentioning

confidence: 99%

See 2 more Smart Citations

Genome-wide transcriptome profiling of Carica papaya L. embryogenic callus

Jamaluddin

Noor

Goh

2017

Physiol Mol Biol Plants

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“…This transcriptomic dataset was generated by QuantSeq 3′ mRNA sequencing [3]. A total of twelve raw sequence data were deposited into NCBI SRA database and can be accessed with the accession number SRP076440 (http://www.ncbi.nlm.nih.gov/sra/SRP076440).…”

Section: Datamentioning

confidence: 99%

Transcriptomic data of Arabidopsis thaliana hypocotyl upon suppression of expansin genes

et al. 2017

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Expansin is a cell wall loosening protein without hydrolytic activity, which allows cell expansion by influencing cell wall extensibility. Previous studies showed that the suppression of expansin genes (EXPA1, EXPA3, EXPA5 and EXPA10) resulted in defective organ growth and altered cell wall chemical composition [1,2]. However, the molecular mechanism on how the suppression of non-enzymatic expansin expression can result in widespread effects on plant cell wall and organ growth is still unclear. In this study, we performed transcriptomic analysis on the hypocotyls of previously reported transgenic Arabidopsis line [1] to investigate the effects of expansin gene suppression on the global gene expression pattern, particularly on the cell wall related genes.

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Hyaluronic acids mediate the infiltration, migration, andM2polarization of macrophages: evaluating metabolic molecular phenotypes in gliomas

Zhang

Dai

et al. 2022

Molecular Oncology

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Gliomas cause high mortality around the world. The metabolic pattern of the tumor was previously suggested to be associated with the patient's survival outcome and immune activity. Yet, this relationship in glioma remains unknown. This study systematically evaluated the immune landscape in different phenotypes classified by metabolic‐related pathways of 3068 glioma samples and 33 glioblastoma single‐cell sequencing samples. Machine learning prediction analysis of microarray with R (pamr) was used for validating clustering results. A total of 5842 pan‐cancer samples were used for external validation of the metabolic clusters. Cell Counting Kit‐8 (CCK8) assay, cell clone assay, EdU assay, wound healing assay, Transwell assay, and co‐culture assay were performed to verify the distinction in molecular characteristics among metabolic clusters. Metabolomics and RNA sequencing were performed on HS683 and U251 cells to annotate potential hyaluronic acid (HA)‐mediated pathways. Three distinct metabolic phenotypes were identified. Metabolic cluster 1 correlated with a high number of immune infiltrating cells and poor survival of glioma patients. Metabolic clusters were proved with different levels of the macrophage markers CD68 and CD163 by multiplex immunofluorescence staining. Glioma cells from other metabolic clusters also expressed various levels of HA. HA was further found to mediate glioma proliferation, progression, and invasion. Moreover, HA potentially promoted macrophage recruitment and M2 polarization through the IL‐1/CHI3L1 and TGF‐b/CHI3L1 axes. HA also regulated the expression of PD‐L1. This work revealed the significant connection between metabolic patterns, especially HA, and tumor immune infiltration in gliomas.

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QuantSeq 3′ mRNA sequencing for RNA quantification

Cited by 240 publications

References 3 publications

Genome-wide transcriptome profiling of Carica papaya L. embryogenic callus

Genome-wide transcriptome profiling of Carica papaya L. embryogenic callus

Transcriptomic data of Arabidopsis thaliana hypocotyl upon suppression of expansin genes

Hyaluronic acids mediate the infiltration, migration, andM2polarization of macrophages: evaluating metabolic molecular phenotypes in gliomas

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