Evidence map›Paper›PMID 39080556›Full record

ArticleBMC genomics2024

siqRNA-seq is a spike-in-independent technique for quantitative mapping of mRNA landscape.

Zhenzhen Wang, Kehan Tao, Jiaojiao Ji, Changbin Sun, Wei Xu

Abstract read
In one paragraph

Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. mStem cell research & therapy · 2026
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhenzhen Wang *Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Kehan Tao *Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Jiaojiao JiShenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Changbin Sun *Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China. sunchangbin@caas.cn.
Wei XuShenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China. xuwei01@caas.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRNA sequencing (RNA-seq) is widely used for gene expression profiling and quantification. Quantitative RNA sequencing usually requires cell counting and spike-in, which is not always applicable to many samples. Here, we present a novel quantitative RNA sequencing method independent of spike-ins or cell counting, named siqRNA-seq, which can be used to quantitatively profile gene expression by utilizing gDNA as an internal control. Single-stranded library preparation used in siqRNA-seq profiles gDNA and cDNA with equal efficiency.

resultsTo quantify mRNA expression levels, siqRNA-seq constructs libraries for total nucleic acid to establish a model for expression quantification. Compared to Relative Quantification RNA-seq, siqRNA-seq is technically reliable and reproducible for expression profiling but also can sequence reads from gDNA which can be used as an internal reference for accurate expression quantification. Applying siqRNA-seq to investigate the effects of actinomycin D on gene expression in HEK293T cells, we show the advantages of siqRNA-seq in accurately identifying differentially expressed genes between samples with distinct global mRNA levels. Furthermore, we analyzed factors influencing the downward trend of gene expression regulated by ActD using siqRNA-seq and found that mRNA with m

conclusionsCollectively, siqRNA-seq is a spike-in independent quantitative RNA sequencing method, which creatively uses gDNA as an internal reference to absolutely quantify gene expression. We consider that siqRNA-seq provides a convenient and versatile method to quantitatively profile the mRNA landscape in various samples.

Indexed as

RNA, MessengerSequence Analysis, RNAGene Expression ProfilingHEK293 CellsHigh-Throughput Nucleotide SequencingHumansRNA, MessengerGene expressionNext-generation sequencingQuantificationRNA sequencingTranscriptome

Identifiers

PMID39080556
PMCPMC11290086

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.