Evidence map›Paper›PMID 33354967›Full record

ArticleChemical research in toxicology2021

Impact of Sequencing Depth and Library Preparation on Toxicological Interpretation of RNA-Seq Data in a "Three-Sample" Scenario.

Dongying Li, Binsheng Gong, Joshua Xu, Baitang Ning, Weida Tong

Open access · greenAbstract read
In one paragraph

Article in Chemical research in toxicology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
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

6 citing papers in PubMed, 17 citations in OpenAlex.

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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 at 1 institution in 1 country.

Dongying LiDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, Arkansas 72079, United States.ORCID 0000-0003-0721-2500
Binsheng GongDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, Arkansas 72079, United States.ORCID 0000-0002-8724-5435
Joshua XuDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, Arkansas 72079, United States.
Baitang NingDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, Arkansas 72079, United States.
Weida TongDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, Arkansas 72079, United States.ORCID 0000-0002-4093-3708
National Center for Toxicological Research · US

Funding

Intramural FDA HHS FD999999
6 · The paper itself

Abstract

While RNA-sequencing (RNA-seq) has emerged as a standard approach in toxicogenomics, its full potential in gaining underlying toxicological mechanisms is still not clear when only three biological replicates are used. This "three-sample" study design is common in toxicological research, particularly in animal studies during preclinical drug development. Sequencing depth (the total number of reads in an experiment) and library preparation are critical to the resolution and integrity of RNA-seq data and biological interpretation. We used aflatoxin b1 (AFB1), a model toxicant, to investigate the effect of sequencing depth and library preparation in RNA-seq on toxicological interpretation in the "three-sample" scenario. We also compared different gene profiling platforms (RNA-seq, TempO-seq, microarray, and qPCR) using identical liver samples. Well-established mechanisms of AFB1 toxicity served as ground truth for our comparative analyses. We found that a minimum of 20 million reads was sufficient to elicit key toxicity functions and pathways underlying AFB1-induced liver toxicity using three replicates and that identification of differentially expressed genes was positively associated with sequencing depth to a certain extent. Further, our results showed that RNA-seq revealed toxicological insights from pathway enrichment with overall higher statistical power and overlap ratio, compared with TempO-seq and microarray. Moreover, library preparation using the same methods was important to reproducing the toxicological interpretation.

Indexed as

Gene LibraryRNA-SeqAflatoxin B1AnimalsChemical and Drug Induced Liver InjuryDatabases, GeneticGene Expression ProfilingHumansAflatoxin B1

Identifiers

PMID33354967
PMCPMC7887111
OpenAlexW3113577179

What OpenQuestion holds

Textmetadata
LicenceTDM
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.