Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data

Campbell, Joshua D.; Lv, Gang; Luo, Lingqi; Xiao, Jianru; Gerrein, Joseph; Juan-Guardela, Brenda; Tedrow, John; Alekseyev, Yuriy O.; Yang, Ivana V.; Correll, Mick; Geraci, Mark W.; Quackenbush, John; Sciurba, Frank C.; Schwartz, David; Kaminski, Naftali; Johnson, W. Evan; Monti, Stefano; Spira, Avrum; Beane, Jennifer; Lenburg, Marc E.

doi:10.1261/rna.046060.114

Cited by 33 publications

(27 citation statements)

References 14 publications

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“…The variations observed between two time points in number of reads mapped to miRNAs may have contributed to the inter-experiment variations in the total and miRNAmapped reads, but it did not influence the time-matched comparisons between pIC and control groups at 24 HPS and 72 HPS. However, the lower number of reads mapped to miRNAs in the pIC-treated samples compared to time-matched controls at 72 HPS may have affected the sensitivity of detection of differentially expressed miRNAs at this time point (Campbell et al, 2015). Some significant pIC-responsive miRNAs (e.g.…”

Section: Discussionmentioning

confidence: 99%

Discovery of microRNAs associated with the antiviral immune response of Atlantic cod macrophages

Eslamloo

Inkpen

Rise

et al. 2018

Molecular Immunology

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MicroRNAs (miRNAs) are known to play important immunoregulatory roles in teleosts, although miRNAs involved in the antiviral immune response of Atlantic cod (Gadus morhua) were previously uncharacterised. Using deep sequencing and qPCR, the present study was conducted to identify miRNAs responsive to the viral mimic, polyriboinosinic polyribocytidylic acid (pIC) in Atlantic cod macrophages. Macrophage samples isolated from Atlantic cod (n=3) and treated with pIC or phosphate buffered saline (PBS control) for 24 and 72h were used for miRNA profiling. Following deep sequencing, DESeq2 analyses identified four (miR-731-3p, miR-125b-3-3p, miR-150-3p and miR-462-3p) and two (miR-2188-3p and miR-462-3p) significantly differentially expressed miRNAs at 24 and 72h post-stimulation (HPS), respectively. Sequencing-identified miRNAs were subjected to qPCR validation using a larger number of biological replicates (n=6) exposed to pIC or PBS over time (i.e. 12, 24, 48 and 72 HPS). As in sequencing, miR-731-3p, miR-462-3p and miR-2188-3p showed significant up-regulation by pIC. The sequencing results were not qPCR-validated for miR-125b-3-3p and miR-150-3p as up- and down-regulated miRNAs at 24 HPS, respectively; however, qPCR results showed significant up-regulation in response to pIC stimulation at later time points (i.e. 48 and/or 72 HPS). We also used qPCR to assess the expression of other miRNAs that were previously shown as immune responsive in other vertebrates. qPCR results at 48 and/or 72 HPS revealed that miR-128-3-5p, miR-214-1-5p and miR-451-3p were induced by pIC, whereas miR-30b-3p and miR-199-1-3p expression were repressed in response to pIC. The present study identified ten pIC-stimulated miRNAs, suggesting them as important in antiviral immune responses of Atlantic cod macrophages. Some pIC-responsive miRNAs identified in this study were predicted to target putative immune-related genes of Atlantic cod (e.g. miR-30b-3p targeting herc4), although the regulatory functions of these miRNAs need to be validated by future studies.

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Section: Discussionmentioning

confidence: 99%

Discovery of microRNAs associated with the antiviral immune response of Atlantic cod macrophages

Eslamloo

Inkpen

Rise

et al. 2018

Molecular Immunology

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“…The scale of miRNAs/genes expression in microarray data sets was consistently different due to different platforms and different batches [ 46 ][ 15 ]. All statistical data sets were normalized and standardized to be approximately equal in scale and normally distributed.…”

Section: Methodsmentioning

confidence: 99%

Integrative microRNA and gene profiling data analysis reveals novel biomarkers and mechanisms for lung cancer

Long

et al. 2016

Oncotarget

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BackgroundStudies on the accuracy of microRNAs (miRNAs) in diagnosing non-small cell lung cancer (NSCLC) have still controversial. Therefore, we conduct to systematically identify miRNAs related to NSCLC, and their target genes expression changes using microarray data sets.MethodsWe screened out five miRNAs and six genes microarray data sets that contained miRNAs and genes expression in NSCLC from Gene Expression Omnibus.ResultsOur analysis results indicated that fourteen miRNAs were significantly dysregulated in NSCLC. Five of them were up-regulated (miR-9, miR-708, miR-296-3p, miR-892b, miR-140-5P) while nine were down-regulated (miR-584, miR-218, miR-30b, miR-522, miR486-5P, miR-34c-3p, miR-34b, miR-516b, miR-592). The integrating diagnosis sensitivity (SE) and specificity (SP) were 82.6% and 89.9%, respectively. We also found that 4 target genes (p < 0.05, fold change > 2.0) were significant correlation with the 14 discovered miRNAs, and the classifiers we built from one training set predicted the validation set with higher accuracy (SE = 0.987, SP = 0.824).ConclusionsOur results demonstrate that integrating miRNAs and target genes are valuable for identifying promising biomarkers, and provided a new insight on underlying mechanism of NSCLC. Further, our well-designed validation studies surely warrant the investigation of the role of target genes related to these 14 miRNAs in the prediction and development of NSCLC.

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“…Furthermore, the total number of mapped reads from the three donors across both kits was comparable ( Figure S3B, paired t-test between Truseq and Nextflex for mapped read was not significant with a p-value of 0.15), as was the type of RNA detected by each kit (Fig S3C). Since small RNA sequencing kits are commonly used to study miRNA expression [16], we compared the unique miRNAs mapped by each kit. We found that the Nextflex kit identified about 150 more unique miRNAs compared to the Truseq kit across donors (Figure 4(b), p-value = 0.01).…”

Section: Choice Of Library Preparation Impacts the Mirna Sequences Dementioning

confidence: 99%

Assessment of methods for serum extracellular vesicle small RNA sequencing to support biomarker development

Srinivasan

Duval

Kaimal

et al. 2019

J of Extracellular Vesicle

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Extracellular vesicles (EVs) have great potential as a source for clinically relevant biomarkers since they can be readily isolated from biofluids and carry microRNA (miRNA), mRNA, and proteins that can reflect disease status. However, the biological and technical variability of EV content is unknown making comparisons between healthy subjects and patients difficult to interpret. In this study, we sought to establish a laboratory and bioinformatics analysis pipeline to analyse the small RNA content within EVs from patient serum that could serve as biomarkers and to assess the biological and technical variability of EV RNA content in healthy individuals. We sequenced EV small RNA from multiple individuals (biological replicates) and sequenced multiple replicates per individual (technical replicates) using the Illumina Truseq protocol. We observed that the replicates of samples clustered by subject indicating that the biological variability (~95%) was greater than the technical variability (~0.50%). We observed that ~30% of the sequencing reads were miRNAs. We evaluated the technical parameters of sequencing by spiking the EV RNA preparation with a mix of synthetic small RNA and demonstrated a disconnect between input concentration of the spike-in RNA and sequencing read frequencies indicating that bias was introduced during library preparation. To determine whether there are differences between library preparation platforms, we compared the Truseq with the Nextflex protocol that had been designed to reduce bias in library preparation. While both methods were technically robust, the Nextflex protocol reduced the bias and exhibited a linear range across input concentrations of the synthetic spike-ins. Altogether, our results indicate that technical variability is much smaller than biological variability supporting the use of EV small RNAs as potential biomarkers. Our findings also indicate that the choice of library preparation method leads to artificial differences in the datasets generated invalidating the comparability of sequencing data across library preparation platforms.

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Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data

Cited by 33 publications

References 14 publications

Discovery of microRNAs associated with the antiviral immune response of Atlantic cod macrophages

Discovery of microRNAs associated with the antiviral immune response of Atlantic cod macrophages

Integrative microRNA and gene profiling data analysis reveals novel biomarkers and mechanisms for lung cancer

Assessment of methods for serum extracellular vesicle small RNA sequencing to support biomarker development

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