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

Small RNA sequencing can be used to gain an unprecedented amount of detail into the microRNA transcriptome. The relatively high cost and low throughput of sequencing bases technologies can potentially be offset by the use of multiplexing. However, multiplexing involves a trade-off between increased...

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Autores principales: Campbell, Joshua D., Liu, Gang, Luo, Lingqi, Xiao, Ji, Gerrein, Joseph, Juan-Guardela, Brenda, Tedrow, John, Alekseyev, Yuriy O., Yang, Ivana V., Correll, Mick, Geraci, Mark, Quackenbush, John, Sciurba, Frank, Schwartz, David A., Kaminski, Naftali, Johnson, W. Evan, Monti, Stefano, Spira, Avrum, Beane, Jennifer, Lenburg, Marc E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4338344/
https://www.ncbi.nlm.nih.gov/pubmed/25519487
http://dx.doi.org/10.1261/rna.046060.114
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author Campbell, Joshua D.
Liu, Gang
Luo, Lingqi
Xiao, Ji
Gerrein, Joseph
Juan-Guardela, Brenda
Tedrow, John
Alekseyev, Yuriy O.
Yang, Ivana V.
Correll, Mick
Geraci, Mark
Quackenbush, John
Sciurba, Frank
Schwartz, David A.
Kaminski, Naftali
Johnson, W. Evan
Monti, Stefano
Spira, Avrum
Beane, Jennifer
Lenburg, Marc E.
author_facet Campbell, Joshua D.
Liu, Gang
Luo, Lingqi
Xiao, Ji
Gerrein, Joseph
Juan-Guardela, Brenda
Tedrow, John
Alekseyev, Yuriy O.
Yang, Ivana V.
Correll, Mick
Geraci, Mark
Quackenbush, John
Sciurba, Frank
Schwartz, David A.
Kaminski, Naftali
Johnson, W. Evan
Monti, Stefano
Spira, Avrum
Beane, Jennifer
Lenburg, Marc E.
author_sort Campbell, Joshua D.
collection PubMed
description Small RNA sequencing can be used to gain an unprecedented amount of detail into the microRNA transcriptome. The relatively high cost and low throughput of sequencing bases technologies can potentially be offset by the use of multiplexing. However, multiplexing involves a trade-off between increased number of sequenced samples and reduced number of reads per sample (i.e., lower depth of coverage). To assess the effect of different sequencing depths owing to multiplexing on microRNA differential expression and detection, we sequenced the small RNA of lung tissue samples collected in a clinical setting by multiplexing one, three, six, nine, or 12 samples per lane using the Illumina HiSeq 2000. As expected, the numbers of reads obtained per sample decreased as the number of samples in a multiplex increased. Furthermore, after normalization, replicate samples included in distinct multiplexes were highly correlated (R > 0.97). When detecting differential microRNA expression between groups of samples, microRNAs with average expression >1 reads per million (RPM) had reproducible fold change estimates (signal to noise) independent of the degree of multiplexing. The number of microRNAs detected was strongly correlated with the log(2) number of reads aligning to microRNA loci (R = 0.96). However, most additional microRNAs detected in samples with greater sequencing depth were in the range of expression which had lower fold change reproducibility. These findings elucidate the trade-off between increasing the number of samples in a multiplex with decreasing sequencing depth and will aid in the design of large-scale clinical studies exploring microRNA expression and its role in disease.
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spelling pubmed-43383442016-02-01 Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data Campbell, Joshua D. Liu, Gang Luo, Lingqi Xiao, Ji Gerrein, Joseph Juan-Guardela, Brenda Tedrow, John Alekseyev, Yuriy O. Yang, Ivana V. Correll, Mick Geraci, Mark Quackenbush, John Sciurba, Frank Schwartz, David A. Kaminski, Naftali Johnson, W. Evan Monti, Stefano Spira, Avrum Beane, Jennifer Lenburg, Marc E. RNA Bioinformatics Small RNA sequencing can be used to gain an unprecedented amount of detail into the microRNA transcriptome. The relatively high cost and low throughput of sequencing bases technologies can potentially be offset by the use of multiplexing. However, multiplexing involves a trade-off between increased number of sequenced samples and reduced number of reads per sample (i.e., lower depth of coverage). To assess the effect of different sequencing depths owing to multiplexing on microRNA differential expression and detection, we sequenced the small RNA of lung tissue samples collected in a clinical setting by multiplexing one, three, six, nine, or 12 samples per lane using the Illumina HiSeq 2000. As expected, the numbers of reads obtained per sample decreased as the number of samples in a multiplex increased. Furthermore, after normalization, replicate samples included in distinct multiplexes were highly correlated (R > 0.97). When detecting differential microRNA expression between groups of samples, microRNAs with average expression >1 reads per million (RPM) had reproducible fold change estimates (signal to noise) independent of the degree of multiplexing. The number of microRNAs detected was strongly correlated with the log(2) number of reads aligning to microRNA loci (R = 0.96). However, most additional microRNAs detected in samples with greater sequencing depth were in the range of expression which had lower fold change reproducibility. These findings elucidate the trade-off between increasing the number of samples in a multiplex with decreasing sequencing depth and will aid in the design of large-scale clinical studies exploring microRNA expression and its role in disease. Cold Spring Harbor Laboratory Press 2015-02 /pmc/articles/PMC4338344/ /pubmed/25519487 http://dx.doi.org/10.1261/rna.046060.114 Text en © 2015 Campbell et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed exclusively by the RNA Society for the first 12 months after the full-issue publication date (see http://rnajournal.cshlp.org/site/misc/terms.xhtml). After 12 months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Bioinformatics
Campbell, Joshua D.
Liu, Gang
Luo, Lingqi
Xiao, Ji
Gerrein, Joseph
Juan-Guardela, Brenda
Tedrow, John
Alekseyev, Yuriy O.
Yang, Ivana V.
Correll, Mick
Geraci, Mark
Quackenbush, John
Sciurba, Frank
Schwartz, David A.
Kaminski, Naftali
Johnson, W. Evan
Monti, Stefano
Spira, Avrum
Beane, Jennifer
Lenburg, Marc E.
Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data
title Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data
title_full Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data
title_fullStr Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data
title_full_unstemmed Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data
title_short Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data
title_sort assessment of microrna differential expression and detection in multiplexed small rna sequencing data
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4338344/
https://www.ncbi.nlm.nih.gov/pubmed/25519487
http://dx.doi.org/10.1261/rna.046060.114
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