Deciphering the RNA landscape by RNAome sequencing

Cesar Ernesto Payan Gomez, Kasper W J Derks, Branislav Misovic , Mirjam CGN van den Hout , Christel EM Kockx , Rutger WW Brouwer , Harry Vrieling , Jan HJ Hoejimakers , Wilfred FJ van IJcken , Joris Pothof

Resultado de la investigación: Contribución a RevistaArtículo

14 Citas (Scopus)

Resumen

Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from rRNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods.
Idioma originalEnglish (US)
Páginas (desde-hasta)30-42
Número de páginas12
PublicaciónRNA Biology
Volumen12
N.º1
DOI
EstadoPublished - 2015

Huella dactilar

RNA
MicroRNAs
RNA Sequence Analysis
Cisplatin
Antisense RNA
Messenger RNA
Protein Isoforms
Gene Expression

Citar esto

Payan Gomez, C. E., Derks, K. W. J., Misovic , B., CGN van den Hout , M., Kockx , C. EM., Brouwer , R. WW., ... Pothof , J. (2015). Deciphering the RNA landscape by RNAome sequencing. RNA Biology, 12(1), 30-42. https://doi.org/10.1080/15476286.2015.1017202
Payan Gomez, Cesar Ernesto ; Derks, Kasper W J ; Misovic , Branislav ; CGN van den Hout , Mirjam ; Kockx , Christel EM ; Brouwer , Rutger WW ; Vrieling , Harry ; Hoejimakers , Jan HJ ; van IJcken , Wilfred FJ ; Pothof , Joris . / Deciphering the RNA landscape by RNAome sequencing. En: RNA Biology. 2015 ; Vol. 12, N.º 1. pp. 30-42.
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title = "Deciphering the RNA landscape by RNAome sequencing",
abstract = "Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from rRNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods.",
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Payan Gomez, CE, Derks, KWJ, Misovic , B, CGN van den Hout , M, Kockx , CEM, Brouwer , RWW, Vrieling , H, Hoejimakers , JHJ, van IJcken , WFJ & Pothof , J 2015, 'Deciphering the RNA landscape by RNAome sequencing', RNA Biology, vol. 12, n.º 1, pp. 30-42. https://doi.org/10.1080/15476286.2015.1017202

Deciphering the RNA landscape by RNAome sequencing. / Payan Gomez, Cesar Ernesto; Derks, Kasper W J; Misovic , Branislav ; CGN van den Hout , Mirjam ; Kockx , Christel EM; Brouwer , Rutger WW; Vrieling , Harry; Hoejimakers , Jan HJ ; van IJcken , Wilfred FJ ; Pothof , Joris .

En: RNA Biology, Vol. 12, N.º 1, 2015, p. 30-42.

Resultado de la investigación: Contribución a RevistaArtículo

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T1 - Deciphering the RNA landscape by RNAome sequencing

AU - Payan Gomez, Cesar Ernesto

AU - Derks, Kasper W J

AU - Misovic , Branislav

AU - CGN van den Hout , Mirjam

AU - Kockx , Christel EM

AU - Brouwer , Rutger WW

AU - Vrieling , Harry

AU - Hoejimakers , Jan HJ

AU - van IJcken , Wilfred FJ

AU - Pothof , Joris

PY - 2015

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N2 - Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from rRNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods.

AB - Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from rRNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods.

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SP - 30

EP - 42

JO - RNA Biology

JF - RNA Biology

SN - 1547-6286

IS - 1

ER -

Payan Gomez CE, Derks KWJ, Misovic B, CGN van den Hout M, Kockx CEM, Brouwer RWW y otros. Deciphering the RNA landscape by RNAome sequencing. RNA Biology. 2015;12(1):30-42. https://doi.org/10.1080/15476286.2015.1017202