Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories

Hoen, Peter A C ‘t; Friedländer, Marc R.; Almlöf, Jonas Carlsson; Sammeth, Michael; Pulyakhina, Irina; Anvar, Seyed Yahya; Laros, Jeroen F. J.; Buermans, Henk P.J.; Karlberg, Olof; Brännvall, Mathias; Dunnen, Johan T. den; Ommen, Gert‐Jan B. van; Gut, Ivo; Guigó, Roderic; Estivill, Xavier; Syvänen, Ann‐Christine; Dermitzakis, Emmanouil T.; Lappalainen, Tuuli

doi:10.1038/nbt.2702

Cited by 260 publications

(221 citation statements)

References 43 publications

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“…: E-GEUV-1); these data were shared by the Geuvadis RNA sequencing project based on the samples of the 1000 Genomes project [30,31]. These gene expression profiles were generated by RNA sequencing experiments.…”

Section: Gene Expression Datamentioning

confidence: 99%

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Interethnic DNA Methylation Difference and Its Implications in Pharmacoepigenetics

Chu

Yang

2017

Epigenomics

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Aim: This is the first systematic study to examine the population differentiation effect of DNA methylation on the treatment response and drug absorption, distribution, metabolism and excretion in multiple tissue types and cancer types. Materials & methods: We analyzed the whole methylome and transcriptome data of primary tumor tissues of four cancer types (breast, colon, head & neck and uterine corpus) and lymphoblastoid cell lines for African and European ancestry populations. Results: Ethnicity-associated CpG sites exhibited similar methylation patterns in the two studied populations, but the patterns differed between tumor tissues and lymphoblastoid cell lines. Ethnicity-associated CpG sites may have triggered gene expression, influenced drug absorption, distribution, metabolism and excretion, and showed tumorspecific patterns of methylation and gene regulation. Conclusion: Ethnicity should be carefully accounted for in future pharmacoepigenetics research.

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Section: Gene Expression Datamentioning

confidence: 99%

“…Finally, 53,934 genes were included in each expression profile. The details of data processing and quality control are described in a previous study [31].…”

Section: Gene Expression Datamentioning

confidence: 99%

Interethnic DNA Methylation Difference and Its Implications in Pharmacoepigenetics

Chu

Yang

2017

Epigenomics

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“…EBV-B cell lines for which RNA-sequence data (.bam files) are available in the GEUVADIS project (18,19) were selected for SNP genotype (þ/þ, þ/À, and À/À) from the 1000 GP (20). For each SNP (rs760462 and rs9945924), two representative individuals per genotype were selected, and bigwig files containing RNAsequence coverage and mapping and split coordinates of individual sequence reads in the region of interest for these EBV-B cell lines were uploaded to the UCSC genome browser (23).…”

Section: Rna-sequence Analysismentioning

confidence: 99%

“…RNA-sequence data were analyzed as online available in the GEUVADIS project (18,19) for 462 EBV-B cell lines for which corresponding whole genome sequences are available in the 1000 GP. On the basis of SNP genotypes, EBV-B cell lines were selected from individuals who were homozygous positive (A/A; þ/þ), heterozygous (A/G; þ/À), or homozygous negative (G/G; À/À) for associating SNP rs760462.…”

Section: Isolation Of T-cell Clones For Hla-bmentioning

confidence: 99%

“…In this study, we explored whether RNA-sequence data as available in the GEUVADIS project (18,19) can be used to identify MiHAs encoded by alternative transcripts. With the rapid advances in sequence technology, the GEUVADIS consortium set out to combine whole genome and transcriptome data and sequenced all mRNA expressed in 462 EBV-B cell lines from the 1000 Genomes Project (1000 GP; ref.…”

Section: Introductionmentioning

confidence: 99%

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Integrated Whole Genome and Transcriptome Analysis Identified a Therapeutic Minor Histocompatibility Antigen in a Splice Variant of ITGB2

Pont

Lee

Meijden

et al. 2016

Clinical Cancer Research

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Purpose: In HLA-matched allogeneic hematopoietic stem cell transplantation (alloSCT), donor T cells recognizing minor histocompatibility antigens (MiHAs) can mediate desired antitumor immunity as well as undesired side effects. MiHAs with hematopoiesis-restricted expression are relevant targets to augment antitumor immunity after alloSCT without side effects. To identify therapeutic MiHAs, we analyzed the in vivo immune response in a patient with strong antitumor immunity after alloSCT. Experimental Design: T-cell clones recognizing patient, but not donor, hematopoietic cells were selected for MiHA discovery by whole genome association scanning. RNA-sequence data from the GEUVADIS project were analyzed to investigate alternative transcripts, and expression patterns were determined by microarray analysis and qPCR. T-cell reactivity was measured by cytokine release and cytotoxicity. Results: T-cell clones were isolated for two HLA-B*15:01–restricted MiHA. LB-GLE1-1V is encoded by a nonsynonymous SNP in exon 6 of GLE1. For the other MiHAs, an associating SNP in intron 3 of ITGB2 was found, but no SNP disparity was present in the normal gene transcript between patient and donor. RNA-sequence analysis identified an alternative ITGB2 transcript containing part of intron 3. qPCR demonstrated that this transcript is restricted to hematopoietic cells and SNP-positive individuals. In silico translation revealed LB-ITGB2-1 as HLA-B*15:01–binding peptide, which was validated as hematopoietic MiHA by T-cell experiments. Conclusions: Whole genome and transcriptome analysis identified LB-ITGB2-1 as MiHAs encoded by an alternative transcript. Our data support the therapeutic relevance of LB-ITGB2-1 and illustrate the value of RNA-sequence analysis for discovery of immune targets encoded by alternative transcripts. Clin Cancer Res; 22(16); 4185–96. ©2016 AACR.

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RNA‐Seq Library Construction Methods for Transcriptome Analysis

Bivens

Zhou

2016

CP Plant Biology

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Next‐generation sequencing (NGS) technologies have revolutionized the study of genomics with an ever‐expanding list of applications. RNA‐Seq has emerged as a powerful method, applying transcriptome analysis to a wider range of organisms—most significantly, non‐model organisms lacking prior genomic sequencing. Whereas an initial concern of NGS datasets was the potential limitation of short read lengths, short read sequences have been successfully employed in creation of de novo transcriptome assemblies that allow for subsequent mapping of reads for expression analysis. Prior genomic sequence knowledge is no longer a requirement for identification of functional transcriptional elements and for global gene expression characterization. Significant cost reductions in generating RNA‐Seq data, and improvements in de novo assemblers, has allowed the analysis of transcriptomes in heretofore unsequenced plant species. These protocols describe standard methods for constructing RNA‐Seq libraries to be sequenced on Illumina sequencing platforms for comprehensive transcriptome analysis. © 2016 by John Wiley & Sons, Inc.

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Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories

Cited by 260 publications

References 43 publications

Interethnic DNA Methylation Difference and Its Implications in Pharmacoepigenetics

Interethnic DNA Methylation Difference and Its Implications in Pharmacoepigenetics

Integrated Whole Genome and Transcriptome Analysis Identified a Therapeutic Minor Histocompatibility Antigen in a Splice Variant of ITGB2

RNA‐Seq Library Construction Methods for Transcriptome Analysis

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