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Synthetic spike-in standards for RNA-seq experiments.

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Synthetic spike-in standards for RNA-seq experiments.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Jiang, Lichun Schlesinger, Felix Davis, Carrie A. Zhang, Yu Li, Renhua Salit, Marc Gingeras, Thomas R. Oliver, Brian
Description	Country affiliation: United States Author Affiliation: Jiang L ( Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA.)
Abstract	High-throughput sequencing of cDNA (RNA-seq) is a widely deployed transcriptome profiling and annotation technique, but questions about the performance of different protocols and platforms remain. We used a newly developed pool of 96 synthetic RNAs with various lengths, and GC content covering a 2(20) concentration range as spike-in controls to measure sensitivity, accuracy, and biases in RNA-seq experiments as well as to derive standard curves for quantifying the abundance of transcripts. We observed linearity between read density and RNA input over the entire detection range and excellent agreement between replicates, but we observed significantly larger imprecision than expected under pure Poisson sampling errors. We use the control RNAs to directly measure reproducible protocol-dependent biases due to GC content and transcript length as well as stereotypic heterogeneity in coverage across transcripts correlated with position relative to RNA termini and priming sequence bias. These effects lead to biased quantification for short transcripts and individual exons, which is a serious problem for measurements of isoform abundances, but that can partially be corrected using appropriate models of bias. By using the control RNAs, we derive limits for the discovery and detection of rare transcripts in RNA-seq experiments. By using data collected as part of the model organism and human Encyclopedia of DNA Elements projects (ENCODE and modENCODE), we demonstrate that external RNA controls are a useful resource for evaluating sensitivity and accuracy of RNA-seq experiments for transcriptome discovery and quantification. These quality metrics facilitate comparable analysis across different samples, protocols, and platforms.
File Format	HTM / HTML
ISSN	10889051
e-ISSN	15495469
DOI	10.1101/gr.121095.111
Journal	Genome Research
Issue Number	9
Volume Number	21
Language	English
Publisher	Cold Spring Harbor Laboratory Press
Publisher Date	2011-09-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Discipline Genetics Discipline Genomics Chemistry Sequence Analysis, Rna Animals Bias (epidemiology) Gene Expression Profiling Gene Library High-throughput Nucleotide Sequencing Reproducibility Of Results Sensitivity And Specificity Research Support, N.i.h., Extramural Research Support, N.i.h., Intramural
Content Type	Text
Resource Type	Article
Subject	Genetics Genetics (clinical)

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Barcoding bias in high-throughput multiplex sequencing of miRNA.

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INTEGRATE: gene fusion discovery using whole genome and transcriptome data

Comparison of CAGE and RNA-seq transcriptome profiling using clonally amplified and single-molecule next-generation sequencing.

Synthetic spike-in standards for RNA-seq experiments.

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