Dataset Information

Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling.

ABSTRACT:

Motivation

Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not. With the compilation of large-scale RNA-Seq datasets with technical replicate samples, however, we can now, for the first time, perform a systematic analysis of the precision of expression level estimates from massively parallel sequencing technology. This then allows considerations for its improvement by computational or experimental means.

Results

We report on a comprehensive study of target identification and measurement precision, including their dependence on transcript expression levels, read depth and other parameters. In particular, an impressive recall of 84% of the estimated true transcript population could be achieved with 331 million 50 bp reads, with diminishing returns from longer read lengths and even less gains from increased sequencing depths. Most of the measurement power (75%) is spent on only 7% of the known transcriptome, however, making less strongly expressed transcripts harder to measure. Consequently, <30% of all transcripts could be quantified reliably with a relative error<20%. Based on established tools, we then introduce a new approach for mapping and analysing sequencing reads that yields substantially improved performance in gene expression profiling, increasing the number of transcripts that can reliably be quantified to over 40%. Extrapolations to higher sequencing depths highlight the need for efficient complementary steps. In discussion we outline possible experimental and computational strategies for further improvements in quantification precision.

Contact

rnaseq10@boku.ac.at

SUBMITTER: Labaj PP

PROVIDER: S-EPMC3117338 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Publications

Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling.

Łabaj Paweł P PP Leparc Germán G GG Linggi Bryan E BE Markillie Lye Meng LM Wiley H Steven HS Kreil David P DP

Bioinformatics (Oxford, England) 20110701 13

<h4>Motivation</h4>Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not. With the compilation of large-scale RNA-Seq datasets with technical replicate samples, however, we can now, for the first time, perform a systematic analysis of the precision of expression level estimates from massively parallel sequencing technology. T ...[more]

PMID: 21685096

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Project description:BackgroundWood formation affects the chemical and physical properties of wood, and thus affects its utility as a building material or a feedstock for biofuels, pulp and paper. To obtain genome-wide insights on the transcriptome changes and regulatory networks in wood formation, we used high-throughput RNA sequencing to characterize cDNA libraries of mature xylem from tension wood (TW), opposite wood (OW), and normal wood (NW), in the industrial tree species Populus tomentosa.ResultsOur sequencing generated 140,978,316 (TW), 128,972,228 (OW), and 117,672,362 (NW) reads, corresponding to 10,127 (TW), 10,129 (OW), and 10,129 (NW) unique genes. Of these, 361 genes were differentially transcribed between TW and OW (log2FC ≥ 1 or ≤ -1, FDR < 0.05), 2,658 differed between OW and NW, and 2,417 differed between TW and NW. This indicates that NW differs significantly from the wood in branches; GO term analysis also indicated that OW experienced more transcriptome remodeling. The differentially expressed genes included 97 encoding transcription factors (TFs), 40 involved in hormone signal transduction, 33 in lignin biosynthesis, 21 in flavonoid biosynthesis, and 43 in cell wall metabolism, including cellulose synthase, sucrose synthase, and COBRA. More than half of the differentially expressed TF showed more than 4-fold lower transcript levels in NW compared with TW or OW, indicating that TF abundances differed dramatically in different wood types and may have important roles in the formation of reaction wood. In addition, transcripts of most of the genes involved in lignin biosynthesis were more abundant in OW compared with TW, consistent with the higher lignin content of OW. We constructed two transcriptomic networks for the regulation of lignin and cellulose biosynthesis, including TFs, based on the co-expression patterns of different genes. Lastly, we used reverse transcription quantitative PCR to validate the differentially expressed genes identified.ConclusionsHere, we identified the global patterns and differences in gene expression among TW, OW, and NW, and constructed two transcriptomic regulatory networks involved in TW formation in P. tomentosa. We also identified candidate genes for molecular breeding of wood quality, and provided a starting point to decipher the molecular mechanisms of wood formation in Populus.

Dataset Information

Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling.

Motivation

Results

Contact

Publications

Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling.

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