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Highly sensitive amplicon-based transcript quantification by semiconductor sequencing.

ABSTRACT: BACKGROUND: In clinical and basic research custom panels for transcript profiling are gaining importance because only project specific informative genes are interrogated. This approach reduces costs and complexity of data analysis and allows multiplexing of samples. Polymerase-chain-reaction (PCR) based TaqMan assays have high sensitivity but suffer from a limited dynamic range and sample throughput. Hence, there is a gap for a technology able to measure expression of large gene sets in multiple samples. RESULTS: We have adapted a commercially available mRNA quantification assay (AmpliSeq-RNA) that measures mRNA abundance based on the frequency of PCR amplicons determined by high-throughput semiconductor sequencing. This approach allows for parallel, accurate quantification of about 1000 transcripts in multiple samples covering a dynamic range of five orders of magnitude. Using samples derived from a well-characterized stem cell differentiation model, we obtained a good correlation (r = 0.78) of transcript levels measured by AmpliSeq-RNA and DNA-microarrays. A significant portion of low abundant transcripts escapes detection by microarrays due to limited sensitivity. Standard quantitative RNA sequencing of the same samples confirms expression of low abundant genes with an overall correlation coefficient of r = 0.87. Based on digital AmpliSeq-RNA imaging we show switches of signaling cascades at four time points during differentiation of stem cells into cardiomyocytes. CONCLUSIONS: The AmpliSeq-RNA technology adapted to high-throughput semiconductor sequencing allows robust transcript quantification based on amplicon frequency. Multiplexing of at least 900 parallel PCR reactions is feasible because sequencing-based quantification eliminates artefacts coming from off-target amplification. Using this approach, RNA quantification and detection of genetic variations can be performed in the same experiment.

SUBMITTER: Zhang JD

PROVIDER: S-EPMC4101174 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Highly sensitive amplicon-based transcript quantification by semiconductor sequencing.

Zhang Jitao David JD Schindler Tobias T Küng Erich E Ebeling Martin M Certa Ulrich U

BMC genomics 20140705

<h4>Background</h4>In clinical and basic research custom panels for transcript profiling are gaining importance because only project specific informative genes are interrogated. This approach reduces costs and complexity of data analysis and allows multiplexing of samples. Polymerase-chain-reaction (PCR) based TaqMan assays have high sensitivity but suffer from a limited dynamic range and sample throughput. Hence, there is a gap for a technology able to measure expression of large gene sets in m ...[more]

PMID: 24997760

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Project description:Until recently, the de facto method for short-read-based amplicon reconstruction was a sequence similarity threshold approach (operational taxonomic units [OTUs]). This has changed with the amplicon sequence variant (ASV) method where distributions are fitted to abundance profiles of individual genes using a noise-error model. While OTU-based approaches are still useful for 16S rRNA/18S rRNA genes, where thresholds of 97% to 99% are used, their use for functional genes is still debatable as there is no consensus on clustering thresholds. Here, we compare OTU- and ASV-based reconstruction approaches and taxonomy assignment methods, the naive Bayesian classifier (NBC) and Bayesian lowest common ancestor (BLCA) algorithm, using a functional gene data set from the microbial nitrogen-cycling community in the Brouage mudflat (France). A range of OTU similarity thresholds and ASVs were used to compare amoA (ammonia-oxidizing archaea [AOA] and ammonia-oxidizing bacteria [AOB]), nxrB, nirS, nirK, and nrfA communities between differing sedimentary structures. Significant effects of the sedimentary structure on weighted UniFrac (WUniFrac) distances were observed for AOA amoA when using ASVs, an OTU at a threshold of 97% sequence identity (OTU-97%), and OTU-85%; AOB amoA when using OTU-85%; and nirS when using ASV, OTU-90%, and OTU-85%. For AOB amoA, significant effects of the sedimentary structures on UniFrac distances were observed when using OTU-97% but not ASVs, and the inverse was found for nrfA. Interestingly, conclusions drawn for nirK and nxrB were consistent between amplicon reconstruction methods. We also show that when the sequences in the reference database are related to the environment in question, the BLCA algorithm leads to more phylogenetically relevant classifications. However, when the reference database contains sequences more dissimilar to the ones retrieved, the NBC obtains more information. IMPORTANCE Several analysis pipelines are available to microbial ecologists to process amplicon sequencing data, yet to date, there is no consensus as to the most appropriate method, and it becomes more difficult for genes that encode a specific function (functional genes). Standardized approaches need to be adopted to increase the reliability and reproducibility of environmental amplicon-sequencing-based data sets. In this paper, we argue that the recently developed ASV approach offers a better opportunity to achieve such standardization than OTUs for functional genes. We also propose a comprehensive framework for quality filtering of the sequencing reads based on protein sequence verification.

Dataset Information

Highly sensitive amplicon-based transcript quantification by semiconductor sequencing.

Publications

Highly sensitive amplicon-based transcript quantification by semiconductor sequencing.

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