Evidence map›Paper›PMID 19646272›Full record

ArticleBMC genomics2009

Comparison of next generation sequencing technologies for transcriptome characterization.

P Kerr Wall, Jim Leebens-Mack, André S Chanderbali, Abdelali Barakat, Erik Wolcott, Haiying Liang, Lena Landherr, Lynn P Tomsho, Yi Hu, John E Carlson and 6 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers.

0numbers the graph read from it
0cells of the map it votes in
92citing papers in PubMed
13.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

92 citing papers in PubMed, 225 citations in OpenAlex.

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  9. Comparative De Novo Transcriptome Assembly ofCalifornian journal of health promotion · 2018
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  11. Microbial Ecology: Where are we now?Postdoc journal : a journal of postdoctoral research and postdoctoral affairs · 2016
    Article
  12. RNA-seq analysis ofPlant diversity · 2016
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32 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 5 institutions in 1 country.

P Kerr WallDepartment of Biology, Institute of Molecular Evolutionary Genetics, and The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA. pkerrwall@psu.edu
Jim Leebens-Mack
André S Chanderbali
Abdelali Barakat
Erik Wolcott
Haiying Liang
Lena Landherr
Lynn P Tomsho
Yi Hu
John E Carlson
Hong Ma
Stephan C Schuster
Douglas E Soltis
Pamela S Soltis
Naomi Altman
Claude W dePamphilis
Pennsylvania State University · USUniversity of Florida · USCenter for Disease Dynamics, Economics & Policy · USFlorida Museum of Natural History · USUniversity of Georgia · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe have developed a simulation approach to help determine the optimal mixture of sequencing methods for most complete and cost effective transcriptome sequencing. We compared simulation results for traditional capillary sequencing with "Next Generation" (NG) ultra high-throughput technologies. The simulation model was parameterized using mappings of 130,000 cDNA sequence reads to the Arabidopsis genome (NCBI Accession SRA008180.19). We also generated 454-GS20 sequences and de novo assemblies for the basal eudicot California poppy (Eschscholzia californica) and the magnoliid avocado (Persea americana) using a variety of methods for cDNA synthesis.

resultsThe Arabidopsis reads tagged more than 15,000 genes, including new splice variants and extended UTR regions. Of the total 134,791 reads (13.8 MB), 119,518 (88.7%) mapped exactly to known exons, while 1,117 (0.8%) mapped to introns, 11,524 (8.6%) spanned annotated intron/exon boundaries, and 3,066 (2.3%) extended beyond the end of annotated UTRs. Sequence-based inference of relative gene expression levels correlated significantly with microarray data. As expected, NG sequencing of normalized libraries tagged more genes than non-normalized libraries, although non-normalized libraries yielded more full-length cDNA sequences. The Arabidopsis data were used to simulate additional rounds of NG and traditional EST sequencing, and various combinations of each. Our simulations suggest a combination of FLX and Solexa sequencing for optimal transcriptome coverage at modest cost. We have also developed ESTcalc http://fgp.huck.psu.edu/NG_Sims/ngsim.pl, an online webtool, which allows users to explore the results of this study by specifying individualized costs and sequencing characteristics.

conclusionNG sequencing technologies are a highly flexible set of platforms that can be scaled to suit different project goals. In terms of sequence coverage alone, the NG sequencing is a dramatic advance over capillary-based sequencing, but NG sequencing also presents significant challenges in assembly and sequence accuracy due to short read lengths, method-specific sequencing errors, and the absence of physical clones. These problems may be overcome by hybrid sequencing strategies using a mixture of sequencing methodologies, by new assemblers, and by sequencing more deeply. Sequencing and microarray outcomes from multiple experiments suggest that our simulator will be useful for guiding NG transcriptome sequencing projects in a wide range of organisms.

Indexed as

ArabidopsisComputer SimulationDNA, ComplementaryEschscholziaGene Expression ProfilingGene LibraryGenome, PlantModels, GeneticPerseaRNA, PlantSequence Analysis, DNADNA, ComplementaryRNA, Plant

Identifiers

PMID19646272
PMCPMC2907694
OpenAlexW1992550017

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.