Evidence map›Paper›PMID 26870317›Full record

ArticleF1000Research2015

YeATS - a tool suite for analyzing RNA-seq derived transcriptome identifies a highly transcribed putative extensin in heartwood/sapwood transition zone in black walnut.

Sandeep Chakraborty, Monica Britton, Jill Wegrzyn, Timothy Butterfield, Pedro José Martínez-García, Russell L Reagan, Basuthkar J Rao, Charles A Leslie, Mallikarjuna Aradhaya, David Neale and 2 more

Open access · goldAbstract read
In one paragraph

Article in F1000Research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

7 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
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  3. Genome-Wide Profiling and Phylogenetic Analysis of theInternational journal of molecular sciences · 2020
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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

12 authors at 4 institutions in 2 countries.

Sandeep ChakrabortyPlant Sciences Department, University of California, Davis, CA, 95616, USA.
Monica BrittonUC Davis Genome Center Bioinformatics Core Facility, University of California, Davis, CA, 95616, USA.
Jill WegrzynDepartment of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, 06269, USA.
Timothy ButterfieldPlant Sciences Department, University of California, Davis, CA, 95616, USA.
Pedro José Martínez-GarcíaPlant Sciences Department, University of California, Davis, CA, 95616, USA.
Russell L ReaganPlant Sciences Department, University of California, Davis, CA, 95616, USA.
Basuthkar J RaoDepartment of Biological Sciences, Tata Institute of Fundamental Research, Homi Bhaba Road, Mumbai, 400, India.
Charles A LesliePlant Sciences Department, University of California, Davis, CA, 95616, USA.
Mallikarjuna AradhayaPlant Sciences Department, University of California, Davis, CA, 95616, USA.
David NealePlant Sciences Department, University of California, Davis, CA, 95616, USA.
Keith WoesteUSDA Forest Service Hardwood Tree Improvement and Regeneration Center, Purdue University, West Lafayette, IN, 47907, USA.
Abhaya M DandekarPlant Sciences Department, University of California, Davis, CA, 95616, USA.
University of California, Davis · USPurdue University West Lafayette · USTata Institute of Fundamental Research · INUniversity of Connecticut · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The transcriptome provides a functional footprint of the genome by enumerating the molecular components of cells and tissues. The field of transcript discovery has been revolutionized through high-throughput mRNA sequencing (RNA-seq). Here, we present a methodology that replicates and improves existing methodologies, and implements a workflow for error estimation and correction followed by genome annotation and transcript abundance estimation for RNA-seq derived transcriptome sequences (YeATS - Yet Another Tool Suite for analyzing RNA-seq derived transcriptome). A unique feature of YeATS is the upfront determination of the errors in the sequencing or transcript assembly process by analyzing open reading frames of transcripts. YeATS identifies transcripts that have not been merged, result in broken open reading frames or contain long repeats as erroneous transcripts. We present the YeATS workflow using a representative sample of the transcriptome from the tissue at the heartwood/sapwood transition zone in black walnut. A novel feature of the transcriptome that emerged from our analysis was the identification of a highly abundant transcript that had no known homologous genes (GenBank accession: KT023102). The amino acid composition of the longest open reading frame of this gene classifies this as a putative extensin. Also, we corroborated the transcriptional abundance of proline-rich proteins, dehydrins, senescence-associated proteins, and the DNAJ family of chaperone proteins. Thus, YeATS presents a workflow for analyzing RNA-seq data with several innovative features that differentiate it from existing software.

Indexed as

black walnutComputational genomicsdehydrinsextensinheartwood/sapwood transition zoneJuglans nigraopen reading frameproline-rich proteinsRNA-seqsenescence-associated proteinstranscriptome

Identifiers

PMID26870317
PMCPMC4732554
OpenAlexW2143685375

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.