Evidence map›Paper›PMID 27812750›Full record

ArticlePlant cell reports2017

Comparative transcriptome profiling of upland (VS16) and lowland (AP13) ecotypes of switchgrass.

Vasudevan Ayyappan, Malay C Saha, Jyothi Thimmapuram, Venkateswara R Sripathi, Ketaki P Bhide, Elizabeth Fiedler, Rita K Hayford, Venu Kal Kalavacharla

Open access · hybridAbstract readComparative Study
In one paragraph

Article in Plant cell reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.0field-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

8 citing papers in PubMed, 23 citations in OpenAlex.

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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

8 authors at 4 institutions in 1 country.

Vasudevan AyyappanMolecular Genetics and Epigenomics Laboratory, College of Agriculture and Related Sciences, Delaware State University, Dover, DE, USA.
Malay C SahaForage Improvement Division, The Samuel Roberts Noble Foundation, Ardmore, OK, USA.
Jyothi ThimmapuramBioinformatics Core, Purdue University, West Lafayette, IN, USA.
Venkateswara R SripathiPlant Molecular Biology and Bioinformatics Laboratory, College of Agricultural, Life and Natural Sciences, Alabama A&M University, Normal, AL, USA.
Ketaki P BhideBioinformatics Core, Purdue University, West Lafayette, IN, USA.
Elizabeth FiedlerMolecular Genetics and Epigenomics Laboratory, College of Agriculture and Related Sciences, Delaware State University, Dover, DE, USA.
Rita K HayfordMolecular Genetics and Epigenomics Laboratory, College of Agriculture and Related Sciences, Delaware State University, Dover, DE, USA.
Venu Kal KalavacharlaMolecular Genetics and Epigenomics Laboratory, College of Agriculture and Related Sciences, Delaware State University, Dover, DE, USA. vkalavacharla@desu.edu.
Delaware State University · USPurdue University West Lafayette · USAlabama Agricultural and Mechanical University · USNoble Research Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

key messageTranscriptomes of two switchgrass genotypes representing the upland and lowland ecotypes will be key tools in switchgrass genome annotation and biotic and abiotic stress functional genomics. Switchgrass (Panicum virgatum L.) is an important bioenergy feedstock for cellulosic ethanol production. We report genome-wide transcriptome profiling of two contrasting tetraploid switchgrass genotypes, VS16 and AP13, representing the upland and lowland ecotypes, respectively. A total of 268 million Illumina short reads (50 nt) were generated, of which, 133 million were obtained in AP13 and the rest 135 million in VS16. More than 90% of these reads were mapped to the switchgrass reference genome (V1.1). We identified 6619 and 5369 differentially expressed genes in VS16 and AP13, respectively. Gene ontology and KEGG pathway analysis identified key genes that regulate important pathways including C4 photosynthesis, photorespiration and phenylpropanoid metabolism. A series of genes (33) involved in photosynthetic pathway were up-regulated in AP13 but only two genes showed higher expression in VS16. We identified three dicarboxylate transporter homologs that were highly expressed in AP13. Additionally, genes that mediate drought, heat, and salinity tolerance were also identified. Vesicular transport proteins, syntaxin and signal recognition particles were seen to be up-regulated in VS16. Analyses of selected genes involved in biosynthesis of secondary metabolites, plant-pathogen interaction, membrane transporters, heat, drought and salinity stress responses confirmed significant variation in the relative expression reflected in RNA-Seq data between VS16 and AP13 genotypes. The phenylpropanoid pathway genes identified here are potential targets for biofuel conversion.

Indexed as

EcotypeGene Expression ProfilingDown-RegulationGene Expression Regulation, PlantGenes, PlantGenotypePanicumReal-Time Polymerase Chain ReactionReproducibility of ResultsSequence Analysis, RNASignal TransductionStress, PhysiologicalUp-RegulationBioenergyLowlandSwitchgrassTranscriptomeUpland

Identifiers

PMID27812750
PMCPMC5206262
OpenAlexW2547012989

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Registered trials

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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.