Evidence map›Paper›PMID 38167203›Full record

ArticleBMC research notes2024

Identification of transcriptional networks controlling leaf sheath growth in Sorghum bicolor.

Samuel De Riseis, Frank G Harmon

Open access · goldAbstract read
In one paragraph

Article in BMC research notes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 100% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Samuel De RiseisPlant Gene Expression Center, USDA-ARS, Albany, 94710, USA.
Frank G HarmonPlant Gene Expression Center, USDA-ARS, Albany, 94710, USA. frank.harmon@usda.gov.
Plant Gene Expression Center · US

Funding

Agricultural Research Service 2030-21000-049-00D
6 · The paper itself

Abstract

objectivesThe objective of this data set was to identify transcriptional networks that control elongation of seedling leaf sheaths in the C4 grass Sorghum bicolor. One motivation was that leaf sheaths are a primary constituent of stems in grass seedlings; therefore, genes that control growth of this organ are important contributors to successful transition from the seedling stage to the mature plant stage and, ultimately, crop success. Since diurnal rhythms contribute to regulation of signaling networks responsible for growth, a time course representing the late afternoon and early evening was anticipated to pinpoint important control genes for stem growth. Ultimately, the expected outcome was discovery of transcript networks that integrate internal and external signals to fine tune leaf sheath growth and, consequently, plant height. DATA DESCRIPTION: The data set is RNAseq profiling of upper leaf sheaths collected from wild type Sorghum bicolor (BTx623 line) plants at four-hour intervals from 12.5 h after dawn to 20 h after dawn. Global transcript levels in leaves were determined by deep sequencing of mRNA from four individual seedlings at each time point. This data set contains sequences representing the spectrum of mRNAs from individual genes. This data set enables detection of significant changes in gene-level expression caused by the progression of the day from late afternoon to the middle of the night. This data set is useful to identify gene expression networks regulating growth in the leaf sheath, an organ that is a major contributor to the sorghum seedling stem and defines seedling height.

Indexed as

SorghumGene Regulatory NetworksPlant LeavesPoaceaeSeedlingsFASTQ fileIllumina sequencingLeaf sheathRNAseqSeedling stemSorghum bicolor

Identifiers

PMID38167203
PMCPMC10759570
OpenAlexW4390508315

What OpenQuestion holds

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LicenceCC BY
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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.