ArticleBMC genomics2020
Genome-wide small RNA profiling reveals tiller development in tall fescue (Festuca arundinacea Schreb).
Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- A haplotype-resolved genome assembly of hexaploid Kentucky-31 tall fescue (Lolium arundinaceum).G3 (Bethesda, Md.) · 2026Article
- MicroRNA Omics Analysis ofBiomolecules · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundTall fescue (Festuca arundinacea Schreb.) is a major cool-season forage and turfgrass species. The low tiller density and size dramatically limits its turf performance and forage yield. MicroRNAs (miRNA)-genes modules play critical roles in tiller development in plants. In this study, a genome-wide small RNA profiling was carried out in two tall fescue genotypes contrasting for tillering production ('Ch-3', high tiller production rate and 'Ch-5', low tiller production rate) and two types of tissue samples at different tillering development stage (Pre-tillering, grass before tillering; Tillering, grass after tillering). 'Ch-3', 'Ch-5', Pre-tillering, and Tillering samples were analyzed using high-throughput RNA sequencing.
resultsA total of 222 million high-quality clean reads were generated and 208 miRNAs were discovered, including 148 known miRNAs belonging to 70 families and 60 novel ones. Furthermore, 18 miRNAs were involved in tall fescue tiller development process. Among them, 14 miRNAs displayed increased abundance in both Ch-3 and Tillering plants compared with that in Ch-5 and Pre-tillering plants and were positive with tillering, while another four miRNAs were negative with tiller development. Out of the three miRNAs osa-miR156a, zma-miR528a-3p and osa-miR444b.2, the rest of 15 miRNAs were newfound and associated with tiller development in plants. Based on our previous full-length transcriptome analysis in tall fescue, 28,927 potential target genes were discovered for all identified miRNAs. Most of the 212 target genes of the 18 miRNAs were dominantly enriched into "ubiquitin-mediated proteolysis", "phagosome", "fatty acid biosynthesis", "oxidative phosphorylation", and "biosynthesis of unsaturated fatty acids" KEGG pathways. In addition, bdi-miR167e-3p targets two kinase proteins EIF2AK4 and IRAK4, and osa-miR397a targets auxin response factor 5, which may be the significant miRNA-genes controllers in tillering development.
conclusionsThis is the first genome-wide miRNA profiles analysis to identify regulators involved in tiller development in cool-season turfgrass. Tillering related 18 miRNAs and their 212 target genes provide novel information for the understanding of the molecular mechanisms of miRNA-genes mediated tiller development in cool-season turfgrass.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.