Evidence map›Paper›PMID 35666179›Full record

ArticleThe Plant cell2022

Identification and functional annotation of long intergenic non-coding RNAs in Brassicaceae.

Kyle Palos, Anna C Nelson Dittrich, Li'ang Yu, Jordan R Brock, Caylyn E Railey, Hsin-Yen Larry Wu, Ewelina Sokolowska, Aleksandra Skirycz, Polly Yingshan Hsu, Brian D Gregory and 3 more

Open access · hybridAbstract read
In one paragraph

Article in The Plant cell, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
9.2field-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

28 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
  2. Article
  3. Long non-coding RNAs link DNA methylation to immune regulatory networks in bovine subclinical mastitis.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Non-coding RNA · 2024
    Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Analysis of lncRNAs inNon-coding RNA · 2023
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 5 institutions in 2 countries.

Kyle PalosThe Boyce Thompson Institute, Cornell University, Ithaca, New York, USA.ORCID 0000-0001-7788-5888
Anna C Nelson DittrichThe Boyce Thompson Institute, Cornell University, Ithaca, New York, USA.ORCID 0000-0002-1968-0670
Li'ang YuThe Boyce Thompson Institute, Cornell University, Ithaca, New York, USA.ORCID 0000-0002-9556-011X
Jordan R BrockDepartment of Horticulture, Michigan State University, East Lansing, Michigan, USA.ORCID 0000-0001-6231-1435
Caylyn E RaileyThe Boyce Thompson Institute, Cornell University, Ithaca, New York, USA.ORCID 0000-0002-9242-9976
Hsin-Yen Larry WuDepartment of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, USA.ORCID 0000-0001-9407-338X
Ewelina SokolowskaMax Planck Institute for Molecular Plant Physiology, Potsdam, Germany.ORCID 0000-0002-6493-5281
Aleksandra SkiryczThe Boyce Thompson Institute, Cornell University, Ithaca, New York, USA.ORCID 0000-0002-7627-7925
Polly Yingshan HsuDepartment of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, USA.ORCID 0000-0001-7071-5798
Brian D GregoryDepartment of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID 0000-0001-7532-0138
Eric LyonsThe School of Plant Sciences, University of Arizona, Tucson, Arizona, USA.ORCID 0000-0002-3348-8845
Mark A BeilsteinThe School of Plant Sciences, University of Arizona, Tucson, Arizona, USA.ORCID 0000-0002-3392-1389
Andrew D L NelsonThe Boyce Thompson Institute, Cornell University, Ithaca, New York, USA.ORCID 0000-0001-9896-1739
Cornell University · USMichigan State University · USUniversity of Arizona · USMax Planck Institute of Molecular Plant Physiology · DEUniversity of Pennsylvania · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long intergenic noncoding RNAs (lincRNAs) are a large yet enigmatic class of eukaryotic transcripts that can have critical biological functions. The wealth of RNA-sequencing (RNA-seq) data available for plants provides the opportunity to implement a harmonized identification and annotation effort for lincRNAs that enables cross-species functional and genomic comparisons as well as prioritization of functional candidates. In this study, we processed >24 Tera base pairs of RNA-seq data from >16,000 experiments to identify ∼130,000 lincRNAs in four Brassicaceae: Arabidopsis thaliana, Camelina sativa, Brassica rapa, and Eutrema salsugineum. We used nanopore RNA-seq, transcriptome-wide structural information, peptide data, and epigenomic data to characterize these lincRNAs and identify conserved motifs. We then used comparative genomic and transcriptomic approaches to highlight lincRNAs in our data set with sequence or transcriptional conservation. Finally, we used guilt-by-association analyses to assign putative functions to lincRNAs within our data set. We tested this approach on a subset of lincRNAs associated with germination and seed development, observing germination defects for Arabidopsis lines harboring T-DNA insertions at these loci. LincRNAs with Brassicaceae-conserved putative miRNA binding motifs, small open reading frames, or abiotic-stress modulated expression are a few of the annotations that will guide functional analyses into this cryptic portion of the transcriptome.

Indexed as

ArabidopsisBrassicaceaeRNA, Long NoncodingGenomicsSequence Analysis, RNATranscriptomeRNA, Long Noncoding

Identifiers

PMID35666179
PMCPMC9421480
OpenAlexW4281622627

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.