Evidence map›Paper›PMID 42638015›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Standardized Workflow for Long Noncoding RNA Prediction and Expression Profiling in Wheat Under Stem Rust Stress.

S Jyothsna, Manickavelu Alagu

Abstract read
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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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.

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.

S JyothsnaDepartment of Genomic Science, Central University of Kerala, Tejaswini Hills, Periya, Kasaragod, Kerala, India.
Manickavelu AlaguDepartment of Genomic Science, Central University of Kerala, Tejaswini Hills, Periya, Kasaragod, Kerala, India. amanicks@cukerala.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long noncoding RNAs (lncRNAs), typically over 200 nucleotides in length, with low or no coding capacity, possess significant regulatory roles in plant growth, development, and stress responses by interacting with DNAs, proteins, and other RNAs. This chapter outlines a comprehensive protocol for identifying and functionally characterizing wheat lncRNAs under stem rust infection. The workflow includes plant growth, pathogen inoculation, RNA isolation, and whole-transcriptome sequencing of wheat. In-silico approaches for data preprocessing, transcriptome assembly and subsequent characterization, and differential expression analysis of candidate lncRNAs are described. The chapter systematically explains the functional analyses performed to detect the lncRNAs as microRNA precursors and targets using sequence homology search and target prediction tools, detect transcription factor binding sites and SSR marker motifs within the lncRNAs through motif scanning and microsatellite detection tools, and assess the lncRNA-mRNA interactions using interaction prediction analyses. qRT-PCR validation of selected lncRNAs supporting in-silico findings is also mentioned. In contrast to conventional methods for studying plant-pathogen interactions that largely focus on protein-coding genes, the approach outlined, in this chapter, presents a comprehensive pipeline for identification and functional interpretation of novel regulatory lncRNAs, making it applicable for exploring ncRNA-mediated regulations in rust-infected wheat and related pathosystems.

Indexed as

Gene Expression ProfilingPlant DiseasesRNA, Long NoncodingStress, PhysiologicalTriticumComputational BiologyGene Expression Regulation, PlantMicroRNAsPucciniaRNA, PlantTranscriptomeWorkflowMicroRNAsRNA, Long NoncodingRNA, PlantDatabasesFunctional annotationLong noncoding RNAmiRNAPredictionStem rustToolsTranscriptomeWheat

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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.