Evidence map›Paper›PMID 36562829›Full record

ArticleFunctional & integrative genomics2022

Comprehensive, integrative genomic analysis of microRNA expression profiles in different tissues of two wheat cultivars with different traits.

Cristina Gómez-Martín, Hui Zhou, José Maria Medina, Ernesto Aparicio-Puerta, Michael Hackenberg, Bujun Shi

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Article in Functional & integrative genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

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1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Cristina Gómez-Martín *Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Hui Zhou *School of Agriculture, Food and Wine, University of Adelaide, Urrbrae, SA, 5064, Australia.
José Maria MedinaComputational Genomics and Bioinformatics Group, Genetics Department, University of Granada, 18071, Granada, Spain.
Ernesto Aparicio-PuertaComputational Genomics and Bioinformatics Group, Genetics Department, University of Granada, 18071, Granada, Spain.
Michael HackenbergComputational Genomics and Bioinformatics Group, Genetics Department, University of Granada, 18071, Granada, Spain. hackenberg@go.ugr.es.
Bujun ShiSchool of Agriculture, Food and Wine, University of Adelaide, Urrbrae, SA, 5064, Australia. bujun.shi@adelaide.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wheat is one of the most important food sources on Earth. MicroRNAs (miRNA) play important roles in wheat productivity. To identify wheat miRNAs, we constructed and sequenced sRNA libraries from leaves and roots of two wheat cultivars (RAC875 and Kukri) with many different traits. Given that available miRNA wheat complement in the plant-specific database PmiREN ( https://pmiren.com ) does not include root tissues and root-associated miRNAs might thus be missing, we performed first the prediction of novel miRNAs using the sRNAbench tool. We found a total of 150 putatively novel miRNA genes with expression of both arms from 289 unique mature sequences and nearly 30% of all miRNA reads in roots corresponded to novel miRNAs. In contrast, this figure in leaves dropped to under 3%, confirming the undersampling of roots in the complement of known miRNAs. By using 120 publicly available wheat datasets, 598 Zea mays small RNA libraries, 64 plant species genomes, wheat degradome library, and functional enrichment analysis, a subset of novel miRNAs were confirmed as bona-fide miRNAs. Of the total 605 miRNAs identified in this study inclusive of 316 known miRNAs, 528 miRNAs were shared by both cultivars, 429 miRNAs were shared by both root tissues and 329 miRNAs were shared by both leaf tissues. In addition, 32 miRNAs were specific to Kukri while 45 miRNAs were specific to RAC875. These miRNAs had diverse functions, such as regulation of gene transcription, protein translation, energy metabolism, and cell cycle progression. Our data provide a genome-wide miRNA expression profile in these two wheat cultivars and help functional studies of wheat genomics.

Indexed as

MicroRNAsTriticumBase SequenceGene Expression ProfilingGene Expression Regulation, PlantGenome, PlantGenomicsRNA, PlantMicroRNAsRNA, PlantCleavage productsGenome conservationmiRNA functionNovel miRNAsTissue-specificWheat

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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.