Evidence map›Paper›PMID 41174462›Full record

ArticleBMC genomics2025

Genome-wide identification and analysis of miR396 family members and their target GRF genes in rubber tree (Hevea brasiliensis).

Mingming Liu, Shenghe Zhao, Jiameng Wang, Zhihua Tu, Jinhui Chen

Abstract read
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Genome-Wide Identification and Expression Analysis of theInternational journal of molecular sciences · 2026
    Article
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mingming LiuSchool of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), School of Tropical Agriculture and Forestry, Hainan University, Sanya, 572019, China.
Shenghe ZhaoSchool of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), School of Tropical Agriculture and Forestry, Hainan University, Sanya, 572019, China.
Jiameng WangSchool of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), School of Tropical Agriculture and Forestry, Hainan University, Sanya, 572019, China.
Zhihua TuSchool of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), School of Tropical Agriculture and Forestry, Hainan University, Sanya, 572019, China.
Jinhui ChenSchool of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), School of Tropical Agriculture and Forestry, Hainan University, Sanya, 572019, China. jinhuichen@hainanu.edu.cn.

Funding

National Natural Science Foundation of China 31960321
6 · The paper itself

Abstract

backgroundMicroRNAs (miRNAs) are key regulators of gene expression as they play crucial roles at the post-transcriptional level. In particular, the miR319-GRF module is an important gene regulatory network in plants, extensively involved in processes such as plant growth and development. Although miR396 is one of the most conserved miRNA families, its role in rubber trees remains poorly understood. In this study, bioinformatics analysis, including target prediction, was performed to reveal the evolutionary and expression patterns of the Hbr-miR396 family members.

resultsA total of six Hbr-miR396 members were identified, distributed across four chromosomes. Secondary structure analysis revealed that the precursor sequences of the six Hbr-miR396 members could form a typical stem-loop (hairpin) structure. Sequence analysis show that the members of the Hbr-miR396 family form three mature sequences. Furthermore, phylogenetic analysis demonstrated that the Hbr-miR396 family members are closely related to those from cassava. Eight members of the growth regulatory factor (GRF) family were predicted as potential targets of Hbr-miR396. The dual-luciferase assays also confirmed that Hbr-miR396b strongly inhibited the expression of HbrGRF3. Expression analysis of the HbrGRF targets in different tissues revealed that HbrGRFs are mainly expressed in the cambium and flowers. Therefore, Hbr-miR396 may potentially regulate growth and floral organ development in rubber trees by targeting HbrGRFs.

conclusionsThe data presented in this study offer valuable insights into the functional and molecular regulatory mechanisms of the miR396-GRFs module in rubber tree growth and development, laying a foundation for further investigation into its biological roles in enhancing both rubber production and timber quality.

Indexed as

HeveaMicroRNAsPlant ProteinsEvolution, MolecularGene Expression Regulation, PlantGenome, PlantMultigene FamilyPhylogenyMicroRNAsPlant ProteinsHbrGRFsmiR396 familyPhylogenetic evolutionRubber tree

Identifiers

PMID41174462
PMCPMC12577359

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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.