Evidence map›Paper›PMID 36810020›Full record

ArticleBMC genomics2023

Identification and analysis of miRNAs differentially expressed in male and female Trichosanthes kirilowii maxim.

Xiu-Qin Hu, Han Song, Na Li, Chun-Xiang Hao, Bo Zhang, Xin-Peng Li, Jie Xin, Yong-Qing Zhang

Abstract read
In one paragraph

Article in BMC genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

8 authors.

Xiu-Qin HuMedical College, Linyi University, Lin'yi, 276000, China.
Han SongMedical College, Linyi University, Lin'yi, 276000, China.
Na LiMedical College, Linyi University, Lin'yi, 276000, China.
Chun-Xiang HaoMedical College, Linyi University, Lin'yi, 276000, China.
Bo ZhangMedical College, Linyi University, Lin'yi, 276000, China.
Xin-Peng LiMedical College, Linyi University, Lin'yi, 276000, China.
Jie XinMedical College, Linyi University, Lin'yi, 276000, China. xinjie@lyu.edu.cn.
Yong-Qing ZhangSchool of Pharmacy, Shandong University of Traditional Chinese Medicine, Ji'nan, 250355, China. zyq622003@126.com.

Funding

National Natural Science Foundation No.81803651Shandong Provincial Natural Science Foundation No.ZR2019PH088
6 · The paper itself

Abstract

Trichosanthes kirilowii Maxim. (TK) is a dioecious plant in the Cucurbitaceae family of which different sexes have separate medicinal uses. We used Illumina high-throughput sequencing technology to sequence miRNAs from male and female flower buds of TK. We performed bioinformatics analysis, miRNA identification, and target gene prediction on the data obtained from sequencing, and association analysis was performed in combination with the results of a previous transcriptome sequencing study. As a result, there were 80 differentially expressed miRNAs (DESs) between the female and male plants (48 upregulated and 32 downregulated in female plants). Moreover, 27 novel miRNAs in DESs were predicted to have 282 target genes, and 51 known miRNAs were predicted to have 3418 target genes. By establishing a regulatory network between miRNAs and target genes, 12 core genes were screened, including 7 miRNAs and 5 target genes. Among them, tkmiR157a-5p, tkmiR156c, tkmiR156_2, and tkmiR156k_2 jointly target the regulation of tkSPL18 and tkSPL13B. These two target genes are specifically expressed in male and female plants, respectively, and are involved in the biosynthesis process of BR, which is closely related to the sex differentiation process of TK. The identification of these miRNAs will provide a reference for the analysis of the sex differentiation mechanism of TK.

Indexed as

CucurbitaceaeMicroRNAsTrichosanthesGene Expression Regulation, PlantHigh-Throughput Nucleotide SequencingMicroRNAsmiRNASex differentiationTKTranscriptome and sRNA sequencing

Identifiers

PMID36810020
PMCPMC9945594

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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.