Evidence map›Paper›PMID 32448205›Full record

ArticleBMC plant biology2020

Transcriptome analyses provide insights into the homeostatic regulation of axillary buds in upland cotton (G. hirsutum L.).

Jianbin Shi, Ning Wang, Hong Zhou, Qinghua Xu, Gentu Yan

Open access · goldAbstract read
In one paragraph

Article in BMC plant biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
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  3. Physiological and Proteomic Analyses ofPlants (Basel, Switzerland) · 2024
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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

5 authors at 2 institutions in 1 country.

Jianbin ShiState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, NO. 38, Huanghe Road, Anyang City, 455000, Henan Province, China.
Ning WangState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, NO. 38, Huanghe Road, Anyang City, 455000, Henan Province, China.
Hong ZhouState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, NO. 38, Huanghe Road, Anyang City, 455000, Henan Province, China.
Qinghua XuState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, NO. 38, Huanghe Road, Anyang City, 455000, Henan Province, China.
Gentu YanState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, NO. 38, Huanghe Road, Anyang City, 455000, Henan Province, China. yangentu@163.com.
Cotton Research Institute · CNChinese Academy of Agricultural Sciences · CN

Funding

STRUCTURE AND REGULATION OF THE CD1 MULTIGENE FAMILYK08AR001805 · NIAMS · MASSACHUSETTS GENERAL HOSPITAL · PI BLEICHER, PAUL A · 1988 to 1992
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Modern Agricultural Industry Technology System of China CARS-18-05the basal research fund of central public-interest scientific institution 1610162019010104the program of National Key R&D Program of China 2018YFD0100300
6 · The paper itself

Abstract

backgroundThe axillary bud is an important index of cotton plant-type traits, and the molecular mechanism of axillary bud development in upland cotton has not yet been reported. We obtained a mutant (designated mZ571) with a high-budding phenotype in axillary bud development from the low-budding phenotype variety G. hirsutum Z571 (CCRI 9A02), which provided ideal materials for the study of complex regulatory networks of axillary bud development. In this study, RNA sequencing was carried out to detect gene expression levels during three stages of axillary buds in Z571 (LB, low budding) and mZ571 mutant (HB, high budding).

resultsA total of 7162 DEGs were identified in the three groups (HB-E vs. LB-E, HB-G1 vs. LB-G1, HB-G2 vs. LB-G2), including 4014 downregulated and 3184 upregulated DEGs. Additionally, 221 DEGs were commonly identified in all three groups, accounting for approximately 3.09% of the total DEGs. These DEGs were identified, annotated and classified. A significant number of DEGs were related to hormone metabolism, hormone signal transduction, and starch and sucrose metabolism. In addition, 45, 22 and 9 DEGs involved in hormone metabolic pathways and 67, 22 and 19 DEGs involved in hormone signal transduction pathwayspathway were identified in HB-E vs. LB-E, HB-G1 vs. LB-G1, and HB-G2 vs. LB-G2, respectively, suggesting that endogenous hormones are the primary factors influencing cotton axillary bud growth. Hormone and soluble sugar content measurements revealed that mZ571 exhibited higher concentrations of zeatin, gibberellins and soluble sugar in all three stages, which confirmed that these hormone metabolism-, hormone signal transduction- and starch metabolism-related genes showed interaction effects contributing to the divergence of axillary bud growth between mZ571 and Z571.

conclusionsOur results confirmed the importance of endogenous hormones and sugars in the development of axillary buds, and we found that mZ571 plants, with a high-budding phenotype of axillary buds, exhibited higher endogenous hormone and sugar concentrations. Overall, we present a model for the emergence and development of cotton axillary buds that provides insights into the complexity and dynamic nature of the regulatory network during axillary bud emergence and development.

Indexed as

TranscriptomeGene Expression ProfilingGossypiumHomeostasisMetabolic Networks and PathwaysPlant Growth RegulatorsPlant ShootsPlant Growth RegulatorsAxillary budDEGsTranscriptomeUpland cotton

Identifiers

PMID32448205
PMCPMC7245931
OpenAlexW3026245441

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.