Evidence map›Paper›PMID 41535744›Full record

ArticleBMC plant biology2026

Excavation and effect analysis of interaction sites between upland cotton yield and fiber quality traits and environmental factors.

Shuqian Yao, Juwu Gong, Wankui Gong, Yang Li, Jingtao Pan, Yuzhen Shi, Youlu Yuan, Haoliang Yan, Haihong Shang

Abstract read
In one paragraph

Article in BMC plant biology, 2026. 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

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

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

9 authors.

Shuqian Yao *National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Juwu Gong *National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Wankui GongNational Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Yang LiNational Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Jingtao PanNational Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Yuzhen ShiNational Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Youlu YuanNational Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China. yuanyoulu@caas.cn.
Haoliang YanNational Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China. yanhaoliang@caas.cn.
Haihong ShangNational Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China. shanghaihong@caas.cn.

Funding

Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences CAAS-ASTIP-2016-ICRChina Agriculture Research System-Cotton CARS-15-02Key R&D Program of Henan Province 241111114200Natural Science Foundation of Henan 242300421592The Central Public-interest Scientific Institution Basal Research Fund 1610162023002
6 · The paper itself

Abstract

Climate change has increased the sensitivity of cropping systems to environmental variability, making the genetic dissection of G×E and phenotypic plasticity essential for adaptive breeding. In this study, a recombinant inbred line population of upland cotton was evaluated across 16 environments from multi-year and multi-location field trials to assess the plasticity of yield- and fiber-quality traits. By integrating the Finlay–Wilkinson regression model with CERIS sliding-window analyses, 13 key meteorological factors and 4 principal component variables were identified, together with their effective time windows. QTL mapping based on trait plasticity slopes and environmental response slopes detected 172 environment-associated loci. A major locus at 188 Mb on chr10 influenced boll weight and seed index in response to multiple environmental variables, including photoperiod, cumulative radiation, growing degree days, and the product of radiation and photoperiod, suggesting a key regulatory site for environmental signal perception. Haplotype analysis further supported functional divergence of alleles within this region in relation to environmental adaptation. Overall, this study identifies critical environmental factors shaping cotton yield and fiber quality and reveals multiple G×E–related loci underlying environmental responsiveness and phenotypic plasticity, providing a theoretical foundation for environmentally informed precision breeding.

Indexed as

Cotton FiberGene-Environment InteractionGossypiumChromosome MappingEnvironmentPhenotypeQuantitative Trait LociEnvironmental factorsFiber qualityGenotype-environment interactionUpland cottonYield traits

Identifiers

PMID41535744
PMCPMC12888543

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.