Evidence map›Paper›PMID 40484873›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2025

GWAS and GS analysis revealed the selection and prediction efficiency for yield, plant morphological, and fiber quality in Gossypium barbadense.

Tao Yang, Honggang Wang, Jikun Song, Kang Zhao, Bo Pang, Yongpan Wang, Ping Luo, Weiwei Liang, Shunyu Shi, Jie Wang and 5 more

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Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
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

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

1 citing paper in PubMed.

  1. Article
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

15 authors.

Tao YangEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Honggang WangEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Jikun SongState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, China.
Kang ZhaoEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Bo PangEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Yongpan WangEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Ping LuoEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Weiwei LiangEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Shunyu ShiEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Jie WangEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Yifeng LinEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Jing LiEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Zhenrui WangEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Yongqin GuoEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China.
Wenwei GaoEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052, China. gww@xjau.edu.cn.ORCID http://orcid.org/0009-0003-6524-1526

Funding

Natural Science Foundation project of Xinjiang 2019D01A41The National Key Research and Development Program of China 2021YFD1900802-4Tianshan Youth Project 2018Q016
6 · The paper itself

Abstract

key messageGenetic variation in a Gossypium barbadense population was revealed using resquencing. GWAS and RNA-seq on Gossypium barbadense population identified several candidate genes associated with fiber length, micronaire, and elongation. Sea Island cotton (Gossypium barbadense), a premier tetraploid cotton species, is globally renowned for its fibers, which exhibit thermal expansion and contraction properties similar to those of animal fibers such as cashmere. Despite its significance, there remains a limited understanding of how genes influence primary traits across germplasms and the relationship between predictive factors identified through genomic selection (GS) technology and heritability. This study aimed to address this academic gap. A total of 203 Sea Island cotton accessions were incorporated for resequencing. Population evolution analysis revealed three distinct groups, which were largely shaped by geographical distribution and breeding objectives. Then, genome-wide association study (GWAS) was performed on 15 traits related to yield, fiber quality, and plant morphological, identifying a greater number of loci associated with fiber quality traits that exhibited higher broad sense heritability. Transcriptomic and gene expression analysis identified six key genes involved in regulating fiber length (GB_A05G1764 and GB_A05G1761), fiber micronaire (GB_A05G1895 and GB_A05G1771), and fiber elongation (GB_A05G1702 and GB_A05G1707). Furthermore, geographical and temporal analyses indicated that these traits underwent directional selection in Sea Island cotton. In addition, this study explored the effects of marker density, significant marker quantities, and population size on prediction accuracy using GS technology, finding that traits with higher broad sense heritability, such as fiber quality, achieved higher prediction accuracy, while those with lower broad sense heritability, such as plant morphological, showed reduced accuracy. This study provides an important reference for future GS breeding, in addition to deepening the scientific understanding of the genetic evolution of Sea Island cotton.

Indexed as

Cotton FiberGenome-Wide Association StudyGossypiumSelection, GeneticPhenotypePlant BreedingPolymorphism, Single NucleotideQuantitative Trait Loci

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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.