Evidence map›Paper›PMID 26734019›Full record

ArticleFrontiers in plant science2015

Genome-Wide Linkage Mapping of QTL for Yield Components, Plant Height and Yield-Related Physiological Traits in the Chinese Wheat Cross Zhou 8425B/Chinese Spring.

Fengmei Gao, Weie Wen, Jindong Liu, Awais Rasheed, Guihong Yin, Xianchun Xia, Xiaoxia Wu, Zhonghu He

Abstract read
In one paragraph

Article in Frontiers in plant science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 144 papers.

0numbers the graph read from it
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144citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

144 citing papers in PubMed.

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  12. Joint linkage and association analysis identifies genomic regions and candidate genes for yield-related traits in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  13. Article
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  15. Fine mapping and candidate gene mining of major QTLFrontiers in plant science · 2025
    Article
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  20. Molecular characterization of QTL for grain zinc and iron concentrations in wheat landrace Chinese Spring.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article

84 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Fengmei GaoKey Laboratory of Soybean Biology, Soybean Research Institute, Ministry of Education, Northeast Agricultural UniversityHarbin, China; National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China; Keshan Sub-Academy, Heilongjiang Academy of Agricultural SciencesKeshan, China.
Weie WenNational Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural Sciences Beijing, China.
Jindong LiuNational Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural Sciences Beijing, China.
Awais RasheedNational Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China; International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o Chinese Academy of Agricultural SciencesBeijing, China.
Guihong YinZhoukou Academy of Agricultural Sciences Zhoukou, China.
Xianchun XiaNational Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural Sciences Beijing, China.
Xiaoxia WuKey Laboratory of Soybean Biology, Soybean Research Institute, Ministry of Education, Northeast Agricultural University Harbin, China.
Zhonghu HeNational Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China; International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o Chinese Academy of Agricultural SciencesBeijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of genes for yield components, plant height (PH), and yield-related physiological traits and tightly linked molecular markers is of great importance in marker-assisted selection (MAS) in wheat breeding. In the present study, 246 F8 RILs derived from the cross of Zhou 8425B/Chinese Spring were genotyped using the high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay. Field trials were conducted at Zhengzhou and Zhoukou of Henan Province, during the 2012-2013 and 2013-2014 cropping season under irrigated conditions, providing data for four environments. Analysis of variance (ANOVA) of agronomic and physiological traits revealed significant differences (P < 0.01) among RILs, environments, and RILs × environments interactions. Broad-sense heritabilities of all traits including thousand kernel weight (TKW), PH, spike length (SL), kernel number per spike (KNS), spike number/m(2) (SN), normalized difference in vegetation index at anthesis (NDVI-A) and at 10 days post-anthesis (NDVI-10), SPAD value of chlorophyll content at anthesis (Chl-A) and at 10 days post-anthesis (Chl-10) ranged between 0.65 and 0.94. A linkage map spanning 3609.4 cM was constructed using 5636 polymorphic SNP markers, with an average chromosome length of 171.9 cM and marker density of 0.64 cM/marker. A total of 866 SNP markers were newly mapped to the hexaploid wheat linkage map. Eighty-six QTL for yield components, PH, and yield-related physiological traits were detected on 18 chromosomes except 1D, 5D, and 6D, explaining 2.3-33.2% of the phenotypic variance. Ten stable QTL were identified across four environments, viz. QTKW.caas-6A.1, QTKW.caas-7AL, QKNS.caas-4AL, QSN.caas-1AL.1, QPH.caas-4BS.2, QPH.caas-4DS.1, QSL.caas-4AS, QSL.caas-4AL.1, QChl-A.caas-5AL, and QChl-10.caas-5BL. Meanwhile, 10 QTL-rich regions were found on chromosome 1BS, 2AL (2), 3AL, 4AL (2), 4BS, 4DS, 5BL, and 7AL exhibiting pleiotropic effects. These QTL or QTL clusters are tightly linked to SNP markers, with genetic distances to the closest SNPs ranging from 0 to 1.5 cM, and could serve as target regions for fine mapping, candidate gene discovery, and MAS in wheat breeding.

Indexed as

linkage analysismolecular markerQTLTriticum aestivumwheat 90K SNP array

Identifiers

PMID26734019
PMCPMC4683206

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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.