Evidence map›Paper›PMID 34081150›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2021

Genetic control and phenotypic characterization of panicle architecture and grain yield-related traits in foxtail millet (Setaria italica).

Hui Zhi, Qiang He, Sha Tang, Junjun Yang, Wei Zhang, Huifang Liu, Yanchao Jia, Guanqing Jia, Aiying Zhang, Yuhui Li and 19 more

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Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

17 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Article
  3. Genetic linkage map construction and QTL mapping for panicle-related traits in foxtail millet (Molecular breeding : new strategies in plant improvement · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Efficient identification of QTL for agronomic traits in foxtail millet (Setaria italica) using RTM- and MLM-GWAS.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Improvement of millets in the post-genomic era.Physiology and molecular biology of plants : an international journal of functional plant biology · 2022
    Review
  16. Article
  17. Review
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

29 authors at 7 institutions in 1 country.

Hui Zhi *Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China.
Qiang He *Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China.
Sha TangInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China.
Junjun YangInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China.
Wei ZhangInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China.
Huifang LiuInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China.
Yanchao JiaInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China.
Guanqing JiaInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China.
Aiying ZhangInstitute of Millet Crops, Shanxi Agricultural University, Changzhi, 046000, Shanxi, China.
Yuhui LiInstitute of Millet Crops, Shanxi Agricultural University, Changzhi, 046000, Shanxi, China.
Erhu GuoInstitute of Millet Crops, Shanxi Agricultural University, Changzhi, 046000, Shanxi, China.
Ming GaoInstitute of Crop Sciences, Jilin Academy of Agricultural Sciences, Gongzhuling, 136100, Jilin, China.
Shujie LiInstitute of Crop Sciences, Jilin Academy of Agricultural Sciences, Gongzhuling, 136100, Jilin, China.
Junxia LiCereal Crops Institute, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
Na QinCereal Crops Institute, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
Cancan ZhuCereal Crops Institute, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
Chunye MaCereal Crops Institute, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
Haijin ZhangInstitute of Dry-Land Agriculture and Forestry, Liaoning Academy of Agricultural Sciences, Chaoyang, 122000, Liaoning, China.
Guoqiu ChenInstitute of Dry-Land Agriculture and Forestry, Liaoning Academy of Agricultural Sciences, Chaoyang, 122000, Liaoning, China.
Wenfei ZhangInstitute of Dry-Land Agriculture and Forestry, Liaoning Academy of Agricultural Sciences, Chaoyang, 122000, Liaoning, China.
Haigang WangCenter for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan, 030031, Shanxi, China.
Zhijun QiaoCenter for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan, 030031, Shanxi, China.
Shunguo LiInstitute of Millet Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, 050035, China.
Ruhong ChengInstitute of Millet Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, 050035, China.
Lu XingAnyang Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
Suying WangAnyang Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
Jinrong LiuAnyang Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
Jun LiuInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China.
Xianmin DiaoInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China. diaoxianmin@caas.cn.ORCID http://orcid.org/0000-0002-8957-4101
Chinese Academy of Agricultural Sciences · CNShanxi Agricultural University · CNAnyang Academy of Agricultural Sciences · CNHenan Academy of Agricultural Sciences · CNLiaoning Academy of Agricultural Sciences · CNJilin Academy of Agricultural Sciences · CNHebei Academy of Agriculture and Forestry Sciences · CN

Funding

Agricultural Science and Technology Innovation Program of CAAS ICS2020YJ08BX-2China Agricultural Research System CARS06-13.5China Postdoctoral Science Foundation 2018M641553National Key R&D Program of China 2019YFD1000700National Key R&D Program of China 2019YFD1000701National Natural Science Foundation of China 31871630
6 · The paper itself

Abstract

key messageMulti-environment QTL mapping identified 23 stable loci and 34 co-located QTL clusters for panicle architecture and grain yield-related traits, which provide a genetic basis for foxtail millet yield improvement. Panicle architecture and grain weight, both of which are influenced by genetic and environmental factors, have significant effects on grain yield potential. Here, we used a recombinant inbred line (RIL) population of 333 lines of foxtail millet, which were grown in 13 trials with varying environmental conditions, to identify quantitative trait loci (QTL) controlling nine agronomic traits related to panicle architecture and grain yield. We found that panicle weight, grain weight per panicle, panicle length, panicle diameter, and panicle exsertion length varied across different geographical locations. QTL mapping revealed 159 QTL for nine traits. Of the 159 QTL, 34 were identified in 2 to 12 environments, suggesting that the genetic control of panicle architecture in foxtail millet is sensitive to photoperiod and/or other environmental factors. Eighty-eight QTL controlling different traits formed 34 co-located QTL clusters, including the triple QTL cluster qPD9.2/qPL9.5/qPEL9.3, which was detected 23 times in 13 environments. Several candidate genes, including Seita.2G388700, Seita.3G136000, Seita.4G185300, Seita.5G241500, Seita.5G243100, Seita.9G281300, and Seita.9G342700, were identified in the genomic intervals of multi-environmental QTL or co-located QTL clusters. Using available phenotypic and genotype data, we conducted haplotype analysis for Seita.2G002300 and Seita.9G064000,which showed high correlations with panicle weight and panicle exsertion length, respectively. These results not only provided a basis for further fine mapping, functional studies and marker-assisted selection of traits related to panicle architecture in foxtail millet, but also provide information for comparative genomics analyses of cereal crops.

Indexed as

Gene Expression Regulation, PlantPhenotypeQuantitative Trait LociChromosome MappingChromosomes, PlantEdible GrainGenome, PlantHigh-Throughput Nucleotide SequencingPlant ProteinsPolymorphism, Single NucleotideSetaria PlantPlant Proteins

Identifiers

PMID34081150
OpenAlexW3163985081

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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.