Evidence map›Paper›PMID 33128073›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2021

QTL mapping for foxtail millet plant height in multi-environment using an ultra-high density bin map.

Qiang He, Hui Zhi, Sha Tang, Lu Xing, Suying Wang, Haigang Wang, Aiying Zhang, Yuhui Li, Ming Gao, Haijin Zhang and 14 more

Abstract read
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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 27 papers.

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27citing 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

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3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

  1. Biology · 2026
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4 · The record

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5 · Who and what money

Authors and funding

24 authors.

Qiang HeInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China.
Hui ZhiInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China.
Sha TangInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China.
Lu XingAnyang Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
Suying WangAnyang Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
Haigang WangInstitute of Crop Germplasm, Shanxi Academy of Agricultural Sciences, Taiyuan, 030000, China.
Aiying ZhangInstitute of Millet Crops, Shanxi Academy of Agricultural Sciences, Changzhi, 046000, Shanxi, China.
Yuhui LiInstitute of Millet Crops, Shanxi Academy of Agricultural Sciences, Changzhi, 046000, Shanxi, China.
Ming GaoInstitute of Crop Sciences, Jilin Academy of Agricultural Sciences, Gongzhuling, Jilin, 136100, 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.
Shutao DaiInstitute of Crop Sciences, Henan Academy of Agricultural Sciences, Zhengzhou, 450000, Henan, China.
Junxia LiInstitute of Crop Sciences, Henan Academy of Agricultural Sciences, Zhengzhou, 450000, Henan, China.
Junjun YangInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China.
Huifang LiuInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China.
Wei ZhangInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China.
Yanchao JiaInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China.
Shujie LiInstitute of Crop Sciences, Jilin Academy of Agricultural Sciences, Gongzhuling, Jilin, 136100, China.
Jinrong LiuAnyang Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
Zhijun QiaoInstitute of Crop Germplasm, Shanxi Academy of Agricultural Sciences, Taiyuan, 030000, China.
Erhu GuoInstitute of Millet Crops, Shanxi Academy of Agricultural Sciences, Changzhi, 046000, Shanxi, China.
Guanqing JiaInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China.
Jun LiuInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China.
Xianmin DiaoInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, Haidian, 100081, China. diaoxianmin@caas.cn.ORCID http://orcid.org/0000-0002-8957-4101

Funding

China agricultural research system CARS-06-13.5National Key R&D Program of China 2018YFD1000700National Key R&D Program of China 2018YFD1000706National Natural Science Foundation of China 31771807National Natural Science Foundation of China 31871630
6 · The paper itself

Abstract

key messageUsing a fixed RIL population derived from a widely used foxtail millet backbone breeding line and an elite cultivar, we constructed a high-density bin map and identified six novel multi-environment effect QTLs and seven candidate genes for dwarf phenotype. Plant height is an important trait that determines tradeoffs between competition and resource allocation, which is crucial for yield potential. To improve the C4 model plant foxtail millet (Setaria italica) productivity, it is necessary to isolate plant height-related genes that contribute to ideal plant architecture in breeding. In the present study, we generated a foxtail millet population of 333 recombinant inbred lines (RILs) derived from a cross between a backbone line Ai 88 and an elite cultivar Liaogu 1. We evaluated plant height in 13 environmental conditions across 4 years, the mean plant height of the RIL population ranged from 89.5 to 149.9 cm. Using deep re-sequencing data, we constructed a high-density bin map with 3744 marker bins. Quantitative trait locus (QTL) mapping identified 26 QTLs significantly associated with plant height. Of these, 13 QTLs were repeatedly detected under multiple environments, including six novel QTLs that have not been reported before. Seita.1G242300, a gene encodes gibberellin 2-oxidase-8, which was detected in nine environments in a 1.54-Mb interval of qPH1.3, was considered as an important candidate gene. Moreover, other six genes involved in GA biosynthesis or signaling pathways, and fifteen genes encode F-box domain proteins which might function as E3 ligases, were also considered as candidate genes in different QTLs. These QTLs and candidate genes identified in this study will help to elucidate the genetic basis of foxtail millet plant height, and the linked markers will be useful for marker-assistant selection of varieties with ideal plant architecture and high yield potential.

Indexed as

Gene Expression Regulation, PlantPlant BreedingQuantitative Trait LociChromosome MappingChromosomes, PlantGenome, PlantHigh-Throughput Nucleotide SequencingPlant ProteinsPolymorphism, Single NucleotideSetaria PlantPlant Proteins

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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.