Evidence map›Paper›PMID 32901412›Full record

ArticlePlant molecular biology2020

Mapping quantitative trait loci associated with stem-related traits in maize (Zea mays L.).

Qiqi Shang, Degui Zhang, Rong Li, Kaixin Wang, Zimeng Cheng, Zhiqiang Zhou, Zhuanfang Hao, Jinbao Pan, Xinhai Li, Liyu Shi

Abstract read
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In one paragraph

Article in Plant molecular biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 17 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Qiqi Shang *College of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China.
Degui Zhang *Institute of Crop Science, The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
Rong Li *College of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China.
Kaixin WangCollege of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China.
Zimeng ChengCollege of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China.
Zhiqiang ZhouInstitute of Crop Science, The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
Zhuanfang HaoInstitute of Crop Science, The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
Jinbao PanCollege of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China.
Xinhai LiInstitute of Crop Science, The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China. lixinhai@caas.cn.
Liyu ShiCollege of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China. shiliyu321@sina.com.ORCID http://orcid.org/0000-0003-2011-9570
Beijing University of Agriculture · CNChinese Academy of Agricultural Sciences · CN

Funding

Beijing Education Commission-General Project KM201810020005National Natural Science Foundation of China (CN) 31671706
6 · The paper itself

Abstract

key messageMapping QTL for stem-related traits using RIL population with ultra-high density bin map can better dissect pleiotropic QTL controlling stem architecture that can provide valuable information for maize genetic improvement. The maize stem is one of the most important parts of the plant and is also a component of many agronomic traits in maize. This study aimed to advance our understanding of the genetic mechanisms underlying maize stem traits. A recombinant inbred line (RIL) population derived from a cross between Ye478 and Qi319 was used to identify quantitative trait loci (QTL) controlling stem height (SH), ear height (EH), stem node number (SN), ear node (EN), and stem diameter (SD), and two derived traits (ear height coefficient (EHc) and ear node coefficient (ENc)). Using an available ultra-high density bin map, 46 putative QTL for these traits were detected on chromosomes 1, 3, 4, 5, 6, 7, 8, and 10. Individual QTL explained 3.5-17.7% of the phenotypic variance in different environments. Two QTL for SH, three for EH, two for EHc, one for SN, one for EN, and one for SD were detected in more than one environment. QTL with pleiotropic effects or multiple linked QTL were also identified on chromosomes 1, 3, 4, 6, 8, and 10, which are potential target regions for fine-mapping and marker-assisted selection in maize breeding programs. Further, we discussed segregation of bin markers (mk1630 and mk4452) associated with EHc QTL in the RIL population. We had identified two putative WRKY DNA-binding domain proteins, AC209050.3_FG003 and GRMZM5G851490, and a putative auxin response factor, GRMZM2G437460, which might be involved in regulating plant growth and development, as candidate genes for the control of stem architecture.

Indexed as

Chromosomes, PlantQuantitative Trait LociChromosome MappingGenetic LinkageGenetic MarkersGenetic VariationPhenotypePlant StemsZea maysGenetic MarkersCandidate genesMaizeQuantitative trait lociRIL populationStem architecture

Identifiers

PMID32901412
OpenAlexW3084324747

What OpenQuestion holds

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Read underepoch 390

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.