Evidence map›Paper›PMID 35563244›Full record

ArticleInternational journal of molecular sciences2022

Identification of Zinc Efficiency-Associated Loci (

Jianqin Xu, Xiaoxin Qin, Zhongfu Ni, Fanjun Chen, Xiuyi Fu, Futong Yu

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.2field-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

6 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
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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

6 authors at 2 institutions in 1 country.

Jianqin XuKey Laboratory of Plant-Soil Interaction (MOE), Centre for Resources, Environment and Food Security, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China.ORCID 0000-0001-6614-2050
Xiaoxin QinKey Laboratory of Plant-Soil Interaction (MOE), Centre for Resources, Environment and Food Security, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China.
Zhongfu NiState Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization (MOE), Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China.
Fanjun ChenKey Laboratory of Plant-Soil Interaction (MOE), Centre for Resources, Environment and Food Security, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China.
Xiuyi FuKey Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture & Forestry Science (BAAFS), Beijing 100097, China.ORCID 0000-0001-6517-1626
Futong YuKey Laboratory of Plant-Soil Interaction (MOE), Centre for Resources, Environment and Food Security, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China.
China Agricultural University · CNBeijing Academy of Agricultural and Forestry Sciences · CN

Funding

National Key Research and Development Program of China 2016YFD0200405
6 · The paper itself

Abstract

Zinc (Zn) deficiency is one of the most common micronutrient disorders in cereal plants, greatly impairing crop productivity and nutritional quality. Identifying the genes associated with Zn deficiency tolerance is the basis for understanding the genetic mechanism conferring tolerance. In this study, the K22×BY815 and DAN340×K22 recombination inbred line (RIL) populations, which were derived from Zn-inefficient and Zn-efficient inbred lines, were utilized to detect the quantitative trait loci (QTLs) associated with Zn deficiency tolerance and to further identify candidate genes within these loci. The BLUP (Best Linear Unbiased Prediction) values under Zn-deficient condition (-Zn) and the ratios of the BLUP values under Zn deficient condition to the BLUP values under Zn-sufficient condition (-Zn/CK) were used to perform linkage mapping. In QTL analysis, 21 QTLs and 33 QTLs controlling the Zn score, plant height, shoot and root dry weight, and root-to-shoot ratio were detected in the K22×BY815 population and the DAN340×K22 population, explaining 5.5-16.6% and 4.2-23.3% of phenotypic variation, respectively. In addition, seventeen candidate genes associated with the mechanisms underlying Zn deficiency tolerance were identified in QTL colocalizations or the single loci, including the genes involved in the uptake, transport, and redistribution of Zn (

Indexed as

Zea maysZincChromosome MappingPhenotypeQuantitative Trait LociRecombination, GeneticZinccandidate genemaize (Zea mays L.)quantitative trait locus (QTL)zinc (Zn)Zn deficiency tolerance

Identifiers

PMID35563244
PMCPMC9106061
OpenAlexW4225014834

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.