Evidence map›Paper›PMID 35270097›Full record

ReviewPlants (Basel, Switzerland)2022

Mining of Potential Gene Resources for Breeding Nutritionally Improved Maize.

Quancan Hou, Tianye Zhang, Kangtai Sun, Tingwei Yan, Linlin Wang, Lu Lu, Wei Zhao, Yuchen Qi, Yan Long, Xun Wei and 1 more

Open access · goldAbstract readReview
In one paragraph

Review in Plants (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

7 citing papers in PubMed, 13 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

11 authors at 2 institutions in 1 country.

Quancan HouResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.ORCID 0000-0002-6971-5341
Tianye ZhangResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.
Kangtai SunAgricultural High-Tech Department, China Rural Technology Development Center, Ministry of Science and Technology, Beijing 100045, China.
Tingwei YanResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.
Linlin WangResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.
Lu LuResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.
Wei ZhaoResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.
Yuchen QiResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.
Yan LongResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.
Xun WeiResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.ORCID 0000-0001-9828-6796
Xiangyuan WanResearch Center of Biology and Agriculture, Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, University of Science and Technology Beijing (USTB), Beijing 100024, China.ORCID 0000-0002-5939-4847
University of Science and Technology Beijing · CNChina Rural Technology Development Center · CN

Funding

Beijing Nova Program Z201100006820114Fundamental Research Funds for the Central Universities 06500060National Natural Science Foundation of China 31900610
6 · The paper itself

Abstract

Maize is one of the leading food crops and its kernel is rich in starch, lipids, protein and other energy substances. In addition, maize kernels also contain many trace elements that are potentially beneficial to human health, such as vitamins, minerals and other secondary metabolites. However, gene resources that could be applied for nutrient improvement are limited in maize. In this review, we summarized 107 genes that are associated with nutrient content from different plant species and identified 246 orthologs from the maize genome. In addition, we constructed physical maps and performed a detailed expression pattern analysis for the 246 maize potential gene resources. Combining expression profiles and their potential roles in maize nutrient improvement, genetic engineering by editing or ectopic expression of these genes in maize are expected to improve resistant starch, oil, essential amino acids, vitamins, iron, zinc and anthocyanin levels of maize grains. Thus, this review provides valuable gene resources for maize nutrient improvement.

Indexed as

biological engineeringhomologous genemaizenutrient improvement

Identifiers

PMID35270097
PMCPMC8912576
OpenAlexW4214714043

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.