Evidence map›Paper›PMID 28224059›Full record

ArticleApplications in plant sciences2017

Identification of downy mildew resistance gene candidates by positional cloning in maize (

Jae Yoon Kim, Jun-Cheol Moon, Hyo Chul Kim, Seungho Shin, Kitae Song, Kyung-Hee Kim, Byung-Moo Lee

Abstract read
In one paragraph

Article in Applications in plant sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Frontiers in microbiology · 2022
    Review
  3. Article
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

7 authors.

Jae Yoon KimDepartment of Plant Resources, College of Industrial Science, Kongju National University, Yesan 32439, Republic of Korea.
Jun-Cheol MoonAgriculture and Life Science Research Institute, Kangwon National University, Chuncheon 24341, Republic of Korea.
Hyo Chul KimDepartment of Life Science, Dongguk University-Seoul, Seoul 04620, Republic of Korea.
Seungho ShinDepartment of Life Science, Dongguk University-Seoul, Seoul 04620, Republic of Korea.
Kitae SongDepartment of Life Science, Dongguk University-Seoul, Seoul 04620, Republic of Korea.
Kyung-Hee KimDepartment of Life Science, Dongguk University-Seoul, Seoul 04620, Republic of Korea.
Byung-Moo LeeDepartment of Life Science, Dongguk University-Seoul, Seoul 04620, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

premise of the studyPositional cloning in combination with phenotyping is a general approach to identify disease-resistance gene candidates in plants; however, it requires several time-consuming steps including population or fine mapping. Therefore, in the present study, we suggest a new combined strategy to improve the identification of disease-resistance gene candidates. METHODS AND

resultsDowny mildew (DM)-resistant maize was selected from five cultivars using a spreader row technique. Positional cloning and bioinformatics tools were used to identify the DM-resistance quantitative trait locus marker (bnlg1702) and 47 protein-coding gene annotations. Eventually, five DM-resistance gene candidates, including

conclusionsThe combined protocol with the spreader row technique, quantitative trait locus positional cloning, and quantitative RT-PCR was effective for identifying DM-resistance candidate genes. This cloning approach may be applied to other whole-genome-sequenced crops or resistance to other diseases.

Indexed as

downy mildewmaizepositional cloningquantitative reverse-transcription PCR (RT-PCR)spreader row technique

Identifiers

PMID28224059
PMCPMC5315382

What OpenQuestion holds

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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.