Evidence map›Paper›PMID 31056001›Full record

ArticlePlant signaling & behavior2019

An efficient

Songnan Yang, Yanfeng Hu, Zongming Cheng, John Hollis Rice, Long Miao, Jing Ma, Tarek Hewezi, Yan Li, Junyi Gai

Abstract read
In one paragraph

Article in Plant signaling & behavior, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. 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

9 authors.

Songnan Yanga State Key Laboratory of Crop Genetics and Germplasm Enhancement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture) , National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University , Nanjing , China.
Yanfeng Hub Department of Plant Sciences , University of Tennessee , Knoxville , USA.
Zongming Chenga State Key Laboratory of Crop Genetics and Germplasm Enhancement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture) , National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University , Nanjing , China.
John Hollis Riceb Department of Plant Sciences , University of Tennessee , Knoxville , USA.ORCID 0000-0003-4046-1672
Long Miaoa State Key Laboratory of Crop Genetics and Germplasm Enhancement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture) , National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University , Nanjing , China.
Jing Mab Department of Plant Sciences , University of Tennessee , Knoxville , USA.
Tarek Hewezib Department of Plant Sciences , University of Tennessee , Knoxville , USA.
Yan Lia State Key Laboratory of Crop Genetics and Germplasm Enhancement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture) , National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University , Nanjing , China.
Junyi Gaia State Key Laboratory of Crop Genetics and Germplasm Enhancement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture) , National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University , Nanjing , China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic transformation plays a vital role in gene functional study and molecular breeding of soybean. Conventional soybean transformation methods using chemical selectable markers, such as antibiotic or herbicide resistance genes, rely on the identification of positive transgenic lines at advanced developmental stages, making selection procedure labor intensive and time consuming. Utilization of a visual maker to track the transgene would avoid the uncertainty and blindness in the transformation process. In this research, we used green fluorescent protein (GFP) as the selectable marker to detect transgenics at early stages of soybean development. Positive transformants were detected recurrently during each stage of the process based on visualization of the green fluorescence signal, which help us to discard the non-transgenic ones in each stage to reduce the unnecessary experimental cost and lab space. In addition, the positive transgenic seeds can be identified before planting for early detection of transgene and obtain homozygous lines in advance. The method established in this study is also a useful reference for other plant species.

Indexed as

Transformation, GeneticAgrobacteriumFluorescenceGenetic MarkersGlycine maxGreen Fluorescent ProteinsPlants, Genetically ModifiedPlant ShootsSeedsTransgenesGenetic MarkersGreen Fluorescent Proteinscauliflower mosaic virus 35S promoterGlycine maxgreen fluorescent proteintransformation

Identifiers

PMID31056001
PMCPMC6619996

What OpenQuestion holds

Textmetadata
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.