Evidence map›Paper›PMID 39771183›Full record

ArticlePlants (Basel, Switzerland)2024

Development and Validation of Kompetitive Allele-Specific Polymerase Chain Reaction Markers for Seed Protein Content in Soybean.

Shuangzhe Li, Chenyijun Guo, Xuezhen Feng, Jing Wang, Wenjing Pan, Chang Xu, Siming Wei, Xue Han, Mingliang Yang, Qingshan Chen and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plants (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Shuangzhe LiNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.ORCID 0009-0004-9337-5537
Chenyijun GuoNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.
Xuezhen FengNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.
Jing WangNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.
Wenjing PanSuihua Branch of Heilongjiang Academy of Agricultural Sciences, Suihua 152052, China.
Chang XuNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.
Siming WeiNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.
Xue HanNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.
Mingliang YangNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.
Qingshan ChenNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.
Jinxing WangSuihua Branch of Heilongjiang Academy of Agricultural Sciences, Suihua 152052, China.
Limin HuNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.
Zhaoming QiNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.

Funding

Biological Breeding-National Science and Technology Major Project, the National Key R&D Program of China 2021YFF1001202China Agriculture Research System CARS-04-PS15China Postdoctoral Science Foundation 2024MD753909Hainan Seed Industry Laboratory and China National Seed Group B23YQ1503Heilongjiang Cooperation and Innovation Breeding Foundation LJGXCG2022-035National Natural Science Foundation of China 32201755, 32301785, 32472108
6 · The paper itself

Abstract

Seed protein content is a critical trait in soybean breeding, as it provides a primary source of high-quality protein for both human consumption and animal feed. This study aimed to enhance molecular marker-assisted selection for high-protein soybean varieties by developing Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) markers targeted at loci associated with seed protein content. Nineteen markers with high genotyping efficacy were identified through screening. Utilizing SN76 (a high-protein line) as the male parent and SN49 and DS1 (both low-protein lines) as female parents, 484 F

Indexed as

Glycine maxKASPmarker-assisted selectionseed protein content

Identifiers

PMID39771183
PMCPMC11728539

What OpenQuestion holds

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LicenceCC BY
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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.