Evidence map›Paper›PMID 36326973›Full record

ArticleRice (New York, N.Y.)2022

Targeted Identification of Rice Grain-Associated Gene Allelic Variation Through Mutation Induction, Targeted Sequencing, and Whole Genome Sequencing Combined with a Mixed-Samples Strategy.

Kai Sun, Dandan Li, Aoyun Xia, Hua Zhao, Qin Wen, Sisi Jia, Jiafeng Wang, Guili Yang, Danhua Zhou, Cuihong Huang and 3 more

Abstract read
In one paragraph

Article in Rice (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

13 authors.

Kai SunNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Dandan LiNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Aoyun XiaNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Hua ZhaoNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Qin WenNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Sisi JiaNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Jiafeng WangNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Guili YangNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Danhua ZhouNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Cuihong HuangNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Hui WangNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Zhiqiang ChenNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China.
Tao GuoNational Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China. guo.tao@vip.163.com.

Funding

Research and Development Plan for Key Areas in Guangdong Province No.2018B020206002Special Rural Revitalization Funds of Guangdong Province 2021KJ382
6 · The paper itself

Abstract

backgroundThe mining of new allelic variation and the induction of new genetic variability are the basis for improving breeding efficiency.

resultsIn this study, in total, 3872 heavy ion-irradiated M

conclusionBased on the above studies, we found 6 granulotype mutants and 9 granulotype-related allelic variants, which provided new functional gene loci and a material basis for molecular breeding and genotype mutation and phenotype analysis. We propose a method for targeted identification of allelic variation in rice grain type genes by combining targeted sequencing of mixed samples and whole genome sequencing. The method has the characteristics of low detection cost, short detection period, and flexible detection of traits and genes.

Indexed as

Allelic variationHeavy-ion irradiationRice grain typeTargeted sequencingWhole genome sequencing

Identifiers

PMID36326973
PMCPMC9633910

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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.