Evidence map›Paper›PMID 31863176›Full record

ArticleMolecular genetics and genomics : MGG2020

Effect of multi-allele combination on rice grain size based on prediction of regression equation model.

Hua Zhong, Chang Liu, Weilong Kong, Yue Zhang, Gangqing Zhao, Tong Sun, Yangsheng Li

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular genetics and genomics : MGG, 2020. 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
–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

7 citing papers in PubMed.

  1. Article
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  5. Article
  6. Research on Rice Yield Prediction Model Based on Deep Learning.Computational intelligence and neuroscience · 2022
    Article
  7. 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.

Hua ZhongState Key Laboratory of Hybrid Rice, Key Laboratory for Research and Utilization of Heterosis in Indica Rice, Ministry of Agriculture, College of Life Sciences, Wuhan University, Wuhan, 430072, People's Republic of China.ORCID http://orcid.org/0000-0002-9358-1582
Chang LiuState Key Laboratory of Hybrid Rice, Key Laboratory for Research and Utilization of Heterosis in Indica Rice, Ministry of Agriculture, College of Life Sciences, Wuhan University, Wuhan, 430072, People's Republic of China.
Weilong KongState Key Laboratory of Hybrid Rice, Key Laboratory for Research and Utilization of Heterosis in Indica Rice, Ministry of Agriculture, College of Life Sciences, Wuhan University, Wuhan, 430072, People's Republic of China.
Yue ZhangState Key Laboratory of Hybrid Rice, Key Laboratory for Research and Utilization of Heterosis in Indica Rice, Ministry of Agriculture, College of Life Sciences, Wuhan University, Wuhan, 430072, People's Republic of China.
Gangqing ZhaoState Key Laboratory of Hybrid Rice, Key Laboratory for Research and Utilization of Heterosis in Indica Rice, Ministry of Agriculture, College of Life Sciences, Wuhan University, Wuhan, 430072, People's Republic of China.
Tong SunState Key Laboratory of Hybrid Rice, Key Laboratory for Research and Utilization of Heterosis in Indica Rice, Ministry of Agriculture, College of Life Sciences, Wuhan University, Wuhan, 430072, People's Republic of China.
Yangsheng LiState Key Laboratory of Hybrid Rice, Key Laboratory for Research and Utilization of Heterosis in Indica Rice, Ministry of Agriculture, College of Life Sciences, Wuhan University, Wuhan, 430072, People's Republic of China. lysh2001@whu.edu.cn.

Funding

Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research, Ministry of Education 313039the 863 program 2014AA10A604-9the National Key Research and Development Program of China 2016YFD0100400the National Special Key Project for Transgenic Breeding 2016ZX08001001
6 · The paper itself

Abstract

Rice yield potential is partially affected by grain size and weight, which associates with a great number of genes and QTLs. However, it is still unclear that how multiple alleles in different genes take a combined effect on grain shape/size. Here, we investigated seven core grain size-related functional genes (GL7, GS3, GW8, GS5, TGW6, WTG1, and An-1) and observed a wide phenotypic variation for five agronomic traits (grain length, grain width, grain length-width ratio, grain thickness and thousand-grain weight) in 521 rice germplasm. The correlation analysis showed a strong association among these grain traits which have distinct impacts on determining the final rice grain size. Genotyping analysis demonstrated that a relatively small number of allele combinations were preserved in the diverse population and these allele combinations were significantly associated with differences in grain size. Furthermore, alleles were regarded as individual variables to develop the multiple regression equation. We found that B and C allelic types of GS3 and conventional type of WTG1 played relevant roles in grain size and thousand-grain weight, separately. The models would conduce to devise instructive approaches by selecting appropriate candidate alleles, which could fuel further research for breeding preferred grain shape and high-yielding crop.

Indexed as

AllelesChromosome MappingChromosomes, PlantEdible GrainHaplotypesOryzaPhenotypePlant ProteinsQuantitative Trait LociPlant ProteinsGrain shapeMultiple allele combinationRegression equation modelRiceYield

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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.