Evidence map›Paper›PMID 39980198›Full record

ArticlePlant communications2025

Integrative transcriptogenomic analyses reveal the regulatory network underlying rice eating and cooking quality and identify a role for alpha-globulin in modulating starch and sucrose metabolism.

Bhagwat Nawade, Su-Hyeon Shim, Sang-Ho Chu, Weiguo Zhao, Sang-Kyu Lee, Aueangporn Somsri, Thant Zin Maung, Kwon Kyoo Kang, Jae Yoon Kim, Chang-Yong Lee and 4 more

Abstract read
In one paragraph

Article in Plant communications, 2025. 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

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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.

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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

14 authors.

Bhagwat NawadeDepartment of Plant Resources, Kongju National University, Yesan 32439, Republic of Korea.
Su-Hyeon ShimGraduate School of Green-Bio Science and Crop Biotech Institute, Kyung Hee University, Yongin 17104, Republic of Korea.
Sang-Ho ChuDepartment of Plant Resources, Kongju National University, Yesan 32439, Republic of Korea.
Weiguo ZhaoDepartment of Plant Resources, Kongju National University, Yesan 32439, Republic of Korea; School of Biotechnology, Jiangsu University of Science and Technology, Sibaidu, Zhenjiang, Jiangsu 212100, P.R. China.
Sang-Kyu LeeDivision of Life Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju 52828, Republic of Korea.
Aueangporn SomsriDepartment of Plant Resources, Kongju National University, Yesan 32439, Republic of Korea.
Thant Zin MaungDepartment of Plant Resources, Kongju National University, Yesan 32439, Republic of Korea.
Kwon Kyoo KangDepartment of Horticultural Life Science, Hankyong National University, Anseong 17579, Republic of Korea.
Jae Yoon KimDepartment of Plant Resources, Kongju National University, Yesan 32439, Republic of Korea.
Chang-Yong LeeDepartment of Industrial and Systems Engineering, Kongju National University, Cheonan 31080, Republic of Korea.
Min-Seok KimDepartment of Food Science and Biotechnology, Institute of Life Science and Resources, Kyung Hee University, Yongin 17104, Republic of Korea.
Moo-Yeol BaikDepartment of Food Science and Biotechnology, Institute of Life Science and Resources, Kyung Hee University, Yongin 17104, Republic of Korea.
Jong-Seong JeonGraduate School of Green-Bio Science and Crop Biotech Institute, Kyung Hee University, Yongin 17104, Republic of Korea. Electronic address: jjeon@khu.ac.kr.
Yong-Jin ParkDepartment of Plant Resources, Kongju National University, Yesan 32439, Republic of Korea. Electronic address: yjpark@kongju.ac.kr.

Funding

Non-US Government Research Support type
6 · The paper itself

Abstract

Rice eating and cooking quality (ECQ) is significantly influenced by the physicochemical properties of rice starch. This study integrates whole-genome resequencing, transcriptomic data, and phenotypic analysis to identify the genetic factors that regulate transcript expression levels and contribute to phenotypic variation in rice ECQ traits. A TWAS (transcriptome-wide association study) identified 285 transcripts linked to 6 ECQ traits. Genome-wide mapping of these transcripts revealed 21 747 local eQTLs (expression quantitative trait loci) and 45 158 distal eQTLs. TWAS and eQTL analysis detected several known and novel genes, including starch synthesis-related genes, heat shock proteins, transcription factors, genes related to ATP accumulation, and UDP-glucosyltransferases, showcasing the complex genetic regulation of rice ECQ. WGCNA (weighted gene co-expression network analysis) uncovered key co-expression networks, including a module that links alpha-globulin1 (GLB1) to starch and sucrose metabolism. Genetic diversity analysis of the GLB1 gene across a Korean rice collection identified 26 haplotypes, with indica and aus forming 7 and 3 haplotypes, respectively, which showed significant phenotypic effects on ECQ traits. CRISPR-Cas9-created knockout lines validated these findings, demonstrating that loss of GLB1 function caused significant changes in seed storage proteins, reduced amylose content, altered starch granules, and modified pasting properties without affecting plant phenotypes. By integrating TWAS, eQTL mapping, haplotype analysis, gene expression networks, and CRISPR validation, this study establishes GLB1 as a regulator of ECQ, linking starch biosynthesis and protein accumulation pathways. This transcriptogenomic convergence approach provides novel insights into the genetic regulation of ECQ in rice, demonstrating its effectiveness for characterizing complex traits and enabling precision breeding.

Indexed as

Alpha-GlobulinsGene Regulatory NetworksOryzaStarchSucroseCookingGene Expression Regulation, PlantGenome-Wide Association StudyPlant ProteinsQuantitative Trait LociAlpha-GlobulinsPlant ProteinsStarchSucroseECQeQTLGLB1regulatory networkriceTWAS

Identifiers

PMID39980198
PMCPMC12143143

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LicenceCC BY-NC-ND
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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.