Evidence map›Paper›PMID 41947696›Full record

ArticleThe plant genome2026

Genome-wide association studies for identifying SNPs and candidate genes associated with grain quality traits in rice (Oryza sativa L.).

Shivani Darmagaru, Abdul Fiyaz Rahaman, Farzana Jabeen, Aravind Kumar Jukanti, Chaithanya Kasarla, Dileep Kumar Gowdru Dhananjaya, Arivelarasan Tamilarasu, LellaVenkata Subba Rao, Supriya Kallakuri, Shoba Venkatanagappa and 1 more

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Article in The plant genome, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Shivani DarmagaruDepartment of Genetics & Plant Breeding, Professor Jayashankar Telangana State Agricultural University, Hyderabad, India.ORCID https://orcid.org/0009-0005-7523-2273
Abdul Fiyaz RahamanDepartment of Plant Breeding, ICAR-Indian Institute of Rice Research (IIRR), Hyderabad, India.ORCID https://orcid.org/0009-0006-8935-7234
Farzana JabeenDepartment of Genetics & Plant Breeding, Professor Jayashankar Telangana State Agricultural University, Hyderabad, India.
Aravind Kumar JukantiDepartment of Plant Breeding, ICAR-Indian Institute of Rice Research (IIRR), Hyderabad, India.
Chaithanya KasarlaDepartment of Plant Breeding, ICAR-Indian Institute of Rice Research (IIRR), Hyderabad, India.
Dileep Kumar Gowdru DhananjayaDepartment of Plant Breeding, ICAR-Indian Institute of Rice Research (IIRR), Hyderabad, India.
Arivelarasan TamilarasuSchool of Agriculture, Kaveri University, Siddipet, India.
LellaVenkata Subba RaoDepartment of Plant Breeding, ICAR-Indian Institute of Rice Research (IIRR), Hyderabad, India.
Supriya KallakuriDepartment of Genetics & Plant Breeding, Professor Jayashankar Telangana State Agricultural University, Hyderabad, India.
Shoba VenkatanagappaInternational Rice Research Institute (IRRI), Los Banos, Philippines.
Raman Meenakshi SundaramDepartment of Plant Breeding, ICAR-Indian Institute of Rice Research (IIRR), Hyderabad, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ensuring superior quality is of paramount objective in modern rice (Oryza sativa L.) breeding program and investigating quality traits is crucial for developing superior rice varieties. The current study aimed for identifying single nucleotide polymorphisms (SNPs) and potential candidate genes for eleven quality traits, namely, hulling %, milling %, kernel length, kernel breadth, kernel length to breadth ratio, grain type, head rice recovery, chalkiness, amylose content, alkali spreading value, and gel consistency, using genome-wide association studies (GWASs) on diverse germplasm sourced from various rice-growing regions around the world. Phenotypic evaluation revealed significant genetic diversity among germplasm, with substantial natural variation observed across 10 quality-related traits. GWAS using 7K SNP chip identified 31 SNPs significantly linked to grain quality traits, of which 20 were novel and 11 had been previously reported, including two co-localized SNPs (GS3 and SNP-6.6652023) associated with multiple traits. In addition, 121 candidate genes related with these traits were identified and categorized into seven molecular functions, four cellular components, and nine biological processes. Notably, 17 putative grain quality-related genes were identified, viz., GS3 (Grain size regulator), Wx (granule-bound starch synthase), OsZIP7 (ZIP family protein), OsRING4 (RING-type E3 ubiquitin ligase), OsMKK3 (Mitogen-activated protein kinase), OsSSIV-2, OsSSIIa/SSII-3 (ALK; soluble starch synthase), and OsbZIP58 (bZIP transcription factor). The identified SNPs and potential candidate genes represent a valuable genomic resource for accelerating rice breeding programs focused on the enhancement of key quality traits.

Indexed as

Edible GrainGenes, PlantGenome-Wide Association StudyOryzaPolymorphism, Single NucleotideSeedsPhenotypeQuantitative Trait Loci

Identifiers

PMID41947696
PMCPMC13058673

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