Evidence map›Paper›PMID 41140841›Full record

ArticleFood chemistry. Molecular sciences2025

Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (

Supriya Sachdeva, Rakesh Singh, Harshita Singh, Rakesh Bharadwaj, Antil Jain, Vikas K Singh, Uma Maheshwar Singh, Arvind Kumar, Gyanendra Pratap Singh

Abstract read
In one paragraph

Article in Food chemistry. Molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Supriya SachdevaDivision of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India.
Rakesh SinghDivision of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India.
Harshita SinghDivision of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India.
Rakesh BharadwajDivision of Germplasm Evaluation, ICAR-NBPGR, Pusa, New Delhi, India.
Antil JainDivision of Germplasm Evaluation, ICAR-NBPGR, Pusa, New Delhi, India.
Vikas K SinghInternational Rice Research Institute (IRRI), South Asia Hub, ICRISAT, Hyderabad, India.
Uma Maheshwar SinghInternational Rice Research Institute (IRRI), South Asia Regional Centre (ISARC), Varanasi, India.
Arvind KumarInternational Crops Research Institute for the Semi-Arid Tropics, Patancheru, Telangana, India.
Gyanendra Pratap SinghDivision of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grain quality is the key concern for rice breeders and is paramount to consumer acceptability. We characterized a diverse subset of 198 rice accessions of 3 K Rice Genome Project (RGP) for grain quality attributes, specifically glycemic index %, total dietary fibre, oil %, protein, amylose, moisture %, phytate, phenol, and starch content. A set of 5,53,229 single nucleotide polymorphism (SNP) markers obtained from the 3 K RG 1 M filtered SNP dataset used for genome wide association studies (GWAS). Consequently, we discovered 200 Quantitative trait nucleotides (QTNs) associated with the traits mentioned above distributed across the genome. These QTNs were grouped into 26 Quantitative Trait Loci (QTL) clusters, of which 20 clusters validated with at least three GWAS methods were considered reliable. Furthermore, 869 putative candidate genes were identified, many of which overlapped between quality traits. Integrating the GWAS, RNA-seq and qRT-PCR results, we finally identified two important genes (

Indexed as

Candidate geneGO enrichmentGrain qualityGWASQTNRice

Identifiers

PMID41140841
PMCPMC12550801

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.