Evidence map›Paper›PMID 41163133›Full record

ArticleBMC plant biology2025

Unveiling novel QTLs for nitrogen use efficiency in temperate Japonica rice.

Karen Marti-Jerez, Mar Català-Forner, Eva Pla, Luis Marques, Julia García-Romeral, Venkata Rami Reddy Yannam, Marta S Lopes, Concha Domingo

Abstract read
In one paragraph

Article in BMC plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Karen Marti-JerezSustainable Field Crops Program, Institute of Agrifood Research and Technology, Crta. Balada km 1, Amposta, 43870, Spain.
Mar Català-FornerSustainable Field Crops Program, Institute of Agrifood Research and Technology, Crta. Balada km 1, Amposta, 43870, Spain. mar.catala@irta.cat.
Eva PlaSustainable Field Crops Program, Institute of Agrifood Research and Technology, Crta. Balada km 1, Amposta, 43870, Spain.
Luis MarquesCooperativa Productores Semillas Arroz, Sueca, Spain. Avda del Mar 1, Sueca, 46410, Valencia, Spain.
Julia García-RomeralDepartamento del Arroz, Centro de Genómica, Instituto Valenciano de Investigaciones Agrarias (IVIA), Carretera CV‑315. km 10.7, Moncada, Valencia, 46113, Spain.
Venkata Rami Reddy YannamSustainable Field Crops Program, Institute of Agrifood Research and Technology, Av. Alcalde Rovira i Roure 191, Lleida, 25198, Spain.
Marta S LopesSustainable Field Crops Program, Institute of Agrifood Research and Technology, Av. Alcalde Rovira i Roure 191, Lleida, 25198, Spain.
Concha DomingoDepartamento del Arroz, Centro de Genómica, Instituto Valenciano de Investigaciones Agrarias (IVIA), Carretera CV‑315. km 10.7, Moncada, Valencia, 46113, Spain. domingo_concar@gva.es.

Funding

Consolidated Research Group 2021 SGR 01429ERDF Program 2021-2027 Comunitat Valenciana IVIA-GVA 52201European Union Next Generation EU/PRTR PLEC2021-007786Instituto Valenciano de Investigaciones Agrarias IVIA-GVA 52201Ministerio de Ciencia, Innovación y Universidades PLEC2021-007786Ministerio de Ciencia, Innovación y Universidades PRE209-089034
6 · The paper itself

Abstract

backgroundNitrogen (N) is essential for rice growth and has driven yield increases since the 1950s. However, excessive use of mineral N fertilizers has led to considerable environmental and economic concerns. Enhancing nitrogen use efficiency (NUE) is essential for reducing these impacts and ensuring global food security. Decades of breeding under high N application have reduced the fertilizer responsiveness of modern temperate japonica rice varieties, further contributing to NUE inefficiencies. This study aimed to uncover the genetic components underlaying NUE in temperate-adapted japonica rice varieties.

resultsA genome-wide association study (GWAS) with PCA and kinship matrix was conducted on a panel of 153 temperate japonica rice accessions using 97,244 single-nucleotide polymorphisms (SNPs) to detect quantitative trait loci (QTLs) for NUE. Phenotypic evaluations were conducted under two distinct nitrogen levels across three different field environments. Significant influences of both nitrogen level and environment were observed on trait expression. A total of 14 marker trait associations (MTAs) were identified and grouped into eight QTLs. Within these regions 350 genes were identified and among them three candidate genes were pinpointed including a gene involved in N uptake and transport (OsNAR2.1) and two transcription factors related to N use and metabolism or regulated by the N availability (OsARF19 and OsMADS27). In addition, three novel loci associated with enhanced NUE (chr02:22969295, chr01:33259076, and chr09:17345345) emerged as promising targets for marker-assisted selection. A phylogenetic analysis of the allele distribution for the candidate genes across the collection revealed significant variation in NUE among the genetic clusters, with one cluster exhibiting superior NUE performance under the tested conditions highlighting the genetic components of NUE.

conclusionsThis study provides genetic insights into NUE in temperate japonica rice. We have identified QTLs associated with NUE traits, some of which co-localized with previously identified genes, while also providing novel molecular markers. The identified loci and candidate genes offer valuable genetic resources to support molecular breeding strategies aimed at improving NUE in japonica rice cultivars adapted to temperate climates.

Indexed as

NitrogenOryzaQuantitative Trait LociGenes, PlantGenome-Wide Association StudyPhenotypePolymorphism, Single NucleotideNitrogenGenome wide association study (GWAS)Nitrogen use efficiency (NUE)Temperate japonica rice

Identifiers

PMID41163133
PMCPMC12573877

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.