Evidence map›Paper›PMID 42711326›Full record

ArticleNature communications2026

Natural variation in BRN1 enhances nitrogen sensitivity to improve rice nitrogen use efficiency.

Huwei Sun, Yake Chen, Yibo Hu, Hanyun Wang, Wenjun Zhu, Yuqing Liu, Ningning Ren, Bin Hu, Chengcai Chu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. 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.

Huwei Sun *Guangdong Basic Research Center of Excellence for Precise Breeding of Future Crops, and Guangdong Laboratory for Lingnan Modern Agriculture, College of Agriculture, South China Agricultural University, Guangzhou, China. hwsun@scau.edu.cn.
Yake Chen *Guangdong Basic Research Center of Excellence for Precise Breeding of Future Crops, and Guangdong Laboratory for Lingnan Modern Agriculture, College of Agriculture, South China Agricultural University, Guangzhou, China.
Yibo HuGuangdong Basic Research Center of Excellence for Precise Breeding of Future Crops, and Guangdong Laboratory for Lingnan Modern Agriculture, College of Agriculture, South China Agricultural University, Guangzhou, China.
Hanyun WangGuangdong Basic Research Center of Excellence for Precise Breeding of Future Crops, and Guangdong Laboratory for Lingnan Modern Agriculture, College of Agriculture, South China Agricultural University, Guangzhou, China.
Wenjun ZhuGuangdong Basic Research Center of Excellence for Precise Breeding of Future Crops, and Guangdong Laboratory for Lingnan Modern Agriculture, College of Agriculture, South China Agricultural University, Guangzhou, China.ORCID 0009-0007-4574-685X
Yuqing LiuGuangdong Basic Research Center of Excellence for Precise Breeding of Future Crops, and Guangdong Laboratory for Lingnan Modern Agriculture, College of Agriculture, South China Agricultural University, Guangzhou, China.
Ningning RenGuangdong Basic Research Center of Excellence for Precise Breeding of Future Crops, and Guangdong Laboratory for Lingnan Modern Agriculture, College of Agriculture, South China Agricultural University, Guangzhou, China.
Bin HuGuangdong Basic Research Center of Excellence for Precise Breeding of Future Crops, and Guangdong Laboratory for Lingnan Modern Agriculture, College of Agriculture, South China Agricultural University, Guangzhou, China.
Chengcai ChuGuangdong Basic Research Center of Excellence for Precise Breeding of Future Crops, and Guangdong Laboratory for Lingnan Modern Agriculture, College of Agriculture, South China Agricultural University, Guangzhou, China. ccchu@scau.edu.cn.ORCID 0000-0001-8097-6115

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Green Revolution rice varieties deliver high yields but require excessive nitrogen (N) fertilizer and show diminished N responsiveness, severely reducing nitrogen-use efficiency (NUE). To dissect the molecular basis of low N sensitivity in modern cultivars, we conducted a genome-wide association study (GWAS) for biomass response to N (BRN), a trait tightly linked to N sensitivity, using a diverse rice germplasm panel. We identified BRN1 as a key regulator of N-dependent biomass accumulation that regulates NLP3, a master transcription factor governing nitrate signaling. Under elevated N supply, the strigolactone signaling repressor D53 accumulates substantially and interacts with BRN1 to repress NLP3 transcription, thereby reducing rice N response. Notably, the high-response BRN1

Indexed as

NitrogenOryzaPlant ProteinsAllelesBiomassGene Expression Regulation, PlantGenome-Wide Association StudyTranscription FactorsNitrogenPlant ProteinsTranscription Factors

Identifiers

PMID42711326
PMCPMC13554061

What OpenQuestion holds

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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.