Evidence map›Paper›PMID 42175697›Full record

ArticleThe plant genome2026

Pan-NLRome analysis uncovers genetic diversity and evolutionary dynamics among rice, maize and sorghum.

Yanbo Wang, Tashi Dorjee, Yinzi Wang, Di Peng, Lang Chen, Chuanzheng Wei, Shichao Sun, Mingyu Duan, Hui Li, Adrian Hathorn and 5 more

Abstract read
In one paragraph

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

15 authors.

Yanbo WangState Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
Tashi DorjeeState Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
Yinzi WangState Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
Di PengZunyi Academy of Agricultural Sciences, Zunyi, China.
Lang ChenZunyi Academy of Agricultural Sciences, Zunyi, China.
Chuanzheng WeiState Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
Shichao SunState Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
Mingyu DuanZunyi Academy of Agricultural Sciences, Zunyi, China.
Hui LiZunyi Academy of Agricultural Sciences, Zunyi, China.
Adrian HathornQueensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Hermitage Research Facility, Warwick, Queensland, Australia.
Emma MaceQueensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Hermitage Research Facility, Warwick, Queensland, Australia.
David JordanQueensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Hermitage Research Facility, Warwick, Queensland, Australia.
Xun WuInstitute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang, China.
Xiaocui ChenZunyi Academy of Agricultural Sciences, Zunyi, China.
Yongfu TaoState Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.ORCID https://orcid.org/0000-0001-9096-7407

Funding

Construction of Scientific Research Capacity and Conditions for the Provincial Key Laboratory of Biological Breeding of Characteristic Grain and Oil Crops in Karst Mountainous Areas Qianke Hefuqi[2024]003-2Guizhou Province Science and Technology Plan Program of China Qian Kehe support Nos.[2026] general 275Guizhou Province Science and Technology Support Program Project Qian Kehe-ZD (2025) 011National Natural Science Foundation of China 32441040The Innovation Capacity Construction of Biological Breeding for Specialty Crops in Karst Mountainous Areas Qianke Hefuqi [2024]003-1Wellcome Trust 202401
6 · The paper itself

Abstract

Nucleotide-binding leucine-rich repeat (NLR) genes constitute one of the largest families of plant immune receptors and are central to crop disease resistance. Rice (Oryza sativa L.), maize (Zea mays L.), and sorghum (Sorghum bicolor (L.) Moench) are major crops underpinning global food security, and enhancing their immunity is critical for yield stability. Here, we conducted a comprehensive analysis of NLR repertoires across 75 genomes from these three grass crops, identifying 24,944 genes that exhibit extensive intra- and interspecific variation. The crops share broadly comparable domain architectures of NLR genes, despite their differences in gene number and genomic clustering pattern. We detected 68 integrated domains, revealing high diversity and pronounced lineage specificity. The pan-NLR profiles of the three crops were generally similar, with strong lineage-restricted expansion of NLR gene families. Cross-species comparisons revealed distinct proportions of common gene and lineage-specific genes between the crops, suggesting divergent evolutionary trajectories. Widespread presence/absence variation of NLR genes was identified within each crop, with an enrichment in clustered loci. NLRs, especially clustered ones, were significantly enriched in disease-resistance quantitative trait locus (QTL) hotspots, supporting their critical role in crop disease resistance. Notably, conserved Rp1-D clusters co-localized with resistance QTLs in the three crops, underscoring functional conservation and the translational potential of cross-species NLR studies. Collectively, these findings provide new insights into the genetic diversity and evolutionary dynamics of NLRs in three major grass crops and provide a valuable genomic resource for enhancing crop disease resistance.

Indexed as

Evolution, MolecularGenetic VariationNLR ProteinsOryzaPlant ProteinsSorghumZea maysGenome, PlantPhylogenyNLR ProteinsPlant Proteins

Identifiers

PMID42175697
PMCPMC13492628

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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.