Evidence map›Paper›PMID 40121401›Full record

ArticleBMC genomics2025

Large-scale integration of meta-QTL and genome-wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheat.

Ming Chen, Tao Chen, Letong Yun, Zhuo Che, Jingfu Ma, Binxue Kong, Jiangying Long, Chunhua Cheng, Kaiqi Guo, Peipei Zhang and 2 more

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Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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3 · Its place in the literature

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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

12 authors.

Ming ChenState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Tao ChenState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Letong YunState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Zhuo CheState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Jingfu MaState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Binxue KongState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Jiangying LongState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Chunhua ChengState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Kaiqi GuoCollege of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
Peipei ZhangState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Lijian GuoState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China.
Delong YangState Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou, 730070, China. yangdl@gsau.edu.cn.

Funding

Breakthrough Project in Seed Industry of Gansu Province GYGG-2024-2Development Fund Project of National Guiding Local Science and Technology 23ZYQA0322Industrial Support Plan of Colleges and Universities in Gansu Province 2022CYZC-44Innovative Research Group Project of Gansu Province 24JRRA633Key Sci & Tech Special Project of Gansu Province 22ZD6NA009Major Cultivation Project for University Research and Innovation Platforms of Gansu Province 2024CXPT-01National Natural Science Foundation of China 32160487National Natural Science Foundation of China 32260520National Natural Science Foundation of China 32360518National Natural Science Foundation of China 32401920
6 · The paper itself

Abstract

backgroundImproving photosynthetic efficiency is an essential strategy for advancing wheat breeding progress. Integrating wheat genetic resources provides an opportunity to discover pivotal genomic regions and candidate genes (CGs) for photosynthetic efficiency traits in wheat.

resultsA large-scale meta-QTL (MQTL) analysis was performed with 1363 initial quantitative trait loci (QTLs) for photosynthetic efficiency traits extracted from 66 independent QTL mapping studies over the past decades. Consequently, 718 initial QTLs were refined into 74 MQTLs, which were distributed on all wheat chromosomes except 1D, 3 A, 4B, and 5B. Compared with the confidence interval (CI) of the initial QTL, the CI of the identified MQTL was 0.03 to 10.97 cM, with an average of 1.46 cM, which was 20.46 times narrower than that of the original QTL. The maximum explained phenotypic variance (PVE) of the MQTL ranged from 7.43 to 20.42, with an average of 11.97, which was 1.07 times higher than that of the original QTL. Of these, 54 MQTLs were validated using genome-wide association study (GWAS) data from different natural populations in previous research. A total of 3,102 CGs were identified within the MQTL intervals, where 342 CGs share homology with rice, and 1,043 CGs are highly expressed in leaves, spikes, and stems. These CGs were mainly involved in porphyrin metabolism, glyoxylate, dicarboxylate metabolism, carbon metabolism and photosynthesis antenna proteins metabolism pathways by the in silico transcriptome assessment. For the key CG TaGGR-6A (TraesCS6A02G307700) involved in the porphyrin metabolism pathway, a functional kompetitive allele-specific PCR (KASP) marker was developed at 2464 bp (A/G) position within the 3' untranslated region, successfully distinguishing two haplotypes: TaGGR-6A-Hap I (type AA) and TaGGR-6A-Hap II (type GG). Varieties with the TaGGR-6A-Hap II allele exhibited approximately 13.42% and 11.45% higher flag leaf chlorophyll content than those carrying the TaGGR-6A-Hap I allele. The elite haplotype TaGGR-6A-Hap II was positively selected during wheat breeding, as evidenced by the geographical and annual frequency distributions of the two TaGGR-6A haplotypes.

conclusionThe findings will give further insights into the genetic determinants of photosynthetic efficiency traits and provide some reliable MQTLs and putative CGs for the genetic improvement of photosynthetic efficiency in wheat.

Indexed as

Genome-Wide Association StudyGenomicsPhotosynthesisQuantitative Trait LociTriticumChromosome MappingChromosomes, PlantGenes, PlantGenome, PlantPhenotypePolymorphism, Single NucleotideCandidate genesHaplotype analysisMeta-analysisPhotosynthetic efficiency traitsWheat

Identifiers

PMID40121401
PMCPMC11929995

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