Large-scale integration of meta-QTL and genome-wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheat
Abstract Background Improving 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. Results A l...
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2025-03-01
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| Online Access: | https://doi.org/10.1186/s12864-025-11472-6 |
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| author | Ming Chen Tao Chen Letong Yun Zhuo Che Jingfu Ma Binxue Kong Jiangying Long Chunhua Cheng Kaiqi Guo Peipei Zhang Lijian Guo Delong Yang |
| author_facet | Ming Chen Tao Chen Letong Yun Zhuo Che Jingfu Ma Binxue Kong Jiangying Long Chunhua Cheng Kaiqi Guo Peipei Zhang Lijian Guo Delong Yang |
| author_sort | Ming Chen |
| collection | DOAJ |
| description | Abstract Background Improving 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. Results A 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. Conclusion The 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. |
| format | Article |
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| institution | Kabale University |
| issn | 1471-2164 |
| language | English |
| publishDate | 2025-03-01 |
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| spelling | doaj-art-9c73d560edcf4d8ab25e92287ffedbb52025-08-20T03:41:39ZengBMCBMC Genomics1471-21642025-03-0126111910.1186/s12864-025-11472-6Large-scale integration of meta-QTL and genome-wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheatMing Chen0Tao Chen1Letong Yun2Zhuo Che3Jingfu Ma4Binxue Kong5Jiangying Long6Chunhua Cheng7Kaiqi Guo8Peipei Zhang9Lijian Guo10Delong Yang11State Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityCollege of Life Science and Technology, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityState Key Laboratory of Aridland Crop Science, Gansu Agricultural UniversityAbstract Background Improving 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. Results A 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. Conclusion The 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.https://doi.org/10.1186/s12864-025-11472-6WheatPhotosynthetic efficiency traitsMeta-analysisCandidate genesHaplotype analysis |
| spellingShingle | Ming Chen Tao Chen Letong Yun Zhuo Che Jingfu Ma Binxue Kong Jiangying Long Chunhua Cheng Kaiqi Guo Peipei Zhang Lijian Guo Delong Yang Large-scale integration of meta-QTL and genome-wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheat BMC Genomics Wheat Photosynthetic efficiency traits Meta-analysis Candidate genes Haplotype analysis |
| title | Large-scale integration of meta-QTL and genome-wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheat |
| title_full | Large-scale integration of meta-QTL and genome-wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheat |
| title_fullStr | Large-scale integration of meta-QTL and genome-wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheat |
| title_full_unstemmed | Large-scale integration of meta-QTL and genome-wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheat |
| title_short | Large-scale integration of meta-QTL and genome-wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheat |
| title_sort | large scale integration of meta qtl and genome wide association study identifies genomic regions and candidate genes for photosynthetic efficiency traits in bread wheat |
| topic | Wheat Photosynthetic efficiency traits Meta-analysis Candidate genes Haplotype analysis |
| url | https://doi.org/10.1186/s12864-025-11472-6 |
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