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Liu X, Xu Z, Feng B, Zhou Q, Guo S, Liao S, Ou Y, Fan X, Wang T. Dissection of a novel major stable QTL on chromosome 7D for grain hardness and its breeding value estimation in bread wheat. FRONTIERS IN PLANT SCIENCE 2024; 15:1356687. [PMID: 38362452 PMCID: PMC10867189 DOI: 10.3389/fpls.2024.1356687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 01/18/2024] [Indexed: 02/17/2024]
Abstract
Grain hardness (Gh) is important for wheat processing and end-product quality. Puroindolines polymorphism explains over 60% of Gh variation and the novel genetic factors remain to be exploited. In this study, a total of 153 quantitative trait loci (QTLs), clustered into 12 genomic intervals (C1-C12), for 13 quality-related traits were identified using a recombinant inbred line population derived from the cross of Zhongkemai138 (ZKM138) and Chuanmai44 (CM44). Among them, C7 (harboring eight QTLs for different quality-related traits) and C8 (mainly harboring QGh.cib-5D.1 for Gh) were attributed to the famous genes, Rht-D1 and Pina, respectively, indicating that the correlation of involved traits was supported by the pleotropic or linked genes. Notably, a novel major stable QTL for Gh was detected in the C12, QGh.cib-7D, with ZKM138-derived allele increasing grain hardness, which was simultaneously mapped by the BSE-Seq method. The geographic pattern and transmissibility of this locus revealed that the increasing-Gh allele is highly frequently present in 85.79% of 373 worldwide wheat varieties and presented 99.31% transmissibility in 144 ZKM138-derivatives, indicating the non-negative effect on yield performance and that its indirect passive selection has happened during the actual breeding process. Thus, the contribution of this new Gh-related locus was highlighted in consideration of improving the efficiency and accuracy of the soft/hard material selection in the molecular marker-assisted process. Further, TraesCS7D02G099400, TraesCS7D02G098000, and TraesCS7D02G099500 were initially deduced to be the most potential candidate genes of QGh.cib-7D. Collectively, this study provided valuable information of elucidating the genetic architecture of Gh for wheat quality improvement.
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Affiliation(s)
- Xiaofeng Liu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- Insitute of Plant Protection, Sichuan Academy of Agricultural Science, Chengdu, China
| | - Zhibin Xu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Bo Feng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Qiang Zhou
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Shaodan Guo
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Simin Liao
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yuhao Ou
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoli Fan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Tao Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- Innovative Academy for Seed Design, Chinese Academy of Sciences, Beijing, China
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Jabran M, Ali MA, Zahoor A, Muhae-Ud-Din G, Liu T, Chen W, Gao L. Intelligent reprogramming of wheat for enhancement of fungal and nematode disease resistance using advanced molecular techniques. FRONTIERS IN PLANT SCIENCE 2023; 14:1132699. [PMID: 37235011 PMCID: PMC10206142 DOI: 10.3389/fpls.2023.1132699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 04/19/2023] [Indexed: 05/28/2023]
Abstract
Wheat (Triticum aestivum L.) diseases are major factors responsible for substantial yield losses worldwide, which affect global food security. For a long time, plant breeders have been struggling to improve wheat resistance against major diseases by selection and conventional breeding techniques. Therefore, this review was conducted to shed light on various gaps in the available literature and to reveal the most promising criteria for disease resistance in wheat. However, novel techniques for molecular breeding in the past few decades have been very fruitful for developing broad-spectrum disease resistance and other important traits in wheat. Many types of molecular markers such as SCAR, RAPD, SSR, SSLP, RFLP, SNP, and DArT, etc., have been reported for resistance against wheat pathogens. This article summarizes various insightful molecular markers involved in wheat improvement for resistance to major diseases through diverse breeding programs. Moreover, this review highlights the applications of marker assisted selection (MAS), quantitative trait loci (QTL), genome wide association studies (GWAS) and the CRISPR/Cas-9 system for developing disease resistance against most important wheat diseases. We also reviewed all reported mapped QTLs for bunts, rusts, smuts, and nematode diseases of wheat. Furthermore, we have also proposed how the CRISPR/Cas-9 system and GWAS can assist breeders in the future for the genetic improvement of wheat. If these molecular approaches are used successfully in the future, they can be a significant step toward expanding food production in wheat crops.
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Affiliation(s)
- Muhammad Jabran
- State Key Laboratory for Biology of Plant Diseases, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Muhammad Amjad Ali
- Department of Plant Pathology, University of Agriculture, Faisalabad, Pakistan
| | - Adil Zahoor
- Department of Biotechnology, Chonnam National University, Yeosu, Republic of Korea
| | - Ghulam Muhae-Ud-Din
- State Key Laboratory for Biology of Plant Diseases, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Taiguo Liu
- State Key Laboratory for Biology of Plant Diseases, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wanquan Chen
- State Key Laboratory for Biology of Plant Diseases, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Li Gao
- State Key Laboratory for Biology of Plant Diseases, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
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