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A bulked segregant analysis tool for out-crossing species (BSATOS) and QTL-based genomics-assisted prediction of complex traits in apple

文献类型： 外文期刊

作者： Shen, Fei 1 ; Bianco, Luca 2 ; Wu, Bei 1 ; Tian, Zhendong 1 ; Wang, Yi 1 ; Wu, Ting 1 ; Xu, Xuefeng 1 ; Han, Zhenhai 1 ; Velasco, Riccardo 4 ; Fontana, Paolo 2 ; Zhang, Xinzhong 1 ;

作者机构： 1.China Agr Univ, Coll Hort, Beijing 100193, Peoples R China

2.Edmund Mach Fdn, Res & Innovat Ctr, I-38010 San Michele All Adige, Italy

3.Beijing Acad Agr & Forestry Sci, Beijing 100097, Peoples R China

4.CREA, Res Ctr Viticulture & Enol, Conegliano, Italy

关键词： Genomics-assisted prediction; Bulked segregant analysis; QTL; Apple

期刊名称：JOURNAL OF ADVANCED RESEARCH （ 影响因子：12.822； 五年影响因子：11.664 ）

ISSN： 2090-1232

年卷期： 2022 年 42 卷

页码：

收录情况： SCI

摘要： Introduction: Genomic heterozygosity, self-incompatibility, and rich-in somatic mutations hinder the molecular breeding efficiency of outcrossing plants.Objectives: We attempted to develop an efficient integrated strategy to identify quantitative trait loci (QTLs) and trait-associated genes, to develop gene markers, and to construct genomics-assisted predic-tion (GAP) modes.Methods: A novel protocol, bulked segregant analysis tool for out-crossing species (BSATOS), is presented here, which is characterized by taking full advantage of all segregation patterns (including AB x AB mark-ers) and haplotype information. To verify the effectiveness of the protocol in dealing with the complex traits of outbreeding species, three apple cross populations with 9,654 individuals were adopted.Results: By using BSATOS, 90, 60, and 77 significant QTLs were identified successfully and candidate genes were predicted for apple fruit weight (FW), fruit ripening date (FRD), and fruit soluble solid content (SSC), respectively. The gene-based markers were developed and genotyped for 1,396 individuals in a training population, including 145 Malus accessions and 1,251 F1 plants of the three full-sib families. GAP models were trained using marker genotype effect estimates of the training population. The predic-tion accuracy was 0.7658, 0.6455, and 0.3758 for FW, FRD, and SSC, respectively.Conclusion: The BSATOS and GAP models provided a convenient and efficient methodology for candidate gene mining and molecular breeding in out-crossing plant species. The BSATOS pipeline can be freely downloaded from: https://github.com/maypoleflyn/BSATOS.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Cairo University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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