Jung Michaela, Roth Morgane, Aranzana Maria José, Auwerkerken Annemarie, Bink Marco, Denancé Caroline, Dujak Christian, Durel Charles-Eric, Font I Forcada Carolina, Cantin Celia M, Guerra Walter, Howard Nicholas P, Keller Beat, Lewandowski Mariusz, Ordidge Matthew, Rymenants Marijn, Sanin Nadia, Studer Bruno, Zurawicz Edward, Laurens François, Patocchi Andrea, Muranty Hélène
Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, 8092, Zurich, Switzerland.
Breeding Research group, Agroscope, 8820, Wädenswil, Switzerland.
Hortic Res. 2020 Nov 1;7(1):189. doi: 10.1038/s41438-020-00408-8.
Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates. Genomics-assisted breeding utilizes genomic and phenotypic information to increase the selection efficiency in breeding programs, and measurements of phenotypes in different environments can facilitate the application of the approach under various climatic conditions. Here we present an apple reference population: the apple REFPOP, a large collection formed of 534 genotypes planted in six European countries, as a unique tool to accelerate apple breeding. The population consisted of 269 accessions and 265 progeny from 27 parental combinations, representing the diversity in cultivated apple and current European breeding material, respectively. A high-density genome-wide dataset of 303,239 SNPs was produced as a combined output of two SNP arrays of different densities using marker imputation with an imputation accuracy of 0.95. Based on the genotypic data, linkage disequilibrium was low and population structure was weak. Two well-studied phenological traits of horticultural importance were measured. We found marker-trait associations in several previously identified genomic regions and maximum predictive abilities of 0.57 and 0.75 for floral emergence and harvest date, respectively. With decreasing SNP density, the detection of significant marker-trait associations varied depending on trait architecture. Regardless of the trait, 10,000 SNPs sufficed to maximize genomic prediction ability. We confirm the suitability of the apple REFPOP design for genomics-assisted breeding, especially for breeding programs using related germplasm, and emphasize the advantages of a coordinated and multinational effort for customizing apple breeding methods in the genomics era.
由于筛选候选品种需要时间和空间，苹果育种是一个长期且成本高昂的过程。基因组辅助育种利用基因组和表型信息来提高育种计划中的选择效率，在不同环境下测量表型有助于该方法在各种气候条件下的应用。在此，我们展示了一个苹果参考群体：苹果REFPOP，这是一个由种植在六个欧洲国家的534个基因型组成的大型集合，作为加速苹果育种的独特工具。该群体由269份种质和来自27个亲本组合的265个后代组成，分别代表了栽培苹果和当前欧洲育种材料的多样性。利用标记填充技术，通过两个不同密度的SNP阵列的联合输出，生成了一个包含303,239个SNP的高密度全基因组数据集，填充准确率为0.95。基于基因型数据，连锁不平衡程度较低，群体结构较弱。我们测量了两个研究充分的具有园艺重要性的物候性状。我们在几个先前确定的基因组区域中发现了标记 - 性状关联，对于花期和收获期，最大预测能力分别为0.57和0.75。随着SNP密度的降低，显著标记 - 性状关联的检测因性状结构而异。无论性状如何，10,000个SNP足以最大化基因组预测能力。我们证实了苹果REFPOP设计适用于基因组辅助育种，特别是对于使用相关种质的育种计划，并强调了在基因组时代通过协调的跨国努力来定制苹果育种方法的优势。
