‘Schmidt's Antonovka’ is identical to ‘Common Antonovka’, an apple cultivar widely used in Russia in breeding for biotic and abiotic stresses

Pikunova, Anna; Madduri, Madhuri; Седов, Е. Н.; Noordijk, Y.; Peil, Andreas; Troggio, Michela; Bus, Vincent G. M.; Visser, Richard G. F.; Weg, Eric van de

doi:10.1007/s11295-013-0679-8

Cited by 31 publications

(22 citation statements)

References 18 publications

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“…The germplasm set used was a subset of the US apple Crop Reference Set supplemented with a Breeding Pedigree Set specific to the WSU program and chosen to efficiently represent genome-wide alleles of important breeding parents of the WSU breeding program as described by Peace et al (2014). Parentage records were verified first using three SSR markers, Md-Exp7 SSR (Costa et al 2008), CH05c06, andHi04e04 (Silfverberg-Dilworth et al 2006;Velasco et al 2010) and then with SNP array markers using procedures described in Pikunova et al (2013) andvan de Weg et al (2018). The final pedigree-connected germplasm consisted of 16 F 1 full-sib families with 200 offspring (Online Resource 1) representing nine important breeding parents ('Arlet,' 'Aurora Golden Gala,' 'Cripps Pink,' 'Delicious,' 'Enterprise,' 'Honeycrisp,' 'Splendour,' 'WA 5,' and selection W1), 25 of their ancestors, and 18 genetically related cultivars and selections supporting the phasing of marker data in ancestral generations.…”

Section: Breeding Germplasmmentioning

confidence: 99%

Two large-effect QTLs, Ma and Ma3, determine genetic potential for acidity in apple fruit: breeding insights from a multi-family study

Verma

Evans

Guan

et al. 2019

Tree Genetics & Genomes

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Acidity is a critical component of the apple fruit consumption experience. In previous biparental family studies, two large-effect acidity QTLs were reported using freshly harvested fruit. Objectives of this study were to determine the number and location of QTLs for acidity variation in a large apple breeding program and ascertain the quantitative effects and breeding relevance of QTL allelic combinations at harvest and after commercially relevant periods of cold storage. Pedigree-connected germplasm of 16 full-sib families representing nine important breeding parents, genotyped for the 8K SNP array, was assessed for titratable acidity at harvest and after 10-and 20-week storage treatments, for three successive seasons. Using pedigree-based QTL mapping software, FlexQTL™, evidence was found for only two QTLs, on linkage groups 16 (the reported Ma locus) and LG 8 (here called Ma3) that jointly explained 66 ± 5% of the phenotypic variation. An additive allele dosage model for the two QTLs effectively explained most acidity variation, with an average of + 1.8 mg/L at harvest per high-acidity allele. The more high-acidity alleles, the faster the depletion with storage, with all combinations appearing to eventually converge to a common baseline. All parent cultivars and selections had one or two of the four possible high-acidity alleles. Each QTL had a rare second high-acidity allele with stronger or reduced effect. Diagnostic SNP markers were identified for QTL alleles derived from distinct sources. Combined QTL effects highlighted utility of the DNAbased information in new cultivar development for targeting desired fruit acidity levels before or after storage.

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Section: Breeding Germplasmmentioning

confidence: 99%

Two large-effect QTLs, Ma and Ma3, determine genetic potential for acidity in apple fruit: breeding insights from a multi-family study

Verma

Evans

Guan

et al. 2019

Tree Genetics & Genomes

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“…The IRSC array greatly facilitated the development of high density linkage maps for segregating apple progenies [5] – [7] . It was used in a Genome-Wide Association Study (GWAS) of the genetic control of several significant fruit traits [8] , for the implementation of Genomic Selection (GS) [9] and for resolving pedigrees [10] . However, these 8,788 potential genetic markers are not sufficient to perform GWAS in wider germplasm sets, or to perform Pedigree-Based Analysis (PBA) [11] with high levels of precision.…”

Section: Introductionmentioning

confidence: 99%

“…However, these 8,788 potential genetic markers are not sufficient to perform GWAS in wider germplasm sets, or to perform Pedigree-Based Analysis (PBA) [11] with high levels of precision. This is due to the rapid linkage disequilibrium decay in apple [12] , the limited proportion of robust, easy to score makers included on the IRSC SNP array [6] , [10] , and their uneven distribution across the genome. A higher density array, with robust genome-wide markers is therefore required to perform such studies successfully.…”

Section: Introductionmentioning

confidence: 99%

Development and Validation of a 20K Single Nucleotide Polymorphism (SNP) Whole Genome Genotyping Array for Apple (Malus × domestica Borkh)

et al. 2014

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High-density SNP arrays for genome-wide assessment of allelic variation have made high resolution genetic characterization of crop germplasm feasible. A medium density array for apple, the IRSC 8K SNP array, has been successfully developed and used for screens of bi-parental populations. However, the number of robust and well-distributed markers contained on this array was not sufficient to perform genome-wide association analyses in wider germplasm sets, or Pedigree-Based Analysis at high precision, because of rapid decay of linkage disequilibrium. We describe the development of an Illumina Infinium array targeting 20K SNPs. The SNPs were predicted from re-sequencing data derived from the genomes of 13 Malus × domestica apple cultivars and one accession belonging to a crab apple species (M. micromalus). A pipeline for SNP selection was devised that avoided the pitfalls associated with the inclusion of paralogous sequence variants, supported the construction of robust multi-allelic SNP haploblocks and selected up to 11 entries within narrow genomic regions of ±5 kb, termed focal points (FPs). Broad genome coverage was attained by placing FPs at 1 cM intervals on a consensus genetic map, complementing them with FPs to enrich the ends of each of the chromosomes, and by bridging physical intervals greater than 400 Kbps. The selection also included ∼3.7K validated SNPs from the IRSC 8K array. The array has already been used in other studies where ∼15.8K SNP markers were mapped with an average of ∼6.8K SNPs per full-sib family. The newly developed array with its high density of polymorphic validated SNPs is expected to be of great utility for Pedigree-Based Analysis and Genomic Selection. It will also be a valuable tool to help dissect the genetic mechanisms controlling important fruit quality traits, and to aid the identification of marker-trait associations suitable for the application of Marker Assisted Selection in apple breeding programs.

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“…The genotyping was carried out with the 20K Infinium array (Illumina; Bianco et al , 2014; ). The SNP data, initially processed with the GenomeStudio Data Analysis software, were finally elaborated with ASSIsT (Di Guardo et al , 2015), a dedicated stand-alone pipeline to filter and re-edit SNP calls with a distorted segregation pattern due to the presence of null alleles (Pikunova et al , 2013). …”

Section: Methodsmentioning

confidence: 99%

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association

Guardo

Bink

Guerra

et al. 2017

Journal of Experimental Botany

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‘Schmidt's Antonovka’ is identical to ‘Common Antonovka’, an apple cultivar widely used in Russia in breeding for biotic and abiotic stresses

Cited by 31 publications

References 18 publications

Two large-effect QTLs, Ma and Ma3, determine genetic potential for acidity in apple fruit: breeding insights from a multi-family study

Two large-effect QTLs, Ma and Ma3, determine genetic potential for acidity in apple fruit: breeding insights from a multi-family study

Development and Validation of a 20K Single Nucleotide Polymorphism (SNP) Whole Genome Genotyping Array for Apple (Malus × domestica Borkh)

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association

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