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      A high-density, multi-parental SNP genetic map on apple validates a new mapping approach for outcrossing species

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          Abstract

          Quantitative trait loci (QTL) mapping approaches rely on the correct ordering of molecular markers along the chromosomes, which can be obtained from genetic linkage maps or a reference genome sequence. For apple ( Malus domestica Borkh), the genome sequence v1 and v2 could not meet this need; therefore, a novel approach was devised to develop a dense genetic linkage map, providing the most reliable marker-loci order for the highest possible number of markers. The approach was based on four strategies: (i) the use of multiple full-sib families, (ii) the reduction of missing information through the use of HaploBlocks and alternative calling procedures for single-nucleotide polymorphism (SNP) markers, (iii) the construction of a single backcross-type data set including all families, and (iv) a two-step map generation procedure based on the sequential inclusion of markers. The map comprises 15 417 SNP markers, clustered in 3 K HaploBlock markers spanning 1 267 cM, with an average distance between adjacent markers of 0.37 cM and a maximum distance of 3.29 cM. Moreover, chromosome 5 was oriented according to its homoeologous chromosome 10. This map was useful to improve the apple genome sequence, design the Axiom Apple 480 K SNP array and perform multifamily-based QTL studies. Its collinearity with the genome sequences v1 and v3 are reported. To our knowledge, this is the shortest published SNP map in apple, while including the largest number of markers, families and individuals. This result validates our methodology, proving its value for the construction of integrated linkage maps for any outbreeding species.

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          Genetic linkage maps of Eucalyptus grandis and Eucalyptus urophylla using a pseudo-testcross: mapping strategy and RAPD markers.

          D Grattapaglia, R. Sederoff (1994)
          We have used a "two-way pseudo-testcross" mapping strategy in combination with the random amplified polymorphic DNA (RAPD) assay to construct two moderate density genetic linkage maps for species of Eucalyptus. In the cross between two heterozygous individuals many single-dose RAPD markers will be heterozygous in one parent, null in the other and therefore segregate 1:1 in their F1 progeny following a testcross configuration. Meiosis and gametic segregation in each individual can be directly and efficiently analyzed using RAPD markers. We screened 305 primers of arbitrary sequence, and selected 151 to amplify a total of 558 markers. These markers were grouped at LOD 5.0, theta = 0.25, resulting in the maternal Eucalyptus grandis map having a total of 240 markers into 14 linkage groups (1552 cM) and the paternal Eucalyptus urophylla map with 251 markers in 11 linkage groups (1101 cM) (n = 11 in Eucalyptus). Framework maps ordered with a likelihood support > or = 1000:1 were assembled covering 95% of the estimated genome size in both individuals. Characterization of genome complexity of a sample of 48 mapped random amplified polymorphic DNA (RAPD) markers indicate that 53% amplify from low copy regions. These are the first reported high coverage linkage maps for any species of Eucalyptus and among the first for any hardwood tree species. We propose the combined use of RAPD markers and the pseudo-testcross configuration as a general strategy for the construction of single individual genetic linkage maps in outbred forest trees as well as in any highly heterozygous sexually reproducing living organisms. A survey of the occurrence of RAPD markers in different individuals suggests that the pseudo-testcross/RAPD mapping strategy should also be efficient at the intraspecific level and increasingly so with crosses of genetically divergent individuals. The ability to quickly construct single-tree genetic linkage maps in any forest species opens the way for a shift from the paradigm of a species index map to the heterodox proposal of constructing several maps for individual trees of a population, therefore mitigating the problem of linkage equilibrium between marker and trait loci for the application of marker assisted strategies in tree breeding.
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            A high-density, SNP-based consensus map of tetraploid wheat as a bridge to integrate durum and bread wheat genomics and breeding.

            Marco Maccaferri, Andrea Ricci, Silvio Salvi … (2015)
            Consensus linkage maps are important tools in crop genomics. We have assembled a high-density tetraploid wheat consensus map by integrating 13 data sets from independent biparental populations involving durum wheat cultivars (Triticum turgidum ssp. durum), cultivated emmer (T. turgidum ssp. dicoccum) and their ancestor (wild emmer, T. turgidum ssp. dicoccoides). The consensus map harboured 30 144 markers (including 26 626 SNPs and 791 SSRs) half of which were present in at least two component maps. The final map spanned 2631 cM of all 14 durum wheat chromosomes and, differently from the individual component maps, all markers fell within the 14 linkage groups. Marker density per genetic distance unit peaked at centromeric regions, likely due to a combination of low recombination rate in the centromeric regions and even gene distribution along the chromosomes. Comparisons with bread wheat indicated fewer regions with recombination suppression, making this consensus map valuable for mapping in the A and B genomes of both durum and bread wheat. Sequence similarity analysis allowed us to relate mapped gene-derived SNPs to chromosome-specific transcripts. Dense patterns of homeologous relationships have been established between the A- and B-genome maps and between nonsyntenic homeologous chromosome regions as well, the latter tracing to ancient translocation events. The gene-based homeologous relationships are valuable to infer the map location of homeologs of target loci/QTLs. Because most SNP and SSR markers were previously mapped in bread wheat, this consensus map will facilitate a more effective integration and exploitation of genes and QTL for wheat breeding purposes.
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              Genome-Wide SNP Detection, Validation, and Development of an 8K SNP Array for Apple

              David Chagné, Ross Crowhurst, Michela Troggio … (2012)
              As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC) has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica) breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of ‘Golden Delicious’, SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional), and genomic selection in apple.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Hortic Res
                Journal ID (iso-abbrev): Hortic Res
                Title: Horticulture Research
                Publisher: Nature Publishing Group
                ISSN (Electronic): 2052-7276
                Publication date (Electronic): 23 November 2016
                Publication date Collection: 2016
                Volume: 3
                Page: 16057
                Affiliations
                [1 ]Department of Biosciences, University of Milan , Milan 20133, Italy
                [2 ]Plant Breeding, Wageningen University and Research , Wageningen 6700AJ, The Netherlands
                [3 ]Research and Innovation Centre, Edmund Mach Foundation , San Michele all’Adige 38010, Italy
                [4 ]Biometris, Wageningen University and Research , Wageningen 6700AA, The Netherlands
                [5 ]IRHS, INRA, AGROCAMPUS-Ouest, Université d’Angers, SFR 4207 QUASAV , Beaucouzé 49071, France
                [6 ]Department of Agricultural Sciences, University of Bologna , Bologna 40127, Italy
                [7 ]Department of Molecular Biology, Laimburg Research Centre for Agriculture and Forestry , Ora 39040, Italy
                [8 ]Department of Plant Breeding, Swedish University of Agricultural Sciences , Alnarp 23053, Sweden
                Author notes
                [9]

                Current address: Hendrix Genetics Research, Technology & Services, Boxmeer 5830 AC, The Netherlands.

                Author information
                http://orcid.org/0000-0002-7644-5968
                Article
                Publisher Item ID: hortres201657
                DOI: 10.1038/hortres.2016.57
                PMC ID: 5120355
                SO-VID: f2d8f502-de6c-435c-a33a-21a72571291f
                Copyright © Copyright © 2016 The Author(s)
                License:

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                Date received : 07 October 2016
                Date revision received : 25 October 2016
                Date accepted : 25 October 2016
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