Sequence-Based Genotyping for Marker Discovery and Co-Dominant Scoring in Germplasm and Populations

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n = 222 samples) and lettuce (n = 87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike

High resolution map of eggplant (Solanum melongena) reveals extensive chromosome rearrangement in domesticated members of the Solanaceae

A linkage map of eggplant was constructed for an interspecific F2 population derived from a cross between Solanum linnaeanum MM195 and S. melongena MM738. The map contains 400 AFLP® (amplified fragment length polymorphism), 348 RFLP (restriction fragment length polymorphism) and 116 COSII (conserved ortholog set) markers. The 864 mapped markers encompass 12 linkage groups, span 1,518 cM and are spaced at an average interval of 1.8 cM. Use of orthologous markers allowed confirmation of the established syntenic relationships between eggplant and tomato chromosomes and helped delineate the nature of the 33 chromosomal rearrangements and 11 transpositions distinguishing the two species. This genetic map provides a 2- to 3-fold improvement in marker density compared to previously published interspecific maps. Because the interspecific mapping population is rich in morphological variation, this greater genome saturation will be useful for QTL (quantitative trait locus) analyses. The recent release of the tomato genome sequence will provide additional opportunities for exploiting this map for comparative genomics and crop improvement.Scientific and Technical Research Council of Turkey (TUBITAK 104T224); DeRuiterZonen C.V.; Rijk Zwaan Zaadteelt; Zaadhandel B.V.; Vilmorin Clause Cie S.A

SNPSelect: A scalable and flexible targeted sequence-based genotyping solution.

In plant breeding the use of molecular markers has resulted in tremendous improvement of the speed with which new crop varieties are introduced into the market. Single Nucleotide Polymorphism (SNP) genotyping is routinely used for association studies, Linkage Disequilibrium (LD) and Quantitative Trait Locus (QTL) mapping studies, marker-assisted backcrosses and validation of large numbers of novel SNPs. Here we present the KeyGene SNPSelect technology, a scalable and flexible multiplexed, targeted sequence-based, genotyping solution. The multiplex composition of SNPSelect assays can be easily changed between experiments by adding or removing loci, demonstrating their content flexibility. To demonstrate this versatility, we first designed a 1,056-plex maize assay and genotyped a total of 374 samples originating from an F2 and a Recombinant Inbred Line (RIL) population and a maize germplasm collection. Next, subsets of the most informative SNP loci were assembled in 384-plex and 768-plex assays for further genotyping. Indeed, selection of the most informative SNPs allows cost-efficient yet highly informative genotyping in a custom-made fashion, with average call rates between 88.1% (1,056-plex assay) and 99.4% (384-plex assay), and average reproducibility rates between duplicate samples ranging from 98.2% (1056-plex assay) to 99.9% (384-plex assay). The SNPSelect workflow can be completed from a DNA sample to a genotype dataset in less than three days. We propose SNPSelect as an attractive and competitive genotyping solution to meet the targeted genotyping needs in fields such as plant breeding

Bioinformatics analysis workflow for SBG.

<p>The Illumina data are first processed to remove low quality reads. The reference sequences are generated by clustering the unique reads present within the dataset. The reads are subsequently aligned to the reference sequences and variation called using the GATK Unified Genotyper. Lastly, the final set of SNPs and genotypes are generated by removing SNPs not meeting the threshold for percentage of missing data and expected genotypic frequencies.</p

Variant calling for the arabidopsis and lettuce sequence datasets.

<p>Variant calling for the arabidopsis and lettuce sequence datasets.</p

Overview of SBG.

<p>(A) The sequencing complexity of genomic DNA is reduced using a combination of rare and frequent cutting enzymes. (B) Sequencing adapters containing sample identification tags are ligated to the restriction fragments to construct SBG libraries. SBG libraries are amplified and sequenced using Illumina sequencing platforms. Only read 1 will be sequenced for single-end sequencing, while both read 1 and read 2 will be sequenced for paired-end sequencing. (C) SNPs are mined between the samples and simultaneously genotyped using the SBG bioinformatics analysis workflow.</p

Parent-based SNP genotyping in the arabidopsis and lettuce sequence datasets after removing SNPs displaying extreme genotypic frequencies and an excessive number of missing genotypes.

<p>Parent-based SNP genotyping in the arabidopsis and lettuce sequence datasets after removing SNPs displaying extreme genotypic frequencies and an excessive number of missing genotypes.</p