Abstract
Molecular markers are a highly valuable tool for creating genetic maps. Like in many other crops, sugar beet (Beta vulgaris L.) breeding is increasingly supported by the application of such genetic markers. Single nucleotide polymorphism (SNP) based markers have a high potential for automated analysis and high-throughput genotyping. We developed a bioinformatics workflow that uses Sanger and 2nd-generation sequence data for detection, evaluation and verification of new transcript-associated SNPs from sugar beet. RNAseq data from one parent of an established mapping population were produced by 454-FLX sequencing and compared to Sanger ESTs derived from the other parent. The workflow established for SNP detection considers the quality values of both types of reads, provides polymorphic alignments as well as selection criteria for reliable SNP detection and allows painless generation of new genetic markers within genes. We obtained a total of 14,323 genic SNPs and InDels. According to empirically optimised settings for the quality parameters, we classified these SNPs into four usability categories. Validation of a subset of the in silico detected SNPs by genotyping the mapping population indicated a high success rate of the SNP detection. Finally, a total of 307 new markers were integrated with existing data into a new genetic map of sugar beet which offers improved resolution and the integration of terminal markers.
Highlights
The biennial plant sugar beet is a member of the order Caryophyllales and is grown commercially for sugar production mainly in the temperate climate zones
A genetic map that had been tightly linked to a physical map in BACs was made available [7], as well as the first sugar beet reference transcriptome based on RNAseq data [8]
For single nucleotide polymorphisms (SNP) genotyping by amplicon sequencing genomic DNA was extracted from the parents K1P1 and K1P2 of the KWS1 mapping population, the K1F1 genotype as well as the F2 genotypes of the KWS1 mapping population
Summary
The biennial plant sugar beet is a member of the order Caryophyllales and is grown commercially for sugar production mainly in the temperate climate zones. During the last decade sugar beet was target of several genetic mapping approaches [3,5]. A genetic map that had been tightly linked to a physical map in BACs was made available [7], as well as the first sugar beet reference transcriptome based on RNAseq data [8]. Genome sequence assemblies from five double haploid sugar beet lines were published, including the high-quality genome sequence of the reference genotype KWS2320 [3]. This reference assembly comprises 566.6 Mbp and displays a N50 size of 1,7 Mbp
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