ArticlePloS one2014
Reliable in silico identification of sequence polymorphisms and their application for extending the genetic map of sugar beet (Beta vulgaris).
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 29 citations in OpenAlex.
- Sugar beet long-read reference assembly of genotype KWS2320.NAR genomics and bioinformatics · 2025Article
- Genomic characterization of a nematode tolerance locus in sugar beet.BMC genomics · 2023Article
- Investigation of the expansin gene family in sugar beet (Beta vulgaris) by the genome-wide level and their expression responses under abiotic stresses.Biologia futura · 2023Article
- Genomic and transcriptomic-based analysis of agronomic traits in sugar beet (Frontiers in plant science · 2022Article
- The effect of heat stress on sugar beet recombination.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Genomes of the wild beets Beta patula and Beta vulgaris ssp. maritima.The Plant journal : for cell and molecular biology · 2019Article
- Two sugar beet chitinase genes,PeerJ · 2018Article
- Crop wild relative populations of Beta vulgaris allow direct mapping of agronomically important genes.Nature communications · 2017Article
- Article
- SBMDb: first whole genome putative microsatellite DNA marker database of sugarbeet for bioenergy and industrial applications.Database : the journal of biological databases and curation · 2015Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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