Reliable in silico identification of sequence polymorphisms and their application for extending the genetic map of sugar beet (Beta vulgaris)

PLoS One. 2014 Oct 10;9(10):e110113. doi: 10.1371/journal.pone.0110113. eCollection 2014.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Beta vulgaris / genetics*
  • Chromosome Mapping
  • Computational Biology
  • Evolution, Molecular
  • Expressed Sequence Tags
  • Genetic Loci
  • Genetic Markers
  • Genome, Plant
  • Genomics
  • Polymorphism, Genetic*
  • Polymorphism, Single Nucleotide
  • Reproducibility of Results
  • Sequence Analysis, DNA

Substances

  • Genetic Markers

Grant support

This work was supported by the Ministry of Education and Science (BMBF) grant ‘Verbundprojekt GABI-Beet Physical map’, FKZ 0313127A and FKZ 0313127D and by the ‘Verbundprojekt GABI BeetSeq’, FKZ 0315069A and FKZ 0315069B. Co-authors BS and DB are employed by KWS Saat AG. KWS Saat AG provided support in the form of salaries for authors BS and DB, but did not have any additional role in the study design, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. TK is employed by Syngenta Seeds AB. Syngenta Seeds AB provided support in the form of salary for author TK, but did not have any additional role in the study design, decision to publish, or preparation of the manuscript. The specific role of this author is articulated in the ‘author contributions’ section.