Effects of ascertainment bias and marker number on estimations of barley diversity from high-throughput SNP genotype data

Theor Appl Genet. 2010 May;120(8):1525-34. doi: 10.1007/s00122-010-1273-1. Epub 2010 Feb 16.


The capability of molecular markers to provide information of genetic structure is influenced by their number and the way they are chosen. This study evaluates the effects of single nucleotide polymorphism (SNP) number and selection strategy on estimates of germplasm diversity and population structure for different types of barley germplasm, namely cultivar and landrace. One hundred and sixty-nine barley landraces from Syria and Jordan and 171 European barley cultivars were genotyped with 1536 SNPs. Different subsets of 384 and 96 SNPs were selected from the 1536 set, based on their ability to detect diversity in landraces or cultivated barley in addition to corresponding randomly chosen subsets. All SNP sets except the landrace-optimised subsets underestimated the diversity present in the landrace germplasm, and all subsets of SNP gave similar estimates for cultivar germplasm. All marker subsets gave qualitatively similar estimates of the population structure in both germplasm sets, but the 96 SNP sets showed much lower data resolution values than the larger SNP sets. From these data we deduce that pre-selecting markers for their diversity in a germplasm set is very worthwhile in terms of the quality of data obtained. Second, we suggest that a properly chosen 384 SNP subset gives a good combination of power and economy for germplasm characterization, whereas the rather modest gain from using 1536 SNPs does not justify the increased cost and 96 markers give unacceptably low performance. Lastly, we propose a specific 384 SNP subset as a standard genotyping tool for middle-eastern landrace barley.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Expressed Sequence Tags
  • Genes, Plant
  • Genetic Markers
  • Genetic Variation
  • Genome, Plant
  • Genotype
  • Hordeum / genetics*
  • Models, Genetic
  • Models, Statistical
  • Polymorphism, Single Nucleotide*
  • Sequence Analysis, DNA
  • Species Specificity


  • Genetic Markers