High-throughput estimation of allele frequencies using combined pooled-population sequencing and haplotype-based data processing.

backgroundIn addition to heterogeneity and artificial selection, natural selection is one of the forces used to combat climate change and improve agrobiodiversity in evolutionary plant breeding. Accurate identification of the specific genomic effects of natural selection will likely accelerate transfer between populations. Thus, insights into changes in allele frequency, adequate population size, gene flow and drift are essential. However, observing such effects often involves a trade-off between costs and resolution when a large sample of genotypes for many loci is analysed. Pool genotyping approaches achieve high resolution and precision in estimating allele frequency when sequence coverage is high. Nevertheless, high-coverage pool sequencing of large genomes is expensive.

resultsThree pool samples (n = 300, 300, 288) from a barley backcross population were generated to assess the population's allele frequency. The tested population (BC

conclusionsThe proposed strategy identified the allele frequency of populations with high accuracy at low cost. This is particularly relevant to evolutionary plant breeding of crops with very large genomes, such as barley. Whole-genome low coverage re-sequencing at 0.03 × coverage per genotype accurately estimated the allele frequency when a loci-based haplotyping approach was applied. The implementation of annotated haplotypes capitalises on the biological background and statistical robustness.