Pooled mapping: an efficient method of calling variations for population samples with low-depth resequencing data

摘要

Whole-genome resequencing (WGR) is a high-throughput way to determine genomic variations in breeding-related research. Accuracy and sensitivity are two of the most important issues in variation calling of WGR, especially for samples with low-depth resequencing data, which are used to reduce cost and save time in studies as survey of core germplasms from natural populations or genome-based breeding selection in segregation populations. An approach called pooled mapping was developed to call variations from low-depth resequencing data of natural or segregation populations. It is highly accurate and sensitive. First, pooled mapping creates a library of confident polymorphic loci in genomes of the population; then, the genotypes are called out at these confident loci for each sample in an efficient manner. The reliability of this pooled mapping method was confirmed using simulated datasets, real resequencing data and experimental genotyping. With onefold simulated resequencing data, results showed that pooled mapping identified SNPs in high accuracy (99.59 %) and sensitivity (93 %), compared to the commonly used method (accuracy: 29 %; sensitivity: 56 %). For the real low-depth resequencing data (approximate to 0.8x) of 281 B. oleracea accessions, four loci corresponding to 1063 sites were selected for KASP genotyping to confirm the performance of pooled mapping. We found for all the 875 homozygous sites analyzed, pooled mapping achieved accuracy as 98.24 % and a sensitivity as 90.97 %. In conclusion, pooled mapping is an efficient means of determining reliable genomic variations with limited resequencing data for population samples. It will be a valuable tool in population genomic analysis and genome-based breeding research.