Abstract

Conifer genomes are characterized by their large size and high abundance of repetitive material, making large-scale genotyping in conifers complicated and expensive. One of the consequences of this is that it has been difficult to generate data on genome-wide levels of genetic variation. To date, researchers have mainly employed various complexity reduction techniques to assess genetic variation across the genome in different conifer species. These methods tend to capture variation in a relatively small subset of a typical conifer genome and it is currently not clear how representative such results are. Here we take advantage of data generated in the first large-scale re-sequencing effort in Norway spruce and assess how well two commonly used complexity reduction methods, targeted capture probes and genotyping by sequencing perform in capturing genome-wide variation in Norway spruce. Our results suggest that both methods perform reasonably well for assessing genetic diversity and population structure in Norway spruce (Picea abies (L.) H. Karst.). Targeted capture probes were slightly more effective than GBS, likely due to them targeting known genomic regions whereas the GBS data contains a substantially greater fraction of repetitive regions, which sometimes can be problematic for assessing genetic diversity. In conclusion, both methods are useful for genotyping large numbers of samples and they greatly reduce the cost involved with genotyping a species with such a complex genome as Norway spruce.

Keywords

genetic diversity; genotyping; GBS; Norway spruce; Picea abies

Published in

Forests
2020, volume: 11, number: 11, article number: 1185
Publisher: MDPI

Authors' information