Leveraging whole-genome sequencing to estimate telomere length in plants

Changes in telomere length are increasingly used to indicate species' response to environmental stress across diverse taxa. Despite this broad use, few studies have explored telomere length in plants. Thus, evaluation of new approaches for measuring telomeres in plants is needed. Rapid advances in sequencing approaches and bioinformatic tools now allow estimation of telomere content from whole-genome sequencing (WGS) data, a proxy for telomere length. While telomere content has been quantified extensively using quantitative polymerase chain reaction (qPCR) and WGS in humans, no study to date has compared the effectiveness of WGS in estimating telomere length in plants relative to qPCR approaches. In this study, we use 100 Populus clones re-sequenced using short-read Illumina sequencing to quantify telomere length comparing three different bioinformatic approaches (Computel, K-seek and TRIP) in addition to qPCR. Overall, telomere length estimates varied across different bioinformatic approaches, but were highly correlated across methods for individual genotypes. A positive correlation was observed between WGS estimates and qPCR, however, Computel estimates exhibited the greatest correlation. Computel incorporates genome coverage into telomere length calculations, suggesting that genome coverage is likely important to telomere length quantification when using WGS data. Overall, telomere estimates from WGS provided greater precision and accuracy of telomere length estimates relative to qPCR. The findings suggest WGS is a promising approach for assessing telomere length and, as the field of telomere ecology evolves, may provide added value to assaying response to biotic and abiotic environments for plants needed to accelerate plant breeding and conservation management.