Telogator: a method for reporting chromosome-specific telomere lengths from long reads

Author:

Stephens Zachary1,Ferrer Alejandro2,Boardman Lisa3,Iyer Ravishankar K1,Kocher Jean-Pierre A4ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign , Urbana, IL 61801, USA

2. Division of Hematology, Mayo Clinic, Rochester, MN 55902, USA

3. Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55902, USA

4. Department of Quantitative Health Sciences, Mayo Clinic , Rochester, MN 55902, USA

Abstract

Abstract Motivation Telomeres are the repetitive sequences found at the ends of eukaryotic chromosomes and are often thought of as a ‘biological clock,’ with their average length shortening during division in most cells. In addition to their association with senescence, abnormal telomere lengths are well known to be associated with multiple cancers, short telomere syndromes and as risk factors for a broad range of diseases. While a majority of methods for measuring telomere length will report average lengths across all chromosomes, it is known that aberrations in specific chromosome arms are biomarkers for certain diseases. Due to their repetitive nature, characterizing telomeres at this resolution is prohibitive for short read sequencing approaches, and is challenging still even with longer reads. Results We present Telogator: a method for reporting chromosome-specific telomere length from long read sequencing data. We demonstrate Telogator’s sensitivity in detecting chromosome-specific telomere length in simulated data across a range of read lengths and error rates. Telogator is then applied to 10 germline samples, yielding a high correlation with short read methods in reporting average telomere length. In addition, we investigate common subtelomere rearrangements and identify the minimum read length required to anchor telomere/subtelomere boundaries in samples with these haplotypes. Availability and implementation Telogator is written in Python3 and is available at github.com/zstephens/telogator. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Cancer Institute

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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