Detection of structural variations in densely-labelled optical DNA barcodes: A hidden Markov model approach
Artikel i vetenskaplig tidskrift, 2021

Large-scale genomic alterations play an important role in disease, gene expression, and chromosome evolution. Optical DNA mapping (ODM), commonly categorized into sparsely-labelled ODM and densely-labelled ODM, provides sequence-specific continuous intensity profiles (DNA barcodes) along single DNA molecules and is a technique well-suited for detecting such alterations. For sparsely-labelled barcodes, the possibility to detect large genomic alterations has been investigated extensively, while densely-labelled barcodes have not received as much attention. In this work, we introduce HMMSV, a hidden Markov model (HMM) based algorithm for detecting structural variations (SVs) directly in densely-labelled barcodes without access to sequence information. We evaluate our approach using simulated data-sets with 5 different types of SVs, and combinations thereof, and demonstrate that the method reaches a true positive rate greater than 80% for randomly generated barcodes with single variations of size 25 kilobases (kb). Increasing the length of the SV further leads to larger true positive rates. For a real data-set with experimental barcodes on bacterial plasmids, we successfully detect matching barcode pairs and SVs without any particular assumption of the types of SVs present. Instead, our method effectively goes through all possible combinations of SVs. Since ODM works on length scales typically not reachable with other techniques, our methodology is a promising tool for identifying arbitrary combinations of genomic alterations.

Författare

Albertas Dvirnas

Lunds universitet

Callum L. Stewart

Lunds universitet

King's College London

Vilhelm Müller

Chalmers, Biologi och bioteknik, Kemisk biologi

Santosh Kumar Bikarolla

Chalmers, Biologi och bioteknik, Kemisk biologi

Ulster University

Karolin Frykholm

Chalmers, Biologi och bioteknik, Kemisk biologi

L. Sandegren

Uppsala universitet

Erik Kristiansson

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Fredrik Westerlund

Chalmers, Biologi och bioteknik, Kemisk biologi

Tobias Ambjörnsson

Lunds universitet

PLoS ONE

1932-6203 (ISSN)

Vol. 16 11 November e0259670

Ämneskategorier

Bioinformatik (beräkningsbiologi)

Bioinformatik och systembiologi

Genetik

DOI

10.1371/journal.pone.0259670

Mer information

Senast uppdaterat

2021-11-25