Efficient detection and assembly of non-reference DNA sequences with synthetic long reads. Academic Article uri icon

Overview

abstract

  • Recent pan-genome studies have revealed an abundance of DNA sequences in human genomes that are not present in the reference genome. A lion's share of these non-reference sequences (NRSs) cannot be reliably assembled or placed on the reference genome. Improvements in long-read and synthetic long-read (aka linked-read) technologies have great potential for the characterization of NRSs. While synthetic long reads require less input DNA than long-read datasets, they are algorithmically more challenging to use. Except for computationally expensive whole-genome assembly methods, there is no synthetic long-read method for NRS detection. We propose a novel integrated alignment-based and local assembly-based algorithm, Novel-X, that uses the barcode information encoded in synthetic long reads to improve the detection of such events without a whole-genome de novo assembly. Our evaluations demonstrate that Novel-X finds many non-reference sequences that cannot be found by state-of-the-art short-read methods. We applied Novel-X to a diverse set of 68 samples from the Polaris HiSeq 4000 PGx cohort. Novel-X discovered 16 691 NRS insertions of size > 300 bp (total length 18.2 Mb). Many of them are population specific or may have a functional impact.

publication date

  • October 14, 2022

Research

keywords

  • Genome, Human
  • High-Throughput Nucleotide Sequencing

Identity

PubMed Central ID

  • PMC9561269

Scopus Document Identifier

  • 85139880602

Digital Object Identifier (DOI)

  • 10.1093/nar/gkac653

PubMed ID

  • 35924489

Additional Document Info

volume

  • 50

issue

  • 18