Journal Article

Linear time complexity de novo long read genome assembly with GoldRush

Zhang, Emily, Wong, Johnathan, Coombe, Lauren, Sidhu, Puneet, Birol, Inanç, Warren, René L., Nikolić, Vladimir, Nip, Ka Ming

2023

Overview

Current state-of-the-art de novo long read genome assemblers follow the Overlap-Layout-Consensus paradigm. While read-to-read overlap – its most costly step – was improved in modern long read genome assemblers, these tools still often require excessive RAM when assembling a typical human dataset. Our work departs from this paradigm, foregoing all-vs-all sequence alignments in favor of a dynamic data structure implemented in GoldRush, a de novo long read genome assembly algorithm with linear time complexity. We tested GoldRush on Oxford Nanopore Technologies long sequencing read datasets with different base error profiles sourced from three human cell lines, rice, and tomato. Here, we show that GoldRush achieves assembly scaffold NGA50 lengths of 18.3-22.2, 0.3 and 2.6 Mbp, for the genomes of human, rice, and tomato, respectively, and assembles each genome within a day, using at most 54.5 GB of random-access memory, demonstrating the scalability of our genome assembly paradigm and its implementation. Current state-of-the-art de novo long read genome assemblers follow the Overlap-Layout-Consensus paradigm. GoldRush departs from this paradigm, generating highly contiguous assemblies with linear time complexity and using an order of magnitude less RAM than state-of-the-art methods.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 49/23 / 631/114/2785/2302 / 631/114/794 / 631/61/212/2302 / Algorithms / Assembling / Assembly / Cell lines / Complexity / Data structures / Datasets / Genome / Genomes / High-Throughput Nucleotide Sequencing / Humanities and Social Sciences / Humans / Layouts / multidisciplinary / Random access memory / Science / Science (multidisciplinary) / Sequence Analysis, DNA / State of the art / Tomatoes