Mengyang Xu1,2,3, Lidong Guo1,4, Shengqiang Gu1,4, Ou Wang3,5, Rui Zhang1, Brock A Peters3,6, Guangyi Fan1,3, Xin Liu1,2,3,7, Xun Xu3,7, Li Deng1,2,3, Yongwei Zhang3,6. 1. BGI-Qingdao, BGI-Shenzhen, 2 Hengyunshan Road, West Coast New Area, Qingdao, 266426, China. 2. State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Building 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China. 3. BGI-Shenzhen, Building 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China. 4. BGI Education Center, University of Chinese Academy of Sciences, Building 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China. 5. MGI, BGI-Shenzhen, Building 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China. 6. Complete Genomics Inc., 2904 Orchard Pkwy, San Jose, CA 95134, USA. 7. China National GeneBank, BGI-Shenzhen, Jinsha Road, Dapeng New District, Shenzhen, 518120, China.
Abstract
BACKGROUND: Analyses that use genome assemblies are critically affected by the contiguity, completeness, and accuracy of those assemblies. In recent years single-molecule sequencing techniques generating long-read information have become available and enabled substantial improvement in contig length and genome completeness, especially for large genomes (>100 Mb), although bioinformatic tools for these applications are still limited. FINDINGS: We developed a software tool to close sequence gaps in genome assemblies, TGS-GapCloser, that uses low-depth (∼10×) long single-molecule reads. The algorithm extracts reads that bridge gap regions between 2 contigs within a scaffold, error corrects only the candidate reads, and assigns the best sequence data to each gap. As a demonstration, we used TGS-GapCloser to improve the scaftig NG50 value of 3 human genome assemblies by 24-fold on average with only ∼10× coverage of Oxford Nanopore or Pacific Biosciences reads, covering with sequence data up to 94.8% gaps with 97.7% positive predictive value. These improved assemblies achieve 99.998% (Q46) single-base accuracy with final inserted sequences having 99.97% (Q35) accuracy, despite the high raw error rate of single-molecule reads, enabling high-quality downstream analyses, including up to a 31-fold increase in the scaftig NGA50 and up to 13.1% more complete BUSCO genes. Additionally, we show that even in ultra-large genome assemblies, such as the ginkgo (∼12 Gb), TGS-GapCloser can cover 71.6% of gaps with sequence data. CONCLUSIONS: TGS-GapCloser can close gaps in large genome assemblies using raw long reads quickly and cost-effectively. The final assemblies generated by TGS-GapCloser have improved contiguity and completeness while maintaining high accuracy. The software is available at https://github.com/BGI-Qingdao/TGS-GapCloser.
BACKGROUND: Analyses that use genome assemblies are critically affected by the contiguity, completeness, and accuracy of those assemblies. In recent years single-molecule sequencing techniques generating long-read information have become available and enabled substantial improvement in contig length and genome completeness, especially for large genomes (>100 Mb), although bioinformatic tools for these applications are still limited. FINDINGS: We developed a software tool to close sequence gaps in genome assemblies, TGS-GapCloser, that uses low-depth (∼10×) long single-molecule reads. The algorithm extracts reads that bridge gap regions between 2 contigs within a scaffold, error corrects only the candidate reads, and assigns the best sequence data to each gap. As a demonstration, we used TGS-GapCloser to improve the scaftig NG50 value of 3 human genome assemblies by 24-fold on average with only ∼10× coverage of Oxford Nanopore or Pacific Biosciences reads, covering with sequence data up to 94.8% gaps with 97.7% positive predictive value. These improved assemblies achieve 99.998% (Q46) single-base accuracy with final inserted sequences having 99.97% (Q35) accuracy, despite the high raw error rate of single-molecule reads, enabling high-quality downstream analyses, including up to a 31-fold increase in the scaftig NGA50 and up to 13.1% more complete BUSCO genes. Additionally, we show that even in ultra-large genome assemblies, such as the ginkgo (∼12 Gb), TGS-GapCloser can cover 71.6% of gaps with sequence data. CONCLUSIONS:TGS-GapCloser can close gaps in large genome assemblies using raw long reads quickly and cost-effectively. The final assemblies generated by TGS-GapCloser have improved contiguity and completeness while maintaining high accuracy. The software is available at https://github.com/BGI-Qingdao/TGS-GapCloser.
Authors: Felipe A Simão; Robert M Waterhouse; Panagiotis Ioannidis; Evgenia V Kriventseva; Evgeny M Zdobnov Journal: Bioinformatics Date: 2015-06-09 Impact factor: 6.937
Authors: Justin M Zook; Brad Chapman; Jason Wang; David Mittelman; Oliver Hofmann; Winston Hide; Marc Salit Journal: Nat Biotechnol Date: 2014-02-16 Impact factor: 54.908
Authors: Grace X Y Zheng; Billy T Lau; Michael Schnall-Levin; Mirna Jarosz; John M Bell; Christopher M Hindson; Sofia Kyriazopoulou-Panagiotopoulou; Donald A Masquelier; Landon Merrill; Jessica M Terry; Patrice A Mudivarti; Paul W Wyatt; Rajiv Bharadwaj; Anthony J Makarewicz; Yuan Li; Phillip Belgrader; Andrew D Price; Adam J Lowe; Patrick Marks; Gerard M Vurens; Paul Hardenbol; Luz Montesclaros; Melissa Luo; Lawrence Greenfield; Alexander Wong; David E Birch; Steven W Short; Keith P Bjornson; Pranav Patel; Erik S Hopmans; Christina Wood; Sukhvinder Kaur; Glenn K Lockwood; David Stafford; Joshua P Delaney; Indira Wu; Heather S Ordonez; Susan M Grimes; Stephanie Greer; Josephine Y Lee; Kamila Belhocine; Kristina M Giorda; William H Heaton; Geoffrey P McDermott; Zachary W Bent; Francesca Meschi; Nikola O Kondov; Ryan Wilson; Jorge A Bernate; Shawn Gauby; Alex Kindwall; Clara Bermejo; Adrian N Fehr; Adrian Chan; Serge Saxonov; Kevin D Ness; Benjamin J Hindson; Hanlee P Ji Journal: Nat Biotechnol Date: 2016-02-01 Impact factor: 54.908
Authors: Brendan J Pinto; Shannon E Keating; Stuart V Nielsen; Daniel P Scantlebury; Juan D Daza; Tony Gamble Journal: J Hered Date: 2022-07-09 Impact factor: 2.679