GAAP: Genome-organization-framework-Assisted Assembly Pipeline for prokaryotic genomes

Springer Science and Business Media LLC - Tập 18 - Trang 1-8 - 2017
Lina Yuan1,2,3, Yang Yu4, Yanmin Zhu1, Yulai Li5, Changqing Li6, Rujiao Li1, Qin Ma7, Gilman Kit-Hang Siu8, Jun Yu1, Taijiao Jiang2,3, Jingfa Xiao1, Yu Kang1
1CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
2Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
3Suzhou Institute of Systems Medicine, Suzhou, China
4School of Life Sciences, Liaoning University, Shenyang, China
5Beijing SpeedyCloud Technologies Co., Ltd., Beijing, China
6Department of Otolaryngology, Beijing Geriatric Hospital, Beijing, China
7Department of Agronomy, Horticulture and Plant Science, South Dakota State University, Brookings, USA
8Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China

Tóm tắt

Next-generation sequencing (NGS) technologies have greatly promoted the genomic study of prokaryotes. However, highly fragmented assemblies due to short reads from NGS are still a limiting factor in gaining insights into the genome biology. Reference-assisted tools are promising in genome assembly, but tend to result in false assembly when the assigned reference has extensive rearrangements. Herein, we present GAAP, a genome assembly pipeline for scaffolding based on core-gene-defined Genome Organizational Framework (cGOF) described in our previous study. Instead of assigning references, we use the multiple-reference-derived cGOFs as indexes to assist in order and orientation of the scaffolds and build a skeleton structure, and then use read pairs to extend scaffolds, called local scaffolding, and distinguish between true and chimeric adjacencies in the scaffolds. In our performance tests using both empirical and simulated data of 15 genomes in six species with diverse genome size, complexity, and all three categories of cGOFs, GAAP outcompetes or achieves comparable results when compared to three other reference-assisted programs, AlignGraph, Ragout and MeDuSa. GAAP uses both cGOF and pair-end reads to create assemblies in genomic scale, and performs better than the currently available reference-assisted assembly tools as it recovers more assemblies and makes fewer false locations, especially for species with extensive rearranged genomes. Our method is a promising solution for reconstruction of genome sequence from short reads of NGS.

Tài liệu tham khảo

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