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July 7, 2019

Whole-genome restriction mapping by “subhaploid”-based RAD sequencing: An efficient and flexible approach for physical mapping and genome scaffolding.

Authors: Dou, Jinzhuang and Dou, Huaiqian and Mu, Chuang and Zhang, Lingling and Li, Yangping and Wang, Jia and Li, Tianqi and Li, Yuli and Hu, Xiaoli and Wang, Shi and Bao, Zhenmin

Assembly of complex genomes using short reads remains a major challenge, which usually yields highly fragmented assemblies. Generation of ultradense linkage maps is promising for anchoring such assemblies, but traditional linkage mapping methods are hindered by the infrequency and unevenness of meiotic recombination that limit attainable map resolution. Here we develop a sequencing-based "in vitro" linkage mapping approach (called RadMap), where chromosome breakage and segregation are realized by generating hundreds of "subhaploid" fosmid/bacterial-artificial-chromosome clone pools, and by restriction site-associated DNA sequencing of these clone pools to produce an ultradense whole-genome restriction map to facilitate genome scaffolding. A bootstrap-based minimum spanning tree algorithm is developed for grouping and ordering of genome-wide markers and is implemented in a user-friendly, integrated software package (AMMO). We perform extensive analyses to validate the power and accuracy of our approach in the model plant Arabidopsis thaliana and human. We also demonstrate the utility of RadMap for enhancing the contiguity of a variety of whole-genome shotgun assemblies generated using either short Illumina reads (300 bp) or long PacBio reads (6-14 kb), with up to 15-fold improvement of N50 (~816 kb-3.7 Mb) and high scaffolding accuracy (98.1-98.5%). RadMap outperforms BioNano and Hi-C when input assembly is highly fragmented (contig N50 = 54 kb). RadMap can capture wide-range contiguity information and provide an efficient and flexible tool for high-resolution physical mapping and scaffolding of highly fragmented assemblies. Copyright © 2017 Dou et al.

Journal: Genetics
DOI: 10.1534/genetics.117.200303
Year: 2017

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