IAGS: Inferring Ancestor Genome Structure under a Wide Range of Evolutionary Scenarios

Author:

Gao Shenghan12,Yang Xiaofei234,Sun Jianyong5ORCID,Zhao Xixi4,Wang Bo12,Ye Kai12467ORCID

Affiliation:

1. School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China

2. MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China

3. School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China

4. Genome Institute, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

5. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi, China

6. School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, China

7. Faculty of Science, Leiden University, Leiden, The Netherlands

Abstract

Abstract Significant improvements in genome sequencing and assembly technology have led to increasing numbers of high-quality genomes, revealing complex evolutionary scenarios such as multiple whole-genome duplication events, which hinders ancestral genome reconstruction via the currently available computational frameworks. Here, we present the Inferring Ancestor Genome Structure (IAGS) framework, a novel block/endpoint matching optimization strategy with single-cut-or-join distance, to allow ancestral genome reconstruction under both simple (single-copy ancestor) and complex (multicopy ancestor) scenarios. We evaluated IAGS with two simulated data sets and applied it to four different real evolutionary scenarios to demonstrate its performance and general applicability. IAGS is available at https://github.com/xjtu-omics/IAGS.

Publisher

Oxford University Press (OUP)

Subject

Genetics,Molecular Biology,Ecology, Evolution, Behavior and Systematics

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