Comprehensive Evaluation of Genome Gap-Filling Tools Utilizing Long Reads

Author:

Zhao Xianjia12,Liu Fang13ORCID,Pan Weihua2

Affiliation:

1. Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China

2. Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences (ICR, CAAS), Shenzhen 518120, China

3. National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China

Abstract

The availability of the complete genome of an organism plays a crucial role in the comprehensive analysis of the entire biological entity. Despite the rapid advancements in sequencing technologies, the inherent complexities of genomes inevitably lead to gaps during genome assembly. To obviate this, numerous genome gap-filling tools utilizing long reads have emerged. However, a comprehensive evaluation of these tools is currently lacking. In this study, we evaluated seven software under various ploidy levels and different data generation methods, and assessing them using QUAST and two additional criteria such as accuracy and completeness. Our findings revealed that the performance of the different tools varied across diverse ploidy levels. Based on accuracy and completeness, FGAP emerged as the top-performing tool, excelling in both haploid and tetraploid scenarios. This evaluation of commonly used genome gap-filling tools aims to provide users with valuable insights for tool selection, assisting them in choosing the most suitable genome gap-filling tool for their specific needs.

Funder

National Natural Science Foundation of China

Shenzhen Science and Technology Program

Innovation Program of the Chinese Academy of Agricultural Sciences

Publisher

MDPI AG

Subject

Genetics (clinical),Genetics

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