De novo genome assembly of next-generation sequencing data

Abstract

With rapid development of next-generation sequencing (NGS) technologies, de novo genome assembly appears increasingly common. However, inherent features of NGS data pose great challenges for de novo genome assembly. Many genomes, such as Brassica rapa, having undergone three paleo-polyploidy events, contain high content repeats, makes genome assembly of NGS data tougher. In past several years, numerous algorithms have been developed to address the challenges in de novo genome assembly from NGS reads. Here we summarize the main approaches for genome assembly. We also describe several algorithms for each approach. In addition, we compare the performance of existing assemblers in the accuracy and contiguity of assemblies. The comparative analysis shows that there is not any assembler that performs best in all the observed measures, which are also dependent on the dataset used.