A Strategy of Assessing Gene Copy Number Differentiation Between Populations Using Ultra-Fast De Novo Assembly of Next-Generation Sequencing Data.

Abstract

Gene duplication and loss play pivotal roles in the evolutionary dynamics of genomes, contributing to species phenotypic diversity and adaptation. However, detecting copy number variations (CNVs) in homoploid populations and newly-diverged species using short reads from next-generation sequencing (NGS) with traditional methods can often be challenging due to uneven read coverage caused by variations in GC content and the presence of repetitive sequences. To address these challenges, we developed a novel pipeline, ST4gCNV, which leverages ultra-fast de novo assemblies of NGS data to detect gene-specific CNVs between populations. The pipeline effectively reduces the variance of read coverage due to technical factors such as GC bias, providing a reliable CNV detection with a minimum sequencing depth of 10. We successfully apply ST4gCNV to the resequencing analysis of homoploid species Nelumbo nucifera and Nelumbo lutea (lotus). We reveal significant CNV-driven differentiation between these species, particularly in genes related to petal colour diversity such as those involved in the anthocyanin pathway. By highlighting the extensive gene duplication and loss events in Nelumbo, our study demonstrates the utility of ST4gCNV in population genomics and underscores its potential of integrating genomic CNV analysis with traditional SNP-based resequencing analysis.