HIGH-THROUGHPUT SEQUENCING STRATEGIES FOR SINGLE-CELL GENOME ASSEMBLY AND ANNOTATION

Abstract

Background: Single-cell genome sequencing has become a promising approach for genome analysis of cellular heterogeneity, rare genomic variants, and structural genome complexity. Traditional bulk sequencing techniques are often unable to detect low-frequency mutations and cell-to-cell genomic differences, since the genomic data is averaged over a large population of cells.

 Objective: This study was designed to evaluate advanced high-throughput sequencing strategies for accurate single-cell genome assembly and functional genome annotation using integrated sequencing and computational approaches.

Methodology: Whole genome amplification, Illumina sequencing, Oxford Nanopore sequencing, PacBio sequencing, and hybrid genome assembly pipelines were applied to a total of 150 single-cell samples from tumor tissues, microbial populations, and stem cell cultures. Bioinformatics analysis involved genome assembly, variant detection and functional annotation.

Findings:  Hybrid sequencing strategies resulted in 97.8% genome assembly completeness and 95.4% annotation accuracy. Long-read sequencing greatly improved repeat-region assembly and structural variant detection, and 312 novel genomic variants and 148 structural variants were identified across single-cell datasets.

Conclusion: Novel high-throughput sequencing approaches greatly enhance the reconstruction of single-cell genomes, the accuracy of annotation and the interpretation of the genomes. Integrated sequencing and bioinformatics platforms could greatly enhance precision medicine, microbial genomics, cancer genomics, and functional single-cell analysis.