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Updated: Aug 11, 2025
11:59
Competitive Genomic Screens of Barcoded Yeast Libraries
Published on: August 11, 2011
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A practical comparison of the next-generation sequencing platform and assemblers using yeast genome
Min-Seung Jeon1, Da Min Jeong1, Huijeong Doh1
1Department of Life Science, Chung-Ang University, Seoul, Korea.
Life Science Alliance
|February 6, 2023
Summary
Choosing the right genome assembly pipeline is crucial for research. This study found Oxford Nanopore sequencing offers more continuous assemblies, while Illumina NovaSeq excels in accuracy for second-generation sequencing pipelines.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Whole-genome assembly from sequencing data is essential for genome-wide research.
- Selecting optimal assembly pipelines is challenging due to species-specific genomic properties.
- This study focuses on sequencing platform and assembly algorithm characteristics.
Purpose of the Study:
- To evaluate and compare different de novo assembly pipelines using various sequencing platforms and algorithms.
- To identify the most effective strategies for assembling repetitive genomes, using yeast as a model.
- To provide insights into selecting optimal assembly pipelines based on sequencing technology and computational parameters.
Main Methods:
- Constructed 212 draft and polished de novo assemblies using diverse sequencing platforms (Oxford Nanopore, PacBio Sequel, Illumina NovaSeq 6000, MGI DNBSEQ-T7) and assembly algorithms.
- Analyzed assembly contiguity, accuracy, and error profiles.
- Investigated the relationship between computational time, read length, and coverage depth.
Main Results:
- Oxford Nanopore (R7.3 flow cells) produced more continuous assemblies than PacBio Sequel, despite homopolymer errors and chimeric contigs.
- Illumina NovaSeq 6000 yielded more accurate and continuous assemblies in second-generation sequencing-first pipelines.
- MGI DNBSEQ-T7 provided cost-effective and accurate reads for the polishing stage.
Conclusions:
- Sequencing platform choice significantly impacts genome assembly quality and contiguity.
- A combination of platforms and algorithms, considering factors like read accuracy and computational resources, is key for optimal assembly.
- The findings offer guidance for selecting efficient de novo assembly strategies for repetitive genomes.
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