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Scaffolding of long read assemblies using long range contact information
Jay Ghurye1, Mihai Pop1, Sergey Koren2
1Department of Computer Science, University of Maryland, 20742 College Park, Maryland, USA.
BMC Genomics
|July 14, 2017
Summary
This study introduces SALSA, a new algorithm that improves genome assembly contiguity using Hi-C data. SALSA generates more accurate chromosome-level scaffolds than existing methods.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Long read sequencing technologies significantly improve de novo genome assembly contiguity.
- Current assemblies often lack chromosome-level completeness, hindering full genome reconstruction.
- Strategies utilizing long-range genomic contact information are needed to achieve chromosome-level assemblies.
Purpose of the Study:
- To develop a scalable and efficient scaffolding method for enhancing genome assembly contiguity.
- To leverage genome-wide chromatin interaction data, such as Hi-C, for improved assembly.
- To create chromosome-level genome assemblies from long-read data.
Main Methods:
- Developed a novel algorithm, SALSA (Sequencing Assembly Linkage Scaffolding Algorithm), for genome scaffolding.
- Utilized Hi-C data to infer long-range chromatin interactions.
- Applied the algorithm to de novo long-read genome assemblies.
Main Results:
- Demonstrated the algorithm's effectiveness on human and goat genome assemblies.
- Compared SALSA-generated scaffolds against those from LACHESIS using multiple metrics.
- SALSA successfully increased the contiguity of de novo long-read genome assemblies.
Conclusions:
- The SALSA algorithm provides more accurate chromosome-level scaffolds compared to existing methods like LACHESIS.
- This advancement facilitates the generation of more complete and contiguous genome assemblies.
- SALSA represents a significant improvement in scaffolding for long-read genome assembly projects.
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