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Multiplex sequencing of bacterial artificial chromosomes for assembling complex plant genomes
Sebastian Beier1, Axel Himmelbach1, Thomas Schmutzer1
1Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Stadt Seeland, Germany.
Plant Biotechnology Journal
|January 24, 2016
Summary
We developed a multiplexed pipeline for shotgun sequencing and assembling bacterial artificial chromosomes (BACs). This method efficiently sequences many BACs in parallel, yielding high-quality genome assemblies for complex plant genomes.
Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- Hierarchical shotgun sequencing is crucial for assembling complex plant genomes.
- High-throughput sequencing necessitates parallel processing of numerous large-insert clones.
- Bacterial artificial chromosomes (BACs) are key for constructing reference genomes.
Purpose of the Study:
- To develop a multiplexed pipeline for shotgun sequencing and assembling individual BACs.
- To enable parallel processing of a large number of BACs using Illumina sequencing.
- To improve the contiguity, completeness, and gene space representation of genome assemblies.
Main Methods:
- Developed a multiplexed pipeline for shotgun sequencing of bacterial artificial chromosomes (BACs).
- Utilized the Illumina sequencing platform for high-throughput data generation.
- Employed a parallelized computational pipeline for sequence assembly of individual BACs.
Main Results:
- Successfully sequenced 668 barley BACs in a single Illumina HiSeq 2000 lane.
- Achieved average BAC assemblies with eight scaffolds, representing >98% of genomic inserts.
- Demonstrated superior contiguity, completeness, and gene space representation compared to whole-genome shotgun assemblies.
Conclusions:
- The developed multiplexed pipeline enables rapid, high-quality BAC assembly.
- This approach is suitable for assembling map-based reference sequences of complex plant and animal genomes.
- The methods facilitate efficient sequencing of numerous clones for genome projects.
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