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High-quality genome (re)assembly using chromosomal contact data.

Hervé Marie-Nelly1, Martial Marbouty2, Axel Cournac2

  • 11] Institut Pasteur, Department of Genomes and Genetics, Groupe Régulation Spatiale des Génomes, 75015 Paris, France [2] CNRS, UMR 3525, 75015 Paris, France [3] Institut Pasteur, Unité Imagerie et Modélisation, 75015 Paris, France [4] CNRS, URA 2582, 75015 Paris, France [5] Sorbonne Universités, UPMC Univ Paris06, IFD, 4 place Jussieu, 75252 Paris, France.

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|December 18, 2014
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Summary
This summary is machine-generated.

Genome assemblies can now be finished using chromosome conformation capture (3C) data. The GRAAL algorithm accurately reconstructs genome structures, improving draft genome assemblies and identifying variations.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Draft genome assemblies are often incomplete due to the cost and time required for gap closure.
  • Unfinished genomes limit downstream analyses and understanding of genomic structure and function.

Purpose of the Study:

  • To present a computational approach, GRAAL, for improving genome assembly quality using chromosome conformation capture (3C) data.
  • To demonstrate GRAAL's ability to accurately represent complex genomic regions and reconstruct chromosomes.

Main Methods:

  • Utilized genome-wide 3C data to infer chromosomal contact information.
  • Developed a polymer physics-based algorithm (GRAAL) to determine the most probable genome structure.
  • Validated GRAAL on yeast (Saccharomyces cerevisiae, T. reesei) and human chromosome assemblies.

Main Results:

  • GRAAL successfully generated high-quality genome assemblies, accurately representing repetitive and duplicated regions.
  • The algorithm identified known and novel chromosomal structural variations in yeast isolates.
  • GRAAL accurately reconstructed human chromosomes from both in silico fragments and de novo assembled contigs.
  • Performance of GRAAL was favorably compared to existing related methods.

Conclusions:

  • 3C data combined with the GRAAL algorithm offers an effective solution for finishing draft genome assemblies.
  • GRAAL provides a probabilistic interpretation of genome structures and accurately resolves complex genomic variations.
  • This approach significantly enhances the quality and completeness of genome assemblies across different species.