Whole Genome Mapping: A New Paradigm for Genomic Characterization

Genomic technologies such as DNA sequencing and microarrays have transformed the field of genomics by making the underlying information that encodes for life available for analysis.  The advent of next generation sequencing (NGS) has continued to evolve by increasing sequencing throughput while also decreasing run times thereby making sequencing more affordable than ever before.  Furthermore, other genomic technologies like microarrays allow for a different way to analyze plant and animal genomes and can provide an additional and unique view into other genome variations that sequencing is unable to offer.   Yet, even with all the advances with these technologies, there are still limitations as to what can be discovered due to the sequencing read lengths, genome structure, sequence assembly algorithms, and other technology specific limitations.

Whole Genome Mapping is a sequence-independent technology that produces single-molecule physical mapping reads of 150 kb to 3 Mb in length with sized and ordered restriction fragments that can be used to improve DNA sequence assembly quality, and to identify structural variants and DNA sequencing misassemblies.  Whole Genome Mapping has been applied to a range of organisms including plant and animal genomes with the ability to improve DNA sequence assembly quality and identify genetic variations.  The Genome-Builder application of Whole Genome Mapping inputs both DNA sequence scaffolds as well as Whole Genome Mapping data in a hybrid approach to produce higher quality assemblies resulting in more accurate downstream plant and animal genome analysis.  In another application, Whole Genome Mapping data is assembled de novo to yield a high resolution ordered physical restriction map.  Recent data demonstrate that Whole Genome Mapping data can be used to effectively construct near chromosome level assemblies to validate DNA sequence assemblies and detect structural variations including balanced rearrangements such as inversions and translocations, which are challenging to detect by other technologies.