Genomic variability arises at a range of scales, from single nucleotides to entire chromosomes. Structural variations, such as translocations and inversions, typically involve rearrangements of tens of kilobase pairs to megabase pairs of DNA. While next-generation sequencing has revolutionized many areas of genomics, it has had less impact on the analysis of structural variations due to short read lengths. Similar issues arise when sequencing is used for cancer diagnosis, owing to the structural complexity of cancer genomes. Thus, a pressing need exists for genome mapping technologies that provide large-scale genomic information (millions of bases) that complements the gold standard generated on the Illumina short-read sequencing platform (hundreds of bases). In the first three-year period of this R01 award, the University of Minnesota and BioNano Genomics have been collaborating to establish the fundamental basis for one such technology: genome mapping in nanochannels arrays. Genome mapping in nanochannel arrays works with massive intact genomic DNA molecules, up to almost a megabase in size, that have been barcoded with sequence-specific labels. These barcoded molecules are extended by confinement in a 45 nm nanochannel, and the barcode is read by fluorescence microscopy. To date, we have developed a comprehensive understanding of the thermal fluctuations of the labeled DNA, which set the lower bound on the measurement error, as well as a suite of tools that allow us to detect (and predict) physical rearrangement of DNA in the nanochannel. The next three- year period of this award builds on our advances to accomplish two new Specific Aims.
Specific Aim 1 moves beyond homopolymer models of DNA to incorporate sequence-dependent micromechanics into the engineering models for both prediction of device performance and analysis of experimental data. The corresponding experiments open up a new measurement modality that (i) associates structural variations with GC content without requiring the genome sequence and (ii) better resolves regions of the genome where the nicking barcodes are similar.
Specific Aim 2 will lead to improved device performance by tuning the buffer composition to optimize the balance between measurement resolution and throughput. In completing these SAs, we will continue the innovative engineering of genome mapping technologies from the first grant period, where we leverage the unique capabilities of both teams to advance our fundamental understanding of confined polymers while providing an engineering basis for the emerging genome mapping technology and developing new functionalities for genome mapping. In addition to publishing fundamental results, this project will impact the community at large through incorporation of any advances in genome mapping technology in the next-generation products from BioNano Genomics and the public release of DNA simulation and data analysis software arising from the project.

Public Health Relevance

The proposed research is relevant to public health because it will improve the accuracy, analysis time, and cost of the devices required for large-scale analysis of human genomes and the genomes of pathogens, in particular those features that are not amenable to analysis by high throughput sequencing or microarrays. The proposed research is relevant to the mission of the NHGRI to develop and improve novel technologies for genome research.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG006851-06
Application #
9418063
Study Section
Instrumentation and Systems Development Study Section (ISD)
Program Officer
Smith, Michael
Project Start
2013-04-11
Project End
2020-01-31
Budget Start
2018-02-01
Budget End
2020-01-31
Support Year
6
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Minnesota Twin Cities
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
555917996
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
Dorfman, Kevin D (2018) The Statistical Segment Length of DNA: Opportunities for Biomechanical Modeling in Polymer Physics and Next-Generation Genomics. J Biomech Eng 140:
Agrawal, Pranav; Bognár, Zsófia; Dorfman, Kevin D (2018) Entropic trap purification of long DNA. Lab Chip 18:955-964
Reifenberger, Jeffrey G; Cao, Han; Dorfman, Kevin D (2018) Odijk excluded volume interactions during the unfolding of DNA confined in a nanochannel. Macromolecules 51:1172-1180
Gupta, Damini; Bhandari, Aditya Bikram; Dorfman, Kevin D (2018) Evaluation of Blob Theory for the Diffusion of DNA in Nanochannels. Macromolecules 51:1748-1755
Cheong, Guo Kang; Li, Xiaolan; Dorfman, Kevin D (2018) Evidence for the extended de Gennes regime of a semiflexible polymer in slit confinement. Phys Rev E 97:
Ödman, D; Werner, E; Dorfman, K D et al. (2018) Distribution of label spacings for genome mapping in nanochannels. Biomicrofluidics 12:034115
Jiang, Kai; Rocha, Sandra; Westling, Alvina et al. (2018) Alpha-Synuclein Modulates the Physical Properties of DNA. Chemistry 24:15685-15690
Werner, E; Cheong, G K; Gupta, D et al. (2017) One-Parameter Scaling Theory for DNA Extension in a Nanochannel. Phys Rev Lett 119:268102
Jain, Aashish; Dorfman, Kevin D (2017) Simulations of knotting of DNA during genome mapping. Biomicrofluidics 11:024117
Reinhart, Wesley F; Reifenberger, Jeff G; Gupta, Damini et al. (2017) Erratum: ""Distribution of distances between DNA barcode labels in nanochannels close to the persistence length"" [J. Chem. Phys. 142, 064902 (2015)]. J Chem Phys 147:029901

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