Objective
Cytogenetic diagnostic approaches provide information on the single-chromosome level but suffer from low resolution and throughput. In contrast, next generation sequencing (NGS) based diagnostics provides single base resolution and high throughput but suffer from short reads that prevent analysis of large genomic aberrations as well as being prone to PCR-amplification bias and erasure of epigenetic information. This proposal aims to bridge the gap between these domains by analyzing long individual DNA molecules without PCR-amplification via utilization of emerging optical DNA mapping technologies. We specifically address three types of challenges to current genomic based diagnostics:
1. Loss of relevant information such as DNA damage lesions, rare mutations or epigenetic markers following PCR amplification.
2. Limitations in resolving long-range variations in genomic layout and correlating them with single point mutations, preventing large scale screens.
3. Limitations imposed by the sample such as low sample amounts (micro biopsy, circulating tumor DNA) or inhomogeneous/highly variable samples (bacterial cultures).
We will develop a robust toolbox for integrated genetic and epigenetic profiling of single DNA molecules that will include automated sample preparation of native unamplified DNA as well as the hardware and software platforms and analysis tools for readout, extraction and quantification of medically relevant genomic information. This technology will be used to develop a set of specific, proof of principle diagnostic assays based on optical barcoding of individual DNA molecules. These assays will address:
-Bacterial infections and antibiotic resistance
-Diagnosis/prognosis tools for hematological malignancies
-Spinal Muscular Atrophy
-Early diagnosis of colorectal and lung cancer.
Ultimately our project will provide reagents, prototype DNA barcoding devices and data analysis software ready for large scale validation and early stage commercialization.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesgeneticsDNA
- medical and health sciencesclinical medicineoncologylung cancer
- medical and health sciencesclinical medicineoncologycolorectal cancer
- medical and health scienceshealth sciencespersonalized medicine
- medical and health sciencesbasic medicinepharmacology and pharmacydrug resistanceantibiotic resistance
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Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
69978 Tel Aviv
Israel