Tremendous advances in genomics during the past two decades hold great potential for the development of new health innovations. For this potential to be realized in the form of advances in biomedical research and novel prevention, diagnosis, treatment and disease management strategies, we must overcome one technological barrier, namely the ability to perform reliable molecular profiling analyses of low quantity cells/nucleic acid material. Current technologies are not suitable for most low-quantity nucleic applications, and require multiple nucleic acid manipulation and amplification steps that are known to introduce biases and artifacts that confound downstream analyses and reduce/eliminate quantitative power. This grant application proposes various strategies for picogram-level DNA and RNA samples to be profiled in an unbiased and amplification-free, high-throughput manner, and paves the way towards single cell measurements. In Phase I, we will set the groundwork for unprecedented technologies enabling attomole-level, amplification-free high- throughput genomics tools. The Phase I specific aims are: (1) Optimization of DNA tailing and sequencing surface capture steps, (2) Development of DNA fragmentation strategies suitable for low DNA quantities, (3) Specific capture and sequencing of polyA+ mRNA from total RNA, and (4) Development of single-step sequence selection and single molecule sequencing technology. In Phase II, we will expand our work from Phase I to develop mature procedures ready for commercialization. The Phase II specific aims are: (1) High- throughput sequencing of limiting DNA samples, (2) Sequencing minute polyA+ RNA quantities using direct RNA sequencing, (3) Optimization of tailing and surface capture steps for direct RNA sequencing, (4) cDNA- based low-quantity RNA sequencing on surface, and (5) Development of a sequencing strategy for damaged and limited quantity nucleic acid samples. These advancements will enable various long desired and needed studies, open new research frontiers and provide a comprehensive understanding of the biological mechanisms underlying disease states, such as cancer, heart disease, diabetes, and others, ultimately leading to revolutionary new ways to diagnose, treat and prevent human disease.

Public Health Relevance

The sequencing of the first human genome was an unprecedented scientific achievement derived from 13years of effort by an international coalition of scientists and some $3 billion in funds. The availability of acomplete human genome sequence has facilitated research by providing a framework for the genome; nowbeing used for further investigation into the biological mechanisms underlying human disease. Technologicaladvancements now enable sequencing of genomes at a fraction of the time and cost; and the widespreadapplication of high-throughput sequencing technologies has transformed the biomedical research field.However; several fundamental technical shortcomings still remain. Among these limitations; arguably the mostcritical one is the requirement for high-quantities of valuable input material; namely DNA/RNA. Progress inmany research areas; such as; but not limited to; stem cell biology; microbiology; cancer; paleoarcheology;forensics; and clinical diagnostics; is severely impeded by our inability to perform comprehensive and reliablemolecular profiling analyses on low-quantity cell and nucleic acid samples. If we are to successfully translatethis research knowledge of genome biology to better diagnosing and treating human disease; we must reliablyuse and analyze minute quantities of nucleic acid derived from patient specimens. This grant applicationproposes various strategies for picogram-level DNA and RNA samples to be profiled in an unbiased andamplification-free; high-throughput manner; and paves the way towards single cell measurements. Theseadvancements will enable various long desired and needed studies; open new research frontiers and provide acomprehensive understanding of the biological mechanisms underlying disease states; such as cancer; heartdisease; diabetes; and others; ultimately leading to revolutionary new ways to diagnose; treat and preventhuman disease.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
Project #
7R44HG005279-04
Application #
8879926
Study Section
Special Emphasis Panel (ZRG1-IMST-E (15))
Program Officer
Schloss, Jeffery
Project Start
2010-06-09
Project End
2015-06-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
4
Fiscal Year
2012
Total Cost
$234,587
Indirect Cost
Name
Seqll, LLC
Department
Type
DUNS #
City
Woburn
State
MA
Country
United States
Zip Code
01801
Shema, Efrat; Jones, Daniel; Shoresh, Noam et al. (2016) Single-molecule decoding of combinatorially modified nucleosomes. Science 352:717-21
Ozsolak, Fatih (2016) Attomole-level Genomics with Single-molecule Direct DNA, cDNA and RNA Sequencing Technologies. Curr Issues Mol Biol 18:43-8
Ozsolak, Fatih (2014) Quantitative polyadenylation site mapping with single-molecule direct RNA sequencing. Methods Mol Biol 1125:145-55
Lin, Yuefeng; Li, Zhihua; Ozsolak, Fatih et al. (2012) An in-depth map of polyadenylation sites in cancer. Nucleic Acids Res 40:8460-71
Ozsolak, Fatih (2012) Third-generation sequencing techniques and applications to drug discovery. Expert Opin Drug Discov 7:231-43
Sherstnev, Alexander; Duc, Céline; Cole, Christian et al. (2012) Direct sequencing of Arabidopsis thaliana RNA reveals patterns of cleavage and polyadenylation. Nat Struct Mol Biol 19:845-52
Orlando, Ludovic; Ginolhac, Aurelien; Raghavan, Maanasa et al. (2011) True single-molecule DNA sequencing of a pleistocene horse bone. Genome Res 21:1705-19
Ozsolak, Fatih; Milos, Patrice M (2011) RNA sequencing: advances, challenges and opportunities. Nat Rev Genet 12:87-98
Goren, Alon; Ozsolak, Fatih; Shoresh, Noam et al. (2010) Chromatin profiling by directly sequencing small quantities of immunoprecipitated DNA. Nat Methods 7:47-9
Ozsolak, Fatih; Goren, Alon; Gymrek, Melissa et al. (2010) Digital transcriptome profiling from attomole-level RNA samples. Genome Res 20:519-25

Showing the most recent 10 out of 11 publications