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ARRA Investments in Forward Technologies

Public Health Burden
In the context of genomics, the term “forward technologies” encompasses a variety of high-tech tools that will enable research to further our understanding of the relation between DNA sequence and human diseases, over a broad range of public health problems. Developing these tools will advance the pace of discovery about the genetic components of human disease, thus leading to new strategies and approaches for improving prevention, diagnosis, and treatment of diseases that constitute a major fraction of the health burden of the U.S. and world populations.

Computational Analysis and Software Pipeline
New genomic technologies are already producing, at an unprecedented rate, increasingly large data sets related to DNA sequence, genetic variation, and genomic function. Innovative approaches to data management and computational analysis are urgently needed to address these burgeoning and extremely rich data resources. ARRA grants will support researchers to continue the development of software and new in silico analytical methods to facilitate the production, analysis, and management of more data with increased efficiency. These projects will pay particular attention to integrating data generated in medical sequencing studies, large population studies, gene expression research, and studies of the interaction between genes and the environment.  

ARRA funds are now being used to fund the following projects:
  • Cloud Computing in Genomics: Through this project, computational researchers will develop informatics tools to realize the potential of high throughput DNA sequencing.  Galaxy, a system for making complex computational analysis accessible and reproducible, will be brought together with "cloud computing," an infrastructure model in which computing resources can be obtained on demand as needed. This innovative approach will make it possible for the majority of investigators, who do not have high-level informatics expertise, to perform data-intensive analysis using cloud resources.1
  • DNA Sequencing Software: Another team of researchers is developing computer software to align the vast quantities of short DNA sequence “reads” (fragments of sequence information) to known genome sequence “maps.” This is the first step in the analysis of the data produced by next-generation sequencing methods; better software will also facilitate the application of newer sequencing technologies in diagnostic and clinical applications.2
Single Cell Technologies
Another example of forward technologies supported by ARRA funds includes those able to measure activities within an individual cell. This is very different from most current tools, which can only assess the properties of a population of cells. Single-cell technologies are needed to understand the molecular phenotype (or state) of a particular cell type in a specific biological environment, the normal variation among single cells within a population, and the role that both such phenotype and variation play in healthy and unhealthy tissue and organ function.

ARRA funds are now being used to fund the following projects:
  • Cancer Cells: Circulating cancer cells are rare, but important, since they play a key role in cancer metastasis. One ARRA project will develop a method to measure gene expression within individual circulating cancer cells obtained from human blood.3
  • Stem Cells: Another project is developing a technique to quantify expression of up to 100 genes in just one to ten cells residing in intact tissue in an animal. This powerful approach will be broadly applicable to the study of a wide variety of biological processes and to understanding regulatory pathways and metabolic processes that are fundamental to stem cell and cancer cell function.4
  • Biomolecules in Brain Cells: One of the greatest challenges in biochemistry is to study simultaneously dozens to hundreds of molecules in single cells or cell types within the complex cell populations in living tissues. One ARRA-funded project seeks to develop a new technology, termed “microlysis technology,” to enable the automated collection and quantitative analysis of single cells embedded in brain slice samples. This will permit the study of biomolecules within their tissue of origin, rather than in a laboratory-derived environment.5
Cell Perturbations
ARRA funds were also used to support investigators to develop and assess methods to conduct, high-throughput studies for cataloguing data describing the relationship between cell function and the cellular response to external perturbation, such as exposure to various biological molecules or changing environmental conditions. Understanding the effects such perturbations have on cellular function will provide insights into systems biology (the study of individual biological processes as a unit, or system) and facilitate analyses relevant to drug discovery.

ARRA funds are now being used to fund the following projects:
  • Better Anti-Cancer Drugs: Researchers will undertake a systematic effort to collect and analyze multi-factorial “Pharmaco-Response Signatures” for 15 therapeutic small molecules (the precursor to many therapeutic compounds) across a set of 80 different cancer cells lines for which genomic data are available. This research will eventually enable investigators and clinicians to identify individual patients who are most likely to benefit from specific therapies,6 thereby contributing to the NIH goal of developing more focused and effective anti-cancer drugs.
  • The Connectivity Map: Researchers supported by ARRA will pursue the development of a comprehensive “functionality table,” called the Connectivity Map. The Connectivity Map will provide the biomedical community with a tool that will facilitate systematic discoveries linking disease biology, genome biology, and chemical biology. This will lay the groundwork for a future, large-scale, community-wide effort to create a public Connectivity Map resource that will facilitate a data-driven connection of disparate scientific disciplines, which will lead to new discoveries about how our bodies function.7

  1. 1RC2HG005542-01 --Dynamically scalable, accessible analysis for next generation sequence data—Taylor, James (GA)
  2. 5R01HG004719-02 --Modular Software for Sequence Data Quality Checking, Alignment & Variant-Calling—Marth, Gabor (MA)
  3. 1RC1HG005471-01 --Transcriptomics from Single Circulating Tumor Cells—Lasken, Roger (MD)
  4. 1RC1HG005428-01 --Quantification of gene expression in targeted rare cells in vivo --Brazelton, Timothy (PA)
  5. 1RC1HG005354-01 --Microlysis Technology: Enabling Cell Type-Specific Proteomics in Living Tissue—Macbeath, Gavin (MA)
  6. 1RC2HG005693-01 --Mechanistic Signatures of Drug Responses in Cancer—Gray, Nathaneal (MA)
  7. 1RC2HG005604-01 --Connectivity Map 100k—Golub, Todd (MA)

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