Opportunity Information: Apply for 10HQPA0022

  • The Geological Survey in the science and technology and other research and development sector is offering a public funding opportunity titled "Cooperative Ecosystem Studies Unit, Souther Appalachian Mountains CESU" and is now available to receive applicants.
  • Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.808 U.S. Geological Survey Research and Data Collection.
  • This funding opportunity was created on Dec 7, 2009 and posted on Dec 9, 2009.
  • Applicants must submit their applications by Dec 19, 2009. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
  • The funding agency has allocated a total of $70,000.00 to eligible and selected applicants.
  • The number of recipients for this funding is limited to 1 candidate(s).
  • Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).
  • This financial assistance opportunity is being issued under a Cooperative Ecosystem Studies Unit (CESU) Program. CESU s are partnerships that provide research, technical assistance, and education. Eligible recipients must be a participating partner of the Southern Appalachian Mountains Cooperative Ecosystem Studies Unit (CESU) Program.
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Opportunity Summary:

The Cooperative Ecosystem Studies Unit, Southern Appalachian Mountains CESU funding opportunity (Funding Opportunity Number 10HQPA0022) is a US Geological Survey (USGS) discretionary research award offered as a cooperative agreement under CFDA 15.808 (USGS Research and Data Collection). The project is focused on advanced bioinformatics support for analyzing laboratory-generated DNA/RNA sequence data, with an emphasis on transcriptome assembly across multiple taxonomic groups, including both invertebrates and vertebrates, and across multiple species within those groups. The work sits squarely in the science and technology research and development category and is framed as collaborative, hands-on technical and analytical assistance rather than a simple, stand-alone research grant.

The core purpose of the award is to fund expertise needed to take large-scale gene expression and sequencing outputs and turn them into interpretable biological results. The announcement highlights a need for specialists who can analyze data related to microarrays and transcriptomics, including identification and interpretation of splice variants, SNP discovery and characterization, regulatory sequence features such as cis elements, and small RNA biology such as miRNAs. A major component is the use of contemporary data mining methods to build and refine gene models, assign gene names, classify paralogous gene families, align assembled sequences to related species, and carry out gene ontology annotation so that downstream ecological or evolutionary inferences can be made from the data.

From a technical standpoint, the opportunity expects strong computational capability and familiarity with practical bioinformatics infrastructure. The work likely involves relational database design and use, writing and optimizing SQL queries, operating in UNIX environments, and developing scripts in PERL. Beyond basic analysis, the award calls for setting up automated or semi-automated processing systems that can handle very large volumes of raw and derived data, supporting repeatable workflows for data processing, data mining, statistical analysis, and results reporting. In other words, the project is not just about running a few tools; it is about building reliable pipelines and quality-controlled analysis cycles that can be reused and scaled.

The scope also emphasizes end-to-end support for microarray data analysis projects, explicitly mentioning a "full cycle" of analysis using a mix of public, licensed, and in-house bioinformatics tools. The successful team or partner is expected to be comfortable with experimental research design and with software used across multiple gene expression profiling approaches. The cooperative agreement format signals close collaboration with the USGS Principal Investigator, including troubleshooting, helping implement and verify laboratory quality control measures, and interpreting outcomes in light of those QC checks. The work is designed to be integrated with a broader interdisciplinary environment, where the bioinformatics contributor interacts routinely with bioinformatics analysts and engineers, molecular biologists, immunologists, statisticians, and computer programmers.

In terms of broader impact, the opportunity ties this analytical capability to federal resource management needs, particularly research that helps identify ecological and evolutionary processes affecting threatened and endangered species or invasive species. The project is positioned as a collaborative research support effort that can directly inform conservation and management decisions by improving how genomic and transcriptomic evidence is processed, annotated, and interpreted for species and systems of management concern.

Administratively, the opportunity anticipated a single award (Expected Awards: 1) with an estimated total funding amount of $70,000. No cost sharing or matching requirement is listed. The posted date was December 9, 2009, with an original and current closing date of December 19, 2009, and an archive date of January 18, 2010. Eligibility is restricted to partners within the Southern Appalachian Mountains CESU Program, reflecting the CESU model as a formal partnership network that provides research, technical assistance, and education. The listed agency contact for access issues is Faith Graves, Contract Specialist, at 703-648-7356.

FAQs: Cooperative Ecosystem Studies Unit (Southern Appalachian Mountains CESU) - USGS Bioinformatics Support (Funding Opportunity Number 10HQPA0022)

What is the funding opportunity number for this award?

The funding opportunity number is 10HQPA0022.

Which federal agency is offering this opportunity?

The opportunity is offered by the U.S. Geological Survey (USGS).

What type of funding instrument is being used?

This is a discretionary research award offered as a cooperative agreement, which indicates close collaboration with the USGS Principal Investigator (PI).

What CFDA program does this opportunity fall under?

This opportunity is under CFDA 15.808, titled USGS Research and Data Collection.

How many awards are expected to be made?

The announcement anticipates a single award (Expected Awards: 1).

What is the estimated total funding amount?

The estimated total funding amount is $70,000.

Is cost sharing or matching required?

No cost sharing or matching requirement is listed in the provided information.

What is the main focus of the project?

The project focuses on advanced bioinformatics support for analyzing laboratory-generated DNA/RNA sequence data, with an emphasis on transcriptome assembly across multiple taxonomic groups (including invertebrates and vertebrates) and across multiple species.

What kind of work is USGS seeking through this cooperative agreement?

The work is framed as collaborative, hands-on technical and analytical assistance to transform large-scale gene expression and sequencing outputs into interpretable biological results, rather than a simple stand-alone research grant.

What scientific category does the work fall under?

The work sits within the science and technology research and development category.

What kinds of biological data and platforms are specifically mentioned?

The announcement references microarrays and transcriptomics, and it emphasizes analysis of laboratory-generated DNA/RNA sequence data.

What transcriptomics topics are highlighted as needs?

Highlighted needs include transcriptome assembly, identification and interpretation of splice variants, SNP discovery and characterization, regulatory sequence feature analysis (such as cis elements), and small RNA biology (such as miRNAs).

What annotation and gene modeling activities are included in the scope?

The scope includes using data mining methods to build and refine gene models, assign gene names, classify paralogous gene families, align assembled sequences to related species, and carry out gene ontology annotation to support downstream ecological or evolutionary inference.

What does "full cycle" microarray analysis mean in this opportunity?

The announcement explicitly calls for end-to-end support for microarray data analysis projects, describing a full cycle of analysis using a mix of public, licensed, and in-house bioinformatics tools.

What technical computing skills are expected?

Expected capabilities include relational database design and use, writing and optimizing SQL queries, working in UNIX environments, and developing scripts in PERL.

Does the opportunity emphasize building automated workflows or pipelines?

Yes. The description calls for setting up automated or semi-automated processing systems capable of handling very large volumes of raw and derived data, supporting repeatable workflows for data processing, data mining, statistical analysis, and results reporting.

Is the work limited to running existing tools?

No. The opportunity emphasizes building reliable, quality-controlled, reusable, and scalable pipelines and analysis cycles, not simply running a small number of tools.

What role does quality control (QC) play in this cooperative agreement?

The cooperative agreement format signals collaboration with the USGS PI on troubleshooting, helping implement and verify laboratory quality control measures, and interpreting outcomes in light of those QC checks.

What kind of interdisciplinary collaboration is described?

The bioinformatics contributor is expected to work in an interdisciplinary environment with bioinformatics analysts and engineers, molecular biologists, immunologists, statisticians, and computer programmers.

What broader mission or application area is this work connected to?

The opportunity ties the analytical capability to federal resource management needs, including research that helps identify ecological and evolutionary processes affecting threatened and endangered species or invasive species.

How can the results of this work be used according to the description?

The work is positioned to directly inform conservation and management decisions by improving how genomic and transcriptomic evidence is processed, annotated, and interpreted for species and systems of management concern.

Who is eligible to apply?

Eligibility is restricted to partners within the Southern Appalachian Mountains CESU Program.

What does the CESU restriction imply about who can apply?

Based on the provided information, applicants must be part of the Southern Appalachian Mountains CESU partnership network, consistent with the CESU model as a formal partnership providing research, technical assistance, and education.

When was the opportunity posted?

The posted date was December 9, 2009.

What was the closing date for applications?

The original and current closing date listed is December 19, 2009.

When was the opportunity archived?

The archive date is January 18, 2010.

Who is the listed contact for access issues, and how can they be reached?

The listed agency contact for access issues is Faith Graves, Contract Specialist, reachable at 703-648-7356.

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