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Pilot Grant Program

Application Information

RNA Bioscience Initiative — Pilot Grant Programs

Fall 2023 

The RNA Bioscience Initiative (RBI) at the University of Colorado Anschutz Medical campus seeks to support RNA biology research and the use of RNA-seq and its analysis to enhance basic science, translational, and clinical studies. Towards that goal, the RBI requests applications for informatics support grants available for Fall 2023. Grant Program description, deadlines, and application guidelines are provided below. We hope that applicants, with assistance from the RBI, will apply RNA technologies creatively to address new and exciting questions.

A major difference between this and previous rounds of RBI pilot awards is that for this round the RBI and investigators will share the cost of the experiments. Investigators will be responsible for the experimental portion of the award. The RBI will provide design support prior to the experiment and full analytical support once data are generated.

Questions should be directed to

To apply for this RFA, you must express your interest using this form by September 21st, 2023.


The RBI will provide informatics support for the analysis of RNA-focused sequencing and related technologies. The RBI informatics fellows are a group of post-doctoral level RNA biologists and bioinformaticians who specialize in developing methods and performing analysis of RNA sequencing and RNA related technologies. The RBI fellows will provide assistance with experimental design and informatics

support for the proposed project. The informatics support grant does not provide a monetary budget. Investigators will provide funds for the generation of any new datasets proposed for the project. Priority will be given to proposals that will generate new datasets, however the analysis of existing datasets or public databases will be supported if the project examines previously unexplored questions with the existing dataset.

We welcome proposals that employ the following RNA technologies:

1. Long read RNA sequencing

Nanopore sequencing on Oxford Nanopore Technology MinION and PromethION platforms enables high throughput sequencing of RNAs and can be used to define full length mRNA splicing isoforms, estimate their polyA tail length, and catalog RNA modifications (e.g., m6A, pseudouridine) with single-base precision (PMID 34750572, 34559589). In addition, advances enable analysis of tRNA populations, providing new insight into metabolic states and translational status. A typical experiment consists of RNA isolation from replicate conditions (done by the investigator), followed by a library preparation and direct RNA analysis by nanopore sequencing (PMID 29334379). Alternatively, the RNA can be converted to cDNA, which provides better performance for analysis of splicing isoforms. cDNA generated via the 10X Genomics Chromium platform can also be profiled using nanopore sequencing, enabling the analysis of long read single cell transcriptomic data.

Nanopore sequencing is not currently available as a core service and sequencing will be conducted by RBI affiliated labs. The experiment will need to be planned in advance with RBI consultation.

2. Ribosome profiling

Ribosome profiling (or “Ribo-seq”) enables precise positioning of ribosomes on mRNAs in cells, and can be used to ask questions about ongoing translation. A typical Ribo-seq experiment enables positioning of ribosomes along mRNA transcripts, providing a measure of translation efficiency per transcript and revealing fundamental aspects of mRNA translation regulation (PMID: 30037969). Moreover, Ribo-seq is a powerful approach to discover non-canonical (unannotated) peptides and antigens that are potential targets for immunotherapy (PMID: 34663921, 34663921).

A typical experiment involves cell culture and flash-freezing the samples (done by the investigator), followed by cell lysis, collecting an aliquot for RNA-seq, isolation of ribosome-mRNA footprints, library preparation, and sequencing (done by the RBI). A minimum of 2 million cells are required and the experiment will need to be planned in advance with RBI consultation.

3. Spatial Transcriptomics

Assessing gene expression within morphological context is critical to our understanding of biology and disease processes. Historically, it has been challenging to spatially interrogate complex heterogeneous tissues in a high-throughput manner, especially without previously generated assumptions about the genes being expressed. Spatial transcriptomics technologies enable measurement of gene expression transcriptome-wide within a morphological tissue context. The

Genomics Shared Research core facility at the Anschutz medical campus provides services to generate data using the 10x Genomics and Nanostring platforms.

4. Single cell RNA sequencing and multimodal technologies

Single-cell technologies have untapped potential to functionally interrogate cellular populations. The RBI has collaboratively developed and applied several new single-cell technologies and hopes to collaborate more broadly with campus investigators to answer new biological questions. These technologies include CITE-Seq, TCR/BCR sequencing + scRNA-seq, clonal or lineage tracing with scRNA-seq, and long read sequencing of scRNA-seq data. Experiments involving single cell technologies that cannot be completed using commercial or core services will need to be planned in advance with RBI consultation.

5. Additional RNA-seq technologies

Analysis of datasets from RNA sequencing methods not previously listed will be supported with strong preference given to projects with questions focused on the following topics: 1) mechanisms or regulation fundamental RNA processes (alternative splicing and polyadenylation, RNA modifications, RNA stability, post-transcriptional regulation), 2) the functions, RNA targets, or regulation of RNA binding proteins, or 3) the role of RNA and RNA binding proteins in biological systems or disease processes.

6. Public Data Integration and Computational Modeling

Embracing the power of public datasets and repositories, we invite proposals exploring fresh RNA-related inquiries through existing resources. This avenue welcomes projects that may incorporate experimental data generated from the previously mentioned cutting-edge RNA technologies. The emphasis here is on the synergy between large-scale datasets and computational analyses. The aim is to uncover novel biological patterns, correlations, and latent insights within the data.


These grants provide informatics support for the proposed projects and do not provide monetary budgets. Investigators will need to support the costs of generating any new datasets proposed for the projects.

The effort level required to complete the proposed analyses should not exceed 10-20% of an informatics fellow FTE for a year’s duration. Projects generating new datasets should be designed such that data collection is completed ideally within 6 months and no later than 1 year from project start.

Timelines for analysis deliverables and effort levels will be determined in consultation with the RNA Bioscience Informatics Fellows and their faculty supervisors, Jay Hesselberth and Neel Mukherjee. Informatics support may be terminated if datasets do not meet technical or quality standards, lack necessary replicates, or have improper experimental design for statistical testing.


Key Dates

Letter of Intent Due: September 21, 2023

Application Due: October 13, 2023

Decisions/Results Communicated to Applicant: November 3, 2023

Project Start Date: November 3, 2023


  • Principal Investigators (PIs) for awards must have faculty appointments at the University of Colorado Anschutz Medical Campus and hold the rank of Assistant, Associate or Full Professor, Research Professor or Instructor. Postdoctoral trainees are also encouraged to apply, provided that a faculty sponsor includes a Letter of Support for the trainee in the application.
  • Proposal may not describe the same specific research that is funded by other sources during the grant period.
  • The application must have a main focus on RNA-related research


Step 1. All applicants must submit a Letter of Intent using this form by September 21st, 2023

Step 2. Full applications must be submitted no later than October 13, 2023 as a single PDF file (file name as follows: PIname.ProposalTitle.pdf) that includes:

a. A brief cover letter from the PI containing the title of the proposal and describing the value of the project and a statement that all collaborators listed on the application agree with the proposal.

b. A proposal consisting of no more than 1 page in standard NIH grant application format. Recommended, but not required, organization for proposals include: specific aims, background and broader impact, and research plan.

c. If an existing dataset or public database is to be analyzed then the proposal must include a supplemental section containing detailed information about the dataset(s) to be analyzed (no more than 1 additional page). Recommended information includes the number of samples and replicates, quality control metrics if available, and any findings from previously performed analysis.

d. NIH formatted Biosketch for the PI or PI’s

Instructions for submitting the application will be provided to applicants that have submitted a Letter of Intent.


Those receiving a grant will be expected to become active members of the University of Colorado RNA research community. Both the PIs and those working on funded projects are expected to:

  • For all bioinformatics support, include the RBI fellows as authors on publications that result from the award

  • Acknowledge RBI Support in publications

  • Self-identify as a member of the RBI on all publications emanating from the work supported by this grant

  • Use awarded funds solely to support the RNA research described in their proposal

  • Provide a progress report 30 days after the end of funding year

  • Contribute a presentation on research accomplishments at a future symposium hosted by the RBI

  • Participate in the “Lunch with RNA Seminar Series” series held alternatively at the AMC and Boulder Campuses


A peer review panel composed of faculty with a range of expertise will be responsible for award decisions, evaluating eligible applications competitively.

The primary factors in award decisions will be the scientific merit of the proposed research, the likelihood to “seed” eventual R series-level or equivalent extramural funding, and the long-term promise of the proposed research.

No critiques will be provided to applicants.

Applicants will be informed with a review response of “Funded”, “Not funded” or “Not eligible”.