# System and Methods for Analysis of Bacterial Transcriptomes

> **NIH NIH R15** · WELLESLEY COLLEGE · 2024 · $394,295

## Abstract

PROJECT SUMMARY 
High-throughput sequencing technology enables, among other things, experiments that produce
massive amounts of data about RNA transcripts in bacteria. These high-throughput sequencing
experiments continue to advance our understanding of bacterial transcriptomes, including
regulatory RNA genes, which pervade bacteria. However, processing the large resulting data
sets from high-throughput sequencing experiments can be a bottleneck in biological and
medical research studies, partly because existing methods are insufficient for analyzing these
data sets from bacteria.
 This project aims to develop new methods for processing high-throughput bacterial
sequencing data. A robust and user-friendly computational system will be implemented for end-
to-end analysis of high-throughput bacterial sequencing data. As part of this system, a novel
algorithm will be implemented to significantly reduce the time it takes for the most
computationally expensive stage of processing bacterial sequencing data, which is aligning
reads from sequencing experiments to a bacterial genome. While high-throughput bacterial
sequencing experiments commonly are performed on large sets of cells in bulk, recent
advances have made possible the effective use of these experiments on individual cells,
enabling greater resolution of bacterial transcriptome studies. New methods will be developed to
process high-throughput bacterial sequencing data from single-cell experiments. Further, a
computational system will be designed for systematic annotation of transcripts evinced from
bacterial sequencing data to aid biological and medical researchers in efficient and reliable
interpretation of the massive data sets. Finally, since many RNA genes in bacteria act as
regulators of other transcripts, novel approaches will be developed to identify the interactions
between these noncoding RNAs and their regulatory targets. The methods developed will be
applied and evaluated in different bacterial systems.

## Key facts

- **NIH application ID:** 10795384
- **Project number:** 2R15GM102755-04
- **Recipient organization:** WELLESLEY COLLEGE
- **Principal Investigator:** BRIAN TJADEN
- **Activity code:** R15 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $394,295
- **Award type:** 2
- **Project period:** 2013-06-03 → 2027-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10795384

## Citation

> US National Institutes of Health, RePORTER application 10795384, System and Methods for Analysis of Bacterial Transcriptomes (2R15GM102755-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10795384. Licensed CC0.

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