# Computational Methods for Analyzing lmmunoglobulin Allelic Diversity in B cells

> **NIH NIH F31** · YALE UNIVERSITY · 2023 · $47,694

## Abstract

PROJECT SUMMARY/ABSTRACT
The development of broadly neutralizing antibodies (BNAbs) remains an ambitious objective for effective vaccine
responses. Methods to reliably elicit BNAbs are not known, nor are the mechanisms for their natural development
fully understood. Prior work, including research from our lab, has identified a handful of germline immunoglobulin
(Ig) variable (V) gene alleles more likely to become broadly neutralizing antibodies for HIV, influenza, and
autoimmunity. Unfortunately, this barely scratches the surface of the over 500 documented alleles broadly
distributed across populations. We will work closely with experimental collaborators to develop computational
methods accelerating Ig characterization with the long-term goal of BNAbs discovery. Success in these
endeavors will contribute to the development of personalized healthcare and vaccination strategies, and increase
our understanding of this critical component of the adaptive immune response.
This proposal will take advantage of the growing quantity of single cell (SC) data being produced, which allows
RNA expression to combine with Ig repertoires to confer a host of useful biological context to analyze. Despite
the advantages of SC data and its potential to immunology analysis forward, it remains either missing or
represents a fractional percentage of adaptive immune receptor repertoire (AIRR) datasets in public repositories
due to a lack of analysis tools appropriate to the challenges of SC. To address this problem, we will develop Ig
analysis methods leveraging SC data. Our goals are to improve coverage and accuracy of Ig V gene analysis
and identify germline alleles associated with differential Ig expression and immunological outcomes. This is an
early critical step in promoting broad use of SC data in AIRR analyses, understanding the complex interplay
between Ig and factors not captured within the allelic sequence, and linking AIRR analysis to multi-omics data.
Results will additionally guide future studies with experimental collaborators and advance novel methodology
suited for Ig genes and B cell biology of diseases.

## Key facts

- **NIH application ID:** 10751541
- **Project number:** 1F31AI179156-01
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Noah Yann Lee
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $47,694
- **Award type:** 1
- **Project period:** 2023-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10751541

## Citation

> US National Institutes of Health, RePORTER application 10751541, Computational Methods for Analyzing lmmunoglobulin Allelic Diversity in B cells (1F31AI179156-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10751541. Licensed CC0.

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