Event
Ph.D. Research Proposal Exam: Ananth Hari
Monday, March 25, 2024
10:00 a.m.
AVW 2328
Maria Hoo
301 405 3681
mch@umd.edu
ANNOUNCEMENT: Ph.D. Research Proposal Exam
Name: Ananth Hari
Committee:
Professor Uzi Vishkin (Chair)
Professor Behtash Babadi
Professor Richard La
Date/time: Monday, March 25, 2024 at 10 AM
Location: AVW 2328
Title: Algorithmic Immunogenomics: Germline Genotyping and Repertoire Phylogeny Reconstruction
Abstract: The human adaptive immune system is the second line of defense in our fight against foreign pathogens or antigens. It mounts a defense more effective than the innate immune system because it tailors its protection to each kind of antigen it encounters. The adaptive immune system mainly consists of B and T cells and their receptors. B cells use genes from the immunoglobulin locus to produce B cell receptors (or antibodies) that are selected and trained to bind to antigens. This thesis presents models and algorithms to characterize, firstly, the genomic sequence composition and next, the phylogenetic evolution of the receptor sequences of the adaptive immune system.
First, we present ImmunoTyper-SR, an algorithmic approach to genotype and analyze copy numbers of the germline immunoglobulin genes using Illumina whole genome sequencing (WGS) data. Because of its highly repetitive sequence composition, the immunoglobulin heavy chain (IGH) locus has been particularly difficult to assemble or genotype through the use of standard short read sequencing technologies. ImmunoTyper-SR is based on a novel combinatorial optimization formulation that aims to minimize the total edit distance between reads and their assigned IGH alleles from a given database, with constraints on the number and distribution of reads across each called allele.
When the innate immune system fails to destroy pathogenic invaders, various immunoglobulin genes combine to form naive B cell receptors and rapidly accumulate mutations to greatly increase binding affinity of the antibodies. The second part of the thesis focuses on studying this evolutionary process, starting from the unmutated root sequences, obtained by ImmunoTyper-SR. We survey the literature and describe currently available computational tools, their assumptions and limitations and propose various novel combinatorial optimization formulations to solve distinct variants of the B cell receptor phylogeny inference problem.
First, we present ImmunoTyper-SR, an algorithmic approach to genotype and analyze copy numbers of the germline immunoglobulin genes using Illumina whole genome sequencing (WGS) data. Because of its highly repetitive sequence composition, the immunoglobulin heavy chain (IGH) locus has been particularly difficult to assemble or genotype through the use of standard short read sequencing technologies. ImmunoTyper-SR is based on a novel combinatorial optimization formulation that aims to minimize the total edit distance between reads and their assigned IGH alleles from a given database, with constraints on the number and distribution of reads across each called allele.
When the innate immune system fails to destroy pathogenic invaders, various immunoglobulin genes combine to form naive B cell receptors and rapidly accumulate mutations to greatly increase binding affinity of the antibodies. The second part of the thesis focuses on studying this evolutionary process, starting from the unmutated root sequences, obtained by ImmunoTyper-SR. We survey the literature and describe currently available computational tools, their assumptions and limitations and propose various novel combinatorial optimization formulations to solve distinct variants of the B cell receptor phylogeny inference problem.
