Probing statistical patterns across the tree of life: Comparative methods for microbial genomes and traits

Li, Zeqian

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https://hdl.handle.net/2142/122088 Copy

Description

Title

Probing statistical patterns across the tree of life: Comparative methods for microbial genomes and traits

Author(s)

Li, Zeqian

Issue Date

2023-07-31

Director of Research (if dissertation) or Advisor (if thesis)

Kuehn, Seppe

Doctoral Committee Chair(s)

Song, Jun

Committee Member(s)

• Maslov, Sergei
• Coleman, Maureen

Department of Study

Physics

Discipline

Physics

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

Microbial ecology

Abstract

Microbes are essential to the global ecosystem and constitute most biodiversity observed in the tree of life. In understanding microbes from natural environments, the central problem is to predict microbial community functions (phenotypes) from structures (composition and genetic content). While community structure measure- ment became accessible through next-generation sequencing, mapping the structure to function remains challenging due to difficulties in each level of the sequence-protein-metabolism-community hierarchy for diverse microbes. To address this challenge, comparative methods serve as a powerful data-driven tool, by identifying dominant statistical patterns in biological data, linking these patterns to biological phenomena, and ultimately accurately predicting functions from structures. In this dissertation, I present my contributions to five projects that employ comparative methods to address the structure-function mapping problem in microbial communities within the sequence-protein-metabolism-community hierarchy. These projects include the statistical prediction of microbial metabolic traits from genomes, the discovery of novel constraints in the genome organization of closely related microbial strains, the investigation of co-evolution patterns within the denitrification pathway, and the measurement of two novel microbial traits using a theoretical framework of chemical equilibria.

Graduation Semester

2023-12

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/122088

Copyright and License Information

Copyright 2023 Zeqian Li

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