Small-sample estimation of the mutational support and the distribution of mutations in the SARS-CoV-2 genome

The problem of accurately estimating and characterizing different mutations in the viral genomes present within a population is of great importance in tracking and mitigating the spread of the virus and is made difficult by the lack of a sufficient number of sequenced genomes especially during the early stages of an outbreak. We consider the problem of determining the mutational support and distribution of mutations in the SARS-Cov-2 genome and its open reading frames (ORFs). The mutational support refers to the unknown number of sites that are mutated among all the viral strains present in a population. The support and distribution of mutations can be used to guide primer selection for RT PCR test kits, study the virulence of the virus, discover adaptation mechanisms deployed by the virus to evade the host immune system, as well as to identify new strains that might be circulating in the population early on. We propose new state-of-the-art polynomial estimation techniques using weighted and regularized Chebyshev approximations for small-sample mutational support estimation and we use a modified Good-Turing estimator for distribution estimation. Our differential analysis of mutations in various population subgroups (based on data retrieved from GISAID repository) revealed several important differences including those in the ORF6 and ORF7a regions for older versus younger patients, ORF1b and ORF10 regions for females versus males, and in several ORFs for Asia versus Europe and North America. We also found no significant mutations in the primer regions from ORF N chosen by CDC for RT-PCR test kits in any of the subpopulations, which is important for the reliability of the test results.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2021

Author dc:creator

• Rana, Vishal

Contributors dc:contributor

• Milenkovic, Olgica

• Comparative ORF study
• Good-Turing estimation
• Mutation rates
• SARS-Cov-2 Data analysis
• Small-sample support estimation

Statement dc:rights

• Copyright 2021 Vishal Rana

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/110417

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F110417