Penn State University
1.
Pandey, Utsav.
Comparative Genomics Provides Insights into Herpesvirus Transmission, Spread, and Virulence.
Degree: 2018, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/15255uup104 
Herpesviruses are widespread in the nature infecting almost every animal
species. They are significant pathogens for human health and agriculture.
Herpes simplex virus 1 (HSV-1) causes millions of chronic infections in humans,
whereas Marek’s disease virus 1 (MDV-1) is a herpesvirus of poultry of great
economic importance. Clinical outcomes of HSV-1 infections are diverse, ranging
from surface lesions, keratitis, to severe and potentially lethal encephalitis.
Similarly, MDV-1 causes nervous system disease and lymphomas in chickens
with mortality approaching 100% in absence of vaccination. Both HSV-1 and
MDV-1 are alphaherpesviruses and contain a double-stranded DNA (dsDNA)
genome as their genetic material. Using high throughput sequencing (HTS) and
comparative genomics, this dissertation seeks to explore the genetic basis of
transmission, spread and virulence of these viruses.
In this dissertation, transmission of HSV-1 between individuals has been
explored using transmission events between father-son and mother-neonate pair.
Comparative genomics of these genomes showed that at the consensus level
HSV-1 genomes can be identical even after multiple cycles of latency and
reactivations. However, we observed that at the population level the parental and
transmitted virus can be quite different. HSV-1 isolates obtained from the fatherson
pair were further characterized phenotypically using a murine animal model.
By examining a series of phenotypic properties, we concluded that parental and
transmitted viruses can also preserve their phenotypes over decades.
Transmission and spread of MDV-1 in the field was depicted by
sequencing viral isolates form poultry farms in central Pennsylvania. This study
presented the first case of MDV-1 genomes obtained directly from chicken
feathers and poultry dander without the use of cell culture. We showed that these
genomes were highly identical at the consensus level, but differed at the
population level, corroborating the findings from transmission events of HSV-1.
This study was also important in laying foundation for studying MDV-1 genomics
using field samples. We further extended comparative genomics of field samples
of MDV-1 to understand the evolution of virulence in MDV-1. To this effect, we
sequenced 64 spatially and temporally separated field isolates of MDV-1 and
explored the role of recombination in emergence of highly virulent isolates over
time. We found that paths to emergence of virulence in field isolates of MDV-1 is
complex and could be explained by multiple recombination events between field
isolates.
We also employed comparative genomics to identify genetic markers of
virulence in HSV-1 and MDV-1. In HSV-1, we identified amino acid variations in
the viral protein VP22 that reliably distinguish low-virulence isolates from highvirulence
isolates of HSV-1. To understand the biological importance of these
amino acid residues in determining HSV-1 virulence, I have initiated the process
of engineering viral mutants. These recombinant viral mutants can then be tested
against…
Advisors/Committee Members: Moriah Louise Szpara, Dissertation Advisor/Co-Advisor, Moriah Louise Szpara, Committee Chair/Co-Chair, Anthony Paul Schmitt, Committee Member, Istvan Albert, Committee Member, Andrew Fraser Read, Outside Member, Timothy Charles Meredith, Committee Member.Subjects/Keywords: Herpes Simplex Virus; Marek's Disease Virus; Bioinformatics; Molecular Biology; Virology; Genomics
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APA (6th Edition):
Pandey, U. (2018). Comparative Genomics Provides Insights into Herpesvirus Transmission, Spread, and Virulence. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/15255uup104
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Pandey, Utsav. “Comparative Genomics Provides Insights into Herpesvirus Transmission, Spread, and Virulence.” 2018. Thesis, Penn State University. Accessed April 16, 2021.
https://submit-etda.libraries.psu.edu/catalog/15255uup104.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Pandey, Utsav. “Comparative Genomics Provides Insights into Herpesvirus Transmission, Spread, and Virulence.” 2018. Web. 16 Apr 2021.
Vancouver:
Pandey U. Comparative Genomics Provides Insights into Herpesvirus Transmission, Spread, and Virulence. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Apr 16].
Available from: https://submit-etda.libraries.psu.edu/catalog/15255uup104.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Pandey U. Comparative Genomics Provides Insights into Herpesvirus Transmission, Spread, and Virulence. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/15255uup104
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Penn State University
2.
Verma, Anurag.
PheWAS AND BEYOND: APPROACHES TO ADDRESS CHALLENGES FOR IDENTIFYING ROBUST ASSOCIATIONS USING CLINICAL DATA.
Degree: 2018, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/15007auv13
In an emerging approach called precision medicine, the primary focus is to utilize an
individual’s clinical data along with genetic, environmental, and lifestyle information to tailor
clinical care. The initial steps toward precision medicine involve enrolling individuals into studies
to link their genotype and phenotype data. Patient data can be used to discover clinically relevant
genetic associations. The most common methodology to identify genetic associations is called an
genome-wide association study (GWAS), in which tests for associations are performed between
single-nucleotide polymorphisms (SNPs) across the genome (usually over 500,000 SNPs) and a
single disease outcome or trait. There is now a growing amount of evidence to demonstrate the
success of some of these genetic associations. However, the impact of GWAS has been limited
due to its focus on a single phenotype, and hence, the effect of a given SNP across multiple
phenotypes cannot be explored. An alternative approach called a phenome-wide association study
(PheWAS) has been successful in simultaneously scanning genome-wide significant variants over
hundreds of phenotypes. Using this approach, we can identify genetic variants associated with a
wide range of phenotypes, also referred to as cross-phenotype associations. Such findings have
the potential to identify pleiotropy (where one variant is affecting two or more independent
phenotypes with same underlying biological mechanism) or an underlying genetic architecture of
comorbidities. The majority of PheWAS have used data from de-identified electronic health
records (EHRs) linked to genotype data, and a few have been performed in large-scale
epidemiologic studies and clinical trials.
While existing studies have demonstrated the development of PheWAS methodology, the
focus has remained on a small set of genome-wide significant SNPs or a genomic region of
iv
interest. After advances in genotyping and sequencing technologies, as well as in phenotype data
collection, it is imperative to apply PheWAS on a genome-wide scale. It will allow us to
investigate genetic associations across all SNPs and phenotypes in a study population. However,
there can be many challenges with expanding the current PheWAS approach to investigate
associations across the genome. In this dissertation, I aim to address following specific challenges
regarding large-scale PheWAS analysis. 1) Evaluating heterogeneous groups simultaneously
makes precision medicine impossible; stratifying samples based on context such as age, sex, or
drugs can help to improve precision in identifying true genetic associations (Chapter 2). 2) The
number of association tests raise the statistical threshold of significance in such a way that finding
the significant associations is difficult. Also, the impact of factors such as sample size, casecontrol
ratio, and minor allele frequency on the statistical power to identify associations have not
been explored (Chapter 3). 3) Integrating results from independent PheWAS using different types
of data sets (e.g.,…
Advisors/Committee Members: Marylyn Ritchie, Dissertation Advisor/Co-Advisor, Moriah Louise Szpara, Committee Chair/Co-Chair, Ross Cameron Hardison, Committee Member, N/A, Committee Member, Yu Zhang, Outside Member.Subjects/Keywords: PheWAS; EHR; GWAS; Genomics; Biobank
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Verma, A. (2018). PheWAS AND BEYOND: APPROACHES TO ADDRESS CHALLENGES FOR IDENTIFYING ROBUST ASSOCIATIONS USING CLINICAL DATA. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/15007auv13
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Verma, Anurag. “PheWAS AND BEYOND: APPROACHES TO ADDRESS CHALLENGES FOR IDENTIFYING ROBUST ASSOCIATIONS USING CLINICAL DATA.” 2018. Thesis, Penn State University. Accessed April 16, 2021.
https://submit-etda.libraries.psu.edu/catalog/15007auv13.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Verma, Anurag. “PheWAS AND BEYOND: APPROACHES TO ADDRESS CHALLENGES FOR IDENTIFYING ROBUST ASSOCIATIONS USING CLINICAL DATA.” 2018. Web. 16 Apr 2021.
Vancouver:
Verma A. PheWAS AND BEYOND: APPROACHES TO ADDRESS CHALLENGES FOR IDENTIFYING ROBUST ASSOCIATIONS USING CLINICAL DATA. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Apr 16].
Available from: https://submit-etda.libraries.psu.edu/catalog/15007auv13.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Verma A. PheWAS AND BEYOND: APPROACHES TO ADDRESS CHALLENGES FOR IDENTIFYING ROBUST ASSOCIATIONS USING CLINICAL DATA. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/15007auv13
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Open Access Theses and Dissertations