Date of Award
1-1-2019
Document Type
Open Access Thesis
Degree Name
Master of Public Health (MPH)
Department
School of Public Health
First Advisor
Josephine Hoh
Abstract
Abstract
Background: There has been extensive research in the study of the dog genome and comparative genomics to human diseases. Dogs were proposed as a candidate primarily because of the relatively low variation within breeds but high variation between breeds. In this study, we used a conserved gene among dogs, SMN, to understand the genetic variability across dog breeds and to compare with human SMN1.
Methods: Using a sequential method design, new dog samples are added into the database as they become available. This paper is an application of the newly developed algorithms in studying the similarities and differences in genes between dogs and humans.
Results: In our analysis, we isolated the sequence for SMN across three dogs (two English Bulldogs and one French Mastiff) and compared the sequence to the reference dog SMN sequence. We identified a number of SNPs but the differences were located in the intron region suggesting that potential difference in the exon regions may exhibit deleterious effects in the animal. The total genetic variation we observed in our three dog samples is less than 1%. When comparing the reference dog SMN to human SMN1, we observed conserved sequences predominantly within the exon region of SMN1. The conserved sequences located in the intron region between SMN1 and dog SMN may suggest that those regions may serve a regulatory function in gene expression.
Conclusion: There were no meaningful genetic variation within the exon region among our dog samples for SMN. As additional dog sequences from different breeds are acquired, the comparison of SMN will be conducted to better understand the genetic variation of the conserved gene.
Recommended Citation
Xie, Emily, "The Potential Of Next Generation Whole Genome Sequencing Using Dogs As A Model To Understand Human Diseases" (2019). Public Health Theses. 1851.
https://elischolar.library.yale.edu/ysphtdl/1851
This Article is Open Access
Comments
This is an Open Access Thesis.