• Login
    View Item 
    •   Mak IR Home
    • College of Health Sciences (CHS)
    • School of Bio-Medical Sciences (Bio-Medical)
    • School of Bio-Medical Sciences (Bio-Medical) Collections
    • View Item
    •   Mak IR Home
    • College of Health Sciences (CHS)
    • School of Bio-Medical Sciences (Bio-Medical)
    • School of Bio-Medical Sciences (Bio-Medical) Collections
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Developing an automated panel design tool for SNP-Based Targeted Amplicon sequencing of Schistosoma mansoni populations

    Thumbnail
    View/Open
    Master's Dissertation (3.278Mb)
    Date
    2022-08-26
    Author
    Nabunje, Ritah
    Metadata
    Show full item record
    Abstract
    Genomic surveillance of Schistosomiasis across endemic regions could provide insights into the efficacy of current control strategies and allow the impact of selection on the parasite genome to be monitored, providing early warning of the emergence of anthelmintic resistance. Studies exploring this require large numbers of samples yet even with decreasing costs for sequencing, it is still prohibitively expensive to sequence whole genomes of large samples of individuals from populations. Targeted amplicon sequencing is a feasible approach to sequencing from populations while excluding possible contaminating sequences and allowing the generation of genome variation data at a reasonable depth and reduced costs. This study introduces an approach to target SNP-rich sites across the parasite’s genome to contribute to molecular marker discovery and analysis in studying natural Schistosoma populations. Here, an automated tool has been created for flexible amplicon panel design, to enable targeted sequencing of Schistosoma mansoni populations. Using an in silico targeted amplicon data set generated from available (unpublished) whole-genome sequencing data for 574 population genetics samples from different geographic regions, the panels designed from the software showed ability to distinguish parasites from geographically unrelated parasites. This automated panel design approach, when validated, will facilitate the quick generation of panels and support application in endemic countries and regions where high-throughput genome sequencing is not readily available. In turn, the approach and software will enable research on targeted sequencing in Schistosoma mansoni populations.
    URI
    http://hdl.handle.net/10570/10795
    Collections
    • School of Bio-Medical Sciences (Bio-Medical) Collections

    DSpace 5.8 copyright © Makerere University 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of Mak IRCommunities & CollectionsTitlesAuthorsBy AdvisorBy Issue DateSubjectsBy TypeThis CollectionTitlesAuthorsBy AdvisorBy Issue DateSubjectsBy Type

    My Account

    LoginRegister

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    DSpace 5.8 copyright © Makerere University 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV