Data and analysis ecosystem for eukaryotic pathogen targeted sequencing

Genomic data can provide an invaluable source of information to understand pathogen evolution, identify patterns of transmission, and characterize phenotypes such as drug resistance and immune escape. For eukaryotic pathogens, larger genomes, sexual recombination, and complicated transmission dynamics including polyclonal infections have historically limited the use of genomic data for many of these applications. However, recent laboratory developments, including multiplexed targeted sequencing, have rapidly increased the pace of genomic data generation for eukaryotic pathogens. Fundamental differences in the biology and transmission of infections caused by these pathogens render many of the genomic data and analysis tools developed for other organisms (primarily humans, viruses, and bacteria) difficult or impossible to use. As a result, many research efforts have needed to rely on bespoke methods for processing and analysis, limiting the reusability of data, the accuracy and reproducibility of results, and more generally the productivity of scientists studying eukaryotic pathogens. There is a need to develop software and computational tools to process, store, share and analyze these data in a way which sets standards, encourages innovation, and facilities scientific discovery. The proposed work also includes harmonizing and developing standards for genomic, epidemiological, and clinical data. The initial focus will be on Plasmodium falciparum, a species of parasite that causes malaria infections, as an organism of direct application which exhibits key complexities of eukaryotic pathogens (recombination, polyclonal infections). As such, standards and software developed during this proposal will have relevance beyond this single organism to other eukaryotic pathogens where similar biological and transmission complexities limit the use of existing tools to leverage genomic data to answer scientific and public health relevant questions. The expected outcome of the proposed research is computational software able to analyze targeted amplicon sequencing data for eukaryotic pathogens. By developing these approaches, with clear engagement within the broader research community, this work will help change the landscape of analyses possible with complex genomic data.

NIH Project details

Digital Tools
Genetics and Genomics
Product Development

Jun 2024 — May 2027

$524,724

United States