Document text
Principal Investigator: Bryan R Greenhouse
Organization: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
Fiscal Year: 2024
Award: $524,724
Funding agency: National Institute of Allergy and Infectious Diseases
ABSTRACT
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. We will develop a suite of data standards and robust software including a) bioinformatic pipelines
including tools to facilitate the sharing and storage of these data, b) a modular software toolkit to conduct
downstream statistical analyses relevant for epidemiologic and population genetic research, and c) work within
a community of advisors and experts in the analysis of genomic data for eukaryotic pathogens to develop
approaches that meet the needs of community and encourage broader uptake. The proposed work also
includes harmonizing and developing standards for genomic, epidemiological, and clinical data. We will initially
focus 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.
Terms: <2019 novel corona virus><2019 novel coronavirus><2019-nCoV><AIDS Virus><Acquired Immune Deficiency Syndrome Virus><Acquired Immunodeficiency Syndrome Virus><Address><Allele Frequency><American><American Trypanosomiasis><Automobile Driving><Bacteria><Bilharziasis><Bio-Informatics><Bioinformatics><Biological><Biology><COVID-19 virus><COVID19 virus><Chagas Disease><Clinical Data><CoV-2><CoV2><Communities><Complex><Computational toolkit><Computer Software Tools><Computer software><DNA Recombination><Data><Data Analyses><Data Analysis><Data Storage and Retrieval><Development><Disease><Disorder><Documentation><Drug resistance><Ecologic Systems><Ecological Systems><Ecosystem><Education and Outreach><Educational workshop><Ensure><Epidemiological data><Epidemiology><Epidemiology data><Evolution><Exhibits><Feedback><Filariasis><Filarioidea Infections><Galaxy><Gene Frequency><Generations><Genetic><Genetic Diversity><Genetic Recombination><Genetic Research><Genetic Variation><Genetic analyses><Genome><Genomics><Goals><Grippe><HIV><Human><Human Immunodeficiency Viruses><Hygiene><Immune><Immunes><Individual><Infection><Influenza><Instruction and Outreach><Investigators><LAV-HTLV-III><Laboratories><Leishmaniasis><Lymphadenopathy-Associated Virus><Malaria><Metadata><Methods><Modern Man><Morbidity><Morbidity - disease rate><Motivation><Nature><Ontology><Organism><Outcome><Output><P falciparum><P. falciparum><P.falciparum><Paludism><Parasites><Pattern><Performance><Phenotype><Plasmodium><Plasmodium Infections><Plasmodium falciparum><Population><Population Genetics><Process><Productivity><Public Health><Recombination><Reproducibility of Findings><Reproducibility of Results><Research><Research Personnel><Research Resources><Researchers><Resolution><Resources><SARS corona virus 2><SARS-CO-V2><SARS-COVID-2><SARS-CoV-2><SARS-CoV2><SARS-associated corona virus 2><SARS-associated coronavirus 2><SARS-coronavirus-2><SARS-related corona virus 2><SARS-related coronavirus 2><SARSCoV2><Sampling><Schistosomiasis><Scientist><Severe Acute Respiratory Coronavirus 2><Severe Acute Respiratory Distress Syndrome CoV 2><Severe Acute Respiratory Distress Syndrome Corona Virus 2><Severe Acute Respiratory Distress Syndrome Coronavirus 2><Severe Acute Respiratory Syndrome CoV 2><Severe Acute Respiratory Syndrome-associated coronavirus 2><Severe Acute Respiratory Syndrome-related coronavirus 2><Severe acute respiratory syndrome associated corona virus 2><Severe acute respiratory syndrome coronavirus 2><Severe acute respiratory syndrome related corona virus 2><Societies><Software><Software Tools><Source><South American Trypanosomiasis><Standardization><Statistical Data Analyses><Statistical Data Analysis><Statistical Data Interpretation><Structure><Techniques><Training and Outreach><Translating><Transmission><Tropical Medicine><Tutoring and Outreach><Validation><Variant><Variation><Viral><Virus><Virus-HIV><Work><Workshop><Wuhan coronavirus><allelic frequency><base><bases><bio-informatics pipeline><bioinformatics pipeline><biologic><cloud platform><cloud server><computational toolbox><computational tools><computational toolset><computerized tools><coronavirus disease 2019 virus><coronavirus disease-19 virus><data interpretation><data re-use><data retrieval><data reuse><data standardization><data standards><data storage><develop software><developing computer software><developmental><direct application><disease control><disorder control><driving><drug resistant><epidemiologic><epidemiologic data><epidemiological><filarial disease><filarial infection><genetic analysis><genomic data><genomic data-set><genomic dataset><hCoV19><improved><innovate><innovation><innovative><interest><interoperability><lab development><laboratory development><living system><malaria infection><malaria-infected><malarial infection><meeting><meetings><meta data><method development><mortality><nCoV2><outreach><pathogen><portability><resistance to Drug><resistant to Drug><resolutions><software development><software toolkit><statistical analysis><targeted sequencing><tool><transmission process><uptake><validations>