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  • RESEARCH
    INFECTIOUS DISEASE FUNCTIONAL ANALYSIS COMPUTATIONAL BIOLOGY

INFECTIOUS DISEASE

Through resources at Harvard University and the Broad Institute, the Sabeti lab is applying next generation, high-throughput sequencing technologies to the creation of tailored sequencing pipelines for some of the world’s most deadly viruses and bacteria.

Working with other collaborators at Tulane University and USAMRIID, the Sabeti lab has obtained a vast repository of valuable clinical samples from patients with viral hemorrhagic fevers. Our hope is to carry out in-depth genomic analysis and diversity studies, elucidating regions of selection and identifying novel strains. The ability to generate full-length sequences will help in creating accurate phylogenies for both Lassa fever and Ebola viruses, as well as refine our ability to predict and identify regions of selection and high mutation within the genomes of these viruses.

Using both 454 and Illumina technologies, the Sabeti lab is developing novel approaches to full-length genome sequencing for both Lassa fever virus and Ebola virus. With the capacity to generate millions of base pairs of data from less than a teaspoon of blood, we are able to assemble complete viral genomes for identification and genetic analysis of known and unknown viruses.

  • LASSA FEVER
  • CHOLERA
  • MALARIA

LASSA FEVER

Happi

In our work studying genetic susceptibility to Lassa, we have established strong collaborations with outstanding partners in Nigeria. Dr. Christian Happi, with whom we have worked for years on malaria, runs a thriving research program at the Redeemer’s University.
We are also working closely with and have support from the Provost of the College of Medicine, University of Ibadan, the Chancellor of Ambrose Ali University, and the chief medical director (CMD) of ISTH in Irrua. We have the guidance and participation of arguably the world’s leading expert on Lassa fever, Joe McCormick, former chief of special pathogens at the CDC.

ISTH copyWe are working with The Specialist Teaching Hospital in Irrua (ISTH), Nigeria, an ideal location for our study. The hospital, with its 140 physicians and ~16,000 annual patients (80% of which have febrile illness), is located in a rural area in Nigeria where Lassa is endemic with yearly outbreaks.

The hospital has a commitment to research and has collaborated with researchers at the Berhnardt-Nocht Institute (BNI) in Hamburg in one of the best recent epidemiological studies on Lassa. Their 2003-2004 study laid the ground work for our research. It examined 31 febrile patients, 17 healthy contacts, and 12 hospital staff, and got basic rates of infection and exposure for the site.

CHOLERA

Cholera is a devastating illness caused by the bacillus Vibrio cholerae, which triggers a severe, dehydrating and occasionally fatal diarrhea. We are investigating the genetics of cholera resistance in Bangladesh, where the disease is endemic, to understand how the human immune system responds to cholera infection. Because cholera has a long history in Bangladesh, any person carrying a gene version protecting them from this devastating disease will have had a significant evolutionary advantage. Thus, these genes should show exceptionally strong natural selection signals. By applying powerful new computational techniques for detecting natural selection to genome-wide genotyping data from the Bangladeshi population, we are identifying genes that likely confer cholera resistance. By then integrating these tests with gene transcription profiling and proteomic analysis, we can learn how these genes alter an individual’s response to cholera infection. As part of this project, we are also researching the evolutionary history of the Bangladeshis by comparing them to the populations from around the world included in the Human Haplotype Map project.

This project is a collaboration with Dr. Regina LaRocque, an Infectious Disease Specialist at MGH, and ICDDRB, an international health research institution and hospital located in Dhaka, Bangladesh that treats tens of thousands of patients every year.

MALARIA

mosquitoPlasmodium falciparum malaria is a major public health challenge that significantly contributes to global morbidity and mortality. Efforts to control and eliminate malaria combine antimalarial drugs, bed nets and indoor residual spraying, with vaccine development a longer-term goal. Genetic variation in the parasite population threatens to undermine these efforts, as the parasite evolves rapidly to evade host immune systems, drugs and vaccines.

Working with the Broad Institute, the Harvard School of Public Health, and the University of Cheikh Anta Diop, Dakar, Senegal, we have been studying genetic variation in parasite populations to help expand our understanding of basic parasite biology and allow us to track parasites as they evolve in response to interventions.

FUNCTIONAL ANALYSIS

Genome-wide scans, such as those our lab develops, generate lists of loci that are probable candidates for recent natural selection. In order to create a case for selection of a candidate gene, we perform follow-up studies to determine the allele’s biological function, using methods such as case/control association studies, the development of cell cultures containing the gene of interest, and in vivo transgenic studies.

COMPUTATIONAL BIOLOGY

In the era of genomics, we can now probe information buried in the millions of sequence variations that have occurred and persisted in the human genome, in search of signatures of genome evolution. 

  • GENOME-WIDE SCANS FOR SELECTION
  • VISUALIZATION SOFTWARE

GENOME-WIDE SCANS FOR SELECTION

We have developed computational methods, such as the LRH, XP-EHH, and CMS tests, to detect genetic variants under positive selection. These methods identify variants that have recently emerged and spread through populations, relying on the breakdown of recombination as a clock for estimating the ages of alleles. We have applied these methods to large datasets of human genetic variation finding many novel candidates for selection.

We are developing methods to further refine the signals from large candidate regions to localize the underlying selected polymorphism. We have developed software to make detection of selection, by these and other methods, possible for the rapidly expanding empirical data on genetic variation in humans and other species.

The lab continues to refine existing, and develop novel, methods and tools to detect and localize signals of selection in humans and other organisms. We are using approaches that take advantage of rapidly expanding datasets of genetic variation and larger population sampling, increasingly affordable full-genome sequencing, and new insights into the structure of genetic variation in the genome. We will apply our methods to look for instances of natural selection, using our own data and data collected for human in 2 international efforts: The International Haplotype Map Consortium (1000 individuals genotyped for 1 million polymorphisms) and the 1000 Genomes Consortium (full genome sequences from 1000 individuals).

VISUALIZATION SOFTWARE

Mirador is a software tool for visual exploration of complex biomedical data sets, specifically designed to find correlations between variables of interest, to propose new hypothesis of association, and to build predictive models. Its interface allows navigation of data sets with thousands of variables and up to millions of individual records. It uses a Mutual Information-based measure of correlation to rapidly quantify the significance of pairwise associations. Mirador has been used to find correlations patterns in several public health, survey, and country databases, to construct clinical prediction models in Ebola Virus Disease and other infectious diseases, and received innovation and scientific excellence awards from the U.S. Department of Health and Human Services. It continues a line of work initiated in the lab by David Reshef and his project Visualyzer, and it is freely available for download at http://fathom.info/mirador/. Mirador has been developed in collaboration with Fathom Information Design, and was initially funded by the Center of Communicable Disease Dynamics and the MIDAS network funded by the National Institutes of Health.

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