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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
biochemistry, genetics and molecular biology
Exome capture from saliva produces high quality genomic and metagenomic data
BMC Genomics, Volume 15, No. 1, Article 262, Year 2014
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Description
Background: Targeted capture of genomic regions reduces sequencing cost while generating higher coverage by allowing biomedical researchers to focus on specific loci of interest, such as exons. Targeted capture also has the potential to facilitate the generation of genomic data from DNA collected via saliva or buccal cells. DNA samples derived from these cell types tend to have a lower human DNA yield, may be degraded from age and/or have contamination from bacteria or other ambient oral microbiota. However, thousands of samples have been previously collected from these cell types, and saliva collection has the advantage that it is a non-invasive and appropriate for a wide variety of research.Results: We demonstrate successful enrichment and sequencing of 15 South African KhoeSan exomes and 2 full genomes with samples initially derived from saliva. The expanded exome dataset enables us to characterize genetic diversity free from ascertainment bias for multiple KhoeSan populations, including new exome data from six HGDP Namibian San, revealing substantial population structure across the Kalahari Desert region. Additionally, we discover and independently verify thirty-one previously unknown KIR alleles using methods we developed to accurately map and call the highly polymorphic HLA and KIR loci from exome capture data. Finally, we show that exome capture of saliva-derived DNA yields sufficient non-human sequences to characterize oral microbial communities, including detection of bacteria linked to oral disease (e.g. Prevotella melaninogenica). For comparison, two samples were sequenced using standard full genome library preparation without exome capture and we found no systematic bias of metagenomic information between exome-captured and non-captured data.Conclusions: DNA from human saliva samples, collected and extracted using standard procedures, can be used to successfully sequence high quality human exomes, and metagenomic data can be derived from non-human reads. We find that individuals from the Kalahari carry a higher oral pathogenic microbial load than samples surveyed in the Human Microbiome Project. Additionally, rare variants present in the exomes suggest strong population structure across different KhoeSan populations. © 2014 Kidd et al.; licensee BioMed Central Ltd.
Available Materials
https://efashare.b-cdn.net/share/pmc/articles/PMC4051168/bin/1471-2164-15-262-S1.PDF
https://efashare.b-cdn.net/share/pmc/articles/PMC4051168/bin/1471-2164-15-262-S2.XLS
Authors & Co-Authors
Kidd, Jeffrey M.
United States, Palo Alto
Stanford University
United States, Ann Arbor
University of Michigan, Ann Arbor
Sharpton, Thomas J.
United States, San Francisco
University of California, San Francisco
United States, Corvallis
Oregon State University
Bobo, Dean Michael
United States, Stony Brook
Stony Brook University
Norman, Paul J.
United States, Palo Alto
Stanford University
Martin, Alicia R.
United States, Palo Alto
Stanford University
Carpenter, Meredith L.
United States, Palo Alto
Stanford University
Sikora, Martin
United States, Palo Alto
Stanford University
Gignoux, Christopher R.
United States, San Francisco
University of California, San Francisco
Nemat-Gorgani, Neda
United States, Palo Alto
Stanford University
Adams, Alexandra
United States, Palo Alto
Stanford University
Guadalupe, Moraima
United States, Cedar Creek
Agilent Technologies
Guo, Xiaosen
China, Shenzhen
Bgi-shenzhen
Feng, Qiang
China, Shenzhen
Bgi-shenzhen
Li, Yingrui
China, Shenzhen
Bgi-shenzhen
Liu, Xiao
China, Shenzhen
Bgi-shenzhen
Parham, Peter R.
United States, Palo Alto
Stanford University
Hoal, Eileen G.
South Africa, Stellenbosch
Stellenbosch University
Feldman, Marcus William
United States, Palo Alto
Stanford University
Pollard, Katherine S.
United States, San Francisco
University of California, San Francisco
Wall, Jeffrey D.
United States, San Francisco
University of California, San Francisco
Bustamante, Carlos Daniel
United States, Palo Alto
Stanford University
Henn, Brenna Mariah
United States, Palo Alto
Stanford University
United States, Stony Brook
Stony Brook University
Statistics
Citations: 22
Authors: 22
Affiliations: 8
Identifiers
Doi:
10.1186/1471-2164-15-262
e-ISSN:
14712164
Research Areas
Genetics And Genomics
Health System And Policy
Study Design
Cross Sectional Study