Molecular analysis of environmental plant DNA in house dust across the United States View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-07-21

AUTHORS

Joseph M. Craine, Albert Barberán, Ryan C. Lynch, Holly L. Menninger, Robert R. Dunn, Noah Fierer

ABSTRACT

Despite the prevalence and costs of allergic diseases caused by pollen, we know little about the distributions of allergenic and non-allergenic pollen inside and outside homes at the continental scale. To better understand patterns in potential pollen diversity across the United States, we used DNA sequencing of a chloroplast marker gene to identify the plant DNA found in settled dust collected on indoor and outdoor surfaces across 459 homes. House location was the best predictor of the relative abundance of plant taxa found in outdoor dust samples. Urban, southern houses in hotter climates that were further from the coast were more likely to have more DNA from grass and moss species, while rural houses in northern, cooler climates closer to the coast were more likely to have higher relative abundances of DNA from Pinus and Cedrus species. In general, those plant taxa that were more abundant outdoors were also more abundant indoors, but indoor dust had uniquely high abundances of DNA from food plants and plants associated with lawns. Approximately 14 % of the plant DNA sequences found outside were from plant taxa that are known to have allergenic pollen compared to just 8 % inside. There was little geographic pattern in the total relative abundance of these allergens highlighting the difficulties associated with trying to predict allergen exposures based on geographic location alone. Together, this work demonstrates the utility of using environmental DNA sequencing to reconstruct the distributions of plant DNA inside and outside buildings, an approach that could prove useful for better understanding and predicting plant allergen exposures. More... »

PAGES

71-86

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10453-016-9451-5

DOI

http://dx.doi.org/10.1007/s10453-016-9451-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1006929315


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