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Malangone, C.

Publications and source records attributed to Malangone, C..

2 recordsLinked to original sources

A Standardized Framework For Representation Of Ancestry Data In Genomics Studies

BackgroundThe accurate description of ancestry is essential to interpret and integrate human genomics data, and to ensure that advances in the field of genomics benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the consistent, unambiguous and standardized description of ancestry. To fill this gap, we provide a framework, designed for the representation of ancestry in GWAS data, but with wider application to studies and resources involving human subjects.\n\nResultHere we describe our framework and its application to the representation of ancestry data in a widely-used publically available genomics resource, the NHGRI-EBI GWAS Catalog. We present the first analyses of GWAS data using our ancestry categories, demonstrating the validity of the framework to facilitate the tracking of ancestry in big data sets. We exhibit the broader relevance and integration potential of our method by its usage to describe the well-established HapMap and 1000 Genomes reference populations. Finally, to encourage adoption, we outline recommendations for authors to implement when describing samples.\n\nConclusionsWhile the known bias towards inclusion of European ancestry individuals in GWA studies persists, African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations, suggesting that analyses including these groups may be more effective at identifying new associations. We believe the widespread adoption of our framework will increase standardization of ancestry data, thus enabling improved analysis, interpretation and integration of human genomics data and furthering our understanding of disease.

genetics

Natural diversity of the malaria vector Anopheles gambiae

The sustainability of malaria control in Africa is threatened by rising levels of insecticide resistance, and new tools to prevent malaria transmission are urgently needed. To gain a better understanding of the mosquito populations that transmit malaria, we sequenced the genomes of 765 wild specimens of Anopheles gambiae and Anopheles coluzzii sampled from 15 locations across Africa. The data reveal high levels of genetic diversity, with over 50 million single nucleotide polymorphisms across the 230 Mbp genome. We observe complex patterns of population structure and marked variations in local population size, some of which may be due at least in part to malaria control interventions. Insecticide resistance genes show strong signatures of recent selection associated with multiple independent mutations spreading over large geographical distances and between species. The genetic variability of natural populations substantially reduces the target space for novel gene-drive strategies for mosquito control. This large dataset provides a foundation for tracking the emergence and spread of insecticide resistance and developing new vector control tools.

genomics