ORCID Profile
0000-0002-0338-3321
Current Organisations
Colorado State University
,
Nacional de Genomica para la Biodiversidad
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Publisher: Elsevier BV
Date: 04-2021
Publisher: Frontiers Media SA
Date: 03-01-2022
DOI: 10.3389/FGENE.2021.719791
Abstract: Current Genome-Wide Association Studies (GWAS) rely on genotype imputation to increase statistical power, improve fine-mapping of association signals, and facilitate meta-analyses. Due to the complex demographic history of Latin America and the lack of balanced representation of Native American genomes in current imputation panels, the discovery of locally relevant disease variants is likely to be missed, limiting the scope and impact of biomedical research in these populations. Therefore, the necessity of better ersity representation in genomic databases is a scientific imperative. Here, we expand the 1,000 Genomes reference panel (1KGP) with 134 Native American genomes (1KGP + NAT) to assess imputation performance in Latin American in iduals of mixed ancestry. Our panel increased the number of SNPs above the GWAS quality threshold, thus improving statistical power for association studies in the region. It also increased imputation accuracy, particularly in low-frequency variants segregating in Native American ancestry tracts. The improvement is subtle but consistent across countries and proportional to the number of genomes added from local source populations. To project the potential improvement with a higher number of reference genomes, we performed simulations and found that at least 3,000 Native American genomes are needed to equal the imputation performance of variants in European ancestry tracts. This reflects the concerning imbalance of ersity in current references and highlights the contribution of our work to reducing it while complementing efforts to improve global equity in genomic research.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 07-2022
Abstract: Micronesia began to be peopled earlier than other parts of Remote Oceania, but the origins of its inhabitants remain unclear. We generated genome-wide data from 164 ancient and 112 modern in iduals. Analysis reveals five migratory streams into Micronesia. Three are East Asian related, one is Polynesian, and a fifth is a Papuan source related to mainland New Guineans that is different from the New Britain–related Papuan source for southwest Pacific populations but is similarly derived from male migrants ~2500 to 2000 years ago. People of the Mariana Archipelago may derive all of their precolonial ancestry from East Asian sources, making them the only Remote Oceanians without Papuan ancestry. Female-inherited mitochondrial DNA was highly differentiated across early Remote Oceanian communities but homogeneous within, implying matrilocal practices whereby women almost never raised their children in communities different from the ones in which they grew up.
Publisher: Wiley
Date: 28-04-2022
DOI: 10.1111/GWMR.12523
Abstract: Forecasting groundwater contaminant plume development is critical for determining risks to downgradient receptors and predicting the time to site closure. However, accurate forecasts are a formidable challenge due to the complexities of a heterogeneous subsurface. While historically groundwater well data in combination with numerical flow models have been used for this task, the advent of machine learning offers new data‐driven opportunities for improving contaminant fate and transport predictions. In this study, we interrogate the viability of two forecasting models—Prophet and d ed Holt's exponential smoothing model—for predicting groundwater contaminant plume development. The impacts of spatial and temporal data density on the accuracy of the forecasts are evaluated. For wells with declining contaminant concentrations, the d ed Holt's method achieves more accurate forecasts. However, only Prophet allows for the inclusion of exogenous regressors, enabling predictions of future declining trends in wells with still increasing contaminant concentrations. Application of these models does not only require robust training data, but also an understanding of model biases. Overall, powerful data‐driven models are already available for contaminant plume prediction, but groundwater s ling approaches will have to improve, for instance, through the collection of real‐time spatial and temporal high‐resolution data, to take full advantage of their capabilities.
Publisher: Cold Spring Harbor Laboratory
Date: 09-2021
DOI: 10.1101/2021.08.31.457499
Abstract: Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this necessity, a large number of specialised simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and tskit library. We summarise msprime ’s many features, and show that its performance is excellent, often many times faster and more memory efficient than specialised alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.
Publisher: Oxford University Press (OUP)
Date: 13-12-2021
Abstract: Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime’s many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.
Publisher: Rockefeller University Press
Date: 20-04-2022
DOI: 10.1084/JEM.20220028
Abstract: Globally, autosomal recessive IFNAR1 deficiency is a rare inborn error of immunity underlying susceptibility to live attenuated vaccine and wild-type viruses. We report seven children from five unrelated kindreds of western Polynesian ancestry who suffered from severe viral diseases. All the patients are homozygous for the same nonsense IFNAR1 variant (p.Glu386*). This allele encodes a truncated protein that is absent from the cell surface and is loss-of-function. The fibroblasts of the patients do not respond to type I IFNs (IFN-α2, IFN-ω, or IFN-β). Remarkably, this IFNAR1 variant has a minor allele frequency & % in Samoa and is also observed in the Cook, Society, Marquesas, and Austral islands, as well as Fiji, whereas it is extremely rare or absent in the other populations tested, including those of the Pacific region. Inherited IFNAR1 deficiency should be considered in in iduals of Polynesian ancestry with severe viral illnesses.
No related grants have been discovered for Consuelo Dayzú Quinto-Cortés.