Detecting individual ancestry in the human genome

Detecting and quantifying the population substructure present in a sample of individuals are of main interest in the fields of genetic epidemiology, population genetics, and forensics among others. To date, several algorithms have been proposed for estimating the amount of genetic ancestry within an individual. In the present review, we introduce the most widely used methods in population genetics for detecting individual genetic ancestry. We further show, by means of simulations, the performance of popular algorithms for detecting individual ancestry in various controlled demographic scenarios. Finally, we provide some hints on how to interpret the results from these algorithms

Història natural de les malalties genètiques mendelianes i complexes

Las enfermedades genéticas se clasifican típicamente en dos grandes grupos: las enfermedades mendelianas y las enfermedades complejas. Mientras que las enfermedades mendelianas se caracterizan por ser de baja frecuencia en la población y estar causadas por mutaciones en un gen particular, las enfermedades complejas son el principal problema sanitario en los países desarrollados y se encuentran producidas por la interacción de factores ambientales y factores genéticos. En este caso no se puede hablar de mutación en un determinado gen, sino de polimorfismo que incrementa en una pequeña fracción el riesgo a padecer la enfermedad. En la presente tesis se ha estudiado la distribución espacial de la variabilidad genética tanto en enfermedades mendelianas (en concreto la fibrosis quística, la fenilcetonuria y la b-talasemia) como en una enfermedad compleja (la enfermedad coronaria) en poblaciones europeas y de todo el mundo. Los resultados obtenidos sugieren que la distribución geográfica de la variabilidad genética de las enfermedades mendelianas depende principalmente de factores demográficos y de la historia de las poblaciones. Ahora bien, este efecto no es independiente de factores selectivos. En particular, fenómenos de selección equilibradora pueden incrementar o disminuir la variabilidad genética en una población dependiendo de el momento en el que se dio el evento selectivo. En el caso de la enfermedad compleja estudiada, la enfermedad coronaria, nuestros resultados indican que la distribución espacial de los polimorfismos de riesgo en poblaciones europeas depende, al igual que sucede con otros marcadores genéticos, principalmente de la historia de poblaciones, especialmente del poblamiento del continente europeo, la posterior reexpansión después del último periodo glacial y de las gran expansión poblacional de los agricultores durante el neolítico

Proceso de implementación en establecimientos comerciales entre los años 2017 - 2020, a través de una gestión, dirección y supervisión de obra

El sector Retail siempre está en constante cambio, buscando cumplir con las necesidades del cliente. Adaptándose a las nuevas tendencias y requerimientos del variado perfil en el público en general. Por ello es vital una buena gestión y coordinación desde el anteproyecto, proyecto y ejecución de la obra. Por ser un sector muy cambiante y dinámico el objetivo de la supervisión es lograr que la obra se ejecute dentro del programa establecido, con la calidad y el costo contratado. El supervisor debe moldearse en los distintos escenarios o frentes que se desarrolle el proyecto, con la finalidad de proponer mejoras, actuar proactivamente durante la construcción identificando cualquier problema que se pudiera presentar afectando el resultado de la obra. No obstante, sin dejar en segundo lugar el factor tiempo ya que es sumamente importante para que la tienda pueda continuar o iniciar sus ventas cuanto antes y generar ingresos

GAGA: A New Algorithm for Genomic Inference of Geographic Ancestry Reveals Fine Level Population Substructure in Europeans

Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics

Statistical analysis of post mortem DNA damage-derived miscoding lesions in Neandertal mitochondrial DNA

Background. We have analysed the distribution of post mortem DNA damage derived miscoding lesions from the datasets of seven published Neandertal specimens that have extensive cloned sequence coverage over the mitochondrial DNA (mtDNA) hypervariable region 1 (HVS1). The analysis was restricted to C → T and G → A miscoding lesions (the predominant manifestation of post mortem damage) that are seen at a frequency of more than one clone among sequences from a single PCR, but do not represent the true endogenous sequence. Findings. The data indicates an extreme bias towards C → T over G → A miscoding lesions (observed ratio of 67:2 compared to an expected ratio of 7:2), implying that the mtDNA Light strand molecule suffers proportionally more damage-derived miscoding lesions than the Heavy strand. Conclusion. The clustering of Cs in the Light strand as opposed to the singleton pattern of Cs in the Heavy strand could explain the observed bias, a phenomenon that could be further tested with non-PCR based approaches. The characterization of the HVS1 hotspots will be of use to future Neandertal mtDNA studies, with specific regards to assessing the authenticity of new positions previously unknown to be polymorphic

Evaluation of mRNA markers for estimating blood deposition time : towards alibi testing from human forensic stains with rhythmic biomarkers

This study was supported by grant 27.011.001 by the Netherlands Organization for Scientific Research (NWO) Forensic Science Program, Erasmus MC University Medical Center Rotterdam, by the EU 6th Framework project EUCLOCK (018741), UK Biotechnology and Biological Sciences Research Council (BBSRC) Grant BB/I019405/1, and by a previous grant from the Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO) within the framework of the Forensic Genomics Consortium Netherlands (FGCN). D.J.S. is a Royal Society Wolfson Research Merit Award holder.Determining the time a biological trace was left at a scene of crime reflects a crucial aspect of forensic investigations as - if possible - it would permit testing the sample donor's alibi directly from the trace evidence, helping to link (or not) the DNA-identified sample donor with the crime event. However, reliable and robust methodology is lacking thus far. In this study, we assessed the suitability of mRNA for the purpose of estimating blood deposition time, and its added value relative to melatonin and cortisol, two circadian hormones we previously introduced for this purpose. By analysing 21 candidate mRNA markers in blood samples from 12 individuals collected around the clock at 2 h intervals for 36 h under real-life, controlled conditions, we identified 11 mRNAs with statistically significant expression rhythms. We then used these 11 significantly rhythmic mRNA markers, with and without melatonin and cortisol also analysed in these samples, to establish statistical models for predicting day/night time categories. We found that although in general mRNA-based estimation of time categories was less accurate than hormone-based estimation, the use of three mRNA markers HSPA1B, MKNK2 and PER3 together with melatonin and cortisol generally enhanced the time prediction accuracy relative to the use of the two hormones alone. Our data best support a model that by using these five molecular biomarkers estimates three time categories, i.e., night/early morning, morning/noon, and afternoon/evening with prediction accuracies expressed as AUC values of 0.88, 0.88, and 0.95, respectively. For the first time, we demonstrate the value of mRNA for blood deposition timing and introduce a statistical model for estimating day/night time categories based on molecular biomarkers, which shall be further validated with additional samples in the future. Moreover, our work provides new leads for molecular approaches on time of death estimation using the significantly rhythmic mRNA markers established here.PostprintPeer reviewe

Proportioning whole-genome single-nucleotide-polymorphism diversity for the identification of geographic population structure and genetic ancestry

The identification of geographic population structure and genetic ancestry on the basis of a minimal set of genetic markers is desirable for a wide range of applications in medical and forensic sciences. However, the absence of sharp discontinuities in the neutral genetic diversity among human populations implies that, in practice, a large number of neutral markers will be required to identify the genetic ancestry of one individual. We showed that it is possible to reduce the amount of markers required for detecting continental population structure to only 10 single-nucleotide polymorphisms (SNPs), by applying a newly developed ascertainment algorithm to Affymetrix GeneChip Mapping 10K SNP array data that we obtained from samples of globally dispersed human individuals (the Y Chromosome Consortium panel). Furthermore, this set of SNPs was able to recover the genetic ancestry of individuals from all four continents represented in the original data set when applied to an independent, much larger, worldwide population data set (Centre d'Etude du Polymorphisme Humain-Human Genome Diversity Project Cell Line Panel). Finally, we provide evidence that the unusual patterns of genetic variation we observed at the respective genomic regions surrounding the five most informative SNPs is in agreement with local positive selection being the explanation for the striking SNP allele-frequency differences we found between continental groups of human populations

Recent human evolution has shaped geographical differences in susceptibility to disease

Background: Searching for associations between genetic variants and complex diseases has been a very active area of research for over two decades. More than 51,000 potential associations have been studied and published, a figure that keeps increasing, especially with the recent explosion of array-based Genome-Wide Association Studies. Even if the number of true associations described so far is high, many of the putative risk variants detected so far have failed to be consistently replicated and are widely considered false positives. Here, we focus on the world-wide patterns of replicability of published association studies.Results: We report three main findings. First, contrary to previous results, genes associated to complex diseases present lower degrees of genetic differentiation among human populations than average genome-wide levels. Second, also contrary to previous results, the differences in replicability of disease associated-loci between Europeans and East Asians are highly correlated with genetic differentiation between these populations. Finally, highly replicated genes present increased levels of high-frequency derived alleles in European and Asian populations when compared to African populations.Conclusions: Our findings highlight the heterogeneous nature of the genetic etiology of complex disease, confirm the importance of the recent evolutionary history of our species in current patterns of disease susceptibility and could cast doubts on the status as false positives of some associations that have failed to replicate across populations