Author
Damian Labuda
Other affiliations: Centre Hospitalier Universitaire Sainte-Justine, HTC, École Polytechnique de Montréal
Bio: Damian Labuda is an academic researcher from Université de Montréal. The author has contributed to research in topics: Population & Alu element. The author has an hindex of 56, co-authored 170 publications receiving 13896 citations. Previous affiliations of Damian Labuda include Centre Hospitalier Universitaire Sainte-Justine & HTC.
Topics: Population, Alu element, Gene, Founder effect, Haplotype
Papers published on a yearly basis
Papers
More filters
TL;DR: The utility of microsatellite-directed DNA fingerprinting by polymerase chain reaction (PCR) amplification of the interrepeat region provides a novel fingerprinting approach applicable for taxonomic and phylogenetic comparisons and as a mapping tool in a wide range of organisms.
3,292 citations
Broad Institute1, Harvard University2, Howard Hughes Medical Institute3, University of California, Berkeley4, University of California, Los Angeles5, Chinese Academy of Sciences6, Max Planck Society7, Columbia University8, Massachusetts Institute of Technology9, Cayetano Heredia University10, University of Pennsylvania11, University College London12, University of Bern13, Leiden University14, Nanyang Technological University15, University of Chicago16, Estonian Biocentre17, National University of La Plata18, University of Oxford19, University of Bergen20, Novosibirsk State University21, Moscow Institute of Physics and Technology22, Sofia Medical University23, Armenian National Academy of Sciences24, Wellcome Trust Sanger Institute25, Raja Isteri Pengiran Anak Saleha Hospital26, Case Western Reserve University27, University of Tartu28, Estonian Academy of Sciences29, Stony Brook University30, Illumina31, Gladstone Institutes32, University of Helsinki33, University of Washington34, Bashkir State University35, Jaramogi Oginga Odinga University of Science and Technology36, Pompeu Fabra University37, University of Arizona38, University of Cambridge39, Leidos40, Université de Montréal41, University of Utah42, Altai State University43, Council of Scientific and Industrial Research44
TL;DR: It is demonstrated that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.
Abstract: Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.
1,133 citations
Harvard University1, Massachusetts Institute of Technology2, University College London3, University of Hong Kong4, Aix-Marseille University5, University of Geneva6, University of Antioquia7, National Scientific and Technical Research Council8, University of Buenos Aires9, Universidade Federal do Rio Grande do Sul10, Federal University of Paraná11, National Autonomous University of Mexico12, Mexican Social Security Institute13, Instituto Politécnico Nacional14, Nestlé15, Universidad Autónoma de Nuevo León16, University of Santiago de Compostela17, Cayetano Heredia University18, University of Chicago19, Russian Academy of Sciences20, Université de Montréal21, University of Costa Rica22, University of Bern23, Swiss Institute of Bioinformatics24, University of Tarapacá25, Paul Sabatier University26, University of California, Berkeley27, Yale University28, Semel Institute for Neuroscience and Human Behavior29
TL;DR: It is shown that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America.
Abstract: The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved. One contentious issue is whether the settlement occurred by means of a single migration or multiple streams of migration from Siberia. The pattern of dispersals within the Americas is also poorly understood. To address these questions at a higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. Here we show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call 'First American'. However, speakers of Eskimo-Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan speakers on both sides of the Panama isthmus, who have ancestry from both North and South America.
696 citations
University College London1, University of Michigan2, Stanford University3, University of Bern4, University of Antioquia5, University of California, Los Angeles6, Cayetano Heredia University7, University of New Mexico8, Université de Montréal9, University of California, Berkeley10, University of Costa Rica11, Universidade Federal do Rio Grande do Sul12, Federal University of Paraná13, University of Chile14, University of Tarapacá15
TL;DR: Evidence is observed of a higher level of diversity and lower level of population structure in western South America compared to eastern South America, a relative lack of differentiation between Mesoamerican and Andean populations, and a partial agreement on a local scale between genetic similarity and the linguistic classification of populations.
Abstract: We examined genetic diversity and population structure in the American landmass using 678 autosomal microsatellite markers genotyped in 422 individuals representing 24 Native American populations sampled from North, Central, and South America. These data were analyzed jointly with similar data available in 54 other indigenous populations worldwide, including an additional five Native American groups. The Native American populations have lower genetic diversity and greater differentiation than populations from other continental regions. We observe gradients both of decreasing genetic diversity as a function of geographic distance from the Bering Strait and of decreasing genetic similarity to Siberians—signals of the southward dispersal of human populations from the northwestern tip of the Americas. We also observe evidence of: (1) a higher level of diversity and lower level of population structure in western South America compared to eastern South America, (2) a relative lack of differentiation between Mesoamerican and Andean populations, (3) a scenario in which coastal routes were easier for migrating peoples to traverse in comparison with inland routes, and (4) a partial agreement on a local scale between genetic similarity and the linguistic classification of populations. These findings offer new insights into the process of population dispersal and differentiation during the peopling of the Americas.
542 citations
Harvard University1, University of Tübingen2, Max Planck Society3, Hungarian Academy of Sciences4, Howard Hughes Medical Institute5, University College Dublin6, University of Vienna7, University of Coimbra8, University of Ferrara9, University of Adelaide10, Trinity College, Dublin11, University of Cambridge12, Broad Institute13, Emory University14, University of Florence15, Bulgarian Academy of Sciences16, Danube Private University17, Romanian Academy18, Centre national de la recherche scientifique19, Eötvös Loránd University20, Sofia University21, University of Oxford22, University of Wyoming23, University of Zagreb24, Pennsylvania State University25, National Academy of Sciences of Ukraine26, Université de Montréal27, University of Bucharest28, Ludwig Maximilian University of Munich29, University of Edinburgh30, University of Wisconsin-Madison31, University of Palermo32, Croatian Academy of Sciences and Arts33, Naturhistorisches Museum34, Russian Academy of Sciences35, University of Toronto36, University of Latvia37, Durham University38, University of Hull39, Grand Valley State University40, Columbia University41
TL;DR: It is shown that southeastern Europe continued to be a nexus between east and west after the arrival of farmers, with intermittent genetic contact with steppe populations occurring up to 2,000 years earlier than the migrations from the steppe that ultimately replaced much of the population of northern Europe.
Abstract: Farming was first introduced to Europe in the mid-seventh millennium bc, and was associated with migrants from Anatolia who settled in the southeast before spreading throughout Europe. Here, to und ...
447 citations
Cited by
More filters
Journal Article•
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.
11,521 citations
TL;DR: An approach to studying population structure (principal components analysis) is discussed that was first applied to genetic data by Cavalli-Sforza and colleagues, and results from modern statistics are used to develop formal significance tests for population differentiation.
Abstract: Current methods for inferring population structure from genetic data do not provide formal significance tests for population differentiation. We discuss an approach to studying population structure (principal components analysis) that was first applied to genetic data by Cavalli-Sforza and colleagues. We place the method on a solid statistical footing, using results from modern statistics to develop formal significance tests. We also uncover a general “phase change” phenomenon about the ability to detect structure in genetic data, which emerges from the statistical theory we use, and has an important implication for the ability to discover structure in genetic data: for a fixed but large dataset size, divergence between two populations (as measured, for example, by a statistic like FST) below a threshold is essentially undetectable, but a little above threshold, detection will be easy. This means that we can predict the dataset size needed to detect structure.
4,456 citations
TL;DR: The Discriminant Analysis of Principal Components (DAPC) is introduced, a multivariate method designed to identify and describe clusters of genetically related individuals that performs generally better than STRUCTURE at characterizing population subdivision.
Abstract: The dramatic progress in sequencing technologies offers unprecedented prospects for deciphering the organization of natural populations in space and time. However, the size of the datasets generated also poses some daunting challenges. In particular, Bayesian clustering algorithms based on pre-defined population genetics models such as the STRUCTURE or BAPS software may not be able to cope with this unprecedented amount of data. Thus, there is a need for less computer-intensive approaches. Multivariate analyses seem particularly appealing as they are specifically devoted to extracting information from large datasets. Unfortunately, currently available multivariate methods still lack some essential features needed to study the genetic structure of natural populations. We introduce the Discriminant Analysis of Principal Components (DAPC), a multivariate method designed to identify and describe clusters of genetically related individuals. When group priors are lacking, DAPC uses sequential K-means and model selection to infer genetic clusters. Our approach allows extracting rich information from genetic data, providing assignment of individuals to groups, a visual assessment of between-population differentiation, and contribution of individual alleles to population structuring. We evaluate the performance of our method using simulated data, which were also analyzed using STRUCTURE as a benchmark. Additionally, we illustrate the method by analyzing microsatellite polymorphism in worldwide human populations and hemagglutinin gene sequence variation in seasonal influenza. Analysis of simulated data revealed that our approach performs generally better than STRUCTURE at characterizing population subdivision. The tools implemented in DAPC for the identification of clusters and graphical representation of between-group structures allow to unravel complex population structures. Our approach is also faster than Bayesian clustering algorithms by several orders of magnitude, and may be applicable to a wider range of datasets.
3,770 citations
TL;DR: It is shown that 12 per cent of colorectal carcinomas carry somatic deletions in poly(dA . dT) sequences and other simple repeats, and it is concluded that these mutations reflect a previously undescribed form of carcinogenesis in the colon mediated by a mutation in a DNA replication factor resulting in reduced fidelity for replication or repair (a 'mutator mutation').
Abstract: Spontaneous errors in DNA replication have been suggested to play a significant role in neoplastic transformation and to explain the chromosomal alterations seen in cancer cells. A defective replication factor could increase the mutation rate in clonal variants arising during tumour progression, but despite intensive efforts, increases in tumour cell mutation rates have not been unambiguously shown. Here we use an unbiased genomic fingerprinting technique to show that 12 per cent of colorectal carcinomas carry somatic deletions in poly(dA.dT) sequences and other simple repeats. We estimate that cells from these tumours can carry more than 100,000 such mutations. Only tumours with affected poly(dA.dT) sequences carry mutations in the other simple repeats examined, and such mutations can be found in all neoplastic regions of multiple tumours from the same patient, including adenomas. Tumours with these mutations show distinctive genotypic and phenotypic features. We conclude that these mutations reflect a previously undescribed form of carcinogenesis in the colon (predisposition to which may be inherited) mediated by a mutation in a DNA replication factor resulting in reduced fidelity for replication or repair (a 'mutator mutation').
2,724 citations
TL;DR: It is demonstrated that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laboratory reagents, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass.
Abstract: The study of microbial communities has been revolutionised in recent years by the widespread adoption of culture independent analytical techniques such as 16S rRNA gene sequencing and metagenomics. One potential confounder of these sequence-based approaches is the presence of contamination in DNA extraction kits and other laboratory reagents. In this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laboratory reagents, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass. Contamination impacts both PCR-based 16S rRNA gene surveys and shotgun metagenomics. We provide an extensive list of potential contaminating genera, and guidelines on how to mitigate the effects of contamination. These results suggest that caution should be advised when applying sequence-based techniques to the study of microbiota present in low biomass environments. Concurrent sequencing of negative control samples is strongly advised.
2,459 citations