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1.
  • Duforet-Frebourg, Nicolas, et al. (creator_code:aut_t)
  • HaploPOP : a software that improves population assignment by combining markers into haplotypes
  • 2015
  • record:In_t: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 16
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Background: In ecology and forensics, some population assignment techniques use molecular markers to assign individuals to known groups. However, assigning individuals to known populations can be difficult if the level of genetic differentiation among populations is small. Most assignment studies handle independent markers, often by pruning markers in Linkage Disequilibrium (LD), ignoring the information contained in the correlation among markers due to LD. Results: To improve the accuracy of population assignment, we present an algorithm, implemented in the HaploPOP software, that combines markers into haplotypes, without requiring independence. The algorithm is based on the Gain of Informativeness for Assignment that provides a measure to decide if a pair of markers should be combined into haplotypes, or not, in order to improve assignment. Because complete exploration of all possible solutions for constructing haplotypes is computationally prohibitive, our approach uses a greedy algorithm based on windows of fixed sizes. We evaluate the performance of HaploPOP to assign individuals to populations using a split-validation approach. We investigate both simulated SNPs data and dense genotype data from individuals from Spain and Portugal. Conclusions: Our results show that constructing haplotypes with HaploPOP can substantially reduce assignment error. The HaploPOP software is freely available as a command-line software at www.ieg.uu.se/Jakobsson/software/HaploPOP/.
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2.
  • Gattepaille, Lucie M., et al. (creator_code:aut_t)
  • Combining Markers into Haplotypes Can Improve Population Structure Inference
  • 2012
  • record:In_t: Genetics. - : Oxford University Press (OUP). - 0016-6731 .- 1943-2631. ; 190:1, s. 159-174
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • High-throughput genotyping and sequencing technologies can generate dense sets of genetic markers for large numbers of individuals. For most species, these data will contain many markers in linkage disequilibrium (LD). To utilize such data for population structure inference, we investigate the use of haplotypes constructed by combining the alleles at single-nucleotide polymorphisms (SNPs). We introduce a statistic derived from information theory, the gain of informativeness for assignment (GIA), which quantifies the additional information for assigning individuals to populations using haplotype data compared to using individual loci separately. Using a two-loci-two-allele model, we demonstrate that combining markers in linkage equilibrium into haplotypes always leads to non-positive GIA, suggesting that combining the two markers is not advantageous for ancestry inference. However, for loci in LD, GIA is often positive, suggesting that assignment can be improved by combining markers into haplotypes. Using GIA as a criterion for combining markers into haplotypes, we demonstrate for simulated data a significant improvement of assigning individuals to candidate populations. For the many cases that we investigate, incorrect assignment was reduced between 26% and 97% using haplotype data. For empirical data from French and German individuals, the incorrectly assigned individuals can, for example, be decreased by 73% using haplotypes. Our results can be useful for challenging population structure and assignment problems, in particular for studies where large-scale population-genomic data are available.
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3.
  • Gattepaille, Lucie M., et al. (creator_code:aut_t)
  • Inferring population size changes with sequence and SNP data : lessons from human bottlenecks
  • 2013
  • record:In_t: Heredity. - : Springer Science and Business Media LLC. - 0018-067X .- 1365-2540. ; 110:5, s. 409-419
  • swepub:Mat_researchreview_t (swepub:level_refereed_t)abstract
    • Reconstructing historical variation of population size from sequence and single-nucleotide polymorphism (SNP) data is valuable for understanding the evolutionary history of species. Changes in the population size of humans have been thoroughly investigated, and we review different methodologies of demographic reconstruction, specifically focusing on human bottlenecks. In addition to the classical approaches based on the site-frequency spectrum (SFS) or based on linkage disequilibrium, we also review more recent approaches that utilize atypical shared genomic fragments, such as identical by descent or homozygous segments between or within individuals. Compared with methods based on the SFS, these methods are well suited for detecting recent bottlenecks. In general, all these various methods suffer from bias and dependencies on confounding factors such as population structure or poor specification of the mutational and recombination processes, which can affect the demographic reconstruction. With the exception of SFS-based methods, the effects of confounding factors on the inference methods remain poorly investigated. We conclude that an important step when investigating population size changes rests on validating the demographic model by investigating to what extent the fitted demographic model can reproduce the main features of the polymorphism data. 
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4.
  • Schlebusch, Carina, 1977-, et al. (creator_code:aut_t)
  • Khoe-San Genomes Reveal Unique Variation and Confirm the Deepest Population Divergence in Homo sapiens
  • 2020
  • record:In_t: Molecular biology and evolution. - : Oxford University Press (OUP). - 0737-4038 .- 1537-1719. ; 37:10, s. 2944-2954
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • The southern African indigenous Khoe-San populations harbor the most divergent lineages of all living peoples. Exploring their genomes is key to understanding deep human history. We sequenced 25 full genomes from five Khoe-San populations, revealing many novel variants, that 25% of variants are unique to the Khoe-San, and that the Khoe-San group harbors the greatest level of diversity across the globe. In line with previous studies, we found several gene regions with extreme values in genome-wide scans for selection, potentially caused by natural selection in the lineage leading to Homo sapiens and more recent in time. These gene regions included immunity-, sperm-, brain-, diet-, and muscle-related genes. When accounting for recent admixture, all Khoe-San groups display genetic diversity approaching the levels in other African groups and a reduction in effective population size starting around 100,000 years ago. Hence, all human groups show a reduction in effective population size commencing around the time of the Out-of-Africa migrations, which coincides with changes in the paleoclimate records, changes that potentially impacted all humans at the time.
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5.
  • Schlebusch, Carina M., et al. (creator_code:aut_t)
  • Genomic Variation in Seven Khoe-San Groups Reveals Adaptation and Complex African History
  • 2012
  • record:In_t: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 338:6105, s. 374-379
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • The history of click-speaking Khoe-San, and African populations in general, remains poorly understood. We genotyped ∼2.3 million SNPs in 220 southern Africans and found that the Khoe-San diverged from other populations ≥100,000 years ago, but structure within the Khoe-San dated back to about 35,000 years ago. Genetic variation in various sub-Saharan populations did not localize the origin of modern humans to a single geographic region within Africa; instead, it indicated a history of admixture and stratification. We found evidence of adaptation targeting muscle function and immune response, potential adaptive introgression of UV-light protection, and selection predating modern human diversification involving skeletal and neurological development. These new findings illustrate the importance of African genomic diversity in understanding human evolutionary history.
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6.
  • Schlebusch, Carina M., et al. (creator_code:aut_t)
  • Human Adaptation to Arsenic-Rich Environments
  • 2015
  • record:In_t: Molecular biology and evolution. - : Oxford University Press (OUP). - 0737-4038 .- 1537-1719. ; 32:6, s. 1544-1555
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Adaptation drives genomic changes; however, evidence of specific adaptations in humans remains limited. We found that inhabitants of the northern Argentinean Andes, an arid region where elevated arsenic concentrations in available drinking water is common, have unique arsenic metabolism, with efficient methylation and excretion of the major metabolite dimethylated arsenic and a less excretion of the highly toxic monomethylated metabolite. We genotyped women from this population for 4,301,332 single nucleotide polymorphisms (SNPs) and found a strong association between the AS3MT (arsenic [+3 oxidation state] methyltransferase) gene and mono- and dimethylated arsenic in urine, suggesting that AS3MT functions as the major gene for arsenic metabolism in humans. We found strong genetic differentiation around AS3MT in the Argentinean Andes population, compared with a highly related Peruvian population (F-ST = 0.014) from a region with much less environmental arsenic. Also, 13 of the 100 SNPs with the highest genome-wide Locus-Specific Branch Length occurred near AS3MT. In addition, our examination of extended haplotype homozygosity indicated a selective sweep of the Argentinean Andes population, in contrast to Peruvian and Colombian populations. Our data show that adaptation to tolerate the environmental stressor arsenic has likely driven an increase in the frequencies of protective variants of AS3MT, providing the first evidence of human adaptation to a toxic chemical.
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