FRANC: a unified framework for multi-way local ancestry deconvolution with high density SNP data

2019 ◽  
Vol 21 (5) ◽  
pp. 1837-1845
Author(s):  
Ephifania Geza ◽  
Nicola J Mulder ◽  
Emile R Chimusa ◽  
Gaston K Mazandu
Keyword(s):  
Phenotypic Variability ◽  
Modern Human ◽  
Genomic Variation ◽  
Unified Framework ◽  
Local Ancestry ◽  
Human Heredity ◽  
Snp Data ◽  
Variation Patterns ◽  
Adaptive Processes ◽  
Local Ancestry Inference

Abstract Several thousand genomes have been completed with millions of variants identified in the human deoxyribonucleic acid sequences. These genomic variations, especially those introduced by admixture, significantly contribute to a remarkable phenotypic variability with medical and/or evolutionary implications. Elucidating local ancestry estimates is necessary for a better understanding of genomic variation patterns throughout modern human evolution and adaptive processes, and consequences in human heredity and health. However, existing local ancestry deconvolution tools are accessible as individual scripts, each requiring input and producing output in its own complex format. This limits the user’s ability to retrieve local ancestry estimates. We introduce a unified framework for multi-way local ancestry inference, FRANC, integrating eight existing state-of-the-art local ancestry deconvolution tools. FRANC is an adaptable, expandable and portable tool that manipulates tool-specific inputs, deconvolutes ancestry and standardizes tool-specific results. To facilitate both medical and population genetics studies, FRANC requires convenient and easy to manipulate input files and allows users to choose output formats to ease their use in further potential local ancestry deconvolution applications.

scholarly journals A comprehensive survey of models for dissecting local ancestry deconvolution in human genome

2018 ◽  
Vol 20 (5) ◽  
pp. 1709-1724 ◽  
Author(s):  
Ephifania Geza ◽  
Jacquiline Mugo ◽  
Nicola J Mulder ◽  
Ambroise Wonkam ◽  
Emile R Chimusa ◽  
...  
Keyword(s):  
Modern Human ◽  
Human Populations ◽  
Population Admixture ◽  
Local Ancestry ◽  
The Past ◽  
Challenges And Opportunities ◽  
Adaptive Processes ◽  
Comprehensive Survey ◽  
Simulation Results ◽  
Shed Light

Abstract Over the past decade, studies of admixed populations have increasingly gained interest in both medical and population genetics. These studies have so far shed light on the patterns of genetic variation throughout modern human evolution and have improved our understanding of the demographics and adaptive processes of human populations. To date, there exist about 20 methods or tools to deconvolve local ancestry. These methods have merits and drawbacks in estimating local ancestry in multiway admixed populations. In this article, we survey existing ancestry deconvolution methods, with special emphasis on multiway admixture, and compare these methods based on simulation results reported by different studies, computational approaches used, including mathematical and statistical models, and biological challenges related to each method. This should orient users on the choice of an appropriate method or tool for given population admixture characteristics and update researchers on current advances, challenges and opportunities behind existing ancestry deconvolution methods.

scholarly journals Evolutionary Subdivision of Domestic Chickens: Implications for Local Breeds as Assessed by Phenotype and Genotype in Comparison to Commercial and Fancy Breeds

Agriculture ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 914
Author(s):  
Tatyana A. Larkina ◽  
Olga Y. Barkova ◽  
Grigoriy K. Peglivanyan ◽  
Olga V. Mitrofanova ◽  
Natalia V. Dementieva ◽  
...  
Keyword(s):  
Egg Production ◽  
Phenotypic Variability ◽  
Genotypic Variation ◽  
Significant Proportion ◽  
Genomic Variation ◽  
Classification Model ◽  
Genotypic Variability ◽  
Marker Assisted Breeding ◽  
Breeding Programs ◽  
Clustering Model

To adjust breeding programs for local, commercial, and fancy breeds, and to implement molecular (marker-assisted) breeding, a proper comprehension of phenotypic and genotypic variation is a sine qua non for breeding progress in animal production. Here, we investigated an evolutionary subdivision of domestic chickens based on their phenotypic and genotypic variability using a wide sample of 49 different breeds/populations. These represent a significant proportion of the global chicken gene pool and all major purposes of breed use (according to their traditional classification model), with many of them being characterized by a synthetic genetic structure and notable admixture. We assessed their phenotypic variability in terms of body weight, body measurements, and egg production. From this, we proposed a phenotypic clustering model (PCM) including six evolutionary lineages of breed formation: egg-type, meat-type, dual purpose (egg-meat and meat-egg), game, fancy, and Bantam. Estimation of genotypic variability was carried out using the analysis of five SNPs, i.e., at the level of genomic variation at the NCAPG-LCORL locus. Based on these data, two generally similar genotypic clustering models (GCM1 and GCM2) were inferred that also had several overlaps with PCM. Further research for SNPs associated with economically important traits can be instrumental in marker-assisted breeding programs.

scholarly journals Testing the utility of dental morphological trait combinations for inferring human neutral genetic variation

2020 ◽  
Vol 117 (20) ◽  
pp. 10769-10777 ◽  
Author(s):  
Hannes Rathmann ◽  
Hugo Reyes-Centeno
Keyword(s):  
Modern Human ◽  
Genomic Variation ◽  
Future Research ◽  
Human Populations ◽  
Dental Morphology ◽  
Genomic Signatures ◽  
Neutral Genetic Variation ◽  
Tooth Form ◽  
Dental Traits ◽  
Population Affinity

Researchers commonly rely on human dental morphological features in order to reconstruct genetic affinities among past individuals and populations, particularly since teeth are often the best preserved part of a human skeleton. Tooth form is considered to be highly heritable and selectively neutral and, therefore, to be an excellent proxy for DNA when none is available. However, until today, it remains poorly understood whether certain dental traits or trait combinations preserve neutral genomic signatures to a greater degree than others. Here, we address this long-standing research gap by systematically testing the utility of 27 common dental traits and >134 million possible trait combinations in reflecting neutral genomic variation in a worldwide sample of modern human populations. Our analyses reveal that not all traits are equally well-suited for reconstructing population affinities. Whereas some traits largely reflect neutral variation and therefore evolved primarily as a result of genetic drift, others can be linked to nonstochastic processes such as natural selection or hominin admixture. We also demonstrate that reconstructions of population affinity based on many traits are not necessarily more reliable than those based on only a few traits. Importantly, we find a set of highly diagnostic trait combinations that preserve neutral genetic signals best (up to x∼r = 0.580; 95% r range = 0.293 to 0.758; P = 0.001). We propose that these trait combinations should be prioritized in future research, as they allow for more accurate inferences about past human population dynamics when using dental morphology as a proxy for DNA.

scholarly journals Simulation-Based Evaluation of Three Methods for Local Ancestry Deconvolution of Non-model Crop Species Genomes

2019 ◽  
Vol 10 (2) ◽  
pp. 569-579
Author(s):  
Aurélien Cottin ◽  
Benjamin Penaud ◽  
Jean-Christophe Glaszmann ◽  
Nabila Yahiaoui ◽  
Mathieu Gautier
Keyword(s):  
R Package ◽  
Source Population ◽  
Crop Species ◽  
Data Set ◽  
Reproduction Mode ◽  
Local Ancestry ◽  
Ancestry Inference ◽  
Source Populations ◽  
Inference Methods ◽  
Local Ancestry Inference

Hybridizations between species and subspecies represented major steps in the history of many crop species. Such events generally lead to genomes with mosaic patterns of chromosomal segments of various origins that may be assessed by local ancestry inference methods. However, these methods have mainly been developed in the context of human population genetics with implicit assumptions that may not always fit plant models. The purpose of this study was to evaluate the suitability of three state-of-the-art inference methods (SABER, ELAI and WINPOP) for local ancestry inference under scenarios that can be encountered in plant species. For this, we developed an R package to simulate genotyping data under such scenarios. The tested inference methods performed similarly well as far as representatives of source populations were available. As expected, the higher the level of differentiation between ancestral source populations and the lower the number of generations since admixture, the more accurate were the results. Interestingly, the accuracy of the methods was only marginally affected by i) the number of ancestries (up to six tested); ii) the sample design (i.e., unbalanced representation of source populations); and iii) the reproduction mode (e.g., selfing, vegetative propagation). If a source population was not represented in the data set, no bias was observed in inference accuracy for regions originating from represented sources and regions from the missing source were assigned differently depending on the methods. Overall, the selected ancestry inference methods may be used for crop plant analysis if all ancestral sources are known.

scholarly journals RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference

2013 ◽  
Vol 93 (2) ◽  
pp. 278-288 ◽  
Author(s):  
Brian K. Maples ◽  
Simon Gravel ◽  
Eimear E. Kenny ◽  
Carlos D. Bustamante
Keyword(s):  
Local Ancestry ◽  
Modeling Approach ◽  
Ancestry Inference ◽  
Local Ancestry Inference

scholarly journals Putting RFMix and ADMIXTURE to the test in a complex admixed population

2019 ◽  
Author(s):  
Caitlin Uren ◽  
Eileen G. Hoal ◽  
Marlo Möller
Keyword(s):  
Association Studies ◽  
Structured Populations ◽  
Human Populations ◽  
Computational Tools ◽  
Local Ancestry ◽  
Population Structure Analysis ◽  
Admixed Population ◽  
Ancestry Inference ◽  
Global And Local ◽  
Local Ancestry Inference

AbstractGlobal and local ancestry inference in admixed human populations can be performed using computational tools implementing distinct algorithms, such as RFMix and ADMIXTURE. The accuracy of these tools has been tested largely on populations with relatively straightforward admixture histories but little is known about how well they perform in more complex admixture scenarios. Using simulations, we show that RFMix outperforms ADMIXTURE in determining global ancestry proportions in a complex 5-way admixed population. In addition, RFMix correctly assigns local ancestry with an accuracy of 89%. The increase in reported local ancestry inference accuracy in this population (as compared to previous studies) can largely be attributed to the recent availability of large-scale genotyping data for more representative reference populations. The ability of RFMix to determine global and local ancestry to a high degree of accuracy, allows for more reliable population structure analysis, scans for natural selection, admixture mapping and case-control association studies. This study highlights the utility of the extension of computational tools to become more relevant to genetically structured populations, as seen with RFMix. This is particularly noteworthy as modern-day societies are becoming increasingly genetically complex and some genetic tools are therefore less appropriate. We therefore suggest that RFMix be used for both global and local ancestry estimation in complex admixture scenarios.

scholarly journals LAIT: a local ancestry inference toolkit

BMC Genetics ◽  
2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Daniel Hui ◽  
Zhou Fang ◽  
Jerome Lin ◽  
Qing Duan ◽  
Yun Li ◽  
...  
Keyword(s):  
Local Ancestry ◽  
Ancestry Inference ◽  
Local Ancestry Inference
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