Dating admixture events is unsolved problem in multi-way admixed populations

Chimusa, Emile R.; Defo, Joel; Thami, Prisca K; Awany, Denis; Mulisa, Delesa Damena; Allali, Imane; Ghazal, Hassan; Moussa, Ahmed; Mazandu, Gaston K.

doi:10.1093/bib/bby112

Cited by 19 publications

(24 citation statements)

References 57 publications

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“…Models based on ancestry blocks for dating admixture are formulated using either an empirical criteria or variants associated with a specific population. In order to determine the average length of the admixture block, these methods then assign ancestry on predefined windows using either wavelet transformation or conditional random fields [35]. On the other hand, there are models requiring rapid decrease in haplotype block sizes to estimate the date of the admixture event [36].…”

Section: Models For Dating Admixture Events In a Genomementioning

confidence: 99%

“…However, this LD formed often decreases with time. Also, the rate of decay of LD is a function of recombination and the proportion of the admixture [35]. Inversely, many methods employ this rate to calculate the time since the admixture event occurs.…”

Section: Ld-based Models For Dating Admixture Eventsmentioning

confidence: 99%

“…This correlation coefficient is further used to measure the LD with ancestral populations [37]. The time of admixture is then determined by analyzing the correlation with respect to the genetic distance, and also fitting using a least squares method the decay of the correlation [35]. This method got improved in 2011 by Loh et al [18].…”

Section: Ld-based Models For Dating Admixture Eventsmentioning

confidence: 99%

“…Their method consists in using the likelihood ratio test to identify the best model for the inference of the date of admixture. Furthermore, they are able to estimate several admixture events with the given optimal model [35].…”

Section: Haplotype Distribution-based Models For Dating Admixture Eventsmentioning

confidence: 99%

“…Finally, different existing models and tools for dating admixture events are summarized in Table 2 extracted from Chimusa et al [35]. 3.…”

Section: Haplotype Distribution-based Models For Dating Admixture Eventsmentioning

confidence: 99%

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Orienting Future Trends in Local Ancestry Deconvolution Models to Optimally Decipher Admixed Individual Genome Variations

Mazandu¹,

Geza²,

Seuneu³

et al. 2019

Bioinformatics Tools for Detection and Clinical Interpretation of Genomic Variations

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Rapid advances in sequencing and genotyping technologies have significantly contributed to shaping the area of medical and population genetics. Several thousand genomes are completed with millions of variants identified in the human deoxyribonucleic acid (DNA) sequences. These genomic variations highly influence changes in phenotypic manifestations and physiological functions of different individuals or population groups. Of particular importance are variations introduced by admixture event, contributing significantly to a remarkable phenotypic variability with medical and/or evolutionary implications. In this case, knowledge of local ancestry estimates and date of admixture is of utmost importance for a better understanding of genomic variation patterns throughout modern human evolution and adaptive processes. In this chapter, we survey existing local ancestry deconvolution and dating admixture event models to identify possible gaps that still need to be filled and orient future trends in designing more effective models, which account for current challenges and produce more accurate and biological relevant estimates.

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Section: Models For Dating Admixture Events In a Genomementioning

confidence: 99%

Section: Ld-based Models For Dating Admixture Eventsmentioning

confidence: 99%

Section: Ld-based Models For Dating Admixture Eventsmentioning

confidence: 99%

Section: Haplotype Distribution-based Models For Dating Admixture Eventsmentioning

confidence: 99%

“…Finally, different existing models and tools for dating admixture events are summarized in Table 2 extracted from Chimusa et al [35]. 3.…”

Section: Haplotype Distribution-based Models For Dating Admixture Eventsmentioning

confidence: 99%

See 3 more Smart Citations

Orienting Future Trends in Local Ancestry Deconvolution Models to Optimally Decipher Admixed Individual Genome Variations

Mazandu¹,

Geza²,

Seuneu³

et al. 2019

Bioinformatics Tools for Detection and Clinical Interpretation of Genomic Variations

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Genetic characterization of two North Italian villages: A story of isolation, ancient admixture, and genetic drift

Mezzavilla

Cocca

Delser

et al. 2022

American Journal of Biological Anthropology

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Objectives Population isolates represent a focus of interest because of their particular genetic history and the possibility of mapping peculiar deleterious variants. Here we investigated the pattern of genetic variation in two North Italian villages: Rotzo (RTZ) and Stoccareddo (STC), in the Asiago plateau. Materials and methods We genotyped over 800 individuals for more than 600.000 markers. We investigated the isolation level by analyzing runs of homozygosity (ROH) and the level of population structure. Then we estimated the time of admixture and the relationship between ancient genomes and these two villages. Finally, we looked at the effect of genetic drift on deleterious variants. Results We highlighted a different isolation level between RTZ and STC; despite the average number of ROH being similar between the two villages, RTZ shows a higher level of total homozygosity. We estimated, from different sources, that the time of admixture for the ancestors of these two populations was between 113 and 88 generations ago. We discovered that a deleterious variant in MCUB gene (rs78025076), which is linked to several lipid traits, is entirely absent in RTZ and at 1%frequency in STC. In contrast, the risk allele frequency is 2% in Europe and 2.4% in North‐East Italy. Discussion These results show the importance of a genetic characterization of geographically isolated populations. Their vast array of past history could highlight specific events in the past and help describe deleterious variants and traits distribution in different regions.

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Prospective avenues for human population genomics and disease mapping in southern Africa

et al. 2020

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Population substructure within human populations is globally evident and a well-known confounding factor in many genetic studies. In contrast, admixture mapping exploits population stratification to detect genotype-phenotype correlations in admixed populations. Southern Africa has untapped potential for disease mapping of ancestry-specific disease risk alleles due to the distinct genetic diversity in its populations compared to other populations worldwide. This diversity contributes to a number of phenotypes, including ancestry-specific disease risk and response to pathogens. Although the 1000 Genomes Project significantly improved our understanding of genetic variation globally, southern African populations are still severely underrepresented in biomedical and human genetic studies due to insufficient large-scale publicly available data. In addition to a lack of genetic data in public repositories, existing software, algorithms and resources used for imputation and phasing of genotypic data (amongst others) are largely ineffective for populations with a complex genetic architecture such as that seen in southern Africa. This review article, therefore, aims to summarise the current limitations of conducting genetic studies on populations with a complex genetic architecture to identify potential areas for further research and development. KeywordsSouthern Africa • Population genetics • Admixture mapping • Disease risk alleles Communicated by S. Hohmann.

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Dating admixture events is unsolved problem in multi-way admixed populations

Cited by 19 publications

References 57 publications

Orienting Future Trends in Local Ancestry Deconvolution Models to Optimally Decipher Admixed Individual Genome Variations

Orienting Future Trends in Local Ancestry Deconvolution Models to Optimally Decipher Admixed Individual Genome Variations

Genetic characterization of two North Italian villages: A story of isolation, ancient admixture, and genetic drift

Prospective avenues for human population genomics and disease mapping in southern Africa

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