Mitonuclear linkage disequilibrium in human populations

There is extensive evidence from model systems that disrupting associations between co-adapted mitochondrial and nuclear genotypes can lead to deleterious and even lethal consequences. While it is tempting to extrapolate from these observations and make inferences about the human-health effects of altering mitonuclear associations, the importance of such associations may vary greatly among species, depending on population genetics, demographic history and other factors. Remarkably, despite the extensive study of human population genetics, the statistical associations between nuclear and mitochondrial alleles remain largely uninvestigated. We analysed published population genomic data to test for signatures of historical selection to maintain mitonuclear associations, particularly those involving nuclear genes that encode mitochondrial-localized proteins (N-mt genes). We found that significant mitonuclear linkage disequilibrium (LD) exists throughout the human genome, but these associations were generally weak, which is consistent with the paucity of population genetic structure in humans. Although mitonuclear LD varied among genomic regions (with especially high levels on the X chromosome), N-mt genes were statistically indistinguishable from background levels, suggesting that selection on mitonuclear epistasis has not preferentially maintained associations involving this set of loci at a species-wide level. We discuss these findings in the context of the ongoing debate over mitochondrial replacement therapy.

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Molecular Population Genetics

A Primer of Population Genetics and Genomics ◽

10.1093/oso/9780198862291.003.0007 ◽

2020 ◽

pp. 179-224

Author(s):

Daniel L. Hartl

Keyword(s):

Population Genetics ◽

Population Dynamics ◽

Amino Acid ◽

Frequency Spectrum ◽

Demographic History ◽

Human Populations ◽

Noncoding Dna ◽

Molecular Population Genetics ◽

Amino Acid Divergence ◽

Site Frequency Spectrum

Chapter 7 is an introduction to molecular population genetics that includes the principal concepts of nucleotide polymorphism and divergence, the site frequency spectrum, and tests of selection and their limitations. Highlighted are rates of nucleotide substitution in coding and noncoding DNA, nucleotide and amino acid divergence between species, corrections for multiple substitutions, and the molecular clock. Discussion of the folded and unfolded site frequency spectrum includes the strengths and limitations of Tajima’s D, Fay and Wu’s H, and other measures. The chapter also discusses an emerging consensus to resolve the celebrated selection–neutrality controversy. It also includes examination of demographic history through the use of ancient DNA with special emphasis on the surprising findings in regard to the ancestral makeup of contemporary human populations. Also discussed are the population dynamics of transposable elements in prokaryotes and eukaryotes.

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Demographic history and linkage disequilibrium in human populations

Nature Genetics ◽

10.1038/ng1297-435 ◽

1997 ◽

Vol 17 (4) ◽

pp. 435-438 ◽

Cited By ~ 111

Author(s):

Maris Laan ◽

Svante Pääbo

Keyword(s):

Linkage Disequilibrium ◽

Demographic History ◽

Human Populations

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A Microsatellite-Based Multilocus Screen for the Identification of Local Selective Sweeps

Genetics ◽

10.1093/genetics/160.2.753 ◽

2002 ◽

Vol 160 (2) ◽

pp. 753-763 ◽

Cited By ~ 12

Author(s):

Christian Schlötterer

Keyword(s):

Microsatellite Loci ◽

Selective Sweep ◽

Demographic History ◽

Human Populations ◽

Selective Sweeps ◽

Test Statistic ◽

Data Set ◽

History Of ◽

Microsatellite Mutation ◽

Genomic Regions

AbstractWith the availability of completely sequenced genomes, multilocus scans of natural variability have become a feasible approach for the identification of genomic regions subjected to natural and artificial selection. Here, I introduce a new multilocus test statistic, ln RV, which is based on the ratio of observed variances in repeat number at a set of microsatellite loci in two groups of populations. The distribution of ln RV values captures demographic history of the populations as well as variation in microsatellite mutation among loci. Given that microsatellite loci associated with a recent selective sweep differ from the remainder of the genome, they are expected to fall outside of the distribution of neutral ln RV values. The ln RV test statistic is applied to a data set of 94 loci typed in eight non-African and two African human populations.

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Models of archaic admixture and recent history from two-locus statistics

10.1101/489401 ◽

2018 ◽

Cited By ~ 4

Author(s):

Aaron P. Ragsdale ◽

Simon Gravel

Keyword(s):

Genetic Diversity ◽

Linkage Disequilibrium ◽

Evolutionary Biology ◽

Demographic History ◽

Population History ◽

Human Populations ◽

Evolutionary Models ◽

Human History ◽

Wide Range ◽

Archaic Admixture

AbstractWe learn about population history and underlying evolutionary biology through patterns of genetic polymorphism. Many approaches to reconstruct evolutionary histories focus on a limited number of informative statistics describing distributions of allele frequencies or patterns of linkage disequilibrium. We show that many commonly used statistics are part of a broad family of two-locus moments whose expectation can be computed jointly and rapidly under a wide range of scenarios, including complex multi-population demographies with continuous migration and admixture events. A full inspection of these statistics reveals that widely used models of human history fail to predict simple patterns of linkage disequilibrium. To jointly capture the information contained in classical and novel statistics, we implemented a tractable likelihood-based inference framework for demographic history. Using this approach, we show that human evolutionary models that include archaic admixture in Africa, Asia, and Europe provide a much better description of patterns of genetic diversity across the human genome. We estimate that an unidentified, deeply diverged population admixed with modern humans within Africa both before and after the split of African and Eurasian populations, contributing 4-8% genetic ancestry to individuals in world-wide populations.Author SummaryThroughout human history, populations have expanded and contracted, split and merged, and ex-changed migrants. Because these events affected genetic diversity, we can learn about human history by comparing predictions from evolutionary models to genetic data. Here, we show how to rapidly compute such predictions for a wide range of diversity measures within and across populations under complex demographic scenarios. While widely used models of human history accurately predict common measures of diversity, we show that they strongly underestimate the co-occurence of low frequency mutations within human populations in Asia, Europe, and Africa. Models allowing for archaic admixture, the relatively recent mixing of human populations with deeply diverged human lineages, resolve this discrepancy. We use such models to infer demographic models that include both recent and ancient features of human history. We recover the well-characterized admixture of Neanderthals in Eurasian populations, as well as admixture from an as-yet unknown diverged human population within Africa, further suggesting that admixture with deeply diverged lineages occurred multiple times in human history. By simultaneously testing model predictions for a broad range of diversity statistics, we can assess the robustness of common evolutionary models, identify missing historical events, and build more informed models of human demography.

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Origin and formation of Yaponesians based on genome sequences

Impact ◽

10.21820/23987073.2020.7.56 ◽

2020 ◽

Vol 2020 (7) ◽

pp. 56-58

Author(s):

Naruya Saitou

Keyword(s):

Population Genetics ◽

Human Migration ◽

Human Populations ◽

Genome Sequences ◽

Japanese Archipelago ◽

Broad Term ◽

The Japanese Archipelago ◽

Ebb And Flow ◽

National Institute Of Genetics

The ebb and flow of human migration across the planet can nowadays be probed with advanced archaeology, linguistics, anthropology and genomics. Together, these can provide a convincing picture of the various divergences and convergences of different human populations across vast areas. It is now possible to better understand how, why and where a particular group or society arose. Professor Naruya Saitou of the Population Genetics Laboratory at the National Institute of Genetics in Mishima has dedicated his career to the synthesis of these disciplines. The current focus of his research is on understanding the origins and formation of the Yaponesian people. This broad term was coined by writer Toshio Shimao in 1960s to encompass the diverse peoples of the Japanese Archipelago over its many thousands of years of inhabitation. Saitou's research is helping to uncover Japan's ancient past.

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A Primer of Population Genetics and Genomics

10.1093/oso/9780198862291.001.0001 ◽

2020 ◽

Author(s):

Daniel L. Hartl

Keyword(s):

Population Genetics ◽

Complex Traits ◽

Evolutionary Biology ◽

Knowledge Retention ◽

Learning By Doing ◽

Human Populations ◽

Gene Drive ◽

Molecular Population Genetics ◽

Genetics And Genomics ◽

And Mathematics

A Primer of Population Genetics and Genomics, 4th edition, has been completely revised and updated to provide a concise but comprehensive introduction to the basic concepts of population genetics and genomics. Recent textbooks have tended to focus on such specialized topics as the coalescent, molecular evolution, human population genetics, or genomics. This primer bucks that trend by encouraging a broader familiarity with, and understanding of, population genetics and genomics as a whole. The overview ranges from mating systems through the causes of evolution, molecular population genetics, and the genomics of complex traits. Interwoven are discussions of ancient DNA, gene drive, landscape genetics, identifying risk factors for complex diseases, the genomics of adaptation and speciation, and other active areas of research. The principles are illuminated by numerous examples from a wide variety of animals, plants, microbes, and human populations. The approach also emphasizes learning by doing, which in this case means solving numerical or conceptual problems. The rationale behind this is that the use of concepts in problem-solving lead to deeper understanding and longer knowledge retention. This accessible, introductory textbook is aimed principally at students of various levels and abilities (from senior undergraduate to postgraduate) as well as practising scientists in the fields of population genetics, ecology, evolutionary biology, computational biology, bioinformatics, biostatistics, physics, and mathematics.

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A Scan for Linkage Disequilibrium Across the Human Genome

Genetics ◽

10.1093/genetics/152.4.1711 ◽

1999 ◽

Vol 152 (4) ◽

pp. 1711-1722 ◽

Cited By ~ 4

Author(s):

Gavin A Huttley ◽

Michael W Smith ◽

Mary Carrington ◽

Stephen J O’Brien

Keyword(s):

Linkage Disequilibrium ◽

Human Genome ◽

Pedigree Analysis ◽

Exact Test ◽

Genomic Scale ◽

Genomic Regions ◽

Formal Test ◽

Scale Data ◽

Short Tandem ◽

Tandem Repeat Polymorphism

Abstract Linkage disequilibrium (LD), the tendency for alleles of linked loci to co-occur nonrandomly on chromosomal haplotypes, is an increasingly useful phenomenon for (1) revealing historic perturbation of populations including founder effects, admixture, or incomplete selective sweeps; (2) estimating elapsed time since such events based on time-dependent decay of LD; and (3) disease and phenotype mapping, particularly for traits not amenable to traditional pedigree analysis. Because few descriptions of LD for most regions of the human genome exist, we searched the human genome for the amount and extent of LD among 5048 autosomal short tandem repeat polymorphism (STRP) loci ascertained as specific haplotypes in the European CEPH mapping families. Evidence is presented indicating that ∼4% of STRP loci separated by <4.0 cM are in LD. The fraction of locus pairs within these intervals that display small Fisher’s exact test (FET) probabilities is directly proportional to the inverse of recombination distance between them (1/cM). The distribution of LD is nonuniform on a chromosomal scale and in a marker density-independent fashion, with chromosomes 2, 15, and 18 being significantly different from the genome average. Furthermore, a stepwise (locus-by-locus) 5-cM sliding-window analysis across 22 autosomes revealed nine genomic regions (2.2-6.4 cM), where the frequency of small FET probabilities among loci was greater than or equal to that presented by the HLA on chromosome 6, a region known to have extensive LD. Although the spatial heterogeneity of LD we detect in Europeans is consistent with the operation of natural selection, absence of a formal test for such genomic scale data prevents eliminating neutral processes as the evolutionary origin of the LD.

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Modeling Linkage Disequilibrium and Identifying Recombination Hotspots Using Single-Nucleotide Polymorphism Data

Genetics ◽

10.1093/genetics/165.4.2213 ◽

2003 ◽

Vol 165 (4) ◽

pp. 2213-2233 ◽

Cited By ~ 41

Author(s):

Na Li ◽

Matthew Stephens

Keyword(s):

Linkage Disequilibrium ◽

Recombination Rate ◽

Population Sample ◽

Simulated Data ◽

Region Of Interest ◽

Population Data ◽

Recombination Rates ◽

Single Nucleotide ◽

Recombination Hotspots ◽

Genomic Regions

AbstractWe introduce a new statistical model for patterns of linkage disequilibrium (LD) among multiple SNPs in a population sample. The model overcomes limitations of existing approaches to understanding, summarizing, and interpreting LD by (i) relating patterns of LD directly to the underlying recombination process; (ii) considering all loci simultaneously, rather than pairwise; (iii) avoiding the assumption that LD necessarily has a “block-like” structure; and (iv) being computationally tractable for huge genomic regions (up to complete chromosomes). We examine in detail one natural application of the model: estimation of underlying recombination rates from population data. Using simulation, we show that in the case where recombination is assumed constant across the region of interest, recombination rate estimates based on our model are competitive with the very best of current available methods. More importantly, we demonstrate, on real and simulated data, the potential of the model to help identify and quantify fine-scale variation in recombination rate from population data. We also outline how the model could be useful in other contexts, such as in the development of more efficient haplotype-based methods for LD mapping.

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mixIndependR: a R package for statistical independence testing of loci in database of multi-locus genotypes

BMC Bioinformatics ◽

10.1186/s12859-020-03945-0 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Bing Song ◽

August E. Woerner ◽

John Planz

Keyword(s):

Population Genetics ◽

Linkage Disequilibrium ◽

Genetic Markers ◽

Software Package ◽

Tandem Repeats ◽

Population Data ◽

Real Data ◽

R Package ◽

Nucleotide Polymorphisms ◽

Mutual Independence

Abstract Background Multi-locus genotype data are widely used in population genetics and disease studies. In evaluating the utility of multi-locus data, the independence of markers is commonly considered in many genomic assessments. Generally, pairwise non-random associations are tested by linkage disequilibrium; however, the dependence of one panel might be triplet, quartet, or other. Therefore, a compatible and user-friendly software is necessary for testing and assessing the global linkage disequilibrium among mixed genetic data. Results This study describes a software package for testing the mutual independence of mixed genetic datasets. Mutual independence is defined as no non-random associations among all subsets of the tested panel. The new R package “mixIndependR” calculates basic genetic parameters like allele frequency, genotype frequency, heterozygosity, Hardy–Weinberg equilibrium, and linkage disequilibrium (LD) by mutual independence from population data, regardless of the type of markers, such as simple nucleotide polymorphisms, short tandem repeats, insertions and deletions, and any other genetic markers. A novel method of assessing the dependence of mixed genetic panels is developed in this study and functionally analyzed in the software package. By comparing the observed distribution of two common summary statistics (the number of heterozygous loci [K] and the number of share alleles [X]) with their expected distributions under the assumption of mutual independence, the overall independence is tested. Conclusion The package “mixIndependR” is compatible to all categories of genetic markers and detects the overall non-random associations. Compared to pairwise disequilibrium, the approach described herein tends to have higher power, especially when number of markers is large. With this package, more multi-functional or stronger genetic panels can be developed, like mixed panels with different kinds of markers. In population genetics, the package “mixIndependR” makes it possible to discover more about admixture of populations, natural selection, genetic drift, and population demographics, as a more powerful method of detecting LD. Moreover, this new approach can optimize variants selection in disease studies and contribute to panel combination for treatments in multimorbidity. Application of this approach in real data is expected in the future, and this might bring a leap in the field of genetic technology. Availability The R package mixIndependR, is available on the Comprehensive R Archive Network (CRAN) at: https://cran.r-project.org/web/packages/mixIndependR/index.html.

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GWAS revealed effect of genotype × environment interactions for grain yield of Nebraska winter wheat

BMC Genomics ◽

10.1186/s12864-020-07308-0 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Shamseldeen Eltaher ◽

P. Stephen Baenziger ◽

Vikas Belamkar ◽

Hamdy A. Emara ◽

Ahmed A. Nower ◽

...

Keyword(s):

Linkage Disequilibrium ◽

Winter Wheat ◽

Grain Yield ◽

Genome Wide Association Study ◽

Phenotypic Selection ◽

Wheat Breeding ◽

Wheat Genotypes ◽

Genome Wide ◽

Genomic Regions ◽

Significant Linkage

Abstract Background Improving grain yield in cereals especially in wheat is a main objective for plant breeders. One of the main constrains for improving this trait is the G × E interaction (GEI) which affects the performance of wheat genotypes in different environments. Selecting high yielding genotypes that can be used for a target set of environments is needed. Phenotypic selection can be misleading due to the environmental conditions. Incorporating information from phenotypic and genomic analyses can be useful in selecting the higher yielding genotypes for a group of environments. Results A set of 270 F3:6 wheat genotypes in the Nebraska winter wheat breeding program was tested for grain yield in nine environments. High genetic variation for grain yield was found among the genotypes. G × E interaction was also highly significant. The highest yielding genotype differed in each environment. The correlation for grain yield among the nine environments was low (0 to 0.43). Genome-wide association study revealed 70 marker traits association (MTAs) associated with increased grain yield. The analysis of linkage disequilibrium revealed 16 genomic regions with a highly significant linkage disequilibrium (LD). The candidate parents’ genotypes for improving grain yield in a group of environments were selected based on three criteria; number of alleles associated with increased grain yield in each selected genotype, genetic distance among the selected genotypes, and number of different alleles between each two selected parents. Conclusion Although G × E interaction was present, the advances in DNA technology provided very useful tools and analyzes. Such features helped to genetically select the highest yielding genotypes that can be used to cross grain production in a group of environments.

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