A new test suggests that balancing selection maintains hundreds of non-synonymous polymorphisms in the human genome

Mapping Intimacies ◽

10.1101/2021.02.08.430226 ◽

2021 ◽

Cited By ~ 1

Author(s):

Vivak Soni ◽

Michiel Vos ◽

Adam Eyre-Walker

Keyword(s):

Genetic Diversity ◽

Human Genome ◽

Balancing Selection ◽

Genomic Data ◽

Demographic Changes ◽

Simple Test ◽

Direct Estimate ◽

Population Genomic

AbstractThe role that balancing selection plays in the maintenance of genetic diversity remains unresolved. Here we introduce a new test, based on the McDonald-Kreitman test, in which the number of polymorphisms that are shared between populations is contrasted to those that are private at selected and neutral sites. We show that this simple test is robust to a variety of demographic changes, and that it can also give a direct estimate of the number of shared polymorphisms that are directly maintained by balancing selection. We apply our method to population genomic data from humans and conclude that more than a thousand non-synonymous polymorphisms are subject to balancing selection.

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Flexible Mixture Model Approaches That Accommodate Footprint Size Variability for Robust Detection of Balancing Selection

Molecular Biology and Evolution ◽

10.1093/molbev/msaa134 ◽

2020 ◽

Vol 37 (11) ◽

pp. 3267-3291 ◽

Cited By ~ 1

Author(s):

Xiaoheng Cheng ◽

Michael DeGiorgio

Keyword(s):

Pain Perception ◽

Balancing Selection ◽

Genomic Data ◽

Composite Likelihood ◽

Ratio Test ◽

Data Set ◽

Robust Detection ◽

Population Genomic ◽

Genomic Regions

Abstract Long-term balancing selection typically leaves narrow footprints of increased genetic diversity, and therefore most detection approaches only achieve optimal performances when sufficiently small genomic regions (i.e., windows) are examined. Such methods are sensitive to window sizes and suffer substantial losses in power when windows are large. Here, we employ mixture models to construct a set of five composite likelihood ratio test statistics, which we collectively term B statistics. These statistics are agnostic to window sizes and can operate on diverse forms of input data. Through simulations, we show that they exhibit comparable power to the best-performing current methods, and retain substantially high power regardless of window sizes. They also display considerable robustness to high mutation rates and uneven recombination landscapes, as well as an array of other common confounding scenarios. Moreover, we applied a specific version of the B statistics, termed B2, to a human population-genomic data set and recovered many top candidates from prior studies, including the then-uncharacterized STPG2 and CCDC169–SOHLH2, both of which are related to gamete functions. We further applied B2 on a bonobo population-genomic data set. In addition to the MHC-DQ genes, we uncovered several novel candidate genes, such as KLRD1, involved in viral defense, and SCN9A, associated with pain perception. Finally, we show that our methods can be extended to account for multiallelic balancing selection and integrated the set of statistics into open-source software named BalLeRMix for future applications by the scientific community.

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Origin and distribution of different retrotransposons in different taxa

Genetics & Applications ◽

10.31383/ga.vol2iss2pp13-19 ◽

2018 ◽

Vol 2 (2) ◽

pp. 13

Author(s):

Buket Cakmak Guner ◽

Nermin Gozukirmizi

Keyword(s):

Human Genome ◽

Population Studies ◽

Genomic Data ◽

Data Sets ◽

Human Genetic Variation ◽

Chain Reaction ◽

Population Genomic ◽

Genomic Studies ◽

Polymerase Chain ◽

Genome Analyses

Novel genome analysis technologies enable genomic studies of transposable elements (TEs) in different organisms. Population studies of human genome show thousands of individual TE insertions. These insertions are important source of natural human genetic variation. Researchers are beginning to develop population genomic data sets for evaluating the phenotypic impact of human TE polymorphisms. Because of the evidences of horizontal transfer of retrotransposons between different species genome, in this study we aimed to detect barley retrotransposons (Nikita and BAGY2) in the human genome. Inter retrotransposon amplified polymorphism polymerase chain reaction (IRAP PCR) were used to measure the distribution of Nikita and BAGY2 retroelements in the human genome. Analyses reveals that Nikita and BAGY2 are present in the human genome and show different distribution in the genome. The polymorphism ratios of retroelements suggest that Nikita and BAGY2 have been active retrotransposons in the human genome.

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Population genomic data in spider mites point to a role for local adaptation in shaping range shifts

Evolutionary Applications ◽

10.1111/eva.13086 ◽

2020 ◽

Vol 13 (10) ◽

pp. 2821-2835

Author(s):

Lei Chen ◽

Jing‐Tao Sun ◽

Peng‐Yu Jin ◽

Ary A. Hoffmann ◽

Xiao‐Li Bing ◽

...

Keyword(s):

Local Adaptation ◽

Genomic Data ◽

Spider Mites ◽

Range Shifts ◽

Population Genomic

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Genetic Diversity of Rice stripe necrosis virus and New Insights into Evolution of the Genus Benyvirus

Viruses ◽

10.3390/v13050737 ◽

2021 ◽

Vol 13 (5) ◽

pp. 737

Author(s):

Issiaka Bagayoko ◽

Marcos Giovanni Celli ◽

Gustavo Romay ◽

Nils Poulicard ◽

Agnès Pinel-Galzi ◽

...

Keyword(s):

Genetic Diversity ◽

Genetic Variability ◽

Sierra Leone ◽

Evolutionary History ◽

Molecular Diversity ◽

Genomic Data ◽

Gene Recombination ◽

Necrosis Virus ◽

History Of ◽

Complex Evolutionary History

The rice stripe necrosis virus (RSNV) has been reported to infect rice in several countries in Africa and South America, but limited genomic data are currently publicly available. Here, eleven RSNV genomes were entirely sequenced, including the first corpus of RSNV genomes of African isolates. The genetic variability was differently distributed along the two genomic segments. The segment RNA1, within which clusters of polymorphisms were identified, showed a higher nucleotidic variability than did the beet necrotic yellow vein virus (BNYVV) RNA1 segment. The diversity patterns of both viruses were similar in the RNA2 segment, except for an in-frame insertion of 243 nucleotides located in the RSNV tgbp1 gene. Recombination events were detected into RNA1 and RNA2 segments, in particular in the two most divergent RSNV isolates from Colombia and Sierra Leone. In contrast to BNYVV, the RSNV molecular diversity had a geographical structure with two main RSNV lineages distributed in America and in Africa. Our data on the genetic diversity of RSNV revealed unexpected differences with BNYVV suggesting a complex evolutionary history of the genus Benyvirus.

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Inferring Adaptive Introgression Using Hidden Markov Models

10.1101/2020.08.02.232934 ◽

2020 ◽

Cited By ~ 1

Author(s):

Jesper Svedberg ◽

Vladimir Shchur ◽

Solomon Reinman ◽

Rasmus Nielsen ◽

Russell Corbett-Detig

Keyword(s):

Markov Models ◽

Hidden Markov ◽

Genomic Data ◽

Diverse Populations ◽

Powerful Method ◽

Adaptive Genetic Variation ◽

Adaptive Introgression ◽

Population Genomic ◽

Significant Interest ◽

Selection Parameters

AbstractAdaptive introgression - the flow of adaptive genetic variation between species or populations - has attracted significant interest in recent years and it has been implicated in a number of cases of adaptation, from pesticide resistance and immunity, to local adaptation. Despite this, methods for identification of adaptive introgression from population genomic data are lacking. Here, we present Ancestry_HMM-S, a Hidden Markov Model based method for identifying genes undergoing adaptive introgression and quantifying the strength of selection acting on them. Through extensive validation, we show that this method performs well on moderately sized datasets for realistic population and selection parameters. We apply Ancestry_HMM-S to a dataset of an admixed Drosophila melanogaster population from South Africa and we identify 17 loci which show signatures of adaptive introgression, four of which have previously been shown to confer resistance to insecticides. Ancestry_HMM-S provides a powerful method for inferring adaptive introgression in datasets that are typically collected when studying admixed populations. This method will enable powerful insights into the genetic consequences of admixture across diverse populations. Ancestry_HMM-S can be downloaded from https://github.com/jesvedberg/Ancestry_HMM-S/.

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Effects of genomic and functional diversity on stand-level productivity and performance of non-native Arabidopsis

10.1101/2020.04.20.049593 ◽

2020 ◽

Author(s):

Kathryn G. Turner ◽

Claire M. Lorts ◽

Asnake T. Haile ◽

Jesse R. Lasky

Keyword(s):

Genetic Diversity ◽

Flowering Time ◽

Phenotypic Diversity ◽

A Priori ◽

Interference Competition ◽

Genomic Data ◽

Total Biomass ◽

High Resource ◽

And Performance ◽

Resource Conditions

AbstractBiodiversity can affect the properties of groups of organisms, such as ecosystem function and the persistence of colonizing populations. Genomic data offer a newly available window to diversity, complementary to other measures like taxonomic or phenotypic diversity. We tested whether native genetic diversity in field experimental stands of Arabidopsis thaliana affected their aboveground biomass and fecundity in their colonized range. We constructed some stands of genotypes that we a priori predicted would differ in performance or show overyielding. We found no relationship between genetic diversity and stand total biomass. However, increasing stand genetic diversity increased fecundity in high resource conditions. Polyculture (multiple genotype) stands consistently yielded less biomass than expected based on the yields of component genotypes in monoculture. This under-yielding was strongest in stands with late-flowering and high biomass genotypes, potentially due to interference competition by these genotypes. Using a new implementation of association mapping, we identified genetic loci whose diversity was associated with stand-level yield, revealing a major flowering time locus associated with under-yielding of polycultures. Our field experiment supports community ecology studies that find a range of diversity-function relationships. Nevertheless, our results suggest diversity in colonizing propagule pools can enhance population fitness. Furthermore, interference competition among genotypes differing in flowering time might limit the advantages of polyculture.

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Level of Inbreeding in Norik of Muran Horse: Pedigree vs. Genomic Data

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis ◽

10.11118/actaun201967061457 ◽

2019 ◽

Vol 67 (6) ◽

pp. 1457-1463 ◽

Cited By ~ 2

Author(s):

Radovan Kasarda ◽

Nina Moravčíková ◽

Ondrej Kadlečík ◽

Anna Trakovická ◽

Marko Halo ◽

...

Keyword(s):

Genetic Diversity ◽

Quality Control ◽

Genomic Analysis ◽

Genomic Data ◽

Reference Population ◽

Pedigree Analysis ◽

Snp Markers ◽

Runs Of Homozygosity ◽

Current Generation ◽

Genomic Inbreeding

The objective of this study was to analyse the level of pedigree and genomic inbreeding in a herd of the Norik of Muran horses. The pedigree file included 1374 animals (603 stallions and 771 mares), while the reference population consisted of animals that were genotyped by using 70k SNP platform (n = 25). The trend of pedigree inbreeding was expressed as the probability that an animal has two identical alleles by descent according to classical formulas. The trend of genomic inbreeding was derived from the distribution of runs of homozygosity (ROHs) with various length in the genome based on the assumption that these regions reflect the autozygosity originated from past generations of ancestors. A maximum of 19 generations was found in pedigree file. As expected, the highest level of pedigree completeness was found in first five generations. Subsequent quality control of genomic data resulted in totally 54432 SNP markers covering 2.242 Mb of the autosomal genome. The pedigree analysis showed that in current generation can be expected the pedigree inbreeding at level 0.23% (ΔFPEDi = 0.19 ± 1.17%). Comparable results was obtained also by the genomic analysis, when the inbreeding in current generation reached level 0.11%. Thus, in term of genetic diversity both analyses reflected sufficient level of variability across analysed population of Norik of Muran horses.

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