Positive and Negative Selection on the Human Genome

Fay, Justin C.; Wyckoff, Gerald J.; Wu, Chung‐I

doi:10.1093/genetics/158.3.1227

Cited by 573 publications

(73 citation statements)

References 23 publications

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“…To our knowledge, three of the identified GRFs, namely ZNF626, ZNF806, and ZNF860, have not been reported in previous analyses of positive selection among primate species (for instance in Nielsen et al, 2005;Su et al, 2016;Van Der Lee et al, 2017). The number of our candidate genes is small in contrast to the genomewide studies (e.g., Su et al, 2016;Van Der Lee et al, 2017), but is in line with studies that estimated the proportion of adaptive amino acid substitutions as low in humans (Fay et al, 2001;Zhang and Li, 2005;Boyko et al, 2008). Furthermore, we focused only on GRFs, which constitute about one sixth of all proteincoding sequences (20,448 in human reference genome, assembly GRCh38.p13, Ensembl).…”

Section: Discussionsupporting

confidence: 85%

Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution

et al. 2021

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Gene regulatory factors (GRFs), such as transcription factors, co-factors and histone-modifying enzymes, play many important roles in modifying gene expression in biological processes. They have also been proposed to underlie speciation and adaptation. To investigate potential contributions of GRFs to primate evolution, we analyzed GRF genes in 27 publicly available primate genomes. Genes coding for zinc finger (ZNF) proteins, especially ZNFs with a Krüppel-associated box (KRAB) domain were the most abundant TFs in all genomes. Gene numbers per TF family differed between all species. To detect signs of positive selection in GRF genes we investigated more than 3,000 human GRFs with their more than 70,000 orthologs in 26 non-human primates. We implemented two independent tests for positive selection, the branch-site-model of the PAML suite and aBSREL of the HyPhy suite, focusing on the human and great ape branch. Our workflow included rigorous procedures to reduce the number of false positives: excluding distantly similar orthologs, manual corrections of alignments, and considering only genes and sites detected by both tests for positive selection. Furthermore, we verified the candidate sites for selection by investigating their variation within human and non-human great ape population data. In order to approximately assign a date to positively selected sites in the human lineage, we analyzed archaic human genomes. Our work revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. These GRFs are scattered on different chromosomes and have been previously linked to diverse functions. For some of them a role in speciation and/or adaptation can be proposed based on the expression pattern or association with human diseases, but it seems that they all contributed independently to human evolution. Four of the positively selected GRFs are KRAB-ZNF proteins, that induce changes in target genes co-expression and/or through arms race with transposable elements. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans.

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Section: Discussionsupporting

confidence: 85%

Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution

et al. 2021

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“…4C, contains 11 positions, with seven positions (4-10) having information content > 1 2 . In the literature, the binding sequence is often depicted by the core GATA motif (positions [5][6][7][8] with the two flanking bases .…”

Section: Binding Sites For the Gata2 Transcription Factormentioning

confidence: 99%

Inference of Natural Selection from Interspersed Genomic Elements Based on Polymorphism and Divergence

Gronau

Arbiza

Mohammed

et al. 2013

Molecular Biology and Evolution

122

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Complete genome sequences contain valuable information about natural selection, but this information is difficult to access for short, widely scattered noncoding elements such as transcription factor binding sites or small noncoding RNAs. Here, we introduce a new computational method, called Inference of Natural Selection from Interspersed Genomically coHerent elemenTs (INSIGHT), for measuring the influence of natural selection on such elements. INSIGHT uses a generative probabilistic model to contrast patterns of polymorphism and divergence in the elements of interest with those in flanking neutral sites, pooling weak information from many short elements in a manner that accounts for variation among loci in mutation rates and coalescent times. The method is able to disentangle the contributions of weak negative, strong negative, and positive selection based on their distinct effects on patterns of polymorphism and divergence. It obtains information about divergence from multiple outgroup genomes using a general statistical phylogenetic approach. The INSIGHT model is efficiently fitted to genome-wide data using an approximate expectation maximization algorithm. Using simulations, we show that the method can accurately estimate the parameters of interest even in complex demographic scenarios, and that it significantly improves on methods based on summary statistics describing polymorphism and divergence. To demonstrate the usefulness of INSIGHT, we apply it to several classes of human noncoding RNAs and to GATA2-binding sites in the human genome.

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“…A large body of work has been put forward in an effort to correct for this skew (Andolfatto, 2008;Charlesworth and Eyre-Walker, 2008;Eyre-Walker and Keightley, 2009;Messer and Petrov, 2012). For example, introducing a low-frequency cut-off for measured polymorphisms significantly improves estimates of α M K for the case of many weakly deleterious mutations (Charlesworth and Eyre-Walker, 2008;Fay et al, 2001), since in the absence of genetic linkage few deleterious mutations will ever reach high frequencies. However, few studies have carefully analysed the effect of linkage on α M K , and particularly on the effect of linked beneficial mutations.…”

Section: Implications For the Mcdonald-kreitman Testmentioning

confidence: 99%

The Dynamics of Genetic Draft in Rapidly Adapting Populations

Kosheleva

Desai

2013

Genetics

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The accumulation of beneficial mutations on competing genetic backgrounds in rapidly adapting populations has a striking impact on evolutionary dynamics. This effect, known as clonal interference, causes erratic fluctuations in the frequencies of observed mutations, randomizes the fixation times of successful mutations, and leaves distinct signatures on patterns of genetic variation. Here, we show how this form of "genetic draft" affects the forward-time dynamics of site frequencies in rapidly adapting asexual populations. We calculate the probability that mutations at individual sites shift in frequency over a characteristic timescale, extending Gillespie's original model of draft to the case where many strongly selected beneficial mutations segregate simultaneously. We then derive the sojourn time of mutant alleles, the expected fixation time of successful mutants, and the site frequency spectrum of beneficial and neutral mutations. Finally, we show how this form of draft affects inferences in the McDonald-Kreitman test and how it relates to recent observations that some aspects of genetic diversity are described by the Bolthausen-Sznitman coalescent in the limit of very rapid adaptation.T HE effects of linkage between beneficial mutations in altering evolutionary dynamics and the structures of genealogies in adapting populations has been recognized for nearly a century, particularly in the context of the evolutionary advantage of sex (Muller 1932). In both asexually reproducing organisms and in regions of low recombination in sexual organisms, the chance congregation of beneficial mutations on competing genetic backgrounds skews evolutionary dynamics. Because of this "clonal interference" effect, the success of a mutation depends not only on its fitness effect, but also on the quality of the genetic background in which it occurs and the fortune of the mutant's progeny in amassing more beneficial mutations (Smith and Haigh 1974;Gerrish and Lenski 1998;Gillespie 2000Gillespie , 2001Kim and Orr 2005).Recent work in experimental evolution has confirmed that clonal interference is widespread in large adapting laboratory microbial and viral populations (de Visser et al. 1999;Miralles et al. 1999;de Visser and Rozen 2006;Kao and Sherlock 2008;Lang et al. 2011Lang et al. , 2013. Several recent studies also suggest that classic "hard" selective sweeps may be rare in Drosophila (Sella et al. 2009;Karasov et al. 2010) and humans (Pritchard et al. 2010;Hernandez et al. 2011), implying that models that better account for linkage between sites need to be explored. As a result, in recent years there has been an influx of theoretical work describing the effects of clonal interference on the evolution of large populations (see Park et al. 2010 for a recent review).This work has provided a good understanding of evolutionary dynamics in the regime of rare interference, where the number of strongly beneficial mutations segregating in a population is rarely more than two (Gerrish and Lenski 1998;Gillespie 2000Gillespie ...

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Positive and Negative Selection on the Human Genome

Cited by 573 publications

References 23 publications

Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution

Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution

Inference of Natural Selection from Interspersed Genomic Elements Based on Polymorphism and Divergence

The Dynamics of Genetic Draft in Rapidly Adapting Populations

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