Derived Allele Frequency Research Articles

Genetic diversity during selective sweeps in non-recombining populations.

Selective sweeps, resulting from the spread of beneficial, neutral, or deleterious mutations through a population, shape patterns of genetic variation at linked neutral sites. While many theoretical, computational, and statistical advances have been made in understanding the genomic signatures of selective sweeps in recombining populations, substantially less is understood in populations with little/no recombination. We present a mathematical framework based on diffusion theory for obtaining the site frequency spectrum (SFS) at linked neutral sites immediately post and during the fixation of moderately or strongly beneficial mutations. We find that when a single hard sweep occurs, the SFS decays as 1/ x for low derived allele frequencies ( x ), similar to the neutral SFS at equilibrium, whereas at higher derived allele frequencies, it follows a 1/ x 2 power law. These power laws are universal in the sense that they are independent of the dominance and inbreeding coefficient, and also characterize the SFS during the sweep. Additionally, we find that the derived allele frequency where the SFS shifts from the 1/ x to 1/ x 2 law, is inversely proportional to the selection strength: thus under strong selection, the SFS follows the 1/ x 2 dependence for most allele frequencies, resembling a rapidly expanding neutral population. When clonal interference is pervasive, the SFS immediately post-fixation becomes U-shaped and is better explained by the equilibrium SFS of selected sites. Our results will be important in developing statistical methods to infer the timing and strength of recent selective sweeps in asexual populations, genomic regions that lack recombination, and clonally propagating tumor populations.

Scalable CNN-based classification of selective sweeps using derived allele frequencies.

Selective sweeps can successfully be distinguished from neutral genetic data using summary statistics and likelihood-based methods that analyze single nucleotide polymorphisms (SNPs). However, these methods are sensitive to confounding factors, such as severe population bottlenecks and old migration. By virtue of machine learning, and specifically convolutional neural networks (CNNs), new accurate classification models that are robust to confounding factors have been recently proposed. However, such methods are more computationally expensive than summary-statistic-based ones, yielding them impractical for processing large-scale genomic data. Moreover, SNP data are frequently preprocessed to improve classification accuracy, further exacerbating the long analysis times. To this end, we propose a 1D CNN-based model, dubbed FAST-NN, that does not require any preprocessing while using only derived allele frequencies instead of summary statistics or raw SNP data, thereby yielding a sample-size-invariant, scalable solution. We evaluated several data fusion approaches to account for the variance of the density of genetic diversity across genomic regions (a selective sweep signature), and performed an extensive neural architecture search based on a state-of-the-art reference network architecture (SweepNet). The resulting model, FAST-NN, outperforms the reference architecture by up to 12% inference accuracy over all challenging evolutionary scenarios with confounding factors that were evaluated. Moreover, FAST-NN is between 30× and 259× faster on a single CPU core, and between 2.0× and 6.2× faster on a GPU, when processing sample sizes between 128 and 1000 samples. Our work paves the way for the practical use of CNNs in large-scale selective sweep detection. https://github.com/SjoerdvandenBelt/FAST-NN.

Native American genetic ancestry and pigmentation allele contributions to skin color in a Caribbean population.

Our interest in the genetic basis of skin color variation between populations led us to seek a Native American population with genetically African admixture but low frequency of European light skin alleles. Analysis of 458 genomes from individuals residing in the Kalinago Territory of the Commonwealth of Dominica showed approximately 55% Native American, 32% African, and 12% European genetic ancestry, the highest Native American genetic ancestry among Caribbean populations to date. Skin pigmentation ranged from 20 to 80 melanin units, averaging 46. Three albino individuals were determined to be homozygous for a causative multi-nucleotide polymorphism OCA2NW273KV contained within a haplotype of African origin; its allele frequency was 0.03 and single allele effect size was -8 melanin units. Derived allele frequencies of SLC24A5A111T and SLC45A2L374F were 0.14 and 0.06, with single allele effect sizes of -6 and -4, respectively. Native American genetic ancestry by itself reduced pigmentation by more than 20 melanin units (range 24-29). The responsible hypopigmenting genetic variants remain to be identified, since none of the published polymorphisms predicted in prior literature to affect skin color in Native Americans caused detectable hypopigmentation in the Kalinago.

Evidence Supporting That C-to-U RNA Editing Is the Major Force That Drives SARS-CoV-2 Evolution.

Mutations of DNA organisms are introduced by replication errors. However, SARS-CoV-2, as an RNA virus, is additionally subjected to rampant RNA editing by hosts. Both resources contributed to SARS-CoV-2 mutation and evolution, but the relative prevalence of the two origins is unknown. We performed comparative genomic analyses at intra-species (world-wide SARS-CoV-2 strains) and inter-species (SARS-CoV-2 and RaTG13 divergence) levels. We made prior predictions of the proportion of each mutation type (nucleotide substitution) under different scenarios and compared the observed versus the expected. C-to-T alteration, representing C-to-U editing, is far more abundant that all other mutation types. Derived allele frequency (DAF) as well as novel mutation rate of C-to-T are the highest in SARS-CoV-2 population, and C-T substitution dominates the divergence sites between SARS-CoV-2 and RaTG13. This is compelling evidence suggesting that C-to-U RNA editing is the major source of SARS-CoV-2 mutation. While replication errors serve as a baseline of novel mutation rate, the C-to-U editing has elevated the mutation rate for orders of magnitudes and accelerates the evolution of the virus.

Epistasis-Driven Evolution of the SARS-CoV-2 Secondary Structure

Epistasis is an evolutionary phenomenon whereby the fitness effect of a mutation depends on the genetic background in which it arises. A key source of epistasis in an RNA molecule is its secondary structure, which contains functionally important topological motifs held together by hydrogen bonds between Watson–Crick (WC) base pairs. Here we study epistasis in the secondary structure of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by examining properties of derived alleles arising from substitution mutations at ancestral WC base-paired and unpaired (UP) sites in 15 conserved topological motifs across the genome. We uncover fewer derived alleles and lower derived allele frequencies at WC than at UP sites, supporting the hypothesis that modifications to the secondary structure are often deleterious. At WC sites, we also find lower derived allele frequencies for mutations that abolish base pairing than for those that yield G·U “wobbles,” illustrating that weak base pairing can partially preserve the integrity of the secondary structure. Last, we show that WC sites under the strongest epistatic constraint reside in a three-stemmed pseudoknot motif that plays an essential role in programmed ribosomal frameshifting, whereas those under the weakest epistatic constraint are located in 3’ UTR motifs that regulate viral replication and pathogenicity. Our findings demonstrate the importance of epistasis in the evolution of the SARS-CoV-2 secondary structure, as well as highlight putative structural and functional targets of different forms of natural selection.

Evidence of selection in the uncoupling protein 1 gene region suggests local adaptation to solar irradiance in savannah monkeys (Chlorocebus spp.).

In the last 300 thousand years, the genus Chlorocebus expanded from equatorial Africa into the southernmost latitudes of the continent, where colder climate was a probable driver of natural selection. We investigated population-level genetic variation in the mitochondrial uncoupling protein 1 (UCP1) gene region-implicated in non-shivering thermogenesis (NST)-in 73 wild savannah monkeys from three taxa representing this southern expansion (Chlorocebus pygerythrus hilgerti, Chlorocebus cynosuros and Chlorocebus pygerythrus pygerythrus) ranging from Kenya to South Africa. We found 17 single nucleotide polymorphisms with extended haplotype homozygosity consistent with positive selective sweeps, 10 of which show no significant linkage disequilibrium with each other. Phylogenetic generalized least-squares modelling with ecological covariates suggest that most derived allele frequencies are significantly associated with solar irradiance and winter precipitation, rather than overall low temperatures. This selection and association with irradiance is demonstrated by a relatively isolated population in the southern coastal belt of South Africa. We suggest that sunbathing behaviours common to savannah monkeys, in combination with the strength of solar irradiance, may mediate adaptations to thermal stress via NST among savannah monkeys. The variants we discovered all lie in non-coding regions, some with previously documented regulatory functions, calling for further validation and research.

Rampant C-to-U deamination accounts for the intrinsically high mutation rate in SARS-CoV-2 spike gene.

The high mutation rate of SARS-CoV-2 largely complicates our control of the pandemic. In particular, it is currently unclear why the spike (S) gene has an extraordinarily high mutation rate among all SARS-CoV-2 genes. By analyzing the occurrence of fixed synonymous mutations between SARS-CoV-2 and RaTG13, and profiling the DAF (derived allele frequency) of polymorphic synonymous sites among millions of worldwide SARS-CoV-2 strains, we found that both fixed and polymorphic mutations show higher mutation rates in the S gene than other genes. The majority of mutations are C-to-T, representing the APOBEC-mediated C-to-U deamination instead of the previously proposed A-to-I deamination. Both in silico and in vivo evidence indicated that the S gene is more likely to be single-stranded compared to other SARS-CoV-2 genes, agreeing with the APOBEC preference of ssRNA. We conclude that the single-stranded property of the S gene makes it a favorable target for C-to-U deamination, leading to its excessively high mutation rate compared to other non-S genes. In conclusion, APOBEC, rather than ADAR, is the "editor-in-chief" of SARS-CoV-2 RNAs. This work helps us to understand the molecular mechanism underlying the mutation and evolution of SARS-CoV-2, and we believe it will contribute to the control of the pandemic.

Deleterious mutations are characterized by higher genomic heterozygosity than other genic variants in plant genomes.

Deleterious mutations can reduce the fitness of crop varieties, which limits the plant breeding efficacy. While crop deleterious mutations have been extensively examined, most studies focused on one specific crop with different analyzing methods, which hinders unveiling shared genomic characteristics of deleterious mutations across diverse crops. Here we used standardized approaches to characterize the deleterious mutations in genomes of domesticated inbreeding (i.e., rice, soybean, and tomato) and clonally propagated crops (i.e., grape and pineapple). We found that deleterious mutations are commonly targeted by purifying selection, and are over-presented in a nearly fixed derived allele frequency in the course of plant domestication. Further, a generally negative correlation between genetic load and the artificial selection strength is observed. Importantly, we consistently uncovered the higher derived genomic heterozygosity for deleterious mutations compared to other genic variants. This study broadens our understanding of the evolution of deleterious mutations in plant genomes.

Context-dependent and -independent selection on synonymous mutations revealed by 1,135 genomes of Arabidopsis thaliana

BackgroundSynonymous mutations do not alter the amino acids and therefore are regarded as neutral for a long time. However, they do change the tRNA adaptation index (tAI) of a particular codon (independent of its context), affecting the tRNA availability during translation. They could also change the isoaccepting relationship with its neighboring synonymous codons in particular context, which again affects the local translation process. Evidence of selection pressure on synonymous mutations has emerged.ResultsThe proposed selection patterns on synonymous mutations are never formally and systematically tested in plant species. We fully take advantage of the SNP data from 1,135 A. thaliana lines, and found that the synonymous mutations that increase tAI or the isoaccepting mutations in isoaccepting codon context tend to have higher derived allele frequencies (DAF) compared to other synonymous mutations of the opposite effects.ConclusionsSynonymous mutations are not strictly neutral. The synonymous mutations that increase tAI or the isoaccepting mutations in isoaccepting codon context are likely to be positively selected. We propose the concept of context-dependent and -independent selection on synonymous mutations. These concepts broaden our knowledge of the functional consequences of synonymous mutations, and should be appealing to phytologists and evolutionary biologists.

Neandertal introgression and accumulation of hypomorphic mutations in the neuropeptide S (NPS) system promote attenuated functionality

The neuropeptide S (NPS) system plays an important role in fear and fear memory processing but has also been associated with allergic and inflammatory diseases. Genes for NPS and its receptor NPSR1 are found in all tetrapods. Compared to non-human primates, several non-synonymous single-nucleotide polymorphisms (SNPs) occur in both human genes that collectively result in functional attenuation, suggesting adaptive mechanisms in a human context. To investigate historic and geographic origins of these hypomorphic mutations and explore genetic signs of selection, we analyzed ancient genomes and worldwide genotype frequencies of four prototypic SNPs in the NPS system. Neandertal and Denisovan genomes contain exclusively ancestral alleles for NPSR1 while all derived alleles occur in ancient genomes of anatomically modern humans, indicating that they arose in modern Homo sapiens. Worldwide genotype frequencies for three hypomorphic NPSR1 SNPs show significant regional homogeneity but follow a gradient towards increasing derived allele frequencies that supports an out-of-Africa scenario. Increased density of high-frequency polymorphisms around the three NPSR1 loci suggests weak or possibly balancing selection. A hypomorphic mutation in the NPS precursor, however, was detected at high frequency in Eurasian Neandertal genomes and shows genetic signatures indicating that it was introgressed into the human gene pool, particularly in Southern Europe, by interbreeding with Neandertals. We discuss potential evolutionary scenarios including behavior and immune-based natural selection.

Probing the aggregated effects of purifying selection per individual on 1,380 medical phenotypes in the UK Biobank.

Understanding the relationship between natural selection and phenotypic variation has been a long-standing challenge in human population genetics. With the emergence of biobank-scale datasets, along with new statistical metrics to approximate strength of purifying selection at the variant level, it is now possible to correlate a proxy of individual relative fitness with a range of medical phenotypes. We calculated a per-individual deleterious load score by summing the total number of derived alleles per individual after incorporating a weight that approximates strength of purifying selection. We assessed four methods for the weight, including GERP, phyloP, CADD, and fitcons. By quantitatively tracking each of these scores with the site frequency spectrum, we identified phyloP as the most appropriate weight. The phyloP-weighted load score was then calculated across 15,129,142 variants in 335,161 individuals from the UK Biobank and tested for association on 1,380 medical phenotypes. After accounting for multiple test correction, we observed a strong association of the load score amongst coding sites only on 27 traits including body mass, adiposity and metabolic rate. We further observed that the association signals were driven by common variants (derived allele frequency > 5%) with high phyloP score (phyloP > 2). Finally, through permutation analyses, we showed that the load score amongst coding sites had an excess of nominally significant associations on many medical phenotypes. These results suggest a broad impact of deleterious load on medical phenotypes and highlight the deleterious load score as a tool to disentangle the complex relationship between natural selection and medical phenotypes.

Human A-to-I RNA editing SNP loci are enriched in GWAS signals for autoimmune diseases and under balancing selection

BackgroundAdenosine-to-inosine (A-to-I) RNA editing plays important roles in diversifying the transcriptome and preventing MDA5 sensing of endogenous dsRNA as nonself. To date, few studies have investigated the population genomic signatures of A-to-I editing due to the lack of editing sites overlapping with SNPs.ResultsIn this study, we applied a pipeline to robustly identify SNP editing sites from population transcriptomic data and combined functional genomics, GWAS, and population genomics approaches to study the function and evolution of A-to-I editing. We find that the G allele, which is equivalent to edited I, is overrepresented in editing SNPs. Functionally, A/G editing SNPs are highly enriched in GWAS signals of autoimmune and immune-related diseases. Evolutionarily, derived allele frequency distributions of A/G editing SNPs for both A and G alleles as the ancestral alleles are skewed toward intermediate frequency alleles relative to neutral SNPs, a hallmark of balancing selection, suggesting that both A and G alleles are functionally important. The signal of balancing selection is confirmed by a number of additional population genomic analyses.ConclusionsWe uncovered a hidden layer of A-to-I RNA editing SNP loci as a common target of balancing selection, and we propose that the maintenance of such editing SNP variations may be at least partially due to constraints on the resolution of the balance between immune activity and self-tolerance.

Genomic analysis of worldwide sheep breeds reveals PDGFD as a major target of fat-tail selection in sheep

BackgroundFat tail is a unique trait in sheep acquired during domestication. Several genomic analyses have been conducted in sheep breeds from limited geographic origins to identify the genetic factors underlying this trait. Nevertheless, these studies obtained different candidates. The results of these regional studies were easily biased by the breed structures.ResultsTo minimize the bias and distinguish the true candidates, we used an extended data set of 968 sheep representing 18 fat-tailed breeds and 14 thin-tailed breeds from around the world, and integrated two statistical tests to detect selection signatures, including Genetic Fixation Index (FST) and difference of derived allele frequency (ΔDAF). The results showed that platelet derived growth factor D (PDGFD) exhibited the highest genetic differentiation between fat- and thin-tailed sheep breeds. Analysis of sequence variation identified that a 6.8-kb region within the first intron of PDGFD is likely the target of positive selection and contains regulatory mutation(s) in fat-tailed sheep. Histological and gene expression analyses demonstrated that PDGFD expression is associated with maturation and hemostasis of adipocytes. Further retrospective analysis of public transcriptomic datasets revealed that PDGFD expression is down-regulated during adipogenesis in both human and mouse, and is higher in fat tissues of obese individuals than that in lean individuals.ConclusionsThese results reveal that PDGFD is the predominant factor for the fat tail phenotype in sheep by contributing to adiopogenesis and maintaining the hemostasis of mature adipocytes. This study provides insights into the selection of fat-tailed sheep and has important application to animal breeding, as well as obesity-related human diseases.

Systematic identification of cis-regulatory variants that cause gene expression differences in a yeast cross.

Sequence variation in regulatory DNA alters gene expression and shapes genetically complex traits. However, the identification of individual, causal regulatory variants is challenging. Here, we used a massively parallel reporter assay to measure the cis-regulatory consequences of 5832 natural DNA variants in the promoters of 2503 genes in the yeast Saccharomyces cerevisiae. We identified 451 causal variants, which underlie genetic loci known to affect gene expression. Several promoters harbored multiple causal variants. In five promoters, pairs of variants showed non-additive, epistatic interactions. Causal variants were enriched at conserved nucleotides, tended to have low derived allele frequency, and were depleted from promoters of essential genes, which is consistent with the action of negative selection. Causal variants were also enriched for alterations in transcription factor binding sites. Models integrating these features provided modest, but statistically significant, ability to predict causal variants. This work revealed a complex molecular basis for cis-acting regulatory variation.

Genomic Variant Analyses in Pyrethroid Resistant and Susceptible Malaria Vector, Anopheles sinensis.

Anopheles sinensis is a major malaria vector in Southeast Asia. Resistance to pyrethroid insecticides in this species has impeded malaria control in the region. Previous studies found that An. sinensis populations from Yunnan Province, China were highly resistant to deltamethrin and did not carry mutations in the voltage-gated sodium channel gene that cause knockdown resistance. In this study, we tested the hypothesis that other genomic variants are associated with the resistance phenotype. Using paired-end whole genome sequencing (DNA-seq), we generated 108 Gb of DNA sequence from deltamethrin -resistant and -susceptible mosquito pools with an average coverage of 83.3× depth. Using a stringent filtering method, we identified a total of 916,926 single nucleotide variants (SNVs), including 32,240 non-synonymous mutations. A total of 958 SNVs differed significantly in allele frequency between deltamethrin -resistant and -susceptible mosquitoes. Of these, 43 SNVs were present within 37 genes that code for immunity, detoxification, cuticular, and odorant proteins. A subset of 12 SNVs were randomly selected for genotyping of individual mosquitoes by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and showed consistent allele frequencies with the pooled DNA-seq derived allele frequencies. In addition, copy number variations (CNVs) were detected in 56 genes, including 33 that contained amplification alleles and 23 that contained deletion alleles in resistant mosquitoes compared to susceptible mosquitoes. The genomic variants described here provide a useful resource for future studies on the genetic mechanism of insecticide resistance in this important malaria vector species.

Genome-wide analysis on the maize genome reveals weak selection on synonymous mutations

BackgroundSynonymous mutations are able to change the tAI (tRNA adaptation index) of a codon and consequently affect the local translation rate. Intuitively, one may hypothesize that those synonymous mutations which increase the tAI values are favored by natural selection.ResultsWe use the maize (Zea mays) genome to test our assumption. The first supporting evidence is that the tAI-increasing synonymous mutations have higher fixed-to-polymorphic ratios than the tAI-decreasing ones. Next, the DAF (derived allele frequency) or MAF (minor allele frequency) of the former is significantly higher than the latter. Moreover, similar results are obtained when we investigate CAI (codon adaptation index) instead of tAI.ConclusionThe synonymous mutations in the maize genome are not strictly neutral. The tAI-increasing mutations are positively selected while those tAI-decreasing ones undergo purifying selection. This selection force might be weak but should not be automatically ignored.

Selected neuropeptide genes show genetic differentiation between Africans and non-Africans

BackgroundPublicly available genome data provides valuable information on the genetic variation patterns across different modern human populations. Neuropeptide genes are crucial to the nervous, immune, endocrine system, and physiological homeostasis as they play an essential role in communicating information in neuronal functions. It remains unclear how evolutionary forces, such as natural selection and random genetic drift, have affected neuropeptide genes among human populations. To date, there are over 100 known human neuropeptides from the over 1000 predicted peptides encoded in the genome. The purpose of this study is to analyze and explore the genetic variation in continental human populations across all known neuropeptide genes by examining highly differentiated SNPs between African and non-African populations.ResultsWe identified a total of 644,225 SNPs in 131 neuropeptide genes in 6 worldwide population groups from a public database. Of these, 5163 SNPs that had ΔDAF |(African - non-African)| ≥ 0.20 were identified and fully annotated. A total of 20 outlier SNPs that included 19 missense SNPs with a moderate impact and one stop lost SNP with high impact, were identified in 16 neuropeptide genes. Our results indicate that an overall strong population differentiation was observed in the non-African populations that had a higher derived allele frequency for 15/20 of those SNPs. Highly differentiated SNPs in four genes were particularly striking: NPPA (rs5065) with high impact stop lost variant; CHGB (rs6085324, rs236150, rs236152, rs742710 and rs742711) with multiple moderate impact missense variants; IGF2 (rs10770125) and INS (rs3842753) with moderate impact missense variants that are in linkage disequilibrium. Phenotype and disease associations of these differentiated SNPs indicated their association with hypertension and diabetes and highlighted the pleiotropic effects of these neuropeptides and their role in maintaining physiological homeostasis in humans.ConclusionsWe compiled a list of 131 human neuropeptide genes from multiple databases and literature survey. We detect significant population differentiation in the derived allele frequencies of variants in several neuropeptide genes in African and non-African populations. The results highlights SNPs in these genes that may also contribute to population disparities in prevalence of diseases such as hypertension and diabetes.

In the presence of population structure: From genomics to candidate genes underlying local adaptation.

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis‐regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low‐frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis‐regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic‐acid pathway to local adaptation.

Selection On synonymous Mutations Revealed by 1135 Genomes of Arabidopsis thaliana.

Synonymous mutations do not change the amino acid but do change the synonymous codon usage. In genomes of different organisms, the gene conversion process is biased toward GC, which is irrespective of mutation bias. In the coding region, this trend is especially obvious and it is possibly caused by the preference on G/C-ending codons over the A/T-ending ones. If the G/C-ending codons are advantageous, then the synonymous mutations that change A/T to G/C would be “optimal” compared to the opposite ones. In theory, one should observe signals of positive selection on these optimal synonymous mutations. The recently released single-nucleotide polymorphism (SNP) data from the 1001 genome project of Arabidopsis thaliana provided researchers with an unprecedented opportunity to verify this assumption. I fully take advantage of the SNP data from 1,135 A thaliana lines and came to the conclusion that synonymous mutations in natural populations are not strictly neutral: the synonymous mutations that increase GC content (from A/T to G/C) tend to have higher derived allele frequencies (DAFs) and, therefore, are likely to be positively selected. My current study broadens our knowledge of the selection patterns of synonymous mutations and should be appealing to evolutionary biologists.One sentence summary: In 1135 genomes of Arabidopsis thaliana, the synonymous mutations that increase the GC content tend to have higher derived allele frequencies (DAFs) and are likely to be positively selected.

No Evidence for Widespread Positive Selection Signatures in Common Risk Alleles Associated with Schizophrenia.

Schizophrenia poses an evolutionary-genetic paradox as it exhibits strongly negative fitness effects (early mortality and decreased fecundity), yet it persists at a prevalence of approximately 1% worldwide. Evidence from several studies have suggested that schizophrenia is evolved and maintained in part as a maladaptive byproduct of recent positive selection and adaptive evolution in human beings. However, inconsistent results have been also proposed, challenging the recent positive selection theory to explain the high population frequency of schizophrenia-associated alleles. Here, we used public domain data to locate signatures of positive selection based on genetic diversity, derived allele frequency, differentiation between populations, and long haplotypes at schizophrenia-associated single nucleotide polymorphisms (SNPs) and randomly selected SNPs (as negative controls). We found evidence for positive selection at 10 out of the 105 schizophrenia-associated SNPs, while 5 of these SNPs involved positive selection for the protective allele. Taken together, the absence of widespread positive selection signals at the schizophrenia-associated SNPs, along with the fact that half of the positive selection favored the protective allele, provide little evidence supporting the positive selection theory in schizophrenia.