Identifying the favored mutation in a positive selective sweep.

Most approaches that capture signatures of selective sweeps in population genomics data do not identify the specific mutation favored by selection. We present iSAFE (for "integrated selection of allele favored by evolution"), a method that enables researchers to accurately pinpoint the favored mutation in a large region (∼5 Mbp) by using a statistic derived solely from population genetics signals. iSAFE does not require knowledge of demography, the phenotype under selection, or functional annotations of mutations

Extreme Evolutionary Disparities Seen in Positive Selection across Seven Complex Diseases

Positive selection is known to occur when the environment that an organism inhabits is suddenly altered, as is the case across recent human history. Genome-wide association studies (GWASs) have successfully illuminated disease-associated variation. However, whether human evolution is heading towards or away from disease susceptibility in general remains an open question. The genetic-basis of common complex disease may partially be caused by positive selection events, which simultaneously increased fitness and susceptibility to disease. We analyze seven diseases studied by the Wellcome Trust Case Control Consortium to compare evidence for selection at every locus associated with disease. We take a large set of the most strongly associated SNPs in each GWA study in order to capture more hidden associations at the cost of introducing false positives into our analysis. We then search for signs of positive selection in this inclusive set of SNPs. There are striking differences between the seven studied diseases. We find alleles increasing susceptibility to Type 1 Diabetes (T1D), Rheumatoid Arthritis (RA), and Crohn's Disease (CD) underwent recent positive selection. There is more selection in alleles increasing, rather than decreasing, susceptibility to T1D. In the 80 SNPs most associated with T1D (p-value <7.01×10−5) showing strong signs of positive selection, 58 alleles associated with disease susceptibility show signs of positive selection, while only 22 associated with disease protection show signs of positive selection. Alleles increasing susceptibility to RA are under selection as well. In contrast, selection in SNPs associated with CD favors protective alleles. These results inform the current understanding of disease etiology, shed light on potential benefits associated with the genetic-basis of disease, and aid in the efforts to identify causal genetic factors underlying complex disease

Fine-scale detection of population-specific linkage disequilibrium using haplotype entropy in the human genome

<p>Abstract</p> <p>Background</p> <p>The creation of a coherent genomic map of recent selection is one of the greatest challenges towards a better understanding of human evolution and the identification of functional genetic variants. Several methods have been proposed to detect linkage disequilibrium (LD), which is indicative of natural selection, from genome-wide profiles of common genetic variations but are designed for large regions.</p> <p>Results</p> <p>To find population-specific LD within small regions, we have devised an entropy-based method that utilizes differences in haplotype frequency between populations. The method has the advantages of incorporating multilocus association, conciliation with low allele frequencies, and independence from allele polarity, which are ideal for short haplotype analysis. The comparison of HapMap SNPs data from African and Caucasian populations with a median resolution size of ~23 kb gave us novel candidates as well as known selection targets. Enrichment analysis for the yielded genes showed associations with diverse diseases such as cardiovascular, immunological, neurological, and skeletal and muscular diseases. A possible scenario for a selective force is discussed. In addition, we have developed a web interface (ENIGMA, available at <url>http://gibk21.bse.kyutech.ac.jp/ENIGMA/index.html</url>), which allows researchers to query their regions of interest for population-specific LD.</p> <p>Conclusion</p> <p>The haplotype entropy method is powerful for detecting population-specific LD embedded in short regions and should contribute to further studies aiming to decipher the evolutionary histories of modern humans.</p

Evidence for Positive Selection on the Osteogenin (BMP3) Gene in Human Populations

BACKGROUND: Human skeletal system has evolved rapidly since the dispersal of modern humans from Africa, potentially driven by selection and adaptation. Osteogenin (BMP3) plays an important role in skeletal development and bone osteogenesis as an antagonist of the osteogenic bone morphogenetic proteins, and negatively regulates bone mineral density. METHODOLOGY/PRINCIPAL FINDINGS: Here, we resequenced the BMP3 gene from individuals in four geographically separated modern human populations. Features supportive of positive selection in the BMP3 gene were found including the presence of an excess of nonsynonymous mutations in modern humans, and a significantly lower genetic diversity that deviates from neutrality. The prevalent haplotypes of the first exon region in Europeans demonstrated features of long-range haplotype homogeneity. In contrast with findings in European, the derived allele SNP Arg192Gln shows higher extended haplotype homozygosity in East Asian. The worldwide allele frequency distribution of SNP shows not only a high-derived allele frequency in Asians, but also in Americans, which is suggestive of functional adaptation. CONCLUSIONS/SIGNIFICANCE: In conclusion, we provide evidence for recent positive selection operating upon a crucial gene in skeletal development, which may provide new insight into the evolution of the skeletal system and bone development

Different level of population differentiation among human genes

<p>Abstract</p> <p>Background</p> <p>During the colonization of the world, after dispersal out of African, modern humans encountered changeable environments and substantial phenotypic variations that involve diverse behaviors, lifestyles and cultures, were generated among the different modern human populations.</p> <p>Results</p> <p>Here, we study the level of population differentiation among different populations of human genes. Intriguingly, genes involved in osteoblast development were identified as being enriched with higher <it>F</it>_STSNPs, a result consistent with the proposed role of the skeletal system in accounting for variation among human populations. Genes involved in the development of hair follicles, where hair is produced, were also found to have higher levels of population differentiation, consistent with hair morphology being a distinctive trait among human populations. Other genes that showed higher levels of population differentiation include those involved in pigmentation, spermatid, nervous system and organ development, and some metabolic pathways, but few involved with the immune system. Disease-related genes demonstrate excessive SNPs with lower levels of population differentiation, probably due to purifying selection. Surprisingly, we find that Mendelian-disease genes appear to have a significant excessive of SNPs with high levels of population differentiation, possibly because the incidence and susceptibility of these diseases show differences among populations. As expected, microRNA regulated genes show lower levels of population differentiation due to purifying selection.</p> <p>Conclusion</p> <p>Our analysis demonstrates different level of population differentiation among human populations for different gene groups.</p

No Evidence for Strong Recent Positive Selection Favoring the 7 Repeat Allele of VNTR in the DRD4 Gene

The human dopamine receptor D4 (DRD4) gene contains a 48-bp variable number of tandem repeat (VNTR) in exon 3, encoding the third intracellular loop of this dopamine receptor. The DRD4 7R allele, which seems to have a single origin, is commonly observed in various human populations and the nucleotide diversity of the DRD4 7R haplotype at the DRD4 locus is reduced compared to the most common DRD4 4R haplotype. Based on these observations, previous studies have hypothesized that positive selection has acted on the DRD4 7R allele. However, the degrees of linkage disequilibrium (LD) of the DRD4 7R allele with single nucleotide polymorphisms (SNPs) outside the DRD4 locus have not been evaluated. In this study, to re-examine the possibility of recent positive selection favoring the DRD4 7R allele, we genotyped HapMap subjects for DRD4 VNTR, and conducted several neutrality tests including long range haplotype test and iHS test based on the extended haplotype homozygosity. Our results indicated that LD of the DRD4 7R allele was not extended compared to SNP alleles with the similar frequency. Thus, we conclude that the DRD4 7R allele has not been subjected to strong recent positive selection

No Evidence for Strong Recent Positive Selection Favoring the 7 Repeat Allele of VNTR in the DRD4 Gene

The human dopamine receptor D4 (DRD4) gene contains a 48-bp variable number of tandem repeat (VNTR) in exon 3, encoding the third intracellular loop of this dopamine receptor. The DRD4 7R allele, which seems to have a single origin, is commonly observed in various human populations and the nucleotide diversity of the DRD4 7R haplotype at the DRD4 locus is reduced compared to the most common DRD4 4R haplotype. Based on these observations, previous studies have hypothesized that positive selection has acted on the DRD4 7R allele. However, the degrees of linkage disequilibrium (LD) of the DRD4 7R allele with single nucleotide polymorphisms (SNPs) outside the DRD4 locus have not been evaluated. In this study, to re-examine the possibility of recent positive selection favoring the DRD4 7R allele, we genotyped HapMap subjects for DRD4 VNTR, and conducted several neutrality tests including long range haplotype test and iHS test based on the extended haplotype homozygosity. Our results indicated that LD of the DRD4 7R allele was not extended compared to SNP alleles with the similar frequency. Thus, we conclude that the DRD4 7R allele has not been subjected to strong recent positive selection

Identifying Selected Regions from Heterozygosity and Divergence Using a Light-Coverage Genomic Dataset from Two Human Populations

When a selective sweep occurs in the chromosomal region around a target gene in two populations that have recently separated, it produces three dramatic genomic consequences: 1) decreased multi-locus heterozygosity in the region; 2) elevated or diminished genetic divergence (FST) of multiple polymorphic variants adjacent to the selected locus between the divergent populations, due to the alternative fixation of alleles; and 3) a consequent regional increase in the variance of FST (S2FST) for the same clustered variants, due to the increased alternative fixation of alleles in the loci surrounding the selection target. In the first part of our study, to search for potential targets of directional selection, we developed and validated a resampling-based computational approach; we then scanned an array of 31 different-sized moving windows of SNP variants (5–65 SNPs) across the human genome in a set of European and African American population samples with 183,997 SNP loci after correcting for the recombination rate variation. The analysis revealed 180 regions of recent selection with very strong evidence in either population or both. In the second part of our study, we compared the newly discovered putative regions to those sites previously postulated in the literature, using methods based on inspecting patterns of linkage disequilibrium, population divergence and other methodologies. The newly found regions were cross-validated with those found in nine other studies that have searched for selection signals. Our study was replicated especially well in those regions confirmed by three or more studies. These validated regions were independently verified, using a combination of different methods and different databases in other studies, and should include fewer false positives. The main strength of our analysis method compared to others is that it does not require dense genotyping and therefore can be used with data from population-based genome SNP scans from smaller studies of humans or other species

Application of site and haplotype-frequency based approaches for detecting selection signatures in cattle

<p>Abstract</p> <p>Background</p> <p>'Selection signatures' delimit regions of the genome that are, or have been, functionally important and have therefore been under either natural or artificial selection. In this study, two different and complementary methods--integrated Haplotype Homozygosity Score (|iHS|) and population differentiation index (F_ST)--were applied to identify traces of decades of intensive artificial selection for traits of economic importance in modern cattle.</p> <p>Results</p> <p>We scanned the genome of a diverse set of dairy and beef breeds from Germany, Canada and Australia genotyped with a 50 K SNP panel. Across breeds, a total of 109 extreme |iHS| values exceeded the empirical threshold level of 5% with 19, 27, 9, 10 and 17 outliers in Holstein, Brown Swiss, Australian Angus, Hereford and Simmental, respectively. Annotating the regions harboring clustered |iHS| signals revealed a panel of interesting candidate genes like SPATA17, MGAT1, PGRMC2 and ACTC1, COL23A1, MATN2, respectively, in the context of reproduction and muscle formation. In a further step, a new Bayesian F_ST-based approach was applied with a set of geographically separated populations including Holstein, Brown Swiss, Simmental, North American Angus and Piedmontese for detecting differentiated loci. In total, 127 regions exceeding the 2.5 per cent threshold of the empirical posterior distribution were identified as extremely differentiated. In a substantial number (56 out of 127 cases) the extreme F_STvalues were found to be positioned in poor gene content regions which deviated significantly (p < 0.05) from the expectation assuming a random distribution. However, significant F_STvalues were found in regions of some relevant genes such as SMCP and FGF1.</p> <p>Conclusions</p> <p>Overall, 236 regions putatively subject to recent positive selection in the cattle genome were detected. Both |iHS| and F_STsuggested selection in the vicinity of the Sialic acid binding Ig-like lectin 5 gene on BTA18. This region was recently reported to be a major QTL with strong effects on productive life and fertility traits in Holstein cattle. We conclude that high-resolution genome scans of selection signatures can be used to identify genomic regions contributing to within- and inter-breed phenotypic variation.</p

Decision Forest Analysis of 61 Single Nucleotide Polymorphisms in a Case-Control Study of Esophageal Cancer; a novel method

BACKGROUND: Systematic evaluation and study of single nucleotide polymorphisms (SNPs) made possible by high throughput genotyping technologies and bioinformatics promises to provide breakthroughs in the understanding of complex diseases. Understanding how the millions of SNPs in the human genome are involved in conferring susceptibility or resistance to disease, or in rendering a drug efficacious or toxic in the individual is a major goal of the relatively new fields of pharmacogenomics. Esophageal squamous cell carcinoma is a high-mortality cancer with complex etiology and progression involving both genetic and environmental factors. We examined the association between esophageal cancer risk and patterns of 61 SNPs in a case-control study for a population from Shanxi Province in North Central China that has among the highest rates of esophageal squamous cell carcinoma in the world. METHODS: High-throughput Masscode mass spectrometry genotyping was done on genomic DNA from 574 individuals (394 cases and 180 age-frequency matched controls). SNPs were chosen from among genes involving DNA repair enzymes, and Phase I and Phase II enzymes. We developed a novel adaptation of the Decision Forest pattern recognition method named Decision Forest for SNPs (DF-SNPs). The method was designated to analyze the SNP data. RESULTS: The classifier in separating the cases from the controls developed with DF-SNPs gave concordance, sensitivity and specificity, of 94.7%, 99.0% and 85.1%, respectively; suggesting its usefulness for hypothesizing what SNPs or combinations of SNPs could be involved in susceptibility to esophageal cancer. Importantly, the DF-SNPs algorithm incorporated a randomization test for assessing the relevance (or importance) of individual SNPs, SNP types (Homozygous common, heterozygous and homozygous variant) and patterns of SNP types (SNP patterns) that differentiate cases from controls. For example, we found that the different genotypes of SNP GADD45B E1122 are all associated with cancer risk. CONCLUSION: The DF-SNPs method can be used to differentiate esophageal squamous cell carcinoma cases from controls based on individual SNPs, SNP types and SNP patterns. The method could be useful to identify potential biomarkers from the SNP data and complement existing methods for genotype analyses