A genome-wide comparison of the functional properties of rare and common genetic variants in humans

One of the longest running debates in evolutionary biology concerns the kind of genetic variation that is primarily responsible for phenotypic variation in species. Here, we address this question for humans specifically from the perspective of population allele frequency of variants across the complete genome, including both coding and noncoding regions. We establish simple criteria to assess the likelihood that variants are functional based on their genomic locations and then use whole-genome sequence data from 29 subjects of European origin to assess the relationship between the functional properties of variants and their population allele frequencies. We find that for all criteria used to assess the likelihood that a variant is functional, the rarer variants are significantly more likely to be functional than the more common variants. Strikingly, these patterns disappear when we focus on only those variants in which the major alleles are derived. These analyses indicate that the majority of the genetic variation in terms of phenotypic consequence may result from a mutation-selection balance, as opposed to balancing selection, and have direct relevance to the study of human disease.     

Analysis of sequence conservation at nucleotide resolution

One of the major goals of comparative genomics is to understand the evolutionary history of each nucleotide in the human genome sequence, and the degree to which it is under selective pressure. Ascertainment of selective constraint at nucleotide resolution is particularly important for predicting the functional significance of human genetic variation and for analyzing the sequence substructure of cis-regulatory sequences and other functional elements. Current methods for analysis of sequence conservation are focused on delineation of conserved regions comprising tens or even hundreds of consecutive nucleotides. We therefore developed a novel computational approach designed specifically for scoring evolutionary conservation at individual base-pair resolution. Our approach estimates the rate at which each nucleotide position is evolving, computes the probability of neutrality given this rate estimate, and summarizes the result in a Sequence CONservation Evaluation (SCONE) score. We computed SCONE scores in a continuous fashion across 1% of the human genome for which high-quality sequence information from up to 23 genomes are available. We show that SCONE scores are clearly correlated with the allele frequency of human polymorphisms in both coding and noncoding regions. We find that the majority of noncoding conserved nucleotides lie outside of longer conserved elements predicted by other conservation analyses, and are experiencing ongoing selection in modern humans as evident from the allele frequency spectrum of human polymorphism. We also applied SCONE to analyze the distribution of conserved nucleotides within functional regions. These regions are markedly enriched in individually conserved positions and short (<15 bp) conserved “chunks.” Our results collectively suggest that the majority of functionally important noncoding conserved positions are highly fragmented and reside outside of canonically defined long conserved noncoding sequences. A small subset of these fragmented positions may be identified with high confidence.     

Natural selection affects multiple aspects of genetic variation at putatively neutral sites across the human genome

A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries of genetic variation, like allele frequencies, are also correlated with recombination rate and whether these correlations can be explained solely by negative selection against deleterious mutations or whether positive selection acting on favorable alleles is also required. Here we attempt to address these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations. However, models with strong positive selection on nonsynonymous mutations and little negative selection predict a stronger negative correlation between neutral diversity and nonsynonymous divergence than observed in the actual data, supporting the importance of negative, rather than positive, selection throughout the genome. Further, we show that the widespread presence of weakly deleterious alleles, rather than a small number of strongly positively selected mutations, is responsible for the correlation between neutral genetic diversity and recombination rate. This work suggests that natural selection has affected multiple aspects of linked neutral variation throughout the human genome and that positive selection is not required to explain these observations.     

Kinetic FP-TDI assay for SNP allele frequency determination

Strategies for identifying genetic risk factors in complex diseases by association studies require the comparison of allele frequencies of numerous SNPs between affected and control populations. Theoretically, hundreds of thousands of SNP markers across the genome will have to be genotyped in these studies. Genotyping SNPs one sample at a time is extremely costly and time consuming. To streamline whole genome association studies, some have proposed to screen SNPs by pooling the DNA samples initially for allele frequency determination and perform individual genotyping only when there is a significant discrepancy in allele frequencies between the affected and control populations. Here we describe a new method for determining the allele frequency of SNPs in pooled DNA samples using a two-color primer extension assay with real-time monitoring of fluorescence polarization (named kinetic FP-TDI assay). By comparing the ratio of the rate of incorporation of the two allele-specific dye-terminators, one can calculate the relative amounts of each allele in the pooled sample. The accuracy of allele frequency determination with pooled samples is within 3.3 +/- 0.8% of that determined by genotyping individual samples that make up the pool.     

Confidence Intervals for Population Allele Frequencies: The General Case of Sampling from a Finite Diploid Population of Any Size

The estimation of population allele frequencies using sample data forms a central component of studies in population genetics. These estimates can be used to test hypotheses on the evolutionary processes governing changes in genetic variation among populations. However, existing studies frequently do not account for sampling uncertainty in these estimates, thus compromising their utility. Incorporation of this uncertainty has been hindered by the lack of a method for constructing confidence intervals containing the population allele frequencies, for the general case of sampling from a finite diploid population of any size. In this study, we address this important knowledge gap by presenting a rigorous mathematical method to construct such confidence intervals. For a range of scenarios, the method is used to demonstrate that for a particular allele, in order to obtain accurate estimates within 0.05 of the population allele frequency with high probability (%), a sample size of is often required. This analysis is augmented by an application of the method to empirical sample allele frequency data for two populations of the checkerspot butterfly (Melitaea cinxia L.), occupying meadows in Finland. For each population, the method is used to derive % confidence intervals for the population frequencies of three alleles. These intervals are then used to construct two joint % confidence regions, one for the set of three frequencies for each population. These regions are then used to derive a % confidence interval for Jost''s D, a measure of genetic differentiation between the two populations. Overall, the results demonstrate the practical utility of the method with respect to informing sampling design and accounting for sampling uncertainty in studies of population genetics, important for scientific hypothesis-testing and also for risk-based natural resource management.     

Polymorphic NumtS trace human population relationships

The human genome is constantly subjected to evolutionary forces which shape its architecture. Insertions of mitochondrial DNA sequences into nuclear genome (NumtS) have been described in several eukaryotic species, including Homo sapiens and other primates. The ongoing process of the generation of NumtS has made them valuable markers in primate phylogenetic studies, as well as potentially informative loci for reconstructing the genetic history of modern humans. Here, we report the identification of 53 human-specific NumtS by inspection of the UCSC genome browser, showing that they may be direct insertions of mitochondrial DNA into the human nuclear DNA after the human-chimpanzee split. In silico analyses allowed us to identify 14 NumtS which are polymorphic in terms of their presence/absence within the human genome in individuals of different ancestry. The allele frequencies of these polymorphic NumtS were calculated for 1000 Genomes Project sequence data from 13 populations worldwide, and principal components analysis and hierarchical clustering methods allowed the detection of strong signals of geographical structure related to the genetic diversity of these loci. All identified polymorphic human-specific NumtS together with a tandemly duplicated NumtS have also been validated by PCR amplification on a panel of 60 samples belonging to five native populations worldwide, confirming the expected NumtS variability. On the basis of these findings, we have succeeded in depicting the landscape of variation of a series of NumtS in several ethnic groups, making an advance in their identification as useful markers in the study on human population genetics.     

Low Frequency Variants,Collapsed Based on Biological Knowledge,Uncover Complexity of Population Stratification in 1000 Genomes Project Data

Analyses investigating low frequency variants have the potential for explaining additional genetic heritability of many complex human traits. However, the natural frequencies of rare variation between human populations strongly confound genetic analyses. We have applied a novel collapsing method to identify biological features with low frequency variant burden differences in thirteen populations sequenced by the 1000 Genomes Project. Our flexible collapsing tool utilizes expert biological knowledge from multiple publicly available database sources to direct feature selection. Variants were collapsed according to genetically driven features, such as evolutionary conserved regions, regulatory regions genes, and pathways. We have conducted an extensive comparison of low frequency variant burden differences (MAF<0.03) between populations from 1000 Genomes Project Phase I data. We found that on average 26.87% of gene bins, 35.47% of intergenic bins, 42.85% of pathway bins, 14.86% of ORegAnno regulatory bins, and 5.97% of evolutionary conserved regions show statistically significant differences in low frequency variant burden across populations from the 1000 Genomes Project. The proportion of bins with significant differences in low frequency burden depends on the ancestral similarity of the two populations compared and types of features tested. Even closely related populations had notable differences in low frequency burden, but fewer differences than populations from different continents. Furthermore, conserved or functionally relevant regions had fewer significant differences in low frequency burden than regions under less evolutionary constraint. This degree of low frequency variant differentiation across diverse populations and feature elements highlights the critical importance of considering population stratification in the new era of DNA sequencing and low frequency variant genomic analyses.     

Sequence Variation within the KIV-2 Copy Number Polymorphism of the Human LPA Gene in African,Asian, and European Populations

Amazingly little sequence variation is reported for the kringle IV 2 copy number variation (KIV 2 CNV) in the human LPA gene. Apart from whole genome sequencing projects, this region has only been analyzed in some detail in samples of European populations. We have performed a systematic resequencing study of the exonic and flanking intron regions within the KIV 2 CNV in 90 alleles from Asian, European, and four different African populations. Alleles have been separated according to their CNV length by pulsed field gel electrophoresis prior to unbiased specific PCR amplification of the target regions. These amplicons covered all KIV 2 copies of an individual allele simultaneously. In addition, cloned amplicons from genomic DNA of an African individual were sequenced. Our data suggest that sequence variation in this genomic region may be higher than previously appreciated. Detection probability of variants appeared to depend on the KIV 2 copy number of the analyzed DNA and on the proportion of copies carrying the variant. Asians had a high frequency of so-called KIV 2 type B and type C (together 70% of alleles), which differ by three or two synonymous substitutions respectively from the reference type A. This is most likely explained by the strong bottleneck suggested to have occurred when modern humans migrated to East Asia. A higher frequency of variable sites was detected in the Africans. In particular, two previously unreported splice site variants were found. One was associated with non-detectable Lp(a). The other was observed at high population frequencies (10% to 40%). Like the KIV 2 type B and C variants, this latter variant was also found in a high proportion of KIV 2 repeats in the affected alleles and in alleles differing in copy numbers. Our findings may have implications for the interpretation of SNP analyses in other repetitive loci of the human genome.     

SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries

High-density single-nucleotide polymorphism (SNP) arrays have revolutionized the ability of genome-wide association studies to detect genomic regions harboring sequence variants that affect complex traits. Extensive numbers of validated SNPs with known allele frequencies are essential to construct genotyping assays with broad utility. We describe an economical, efficient, single-step method for SNP discovery, validation and characterization that uses deep sequencing of reduced representation libraries (RRLs) from specified target populations. Using nearly 50 million sequences generated on an Illumina Genome Analyzer from DNA of 66 cattle representing three populations, we identified 62,042 putative SNPs and predicted their allele frequencies. Genotype data for these 66 individuals validated 92% of 23,357 selected genome-wide SNPs, with a genotypic and sequence allele frequency correlation of r = 0.67. This approach for simultaneous de novo discovery of high-quality SNPs and population characterization of allele frequencies may be applied to any species with at least a partially sequenced genome.     

A comprehensive map of mobile element insertion polymorphisms in humans

As a consequence of the accumulation of insertion events over evolutionary time, mobile elements now comprise nearly half of the human genome. The Alu, L1, and SVA mobile element families are still duplicating, generating variation between individual genomes. Mobile element insertions (MEI) have been identified as causes for genetic diseases, including hemophilia, neurofibromatosis, and various cancers. Here we present a comprehensive map of 7,380 MEI polymorphisms from the 1000 Genomes Project whole-genome sequencing data of 185 samples in three major populations detected with two detection methods. This catalog enables us to systematically study mutation rates, population segregation, genomic distribution, and functional properties of MEI polymorphisms and to compare MEI to SNP variation from the same individuals. Population allele frequencies of MEI and SNPs are described, broadly, by the same neutral ancestral processes despite vastly different mutation mechanisms and rates, except in coding regions where MEI are virtually absent, presumably due to strong negative selection. A direct comparison of MEI and SNP diversity levels suggests a differential mobile element insertion rate among populations.     

PPC: an algorithm for accurate estimation of SNP allele frequencies in small equimolar pools of DNA using data from high density microarrays

Robust estimation of allele frequencies in pools of DNA has the potential to reduce genotyping costs and/or increase the number of individuals contributing to a study where hundreds of thousands of genetic markers need to be genotyped in very large populations sample sets, such as genome wide association studies. In order to make accurate allele frequency estimations from pooled samples a correction for unequal allele representation must be applied. We have developed the polynomial based probe specific correction (PPC) which is a novel correction algorithm for accurate estimation of allele frequencies in data from high-density microarrays. This algorithm was validated through comparison of allele frequencies from a set of 10 individually genotyped DNA's and frequencies estimated from pools of these 10 DNAs using GeneChip 10K Mapping Xba 131 arrays. Our results demonstrate that when using the PPC to correct for allelic biases the accuracy of the allele frequency estimates increases dramatically.     

Weak selection and protein evolution

The "nearly neutral" theory of molecular evolution proposes that many features of genomes arise from the interaction of three weak evolutionary forces: mutation, genetic drift, and natural selection acting at its limit of efficacy. Such forces generally have little impact on allele frequencies within populations from generation to generation but can have substantial effects on long-term evolution. The evolutionary dynamics of weakly selected mutations are highly sensitive to population size, and near neutrality was initially proposed as an adjustment to the neutral theory to account for general patterns in available protein and DNA variation data. Here, we review the motivation for the nearly neutral theory, discuss the structure of the model and its predictions, and evaluate current empirical support for interactions among weak evolutionary forces in protein evolution. Near neutrality may be a prevalent mode of evolution across a range of functional categories of mutations and taxa. However, multiple evolutionary mechanisms (including adaptive evolution, linked selection, changes in fitness-effect distributions, and weak selection) can often explain the same patterns of genome variation. Strong parameter sensitivity remains a limitation of the nearly neutral model, and we discuss concave fitness functions as a plausible underlying basis for weak selection.     

A whole genome long-range haplotype (WGLRH) test for detecting imprints of positive selection in human populations

MOTIVATION: The identification of signatures of positive selection can provide important insights into recent evolutionary history in human populations. Current methods mostly rely on allele frequency determination or focus on one or a small number of candidate chromosomal regions per study. With the availability of large-scale genotype data, efficient approaches for an unbiased whole genome scan are becoming necessary. METHODS: We have developed a new method, the whole genome long-range haplotype test (WGLRH), which uses genome-wide distributions to test for recent positive selection. Adapted from the long-range haplotype (LRH) test, the WGLRH test uses patterns of linkage disequilibrium (LD) to identify regions with extremely low historic recombination. Common haplotypes with significantly longer than expected ranges of LD given their frequencies are identified as putative signatures of recent positive selection. In addition, we have also determined the ancestral alleles of SNPs by genotyping chimpanzee and gorilla DNA, and have identified SNPs where the non-ancestral alleles have risen to extremely high frequencies in human populations, termed 'flipped SNPs'. Combining the haplotype test and the flipped SNPs determination, the WGLRH test serves as an unbiased genome-wide screen for regions under putative selection, and is potentially applicable to the study of other human populations. RESULTS: Using WGLRH and high-density oligonucleotide arrays interrogating 116 204 SNPs, we rapidly identified putative regions of positive selection in three populations (Asian, Caucasian, African-American), and extended these observations to a fourth population, Yoruba, with data obtained from the International HapMap consortium. We mapped significant regions to annotated genes. While some regions overlap with genes previously suggested to be under positive selection, many of the genes have not been previously implicated in natural selection and offer intriguing possibilities for further study. AVAILABILITY: the programs for the WGLRH algorithm are freely available and can be downloaded at http://www.affymetrix.com/support/supplement/WGLRH_program.zip.     

Physiological stress and the maintenance of adaptive genetic variation in a livebearing fish

The importance of genetic variation in evolution is well established. Yet, the mechanisms by which genetic variation—particularly variation in traits under selection—is maintained in natural populations has long been an evolutionary puzzle. Understanding individual variables driving selection and their functional mechanisms is increasingly important in the context of global change and its potential consequences for biodiversity. Here we examined intra-population performance among allelic variants of a pleiotropic locus in response to thermal stress in the variable platyfish, Xiphophorus variatus. The wild-type tailspot allele exhibited significantly lower heat tolerance than all three pattern alleles found in the population, conforming to predictions based on previously observed correlations between temperature and pattern frequencies in the wild. Furthermore, differences between tailspot pattern frequencies in adults and juveniles were broadly consistent with this trend. Thus, it appears that physiological stress and reduced performance of the wild-type allele at higher relative temperatures is a mechanism balancing its frequency in natural populations. Temperature variation and not dissolved oxygen alone, as previously reported, is likely a important abiotic variable contributing to the maintenance of adaptive polymorphism. Furthermore, our findings underscore the potential implications of rising temperatures and physiological stress for levels of genetic variation in natural populations.     

Nucleosomes Shape DNA Polymorphism and Divergence

An estimated 80% of genomic DNA in eukaryotes is packaged as nucleosomes, which, together with the remaining interstitial linker regions, generate higher order chromatin structures [1]. Nucleosome sequences isolated from diverse organisms exhibit ∼10 bp periodic variations in AA, TT and GC dinucleotide frequencies. These sequence elements generate intrinsically curved DNA and help establish the histone-DNA interface. We investigated an important unanswered question concerning the interplay between chromatin organization and genome evolution: do the DNA sequence preferences inherent to the highly conserved histone core exert detectable natural selection on genomic divergence and polymorphism? To address this hypothesis, we isolated nucleosomal DNA sequences from Drosophila melanogaster embryos and examined the underlying genomic variation within and between species. We found that divergence along the D. melanogaster lineage is periodic across nucleosome regions with base changes following preferred nucleotides, providing new evidence for systematic evolutionary forces in the generation and maintenance of nucleosome-associated dinucleotide periodicities. Further, Single Nucleotide Polymorphism (SNP) frequency spectra show striking periodicities across nucleosomal regions, paralleling divergence patterns. Preferred alleles occur at higher frequencies in natural populations, consistent with a central role for natural selection. These patterns are stronger for nucleosomes in introns than in intergenic regions, suggesting selection is stronger in transcribed regions where nucleosomes undergo more displacement, remodeling and functional modification. In addition, we observe a large-scale (∼180 bp) periodic enrichment of AA/TT dinucleotides associated with nucleosome occupancy, while GC dinucleotide frequency peaks in linker regions. Divergence and polymorphism data also support a role for natural selection in the generation and maintenance of these super-nucleosomal patterns. Our results demonstrate that nucleosome-associated sequence periodicities are under selective pressure, implying that structural interactions between nucleosomes and DNA sequence shape sequence evolution, particularly in introns.     

Distribution of single‐nucleotide variants on protein–protein interaction sites and its relationship with minor allele frequency

Recent advances in DNA sequencing techniques have identified rare single‐nucleotide variants with less than 1% minor allele frequency. Despite the growing interest and physiological importance of rare variants in genome sciences, less attention has been paid to the allele frequency of variants in protein sciences. To elucidate the characteristics of genetic variants on protein interaction sites, from the viewpoints of the allele frequency and the structural position of variants, we mapped about 20,000 human SNVs onto protein complexes. We found that variants are less abundant in protein interfaces, and specifically the core regions of interfaces. The tendency to “avoid” the interfacial core is stronger among common variants than rare variants. As amino acid substitutions, the trend of mutating amino acids among rare variants is consistent in different interfacial regions, reflecting the fact that rare variants result from random mutations in DNA sequences, whereas amino acid changes of common variants vary between the interfacial core and rim regions, possibly due to functional constraints on proteins. This study illustrated how the allele frequency of variants relates to the protein structural regions and the functional sites in general and will lead to deeper understanding of the potential deleteriousness of rare variants at the structural level. Exceptional cases of the observed trends will shed light on the limitations of structural approaches to evaluate the functional impacts of variants.     

Allele frequency distributions of Apo B VNTR locus in Cukurova, Turkey

The highly polymorphic minisatellites contain a variable number of tandemly repeated (VNTR) DNA sequences. They are extremely useful and informative markers to study genetic variation among human populations. We have analysed the allele frequency distribution at the highly polymorphic apolipoprotein B (Apo B) VNTR locus in order to obtain the population data for the Cukurova region in Turkey by using the polymerase chain reaction and polyacrylamide gel electrophoresis. We observed 10 different alleles and 21 genotypes in a sample of 100 unrelated individuals. The allele frequencies ranged from 0.01 to 0.4, with an expected heterozygosity of 0.69 for the Apo B locus. Alleles 37 (frequency = 0.4) and 35 (frequency = 0.17) were the most common in the Cukurova population. There was a significant deviation from the Hardy-Weinberg equilibrium (HWE) for genotype frequencies (chi2 = 29.12; df = 1; p = 0.000). This study possesses novelty as it is the first DNA polymorphism study conducted at the Cukurova population using an Apo B minisatellite locus.     

HLA DNA sequence variation among human populations: molecular signatures of demographic and selective events

Molecular differences between HLA alleles vary up to 57 nucleotides within the peptide binding coding region of human Major Histocompatibility Complex (MHC) genes, but it is still unclear whether this variation results from a stochastic process or from selective constraints related to functional differences among HLA molecules. Although HLA alleles are generally treated as equidistant molecular units in population genetic studies, DNA sequence diversity among populations is also crucial to interpret the observed HLA polymorphism. In this study, we used a large dataset of 2,062 DNA sequences defined for the different HLA alleles to analyze nucleotide diversity of seven HLA genes in 23,500 individuals of about 200 populations spread worldwide. We first analyzed the HLA molecular structure and diversity of these populations in relation to geographic variation and we further investigated possible departures from selective neutrality through Tajima's tests and mismatch distributions. All results were compared to those obtained by classical approaches applied to HLA allele frequencies.Our study shows that the global patterns of HLA nucleotide diversity among populations are significantly correlated to geography, although in some specific cases the molecular information reveals unexpected genetic relationships. At all loci except HLA-DPB1, populations have accumulated a high proportion of very divergent alleles, suggesting an advantage of heterozygotes expressing molecularly distant HLA molecules (asymmetric overdominant selection model). However, both different intensities of selection and unequal levels of gene conversion may explain the heterogeneous mismatch distributions observed among the loci. Also, distinctive patterns of sequence divergence observed at the HLA-DPB1 locus suggest current neutrality but old selective pressures on this gene. We conclude that HLA DNA sequences advantageously complement HLA allele frequencies as a source of data used to explore the genetic history of human populations, and that their analysis allows a more thorough investigation of human MHC molecular evolution.     

How to optimize the precision of allele and haplotype frequency estimates using pooled‐sequencing data

Sequencing pools of individuals rather than individuals separately reduces the costs of estimating allele frequencies at many loci in many populations. Theoretical and empirical studies show that sequencing pools comprising a limited number of individuals (typically fewer than 50) provides reliable allele frequency estimates, provided that the DNA pooling and DNA sequencing steps are carefully controlled. Unequal contributions of different individuals to the DNA pool and the mean and variance in sequencing depth both can affect the standard error of allele frequency estimates. To our knowledge, no study separately investigated the effect of these two factors on allele frequency estimates; so that there is currently no method to a priori estimate the relative importance of unequal individual DNA contributions independently of sequencing depth. We develop a new analytical model for allele frequency estimation that explicitly distinguishes these two effects. Our model shows that the DNA pooling variance in a pooled sequencing experiment depends solely on two factors: the number of individuals within the pool and the coefficient of variation of individual DNA contributions to the pool. We present a new method to experimentally estimate this coefficient of variation when planning a pooled sequencing design where samples are either pooled before or after DNA extraction. Using this analytical and experimental framework, we provide guidelines to optimize the design of pooled sequencing experiments. Finally, we sequence replicated pools of inbred lines of the plant Medicago truncatula and show that the predictions from our model generally hold true when estimating the frequency of known multilocus haplotypes using pooled sequencing.