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.     

Drosophila Evolution over Space and Time (DEST): A New Population Genomics Resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in >20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.     

Population genomic footprints of selection and associations with climate in natural populations of Arabidopsis halleri from the Alps

Natural genetic variation is essential for the adaptation of organisms to their local environment and to changing environmental conditions. Here, we examine genomewide patterns of nucleotide variation in natural populations of the outcrossing herb Arabidopsis halleri and associations with climatic variation among populations in the Alps. Using a pooled population sequencing (Pool‐Seq) approach, we discovered more than two million SNPs in five natural populations and identified highly differentiated genomic regions and SNPs using F_ST‐based analyses. We tested only the most strongly differentiated SNPs for associations with a nonredundant set of environmental factors using partial Mantel tests to identify topo‐climatic factors that may underlie the observed footprints of selection. Possible functions of genes showing signatures of selection were identified by Gene Ontology analysis. We found 175 genes to be highly associated with one or more of the five tested topo‐climatic factors. Of these, 23.4% had unknown functions. Genetic variation in four candidate genes was strongly associated with site water balance and solar radiation, and functional annotations were congruent with these environmental factors. Our results provide a genomewide perspective on the distribution of adaptive genetic variation in natural plant populations from a highly diverse and heterogeneous alpine environment.     

Rapid Assessment of Genetic Ancestry in Populations of Unknown Origin by Genome-Wide Genotyping of Pooled Samples

As we move forward from the current generation of genome-wide association (GWA) studies, additional cohorts of different ancestries will be studied to increase power, fine map association signals, and generalize association results to additional populations. Knowledge of genetic ancestry as well as population substructure will become increasingly important for GWA studies in populations of unknown ancestry. Here we propose genotyping pooled DNA samples using genome-wide SNP arrays as a viable option to efficiently and inexpensively estimate admixture proportion and identify ancestry informative markers (AIMs) in populations of unknown origin. We constructed DNA pools from African American, Native Hawaiian, Latina, and Jamaican samples and genotyped them using the Affymetrix 6.0 array. Aided by individual genotype data from the African American cohort, we established quality control filters to remove poorly performing SNPs and estimated allele frequencies for the remaining SNPs in each panel. We then applied a regression-based method to estimate the proportion of admixture in each cohort using the allele frequencies estimated from pooling and populations from the International HapMap Consortium as reference panels, and identified AIMs unique to each population. In this study, we demonstrated that genotyping pooled DNA samples yields estimates of admixture proportion that are both consistent with our knowledge of population history and similar to those obtained by genotyping known AIMs. Furthermore, through validation by individual genotyping, we demonstrated that pooling is quite effective for identifying SNPs with large allele frequency differences (i.e., AIMs) and that these AIMs are able to differentiate two closely related populations (HapMap JPT and CHB).     

Detecting selective sweeps from pooled next-generation sequencing samples

Due to its cost effectiveness, next-generation sequencing of pools of individuals (Pool-Seq) is becoming a popular strategy for characterizing variation in population samples. Because Pool-Seq provides genome-wide SNP frequency data, it is possible to use them for demographic inference and/or the identification of selective sweeps. Here, we introduce a statistical method that is designed to detect selective sweeps from pooled data by accounting for statistical challenges associated with Pool-Seq, namely sequencing errors and random sampling among chromosomes. This allows for an efficient use of the information: all base calls are included in the analysis, but the higher credibility of regions with higher coverage and base calls with better quality scores is accounted for. Computer simulations show that our method efficiently detects sweeps even at very low coverage (0.5× per chromosome). Indeed, the power of detecting sweeps is similar to what we could expect from sequences of individual chromosomes. Since the inference of selective sweeps is based on the allele frequency spectrum (AFS), we also provide a method to accurately estimate the AFS provided that the quality scores for the sequence reads are reliable. Applying our approach to Pool-Seq data from Drosophila melanogaster, we identify several selective sweep signatures on chromosome X that include some previously well-characterized sweeps like the wapl region.     

A Genome-Wide,Fine-Scale Map of Natural Pigmentation Variation in Drosophila melanogaster

Various approaches can be applied to uncover the genetic basis of natural phenotypic variation, each with their specific strengths and limitations. Here, we use a replicated genome-wide association approach (Pool-GWAS) to fine-scale map genomic regions contributing to natural variation in female abdominal pigmentation in Drosophila melanogaster, a trait that is highly variable in natural populations and highly heritable in the laboratory. We examined abdominal pigmentation phenotypes in approximately 8000 female European D. melanogaster, isolating 1000 individuals with extreme phenotypes. We then used whole-genome Illumina sequencing to identify single nucleotide polymorphisms (SNPs) segregating in our sample, and tested these for associations with pigmentation by contrasting allele frequencies between replicate pools of light and dark individuals. We identify two small regions near the pigmentation genes tan and bric-à-brac 1, both corresponding to known cis-regulatory regions, which contain SNPs showing significant associations with pigmentation variation. While the Pool-GWAS approach suffers some limitations, its cost advantage facilitates replication and it can be applied to any non-model system with an available reference genome.     

Sequencing of pooled DNA samples (Pool-Seq) uncovers complex dynamics of transposable element insertions in Drosophila melanogaster

Transposable elements (TEs) are mobile genetic elements that parasitize genomes by semi-autonomously increasing their own copy number within the host genome. While TEs are important for genome evolution, appropriate methods for performing unbiased genome-wide surveys of TE variation in natural populations have been lacking. Here, we describe a novel and cost-effective approach for estimating population frequencies of TE insertions using paired-end Illumina reads from a pooled population sample. Importantly, the method treats insertions present in and absent from the reference genome identically, allowing unbiased TE population frequency estimates. We apply this method to data from a natural Drosophila melanogaster population from Portugal. Consistent with previous reports, we show that low recombining genomic regions harbor more TE insertions and maintain insertions at higher frequencies than do high recombining regions. We conservatively estimate that there are almost twice as many "novel" TE insertion sites as sites known from the reference sequence in our population sample (6,824 novel versus 3,639 reference sites, with on average a 31-fold coverage per insertion site). Different families of transposable elements show large differences in their insertion densities and population frequencies. Our analyses suggest that the history of TE activity significantly contributes to this pattern, with recently active families segregating at lower frequencies than those active in the more distant past. Finally, using our high-resolution TE abundance measurements, we identified 13 candidate positively selected TE insertions based on their high population frequencies and on low Tajima's D values in their neighborhoods.     

High-density single-nucleotide polymorphism maps of the human genome

Here we report a large, extensively characterized set of single-nucleotide polymorphisms (SNPs) covering the human genome. We determined the allele frequencies of 55,018 SNPs in African Americans, Asians (Japanese-Chinese), and European Americans as part of The SNP Consortium's Allele Frequency Project. A subset of 8333 SNPs was also characterized in Koreans. Because these SNPs were ascertained in the same way, the data set is particularly useful for modeling. Our results document that much genetic variation is shared among populations. For autosomes, some 44% of these SNPs have a minor allele frequency > or =10% in each population, and the average allele frequency differences between populations with different continental origins are less than 19%. However, the several percentage point allele frequency differences among the closely related Korean, Japanese, and Chinese populations suggest caution in using mixtures of well-established populations for case-control genetic studies of complex traits. We estimate that approximately 7% of these SNPs are private SNPs with minor allele frequencies <1%. A useful set of characterized SNPs with large allele frequency differences between populations (>60%) can be used for admixture studies. High-density maps of high-quality, characterized SNPs produced by this project are freely available.     

A Population Genomic Assessment of Three Decades of Evolution in a Natural Drosophila Population

Population genetics seeks to illuminate the forces shaping genetic variation, often based on a single snapshot of genomic variation. However, utilizing multiple sampling times to study changes in allele frequencies can help clarify the relative roles of neutral and non-neutral forces on short time scales. This study compares whole-genome sequence variation of recently collected natural population samples of Drosophila melanogaster against a collection made approximately 35 years prior from the same locality—encompassing roughly 500 generations of evolution. The allele frequency changes between these time points would suggest a relatively small local effective population size on the order of 10,000, significantly smaller than the global effective population size of the species. Some loci display stronger allele frequency changes than would be expected anywhere in the genome under neutrality—most notably the tandem paralogs Cyp6a17 and Cyp6a23, which are impacted by structural variation associated with resistance to pyrethroid insecticides. We find a genome-wide excess of outliers for high genetic differentiation between old and new samples, but a larger number of adaptation targets may have affected SNP-level differentiation versus window differentiation. We also find evidence for strengthening latitudinal allele frequency clines: northern-associated alleles have increased in frequency by an average of nearly 2.5% at SNPs previously identified as clinal outliers, but no such pattern is observed at random SNPs. This project underscores the scientific potential of using multiple sampling time points to investigate how evolution operates in natural populations, by quantifying how genetic variation has changed over ecologically relevant timescales.     

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.     

Identification of selective sweeps in closely related populations of the house mouse based on microsatellite scans

Genome scans of polymorphisms promise to provide insights into the patterns and frequencies of positive selection under natural conditions. The use of microsatellites as markers has the potential to focus on very recent events, since in contrast to SNPs, their high mutation rates should remove signatures of older events. We assess this concept here in a large-scale study. We have analyzed two population pairs of the house mouse, one pair of the subspecies Mus musculus domesticus and the other of M. m. musculus. A total of 915 microsatellite loci chosen to cover the whole genome were assessed in a prescreening procedure, followed by individual typing of candidate loci. Schlötterer's ratio statistics (lnRH) were applied to detect loci with significant deviations from patterns of neutral expectation. For eight loci from each population pair we have determined the size of the potential sweep window and applied a second statistical procedure (linked locus statistics). For the two population pairs, we find five and four significant sweep loci, respectively, with an average estimated window size of 120 kb. On the basis of the analysis of individual allele frequencies, it is possible to identify the most recent sweep, for which we estimate an onset of 400–600 years ago. Given the known population history for the French–German population pair, we infer that the average frequency of selective sweeps in these populations is higher than 1 in 100 generations across the whole genome. We discuss the implications for adaptation processes in natural populations.     

Empirical Validation of Pooled Whole Genome Population Re-Sequencing in Drosophila melanogaster

The sequencing of pooled non-barcoded individuals is an inexpensive and efficient means of assessing genome-wide population allele frequencies, yet its accuracy has not been thoroughly tested. We assessed the accuracy of this approach on whole, complex eukaryotic genomes by resequencing pools of largely isogenic, individually sequenced Drosophila melanogaster strains. We called SNPs in the pooled data and estimated false positive and false negative rates using the SNPs called in individual strain as a reference. We also estimated allele frequency of the SNPs using "pooled" data and compared them with "true" frequencies taken from the estimates in the individual strains. We demonstrate that pooled sequencing provides a faithful estimate of population allele frequency with the error well approximated by binomial sampling, and is a reliable means of novel SNP discovery with low false positive rates. However, a sufficient number of strains should be used in the pooling because variation in the amount of DNA derived from individual strains is a substantial source of noise when the number of pooled strains is low. Our results and analysis confirm that pooled sequencing is a very powerful and cost-effective technique for assessing of patterns of sequence variation in populations on genome-wide scales, and is applicable to any dataset where sequencing individuals or individual cells is impossible, difficult, time consuming, or expensive.     

A Genome Scan for Genes Underlying Microgeographic-Scale Local Adaptation in a Wild Arabidopsis Species

Adaptive divergence at the microgeographic scale has been generally disregarded because high gene flow is expected to disrupt local adaptation. Yet, growing number of studies reporting adaptive divergence at a small spatial scale highlight the importance of this process in evolutionary biology. To investigate the genetic basis of microgeographic local adaptation, we conducted a genome-wide scan among sets of continuously distributed populations of Arabidopsis halleri subsp. gemmifera that show altitudinal phenotypic divergence despite gene flow. Genomic comparisons were independently conducted in two distinct mountains where similar highland ecotypes are observed, presumably as a result of convergent evolution. Here, we established a de novo reference genome and employed an individual-based resequencing for a total of 56 individuals. Among 527,225 reliable SNP loci, we focused on those showing a unidirectional allele frequency shift across altitudes. Statistical tests on the screened genes showed that our microgeographic population genomic approach successfully retrieve genes with functional annotations that are in line with the known phenotypic and environmental differences between altitudes. Furthermore, comparison between the two distinct mountains enabled us to screen out those genes that are neutral or adaptive only in either mountain, and identify the genes involved in the convergent evolution. Our study demonstrates that the genomic comparison among a set of genetically connected populations, instead of the commonly-performed comparison between two isolated populations, can also offer an effective screening for the genetic basis of local adaptation.     

A method for finding single-nucleotide polymorphisms with allele frequencies in sequences of deep coverage

Background  

The allele frequencies of single-nucleotide polymorphisms (SNPs) are needed to select an optimal subset of common SNPs for use in association studies. Sequence-based methods for finding SNPs with allele frequencies may need to handle thousands of sequences from the same genome location (sequences of deep coverage).     

Efficient and cost effective population resequencing by pooling and in-solution hybridization

High-throughput sequencing of targeted genomic loci in large populations is an effective approach for evaluating the contribution of rare variants to disease risk. We evaluated the feasibility of using in-solution hybridization-based target capture on pooled DNA samples to enable cost-efficient population sequencing studies. For this, we performed pooled sequencing of 100 HapMap samples across ～ 600 kb of DNA sequence using the Illumina GAIIx. Using our accurate variant calling method for pooled sequence data, we were able to not only identify single nucleotide variants with a low false discovery rate (<1%) but also accurately detect short insertion/deletion variants. In addition, with sufficient coverage per individual in each pool (30-fold) we detected 97.2% of the total variants and 93.6% of variants below 5% in frequency. Finally, allele frequencies for single nucleotide variants (SNVs) estimated from the pooled data and the HapMap genotype data were tightly correlated (correlation coefficient > = 0.995).     

Population screening of single-nucleotide polymorphisms exemplified by analysis of 8000 alleles

The authors describe a method in which the population frequency of single-nucleotide polymorphisms (SNPs) can be efficiently detected and their allele frequencies accurately measured. Selected SNPs in TNFbeta, IL-4, and CTLA-4 were used to demonstrate the method. Blood from 4000 individuals was pooled, DNA was extracted, and target sequences were PCR amplified and analyzed by denaturant capillary electrophoresis. Alleles were separated into peaks based on melting properties of the double DNA helix. Frequencies of the different alleles were determined by calculating the area under the peaks. Allele frequencies and Hardy-Weinberg equilibrium estimated from the pooled data were verified by analyzing 7.5% of the samples randomly selected from the blood donor series. The method herein is equally suitable for single-samples and/or pooled-samples analysis of SNPs, in which sample treatment is kept to a minimum. The potential throughput of the method is beyond obtainable numbers of samples.     

Empirical Distributions of F ST from Large-Scale Human Polymorphism Data

Studies of the apportionment of human genetic variation have long established that most human variation is within population groups and that the additional variation between population groups is small but greatest when comparing different continental populations. These studies often used Wright’s F _ST that apportions the standardized variance in allele frequencies within and between population groups. Because local adaptations increase population differentiation, high-F _ST may be found at closely linked loci under selection and used to identify genes undergoing directional or heterotic selection. We re-examined these processes using HapMap data. We analyzed 3 million SNPs on 602 samples from eight worldwide populations and a consensus subset of 1 million SNPs found in all populations. We identified four major features of the data: First, a hierarchically F _ST analysis showed that only a paucity (12%) of the total genetic variation is distributed between continental populations and even a lesser genetic variation (1%) is found between intra-continental populations. Second, the global F _ST distribution closely follows an exponential distribution. Third, although the overall F _ST distribution is similarly shaped (inverse J), F _ST distributions varies markedly by allele frequency when divided into non-overlapping groups by allele frequency range. Because the mean allele frequency is a crude indicator of allele age, these distributions mark the time-dependent change in genetic differentiation. Finally, the change in mean-F _ST of these groups is linear in allele frequency. These results suggest that investigating the extremes of the F _ST distribution for each allele frequency group is more efficient for detecting selection. Consequently, we demonstrate that such extreme SNPs are more clustered along the chromosomes than expected from linkage disequilibrium for each allele frequency group. These genomic regions are therefore likely candidates for natural selection.