Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations.

Genetic studies in underrepresented populations identify disproportionate numbers of novel associations. However, most genetic studies use genotyping arrays and sequenced reference panels that best capture variation most common in European ancestry populations. To compare data generation strategies best suited for underrepresented populations, we sequenced the whole genomes of 91 individuals to high coverage as part of the Neuropsychiatric Genetics of African Population-Psychosis (NeuroGAP-Psychosis) study with participants from Ethiopia, Kenya, South Africa, and Uganda. We used a downsampling approach to evaluate the quality of two cost-effective data generation strategies, GWAS arrays versus low-coverage sequencing, by calculating the concordance of imputed variants from these technologies with those from deep whole-genome sequencing data. We show that low-coverage sequencing at a depth of ≥4× captures variants of all frequencies more accurately than all commonly used GWAS arrays investigated and at a comparable cost. Lower depths of sequencing (0.5-1×) performed comparably to commonly used low-density GWAS arrays. Low-coverage sequencing is also sensitive to novel variation; 4× sequencing detects 45% of singletons and 95% of common variants identified in high-coverage African whole genomes. Low-coverage sequencing approaches surmount the problems induced by the ascertainment of common genotyping arrays, effectively identify novel variation particularly in underrepresented populations, and present opportunities to enhance variant discovery at a cost similar to traditional approaches.

A panel of 32 AIMs suitable for population stratification correction and global ancestry estimation in Mexican mestizos.

BACKGROUND: Association studies are useful to unravel the genetic basis of common human diseases. However, the presence of undetected population structure can lead to both false positive results and failures to detect genuine associations. Even when most of the approaches to deal with population stratification require genome-wide data, the use of a well-selected panel of ancestry informative markers (AIMs) may appropriately correct for population stratification. Few panels of AIMs have been developed for Latino populations and most contain a high number of markers (> 100 AIMs). For some association studies such as candidate gene approaches, it may be unfeasible to genotype a numerous set of markers to avoid false positive results. In such cases, methods that use fewer AIMs may be appropriate. RESULTS: We validated an accurate and cost-effective panel of AIMs, for use in population stratification correction of association studies and global ancestry estimation in Mexicans, as well as in populations having large proportions of both European and Native American ancestries. Based on genome-wide data from 1953 Mexican individuals, we performed a PCA and SNP weights were calculated to select subsets of unlinked AIMs within percentiles 0.10 and 0.90, ensuring that all chromosomes were represented. Correlations between PC1 calculated using genome-wide data versus each subset of AIMs (16, 32, 48 and 64) were r2 = 0.923, 0.959, 0.972 and 0.978, respectively. When evaluating PCs performance as population stratification adjustment covariates, no correlation was found between P values obtained from uncorrected and genome-wide corrected association analyses (r2 = 0.141), highlighting that population stratification correction is compulsory for association analyses in admixed populations. In contrast, high correlations were found when adjusting for both PC1 and PC2 for either subset of AIMs (r2 > 0.900). After multiple validations, including an independent sample, we selected a minimal panel of 32 AIMs, which are highly informative of the major ancestral components of Mexican mestizos, namely European and Native American ancestries. Finally, the correlation between the global ancestry proportions calculated using genome-wide data and our panel of 32 AIMs was r2 = 0.972. CONCLUSIONS: Our panel of 32 AIMs accurately estimated global ancestry and corrected for population stratification in association studies in Mexican individuals.

Microsatellite loci cross-species transferability in Aedes fluviatilis (Diptera:Culicidae): a cost-effective approach for population genetics studies.

BACKGROUND: Aedes fluviatilis is a neotropical mosquito species thought to be a potential vector of Yellow Fever viruses and can be infected with Plasmodium gallinaceum in laboratory. A better understanding of its genetic structure is very important to understand its epidemiologic potential and how it is responding to urbanization. The objective of this study was to survey the transferability of microsatellites loci developed for other Aedes to Ae. fluviatilis. FINDINGS: We tested in Ae. fluviatilis 40 pairs of primers known to flank microsatellite regions in Aedes aegypti, Aedes albopictus and Aedes caspius, and found eight loci that amplified consistently. The number of alleles per locus ranged from 2 to 15, and the expected heterozygosity ranged from 0.09 to 0.85. CONCLUSIONS: We found that several microsatellite primers successfully transferred to Ae. fluviatilis. This finding opens avenues for cost-effective optimization of high-resolution population genetic tools.

Cost-effective enrichment hybridization capture of chloroplast genomes at deep multiplexing levels for population genetics and phylogeography studies.

Biodiversity, phylogeography and population genetic studies will be revolutionized by access to large data sets thanks to next-generation sequencing methods. In this study, we develop an easy and cost-effective protocol for in-solution enrichment hybridization capture of complete chloroplast genomes applicable at deep-multiplexed levels. The protocol uses cheap in-house species-specific probes developed via long-range PCR of the entire chloroplast. Barcoded libraries are constructed, and in-solution enrichment of the chloroplasts is carried out using the probes. This protocol was tested and validated on six economically important West African crop species, namely African rice, pearl millet, three African yam species and fonio. For pearl millet, we also demonstrate the effectiveness of this protocol to retrieve 95% of the sequence of the whole chloroplast on 95 multiplexed individuals in a single MiSeq run at a success rate of 95%. This new protocol allows whole chloroplast genomes to be retrieved at a modest cost and will allow unprecedented resolution for closely related species in phylogeography studies using plastomes.

[A surprising commercial success]. / Chroniques génomiques - Un triomphe commercial surprenant.

Direct-to-consumer (DTC) genetic tests have become quite popular in the USA. This article explores the uses to which they are put and the motivations of the customers.

Design of association studies with pooled or un-pooled next-generation sequencing data.

Most common hereditary diseases in humans are complex and multifactorial. Large-scale genome-wide association studies based on SNP genotyping have only identified a small fraction of the heritable variation of these diseases. One explanation may be that many rare variants (a minor allele frequency, MAF <5%), which are not included in the common genotyping platforms, may contribute substantially to the genetic variation of these diseases. Next-generation sequencing, which would allow the analysis of rare variants, is now becoming so cheap that it provides a viable alternative to SNP genotyping. In this paper, we present cost-effective protocols for using next-generation sequencing in association mapping studies based on pooled and un-pooled samples, and identify optimal designs with respect to total number of individuals, number of individuals per pool, and the sequencing coverage. We perform a small empirical study to evaluate the pooling variance in a realistic setting where pooling is combined with exon-capturing. To test for associations, we develop a likelihood ratio statistic that accounts for the high error rate of next-generation sequencing data. We also perform extensive simulations to determine the power and accuracy of this method. Overall, our findings suggest that with a fixed cost, sequencing many individuals at a more shallow depth with larger pool size achieves higher power than sequencing a small number of individuals in higher depth with smaller pool size, even in the presence of high error rates. Our results provide guidelines for researchers who are developing association mapping studies based on next-generation sequencing.

"Forward genetics" as a method to maximize power and cost-efficiency in studies of human complex traits.

There is increasing interest in methods to disentangle the relationship between genotype and (endo)phenotypes in human complex traits. We present a population-based method of increasing the power and cost-efficiency of studies by selecting random individuals with a particular genotype and then assessing the accompanying quantitative phenotypes. Using statistical derivations, power- and cost graphs we show that such a "forward genetics" approach can lead to a marked reduction in sample size and costs. This approach is particularly apt for implementing in epidemiological studies for which DNA is already available but the phenotyping costs are high.

Association Analysis under Population Stratification: A Two-Stage Procedure Utilizing Population- and Family-Based Analyses.

OBJECTIVE: The association analysis based on a population-based case-control study is convenient and powerful, but may be biased under population stratification (PS), namely the study population consists of strata heterogeneous in disease rates and allele frequencies. On the other hand, a family-based (e.g. case-parents) study is robust against the PS bias, but may be less convenient to implement. We propose an association analysis that preserves the full robustness property of the family-based analysis while allowing for borrowing information from a population-based analysis. METHODS: A two-stage procedure is proposed. In the first stage, one selects a population-based case-control sample and performs a traditional case-control association analysis. In the second stage, one randomly selects a subset of the first-stage cases and recruits their family controls (e.g. parents), and performs a family-based association analysis. An overall two-stage analysis is then performed to utilize information from the two stages. RESULTS: The proposed two-stage analysis achieves higher power than the second-stage family-based analysis by utilizing information in the first-stage population study, while maintaining the full robustness of the family study and hence is still valid under PS. The proposal can also accommodate parental missingness when the case-parents study is used as the second-stage family study. CONCLUSION: The two-stage analysis facilitates efficient and robust association analysis under PS. Its computation- and cost-effectiveness render it very promising in genome-wide association studies.

Incorporation of genetic model parameters for cost-effective designs of genetic association studies using DNA pooling.

BACKGROUND: Studies of association methods using DNA pooling of single nucleotide polymorphisms (SNPs) have focused primarily on the effects of "machine-error", number of replicates, and the size of the pool. We use the non-centrality parameter (NCP) for the analysis of variance test to compute the approximate power for genetic association tests with DNA pooling data on cases and controls. We incorporate genetic model parameters into the computation of the NCP. Parameters involved in the power calculation are disease allele frequency, frequency of the marker SNP allele in coupling with the disease locus, disease prevalence, genotype relative risk, sample size, genetic model, number of pools, number of replicates of each pool, and the proportion of variance of the pooled frequency estimate due to machine variability. We compute power for different settings of number of replicates and total number of genotypings when the genetic model parameters are fixed. Several significance levels are considered, including stringent significance levels (due to the increasing popularity of 100 K and 500 K SNP "chip" data). We use a factorial design with two to four settings of each parameter and multiple regression analysis to assess which parameters most significantly affect power. RESULTS: The power can increase substantially as the genotyping number increases. For a fixed number of genotypings, the power is a function of the number of replicates of each pool such that there is a setting with maximum power. The four most significant parameters affecting power for association are: (1) genotype relative risk, (2) genetic model, (3) sample size, and (4) the interaction term between disease and SNP marker allele probabilities. CONCLUSION: For a fixed number of genotypings, there is an optimal number of replicates of each pool that increases as the number of genotypings increases. Power is not substantially reduced when the number of replicates is close to but not equal to the optimal setting.

Are molecular haplotypes worth the time and expense? A cost-effective method for applying molecular haplotypes.

Because current molecular haplotyping methods are expensive and not amenable to automation, many researchers rely on statistical methods to infer haplotype pairs from multilocus genotypes, and subsequently treat these inferred haplotype pairs as observations. These procedures are prone to haplotype misclassification. We examine the effect of these misclassification errors on the false-positive rate and power for two association tests. These tests include the standard likelihood ratio test (LRTstd) and a likelihood ratio test that employs a double-sampling approach to allow for the misclassification inherent in the haplotype inference procedure (LRTae). We aim to determine the cost-benefit relationship of increasing the proportion of individuals with molecular haplotype measurements in addition to genotypes to raise the power gain of the LRTae over the LRTstd. This analysis should provide a guideline for determining the minimum number of molecular haplotypes required for desired power. Our simulations under the null hypothesis of equal haplotype frequencies in cases and controls indicate that (1) for each statistic, permutation methods maintain the correct type I error; (2) specific multilocus genotypes that are misclassified as the incorrect haplotype pair are consistently misclassified throughout each entire dataset; and (3) our simulations under the alternative hypothesis showed a significant power gain for the LRTae over the LRTstd for a subset of the parameter settings. Permutation methods should be used exclusively to determine significance for each statistic. For fixed cost, the power gain of the LRTae over the LRTstd varied depending on the relative costs of genotyping, molecular haplotyping, and phenotyping. The LRTae showed the greatest benefit over the LRTstd when the cost of phenotyping was very high relative to the cost of genotyping. This situation is likely to occur in a replication study as opposed to a whole-genome association study.

Heated oligonucleotide ligation assay (HOLA): an affordable single nucleotide polymorphism assay.

Most single nucleotide polymorphism (SNP) detection requires expensive equipment and reagents. The oligonucleotide ligation assay (OLA) is an inexpensive SNP assay that detects ligation between a biotinylated "allele-specific detector" and a 3' fluorescein-labeled "reporter" oligonucleotide. No ligation occurs unless the 3' detector nucleotide is complementary to the SNP nucleotide. The original OLA used chemical denaturation and neutralization. Heated OLA (HOLA) instead uses a thermal stable ligase and cycles of denaturing and hybridization for ligation and SNP detection. The cost per genotype is approximately US$1.25 with two-allele SNPs or approximately US$1.75 with three-allele SNPs. We illustrate the development of HOLA for SNP detection in the Early Trypsin and Abundant Trypsin loci in the mosquito Aedes aegypti (L.) and at the a-glycerophosphate dehydrogenase locus in the mosquito Anopheles gambiae s.s.

Genotyping African haplotypes in ATM using a co-spotted single-base extension assay.

Human genetic analysis, including population genetic studies, increasingly calls for cost-effective, high-throughput methods for the rapid screening of single nucleotide polymorphisms (SNPs) across many individuals. The modified single-base extension assay described here (arrayed SBE) is a highly accurate and robust method for SNP genotyping that can deliver genotypes at 3.5 cents each, following PCR. Specifically, amino-modified probe/target pairs were prehybridized, then co-spotted in a microarray format prior to enzymatic addition of allele-specific nucleotides. Probe/target identity was determined solely by its physical location on the array rather than by hybridization to a complementary target, resulting in a call rate of 99-100%. These innovations result in an inexpensive, accurate assay with exceptional signal-to-noise ratios, depending on the glass surface employed. Comparison of glass slides from three different manufacturers indicated that aldehyde-based Zyomyx slides provided superior performance for this assay. Arrayed SBE was applied to study the geographic distribution of three African-specific haplotypes in the human ATM gene. Four selectively neutral markers, which define the haplotypes H5, H6, and H7, were screened in a total of 415 individuals. Region-specific haplotype frequencies were consistent with patterns of human migration across and outside of Africa, suggesting a possible haplotype origin in East Africa. Arrayed SBE was a robust tool for this analysis that could be applied to any situation requiring the genotyping of a few SNPs in many individuals.

On the use of DNA pooling to estimate haplotype frequencies.

Genome-wide association studies may be necessary to identify genes underlying certain complex diseases. Because such studies can be extremely expensive, DNA pooling has been introduced, as it may greatly reduce the genotyping burden. Parallel to DNA pooling developments, the importance of haplotypes in genetic studies has been amply demonstrated in the literature. However, DNA pooling of a large number of samples may lose haplotype information among tightly linked genetic markers. Here, we examine the cost-effectiveness of DNA pooling in the estimation of haplotype frequencies from population data. When the maximum likelihood estimates of haplotype frequencies are obtained from pooled samples, we compare the overall cost of the study, including both DNA collection and marker genotyping, between the individual genotyping strategy and the DNA pooling strategy. We find that the DNA pooling of two individuals can be more cost-effective than individual genotypings, especially when a large number of haplotype systems are studied.