Identification and analysis of genomic regions with large between-population differentiation in humans

The rs7208505 Polymorphism and Differential Expression of the SKA2 Gene in the Prefrontal Cortex of Suicide Victims from the Mexican Population

OBJECTIVE

The main aim of the current study was to investigate whether SKA2 gene expression in the postmortem brain of rs7208505 genotype are altered in suicide victims from a Mexican population.

METHODS

In this study, we report a genetic analysis of expression levels of the SKA2 gene in the prefrontal cortex of the postmortem brain of suicidal subjects (n = 22) compared to subjects who died of causes other than suicide (n = 22) in a Mexican population using RT-qPCR assays. Additionally, we genotyped the rs7208505 polymorphism in suicide victims (n = 98) and controls (n = 88) and we evaluate the association of genotypes for the SNP rs7208505 with expression level of SKA2.

RESULTS

The results showed that the expression of the SKA2 gene was significantly higher in suicide victims compared to control subjects (p = 0.044). Interestingly, we observed a greater proportion of allele A of the rs7208505 in suicide victims than controls. Even though there was no association between the SNP with suicide in the study population we found a significative association of the expression level from SKA2 with the allele A of the rs7208505 and suicide.

CONCLUSION

The evidence suggests that the expression of SKA2 in the prefrontal cortex may be a critical factor in the etiology of suicidal behavior.

Genetic Diversity of Creole Sheep Managed by Indigenous Communities of the Central Region of Veracruz, Mexico

Simple Summary

The genetic diversity in three populations of creole sheep managed by indigenous communities of the central region of Veracruz, Mexico, is reported from blood samples of 90 sheep, taken from the herds of indigenous families in the municipalities of Tehuipango, Astacinga, and Tlaquilpa, Veracruz, Mexico. The genomic DNA of the sheep was evaluated using four microsatellites amplified by PCR and visualized on polyacrylamide gels. The four microsatellites were polymorphic, observed heterozygosity was lower than the expected level, and the indices of endogamy indicated a slight diminution of homozygotes and the variation was hosted at the individual level. The evaluated sheep present a genetic diversity that is conserved across endogamic crosses, for which reason the design of a plan of protection and use of these sheep populations would permit their sustainable management.

Abstract

In the indigenous communities of central Veracruz, herds of creole sheep have been established and managed through traditional practices of crossing, but their genetic characteristics have never been examined in order to evaluate their state of endogamy, and to help the management programs to protect this genetic resource. The objective of the present study was to characterize the genetic diversity of three populations of creole sheep managed by indigenous communities in the central region of Veracruz, Mexico. Indigenous family producers of creole sheep were located and blood samples taken from 90 individual sheep from the municipalities of Tehuipango, Astacinga and Tlaquilpa, Veracruz. In the laboratory, the genomic DNA was extracted and genetic diversity characterized using four microsatellites (ILSTS11, ILSTS5, SRCRSP9 and OarFCB128) amplified by PCR and visualized on polyacrylamide gels. The four microsatellites were highly informative (PIC = 85%) and presented values of 0.6 to 0.81 of heterozygosity, with an average number of 16 alleles. According to the Hardy–Weinberg equilibrium model, three of the loci were not significant (p < 0.05), presumably this means that they do not deviate significantly from H–W predictions and there was slight genetic differentiation (F_ST = 0.025), along with a slight decrease in homozygotes (F_IS = −0.021). According to the analysis of variance, 99% of the total variation was hosted at the individual level. It is concluded that the three creole sheep populations still present genetic diversity at the four loci and non-random pairings have occurred.

Cytokines mapping for tissue-specific expression, eQTLs and GWAS traits

Dysregulation in cytokine production has been linked to the pathogenesis of various immune-mediated traits, in which genetic variability contributes to the etiopathogenesis. GWA studies have identified many genetic variants in or near cytokine genes, nonetheless, the translation of these findings into knowledge of functional determinants of complex traits remains a fundamental challenge. In this study we aimed at collection, analysis and interpretation of data on cytokines focused on their tissue-specific expression, eQTLs and GWAS traits. Using GO annotations, we generated a list of 314 cytokines and analyzed them with the GTEx resource. Cytokines were highly tissue-specific, 82.3% of cytokines had Tau expression metrics ≥ 0.8. In total, 3077 associations for 1760 unique SNPs in or near 244 cytokines were mapped in the NHGRI-EBI GWAS Catalog. According to the Experimental Factor Ontology resource, the largest numbers of disease associations were related to 'Inflammatory disease', 'Immune system disease' and 'Asthma'. The GTEx-based analysis revealed that among GWAS SNPs, 1142 SNPs had eQTL effects and influenced expression levels of 999 eGenes, among them 178 cytokines. Several types of enrichment analysis showed that it was cytokines expression variability that fundamentally contributed to the molecular origins of considered immune-mediated conditions.

A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

The aim of the present study was to identify genomic region(s) associated with the length of the calving interval in primiparous (n = 6866) and multiparous (n = 5071) Holstein cows. The single nucleotide polymorphism (SNP) solutions were estimated using a weighted single-step genomic best linear unbiased prediction (WssGBLUP) approach and imputed high-density panel (777 k) genotypes. The effects of markers and the genomic estimated breeding values (GEBV) of the animals were obtained by five iterations of WssGBLUP. The results showed that the accuracies of GEBVs with WssGBLUP improved by +5.4 to +5.7, (primiparous cows) and +9.4 to +9.7 (multiparous cows) percent points over accuracies from the pedigree-based BLUP. The most accurate genomic evaluation was provided at the second iteration of WssGBLUP, which was used to identify associated genomic regions using a windows-based GWAS procedure. The proportion of additive genetic variance explained by windows of 50 consecutive SNPs (with an average of 165 Kb) was calculated and the region(s) that accounted for equal to or more than 0.20% of the total additive genetic variance were used to search for candidate genes. Three windows of 50 consecutive SNPs (BTA3, BTA6, and BTA7) were identified to be associated with the length of the calving interval in primi- and multiparous cows, while the window with the highest percentage of explained genetic variance was located on BTA3 position 49.42 to 49.52 Mb. There were five genes including ARHGAP29, SEC24D, METTL14, SLC36A2, and SLC36A3 inside the windows associated with the length of the calving interval. The biological process terms including alanine transport, L-alanine transport, proline transport, and glycine transport were identified as the most important terms enriched by the genes inside the identified windows.

A local score approach improves GWAS resolution and detects minor QTL: application to Medicago truncatula quantitative disease resistance to multiple Aphanomyces euteiches isolates

Quantitative trait loci (QTL) with small effects, which are pervasive in quantitative phenotypic variation, are difficult to detect in genome-wide association studies (GWAS). To improve their detection, we propose to use a local score approach that accounts for the surrounding signal due to linkage disequilibrium, by accumulating association signals from contiguous single markers. Simulations revealed that, in a GWAS context with high marker density, the local score approach outperforms single SNP p-value-based tests for detecting minor QTL (heritability of 5-10%) and is competitive with regard to alternative methods, which also aggregate p-values. Using more than five million SNPs, this approach was applied to identify loci involved in Quantitative Disease Resistance (QDR) to different isolates of the plant root rot pathogen Aphanomyces euteiches, from a GWAS performed on a collection of 174 accessions of the model legume Medicago truncatula. We refined the position of a previously reported major locus, underlying MYB/NB-ARC/tyrosine kinase candidate genes conferring resistance to two closely related A. euteiches isolates belonging to pea pathotype I. We also discovered a diversity of minor resistance QTL, not detected using p-value-based tests, some of which being putatively shared in response to pea (pathotype I and III) and/or alfalfa (race 1 and 2) isolates. Candidate genes underlying these QTL suggest pathogen effector recognition and plant proteasome as key functions associated with M. truncatula resistance to A. euteiches. GWAS on any organism can benefit from the local score approach to uncover many weak-effect QTL.

Transferability of genome-wide associated loci for asthma in African Americans

OBJECTIVE

Transferability of significantly associated loci or GWAS "hits" adds credibility to genotype-disease associations and provides evidence for generalizability across different ancestral populations. We sought evidence of association of known asthma-associated single nucleotide polymorphisms (SNPs) in an African American population.

METHODS

Subjects comprised 661 participants (261 asthma cases and 400 controls) from the Howard University Family Study. Forty-eight SNPs previously reported to be associated with asthma by GWAS were selected for testing. We adopted a combined strategy by first adopting an "exact" approach where we looked-up only the reported index SNP. For those index SNPs missing form our dataset, we used a "local" approach that examined all the regional SNPs in LD with the index SNP.

RESULTS

Out of the 48 SNPs, our cohort had genotype data available for 27, which were examined for exact replication. Of these, two SNPs were found positively associated with asthma. These included: rs10508372 (OR = 1.567 [95%CI, 1.133-2.167], P = 0.0066) and rs2378383 (OR = 2.147 [95%CI, 1.149-4.013], P = 0.0166), located on chromosomal bands 10p14 and 9q21.31, respectively. Local replication of the remaining 21 loci showed association at two chromosomal loci (9p24.1-rs2381413 and 6p21.32-rs3132947; Bonferroni-corrected P values: 0.0033 and 0.0197, respectively). Of note, multiple SNPs in LD with rs2381413 located upstream of IL33 were significantly associated with asthma.

CONCLUSIONS

This study has successfully transferred four reported asthma-associated loci in an independent African American population. Identification of several asthma-associated SNPs in the upstream of the IL33, a gene previously implicated in allergic inflammation of asthmatic airway, supports the generalizability of this finding.

Diversity of Mycobacterium tuberculosis across Evolutionary Scales

Tuberculosis (TB) is a global public health emergency. Increasingly drug resistant strains of Mycobacterium tuberculosis (M.tb) continue to emerge and spread, highlighting adaptability of this pathogen. Most studies of M.tb evolution have relied on ‘between-host’ samples, in which each person with TB is represented by a single M.tb isolate. However, individuals with TB commonly harbor populations of M.tb numbering in the billions. Here, we use analyses of M.tb genomic data from within and between hosts to gain insight into influences shaping genetic diversity of this pathogen. We find that the amount of M.tb genetic diversity harbored by individuals with TB can vary dramatically, likely as a function of disease severity. Surprisingly, we did not find an appreciable impact of TB treatment on M.tb diversity. In examining genomic data from M.tb samples within and between hosts with TB, we find that genes involved in the regulation, synthesis, and transportation of immunomodulatory cell envelope lipids appear repeatedly in the extremes of various statistical measures of diversity. Many of these genes have been identified as possible targets of selection in other studies employing different methods and data sets. Taken together, these observations suggest that M.tb cell envelope lipids are targets of selection within hosts. Many of these lipids are specific to pathogenic mycobacteria and, in some cases, human-pathogenic mycobacteria. We speculate that rapid adaptation of cell envelope lipids is facilitated by functional redundancy, flexibility in their metabolism, and their roles mediating interactions with the host.

Tuberculosis (TB) is a grave threat to global public health and is the second leading cause of death due to infectious disease. The causative agent, Mycobacterium tuberculosis (M.tb), has emerged in increasingly drug resistant forms that hamper our efforts to control TB. We need a better understanding of M.tb adaptation to guide development of more effective TB treatment and control strategies. The goal of this study was to gain insight into M.tb evolution within individual patients with TB. We found that TB patients harbor a diverse population of M.tb. We further found evidence to suggest that the bacterial population evolves measurably in response to selection pressures imposed by the environment within hosts. Changes were particularly notable in M.tb genes involved in the regulation, synthesis, and transportation of lipids and glycolipids of the bacterial cell envelope. These findings have important implications for drug and vaccine development, and provide insight into TB host pathogen interactions.

Characterization of the biological processes shaping the genetic structure of the Italian population

Background

The genetic structure of human populations is the outcome of the combined action of different processes such as demographic dynamics and natural selection. Several efforts toward the characterization of population genetic architectures and the identification of adaptation signatures were recently made. In this study, we provide a genome-wide depiction of the Italian population structure and the analysis of the major determinants of the current existing genetic variation.

Results

We defined and characterized 210 genomic loci associated with the first Principal Component calculated on the Italian genotypic data and correlated to the North–south genetic gradient. Using a gene-enrichment approach we identified the immune function as primarily involved in the Italian population differentiation and we described a locus on chromosome 13 showing combined evidence of North–south diversification in allele frequencies and signs of recent positive selection. In this region our bioinformatics analysis pinpointed an uncharacterized long intergenic non-coding (lincRNA), whose expression appeared specific for immune-related tissues suggesting its relevance for the immune function.

Conclusions

Our study, combining population genetic analyses with biological insights provides a description of the Italian genetic structure that in future could contribute to the evaluation of complex diseases risk in the population context.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0293-x) contains supplementary material, which is available to authorized users.

Fifteen years of genomewide scans for selection: trends, lessons and unaddressed genetic sources of complication

Genomewide scans for natural selection (GWSS) have become increasingly common over the last 15 years due to increased availability of genome-scale genetic data. Here, we report a representative survey of GWSS from 1999 to present and find that (i) between 1999 and 2009, 35 of 49 (71%) GWSS focused on human, while from 2010 to present, only 38 of 83 (46%) of GWSS focused on human, indicating increased focus on nonmodel organisms; (ii) the large majority of GWSS incorporate interpopulation or interspecific comparisons using, for example F(ST), cross-population extended haplotype homozygosity or the ratio of nonsynonymous to synonymous substitutions; (iii) most GWSS focus on detection of directional selection rather than other modes such as balancing selection; and (iv) in human GWSS, there is a clear shift after 2004 from microsatellite markers to dense SNP data. A survey of GWSS meant to identify loci positively selected in response to severe hypoxic conditions support an approach to GWSS in which a list of a priori candidate genes based on potential selective pressures are used to filter the list of significant hits a posteriori. We also discuss four frequently ignored determinants of genomic heterogeneity that complicate GWSS: mutation, recombination, selection and the genetic architecture of adaptive traits. We recommend that GWSS methodology should better incorporate aspects of genomewide heterogeneity using empirical estimates of relevant parameters and/or realistic, whole-chromosome simulations to improve interpretation of GWSS results. Finally, we argue that knowledge of potential selective agents improves interpretation of GWSS results and that new methods focused on correlations between environmental variables and genetic variation can help automate this approach.

Defining window-boundaries for genomic analyses using smoothing spline techniques

Background

High-density genomic data is often analyzed by combining information over windows of adjacent markers. Interpretation of data grouped in windows versus at individual locations may increase statistical power, simplify computation, reduce sampling noise, and reduce the total number of tests performed. However, use of adjacent marker information can result in over- or under-smoothing, undesirable window boundary specifications, or highly correlated test statistics. We introduce a method for defining windows based on statistically guided breakpoints in the data, as a foundation for the analysis of multiple adjacent data points. This method involves first fitting a cubic smoothing spline to the data and then identifying the inflection points of the fitted spline, which serve as the boundaries of adjacent windows. This technique does not require prior knowledge of linkage disequilibrium, and therefore can be applied to data collected from individual or pooled sequencing experiments. Moreover, in contrast to existing methods, an arbitrary choice of window size is not necessary, since these are determined empirically and allowed to vary along the genome.

Results

Simulations applying this method were performed to identify selection signatures from pooled sequencing F_ST data, for which allele frequencies were estimated from a pool of individuals. The relative ratio of true to false positives was twice that generated by existing techniques. A comparison of the approach to a previous study that involved pooled sequencing F_ST data from maize suggested that outlying windows were more clearly separated from their neighbors than when using a standard sliding window approach.

Conclusions

We have developed a novel technique to identify window boundaries for subsequent analysis protocols. When applied to selection studies based on F_ST data, this method provides a high discovery rate and minimizes false positives. The method is implemented in the R package GenWin, which is publicly available from CRAN.

Evaluating intra- and inter-individual variation in the human placental transcriptome

BACKGROUND

Gene expression variation is a phenotypic trait of particular interest as it represents the initial link between genotype and other phenotypes. Analyzing how such variation apportions among and within groups allows for the evaluation of how genetic and environmental factors influence such traits. It also provides opportunities to identify genes and pathways that may have been influenced by non-neutral processes. Here we use a population genetics framework and next generation sequencing to evaluate how gene expression variation is apportioned among four human groups in a natural biological tissue, the placenta.

RESULTS

We estimate that on average, 33.2%, 58.9%, and 7.8% of the placental transcriptome is explained by variation within individuals, among individuals, and among human groups, respectively. Additionally, when technical and biological traits are included in models of gene expression they each account for roughly 2% of total gene expression variation. Notably, the variation that is significantly different among groups is enriched in biological pathways associated with immune response, cell signaling, and metabolism. Many biological traits demonstrate correlated changes in expression in numerous pathways of potential interest to clinicians and evolutionary biologists. Finally, we estimate that the majority of the human placental transcriptome exhibits expression profiles consistent with neutrality; the remainder are consistent with stabilizing selection, directional selection, or diversifying selection.

CONCLUSIONS

We apportion placental gene expression variation into individual, population, and biological trait factors and identify how each influence the transcriptome. Additionally, we advance methods to associate expression profiles with different forms of selection.

CardioGxE, a catalog of gene-environment interactions for cardiometabolic traits

Background

Genetic understanding of complex traits has developed immensely over the past decade but remains hampered by incomplete descriptions of contribution to phenotypic variance. Gene-environment (GxE) interactions are one of these contributors and in the guise of diet and physical activity are important modulators of cardiometabolic phenotypes and ensuing diseases.

Results

We mined the scientific literature to collect GxE interactions from 386 publications for blood lipids, glycemic traits, obesity anthropometrics, vascular measures, inflammation and metabolic syndrome, and introduce CardioGxE, a gene-environment interaction resource. We then analyzed the genes and SNPs supporting cardiometabolic GxEs in order to demonstrate utility of GxE SNPs and to discern characteristics of these important genetic variants. We were able to draw many observations from our extensive analysis of GxEs. 1) The CardioGxE SNPs showed little overlap with variants identified by main effect GWAS, indicating the importance of environmental interactions with genetic factors on cardiometabolic traits. 2) These GxE SNPs were enriched in adaptation to climatic and geographical features, with implications on energy homeostasis and response to physical activity. 3) Comparison to gene networks responding to plasma cholesterol-lowering or regression of atherosclerotic plaques showed that GxE genes have a greater role in those responses, particularly through high-energy diets and fat intake, than do GWAS-identified genes for the same traits. Other aspects of the CardioGxE dataset were explored.

Conclusions

Overall, we demonstrate that SNPs supporting cardiometabolic GxE interactions often exhibit transcriptional effects or are under positive selection. Still, not all such SNPs can be assigned potential functional or regulatory roles often because data are lacking in specific cell types or from treatments that approximate the environmental factor of the GxE. With research on metabolic related complex disease risk embarking on genome-wide GxE interaction tests, CardioGxE will be a useful resource.

A whole genome analyses of genetic variants in two Kelantan Malay individuals

Background

The sequencing of two members of the Royal Kelantan Malay family genomes will provide insights on the Kelantan Malay whole genome sequences. The two Kelantan Malay genomes were analyzed for the SNP markers associated with thalassemia and Helicobacter pylori infection. Helicobacter pylori infection was reported to be low prevalence in the north-east as compared to the west coast of the Peninsular Malaysia and beta-thalassemia was known to be one of the most common inherited and genetic disorder in Malaysia.

Result

By combining SNP information from literatures, GWAS study and NCBI ClinVar, 18 unique SNPs were selected for further analysis. From these 18 SNPs, 10 SNPs came from previous study of Helicobacter pylori infection among Malay patients, 6 SNPs were from NCBI ClinVar and 2 SNPs from GWAS studies. The analysis reveals that both Royal Kelantan Malay genomes shared all the 10 SNPs identified by Maran (Single Nucleotide Polymorphims (SNPs) genotypic profiling of Malay patients with and without Helicobacter pylori infection in Kelantan, 2011) and one SNP from GWAS study. In addition, the analysis also reveals that both Royal Kelantan Malay genomes shared 3 SNP markers; HBG1 (rs1061234), HBB (rs1609812) and BCL11A (rs766432) where all three markers were associated with beta-thalassemia.

Conclusions

Our findings suggest that the Royal Kelantan Malays carry the SNPs which are associated with protection to Helicobacter pylori infection. In addition they also carry SNPs which are associated with beta-thalassemia. These findings are in line with the findings by other researchers who conducted studies on thalassemia and Helicobacter pylori infection in the non-royal Malay population.

Population-specific common SNPs reflect demographic histories and highlight regions of genomic plasticity with functional relevance

BACKGROUND

Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data.

RESULTS

The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones.

CONCLUSIONS

Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.

Population genomic analyses based on 1 million SNPs in commercial egg layers

Identifying signatures of selection can provide valuable insight about the genes or genomic regions that are or have been under selective pressure, which can lead to a better understanding of genotype-phenotype relationships. A common strategy for selection signature detection is to compare samples from several populations and search for genomic regions with outstanding genetic differentiation. Wright's fixation index, F_ST, is a useful index for evaluation of genetic differentiation between populations. The aim of this study was to detect selective signatures between different chicken groups based on SNP-wise F_ST calculation. A total of 96 individuals of three commercial layer breeds and 14 non-commercial fancy breeds were genotyped with three different 600K SNP-chips. After filtering a total of 1 million SNPs were available for F_ST calculation. Averages of F_ST values were calculated for overlapping windows. Comparisons of these were then conducted between commercial egg layers and non-commercial fancy breeds, as well as between white egg layers and brown egg layers. Comparing non-commercial and commercial breeds resulted in the detection of 630 selective signatures, while 656 selective signatures were detected in the comparison between the commercial egg-layer breeds. Annotation of selection signature regions revealed various genes corresponding to productions traits, for which layer breeds were selected. Among them were NCOA1, SREBF2 and RALGAPA1 associated with reproductive traits, broodiness and egg production. Furthermore, several of the detected genes were associated with growth and carcass traits, including POMC, PRKAB2, SPP1, IGF2, CAPN1, TGFb2 and IGFBP2. Our approach demonstrates that including different populations with a specific breeding history can provide a unique opportunity for a better understanding of farm animal selection.

A genome-wide scan for evidence of selection in a maize population under long-term artificial selection for ear number

A genome-wide scan to detect evidence of selection was conducted in the Golden Glow maize long-term selection population. The population had been subjected to selection for increased number of ears per plant for 30 generations, with an empirically estimated effective population size ranging from 384 to 667 individuals and an increase of more than threefold in the number of ears per plant. Allele frequencies at >1.2 million single-nucleotide polymorphism loci were estimated from pooled whole-genome resequencing data, and FST values across sliding windows were employed to assess divergence between the population preselection and the population postselection. Twenty-eight highly divergent regions were identified, with half of these regions providing gene-level resolution on potentially selected variants. Approximately 93% of the divergent regions do not demonstrate a significant decrease in heterozygosity, which suggests that they are not approaching fixation. Also, most regions display a pattern consistent with a soft-sweep model as opposed to a hard-sweep model, suggesting that selection mostly operated on standing genetic variation. For at least 25% of the regions, results suggest that selection operated on variants located outside of currently annotated coding regions. These results provide insights into the underlying genetic effects of long-term artificial selection and identification of putative genetic elements underlying number of ears per plant in maize.

Detecting signatures of selection through haplotype differentiation among hierarchically structured populations

The detection of molecular signatures of selection is one of the major concerns of modern population genetics. A widely used strategy in this context is to compare samples from several populations and to look for genomic regions with outstanding genetic differentiation between these populations. Genetic differentiation is generally based on allele frequency differences between populations, which are measured by FST or related statistics. Here we introduce a new statistic, denoted hapFLK, which focuses instead on the differences of haplotype frequencies between populations. In contrast to most existing statistics, hapFLK accounts for the hierarchical structure of the sampled populations. Using computer simulations, we show that each of these two features-the use of haplotype information and of the hierarchical structure of populations-significantly improves the detection power of selected loci and that combining them in the hapFLK statistic provides even greater power. We also show that hapFLK is robust with respect to bottlenecks and migration and improves over existing approaches in many situations. Finally, we apply hapFLK to a set of six sheep breeds from Northern Europe and identify seven regions under selection, which include already reported regions but also several new ones. We propose a method to help identifying the population(s) under selection in a detected region, which reveals that in many of these regions selection most likely occurred in more than one population. Furthermore, several of the detected regions correspond to incomplete sweeps, where the favorable haplotype is only at intermediate frequency in the population(s) under selection.

Transferability and fine-mapping of glucose and insulin quantitative trait loci across populations: CARe, the Candidate Gene Association Resource

AIMS/HYPOTHESIS

Hyperglycaemia disproportionately affects African-Americans (AfAs). We tested the transferability of 18 single-nucleotide polymorphisms (SNPs) associated with glycaemic traits identified in European ancestry (EuA) populations in 5,984 non-diabetic AfAs.

METHODS

We meta-analysed SNP associations with fasting glucose (FG) or insulin (FI) in AfAs from five cohorts in the Candidate Gene Association Resource. We: (1) calculated allele frequency differences, variations in linkage disequilibrium (LD), fixation indices (F(st)s) and integrated haplotype scores (iHSs); (2) tested EuA SNPs in AfAs; and (3) interrogated within ± 250 kb around each EuA SNP in AfAs.

RESULTS

Allele frequency differences ranged from 0.6% to 54%. F(st) exceeded 0.15 at 6/16 loci, indicating modest population differentiation. All iHSs were <2, suggesting no recent positive selection. For 18 SNPs, all directions of effect were the same and 95% CIs of association overlapped when comparing EuA with AfA. For 17 of 18 loci, at least one SNP was nominally associated with FG in AfAs. Four loci were significantly associated with FG (GCK, p = 5.8 × 10(-8); MTNR1B, p = 8.5 × 10(-9); and FADS1, p = 2.2 × 10(-4)) or FI (GCKR, p = 5.9 × 10(-4)). At GCK and MTNR1B the EuA and AfA SNPs represented the same signal, while at FADS1, and GCKR, the EuA and best AfA SNPs were weakly correlated (r(2) <0.2), suggesting allelic heterogeneity for association with FG at these loci.

CONCLUSIONS/INTERPRETATION

Few glycaemic SNPs showed strict evidence of transferability from EuA to AfAs. Four loci were significantly associated in both AfAs and those with EuA after accounting for varying LD across ancestral groups, with new signals emerging to aid fine-mapping.

Limited evidence for classic selective sweeps in African populations

While hundreds of loci have been identified as reflecting strong-positive selection in human populations, connections between candidate loci and specific selective pressures often remain obscure. This study investigates broader patterns of selection in African populations, which are underrepresented despite their potential to offer key insights into human adaptation. We scan for hard selective sweeps using several haplotype and allele-frequency statistics with a data set of nearly 500,000 genome-wide single-nucleotide polymorphisms in 12 highly diverged African populations that span a range of environments and subsistence strategies. We find that positive selection does not appear to be a strong determinant of allele-frequency differentiation among these African populations. Haplotype statistics do identify putatively selected regions that are shared across African populations. However, as assessed by extensive simulations, patterns of haplotype sharing between African populations follow neutral expectations and suggest that tails of the empirical distributions contain false-positive signals. After highlighting several genomic regions where positive selection can be inferred with higher confidence, we use a novel method to identify biological functions enriched among populations' empirical tail genomic windows, such as immune response in agricultural groups. In general, however, it seems that current methods for selection scans are poorly suited to populations that, like the African populations in this study, are affected by ascertainment bias and have low levels of linkage disequilibrium, possibly old selective sweeps, and potentially reduced phasing accuracy. Additionally, population history can confound the interpretation of selection statistics, suggesting that greater care is needed in attributing broad genetic patterns to human adaptation.

Worldwide variation in human drug-metabolism enzyme genes CYP2B6 and UGT2B7: implications for HIV/AIDS treatment

AIM

Hepatic enzymes, CYP2B6 and UGT2B7 play a major role in the metabolism of the widely used antiretroviral drugs efavirenz, nevirapine and zidovudine. In the present study, we provide a view of UGT2B7 haplotype structure, and quantify the genetic diversity and differentiation at both CYP2B6 and UGT2B7 genes on a worldwide scale.

MATERIALS & METHODS

We genotyped one intronic and three promoter SNPs, and together with three nonsynonymous SNPs, inferred UGT2B7 alleles in north American (n = 326), west African (n = 133) and Papua New Guinean (n = 142) populations. We also included genotype data for five CYP2B6 and six UGT2B7 SNPs from an additional 12 worldwide populations (n = 629) analyzed in the 1000 Genomes Project.

RESULTS

We observed significant differences in certain SNP and allele frequencies of CYP2B6 and UGT2B7 among worldwide populations. Diversity values were higher for UGT2B7 than for CYP2B6, although there was more diversity between populations for CYP2B6. For both genes, most of the genetic variation was observed among individuals within populations, with the Papua New Guinean population showing the highest pairwise differentiation values for CYP2B6, and the Asian and European populations showing higher pairwise differentiation values for UGT2B7.

CONCLUSION

These new genetic distinctions provide additional insights for investigating differences in antiretroviral pharmacokinetics and therapy outcomes among ethnically and geographically diverse populations.

Two new ArrayTrack libraries for personalized biomedical research

Background

Recent advances in high-throughput genotyping technology are paving the way for research in personalized medicine and nutrition. However, most of the genetic markers identified from association studies account for a small contribution to the total risk/benefit of the studied phenotypic trait. Testing whether the candidate genes identified by association studies are causal is critically important to the development of personalized medicine and nutrition. An efficient data mining strategy and a set of sophisticated tools are necessary to help better understand and utilize the findings from genetic association studies.

Description

SNP (single nucleotide polymorphism) and QTL (quantitative trait locus) libraries were constructed and incorporated into ArrayTrack, with user-friendly interfaces and powerful search features. Data from several public repositories were collected in the SNP and QTL libraries and connected to other domain libraries (genes, proteins, metabolites, and pathways) in ArrayTrack. Linking the data sets within ArrayTrack allows searching of SNP and QTL data as well as their relationships to other biological molecules. The SNP library includes approximately 15 million human SNPs and their annotations, while the QTL library contains publically available QTLs identified in mouse, rat, and human. The QTL library was developed for finding the overlap between the map position of a candidate or metabolic gene and QTLs from these species. Two use cases were included to demonstrate the utility of these tools. The SNP and QTL libraries are freely available to the public through ArrayTrack at http://www.fda.gov/ArrayTrack.

Conclusions

These libraries developed in ArrayTrack contain comprehensive information on SNPs and QTLs and are further cross-linked to other libraries. Connecting domain specific knowledge is a cornerstone of systems biology strategies and allows for a better understanding of the genetic and biological context of the findings from genetic association studies.

Adaptations to new environments in humans: the role of subtle allele frequency shifts

Humans show tremendous phenotypic diversity across geographically distributed populations, and much of this diversity undoubtedly results from genetic adaptations to different environmental pressures. The availability of genome-wide genetic variation data from densely sampled populations offers unprecedented opportunities for identifying the loci responsible for these adaptations and for elucidating the genetic architecture of human adaptive traits. Several approaches have been used to detect signals of selection in human populations, and these approaches differ in the assumptions they make about the underlying mode of selection. We contrast the results of approaches based on haplotype structure and differentiation of allele frequencies to those from a method for identifying single nucleotide polymorphisms strongly correlated with environmental variables. Although the first group of approaches tends to detect new beneficial alleles that were driven to high frequencies by selection, the environmental correlation approach has power to identify alleles that experienced small shifts in frequency owing to selection. We suggest that the first group of approaches tends to identify only variants with relatively strong phenotypic effects, whereas the environmental correlation methods can detect variants that make smaller contributions to an adaptive trait.

How culture shaped the human genome: bringing genetics and the human sciences together

Researchers from diverse backgrounds are converging on the view that human evolution has been shaped by gene-culture interactions. Theoretical biologists have used population genetic models to demonstrate that cultural processes can have a profound effect on human evolution, and anthropologists are investigating cultural practices that modify current selection. These findings are supported by recent analyses of human genetic variation, which reveal that hundreds of genes have been subject to recent positive selection, often in response to human activities. Here, we collate these data, highlighting the considerable potential for cross-disciplinary exchange to provide novel insights into how culture has shaped the human genome.

Genomic and geographic distribution of private SNPs and pathways in human populations

AIMS: Geography-based genetic differentials operating on entire biochemical pathways may reflect different adaptive evolutionary processes that separated populations may have undergone. They may also influence treatment outcome for a variety of drugs - an emerging and important area of study. This research article leverages the International HapMap Consortium data to identify pathway components that differ in genotype frequency for four populations: individuals of Northern European descent from the USA (CEU), individuals from West Africa (YRI), Japan (JPT) and China (CHB). MATERIALS #ENTITYSTARTX00026; METHODS: By identifying loci with fixed or large frequency differences (δ = 1) between paired population samples (CEU vs YRI, CEU vs CHB, CEU vs JPT, YRI vs CHB, YRI vs JPT and CHB vs JPT), and reconstructing the physiological functions of genes at these loci, we report a list of pathways affected by natural selection during human evolution. RESULTS: Of the 3.7 million HapMap SNPs, 463 loci (which mapped to 38 genes) were fixed (δ = 1) in at least one population pair. These private loci included four nonsynonymous coding SNPs: rs4536103 (NEUROG3), rs1385699 (EDA2R), rs11946338 (ARHGAP24) and rs4422842 (CACNA1B). A total of four additional genes demonstrated evidence of recent positive selection: three genes in European subjects (IER5L, NPNT and SESTD1) and a single gene in Asian subjects (EXOC6B). DISCUSSION: Gene ontology and pathway analyses suggest that cellular differentiation, apoptosis and activation of the NF-κB transcription factor vary between populations in genomic regions of fixed (private) SNPs identified in this study. Variability in these pathways may provide important clues into the mechanisms of human adaptation to different environments. An improved understanding of their variability may also help to explain race-specific differences in the treatment outcomes observed for a variety of modern drugs.

Enhanced Edar signalling has pleiotropic effects on craniofacial and cutaneous glands

The skin carries a number of appendages, including hair follicles and a range of glands, which develop under the influence of EDAR signalling. A gain of function allele of EDAR is found at high frequency in human populations of East Asia, with genetic evidence suggesting recent positive selection at this locus. The derived EDAR allele, estimated to have reached fixation more than 10,000 years ago, causes thickening of hair fibres, but the full spectrum of phenotypic changes induced by this allele is unknown. We have examined the changes in glandular structure caused by elevation of Edar signalling in a transgenic mouse model. We find that sebaceous and Meibomian glands are enlarged and that salivary and mammary glands are more elaborately branched with increased Edar activity, while the morphology of eccrine sweat and tracheal submucosal glands appears to be unaffected. Similar changes to gland sizes and structures may occur in human populations carrying the derived East Asian EDAR allele. As this allele attained high frequency in an environment that was notably cold and dry, increased glandular secretions could represent a trait that was positively selected to achieve increased lubrication and reduced evaporation from exposed facial structures and upper airways.

Population differentiation as an indicator of recent positive selection in humans: an empirical evaluation

We have evaluated the extent to which SNPs identified by genomewide surveys as showing unusually high levels of population differentiation in humans have experienced recent positive selection, starting from a set of 32 nonsynonymous SNPs in 27 genes highlighted by the HapMap1 project. These SNPs were genotyped again in the HapMap samples and in the Human Genome Diversity Project-Centre d'Etude du Polymorphisme Humain (HGDP-CEPH) panel of 52 populations representing worldwide diversity; extended haplotype homozygosity was investigated around all of them, and full resequence data were examined for 9 genes (5 from public sources and 4 from new data sets). For 7 of the genes, genotyping errors were responsible for an artifactual signal of high population differentiation and for 2, the population differentiation did not exceed our significance threshold. For the 18 genes with confirmed high population differentiation, 3 showed evidence of positive selection as measured by unusually extended haplotypes within a population, and 7 more did in between-population analyses. The 9 genes with resequence data included 7 with high population differentiation, and 5 showed evidence of positive selection on the haplotype carrying the nonsynonymous SNP from skewed allele frequency spectra; in addition, 2 showed evidence of positive selection on unrelated haplotypes. Thus, in humans, high population differentiation is (apart from technical artifacts) an effective way of enriching for recently selected genes, but is not an infallible pointer to recent positive selection supported by other lines of evidence.

Recent positive selection of a human androgen receptor/ectodysplasin A2 receptor haplotype and its relationship to male pattern baldness

Genetic variants in the human androgen receptor gene (AR) are associated with male pattern baldness (androgenetic alopecia, AGA) in Europeans. Previous observations of long-range linkage disequilibrium at the AR locus are consistent with the hypothesis of recent positive selection. Here, we further investigate this signature and its relationship to the AGA risk haplotype. The haplotype homozygosity suggests that the AGA risk haplotype was driven to high frequency by positive selection in Europeans although a low meiotic recombination rate contributed to the high haplotype homozygosity. Further, we find high levels of population differentiation as measured by F(ST) and a series of fixed derived alleles along an extended region centromeric to AR in the Asian HapMap sample. The predominant AGA risk haplotype also carries the putatively functional variant 57K in the flanking ectodysplasin A2 receptor gene (EDA2R). It is therefore probable that the AGA risk haplotype rose to high frequency in combination with this EDA2R variant, possibly by hitchhiking on a positively selected 57K haplotype.

An assessment of the portability of ancestry informative markers between human populations

Background

Recent work has shown that population stratification can have confounding effects on genetic association studies and statistical methods have been developed to correct for these effects. Subsets of markers that are highly-differentiated between populations, ancestry-informative markers (AIMs), have been used to correct for population stratification. Often AIMs are discovered in one set of populations and then employed in a different set of populations. The underlying assumption in these cases is that the population under study has the same substructure as the population in which the AIMs were discovered. The present study assesses this assumption and evaluates the portability between worldwide populations of 10 SNPs found to be highly-differentiated within Britain (BritAIMs).

Methods

We genotyped 10 BritAIMs in ~1000 individuals from 53 populations worldwide. We assessed the degree to which these 10 BritAIMs capture population stratification in other groups of populations by use of the Fst statistic. We used Fst values from 2750 random markers typed in the same set of individuals as an empirical distribution to which the Fst values of the 10 BritAIMs were compared.

Results

Allele frequency differences between continental groups for the BritAIMs are not unusually high. This is also the case for comparisons within continental groups distantly related to Britain. However, two BritAIMs show high Fst between European populations and two BritAIMs show high Fst between populations from the Middle East. Overall the median Fst across all BritAIMs is not unusually high compared to the empirical distribution.

Conclusion

We find that BritAIMs are generally not useful to distinguish between continental groups or within continental groups distantly related to Britain. Moreover, our analyses suggest that the portability of AIMs across geographical scales (e.g. between Europe and Britain) can be limited and should therefore be taken into consideration in the design and interpretation of genetic association studies.

A strategy for analyzing gene-nutrient interactions in type 2 diabetes

Type 2 diabetes mellitus (T2DM), like all chronic diseases, results from interactions between multiple genes and multiple environmental factors. Nevertheless, many research studies focus on either nutrition or genetic factors independently of each other. The challenges of analyzing gene-nutrient interactions in T2DM are the (i) genetic heterogeneity in humans, (ii) complexity of environmental factors, particularly dietary chemicals, and (iii) diverse physiologies that produce the same apparent disease. Many of these variables are not accounted for in the design or study of T2DM or, indeed, most chronic diseases, although exceptions are noteworthy. Establishing experimental paradigms to analyze the complexity of these interactions and physiologies is challenging, but possible. This article provides a strategy to extend nutrigenomic experimental strategies to include early environmental influences that may promote adult-onset disease.

A genome scan for positive selection in thoroughbred horses

Thoroughbred horses have been selected for exceptional racing performance resulting in system-wide structural and functional adaptations contributing to elite athletic phenotypes. Because selection has been recent and intense in a closed population that stems from a small number of founder animals Thoroughbreds represent a unique population within which to identify genomic contributions to exercise-related traits. Employing a population genetics-based hitchhiking mapping approach we performed a genome scan using 394 autosomal and X chromosome microsatellite loci and identified positively selected loci in the extreme tail-ends of the empirical distributions for (1) deviations from expected heterozygosity (Ewens-Watterson test) in Thoroughbred (n = 112) and (2) global differentiation among four geographically diverse horse populations (F(ST)). We found positively selected genomic regions in Thoroughbred enriched for phosphoinositide-mediated signalling (3.2-fold enrichment; P<0.01), insulin receptor signalling (5.0-fold enrichment; P<0.01) and lipid transport (2.2-fold enrichment; P<0.05) genes. We found a significant overrepresentation of sarcoglycan complex (11.1-fold enrichment; P<0.05) and focal adhesion pathway (1.9-fold enrichment; P<0.01) genes highlighting the role for muscle strength and integrity in the Thoroughbred athletic phenotype. We report for the first time candidate athletic-performance genes within regions targeted by selection in Thoroughbred horses that are principally responsible for fatty acid oxidation, increased insulin sensitivity and muscle strength: ACSS1 (acyl-CoA synthetase short-chain family member 1), ACTA1 (actin, alpha 1, skeletal muscle), ACTN2 (actinin, alpha 2), ADHFE1 (alcohol dehydrogenase, iron containing, 1), MTFR1 (mitochondrial fission regulator 1), PDK4 (pyruvate dehydrogenase kinase, isozyme 4) and TNC (tenascin C). Understanding the genetic basis for exercise adaptation will be crucial for the identification of genes within the complex molecular networks underlying obesity and its consequential pathologies, such as type 2 diabetes. Therefore, we propose Thoroughbred as a novel in vivo large animal model for understanding molecular protection against metabolic disease.

Medaka: a promising model animal for comparative population genomics

Background

Within-species genome diversity has been best studied in humans. The international HapMap project has revealed a tremendous amount of single-nucleotide polymorphisms (SNPs) among humans, many of which show signals of positive selection during human evolution. In most of the cases, however, functional differences between the alleles remain experimentally unverified due to the inherent difficulty of human genetic studies. It would therefore be highly useful to have a vertebrate model with the following characteristics: (1) high within-species genetic diversity, (2) a variety of gene-manipulation protocols already developed, and (3) a completely sequenced genome. Medaka (Oryzias latipes) and its congeneric species, tiny fresh-water teleosts distributed broadly in East and Southeast Asia, meet these criteria.

Findings

Using Oryzias species from 27 local populations, we conducted a simple screening of nonsynonymous SNPs for 11 genes with apparent orthology between medaka and humans. We found medaka SNPs for which the same sites in human orthologs are known to be highly differentiated among the HapMap populations. Importantly, some of these SNPs show signals of positive selection.

Conclusion

These results indicate that medaka is a promising model system for comparative population genomics exploring the functional and adaptive significance of allelic differentiations.

Planning the human variome project: the Spain report

The remarkable progress in characterizing the human genome sequence, exemplified by the Human Genome Project and the HapMap Consortium, has led to the perception that knowledge and the tools (e.g., microarrays) are sufficient for many if not most biomedical research efforts. A large amount of data from diverse studies proves this perception inaccurate at best, and at worst, an impediment for further efforts to characterize the variation in the human genome. Because variation in genotype and environment are the fundamental basis to understand phenotypic variability and heritability at the population level, identifying the range of human genetic variation is crucial to the development of personalized nutrition and medicine. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) was proposed initially to systematically collect mutations that cause human disease and create a cyber infrastructure to link locus specific databases (LSDB). We report here the discussions and recommendations from the 2008 HVP planning meeting held in San Feliu de Guixols, Spain, in May 2008.

African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping

Comparative studies of ethnically diverse human populations, particularly in Africa, are important for reconstructing human evolutionary history and for understanding the genetic basis of phenotypic adaptation and complex disease. African populations are characterized by greater levels of genetic diversity, extensive population substructure, and less linkage disequilibrium (LD) among loci compared to non-African populations. Africans also possess a number of genetic adaptations that have evolved in response to diverse climates and diets, as well as exposure to infectious disease. This review summarizes patterns and the evolutionary origins of genetic diversity present in African populations, as well as their implications for the mapping of complex traits, including disease susceptibility.

Positive selection in East Asians for an EDAR allele that enhances NF-kappaB activation

Genome-wide scans for positive selection in humans provide a promising approach to establish links between genetic variants and adaptive phenotypes. From this approach, lists of hundreds of candidate genomic regions for positive selection have been assembled. These candidate regions are expected to contain variants that contribute to adaptive phenotypes, but few of these regions have been associated with phenotypic effects. Here we present evidence that a derived nonsynonymous substitution (370A) in EDAR, a gene involved in ectodermal development, was driven to high frequency in East Asia by positive selection prior to 10,000 years ago. With an in vitro transfection assay, we demonstrate that 370A enhances NF-kappaB activity. Our results suggest that 370A is a positively selected functional genetic variant that underlies an adaptive human phenotype.