Patterns of population differentiation of candidate genes for cardiovascular disease

Deciphering climate resilience in Indian cattle breeds by selection signature analyses

The signature of selection is a crucial concept in evolutionary biology that refers to the pattern of genetic variation which arises in a population due to natural selection. In the context of climate adaptation, the signature of selection can reveal the genetic basis of adaptive traits that enable organisms to survive and thrive in changing environmental conditions. Breeds living in diverse agroecological zones exhibit genetic "footprints" within their genomes that mirror the influence of climate-induced selective pressures, subsequently impacting phenotypic variance. It is assumed that the genomes of animals residing in these regions have been altered through selection for various climatic adaptations. These regions are known as signatures of selection and can be identified using various summary statistics. We examined genotypic data from eight different cattle breeds (Gir, Hariana, Kankrej, Nelore, Ongole, Red Sindhi, Sahiwal, and Tharparkar) that are adapted to diverse regional climates. To identify selection signature regions in this investigation, we used four intra-population statistics: Tajima's D, CLR, iHS, and ROH. In this study, we utilized Bovine 50 K chip data and four genome scan techniques to assess the genetic regions of positive selection for high-temperature adaptation. We have also performed a genome-wide investigation of genetic diversity, inbreeding, and effective population size in our target dataset. We identified potential regions for selection that are likely to be caused by adverse climatic conditions. We observed many adaptation genes in several potential selection signature areas. These include genes like HSPB2, HSPB3, HSP20, HSP90AB1, HSF4, HSPA1B, CLPB, GAP43, MITF, and MCHR1 which have been reported in the cattle populations that live in varied climatic regions. The findings demonstrated that genes involved in disease resistance and thermotolerance were subjected to intense selection. The findings have implications for marker-assisted breeding, understanding the genetic landscape of climate-induced adaptation, putting breeding and conservation programs into action.

Genetic Diversity and Signatures of Selection for Thermal Stress in Cattle and Other Two Bos Species Adapted to Divergent Climatic Conditions

Understanding the biological mechanisms of climatic adaptation is of paramount importance for the optimization of breeding programs and conservation of genetic resources. The aim of this study was to investigate genetic diversity and unravel genomic regions potentially under selection for heat and/or cold tolerance in thirty-two worldwide cattle breeds, with a focus on Chinese local cattle breeds adapted to divergent climatic conditions, Datong yak (Bos grunniens; YAK), and Bali (Bos javanicus) based on dense SNP data. In general, moderate genetic diversity levels were observed in most cattle populations. The proportion of polymorphic SNP ranged from 0.197 (YAK) to 0.992 (Mongolian cattle). Observed and expected heterozygosity ranged from 0.023 (YAK) to 0.366 (Sanhe cattle; SH), and from 0.021 (YAK) to 0.358 (SH), respectively. The overall average inbreeding (±SD) was: 0.118 ± 0.028, 0.228 ± 0.059, 0.194 ± 0.041, and 0.021 ± 0.004 based on the observed versus expected number of homozygous genotypes, excess of homozygosity, correlation between uniting gametes, and runs of homozygosity (ROH), respectively. Signatures of selection based on multiple scenarios and methods (F ST, HapFLK, and ROH) revealed important genomic regions and candidate genes. The candidate genes identified are related to various biological processes and pathways such as heat-shock proteins, oxygen transport, anatomical traits, mitochondrial DNA maintenance, metabolic activity, feed intake, carcass conformation, fertility, and reproduction. This highlights the large number of biological processes involved in thermal tolerance and thus, the polygenic nature of climatic resilience. A comprehensive description of genetic diversity measures in Chinese cattle and YAK was carried out and compared to 24 worldwide cattle breeds to avoid potential biases. Numerous genomic regions under positive selection were detected using three signature of selection methods and candidate genes potentially under positive selection were identified. Enriched function analyses pinpointed important biological pathways, molecular function and cellular components, which contribute to a better understanding of the biological mechanisms underlying thermal tolerance in cattle. Based on the large number of genomic regions identified, thermal tolerance has a complex polygenic inheritance nature, which was expected considering the various mechanisms involved in thermal stress response.

Genomic scans for selective sweeps through haplotype homozygosity and allelic fixation in 14 indigenous sheep breeds from Middle East and South Asia

The performance and productivity of livestock have consistently improved by natural and artificial selection over the centuries. Both these selections are expected to leave patterns on the genome and lead to changes in allele frequencies, but natural selection has played the major role among indigenous populations. Detecting selective sweeps in livestock may assist in understanding the processes involved in domestication, genome evolution and discovery of genomic regions associated with economically important traits. We investigated population genetic diversity and selection signals in this study using SNP genotype data of 14 indigenous sheep breeds from Middle East and South Asia, including six breeds from Iran, namely Iranian Balochi, Afshari, Moghani, Qezel, Zel, and Lori-Bakhtiari, three breeds from Afghanistan, namely Afghan Balochi, Arabi, and Gadik, three breeds from India, namely Indian Garole, Changthangi, and Deccani, and two breeds from Bangladesh, namely Bangladeshi Garole and Bangladesh East. The SNP genotype data were generated by the Illumina OvineSNP50 Genotyping BeadChip array. To detect genetic diversity and population structure, we used principal component analysis (PCA), admixture, phylogenetic analyses, and Runs of homozygosity. We applied four complementary statistical tests, FST (fixation index), xp-EHH (cross-population extended haplotype homozygosity), Rsb (extended haplotype homozygosity between-populations), and FLK (the extension of the Lewontin and Krakauer) to detect selective sweeps. Our results not only confirm the previous studies but also provide a suite of novel candidate genes involved in different traits in sheep. On average, FST, xp-EHH, Rsb, and FLK detected 128, 207, 222, and 252 genomic regions as candidates for selective sweeps, respectively. Furthermore, nine overlapping candidate genes were detected by these four tests, especially TNIK, DOCK1, USH2A, and TYW1B which associate with resistance to diseases and climate adaptation. Knowledge of candidate genomic regions in sheep populations may facilitate the identification and potential exploitation of the underlying genes in sheep breeding.

A selection signatures study among Middle Eastern and European sheep breeds

Selection, both natural and artificial, leaves patterns on the genome during domestication of animals and leads to changes in allele frequencies among populations. Detecting genomic regions influenced by selection in livestock may assist in understanding the processes involved in genome evolution and discovering genomic regions related to traits of economic and ecological interests. In the current study, genetic diversity analyses were conducted on 34,206 quality-filtered SNP positions from 450 individuals in 15 sheep breeds, including six indigenous breeds from the Middle East, namely Iranian Balouchi, Afshari, Moghani, Qezel, Karakas and Norduz, and nine breeds from Europe, namely East Friesian Sheep, Ile de France, Mourerous, Romane, Swiss Mirror, Spaelsau, Suffolk, Comisana and Engadine Red Sheep. The SNP genotype data generated by the Illumina OvineSNP50 Genotyping BeadChip array were used in this analysis. We applied two complementary statistical analyses, F_ST (fixation index) and xp-EHH (cross-population extended haplotype homozygosity), to detect selection signatures in Middle Eastern and European sheep populations. F_ST and xp-EHH detected 629 and 256 genes indicating signatures of selection, respectively. Genomic regions identified using F_ST and xp-EHH contained the CIDEA, HHATL, MGST1, FADS1, RTL1 and DGKG genes, which were reported earlier to influence a number of economic traits. Both F_ST and xp-EHH approaches identified 60 shared genes as the signatures of selection, including four candidate genes (NT5E, ADA2, C8A and C8B) that were enriched for two significant Gene Ontology (GO) terms associated with the adenosine metabolic procedure. Knowledge about the candidate genomic regions under selective pressure in sheep breeds may facilitate identification of the underlying genes and enhance our understanding on these genes role in local adaptation.

Genomic diversity, linkage disequilibrium and selection signatures in European local pig breeds assessed with a high density SNP chip

Genetic characterization of local breeds is essential to preserve their genomic variability, to advance conservation policies and to contribute to their promotion and sustainability. Genomic diversity of twenty European local pig breeds and a small sample of Spanish wild pigs was assessed using high density SNP chips. A total of 992 DNA samples were analyzed with the GeneSeek Genomic Profiler (GGP) 70 K HD porcine genotyping chip. Genotype data was employed to compute genetic diversity, population differentiation and structure, genetic distances, linkage disequilibrium and effective population size. Our results point out several breeds, such as Turopolje, Apulo Calabrese, Casertana, Mora Romagnola and Lithuanian indigenous wattle, having the lowest genetic diversity, supported by low heterozygosity and very small effective population size, demonstrating the need of enhanced conservation strategies. Principal components analysis showed the clustering of the individuals of the same breed, with few breeds being clearly isolated from the rest. Several breeds were partially overlapped, suggesting genetic closeness, which was particularly marked in the case of Iberian and Alentejana breeds. Spanish wild boar was also narrowly related to other western populations, in agreement with recurrent admixture between wild and domestic animals. We also searched across the genome for loci under diversifying selection based on F_ST outlier tests. Candidate genes that may underlie differences in adaptation to specific environments and productive systems and phenotypic traits were detected in potentially selected genomic regions.

Cardiovascular Disease Epidemiology in Portuguese-Speaking Countries: data from the Global Burden of Disease, 1990 to 2016

Background

Portuguese-speaking countries (PSC) share the influence of the Portuguese culture but have socioeconomic development patterns that differ from that of Portugal.

Objective

To describe trends in cardiovascular disease (CVD) morbidity and mortality in the PSC between 1990 and 2016, stratified by sex, and their association with the respective sociodemographic indexes (SDI).

Methods

This study used the Global Burden of Disease (GBD) 2016 data and methodology. Data collection followed international standards for death certification, through information systems on vital statistics and mortality surveillance, surveys, and hospital registries. Techniques were used to standardize causes of death by the direct method, as were corrections for underreporting of deaths and garbage codes. To determine the number of deaths due to each cause, the CODEm (Cause of Death Ensemble Model) algorithm was applied. Disability-adjusted life years (DALYs) and SDI (income per capita, educational attainment and total fertility rate) were estimated for each country. A p-value <0.05 was considered significant.

Results

There are large differences, mainly related to socioeconomic conditions, in the relative impact of CVD burden in PSC. Among CVD, ischemic heart disease was the leading cause of death in all PSC in 2016, except for Mozambique and Sao Tome and Principe, where cerebrovascular diseases have supplanted it. The most relevant attributable risk factors for CVD among all PSC are hypertension and dietary factors.

Conclusion

Collaboration among PSC may allow successful experiences in combating CVD to be shared between those countries.

Infectious diseases, IL6 -174G>C polymorphism, and human development

Interleukin-6 (IL6) is a pro-inflammatory cytokine that is required for resistance against many pathogens. However, sustained IL6 activity can cause tissue damage in the periphery and brain. Previous studies have shown that populations in disease-endemic regions adapt by selecting the high-producing G-allele at the -174G>C (rs1800795) polymorphism, while others have linked increased IL6 to cognitive impairments. The present study sought to determine whether up-regulation of IL6 by the G-allele at rs1800795 polymorphism in disease-endemic regions was associated with increased cognitive deficits and corollary reductions in social, economic, and political development. We tested these hypotheses in a global sample of 189 nations with World Health Organization ratings for infectious diseases. We also included the Historical Pathogen Prevalence index, a measure of national average intelligence (IQ), and the United Nation Human Development Index (HDI) including per capita income, life expectancy, child mortality, and fertility rate. IL6 -174G>C allele frequencies were obtained from 171,168 individuals spanning 84 nations. The high-producing G-allele frequency was positively correlated with infectious disease ranking (r=0.745, P<0.001) and negatively with IQ (r=-0.524, P<0.001) and HDI (r=-0.671, P<0.001). These robust findings suggest that in regions with a high pathogen burden the need for a strong IL6 response is accompanied by cognitive deficits and reduced HDI ranking.

Genetic polymorphisms of PAI-1 and PAR-1 are associated with acute normal tissue toxicity in Chinese rectal cancer patients treated with pelvic radiotherapy

Plasminogen activator inhibitor type 1 (PAI-1) and protease-activated receptor-1 (PAR-1) are crucial mediators of the intestinal microenvironment and are involved in radiation-induced acute and chronic injury. To evaluate whether genetic polymorphisms of PAI-1 and PAR-1 were predictors of radiation-induced injury in patients with rectal cancer, we retrospectively evaluated 356 rectal cancer patients who had received pelvic radiotherapy and analyzed the association of genetic polymorphisms of PAI-1 and PAR-1 with acute toxicities after radiotherapy. Acute adverse events were scored, including dermatitis, fecal incontinence (anal toxicity), hematological toxicity, diarrhea, and vomiting. The patients were grouped into grade ≥2 and grade 0-1 toxicity groups to analyze the acute toxicities. Genotyping of six single nucleotide polymorphisms (SNPs) of PAI-1 and PAR-1 was performed using TaqMan assays. A logistic regression model was used to estimate the odds ratios and 95% confidence intervals. Of the 356 individuals, 264 (72.5%) had grade ≥2 total toxicities; within this group, there were 65 (18.3%) individuals who reached grade ≥3 toxicities. There were 19.5% (69/354) and 36.9% (130/352) patients that developed grade ≥2 toxicities for diarrhea and fecal incontinence, respectively. The variant genotype GG of rs1050955 in PAI-1 was found to be negatively associated with the risk of diarrhea and incontinence (P<0.05), whereas the AG and GG genotypes of rs2227631 in PAI-1 were associated with an increased risk of incontinence. The CT genotype of PAR-1 rs32934 was associated with an increased risk of total toxicity compared with the CC allele. Our results demonstrated that SNPs in the PAI-1 and PAR-1 genes were associated with acute injury in rectal cancer patients treated with pelvic irradiation. These SNPs may be useful biomarkers for predicting acute radiotoxicity in patients with rectal cancer if validated in future studies.

Detection of selection signatures in dairy and beef cattle using high-density genomic information

Background

Artificial selection for economically important traits in cattle is expected to have left distinctive selection signatures on the genome. Access to high-density genotypes facilitates the accurate identification of genomic regions that have undergone positive selection. These findings help to better elucidate the mechanisms of selection and to identify candidate genes of interest to breeding programs.

Results

Information on 705 243 autosomal single nucleotide polymorphisms (SNPs) in 3122 dairy and beef male animals from seven cattle breeds (Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental) were used to detect selection signatures by applying two complementary methods, integrated haplotype score (iHS) and global fixation index (F_ST). To control for false positive results, we used false discovery rate (FDR) adjustment to calculate adjusted iHS within each breed and the genome-wide significance level was about 0.003. Using the iHS method, 83, 92, 91, 101, 85, 101 and 86 significant genomic regions were detected for Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental cattle, respectively. None of these regions was common to all seven breeds. Using the F_ST approach, 704 individual SNPs were detected across breeds. Annotation of the regions of the genome that showed selection signatures revealed several interesting candidate genes i.e. DGAT1, ABCG2, MSTN, CAPN3, FABP3, CHCHD7, PLAG1, JAZF1, PRKG2, ACTC1, TBC1D1, GHR, BMP2, TSG1, LYN, KIT and MC1R that play a role in milk production, reproduction, body size, muscle formation or coat color. Fifty-seven common candidate genes were found by both the iHS and global F_ST methods across the seven breeds. Moreover, many novel genomic regions and genes were detected within the regions that showed selection signatures; for some candidate genes, signatures of positive selection exist in the human genome. Multilevel bioinformatic analyses of the detected candidate genes suggested that the PPAR pathway may have been subjected to positive selection.

Conclusions

This study provides a high-resolution bovine genomic map of positive selection signatures that are either specific to one breed or common to a subset of the seven breeds analyzed. Our results will contribute to the detection of functional candidate genes that have undergone positive selection in future studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0127-3) contains supplementary material, which is available to authorized users.

Molecular cloning and characterization of NPR1 gene from Arachis hypogaea

The NPR1 gene was an important regulator for a plant disease resistance. The cDNA of NPR1 gene was cloned from peanut cultivar Ri Hua 1 by rapid amplification of cDNA ends-polymerase chain reaction (RACE-PCR). The full length cDNA of Arachis hypogaea NPR1 consisted of 2,078 base pairs with a 1,446 bp open-reading frame encoding 481 amino acids. The predicted NPR1 contained the highly conserved functional domains (BTB/POZ domain from M1 to D116), protein-protein interaction domains (three ankyrin repeats from K158 to L186; N187 to L217 and R221 to D250) and one NPR1-like domain (C262 to S469). The DNA sequence of the NPR1 gene was 2,332 or 2,223 bp. Both two sequences contained three introns and four exons. The NPR1 transcripts were expressed mainly in roots and leaves, while fewer signals were detected in the stems. Amount of the NPR1 transcript was significantly increased 1 h after salicylic acid challenge and was eventually 5.3 times greater than that in the control group. Both the DNA sequence and the coding sequence were obtained from eight cultivars and nine wild species of Arachis. Maximum likelihood analyses of d N/d S ratios for 25 sequences from different species showed that different selection pressures may have acted on different branches.

Signatures of natural selection on genetic variants affecting complex human traits

It has recently been hypothesized that polygenic adaptation, resulting in modest allele frequency changes at many loci, could be a major mechanism behind the adaptation of complex phenotypes in human populations. Here we leverage the large number of variants that have been identified through genome-wide association (GWA) studies to comprehensively study signatures of natural selection on genetic variants associated with complex traits. Using population differentiation based methods, such as FST and phylogenetic branch length analyses, we systematically examined nearly 1300 SNPs associated with 38 complex phenotypes. Instead of detecting selection signatures at individual variants, we aimed to identify combined evidence of natural selection by aggregating signals across many trait associated SNPs. Our results have revealed some general features of polygenic selection on complex traits associated variants. First, natural selection acting on standing variants associated with complex traits is a common phenomenon. Second, characteristics of selection for different polygenic traits vary both temporarily and geographically. Third, some studied traits (e.g. height and urate level) could have been the primary targets of selection, as indicated by the significant correlation between the effect sizes and the estimated strength of selection in the trait associated variants; however, for most traits, the allele frequency changes in trait associated variants might have been driven by the selection on other correlated phenotypes. Fourth, the changes in allele frequencies as a result of selection can be highly stochastic, such that, polygenic adaptation may accelerate differentiation in allele frequencies among populations, but generally does not produce predictable directional changes. Fifth, multiple mechanisms (pleiotropy, hitchhiking, etc) may act together to govern the changes in allele frequencies of genetic variants associated with complex traits.

Allelic variation in a cellulose synthase gene (PtoCesA4) associated with growth and wood properties in Populus tomentosa

Lignocellulosic biomass from trees provides a renewable feedstock for biofuels, lumber, pulp, paper, and other uses. Dissecting the mechanism underlying natural variation of the complex traits controlling growth and lignocellulose biosynthesis in trees can enable marker-assisted breeding to improve wood quality and yield. Here, we combined linkage disequilibrium (LD)-based association analysis with traditional linkage analysis to detect the genetic effect of a Populus tomentosa cellulose synthase gene, PtoCesA4. PtoCesA4 is strongly expressed in developing xylem and leaves. Nucleotide diversity and LD in PtoCesA4, sampled from the P. tomentosa natural distribution, revealed that PtoCesA4 harbors high single nucleotide polymorphism (SNP) diversity (πT = 0.0080 and θw = 0.0098) and low LD (r(2) ≥ 0.1, within 1400 bp), demonstrating that the potential of a candidate-gene-based LD approach in understanding the molecular basis underlying quantitative variation in this species. By combining single SNP, multi-SNP, and haplotype-based associations in an association population of 460 individuals with single SNP linkage analysis in a family-based linkage populations (1200 individuals), we identified three strong associations (false discovery rate Q < 0.05) in both populations. These include two nonsynonymous markers (SNP49 associated with α-cellulose content and SNP59 associated with fiber width) and a noncoding marker (SNP18 associated with α-cellulose content). Variation in RNA transcript abundance among genotypic classes of SNP49 was confirmed in these two populations. Therefore, combining different methods allowed us to examine functional PtoCesA4 allelic variation underlying natural variation in complex quantitative traits related to growth and lignocellulosic biosynthesis.

A comparison of tests for Hardy-Weinberg Equilibrium in national genetic household surveys

Background

This study is motivated by National Household Surveys that collect genetic data, in which complex samples (e.g. stratified multistage cluster sample), partially from the same family, are selected. In addition to the differential selection probabilities of selecting households and persons within the sampled households, there are two levels of correlations of the collected genetic data in National Genetic Household Surveys (NGHS). The first level of correlation is induced by the hierarchical geographic clustered sampling of households and the second level of correlation is induced by biological inheritances from individuals sampled in the same household.

Results

To test for Hardy-Weinberg Equilibrium (HWE) in NGHS, two test statistics, the CCS method [1] and the QS method [2], appear to be the only existing methods that take account of both correlations. In this paper, I evaluate both methods in terms of the test size and power under a variety of complex designs with different weighting schemes and varying magnitudes of the two correlation effects. Both methods are applied to a real data example from the Hispanic Health and Nutrition Examination Survey with simulated genotype data.

Conclusions

The QS method maintains the nominal size well and consistently achieves higher power than the CCS method in testing HWE under a variety of sample designs, and therefore is recommended for testing HWE of genetic survey data with complex designs.

Screen for Footprints of Selection during Domestication/Captive Breeding of Atlantic Salmon

Domesticated animals provide a unique opportunity to identify genomic targets of artificial selection to the captive environment. Here, we screened three independent domesticated/captive Atlantic salmon (Salmo salar) strains and their wild progenitor populations in an effort to detect potential signals of domestication selection by typing of 261 SNPs and 70 microsatellite loci. By combining information from four different neutrality tests, in total ten genomic regions showed signs of directional selection based on multiple sources of evidence. Most of the identified candidate regions were rather small ranging from zero to a few centimorgans (cM) in the female Atlantic salmon linkage map. We also evaluated how adaptation from standing variation affects adjacent SNP and microsatellite variation along the chromosomes and, by using forward simulations with strong selection, we were able to generate genetic differentiation patterns comparable to the observed data. This study highlights the significance of standing genetic variation during the early stages of adaptation and represents a useful step towards identifying functional variants involved in domestication of Atlantic salmon.

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.

Worldwide genetic structure in 37 genes important in telomere biology

Telomeres form the ends of eukaryotic chromosomes and are vital in maintaining genetic integrity. Telomere dysfunction is associated with cancer and several chronic diseases. Patterns of genetic variation across individuals can provide keys to further understanding the evolutionary history of genes. We investigated patterns of differentiation and population structure of 37 telomere maintenance genes among 53 worldwide populations. Data from 898 unrelated individuals were obtained from the genome-wide scan of the Human Genome Diversity Panel (HGDP) and from 270 unrelated individuals from the International HapMap Project at 716 single-nucleotide polymorphism (SNP) loci. We additionally compared this gene set to HGDP data at 1396 SNPs in 174 innate immunity genes. The majority of the telomere biology genes had low to moderate haplotype diversity (45-85%), high ancestral allele frequencies (>60%) and low differentiation (FST<0.10). Heterozygosity and differentiation were significantly lower in telomere biology genes compared with the innate immunity genes. There was evidence of evolutionary selection in ACD, TERF2IP, NOLA2, POT1 and TNKS in this data set, which was consistent in HapMap 3. TERT had higher than expected levels of haplotype diversity, likely attributable to a lack of linkage disequilibrium, and a potential cancer-associated SNP in this gene, rs2736100, varied substantially in genotype frequency across major continental regions. It is possible that the genes under selection could influence telomere biology diseases. As a group, there appears to be less diversity and differentiation in telomere biology genes than in genes with different functions, possibly due to their critical role in telomere maintenance and chromosomal stability.

A genome-wide survey for SNPs altering microRNA seed sites identifies functional candidates in GWAS

Background

Gene variants within regulatory regions are thought to be major contributors of the variation of complex traits/diseases. Genome wide association studies (GWAS), have identified scores of genetic variants that appear to contribute to human disease risk. However, most of these variants do not appear to be functional. Thus, the significance of the association may be brought up by still unknown mechanisms or by linkage disequilibrium (LD) with functional polymorphisms. In the present study, focused on functional variants related with the binding of microRNAs (miR), we utilized SNP data, including newly released 1000 Genomes Project data to perform a genome-wide scan of SNPs that abrogate or create miR recognition element (MRE) seed sites (MRESS).

Results

We identified 2723 SNPs disrupting, and 22295 SNPs creating MRESSs. We estimated the percent of SNPs falling within both validated (5%) and predicted conserved MRESSs (3%). We determined 87 of these MRESS SNPs were listed in GWAS association studies, or in strong LD with a GWAS SNP, and may represent the functional variants of identified GWAS SNPs. Furthermore, 39 of these have evidence of co-expression of target mRNA and the predicted miR. We also gathered previously published eQTL data supporting a functional role for four of these SNPs shown to associate with disease phenotypes. Comparison of F_ST statistics (a measure of population subdivision) for predicted MRESS SNPs against non MRESS SNPs revealed a significantly higher (P = 0.0004) degree of subdivision among MRESS SNPs, suggesting a role for these SNPs in environmentally driven selection.

Conclusions

We have demonstrated the potential of publicly available resources to identify high priority candidate SNPs for functional studies and for disease risk prediction.

Persistent Inflammatory Pathways Associated with Early Onset Myocardial Infarction in a Medicated Multiethnic Hawaiian Cohort

In spite of current standard therapies to target the major pathomechanisms in myocardial infarction (MI), inflammatory gene expression patterns have been consistently revealed in MI patients. In a multiethnic cohort, we aimed to identify MI-associated pathomechanisms that may be unresponsive to medical treatment to improve diagnosis and therapy. Gene expression profiles in whole blood were analyzed in medicated Asian, African American and Caucasian patients living in Hawaii with a history of early MI and age, ethnicity, risk factor and medication-matched controls. PANTHER ontological and Ingenuity Pathway analysis and functional evaluation of the consistently differentially expressed genes identified coordinated up-regulation of genes for inflammation (LGALS3, PTX3, ZBTB32, BCL2L1), T-cell activation (IL12RB1, VAV3, JAG1, CAMP), immune imbalance (IL-8, IL2RA, CCR7, AHNAK), and active atherosclerosis (NR1H4, BIN1, GSTT1, MARCO) that persist in MI patients in spite of concerted treatment efforts to control vascular pathology. Furthermore, significant ethnic differences appear to exist within the active disease mechanisms that need to be further investigated to identify key targets for effective medical intervention.

Geographic differences in allele frequencies of susceptibility SNPs for cardiovascular disease

BACKGROUND

We hypothesized that the frequencies of risk alleles of SNPs mediating susceptibility to cardiovascular diseases differ among populations of varying geographic origin and that population-specific selection has operated on some of these variants.

METHODS

From the database of genome-wide association studies (GWAS), we selected 36 cardiovascular phenotypes including coronary heart disease, hypertension, and stroke, as well as related quantitative traits (eg, body mass index and plasma lipid levels). We identified 292 SNPs in 270 genes associated with a disease or trait at P < 5 × 10⁻⁸. As part of the Human Genome-Diversity Project (HGDP), 158 (54.1%) of these SNPs have been genotyped in 938 individuals belonging to 52 populations from seven geographic areas. A measure of population differentiation, F(ST), was calculated to quantify differences in risk allele frequencies (RAFs) among populations and geographic areas.

RESULTS

Large differences in RAFs were noted in populations of Africa, East Asia, America and Oceania, when compared with other geographic regions. The mean global F(ST) (0.1042) for 158 SNPs among the populations was not significantly higher than the mean global F(ST) of 158 autosomal SNPs randomly sampled from the HGDP database. Significantly higher global F(ST) (P < 0.05) was noted in eight SNPs, based on an empirical distribution of global F(ST) of 2036 putatively neutral SNPs. For four of these SNPs, additional evidence of selection was noted based on the integrated Haplotype Score.

CONCLUSION

Large differences in RAFs for a set of common SNPs that influence risk of cardiovascular disease were noted between the major world populations. Pairwise comparisons revealed RAF differences for at least eight SNPs that might be due to population-specific selection or demographic factors. These findings are relevant to a better understanding of geographic variation in the prevalence of cardiovascular disease.

What happened after the initial global spread of pandemic human influenza virus A (H1N1)? A population genetics approach

Viral population evolution dynamics of influenza A is crucial for surveillance and control. In this paper we analyzed viral genetic features during the recent pandemic caused by the new influenza human virus A H1N1, using a conventional population genetics approach based on 4689 hemagglutinin (HA) and neuraminidase (NA) sequences available in GenBank submitted between March and December of 2009. This analysis showed several relevant aspects: a) a scarce initial genetic variability within the viral isolates from some countries that increased along 2009 when influenza was dispersed around the world; b) a worldwide virus polarized behavior identified when comparing paired countries, low differentiation and high gene flow were found in some pairs and high differentiation and moderate or scarce gene flow in others, independently of their geographical closeness, c) lack of positive selection in HA and NA due to increase of the population size of virus variants, d) HA and NA variants spread in a few months all over the world being identified in the same countries in different months along 2009, and e) containment of viral variants in Mexico at the beginning of the outbreak, probably due to the control measures applied by the government.

Beyond MHC: signals of elevated selection pressure on Atlantic salmon (Salmo salar) immune-relevant loci

Using Atlantic salmon (Salmo salar) as a model system, we investigated whether 18 microsatellites tightly linked to immune-relevant genes have experienced different selection pressures than 76 loci with no obvious association with immune function. Immune-relevant loci were identified as outliers by two outlier tests significantly more often than nonimmune linked loci (22% vs. 1.6%). In addition, the allele frequencies of immune relevant markers were more often correlated with latitude and temperature. Combined, these results support the hypothesis that immune-relevant loci more frequently exhibit footprints of selection than other loci. They also indicate that the correlation between immune-relevant loci and latitude may be due to temperature-induced differences in pathogen-driven selection or some other environmental factor correlated with latitude.

Disparities in allele frequencies and population differentiation for 101 disease-associated single nucleotide polymorphisms between Puerto Ricans and non-Hispanic whites

Background

Variations in gene allele frequencies can contribute to differences in the prevalence of some common complex diseases among populations. Natural selection modulates the balance in allele frequencies across populations. Population differentiation (F_ST) can evidence environmental selection pressures. Such genetic information is limited in Puerto Ricans, the second largest Hispanic ethnic group in the US, and a group with high prevalence of chronic disease. We determined allele frequencies and population differentiation for 101 single nucleotide polymorphisms (SNPs) in 30 genes involved in major metabolic and disease-relevant pathways in Puerto Ricans (n = 969, ages 45–75 years) and compared them to similarly aged non-Hispanic whites (NHW) (n = 597).

Results

Minor allele frequency (MAF) distributions for 45.5% of the SNPs assessed in Puerto Ricans were significantly different from those of NHW. Puerto Ricans carried risk alleles in higher frequency and protective alleles in lower frequency than NHW. Patterns of population differentiation showed that Puerto Ricans had SNPs with exceptional F_ST values in intronic, non-synonymous and promoter regions. NHW had exceptional F_ST values in intronic and promoter region SNPs only.

Conclusion

These observations may serve to explain and broaden studies on the impact of gene polymorphisms on chronic diseases affecting Puerto Ricans.

Genetic variants associated with complex human diseases show wide variation across multiple populations

BACKGROUND

The wide use of genome wide association studies (GWAS) has led to the successful identification of multiple genetic susceptibility variants to several complex human diseases. Given the limited amount of data on genetic variation at these loci in populations of non-European origin, we investigated population variation among 11 population groups for loci showing strong and consistent association from GWAS with several complex human diseases.

METHODS

Data from the International HapMap Project Phase 3, comprising 11 population groups, were used to estimate allele frequencies at loci showing strong and consistent association from GWAS with any of 26 complex human diseases and traits. Allele frequency summary statistics and F(ST) at each locus were used to estimate population differentiation.

RESULTS

There is wide variation in allele frequencies and F(ST) across the 11 population groups for susceptibility loci to these complex human diseases and traits. Allele frequencies varied widely across populations, often by as much as 20- to 40-fold. F(ST), as a measure of population differentiation, also varied widely across the loci studied (for example, 0.019 to 0.201 for type 2 diabetes, 0.022 to 0.520 for prostate cancer loci, and 0.006 to 0.520 for serum lipid levels).

CONCLUSIONS

The public health risk posed by any of these risk alleles is likely to show wide variation across populations simply as a function of its frequency, and this risk difference may be amplified by gene-gene and gene-environment interactions. These analyses offer compelling reasons for including multiple human populations from different parts of the world in the international effort to use genomic tools to understand disease etiology and differential distribution of diseases across ethnic groups.

Molecular population genetics of PCSK9: a signature of recent positive selection

OBJECTIVE

Proprotein convertase subtilisin-like kexin type 9 (PCSK9) is a newly discovered serine protease that plays a key role in regulating plasma low density lipoprotein (LDL) cholesterol levels. Both rare mutations and common variants in the coding regions of PCSK9 affect LDL cholesterol levels and coronary heart disease risk, as well as response to lipid-lowering therapy.

METHODS

The authors characterized the patterns of variation at the PCSK9 locus in African-Americans and European-Americans using resequenced data from the SeattleSNPs database (pga.gs.washington.edu). The authors performed a test of population differentiation and the long-range haplotype test to detect signatures of recent position selection on PCSK9.

RESULTS

A significantly high FST (a measure of population differentiation) between African-Americans and European-Americans was noted for single nucleotide polymorphism (SNP) rs505151 (FST=0.309). The long-range haplotype test was suggestive of non-neutral evolution of two SNPs, rs505151 and rs562556 that are associated with elevated LDL cholesterol levels ('gain-of-function' mutations). The modes of selection were different between African-Americans and European-Americans. The authors observed signals of recent positive selection on the ancestral allele of nonsynonymous SNP rs505151 (E670G, P=0.0227 and P=0.0001 in theoretical and empirical distribution, respectively) and the derived allele of nonsynonymous SNP rs562556 (I474V, P=0.0227 and 0.0001) in African-Americans, whereas in European-Americans the ancestral allele of SNP rs562556 (P=0.1320 and 0.0370) appeared to be under positive selection.

CONCLUSION

The authors' findings suggest that evolutionary dynamics may underlie the 'gain-of-function' mutations in PCSK9 that are associated with higher LDL cholesterol levels.

Evidence for positive selection in the C-terminal domain of the cholesterol metabolism gene PCSK9 based on phylogenetic analysis in 14 primate species

Background

Cholesterol homeostasis is maintained through finely tuned mechanisms regulating intestinal absorption, hepatic biosynthesis and secretion as well as plasma clearance. Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a secreted enzyme of the serine protease family that reduces cellular uptake of plasma low-density lipoprotein (LDL) cholesterol by promoting LDL receptor (LDL-R) degradation. Species-specific positive selection has been noted in the LDLR promoter, leading to differential expression of LDLR among primates. Whether PCSK9 experienced significant selective pressure to maintain a functional relationship with its target protein, LDL-R, is unknown.

Methodology/Principal Findings

We compiled the sequences of the coding regions of PCSK9 from 14 primate species in the clade of Hominoids, Old World monkeys and New World monkeys. To detect selective pressure at the protein level, the ratios of nonsynonymous/synonymous substitution rate (d_N/d_S) under different evolutionary models were calculated across the phylogeny of PCSK9. Maximum likelihood analyses of d_N/d_S ratios for the aligned coding region sequences among 14 primate species indicated that PCSK9 was subject to a strong functional constraint (i.e., purifying selection). However, positive selection was noted in the functional carboxyl-terminal (C-terminal) domain in many branches across the phylogeny, especially in the lineage leading to the orangutan. Furthermore, at least five positively selected amino acids were detected in this lineage using the branch-site model A. In a sliding-window analysis, several d_N/d_S peaks in the C-terminal domain in both the human and the orangutan branches were noted.

Conclusions

These results suggest that among primates, differential selective pressure has shaped evolutionary patterns in the functional domains of PCSK9, an important regulator of cholesterol homeostasis.