Lower rate of genomic variation identified in the trans-membrane domain of monoamine sub-class of Human G-Protein Coupled Receptors: The Human GPCR-DB Database

Background  

We have surveyed, compiled and annotated nucleotide variations in 338 human 7-transmembrane receptors (G-protein coupled receptors). In a sample of 32 chromosomes from a Nordic population, we attempted to determine the allele frequencies of 80 non-synonymous SNPs, and found 20 novel polymorphic markers. GPCR receptors of physiological and clinical importance were prioritized for statistical analysis. Natural variation and rare mutation information were merged and presented online in the Human GPCR-DB database .     

Worldwide population differentiation at disease-associated SNPs

Background

Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs).

Methods

We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals.

Results

On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations.

Conclusion

Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.     

Current limitations of SNP data from the public domain for studies of complex disorders: a test for ten candidate genes for obesity and osteoporosis

Background

Public SNP databases are frequently used to choose SNPs for candidate genes in the association and linkage studies of complex disorders. However, their utility for such studies of diseases with ethnic-dependent background has never been evaluated.

Results

To estimate the accuracy and completeness of SNP public databases, we analyzed the allele frequencies of 41 SNPs in 10 candidate genes for obesity and/or osteoporosis in a large American-Caucasian sample (1,873 individuals from 405 nuclear families) by PCR-invader assay. We compared our results with those from the databases and other published studies. Of the 41 SNPs, 8 were monomorphic in our sample. Twelve were reported for the first time for Caucasians and the other 29 SNPs in our sample essentially confirmed the respective allele frequencies for Caucasians in the databases and previous studies. The comparison of our data with other ethnic groups showed significant differentiation between the three major world ethnic groups at some SNPs (Caucasians and Africans differed at 3 of the 18 shared SNPs, and Caucasians and Asians differed at 13 of the 22 shared SNPs). This genetic differentiation may have an important implication for studying the well-known ethnic differences in the prevalence of obesity and osteoporosis, and complex disorders in general.

Conclusion

A comparative analysis of the SNP data of the candidate genes obtained in the present study, as well as those retrieved from the public domain, suggests that the databases may currently have serious limitations for studying complex disorders with an ethnic-dependent background due to the incomplete and uneven representation of the candidate SNPs in the databases for the major ethnic groups. This conclusion attests to the imperative necessity of large-scale and accurate characterization of these SNPs in different ethnic groups.     

Seq4SNPs: new software for retrieval of multiple, accurately annotated DNA sequences, ready formatted for SNP assay design

Background  

In moderate-throughput SNP genotyping there was a gap in the workflow, between choosing a set of SNPs and submitting their sequences to proprietary assay design software, which was not met by existing software. Retrieval and formatting of sequences flanking each SNP, prior to assay design, becomes rate-limiting for more than about ten SNPs, especially if annotated for repetitive regions and adjacent variations. We routinely process up to 50 SNPs at once.     

In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species?

Background

There is considerable interest in the high-throughput discovery and genotyping of single nucleotide polymorphisms (SNPs) to accelerate genetic mapping and enable association studies. This study provides an assessment of EST-derived and resequencing-derived SNP quality in maritime pine (Pinus pinaster Ait.), a conifer characterized by a huge genome size (∼23.8 Gb/C).

Methodology/Principal Findings

A 384-SNPs GoldenGate genotyping array was built from i/ 184 SNPs originally detected in a set of 40 re-sequenced candidate genes (in vitro SNPs), chosen on the basis of functionality scores, presence of neighboring polymorphisms, minor allele frequencies and linkage disequilibrium and ii/ 200 SNPs screened from ESTs (in silico SNPs) selected based on the number of ESTs used for SNP detection, the SNP minor allele frequency and the quality of SNP flanking sequences. The global success rate of the assay was 66.9%, and a conversion rate (considering only polymorphic SNPs) of 51% was achieved. In vitro SNPs showed significantly higher genotyping-success and conversion rates than in silico SNPs (+11.5% and +18.5%, respectively). The reproducibility was 100%, and the genotyping error rate very low (0.54%, dropping down to 0.06% when removing four SNPs showing elevated error rates).

Conclusions/Significance

This study demonstrates that ESTs provide a resource for SNP identification in non-model species, which do not require any additional bench work and little bio-informatics analysis. However, the time and cost benefits of in silico SNPs are counterbalanced by a lower conversion rate than in vitro SNPs. This drawback is acceptable for population-based experiments, but could be dramatic in experiments involving samples from narrow genetic backgrounds. In addition, we showed that both the visual inspection of genotyping clusters and the estimation of a per SNP error rate should help identify markers that are not suitable to the GoldenGate technology in species characterized by a large and complex genome.     

Association between fatty acid compositions and genotypes of FABP4 and LXR-alpha in Japanese Black cattle

Background

Single nucleotide polymorphisms (SNPs) and small insertions or deletions (indels) are the most common type of polymorphisms and are frequently used for molecular marker development. Such markers have become very popular for all kinds of genetic analysis, including haplotype reconstruction. Haplotypes can be reconstructed for whole chromosomes but also for specific genes, based on the SNPs present. Haplotypes in the latter context represent the different alleles of a gene. The computational approach to SNP mining is becoming increasingly popular because of the continuously increasing number of sequences deposited in databases, which allows a more accurate identification of SNPs. Several software packages have been developed for SNP mining from databases. From these, QualitySNP is the only tool that combines SNP detection with the reconstruction of alleles, which results in a lower number of false positive SNPs and also works much faster than other programs. We have build a web-based SNP discovery and allele detection tool (HaploSNPer) based on QualitySNP.

Results

HaploSNPer is a flexible web-based tool for detecting SNPs and alleles in user-specified input sequences from both diploid and polyploid species. It includes BLAST for finding homologous sequences in public EST databases, CAP3 or PHRAP for aligning them, and QualitySNP for discovering reliable allelic sequences and SNPs. All possible and reliable alleles are detected by a mathematical algorithm using potential SNP information. Reliable SNPs are then identified based on the reconstructed alleles and on sequence redundancy.

Conclusion

Thorough testing of HaploSNPer (and the underlying QualitySNP algorithm) has shown that EST information alone is sufficient for the identification of alleles and that reliable SNPs can be found efficiently. Furthermore, HaploSNPer supplies a user friendly interface for visualization of SNP and alleles. HaploSNPer is available from http://www.bioinformatics.nl/tools/haplosnper/.     

Association of RAC1 Gene Polymorphisms with Primary End-Stage Renal Disease in Chinese Renal Recipients

Background/Objective

RAC1 gene could influence susceptibility to renal failure by altering the activity and expression of Rac1, which is a member of the Rho family of small GTP-binding proteins. In clinical practice, renal transplantation provides the optimal treatment for people with end-stage renal disease (ESRD). The objective of this present study was to determine whether the RAC1 gene polymorphisms were associated with primary ESRD susceptibility in Chinese renal recipients.

Methods

Six single nucleotide polymorphisms (SNPs) of RAC1 gene, including rs836488 T>C, rs702482 A>T, rs10951982 G>A, rs702483 A>G, rs6954996 G>A, and rs9374 G>A, were genotyped in 300 renal transplant recipients (cases) and 998 healthy Chinese subjects (controls) by using TaqMan SNP genotyping assay. Allele, genotype, and haplotype frequencies of the six SNPs were compared between cases and controls. Odds ratios (OR) and 95% confidence intervals (CI) were calculated in logistic regression models to evaluate the associations of the six SNPs with ESRD risk.

Results

The genotype distributions for the six SNPs in controls were consistent with Hardy-Weinberg equilibrium (P > 0.05). Association analysis revealed that three SNPs were significantly associated with ESRD risk. Positive associations with ESRD risk were found for the rs836488, rs702482, and rs702483 in the co-dominant model (minor allele homozygotes versus major allele homozygotes); specifically, the frequencies of the minor allele homozygotes and the minor allele for the three SNPs were higher in the cases than in the controls. In addition, these three SNPs also had associations with increased ESRD risk under the additive model (P < 0.05), and positive associations were also found for the rs836488 in the dominant model (P < 0.05) and for the rs702483 in the recessive model (P < 0.05). All these associations were independent of confounding factors. The other three SNPs (rs10951982, rs6954996, and rs9374), in all comparison models, were not associated with ESRD risk (P > 0.05). In haplotype analysis, carriers with "C-T-G-G-G-G" haplotype had a significantly higher risk of ESRD compared with the most common haplotype "T-A-G-A-G-G" (P = 0.011, OR = 1.46, 95% CI = 1.09–1.94).

Conclusion

This study suggested that polymorphisms of RAC1 gene might influence the susceptibility to ESRD in Chinese Han population. Further studies are necessary to confirm our findings.     

QualitySNP: a pipeline for detecting single nucleotide polymorphisms and insertions/deletions in EST data from diploid and polyploid species

Background  

Single nucleotide polymorphisms (SNPs) are important tools in studying complex genetic traits and genome evolution. Computational strategies for SNP discovery make use of the large number of sequences present in public databases (in most cases as expressed sequence tags (ESTs)) and are considered to be faster and more cost-effective than experimental procedures. A major challenge in computational SNP discovery is distinguishing allelic variation from sequence variation between paralogous sequences, in addition to recognizing sequencing errors. For the majority of the public EST sequences, trace or quality files are lacking which makes detection of reliable SNPs even more difficult because it has to rely on sequence comparisons only.     

Genotype determination for polymorphisms in linkage disequilibrium

Background  

Genome-wide association studies with single nucleotide polymorphisms (SNPs) show great promise to identify genetic determinants of complex human traits. In current analyses, genotype calling and imputation of missing genotypes are usually considered as two separated tasks. The genotypes of SNPs are first determined one at a time from allele signal intensities. Then the missing genotypes, i.e., no-calls caused by not perfectly separated signal clouds, are imputed based on the linkage disequilibrium (LD) between multiple SNPs. Although many statistical methods have been developed to improve either genotype calling or imputation of missing genotypes, treating the two steps independently can lead to loss of genetic information.     

A promoter SNP rs4073T>A in the common allele of the interleukin 8 gene is associated with the development of idiopathic pulmonary fibrosis via the IL-8 protein enhancing mode

Background

Interleukin-8 (IL-8) is a potent chemo-attractant cytokine responsible for neutrophil infiltration in lungs with idiopathic pulmonary fibrosis (IPF). The IL-8 protein and mRNA expression are increased in the lung with IPF. We evaluated the effect of single nucleotide polymorphisms (SNPs) of the IL-8 gene on the risk of IPF.

Methods

One promoter (rs4073T>A) and two intronic SNPs (rs2227307T>G and rs2227306C>T) of the IL-8 genes were genotyped in 237 subjects with IPF and 456 normal controls. Logistic regression analysis was applied to evaluate the association of these SNPs with IPF. IL-8 in BAL fluids was measured using a quantitative sandwich enzyme immunoassay, and promoter activity was assessed using the luciferase reporter assay.

Results

The minor allele frequencies of rs4073T>A and rs2227307T>G were significantly lower in the 162 subjects with surgical biopsy-proven IPF and 75 subjects with clinical IPF compared with normal controls in the recessive model (OR = 0.46 and 0.48, p = 0.006 and 0.007, respectively). The IL-8 protein concentration in BAL fluids significantly increased in 24 subjects with IPF compared with 14 controls (p = 0.009). Nine IPF subjects homozygous for the rs4073 T>A common allele exhibited higher levels of the IL-8 protein compared with six subjects homozygous for the minor allele (p = 0.024). The luciferase activity of the rs4073T>A common allele was significantly higher than that of the rs4073T>A minor allele (p = 0.002).

Conclusion

The common allele of a promoter SNP, rs4073T>A, may increase susceptibility to the development of IPF via up-regulation of IL-8.     

Perspectives on the use of multiple sclerosis risk genes for prediction

Objective

A recent collaborative genome-wide association study replicated a large number of susceptibility loci and identified novel loci. This increase in known multiple sclerosis (MS) risk genes raises questions about clinical applicability of genotyping. In an empirical set we assessed the predictive power of typing multiple genes. Next, in a modelling study we explored current and potential predictive performance of genetic MS risk models.

Materials and Methods

Genotype data on 6 MS risk genes in 591 MS patients and 600 controls were used to investigate the predictive value of combining risk alleles. Next, the replicated and novel MS risk loci from the recent and largest international genome-wide association study were used to construct genetic risk models simulating a population of 100,000 individuals. Finally, we assessed the required numbers, frequencies, and ORs of risk SNPs for higher discriminative accuracy in the future.

Results

Individuals with 10 to 12 risk alleles had a significantly increased risk compared to individuals with the average population risk for developing MS (OR 2.76 (95% CI 2.02–3.77)). In the simulation study we showed that the area under the receiver operating characteristic curve (AUC) for a risk score based on the 6 SNPs was 0.64. The AUC increases to 0.66 using the well replicated 24 SNPs and to 0.69 when including all replicated and novel SNPs (n = 53) in the risk model. An additional 20 SNPs with allele frequency 0.30 and ORs 1.1 would be needed to increase the AUC to a slightly higher level of 0.70, and at least 50 novel variants with allele frequency 0.30 and ORs 1.4 would be needed to obtain an AUC of 0.85.

Conclusion

Although new MS risk SNPs emerge rapidly, the discriminatory ability in a clinical setting will be limited.     

Approximation properties of haplotype tagging

Background  

Single nucleotide polymorphisms (SNPs) are locations at which the genomic sequences of population members differ. Since these differences are known to follow patterns, disease association studies are facilitated by identifying SNPs that allow the unique identification of such patterns. This process, known as haplotype tagging, is formulated as a combinatorial optimization problem and analyzed in terms of complexity and approximation properties.     

Snat: a SNP annotation tool for bovine by integrating various sources of genomic information

Background

Genome-wide association (GWA) study has recently become a powerful approach for detecting genetic variants for common diseases without prior knowledge of the variant's location or function. Generally, in GWA studies, the most significant single-nucleotide polymorphisms (SNPs) associated with top-ranked p values are selected in stage one, with follow-up in stage two. The value of selecting SNPs based on statistically significant p values is obvious. However, when minor allele frequencies (MAFs) are relatively low, less-significant p values can still correspond to higher odds ratios (ORs), which might be more useful for prediction of disease status. Therefore, if SNPs are selected using an approach based only on significant p values, some important genetic variants might be missed. We proposed a hybrid approach for selecting candidate SNPs from the discovery stage of GWA study, based on both p values and ORs, and conducted a simulation study to demonstrate the performance of our approach.

Results

The simulation results showed that our hybrid ranking approach was more powerful than the existing ranked p value approach for identifying relatively less-common SNPs. Meanwhile, the type I error probabilities of the hybrid approach is well-controlled at the end of the second stage of the two-stage GWA study.

Conclusions

In GWA studies, SNPs should be considered for inclusion based not only on ranked p values but also on ranked ORs.     

Leptin and leptin receptor gene polymorphisms and their association with plasma leptin levels and obesity in a multi-ethnic Malaysian suburban population

Background

This study was to investigate the prevalence of single nucleotide polymorphisms (SNPs) in leptin gene LEP (A19G and G2548A) and leptin receptor gene LEPR (K109R and Q223R) and their association with fasting plasma leptin level (PLL) and obesity in a Malaysian suburban population in Kampar, Perak.

Methods

Convenience sampling was performed with informed consents, and the study sample was drawn from patients who were patrons of the Kampar Health Clinic. A total of 408 subjects (mean age, 52.4 ± 13.7 years; 169 men, 239 women; 190 obese, 218 non-obese; 148 Malays, 177 ethnic Chinese, 83 ethnic Indians) participated. Socio-demographic data and anthropometric measurements were taken, and genotyping was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP).

Results

The LEP A19G, G2548A and LEPR K109R, Q223R variant allele frequencies were 0.74, 0.67 and 0.61, 0.79, respectively. The genotype and allele distributions of these gene variants were significantly different among ethnic groups, but not among body mass index (BMI) classes. Subjects with LEPR K109 and Q223 allele had significantly higher systolic blood pressure and adiposity indices after adjustment for ethnicity (higher BMI, total body and subcutaneous fat; lower skeletal muscle percentage). Subjects with LEPR 109R allele had lower PLL than their wild-type allele counterparts. The influence of LEP A19G and G2548A SNPs on blood pressures, anthropometrics, and PLL was not evident. Interestingly, synergistic effect of the LEP and LEPR SNPs was observed as subjects homozygous for all four SNPs studied exhibited significantly higher subcutaneous fat and PLL than those with other genotype combinations.

Conclusions

The LEP and LEPR SNPs in this study may not be an obesity marker among Malaysians in this population, but were associated with ethnicity. Our findings suggest that each of these SNPs contributes to minor but significant variation in obesity-related traits and in combination they display synergistic effects on subcutaneous fat and PLL.     

Liver X Receptor Gene Polymorphisms in Tuberculosis: Effect on Susceptibility

Objectives

The Liver X receptors (LXRs), Liver X receptor A (LXRA) and Liver X receptor B (LXRB), regulate lipid metabolism and antimicrobial response. LXRs have a crucial role in the control of Mycobacterium tuberculosis (M.tb). Lacking LXRs mice is more susceptibility to infection M.tb, developing higher bacterial burdens and an increase in the size and number of granulomatous lesions. We aimed to assess the associations between single nucleotide polymorphisms (SNPs) in LXRs and risk of tuberculosis.

Methods

We sequenced the LXRs genes to detect SNPs and to examine genotypic frequencies in 600 patients and 620 healthy controls to investigate for associations with tuberculosis (TB) in the Chinese Han population. DNA re-sequencing revealed eight common variants in the LXRs genes.

Results

The G allele of rs1449627 and the T allele of rs1405655 demonstrated an increased risk of developing TB (p<0.001, p = 0.002), and the T allele of rs3758673, the T allele of rs2279238, and the C allele of rs1449626 in LXRA and the C allele of rs17373080, the G allele of rs2248949, and the C allele of rs1052677 in LXRB were protective against TB patients compared to healthy controls (p = 0.0002, p = 0.006, p<0.001, p = 0.004, p = 0.008, p = 0.003, respectively). All SNP genotypes were significantly associated with TB. An estimation of the frequencies of haplotypes revealed two potential risk haplotypes,GGCG in LXRB (p = 0.004,) and TTCG in LXRA (p<0.001, p = 0.004). Moreover, three protective haplotypes, TTAT and CCAT in LXRA and CATC in LXRB, were significantly “protective” (p = 0.008, p<0.001, p = 0.031) for TB. Furthermore, we determined that the LXRs SNPs were nominally associated with the clinical pattern of disease.

Conclusions

Our study data supported that LXRs play a fundamental role in the genetic susceptibility to TB and to different clinical patterns of disease. Thus, further investigation is required in larger populations and in additional areas.     

Bias in effect size of systemic lupus erythematosus susceptibility loci across Europe: a case-control study

Introduction

We aimed to investigate whether the effect size of the systemic lupus erythematosus (SLE) risk alleles varies across European subpopulations.

Methods

European SLE patients (n = 1,742) and ethnically matched healthy controls (n = 2,101) were recruited at 17 centres from 10 different countries. Only individuals with self-reported ancestry from the country of origin were included. In addition, participants were genotyped for top ancestry informative markers and for 25 SLE associated SNPs. The results were used to compare effect sizes between the Central Eureopan and Southern European subgroups.

Results

Twenty of the 25 SNPs showed independent association with SLE, These SNPs showed a significant bias to larger effect sizes in the Southern subgroup, with 15/20 showing this trend (P = 0.019) and a larger mean odds ratio of the 20 SNPs (1.46 vs. 1.34, P = 0.02) as well as a larger difference in the number of risk alleles (2.06 vs. 1.63, P = 0.027) between SLE patients and controls than for Central Europeans. This bias was reflected in a very significant difference in the cumulative genetic risk score (4.31 vs. 3.48, P = 1.8 × 10^-32). Effect size bias was accompanied by a lower number of SLE risk alleles in the Southern subjects, both patients and controls, the difference being more marked between the controls (P = 1.1 × 10^-8) than between the Southern and Central European patients (P = 0.016). Seven of these SNPs showed significant allele frequency clines.

Conclusion

Our findings showed a bias to larger effect sizes of SLE loci in the Southern Europeans relative to the Central Europeans together with clines of SLE risk allele frequencies. These results indicate the need to study risk allele clines and the implications of the polygenic model of inheritance in SLE.     

Genetic variations in chemoattractant receptor expressed on Th2 cells (CRTH2) is associated with asthma susceptibility in Chinese children

We investigated the allele and genotype frequencies of two common CRTH2 single nucleotide polymorphisms (SNPs) [G1544C and A1651G (rs 545659)] in the 3′-untranslated region and the relationship between these SNPs and serum IL-13 levels in Chinese children patients with asthma. For G1544C and A1651G SNPs, there were significant differences in allele and genotype frequencies between asthma patients and controls. Haplotype analysis yielded additional evidence of linkage disequilibrium for the 1544G–1651G haplotype (P < 0.01). Moreover, serum IL-13 levels were significantly different among genotypes in G1544C, A1651G SNPs. These results suggest that SNPs of G1544C and A1651G might be act as susceptibility genetic factors of asthma. Jinhui Wang and Yongchen Xu should be regarded as joint First Authors.     

A model-based approach to selection of tag SNPs

Background  

Single Nucleotide Polymorphisms (SNPs) are the most common type of polymorphisms found in the human genome. Effective genetic association studies require the identification of sets of tag SNPs that capture as much haplotype information as possible. Tag SNP selection is analogous to the problem of data compression in information theory. According to Shannon's framework, the optimal tag set maximizes the entropy of the tag SNPs subject to constraints on the number of SNPs. This approach requires an appropriate probabilistic model. Compared to simple measures of Linkage Disequilibrium (LD), a good model of haplotype sequences can more accurately account for LD structure. It also provides a machinery for the prediction of tagged SNPs and thereby to assess the performances of tag sets through their ability to predict larger SNP sets.     

Genome wide SNP discovery,analysis and evaluation in mallard (<Emphasis Type="Italic">Anas platyrhynchos</Emphasis>)

Background

Next generation sequencing technologies allow to obtain at low cost the genomic sequence information that currently lacks for most economically and ecologically important organisms. For the mallard duck genomic data is limited. The mallard is, besides a species of large agricultural and societal importance, also the focal species when it comes to long distance dispersal of Avian Influenza. For large scale identification of SNPs we performed Illumina sequencing of wild mallard DNA and compared our data with ongoing genome and EST sequencing of domesticated conspecifics. This is the first study of its kind for waterfowl.

Results

More than one billion base pairs of sequence information were generated resulting in a 16× coverage of a reduced representation library of the mallard genome. Sequence reads were aligned to a draft domesticated duck reference genome and allowed for the detection of over 122,000 SNPs within our mallard sequence dataset. In addition, almost 62,000 nucleotide positions on the domesticated duck reference showed a different nucleotide compared to wild mallard. Approximately 20,000 SNPs identified within our data were shared with SNPs identified in the sequenced domestic duck or in EST sequencing projects. The shared SNPs were considered to be highly reliable and were used to benchmark non-shared SNPs for quality. Genotyping of a representative sample of 364 SNPs resulted in a SNP conversion rate of 99.7%. The correlation of the minor allele count and observed minor allele frequency in the SNP discovery pool was 0.72.

Conclusion

We identified almost 150,000 SNPs in wild mallards that will likely yield good results in genotyping. Of these, ~101,000 SNPs were detected within our wild mallard sequences and ~49,000 were detected between wild and domesticated duck data. In the ~101,000 SNPs we found a subset of ~20,000 SNPs shared between wild mallards and the sequenced domesticated duck suggesting a low genetic divergence. Comparison of quality metrics between the total SNP set (122,000 + 62,000 = 184,000 SNPs) and the validated subset shows similar characteristics for both sets. This indicates that we have detected a large amount (~150,000) of accurately inferred mallard SNPs, which will benefit bird evolutionary studies, ecological studies (e.g. disentangling migratory connectivity) and industrial breeding programs.

     

The Lewis Histo-Blood Group System: Molecular Analysis of the 59T>G, 508G>A,and 1067T>A Polymorphisms in an Amazonian Population

Background

The Lewis (FUT3) gene is responsible for the expression of the Le^a and Le^b blood group antigens. The individuals, who not synthesize these antigens have the phenotype Lewis negative, due to the presence of some single nucleotide polymorphisms (SNPs), such as 59T>G, 508G>A and 1067T>A, whose distribution is different in various ethnic groups. Our aim was to verify the frequencies of these SNPs in an admixed population of Belém-Pará-Brazil.

Materials and Methods

Polymerase chain reaction/restriction enzyme method were used to detect these SNPs in the FUT3 gene, whereas Lewis phenotypes were defined by the direct hemagglutination and in saliva by Dot-Elisa assay in a random sample of 150 individuals from admixed population of Belém in the northeast Brazilian Amazon region.

Results

The frequency of these SNPs was detected as 47.6% (59T>G), 17.3% (508G>A) and 5.3% (1067T>A).The discrepancies between blood and salivary Lewis phenotypes are related to the relatively high frequencies of 59T>G and the null allele 508G>A. Whereas 38.6% of the individuals were Lewis negative based on blood, only 17.24% also tested negative when their saliva were analyzed.

Conclusion

We have found a marked consistency between the phenotypes and genotypes of the Lewis blood group system. Furthermore, our obtained F_ST values reveal distinct frequencies of the FUT3 SNPs between the present sample and its representative ancestral populations. These observations will help to evaluate the Lewis antigens impact as susceptibility markers, in genetic association studies to certain diseases.