Minor Allele Frequency Values Research Articles

Effect of minor allele frequency and density of single nucleotide polymorphism marker arrays on imputation performance and prediction ability using the single-step genomic Best Linear Unbiased Prediction in a simulated beef cattle population

Context In beef cattle populations, there is little evidence regarding the minimum number of genetic markers needed to obtain reliable genomic prediction and imputed genotypes. Aims This study aimed to evaluate the impact of single nucleotide polymorphism (SNP) marker density and minor allele frequency (MAF), on genomic predictions and imputation performance for high and low heritability traits using the single-step genomic Best Linear Unbiased Prediction methodology (ssGBLUP) in a simulated beef cattle population. Methods The simulated genomic and phenotypic data were obtained through QMsim software. 735 293 SNPs markers and 7000 quantitative trait loci (QTL) were randomly simulated. The mutation rate (10−5), QTL effects distribution (gamma distribution with shape parameter = 0.4) and minor allele frequency (MAF ≥ 0.02) of markers were used for quality control. A total of 335k SNPs (high density, HD) and 1000 QTLs were finally considered. Densities of 33 500 (35k), 16 750 (16k), 4186 (4k) and 2093 (2k) SNPs were customised through windows of 10, 20, 80 and 160 SNPs by chromosome, respectively. Three marker selection criteria were used within windows: (1) informative markers with MAF values close to 0.5 (HI); (2) less informative markers with the lowest MAF values (LI); (3) markers evenly distributed (ED). We evaluated the prediction of the high-density array and of 12 scenarios of customised SNP arrays, further the imputation performance of them. The genomic predictions and imputed genotypes were obtained with Blupf90 and FImpute software, respectively, and statistics parameters were applied to evaluate the accuracy of genotypes imputed. The Pearson’s correlation, the coefficient of regression, and the difference between genomic predictions and true breeding values were used to evaluate the prediction ability (PA), inflation (b), and bias (d), respectively. Key results Densities above 16k SNPs using HI and ED criteria displayed lower b, higher PA and higher imputation accuracy. Consequently, similar values of PA, b and d were observed with the use of imputed genotypes. The LI criterion with densities higher than 35k SNPs, showed higher PA and similar predictions using imputed genotypes, however lower b and quality of imputed genotypes were observed. Conclusion The results obtained showed that at least 5% of HI or ED SNPs available in the HD array are necessary to obtain reliable genomic predictions and imputed genotypes. Implications The development of low-density customised arrays based on criteria of MAF and even distribution of SNPs, might be a cost-effective and feasible approach to implement genomic selection in beef cattle.

A Novel Quality-Control Procedure to Improve the Accuracy of Rare Variant Calling in SNP Arrays.

Background: Single-nucleotide polymorphism (SNP) arrays are an ideal technology for genotyping genetic variants in mass screening. However, using SNP arrays to detect rare variants [with a minor allele frequency (MAF) of <1%] is still a challenge because of noise signals and batch effects. An approach that improves the genotyping quality is needed for clinical applications. Methods: We developed a quality-control procedure for rare variants which integrates different algorithms, filters, and experiments to increase the accuracy of variant calling. Using data from the TWB 2.0 custom Axiom array, we adopted an advanced normalization adjustment to prevent false calls caused by splitting the cluster and a rare het adjustment which decreases false calls in rare variants. The concordance of allelic frequencies from array data was compared to those from sequencing datasets of Taiwanese. Finally, genotyping results were used to detect familial hypercholesterolemia (FH), thrombophilia (TH), and maturity-onset diabetes of the young (MODY) to assess the performance in disease screening. All heterozygous calls were verified by Sanger sequencing or qPCR. The positive predictive value (PPV) of each step was estimated to evaluate the performance of our procedure. Results: We analyzed SNP array data from 43,433 individuals, which interrogated 267,247 rare variants. The advanced normalization and rare het adjustment methods adjusted genotyping calling of 168,134 variants (96.49%). We further removed 3916 probesets which were discordant in MAFs between the SNP array and sequencing data. The PPV for detecting pathogenic variants with 0.01%<MAF≤1% exceeded 99.37%. PPVs for those with an MAF of ≤0.01% improved from 95% to 100% for FH, 42.11% to 85.19% for TH, and 18.24% to 72.22% for MODY after adopting our rare variant quality-control procedure and experimental verification. Conclusion: Adopting our quality-control procedure, SNP arrays can adequately detect variants with MAF values ranging 0.01%∼0.1%. For variants with MAF values of ≤0.01%, experimental validation is needed unless sequencing data from a homogeneous population of >10,000 are available. The results demonstrated our procedure could perform correct genotype calling of rare variants. It provides a solution of pathogenic variant detection through SNP array. The approach brings tremendous promise for implementing precision medicine in medical practice.

SNP Development in Penaeus vannamei via Next-Generation Sequencing and DNA Pool Sequencing

Next-generation sequencing and pool sequencing have been widely used in SNP (single-nucleotide polymorphism) detection and population genetics research; however, there are few reports on SNPs related to the growth of Penaeus vannamei. The purpose of this study was to call SNPs from rapid-growing (RG) and slow-growing (SG) individuals’ transcriptomes and use DNA pool sequencing to assess the reliability of SNPs. Two parameters were applied to detect SNPs. One parameter was the p-values generated using Fisher’s exact test, which were used to calculate the significance of allele frequency differences between RG and SG. The other one was the AFI (minor allele frequency imbalance), which was defined to highlight the fold changes in MAF (minor allele frequency) values between RG and SG. There were 216,015 hypothetical SNPs, which were obtained based on the transcriptome data. Finally, 104 high-quality SNPs and 96,819 low-quality SNPs were predicted. Then, 18 high-quality SNPs and 17 low-quality SNPs were selected to assess the reliability of the detection process. Here, 72.22% (13/18) accuracy was achieved for high-quality SNPs, while only 52.94% (9/17) accuracy was achieved for low-quality SNPs. These SNPs enrich the data for population genetics studies of P. vannamei and may play a role in the development of SNP markers for future breeding studies.

New resources for genetic studies in maize (Zea mays L.): a genome-wide Maize6H-60K single nucleotide polymorphism array and its application.

Despite the availability of numerous molecular markers in maize, effective evaluation of all types of germplasm resources, accurate identification of varieties and analysis of a large number of materials in a timely, low-cost manner is challenging. Here, we present Maize6H-60K, a genome-wide single nucleotide polymorphism (SNP) array to facilitate maize genotyping. We first identified 160 million variants by sequencing data of 388 representative inbreds and then tiled 200000 high-quality variants on a screening array. These variants were further narrowed down to 61282 using stringent filtering criteria. Among the 60000 markers, 21460 SNPs (35%) were within genic regions and 12835 (21%) were located in coding regions. To assess their effectiveness, 329 inbreds, 221 hybrids, 34 parent-offspring sets and six breeding samples were genotyped. Overall, 48972 SNPs (80%) were categorized into the highest quality class, that of 'poly high resolution'. A total of 54658 (89.29%) and 53091 (86.73%) SNPs had minor allele frequency values≥0.20 in inbreds and hybrids respectively. A linkage disequilibrium (LD) analysis revealed that LD decline was in equilibrium when r2 was between 0.10 and 0.15, which corresponds to a physical distance of 400-600kb. UPGMA clustering analysis divided the 329 inbred lines into nine groups that were consistent with known pedigrees. A background analysis of breeding materials indicated that the 60000 markers were suitable for evaluation of breeding populations constructed by materials between or within heterotic groups. The developed Maize6H-60K array should be an important tool in maize genetic studies, variety identification and molecular breeding.

Development of an SNP-based parentage verification panel for lovebirds.

The genus Agapornis, or lovebirds, are popular pet parrots worldwide. Currently, breeders are dependent on pedigree records as a selection tool as no molecular parentage verification test is available for any of the nine species. The A.roseicollis reference genome was recently assembled. This was followed by the sequencing of the whole genomes of the parents of the reference genome individual at 30× coverage. The parents' reads were mapped against the reference genome to identify SNPs. Over 1.6 million SNPs, shared between the parents, were discovered using the Genome Analysis Toolkit pipeline. SNPs were filtered to a panel of 480 SNPs based on Genome Analysis Toolkit parameters. The panel of 480 SNPs was genotyped in a population of 960 lovebirds across seven species. A panel of 262 SNPs was compiled that included SNPs successfully amplified across all species. The 262-SNP panel was reduced based on the observed heterozygosity (HO ) and minor allele frequency (MAF) values per SNP to include the lowest number of SNPs with the highest exclusion power for parentage verification. Two smaller panels consisting of 195 SNPs with MAF and HO values>0.1 and 40 SNPs with MAF and HO values>0.3, were constructed. The panels were verified using 43 families from different species with known relationships to evaluate the exclusion power of each panel. The 195 SNP panel with an average exclusion probability of 99.9% and MAF and HO values>0.1 was proposed as the routine Agapornis parentage verification panel.

Genome-Wide Linkage Disequilibrium and the Extent of Effective Population Sizes in Six Chinese Goat Populations Using a 50K Single Nucleotide Polymorphism Panel.

Simple SummaryInformation on linkage disequilibrium (LD) and the extent of effective population size (Ne) has important implications for exploring the degree of biological diversity, for predicting underlying selection pressure, and for designing animal breeding programs. In this study, we assessed LD, Ne, and the distribution of minor allele frequency in six goat populations. Accordingly, the results of LD and Ne using a single nucleotide polymorphism (SNP) panel (Caprine SNP 50K BeadChip, Lincoln, NE, USA) are helpful for the sustainable conservation, proper management, and utilization of Chinese goat populations.Genome-wide linkage disequilibrium is a useful parameter to study quantitative trait locus (QTL) mapping and genetic selection. In many genomic methodologies, effective population size is an important genetic parameter because of its relationship to the loss of genetic variation, increases in inbreeding, the accumulation of mutations, and the effectiveness of selection. In this study, a total of 193 individuals were genotyped to assess the extent of LD and Ne in six Chinese goat populations using the SNP 50K BeadChip. Across the determined autosomal chromosomes, we found an average of 0.02 and 0.23 for r2 and D’ values, respectively. The average r2 between all the populations varied little and ranged from 0.055 r2 for the Jining Grey to 0.128 r2 for the Guangfeng, with an overall mean of 0.083. Across the 29 autosomal chromosomes, minor allele frequency (MAF) was highest on chromosome 1 (0.321) and lowest on chromosome 25 (0.309), with an average MAF of 0.317, and showing the lowest (25.5% for Louping) and highest (28.8% for Qingeda) SNP proportions at MAF values > 0.3. The inbreeding coefficient ranged from 0.064 to 0.085, with a mean of 0.075 for all the autosomes. The Jining Grey and Qingeda populations showed higher Ne estimates, highlighting that these animals could have been influenced by artificial selection. Furthermore, a declining recent Ne was distinguished for the Arbas Cashmere and Guangfeng populations, and their estimated values were closer to 64 and 95, respectively, 13 generations ago, which indicates that these breeds were exposed to strong selection. This study provides an insight into valuable genetic information and will open up the opportunity for further genomic selection analysis of Chinese goat populations.

Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection

Understanding the role of rare variants is important in elucidating the genetic basis of human disease. Negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1 − p)]α, where p is the MAF and negative values of α imply larger effect sizes for rare variants. We estimate α for 25 UK Biobank diseases and complex traits. All traits produce negative α estimates, with best-fit mean of –0.38 (s.e. 0.02) across traits. Despite larger rare variant effect sizes, rare variants (MAF < 1%) explain less than 10% of total SNP-heritability for most traits analyzed. Using evolutionary modeling and forward simulations, we validate the α model of MAF-dependent trait effects and assess plausible values of relevant evolutionary parameters.

Response Surface Analysis of Genomic Prediction Accuracy Values Using Quality Control Covariates in Soybean.

An important and broadly used tool for selection purposes and to increase yield and genetic gain in plant breeding programs is genomic prediction (GP). Genomic prediction is a technique where molecular marker information and phenotypic data are used to predict the phenotype (eg, yield) of individuals for which only marker data are available. Higher prediction accuracy can be achieved not only by using efficient models but also by using quality molecular marker and phenotypic data. The steps of a typical quality control (QC) of marker data include the elimination of markers with certain level of minor allele frequency (MAF) and missing marker values and the imputation of missing marker values. In this article, we evaluated how the prediction accuracy is influenced by the combination of 12 MAF values, 27 different percentages of missing marker values, and 2 imputation techniques (IT; naïve and Random Forest (RF)). We constructed a response surface of prediction accuracy values for the two ITs as a function of MAF and percentage of missing marker values using soybean data from the University of Nebraska–Lincoln Soybean Breeding Program. We found that both the genetic architecture of the trait and the IT affect the prediction accuracy implying that we have to be careful how we perform QC on the marker data. For the corresponding combinations MAF-percentage of missing values we observed that implementing the RF imputation increased the number of markers by 2 to 5 times than the simple naïve imputation method that is based on the mean allele dosage of the non-missing values at each loci. We conclude that there is not a unique strategy (combination of the QCs and imputation method) that outperforms the results of the others for all traits.

Characterization of ADME genes variation in Roma and 20 populations worldwide.

The products of the polymorphic ADME genes are involved in Absorption, Distribution, Metabolism, and Excretion of drugs. The pharmacogenetic data have been studied extensively due to their clinical importance in the appropriate drug prescription, but such data from the isolated populations are rather scarce. We analyzed the distribution of 95 polymorphisms in 31 core ADME genes in 20 populations worldwide and in newly genotyped samples from the Roma (Gypsy) population living in Croatia. Global distribution of ADME core gene loci differentiated three major clusters; (1) African, (2) East Asian, and (3) joint European, South Asian and South American cluster. The SLCO1B3 (rs4149117) and CYP3A4 (rs2242480) genes differentiated at the highest level the African group of populations, while NAT2 gene loci (rs1208, rs1801280, and rs1799929) and VKORC1 (rs9923231) differentiated East Asian populations. The VKORC1 rs9923231 was among the investigated loci the one with the largest global minor allele frequency (MAF) range; its MAF ranged from 0.027 in Nigeria to 0.924 in Han Chinese. The distribution of the investigated gene loci positions Roma population within the joined European and South Asian clusters, suggesting that their ADME gene pool is a combination of ancestral (Indian) and more recent (European) surrounding, as it was already implied by other genetic markers. However, when compared to the populations worldwide, the Croatian Roma have extreme MAF values in 10 out of the 95 investigated ADME core gene loci. Among loci which have extraordinary MAFs in Roma population two have strong proof of clinical importance: rs1799853 (CYP2C9) for warfarin dosage, and rs12248560 (CYP2C19) for clopidogrel dosage, efficacy and toxicity. This finding confirms the importance of taking the Roma as well as the other isolated populations`genetic profiles into account in pharmaco-therapeutic practice.

Interbreed Distribution of the Myostatin (MSTN) Gene 5′-Flanking Variants and Their Relationship With Horse Biometric Traits

To assess the involvement of the MSTN gene polymorphisms in the biometric traits interbreed variability, we have examined the distribution of the three known 5′-flanking variants (g.66495696T>C, g.66495826T>C, and 272 bp SINE insertion) within the group of 2,052 horses representing 12 breeds and compared the allele frequencies between breeds assigned to the different morphological types. Additionally, the association of particular genotypes with selected biometric traits intrabreed variability was studied in five horse breeds. Genotyping of the two SNPs (g.66495696T>C and g.66495826T>C) revealed significant (P < .01) differences of minor allele frequencies between horses representing various morphological types. The highest and the lowest minor allele frequency values were recorded for horses representing brachymorphic and dolichomorphic morphological types, respectively. The association study revealed significant (P < .05) differences in height at the withers (Silesian [SIL]) and cannon bone circumference (Polish Coldblood Horse) — the lowest trait means were recorded for horses carrying the CC genotype in the g.66495696T>C polymorphic site. The heterozygous genotype in g.66495826T>C SNP turned out to be associated (P < .05) with the lower chest circumference if compared to the TT genotype carriers in the Hucul horse breed. Similarly to other investigations, the SINE insertion was present predominantly in Thoroughbred and occurred sporadically in other warmblood horse breeds (Wielkopolski [WLKP], SIL). Our study has confirmed the impact of the MSTN gene polymorphisms on the interbreed and intrabreed variability of horse biometric traits.

Development of SNP markers in lined seahorse (Hippocampus erectus) based on transcriptome sequencing

The population of lined seahorse (Hippocampus erectus) rapidly reduced because of the heavy exploitation in the wild. The single nucleotide polymorphism (SNP), known as one of the popular third-generation molecular markers can be developed easier and faster from high-throughput transcriptome sequencing. In this study, we developed 46 novel SNP markers based on transcriptome of H. erectus. Genetic diversity analysis showed that observed heterozygosity (Ho) and expected heterozygosity (He) were varied from 0.1724 to 0.5250 and from 0.1588 to 0.5000, respectively, and the minor allele frequency value was from 0.0625 to 0.5000. Seven loci were significantly different from Hardy–Weinberg equilibrium (P < 0.05) and significant linkage disequilibrium occurred between HeSNP24 and HeSNP38 (P < 0.01). The present study can provide an effective tool for population study and genetic breeding.

Simple SNP-based minimal marker genotyping for Humulus lupulus L. identification and variety validation.

BackgroundHop is an economically important crop for the Pacific Northwest USA as well as other regions of the world. It is a perennial crop with rhizomatous or clonal propagation system for varietal distribution. A big concern for growers as well as brewers is variety purity and questions are regularly posed to public agencies concerning the availability of genotype testing. Current means for genotyping are based upon 25 microsatellites that provides relatively accurate genotyping but cannot always differentiate sister-lines. In addition, numerous PCR runs (25) are required to complete this process and only a few laboratories exist that perform this service. A genotyping protocol based upon SNPs would enable rapid accurate genotyping that can be assayed at any laboratory facility set up for SNP-based genotyping. The results of this study arose from a larger project designed for whole genome association studies upon the USDA-ARS hop germplasm collection consisting of approximately 116 distinct hop varieties and germplasm (female lines) from around the world.ResultsThe original dataset that arose from partial sequencing of 121 genotypes resulted in the identification of 374,829 SNPs using TASSEL-UNEAK pipeline. After filtering out genotypes with more than 50 % missing data (5 genotypes) and SNP markers with more than 20 % missing data, 32,206 highly filtered SNP markers across 116 genotypes were identified and considered for this study. Minor allele frequency (MAF) was calculated for each SNP and ranked according to the most informative to least informative. Only those markers without missing data across genotypes as well as 60 % or less heterozygous gamete calls were considered for further analysis. Genetic distances among individuals in the study were calculated using the marker with the highest MAF value, then by using a combination of the two markers with highest MAF values and so on. This process was reiterated until a set of markers was identified that allowed for all genotypes in the study to be genetically differentiated from each other. Next, we compared genetic matrices calculated from the minimal marker sets [(Table 2; 6-, 7-, 8-, 10- and 12-marker set matrices] and that of a matrix calculated from a set of markers with no missing data across all 116 samples (1006 SNP markers). The minimum number of markers required to meet both specifications was a set of 7-markers (Table 3). These seven SNPs were then aligned with a genome assembly, and DNA sequence both upstream and downstream were used to identify primer sequences that can be used to develop seven amplicons for high resolution melting curve PCR detection or other SNP-based PCR detection methods.ConclusionsThis study identifies a set of 7 SNP markers that may prove useful for the identification and validation of hop varieties and accessions. Variety validation of unknown samples assumes that the variety under question has been included a priori in a discovery panel. These results are based upon in silica studies and markers need to be validated using different SNP marker technology upon a differential set of hop genotypes. The marker sequence data and suggested primer sets provide potential means to fingerprint hop varieties in most genetic laboratories utilizing SNP-marker technology.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1492-2) contains supplementary material, which is available to authorized users.

Development of maizeSNP3072, a high-throughput compatible SNP array, for DNA fingerprinting identification of Chinese maize varieties.

Single nucleotide polymorphisms (SNPs) are abundant and evenly distributed throughout the maize (Zea mays L.) genome. SNPs have several advantages over simple sequence repeats, such as ease of data comparison and integration, high-throughput processing of loci, and identification of associated phenotypes. SNPs are thus ideal for DNA fingerprinting, genetic diversity analysis, and marker-assisted breeding. Here, we developed a high-throughput and compatible SNP array, maizeSNP3072, containing 3072 SNPs developed from the maizeSNP50 array. To improve genotyping efficiency, a high-quality cluster file, maizeSNP3072_GT.egt, was constructed. All 3072 SNP loci were localized within different genes, where they were distributed in exons (43 %), promoters (21 %), 3′ untranslated regions (UTRs; 22 %), 5′ UTRs (9 %), and introns (5 %). The average genotyping failure rate using these SNPs was only 6 %, or 3 % using the cluster file to call genotypes. The genotype consistency of repeat sample analysis on Illumina GoldenGate versus Infinium platforms exceeded 96.4 %. The minor allele frequency (MAF) of the SNPs averaged 0.37 based on data from 309 inbred lines. The 3072 SNPs were highly effective for distinguishing among 276 examined hybrids. Comparative analysis using Chinese varieties revealed that the 3072SNP array showed a better marker success rate and higher average MAF values, evaluation scores, and variety-distinguishing efficiency than the maizeSNP50K array. The maizeSNP3072 array thus can be successfully used in DNA fingerprinting identification of Chinese maize varieties and shows potential as a useful tool for germplasm resource evaluation and molecular marker-assisted breeding.Electronic supplementary materialThe online version of this article (doi:10.1007/s11032-015-0335-0) contains supplementary material, which is available to authorized users.

Genome-wide Single Nucleotide Polymorphism Analyses Reveal Genetic Diversity and Structure of Wild and Domestic Cattle in Bangladesh.

In spite of variation in coat color, size, and production traits among indigenous Bangladeshi cattle populations, genetic differences among most of the populations have not been investigated or exploited. In this study, we used a high-density bovine single nucleotide polymorphism (SNP) 80K Bead Chip derived from Bos indicus breeds to assess genetic diversity and population structure of 2 Bangladeshi zebu cattle populations (red Chittagong, n = 28 and non-descript deshi, n = 28) and a semi-domesticated population (gayal, n = 17). Overall, 95% and 58% of the total SNPs (69,804) showed polymorphisms in the zebu and gayal populations, respectively. Similarly, the average minor allele frequency value was as high 0.29 in zebu and as low as 0.09 in gayal. The mean expected heterozygosity varied from 0.42±0.14 in zebu to 0.148±0.14 in gayal with significant heterozygosity deficiency of 0.06 (FIS) in the latter. Coancestry estimations revealed that the two zebu populations are weakly differentiated, with over 99% of the total genetic variation retained within populations and less than 1% accounted for between populations. Conversely, strong genetic differentiation (FST = 0.33) was observed between zebu and gayal populations. Results of population structure and principal component analyses suggest that gayal is distinct from Bos indicus and that the two zebu populations were weakly structured. This study provides basic information about the genetic diversity and structure of Bangladeshi cattle and the semi-domesticated gayal population that can be used for future appraisal of breed utilization and management strategies.

Variants in genes encoding pyrophosphate metabolizing enzymes are associated with Pseudoxanthoma elasticum

ObjectivesPseudoxanthoma elasticum (PXE) is a rare hereditary disorder characterized by progressive calcification and fragmentation of elastic fibers. Because of the great clinical variability between PXE patients the involvement of modifier genes was recently suggested. Therefore, we investigated the association of single nucleotide variants (SNVs) in selected candidate genes known to regulate cellular pyrophosphate metabolism. Design and methodsWe used RLFP analyses to evaluate the distribution of SNVs in alkaline phosphatase (ALP), ectonucleotide pyrophosphatase 1 (ENPP1) and ankylosis (ANKH) in DNA samples from 190 German PXE patients and 190 age- and sex-matched healthy controls. Statistical analyses were performed using Fisher exact test and Bonferroni correction. ResultsThe screening revealed three different SNVs in three genes, which were associated with PXE. The SNV c.1190-65C>A (rs1780329, minor allele frequency (MAF) patients: 0.17; controls: 0.11; P=0.04) in the ALP gene was significantly more frequent in PXE patients. Furthermore, PXE was highly associated with ANKH p.A98A genotype TT (P=0.0012), although the MAF was not different between patients and controls. After correction for multiple testing according to the Bonferroni method, one SNV in the ENPP1 gene (c.313+9G>T, rs7773477) remained significantly associated with PXE with significantly higher MAF values in the patient cohort (MAF: 0.04 vs. 0.00; P=0.0024) and a high association with PXE susceptibility (OR 27.96). ConclusionPolymorphisms in ALP, ENPP1 and ANKH are important genetic risk factors contributing to PXE.

Linkage disequilibrium and genomic scan to detect selective loci in cattle populations adapted to different ecological conditions in Ethiopia

Despite the wide range of observed phenotypic diversities and adaptation to different ecological conditions, little has been studied regarding the genetics of adaptation in the genome of indigenous cattle breeds of developing countries. Here, we investigated the linkage disequilibrium (LD) and identified the subset of outlier loci that are highly differentiated among cattle populations adapted to different ecological conditions in Ethiopia. Specifically, we genotyped 47 unrelated animals sampled from high- versus low-altitude environments using a Bovine 50K SNP BeadChip. Linkage disequilibrium was assessed using both D' and r(2) between adjacent SNPs. We calculated FST and heterozygosity at different significance levels as measures of genetic differentiation for each locus between high- and low-altitude populations following the hierarchical island model approach. We identified 816 loci (p < 0.01) showing selection signals and are associated with genes that might have roles in local adaptation. Some of them are associated with candidate genes that are involved in metabolism (ATP2A3, CA2, MYO18B, SIK3, INPP4A, and IREB2), hypoxia response (BDNF, TFRC, and PML) and heat stress (PRKDC, CDK1, and TFDC). Average r(2) and D' values were 0.14 ± 0.21 and 0.57 ± 0.34, respectively, for a minor allele frequency (MAF) ≥ 0.05 and were found to increase with increasing MAF value. The outlier loci identified in the studied Ethiopian cattle populations indicate the presence of genetic variation produced/shaped by adaptation to different environmental conditions and provide a basis for further validation and functional analysis using a reasonable sample size and high-density markers.

Detection of p53 Common Intron Polymorphisms in Patients with Gastritis Lesions from Iran

p53 alterations have been implicated in the development of many cancers, such as gastric cancer, but there is no evidence of p53 intron alterations in gastritis lesions. The aim of this study was to investigate the p53 intron alterations in gastritis along with p53 and mismatch repair protein expression and microsatellite status. PCR-sequencing was conducted for introns 2-7 on DNA extracted from 97 paired samples of gastritis lesions and normal adjacent tissue. Abnormal accumulation of p53 and mismatch repair proteins was investigated using immunohistochemistry. In addition, microsatellite status was evaluated with reference to five mononucleotide markers. Gastritis cases included 41 males and 56 females in the age range of 15-83 years, 87.6% being H.pylori positive. IVS2+38, IVS3ins16 and IVS7+72 were the most polymorphic sites. Their minor allele frequency values were as follows: 0.38, 0.21 and 0.06, respectively. Samples with GG genotype at IVS2+38 and CT at IVS7+72 had no insertion. Moreover, most of the stable samples (91.9 %) had a G allele at IVS2+38. All of the samples were IHC negative for p53 protein, microsatellite stable and expressed mismatch repair proteins. p53 alterations were prominent in the HP+ group, but without statistical significance. According to our results, some p53 polymorphisms such as IVS2+38, IVS3ins16 and IVS7+72, because of their correlations together or with microsatellite status may contribute to gastritis development. However, so far effects on p53 expression and function remain unclear. Therefore, a comprehensive survey is needed to delineate their biological significance.

Developing genomic resources for the common bottlenose dolphin (Tursiops truncatus): isolation and characterization of 153 single nucleotide polymorphisms and 53 genotyping assays

Although single nucleotide polymorphisms (SNPs) are commonly used in human genetics, they have only recently been incorporated into genetic studies of non-model organisms, including cetaceans. SNPs have several advantages over other molecular markers for studies of population genetics: they are quicker and more straightforward to score, cross-laboratory comparisons of data are less complicated, and they can be used successfully with low-quality DNA. We screened portions of the genome of one of the most abundant cetaceans in U.S. waters, the common bottlenose dolphin (Tursiops truncatus), and identified 153 SNPs resulting in an overall average of one SNP every 463 base pairs. Custom TaqMan(®) Assays were designed for 53 of these SNPs, and their performance was tested by genotyping a set of bottlenose dolphin samples, including some with low-quality DNA. We found that in 19% of the loci examined, the minor allele frequency (MAF) estimated during initial SNP ascertainment using a DNA pool of 10 individuals differed significantly from the final MAF after genotyping over 100 individuals, suggesting caution when making inferences about MAF values based on small data sets. For two assays, we also characterized the basis for unusual clustering patterns to determine whether their data could still be utilized for further genetic studies. Overall results support the use of these SNPs for accurate analysis of both poor and good-quality DNA. We report the first SNP markers and genotyping assays for use in population and conservation genetic studies of bottlenose dolphins.

Development of versatile gene-based SNP assays in maize (Zea mays L.)

A large number of maize single nucleotide polymorphism (SNP) candidate sequences have been generated and deposited in public databases. However, very little work has been done to date to comprehensively characterize those SNPs and identify a set of markers, which potentially would have high impact in molecular genetics research and breeding programs. Here we describe a multi-step process to identify highly polymorphic gene-based SNPs among ~130,000 public markers. A set of 695 highly polymorphic SNPs (minor allele frequency value >0.3), identified within exons, 5′ and 3′ untranslated regions of genes, were converted into four of the most popular high-throughput genotyping assays that include Illumina’s GoldenGate and Infinium chemistries, Life Technologies’ TaqMan assay and KBioSciences’ KASPar assay. The term “versatile” was applied to 162 gene-based SNPs that were successfully converted into all four chemistries and had perfect genotypic clustering patterns. This subset of discovered versatile SNP markers represents a universal tool for application in various molecular genetics and breeding projects in maize, where genotyping is based on one of the four above-mentioned chemistries. This study demonstrated that despite the availability of millions of discovered SNPs in maize, only a very small portion of those polymorphisms could be utilized for the development of robust, versatile assays, and has real practical value in marker-assisted selection.

GLOSSI: a method to assess the association of genetic loci-sets with complex diseases

BackgroundThe developments of high-throughput genotyping technologies, which enable the simultaneous genotyping of hundreds of thousands of single nucleotide polymorphisms (SNP) have the potential to increase the benefits of genetic epidemiology studies. Although the enhanced resolution of these platforms increases the chance of interrogating functional SNPs that are themselves causative or in linkage disequilibrium with causal SNPs, commonly used single SNP-association approaches suffer from serious multiple hypothesis testing problems and provide limited insights into combinations of loci that may contribute to complex diseases. Drawing inspiration from Gene Set Enrichment Analysis developed for gene expression data, we have developed a method, named GLOSSI (Gene-loci Set Analysis), that integrates prior biological knowledge into the statistical analysis of genotyping data to test the association of a group of SNPs (loci-set) with complex disease phenotypes. The most significant loci-sets can be used to formulate hypotheses from a functional viewpoint that can be validated experimentally.ResultsIn a simulation study, GLOSSI showed sufficient power to detect loci-sets with less than 10% of SNPs having moderate-to-large effect sizes and intermediate minor allele frequency values. When applied to a biological dataset where no single SNP-association was found in a previous study, GLOSSI was able to identify several loci-sets that are significantly related to blood pressure response to an antihypertensive drug.ConclusionGLOSSI is valuable for association of SNPs at multiple genetic loci with complex disease phenotypes. In contrast to methods based on the Kolmogorov-Smirnov statistic, the approach is parametric and only utilizes information from within the interrogated loci-set. It properly accounts for dependency among SNPs and allows the testing of loci-sets of any size.