The association of TMPRSS6 gene polymorphism with iron status in Egyptian children (a pilot study)

Several studies have shown association of single nucleotide polymorphisms (SNPs) of hepcidin regulatory pathways genes with impaired iron status. The most common is in the TMPRSS6 gene. In Africa, very few studies have been reported. We aimed to investigate the correlation between the common SNPs in the transmembrane protease, serine 6 (TMPRSS6) gene and iron indicators in a sample of Egyptian children for identifying the suitable candidate for iron supplementation.Patients and methods One hundred and sixty children aged 5-13 years were included & classified into iron deficient, iron deficient anemia and normal healthy controls. All were subjected to assessment of serum iron, serum ferritin, total iron binding capacity, complete blood count, reticulocyte count, serum soluble transferrin receptor and serum hepcidin. Molecular study of TMPRSS6 genotyping polymorphisms (rs4820268, rs855791 and rs11704654) were also evaluated.Results There was an association of iron deficiency with AG of rs855791 SNP, (P = 0.01). The minor allele frequency for included children were 0.43, 0.45 & 0.17 for rs4820268, rs855791 & rs11704654 respectively. Genotype GG of rs4820268 expressed the highest hepcidin gene expression fold, the lowest serum ferroportin & iron store compared to AA and AG genotypes (p = 0.05, p = 0.05, p = 0.03 respectively). GG of rs855791 had lower serum ferritin than AA (p = 0.04), lowest iron store & highest serum hepcidin compared to AA and AG genotypes (p = 0.04, p = 0.01 respectively). Children having CC of rs11704654 had lower level of hemoglobin, serum ferritin and serum hepcidin compared with CT genotype (p = 0.01, p = 0.01, p = 0.02) respectively.Conclusion Possible contribution of SNPs (rs855791, rs4820268 and rs11704654) to low iron status.

Peroxisome Proliferator-Activated Receptor α and γ Gene Polymorphisms among South Indian Patients with Diabetic Dyslipidaemia

Background

Peroxisome proliferator-activated receptors (PPAR) α and γ genes play an important role in dyslipidaemia of T2DM.

Aims

To estimate the frequency distribution of PPAR α and γ gene polymorphisms in South Indian T2DM patients with dyslipidaemia compared to healthy controls. Normative frequencies of SNPs were established and compared with data for 1000 genome populations.

Methods

Eligible 382 cases and 336 age and sex-matched controls were enrolled. Six SNPs in PPARα [rs1800206 C>G (Leu162Val), rs4253778 G>C, rs135542 T>C] and PPARγ [rs3856806 (C>T), rs10865710 (C>G), rs1805192 C>G (Pro12Ala)] genes were selected for genotyping.

Results

The allele and gene frequencies did not significantly differ between the diabetic dyslipidaemia cases and healthy controls. However, they were significantly different from that of 1000 genome populations except for rs1800206 C>G (Leu162Val) and rs1805192 C>G (Pro12Ala).

Conclusion

The studied polymorphisms in PPARα and PPARγ genes are not associated with diabetic dyslipidaemia among South Indian patients.

Prediction ability for growth and maternal traits using SNP arrays based on different marker densities in Nellore cattle using the ssGBLUP

This study aimed to investigate the prediction ability for growth and maternal traits using different low-density customized SNP arrays selected by informativeness and distribution of markers across the genome employing single-step genomic BLUP (ssGBLUP). Phenotypic records for adjusted weight at 210 and 450 days of age were utilized. A total of 945 animals were genotyped with high-density chip, and 267 individuals born after 2008 were selected as validation population. We evaluated 11 scenarios using five customized density arrays (40 k, 20 k, 10 k, 5 k and 2 k) and the HD array was used as desirable scenario. The GEBV predictions and BIF (Beef Improvement Federation) accuracy were obtained with BLUPF90 family programs. Linear regression was used to evaluate the prediction ability, inflation, and bias of GEBV of each customized array. An overestimation of partial GEBVs in contrast with complete GEBVs and increase of BIF accuracy with the density arrays diminished were observed. For all traits, the prediction ability was higher as the array density increased and it was similar with customized arrays higher than 10 k SNPs. Level of inflation was lower as the density array increased of and was higher for MW210 effect. The bias was susceptible to overestimation of GEBVs when the density customized arrays decreased. These results revealed that the BIF accuracy is sensible to overestimation using low-density customized arrays while the prediction ability with least 10,000 informative SNPs obtained from the Illumina BovineHD BeadChip shows accurate and less biased predictions. Low-density customized arrays under ssGBLUP method could be feasible and cost-effective in genomic selection.

Assessing accuracy of genotype imputation in the Afrikaner and Brahman cattle breeds of South Africa

Imputation may be used to rescue genomic data from animals that would otherwise be eliminated due to a lower than desired call rate. The aim of this study was to compare the accuracy of genotype imputation for Afrikaner, Brahman, and Brangus cattle of South Africa using within- and multiple-breed reference populations. A total of 373, 309, and 101 Afrikaner, Brahman, and Brangus cattle, respectively, were genotyped using the GeneSeek Genomic Profiler 150 K panel that contained 141,746 markers. Markers with MAF ≤ 0.02 and call rates ≤ 0.95 or that deviated from Hardy Weinberg Equilibrium frequency with a probability of ≤ 0.0001 were excluded from the data as were animals with a call rate ≤ 0.90. The remaining data included 99,086 SNPs and 360 Afrikaner, 75,291 SNPs and 288 animals Brahman, and 97,897 SNPs and 99 Brangus animals. A total of 7986, 7002, and 7000 SNP from 50 Afrikaner and Brahman and 30 Brangus cattle, respectively, were masked and then imputed using BEAGLE v3 and FImpute v2. The within-breed imputation yielded accuracies ranging from 89.9 to 96.6% for the three breeds. The multiple-breed imputation yielded corresponding accuracies from 69.21 to 88.35%. The results showed that population homogeneity and numerical representation for within and across breed strategies, respectively, are crucial components for improving imputation accuracies.

SNPs with intermediate minor allele frequencies facilitate accurate breed assignment of Indian Tharparkar cattle

Tharparkar cattle breed is widely known for its superior milch quality and hardiness attributes. This study aimed to develop an ultra-low density breed-specific single nucleotide polymorphism (SNP) genotype panel to accurately quantify Tharparkar populations in biological samples. In this study, we selected and genotyped 72 Tharparkar animals randomly from Cattle & Buffalo Farm of IVRI, India. This Bovine SNP50 BeadChip genotypic datum was merged with the online data from six indigenous cattle breeds and five taurine breeds. Here, we used a combination of pre-selection statistics and the MAF-LD method developed in our laboratory to analyze the genotypic data obtained from 317 individuals of 12 distinct breeds to identify breed-informative SNPs for the selection of Tharparkar cattle. This methodology identified 63 unique Tharparkar-specific SNPs near intermediate gene frequencies. We report several informative SNPs in genes/QTL regions affecting phenotypes or production traits that might differentiate the Tharparkar breed.

Assessing the power of principal components and wright's fixation index analyzes applied to reveal the genome-wide genetic differences between herds of Holstein cows

Background

Due to the advent of SNP array technology, a genome-wide analysis of genetic differences between populations and breeds has become possible at a previously unattainable level. The Wright’s fixation index (F_st) and the principal component analysis (PCA) are widely used methods in animal genetics studies. In paper we compared the power of these methods, their complementing each other and which of them is the most powerful.

Results

Comparative analysis of the power Principal Components Analysis (PCA) and F_st were carried out to reveal genetic differences between herds of Holsteinized cows. Totally, 803 BovineSNP50 genotypes of cows from 13 herds were used in current study. Obtained F_st values were in the range of 0.002–0.012 (mean 0.0049) while for rare SNPs with MAF 0.0001–0.005 they were even smaller in the range of 0.001–0.01 (mean 0.0027). Genetic relatedness of the cows in the herds was the cause of such small F_st values. The contribution of rare alleles with MAF 0.0001–0.01 to the F_st values was much less than common alleles and this effect depends on linkage disequilibrium (LD). Despite of substantial change in the MAF spectrum and the number of SNPs we observed small effect size of LD - based pruning on F_st data. PCA analysis confirmed the mutual admixture and small genetic difference between herds. Moreover, PCA analysis of the herds based on the visualization the results of a single eigenvector cannot be used to significantly differentiate herds. Only summed eigenvectors should be used to realize full power of PCA to differentiate small between herds genetic difference. Finally, we presented evidences that the significance of F_st data far exceeds the significance of PCA data when these methods are used to reveal genetic differences between herds.

Conclusions

LD - based pruning had a small effect on findings of F_st and PCA analyzes. Therefore, for weakly structured populations the LD - based pruning is not effective. In addition, our results show that the significance of genetic differences between herds obtained by F_st analysis exceeds the values of PCA. Proposed, to differentiate herds or low structured populations we recommend primarily using the F_st approach and only then PCA.

How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species

Background

PLINK is probably the most used program for analyzing SNP genotypes and runs of homozygosity (ROH), both in human and in animal populations. The last decade, ROH analyses have become the state-of-the-art method for inbreeding assessment. In PLINK, the --homozyg function is used to perform ROH analyses and relies on several input settings. These settings can have a large impact on the outcome and default values are not always appropriate for medium density SNP array data. Guidelines for a robust and uniform ROH analysis in PLINK using medium density data are lacking, albeit these guidelines are vital for comparing different ROH studies. In this study, 8 populations of different livestock and pet species are used to demonstrate the importance of PLINK input settings. Moreover, the effects of pruning SNPs for low minor allele frequencies and linkage disequilibrium on ROH detection are shown.

Results

We introduce the genome coverage parameter to appropriately estimate F_ROH and to check the validity of ROH analyses. The effect of pruning for linkage disequilibrium and low minor allele frequencies on ROH analyses is highly population dependent and such pruning may result in missed ROH. PLINK’s minimal density requirement is crucial for medium density genotypes and if set too low, genome coverage of the ROH analysis is limited. Finally, we provide recommendations for the maximal gap, scanning window length and threshold settings.

Conclusions

In this study, we present guidelines for an adequate and robust ROH analysis in PLINK on medium density SNP data. Furthermore, we advise to report parameter settings in publications, and to validate them prior to analysis. Moreover, we encourage authors to report genome coverage to reflect the ROH analysis’ validity. Implementing these guidelines will substantially improve the overall quality and uniformity of ROH analyses.

Correlation study on chromogranin A genetic polymorphism and prognosis of critically ill patients

OBJECTIVE

The objective was to investigate the correlation between single nucleotide polymorphism (SNP) of chromogranin A (CHGA) and prognosis of critically ill patients.

METHODS

We screened 357 critically ill patients consecutively admitted to our intensive care unit. The -89/-415/-462 SNP locus in the promoter region and the +9559/+9578/+9590/+9611 SNP locus in exon 7 coding of CHGA were genotyped by polymerase chain reaction and DNA sequencing technology. Subsequently, the correlation between genotype and prognosis of patients was analyzed.

RESULTS

(1) Three hundred critically ill Chinese Han patients were enrolled in the study. CHGA-415/-462/+9559/+9611 SNPs were polymorphically distributed. Phenotypes of the 4 SNPs were shown not to be in linkage disequilibrium, and there were no significant differences in the minor allele frequencies (MAFs) of the 4 SNPs between participants of this study and healthy people in Asia. (2) The CHGA-415 T/C MAF of the nonsurvival group was significantly higher than that of the survival group (MAF 0.3813 and 0.2864, respectively; P=.026). Survival analysis showed that there were significant differences between the CHGA-415 T/C mutation group (including TC and CC genotypes) and the wild-type group (TT genotype) (log rank=8.887, P=.003). The mortality in the mutant group was significantly higher than that in the wild-type group (0.3333 and 0.1852, respectively; P=.004). (3) Binary logistic analysis showed that CHGA-415 T/C polymorphism was an independent risk factor for the mortality of critically ill patients (odds ratio, 2.286; 95% confidence interval, 1.165-4.484; P=.016).

CONCLUSIONS

Critically ill patients with CHGA-415 T/C mutant genotype display higher 30-day mortality than those with the wild-type group. CHGA-415 T/C polymorphism is an independent risk factor of poor prognosis in critically ill Chinese Han patients.

Minor Allele Frequency Changes the Nature of Genotype by Environment Interactions

In the classical twin study, phenotypic variation is often partitioned into additive genetic (A), common (C) and specific environment (E) components. From genetical theory, the outcome of genotype by environment interaction is expected to inflate A when the interacting factor is shared (i.e., C) between the members of a twin pair. We show that estimates of both A and C can be inflated. When the shared interacting factor changes the size of the difference between homozygotes' means, the expected sibling or DZ twin correlation is .5 if and only if the minor allele frequency (MAF) is .5; otherwise the expected DZ correlation is greater than this value, consistent (and confounded) with some additional effect of C. This result is considered in the light of the distribution of minor allele frequencies for polygenic traits. Also discussed is whether such interactions take place at the locus level or affect an aggregated biological structure or system. Interactions with structures or endophenotypes that result from the aggregated effects of many loci will generally emerge as part of the A estimate.

Analysis of Genotyping-by-Sequencing (GBS) Data

The development of genotyping-by-sequencing (GBS) to rapidly detect nucleotide variation at the whole genome level, in many individuals simultaneously, has provided a transformative genetic profiling technique. GBS can be carried out in species with or without reference genome sequences yields huge amounts of potentially informative data. One limitation with the approach is the paucity of tools to transform the raw data into a format that can be easily interrogated at the genetic level. In this chapter we describe bioinformatics tools developed to address this shortfall together with experimental design considerations to fully leverage the power of GBS for genetic analysis.

Lists of HumanMethylation450 BeadChip probes with nucleotide-variant information obtained from the Phase 3 data of the 1000 Genomes Project

The Illumina's Infinium HumanMethylation450 (HM450) BeadChip array provides a simultaneous examination of DNA methylation status of more than 480,000 CpG sites in the human genome. Its relatively simple protocol is achieved by employing a hybridization methodology followed by single-base extension reactions. However, nucleotide variations among individuals in the hybridization probe sequences can affect the results, i.e. estimates of methylation levels. To investigate possible effects of maternal nutritional conditions on the extent of epigenetic alterations in utero, we examined genome-wide DNA methylation profiles of 33 chorionic villi samples collected in Japan (GEO accession number GSE62733), and revealed using Smirnov-Grubbs' outlier test that epigenetic alterations accumulate in placentas under adverse in utero environments. In that study, we compiled a list of HM450 probes overlapping with the reported nucleotide variants in the Phase 3 dataset (release 20130502) of the 1000 Genomes Project. We excluded the probes whose sequences overlapped with variants with minor allele frequency (MAF) higher than 1% in the Japanese population from identified methylation outliers, to diminish the number of outliers that could have been spuriously identified due to variants at/near the target CpG sites. We herein compiled lists of HM450 probes with MAF information of the African, European, American, South Asian and East Asian populations, in addition to the Japanese population. The provided lists are useful for methylome analyses for human populations using the HM450 BeadChip arrays.

A genome-wide association study of bronchodilator response in Latinos implicates rare variants

BACKGROUND

The primary rescue medication to treat acute asthma exacerbation is the short-acting β₂-adrenergic receptor agonist; however, there is variation in how well a patient responds to treatment. Although these differences might be due to environmental factors, there is mounting evidence for a genetic contribution to variability in bronchodilator response (BDR).

OBJECTIVE

To identify genetic variation associated with bronchodilator drug response in Latino children with asthma.

METHODS

We performed a genome-wide association study (GWAS) for BDR in 1782 Latino children with asthma using standard linear regression, adjusting for genetic ancestry and ethnicity, and performed replication studies in an additional 531 Latinos. We also performed admixture mapping across the genome by testing for an association between local European, African, and Native American ancestry and BDR, adjusting for genomic ancestry and ethnicity.

RESULTS

We identified 7 genetic variants associated with BDR at a genome-wide significant threshold (P < 5 × 10(-8)), all of which had frequencies of less than 5%. Furthermore, we observed an excess of small P values driven by rare variants (frequency, <5%) and by variants in the proximity of solute carrier (SLC) genes. Admixture mapping identified 5 significant peaks; fine mapping within these peaks identified 2 rare variants in SLC22A15 as being associated with increased BDR in Mexicans. Quantitative PCR and immunohistochemistry identified SLC22A15 as being expressed in the lung and bronchial epithelial cells.

CONCLUSION

Our results suggest that rare variation contributes to individual differences in response to albuterol in Latinos, notably in SLC genes that include membrane transport proteins involved in the transport of endogenous metabolites and xenobiotics. Resequencing in larger, multiethnic population samples and additional functional studies are required to further understand the role of rare variation in BDR.

Glucagon gene polymorphism modifies the effects of smoking and physical activity on risk of type 2 diabetes mellitus in Han Chinese

Few genome-wide association studies have considered interactions between multiple genetic variants and environmental factors associated with disease. The interaction was examined between a glucagon gene (GCG) polymorphism and smoking, alcohol consumption and physical activity and the association with risk of type 2 diabetes mellitus (T2DM) in a case-control study of Chinese Han subjects. The rs12104705 polymorphism of GCG and interactions with environmental variables were analyzed for 9619 participants by binary multiple logistic regression. Smoking with the C-C haplotype of rs12104705 was associated with increased risk of T2DM (OR=1.174, 95% CI=1.013-1.361). Moderate and high physical activity with the C-C genotype was associated with decreased risk of T2DM as compared with low physical activity with the genotype (OR=0.251, 95% CI=0.206-0.306 and OR=0.190, 95% CI=0.164-0.220). However, the interaction of drinking and genotype was not associated with risk of T2DM. Genetic polymorphism in rs12104705 of GCG may interact with smoking and physical activity to modify the risk of T2DM.

Differences in asthma genetics between Chinese and other populations

Asthma is caused by complex gene-gene and gene-environment interactions. Most asthma genes are not replicable across populations, which is possibly because of differences in the epidemiology of these genes. Our case-control association and next-generation sequencing studies revealed substantial discrepancies in the frequencies of single nucleotide polymorphisms (SNPs) and haplotype blocks for asthma genes between Chinese and other populations. The minor allele frequencies for nearly half of our studied SNPs differed by 0.2 or greater between southern Chinese subjects in Hong Kong and European white populations, African populations, or both. Because genome-wide association studies for asthma have not been performed in Chinese subjects, we cannot tell whether the genomic findings of recent consortium-based genome-wide association studies are applicable to our population. In addition, our group performed Roche 454 pyrosequencing on a 100-kb area spanning each of 10 asthma loci in 24 healthy Hong Kong children. For the 17q21 locus, there was substantial variation in the haplotype structures that were constructed from 224 common SNPs among Hong Kong subjects and 6 ethnic groups under the 1000 Genomes Project. Sixteen mostly small haplotype blocks were formed in Hong Kong, whereas 6 haplotype blocks were identified in Han Chinese in Beijing and central European subjects and 11 and 19 blocks were identified in Puerto Rican and Yoruba African subjects. In conclusion, differences in allele frequencies of asthma genes and haplotype structures of asthma loci are found between Chinese subjects and other ethnic groups. These sequence variations must be considered during the selection of tagging SNPs for replicating genetic associations between populations.

Multiple polymorphisms within the PLCE1 are associated with esophageal cancer via promoting the gene expression in a Chinese Kazakh population

Although recent genome-wide association studies of esophageal squamous cell carcinoma (ESCC) identified a susceptibility locus in phospholipase C epsilon 1 (PLCE1) in Chinese Han populations, few studies further confirmed these findings in pure Kazakh population in which there are higher incidence and mortality of ESCC. Here, we investigated the potential associations between 19 SNPs of PLCE1 and susceptibility to ESCC in 222 cases and 326 controls from a pure ethnic population of Kazakh. Real-time PCR and immunohistochemistry were performed to detect the PLCE1 expression levels and evaluate their association with PLCE1 polymorphism. We found that only 4 SNPs (rs753724, rs11187842, rs2274223, and rs12263737) with moderate linkage disequilibrium (LD) confer significantly increased risk of ESCC, with the ORs ranging from 1.43 to 2.04, and there was a risk allele dose-dependent increase in ESCC risk (P-trend=0.043). Especially, the risk effects of rs2274223 were more evident in poor differentiation and advanced clinical stages of Kazakh ESCC. Additionally, the significantly lowest PLCE1 mRNA expression was found in the KYSE-150 cell line having no risk alleles compared with other three cell lines having risk alleles, and the normal tissues of both homozygous mutant type of PLCE1 rs12263737 and rs2274223 had a higher PLCE1 staining score than that of homozygous wild type. Our findings suggested that genetic variants in PLCE1 might serve as candidate markers for Kazakh ESCC susceptibility, and these LD variants might influence ESCC risk individually and jointly by promoting the messenger RNA and protein expression of the gene.