Paternal or Maternal Uniparental Disomy of Chromosome 16 Resulting in Homozygosity of a Mutant Allele Causes Fanconi Anemia.
Hum Mutat. 2016 Feb 3;
Authors: Donovan FX, Kimble DC, Kim Y, Lach FP, Harper U, Kamat A, Jones M, Sanborn EM, Tryon R, Wagner JE, MacMillan ML, Ostrander EA, Auerbach AD, Smogorzewska A, Chandrasekharappa SC
Fanconi anemia (FA) is a rare inherited disorder caused by pathogenic variants in one of 19 FANC genes. FA patients display congenital abnormalities, and develop bone marrow failure, and cancer susceptibility. We identified homozygous mutations in four FA patients and, in each case, only one parent carried the obligate mutant allele. FANCA and FANCP/SLX4 genes, both located on chromosome 16, were the affected recessive FA genes in three and one family respectively. Genotyping with short tandem repeat markers and single nucleotide polymorphism (SNP) arrays revealed uniparental disomy (UPD) of the entire mutation-carrying chromosome 16 in all four patients. One FANCA patient had paternal UPD, whereas FA in the other three patients resulted from maternal UPD. These are the first reported cases of UPD as a cause of FA. UPD indicates a reduced risk of having another child with FA in the family and has implications in prenatal diagnosis. This article is protected by copyright. All rights reserved.
PMID: 26841305 [PubMed - as supplied by publisher]
Genetic variation in vascular endothelial growth factor gene and its association with recurrent spontaneous abortion.
Bratisl Lek Listy. 2016;117(2):80-6
Authors: Saboori S, Noormohammadi Z, Zare-Karizi S
BACKGROUND: Vascular endothelial growth factor (VEGF) plays a main role in fetal and placental angiogenesis and is secreted by different cells of endometrium and placenta.
OBJECTIVE: In the present study we investigated the association of VEGF gene polymorphisms with recurrent spontaneous abortion (RSA).
METHODS: A case-control study of 100 women with at least two consecutive pregnancy losses before 20 weeks of gestational age and 100 fertile controls was performed to evaluate four VEGF gene polymorphisms including + 936C/T (rs3025039), -154G>A (rs1570360), rs3025010 and +5092A/C (rs2146323). Genotyping was performed by PCR based restriction fragment length polymorphism (PCR-RFLP) analysis. Haplotype frequency was estimated for three SNPs' genotypes. Analysis of genetic STRUCTURE and K means clustering were performed to estimate genetic variation.
RESULTS: We found an association between -154G/A heterozygous genotype (GA) and RSA. The VEGF single nucleotide polymorphism (SNP) in intron region (rs3025010) in different inheritance models was also associated with RSA. Linkage disequilibrium analysis revealed that VEGF SNP in intron 5 (rs3025010) was linked to promoter region SNP (rs1570360). Cluster analysis including Neighbor Joining and K-means clustering supported genetic differentiation of women with RSA and controls.
CONCLUSION: Allelic polymorphisms in common VEGF SNPs was associated with RSA samples and haplotypes with at least one minor allele showing an association with RSA pathogenesis (Tab. 8, Fig. 2, Ref. 35).
PMID: 26830037 [PubMed - in process]
Impact of imputation methods on the amount of genetic variation captured by a single-nucleotide polymorphism panel in soybeans.
BMC Bioinformatics. 2016;17(1):55
Authors: Xavier A, Muir WM, Rainey KM
BACKGROUND: Success in genome-wide association studies and marker-assisted selection depends on good phenotypic and genotypic data. The more complete this data is, the more powerful will be the results of analysis. Nevertheless, there are next-generation technologies that seek to provide genotypic information in spite of great proportions of missing data. The procedures these technologies use to impute genetic data, therefore, greatly affect downstream analyses. This study aims to (1) compare the genetic variance in a single-nucleotide polymorphism panel of soybean with missing data imputed using various methods, (2) evaluate the imputation accuracy and post-imputation quality associated with these methods, and (3) evaluate the impact of imputation method on heritability and the accuracy of genome-wide prediction of soybean traits. The imputation methods we evaluated were as follows: multivariate mixed model, hidden Markov model, logical algorithm, k-nearest neighbor, single value decomposition, and random forest. We used raw genotypes from the SoyNAM project and the following phenotypes: plant height, days to maturity, grain yield, and seed protein composition.
RESULTS: We propose an imputation method based on multivariate mixed models using pedigree information. Our methods comparison indicate that heritability of traits can be affected by the imputation method. Genotypes with missing values imputed with methods that make use of genealogic information can favor genetic analysis of highly polygenic traits, but not genome-wide prediction accuracy. The genotypic matrix captured the highest amount of genetic variance when missing loci were imputed by the method proposed in this paper.
CONCLUSIONS: We concluded that hidden Markov models and random forest imputation are more suitable to studies that aim analyses of highly heritable traits while pedigree-based methods can be used to best analyze traits with low heritability. Despite the notable contribution to heritability, advantages in genomic prediction were not observed by changing the imputation method. We identified significant differences across imputation methods in a dataset missing 20 % of the genotypic values. It means that genotypic data from genotyping technologies that provide a high proportion of missing values, such as GBS, should be handled carefully because the imputation method will impact downstream analysis.
PMID: 26830693 [PubMed - in process]
Polymorphisms in RAD51 and their relation with breast cancer in Saudi females.
Onco Targets Ther. 2016;9:269-77
Authors: Tulbah S, Alabdulkarim H, Alanazi M, Parine NR, Shaik J, Pathan AA, Al-Amri A, Khan W, Warsy A
The present study aimed at investigating the relationship between rs1801320 (G>C), rs1801321 (G>T), and rs2619681 (C>T) RAD51 gene polymorphisms and the risk of breast cancer development in Saudi females. The genotypes were analyzed using TaqMan genotyping assay and polymerase chain reaction-restriction fragment length polymorphism. The genotype and allele frequencies were computed using chi-square or Fisher's exact test (two-tailed) by SPSS 21 software. The results showed that rs1801321G>T GG genotype and G allele frequency were strongly (P<0.0001) related to an elevated risk of breast cancer, while the mutant T allele appeared to provide protection against breast cancer development as observed from the significantly lower (P<0.0001) frequencies of the TT and GT genotypes in cancer patients compared to the healthy controls. The variant rs1801320G>C showed no significant differences in the frequencies of the genotypes and alleles in the patients and the control groups. The CC genotype and C allele frequency of rs2619681 (C>T) variant were significantly (P=0.012) higher in cancer patients, whereas the T allele showed a protective effect against cancer development. The frequencies of the three single-nucleotide polymorphisms did not differ in cancer patients with different tumor grades and human epidermal growth factor receptor 2 status (+ or -). However, the genotype frequency of rs1801320 (135G>C) differed in the patients with estrogen receptor (ER)+ and ER-, where CC genotype showed a significantly higher prevalence in the females with ER- who were suffering from breast cancer. In addition, the frequency of C allele of rs2619681 (C>T) was also significantly higher in the breast cancer patients who were ER+ and progesterone receptor (PR)+ compared to those with ER- and PR-. In the Saudi females, rs1801320 did not show an association with risk of breast cancer. Taken together, the results suggest that RAD51 rs1801321 polymorphism may be involved in the etiology of breast cancer in the Saudi females; however, further studies are necessary to confirm this relation.
PMID: 26834486 [PubMed]