Increased Frequency of De Novo Copy Number Variations in Congenital Heart Disease by Integrative Analysis of SNP Array and Exome Sequence Data.
Circ Res. 2014 Sep 9;
Authors: Glessner J, Bick AG, Ito K, Homsy J, Rodriguez-Murillo L, Fromer M, Mazaika EJ, Vardarajan B, Italia MJ, Leipzig J, DePalma S, Golhar R, Sanders SJ, Yamrom B, Ronemus M, Iossifov I, Willsey AJ, State MW, Kaltman JR, White PS, Shen Y, Warburton D, Brueckner M, Seidman C, Goldmuntz E, Gelb BD, Lifton R, Seidman JG, Hakonarson H, Chung WK
Rationale: Congenital heart disease (CHD) is among the most common birth defects. Most cases are of unknown etiology. Objective: To determine the contribution of de novo copy number variants (CNVs) in the etiology of sporadic CHD. Methods and Results: We studied 538 CHD trios using genome-wide dense single nucleotide polymorphism (SNP) arrays and/or whole exome sequencing (WES). Results were experimentally validated using digital droplet PCR. We compared validated CNVs in CHD cases to CNVs in 1,301 healthy control trios. The two complementary high-resolution technologies identified 63 validated de novo CNVs in 51 CHD cases. A significant increase in CNV burden was observed when comparing CHD trios with healthy trios, using either SNP array (p=7x10-5, Odds Ratio (OR)=4.6) or WES data (p=6x10-4, OR=3.5) and remained after removing 16% of de novo CNV loci previously reported as pathogenic (p=0.02, OR=2.7). We observed recurrent de novo CNVs on 15q11.2 encompassing CYFIP1, NIPA1, and NIPA2 and single de novo CNVs encompassing DUSP1, JUN, JUP, MED15, MED9, PTPRE SREBF1, TOP2A, and ZEB2, genes that interact with established CHD proteins NKX2-5 and GATA4. Integrating de novo variants in WES and CNV data suggests that ETS1 is the pathogenic gene altered by 11q24.2-q25 deletions in Jacobsen syndrome and that CTBP2 is the pathogenic gene in 10q sub-telomeric deletions. Conclusions: We demonstrate a significantly increased frequency of rare de novo CNVs in CHD patients compared with healthy controls and suggest several novel genetic loci for CHD.
PMID: 25205790 [PubMed - as supplied by publisher]
Immunochip SNP array identifies novel genetic variants conferring susceptibility to candidaemia.
Nat Commun. 2014;5:4675
Authors: Kumar V, Cheng SC, Johnson MD, Smeekens SP, Wojtowicz A, Giamarellos-Bourboulis E, Karjalainen J, Franke L, Withoff S, Plantinga TS, van de Veerdonk FL, van der Meer JW, Joosten LA, Sokol H, Bauer H, Herrmann BG, Bochud PY, Marchetti O, Perfect JR, Xavier RJ, Kullberg BJ, Wijmenga C, Netea MG
Candidaemia is the fourth most common cause of bloodstream infection, with a high mortality rate of up to 40%. Identification of host genetic factors that confer susceptibility to candidaemia may aid in designing adjunctive immunotherapeutic strategies. Here we hypothesize that variation in immune genes may predispose to candidaemia. We analyse 118,989 single-nucleotide polymorphisms (SNPs) across 186 loci known to be associated with immune-mediated diseases in the largest candidaemia cohort to date of 217 patients of European ancestry and a group of 11,920 controls. We validate the significant associations by comparison with a disease-matched control group. We observe significant association between candidaemia and SNPs in the CD58 (P=1.97 × 10(-11); odds ratio (OR)=4.68), LCE4A-C1orf68 (P=1.98 × 10(-10); OR=4.25) and TAGAP (P=1.84 × 10(-8); OR=2.96) loci. Individuals carrying two or more risk alleles have an increased risk for candidaemia of 19.4-fold compared with individuals carrying no risk allele. We identify three novel genetic risk factors for candidaemia, which we subsequently validate for their role in antifungal host defence.
PMID: 25197941 [PubMed - as supplied by publisher]
A high-throughput SNP array in the amphidiploid species Brassica napus shows diversity in resistance genes.
Funct Integr Genomics. 2014 Aug 22;
Authors: Dalton-Morgan J, Hayward A, Alamery S, Tollenaere R, Mason AS, Campbell E, Patel D, Lorenc MT, Yi B, Long Y, Meng J, Raman R, Raman H, Lawley C, Edwards D, Batley J
Single-nucleotide polymorphisms (SNPs)are molecular markers based on nucleotide variation and can be used for genotyping assays across populations and to track genomic inheritance. SNPs offer a comprehensive genotyping alternative to whole-genome sequencing for both agricultural and research purposes including molecular breeding and diagnostics, genome evolution and genetic diversity analyses, genetic mapping, and trait association studies. Here genomic SNPs were discovered between four cultivars of the important amphidiploid oilseed species Brassica napus and used to develop a B. napus Infinium™ array containing 5,306 SNPs randomly dispersed across the genome. Assay success was high, with >94 % of these producing a reproducible, polymorphic genotype in the 1,070 samples screened. Although the assay was designed to B. napus, successful SNP amplification was achieved in the B. napus progenitor species, Brassica rapa and Brassica oleracea, and to a lesser extent in the related species Brassica nigra. Phylogenetic analysis was consistent with the expected relationships between B. napus individuals. This study presents an efficient custom SNP assay development pipeline in the complex polyploid Brassica genome and demonstrates the utility of the array for high-throughput genotyping in a number of related Brassica species. It also demonstrates the utility of this assay in genotyping resistance genes on chromosome A7, which segregate amongst the 1,070 samples.
PMID: 25147024 [PubMed - as supplied by publisher]
Pharmacogenomics: accessing important alleles by imputation from commercial genome-wide SNP arrays.
Genet Mol Res. 2014;13(3):5713-21
Authors: Liboredo R, Pena SD
Personalized medicine is becoming a medical reality, as important genotype-phenotype relationships are being unraveled. The availability of pharmacogenomic data is a key element of individualized care. In this study, we explored genotype imputation as a means to infer important pharmacogenomic alleles from a regular commercially available genome-wide SNP array. Using these arrays as a starting point can reduce testing costs, increasing access to these pharmacogenomic data and still retain a larger amount of genome-wide information. IMPUTE2 and MaCH-Admix were used to perform genotype imputation with a dense reference panel from 1000 Genomes data. We were able to correctly infer genotypes for the warfarin-related loci VKORC1 and CYP2C9 alleles *2, *3, *5, and *11 and also clopidogrel-related CYP2C19 alleles *2 and *17 for a small sample of Brazilian individuals, as well as for HapMap samples. The success of an imputation approach in admixed samples using publicly available reference panels can encourage further imputation initiatives in those populations.
PMID: 25117329 [PubMed - in process]