Investigating the utility of combining Φ29 whole genome amplification and highly multiplexed single nucleotide polymorphism BeadArray™ genotyping

BACKGROUND: Sustainable DNA resources and reliable high-throughput genotyping methods are required for large-scale, long-term genetic association studies. In the genetic dissection of common disease it is now recognised that thousands of samples and hundreds of thousands of markers, mostly single nucleotide polymorphisms (SNPs), will have to be analysed. In order to achieve these aims, both an ability to boost quantities of archived DNA and to genotype at low costs are highly desirable. We have investigated Φ29 polymerase Multiple Displacement Amplification (MDA)-generated DNA product (MDA product), in combination with highly multiplexed BeadArray™ genotyping technology. As part of a large-scale BeadArray genotyping experiment we made a direct comparison of genotyping data generated from MDA product with that from genomic DNA (gDNA) templates. RESULTS: Eighty-six MDA product and the corresponding 86 gDNA samples were genotyped at 345 SNPs and a concordance rate of 98.8% was achieved. The BeadArray sample exclusion rate, blind to sample type, was 10.5% for MDA product compared to 5.8% for gDNA. CONCLUSIONS: We conclude that the BeadArray technology successfully produces high quality genotyping data from MDA product. The combination of these technologies improves the feasibility and efficiency of mapping common disease susceptibility genes despite limited stocks of gDNA samples

Analysis of polymorphisms in 16 genes in type 1 diabetes that have been associated with other immune-mediated diseases.

BACKGROUND: The identification of the HLA class II, insulin (INS), CTLA-4 and PTPN22 genes as determinants of type 1 diabetes (T1D) susceptibility indicates that fine tuning of the immune system is centrally involved in disease development. Some genes have been shown to affect several immune-mediated diseases. Therefore, we tested the hypothesis that alleles of susceptibility genes previously associated with other immune-mediated diseases might perturb immune homeostasis, and hence also associate with predisposition to T1D. METHODS: We resequenced and genotyped tag single nucleotide polymorphisms (SNPs) from two genes, CRP and FCER1B, and genotyped 27 disease-associated polymorphisms from thirteen gene regions, namely FCRL3, CFH, SLC9A3R1, PADI4, RUNX1, SPINK5, IL1RN, IL1RA, CARD15, IBD5-locus (including SLC22A4), LAG3, ADAM33 and NFKB1. These genes have been associated previously with susceptibility to a range of immune-mediated diseases including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Graves' disease (GD), psoriasis, psoriatic arthritis (PA), atopy, asthma, Crohn disease and multiple sclerosis (MS). Our T1D collections are divided into three sample subsets, consisting of set 1 families (up to 754 families), set 2 families (up to 743 families), and a case-control collection (ranging from 1,500 to 4,400 cases and 1,500 to 4,600 controls). Each SNP was genotyped in one or more of these subsets. Our study typically had approximately 80% statistical power for a minor allele frequency (MAF) >5% and odds ratios (OR) of 1.5 with the type 1 error rate, alpha = 0.05. RESULTS: We found no evidence of association with T1D at most of the loci studied 0.02 <P < 1.0. Only a SNP in ADAM33, rs2787094, was any evidence of association obtained, P = 0.0004 in set 1 families (relative risk (RR) = 0.78), but further support was not observed in the 4,326 cases and 4,610 controls, P = 0.57 (OR = 1.02). CONCLUSION: Polymorphisms in a variety of genes previously associated with immune-mediated disease susceptibility and/or having effects on gene function and the immune system, are unlikely to be affecting T1D susceptibility in a major way, even though some of the genes tested encode proteins of immune pathways that are believed to be central to the development of T1D. We cannot, however, rule out effect sizes smaller than OR 1.5

Development of an integrated genome informatics, data management and workflow infrastructure: a toolbox for the study of complex disease genetics.

The genetic dissection of complex disease remains a significant challenge. Sample-tracking and the recording, processing and storage of high-throughput laboratory data with public domain data, require integration of databases, genome informatics and genetic analyses in an easily updated and scaleable format. To find genes involved in multifactorial diseases such as type 1 diabetes (T1D), chromosome regions are defined based on functional candidate gene content, linkage information from humans and animal model mapping information. For each region, genomic information is extracted from Ensembl, converted and loaded into ACeDB for manual gene annotation. Homology information is examined using ACeDB tools and the gene structure verified. Manually curated genes are extracted from ACeDB and read into the feature database, which holds relevant local genomic feature data and an audit trail of laboratory investigations. Public domain information, manually curated genes, polymorphisms, primers, linkage and association analyses, with links to our genotyping database, are shown in Gbrowse. This system scales to include genetic, statistical, quality control (QC) and biological data such as expression analyses of RNA or protein, all linked from a genomics integrative display. Our system is applicable to any genetic study of complex disease, of either large or small scale.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Construction and analysis of tag single nucleotide polymorphism maps for six human-mouse orthologous candidate genes in type 1 diabetes.

BACKGROUND: One strategy to help identify susceptibility genes for complex, multifactorial diseases is to map disease loci in a representative animal model of the disorder. The nonobese diabetic (NOD) mouse is a model for human type 1 diabetes. Linkage and congenic strain analyses have identified several NOD mouse Idd (insulin dependent diabetes) loci, which have been mapped to small chromosome intervals, for which the orthologous regions in the human genome can be identified. Here, we have conducted re-sequencing and association analysis of six orthologous genes identified in NOD Idd loci: NRAMP1/SLC11A1 (orthologous to Nramp1/Slc11a1 in Idd5.2), FRAP1 (orthologous to Frap1 in Idd9.2), 4-1BB/CD137/TNFRSF9 (orthologous to 4-1bb/Cd137/Tnrfrsf9 in Idd9.3), CD101/IGSF2 (orthologous to Cd101/Igsf2 in Idd10), B2M (orthologous to B2m in Idd13) and VAV3 (orthologous to Vav3 in Idd18). RESULTS: Re-sequencing of a total of 110 kb of DNA from 32 or 96 type 1 diabetes cases yielded 220 single nucleotide polymorphisms (SNPs). Sixty-five SNPs, including 54 informative tag SNPs, and a microsatellite were selected and genotyped in up to 1,632 type 1 diabetes families and 1,709 cases and 1,829 controls. CONCLUSION: None of the candidate regions showed evidence of association with type 1 diabetes (P values > 0.2), indicating that common variation in these key candidate genes does not play a major role in type 1 diabetes susceptibility in the European ancestry populations studied.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Analysis of polymorphisms in 16 genes in type 1 diabetes that have been associated with other immune-mediated diseases.

BACKGROUND: The identification of the HLA class II, insulin (INS), CTLA-4 and PTPN22 genes as determinants of type 1 diabetes (T1D) susceptibility indicates that fine tuning of the immune system is centrally involved in disease development. Some genes have been shown to affect several immune-mediated diseases. Therefore, we tested the hypothesis that alleles of susceptibility genes previously associated with other immune-mediated diseases might perturb immune homeostasis, and hence also associate with predisposition to T1D. METHODS: We resequenced and genotyped tag single nucleotide polymorphisms (SNPs) from two genes, CRP and FCER1B, and genotyped 27 disease-associated polymorphisms from thirteen gene regions, namely FCRL3, CFH, SLC9A3R1, PADI4, RUNX1, SPINK5, IL1RN, IL1RA, CARD15, IBD5-locus (including SLC22A4), LAG3, ADAM33 and NFKB1. These genes have been associated previously with susceptibility to a range of immune-mediated diseases including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Graves' disease (GD), psoriasis, psoriatic arthritis (PA), atopy, asthma, Crohn disease and multiple sclerosis (MS). Our T1D collections are divided into three sample subsets, consisting of set 1 families (up to 754 families), set 2 families (up to 743 families), and a case-control collection (ranging from 1,500 to 4,400 cases and 1,500 to 4,600 controls). Each SNP was genotyped in one or more of these subsets. Our study typically had approximately 80% statistical power for a minor allele frequency (MAF) >5% and odds ratios (OR) of 1.5 with the type 1 error rate, alpha = 0.05. RESULTS: We found no evidence of association with T1D at most of the loci studied 0.02 <P < 1.0. Only a SNP in ADAM33, rs2787094, was any evidence of association obtained, P = 0.0004 in set 1 families (relative risk (RR) = 0.78), but further support was not observed in the 4,326 cases and 4,610 controls, P = 0.57 (OR = 1.02). CONCLUSION: Polymorphisms in a variety of genes previously associated with immune-mediated disease susceptibility and/or having effects on gene function and the immune system, are unlikely to be affecting T1D susceptibility in a major way, even though some of the genes tested encode proteins of immune pathways that are believed to be central to the development of T1D. We cannot, however, rule out effect sizes smaller than OR 1.5

Construction and analysis of tag single nucleotide polymorphism maps for six human-mouse orthologous candidate genes in type 1 diabetes.

BACKGROUND: One strategy to help identify susceptibility genes for complex, multifactorial diseases is to map disease loci in a representative animal model of the disorder. The nonobese diabetic (NOD) mouse is a model for human type 1 diabetes. Linkage and congenic strain analyses have identified several NOD mouse Idd (insulin dependent diabetes) loci, which have been mapped to small chromosome intervals, for which the orthologous regions in the human genome can be identified. Here, we have conducted re-sequencing and association analysis of six orthologous genes identified in NOD Idd loci: NRAMP1/SLC11A1 (orthologous to Nramp1/Slc11a1 in Idd5.2), FRAP1 (orthologous to Frap1 in Idd9.2), 4-1BB/CD137/TNFRSF9 (orthologous to 4-1bb/Cd137/Tnrfrsf9 in Idd9.3), CD101/IGSF2 (orthologous to Cd101/Igsf2 in Idd10), B2M (orthologous to B2m in Idd13) and VAV3 (orthologous to Vav3 in Idd18). RESULTS: Re-sequencing of a total of 110 kb of DNA from 32 or 96 type 1 diabetes cases yielded 220 single nucleotide polymorphisms (SNPs). Sixty-five SNPs, including 54 informative tag SNPs, and a microsatellite were selected and genotyped in up to 1,632 type 1 diabetes families and 1,709 cases and 1,829 controls. CONCLUSION: None of the candidate regions showed evidence of association with type 1 diabetes (P values > 0.2), indicating that common variation in these key candidate genes does not play a major role in type 1 diabetes susceptibility in the European ancestry populations studied.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Localization of a Type 1 Diabetes Locus in the IL2RA/CD25 Region by Use of Tag Single-Nucleotide Polymorphisms

As part of an ongoing search for genes associated with type 1 diabetes (T1D), a common autoimmune disease, we tested the biological candidate gene IL2RA (CD25), which encodes a subunit (IL-2Rα) of the high-affinity interleukin-2 (IL-2) receptor complex. We employed a tag single-nucleotide polymorphism (tag SNP) approach in large T1D sample collections consisting of 7,457 cases and controls and 725 multiplex families. Tag SNPs were analyzed using a multilocus test to provide a regional test for association. We found strong statistical evidence in the case-control collection (P=6.5×10(-8)) for a T1D locus in the CD25 region of chromosome 10p15 and replicated the association in the family collection (P=7.3×10(-3); combined P=1.3×10(-10)). These results illustrate the utility of tag SNPs in a chromosome-regional test of disease association and justify future fine mapping of the causal variant in the region

Development of an integrated genome informatics, data management and workflow infrastructure: A toolbox for the study of complex disease genetics

Abstract The genetic dissection of complex disease remains a significant challenge. Sample-tracking and the recording, processing and storage of high-throughput laboratory data with public domain data, require integration of databases, genome informatics and genetic analyses in an easily updated and scaleable format. To find genes involved in multifactorial diseases such as type 1 diabetes (T1D), chromosome regions are defined based on functional candidate gene content, linkage information from humans and animal model mapping information. For each region, genomic information is extracted from Ensembl, converted and loaded into ACeDB for manual gene annotation. Homology information is examined using ACeDB tools and the gene structure verified. Manually curated genes are extracted from ACeDB and read into the feature database, which holds relevant local genomic feature data and an audit trail of laboratory investigations. Public domain information, manually curated genes, polymorphisms, primers, linkage and association analyses, with links to our genotyping database, are shown in Gbrowse. This system scales to include genetic, statistical, quality control (QC) and biological data such as expression analyses of RNA or protein, all linked from a genomics integrative display. Our system is applicable to any genetic study of complex disease, of either large or small scale.</p