923 resultados para Microarray, SNPs, forensisch, Single Nucletide Polymorphisms, Multiplex
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Die Analyse tandem-repetitiver DNA-Sequenzen hat einen festen Platz als genetisches Typisierungsverfahren in den Breichen der stammesgeschichtlichen Untersuchung, der Verwandtschaftsanalyse und vor allem in der forensischen Spurenkunde, bei der es durch den Einsatz der Multiplex-PCR-Analyse von Short Tandem Repeat-Systemen (STR) zu einem Durchbruch bei der Aufklärung und sicheren Zuordnung von biologischen Tatortspuren kam. Bei der Sequenzierung des humanen Genoms liegt ein besonderes Augenmerk auf den genetisch polymorphen Sequenzvariationen im Genom, den SNPs (single nucleotide polymorphisms). Zwei ihrer Eigenschaften – das häufige Vorkommen innerhalb des humanen Genoms und ihre vergleichbar geringe Mutationsrate – machen sie zu besonders gut geeigneten Werkzeugen sowohl für die Forensik als auch für die Populationsgenetik.rnZum Ziel des EU-Projekts „SNPforID“, aus welchem die vorliegende Arbeit entstanden ist, wurde die Etablierung neuer Methoden zur validen Typisierung von SNPs in Multiplexverfahren erklärt. Die Berücksichtigung der Sensitivität bei der Untersuchung von Spuren sowie die statistische Aussagekraft in der forensischen Analyse standen dabei im Vordergrund. Hierfür wurden 52 autosomale SNPs ausgewählt und auf ihre maximale Individualisierungsstärke hin untersucht. Die Untersuchungen der ersten 23 selektierten Marker stellen den ersten Teil der vorliegenden Arbeit dar. Sie umfassen die Etablierung des Multiplexverfahrens und der SNaPshot™-Typisierungsmethode sowie ihre statistische Auswertung. Die Ergebnisse dieser Untersuchung sind ein Teil der darauf folgenden, in enger Zusammenarbeit der Partnerlaboratorien durchgeführten Studie der 52-SNP-Multiplexmethode. rnEbenfalls im Rahmen des Projekts und als Hauptziel der Dissertation erfolgten Etablierung und Evaluierung des auf der Microarray-Technologie basierenden Verfahrens der Einzelbasenverlängerung auf Glasobjektträgern. Ausgehend von einer begrenzten DNA-Menge wurde hierbei die Möglichkeit der simultanen Hybridisierung einer möglichst hohen Anzahl von SNP-Systemen untersucht. Die Auswahl der hierbei eingesetzten SNP-Marker erfolgte auf der Basis der Vorarbeiten, die für die Etablierung des 52-SNP-Multiplexes erfolgreich durchgeführt worden waren. rnAus einer Vielzahl von Methoden zur Genotypisierung von biallelischen Markern hebt sich das Assay in seiner Parallelität und der Einfachheit des experimentellen Ansatzes durch eine erhebliche Zeit- und Kostenersparnis ab. In der vorliegenden Arbeit wurde das „array of arrays“-Prinzip eingesetzt, um zur gleichen Zeit unter einheitlichen Versuchsbedingungen zwölf DNA-Proben auf einem Glasobjektträger zu typisieren. Auf der Basis von insgesamt 1419 typisierten Allelen von 33 Markern konnte die Validierung mit einem Typisierungserfolg von 86,75% abgeschlossen werden. Dabei wurden zusätzlich eine Reihe von Randbedingungen in Bezug auf das Sonden- und Primerdesign, die Hybridisierungsbedingungen sowie physikalische Parameter der laserinduzierten Fluoreszenzmessung der Signale ausgetestet und optimiert. rn
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Accurate and fast genotyping of single nucleotide polymorphisms (SNPs) is important in the human genome project. Here an automated fluorescent method that can rapidly and accurately genotype multiplex known SNPs was developed by using a homemade kit, which has lower cost but higher resolution than commercial kit. With this method, oncogene K-ras was investigated, four known SNPs of K-ras gene exon 1 in 31 coloerctal cancer patients were detected. Results indicate that mutations were present in 8(26%) of 31 patients, and most mutations were localized in codon 12. The presence of these mutations is thought to be a critical step and plays an important role in human colorectal carcinogenesisas. (C) 2003 Elsevier B.V. All rights reserved.
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A SNP genotyping method was developed for E. faecalis and E. faecium using the 'Minimum SNPs' program. SNP sets were interrogated using allele-specific real-time PCR. SNP-typing sub-divided clonal complexes 2 and 9 of E. faecalis and 17 of E. faecium, members of which cause the majority of nosocomial infections globally.
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Endometrial cancer is one of the most common female diseases in developed nations and is the most commonly diagnosed gynaecological cancer in Australia. The disease is commonly classified by histology: endometrioid or non-endometrioid endometrial cancer. While non-endometrioid endometrial cancers are accepted to be high-grade, aggressive cancers, endometrioid cancers (comprising 80% of all endometrial cancers diagnosed) generally carry a favourable patient prognosis. However, endometrioid endometrial cancer patients endure significant morbidity due to surgery and radiotherapy used for disease treatment, and patients with recurrent disease have a 5-year survival rate of less than 50%. Genetic analysis of women with endometrial cancer could uncover novel markers associated with disease risk and/or prognosis, which could then be used to identify women at high risk and for the use of specialised treatments. Proteases are widely accepted to play an important role in the development and progression of cancer. This PhD project hypothesised that SNPs from two protease gene families, the matrix metalloproteases (MMPs, including their tissue inhibitors, TIMPs) and the tissue kallikrein-related peptidases (KLKs) would be associated with endometrial cancer susceptibility and/or prognosis. In the first part of this study, optimisation of the genotyping techniques was performed. Results from previously published endometrial cancer genetic association studies were attempted to be validated in a large, multicentre replication set (maximum cases n = 2,888, controls n = 4,483, 3 studies). The rs11224561 progesterone receptor SNP (PGR, A/G) was observed to be associated with increased endometrial cancer risk (per A allele OR 1.31, 95% CI 1.12-1.53; p-trend = 0.001), a result which was initially reported among a Chinese sample set. Previously reported associations for the remaining 8 SNPs investigated for this section of the PhD study were not confirmed, thereby reinforcing the importance of validation of genetic association studies. To examine the effect of SNPs from the MMP and KLK families on endometrial cancer risk, we selected the most significantly associated MMP and KLK SNPs from genome-wide association study analysis (GWAS) to be genotyped in the GWAS replication set (cases n = 4,725, controls n = 9,803, 13 studies). The significance of the MMP24 rs932562 SNP was unchanged after incorporation of the stage 2 samples (Stage 1 per allele OR 1.18, p = 0.002; Combined Stage 1 and 2 OR 1.09, p = 0.002). The rs10426 SNP, located 3' to KLK10 was predicted by bioinformatic analysis to effect miRNA binding. This SNP was observed in the GWAS stage 1 result to exhibit a recessive effect on endometrial cancer risk, a result which was not validated in the stage 2 sample set (Stage 1 OR 1.44, p = 0.007; Combined Stage 1 and 2 OR 1.14, p = 0.08). Investigation of the regions imputed surrounding the MMP, TIMP and KLK genes did not reveal any significant targets for further analysis. Analysis of the case data from the endometrial cancer GWAS to identify genetic variation associated with cancer grade did not reveal SNPs from the MMP, TIMP or KLK genes to be statistically significant. However, the representation of SNPs from the MMP, TIMP and KLK families by the GWAS genotyping platform used in this PhD project was examined and observed to be very low, with the genetic variation of four genes (MMP23A, MMP23B, MMP28 and TIMP1) not captured at all by this technique. This suggests that comprehensive candidate gene association studies will be required to assess the role of SNPs from these genes with endometrial cancer risk and prognosis. Meta-analysis of gene expression microarray datasets curated as part of this PhD study identified a number of MMP, TIMP and KLK genes to display differential expression by endometrial cancer status (MMP2, MMP10, MMP11, MMP13, MMP19, MMP25 and KLK1) and histology (MMP2, MMP11, MMP12, MMP26, MMP28, TIMP2, TIMP3, KLK6, KLK7, KLK11 and KLK12). In light of these findings these genes should be prioritised for future targeted genetic association studies. Two SNPs located 43.5 Mb apart on chromosome 15 were observed from the GWAS analysis to be associated with increased endometrial cancer grade, results that were validated in silico in two independent datasets. One of these SNPs, rs8035725 is located in the 5' untranslated region of a MYC promoter binding protein DENND4A (Stage 1 OR 1.15, p = 9.85 x 10P -5 P, combined Stage 1 and in silico validation OR 1.13, p = 5.24 x 10P -6 P). This SNP has previously been reported to alter the expression of PTPLAD1, a gene involved in the synthesis of very long fatty acid chains and in the Rac1 signaling pathway. Meta-analysis of gene expression microarray data found PTPLAD1 to display increased expression in the aggressive non-endometrioid histology compared with endometrioid endometrial cancer, suggesting that the causal SNP underlying the observed genetic association may influence expression of this gene. Neither rs8035725 nor significant SNPs identified by imputation were predicted bioinformatically to affect transcription factor binding sites, indicating that further studies are required to assess their potential effect on other regulatory elements. The other grade- associated SNP, rs6606792, is located upstream of an inferred pseudogene, ELMO2P1 (Stage 1 OR 1.12, p = 5 x 10P -5 P; combined Stage 1 and in silico validation OR 1.09, p = 3.56 x 10P -5 P). Imputation of the ±1 Mb region surrounding this SNP revealed a cluster of significantly associated variants which are predicted to abolish various transcription factor binding sites, and would be expected to decrease gene expression. ELMO2P1 was not included on the microarray platforms collected for this PhD, and so its expression could not be investigated. However, the high sequence homology of ELMO2P1 with ELMO2, a gene important to cell motility, indicates that ELMO2 could be the parent gene for ELMO2P1 and as such, ELMO2P1 could function to regulate the expression of ELMO2. Increased expression of ELMO2 was seen to be associated with increasing endometrial cancer grade, as well as with aggressive endometrial cancer histological subtypes by microarray meta-analysis. Thus, it is hypothesised that SNPs in linkage disequilibrium with rs6606792 decrease the transcription of ELMO2P1, reducing the regulatory effect of ELMO2P1 on ELMO2 expression. Consequently, ELMO2 expression is increased, cell motility is enhanced leading to an aggressive endometrial cancer phenotype. In summary, these findings have identified several areas of research for further study. The results presented in this thesis provide evidence that a SNP in PGR is associated with risk of developing endometrial cancer. This PhD study also reports two independent loci on chromosome 15 to be associated with increased endometrial cancer grade, and furthermore, genes associated with these SNPs to be differentially expressed according in aggressive subtypes and/or by grade. The studies reported in this thesis support the need for comprehensive SNP association studies on prioritised MMP, TIMP and KLK genes in large sample sets. Until these studies are performed, the role of MMP, TIMP and KLK genetic variation remains unclear. Overall, this PhD study has contributed to the understanding of genetic variation involvement in endometrial cancer susceptibility and prognosis. Importantly, the genetic regions highlighted in this study could lead to the identification of novel gene targets to better understand the biology of endometrial cancer and also aid in the development of therapeutics directed at treating this disease.
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Single nucleotide polymorphisms (SNPs) have been classically used for dissecting various human complex disorders using candidate gene studies. During the last decade, large scale SNP analysis i.e. genome-wide association studies (GWAS) have provided an agnostic approach to identify possible genetic loci associated with heterogeneous disease such as cancer susceptibility, prognosis of survival or drug response. Further, the advent of new technologies, including microarray based genotyping as well as high throughput next generation sequencing has opened new avenues for SNPs to be used in clinical practice. It is speculated that the utility of SNPs to understand the mechanisms, biology of variable drug response and ultimately treatment individualization based on the individual’s genome composition will be indispensable in the near future. In the current review, we discuss the advantages and disadvantages of the clinical utility of genetic variants in disease risk-prediction, prognosis, clinical outcome and pharmacogenomics. The lessons and challenges for the utility of SNP based biomarkers are also discussed, including the need for additional functional validation studies.
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Luteal insufficiency affects fertility and hence study of mechanisms that regulate corpus luteum (CL) function is of prime importance to overcome infertility problems. Exploration of human genome sequence has helped to study the frequency of single nucleotide polymorphisms (SNPs). Clinical benefits of screening SNPs in infertility are being recognized well in recent times. Examining SNPs in genes associated with maintenance and regression of CL may help to understand unexplained luteal insufficiency and related infertility. Publicly available microarray gene expression databases reveal the global gene expression patterns in primate CL during the different functional state. We intend to explore computationally the deleterious SNPs of human genes reported to be common targets of luteolysin and luteotropin in primate CL Different computational algorithms were used to dissect out the functional significance of SNPs in the luteinizing hormone sensitive genes. The results raise the possibility that screening for SNPs might be integrated to evaluate luteal insufficiency associated with human female infertility for future studies. (C) 2012 Elsevier B.V. All rights reserved,
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SNPNB is a user-friendly and platform-independent application for analyzing Single Nucleotide Polymorphism NeighBoring sequence context and nucleotide bias patterns, and subsequently evaluating the effective SNP size for the bias patterns observed from the whole data. It was implemented by Java and Perl. SNPNB can efficiently handle genome-wide or chromosome-wide SNP data analysis in a PC or a workstation. It provides visualizations of the bias patterns for SNPs or each type of SNPs.
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We report here for the first time 12 polymorphic single nucleotide polymorphisms (SNPs) in a commercially important gastropod, Pacific abalone (Haliotis discus hannai) that were identified by searching expressed sequence tag database. These SNP loci (seven nuclear and five mitochondrial SNPs) were polymorphic among 37 wild abalone individuals, based on a four-primer allele-specific polymerase chain reaction analysis. All loci had two alleles and the minor allele frequency ranged from 0.027 to 0.473. For the seven nuclear SNPs, the expected and observed heterozygosities ranged from 0.053 to 0.499 and from 0.054 to 0.811, respectively.
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Most of the cultivated species of citrus have narrow genetic basis. Relationships among species and cultivars are obscured by sexual compatibility, polyembryony, apomixis and a high incidence of somatic mutations. DNA analysis is crucial in genetic studies not only for citrus breeding programs but also for characterization of hybrids and species. In this paper, single nucleotide polymorphisms ( SNPs) were investigated in 58 accessions of Citrus, hybrids and related genera. Genomic sequences of 'Pera IAC' sweet orange ( Citrus sinensis L. Osbeck) were used for primer design and selection of sequence tagged sites (STSs) for identification of SNPs. Analysis of 36 STSs showed identical sequences among 40 of the 41 sweet orange accessions studied. However, these accessions were heterozygous for many SNPs. Ten selected STSs were analyzed in 17 additional accessions from 13 species and hybrids. Comparing to the 'Pera IAC' sweet orange accession, a total of 150 polymorphic nucleotides were identified and most of the alterations were transitions ( 52.7%). The greatest number of SNPs was observed in Poncirus trifoliata ( L.) Raf. and the smallest in 'Ponkan' mandarin ( Citrus reticulata Blanco). At the intra-specific level, 'Bafa Gigante' ( Citrus sinensis L. Osbeck) was the only sweet orange accession with a divergent SNPs genotype, which corroborates the hypothesis of a hybrid origin for this accession. Although the STSs analyzed represent randomly sampled genomic sequences, they provided consistent information about the level of polymorphism and showed the potential of SNPs markers for characterization and phylogenetic studies.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Single nucleotide polymorphisms (SNPs) may be used in biodiversity studies and commercial tasks like traceability, paternity testing and selection for suitable genotypes. Twenty-seven SNPs were characterized and genotyped on 250 individuals belonging to eight Italian goat breeds. Multilocus genotype data were used to infer population structure and assign individuals to populations. To estimate the number of groups (K) to test in population structure analysis we used likelihood values and variance of the bootstrap samples, deriving optimal K from a drop in the likelihood and a rise in the variance plots against K.
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Systemic sclerosis (SSc) or Scleroderma is a complex disease and its etiopathogenesis remains unelucidated. Fibrosis in multiple organs is a key feature of SSc and studies have shown that transforming growth factor-β (TGF-β) pathway has a crucial role in fibrotic responses. For a complex disease such as SSc, expression quantitative trait loci (eQTL) analysis is a powerful tool for identifying genetic variations that affect expression of genes involved in this disease. In this study, a multilevel model is described to perform a multivariate eQTL for identifying genetic variation (SNPs) specifically associated with the expression of three members of TGF-β pathway, CTGF, SPARC and COL3A1. The uniqueness of this model is that all three genes were included in one model, rather than one gene being examined at a time. A protein might contribute to multiple pathways and this approach allows the identification of important genetic variations linked to multiple genes belonging to the same pathway. In this study, 29 SNPs were identified and 16 of them located in known genes. Exploring the roles of these genes in TGF-β regulation will help elucidate the etiology of SSc, which will in turn help to better manage this complex disease. ^