959 resultados para Candidate genes
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Target region amplification polymorphism (TRAP) markers were used to estimate the genetic similarity (GS) among 53 sugarcane varieties and five species of the Saccharum complex. Seven fixed primers designed from candidate genes involved in sucrose metabolism and three from those involved in drought response metabolism were used in combination with three arbitrary primers. The clustering of the genotypes for sucrose metabolism and drought response were similar, but the GS based on Jaccard`s coefficient changed. The GS based on polymorphism in sucrose genes estimated in a set of 46 Brazilian varieties, all of which belong to the three Brazilian breeding programs, ranged from 0.52 to 0.9, and that based on drought data ranged from 0.44 to 0.95. The results suggest that genetic variability in the evaluated genes was lower in the sucrose metabolism genes than in the drought response metabolism ones.
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Background: A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term patholog to mean a homolog of a human disease-related gene encoding a product ( transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. Results: Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity ( 70 - 85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool ( FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic ( 53%), hereditary ( 24%), immunological ( 5%), cardio-vascular (4%), or other (14%), disorders. Conclusions: Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.
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Considering that the importance of cancer/testis (CT) antigens in multiple myeloma (MM) biology is still under investigation, the present study aimed to: (1) identify genes differentially expressed in MM using microarray analysis of plasma cell samples, separated according to the number of expressed CTs; (2) examine possible pathways related to MM pathogenesis; (3) validate the expression of candidate genes by quantitative real-time PCR (RQ-PCR). Three samples predominantly positive (>6 expressed), including the U266 cell line, and three samples predominantly negative (0 or 1 expressed CT for the 13 analyzed CT antigens), were submitted for microarray analysis. Validation by RQ-PCR from 24 MM samples showed that the ITGAS gene was downregulated in predominantly positive (>6 expressed CTs, p = 0.0030) and in tumor versus normal plasma cells (p = 0.0182). The RhoD gene was overexpressed in tumor plasma cells when compared to normal plasma cells (p = 0.0339). Results of the microarray analysis corroborate the hypothesis that MM could be separated into predominantly positive and predominantly negative expression. The differential expression of ITGA5 and RhoD suggests disruption of the focal adhesion pathway in MM and offers a new target field to be explored in this disease.
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Resumo: Cinco genes candidatos foram selecionados para identificar polimorfismos de nucleotídeo único e sua associação com a resposta de caprinos a nematoides gastrintestinais. Para isso, o DNA genômico dos animais mais resistentes e mais susceptíveis foi extraído e submetido ao sequenciamento de nova geração. Foram observados 71 SNPs, sendo 4 associados à resistência, o que os tornam alvos de estudos em toda a população de caprinos a fim de se confirmar essa associação. [Polymorphisms in IL-2, IL-5, IL-8, IL-12 e IFN-y genes and the response to gastrointestinal nematode in goats]. Abstract: Five candidate genes were selected to identify single nucleotide polymorphisms and its association with goat response to gastrointestinal nematodes. Genomic DNA from resistant and susceptible animals was extracted and submitted to new generation sequencing. It was observed 71 SNPs with 4 associated with resistance, which make them targets for studies on the entire population goats in order to confirm this association.
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OBJECTIVE: To assess the relationships and possible interactions between polymorphisms related to HDL levels and alcohol consumption. METHODS: Cross-sectional population-based study including 2863 women and 2546 men aged 35-75 years (CoLaus study). Alcohol intake was assessed by the reported alcohol consumption of the last 7 days. Nineteen candidate genes known to influence HDL levels were studied. RESULTS: Alcohol consumption increased HDL cholesterol levels in both genders. After multivariate adjustment for gender, age, body mass index, smoking, hypolipidaemic drug treatment, physical activity and alcohol consumption, APOA5, CETP, LIPC and LPL gene polymorphisms were significantly (10(-5) threshold) related with HDL cholesterol levels, while no genexalcohol intake interaction was found for all SNPs studied. ABCA1 polymorphisms were related to HDL cholesterol levels on bivariate analysis but the relationship was no longer significant after multivariate analysis. CONCLUSION: Our data confirm the association of alcohol consumption and of APOA5, CETP, LIPC and LPL gene polymorphisms with HDL cholesterol levels. Conversely, no genexalcohol consumption interactions were found, suggesting that the effect of alcohol consumption on HDL cholesterol levels is not mediated via a modulation of HDL related genes.
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DNA methylation has an important impact on normal cell physiology, thus any defects in this mechanism may be related to the development of various diseases In this project we are interested in identifying epigeneticaliy modified genes, in general controlled by processes related to the DNA methylation, by means of a new strategy combining protomic and genomic analyses. First, the two Dimensional-Difference Gel Electrophoresis (2-DIGE) protein analyses of extracts obtained from HCT-116 wt and double knockout for DNMT1 and DNMT3b (DKO) cells revealed 34 proteins overexpressed in the condition of DNMTs depletion. From five genes with higher transcript lavels in DKO cells, comparing with HCT-116 wt. oniy AKR1B1, UCHLl and VIM are melhylated in HCT-116. As expected. the DNA methvlation 1s lost in DKO cells. The rneth,vl ation of VIM and UCHLl promoters in some cancer samples has already been repaired, thus further studies has been focused on AKRlBI. AKR1B1 expression due lo DNA methyiaton of promoter region seems to occur specilfically in the colon cancer cell Iines. which was confirmed in the DNA rnethylation status and expression analyses. performed on 32 different cancer cell lines (including colon, breast, lymphoma, leukemia, neuroblastoma, glioma and lung cancer cell Iines) as well as normal colon and normal lymphocytes samples. AKRIBI expression after treatments with DNA demethvlating agent (AZA) was rescued in 5 coloncancer cell lines (including genetic regulation of the candidate gene. The methylation status of the rest of the genes identified in proteomic analysis was checked by methylation specific PCR (MSP) experiment and all appeared to be unmethylated. The similar research has been done also bv means of Mecp2-null mouse model For 14 selected candidate genes the analyses of expression leveis, methylation Status and MeCP2 interaction with promoters are currently being performed.
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Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.
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Cancer genomes frequently contain somatic copy number alterations (SCNA) that can significantly perturb the expression level of affected genes and thus disrupt pathways controlling normal growth. In melanoma, many studies have focussed on the copy number and gene expression levels of the BRAF, PTEN and MITF genes, but little has been done to identify new genes using these parameters at the genome-wide scale. Using karyotyping, SNP and CGH arrays, and RNA-seq, we have identified SCNA affecting gene expression ('SCNA-genes') in seven human metastatic melanoma cell lines. We showed that the combination of these techniques is useful to identify candidate genes potentially involved in tumorigenesis. Since few of these alterations were recurrent across our samples, we used a protein network-guided approach to determine whether any pathways were enriched in SCNA-genes in one or more samples. From this unbiased genome-wide analysis, we identified 28 significantly enriched pathway modules. Comparison with two large, independent melanoma SCNA datasets showed less than 10% overlap at the individual gene level, but network-guided analysis revealed 66% shared pathways, including all but three of the pathways identified in our data. Frequently altered pathways included WNT, cadherin signalling, angiogenesis and melanogenesis. Additionally, our results emphasize the potential of the EPHA3 and FRS2 gene products, involved in angiogenesis and migration, as possible therapeutic targets in melanoma. Our study demonstrates the utility of network-guided approaches, for both large and small datasets, to identify pathways recurrently perturbed in cancer.
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In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.
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BACKGROUND: The reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a widely used, highly sensitive laboratory technique to rapidly and easily detect, identify and quantify gene expression. Reliable RT-qPCR data necessitates accurate normalization with validated control genes (reference genes) whose expression is constant in all studied conditions. This stability has to be demonstrated.We performed a literature search for studies using quantitative or semi-quantitative PCR in the rat spared nerve injury (SNI) model of neuropathic pain to verify whether any reference genes had previously been validated. We then analyzed the stability over time of 7 commonly used reference genes in the nervous system - specifically in the spinal cord dorsal horn and the dorsal root ganglion (DRG). These were: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) and L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) and hydroxymethylbilane synthase (HMBS). We compared the candidate genes and established a stability ranking using the geNorm algorithm. Finally, we assessed the number of reference genes necessary for accurate normalization in this neuropathic pain model. RESULTS: We found GAPDH, HMBS, Actb, HPRT1 and 18S cited as reference genes in literature on studies using the SNI model. Only HPRT1 and 18S had been once previously demonstrated as stable in RT-qPCR arrays. All the genes tested in this study, using the geNorm algorithm, presented gene stability values (M-value) acceptable enough for them to qualify as potential reference genes in both DRG and spinal cord. Using the coefficient of variation, 18S failed the 50% cut-off with a value of 61% in the DRG. The two most stable genes in the dorsal horn were RPL29 and RPL13a; in the DRG they were HPRT1 and Actb. Using a 0.15 cut-off for pairwise variations we found that any pair of stable reference gene was sufficient for the normalization process. CONCLUSIONS: In the rat SNI model, we validated and ranked Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 and 18S as good reference genes in the spinal cord. In the DRG, 18S did not fulfill stability criteria. The combination of any two stable reference genes was sufficient to provide an accurate normalization.
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Humans differ substantially with respect to susceptibility to human immunodeficiency virus type 1 (HIV-1). We evaluated variants of nine host genes participating in the viral life cycle for their role in modulating HIV-1 infection. Alleles were assessed ex vivo for their impact on viral replication in purified CD4 T cells from healthy blood donors (n = 128). Thereafter, candidate alleles were assessed in vivo in a cohort of HIV-1-infected individuals (n = 851) not receiving potent antiretroviral therapy. As a benchmark test, we tested 12 previously reported host genetic variants influencing HIV-1 infection as well as single nucleotide polymorphisms in the nine candidate genes. This led to the proposition of three alleles of PML, TSG101, and PPIA as potentially associated with differences in progression of HIV-1 disease. In a model considering the combined effects of new and previously reported gene variants, we estimated that their effect might be responsible for lengthening or shortening by up to 2.8 years the period from 500 CD4 T cells/mul to <200 CD4 T cells/mul.
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The current availability of five complete genomes of different primate species allows the analysis of genetic divergence over the last 40 million years of evolution. We hypothesized that the interspecies differences observed in susceptibility to HIV-1 would be influenced by the long-range selective pressures on host genes associated with HIV-1 pathogenesis. We established a list of human genes (n = 140) proposed to be involved in HIV-1 biology and pathogenesis and a control set of 100 random genes. We retrieved the orthologous genes from the genome of humans and of four nonhuman primates (Pan troglodytes, Pongo pygmaeus abeli, Macaca mulatta, and Callithrix jacchus) and analyzed the nucleotide substitution patterns of this data set using codon-based maximum likelihood procedures. In addition, we evaluated whether the candidate genes have been targets of recent positive selection in humans by analyzing HapMap Phase 2 single-nucleotide polymorphisms genotyped in a region centered on each candidate gene. A total of 1,064 sequences were used for the analyses. Similar median K(A)/K(S) values were estimated for the set of genes involved in HIV-1 pathogenesis and for control genes, 0.19 and 0.15, respectively. However, genes of the innate immunity had median values of 0.37 (P value = 0.0001, compared with control genes), and genes of intrinsic cellular defense had K(A)/K(S) values around or greater than 1.0 (P value = 0.0002). Detailed assessment allowed the identification of residues under positive selection in 13 proteins: AKT1, APOBEC3G, APOBEC3H, CD4, DEFB1, GML, IL4, IL8RA, L-SIGN/CLEC4M, PTPRC/CD45, Tetherin/BST2, TLR7, and TRIM5alpha. A number of those residues are relevant for HIV-1 biology. The set of 140 genes involved in HIV-1 pathogenesis did not show a significant enrichment in signals of recent positive selection in humans (intraspecies selection). However, we identified within or near these genes 24 polymorphisms showing strong signatures of recent positive selection. Interestingly, the DEFB1 gene presented signatures of both interspecies positive selection in primates and intraspecies recent positive selection in humans. The systematic assessment of long-acting selective pressures on primate genomes is a useful tool to extend our understanding of genetic variation influencing contemporary susceptibility to HIV-1.
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PURPOSE: Mutations in IDH3B, an enzyme participating in the Krebs cycle, have recently been found to cause autosomal recessive retinitis pigmentosa (arRP). The MDH1 gene maps within the RP28 arRP linkage interval and encodes cytoplasmic malate dehydrogenase, an enzyme functionally related to IDH3B. As a proof of concept for candidate gene screening to be routinely performed by ultra high throughput sequencing (UHTs), we analyzed MDH1 in a patient from each of the two families described so far to show linkage between arRP and RP28. METHODS: With genomic long-range PCR, we amplified all introns and exons of the MDH1 gene (23.4 kb). PCR products were then sequenced by short-read UHTs with no further processing. Computer-based mapping of the reads and mutation detection were performed by three independent software packages. RESULTS: Despite the intrinsic complexity of human genome sequences, reads were easily mapped and analyzed, and all algorithms used provided the same results. The two patients were homozygous for all DNA variants identified in the region, which confirms previous linkage and homozygosity mapping results, but had different haplotypes, indicating genetic or allelic heterogeneity. None of the DNA changes detected could be associated with the disease. CONCLUSIONS: The MDH1 gene is not the cause of RP28-linked arRP. Our experimental strategy shows that long-range genomic PCR followed by UHTs provides an excellent system to perform a thorough screening of candidate genes for hereditary retinal degeneration.
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Background: Mantle cell lymphoma (MCL) is genetically characterized by the t(11;14)(q13;q32) translocation and a high number of secondary chromosomal alterations. The contribution of DNA methylation to MCL lymphomagenesis is not well known. We sought to identify epigenetically silenced genes in these tumours that might have clinical relevance. Methodology/Principal Findings: To identify potential methylated genes in MCL we initially investigated seven MCL cell lines treated with epigenetic drugs and gene expression microarray profiling. The methylation status of selected candidate genes was validated by a quantitative assay and subsequently analyzed in a series of primary MCL (n=38). After pharmacological reversion we identified 252 potentially methylated genes. The methylation analysis of a subset of these genes (n=25) in the MCL cell lines and normal B lymphocytes confirmed that 80% of them were methylated in the cell lines but not in normal lymphocytes. The subsequent analysis in primary MCL identified five genes (SOX9,HOXA9,AHR,NR2F2 ,and ROBO1) frequently methylated in these tumours. The gene methylation events tended to occur in the same primary neoplasms and correlated with higher proliferation, increased number of chromosomal abnormalities, and shorter survival of the patients. Conclusions: We have identified a set of genes whose methylation degree and gene expression levels correlate with aggressive clinicopathological features of MCL. Our findings also suggest that a subset of MCL might show a CpG island methylator phenotype (CIMP) that may influence the behaviour of the tumours.
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PURPOSE: Phenotypic, genetic and molecular characterization of 69 index patients with retinitis pigmentosa (RP) and various inherited retinal diseases. PATIENTS AND METHOD: patients went through complete ocular examination and blood samples were drawn for mutational screening of three candidate genes: rhodopsin (RHO), peripherin/RDS, and ROM-1. RESULTS: the most frequent type of RP among our population was the autosomal dominant (43.6%). Three RHO mutations were found among the RP patients. A RDS mutation was detected in three unrelated families segregating dominant macular dystrophy. DISCUSSION AND CONCLUSIONS: 18% of the autosomal dominant RP patients presented a RHO mutation; RDS R172W mutation was present in 25% of the dominant macular dystrophies.