Homo sapiens isolate:Arachidonate 12 Lipoxygenase Gene
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ABSTRACT:
PROVIDER: PRJNA379762 | ENA |
REPOSITORIES: ENA
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Project description:The diploid isolate EM93 is the main ancestor to the widely used Saccharomyces cerevisiae haploid laboratory strain, S288C. In this study, we first hybridise DNA from eight EM93 segregants from two tetrads to Affymetrix genechip S. cerevisiae Tiling 1.0R Arrays to generate a high-resolution overview of the genetic differences between EM93 and S288C. We show that EM93 is heterozygous for many polymorphisms, including large sequence polymorphisms, such as deletions and a Saccharomyces paradoxus introgression. We also find that many of the large sequence polymorphisms are associated with Ty-elements and sub-telomeric regions. We next utilize the hybridization profiles of the 3.2 million Tiling Array probes to identify 2,965 genetic markers, which we then used to design an EM93 genotyping array. By genotyping 120 EM93 tetrads, we deduced the structures of all EM93 chromosomes and found that the average EM93 meiosis produces 144 detectable recombination events, consisting of 87 crossover and 57 non-crossover events; we also identified 203 recombination hot-spots and provide evidence for crossover interference. We find that the effect of heterozygous large sequence polymorphisms on recombination is chromosome position-dependent, with sub-telomeric large sequence polymorphisms having no discernable effect on recombination but non-sub-telomeric large sequence polymorphisms reducing recombination. Finally, we find that recombination hotspots show limited conservation, with some but not all strain-specific hotspots being due to heterozygous non-sub-telomeric large sequence polymorphisms.
2012-06-08 | E-MEXP-3246 | biostudies-arrayexpress
Project description:SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip
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Project description:Detection of single feature polymorphisms comparing five barley genotypes. Gene expression under unstressed and drought stressed conditions. Tissue from five entire five day old seedlings from drought stress or unstressed growth conditions was used for RNA extraction. For Barke, Morex and Stepoe the two types of RNA were pooled. For Oregon Wolfe Barley Dominant and Recessive (OWBs), the two types of RNA were handled separately. Targets from three biological replicates of each genotype-treatment were generated and transcript levels were determined using Affymetrix Barley1 GeneChip arrays. Probe set, followed by single probe, comparisons between genotypes allows the identification of single feature polymorphisms in comparisons between genotypes. For the OWBs, comparisons between stressed and unstressed conditions defines stress-regulated genes. Experiment Overall Design: Three genotypes, three replicates each. Two additional genotypes, two sets of three replicates each.
2008-06-12 | E-GEOD-3170 | biostudies-arrayexpress
Project description:Sensitive detection of chromatin-altering polymorphisms reveals autoimmune disease mechanisms
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Project description:The use of DNA microarrays to identify nucleotide variation is almost 20 years old. A variety of improvements in probe design and experimental conditions have brought this technology to the point that single-nucleotide differences can be efficiently detected in unmixed samples, although developing reliable methods for detection of mixed sequences (e.g. heterozygotes) remains challenging. Surprisingly, a comprehensive study of the probe design parameters and experimental conditions that optimize discrimination of single nucleotide polymorphisms (SNPs) has yet to be reported, so the limits of this technology remain uncertain. By targeting 24,549 SNPs that differ between two Saccharomyces cerevisiae strains, we studied the effect of SNPs on hybridization efficiency to DNA microarray probes of different lengths under different hybridization conditions. We found that the critical parameter for optimization of sequence discrimination is the relationship between probe melting temperature (Tm) and the temperature at which the hybridization reaction is performed. This relationship can be exploited through the design of microarrays containing probes of equal Tm by varying the length of probes. We demonstrate that using such a microarray we detect >90% homozygous SNPs and >80% heterozygous SNPs using the SNPScanner algorithm. The optimized design and experimental parameters determined in this study should guide DNA microarray designs for applications that require sequence discrimination such as mutation detection, genotyping of unmixed and mixed samples and allele-specific gene expression. Moreover, designing microarray probes with optimized sensitivity to mismatches should increase the accuracy of standard microarray applications such as copy number variation detection and gene expression analysis. Keyword(s): MutationDetection_CGH
2009-12-10 | GSE19319 | GEO
Project description:Cell-free DNA sequencing using insertion/deletion polymorphisms
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Project description:The accurate choice of anti-cancer drugs is important problem of modern medicine. We developed a new method for the selection of targeted drugs based on detection of specific intracellular signaling and metabolic pathways in the bioinformatic system termed OncoFinder before the treatment. We obtained transcriptomic data 12 human cancer cell lines (NT2/D1, Tera-1, NGP, HepG2, BT474, Skov-3, T3M4, HeLa, A549, MCF-7, Jurkat, BxPc1) before a treatment. In our research for gene expression quantile normalization of the experimental data of all 12 cell lines together, we used separately eleven gene expression datasets corresponding to different normal human tissues profiled on Illumina HT-12v3-4 platform, 4-33 samples per dataset (from GEO). Normalization datasets used for the processing of the experimental transcriptomic data: GSE17822 (GSM444688, GSM444689, GSM444690, GSM444691, GSM444692, GSM444693), GSE26852 (GSM661123, GSM661124, GSM661125, GSM661126, GSM661127, GSM661128, GSM661130), GSE32124 (GSM796359, GSM796360, GSM796361, GSM796362, GSM796363, GSM796364, GSM796365, GSM796366, GSM796367, GSM796368, GSM796369, GSM796370, GSM796371, GSM796372, GSM796373, GSM796374, GSM796375, GSM796376, GSM796377, GSM796378, GSM796379, GSM796380, GSM796381, GSM796382, GSM796383, GSM796384, GSM796385, GSM796386, GSM796387, GSM796388, GSM796389, GSM796390, GSM796391), GSE34074 (GSM841415, GSM841419, GSM841423, GSM841427, GSM841431, GSM841435), GSE37013 (GSM908514, GSM908515, GSM908516, GSM908517, GSM908518, GSM908519, GSM908520), GSE40645 (GSM998797, GSM998798, GSM998799, GSM998800, GSM998801, GSM998802, GSM998803, GSM998804, GSM998805, GSM998806, GSM998807, GSM998808, GSM998809, GSM998810), GSE42656 (GSM1047460, GSM1047462, GSM1047463, GSM1047467), GSE52130 (GSM1260102, GSM1260103, GSM1260104, GSM1260105, GSM1260106, GSM1260107, GSM1260108), GSE54563 (GSM1318920, GSM1318921, GSM1318922, GSM1318923, GSM1318924, GSM1318925, GSM1318926, GSM1318927, GSM1318928, GSM1318929, GSM1318930, GSM1318931, GSM1318932, GSM1318933, GSM1318934, GSM1318935, GSM1318936, GSM1318937, GSM1318938, GSM1318939, GSM1318940, GSM1318941, GSM1318945, GSM1318946, GSM1318947), GSE57218 (GSM1380887, GSM1380888, GSM1380956, GSM1380957, GSM1380958, GSM1380959), GSE60709 (GSM1486145, GSM1486146, GSM1486160, GSM1486161, GSM1486162, GSM1486163, GSM1486164, GSM1486165, GSM1486166, GSM1486167, GSM1486168, GSM1486169, GSM1486170, GSM1486171, GSM1486172, GSM1486173). Normalization of the 12 new cell line data was performed independently 11 times together with the data from the GSM ID numbers listed above. For GSM1486145, data for replicate samples 34 and 35 were used. For sample GSM1486146, data for replicate sample 36 was used. Total RNA obtained from NT2/D1, Tera-1, NGP, HepG2, BT474, Skov-3, T3M4, HeLa, A549, MCF-7, Jurkat, BxPc1 cell lines.
2015-01-27 | E-GEOD-65314 | biostudies-arrayexpress
Project description:The accurate choice of anti-cancer drugs is important problem of modern medicine. We developed a new method for the selection of targeted drugs based on detection of specific intracellular signaling and metabolic pathways in the bioinformatic system termed OncoFinder before the treatment. We obtained transcriptomic data 12 human cancer cell lines (NT2/D1, Tera-1, NGP, HepG2, BT474, Skov-3, T3M4, HeLa, A549, MCF-7, Jurkat, BxPc1) before a treatment. In our research for gene expression quantile normalization of the experimental data of all 12 cell lines together, we used separately eleven gene expression datasets corresponding to different normal human tissues profiled on Illumina HT-12v3-4 platform, 4-33 samples per dataset (from GEO). Normalization datasets used for the processing of the experimental transcriptomic data: GSE17822 (GSM444688, GSM444689, GSM444690, GSM444691, GSM444692, GSM444693), GSE26852 (GSM661123, GSM661124, GSM661125, GSM661126, GSM661127, GSM661128, GSM661130), GSE32124 (GSM796359, GSM796360, GSM796361, GSM796362, GSM796363, GSM796364, GSM796365, GSM796366, GSM796367, GSM796368, GSM796369, GSM796370, GSM796371, GSM796372, GSM796373, GSM796374, GSM796375, GSM796376, GSM796377, GSM796378, GSM796379, GSM796380, GSM796381, GSM796382, GSM796383, GSM796384, GSM796385, GSM796386, GSM796387, GSM796388, GSM796389, GSM796390, GSM796391), GSE34074 (GSM841415, GSM841419, GSM841423, GSM841427, GSM841431, GSM841435), GSE37013 (GSM908514, GSM908515, GSM908516, GSM908517, GSM908518, GSM908519, GSM908520), GSE40645 (GSM998797, GSM998798, GSM998799, GSM998800, GSM998801, GSM998802, GSM998803, GSM998804, GSM998805, GSM998806, GSM998807, GSM998808, GSM998809, GSM998810), GSE42656 (GSM1047460, GSM1047462, GSM1047463, GSM1047467), GSE52130 (GSM1260102, GSM1260103, GSM1260104, GSM1260105, GSM1260106, GSM1260107, GSM1260108), GSE54563 (GSM1318920, GSM1318921, GSM1318922, GSM1318923, GSM1318924, GSM1318925, GSM1318926, GSM1318927, GSM1318928, GSM1318929, GSM1318930, GSM1318931, GSM1318932, GSM1318933, GSM1318934, GSM1318935, GSM1318936, GSM1318937, GSM1318938, GSM1318939, GSM1318940, GSM1318941, GSM1318945, GSM1318946, GSM1318947), GSE57218 (GSM1380887, GSM1380888, GSM1380956, GSM1380957, GSM1380958, GSM1380959), GSE60709 (GSM1486145, GSM1486146, GSM1486160, GSM1486161, GSM1486162, GSM1486163, GSM1486164, GSM1486165, GSM1486166, GSM1486167, GSM1486168, GSM1486169, GSM1486170, GSM1486171, GSM1486172, GSM1486173). Normalization of the 12 new cell line data was performed independently 11 times together with the data from the GSM ID numbers listed above. For GSM1486145, data for replicate samples 34 and 35 were used. For sample GSM1486146, data for replicate sample 36 was used.
2015-01-27 | GSE65314 | GEO
Project description:Detection of single feature polymorphisms comparing five barley genotypes. Gene expression under unstressed and drought stressed conditions. Tissue from five entire five day old seedlings from drought stress or unstressed growth conditions was used for RNA extraction. For Barke, Morex and Stepoe the two types of RNA were pooled. For Oregon Wolfe Barley Dominant and Recessive (OWBs), the two types of RNA were handled separately. Targets from three biological replicates of each genotype-treatment were generated and transcript levels were determined using Affymetrix Barley1 GeneChip arrays. Probe set, followed by single probe, comparisons between genotypes allows the identification of single feature polymorphisms in comparisons between genotypes. For the OWBs, comparisons between stressed and unstressed conditions defines stress-regulated genes. Keywords: repeat
2005-08-25 | GSE3170 | GEO
Project description:Detection and Validation of Single Feature Polymorphisms in Cowpea using a Soybean Genome Array
| PRJNA108489 | ENA