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Short tandem repeats (STRs) are repetitive sequences of a polymorphic stretch of two to six nucleotides. We hypothesized that STRs are associated with prostate cancer development and/or progression. We undertook RNA sequencing analysis of prostate tumors and adjacent non-malignant cells to identify polymorphic STRs that are readily expressed in these cells. Most of the expressed STRs in the clinical samples mapped to intronic and intergenic DNA. Our analysis indicated that three of these STRs (TAAA-ACTG2, TTTTG-TRIB1, and TG-PCA3) are polymorphic and differentially expressed in prostate tumors compared to adjacent non-malignant cells. TG-PCA3 STR expression was repressed by the anti-androgen drug enzalutamide in prostate cancer cells. Genetic analysis of prostate cancer patients and healthy controls (N > 2,000) showed a significant association of the most common 11 repeat allele of TG-PCA3 STR with prostate cancer risk (OR = 1.49; 95% CI 1.11-1.99; P = 0.008). A significant association was also observed with aggressive disease (OR = 2.00; 95% CI 1.06-3.76; P = 0.031) and high mortality rates (HR = 3.0; 95% CI 1.03-8.77; P = 0.045). We propose that TG-PCA3 STR has both diagnostic and prognostic potential for prostate cancer. We provided a proof of concept to be applied to other RNA sequencing datasets to identify disease-associated STRs for future clinical exploratory studies.
Pubmed ID: 29203868 RIS Download
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View all literature mentionsA commercial organization which provides assay technologies to isolate DNA, RNA, and proteins from any biological sample. Assay technologies are then used to make specific target biomolecules, such as the DNA of a specific virus, visible for subsequent analysis.
View all literature mentionsA software tool for profiling Short Tandem Repeats (STRs) from high throughput sequencing data.
View all literature mentionsA dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
View all literature mentionsSoftware tool that screens DNA sequences for interspersed repeats and low complexity DNA sequences. The output of the program is a detailed annotation of the repeats that are present in the query sequence as well as a modified version of the query sequence in which all the annotated repeats have been masked (default: replaced by Ns). Currently over 56% of human genomic sequence is identified and masked by the program. Sequence comparisons in RepeatMasker are performed by one of several popular search engines including nhmmer, cross_match, ABBlast/WUBlast, RMBlast and Decypher. RepeatMasker makes use of curated libraries of repeats and currently supports Dfam ( profile HMM library ) and RepBase ( consensus sequence library ).
View all literature mentionsGenotyping software package that provides DNA sizing and quality allele calls for all Applied Biosystems electrophoresis-based genotyping systems. GeneMapper specializes in multiapplication functionality, including amplified fragment length polymorphism, loss of heterozygosity, microsatellite, and SNP genotyping analysis. The software provides remote auto-analysis and command line operation, and allows for multiuser, client-server deployment.
View all literature mentionsCell line LNCaP is a Cancer cell line with a species of origin Homo sapiens (Human)
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