8 resultados para dna sequence

em Cambridge University Engineering Department Publications Database


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BACKGROUND: With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. FINDINGS: Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. CONCLUSIONS: BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

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Plants use siRNAs to target cytosine DNA methylation to both symmetrical CG and nonsymmetrical (CHG and CHH) sequence contexts. DNA methylation and siRNA clusters most frequently overlap with transposons in the Arabidopsis thaliana genome. However, a significant number of protein-coding genes also show promoter DNA methylation, and this can be used to silence their expression. Loss of the majority of non-CG DNA methylation in drm1 drm2 cmt3 triple mutants leads to developmental phenotypes. We identified the gene responsible for these phenotypes as SUPPRESSOR OF drm1 drm2 cmt3 (SDC), which encodes an F-box protein and possesses seven promoter tandem repeats. The SDC repeats show a unique silencing requirement for non-CG DNA methylation directed redundantly by histone methylation and siRNAs, and display spreading of siRNAs and methylation beyond the repeated region. In addition to revealing the complexity of DNA methylation control in A. thaliana, SDC has important implications for how plant genomes utilize gene silencing to repress endogenous genes.

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Cytosine DNA methylation protects eukaryotic genomes by silencing transposons and harmful DNAs, but also regulates gene expression during normal development. Loss of CG methylation in the Arabidopsis thaliana met1 and ddm1 mutants causes varied and stochastic developmental defects that are often inherited independently of the original met1 or ddm1 mutation. Loss of non-CG methylation in plants with combined mutations in the DRM and CMT3 genes also causes a suite of developmental defects. We show here that the pleiotropic developmental defects of drm1 drm2 cmt3 triple mutant plants are fully recessive, and unlike phenotypes caused by met1 and ddm1, are not inherited independently of the drm and cmt3 mutations. Developmental phenotypes are also reversed when drm1 drm2 cmt3 plants are transformed with DRM2 or CMT3, implying that non-CG DNA methylation is efficiently re-established by sequence-specific signals. We provide evidence that these signals include RNA silencing though the 24-nucleotide short interfering RNA (siRNA) pathway as well as histone H3K9 methylation, both of which converge on the putative chromatin-remodeling protein DRD1. These signals act in at least three partially intersecting pathways that control the locus-specific patterning of non-CG methylation by the DRM2 and CMT3 methyltransferases. Our results suggest that non-CG DNA methylation that is inherited via a network of persistent targeting signals has been co-opted to regulate developmentally important genes. © 2006 Chan et al.

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High-throughput DNA sequencing (HTS) instruments today are capable of generating millions of sequencing reads in a short period of time, and this represents a serious challenge to current bioinformatics pipeline in processing such an enormous amount of data in a fast and economical fashion. Modern graphics cards are powerful processing units that consist of hundreds of scalar processors in parallel in order to handle the rendering of high-definition graphics in real-time. It is this computational capability that we propose to harness in order to accelerate some of the time-consuming steps in analyzing data generated by the HTS instruments. We have developed BarraCUDA, a novel sequence mapping software that utilizes the parallelism of NVIDIA CUDA graphics cards to map sequencing reads to a particular location on a reference genome. While delivering a similar mapping fidelity as other mainstream programs , BarraCUDA is a magnitude faster in mapping throughput compared to its CPU counterparts. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the mapping throughput. BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the mapping of millions of sequencing reads generated by HTS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology. BarraCUDA is currently available at http://seqbarracuda.sf.net