Application of Bayesian Networks to Coverage Directed Test Generation for the Verification of Digital Hardware Designs

Functional verification is generally regarded as the most critical phase in the successful development of digital integrated circuits. The increasing complexity and size of chip designs make it more challenging to find bugs and meet test coverage goals in time for market demands. These challenges have led to more automated methods of simulation with constrained random test generation and coverage analysis. Recent goals in industry have focused on improving the process further by applying Coverage Directed Test Generation (CDG) to automate the feedback from coverage analysis to test input generation. Previous research has presented Bayesian networks as a way to achieve CDG. Bayesian networks provide a means of capturing behaviors of a design under verification and making predictions to help guide test input generation to reach coverage goals more quickly. Previous research has shown methods for defining a Bayesian network for a design domain and generating input parameters for dynamic simulation. This thesis demonstrates that existing commercial verification tools can be combined with a Bayesian inference engine as a feasible solution for creating a fully automated CDG environment. This solution is demonstrated using methods from previous research for applying Bayesian networks to verification. The CDG framework was implemented by combining the Questa verification platform with the Bayesian inference engine SMILE (Structural Modeling, Inference, and Learning Engine) in a single simulation environment. SystemVerilog testbenches and custom software were created to automatically find coverage holes, predict test input parameters, and dynamically change these parameters to complete verification with a fewer number of test cases. The CDG framework was demonstrated by performing verification on both a combinational logic design and a sequential logic design. The results show that Bayesian networks can be successfully used to improve the efficiency and quality of the verification process

Statistical Viewer: a tool to upload and integrate linkage and association data as plots displayed within the Ensembl genome browser

BACKGROUND: To facilitate efficient selection and the prioritization of candidate complex disease susceptibility genes for association analysis, increasingly comprehensive annotation tools are essential to integrate, visualize and analyze vast quantities of disparate data generated by genomic screens, public human genome sequence annotation and ancillary biological databases. We have developed a plug-in package for Ensembl called "Statistical Viewer" that facilitates the analysis of genomic features and annotation in the regions of interest defined by linkage analysis. RESULTS: Statistical Viewer is an add-on package to the open-source Ensembl Genome Browser and Annotation System that displays disease study-specific linkage and/or association data as 2 dimensional plots in new panels in the context of Ensembl's Contig View and Cyto View pages. An enhanced upload server facilitates the upload of statistical data, as well as additional feature annotation to be displayed in DAS tracts, in the form of Excel Files. The Statistical View panel, drawn directly under the ideogram, illustrates lod score values for markers from a study of interest that are plotted against their position in base pairs. A module called "Get Map" easily converts the genetic locations of markers to genomic coordinates. The graph is placed under the corresponding ideogram features a synchronized vertical sliding selection box that is seamlessly integrated into Ensembl's Contig- and Cyto- View pages to choose the region to be displayed in Ensembl's "Overview" and "Detailed View" panels. To resolve Association and Fine mapping data plots, a "Detailed Statistic View" plot corresponding to the "Detailed View" may be displayed underneath. CONCLUSION: Features mapping to regions of linkage are accentuated when Statistic View is used in conjunction with the Distributed Annotation System (DAS) to display supplemental laboratory information such as differentially expressed disease genes in private data tracks. Statistic View is a novel and powerful visual feature that enhances Ensembl's utility as valuable resource for integrative genomic-based approaches to the identification of candidate disease susceptibility genes. At present there are no other tools that provide for the visualization of 2-dimensional plots of quantitative data scores against genomic coordinates in the context of a primary public genome annotation browser

The Deacetylase HDAC6 Regulates Aggresome Formation and Cell Viability in Response to Misfolded Protein Stress

AbstractThe efficient clearance of cytotoxic misfolded protein aggregates is critical for cell survival. Misfolded protein aggregates are transported and removed from the cytoplasm by dynein motors via the microtubule network to a novel organelle termed the aggresome where they are processed. However, the means by which dynein motors recognize misfolded protein cargo, and the cellular factors that regulate aggresome formation, remain unknown. We have discovered that HDAC6, a microtubule-associated deacetylase, is a component of the aggresome. We demonstrate that HDAC6 has the capacity to bind both polyubiquitinated misfolded proteins and dynein motors, thereby acting to recruit misfolded protein cargo to dynein motors for transport to aggresomes. Indeed, cells deficient in HDAC6 fail to clear misfolded protein aggregates from the cytoplasm, cannot form aggresomes properly, and are hypersensitive to the accumulation of misfolded proteins. These findings identify HDAC6 as a crucial player in the cellular management of misfolded protein-induced stress

SRRM2, a Potential Blood Biomarker Revealing High Alternative Splicing in Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects about five million people worldwide. Diagnosis remains clinical, based on phenotypic patterns. The discovery of laboratory markers that will enhance diagnostic accuracy, allow pre-clinical detection and tracking of disease progression is critically needed. These biomarkers may include transcripts with different isoforms.We performed extensive analysis on 3 PD microarray experiments available through GEO and found that the RNA splicing gene SRRM2 (or SRm300), sereine/arginine repetitive matrix 2, was the only gene differentially upregulated among all the three PD experiments. SRRM2 expression was not changed in the blood of other neurological diseased patients versus the healthy controls. Using real-time PCR, we report that the shorter transcript of SRRM2 was 1.7 fold (p = 0.008) upregulated in the substantia nigra of PDs vs controls while the longer transcript was 0.4 downregulated in both the substantia nigra (p = 0.03) and amygdala (p = 0.003). To validate our results and test for the possibility of alternative splicing in PD, we performed independent microarray scans, using Affymetrix Exon_ST1 arrays, from peripheral blood of 28 individuals (17 PDs and 11 Ctrls) and found a significant upregulation of the upstream (5') exons of SRRM2 and a downregulation of the downstream exons, causing a total of 0.7 fold down regulation (p = 0.04) of the long isoform. In addition, we report novel information about hundreds of genes with significant alternative splicing (differential exonic expression) in PD blood versus controls.The consistent dysregulation of the RNA splicing factor SRRM2 in two different PD neuronal sources and in PD blood but not in blood of other neurologically diseased patients makes SRRM2 a strong candidate gene for PD and draws attention to the role of RNA splicing in the disease

A Rare Novel Deletion of the Tyrosine Hydroxylase Gene in Parkinson Disease

Tyrosine hydroxylase (TH) enzyme is a rate limiting enzyme in dopamine biosynthesis. Missense mutation in both alleles of the TH gene is known to cause dopamine-related phenotypes, including dystonia and infantile Parkinsonism. However, it is not clear if single allele mutation in TH modifies the susceptibility to the adult form of Parkinson disease (PD). We reported a novel deletion of entire TH gene in an adult with PD. The deletion was first identified by copy number variation (CNV) analysis in a genome-wide association study using Illumina Infinium BeadChips. After screening 635 cases and 642 controls, the deletion was found in one PD case but not in any control. The deletion was confirmed by multiple quantitative PCR (qPCR) assays. There is no additional exonic single nucleotide variant in the one copy of TH gene of the patient. The patient has an age-at-onset of 54 years, no evidence for dystonia, and was responsive to L-DOPA. This case supports the importance of the TH gene in PD pathogenesis and raises more attention to rare variants in candidate genes being a risk factor for Parkinson disease. © 2010 Wiley-Liss, Inc

A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism

<p>Abstract</p> <p>Background</p> <p>Genome-wide Association Studies (GWAS) have proved invaluable for the identification of disease susceptibility genes. However, the prioritization of candidate genes and regions for follow-up studies often proves difficult due to false-positive associations caused by statistical noise and multiple-testing. In order to address this issue, we propose the novel GWAS noise reduction (GWAS-NR) method as a way to increase the power to detect true associations in GWAS, particularly in complex diseases such as autism.</p> <p>Methods</p> <p>GWAS-NR utilizes a linear filter to identify genomic regions demonstrating correlation among association signals in multiple datasets. We used computer simulations to assess the ability of GWAS-NR to detect association against the commonly used joint analysis and Fisher's methods. Furthermore, we applied GWAS-NR to a family-based autism GWAS of 597 families and a second existing autism GWAS of 696 families from the Autism Genetic Resource Exchange (AGRE) to arrive at a compendium of autism candidate genes. These genes were manually annotated and classified by a literature review and functional grouping in order to reveal biological pathways which might contribute to autism aetiology.</p> <p>Results</p> <p>Computer simulations indicate that GWAS-NR achieves a significantly higher classification rate for true positive association signals than either the joint analysis or Fisher's methods and that it can also achieve this when there is imperfect marker overlap across datasets or when the closest disease-related polymorphism is not directly typed. In two autism datasets, GWAS-NR analysis resulted in 1535 significant linkage disequilibrium (LD) blocks overlapping 431 unique reference sequencing (RefSeq) genes. Moreover, we identified the nearest RefSeq gene to the non-gene overlapping LD blocks, producing a final candidate set of 860 genes. Functional categorization of these implicated genes indicates that a significant proportion of them cooperate in a coherent pathway that regulates the directional protrusion of axons and dendrites to their appropriate synaptic targets.</p> <p>Conclusions</p> <p>As statistical noise is likely to particularly affect studies of complex disorders, where genetic heterogeneity or interaction between genes may confound the ability to detect association, GWAS-NR offers a powerful method for prioritizing regions for follow-up studies. Applying this method to autism datasets, GWAS-NR analysis indicates that a large subset of genes involved in the outgrowth and guidance of axons and dendrites is implicated in the aetiology of autism.</p

Clinical and genetic heterogeneity in familial focal segmental glomerulosclerosis

Clinical and genetic heterogeneity in familial focal segmental glomerulosclerosis.BackgroundFamilial forms of focal segmental glomerulosclerosis (FFSGS) that exhibit autosomal dominant or recessive patterns of inheritance have been described. The genetic basis of these hereditary forms of FSGS is unknown. One recent study of a kindred from Oklahoma with an autosomal dominant form of FSGS linked this disease to a region of chromosome 19q. In addition, polymorphisms in a gene in this region on chromosome 19q13 have been linked to congenital nephrotic syndrome of the Finnish type. We have ascertained and characterized a large family with autosomal dominant FFSGS (Duke 6530).MethodsFamilies were compared for clinical and genetic heterogeneity. To test for linkage of our family to this portion of chromosome 19, genomic DNA was isolated from 102 family members, and polymerase chain reaction was performed using eight microsatellite markers that spanned the area of interest on chromosome 19. Data were evaluated using two-point linkage analysis, multipoint analysis, and an admixture test.ResultsLinkage was excluded at a distance of ±5 to 10cm for all markers tested with two-point log10 of the odds of linkage (LOD) scores and from an approximate 60cm interval in this area of chromosome 19q via multipoint analysis.ConclusionFSGS has been called the “final common pathway” of glomerular injury, as it is a frequent pathological manifestation with diverse etiologies. This diversity likely correlates with the genetic heterogeneity that we have established. Thus, our data demonstrate that there are at least two genes responsible for this disease, and there is genetic as well as clinical heterogeneity in autosomal dominant FSGS

Quantitative DNA pooling to increase the efficiency of linkage analysis in autosomal dominant disease

DNA pooling is an efficient method to rapidly perform genome-wide linkage scans in autosomal recessive diseases in inbred populations where affected individuals are likely to be homozygous for alleles near the disease gene locus. We wanted to examine whether this approach would detect linkage in autosomal dominant (AD) disorders where affected individuals may share one allele identical by descent at loci tightly linked to the disease. Two large outbred pedigrees in which the AD diseases familial venous malformation (FVM) and hereditary hemorrhagic telangiectasia (HHT1), linked to 9p and 9q, respectively, were investigated. Separate pools of DNA from affected ( n = 21 for FVM and 17 for HHT1) and unaffected family members ( n = 9 FVM and HHT1), and 25 unrelated population controls were established. Polymorphic markers spanning chromosome 9 at approximately 13.5-cM intervals were amplified using standard PCR. Allele quantitation was performed with a fluorimager. Visual inspection of allele intensities and frequency distributions suggested a shift in frequency of the most common allele in the affecteds lane when compared to control lanes for markers within 30 cM of the FVM and HHT1 loci. These subjective assessments were confirmed statistically by testing for the difference between two proportions (one-sided; P ≤ 0.05). When using population controls, the true-positive rates for FVM and HHT1 were 5/5 and 2/5 markers, respectively. False-positive rates for FVM and HHT1 were 3/9 and 2/9, respectively. In both AD diseases investigated, quantitative DNA pooling detected shifts in allele frequency, thus identifying areas of known linkage in most cases. The utility of this technique depends on the size of the pedigree, frequency of the disease-associated allele in the population, and the choice of appropriate controls. Although the false-positive rate appears to be high, this approach still serves to reduce the amount of overall genotyping by about 60%. DNA pooling merits further investigation as a potential strategy in increasing the efficiency of genomic linkage scans.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42260/1/439-102-2-207_81020207.pd