Custom Sequence Research Articles

Evaluation of a cancer gene sequencing panel in a hereditary risk assessment clinic.

7 Background: Multiple-gene sequencing panels are entering clinical practice. We report on research testing with a custom sequencing panel comprising 43 genes and 32 cancer-associated variants among patients referred for assessment of hereditary breast and ovarian cancer risk. Methods: Patients referred to the Stanford Cancer Genetics Program for clinical BRCA1 and BRCA2 (BRCA1/2) mutation testing from 2002-2012 were invited to donate a blood sample for research on an Institutional Review Board-approved protocol. Blood samples were frozen at -80 degrees, and DNA extracted after <1-10 years. The entire coding region, exon-intron boundaries (+/- 10bp) and all known pathogenic variants in other regions were sequenced for 43 genes that have published associations with risk of breast, ovarian and other cancers. An additional 32 cancer-associated variants were also sequenced. Clinically significant results were disclosed to patients. Results: Germline DNA samples were sequenced from 199 women: 141 had breast cancer, and 57 carried known BRCA1/2 mutations. Analytic results for BRCA1/2 sequencing and pathogenicity interpretations were concordant with prior clinical testing for all patients. Twenty variants designated as pathogenic, either based on published literature or due to a novel truncating or splice donor/acceptor effect, were observed in genes other than BRCA1/2, including ATM, BLM, CDH1, CDKN2A, MUTYH, MLH1, NBN, PRSS1, and SLX4. Thirteen patients had pathogenic variants warranting a change in cancer screening or risk reduction based on practice guidelines; they were invited for confirmatory clinical testing and counseling. One 53-year old patient with a personal history of breast and endometrial cancers was found to carry a pathogenic MLH1 mutation; she underwent risk-reducing salpingo-oophorectomy and colonoscopy, with removal of a tubular adenoma. Conclusions: Among patients referred for BRCA1/2 mutation testing, a comprehensive sequencing assay identified 20 [10.1%, 95% confidence interval (CI) 6.5%-15.1%] pathogenic mutations in other genes, of which 13 (6.5%, CI 3.8%-11%) prompted a change in care. Disclosure of research results to participants was feasible and well-tolerated.

Finite and infinite-horizon single vehicle routing problems with a predefined customer sequence and pickup and delivery

We consider the problem of finding the optimal routing of a single vehicle that starts its route from a depot and picks up from and delivers K different products to N customers that are served according to a predefined customer sequence. The vehicle is allowed during its route to return to the depot to unload returned products and restock with new products. The items of all products are of the same size. For each customer the demands for the products that are delivered by the vehicle and the quantity of the products that is returned to the vehicle are discrete random variables with known joint distribution. Under a suitable cost structure, it is shown that the optimal policy that serves all customers has a specific threshold-type structure. We also study a corresponding infinite-time horizon problem in which the service of the customers is not completed when the last customer has been serviced but it continues indefinitely with the same customer order. For each customer, the joint distribution of the quantities that are delivered and the quantity that is picked up is the same at each cycle. The discounted-cost optimal policy and the average-cost optimal policy have the same structure as the optimal policy in the finite-horizon problem. Numerical results are given that illustrate the structural results.

Next generation diagnostics of cystic fibrosis and CFTR-related disorders by targeted multiplex high-coverage resequencing of CFTR

BackgroundHere we have developed a novel and much more efficient strategy for the complete molecular characterisation of the cystic fibrosis (CF) transmembrane regulator (CFTR) gene, based on multiplexed targeted resequencing....

Experimental demonstration of superluminal space-to-time mapping in long period gratings

We experimentally demonstrate a superluminal space-to-time mapping process in grating-assisted (GA) codirectional coupling devices, particularly fiber long period gratings (LPGs). Through this process, the grating complex (amplitude and phase) apodization profile is directly mapped into the device's temporal impulse response. In contrast to GA counterdirectional couplers, e.g., Bragg gratings, this mapping occurs with a space-to-time scaling factor that is much higher than the propagation speed of light in vacuum. This phenomenon has been used for synthesizing customized complex optical pulse data sequences with femtosecond features (3.5 Tbit/s data rate) using readily feasible fiber LPG designs, e.g., with subcentimeter resolutions.

Long-Haul Vehicle Routing and Scheduling with Working Hour Rules

Long-haul carriers must comply with various safety rules which are rarely taken into account in models and algorithms for vehicle routing problems. In this paper, we consider the rules on truck driver safety during long-haul trips in the United States. The problem under study has two dominant features: a routing component that consists of determining the sequence of customers visited by each vehicle and a scheduling component that consists of planning the rest periods and the service time of each customer. We have developed different scheduling algorithms embedded within a tabu search heuristic. The overall solution methods were tested on modified Solomon instances, and the computational results confirm the benefits of using a sophisticated scheduling procedure when planning long-haul transportation.

Knowledge discovery of weighted RFM sequential patterns from customer sequence databases

In today's business environment, there is tremendous interest in the mining of interesting patterns for superior decision making. Although many successful customer relationship management (CRM) applications have been developed based on sequential pattern mining techniques, they basically assume that the importance of each customer is the same. Previous studies in CRM show that not all customers make the same contribution to a business, and it is indispensible to evaluate customer value before developing effective marketing strategies. Therefore, this study includes the concepts of recency, frequency, and monetary (RFM) analysis in the sequential pattern mining process. For a given subsequence, each customer sequence contributes its own recency, frequency, and monetary scores to represent customer importance. An efficient algorithm is developed to discover sequential patterns with high recency, frequency, and monetary scores. Empirical results show that the proposed method is efficient and can effectively discover more valuable patterns than conventional frequent pattern mining.

New Insights into the Mechanism of Initial Transcription

RNA polymerases undergo substantial structural and functional changes in transitioning from sequence-specific initial transcription to stable and relatively sequence-independent elongation. Initially, transcribing complexes are characteristically unstable, yielding short abortive products on the path to elongation. However, protein mutations have been isolated in RNA polymerases that dramatically reduce abortive instability. Understanding these mutations is essential to understanding the energetics of initial transcription and promoter clearance. We demonstrate here that the P266L point mutation in T7 RNA polymerase, which shows dramatically reduced abortive cycling, also transitions to elongation later, i.e. at longer lengths of RNA. These two properties of the mutant are not necessarily coupled, but rather we propose that they both derive from a weakening of the barrier to RNA-DNA hybrid-driven rotation of the promoter binding N-terminal platform, a motion necessary to achieve programmatically timed release of promoter contacts in the transition to elongation. Parallels in the multisubunit RNA polymerases are discussed.

Correction to Protein Identification Using Customized Protein Sequence Databases Derived from RNA-Seq Data

Correction to Protein Identification Using Customized Protein Sequence Databases Derived from RNA-Seq Data

Sparse Principal Component Analysis for Identifying Ancestry‐Informative Markers in Genome‐Wide Association Studies

Genome-wide association studies (GWAS) routinely apply principal component analysis (PCA) to infer population structure within a sample to correct for confounding due to ancestry. GWAS implementation of PCA uses tens of thousands of single-nucleotide polymorphisms (SNPs) to infer structure, despite the fact that only a small fraction of such SNPs provides useful information on ancestry. The identification of this reduced set of ancestry-informative markers (AIMs) from a GWAS has practical value; for example, researchers can genotype the AIM set to correct for potential confounding due to ancestry in follow-up studies that utilize custom SNP or sequencing technology. We propose a novel technique to identify AIMs from genome-wide SNP data using sparse PCA. The procedure uses penalized regression methods to identify those SNPs in a genome-wide panel that significantly contribute to the principal components while encouraging SNPs that provide negligible loadings to vanish from the analysis. We found that sparse PCA leads to negligible loss of ancestry information compared to traditional PCA analysis of genome-wide SNP data. We further demonstrate the value of sparse PCA for AIM selection using real data from the International HapMap Project and a genomewide study of inflammatory bowel disease. We have implemented our approach in open-source R software for public use.

Manifestation and post hoc correction of gradient cross-term artifacts in DTI

Cross-terms between imaging and diffusion gradients, unaccounted for during tensor calculations, can lead to erroneous estimation of diffusivity and fractional anisotropy (FA) in regions of isotropic and anisotropic diffusion. Cross-term of magnitude 136.8±1.6 s/mm2, artificially introduced in the slice-encode direction, caused an increase in FA in isotropic phantom from 0.0546±0.0001 to 0.0996±0.0001, while the change in chimpanzee brain depended on the orientation of the white matter (WM). Mean diffusivity (MD) remained unchanged in isotropic phantom, but increased by ∼20% in the WM due to cross-terms. A bias was observed in the principal eigenvectors in both phantom and chimpanzee brain, resulting in significant increase in midline crossing fibers along the bias than perpendicular to it in tractography in chimpanzee brain. Post hoc correction of these artifacts was achieved by estimating the cross-term factors using calibration scans on an isotropic phantom and modifying the b-matrix before tensor calculation. Upon correction, the FA and MD values closely resembled the values obtained from sequence without cross-terms, and the bias in principal eigenvectors was eliminated. Customized sequences involving large b-values, high-resolution imaging, or long diffusion or echo times should therefore be evaluated and any residual cross-terms corrected before implementation.

Abstract 3736: Applying the Carotid Atherosclerosis Score in a Clinical Environment: a Feasibility Study

Background Carotid atherosclerosis is a leading cause of stoke. Recent studies have shown that its severity can be stratified by the Carotid Atherosclerosis Score (CAS) as measured by MRI. However, these studies were performed using customized imaging sequences, coils and comprehensive plaque analysis by specialized human reviewers, which are not generally available in a clinical environment. Whether CAS can be applied for clinical risk assessment is unknown. In this study, we used clinically collected MRI data to compute CAS. We investigated the correlation between CAS and the prevalence of neurological symptoms and disrupted luminal surface (DLS), an indicator of plaque instability, to evaluate the feasibility of translating CAS for clinical use. Methods Seventy six patients with either symptomatic or asymptomatic carotid disease detected by ultrasound were recruited. All patients underwent a multi-contrast MRI with clinical sequences and a commercially available coil. The lumen and outer wall boundaries and DLS were outlined manually and the plaque components were identified automatically using histologically validated image analysis software. The maximum wall thickness (MWT) and maximum % area (100 x area/[wall area]) of lipid-rich necrotic core (LRNC) were outputted by the software to compute CAS as follows: CAS=1 with MWT&lt2.0mm, CAS=2 with LRNC&lt20%, CAS=3 with LRNC between 20% and 40% and CAS=4 with LRNC&gt40%. Trend analysis was done to evaluate the associations between CAS and prevalence of symptoms and DLS. The area under the receiver operating characteristic (ROC) curve was used to evaluate the classification performance of CAS. Results Of the 76 patients, there was a significant increasing trend (p=0.01) between CAS scores and neurological symptom status. The presence of DLS also demonstrated a significant increasing trend (p&lt0.001) versus CAS with rates 0% (0/7), 7% (2/27), 35% (7/20) and 59% (13/22). ROC analysis of CAS also showed it was a good classifier of symptom status (AUC = 0.67, p=0.01) and DLS (AUC = 0.80, p&lt0.001) Conclusion In this study, we conclude that the CAS computed from clinically collected MRI data can stratify the severity of carotid atherosclerotic disease as indicated by neurological symptom status and DLS, both of which are important in monitoring patients and evaluating treatment options. Further study is needed to assess how a fully automated CAS analysis affects the quality of the score and how well the score can stratify the risk of future outcomes.

Protein Identification Using Customized Protein Sequence Databases Derived from RNA-Seq Data

The standard shotgun proteomics data analysis strategy relies on searching MS/MS spectra against a context-independent protein sequence database derived from the complete genome sequence of an organism. Because transcriptome sequence analysis (RNA-Seq) promises an unbiased and comprehensive picture of the transcriptome, we reason that a sample-specific protein database derived from RNA-Seq data can better approximate the real protein pool in the sample and thus improve protein identification. In this study, we have developed a two-step strategy for building sample-specific protein databases from RNA-Seq data. First, the database size is reduced by eliminating unexpressed or lowly expressed genes according to transcript quantification. Second, high-quality nonsynonymous coding single nucleotide variations (SNVs) are identified based on RNA-Seq data, and corresponding protein variants are added to the database. Using RNA-Seq and shotgun proteomics data from two colorectal cancer cell lines SW480 and RKO, we demonstrated that customized protein sequence databases could significantly increase the sensitivity of peptide identification, reduce ambiguity in protein assembly, and enable the detection of known and novel peptide variants. Thus, sample-specific databases from RNA-Seq data can enable more sensitive and comprehensive protein discovery in shotgun proteomics studies.

A template-based Tabu Search algorithm for the Consistent Vehicle Routing Problem

This paper presents a generic template-based solution framework and its application to the so-called Consistent Vehicle Routing Problem (ConVRP). The ConVRP is an NP-hard combinatorial optimization problem and involves the design of a set of minimum cost vehicle routes to service a set of customers with known demands over multiple days. Customers may receive service either once or with a predefined frequency; however frequent customers must receive consistent service, i.e., must be visited by the same driver over approximately the same time throughout the planning period. The proposed solution framework adopts a two-level master–slave decomposition scheme. Initially, a master template route schedule is constructed in an effort to determine the service sequence and assignment of frequent customers to vehicles. On return, the master template is used as the basis to design the actual vehicle routes and service schedules for both frequent and non-frequent customers over multiple days. To this end, a Tabu Search improvement method is employed that operates on a dual mode basis and modifies both the template routes and the actual daily schedules in a sequential fashion. Computational experiments on benchmark data sets illustrate the competitiveness of the proposed approach compared to existing results.

Single vehicle routing problems with a predefined customer sequence, compartmentalized load and stochastic demands

We consider the problem of finding the optimal routing of a single vehicle that delivers K different products to N customers according to a particular customer order. The demands of the customers for each product are assumed to be random variables with known distributions. Each product type is stored in its dedicated compartment in the vehicle. Using a suitable dynamic programming algorithm we find the policy that satisfies the demands of the customers with the minimum total expected cost. We also prove that this policy has a specific threshold-type structure. Furthermore, we investigate a corresponding infinite-time horizon problem in which the service of the customers does not stop when the last customer has been serviced but it continues indefinitely with the same customer order. It is assumed that the demands of the customers at different tours have the same distributions. It is shown that the discounted-cost optimal policy and the average-cost optimal policy have the same threshold-type structure as the optimal policy in the original problem. The theoretical results are illustrated by numerical examples.

An effective local search approach for the Vehicle Routing Problem with Backhauls

This paper deals with a practical transportation model known as the Vehicle Routing Problem with Backhauls (VRPB), which aims at designing the minimum cost route set for satisfying both delivery and pick-up demands. In methodological terms, we propose a local search metaheuristic which explores rich solution neighborhoods composed of exchanges of variable-length customer sequences. To efficiently investigate these rich solution neighborhoods, tentative local search move are statically encoded by data structures stored in Fibonacci Heaps which are special priority queue structures offering fast minimum retrieval, insertion and deletion capabilities. To avoid cycling phenomena and induce diversification, we introduce the concept of promises, which is a parameter-free mechanism based on the regional aspiration criterion used in Tabu Search implementations. The proposed metaheuristic development was tested on well-known VRPB benchmark instances. It exhibited fine performance, as it consistently generated the best-known solutions for all the examined benchmark problems.

A White Spruce Gene Catalog for Conifer Genome Analyses

Several angiosperm plant genomes, including Arabidopsis (Arabidopsis thaliana), rice (Oryza sativa), poplar (Populus trichocarpa), and grapevine (Vitis vinifera), have been sequenced, but the lack of reference genomes in gymnosperm phyla reduces our understanding of plant evolution and restricts the potential impacts of genomics research. A gene catalog was developed for the conifer tree Picea glauca (white spruce) through large-scale expressed sequence tag sequencing and full-length cDNA sequencing to facilitate genome characterizations, comparative genomics, and gene mapping. The resource incorporates new and publicly available sequences into 27,720 cDNA clusters, 23,589 of which are represented by full-length insert cDNAs. Expressed sequence tags, mate-pair cDNA clone analysis, and custom sequencing were integrated through an iterative process to improve the accuracy of clustering outcomes. The entire catalog spans 30 Mb of unique transcribed sequence. We estimated that the P. glauca nuclear genome contains up to 32,520 transcribed genes owing to incomplete, partially sequenced, and unsampled transcripts and that its transcriptome could span up to 47 Mb. These estimates are in the same range as the Arabidopsis and rice transcriptomes. Next-generation methods confirmed and enhanced the catalog by providing deeper coverage for rare transcripts, by extending many incomplete clusters, and by augmenting the overall transcriptome coverage to 38 Mb of unique sequence. Genomic sample sequencing at 8.5% of the 19.8-Gb P. glauca genome identified 1,495 clusters representing highly repeated sequences among the cDNA clusters. With a conifer transcriptome in full view, functional and protein domain annotations clearly highlighted the divergences between conifers and angiosperms, likely reflecting their respective evolutionary paths.

Stochastic single vehicle routing problem with delivery and pick up and a predefined customer sequence

In this paper we study the routing of a single vehicle that delivers products and picks up items with stochastic demand. The vehicle follows a predefined customer sequence and is allowed to return to the depot for loading/unloading as needed. A suitable dynamic programming algorithm is proposed to determine the minimum expected routing cost. Furthermore, the optimal routing policy to be followed by the vehicle’s driver is derived by proposing an appropriate theorem. The efficiency of the algorithm is studied by solving large problem sets.

An incremental mining algorithm for maintaining sequential patterns using pre-large sequences

Mining useful information and helpful knowledge from large databases has evolved into an important research area in recent years. Among the classes of knowledge derived, finding sequential patterns in temporal transaction databases is very important since it can help model customer behavior. In the past, researchers usually assumed databases were static to simplify data-mining problems. In real-world applications, new transactions may be added into databases frequently. Designing an efficient and effective mining algorithm that can maintain sequential patterns as a database grows is thus important. In this paper, we propose a novel incremental mining algorithm for maintaining sequential patterns based on the concept of pre-large sequences to reduce the need for rescanning original databases. Pre-large sequences are defined by a lower support threshold and an upper support threshold that act as gaps to avoid the movements of sequences directly from large to small and vice versa. The proposed algorithm does not require rescanning original databases until the accumulative amount of newly added customer sequences exceeds a safety bound, which depends on database size. Thus, as databases grow larger, the numbers of new transactions allowed before database rescanning is required also grow. The proposed approach thus becomes increasingly efficient as databases grow.

Molecular diagnosis for heterogeneous genetic diseases with targeted high-throughput DNA sequencing applied to retinitis pigmentosa

BackgroundThe genetic heterogeneity of many Mendelian disorders, such as retinitis pigmentosa which results from mutations in over 40 genes, is a major obstacle to obtaining a molecular diagnosis in clinical...

Lightweight secure multimedia distribution based on homomorphic operations

A secure media distribution scheme is proposed in this paper, which distributes different media copy to different customer in a secure and efficient manner and is able to trace illegal redistribution. At the sender side, media data are scrambled with a random sequence under the control of a secret key. At the receiver side, the scrambled media data are descrambled with a new random sequence under the control of a unique customer code besides the secret key. The scrambling and descrambling strength can be adjusted by the parameter named quantization factor. Generally, the bigger factor is used in scrambling and the smaller one is used in descrambling. After descrambling, the recovered media copy that contains a unique customer sequence, named fingerprint, is slightly different from the original one. This difference is imperceptible to human eyes, while can be detected by computers and used to trace the redistribution of the media copy. Additionally, the unique customer sequence is produced by the collusion-resistant code, which can survive the attacks that combine several copies by averaging. The scheme's performances, including security, imperceptibility, robustness and efficiency, are analyzed and tested in detail. Its good performances make it a suitable choice for lightweight secure multimedia distribution, such as music download, image sharing, live TV or video-on-demand, etc., especially over Mobile terminals.