Whole genome and exome sequencing of melanoma

Melanoma has historically been refractive to traditional therapeutic approaches. As such, the development of novel drug strategies has been needed to improve rates of overall survival in patients with melanoma, particularly those with late stage or disseminated disease. Recent success with molecularly based targeted drugs, such as Vemurafenib in BRAF-mutant melanomas, has now made “personalized medicine” a reality within some oncology clinics. In this sense, tailored drugs can be administered to patients according to their tumor “mutation profiles.” The success of these drug strategies, in part, can be attributed to the identification of the genetic mechanisms responsible for the development and progression of metastatic melanoma. Recently, the advances in sequencing technology have allowed for comprehensive mutation analysis of tumors and have led to the identification of a number of genes involved in the etiology of metastatic melanoma. As the methodology and costs associated with next-generation sequencing continue to improve, this technology will be rapidly adopted into routine clinical oncology practices and will significantly impact on personalized therapy. This review summarizes current and emerging molecular targets in metastatic melanoma, discusses the potential application of next-generation sequencing within the paradigm of personalized medicine, and describes the current limitations for the adoption of this technology within the clinic.

Facile mutant identification via a single parental backcross method and application of whole genome sequencing based mapping pipelines

Forward genetic screens have identified numerous genes involved in development and metabolism, and remain a cornerstone of biological research. However, to locate a causal mutation, the practice of crossing to a polymorphic background to generate a mapping population can be problematic if the mutant phenotype is difficult to recognize in the hybrid F2 progeny, or dependent on parental specific traits. Here in a screen for leaf hyponasty mutants, we have performed a single backcross of an Ethane Methyl Sulphonate (EMS) generated hyponastic mutant to its parent. Whole genome deep sequencing of a bulked homozygous F2 population and analysis via the Next Generation EMS mutation mapping pipeline (NGM) unambiguously determined the causal mutation to be a single nucleotide polymorphisim (SNP) residing in HASTY, a previously characterized gene involved in microRNA biogenesis. We have evaluated the feasibility of this backcross approach using three additional SNP mapping pipelines; SHOREmap, the GATK pipeline, and the samtools pipeline. Although there was variance in the identification of EMS SNPs, all returned the same outcome in clearly identifying the causal mutation in HASTY. The simplicity of performing a single parental backcross and genome sequencing a small pool of segregating mutants has great promise for identifying mutations that may be difficult to map using conventional approaches.

Small RNA sequencing of potato leafroll virus-infected plants reveals an additional subgenomic RNA encoding a sequence-specific RNA-binding protein

Potato leafroll virus (PLRV) is a positive-strand RNA virus that generates subgenomic RNAs (sgRNA) for expression of 3' proximal genes. Small RNA (sRNA) sequencing and mapping of the PLRV-derived sRNAs revealed coverage of the entire viral genome with the exception of four distinctive gaps. Remarkably, these gaps mapped to areas of PLRV genome with extensive secondary structures, such as the internal ribosome entry site and 5' transcriptional start site of sgRNA1 and sgRNA2. The last gap mapped to ~500. nt from the 3' terminus of PLRV genome and suggested the possible presence of an additional sgRNA for PLRV. Quantitative real-time PCR and northern blot analysis confirmed the expression of sgRNA3 and subsequent analyses placed its 5' transcriptional start site at position 5347 of PLRV genome. A regulatory role is proposed for the PLRV sgRNA3 as it encodes for an RNA-binding protein with specificity to the 5' of PLRV genomic RNA. © 2013.

Sequencing risk : the worst returns in their worst order

For the first of the baby boomers turning 65 years of age, after a decade littered with financial shocks (dot.com bubble, sub-prime, global financial crisis, sovereign debt), sequencing risk can represent a significant threat to their retirement nest eggs. This paper takes an outcomeoriented approach to the problem, to provide practical insights into how sequencing risk works and the critical dependency of retirement outcomes on sequencing risk. Our analysis challenges the conventional wisdom that it is the accumulated average of investment returns that matter. We show, instead, that it is the realised sequence of returns which largely determines the sustainability of retirement incomes.

Whole-genome sequencing reveals untapped genetic potential in Africa’s indigenous cereal crop sorghum

Sorghum is a food and feed cereal crop adapted to heat and drought and a staple for 500 million of the world’s poorest people. Its small diploid genome and phenotypic diversity make it an ideal C4 grass model as a complement to C3 rice. Here we present high coverage (16–45 × ) resequenced genomes of 44 sorghum lines representing the primary gene pool and spanning dimensions of geographic origin, end-use and taxonomic group. We also report the first resequenced genome of S. propinquum, identifying 8 M high-quality SNPs, 1.9 M indels and specific gene loss and gain events in S. bicolor. We observe strong racial structure and a complex domestication history involving at least two distinct domestication events. These assembled genomes enable the leveraging of existing cereal functional genomics data against the novel diversity available in sorghum, providing an unmatched resource for the genetic improvement of sorghum and other grass species.

Supplementary material : large scale read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

Source code watermarking based on function dependency oriented sequencing

In the current market, extensive software development is taking place and the software industry is thriving. Major software giants have stated source code theft as a major threat to revenues. By inserting an identity-establishing watermark in the source code, a company can prove it's ownership over the source code. In this paper, we propose a watermarking scheme for C/C++ source codes by exploiting the language restrictions. If a function calls another function, the latter needs to be defined in the code before the former, unless one uses function pre-declarations. We embed the watermark in the code by imposing an ordering on the mutually independent functions by introducing bogus dependency. Removal of dependency by the attacker to erase the watermark requires extensive manual intervention thereby making the attack infeasible. The scheme is also secure against subtractive and additive attacks. Using our watermarking scheme, an n-bit watermark can be embedded in a program having n independent functions. The scheme is implemented on several sample codes and performance changes are analyzed.

An integrated approach for earthwork allocation, sequencing and routing

Planning techniques for large scale earthworks have been considered in this article. To improve these activities a “block theoretic” approach was developed that provides an integrated solution consisting of an allocation of cuts to fills and a sequence of cuts and fills over time. It considers the constantly changing terrain by computing haulage routes dynamically. Consequently more realistic haulage costs are used in the decision making process. A digraph is utilised to describe the terrain surface which has been partitioned into uniform grids. It reflects the true state of the terrain, and is altered after each cut and fill. A shortest path algorithm is successively applied to calculate the cost of each haul, and these costs are summed over the entire sequence, to provide a total cost of haulage. To solve this integrated optimisation problem a variety of solution techniques were applied, including constructive algorithms, meta-heuristics and parallel programming. The extensive numerical investigations have successfully shown the applicability of our approach to real sized earthwork problems.

N-terminal acetylome analyses and functional insights of the N-terminal acetyltransferase NatB

Protein N-terminal acetylation (Nt-acetylation) is an important mediator of protein function, stability, sorting, and localization. Although the responsible enzymes are thought to be fairly well characterized, the lack of identified in vivo substrates, the occurrence of Nt-acetylation substrates displaying yet uncharacterized N-terminal acetyltransferase (NAT) specificities, and emerging evidence of posttranslational Nt-acetylation, necessitate the use of genetic models and quantitative proteomics. NatB, which targets Met-Glu-, Met-Asp-, and Met-Asn-starting protein N termini, is presumed to Nt-acetylate 15% of all yeast and 18% of all human proteins. We here report on the evolutionary traits of NatB from yeast to human and demonstrate that ectopically expressed hNatB in a yNatB-Δ yeast strain partially complements the natB-Δ phenotypes and partially restores the yNatB Nt-acetylome. Overall, combining quantitative N-terminomics with yeast studies and knockdown of hNatB in human cell lines, led to the unambiguous identification of 180 human and 110 yeast NatB substrates. Interestingly, these substrates included Met-Gln- N-termini, which are thus now classified as in vivo NatB substrates. We also demonstrate the requirement of hNatB activity for maintaining the structure and function of actomyosin fibers and for proper cellular migration. In addition, expression of tropomyosin-1 restored the altered focal adhesions and cellular migration defects observed in hNatB-depleted HeLa cells, indicative for the conserved link between NatB, tropomyosin, and actin cable function from yeast to human.

Applying a validation framework to a working airport terminal model

Validation is an important issue in the development and application of Bayesian Belief Network (BBN) models, especially when the outcome of the model cannot be directly observed. Despite this, few frameworks for validating BBNs have been proposed and fewer have been applied to substantive real-world problems. In this paper we adopt the approach by Pitchforth and Mengersen (2013), which includes nine validation tests that each focus on the structure, discretisation, parameterisation and behaviour of the BBNs included in the case study. We describe the process and result of implementing a validation framework on a model of a real airport terminal system with particular reference to its effectiveness in producing a valid model that can be used and understood by operational decision makers. In applying the proposed validation framework we demonstrate the overall validity of the Inbound Passenger Facilitation Model as well as the effectiveness of the validity framework itself.

Large scale read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

Role of the N-terminal region in G protein-coupled receptor functions : negative modulation revealed by 5-HT2B receptor polymorphisms

The putative role of the N-terminal region of rhodopsin-like 7 transmembrane biogenic amine receptors in agonist-induced signaling has not yet been clarified despite recent advances in 7 transmembrane receptor structural biology. Given the existence of N-terminal nonsynonymous polymorphisms (R6G;E42G) within the HTR2B gene in a drug-abusing population, we assessed whether these polymorphisms affect 5-hydroxytryptamine 2B (5-HT2B) receptor in vitro pharmacologic and coupling properties in transfected COS-7 cells. Modification of the 5-HT2B receptor N terminus by the R6G;E42G polymorphisms increases such agonist signaling pathways as inositol phosphate accumulation as assessed by either classic or operational models. The N-terminal R6G;E42G mutations of the 5-HT2B receptor also increase cell proliferation and slow its desensitization kinetics compared with the wild-type receptor, further supporting a role for the N terminus in transduction efficacy. Furthermore, by coexpressing a tethered wild-type 5-HT2B receptor N terminus with a 5-HT2B receptor bearing a N-terminal deletion, we were able to restore original coupling. This reversion to normal activity of a truncated 5-HT2B receptor by coexpression of the membrane-tethered wild-type 5-HT2B receptor N terminus was not observed using a membrane-tethered 5-HT2B receptor R6G;E42G N terminus. These data suggest that the N terminus exerts a negative control over basal as well as agonist-stimulated receptor activity that is lost in the R6G;E42G mutant. Our findings reveal a new and unanticipated role of the 5-HT2B receptor N terminus as a negative modulator, affecting both constitutive and agonist-stimulated activity. Moreover, our data caution against excluding the N terminus and extracellular loops in structural studies of this 7 transmembrane receptor family

miRPlant : an integrated tool for identification of plant miRNA from RNA sequencing data

Background Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction. Result We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram. Conclusions We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.