Combined targeting of MEK and PI3K/mTOR effector pathways is necessary to effectively inhibit NRAS mutant melanoma in vitro and in vivo.

Activating mutations in the neuroblastoma rat sarcoma viral oncogene homolog (NRAS) gene are common genetic events in malignant melanoma being found in 15-25% of cases. NRAS is thought to activate both mitogen activated protein kinase (MAPK) and PI3K signaling in melanoma cells. We studied the influence of different components on the MAP/extracellular signal-regulated (ERK) kinase (MEK) and PI3K/mammalian target of rapamycin (mTOR)-signaling cascade in NRAS mutant melanoma cells. In general, these cells were more sensitive to MEK inhibition compared with inhibition in the PI3K/mTOR cascade. Combined targeting of MEK and PI3K was superior to MEK and mTOR1,2 inhibition in all NRAS mutant melanoma cell lines tested, suggesting that PI3K signaling is more important for cell survival in NRAS mutant melanoma when MEK is inhibited. However, targeting of PI3K/mTOR1,2 in combination with MEK inhibitors is necessary to effectively abolish growth of NRAS mutant melanoma cells in vitro and regress xenografted NRAS mutant melanoma. Furthermore, we showed that MEK and PI3K/mTOR1,2 inhibition is synergistic. Expression analysis confirms that combined MEK and PI3K/mTOR1,2 inhibition predominantly influences genes in the rat sarcoma (RAS) pathway and growth factor receptor pathways, which signal through MEK/ERK and PI3K/mTOR, respectively. Our results suggest that combined targeting of the MEK/ERK and PI3K/mTOR pathways has antitumor activity and might serve as a therapeutic option in the treatment of NRAS mutant melanoma, for which there are currently no effective therapies.

Assemblathon 1: a competitive assessment of de novo short read assembly methods.

Low-cost short read sequencing technology has revolutionized genomics, though it is only just becoming practical for the high-quality de novo assembly of a novel large genome. We describe the Assemblathon 1 competition, which aimed to comprehensively assess the state of the art in de novo assembly methods when applied to current sequencing technologies. In a collaborative effort, teams were asked to assemble a simulated Illumina HiSeq data set of an unknown, simulated diploid genome. A total of 41 assemblies from 17 different groups were received. Novel haplotype aware assessments of coverage, contiguity, structure, base calling, and copy number were made. We establish that within this benchmark: (1) It is possible to assemble the genome to a high level of coverage and accuracy, and that (2) large differences exist between the assemblies, suggesting room for further improvements in current methods. The simulated benchmark, including the correct answer, the assemblies, and the code that was used to evaluate the assemblies is now public and freely available from http://www.assemblathon.org/.

RNA-Seq analysis of splicing in Plasmodium falciparum uncovers new splice junctions, alternative splicing and splicing of antisense transcripts.

Over 50% of genes in Plasmodium falciparum, the deadliest human malaria parasite, contain predicted introns, yet experimental characterization of splicing in this organism remains incomplete. We present here a transcriptome-wide characterization of intraerythrocytic splicing events, as captured by RNA-Seq data from four timepoints of a single highly synchronous culture. Gene model-independent analysis of these data in conjunction with publically available RNA-Seq data with HMMSplicer, an in-house developed splice site detection algorithm, revealed a total of 977 new 5' GU-AG 3' and 5 new 5' GC-AG 3' junctions absent from gene models and ESTs (11% increase to the current annotation). In addition, 310 alternative splicing events were detected in 254 (4.5%) genes, most of which truncate open reading frames. Splicing events antisense to gene models were also detected, revealing complex transcriptional arrangements within the parasite's transcriptome. Interestingly, antisense introns overlap sense introns more than would be expected by chance, perhaps indicating a functional relationship between overlapping transcripts or an inherent organizational property of the transcriptome. Independent experimental validation confirmed over 30 new antisense and alternative junctions. Thus, this largest assemblage of new and alternative splicing events to date in Plasmodium falciparum provides a more precise, dynamic view of the parasite's transcriptome.

RNA-seq analyses of blood-induced changes in gene expression in the mosquito vector species, Aedes aegypti.

BACKGROUND: Hematophagy is a common trait of insect vectors of disease. Extensive genome-wide transcriptional changes occur in mosquitoes after blood meals, and these are related to digestive and reproductive processes, among others. Studies of these changes are expected to reveal molecular targets for novel vector control and pathogen transmission-blocking strategies. The mosquito Aedes aegypti (Diptera, Culicidae), a vector of Dengue viruses, Yellow Fever Virus (YFV) and Chikungunya virus (CV), is the subject of this study to look at genome-wide changes in gene expression following a blood meal. RESULTS: Transcriptional changes that follow a blood meal in Ae. aegypti females were explored using RNA-seq technology. Over 30% of more than 18,000 investigated transcripts accumulate differentially in mosquitoes at five hours after a blood meal when compared to those fed only on sugar. Forty transcripts accumulate only in blood-fed mosquitoes. The list of regulated transcripts correlates with an enhancement of digestive activity and a suppression of environmental stimuli perception and innate immunity. The alignment of more than 65 million high-quality short reads to the Ae. aegypti reference genome permitted the refinement of the current annotation of transcript boundaries, as well as the discovery of novel transcripts, exons and splicing variants. Cis-regulatory elements (CRE) and cis-regulatory modules (CRM) enriched significantly at the 5'end flanking sequences of blood meal-regulated genes were identified. CONCLUSIONS: This study provides the first global view of the changes in transcript accumulation elicited by a blood meal in Ae. aegypti females. This information permitted the identification of classes of potentially co-regulated genes and a description of biochemical and physiological events that occur immediately after blood feeding. The data presented here serve as a basis for novel vector control and pathogen transmission-blocking strategies including those in which the vectors are modified genetically to express anti-pathogen effector molecules.

High Rhodotorula sequences in skin transcriptome of patients with diffuse systemic sclerosis.

Previous studies have suggested a role for pathogens as a trigger of systemic sclerosis (SSc), although neither a pathogen nor a mechanism of pathogenesis is known. Here we show enrichment of Rhodotorula sequences in the skin of patients with early, diffuse SSc compared with that in normal controls. RNA-seq was performed on four SSc patients and four controls, to a depth of 200 million reads per patient. Data were analyzed to quantify the nonhuman sequence reads in each sample. We found little difference between bacterial microbiome and viral read counts, but found a significant difference between the read counts for a mycobiome component, R. glutinis. Normal samples contained almost no detected R. glutinis or other Rhodotorula sequence reads (mean score 0.021 for R. glutinis, 0.024 for all Rhodotorula). In contrast, SSc samples had a mean score of 5.039 for R. glutinis (5.232 for Rhodotorula). We were able to assemble the D1-D2 hypervariable region of the 28S ribosomal RNA (rRNA) of R. glutinis from each of the SSc samples. Taken together, these results suggest that R. glutinis may be present in the skin of early SSc patients at higher levels than in normal skin, raising the possibility that it may be triggering the inflammatory response found in SSc.

IMSA: integrated metagenomic sequence analysis for identification of exogenous reads in a host genomic background.

Metagenomics, the study of microbial genomes within diverse environments, is a rapidly developing field. The identification of microbial sequences within a host organism enables the study of human intestinal, respiratory, and skin microbiota, and has allowed the identification of novel viruses in diseases such as Merkel cell carcinoma. There are few publicly available tools for metagenomic high throughput sequence analysis. We present Integrated Metagenomic Sequence Analysis (IMSA), a flexible, fast, and robust computational analysis pipeline that is available for public use. IMSA takes input sequence from high throughput datasets and uses a user-defined host database to filter out host sequence. IMSA then aligns the filtered reads to a user-defined universal database to characterize exogenous reads within the host background. IMSA assigns a score to each node of the taxonomy based on read frequency, and can output this as a taxonomy report suitable for cluster analysis or as a taxonomy map (TaxMap). IMSA also outputs the specific sequence reads assigned to a taxon of interest for downstream analysis. We demonstrate the use of IMSA to detect pathogens and normal flora within sequence data from a primary human cervical cancer carrying HPV16, a primary human cutaneous squamous cell carcinoma carrying HPV 16, the CaSki cell line carrying HPV16, and the HeLa cell line carrying HPV18.

ReCombine: a suite of programs for detection and analysis of meiotic recombination in whole-genome datasets.

In meiosis, the exchange of DNA between chromosomes by homologous recombination is a critical step that ensures proper chromosome segregation and increases genetic diversity. Products of recombination include reciprocal exchanges, known as crossovers, and non-reciprocal gene conversions or non-crossovers. The mechanisms underlying meiotic recombination remain elusive, largely because of the difficulty of analyzing large numbers of recombination events by traditional genetic methods. These traditional methods are increasingly being superseded by high-throughput techniques capable of surveying meiotic recombination on a genome-wide basis. Next-generation sequencing or microarray hybridization is used to genotype thousands of polymorphic markers in the progeny of hybrid yeast strains. New computational tools are needed to perform this genotyping and to find and analyze recombination events. We have developed a suite of programs, ReCombine, for using short sequence reads from next-generation sequencing experiments to genotype yeast meiotic progeny. Upon genotyping, the program CrossOver, a component of ReCombine, then detects recombination products and classifies them into categories based on the features found at each location and their distribution among the various chromatids. CrossOver is also capable of analyzing segregation data from microarray experiments or other sources. This package of programs is designed to allow even researchers without computational expertise to use high-throughput, whole-genome methods to study the molecular mechanisms of meiotic recombination.

HMMSplicer: a tool for efficient and sensitive discovery of known and novel splice junctions in RNA-Seq data.

BACKGROUND: High-throughput sequencing of an organism's transcriptome, or RNA-Seq, is a valuable and versatile new strategy for capturing snapshots of gene expression. However, transcriptome sequencing creates a new class of alignment problem: mapping short reads that span exon-exon junctions back to the reference genome, especially in the case where a splice junction is previously unknown. METHODOLOGY/PRINCIPAL FINDINGS: Here we introduce HMMSplicer, an accurate and efficient algorithm for discovering canonical and non-canonical splice junctions in short read datasets. HMMSplicer identifies more splice junctions than currently available algorithms when tested on publicly available A. thaliana, P. falciparum, and H. sapiens datasets without a reduction in specificity. CONCLUSIONS/SIGNIFICANCE: HMMSplicer was found to perform especially well in compact genomes and on genes with low expression levels, alternative splice isoforms, or non-canonical splice junctions. Because HHMSplicer does not rely on pre-built gene models, the products of inexact splicing are also detected. For H. sapiens, we find 3.6% of 3' splice sites and 1.4% of 5' splice sites are inexact, typically differing by 3 bases in either direction. In addition, HMMSplicer provides a score for every predicted junction allowing the user to set a threshold to tune false positive rates depending on the needs of the experiment. HMMSplicer is implemented in Python. Code and documentation are freely available at http://derisilab.ucsf.edu/software/hmmsplicer.