Bioinformatics Monitor

Dissection of Dom34–Hbs1 reveals independent functions in two RNA quality control pathways

2010-11-24T13:43:00.000-08:00

Eukaryotic cells have several quality control pathways that rely on translation to detect and degrade defective RNAs. Dom34 and Hbs1 are two proteins that are related to translation termination factors and are involved in no-go decay (NGD) and nonfunctional 18S ribosomal RNA (rRNA) decay (18S NRD) pathways that eliminate RNAs that cause strong ribosomal stalls. Here we present the structure of Hbs1 with and without GDP and a low-resolution model of the Dom34–Hbs1 complex. This complex mimics complexes of the elongation factor and transfer RNA or of the translation termination factors eRF1 and eRF3, supporting the idea that it binds to the ribosomal A-site. Scientists show that nucleotide binding by Hbs1 is essential for NGD and 18S NRD. Mutations in Hbs1 that disrupted the interaction between Dom34 and Hbs1 strongly impaired NGD but had almost no effect on 18S NRD. Hence, NGD and 18S NRD could be genetically uncoupled, suggesting that mRNA and rRNA in a stalled translation complex may not always be degraded simultaneously.

Mre11–Rad50–Xrs2 and Sae2 promote 5′ strand resection of DNA double-strand breaks

2010-11-23T14:02:00.000-08:00

The repair of DNA double-strand breaks (DSBs) by homologous recombination is essential for genomic stability. The first step in this process is resection of 5′ strands to generate 3′ single-stranded DNA intermediates. Efficient resection in budding yeast requires the Mre11–Rad50–Xrs2 (MRX) complex and the Sae2 protein, although the role of MRX has been unclear because Mre11 paradoxically has 3′5′ exonuclease activity in vitro. Here scientists reconstitute resection with purified MRX, Sae2 and Exo1 proteins and show that degradation of the 5′ strand is catalyzed by Exo1 yet completely dependent on MRX and Sae2 when Exo1 levels are limiting. This stimulation is mainly caused by cooperative binding of DNA substrates by Exo1, MRX and Sae2. This work establishes the direct role of MRX and Sae2 in promoting the resection of 5′ strands in DNA DSB repair.

The G Protein regulators EGL-10 and EAT-16, the Gialpha GOA-1 and the Gqalpha EGL-30

2010-11-23T13:55:00.000-08:00

Polymodal, nociceptive sensory neurons are key cellular elements of the way animals sense aversive and painful stimuli. In Caenorhabditis elegans, the polymodal nociceptive ASH sensory neurons detect aversive stimuli and release glutamate to generate avoidance responses. They are thus useful models for the nociceptive neurons of mammals. While several molecules affecting signal generation and transduction in ASH have been identified, less is known about transmission of the signal from ASH to downstream neurons and about the molecules involved in its modulation.

Researchers discovered that the regulator of G protein signalling (RGS) protein, EGL-10, is required for appropriate avoidance responses to noxious stimuli sensed by ASH. As it does for other behaviours in which it is also involved, egl-10 interacts genetically with the Go/ialpha protein GOA-1, the Gqalpha protein EGL-30 and the RGS EAT-16. Genetic, behavioural and Ca2+ imaging analyses of ASH neurons in live animals demonstrate that, within ASH, EGL-10 and GOA-1 act downstream of stimulus-evoked signal transduction and of the main transduction channel OSM-9. EGL-30 instead appears to act upstream by regulating Ca2+ transients in response to aversive stimuli. Analysis of the delay in the avoidance response, of the frequency of spontaneous inversions and of the genetic interaction with the diacylglycerol kinase gene, dgk-1, indicate that EGL-10 and GOA-1 do not affect signal transduction and neuronal depolarization in response to aversive stimuli but act in ASH to modulate downstream transmission of the signal. The ASH polymodal nociceptive sensory neurons can be modulated not only in their capacity to detect stimuli but also in the efficiency with which they respond to them. The Galpha and RGS molecules studied in this work are conserved in evolution and, for each of them, mammalian orthologs can be identified. The discovery of their role in the modulation of signal transduction and signal transmission of nociceptors may help us to understand how pain is generated and how its control can go astray (such as chronic pain) and may suggest new pain control therapies.

Transcriptional regulation of BRCA1 expression by a metabolic switch

2010-11-23T13:36:00.000-08:00

Though the linkages between germline mutations of BRCA1 and hereditary breast cancer are well known, recent evidence suggests that altered BRCA1 transcription may also contribute to sporadic forms of breast cancer. Here we show that BRCA1expression is controlled by a dynamic equilibrium between transcriptional coactivators and co-repressors that govern histone acetylation and DNA accessibility at the BRCA1 promoter. Eviction of the transcriptional co-repressor and metabolic sensor, C terminal–binding protein (CtBP), has a central role in this regulation. Loss of CtBP from the BRCA1 promoter through estrogen induction, depletion by RNA interference or increased NAD+/NADH ratio leads to HDAC1 dismissal, elevated histone acetylation and increased BRCA1 transcription. The active control of chromatin marks, DNA accessibility and gene expression at theBRCA1 promoter by this 'metabolic switch' provides an important molecular link between caloric intake and tumor suppressor expression in mammary cells.

A Computational Approach to Analyze the Mechanism of Action of the Kinase Inhibitor Bafetinib

2010-11-20T12:36:00.000-08:00

Prediction of drug action in human cells is a major challenge in biomedical research. Additionally, there is strong interest in finding new applications for approved drugs and identifying potential side effects. Scientists present a computational strategy to predict mechanisms, risks and potential new domains of drug treatment on the basis of target profiles acquired through chemical proteomics. Functional protein-protein interaction networks that share one biological function are constructed and their crosstalk with the drug is scored regarding function disruption. They apply this procedure to the target profile of the second-generation BCR-ABL inhibitor bafetinib which is in development for the treatment of imatinib-resistant chronic myeloid leukemia. Beside the well known effect on apoptosis, they propose potential treatment of lung cancer and IGF1R expressing blast crisis.

Protein interaction data are accumulating rapidly and, although imperfect and incomplete, they provide a valuable global description of the complex interplay of proteins in a human cell. In parallel, modern proteomics technologies make it possible to measure in an unbiased manner the protein targets of a drug. Such data reveal multiple targets in a view that contrasts with a previously prevalent paradigm that drugs had single – or a very limited number of – targets. In this context of newly available systems level data and more precise and complete information about drug interactions, it is natural to try to determine the global perturbation exerted by a drug on a human cell to identify potential side effects and additional indications. They present a computational method that aims at making such predictions and apply it to bafetinib, a recently developed leukemia drug. Researchers show that meaningful predictions of additional applications to other cancers or resistant cases and likely side effects are obtained that are not straightforward to determine with existing algorithms. Our method has a strong potential to be applicable to other drugs.

Gene expression in developing fibers of Upland cotton (Gossypium hirsutum L.)

2010-11-17T16:14:00.000-08:00

Understanding the genetics of modern crop phenotypes has a dual relevance to biology and crop improvement. Modern upland cotton (Gossypium hirsutum L.) was developed following thousands of years of artificial selection from a wild form, G. hirsutum var. yucatanense, which bears a shorter, sparser, layer of single-celled, ovular trichomes ('fibre'). In order to gain an insight into the nature of the developmental genetic transformations that accompanied domestication and crop improvement, we studied the transcriptomes of cotton fibres from wild and domesticated accessions over a developmental time course.

Fibre cells were harvested between 2 and 25 days post-anthesis and encompassed the primary and secondary wall synthesis stages. Using amplified messenger RNA and a custom microarray platform designed to interrogate expression for 40,430 genes, we determined global patterns of expression during fibre development. The fibre transcriptome of domesticated cotton is far more dynamic than that of wild cotton, with over twice as many genes being differentially expressed during development (12,626 versus 5273). Remarkably, a total of 9465 genes were diagnosed as differentially expressed between wild and domesticated fibres when summed across five key developmental time points. Human selection during the initial domestication and subsequent crop improvement has resulted in a biased upregulation of components of the transcriptional network that are important for agronomically advanced fibre, especially in the early stages of development. About 15% of the differentially expressed genes in wild versus domesticated cotton fibre have no homology to the genes in databases.

Systematic Inference of Copy-Number Genotypes from Personal Genome Sequencing

2010-11-12T13:26:00.000-08:00

Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel computational approach with an underlying statistical framework that analyzes the depth-of-coverage of high-throughput DNA sequencing reads, and can incorporate paired-end and breakpoint junction analysis based CNV-analysis approaches, to infer locus copy-number genotypes. Researchers benchmarked CopySeq by genotyping 500 chromosome 1 CNV regions in 150 personal genomes sequenced at low-coverage. The assessed copy-number genotypes were highly concordant with our performed qPCR experiments (Pearson correlation coefficient 0.94), and with the published results of two microarray platforms (95–99% concordance). They further demonstrated the utility of CopySeq for analyzing gene regions enriched for segmental duplications by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci. CopySeq revealed that OR loci display an extensive range of locus copy-numbers across individuals, with zero to two copies in some OR loci, and two to nine copies in others. Among genetic variants affecting OR loci we identified deleterious variants including CNVs and SNPs affecting ~15% and ~20% of the human OR gene repertoire, respectively, implying that genetic variants with a possible impact on smell perception are widespread. Finally, scientists found that for several OR loci the reference genome appears to represent a minor-frequency variant, implying a necessary revision of the OR repertoire for future functional studies. CopySeq can ascertain genomic structural variation in specific gene families as well as at a genome-wide scale, where it may enable the quantitative evaluation of CNVs in genome-wide association studies involving high-throughput sequencing.

Reduced Rif2 and lack of Mec1 target short telomeres for elongation

2010-11-10T15:40:00.000-08:00

Telomerase in Saccharomyces cerevisiae binds and preferentially elongates short telomeres, and this process requires the checkpoint kinase Tel1. Here scientists show that the Mre11 complex bound preferentially to short telomeres, which could explain the preferential binding of Tel1 to these ends. Compared to wild-type length telomeres, short telomeres generated by incomplete replication had low levels of the telomerase inhibitory protein Rif2. Moreover, in the absence of Rif2, Tel1 bound equally well to short and wild-type length telomeres, suggesting that low Rif2 content marks short telomeres for preferential elongation. In congenic strains, a double-strand break bound at least 140 times as much Mec1 in the first cell cycle after breakage as did a short telomere in the same time frame. Binding of replication protein A was also much lower at short telomeres. The absence of Mec1 at short telomeres could explain why they do not trigger a checkpoint-mediated cell-cycle arrest.

Interleukin-13 receptor alpha2 DNA prime boost vaccine induces tumor immunity (JTM)

2010-11-10T15:34:00.000-08:00

DNA vaccines represent an attractive approach for cancer treatment by inducing active T cell and B cell immune responses to tumor antigens. Previous studies have shown that interleukin-13 receptor alpha2 chain (IL-13Ralpha2), a tumor-associated antigen is a promising target for cancer immunotherapy as high levels of IL-13Ralpha2 are expressed on a variety of human tumors. To enhance the effectiveness of DNA vaccine, we used extracellular domain of IL-13Ralpha2 (ECDalpha2) as a protein-boost against murine tumor models. Researchers developed murine models of tumors naturally expressing IL13Ralpha2 (MCA304 sarcoma, 4T1 breast carcinoma and D5 melanoma) in syngeneic mice and examined the antitumor activity of DNA vaccine expressing IL-13Ralpha2 gene with or without ECDalpha2 protein mixed with CpG and IFA adjuvants as a boost vaccine.

Mice receiving IL-13Ralpha2 DNA vaccine boosted with ECDalpha2 protein were superior in exhibiting inhibition of tumor growth, compared to mice receiving DNA vaccine alone, in both prophylactic and therapeutic vaccine settings. In addition, prime-boost vaccination significantly prolonged the survival of mice compared to DNA vaccine alone. Furthermore, ECDalpha2 booster vaccination increased the induction of specific IFN-gamma production and CTL activity to tumor expressing IL-13Ralpha2. The immunohistochemical analysis showed the infiltration of CD4 and CD8 positive T cells and IFN-gamma-induced chemokines (CXCL9 and CXCL10) in regressing tumors of immunized mice. Finally, the prime boost strategy was able to reduce immunosuppressive CD4+CD25+FoxP3+ regulatory T cells (Tregs) in the spleen and tumor of vaccinated mice. These results suggest that immunization with IL-13Ralpha2 DNA vaccine followed by ECDalpha2 boost mixed with CpG and IFA adjuvants inhibits tumor growth in T cell dependent manner. Their results show an enhancement of efficacy of IL-13Ralpha2 DNA vaccine with ECDalpha2 protein boost and offers an exciting approach in the development of new DNA vaccine targeting IL-13Ralpha2 for cancer immunotherapy.

Correlated conformational events in EF-G and the ribosome regulate translocation

2010-11-09T12:47:00.000-08:00

In bacteria, the translocation of tRNA and mRNA with respect to the ribosome is catalyzed by the conserved GTPase elongation factor-G (EF-G). To probe the rate-determining features in this process, we imaged EF-G–catalyzed translocation from two unique structural perspectives using single-molecule fluorescence resonance energy transfer. The data reveal that the rate at which the ribosome spontaneously achieves a transient, 'unlocked' state is closely correlated with the rate at which the tRNA-like domain IV-V element of EF-G engages the A site. After these structural transitions, translocation occurs comparatively fast, suggesting that conformational processes intrinsic to the ribosome determine the rate of translocation. Experiments conducted in the presence of non-hydrolyzable GTP analogs and specific antibiotics further reveal that allosterically linked conformational events in EF-G and the ribosome mediate rapid, directional substrate movement and EF-G release.

H2A.Z nucleosomes enriched over active genes are homotypic

2010-11-08T13:47:00.000-08:00

Nucleosomes that contain the histone variant H2A.Z are enriched around transcriptional start sites, but the mechanistic basis for this enrichment is unknown. A single octameric nucleosome can contain two H2A.Z histones (homotypic) or one H2A.Z and one canonical H2A (heterotypic). To elucidate the function of H2A.Z, we generated high-resolution maps of homotypic and heterotypic Drosophila H2A.Z (H2Av) nucleosomes. Although homotypic and heterotypic H2A.Z nucleosomes mapped throughout most of the genome, homotypic nucleosomes were enriched and heterotypic nucleosomes were depleted downstream of active promoters and intron-exon junctions. The distribution of homotypic H2A.Z nucleosomes resembled that of classical active chromatin and showed evidence of disruption during transcriptional elongation. Both homotypic H2A.Z nucleosomes and classical active chromatin were depleted downstream of paused polymerases. Results suggest that H2A.Z enrichment patterns result from intrinsic structural differences between heterotypic and homotypic H2A.Z nucleosomes that follow disruption during transcriptional elongation.

Modeling compositional dynamics based on GC and purine contents of protein-coding sequences

2010-11-08T12:29:00.000-08:00

Understanding the compositional dynamics of genomes and their coding sequences is of great significance in gaining clues into molecular evolution and a large number of publically-available genome sequences have allowed us to quantitatively predict deviations of empirical data from their theoretical counterparts. However, the quantification of theoretical compositional variations for a wide diversity of genomes remains a major challenge.

To model the compositional dynamics of protein-coding sequences, researchers propose two simple models that take into account both mutation and selection effects, which act differently at the three codon positions, and use both GC and purine contents as compositional parameters. The two models concern the theoretical composition of nucleotides, codons, and amino acids, with no prerequisite of homologous sequences or their alignments. We evaluated the two models by quantifying theoretical compositions of a large collection of protein-coding sequences (including 46 of Archaea, 686 of Bacteria, and 826 of Eukarya), yielding consistent theoretical compositions across all the collected sequences. Scientists show that the compositions of nucleotides, codons, and amino acids are largely determined by both GC and purine contents and suggest that deviations of the observed from the expected compositions may reflect compositional signatures that arise from a complex interplay between mutation and selection via DNA replication and repair mechanisms.

Role of aspartyl-(asparaginyl)- beta-hydroxylase mediated Notch signaling in cerebellar development

2010-11-04T15:03:00.000-07:00

Aspartyl-(Asparaginyl)-beta-Hydroxylase (AAH) is a hydroxylating enzyme that promotes cell motility by enhancing Notch-Jagged-HES-1 signaling. Ethanol impaired cerebellar neuron migration during development is associated with reduced expression of AAH. To further characterize the role of AAH in relation to cerebellar development, structure, and function, scientists utilized an in vivo model of early postnatal (P2) intracerebro-ventricular gene delivery to silence AAH with small interfering RNA (siAAH), or over-express it with recombinant plasmid DNA (pAAH). On P20, researchers assessed cerebellar motor function by rotarod testing. Cerebella harvested on P21 were used to measure AAH, genes/proteins that mediate AAH's downstream signaling, i.e. Notch-1, Jagged-1, and HES-1, and immunoreactivity corresponding to neuronal and glial elements.

The findings demonstrated that: 1) siAAH transfection impaired motor performance and blunted cerebellar foliation, and decreased expression of neuronal and glial specific genes; 2) pAAH transfection enhanced motor performance and increased expression of neuronal and glial cytoskeletal proteins; and 3) alterations in AAH expression produced similar shifts in Notch-1, Jagged-1, and HES-1 protein or gene expression. The results support the hypothesis that AAH is an important mediator of cerebellar development and function, and link AAH expression to Notch signaling pathways in the developing brain.

Genome-Wide Association Study of Blood Pressure Extremes Identifies Variant near UMOD

2010-11-02T13:42:00.000-07:00

Hypertension is a heritable and major contributor to the global burden of disease. The sum of rare and common genetic variants robustly identified so far explain only 1%–2% of the population variation in BP and hypertension. This suggests the existence of more undiscovered common variants. Researchers conducted a genome-wide association study in 1,621 hypertensive cases and 1,699 controls and follow-up validation analyses in 19,845 cases and 16,541 controls using an extreme case-control design. They identified a locus on chromosome 16 in the 5′ region of Uromodulin (UMOD; rs13333226, combined P value of 3.6×10−11). The minor G allele is associated with a lower risk of hypertension (OR [95%CI]: 0.87 [0.84–0.91]), reduced urinary uromodulin excretion, better renal function; and each copy of the G allele is associated with a 7.7% reduction in risk of CVD events after adjusting for age, sex, BMI, and smoking status (H.R. = 0.923, 95% CI 0.860–0.991; p = 0.027). In a subset of 13,446 individuals with estimated glomerular filtration rate (eGFR) measurements, scientists show that rs13333226 is independently associated with hypertension (unadjusted for eGFR: 0.89 [0.83–0.96], p = 0.004; after eGFR adjustment: 0.89 [0.83–0.96], p = 0.003). In clinical functional studies, they also consistently show the minor G allele is associated with lower urinary uromodulin excretion. The exclusive expression of uromodulin in the thick portion of the ascending limb of Henle suggests a putative role of this variant in hypertension through an effect on sodium homeostasis. The newly discovered UMOD locus for hypertension has the potential to give new insights into the role of uromodulin in BP regulation and to identify novel drugable targets for reducing cardiovascular risk.

Predicting success of oligomerized pool engineering (OPEN) for zinc finger target site sequences

2010-11-02T12:45:00.000-07:00

Precise and efficient methods for gene targeting are critical for detailed functional analysis of genomes and regulatory networks and for potentially improving the efficacy and safety of gene therapies. Oligomerized Pool ENgineering (OPEN) is a recently developed method for engineering C2H2 zinc finger proteins (ZFPs) designed to bind specific DNA sequences with high affinity and specificity in vivo. Because generation of ZFPs using OPEN requires considerable effort, a computational method for identifying the sites in any given gene that are most likely to be successfully targeted by this method is desirable.

Analysis of the base composition of experimentally validated ZFP target sites identified important constraints on the DNA sequence space that can be effectively targeted using OPEN. Using alternate encodings to represent ZFP target sites, we implemented Naive Bayes and Support Vector Machine classifiers capable of distinguishing "active" targets, i.e., ZFP binding sites that can be targeted with a high rate of success, from those that are "inactive" or poor targets for ZFPs generated using current OPEN technologies. When evaluated using leave-one-out cross-validation on a dataset of 135 experimentally validated ZFP target sites, the best Naive Bayes classifier, designated ZiFOpT, achieved overall accuracy of 87% and specificity+ of 90%, with an ROC AUC of 0.89. When challenged with a completely independent test set of 140 newly validated ZFP target sites, ZiFOpT performance was comparable in terms of overall accuracy (88%) and specificity+ (92%), but with reduced ROC AUC (0.77). Users can rank potentially active ZFP target sites using a confidence score derived from the posterior probability returned by ZiFOpT. ZiFOpT, a machine learning classifier trained to identify DNA sequences amenable for targeting by OPEN-generated zinc finger arrays, can guide users to target sites that are most likely to function successfully in vivo, substantially reducing the experimental effort required.

Circadian signatures in rat liver - from gene expression to pathways

2010-11-01T14:07:00.000-07:00

Circadian rhythms are 24 hour oscillations in many behavioural, physiological, cellular and molecular processes that are controlled by an endogenous clock which is entrained to environmental factors including light, food and stress. Transcriptional analyses of circadian patterns demonstrate that genes showing circadian rhythms are part of a wide variety of biological pathways. Pathway activity method can identify the significant pattern of the gene expression levels within a pathway. In this method, the overall gene expression levels are translated to a reduced form, pathway activity levels, via singular value decomposition (SVD). A given pathway represented by pathway activity levels can then be as analyzed using the same approaches used for analyzing gene expression levels. We propose to use pathway activity method across time to identify underlying circadian pattern of pathways.

Researchers used synthetic data to demonstrate that pathway activity analysis can evaluate the underlying circadian pattern within a pathway even when circadian patterns cannot be captured by the individual gene expression levels. In addition, we illustrated that pathway activity formulation should be coupled with a significance analysis to distinguish biologically significant information from random deviations. Next, scientists performed pathway activity level analysis on a rich time series of transcriptional profiling in rat liver. The over-represented five specific patterns of pathway activity levels, which cannot be explained by random event, exhibited circadian rhythms. The identification of the circadian signatures at the pathway level identified 78 pathways related to energy metabolism, amino acid metabolism, lipid metabolism and DNA replication and protein synthesis, which are biologically relevant in rat liver. Further, they observed tight coordination between cholesterol biosynthesis and bile acid biosynthesis as well as between folate biosynthesis, one carbon pool by folate and purine-pyrimidine metabolism. These coupled pathways are parts of a sequential reaction series where the product of one pathway is the substrate of another pathway. Rather than assessing the importance of a single gene beforehand and map these genes onto pathways, they instead examined the orchestrated change within a pathway. Pathway activity level analysis could reveal the underlying circadian dynamics in the microarray data with an unsupervised approach and biologically relevant results were obtained.

GeneForce: An Automated Phenotype-Driven Approach for Refining Metabolic and Regulatory Models

2010-10-29T13:51:00.000-07:00

Computational models of biological networks are useful for explaining experimental observations and predicting phenotypic behaviors. The construction of genome-scale metabolic and regulatory models is still a labor-intensive process, even with the availability of genome sequences and high-throughput datasets. Since our knowledge about biological systems is incomplete, these models are iteratively refined and validated as researchers discover new connections in biological networks, and eliminate inconsistencies between model predictions and experimental observations. To enable researchers to quickly determine what causes discrepancies between observed phenotypes and model predictions, we developed a new approach (GeneForce) that automatically corrects integrated metabolic and transcriptional regulatory network models. To illustrate the utility of the approach, they applied the developed method to well-curated models of E. coli metabolism and regulation. scientists found that the approach significantly improved the accuracy of phenotype predictions and suggested changes needed to the metabolic and/or regulatory models. Researchers also used the approach to identify rescue non-growth phenotypes and to evaluate the conservation of transcriptional regulatory interactions between E. coli and S. typhimurium. The developed approach helps reconcile discrepancies between model predictions and experimental data by hypothesizing required network changes, and helps facilitate the development of new genome-scale models.

NES consensus redefined by structures of PKI-type and Rev-type nuclear export signals bound to CRM1

2010-10-28T13:30:00.000-07:00

Classic nuclear export signals (NESs) confer CRM1-dependent nuclear export. Here researchers present crystal structures of the RanGTP−CRM1 complex alone and bound to the prototypic PKI or HIV-1 Rev NESs. These NESs differ markedly in the spacing of their key hydrophobic (Φ) residues, yet CRM1 recognizes them with the same rigid set of five Φ pockets. The different Φ spacings are compensated for by different conformations of the bound NESs: in the case of PKI, an α-helical conformation, and in the case of Rev, an extended conformation with a critical proline docking into a Φpocket. NMR analyses of CRM1-bound and CRM1-free PKI NES suggest that CRM1 selects NES conformers that pre-exist in solution. Data lead to a new structure-based NES consensus, and explain why NESs differ in their affinities for CRM1 and why supraphysiological NESs bind the exporting so tightly.

SNP detection and genotyping from low-coverage sequencing data on multiple diploid samples

2010-10-28T13:24:00.000-07:00

Reductions in the cost of sequencing have enabled whole-genome sequencing to identify sequence variants segregating in a population. An efficient approach is to sequence many samples at low coverage, then to combine data across samples to detect shared variants. Here, we present methods to discover and genotype single-nucleotide polymorphism (SNP) sites from low-coverage sequencing data, making use of shared haplotype (linkage disequilibrium) information. For each population, scientists first collect SNP candidates based on independent sequence calls per site. They then use MARGARITA with genotype or phased haplotype data from the same samples to collect 20 ancestral recombination graphs (ARGs). The researchers refine the posterior probability of SNP candidates by considering possible mutations at internal branches of the 40 marginal ancestral trees inferred from the 20 ARGs at the left and right flanking genotype sites. Using a population genetic prior on tree-branch length and Bayesian inference, we determine a posterior probability of the SNP being real and also the most probable phased genotype call for each individual. They present experiments on both simulation data and real data from the 1000 Genomes Project to prove the applicability of the methods. Finally, they also explore the relative tradeoff between sequencing depth and the number of sequenced samples.

Cotranscriptional exon skipping in the genotoxic stress response

2010-10-27T13:04:00.000-07:00

Pre-mRNA splicing is functionally coupled to transcription, and genotoxic stresses can enhance alternative exon inclusion by affecting elongating RNA polymerase II. We report here that various genotoxic stress inducers, including camptothecin (CPT), inhibit the interaction between Ewing's sarcoma proto-oncoprotein (EWS), an RNA polymerase II–associated factor, and YB-1, a spliceosome-associated factor. This results in the cotranscriptional skipping of several exons of the MDM2 gene, which encodes the main p53 ubiquitin ligase. This reversible exon skipping participates in the regulation of MDM2 expression that may contribute to the accumulation of p53 during stress exposure and its rapid shut-off when stress is removed. Finally, a splicing-sensitive microarray identified numerous exons that are skipped in response to CPT and EWS–YB-1 depletion. These data demonstrate genotoxic stress-induced alteration of the communication between the transcriptional and splicing machineries, which results in widespread exon skipping and plays a central role in the genotoxic stress response.

Colorectal carcinomas with microsatellite instability display a different pattern of target gene mutations according to large bowel site of origin

2010-10-27T12:59:00.000-07:00

Only a few studies have addressed the molecular pathways specifically involved in carcinogenesis of the distal colon and rectum. Scientists aimed to identify potential differences among genetic alterations in distal colon and rectal carcinomas as compared to cancers arising elsewhere in the large bowel. Constitutional and tumor DNA from a test series of 37 patients with rectal and 25 patients with sigmoid carcinomas, previously analyzed for microsatellite instability (MSI), was studied for BAX, IGF2R, TGFBR2, MSH3, and MSH6 microsatellite sequence alterations, BRAF and KRAS mutations, and MLH1 promoter methylation. The findings were then compared with those of an independent validation series consisting of 36 MSI-H carcinomas with origin from each of the large bowel regions. Immunohistochemical and germline mutation analyses of the mismatch repair system were performed when appropriate.

In the test series, IGFR2 and BAX mutations were present in one and two out of the six distal MSI-H carcinomas, respectively, and no mutations were detected in TGFBR2, MSH3, and MSH6. We confirmed these findings in the validation series, with TGFBR2 and MSH3 microsatellite mutations occurring less frequently in MSI-H rectal and sigmoid carcinomas than in MSI-H colon carcinomas elsewhere (P=0.00005 and P=0.0000005, respectively, when considering all MSI-carcinomas of both series). No MLH1 promoter methylation was observed in the MSI-H rectal and sigmoid carcinomas of both series, as compared to 53% found in MSI-H carcinomas from other locations (P=0.004). KRAS and BRAF mutational frequencies were 19% and 43% in proximal carcinomas and 25% and 17% in rectal/sigmoid carcinomas, respectively. The mechanism and the pattern of genetic changes driving MSI-H carcinogenesis in distal colon and rectum appears to differ from that occurring elsewhere in the colon and further investigation is warranted both in patients with sporadic or hereditary disease.

The Most Redundant Sequences in Human CpG Island Library Are Derived from Mitochondrial Genome

2010-10-26T13:44:00.000-07:00

An altered pattern of epigenetic modifications, such as DNA methylation and histone modification, is critical to many common human diseases, including cancer. Recently, mitochondrial DNA (mtDNA) was reported to be associated with tumorigenesis through epigenetic regulation of methylation patterns. One of the promising approaches to study DNA methylation and CpG islands (CGIs) is sequencing and analysis of clones derived from the physical library generated by methyl-CpG-binding domain proteins and restriction enzyme MseI. In this study, we observed that the most redundant sequences of 349 clones in a human CGI library were all generated from the human mitochondrial genome. Further analysis indicated that there was a 5,845-bp DNA transfer from mtDNA to chromosome 1, and all the clones should be the products of a 510-bp MseI fragment, which contained a putative CGI of 270 bp. The 510-bp fragment was annotated as part of cytochrome c oxidase subunit II (COXII), and phylogenetic analysis of homologous sequences containing COXII showed three DNA transfer events from mtDNA to nuclear genome, one of which underwent secondary transfer events between different chromosomes. These results may further our understanding of how the mtDNA regulates DNA methylation in the nucleus.

BMC Bioinformatics Reports Parameters for Accurate Genome Alignment

2010-10-26T13:39:00.000-07:00

Genome sequence alignments are a priceless resource for finding functional elements (protein-coding sequences, RNA structures, cis-regulatory elements, miRNA target sites, etc.) and charting evolutionary history. Many genome alignment algorithms have been developed. All of these algorithms require selection of various mundane but critical parameters. In the most classic approach to alignment (Smith-Waterman/BLAST), these parameters include the scoring matrix and gap costs, which determine alignment scores, and thus which alignments are produced. This study aims to reveal the influence of these and other parameters, and to guide their selection for accurate genome alignment.

In the classic alignment framework, it is necessary to choose an alignment score cutoff: low enough to find weak homologies, but high enough to avoid too many spurious alignments. A rational approach is to calculate the E-value--the expected number of alignments between two random sequences scoring above the cutoff--and choose a cutoff that has an acceptable E-value. Surprisingly, this approach does not seem to be used for genome alignment (or if it is, it is not mentioned in method descriptions). The authors of BLASTZ tested their score cutoff by aligning two genomes after reversing, but not complementing, one of them. Homology between reversed and non-reversed DNA is (thought to be) impossible, so this is a good measure of the spurious alignment rate, but it is inconvenient to repeat it with each new pair of genomes.

Structural and mechanistic insights into cooperative assembly of dimeric Notch ankyrin domains

2010-10-26T13:14:00.000-07:00

Ligand-induced proteolysis of Notch produces an intracellular effector domain that transduces essential signals by regulating the transcription of target genes. This function relies on the formation of transcriptional activation complexes that include intracellular Notch, a Mastermind co-activator and the transcription factor CSL bound to cognate DNA. These complexes form higher-order assemblies on paired, head-to-head CSL recognition sites. Here we report the X-ray structure of a dimeric human Notch1 transcription complex loaded on the paired site from the human HES1 promoter. The small interface between the Notch ankyrin domains could accommodate DNA bending and untwisting to allow a range of spacer lengths between the two sites. Cooperative dimerization occurred on the human and mouse Hes5 promoters at a sequence that diverged from the CSL-binding consensus at one of the sites. These studies reveal how promoter organizational features control cooperativity and, thus, the responsiveness of different promoters to Notch signaling.

Broad Institute digs deep into the malaria mosquito genome

2010-10-23T11:50:00.000-07:00

Malaria causes suffering and death to millions of people worldwide every year, primarily in sub-Saharan Africa. And the major perpetrator is the Anopheles gambiae mosquito, which transmits the malaria-causing Plasmodium parasite to its victims when it takes bloodmeals. But not all A. gambiae mosquitoes do so with equal success or even under the same conditions. This is because this mosquito species is branching out genetically, or speciating, creating new populations with very different characteristics.

To the eye, all A. gambiae mosquitoes look the same. But the details within their genomes - their genetic makeup - tell stories of increasing diversity that scientists want to read, in the attempt to understand why different groups of A. gambiaemosquitoes thrive in different environments. To hone in on these differences, researchers at the Broad Institute of MIT and Harvard in collaboration with Imperial College, London have created a new genomic tool to identify the precise genetic differences between groups of A. gambiae mosquitoes. This tool maps single nucleotide polymorphisms (SNPs) - single letter differences in the mosquito’s genome. The researchers have found that by using these so-called SNP arrays they can precisely identify the genomic differences between various groups of A. gambiae mosquitoes. Their work is published in the October 21 online version of Science.

“This is the first high-throughput genotyping tool to study the enormously variable A. gambiaemosquito,” explains co-lead author Daniel Neafsey, a computational biologist in the Broad’s Microbial Genome Analysis and Annotation group who co-developed the technique. By linking particular genetic variations with particular mosquito populations, researchers and public health officials hope to determine exactly what types of mosquitoes they are dealing with in particular geographic areas and ecological settings.