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

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

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

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

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

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

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

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

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

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.

Genomic selection and trait prediction using a fast EM algorithm applied to genome-wide markers

The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding programs. Genome-wide association studies relate individual single nucleotide polymorphisms (SNP) from dense SNP panels to individual measurements of complex traits, with the underlying assumption being that any association is caused by linkage disequilibrium (LD) between SNP and quantitative trait loci (QTL) affecting the trait. Often SNP are in genomic regions of no trait variation. Whole genome Bayesian models are an effective way of incorporating this and other important prior information into modelling. However a full Bayesian analysis is often not feasible due to the large computational time involved.

This article proposes an expectation-maximization (EM) algorithm called emBayesB which allows only a proportion of SNP to be in LD with QTL and incorporates prior information about the distribution of SNP effects. The posterior probability of being in LD with at least one QTL is calculated for each SNP along with estimates of the hyperparameters for the mixture prior. A simulated example of genomic selection from an international workshop is used to demonstrate the features of the EM algorithm. The accuracy of prediction is comparable to a full Bayesian analysis but the EM algorithm is considerably faster. The EM algorithm was accurate in locating QTL which explained more than 1% of the total genetic variation. A computational algorithm for very large SNP panels is described. emBayesB is a fast and accurate EM algorithm for implementing genomic selection and predicting complex traits by mapping QTL in genome-wide dense SNP marker data. Its accuracy is similar to Bayesian methods but it takes only a fraction of the time.

Functional annotation, genome organization and phylogeny of the grapevine (Vitis vinifera) terpene synthase gene family based on genome assembly, FLcDNA cloning, and enzyme assays

Terpenoids are among the most important constituents of grape flavour and wine bouquet, and serve as useful metabolite markers in viticulture and enology. Based on the initial 8-fold sequencing of a nearly homozygous Pinot noir inbred line, 89 putative terpenoid synthase genes (VvTPS) were predicted by in silico analysis of the grapevine (Vitis vinifera) genome assembly. The finding of this very large VvTPS family, combined with the importance of terpenoid metabolism for the organoleptic properties of grapevine berries and finished wines, prompted a detailed examination of this gene family at the genomic level as well as an investigation into VvTPS biochemical functions.

Scientists present findings from the analysis of the up-dated 12-fold sequencing and assembly of the grapevine genome that place the number of predicted VvTPS genes at 69 putatively functional VvTPS, 20 partial VvTPS, and 63 VvTPS probable pseudogenes. Gene discovery and annotation included information about gene architecture and chromosomal location. A dense cluster of 45 VvTPS is localized on chromosome 18. Extensive FLcDNA cloning, gene synthesis, and protein expression enabled functional characterization of 39 VvTPS; this is the largest number of functionally characterized TPS for any species reported to date. Of these enzymes, 23 have unique functions and/or phylogenetic locations within the plant TPS gene family. Phylogenetic analyses of the TPS gene family showed that while most VvTPS form species-specific gene clusters, there are several examples of gene orthology with TPS of other plant species, representing perhaps more ancient VvTPS, which have maintained functions independent of speciation. The highly expanded VvTPS gene family underpins the prominence of terpenoid metabolism in grapevine. Researchers provide a detailed experimental functional annotation of 39 members of this important gene family in grapevine and comprehensive information about gene structure and phylogeny for the entire currently known VvTPS gene family.

High-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis

The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardizable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens. Scientists developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes.

Results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by horizontal gene transfer. Moreover, a broad range of pathogens have been covered by an efficient probe set size enabling the design of high-throughput diagnostics.

VBI awarded $10.6 million from NIH to model immune responses to gut pathogens

The National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health, has awarded a $10.6 million grant to researchers at the Virginia Bioinformatics Institute (VBI) and collaborators to determine how the human immune system responds to infection by pathogens of the gut. The funding will be used to apply mathematical modeling to the study of immune responses to gut pathogens.

“The Center for Modeling Immunity to Enteric Pathogens will generate new hypotheses based on computer simulations of the immune responses in the gut and perform pre-clinical and clinical experiments that will reveal how the immune system works when intestinal pathogens invade the human body,” said Josep Bassaganya-Riera, Associate Professor at VBI, Leader of the Nutritional Immunology and Molecular Medicine Group in VBI’s CyberInfrastructure Division, and Director of the Center for Modeling Immunity to Enteric Pathogens (MIEP).

“We want to use powerful computer simulations to uncover the mechanisms of action underlying immune responses to intestinal pathogens and accelerate the discovery of drug targets suitable for the prevention and treatment of diseases and disorders caused by gut pathogens, such as persistent diarrhea, gastric cancer, inflammation, and ulcers,” said Bassaganya-Riera. The MIEP team will work with a wide range of collaborators and engage the infectious disease and immunology communities to disseminate user-friendly mathematical and computational models for the study of human immunity to infection or vaccination. “In addition to providing a user-friendly web-based immunological information system that incorporates the models, MIEP is programmatically tied to the Immunology Database and Analysis Portal (ImmPort), the Middle Atlantic Regional Center of Excellence for Biodefense and Emerging Infectious Diseases (MARCE), and offers training on modeling mucosal immune responses to biodefense-related NIAID category A-C priority enteric pathogens,” said Bassaganya-Riera.

Binding-induced folding of prokaryotic ubiquitin-like protein on the Mycobacterium proteasomal ATPase targets substrates for degradation

Mycobacterium tuberculosis uses a proteasome system that is analogous to the eukaryotic ubiquitin-proteasome pathway and is required for pathogenesis. However, the bacterial analog of ubiquitin, prokaryotic ubiquitin-like protein (Pup), is an intrinsically disordered protein that bears little sequence or structural resemblance to the highly structured ubiquitin. Thus, it was unknown how pupylated proteins were recruited to the proteasome. Here, researchers show that the Mycobacterium proteasomal ATPase (Mpa) has three pairs of tentacle-like coiled coils that recognize Pup. Mpa bound unstructured Pup through hydrophobic interactions and a network of hydrogen bonds, leading to the formation of an α-helix in Pup. This work describes a binding-induced folding recognition mechanism in the Pup-proteasome system that differs mechanistically from substrate recognition in the ubiquitin-proteasome system. This key difference between the prokaryotic and eukaryotic systems could be exploited for the development of a small molecule-based treatment for tuberculosis.

Expression and purification of ELP-intein-tagged target proteins in high cell density E. coli fermentation

Elastin-like polypeptides (ELPs) are useful tools that can be used to non-chromatographically purify proteins. When paired with self-cleaving inteins, they can be used as economical self-cleaving purification tags. However, ELPs and ELP-tagged target proteins have been traditionally expressed using highly enriched media in shake flask cultures, which are generally not amenable to scale-up. In this work, we describe the high cell-density expression of self-cleaving ELP-tagged targets in a supplemented minimal medium at a 2.5 liter fermentation scale, with increased yields and purity compared to traditional shake flask cultures. This demonstration of ELP expression in supplemented minimal media is juxtaposed to previous expression of ELP tags in extract-based rich media. We also describe several sets of fed-batch conditions and their impact on ELP expression and growth medium cost. By using fed batch E. coli fermentation at high cell density, ELP-intein-tagged proteins can be expressed and purified at high yield with low cost. Further, the impact of media components and fermentation design can significantly impact the overall process cost, particularly at large scale. This work thus demonstrates an important advances in the scale up of self-cleaving ELP tag-mediated processes.

Dynamic interaction networks in a hierarchically organized tissue (Molecular Systems Biology)

Intercellular communication networks maintain homeostasis and coordinate regenerative and developmental cues in multicellular organisms. These constitute local juxtacrine and paracrine signaling for within-tissue cellular regulation, and systemic endocrine signaling for organism-level interactions. Adult or tissue-resident stem cells, while normally quiescent, are activated under appropriate circumstances, giving rise to a hierarchy of increasingly differentiated progenitors, thereby regenerating damaged tissue. Intercellular networks are of particular relevance for stem cell biology as stem and progenitor cell fate must be dynamically responsive to physiological demand and external perturbations. For example, adult blood stem cell fate decisions in vivo are regulated via interactions within the bone marrow microenvironment—the stem cell ‘niche’. Recent progress has been made in elucidating the physical location and cellular components of this niche, including molecular cross-talk between hematopoietic stem cells (HSCs) and niche cells (Kiel and Morrison, 2008). However, local interactions within the microenvironment are insufficient to explain the dynamic responsiveness of tissue-resident stem cells to systemic signals (Mayack et al, 2010). Numerous studies have indirectly demonstrated hematopoietic stem and progenitor cell fate as responsive to systemic perturbations such as bleeding and irradiation via (undefined) feedback signaling from mature cells (Kirouac and Zandstra, 2006). Such regulatory mechanisms appear to be a conserved feature in other adult stem cells, including neural and epithelial tissues (Lander et al, 2009).

Detecting two-locus associations allowing for interactions in genome-wide association studies

Genome-wide association studies (GWASs) aim to identify genetic susceptibility to complex diseases by assaying and analyzing hundreds of thousands of single nucleotide polymorphisms (SNPs). Although traditional single-locus statistical tests have identified many genetic determinants of susceptibility, those findings cannot completely explain genetic contributions to complex diseases. Marchini and coauthors demonstrated the importance of testing two-locus associations allowing for interactions through a wide range of simulation studies. However, such a test is computationally demanding as we need to test hundreds of billions of SNP pairs in GWAS. Here, we provide a method to address this computational burden for dichotomous phenotypes.

Researchers have applied their method on nine datasets from GWAS, including the aged-related macular degeneration (AMD) dataset, the Parkinson's disease dataset and seven datasets from the Wellcome Trust Case Control Consortium (WTCCC). Our method has discovered many associations that were not identified before. The running time for the AMD dataset, the Parkinson's disease dataset and each of seven WTCCC datasets are 2.5, 82 and 90 h on a standard 3.0 GHz desktop with 4 G memory running Windows XP system. Their experiment results demonstrate that their method is feasible for the full-scale analyses of both single- and two-locus associations allowing for interactions in GWAS.

NSMB - The program for processing newly synthesized histones H3.1 and H4

The mechanism by which newly synthesized histones are imported into the nucleus and deposited onto replicating chromatin alongside segregating nucleosomal counterparts is poorly understood, yet this program is expected to bear on the putative epigenetic nature of histone post-translational modifications. To define the events by which naive pre-deposition histones are imported into the nucleus, scientists biochemically purified and characterized the full gamut of histone H3.1–containing complexes from human cytoplasmic fractions and identified their associated histone post-translational modifications. Through reconstitution assays, biophysical analyses and live cell manipulations, we describe in detail this series of events, namely the assembly of H3–H4 dimers, the acetylation of histones by the HAT1 holoenzyme and the transfer of histones between chaperones that culminates with their karyopherin-mediated nuclear import. Researchers further demonstrate the high degree of conservation for this pathway between higher and lower eukaryotes.

DOE Joint Genome Institute Announces 2011 Community Sequencing Program Portfolio

Supported by the Office of Biological and Environmental Research in the DOE Office of Science, the DOE JGI’s Community Sequencing Program enables scientists from universities and national laboratories around the world to probe the hidden world of microbes and plants for innovative solutions to the nation’s major challenges in energy, climate, and environment. This year’s portfolio is composed mostly of large-scale projects, which DOE JGI Director Eddy Rubin said was in keeping with the facility’s mission of large-scale genomics and analysis, and that meet the DOE missions of bioenergy, carbon cycling and biogeochemistry.

“Advances in sequencing technologies are really changing the landscape and have dramatically increased data output,” he said. “This has led to enormous changes which have impacted the science we produce. In the past year alone, the JGI’s sequence output has increased fivefold to five terabytes or five trillion nucleotides. Connected with the increased productivity, we’re beginning to position the JGI to work on projects of tera- and peta- or quadrillion-base scale. Our mission hasn’t changed; what is changing is the scale and complexity of the projects – which will increase. This highlights one of the directions genomics is going as data output begins to rival the output of the high-energy physics and astronomy communities.”

To highlight the directional shift, the CSP 2011 call urged researchers to submit proposals for projects that advance capabilities in fields such as large-scale resequencing, single-cell genomics and metatranscriptomics. A total of 35 proposals were approved from the 127 submitted, selected from the 145 letters of intent originally received. Of the approved proposals, two involve plant genomes and two involve algal genomes; 10 are fungal projects; nine are microbial projects, six of which involve single-cell genomics; and 12 are metagenome (microbial communities) or metatranscriptome projects. The projects approved by an outside review panel and vetted by the DOE make the most of the DOE JGI’s increased sequencing capacity, allocating 10 trillion bases (TB or terabases), a 30-fold increase compared with last year’s one-third of a trillion nucleotides.

A Covering Method for Detecting Genetic Associations between Rare Variants and Common Phenotypes

Genome wide association (GWA) studies, which test for association between common genetic markers and a disease phenotype, have shown varying degrees of success. While many factors could potentially confound GWA studies, researchers focus on the possibility that multiple, rare variants (RVs) may act in concert to influence disease etiology. Here, they describe an algorithm for RV analysis, RARECOVER. The algorithm combines a disparate collection of RVs with low effect and modest penetrance. Further, it does not require the rare variants be adjacent in location. Extensive simulations over a range of assumed penetrance and population attributable risk (PAR) values illustrate the power of our approach over other published methods, including the collapsing and weighted-collapsing strategies. To showcase the method, scientists apply RARECOVER to re-sequencing data from a cohort of 289 individuals at the extremes of Body Mass Index distribution (NCT00263042). Individual samples were re-sequenced at two genes, FAAH and MGLL, known to be involved in endocannabinoid metabolism (187Kbp for 148 obese and 150 controls). The RARECOVER analysis identifies exactly one significantly associated region in each gene, each about 5 Kbp in the upstream regulatory regions. The data suggests that the RVs help disrupt the expression of the two genes, leading to lowered metabolism of the corresponding cannabinoids. Overall, their results point to the power of including RVs in measuring genetic associations.

The rhizosphere competent entomopathogen Metarhizium anisopliae expresses a subset of genes

Metarhizium anisopliae and Beauveria bassiana are ubiquitous insect pathogens and possible plant symbionts as some strains are endophytic or colonize the rhizosphere. Scientists evaluated eleven strains of M. anisopliae and B. bassiana, and two soil saprophytes (the non-rhizospheric Aspergillus niger and the rhizosphere competent Trichoderma harzianum) for their ability to germinate in bean root exudates (RE). Our results showed that some generalist strains of M. anisopliae were as good at germinating in RE as T. harzianum but germination rates of the specialized acridid pathogen M. acridum and the B. bassiana strains were significantly lower. At RE concentrations <1 mg ml-1, M. anisopliae strain ARSEF 2575 showed higher germination rates than T. harzianum. Microarrays showed that strain 2575 up-regulated twenty-nine genes over a 12 hour period in RE. A similar number (21) of genes were down regulated. Up-regulated genes were involved in carbohydrate metabolism, lipid metabolism, cofactor and vitamins, energy metabolism, proteolysis, extra cellular matrix/cell wall proteins, transport proteins, DNA synthesis, the sexual cycle and stress response. However, 41.3% of the up-regulated genes were hypotheticals or orphan sequences indicating that many previously uncharacterized genes have functions related to saprophytic survival. Genes up-regulated in response to RE included the subtilisin Pr1A that is also involved in pathogenicity to insects. However, the up-regulated Mad2 adhesin specifically mediates adhesion to plant surfaces, demonstrating that M. anisopliae has genes for rhizosphere competence that are induced by RE.

Genetic Signatures in the Envelope Glycoproteins of HIV-1 that Associate with Neutralizing Antibodies

A steady increase in knowledge of the molecular and antigenic structure of the gp120 and gp41 HIV-1 envelope glycoproteins (Env) is yielding important new insights for vaccine design, but it has been difficult to translate this information to an immunogen that elicits broadly neutralizing antibodies. To help bridge this gap, we used phylogenetically corrected statistical methods to identify amino acid signature patterns in Envs derived from people who have made potently neutralizing antibodies, with the hypothesis that these Envs may share common features that would be useful for incorporation in a vaccine immunogen. Before attempting this, essentially as a control, researchers explored the utility of our computational methods for defining signatures of complex neutralization phenotypes by analyzing Env sequences from 251 clonal viruses that were differentially sensitive to neutralization by the well-characterized gp120-specific monoclonal antibody, b12. We identified ten b12-neutralization signatures, including seven either in the b12-binding surface of gp120 or in the V2 region of gp120 that have been previously shown to impact b12 sensitivity. A simple algorithm based on the b12 signature pattern was predictive of b12 sensitivity/resistance in an additional blinded panel of 57 viruses. Upon obtaining these reassuring outcomes, we went on to apply these same computational methods to define signature patterns in Env from HIV-1 infected individuals who had potent, broadly neutralizing responses. Scientists analyzed a checkerboard-style neutralization dataset with sera from 69 HIV-1-infected individuals tested against a panel of 25 different Envs. Distinct clusters of sera with high and low neutralization potencies were identified. Six signature positions in Env sequences obtained from the 69 samples were found to be strongly associated with either the high or low potency responses. Five sites were in the CD4-induced coreceptor binding site of gp120, suggesting an important role for this region in the elicitation of broadly neutralizing antibody responses against HIV-1.

Selection upon Genome Architecture: Conservation of Functional Neighborhoods with Changing Genes

An increasing number of evidences show that genes are not distributed randomly across eukaryotic chromosomes, but rather in functional neighborhoods. Nevertheless, the driving force that originated and maintains such neighborhoods is still a matter of controversy. Researchers present the first detailed multispecies cartography of genome regions enriched in genes with related functions and study the evolutionary implications of such clustering. Results indicate that the chromosomes of higher eukaryotic genomes contain up to 12% of genes arranged in functional neighborhoods, with a high level of gene co-expression, which are consistently distributed in phylogenies. Unexpectedly, neighborhoods with homologous functions are formed by different (non-orthologous) genes in different species. Actually, instead of being conserved, functional neighborhoods present a higher degree of synteny breaks than the genome average. This scenario is compatible with the existence of selective pressures optimizing the coordinated transcription of blocks of functionally related genes. If these neighborhoods were broken by chromosomal rearrangements, selection would favor further rearrangements reconstructing other neighborhoods of similar function. The picture arising from this study is a dynamic genomic landscape with a high level of functional organization.

Identification of differences in human and great ape phytanic acid metabolism that could influence gene expression profiles and physiological functions

It has been proposed that anatomical differences in human and great ape guts arose in response to species-specific diets and energy demands. To investigate functional genomic consequences of these differences, we compared their physiological levels of phytanic acid, a branched chain fatty acid that can be derived from the microbial degradation of chlorophyll in ruminant guts. Humans who accumulate large stores of phytanic acid commonly develop cerebellar ataxia, peripheral polyneuropathy, and retinitis pigmentosa in addition to other medical conditions. Furthermore, phytanic acid is an activator of the PPAR-alpha transcription factor that influences the expression of genes relevant to lipid metabolism. Despite their trace dietary phytanic acid intake, all great ape species had elevated red blood cell (RBC) phytanic acid levels relative to humans on diverse diets. Unlike humans, chimpanzees showed sexual dimorphism in RBC phytanic acid levels, which were higher in males relative to females. Cultured skin fibroblasts from all species had a robust capacity to degrade phytanic acid. We provide indirect evidence that great apes, in contrast to humans, derive significant amounts of phytanic acid from the hindgut fermentation of plant materials. This would represent a novel reduction of metabolic activity in humans relative to the great apes.

Researchers identified differences in the physiological levels of phytanic acid in humans and great apes and propose this is causally related to their gut anatomies and microbiomes. Phytanic acid levels could contribute to cross-species and sex-specific differences in human and great ape transcriptomes, especially those related to lipid metabolism. Based on the medical conditions caused by phytanic acid accumulation, we suggest that differences in phytanic acid metabolism could influence the functions of human and great ape nervous, cardiovascular, and skeletal systems.

Reduced histone biosynthesis and chromatin changes arising from a damage signal at telomeres

During replicative aging of primary cells morphological transformations occur, the expression pattern is altered and chromatin changes globally. Here we show that chronic damage signals, probably caused by telomere processing, affect expression of histones and lead to their depletion. Researchers investigated the abundance and cell cycle expression of histones and histone chaperones and found defects in histone biosynthesis during replicative aging. Simultaneously, epigenetic marks were redistributed across the phases of the cell cycle and the DNA damage response (DDR) machinery was activated. The age-dependent reprogramming affected telomeric chromatin itself, which was progressively destabilized, leading to a boost of the telomere-associated DDR with each successive cell cycle. They propose a mechanism in which changes in the structural and epigenetic integrity of telomeres affect core histones and their chaperones, enforcing a self-perpetuating pathway of global epigenetic changes that ultimately leads to senescence.

Structure of the Dom34–Hbs1 complex and implications for no-go decay

No-go decay (NGD) targets mRNAs with stalls in translation elongation for endonucleolytic cleavage in a process involving the Dom34 and Hbs1 proteins. The crystal structure of a Schizosaccharomyces pombe Dom34–Hbs1 complex reveals an overall shape similar to that of eRF1–eRF3–GTP and EF-Tu–tRNA–GDPNP. Similarly to eRF1 and GTP binding to eRF3, Dom34 and GTP bind to Hbs1 with strong cooperativity, and Dom34 acts as a GTP-dissociation inhibitor (GDI). A marked conformational change in Dom34 occurs upon binding to Hbs1, leading Dom34 to resemble a portion of a tRNA and to position a conserved basic region in a position expected to be near the peptidyl transferase center. These results support the idea that the Dom34–Hbs1 complex functions to terminate translation and thereby commit mRNAs to NGD. Consistent with this role, NGD at runs of arginine codons, which cause a strong block to elongation, is independent of the Dom34–Hbs1 complex.

Glycogen Synthase Kinase-3 regulates multiple myeloma cell growth and bortezomib-induced cell death

Glycogen Synthase Kinase-3 (GSK-3) alpha and beta are two serine-threonine kinases controlling insulin, Wnt/beta-catenin, NF-kappaB signaling and other cancer-associated transduction pathways. Recent evidence suggests that GSK-3 could function as growth-promoting kinases, especially in malignant cells. In this study, we have investigated GSK-3alpha and GSK-3beta function in multiple myeloma (MM). GSK-3 alpha and beta expression and cellular localization were investigated by Western blot (WB) and immunofluorescence analysis in a panel of MM cell lines and in freshly isolated plasma cells from patients. MM cell growth, viability and sensitivity to bortezomib was assessed upon treatment with GSK-3 specific inhibitors or transfection with siRNAs against GSK-3 alpha and beta isoforms. Survival signaling pathways were studied with WB analysis.

GSK-3alpha and GSK-3beta were differently expressed and phosphorylated in MM cells. Inhibition of GSK-3 with the ATP-competitive, small chemical compounds SB216763 and SB415286 caused MM cell growth arrest and apoptosis through the activation of the intrinsic pathway. Importantly, the two inhibitors augmented the bortezomib-induced MM cell cytotoxicity. RNA interference experiments showed that the two GSK-3 isoforms have distinct roles: GSK-3beta knock down decreased MM cell viability, while GSK-3alpha knock down was associated with a higher rate of bortezomib-induced cytotoxicity. GSK-3 inhibition caused accumulation of beta-catenin and nuclear phospho-ERK1, 2. Moreover, GSK-3 inhibition and GSK-3alpha knockdown enhanced bortezomib-induced AKT and MCL-1 protein degradation. Interestingly, bortezomib caused a reduction of GSK-3 serine phosphorylation and its nuclear accumulation with a mechanism that resulted partly dependent on GSK-3 itself.