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Abstract Genomic tumor testing (GTT) is an emerging technology aimed at identifying variants in tumors that can be targeted with genomically matched drugs. Due to limited resources, rural patients receiving care in community oncology settings may be less likely to benefit from GTT. We analyzed GTT results and observational clinical outcomes data from patients enrolled in the Maine Cancer Genomics Initiative (MCGI), which provided access to GTTs; clinician educational resources; and genomic tumor boards in community practices in a predominantly rural state. 1603 adult cancer patients completed enrollment; 1258 had at least one potentially actionable variant identified. 206 (16.4%) patients received a total of 240 genome matched treatments, of those treatments, 64% were FDA-approved in the tumor type, 27% FDA-approved in a different tumor type and 9% were given on a clinical trial. Using Inverse Probability of Treatment Weighting to adjust for baseline characteristics, a Cox proportional hazards model demonstrated that patients who received genome matched treatment were 31% less likely to die within 1 year compared to those who did not receive genome matched treatment (HR: 0.69; 95% CI: 0.52–0.90; p-value: 0.006). Overall, GTT through this initiative resulted in levels of genome matched treatment that were similar to other initiatives, however, clinical trials represented a smaller share of treatments than previously reported, and "off-label" treatments represented a greater share. Although this was an observational study, we found evidence for a potential 1-year survival benefit for patients who received genome matched treatments. These findings suggest that when disseminated and implemented with a supportive infrastructure, GTT may benefit cancer patients in rural community oncology settings, with further work remaining on providing genome-matched clinical trials.

Abstract Three-dimensional (3D) organoid cultures are flexible systems to interrogate cellular growth, morphology, multicellular spatial architecture, and cellular interactions in response to treatment. However, computational methods for analysis of 3D organoids with sufficiently high-throughput and cellular resolution are needed. Here we report Cellos, an accurate, high-throughput pipeline for 3D organoid segmentation using classical algorithms and nuclear segmentation using a trained Stardist-3D convolutional neural network. To evaluate Cellos, we analyze ~100,000 organoids with ~2.35 million cells from multiple treatment experiments. Cellos segments dye-stained or fluorescently-labeled nuclei and accurately distinguishes distinct labeled cell populations within organoids. Cellos can recapitulate traditional luminescence-based drug response of cells with complex drug sensitivities, while also quantifying changes in organoid and nuclear morphologies caused by treatment as well as cell-cell spatial relationships that reflect ecological affinity. Cellos provides powerful tools to perform high-throughput analysis for pharmacological testing and biological investigation of organoids based on 3D imaging.

Cancer functional genomics is the study of how genetic, epigenetic, and transcriptional alterations affect cancer phenotypes, such as growth and therapeutic response. Here, we comment on how, taking advantage of next generation sequencing, functional genomics, often combined with systems biology approaches, has revealed novel cancer vulnerabilities beyond the original paradigm of one gene-one phenotype.

Abstract Background Acute promyeloid leukemia (APL) is characterized by the oncogenic fusion protein PML-RARα, a major etiological agent in APL. However, the molecular mechanisms underlying the role of PML-RARα in leukemogenesis remain largely unknown. Results Using an inducible system, we comprehensively analyze the 3D genome organization in myeloid cells and its reorganization after PML-RARα induction and perform additional analyses in patient-derived APL cells with native PML-RARα. We discover that PML-RARα mediates extensive chromatin interactions genome-wide. Globally, it redefines the chromatin topology of the myeloid genome toward a more condensed configuration in APL cells; locally, it intrudes RNAPII-associated interaction domains, interrupts myeloid-specific transcription factors binding at enhancers and super-enhancers, and leads to transcriptional repression of genes critical for myeloid differentiation and maturation. Conclusions Our results not only provide novel topological insights for the roles of PML-RARα in transforming myeloid cells into leukemia cells, but further uncover a topological framework of a molecular mechanism for oncogenic fusion proteins in cancers.

Employers have begun to offer voluntary workplace genomic testing (wGT) as part of employee wellness benefit programs, but few empirical studies have examined the ethical, legal, and social implications (ELSI) of wGT. To better understand employee perspectives on wGT, employees were surveyed at a large biomedical research institution. Survey respondents were presented with three hypothetical scenarios for accessing health-related genomic testing: via (1) their doctor; (2) their workplace; and 3) a commercial direct-to-consumer (DTC) genetic testing company. Overall, 594 employees (28%) responded to the survey. Respondents indicated a preference for genomic testing in the workplace setting (70%; 95% CI 66–74%), followed by doctor’s office (54%; 95% CI 50–58%), and DTC testing (20%; 95% CI 17–24%). Prior to participating in wGT, respondents wanted to know about confidentiality of test results (79%), existence of relevant laws and policies (70%), and privacy protection (64%). Across scenarios, 92% of respondents preferred to view the test results with a genetic counselor. These preliminary results suggest that many employees are interested and even prefer genetic testing in the workplace and would prefer testing with support from genetic health professionals. Confirmation in more diverse employer settings will be needed to generalize such findings.

We report herein that trefoil factor 3 (TFF3) is oncogenic and mediates anti-estrogen resistance in human mammary carcinoma. Forced expression of TFF3 in mammary carcinoma cells increased cell proliferation and survival, enhanced anchorage-independent growth, and promoted migration and invasion. Moreover, forced expression of TFF3 increased tumor size in xenograft models. Conversely, depletion of endogenous TFF3 with small interfering RNA (siRNA) decreased the oncogenicity and invasiveness of mammary carcinoma cells. Neutralization of secreted TFF3 by antibody promoted apoptosis, decreased cell growth in vitro, and arrested mammary carcinoma xenograft growth. TFF3 expression was significantly correlated to decreased survival of estrogen receptor (ER)-positive breast cancer patients treated with tamoxifen. Forced expression of TFF3 in mammary carcinoma cells increased ER transcriptional activity, promoted estrogen-independent growth, and produced resistance to tamoxifen and fulvestrant in vitro and to tamoxifen in xenograft models. siRNA-mediated depletion or antibody inhibition of TFF3 significantly enhanced the efficacy of antiestrogens. Increased TFF3 expression was observed in tamoxifen-resistant (TAMR) cells and antibody inhibition of TFF3 in TAMR cells improved tamoxifen sensitivity. Functional antagonism of TFF3 therefore warrants consideration as a novel therapeutic strategy for mammary carcinoma.

DNA microarrays are valuable but expensive tools for expression profiling of cells, tissues, and organs. The design of custom microarrays leads to cost reduction without necessarily compromising their biological value. Here we present a strategy for designing custom cDNA microarrays and constructed a microarray for mouse immunology research (ImmunoChipTM). The strategy used interrogates expressed sequence tag databases available in the public domain but overcomes many of the problems encountered. Immunologically relevant clusters were selected based on the expression of expressed sequence tags in relevant libraries. Selected clusters were organized in modules, and the best representative clones were identified. When tested, this microarray was found to have minimal clone identity errors or phage contamination and identified molecular signatures of lymphoid cell lines. Our proposed design of custom microarrays avoids probe redundancy, allows the organization of the chip to optimize chip production, and reduces microarray production costs. The strategy described is also useful for the design of oligonucleotide microarrays.

Using a chromatin immunoprecipitation-paired end diTag cloning and sequencing strategy, we mapped estrogen receptor alpha (ERalpha) binding sites in MCF-7 breast cancer cells. We identified 1,234 high confidence binding clusters of which 94% are projected to be bona fide ERalpha binding regions. Only 5% of the mapped estrogen receptor binding sites are located within 5 kb upstream of the transcriptional start sites of adjacent genes, regions containing the proximal promoters, whereas vast majority of the sites are mapped to intronic or distal locations (>5 kb from 5' and 3' ends of adjacent transcript), suggesting transcriptional regulatory mechanisms over significant physical distances. Of all the identified sites, 71% harbored putative full estrogen response elements (EREs), 25% bore ERE half sites, and only 4% had no recognizable ERE sequences. Genes in the vicinity of ERalpha binding sites were enriched for regulation by estradiol in MCF-7 cells, and their expression profiles in patient samples segregate ERalpha-positive from ERalpha-negative breast tumors. The expression dynamics of the genes adjacent to ERalpha binding sites suggest a direct induction of gene expression through binding to ERE-like sequences, whereas transcriptional repression by ERalpha appears to be through indirect mechanisms. Our analysis also indicates a number of candidate transcription factor binding sites adjacent to occupied EREs at frequencies much greater than by chance, including the previously reported FOXA1 sites, and demonstrate the potential involvement of one such putative adjacent factor, Sp1, in the global regulation of ERalpha target genes. Unexpectedly, we found that only 22%-24% of the bona fide human ERalpha binding sites were overlapping conserved regions in whole genome vertebrate alignments, which suggest limited conservation of functional binding sites. Taken together, this genome-scale analysis suggests complex but definable rules governing ERalpha binding and gene regulation.

Since the emergence of the pandemic H1N1pdm09 virus in Mexico and California, biannual increases in the number of cases have been detected in Mexico. As observed in previous seasons, pandemic A/H1N1 09 virus was detected in severe cases during the 2011-2012 winter season and finally, during the 2013-2014 winter season it became the most prevalent influenza virus. Molecular and phylogenetic analyses of the whole viral genome are necessary to determine the antigenic and pathogenic characteristics of influenza viruses that cause severe outcomes of the disease. In this paper, we analyzed the evolution, antigenic and genetic drift of Mexican isolates from 2009, at the beginning of the pandemic, to 2014. We found a clear variation of the virus in Mexico from the 2011-2014 season due to different markers and in accordance with previous reports. In this study, we identified 13 novel substitutions with important biological effects, including virulence, T cell epitope presented by MHC and host specificity shift and some others substitutions might have more than one biological function. The systematic monitoring of mutations on whole genome of influenza A pH1N1 (2009) virus circulating at INER in Mexico City might provide valuable information to predict the emergence of new pathogenic influenza virus.

Abstract The closely related transcription factors (TFs), estrogen receptors ERα and ERβ, regulate divergent gene expression programs and proliferative outcomes in breast cancer. Utilizing breast cancer cells with ERα, ERβ, or both receptors as a model system to define the basis for differing response specification by related TFs, we show that these TFs and their key coregulators, SRC3 and RIP140, generate overlapping as well as unique chromatin‐binding and transcription‐regulating modules. Cistrome and transcriptome analyses and the use of clustering algorithms delineated 11 clusters representing different chromatin‐bound receptor and coregulator assemblies that could be functionally associated through enrichment analysis with distinct patterns of gene regulation and preferential coregulator usage, RIP140 with ERβ and SRC3 with ERα. The receptors modified each other's transcriptional effect, and ERβ countered the proliferative drive of ERα through several novel mechanisms associated with specific binding‐site clusters. Our findings delineate distinct TF‐coregulator assemblies that function as control nodes, specifying precise patterns of gene regulation, proliferation, and metabolism, as exemplified by two of the most important nuclear hormone receptors in human breast cancer.

Abstract Despite the role of the estrogen receptor α (ERα) pathway as a key growth driver for breast cells, the phenotypic consequence of exogenous introduction of ERα into ERα‐negative cells paradoxically has been growth inhibition. We mapped the binding profiles of ERα and its interacting transcription factors (TFs), FOXA1 and GATA3 in MCF‐7 breast carcinoma cells, and observed that these three TFs form a functional enhanceosome that regulates the genes driving core ERα function and cooperatively modulate the transcriptional networks previously ascribed to ERα alone. We demonstrate that these enhanceosome occupied sites are associated with optimal enhancer characteristics with highest p300 co‐activator recruitment, RNA Pol II occupancy, and chromatin opening. Most importantly, we show that the transfection of all three TFs was necessary to reprogramme the ERα‐negative MDA‐MB‐231 and BT‐549 cells to restore the estrogen‐responsive growth resembling estrogen‐treated ERα‐positive MCF‐7 cells. Cumulatively, these results suggest that all the enhanceosome components comprising ERα, FOXA1, and GATA3 are necessary for the full repertoire of cancer‐associated effects of the ERα.

Abstract A major question in transcription factor (TF) biology is why a TF binds to only a small fraction of motif eligible binding sites in the genome. Using the estrogen receptor‐α as a model system, we sought to explicitly define parameters that determine TF‐binding site selection. By examining 12 genetic and epigenetic parameters, we find that an energetically favorable estrogen response element (ERE) motif sequence, co‐occupancy by the TF FOXA1, the presence of the H3K4me1 mark and an open chromatin configuration in the pre‐ligand state provide specificity for ER binding. These factors can model estrogen‐induced ER binding with high accuracy (ROC‐AUC=0.95 and 0.88 using different genomic backgrounds). Moreover, when assessed in another estrogen‐responsive cell line, this model was highly predictive for ERα binding (ROC‐AUC=0.86). Variance in binding site selection between MCF‐7 and T47D resides in sites with suboptimal ERE motifs, but modulated by the chromatin configuration. These results suggest a definable interplay between sequence motifs and local chromatin in selecting TF binding.

Genome-wide functional analyses require high-resolution genome assembly and annotation. We applied ChIA-PET to analyze gene regulatory networks, including 3D chromosome interactions, underlying thyroid hormone (TH) signaling in the frog Xenopus tropicalis. As the available versions of Xenopus tropicalis assembly and annotation lacked the resolution required for ChIA-PET we improve the genome assembly version 4.1 and annotations using data derived from the paired end tag (PET) sequencing technologies and approaches (e.g., DNA-PET [gPET], RNA-PET etc.). The large insert (~10 Kb, ~17 Kb) paired end DNA-PET with high throughput NGS sequencing not only significantly improved genome assembly quality, but also strongly reduced genome "fragmentation", reducing total scaffold numbers by ~60%. Next, RNA-PET technology, designed and developed for the detection of full-length transcripts and fusion mRNA in whole transcriptome studies (ENCODE consortia), was applied to capture the 5' and 3' ends of transcripts. These amendments in assembly and annotation were essential prerequisites for the ChIA-PET analysis of TH transcription regulation. Their application revealed complex regulatory configurations of target genes and the structures of the regulatory networks underlying physiological responses. Our work allowed us to improve the quality of Xenopus tropicalis genomic resources, reaching the standard required for ChIA-PET analysis of transcriptional networks. We consider that the workflow proposed offers useful conceptual and methodological guidance and can readily be applied to other non-conventional models that have low-resolution genome data.

Zebrafish (Danio rerio) is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula) revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html).

Delineating candidate genes at the chromosomal breakpoint regions in the apparently balanced chromosome rearrangements (ABCR) has been shown to be more effective with the emergence of next-generation sequencing (NGS) technologies. We employed a large-insert (7-11 kb) paired-end tag sequencing technology (DNA-PET) to systematically analyze genome of four patients harbouring cytogenetically defined ABCR with neurodevelopmental symptoms, including developmental delay (DD) and speech disorders. We characterized structural variants (SVs) specific to each individual, including those matching the chromosomal breakpoints. Refinement of these regions by Sanger sequencing resulted in the identification of five disrupted genes in three individuals: guanine nucleotide binding protein, q polypeptide (GNAQ), RNA-binding protein, fox-1 homolog (RBFOX3), unc-5 homolog D (C.elegans) (UNC5D), transmembrane protein 47 (TMEM47), and X-linked inhibitor of apoptosis (XIAP). Among them, XIAP is the causative gene for the immunodeficiency phenotype seen in the patient. The remaining genes displayed specific expression in the fetal brain and have known biologically relevant functions in brain development, suggesting putative candidate genes for neurodevelopmental phenotypes. This study demonstrates the application of NGS technologies in mapping individual gene disruptions in ABCR as a resource for deciphering candidate genes in human neurodevelopmental disorders (NDDs).

BackgroundGenome-wide comparisons of transcription factor binding sites in different species can be used to evaluate evolutionary constraints that shape gene regulatory circuits and to understand how the interaction between transcription factors shapes their binding landscapes over evolution.ResultsWe have compared the PPARG binding landscapes in macrophages to investigate the evolutionary impact on PPARG binding diversity in mouse and humans for this important nuclear receptor. Of note, only 5% of the PPARG binding sites were shared between the two species. In contrast, at the gene level, PPARG target genes conserved between both species constitute more than 30% of the target genes regulated by PPARG ligand in human macrophages. Moreover, the majority of all PPARG binding sites (55-60%) in macrophages show co-occupancy of the lineage-specification factor PU.1 in both species. Exploring the evolutionary dynamics of PPARG binding sites, we observed that PU.1 co-binding to PPARG sites appears to be important for possible PPARG ancestral functions such as lipid metabolism. Thus we speculate that PU.1 may have guided utilization of these species-specific PPARG conserved binding sites in macrophages during evolution.ConclusionsWe propose a model in which PU.1 sites may have served as "anchor" loci for the formation of new and functionally relevant PPARG binding sites throughout evolution. As PU.1 is an essential factor in macrophage biology, such an evolutionary mechanism would allow for the establishment of relevant PPARG regulatory modules in a PU.1-dependent manner and yet permit for nuanced regulatory changes in individual species.

Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. While genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs, the current application of PET sequencing with short insert size DNA can be insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We employed a recently developed procedure to generate PET sequencing data using large DNA inserts of 10-20 kb and compared their characteristics with short insert (1 kb) libraries for their ability to identify SVs. Our results suggest that although short insert libraries bear an advantage in identifying small deletions, they do not provide significantly better breakpoint resolution. In contrast, large inserts are superior to short inserts in providing higher physical genome coverage for the same sequencing cost and achieve greater sensitivity, in practice, for the identification of several classes of SVs, such as copy number neutral and complex events. Furthermore, our results confirm that large insert libraries allow for the identification of SVs within repetitive sequences, which cannot be spanned by short inserts. This provides a key advantage in studying rearrangements in cancer, and we show how it can be used in a fusion-point-guided-concatenation algorithm to study focally amplified regions in cancer.

Non-Hodgkin lymphoma (NHL) represents a diverse group of hematological malignancies, of which follicular lymphoma (FL) is a prevalent subtype. A previous genome-wide association study has established a marker, rs10484561 in the human leukocyte antigen (HLA) class II region on 6p21.32 associated with increased FL risk. Here, in a three-stage genome-wide association study, starting with a genome-wide scan of 379 FL cases and 791 controls followed by validation in 1,049 cases and 5,790 controls, we identified a second independent FL-associated locus on 6p21.32, rs2647012 (OR(combined) = 0.64, P(combined) = 2 × 10(-21)) located 962 bp away from rs10484561 (r(2)

Despite the central role of estrogen exposure in breast and endometrial cancer development and numerous studies of genes in the estrogen metabolic pathway, polymorphisms within the pathway have not been consistently associated with these cancers. We posit that this is due to the complexity of multiple weak genetic effects within the metabolic pathway that can only be effectively detected through multi-variant analysis. We conducted a comprehensive association analysis of the estrogen metabolic pathway by interrogating 239 tagSNPs within 35 genes of the pathway in three tumor samples. The discovery sample consisted of 1,596 breast cancer cases, 719 endometrial cancer cases, and 1,730 controls from Sweden; and the validation sample included 2,245 breast cancer cases and 1,287 controls from Finland. We performed admixture maximum likelihood (AML)-based global tests to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three sub-pathways for androgen synthesis, androgen-to-estrogen conversion, and estrogen removal. In the discovery sample, although no single polymorphism was significant after correction for multiple testing, the pathway-based AML global test suggested association with both breast (p(global) = 0.034) and endometrial (p(global) = 0.052) cancers. Further testing revealed the association to be focused on polymorphisms within the androgen-to-estrogen conversion sub-pathway, for both breast (p(global) = 0.008) and endometrial cancer (p(global) = 0.014). The sub-pathway association was validated in the Finnish sample of breast cancer (p(global) = 0.015). Further tumor subtype analysis demonstrated that the association of the androgen-to-estrogen conversion sub-pathway was confined to postmenopausal women with sporadic estrogen receptor positive tumors (p(global) = 0.0003). Gene-based AML analysis suggested CYP19A1 and UGT2B4 to be the major players within the sub-pathway. Our study indicates that the composite genetic determinants related to the androgen-estrogen conversion are important for the induction of two hormone-associated cancers, particularly for the hormone-driven breast tumour subtypes.

BACKGROUND: The pathophysiology of obesity and type 2 diabetes mellitus is associated with abnormalities in endocrine signaling in adipose tissue and one of the key signaling affectors operative in these disorders is the nuclear hormone transcription factor peroxisome proliferator-activated receptor-gamma (PPARgamma). PPARgamma has pleiotropic functions affecting a wide range of fundamental biological processes including the regulation of genes that modulate insulin sensitivity, adipocyte differentiation, inflammation and atherosclerosis. To date, only a limited number of direct targets for PPARgamma have been identified through research using the well established pre-adipogenic cell line, 3T3-L1. In order to obtain a genome-wide view of PPARgamma binding sites, we applied the pair end-tagging technology (ChIP-PET) to map PPARgamma binding sites in 3T3-L1 preadipocyte cells. METHODOLOGY/PRINCIPAL FINDINGS: Coupling gene expression profile analysis with ChIP-PET, we identified in a genome-wide manner over 7700 DNA binding sites of the transcription factor PPARgamma and its heterodimeric partner RXR during the course of adipocyte differentiation. Our validation studies prove that the identified sites are bona fide binding sites for both PPARgamma and RXR and that they are functionally capable of driving PPARgamma specific transcription. Our results strongly indicate that PPARgamma is the predominant heterodimerization partner for RXR during late stages of adipocyte differentiation. Additionally, we find that PPARgamma/RXR association is enriched within the proximity of the 5' region of the transcription start site and this association is significantly associated with transcriptional up-regulation of genes involved in fatty acid and lipid metabolism confirming the role of PPARgamma as the master transcriptional regulator of adipogenesis. Evolutionary conservation analysis of these binding sites is greater when adjacent to up-regulated genes than down-regulated genes, suggesting the primordial function of PPARgamma/RXR is in the induction of genes. Our functional validations resulted in identifying novel PPARgamma direct targets that have not been previously reported to promote adipogenic differentiation. CONCLUSIONS/SIGNIFICANCE: We have identified in a genome-wide manner the binding sites of PPARgamma and RXR during the course of adipogenic differentiation in 3T3L1 cells, and provide an important resource for the study of PPARgamma function in the context of adipocyte differentiation.

The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly), is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated) aromatic hydrocarbons [P(H)AHs] and estrogenic compounds (ECs), we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR) and estrogen receptor (ER) agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology.

BACKGROUND: During S. pombe S-phase, initiation of DNA replication occurs at multiple sites (origins) that are enriched with AT-rich sequences, at various times. Current studies of genome-wide DNA replication profiles have focused on the DNA replication timing and origin location. However, the replication and/or firing efficiency of the individual origins on the genomic scale remain unclear. METHODOLOGY/PRINCIPAL FINDINGS: Using the genome-wide ORF-specific DNA microarray analysis, we show that in S. pombe, individual origins fire with varying efficiencies and at different times during S-phase. The increase in DNA copy number plotted as a function of time is approximated to the near-sigmoidal model, when considering the replication start and end timings at individual loci in cells released from HU-arrest. Replication efficiencies differ from origin to origin, depending on the origin's firing efficiency. We have found that DNA replication is inefficient early in S-phase, due to inefficient firing at origins. Efficient replication occurs later, attributed to efficient but late-firing origins. Furthermore, profiles of replication timing in cds1Delta cells are abnormal, due to the failure in resuming replication at the collapsed forks. The majority of the inefficient origins, but not the efficient ones, are found to fire in cds1Delta cells after HU removal, owing to the firing at the remaining unused (inefficient) origins during HU treatment. CONCLUSIONS/SIGNIFICANCE: Taken together, our results indicate that efficient DNA replication/firing occurs late in S-phase progression in cells after HU removal, due to efficient late-firing origins. Additionally, checkpoint kinase Cds1p is required for maintaining the efficient replication/firing late in S-phase. We further propose that efficient late-firing origins are essential for ensuring completion of DNA duplication by the end of S-phase.

BACKGROUND: Checkpoint kinase 2 (CHEK2) averts cancer development by promoting cell cycle arrest and activating DNA repair in genetically damaged cells. Previous investigation has established a role for the CHEK2 gene in breast cancer aetiology, but studies have largely been limited to the rare 1100delC mutation. Whether common polymorphisms in this gene influence breast cancer risk remains unknown. In this study, we aimed to assess the importance of common CHEK2 variants on population risk for breast cancer by capturing the majority of diversity in the gene using haplotype tagging single nucleotide polymorphisms (tagSNPs). METHODS AND FINDINGS: We analyzed 14 common SNPs spanning 52 kilobases (kb) of the CHEK2 gene in 92 Swedish women. Coverage evaluation indicated that these typed SNPs would efficiently convey association signal also from untyped SNPs in the same region. Six of the 14 SNPs predicted well both the haplotypic and single SNP variations within CHEK2. We genotyped these six tagSNPs in 1,577 postmenopausal breast cancer cases and 1,513 population controls, but found no convincing association between any common CHEK2 haplotype and breast cancer risk. The 1100delC mutation was rare in our Swedish population--0.7% in cases and 0.4% in controls--with a corresponding odds ratio for carriers versus noncarriers of 2.26 (95% confidence interval, 0.99-5.15). Estimates of the population frequency and the odds ratio of 1100delC indicate that our sample is representative of a Northern European population. CONCLUSIONS: Notwithstanding the involvement of the CHEK2 gene in breast cancer aetiology, we show that common polymorphisms do not influence postmenopausal breast cancer risk.

The human gut is known to be a reservoir of a wide variety of microbes, including viruses. Many RNA viruses are known to be associated with gastroenteritis; however, the enteric RNA viral community present in healthy humans has not been described. Here, we present a comparative metagenomic analysis of the RNA viruses found in three fecal samples from two healthy human individuals. For this study, uncultured viruses were concentrated by tangential flow filtration, and viral RNA was extracted and cloned into shotgun viral cDNA libraries for sequencing analysis. The vast majority of the 36,769 viral sequences obtained were similar to plant pathogenic RNA viruses. The most abundant fecal virus in this study was pepper mild mottle virus (PMMV), which was found in high concentrations--up to 10(9) virions per gram of dry weight fecal matter. PMMV was also detected in 12 (66.7%) of 18 fecal samples collected from healthy individuals on two continents, indicating that this plant virus is prevalent in the human population. A number of pepper-based foods tested positive for PMMV, suggesting dietary origins for this virus. Intriguingly, the fecal PMMV was infectious to host plants, suggesting that humans might act as a vehicle for the dissemination of certain plant viruses.

BackgroundEpidemiological investigations of infectious disease are mainly dependent on indirect contact information and only occasionally assisted by characterization of pathogen sequence variation from clinical isolates. Direct sequence analysis of the pathogen, particularly at a population level, is generally thought to be too cumbersome, technically difficult, and expensive. We present here a novel application of mass spectrometry (MS)-based technology in characterizing viral sequence variations that overcomes these problems, and we apply it retrospectively to the severe acute respiratory syndrome (SARS) outbreak in Singapore.Methods and findingsThe success rate of the MS-based analysis for detecting SARS coronavirus (SARS-CoV) sequence variations was determined to be 95% with 75 copies of viral RNA per reaction, which is sufficient to directly analyze both clinical and cultured samples. Analysis of 13 SARS-CoV isolates from the different stages of the Singapore outbreak identified nine sequence variations that could define the molecular relationship between them and pointed to a new, previously unidentified, primary route of introduction of SARS-CoV into the Singapore population. Our direct determination of viral sequence variation from a clinical sample also clarified an unresolved epidemiological link regarding the acquisition of SARS in a German patient. We were also able to detect heterogeneous viral sequences in primary lung tissues, suggesting a possible coevolution of quasispecies of virus within a single host.ConclusionThis study has further demonstrated the importance of improving clinical and epidemiological studies of pathogen transmission through the use of genetic analysis and has revealed the MS-based analysis to be a sensitive and accurate method for characterizing SARS-CoV genetic variations in clinical samples. We suggest that this approach should be used routinely during outbreaks of a wide variety of agents, in order to allow the most effective control.