Genomic sites hypersensitive to ultraviolet radiation.

If the genome contains outlier sequences extraordinarily sensitive to environmental agents, these would be sentinels for monitoring personal carcinogen exposure and might drive direct changes in cell physiology rather than acting through rare mutations. New methods, adductSeq and freqSeq, provided statistical resolution to quantify rare lesions at single-base resolution across the genome. Primary human melanocytes, but not fibroblasts, carried spontaneous apurinic sites and TG sequence lesions more frequent than ultraviolet (UV)-induced cyclobutane pyrimidine dimers (CPDs). UV exposure revealed hyperhotspots acquiring CPDs up to 170-fold more frequently than the genomic average; these sites were more prevalent in melanocytes. Hyperhotspots were disproportionately located near genes, particularly for RNA-binding proteins, with the most-recurrent hyperhotspots at a fixed position within 2 motifs. One motif occurs at ETS family transcription factor binding sites, known to be UV targets and now shown to be among the most sensitive in the genome, and at sites of mTOR/5' terminal oligopyrimidine-tract translation regulation. The second occurs at A2-15TTCTY, which developed "dark CPDs" long after UV exposure, repaired CPDs slowly, and had accumulated CPDs prior to the experiment. Motif locations active as hyperhotspots differed between cell types. Melanocyte CPD hyperhotspots aligned precisely with recurrent UV signature mutations in individual gene promoters of melanomas and with known cancer drivers. At sunburn levels of UV exposure, every cell would have a hyperhotspot CPD in each of the ∼20 targeted cell pathways, letting hyperhotspots act as epigenetic marks that create phenome instability; high prevalence favors cooccurring mutations, which would allow tumor evolution to use weak drivers.

MetaCycle: an integrated R package to evaluate periodicity in large scale data.

Detecting periodicity in large scale data remains a challenge. While efforts have been made to identify best of breed algorithms, relatively little research has gone into integrating these methods in a generalizable method. Here, we present MetaCycle, an R package that incorporates ARSER, JTK_CYCLE and Lomb-Scargle to conveniently evaluate periodicity in time-series data. MetaCycle has two functions, meta2d and meta3d, designed to analyze two-dimensional and three-dimensional time-series datasets, respectively. Meta2d implements N-version programming concepts using a suite of algorithms and integrating their results. AVAILABILITY AND IMPLEMENTATION: MetaCycle package is available on the CRAN repository (https://cran.r-project.org/web/packages/MetaCycle/index.html) and GitHub (https://github.com/gangwug/MetaCycle). CONTACT: hogenesch@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online.

Pervasive Induction of Regulatory Mutation Microclones in Sun-exposed Skin.

Carcinogen-induced mutations are thought near-random, with rare cancer-driver mutations underlying clonal expansion. Using high-fidelity Duplex Sequencing to reach a mutation frequency sensitivity of 4×10 -9 per nt, we report that sun exposure creates pervasive mutations at sites with ∼100-fold UV-sensitivity in RNA-processing gene promoters - cyclobutane pyrimidine dimer (CPD) hyperhotspots - and these mutations have a mini-driver clonal expansion phenotype. Numerically, human skin harbored 10-fold more genuine mutations than previously reported, with neonatal skin containing 90,000 per cell; UV signature mutations increased 8,000-fold in sun-exposed skin, averaging 3×10 -5 per nt. Clonal expansion by neutral drift or passenger formation was nil. Tumor suppressor gene hotspots reached variant allele frequency 0.1-10% via 30-3,000 fold clonal expansion, in occasional biopsies. CPD hyperhotspots reached those frequencies in every biopsy, with modest clonal expansion. In vitro, tumor hotspot mutations arose occasionally over weeks of chronic low-dose exposure, whereas CPD hyperhotspot mutations arose in days at 1000-fold higher frequencies, growing exponentially. UV targeted mini-drivers in every skin cell.

Synergistic function of E2F7 and E2F8 is essential for cell survival and embryonic development.

The E2f7 and E2f8 family members are thought to function as transcriptional repressors important for the control of cell proliferation. Here, we have analyzed the consequences of inactivating E2f7 and E2f8 in mice and show that their individual loss had no significant effect on development. Their combined ablation, however, resulted in massive apoptosis and dilation of blood vessels, culminating in lethality by embryonic day E11.5. A deficiency in E2f7 and E2f8 led to an increase in E2f1 and p53, as well as in many stress-related genes. Homo- and heterodimers of E2F7 and E2F8 were found on target promoters, including E2f1. Importantly, loss of either E2f1 or p53 suppressed the massive apoptosis in double-mutant embryos. These results identify E2F7 and E2F8 as a unique repressive arm of the E2F transcriptional network that is critical for embryonic development and control of the E2F1-p53 apoptotic axis.

The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding.

BACKGROUND: Chromatin immunoprecipitation combined with high-throughput sequencing (ChIP-Seq) is the most frequently used method to identify the binding sites of transcription factors. Active binding sites can be seen as peaks in enrichment profiles when the sequencing reads are mapped to a reference genome. However, the profiles are normally noisy, making it challenging to identify all significantly enriched regions in a reliable way and with an acceptable false discovery rate. RESULTS: We present the Triform algorithm, an improved approach to automatic peak finding in ChIP-Seq enrichment profiles for transcription factors. The method uses model-free statistics to identify peak-like distributions of sequencing reads, taking advantage of improved peak definition in combination with known characteristics of ChIP-Seq data. CONCLUSIONS: Triform outperforms several existing methods in the identification of representative peak profiles in curated benchmark data sets. We also show that Triform in many cases is able to identify peaks that are more consistent with biological function, compared with other methods. Finally, we show that Triform can be used to generate novel information on transcription factor binding in repeat regions, which represents a particular challenge in many ChIP-Seq experiments. The Triform algorithm has been implemented in R, and is available via http://tare.medisin.ntnu.no/triform.

RNA-Seq and molecular docking reveal multi-level pesticide resistance in the bed bug.

BACKGROUND: Bed bugs (Cimex lectularius) are hematophagous nocturnal parasites of humans that have attained high impact status due to their worldwide resurgence. The sudden and rampant resurgence of C. lectularius has been attributed to numerous factors including frequent international travel, narrower pest management practices, and insecticide resistance. RESULTS: We performed a next-generation RNA sequencing (RNA-Seq) experiment to find differentially expressed genes between pesticide-resistant (PR) and pesticide-susceptible (PS) strains of C. lectularius. A reference transcriptome database of 51,492 expressed sequence tags (ESTs) was created by combining the databases derived from de novo assembled mRNA-Seq tags (30,404 ESTs) and our previous 454 pyrosequenced database (21,088 ESTs). The two-way GLMseq analysis revealed ~15,000 highly significant differentially expressed ESTs between the PR and PS strains. Among the top 5,000 differentially expressed ESTs, 109 putative defense genes (cuticular proteins, cytochrome P450s, antioxidant genes, ABC transporters, glutathione S-transferases, carboxylesterases and acetyl cholinesterase) involved in penetration resistance and metabolic resistance were identified. Tissue and development-specific expression of P450 CYP3 clan members showed high mRNA levels in the cuticle, Malpighian tubules, and midgut; and in early instar nymphs, respectively. Lastly, molecular modeling and docking of a candidate cytochrome P450 (CYP397A1V2) revealed the flexibility of the deduced protein to metabolize a broad range of insecticide substrates including DDT, deltamethrin, permethrin, and imidacloprid. CONCLUSIONS: We developed significant molecular resources for C. lectularius putatively involved in metabolic resistance as well as those participating in other modes of insecticide resistance. RNA-Seq profiles of PR strains combined with tissue-specific profiles and molecular docking revealed multi-level insecticide resistance in C. lectularius. Future research that is targeted towards RNA interference (RNAi) on the identified metabolic targets such as cytochrome P450s and cuticular proteins could lay the foundation for a better understanding of the genetic basis of insecticide resistance in C. lectularius.

Cyclobutane Pyrimidine Dimer Hyperhotspots as Sensitive Indicators of Keratinocyte UV Exposure†.

The dominant DNA damage generated by UV exposure is the cyclobutane pyrimidine dimer (CPD), which alters skin cell physiology and induces cell death and mutation. Genome-wide nucleotide-resolution analysis of CPDs in melanocytes and fibroblasts has identified "CPD hyperhotspots", pyrimidine-pyrimidine sites hundreds of fold more susceptible to the generation of CPDs than the genomic average. Identifying hyperhotspots in keratinocytes could enable measuring individual past UV exposure in small skin samples and predicting future skin cancer risk. We therefore exposed neonatal human epidermal keratinocytes to narrowband UVB and quantified CPDs using the adductSeq high-throughput DNA sequencing method. Keratinocytes contained thousands of CPD hyperhotspots, with a UVB-sensitivity up to 550 fold greater than the genomic average. As with melanocytes, the most sensitive sites were located in promoter regions at ETS-family transcription factor binding sequence motifs, near RNA processing genes. Moreover, they lay at sequence motifs bound to ETS1 in CpG islands. These genes were specifically upregulated in skin and the CPD hyperhotspots were mutated in a fraction of keratinocyte cancers. Crucially for their biological importance and practical application, CPD hyperhotspot locations and UV-sensitivity ranking demonstrated high reproducibility across experiments and across skin donors. CPD hyperhotspots are therefore sensitive indicators of UV exposure.

Expression Profiling Using Affymetrix GeneChip Microarrays.

The approximately 25,000 genes in mammalian genomes can be transcribed at different levels. Measurements of gene expression for ten thousands of genes in parallel give the most comprehensive picture of steady-state levels of transcripts and is used in basic and applied research. Microarrays are the most frequently used technology for genome-wide expression profiling; from the various available microarray platforms, Affymetrix GeneChips are most frequently used for expression profiling and over 3,000 scientific publications describe results of this technology. In medical research, expression profiling by microarrays holds great promises for better understanding of diseases, identification of new therapeutic targets, and subclassification of diseases to identify individualized treatment strategies.

Accurate quantification of DNA methylation using combined bisulfite restriction analysis coupled with the Agilent 2100 Bioanalyzer platform.

DNA methylation is the best-studied epigenetic modification and describes the conversion of cytosine to 5-methylcytosine. The importance of this phenomenon is that aberrant promoter hypermethylation is a common occurrence in cancer and is frequently associated with gene silencing. Various techniques are currently available for the analysis of DNA methylation. However, accurate and reproducible quantification of DNA methylation remains challenging. In this report, we describe Bio-COBRA (combined bisulfite restriction analysis coupled with the Agilent 2100 Bioanalyzer platform), as a novel approach to quantitative DNA methylation analysis. The combination of a well-established method, COBRA, which interrogates DNA methylation via the restriction enzyme analysis of PCR-amplified bisulfite treated DNAs, with the Bioanalyzer platform allows for the rapid and quantitative assessment of DNA methylation patterns in large sample sets. The sensitivity and reproducibility of Bio-COBRA make it a valuable tool for the analysis of DNA methylation in clinical samples, which could aid in the development of diagnostic and prognostic parameters with respect to disease detection and management.

Gene-resolution analysis of DNA copy number variation using oligonucleotide expression microarrays.

BACKGROUND: Array-based comparative genomic hybridization (aCGH) is a high-throughput method for measuring genome-wide DNA copy number changes. Current aCGH methods have limited resolution, sensitivity and reproducibility. Microarrays for aCGH are available only for a few organisms and combination of aCGH data with expression data is cumbersome. RESULTS: We present a novel method of using commercial oligonucleotide expression microarrays for aCGH, enabling DNA copy number measurements and expression profiles to be combined using the same platform. This method yields aCGH data from genomic DNA without complexity reduction at a median resolution of approximately 17,500 base pairs. Due to the well-defined nature of oligonucleotide probes, DNA amplification and deletion can be defined at the level of individual genes and can easily be combined with gene expression data. CONCLUSION: A novel method of gene resolution analysis of copy number variation (graCNV) yields high-resolution maps of DNA copy number changes and is applicable to a broad range of organisms for which commercial oligonucleotide expression microarrays are available. Due to the standardization of oligonucleotide microarrays, graCNV results can reliably be compared between laboratories and can easily be combined with gene expression data using the same platform.

Big results from small samples: evaluation of amplification protocols for gene expression profiling.

Microarrays have revolutionized many areas of biology due to our technical ability to quantify tens of thousands of transcripts within a single experiment. However, there are still many areas that cannot benefit from this technology due to the amount of biological material needed for microarray analysis. In response to this demand, chemistries have been developed that boast the capability of generating targets from nanogram amounts of total RnA, reflecting minimal amounts of biological material, on the order of several hundred or thousand cells. Herein, we describe the evaluation of four chemistries for RnA amplification in terms of reproducibility, sensitivity, accuracy, and comparability to results from a single round of T7 amplification. No evidence for false-positive measurements of differential expression was observed. In contrast, clear differences between chemistries in sensitivity and accuracy were detected. PCR validation showed an interaction of probe sequence on the array and target labeling chemistry, resulting in a chemistry-dependent probe set sensitivity varying over an order of magnitude.

Guidelines for Genome-Scale Analysis of Biological Rhythms.

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding "big data" that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

Excitatory/inhibitory synaptic imbalance leads to hippocampal hyperexcitability in mouse models of tuberous sclerosis.

Neural circuits are regulated by activity-dependent feedback systems that tightly control network excitability and which are thought to be crucial for proper brain development. Defects in the ability to establish and maintain network homeostasis may be central to the pathogenesis of neurodevelopmental disorders. Here, we examine the function of the tuberous sclerosis complex (TSC)-mTOR signaling pathway, a common target of mutations associated with epilepsy and autism spectrum disorder, in regulating activity-dependent processes in the mouse hippocampus. We find that the TSC-mTOR pathway is a central component of a positive feedback loop that promotes network activity by repressing inhibitory synapses onto excitatory neurons. In Tsc1 KO neurons, weakened inhibition caused by deregulated mTOR alters the balance of excitatory and inhibitory synaptic transmission, leading to hippocampal hyperexcitability. These findings identify the TSC-mTOR pathway as a regulator of neural network activity and have implications for the neurological dysfunction in disorders exhibiting deregulated mTOR signaling.

Age-associated disruption of molecular clock expression in skeletal muscle of the spontaneously hypertensive rat.

It is well known that spontaneously hypertensive rats (SHR) develop muscle pathologies with hypertension and heart failure, though the mechanism remains poorly understood. Woon et al. (2007) linked the circadian clock gene Bmal1 to hypertension and metabolic dysfunction in the SHR. Building on these findings, we compared the expression pattern of several core-clock genes in the gastrocnemius muscle of aged SHR (80 weeks; overt heart failure) compared to aged-matched control WKY strain. Heart failure was associated with marked effects on the expression of Bmal1, Clock and Rora in addition to several non-circadian genes important in regulating skeletal muscle phenotype including Mck, Ttn and Mef2c. We next performed circadian time-course collections at a young age (8 weeks; pre-hypertensive) and adult age (22 weeks; hypertensive) to determine if clock gene expression was disrupted in gastrocnemius, heart and liver tissues prior to or after the rats became hypertensive. We found that hypertensive/hypertrophic SHR showed a dampening of peak Bmal1 and Rev-erb expression in the liver, and the clock-controlled gene Pgc1α in the gastrocnemius. In addition, the core-clock gene Clock and the muscle-specific, clock-controlled gene Myod1, no longer maintained a circadian pattern of expression in gastrocnemius from the hypertensive SHR. These findings provide a framework to suggest a mechanism whereby chronic heart failure leads to skeletal muscle pathologies; prolonged dysregulation of the molecular clock in skeletal muscle results in altered Clock, Pgc1α and Myod1 expression which in turn leads to the mis-regulation of target genes important for mechanical and metabolic function of skeletal muscle.

JTK_CYCLE: an efficient nonparametric algorithm for detecting rhythmic components in genome-scale data sets.

Circadian rhythms are oscillations of physiology, behavior, and metabolism that have period lengths near 24 hours. In several model organisms and humans, circadian clock genes have been characterized and found to be transcription factors. Because of this, researchers have used microarrays to characterize global regulation of gene expression and algorithmic approaches to detect cycling. This article presents a new algorithm, JTK_CYCLE, designed to efficiently identify and characterize cycling variables in large data sets. Compared with COSOPT and the Fisher's G test, two commonly used methods for detecting cycling transcripts, JTK_CYCLE distinguishes between rhythmic and nonrhythmic transcripts more reliably and efficiently. JTK_CYCLE's increased resistance to outliers results in considerably greater sensitivity and specificity. Moreover, JTK_CYCLE accurately measures the period, phase, and amplitude of cycling transcripts, facilitating downstream analyses. Finally, JTK_CYCLE is several orders of magnitude faster than COSOPT, making it ideal for large-scale data sets. JTK_CYCLE was used to analyze legacy data sets including NIH3T3 cells, which have comparatively low amplitude oscillations. JTK_CYCLE's improved power led to the identification of a novel cluster of RNA-interacting genes whose abundance is under clear circadian regulation. These data suggest that JTK_CYCLE is an ideal tool for identifying and characterizing oscillations in genome-scale data sets.

Accurate expression profiling of very small cell populations.

BACKGROUND: Expression profiling, the measurement of all transcripts of a cell or tissue type, is currently the most comprehensive method to describe their physiological states. Given that accurate profiling methods currently available require RNA amounts found in thousands to millions of cells, many fields of biology working with specialized cell types cannot use these techniques because available cell numbers are limited. Currently available alternative methods for expression profiling from nanograms of RNA or from very small cell populations lack a broad validation of results to provide accurate information about the measured transcripts. METHODS AND FINDINGS: We provide evidence that currently available methods for expression profiling of very small cell populations are prone to technical noise and therefore cannot be used efficiently as discovery tools. Furthermore, we present Pico Profiling, a new expression profiling method from as few as ten cells, and we show that this approach is as informative as standard techniques from thousands to millions of cells. The central component of Pico Profiling is Whole Transcriptome Amplification (WTA), which generates expression profiles that are highly comparable to those produced by others, at different times, by standard protocols or by Real-time PCR. We provide a complete workflow from RNA isolation to analysis of expression profiles. CONCLUSIONS: Pico Profiling, as presented here, allows generating an accurate expression profile from cell populations as small as ten cells.

Stimulation of the insulin/mTOR pathway delays cone death in a mouse model of retinitis pigmentosa.

Retinitis pigmentosa is an incurable retinal disease that leads to blindness. One puzzling aspect concerns the progression of the disease. Although most mutations that cause retinitis pigmentosa are in rod photoreceptor-specific genes, cone photoreceptors also die as a result of such mutations. To understand the mechanism of non-autonomous cone death, we analyzed four mouse models harboring mutations in rod-specific genes. We found changes in the insulin/mammalian target of rapamycin pathway that coincided with the activation of autophagy during the period of cone death. We increased or decreased the insulin level and measured the survival of cones in one of the models. Mice that were treated systemically with insulin had prolonged cone survival, whereas depletion of endogenous insulin had the opposite effect. These data suggest that the non-autonomous cone death in retinitis pigmentosa could, at least in part, be a result of the starvation of cones.

Transcriptional profiling of the megabladder mouse: a unique model of bladder dysmorphogenesis.

Recent studies in our lab identified a mutant mouse model of obstructive nephropathy designated mgb for megabladder. Homozygotic mgb mice (mgb-/-) develop lower urinary tract obstruction in utero due to a lack of bladder smooth muscle differentiation. This defect is the result of a random transgene insertion/translocation into chromosomes 11 and 16. Transcriptional profiling identified a significantly over-expressed cluster of gene products located on the translocated fragment of chromosome 16 including urotensin II-related peptide (Urp), which was shown to be preferentially over-expressed in developing mgb-/- bladders. Pathway analysis of mgb microarray data indicated dysregulation of at least 60 gene products associated with smooth muscle development. In conclusion, the results of this study indicate that the molecular pathways controlling normal smooth muscle development are severely altered in mgb-/- bladders, and provide the first evidence that Urp may play a critical role in bladder smooth muscle development.

Identification of a unique transgenic mouse line that develops megabladder, obstructive uropathy, and renal dysfunction.

Urinary tract malformations, obstructive uropathy, and hypoplasia/dysplasia are extremely important in terms of pediatric health care costs, with end-stage renal failure in children estimated to cost >$15 billion annually in the United States alone. Even so, little is known regarding the mechanisms that control these processes. Identified was a unique mutant mouse model that develops in utero megabladder, resulting in variable hydroureteronephrosis and chronic renal failure secondary to obstructive uropathy. These animals, designated mgb for megabladder, possess a primary defect in bladder smooth muscle development that is apparent by embryonic day 15. The mgb mouse represents an excellent model for the study of normal and pathogenic bladder development, including the postnatal progression of chronic renal failure that results from the development of in utero obstructive uropathy.