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Background and Objectives: The objectives of this study were to investigate the prognostic value of primary symptoms and leading symptoms in adult patients with diffuse infiltrating glioma and to provide a clinical perspective for evaluating survival., Methods: This study included a retrospective cohort from two tertiary university hospitals ( n = 604, 2006-2013, Tampere University Hospital and Turku University Hospital) and a prospective cohort ( n = 156, 2014-2018, Tampere University Hospital). Preoperative symptoms were divided into primary and leading symptoms. Results were validated with the newer WHO 2021 classification criteria., Results: The most common primary symptoms were epileptic seizure (30.8% retrospective, 28.2% prospective), cognitive disorder (13.2% retrospective, 16.0% prospective), headache (8.6% retrospective, 12.8% prospective), and motor paresis (7.0% retrospective, 7.1% prospective). Symptoms that predicted better survival were epileptic seizure and visual or other sense-affecting symptom in the retrospective cohort and epileptic seizure and headache in the prospective cohort. Predictors of poor survival were cognitive disorder, motor dysfunction, sensory symptom, tumor hemorrhage, speech disorder and dizziness in the retrospective cohort and cognitive disorder, motor dysfunction, sensory symptom, and dizziness in the prospective cohort. Motor dysfunction served as an independent predictor of survival in a multivariate model (OR = 1.636)., Conclusion: Primary and leading symptoms in diffuse gliomas are associated with prognoses in retrospective and prospective settings. Motor paresis was an independent prognostic factor for poor survival in multivariate analysis for grade 2-4 diffuse gliomas, especially in glioblastomas., Competing Interests: Authors HH and JH were employed by the company Fimlab Laboratories Ltd, which is a public limited company. Individual funding outside of this submitted work: Academy of Finland #17379 to JP; Government’s Special Financial Transfer tied to academic research in Health Sciences, Finland #11129 to JP; the Maire Taponen Foundation. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Kivioja, Posti, Sipilä, Rauhala, Frantzén, Gardberg, Rahi, Rautajoki, Nykter, Vuorinen, Nordfors, Haapasalo and Haapasalo.)

Background: The purpose of our study was to analyze the impact of time interval from referral to surgery and from surgery to adjuvant treatment on survival of adult isocitrate dehydrogenase-wild-type (IDH-wt) glioblastomas., Methods: Data on 392 IDH-wt glioblastomas diagnosed at the Tampere University Hospital in 2004-2016 were obtained from the electronic patient record system. Piecewise Cox regression was used to calculate hazard ratios for different time intervals between referral and surgery, as well as between surgery and adjuvant treatments., Results: The median survival time from primary surgery was 9.5 months (interquartile range: 3.8-16.0). Survival among patients with an interval exceeding 4 weeks from referral to surgery was no worse compared to <2 weeks (hazard ratio: 0.78, 95% confidence interval: 0.54-1.14). We found indications of poorer outcome when the interval from surgery to radiotherapy exceeded 30 days (hazard ratio: 1.42, 95% confidence interval: 0.91-2.21 for 31-44 days; and 1.59, 0.94-2.67 for over 45 days)., Conclusions: Interval from referral to surgery in the range of 4-10 weeks was not associated with decreased survivals in IDH-wt glioblastomas. In contrast, delay exceeding 30 days from surgery to adjuvant treatment may decrease long-term survival., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Here we describe a competitive genome editing method that measures the effect of mutations on molecular functions, based on precision CRISPR editing using template libraries with either the original or altered sequence, and a sequence tag, enabling direct comparison between original and mutated cells. Using the example of the MYC oncogene, we identify important transcriptional targets and show that E-box mutations at MYC target gene promoters reduce cellular fitness., (© 2022. The Author(s).)

The transcription factor Myc drives cell growth across animal phyla and is activated in most forms of human cancer. However, it is unclear which Myc target genes need to be regulated to induce growth and whether multiple targets act additively or if induction of each target is individually necessary. Here, we identified Myc target genes whose regulation is conserved between humans and flies and deleted Myc-binding sites (E-boxes) in the promoters of fourteen of these genes in Drosophila. E-box mutants of essential genes were homozygous viable, indicating that the E-boxes are not required for basal expression. Eight E-box mutations led to Myc-like phenotypes; the strongest mutant, ppan Ebox-/- , also made the flies resistant to Myc-induced cell growth without affecting Myc-induced apoptosis. The ppan Ebox-/- flies are healthy and display only a minor developmental delay, suggesting that it may be possible to treat or prevent tumorigenesis by targeting individual downstream targets of Myc., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

DNA can determine where and when genes are expressed, but the full set of sequence determinants that control gene expression is unknown. Here, we measured the transcriptional activity of DNA sequences that represent an ~100 times larger sequence space than the human genome using massively parallel reporter assays (MPRAs). Machine learning models revealed that transcription factors (TFs) generally act in an additive manner with weak grammar and that most enhancers increase expression from a promoter by a mechanism that does not appear to involve specific TF-TF interactions. The enhancers themselves can be classified into three types: classical, closed chromatin and chromatin dependent. We also show that few TFs are strongly active in a cell, with most activities being similar between cell types. Individual TFs can have multiple gene regulatory activities, including chromatin opening and enhancing, promoting and determining transcription start site (TSS) activity, consistent with the view that the TF binding motif is the key atomic unit of gene expression., (© 2022. The Author(s).)

RNA-binding proteins (RBPs) regulate RNA metabolism at multiple levels by affecting splicing of nascent transcripts, RNA folding, base modification, transport, localization, translation, and stability. Despite their central role in RNA function, the RNA-binding specificities of most RBPs remain unknown or incompletely defined. To address this, we have assembled a genome-scale collection of RBPs and their RNA-binding domains (RBDs) and assessed their specificities using high-throughput RNA-SELEX (HTR-SELEX). Approximately 70% of RBPs for which we obtained a motif bound to short linear sequences, whereas ∼30% preferred structured motifs folding into stem-loops. We also found that many RBPs can bind to multiple distinctly different motifs. Analysis of the matches of the motifs in human genomic sequences suggested novel roles for many RBPs. We found that three cytoplasmic proteins-ZC3H12A, ZC3H12B, and ZC3H12C-bound to motifs resembling the splice donor sequence, suggesting that these proteins are involved in degradation of cytoplasmic viral and/or unspliced transcripts. Structural analysis revealed that the RNA motif was not bound by the conventional C3H1 RNA-binding domain of ZC3H12B. Instead, the RNA motif was bound by the ZC3H12B's PilT N terminus (PIN) RNase domain, revealing a potential mechanism by which unconventional RBDs containing active sites or molecule-binding pockets could interact with short, structured RNA molecules. Our collection containing 145 high-resolution binding specificity models for 86 RBPs is the largest systematic resource for the analysis of human RBPs and will greatly facilitate future analysis of the various biological roles of this important class of proteins., (© 2020 Jolma et al.; Published by Cold Spring Harbor Laboratory Press.)

Point mutations in cancer have been extensively studied but chromosomal gains and losses have been more challenging to interpret due to their unspecific nature. Here we examine high-resolution allelic imbalance (AI) landscape in 1699 colorectal cancers, 256 of which have been whole-genome sequenced (WGSed). The imbalances pinpoint 38 genes as plausible AI targets based on previous knowledge. Unbiased CRISPR-Cas9 knockout and activation screens identified in total 79 genes within AI peaks regulating cell growth. Genetic and functional data implicate loss of TP53 as a sufficient driver of AI. The WGS highlights an influence of copy number aberrations on the rate of detected somatic point mutations. Importantly, the data reveal several associations between AI target genes, suggesting a role for a network of lineage-determining transcription factors in colorectal tumorigenesis. Overall, the results unravel the contribution of AI in colorectal cancer and provide a plausible explanation why so few genes are commonly affected by point mutations in cancers.

Nuclear factor erythroid 2-related factor 2 (NRF2), DJ1 and sulfiredoxin 1 (SRXN1) are transcription factors which protect cells from the oxidative damage caused by reactive oxygen species and, on the other hand, are associated with resistance to cancer treatments. The immunohistochemical expression of NRF2, DJ1 and SRNX1 was assessed in human grade II-IV astrocytic gliomas. Their association to clinicopathologic and essential molecular factors was evaluated. The RNA expression levels and genetic alterations were analyzed from publicly available datasets. All studied molecules were commonly expressed. The cytoplasmic NRF2 expression was higher in tumors with a higher malignancy grade, whereas the nuclear and cytoplasmic DJ1 expression was associated with a lower grade. The presence of the isocitrate dehyrdogenase 1 mutation (IDH1) was associated with an increasing cytoplasmic and nuclear expression of NRF2 and a nuclear DJ1 expression. When primary grade IV astrocytomas were compared to secondary glioblastomas, nuclear DJ1 was associated with secondary tumors. In grade II-IV tumors, the cytoplasmic NRF2 expression was associated with a poor prognosis, whereas nuclear NRF2 and both cytoplasmic and nuclear DJ1 were associated with a better patient prognosis. Recurrent homozygous deletions of DJ1 were observed, especially in the IDH wild-type samples. When only the glioblastomas were evaluated, nuclear NRF2 and SRNX1 predicted better survival. As a conclusion, NRF2, DJ1 and SNXR1 can be used as prognosticators in gliomas.

No existing method to characterize transcription factor (TF) binding to DNA allows genome-wide measurement of all TF-binding activity in cells. Here we present a massively parallel protein activity assay, active TF identification (ATI), that measures the DNA-binding activity of all TFs in cell or tissue extracts. ATI is based on electrophoretic separation of protein-bound DNA sequences from a highly complex DNA library and subsequent mass-spectrometric identification of the DNA-bound proteins. We applied ATI to four mouse tissues and mouse embryonic stem cells and found that, in a given tissue or cell type, a small set of TFs, which bound to only ∼10 distinct motifs, displayed strong DNA-binding activity. Some of these TFs were found in all cell types, whereas others were specific TFs known to determine cell fate in the analyzed tissue or cell type. We also show that a small number of TFs determined the accessible chromatin landscape of a cell, suggesting that gene regulatory logic may be simpler than previously appreciated.

In some dimeric cases of transcription factor (TF) binding, the specificity of dimeric motifs has been observed to differ notably from what would be expected were the two factors to bind to DNA independently of each other. Current motif discovery methods are unable to learn monomeric and dimeric motifs in modular fashion such that deviations from the expected motif would become explicit and the noise from dimeric occurrences would not corrupt monomeric models. We propose a novel modeling technique and an expectation maximization algorithm, implemented as software tool MODER, for discovering monomeric TF binding motifs and their dimeric combinations. Given training data and seeds for monomeric motifs, the algorithm learns in the same probabilistic framework a mixture model which represents monomeric motifs as standard position-specific probability matrices (PPMs), and dimeric motifs as pairs of monomeric PPMs, with associated orientation and spacing preferences. For dimers the model represents deviations from pure modular model of two independent monomers, thus making co-operative binding effects explicit. MODER can analyze in reasonable time tens of Mbps of training data. We validated the tool on HT-SELEX and ChIP-seq data. Our findings include some TFs whose expected model has palindromic symmetry but the observed model is directional.

Loss-of-function screening by CRISPR/Cas9 gene knockout with pooled, lentiviral guide libraries is a widely applicable method for systematic identification of genes contributing to diverse cellular phenotypes. Here, Random Sequence Labels (RSLs) are incorporated into the guide library, which act as unique molecular identifiers (UMIs) to allow massively parallel lineage tracing and lineage dropout screening. RSLs greatly improve the reproducibility of results by increasing both the precision and the accuracy of screens. They reduce the number of cells needed to reach a set statistical power, or allow a more robust screen using the same number of cells., (© 2017 The Authors. Published under the terms of the CC BY 4.0 license.)

The majority of CpG dinucleotides in the human genome are methylated at cytosine bases. However, active gene regulatory elements are generally hypomethylated relative to their flanking regions, and the binding of some transcription factors (TFs) is diminished by methylation of their target sequences. By analysis of 542 human TFs with methylation-sensitive SELEX (systematic evolution of ligands by exponential enrichment), we found that there are also many TFs that prefer CpG-methylated sequences. Most of these are in the extended homeodomain family. Structural analysis showed that homeodomain specificity for methylcytosine depends on direct hydrophobic interactions with the methylcytosine 5-methyl group. This study provides a systematic examination of the effect of an epigenetic DNA modification on human TF binding specificity and reveals that many developmentally important proteins display preference for mCpG-containing sequences., (Copyright © 2017, American Association for the Advancement of Science.)

To identify cell cycle regulators that enable cancer cells to replicate DNA and divide in an unrestricted manner, we performed a parallel genome-wide RNAi screen in normal and cancer cell lines. In addition to many shared regulators, we found that tumor and normal cells are differentially sensitive to loss of the histone genes transcriptional regulator CASP8AP2. In cancer cells, loss of CASP8AP2 leads to a failure to synthesize sufficient amount of histones in the S-phase of the cell cycle, resulting in slowing of individual replication forks. Despite this, DNA replication fails to arrest, and tumor cells progress in an elongated S-phase that lasts several days, finally resulting in death of most of the affected cells. In contrast, depletion of CASP8AP2 in normal cells triggers a response that arrests viable cells in S-phase. The arrest is dependent on p53, and preceded by accumulation of markers of DNA damage, indicating that nucleosome depletion is sensed in normal cells via a DNA-damage -like response that is defective in tumor cells.

Motivation: Transcription factor (TF) binding can be studied accurately in vivo with ChIP-exo and ChIP-Nexus experiments. Only fraction of TF binding mechanisms are yet fully understood and accurate knowledge of binding locations and patterns of TFs is key to understanding binding that is not explained by simple positional weight matrix models. ChIP-exo/Nexus experiments can also offer insight on the effect of single nucleotide polymorphism (SNP) at TF binding sites on expression of the target genes. This is an important mechanism of action for disease-causing SNPs at non-coding genomic regions., Results: We describe a peak caller PeakXus that is specifically designed to leverage the increased resolution of ChIP-exo/Nexus and developed with the aim of making as few assumptions of the data as possible to allow discoveries of novel binding patterns. We apply PeakXus to ChIP-Nexus and ChIP-exo experiments performed both in Homo sapiens and in Drosophila melanogaster cell lines. We show that PeakXus consistently finds more peaks overlapping with a TF-specific recognition sequence than published methods. As an application example we demonstrate how PeakXus can be coupled with unique molecular identifiers (UMIs) to measure the effect of a SNP overlapping with a TF binding site on the in vivo binding of the TF., Availability and Implementation: Source code of PeakXus is available at https://github.com/hartonen/PeakXus, Contact: tuomo.hartonen@helsinki.fi or jussi.taipale@ki.se., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Gene expression is regulated by transcription factors (TFs), proteins that recognize short DNA sequence motifs. Such sequences are very common in the human genome, and an important determinant of the specificity of gene expression is the cooperative binding of multiple TFs to closely located motifs. However, interactions between DNA-bound TFs have not been systematically characterized. To identify TF pairs that bind cooperatively to DNA, and to characterize their spacing and orientation preferences, we have performed consecutive affinity-purification systematic evolution of ligands by exponential enrichment (CAP-SELEX) analysis of 9,400 TF-TF-DNA interactions. This analysis revealed 315 TF-TF interactions recognizing 618 heterodimeric motifs, most of which have not been previously described. The observed cooperativity occurred promiscuously between TFs from diverse structural families. Structural analysis of the TF pairs, including a novel crystal structure of MEIS1 and DLX3 bound to their identified recognition site, revealed that the interactions between the TFs were predominantly mediated by DNA. Most TF pair sites identified involved a large overlap between individual TF recognition motifs, and resulted in recognition of composite sites that were markedly different from the individual TF's motifs. Together, our results indicate that the DNA molecule commonly plays an active role in cooperative interactions that define the gene regulatory lexicon.

Cohesin is present in almost all active enhancer regions, where it is associated with transcription factors. Cohesin frequently colocalizes with CTCF (CCCTC-binding factor), affecting genomic stability, expression and epigenetic homeostasis. Cohesin subunits are mutated in cancer, but CTCF/cohesin-binding sites (CBSs) in DNA have not been examined for mutations. Here we report frequent mutations at CBSs in cancers displaying a mutational signature where mutations in A•T base pairs predominate. Integration of whole-genome sequencing data from 213 colorectal cancer (CRC) samples and chromatin immunoprecipitation sequencing (ChIP-exo) data identified frequent point mutations at CBSs. In contrast, CRCs showing an ultramutator phenotype caused by defects in the exonuclease domain of DNA polymerase ɛ (POLE) displayed significantly fewer mutations at and adjacent to CBSs. Analysis of public data showed that multiple cancer types accumulate CBS mutations. CBSs are a major mutational hotspot in the noncoding cancer genome.

Divergent morphology of species has largely been ascribed to genetic differences in the tissue-specific expression of proteins, which could be achieved by divergence in cis-regulatory elements or by altering the binding specificity of transcription factors (TFs). The relative importance of the latter has been difficult to assess, as previous systematic analyses of TF binding specificity have been performed using different methods in different species. To address this, we determined the binding specificities of 242 Drosophila TFs, and compared them to human and mouse data. This analysis revealed that TF binding specificities are highly conserved between Drosophila and mammals, and that for orthologous TFs, the similarity extends even to the level of very subtle dinucleotide binding preferences. The few human TFs with divergent specificities function in cell types not found in fruit flies, suggesting that evolution of TF specificities contributes to emergence of novel types of differentiated cells.

Somatic mutations in exon 2 of the RNA polymerase II transcriptional Mediator subunit MED12 occur at very high frequency (∼70%) in uterine leiomyomas. However, the influence of these mutations on Mediator function and the molecular basis for their tumorigenic potential remain unknown. To clarify the impact of these mutations, we used affinity-purification mass spectrometry to establish the global protein-protein interaction profiles for both wild-type and mutant MED12. We found that uterine leiomyoma-linked mutations in MED12 led to a highly specific decrease in its association with Cyclin C-CDK8/CDK19 and loss of Mediator-associated CDK activity. Mechanistically, this occurs through disruption of a MED12-Cyclin C binding interface that we also show is required for MED12-mediated stimulation of Cyclin C-dependent CDK8 kinase activity. These findings indicate that uterine leiomyoma-linked mutations in MED12 uncouple Cyclin C-CDK8/19 from core Mediator and further identify the MED12/Cyclin C interface as a prospective therapeutic target in CDK8-driven cancers., (Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.)

During cell division, transcription factors (TFs) are removed from chromatin twice, during DNA synthesis and during condensation of chromosomes. How TFs can efficiently find their sites following these stages has been unclear. Here, we have analyzed the binding pattern of expressed TFs in human colorectal cancer cells. We find that binding of TFs is highly clustered and that the clusters are enriched in binding motifs for several major TF classes. Strikingly, almost all clusters are formed around cohesin, and loss of cohesin decreases both DNA accessibility and binding of TFs to clusters. We show that cohesin remains bound in S phase, holding the nascent sister chromatids together at the TF cluster sites. Furthermore, cohesin remains bound to the cluster sites when TFs are evicted in early M phase. These results suggest that cohesin-binding functions as a cellular memory that promotes re-establishment of TF clusters after DNA replication and chromatin condensation., (Copyright © 2013 Elsevier Inc. All rights reserved.)

In this work, we map the transcriptional targets of 107 previously identified Drosophila genes whose loss caused the strongest cell-cycle phenotypes in a genome-wide RNA interference screen and mine the resulting data computationally. Besides confirming existing knowledge, the analysis revealed several regulatory systems, among which were two highly-specific and interconnected feedback circuits, one between the ribosome and the proteasome that controls overall protein homeostasis, and the other between the ribosome and Myc/Max that regulates the protein synthesis capacity of cells. We also identified a set of genes that alter the timing of mitosis without affecting gene expression, indicating that the cyclic transcriptional program that produces the components required for cell division can be partially uncoupled from the cell division process itself. These genes all have a function in a pathway that regulates the phosphorylation state of Cdk1. We provide evidence showing that this pathway is involved in regulation of cell size, indicating that a Cdk1-regulated cell size checkpoint exists in metazoans.

Fungal infection of barley and malt, particularly by the Fusarium species, is a direct cause of spontaneous overfoaming of beer, referred to as gushing. We have shown previously that small fungal proteins, hydrophobins, act as gushing-inducing factors in beer. The aim of our present study was to isolate and characterize hydrophobins from a gushing-active fungus, Fusarium graminearum (teleomorph Gibberella zeae) and related species. We generated profile hidden Markov models (profile HMMs) for the hydrophobin classes Ia, Ib and II from the multiple sequence alignments of their known members available in public domain databases. We searched the published Fusarium graminearum genome with the Markov models. The best matching sequences and the corresponding genes were isolated from F. graminearum and the related species F. culmorum and F. poae by PCR and characterized. One each of the putative F. graminearum and F. poae hydrophobin genes were expressed in the heterologous host Trichoderma reesei. The proteins corresponding to the genes were purified and identified as hydrophobins and named GzHYD5 and FpHYD5, respectively. Concentrations of 0.003 ppm of these hydrophobins were observed to induce vigorous beer gushing., (Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Counting individual RNA or DNA molecules is difficult because they are hard to copy quantitatively for detection. To overcome this limitation, we applied unique molecular identifiers (UMIs), which make each molecule in a population distinct, to genome-scale human karyotyping and mRNA sequencing in Drosophila melanogaster. Use of this method can improve accuracy of almost any next-generation sequencing method, including chromatin immunoprecipitation-sequencing, genome assembly, diagnostics and manufacturing-process control and monitoring.

Species-specific genes play an important role in defining the phenotype of an organism. However, current gene prediction methods can only efficiently find genes that share features such as sequence similarity or general sequence characteristics with previously known genes. Novel sequencing methods and tiling arrays can be used to find genes without prior information and they have demonstrated that novel genes can still be found from extensively studied model organisms. Unfortunately, these methods are expensive and thus are not easily applicable, e.g., to finding genes that are expressed only in very specific conditions. We demonstrate a method for finding novel genes with sparse arrays, applying it on the 33.9 Mb genome of the filamentous fungus Trichoderma reesei. Our computational method does not require normalisations between arrays and it takes into account the multiple-testing problem typical for analysis of microarray data. In contrast to tiling arrays, that use overlapping probes, only one 25 mer microarray oligonucleotide probe was used for every 100b. Thus, only relatively little space on a microarray slide was required to cover the intergenic regions of a genome. The analysis was done as a by-product of a conventional microarray experiment with no additional costs. We found at least 23 good candidates for novel transcripts that could code for proteins and all of which were expressed at high levels. Candidate genes were found to neighbour ire1 and cre1 and many other regulatory genes. Our simple, low-cost method can easily be applied to finding novel species-specific genes without prior knowledge of their sequence properties., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Members of the large ETS family of transcription factors (TFs) have highly similar DNA-binding domains (DBDs)-yet they have diverse functions and activities in physiology and oncogenesis. Some differences in DNA-binding preferences within this family have been described, but they have not been analysed systematically, and their contributions to targeting remain largely uncharacterized. We report here the DNA-binding profiles for all human and mouse ETS factors, which we generated using two different methods: a high-throughput microwell-based TF DNA-binding specificity assay, and protein-binding microarrays (PBMs). Both approaches reveal that the ETS-binding profiles cluster into four distinct classes, and that all ETS factors linked to cancer, ERG, ETV1, ETV4 and FLI1, fall into just one of these classes. We identify amino-acid residues that are critical for the differences in specificity between all the classes, and confirm the specificities in vivo using chromatin immunoprecipitation followed by sequencing (ChIP-seq) for a member of each class. The results indicate that even relatively small differences in in vitro binding specificity of a TF contribute to site selectivity in vivo.

The circadian clock regulates daily variations in physiologic processes. CLOCK acts as a regulator in the circadian apparatus controlling the expression of other clock genes, including PER1. Clock genes have been implicated in cancer-related functions; in this work, we investigated CLOCK as a possible target of somatic mutations in microsatellite unstable colorectal cancers. Combining microarray gene expression data and public gene sequence information, we identified CLOCK as 1 of 790 putative novel microsatellite instability (MSI) target genes. A total of 101 MSI colorectal carcinomas (CRC) were sequenced for a coding microsatellite in CLOCK. The effect of restoring CLOCK expression was studied in LS180 cells lacking wild-type CLOCK by stably expressing GST-CLOCK or glutathione S-transferase empty vector and testing the effects of UV-induced apoptosis and radiation by DNA content analysis using flow cytometry. Putative novel CLOCK target genes were searched by using ChIP-seq. CLOCK mutations occurred in 53% of MSI CRCs. Restoring CLOCK expression in cells with biallelic CLOCK inactivation resulted in protection against UV-induced apoptosis and decreased G(2)-M arrest in response to ionizing radiation. Using ChIP-Seq, novel CLOCK-binding elements were identified near DNA damage genes p21, NBR1, BRCA1, and RAD50. CLOCK is shown to be mutated in cancer, and altered response to DNA damage provides one plausible mechanism of tumorigenesis.

The genetic code-the binding specificity of all transfer-RNAs--defines how protein primary structure is determined by DNA sequence. DNA also dictates when and where proteins are expressed, and this information is encoded in a pattern of specific sequence motifs that are recognized by transcription factors. However, the DNA-binding specificity is only known for a small fraction of the approximately 1400 human transcription factors (TFs). We describe here a high-throughput method for analyzing transcription factor binding specificity that is based on systematic evolution of ligands by exponential enrichment (SELEX) and massively parallel sequencing. The method is optimized for analysis of large numbers of TFs in parallel through the use of affinity-tagged proteins, barcoded selection oligonucleotides, and multiplexed sequencing. Data are analyzed by a new bioinformatic platform that uses the hundreds of thousands of sequencing reads obtained to control the quality of the experiments and to generate binding motifs for the TFs. The described technology allows higher throughput and identification of much longer binding profiles than current microarray-based methods. In addition, as our method is based on proteins expressed in mammalian cells, it can also be used to characterize DNA-binding preferences of full-length proteins or proteins requiring post-translational modifications. We validate the method by determining binding specificities of 14 different classes of TFs and by confirming the specificities for NFATC1 and RFX3 using ChIP-seq. Our results reveal unexpected dimeric modes of binding for several factors that were thought to preferentially bind DNA as monomers.

Homozygosity for the G allele of rs6983267 at 8q24 increases colorectal cancer (CRC) risk approximately 1.5 fold. We report here that the risk allele G shows copy number increase during CRC development. Our computer algorithm, Enhancer Element Locator (EEL), identified an enhancer element that contains rs6983267. The element drove expression of a reporter gene in a pattern that is consistent with regulation by the key CRC pathway Wnt. rs6983267 affects a binding site for the Wnt-regulated transcription factor TCF4, with the risk allele G showing stronger binding in vitro and in vivo. Genome-wide ChIP assay revealed the element as the strongest TCF4 binding site within 1 Mb of MYC. An unambiguous correlation between rs6983267 genotype and MYC expression was not detected, and additional work is required to scrutinize all possible targets of the enhancer. Our work provides evidence that the common CRC predisposition associated with 8q24 arises from enhanced responsiveness to Wnt signaling.

To allow genome-scale identification of genes that regulate cellular signaling, we cloned >90% of all human full-length protein kinase cDNAs and constructed the corresponding kinase activity-deficient mutants. To establish the utility of this resource, we tested the effect of expression of the kinases on three different cellular signaling models. In all screens, many kinases had a modest but significant effect, apparently due to crosstalk between signaling pathways. However, the strongest effects were found with known regulators and novel components, such as MAP3K10 and DYRK2, which we identified in a mammalian Hedgehog (Hh) signaling screen. DYRK2 directly phosphorylated and induced the proteasome-dependent degradation of the key Hh pathway-regulated transcription factor, GLI2. MAP3K10, in turn, affected GLI2 indirectly by modulating the activity of DYRK2 and the known Hh pathway component, GSK3beta. Our results establish kinome expression screening as a highly effective way to identify physiological signaling pathway components and genes involved in pathological signaling crosstalk.

Gene and protein expression is controlled so that cells can react to changing intra- and extracellular signals by modulating biochemical networks and pathways. We have previously shown that gene expression and the properties of expressed proteins are dynamically correlated. Here we investigated correlations between gene related parameters and gene expression patterns, and found statistically significant correlations in microarray datasets for different cell types, organisms and processes, including human B and T cell stimulation, cell cycle in HeLa cells, infection in intestinal epithelial cells, Drosophila melanogaster life span, and Saccharomyces cerevisiae cell cycle. Our method was applied to time course datasets individually for each time point. We derived from sequence information numerous parameters for nucleotide composition, two-base composition, codon usage, skew parameters, and codon bias. In addition to coding regions, we also investigated correlations for complete genes and introns. Significant dynamic correlations were identified for each of the analyses. Our method also proved useful for detecting dynamic shifts in gene expression profiles, such as in the D. melanogaster dataset. Detection of changes in the properties of expressed genes and proteins might be useful for predicting or following biological processes, responses, growth, differentiation and possibly in related disorders.

The heterogeneity of common variable immunodeficiency (CVID) calls for a classification addressing pathogenic mechanisms as well as clinical relevance. This European multicenter trial was initiated to develop a consensus of 2 existing classification schemes based on flowcytometric B-cell phenotyping and the clinical course. The clinical evaluation of 303 patients with the established diagnosis of CVID demonstrated a significant coincidence of granulomatous disease, autoimmune cytopenia, and splenomegaly. Phenotyping of B-cell subpopulations confirmed a severe reduction of switched memory B cells in most of the patients that was associated with a higher risk for splenomegaly and granulomatous disease. An expansion of CD21(low) B cells marked patients with splenomegaly. Lymphadenopathy was significantly linked with transitional B-cell expansion. Based on these findings and pathogenic consideration of B-cell differentiation, we suggest an improved classification for CVID (EUROclass), separating patients with nearly absent B cells (less than 1%), severely reduced switched memory B cells (less than 2%), and expansion of transitional (more than 9%) or CD21(low) B cells (more than 10%). Whereas the first group contains all patients with severe defects of early B-cell differentiation, severely reduced switched memory B cells indicate a defective germinal center development as found in inducible constimulator (ICOS) or CD40L deficiency. The underlying defects of expanded transitional or CD21(low) B cells remain to be elucidated. This trial is re-gistered at http://www.uniklinik-freiburg.de/zks/live/uklregister/Oeffentlich.html as UKF000308.

Background: Several dozen fungi encompassing traditional model organisms, industrial production organisms and human and plant pathogens have been sequenced recently and their particular genomic features analysed in detail. In addition comparative genomics has been used to analyse specific sub groups of fungi. Notably, analysis of the phylum Saccharomycotina has revealed major events of evolution such as the recent genome duplication and subsequent gene loss. However, little has been done to gain a comprehensive comparative view to the fungal kingdom. We have carried out a computational genome wide comparison of protein coding gene content of Saccharomycotina and Pezizomycotina, which include industrially important yeasts and filamentous fungi, respectively., Results: Our analysis shows that based on genome redundancy, the traditional model organisms Saccharomyces cerevisiae and Neurospora crassa are exceptional among fungi. This can be explained by the recent genome duplication in S. cerevisiae and the repeat induced point mutation mechanism in N. crassa. Interestingly in Pezizomycotina a subset of protein families related to plant biomass degradation and secondary metabolism are the only ones showing signs of recent expansion. In addition, Pezizomycotina have a wealth of phylum specific poorly characterised genes with a wide variety of predicted functions. These genes are well conserved in Pezizomycotina, but show no signs of recent expansion. The genes found in all fungi except Saccharomycotina are slightly better characterised and predicted to encode mainly enzymes. The genes specific to Saccharomycotina are enriched in transcription and mitochondrion related functions. Especially mitochondrial ribosomal proteins seem to have diverged from those of Pezizomycotina. In addition, we highlight several individual gene families with interesting phylogenetic distributions., Conclusion: Our analysis predicts that all Pezizomycotina unlike Saccharomycotina can potentially produce a wide variety of secondary metabolites and secreted enzymes and that the responsible gene families are likely to evolve fast. Both types of fungal products can be of commercial value, or on the other hand cause harm to humans. In addition, a great number of novel predicted and known enzymes are found from all fungi except Saccharomycotina. Therefore further studies and exploitation of fungal metabolism appears very promising.

Background: Biologically relevant molecular markers can be used in evaluation of the physiological state of an organism in biotechnical processes. We monitored at high frequency the expression of 34 marker genes in batch, fed-batch and continuous cultures of the filamentous fungus Trichoderma reesei by the transcriptional analysis method TRAC (TRanscript analysis with the aid of Affinity Capture). Expression of specific genes was normalised either with respect to biomass or to overall polyA RNA concentration. Expressional variation of the genes involved in various process relevant cellular functions, such as protein production, growth and stress responses, was related to process parameters such as specific growth and production rates and substrate and dissolved oxygen concentrations., Results: Gene expression of secreted cellulases and recombinant Melanocarpus albomyces laccase predicted the trends in the corresponding extracellular enzyme production rates and was highest in a narrow "physiological window" in the specific growth rate (micro) range of 0.03-0.05 h-1. Expression of ribosomal protein mRNAs was consistent with the changes in mu. Nine starvation-related genes were found as potential markers for detection of insufficient substrate feed for maintaining optimal protein production. For two genes induced in anaerobic conditions, increasing transcript levels were measured as dissolved oxygen decreased., Conclusion: The data obtained by TRAC supported the usefulness of focused and intensive transcriptional analysis in monitoring of biotechnical processes providing thus tools for process optimisation purposes.

A method is presented that reliably detects spherical viruses from a wide variety of noisy low-contrast electron micrographs. Such detection is one of the first image analysis steps in the computer-aided reconstruction of three-dimensional density distribution models of viruses. Particle detection is based on the comparison of intensity in a circular area and in the surrounding ring followed by a number of tests to validate the potential particles. The only required input from the user in addition to the micrograph is an approximate radius of the particle. The method has been implemented as program ETHAN that has been tested for several different data sets. ETHAN has also successfully been used to detect DNA-less virus particles for an actual reconstruction., (Copyright 2000 Academic Press.)