Search

Cleavage and polyadenylation (CPA) sites define eukaryotic gene ends. CPA sites are associated with five key sequence recognition elements: the upstream UGUA, the polyadenylation signal (PAS), and U-rich sequences; the CA / UA dinucleotide where cleavage occurs; and GU-rich downstream elements (DSEs). Currently, it is not clear whether these sequences are sufficient to delineate CPA sites. Additionally, numerous other sequences and factors have been described, often in the context of promoting alternative CPA sites and preventing cryptic CPA site usage. Here, we dissect the contributions of individual sequence features to CPA using standard discriminative models. We show that models comprised only of the five primary CPA sequence features give highest probability scores to constitutive CPA sites at the ends of coding genes, relative to the entire pre-mRNA sequence, for 59% of all human genes. U1-hybridizing sequences provide a small boost in performance. The addition of all known RBP RNA binding motifs to the model increases this figure to only 61%, suggesting that additional factors beyond the core CPA machinery have a minimal role in delineating real from cryptic sites. To our knowledge, this high effectiveness of established features to predict human gene ends has not previously been documented., (© The Author(s) 2023. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Modelling both primary sequence and secondary structure preferences for RNA binding proteins (RBPs) remains an ongoing challenge. Current models use varied RNA structure representations and can be difficult to interpret and evaluate. To address these issues, we present a universal RNA motif-finding/scanning strategy, termed PRIESSTESS (Predictive RBP-RNA InterpretablE Sequence-Structure moTif regrESSion), that can be applied to diverse RNA binding datasets. PRIESSTESS identifies dozens of enriched RNA sequence and/or structure motifs that are subsequently reduced to a set of core motifs by logistic regression with LASSO regularization. Importantly, these core motifs are easily visualized and interpreted, and provide a measure of RBP secondary structure specificity. We used PRIESSTESS to interrogate new HTR-SELEX data for 23 RBPs with diverse RNA binding modes and captured known primary sequence and secondary structure preferences for each. Moreover, when applying PRIESSTESS to 144 RBPs across 202 RNA binding datasets, 75% showed an RNA secondary structure preference but only 10% had a preference besides unpaired bases, suggesting that most RBPs simply recognize the accessibility of primary sequences., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Sequences derived from the Long INterspersed Element-1 (L1) family of retrotransposons occupy at least 17% of the human genome, with 67 distinct subfamilies representing successive waves of expansion and extinction in mammalian lineages. L1s contribute extensively to gene regulation, but their molecular history is difficult to trace, because most are present only as truncated and highly mutated fossils. Consequently, L1 entries in current databases of repeat sequences are composed mainly of short diagnostic subsequences, rather than full functional progenitor sequences for each subfamily. Here, we have coupled 2 levels of sequence reconstruction (at the level of whole genomes and L1 subfamilies) to reconstruct progenitor sequences for all human L1 subfamilies that are more functionally and phylogenetically plausible than existing models. Most of the reconstructed sequences are at or near the canonical length of L1s and encode uninterrupted ORFs with expected protein domains. We also show that the presence or absence of binding sites for KRAB-C2H2 Zinc Finger Proteins, even in ancient-reconstructed progenitor L1s, mirrors binding observed in human ChIP-exo experiments, thus extending the arms race and domestication model. RepeatMasker searches of the modern human genome suggest that the new models may be able to assign subfamily resolution identities to previously ambiguous L1 instances. The reconstructed L1 sequences will be useful for genome annotation and functional study of both L1 evolution and L1 contributions to host regulatory networks., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America.)

Cleavage and polyadenylation (CPA) sites define eukaryotic gene ends. CPA sites are associated with five key sequence recognition elements: the upstream UGUA, the polyadenylation signal (PAS), and U-rich sequences; the CA/UA dinucleotide where cleavage occurs; and GU-rich downstream elements (DSEs). Currently, it is not clear whether these sequences are sufficient to delineate CPA sites. Additionally, numerous other sequences and factors have been described, often in the context of promoting alternative CPA sites and preventing cryptic CPA site usage. Here, we dissect the contributions of individual sequence features to CPA using standard discriminative models. We show that models comprised only of the five primary CPA sequence features give highest probability scores to constitutive CPA sites at the ends of coding genes, relative to the entire pre-mRNA sequence, for 41% of all human genes. U1-hybridizing sequences provide a small boost in performance. The addition of all known RBP RNA binding motifs to the model, however, increases this figure to 49%, and suggests an involvement of both known and suspected CPA regulators as well as potential new factors in delineating constitutive CPA sites. To our knowledge, this high effectiveness of established features to predict human gene ends has not previously been documented., (© The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

The human transcription factor (TF) CGGBP1 (CGG-binding protein) is conserved only in amniotes and is believed to derive from the zf-BED and Hermes transposase DNA-binding domains (DBDs) of a hAT DNA transposon. Here, we show that sequence-specific DNA-binding proteins with this bipartite domain structure have resulted from dozens of independent hAT domestications in different eukaryotic lineages. CGGBPs display a wide range of sequence specificity, usually including preferences for CGG or CGC trinucleotides, whereas some bind AT-rich motifs. The CGGBPs are almost entirely nonsyntenic, and their protein sequences, DNA-binding motifs, and patterns of presence or absence in genomes are uncharacteristic of ancestry via speciation. At least eight CGGBPs in the coelacanth Latimeria chalumnae bind distinct motifs, and the expression of the corresponding genes varies considerably across tissues, suggesting tissue-restricted function., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Stress hormones bind and activate the glucocorticoid receptor (GR) in many tissues including the brain. We identified arginine and glutamate rich 1 (ARGLU1) in a screen for new modulators of glucocorticoid signaling in the CNS. Biochemical studies show that the glutamate rich C-terminus of ARGLU1 coactivates multiple nuclear receptors including the glucocorticoid receptor (GR) and the arginine rich N-terminus interacts with splicing factors and binds to RNA. RNA-seq of neural cells depleted of ARGLU1 revealed significant changes in the expression and alternative splicing of distinct genes involved in neurogenesis. Loss of ARGLU1 is embryonic lethal in mice, and knockdown in zebrafish causes neurodevelopmental and heart defects. Treatment with dexamethasone, a GR activator, also induces changes in the pattern of alternatively spliced genes, many of which were lost when ARGLU1 was absent. Importantly, the genes found to be alternatively spliced in response to glucocorticoid treatment were distinct from those under transcriptional control by GR, suggesting an additional mechanism of glucocorticoid action is present in neural cells. Our results thus show that ARGLU1 is a novel factor for embryonic development that modulates basal transcription and alternative splicing in neural cells with consequences for glucocorticoid signaling., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Bacterial xenogeneic silencers play important roles in bacterial evolution by recognizing and inhibiting expression from foreign genes acquired through horizontal gene transfer, thereby buffering against potential fitness consequences of their misregulated expression. Here, the detailed DNA binding properties of Rok, a xenogeneic silencer in Bacillus subtilis, was studied using protein binding microarray, and the solution structure of its C-terminal DNA binding domain was determined in complex with DNA. The C-terminal domain of Rok adopts a typical winged helix fold, with a novel DNA recognition mechanism different from other winged helix proteins or xenogeneic silencers. Rok binds the DNA minor groove by forming hydrogen bonds to bases through N154, T156 at the N-terminal of α3 helix and R174 of wing W1, assisted by four lysine residues interacting electrostatically with DNA backbone phosphate groups. These structural features endow Rok with preference towards DNA sequences harboring AACTA, TACTA, and flexible multiple TpA steps, while rigid A-tracts are disfavored. Correspondingly, the Bacillus genomes containing Rok are rich in A-tracts and show a dramatic underrepresentation of AACTA and TACTA, which are significantly enriched in Rok binding regions. These observations suggest that the xenogeneic silencing protein and its resident genome may have evolved cooperatively.

KRAB C2H2 zinc finger proteins (KZNFs) are the largest and most diverse family of human transcription factors, likely due to diversifying selection driven by novel endogenous retroelements (EREs), but the vast majority lack binding motifs or functional data. Two recent studies analyzed a majority of the human KZNFs using either ChIP-seq (60 proteins) or ChIP-exo (221 proteins) in the same cell type (HEK293). The ChIP-exo paper did not describe binding motifs, however. Thirty-nine proteins are represented in both studies, enabling the systematic comparison of the data sets presented here. Typically, only a minority of peaks overlap, but the two studies nonetheless display significant similarity in ERE binding for 32/39, and yield highly similar DNA binding motifs for 23 and related motifs for 34 (MoSBAT similarity score >0.5 and >0.2, respectively). Thus, there is overall (albeit imperfect) agreement between the two studies. For the 242 proteins represented in at least one study, we selected a highest-confidence motif for each protein, utilizing several motif-derivation approaches, and evaluating motifs within and across data sets. Peaks for the majority (158) are enriched (96% with AUC >0.6 predicting peak vs. nonpeak) for a motif that is supported by the C2H2 "recognition code," consistent with intrinsic sequence specificity driving DNA binding in cells. An additional 63 yield motifs enriched in peaks, but not supported by the recognition code, which could reflect indirect binding. Altogether, these analyses validate both data sets, and provide a reference motif set with associated quality metrics., (Copyright © 2018 Barazandeh et al.)

Measuring motif similarity is essential for identifying functionally related transcription factors (TFs) and RNA-binding proteins, and for annotating de novo motifs. Here, we describe Motif Similarity Based on Affinity of Targets (MoSBAT), an approach for measuring the similarity of motifs by computing their affinity profiles across a large number of random sequences. We show that MoSBAT successfully associates de novo ChIP-seq motifs with their respective TFs, accurately identifies motifs that are obtained from the same TF in different in vitro assays, and quantitatively reflects the similarity of in vitro binding preferences for pairs of TFs., Availability and Implementation: MoSBAT is available as a webserver at mosbat.ccbr.utoronto.ca, and for download at github.com/csglab/MoSBAT., Contact: t.hughes@utoronto.ca or hamed.najafabadi@mcgill.caSupplementary information: Supplementary data are available at Bioinformatics online., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Development of an accurate protein-DNA recognition code that can predict DNA specificity from protein sequence is a central problem in biology. C2H2 zinc fingers constitute by far the largest family of DNA binding domains and their binding specificity has been studied intensively. However, despite decades of research, accurate prediction of DNA specificity remains elusive. A major obstacle is thought to be the inability of current methods to account for the influence of neighbouring domains. Here we show that this problem can be addressed using a structural approach: we build structural models for all C2H2-ZF-DNA complexes with known binding motifs and find six distinct binding modes. Each mode changes the orientation of specificity residues with respect to the DNA, thereby modulating base preference. Most importantly, the structural analysis shows that residues at the domain interface strongly and predictably influence the binding mode, and hence specificity. Accounting for predicted binding mode significantly improves prediction accuracy of predicted motifs. This new insight into the fundamental behaviour of C2H2-ZFs has implications for both improving the prediction of natural zinc finger-binding sites, and for prioritizing further experiments to complete the code. It also provides a new design feature for zinc finger engineering., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Unlabelled: Current methods for motif discovery from chromatin immunoprecipitation followed by sequencing (ChIP-seq) data often identify non-targeted transcription factor (TF) motifs, and are even further limited when peak sequences are similar due to common ancestry rather than common binding factors. The latter aspect particularly affects a large number of proteins from the Cys2His2 zinc finger (C2H2-ZF) class of TFs, as their binding sites are often dominated by endogenous retroelements that have highly similar sequences. Here, we present recognition code-assisted discovery of regulatory elements (RCADE) for motif discovery from C2H2-ZF ChIP-seq data. RCADE combines predictions from a DNA recognition code of C2H2-ZFs with ChIP-seq data to identify models that represent the genuine DNA binding preferences of C2H2-ZF proteins. We show that RCADE is able to identify generalizable binding models even from peaks that are exclusively located within the repeat regions of the genome, where state-of-the-art motif finding approaches largely fail., Availability and Implementation: RCADE is available as a webserver and also for download at http://rcade.ccbr.utoronto.ca/., Supplementary Information: Supplementary data are available at Bioinformatics online., Contact: t.hughes@utoronto.ca., (© The Author 2015. Published by Oxford University Press.)

Chronic relapsing experimental autoimmune encephalomyelitis (crEAE) in mice recapitulates many of the clinical and histopathological features of human multiple sclerosis (MS), making it a preferred model for the disease. In both, adaptive immunity and anti-myelin T cells responses are thought to be important, while in MS a role for innate immunity and complement has emerged. Here we sought to test whether complement is activated in crEAE and important for disease. Disease was induced in Biozzi ABH mice that were terminated at different stages of the disease to assess complement activation and local complement expression in the central nervous system. Complement activation products were abundant in all spinal cord areas examined in acute disease during relapse and in the progressive phase, but were absent in early disease remission, despite significant residual clinical disease. Local expression of C1q and C3 was increased at all stages of disease, while C9 expression was increased only in acute disease; expression of the complement regulators CD55, complement receptor 1-related gene/protein y (Crry) and CD59a was reduced at all stages of the disease compared to naive controls. These data show that complement is activated in the central nervous system in the model and suggest that it is a suitable candidate for exploring whether anti-complement agents might be of benefit in MS., (© 2015 British Society for Immunology.)

RNA-binding proteins (RBPs) are important regulators of eukaryotic gene expression. Genomes typically encode dozens to hundreds of proteins containing RNA-binding domains, which collectively recognize diverse RNA sequences and structures. Recent advances in high-throughput methods for assaying the targets of RBPs in vitro and in vivo allow large-scale derivation of RNA-binding motifs as well as determination of RNA-protein interactions in living cells. In parallel, many computational methods have been developed to analyze and interpret these data. The interplay between RNA secondary structure and RBP binding has also been a growing theme. Integrating RNA-protein interaction data with observations of post-transcriptional regulation will enhance our understanding of the roles of these important proteins., (© The Author 2014. Published by Oxford University Press.)

The term "transcriptional network" refers to the mechanism(s) that underlies coordinated expression of genes, typically involving transcription factors (TFs) binding to the promoters of multiple genes, and individual genes controlled by multiple TFs. A multitude of studies in the last two decades have aimed to map and characterize transcriptional networks in the yeast Saccharomyces cerevisiae. We review the methodologies and accomplishments of these studies, as well as challenges we now face. For most yeast TFs, data have been collected on their sequence preferences, in vivo promoter occupancy, and gene expression profiles in deletion mutants. These systematic studies have led to the identification of new regulators of numerous cellular functions and shed light on the overall organization of yeast gene regulation. However, many yeast TFs appear to be inactive under standard laboratory growth conditions, and many of the available data were collected using techniques that have since been improved. Perhaps as a consequence, comprehensive and accurate mapping among TF sequence preferences, promoter binding, and gene expression remains an open challenge. We propose that the time is ripe for renewed systematic efforts toward a complete mapping of yeast transcriptional regulatory mechanisms.

The yeast Saccharomyces cerevisiae is a prevalent system for the analysis of transcriptional networks. As a result, multiple DNA-binding sequence specificities (motifs) have been derived for most yeast transcription factors (TFs). However, motifs from different studies are often inconsistent with each other, making subsequent analyses complicated and confusing. Here, we have created YeTFaSCo (The Yeast Transcription Factor Specificity Compendium, http://yetfasco.ccbr.utoronto.ca/), an extensive collection of S. cerevisiae TF specificities. YeTFaSCo differs from related databases by being more comprehensive (including 1709 motifs for 256 proteins or protein complexes), and by evaluating the motifs using multiple objective quality metrics. The metrics include correlation between motif matches and ChIP-chip data, gene expression patterns, and GO terms, as well as motif agreement between different studies. YeTFaSCo also features an index of 'expert-curated' motifs, each associated with a confidence assessment. In addition, the database website features tools for motif analysis, including a sequence scanning function and precomputed genome-browser tracks of motif occurrences across the entire yeast genome. Users can also search the database for motifs that are similar to a query motif.

C2H2 zinc fingers (C2H2-ZFs) are the most prevalent type of vertebrate DNA-binding domain, and typically appear in tandem arrays (ZFAs), with sequential C2H2-ZFs each contacting three (or more) sequential bases. C2H2-ZFs can be assembled in a modular fashion, providing one explanation for their remarkable evolutionary success. Given a set of modules with defined three-base specificities, modular assembly also presents a way to construct artificial proteins with specific DNA-binding preferences. However, a recent survey of a large number of three-finger ZFAs engineered by modular assembly reported high failure rates (∼70%), casting doubt on the generality of modular assembly. Here, we used protein-binding microarrays to analyze 28 ZFAs that failed in the aforementioned study. Most (17) preferred specific sequences, which in all but one case resembled the intended target sequence. Like natural ZFAs, the engineered ZFAs typically yielded degenerate motifs, binding dozens to hundreds of related individual sequences. Thus, the failure of these proteins in previous assays is not due to lack of sequence-specific DNA-binding activity. Our findings underscore the relevance of individual C2H2-ZF sequence specificities within tandem arrays, and support the general ability of modular assembly to produce ZFAs with sequence-specific DNA-binding activity.

Tiling microarrays have proven to be a valuable tool for gaining insights into the transcriptomes of microbial organisms grown under various nutritional or stress conditions. Here, we describe the use of such an array, constructed at the level of 20 nt resolution for the Escherichia coli MG1655 genome, to observe genome-wide changes in the steady-state RNA levels in mutants defective in either RNase E or RNase III. The array data were validated by comparison to previously published results for a variety of specific transcripts as well as independent northern analysis of additional mRNAs and sRNAs. In the absence of RNase E, 60% of the annotated coding sequences showed either increases or decreases in their steady-state levels. In contrast, only 12% of the coding sequences were affected in the absence of RNase III. Unexpectedly, many coding sequences showed decreased abundance in the RNase E mutant, while more than half of the annotated sRNAs showed changes in abundance. Furthermore, the steady-state levels of many transcripts showed overlapping effects of both ribonucleases. Data are also presented demonstrating how the arrays were used to identify potential new genes, RNase III cleavage sites and the direct or indirect control of specific biological pathways.

The RNA-Binding Protein DataBase (RBPDB) is a collection of experimental observations of RNA-binding sites, both in vitro and in vivo, manually curated from primary literature. To build RBPDB, we performed a literature search for experimental binding data for all RNA-binding proteins (RBPs) with known RNA-binding domains in four metazoan species (human, mouse, fly and worm). In total, RPBDB contains binding data on 272 RBPs, including 71 that have motifs in position weight matrix format, and 36 sets of sequences of in vivo-bound transcripts from immunoprecipitation experiments. The database is accessible by a web interface which allows browsing by domain or by organism, searching and export of records, and bulk data downloads. Users can also use RBPDB to scan sequences for RBP-binding sites. RBPDB is freely available, without registration at http://rbpdb.ccbr.utoronto.ca/.

Classifying proteins into subgroups with similar molecular function on the basis of sequence is an important step in deriving reliable functional annotations computationally. So far, however, available classification procedures have been evaluated against protein subgroups that are defined by experts using mainly qualitative descriptions of molecular function. Recently, in vitro DNA-binding preferences to all possible 8-nt DNA sequences have been measured for 178 mouse homeodomains using protein-binding microarrays, offering the unprecedented opportunity of evaluating the classification methods against quantitative measures of molecular function. To this end, we automatically derive homeodomain subtypes from the DNA-binding data and independently group the same domains using sequence information alone. We test five sequence-based methods, which use different sequence-similarity measures and algorithms to group sequences. Results show that methods that optimize the classification robustness reflect well the detailed functional specificity revealed by the experimental data. In some of these classifications, 73-83% of the subfamilies exactly correspond to, or are completely contained in, the function-based subtypes. Our findings demonstrate that certain sequence-based classifications are capable of yielding very specific molecular function annotations. The availability of quantitative descriptions of molecular function, such as DNA-binding data, will be a key factor in exploiting this potential in the future.

Summary: Computational gene function prediction can serve to focus experimental resources on high-priority experimental tasks. FuncBase is a web resource for viewing quantitative machine learning-based gene function annotations. Quantitative annotations of genes, including fungal and mammalian genes, with Gene Ontology terms are accompanied by a community feedback system. Evidence underlying function annotations is shown. For example, a custom Cytoscape viewer shows functional linkage graphs relevant to the gene or function of interest. FuncBase provides links to external resources, and may be accessed directly or via links from species-specific databases., Availability: FuncBase as well as all underlying data and annotations are freely available via http://func.med.harvard.edu/

Activation of complement occurs during autoimmune retinal and intraocular inflammatory disease as well as neuroretinal degenerative disorders. The cleavage of C5 into fragments C5a and C5b is a critical event during the complement cascade. C5a is a potent proinflammatory anaphylatoxin capable of inducing cell migration, adhesion and cytokine release, while membrane attack complex C5b-9 causes cell lysis. Therapeutic approaches to prevent complement-induced inflammation include the use of blocking monoclonal antibodies (mAb) to prevent C5 cleavage. In these current experiments, the rat anti-mouse C5 mAb (BB5.1) was utilized to investigate the effects of inhibition of C5 cleavage on disease progression and severity in experimental autoimmune uveoretinitis (EAU), a model of organ-specific autoimmunity in the eye characterized by structural retinal damage mediated by infiltrating macrophages. Systemic treatment with BB5.1 results in significantly reduced disease scores compared with control groups, while local administration results in an earlier resolution of disease. In vitro, contemporaneous C5a and interferon-gamma signalling enhanced nitric oxide production, accompanied by down-regulation of the inhibitory myeloid CD200 receptor, contributing to cell activation. These experiments demonstrate that C5 cleavage contributes to the full expression of EAU, and that selective C5 blockade via systemic and local routes of administration can suppress disease. This presents great therapeutic potential to protect against tissue damage during autoimmune responses in the retina or inflammation-induced degenerative disease.

The last decade has seen an explosion of interest in new classes of non-coding RNA. While some are now firmly established as new categories of legitimate functional RNAs, the purpose and even existence of others remain to be solidified. Here, we discuss the challenges associated with discovery and characterization of non-traditional categories of non-coding RNA.

Motivation: Recognition of specific DNA sequences is a central mechanism by which transcription factors (TFs) control gene expression. Many TF-binding preferences, however, are unknown or poorly characterized, in part due to the difficulty associated with determining their specificity experimentally, and an incomplete understanding of the mechanisms governing sequence specificity. New techniques that estimate the affinity of TFs to all possible k-mers provide a new opportunity to study DNA-protein interaction mechanisms, and may facilitate inference of binding preferences for members of a given TF family when such information is available for other family members., Results: We employed a new dataset consisting of the relative preferences of mouse homeodomains for all eight-base DNA sequences in order to ask how well we can predict the binding profiles of homeodomains when only their protein sequences are given. We evaluated a panel of standard statistical inference techniques, as well as variations of the protein features considered. Nearest neighbour among functionally important residues emerged among the most effective methods. Our results underscore the complexity of TF-DNA recognition, and suggest a rational approach for future analyses of TF families.

Motivation: The sequence specificity of DNA-binding proteins is typically represented as a position weight matrix in which each base position contributes independently to relative affinity. Assessment of the accuracy and broad applicability of this representation has been limited by the lack of extensive DNA-binding data. However, new microarray techniques, in which preferences for all possible K-mers are measured, enable a broad comparison of both motif representation and methods for motif discovery. Here, we consider the problem of accounting for all of the binding data in such experiments, rather than the highest affinity binding data. We introduce the RankMotif++, an algorithm designed for finding motifs whenever sequences are associated with a semi-quantitative measure of protein-DNA-binding affinity. RankMotif++ learns motif models by maximizing the likelihood of a set of binding preferences under a probabilistic model of how sequence binding affinity translates into binding preference observations. Because RankMotif++ makes few assumptions about the relationship between binding affinity and the semi-quantitative readout, it is applicable to a wide variety of experimental assays of DNA-binding preference., Results: By several criteria, RankMotif++ predicts binding affinity better than two widely used motif finding algorithms (MDScan, MatrixREDUCE) or more recently developed algorithms (PREGO, Seed and Wobble), and its performance is comparable to a motif model that separately assigns affinities to 8-mers. Our results validate the PWM model and provide an approximation of the precision and recall that can be expected in a genomic scan., Availability: RankMotif++ is available upon request., Supplementary Information: Supplementary data are available at Bioinformatics online.

The yeast genetics community has embraced genomic biology, and there is a general understanding that obtaining a full encyclopedia of functions of the approximately 6000 genes is a worthwhile goal. The yeast literature comprises over 40,000 research papers, and the number of yeast researchers exceeds the number of genes. There are mutated and tagged alleles for virtually every gene, and hundreds of high-throughput data sets and computational analyses have been described. Why, then, are there >1000 genes still listed as uncharacterized on the Saccharomyces Genome Database, 10 years after sequencing the genome of this powerful model organism? Examination of the currently uncharacterized gene set suggests that while some are small or newly discovered, the vast majority were evident from the initial genome sequence. Most are present in multiple genomics data sets, which may provide clues to function. In addition, roughly half contain recognizable protein domains, and many of these suggest specific metabolic activities. Notably, the uncharacterized gene set is highly enriched for genes whose only homologs are in other fungi. Achieving a full catalog of yeast gene functions may require a greater focus on the life of yeast outside the laboratory.

Understanding transcriptional regulation in early developmental stages is fundamental to understanding mammalian development and embryonic stem (ES) cell properties. Expression surveys suggest that the putative SCAN-Zinc finger transcription factor Zfp206 is expressed specifically in ES cells [Zhang,W., Morris,Q.D., Chang,R., Shai,O., Bakowski,M.A., Mitsakakis,N., Mohammad,N., Robinson,M.D., Zirngibl,R., Somogyi,E. et al., (2004) J. Biol., 3, 21; Brandenberger,R., Wei,H., Zhang,S., Lei,S., Murage,J., Fisk,G.J., Li,Y., Xu,C., Fang,R., Guegler,K. et al., (2004) Nat. Biotechnol., 22, 707-716]. Here, we confirm this observation, and we show that ZFP206 expression decreases rapidly upon differentiation of cultured mouse ES cells, and during development of mouse embryos. We find that there are at least six isoforms of the ZFP206 transcript, the longest being predominant. Overexpression and depletion experiments show that Zfp206 promotes formation of undifferentiated ES cell clones, and positively regulates abundance of a very small set of transcripts whose expression is also specific to ES cells and the two- to four-cell stages of preimplantation embryos. This set includes members of the Zscan4, Thoc4, Tcstv1 and eIF-1A gene families, none of which have been functionally characterized in vivo but whose members include apparent transcription factors, RNA-binding proteins and translation factors. Together, these data indicate that Zfp206 is a regulator of ES cell differentiation that controls a set of genes expressed very early in development, most of which themselves appear to be regulators.

Motivation: Microarray designs containing millions to hundreds of millions of probes that tile entire genomes are currently being released. Within the next 2 months, our group will release a microarray data set containing over 12,000,000 microarray measurements taken from 37 mouse tissues. A problem that will become increasingly significant in the upcoming era of genome-wide exon-tiling microarray experiments is the removal of cross-hybridization noise. We present a probabilistic generative model for cross-hybridization in microarray data and a corresponding variational learning method for cross-hybridization compensation, GenXHC, that reduces cross-hybridization noise by taking into account multiple sources for each mRNA expression level measurement, as well as prior knowledge of hybridization similarities between the nucleotide sequences of microarray probes and their target cDNAs., Results: The algorithm is applied to a subset of an exon-resolution genome-wide Agilent microarray data set for chromosome 16 of Mus musculus and is found to produce statistically significant reductions in cross-hybridization noise. The denoised data is found to produce enrichment in multiple gene ontology-biological process (GO-BP) functional groups. The algorithm is found to outperform robust multi-array analysis, another method for cross-hybridization compensation.

We used a microarray containing probes that tile all known yeast noncoding RNAs (ncRNAs) to investigate RNA biogenesis on a global scale. The microarray verified a general loss of Box C/D snoRNAs in the TetO7-BCD1 mutant, which had previously been shown for only a handful of snoRNAs. We also monitored the accumulation of improperly processed flank sequences of pre-RNAs in strains depleted for known RNA nucleases, including RNase III, Dbr1p, Xrn1p, Rat1p and components of the exosome and RNase P complexes. Among the hundreds of aberrant RNA processing events detected, two novel substrates of Rnt1p (the RUF1 and RUF3 snoRNAs) were identified. We also identified a relationship between tRNA 5' end processing and tRNA splicing, processes that were previously thought to be independent. This analysis demonstrates the applicability of microarray technology to the study of global analysis of ncRNA synthesis and provides an extensive directory of processing events mediated by yeast ncRNA processing enzymes.

Using a microarray that tiles all known yeast non-coding RNAs, we compared RNA from wild-type cells with RNA from mutants encoding known and putative RNA modifying enzymes. We show that at least five types of RNA modification (dihydrouridine, m1G, m2(2)G, m1A and m6(2)A) catalyzed by 10 different enzymes (Trm1p, Trm5, Trm10p, Dus1p-Dus4p, Dim1p, Gcd10p and Gcd14p) can be detected by virtue of differential hybridization to oligonucleotides on the array that are complementary to the modified sites. Using this approach, we identified a previously undetected m1A modification in GlnCTG tRNA, the formation of which is catalyzed by the Gcd10/Gcd14 complex. complex.

We report that Esf1p (Ydr365cp), an essential, evolutionarily conserved nucleolar protein, is required for the biogenesis of 18S rRNA in Saccharomyces cerevisiae. Depletion of Esf1p resulted in delayed processing of 35S precursor and a striking loss of 18S rRNA. Esf1p physically associated with ribosomal proteins and proteins involved in 18S rRNA biogenesis. Consistent with its role in 18S rRNA biogenesis, Esf1p also physically associated with U3 and U14 snoRNAs, but did not appear to be a core component of the SSU processome. These data indicate that Esf1p plays a direct role in early pre-rRNA processing.

Transcription factors belonging to the CCAAT-enhancer binding protein (C/EBP) family have been implicated in the regulation of gene expression during differentiation, development and disease. Autoregulation is relatively common in the modulation of C/EBP gene expression and the murine and human C/EBPalpha genes have been shown to be auto-activated by different mechanisms. In the light of this finding, it is essential that autoregulation of C/EBPalpha genes from a wider range of different species be investigated in order to gauge the degree of commonality, or otherwise, that may exist. We report here studies that investigate the regulation of the Xenopus laevis C/EBPalpha gene (xC/EBPalpha). The -1131/+41 promoter region was capable of directing high levels of expression in both the human hepatoma Hep3B and the Xenopus kidney epithelial A6 cell lines, and was auto-activated by expression vectors specifying for xC/EBPalpha or xC/EBPss. Deletion analysis showed that the -321/+41 sequence was sufficient for both the constitutive promoter activity and auto-activation and electrophoretic mobility shift assays identified the interaction of C/EBPs and Sp1 to this region. Although deletion of either the C/EBP or the Sp1 site drastically reduced the xC/EBPalpha promoter activity, multimers of only the C/EBP site could confer autoregulation to a heterologous SV40 promoter. These results indicate that, in contrast to the human promoter and in common with the murine gene, the xC/EBPalpha promoter was subject to direct autoregulation. In addition, we demonstrate a novel species-specific action of Sp1 in the regulation of C/EBPalpha expression, with the factor able to repress the murine promoter but activate the Xenopus gene.