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Pseudogenes (genes disrupted by frameshift or in-frame stop codons) are ubiquitously present in the bacterial genome and considered as nonfunctional fossil. Here, we used RNA-seq and mass-spectrometry technologies to measure the transcriptomes and proteomes of Salmonella enterica serovars Paratyphi A and Typhi. All pseudogenes’ mRNA sequences remained disrupted, and were present at comparable levels to their intact homologs. At the protein level, however, 101 out of 161 pseudogenes suggested successful translation, with their low expression regardless of growth conditions, genetic background and pseudogenization causes. The majority of frameshifting detected was compensatory for -1 frameshift mutations. Readthrough of in-frame stop codons primarily involved UAG; and cytosine was the most frequent base adjacent to the codon. Using a fluorescence reporter system, fifteen pseudogenes were confirmed to express successfully in vivo in Escherichia coli. Expression of the intact copy of the fifteen pseudogenes in S. Typhi affected bacterial pathogenesis as revealed in human macrophage and epithelial cell infection models. The above findings suggest the need to revisit the nonstandard translation mechanism as well as the biological role of pseudogenes in the bacterial genome.

© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. The GENCODE project annotates human and mouse genes and transcripts supported by experimental data with high accuracy, providing a foundational resource that supports genome biology and clinical genomics. GENCODE annotation processes make use of primary data and bioinformatic tools and analysis generated both within the consortium and externally to support the creation of transcript structures and the determination of their function. Here, we present improvements to our annotation infrastructure, bioinformatics tools, and analysis, and the advances they support in the annotation of the human and mouse genomes including: the completion of first pass manual annotation for the mouse reference genome; targeted improvements to the annotation of genes associated with SARS-CoV-2 infection; collaborative projects to achieve convergence across reference annotation databases for the annotation of human and mouse protein-coding genes; and the first GENCODE manually supervised automated annotation of lncRNAs. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org. National Human Genome Research Institute of the National Institutes of Health [U41HG007234]; the content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health; Wellcome Trust [WT108749/Z/15/Z, WT200990/Z/16/Z]; European Molecular Biology Laboratory; Swiss National Science Foundation through the National Center of Competence in Research ‘RNA & Disease’ (to R.J.); Medical Faculty of the University of Bern (to R.J). Funding for open access charge: National Institutes of Health.

Alternative splicing (AS) and alternative polyadenylation (APA) generate diverse transcripts in mammalian genomes during development and differentiation. Epigenetic marks such as trimethylation of histone H3 lysine 36 (H3K36me3) and DNA methylation play a role in generating transcriptome diversity. Intragenic CpG islands (iCGIs) and their corresponding host genes exhibit dynamic epigenetic and gene expression patterns during development and between different tissues. We hypothesise that iCGI-associated H3K36me3, DNA methylation and transcription can influence host gene AS and/or APA. We investigate H3K36me3 and find that this histone mark is not a major regulator of AS or APA in our model system. Genomewide, we identify over 4000 host genes that harbour an iCGI in the mammalian genome, including both previously annotated and novel iCGI/host gene pairs. The transcriptional activity of these iCGIs is tissue- and developmental stage-specific and, for the first time, we demonstrate that the premature termination of host gene transcripts upstream of iCGIs is closely correlated with the level of iCGI transcription in a DNA-methylation independent manner. These studies suggest that iCGI transcription, rather than H3K36me3 or DNA methylation, interfere with host gene transcription and pre-mRNA processing genomewide and contributes to the spatiotemporal diversification of both the transcriptome and proteome.

The rapid expansion of high-quality genome assemblies, exemplified by ongoing initiatives such as the Genome-10K and i5k, demands novel automated methods to approach comparative genomics. Of these, the study of inactivating mutations in the coding region of genes, or pseudogenization, as a source of evolutionary novelty is mostly overlooked. Thus, to address such evolutionary/genomic events, a systematic, accurate and computationally automated approach is required. Here, we present PseudoChecker, the first integrated online platform for gene inactivation inference. Unlike the few existing methods, our comparative genomics-based approach displays full automation, a built-in graphical user interface and a novel index, PseudoIndex, for an empirical evaluation of the gene coding status. As a multi-platform online service, PseudoChecker simplifies access and usability, allowing a fast identification of disruptive mutations. An analysis of 30 genes previously reported to be eroded in mammals, and 30 viable genes from the same lineages, demonstrated that PseudoChecker was able to correctly infer 97% of loss events and 95% of functional genes, confirming its reliability. PseudoChecker is freely available, without login required, at http://pseudochecker.ciimar.up.pt.

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, Ensembl Biomart, Ensembl Perl and REST APIs as well as https://www.gencodegenes.org. We thank Tim Hubbard and Jennifer Harrow for their lead- ership in the GENCODE project from 2003-2016 as well as all groups and group members involved in the GENCODE project since its inception including the HAVANA manual annotation group formerly at Wellcome Sanger Institute now at EMBL-EBI (founder), the Guigo group at Centre for Genomic Regulation (founder), the Gerstein group at Yale (founder), the Center for Biomolecular Science & En- gineering at UCSC (founder), the Ensembl team at EMBL- EBI (joined 2007), the Kellis group at MIT (joined 2007), the Tress group at CNIO (joined 2007), the Choudhary group formerly at Wellcome Sanger Institute now at Insti- tute of Cancer Research (joined 2012), the Reymond group at University of Lausanne (2003–2017), the Antonarakis group at University of Geneva (2003–2007), the Wei group at Genome Institute of Singapore (2003–2007), the Gin- geras group at Affymetrix Ltd (2003–2007) and the Brent group at Washington University in St. Louis (2007–2012). Sí

Although thousands of pseudogenes have been annotated in the human genome, their transcriptional regulation, expression profiles and functional mechanisms are largely unknown. In this study, we developed dreamBase (http://rna.sysu.edu.cn/dreamBase) to facilitate the investigation of DNA modification, RNA regulation and protein binding of potential expressed pseudogenes from multidimensional high-throughput sequencing data. Based on ∼5500 ChIP-seq and DNase-seq datasets, we identified genome-wide binding profiles of various transcription-associated factors around pseudogene loci. By integrating ∼18 000 RNA-seq data, we analysed the expression profiles of pseudogenes and explored their co-expression patterns with their parent genes in 32 cancers and 31 normal tissues. By combining microRNA binding sites, we demonstrated complex post-transcriptional regulation networks involving 275 microRNAs and 1201 pseudogenes. We generated ceRNA networks to illustrate the crosstalk between pseudogenes and their parent genes through competitive binding of microRNAs. In addition, we studied transcriptome-wide interactions between RNA binding proteins (RBPs) and pseudogenes based on 458 CLIP-seq datasets. In conjunction with epitranscriptome sequencing data, we also mapped 1039 RNA modification sites onto 635 pseudogenes. This database will provide insights into the transcriptional regulation, expression, functions and mechanisms of pseudogenes as well as their roles in biological processes and diseases.

Non-coding RNAs play a vital role in diverse cellular processes. Pseudogenes, which are non-coding homologs of protein-coding genes, were once considered non-functional evolutional relics. However, recent studies have shown that pseudogene transcripts can regulate their parental transcripts by sequestering shared microRNAs (miRNAs), thus acting as competing endogenous RNAs (ceRNAs). In this study, we utilize an unbiased screen to identify the ferritin heavy chain 1 (FTH1) transcript and multiple FTH1 pseudogenes as targets of several oncogenic miRNAs in prostate cancer (PCa). We characterize the critical role of this FTH1 gene:pseudogene:miRNA network in regulating tumorigenesis in PCa, whereby oncogenic miRNAs downregulate the expression of FTH1 and its pseudogenes to drive oncogenesis. We further show that impairing miRNA binding and subsequent ceRNA crosstalk completely rescues the slow growth phenotype in vitro and in vivo. Our results also demonstrate the reciprocal regulation between the pseudogenes and intracellular iron levels, which are crucial for multiple physiological and pathophysiological processes. In summary, we describe an extensive gene:pseudogene network comprising multiple miRNAs and multiple pseudogenes derived from a single parental gene. The network could be regulated through multiple mechanisms to modulate iron storage in various signaling pathways, the deregulation of which results in PCa development and progression.

Although microRNAs (miRNAs), other non-coding RNAs (ncRNAs) (e.g. lncRNAs, pseudogenes and circRNAs) and competing endogenous RNAs (ceRNAs) have been implicated in cell-fate determination and in various human diseases, surprisingly little is known about the regulatory interaction networks among the multiple classes of RNAs. In this study, we developed starBase v2.0 (http://starbase.sysu.edu.cn/) to systematically identify the RNA-RNA and protein-RNA interaction networks from 108 CLIP-Seq (PAR-CLIP, HITS-CLIP, iCLIP, CLASH) data sets generated by 37 independent studies. By analyzing millions of RNA-binding protein binding sites, we identified ∼9000 miRNA-circRNA, 16 000 miRNA-pseudogene and 285,000 protein-RNA regulatory relationships. Moreover, starBase v2.0 has been updated to provide the most comprehensive CLIP-Seq experimentally supported miRNA-mRNA and miRNA-lncRNA interaction networks to date. We identified ∼10,000 ceRNA pairs from CLIP-supported miRNA target sites. By combining 13 functional genomic annotations, we developed miRFunction and ceRNAFunction web servers to predict the function of miRNAs and other ncRNAs from the miRNA-mediated regulatory networks. Finally, we developed interactive web implementations to provide visualization, analysis and downloading of the aforementioned large-scale data sets. This study will greatly expand our understanding of ncRNA functions and their coordinated regulatory networks.

Seventeen years after the sequencing of the human genome, the human proteome is still under revision. One in eight of the 22 210 coding genes listed by the Ensembl/GENCODE, RefSeq and UniProtKB reference databases are annotated differently across the three sets. We have carried out an in-depth investigation on the 2764 genes classified as coding by one or more sets of manual curators and not coding by others. Data from large-scale genetic variation analyses suggests that most are not under protein-like purifying selection and so are unlikely to code for functional proteins. A further 1470 genes annotated as coding in all three reference sets have characteristics that are typical of non-coding genes or pseudogenes. These potential non-coding genes also appear to be undergoing neutral evolution and have considerably less supporting transcript and protein evidence than other coding genes. We believe that the three reference databases currently overestimate the number of human coding genes by at least 2000, complicating and adding noise to large-scale biomedical experiments. Determining which potential non-coding genes do not code for proteins is a difficult but vitally important task since the human reference proteome is a fundamental pillar of most basic research and supports almost all large-scale biomedical projects. National Institutes of Health [2 U41 HG007234 to I.J., L.M., J.M.R. and M.L.T., R01 HG004037 to I.J.]. Funding for open access charge: NIH [2 U41 HG007234]. Sí

The olfactory system integrates signals from receptors expressed in olfactory sensory neurons. Each sensory neuron expresses only one of many similar olfactory receptors (ORs). The choice of receptor is made stochastically early in the differentiation process and is maintained throughout the life of the neuron. The underlying mechanism of this stochastic commitment to one of multiple similar OR genes remains elusive. We present a theoretical analysis of a mechanism that invokes important epigenetic properties of the system. The proposed model combines nucleosomes and associated read–write enzymes as mediators of a cis-acting positive feedback with a trans-acting negative feedback, thereby coupling the local epigenetic landscape of the individual OR genes in a way that allow one and only one gene to be active at any time. The model pinpoint that singular gene selection does not require transient mechanisms, enhancer elements or transcription factors to separate choice from maintenance. In addition, our hypothesis allow us to combine all reported characteristics of singular OR gene selection, in particular that OR genes are silenced from OR transgenes. Intriguingly, it predicts that OR transgenes placed in close proximity should always be expressed simultaneously, though rarely.

Pseudogenes, especially those that are transcribed, may not be mere genomic fossils, but their biological significance remains unclear. Postulating that in the human genome, as in animal models, pseudogenes may function as gene regulators through generation of endo-siRNAs (esiRNAs), antisense RNAs or RNA decoys, we performed bioinformatic and subsequent experimental tests to explore esiRNA-mediated mechanisms of pseudogene involvement in oncogenesis. A genome-wide survey revealed a partial retrotranscript pseudogene ψPPM1K containing inverted repeats capable of folding into hairpin structures that can be processed into two esiRNAs; these esiRNAs potentially target many cellular genes, including NEK8. In 41 paired surgical specimens, we found significantly reduced expression of two predicted ψPPM1K-specific esiRNAs, and the cognate gene PPM1K, in hepatocellular carcinoma compared with matched non-tumour tissues, whereas the expression of target gene NEK8 was increased in tumours. Additionally, NEK8 and PPM1K were downregulated in stably transfected ψPPM1K-overexpressing cells, but not in cells transfected with an esiRNA1-deletion mutant of ψPPM1K. Furthermore, expression of NEK8 in ψPPM1K-transfected cells demonstrated that NEK8 can counteract the growth inhibitory effects of ψPPM1K. These findings indicate that a transcribed pseudogene can exert tumour-suppressor activity independent of its parental gene by generation of esiRNAs that regulate human cell growth.

Transfer RNAs (tRNAs) are present in all types of cells as well as in organelles. tRNAs of animal mitochondria show a low level of primary sequence conservation and exhibit 'bizarre' secondary structures, lacking complete domains of the common cloverleaf. Such sequences are hard to detect and hence frequently missed in computational analyses and mitochondrial genome annotation. Here, we introduce an automatic annotation procedure for mitochondrial tRNA genes in Metazoa based on sequence and structural information in manually curated covariance models. The method, applied to re-annotate 1876 available metazoan mitochondrial RefSeq genomes, allows to distinguish between remaining functional genes and degrading 'pseudogenes', even at early stages of divergence. The subsequent analysis of a comprehensive set of mitochondrial tRNA genes gives new insights into the evolution of structures of mitochondrial tRNA sequences as well as into the mechanisms of genome rearrangements. We find frequent losses of tRNA genes concentrated in basal Metazoa, frequent independent losses of individual parts of tRNA genes, particularly in Arthropoda, and wide-spread conserved overlaps of tRNAs in opposite reading direction. Direct evidence for several recent Tandem Duplication-Random Loss events is gained, demonstrating that this mechanism has an impact on the appearance of new mitochondrial gene orders.

In the course of analyzing 9,522,746 pyrosequencing reads from 23 stations in the Southwestern Pacific and equatorial Atlantic oceans, it came to our attention that misannotations of rRNA as proteins is now so widespread that false positive matching of rRNA pyrosequencing reads to the National Center for Biotechnology Information (NCBI) non-redundant protein database approaches 90%. One conserved portion of 23S rRNA was consistently misannotated often enough to prompt curators at Pfam to create a spurious protein family. Detailed examination of the annotation history of each seed sequence in the spurious Pfam protein family (PF10695, 'Cw-hydrolase') uncovered issues in the standard operating procedures and quality assurance programs of major sequencing centers, and other issues relating to the curation practices of those managing public databases such as GenBank and SwissProt. We offer recommendations for all these issues, and recommend as well that workers in the field of metatranscriptomics take extra care to avoid including false positive matches in their datasets.

In the human genome, it has been estimated that considerably more sequence is under natural selection in non-coding regions [such as transcription-factor binding sites (TF-binding sites) and non-coding RNAs (ncRNAs)] compared to protein-coding ones. However, less attention has been paid to them. To study selective pressure on non-coding elements, we use next-generation sequencing data from the recently completed pilot phase of the 1000 Genomes Project, which, compared to traditional methods, allows for the characterization of a full spectrum of genomic variations, including single-nucleotide polymorphisms (SNPs), short insertions and deletions (indels) and structural variations (SVs). We develop a framework for combining these variation data with non-coding elements, calculating various population-based metrics to compare classes and subclasses of elements, and developing element-aware aggregation procedures to probe the internal structure of an element. Overall, we find that TF-binding sites and ncRNAs are less selectively constrained for SNPs than coding sequences (CDSs), but more constrained than a neutral reference. We also determine that the relative amounts of constraint for the three types of variations are, in general, correlated, but there are some differences: counter-intuitively, TF-binding sites and ncRNAs are more selectively constrained for indels than for SNPs, compared to CDSs. After inspecting the overall properties of a class of elements, we analyze selective pressure on subclasses within an element class, and show that the extent of selection is associated with the genomic properties of each subclass. We find, for instance, that ncRNAs with higher expression levels tend to be under stronger purifying selection, and the actual regions of TF-binding motifs are under stronger selective pressure than the corresponding peak regions. Further, we develop element-aware aggregation plots to analyze selective pressure across the linear structure of an element, with the confidence intervals evaluated using both simple bootstrapping and block bootstrapping techniques. We find, for example, that both micro-RNAs (particularly the seed regions) and their binding targets are under stronger selective pressure for SNPs than their immediate genomic surroundings. In addition, we demonstrate that substitutions in TF-binding motifs inversely correlate with site conservation, and SNPs unfavorable for motifs are under more selective constraints than favorable SNPs. Finally, to further investigate intra-element differences, we show that SVs have the tendency to use distinctive modes and mechanisms when they interact with genomic elements, such as enveloping whole gene(s) rather than disrupting them partially, as well as duplicating TF motifs in tandem.

Almost 50 years following the discovery of the prokaryotic operon, the functional relevance of gene order within operons remains unclear. In this work, we take advantage of the eroded genome of Mycobacterium leprae to add evidence supporting the notion that functionally less important genes have a tendency to be located at the end of its operons. M. leprae’s genome includes 1133 pseudogenes and 1614 protein-coding genes and can be compared with the close genome of M. tuberculosis. Assuming M. leprae’s pseudogenes to represent dispensable genes, we have studied the position of these pseudogenes in the operons of M. leprae and of their orthologs in M. tuberculosis .W e observed that both tend to be located in the 3 0 (downstream) half of the operon (P-values of 0.03 and 0.18, respectively). Analysis of pseudogenes in all available prokaryotic genomes confirms this trend (P-value of 7.1 � 10 � 7 ). In a complementary analysis, we found a significant tendency for essential genes to be located at the 5 0 (upstream) half of the operon (P-value of 0.006). Our work provides an indication that, in prokarya, functionally less important genes have a tendency to be located at the end of operons, while more relevant genes tend to be located toward operon starts.

Duplicated pseudogenes in the human genome are disabled copies of functioning parent genes. They result from block duplication events occurring throughout evolutionary history. Relatively recent duplications (with sequence similarity ≥90% and length ≥1 kb) are termed segmental duplications (SDs); here, we analyze the interrelationship of SDs and pseudogenes. We present a decision-tree approach to classify pseudogenes based on their (and their parents’) characteristics in relation to SDs. The classification identifies 140 novel pseudogenes and makes possible improved annotation for the 3172 pseudogenes located in SDs. In particular, it reveals that many pseudogenes in SDs likely did not arise directly from parent genes, but are the result of a multi-step process. In these cases, the initial duplication or retrotransposition of a parent gene gives rise to a ‘parent pseudogene’, followed by further duplication creating duplicated–duplicated or duplicated–processed pseudogenes, respectively. Moreover, we can precisely identify these parent pseudogenes by overlap with ancestral SD loci. Finally, a comparison of nucleotide substitutions per site in a pseudogene with its surrounding SD region allows us to estimate the time difference between duplication and disablement events, and this suggests that most duplicated pseudogenes in SDs were likely disabled around the time of the original duplication.

More than 40% of the human genome is generated by retrotransposition, a series of in vivo processes involving reverse transcription of RNA molecules and integration of the transcripts into the genomic sequence. The mechanism of retrotransposition, however, is not fully understood, and additional genomic elements generated by retrotransposition may remain to be discovered. Here, we report that the human genome contains many previously unidentified short pseudogenes generated by retrotransposition of mRNAs. Genomic elements generated by non-long terminal repeat retrotransposition have specific sequence signatures: a poly-A tract that is immediately downstream and a pair of duplicated sequences, called target site duplications (TSDs), at either end. Using a new computer program, TSDscan, that can accurately detect pseudogenes based on the presence of the poly-A tract and TSDs, we found 654 short (< or = 300 bp), previously unknown pseudogenes derived from mRNAs. Comprehensive analyses of the pseudogenes that we identified and their parent mRNAs revealed that the pseudogene length depends on the parent mRNA length: long mRNAs generate more short pseudogenes than do short mRNAs. To explain this phenomenon, we hypothesize that most long mRNAs are truncated before they are reverse transcribed. Truncated mRNAs would be rapidly degraded during reverse transcription, resulting in the generation of short pseudogenes.

NCBI's Reference Sequence (RefSeq) database (http://www.ncbi.nlm.nih.gov/RefSeq/) is a curated non-redundant collection of sequences representing genomes, transcripts and proteins. RefSeq records integrate information from multiple sources and represent a current description of the sequence, the gene and sequence features. The database includes over 5300 organisms spanning prokaryotes, eukaryotes and viruses, with records for more than 5.5 x 10(6) proteins (RefSeq release 30). Feature annotation is applied by a combination of curation, collaboration, propagation from other sources and computation. We report here on the recent growth of the database, recent changes to feature annotations and record types for eukaryotic (primarily vertebrate) species and policies regarding species inclusion and genome annotation. In addition, we introduce RefSeqGene, a new initiative to support reporting variation data on a stable genomic coordinate system.

Pseudofam (http://pseudofam.pseudogene.org) is a database of pseudogene families based on the protein families from the Pfam database. It provides resources for analyzing the family structure of pseudogenes including query tools, statistical summaries and sequence alignments. The current version of Pseudofam contains more than 125 000 pseudogenes identified from 10 eukaryotic genomes and aligned within nearly 3000 families (approximately one-third of the total families in PfamA). Pseudofam uses a large-scale parallelized homology search algorithm (implemented as an extension of the PseudoPipe pipeline) to identify pseudogenes. Each identified pseudogene is assigned to its parent protein family and subsequently aligned to each other by transferring the parent domain alignments from the Pfam family. Pseudogenes are also given additional annotation based on an ontology, reflecting their mode of creation and subsequent history. In particular, our annotation highlights the association of pseudogene families with genomic features, such as segmental duplications. In addition, pseudogene families are associated with key statistics, which identify outlier families with an unusual degree of pseudogenization. The statistics also show how the number of genes and pseudogenes in families correlates across different species. Overall, they highlight the fact that housekeeping families tend to be enriched with a large number of pseudogenes.

The MITOMAP (http://www.mitomap.org) data system for the human mitochondrial genome has been greatly enhanced by the addition of a navigable mutational mitochondrial DNA (mtDNA) phylogenetic tree of approximately 3000 mtDNA coding region sequences plus expanded pathogenic mutation tables and a nuclear-mtDNA pseudogene (NUMT) data base. The phylogeny reconstructs the entire mutational history of the human mtDNA, thus defining the mtDNA haplogroups and differentiating ancient from recent mtDNA mutations. Pathogenic mutations are classified by both genotype and phenotype, and the NUMT sequences permits detection of spurious inclusion of pseudogene variants during mutation analysis. These additions position MITOMAP for the implementation of our automated mtDNA sequence analysis system, Mitomaster.

The Pseudogene.org knowledgebase serves as a comprehensive repository for pseudogene annotation. The definition of a pseudogene varies within the literature, resulting in significantly different approaches to the problem of identification. Consequently, it is difficult to maintain a consistent collection of pseudogenes in detail necessary for their effective use. Our database is designed to address this issue. It integrates a variety of heterogeneous resources and supports a subset structure that highlights specific groups of pseudogenes that are of interest to the research community. Tools are provided for the comparison of sets and the creation of layered set unions, enabling researchers to derive a current 'consensus' set of pseudogenes. Additional features include versatile search, the capacity for robust interaction with other databases, the ability to reconstruct older versions of the database (accounting for changing genome builds) and an underlying object-oriented interface designed for researchers with a minimal knowledge of programming. At the present time, the database contains more than 100,000 pseudogenes spanning 64 prokaryote and 11 eukaryote genomes, including a collection of human annotations compiled from 16 sources.

The identification of pseudogenes is an integral and significant part of the genome annotation because of their abundance and their impact on the experimental analysis of functional genes. Most of the computational annotation systems are not optimized for systematic pseudogene recognition, often annotating pseudogenes as functional genes, and users then propagate these errors to subsequent analyses and interpretations. In order to validate gene annotations and to identify pseudogenes that are potentially mis-annotated, we developed a novel approach based on whole genome profiling of existing transcript and protein sequences. This method has two important features: (i) equally detects both processed and non-processed pseudogenes and (ii) can identify transcribed pseudogenes. Applying this method to the human Ensembl gene predictions, we discovered that 2011 (9% of total) Ensembl genes in the categories of known and novel might be pseudogenes based on expression evidence. Of these, 1200 genes are found to have no existing evidence of transcription, and 811 genes are found with transcription evidence but contain significant translation disruption. Approximately 40% of the 2011 identified pseudogenes presented a multi-exon structure, representing non-processed pseudogenes. We have demonstrated the power of whole genome profiling of expression sequences to improve the accuracy of gene annotations.

The Shigella bacteria cause bacillary dysentery, which remains a significant threat to public health. The genus status and species classification appear no longer valid, as compelling evidence indicates that Shigella, as well as enteroinvasive Escherichia coli, are derived from multiple origins of E.coli and form a single pathovar. Nevertheless, Shigella dysenteriae serotype 1 causes deadly epidemics but Shigella boydii is restricted to the Indian subcontinent, while Shigella flexneri and Shigella sonnei are prevalent in developing and developed countries respectively. To begin to explain these distinctive epidemiological and pathological features at the genome level, we have carried out comparative genomics on four representative strains. Each of the Shigella genomes includes a virulence plasmid that encodes conserved primary virulence determinants. The Shigella chromosomes share most of their genes with that of E.coli K12 strain MG1655, but each has over 200 pseudogenes, 300 approximately 700 copies of insertion sequence (IS) elements, and numerous deletions, insertions, translocations and inversions. There is extensive diversity of putative virulence genes, mostly acquired via bacteriophage-mediated lateral gene transfer. Hence, via convergent evolution involving gain and loss of functions, through bacteriophage-mediated gene acquisition, IS-mediated DNA rearrangements and formation of pseudogenes, the Shigella spp. became highly specific human pathogens with variable epidemiological and pathological features.

Pseudogenes are now known to be a regular feature of bacterial genomes and are found in particularly high numbers within the genomes of recently emerged bacterial pathogens. As most pseudogenes are recognized by sequence alignments, we use newly available genomic sequences to identify the pseudogenes in 11 genomes from 4 bacterial genera, each of which contains at least 1 human pathogen. The numbers of pseudogenes range from 27 in Staphylococcus aureus MW2 to 337 in Yersinia pestis CO92 (e.g. 1–8% of the annotated genes in the genome). Most pseudogenes are formed by small frameshifting indels, but because stop codons are A + T-rich, the two low-G + C Gram-positive taxa (Streptococcus and Staphylococcus) have relatively high fractions of pseudogenes generated by nonsense mutations when compared with more G + C-rich genomes. Over half of the pseudogenes are produced from genes whose original functions were annotated as ‘hypothetical’ or ‘unknown’; however, several broadly distributed genes involved in nucleotide processing, repair or replication have become pseudogenes in one of the sequenced Vibrio vulnificus genomes. Although many of our comparisons involved closely related strains with broadly overlapping gene inventories, each genome contains a largely unique set of pseudogenes, suggesting that pseudogenes are formed and eliminated relatively rapidly from most bacterial genomes.

Pseudogenes, in the case of protein-coding genes, are gene copies that have lost the ability to code for a protein; they are typically identified through annotation of disabled, decayed or incomplete protein-coding sequences. Processed pseudogenes (PPsigs) are made through mRNA retrotransposition. There is overwhelming genomic evidence for thousands of human PPsigs and also dozens of human processed genes that comprise complete retrotransposed copies of other genes. Here, we survey for an intermediate entity, the transcribed processed pseudogene (TPPsig), which is disabled but nonetheless transcribed. TPPsigs may affect expression of paralogous genes, as observed in the case of the mouse makorin1-p1 TPPsig. To elucidate their role, we identified human TPPsigs by mapping expressed sequences onto PPsigs and, reciprocally, extracting TPPsigs from known mRNAs. We consider only those PPsigs that are homologous to either non-mammalian eukaryotic proteins or protein domains of known structure, and require detection of identical coding-sequence disablements in both the expressed and genomic sequences. Oligonucleotide microarray data provide further expression verification. Overall, we find 166-233 TPPsigs ( approximately 4-6% of PPsigs). Proteins/transcripts with the highest numbers of homologous TPPsigs generally have many homologous PPsigs and are abundantly expressed. TPPsigs are significantly over-represented near both the 5' and 3' ends of genes; this suggests that TPPsigs can be formed through gene-promoter co-option, or intrusion into untranslated regions. However, roughly half of the TPPsigs are located away from genes in the intergenic DNA and thus may be co-opting cryptic promoters of undesignated origin. Furthermore, TPPsigs are unlike other PPsigs and processed genes in the following ways: (i) they do not show a significant tendency to either deposit on or originate from the X chromosome; (ii) only 5% of human TPPsigs have potential orthologs in mouse. This latter finding indicates that the vast majority of TPPsigs is lineage specific. This is likely linked to well-documented extensive lineage-specific SINE/LINE activity. The list of TPPsigs is available at: http://www.biology.mcgill.ca/faculty/harrison/tppg/bppg.tov (or) http:pseudogene.org.

We report the characterization in the human genome of 966 pseudogenes derived from the four human Y (hY) RNAs, components of the Ro/SS-A autoantigen. About 95% of the Y RNA pseudogenes are found in corresponding locations on the chimpanzee and human chromosomes. On the contrary, Y pseudogenes in mice are both infrequent and found in different genomic regions. In addition to this rodent/primate discrepancy, the conservation of hY pseudogenes relative to hY genes suggests that they occurred after rodent/primate divergence. Flanking regions of hY pseudogenes contain convincing evidence for involvement of the L1 retrotransposition machinery. Although Alu elements are found in close proximity to most hY pseudogenes, these are not chimeric retrogenes. Point mutations in hY RNA transcripts specifically affecting binding of Ro60 protein likely contributed to their selection for direct trans retrotransposition. This represents a novel requirement for the selection of specific RNAs for their genomic integration by the L1 retrotransposition machinery. Over 40% of the hY pseudogenes are found in intronic regions of protein-coding genes. Considering the functions of proteins known to bind subsets of hY RNAs, hY pseudogenes constitute a new class of L1-dependent non-autonomous retroelements, potentially involved in post-transcriptional regulation of gene expression.

Salmonella enterica serovar Choleraesuis (S. Choleraesuis), a highly invasive serovar among non-typhoidal Salmonella, usually causes sepsis or extra-intestinal focal infections in humans. S. Choleraesuis infections have now become particularly difficult to treat because of the emergence of resistance to multiple antimicrobial agents. The 4.7 Mb genome sequence of a multidrug-resistant S. Choleraesuis strain SC-B67 was determined. Genome wide comparison of three sequenced Salmonella genomes revealed that more deletion events occurred in S. Choleraesuis SC-B67 and S.Typhi CT18 relative to S. Typhimurium LT2. S. Choleraesuis has 151 pseudogenes, which, among the three Salmonella genomes, include the highest percentage of pseudogenes arising from the genes involved in bacterial chemotaxis signal-transduction pathways. Mutations in these genes may increase smooth swimming of the bacteria, potentially allowing more effective interactions with and invasion of host cells to occur. A key regulatory gene of TetR/AcrR family, acrR, was inactivated through the introduction of an internal stop codon resulting in overexpression of AcrAB that appears to be associated with ciprofloxacin resistance. While lateral gene transfer providing basic functions to allow niche expansion in the host and environment is maintained during the evolution of different serovars of Salmonella, genes providing little overall selective benefit may be lost rapidly. Our findings suggest that the formation of pseudogenes may provide a simple evolutionary pathway that complements gene acquisition to enhance virulence and antimicrobial resistance in S. Choleraesuis.

We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83 percent accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacter pylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from six phylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC 6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.

Pseudogenes are copies of genes that cannot produce a protein. They can be detected from disruptions to their apparent coding sequence, caused by frameshifts and premature stop codons. They are classed as either processed pseudogenes (made by reverse transcription from an mRNA) or duplicated pseudogenes, arising from duplication in the genomic DNA and subsequent disablement. Historically, there is anecdotal evidence that the fruit fly (Drosophila melanogaster) has few pseudogenes. Investigators have linked this to a high deletion rate of genomic DNA, for which there is evidence from genetic experiments on genome size. Here, we apply a homology-based pipeline that was developed previously to identify pseudogenes in other eukaryotic genomes, to the fruit fly, so as to derive the first complete survey of its pseudogene population. We find approximately 100 pseudogenes, with at least a sixth of these as candidate processed pseudogenes. This gives a much lower proportion of pseudogenes (compared with the size of the proteome) than in the genomes of other eukaryotes for which data are available (human, nematode and budding yeast). Closest matching proteins to Drosophila pseudogenes are significantly longer than the average protein in its proteome (up to approximately 60% more than the average protein's length), in contrast to the situation in the three other eukaryotic genomes. This may be due to the persistence of fragments of longer genes. In the fly pseudogene population, we found most pseudogenes for serine proteases (which are more abundant in the Drosophila lineage compared with the other eukaryotes), immunoglobulin-motif-containing proteins and cytochromes P450. Data on the sequences and positions of the putative pseudogenes are available at: http://www.pseudogene.org/fly. The detection of a small number of pseudogenes in the Drosophila genome and the higher mean length for the closest matching proteins to pseudogenes (possibly because remnants of genes encoding longer proteins are more likely to persist) are further evidence for a high deletion rate of genomic DNA in the fruit fly. The data are useful for molecular evolution study in Drosophila.

The goal of the NCBI Reference Sequence (RefSeq) project is to provide the single best non-redundant and comprehensive collection of naturally occurring biological molecules, representing the central dogma. Nucleotide and protein sequences are explicitly linked on a residue-by-residue basis in this collection. Ideally all molecule types will be available for each well-studied organism, but the initial database collection pragmatically includes only those molecules and organisms that are most readily identified. Thus different amounts of information are available for different organisms at any given time. Furthermore, for some organisms additional intermediate records are provided when the genome sequence is not yet finished. The collection is supplied by NCBI through three distinct pipelines in addition to collaborations with community groups. The collection is curated on an ongoing basis. Additional information about the NCBI RefSeq project is available at http://www.ncbi.nih.gov/RefSeq/.

We have sequenced the genome of Shigella flexneri serotype 2a, the most prevalent species and serotype that causes bacillary dysentery or shigellosis in man. The whole genome is composed of a 4 607 203 bp chromosome and a 221 618 bp virulence plasmid, designated pCP301. While the plasmid shows minor divergence from that sequenced in serotype 5a, striking characteristics of the chromosome have been revealed. The S.flexneri chromosome has, astonishingly, 314 IS elements, more than 7-fold over those possessed by its close relatives, the non-pathogenic K12 strain and enterohemorrhagic O157:H7 strain of Escherichia coli. There are 13 translocations and inversions compared with the E.coli sequences, all involve a segment larger than 5 kb, and most are associated with deletions or acquired DNA sequences, of which several are likely to be bacteriophage-transmitted pathogenicity islands. Furthermore, S.flexneri, resembling another human-restricted enteric pathogen, Salmonella typhi, also has hundreds of pseudogenes compared with the E.coli strains. All of these could be subjected to investigations towards novel preventative and treatment strategies against shigellosis.

Prokaryotic genome annotation is highly dependent on automated methods, as manual curation cannot keep up with the exponential growth of sequenced genomes. Current automated methods depend heavily on sequence composition and often underestimate the complexity of the proteome. We developed RibosomeE Profiling Assisted (re-)AnnotaTION (REPARATION), a de novo machine learning algorithm that takes advantage of experimental protein synthesis evidence from ribosome profiling (Ribo-seq) to delineate translated open reading frames (ORFs) in bacteria, independent of genome annotation (https://github.com/Biobix/REPARATION). REPARATION evaluates all possible ORFs in the genome and estimates minimum thresholds based on a growth curve model to screen for spurious ORFs. We applied REPARATION to three annotated bacterial species to obtain a more comprehensive mapping of their translation landscape in support of experimental data. In all cases, we identified hundreds of novel (small) ORFs including variants of previously annotated ORFs and >70% of all (variants of) annotated protein coding ORFs were predicted by REPARATION to be translated. Our predictions are supported by matching mass spectrometry proteomics data, sequence composition and conservation analysis. REPARATION is unique in that it makes use of experimental translation evidence to intrinsically perform a de novo ORF delineation in bacterial genomes irrespective of the sequence features linked to open reading frames.

Programmed excision of internal eliminated sequences (IESs) occurs at thousands of sites in ciliate genomes. How this is controlled is largely unknown. Here, we report the characterization of the non-efficiently excised 156psiG-11 IES from Paramecium primaurelia strain 156 and that of the efficiently excised 168psiG-11 IES, an allelic variant from strain 168. Then, we report a genetic and molecular analysis of IES excision efficiency in F(1) progeny derived from interstrain crosses and in F(2) homozygous progeny derived from F(1) autogamy. IES 168psiG-11 excision efficiency was approximately 100% in all cases. IES 156psiG-11 excision efficiency was 19 +/- 13% in F(1) progeny and 0.6 +/- 1.1% in F(2) progeny. No trans-excision event between IESs 156psiG-11 and 168psiG-11 was detected within the F(1) progeny. These data demonstrate that the excision efficiency of this IES is variable and controlled by a cis-acting element. This should encompass positions 8 and/or 9 of the right IES end, which display allele differences. Finally, the 30-fold stimulation of IES 156psiG-11 excision efficiency within F(1) progeny relative to F(2) progeny demonstrates that Paramecium IES excision efficiency is sensitive either to a conjugation-specific trans-acting factor provided by the zygotic genome, or to homologous chromosome cross-talk.

African trypanosomes evade the immune response of their mammalian hosts by sequentially expressing genes for different variant surface glycoproteins (VSGs) from telomere-linked VSG expression sites. In the Trypanosoma brucei clone whose genome is being sequenced (GUTat 10.1), we show that the expressed VSG (VSG 10.1) is duplicated from a silent donor VSG located at another telomere-linked site. We have determined two 130 kb sequences representing the VSG 10.1 donor and expression sites. The telomere-linked donor VSG 10.1 resembles metacyclic VSG expression sites, and is preceded by a cluster of 35 or more tandem housekeeping genes, all of which are transcribed away from the telomere. The 45 kb telomere-linked VSG 10.1 expression site contains a promoter followed by seven expression site-associated genes (ESAGs), three pseudo ESAGs, two pseudo VSGs and VSG 10.1. The 80 kb preceding the expression site has few, if any, functional ORFs, but contains 50 bp repeats, INGI retrotransposon-like elements, and novel 4–12 kb repeats found near other telomeres. This analysis provides the first look over a 130 kb range of a telomere-linked donor VSG and its corresponding telomere-linked VSG expression site and forms the basis for studies on antigenic variation in the context of a completely sequenced genome.

Pseudogenes are non-functioning copies of genes in genomic DNA, which may either result from reverse transcription from an mRNA transcript (processed pseudogenes) or from gene duplication and subsequent disablement (non-processed pseudogenes). As pseudogenes are apparently ‘dead’, they usually have a variety of obvious disablements (e.g., insertions, deletions, frameshifts and truncations) relative to their functioning homologs. We have derived an initial estimate of the size, distribution and characteristics of the pseudogene population in the Caenorhabditis elegans genome, performing a survey in ‘molecular archaeology’. Corresponding to the 18 576 annotated proteins in the worm (i.e., in Wormpep18), we have found an estimated total of 2168 pseudogenes, about one for every eight genes. Few of these appear to be processed. Details of our pseudogene assignments are available from http://bioinfo.mbb.yale.edu/genome/worm/pseudogene. The population of pseudogenes differs significantly from that of genes in a number of respects: (i) pseudogenes are distributed unevenly across the genome relative to genes, with a disproportionate number on chromosome IV; (ii) the density of pseudogenes is higher on the arms of the chromosomes; (iii) the amino acid composition of pseudogenes is midway between that of genes and (translations of) random intergenic DNA, with enrichment of Phe, Ile, Leu and Lys, and depletion of Asp, Ala, Glu and Gly relative to the worm proteome; and (iv) the most common protein folds and families differ somewhat between genes and pseudogenes—whereas the most common fold found in the worm proteome is the immunoglobulin fold and the most common ‘pseudofold’ is the C-type lectin. In addition, the size of a gene family bears little overall relationship to the size of its corresponding pseudogene complement, indicating a highly dynamic genome. There are in fact a number of families associated with large populations of pseudogenes. For example, one family of seven-transmembrane receptors (represented by gene B0334.7) has one pseudogene for every four genes, and another uncharacterized family (represented by gene B0403.1) is approximately two-thirds pseudogenic. Furthermore, over a hundred apparent pseudogenic fragments do not have any obvious homologs in the worm.

We determined the complete nucleotide sequence of the mitochondrial genome of an angiosperm, sugar beet (Beta vulgaris cv TK81-O). The 368 799 bp genome contains 29 protein, five rRNA and 25 tRNA genes, most of which are also shared by the mitochondrial genome of Arabidopsis thaliana, the only other completely sequenced angiosperm mitochondrial genome. However, four genes identified here (namely rps13, trnF-GAA, ccb577 and trnC2-GCA) are missing in Arabidopsis mitochondria. In addition, four genes found in Arabidopsis (ccb228, rpl2, rpl16 and trnY2-GUA) are entirely absent in sugar beet or present only in severely truncated form. Introns, duplicated sequences, additional reading frames and inserted foreign sequences (chloroplast, nuclear and plasmid DNA sequences) contribute significantly to the overall size of the sugar beet mitochondrial genome. Nevertheless, 55.6% of the genome has no obvious features of information. We identified a novel tRNA(Cys) gene (trnC2-GCA) which shows no sequence homology with any tRNA(Cys) genes reported so far in higher plants. Intriguingly, this tRNA gene is actually transcribed into a mature tRNA, whereas the native tRNA(Cys) gene (trnC1-GCA) is most likely a pseudogene.

We have characterized four novel murine ribonuclease genes that, together with the murine eosinophil-associated ribonucleases 1 and 2, form a distinct and unusual cluster within the RNase A gene superfamily. Three of these genes (mR-3, mR-4, mR-5) include complete open reading frames, encoding ribonucleases with eight cysteines and appropriately spaced histidines (His11 and His124) and lysine (Lys35) that are characteristic of this enlarging protein family; the fourth sequence encodes a non-functional pseudogene (mR-6P). Although the amino acid sequence similarities among these murine ribonucleases varies from 60 to 94%, they form a unique cluster, as each sequence is found to be more closely related to another of this group than to either murine angiogenin or to murine pancreatic ribonuclease. Interestingly, the relationship between the six genes in this 'mR cluster' and the defined lineages of the RNase A gene family could not be determined by amino acid sequence homology, suggesting the possibility that there are one or more additional ribonuclease lineages that have yet to be defined. Although the nature of the evolutionary constraints promoting this unusual expansion and diversification remain unclear, the implications with respect to function are intriguing.

LINE1s occupy 17% of the human genome and are its only active autonomous mobile DNA. L1s are also responsible for genomic insertion of processed pseudogenes and >1 million non-autonomous retrotransposons (Alus and SVAs). These elements have significant effects on gene organization and expression. Despite the importance of retrotransposons for genome evolution, much about their biology remains unknown, including cellular factors involved in the complex processes of retrotransposition and forming and transporting L1 ribonucleoprotein particles. By co-immunoprecipitation of tagged L1 constructs and mass spectrometry, we identified proteins associated with the L1 ORF1 protein and its ribonucleoprotein. These include RNA transport proteins, gene expression regulators, post-translational modifiers, helicases and splicing factors. Many cellular proteins co-localize with L1 ORF1 protein in cytoplasmic granules. We also assayed the effects of these proteins on cell culture retrotransposition and found strong inhibiting proteins, including some that control HIV and other retroviruses. These data suggest candidate cofactors that interact with the L1 to modulate its activity and increase our understanding of the means by which the cell coexists with these genomic 'parasites'.

POU genes encode a family of transcription factors involved in a wide variety of cell fate decisions and in the regulation of differentiation pathways. We have searched for POU genes in the zebrafish, a popular model organism for the study of early development of vertebrates. Besides five putative pseudogenes we have identified five POU genes that are expressed during embryogenesis. Probes obtained by PCR were used to isolate full-length cDNAs. Four of the isolated genes encode proteins with class III POU domains. Analysis of genomic clones suggests that the fish genes in general do not contain introns, similar to class III genes of mammals. However, the C-termini of two of the encoded proteins vary due to facultative splicing of a short intervening sequence. These two genes show very strong similarities in their sequence. They have probably arisen by gene duplication, possibly as part of a larger scale duplication of part of the zebrafish genome. Analysis of the expression of the class III genes shows that they are predominantly expressed in the central nervous system and that they may play important roles in patterning the embryonic brain.

The murine poly(C)-binding protein (mCBP) was previously shown to belong to the group of K-homology (KH) proteins by virtue of its homology to hnRNP-K. We have isolated cDNA-splice variants of mCBP which differ by two variable regions of 93 bp and/or 39 +/- 3 bp respectively. Both variable regions are located between the second and third KH-domain of mCBP. The characterization of a partial genomic clone enabled us to propose a model for the generation of the second variable region by the use of a putative alternative splice signal. The mCBP mRNA is expressed ubiquitously and the protein is found predominantly in the nucleus with the exception of the nucleoli. We have identified five proteins which interact with mCBP in the yeast two hybrid system: mouse y-box protein 1 (msy-1), y-box-binding protein, hnRNP-L, filamin and splicing factor 9G8. The interaction between mCBP and splicing factor 9G8 was confirmed in vivo. These results suggest a function of mCBP in RNA metabolism.

The macronuclear genome of Euplotes crassus contains two different genes, EFA1 and EFA2, encoding EF-1alpha proteins. They are derived from micronuclear precursors in the course of a sexual process termed conjugation. We have found that two apparent micronuclear precursors exist for EFA1. They differ in their potential coding sequences and in the internal sequences interrupting the genes, which are normally removed during the processing from micronuclear into macronuclear genes. One of these genes is not processed into a macronuclear gene and has accumulated C-->T transitions in a limited section of the coding region. The gene obviously constitutes a recent duplication which has lost its ability to be processed into a macronuclear gene and has therefore become a micronuclear pseudogene. The true EFA1 precursor harbours a novel type of internal sequence in addition to a classical AT-rich IES. As usual, only one micronuclear EFA2 precursor gene was found. Its coding sequence is interrupted by a 79 bp TeIIES.

Six human 5S rRNA genes and gene variants and one pseudogene have been sequenced. The six genes/variants were transcribed in a HeLa cell extract with about equal efficiency. Three genes contain the Sp1 binding sequence GGGCGG in position -43 to -38 and three genes contain the Sp1 like sequence GGGCCG in this position. The six genes contain furthermore one Sp1 binding site in a position about -245 and one ATF recognition site in a position about -202. A 12 bp sequence (GGCTCTTGGGGC) found in position -32 to -21 strongly influenced the transcriptional efficiency in vitro. This 12-mer, designated the D box, has also been found upstream a 5S rRNA gene from hamster and mouse. Removal of the Sp1 binding sites had no effect on the transcription in vitro whereas the transcriptional efficiency decreased to 10% if the D box was removed from the human 5S rRNA gene.

An updated list of DNA sequences cloned from the human genome over the past year (1991) is presented. Intended as a guide to clone availability, this list includes published reports of cDNA, genomic and synthetic probes comprising both gene and pseudogene sequences.

Transcription factors containing the POU-domain have been shown to be important regulators of tissue-specific gene expression in the pituitary and lymphoid cells. Using a polymerase chain reaction (PCR)-based strategy, we have searched for similar factors that may be expressed in adult human pancreatic islets. This approach resulted in the amplification of sequences encoding the octamer binding proteins Oct1 and Oct3 (also called Oct4). The isolation of cDNAs encoding Oct3 revealed the expression of two isoforms of this transcription factor termed Oct3A and Oct3B that are generated by alternative splicing. Human Oct3A and Oct3B are composed of 360 and 265 amino acids, respectively, of which the 225 amino acids at the COOH-termini are identical. The sequence of human Oct3A shows 87% amino acid identity with mouse Oct3. Reverse-transcriptase PCR showed low levels of expression of both Oct3A and Oct3B mRNA in all adult human tissues examined. We also isolated and characterized the human Oct3 gene (OTF3) and a related gene, OTF3C. The human Oct3 gene, localized to human chromosome 6 in the region of the MHC complex, spans about 7 kb and consists of five exons. The Oct3-related gene, OTF3C, is a retroposon and has been localized to human chromosome 8. Southern blotting and PCR amplification of human DNA indicated the presence of other OTF3-related genes as has been previously noted in the mouse. Two polymorphisms which can be typed using PCR were identified in OTF3 which will facilitate genetic studies of this gene.

Expression of the X-linked repeated Stellate (Ste) genes, which code for a protein with 38% similarity to the beta-subunit of casein kinase II, is suppressed by the Su(Ste) locus on the Y chromosome. The structure and evolution of the Y-linked repeats in the region of the Su(Ste) locus were studied. The 2800 bp repeats consist of three main elements: the region of homology to the Ste genes, an adjacent AT-rich, Y-specific segment, and mobile element 1360 inserted in the Ste sequence. Amplification of repeats was followed by point mutations, deletions, and insertions of mobile elements. DNA sequencing shows that these repeats may be considered as Ste pseudogenes or as damaged variants of a putative gene(s) encoding a protein quite different from the Ste protein as a result of an alternative splicing pattern. A comparison of 5 variants of the Y-Su(Ste) repeats shows a number of recombination events between amplified and diverged sequences that could be due to either multiple unequal mitotic sister-chromatid exchanges or to gene conversion. It is a first demonstration on a molecular level of these processes occurring in heterochromatic non-rDNA tandemly organized sequences in an eukaryotic genome.

An updated list of DNA sequences cloned from the human genome over the past year (1990) is presented. Intended as a guide to clone availability, this list includes published reports of cDNA, genomic and synthetic clones comprising both gene and pseudogene sequences.