Digging for dead genes: an analysis of the characteristics of the pseudogene population in the Caenorhabditis elegans genome

Comparative analysis of processed pseudogenes in the mouse and human genomes

Pseudogenes are important resources in evolutionary and comparative genomics because they provide molecular records of the ancient genes that existed in the genome millions of years ago. We have systematically identified approximately 5000 processed pseudogenes in the mouse genome, and estimated that approximately 60% are lineage specific, created after the mouse and human diverged. In both mouse and human genomes, similar types of genes give rise to many processed pseudogenes. These tend to be housekeeping genes, which are highly expressed in the germ line. Ribosomal-protein genes, in particular, form the largest sub-group. The processed pseudogenes in the mouse occur with a distinctly different chromosomal distribution than LINEs or SINEs - preferentially in GC-poor regions. Finally, the age distribution of mouse-processed pseudogenes closely resembles that of LINEs, in contrast to human, where the age distribution closely follows Alus (SINEs).

A genome-wide survey of human pseudogenes

We screened all intergenic regions in the human genome to identify pseudogenes with a combination of homology searches and a functionality test using the ratio of silent to replacement nucleotide substitutions (KA/KS). We identified 19,724 regions of which 95% +/- 3% are estimated to evolve neutrally and thus are likely to encode pseudogenes. Half of these have no detectable truncation in their pseudocoding regions and therefore are not identifiable by methods that require the presence of truncations to prove nonfunctionality. A comparative analysis with the mouse genome showed that 70% of these pseudogenes have a retrotranspositional origin (processed), and the rest arose by segmental duplication (nonprocessed). Although the spread of both types of pseudogenes correlates with chromosome size, nonprocessed pseudogenes appear to be enriched in regions with high gene density. It is likely that the human pseudogenes identified here represent only a small fraction of the total, which probably exceeds the number of genes.

Millions of years of evolution preserved: a comprehensive catalog of the processed pseudogenes in the human genome

Processed pseudogenes were created by reverse-transcription of mRNAs; they provide snapshots of ancient genes existing millions of years ago in the genome. To find them in the present-day human, we developed a pipeline using features such as intron-absence, frame-disruption, polyadenylation, and truncation. This has enabled us to identify in recent genome drafts approximately 8000 processed pseudogenes (distributed from http://pseudogene.org). Overall, processed pseudogenes are very similar to their closest corresponding human gene, being 94% complete in coding regions, with sequence similarity of 75% for amino acids and 86% for nucleotides. Their chromosomal distribution appears random and dispersed, with the numbers on chromosomes proportional to length, suggesting sustained "bombardment" over evolution. However, it does vary with GC-content: Processed pseudogenes occur mostly in intermediate GC-content regions. This is similar to Alus but contrasts with functional genes and L1-repeats. Pseudogenes, moreover, have age profiles similar to Alus. The number of pseudogenes associated with a given gene follows a power-law relationship, with a few genes giving rise to many pseudogenes and most giving rise to few. The prevalence of processed pseudogenes agrees well with germ-line gene expression. Highly expressed ribosomal proteins account for approximately 20% of the total. Other notables include cyclophilin-A, keratin, GAPDH, and cytochrome c.

The Structure and Early Evolution of Recently Arisen Gene Duplicates in theCaenorhabditis elegansGenome

The significance of gene duplication in provisioning raw materials for the evolution of genomic diversity is widely recognized, but the early evolutionary dynamics of duplicate genes remain obscure. To elucidate the structural characteristics of newly arisen gene duplicates at infancy and their subsequent evolutionary properties, we analyzed gene pairs with ≤10% divergence at synonymous sites within the genome of Caenorhabditis elegans. Structural heterogeneity between duplicate copies is present very early in their evolutionary history and is maintained over longer evolutionary timescales, suggesting that duplications across gene boundaries in conjunction with shuffling events have at least as much potential to contribute to long-term evolution as do fully redundant (complete) duplicates. The median duplication span of 1.4 kb falls short of the average gene length in C. elegans (2.5 kb), suggesting that partial gene duplications are frequent. Most gene duplicates reside close to the parent copy at inception, often as tandem inverted loci, and appear to disperse in the genome as they age, as a result of reduced survivorship of duplicates located in proximity to the ancestral copy. We propose that illegitimate recombination events leading to inverted duplications play a disproportionately large role in gene duplication within this genome in comparison with other mechanisms.

GENEANNOTATION: PREDICTION ANDTESTING

Fifty years after the publication of DNA structure, the whole human genome sequence will be officially finished. This achievement marks the beginning of the task to catalogue every human gene and identify each of their function expression patterns. Currently, researchers estimate that there are about 30,000 human genes and approximately 70% of these can be automatically predicted using a combination of ab initio and similarity-based programs. However, to experimentally investigate every gene's function, the research community requires a high-quality annotation of alternative splicing, pseudogenes, and promoter regions that can only be provided by manual intervention. Manual curation of the human genome will be a long-term project as experimental data are continually produced to confirm or refine the predictions, and new features such as noncoding RNAs and enhancers have not been fully identified. Such a highly curated human gene-set made publicly available will be a great asset for the experimental community and for future comparative genome projects.

Multiple ace genes encoding acetylcholinesterases of Caenorhabditis elegans have distinct tissue expression

ace-1 and ace-2 genes encoding acetylcholinesterase in the nematode Caenorhabditis elegans present 35% identity in coding sequences but no homology in noncoding regions (introns, 5'- and 3'-untranslated regions). A 5'-region of ace-2 was defined by rescue of ace-1;ace-2 mutants. When green fluorescent protein (GFP) expression was driven by this regulatory region, the resulting pattern was distinct from that of ace-1. This latter gene is expressed in all body-wall and vulval muscle cells (Culetto et al., 1999), whereas ace-2 is expressed almost exclusively in neurons. ace-3 and ace-4 genes are located in close proximity on chromosome II (Combes et al., 2000). These two genes were first transcribed in vivo as a bicistronic messenger and thus constitute an ace-3;ace-4 operon. However, there was a very low level of monocistronic mRNA of ace-4 (the upstream gene) in vivo, and no ACE-4 enzymatic activity was ever detected. GFP expression driven by a 5' upstream region of the ace-3;ace-4 operon was detected in several muscle cells of the pharynx (pm3, pm4, pm5 and pm7) and in the two canal associated neurons (CAN cells). A dorsal row of body-wall muscle cells was intensively labelled in larval stages but no longer detected in adults. The distinct tissue-specific expression of ace-1, ace-2 and ace-3 (coexpressed only in pm5 cells) indicates that ace genes are not redundant.

Effects of recombination rate and gene density on transposable element distributions in Arabidopsis thaliana

Transposable elements (TEs) comprise a major component of eukaryotic genomes, and exhibit striking deviations from random distribution across the genomes studied, including humans, flies, nematodes, and plants. Although considerable progress has been made in documenting these patterns, the causes are subject to debate. Here, we use the genome sequence of Arabidopsis thaliana to test for the importance of competing models of natural selection against TE insertions. We show that, despite TE accumulation near the centromeres, recombination does not generally correlate with TE abundance, suggesting that selection against ectopic recombination does not influence TE distribution in A. thaliana. In contrast, a consistent negative correlation between gene density and TE abundance, and a strong under-representation of TE insertions in introns suggest that selection against TE disruption of gene expression is playing a more important role in A. thaliana. High rates of self-fertilization may reduce the importance of recombination rate in genome structuring in inbreeding organisms such as A. thaliana and Caenorhabditis elegans.

C. elegans ORFeome version 1.1: experimental verification of the genome annotation and resource for proteome-scale protein expression

To verify the genome annotation and to create a resource to functionally characterize the proteome, we attempted to Gateway-clone all predicted protein-encoding open reading frames (ORFs), or the 'ORFeome,' of Caenorhabditis elegans. We successfully cloned approximately 12,000 ORFs (ORFeome 1.1), of which roughly 4,000 correspond to genes that are untouched by any cDNA or expressed-sequence tag (EST). More than 50% of predicted genes needed corrections in their intron-exon structures. Notably, approximately 11,000 C. elegans proteins can now be expressed under many conditions and characterized using various high-throughput strategies, including large-scale interactome mapping. We suggest that similar ORFeome projects will be valuable for other organisms, including humans.

Identification of pseudogenes in the Drosophila melanogaster genome

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.

Digging deep for ancient relics: a survey of protein motifs in the intergenic sequences of four eukaryotic genomes

We have examined conserved protein motifs in the non-coding, intergenic regions ("pseudomotif patterns") and surveyed their occurrence in the fly, worm, yeast and human genomes (chromosomes 21 and 22 only). To identify these patterns, we masked out annotated genes, pseudogenes and repeat regions from the raw genomic sequence and then compared the remaining sequence, in six-frame translation, against 1319 patterns from the PROSITE database. For each pseudomotif pattern, the absolute number of occurrences is not very informative unless compared against a statistical expectation; consequently, we calculated the expected occurrence of each pattern using a Poisson model and verified this with simulations. Using a p-value cut-off of 0.01, we found 67 pseudomotif patterns over-represented in fly intergenic regions, 34 in worm, 21 in human and six in yeast. These include the zinc finger, leucine zipper, nucleotide-binding motif and EGF domain. Many of the over-represented patterns were common to two or more organisms, but there were a few that were unique to specific ones. Furthermore, we found more over-represented patterns in the fly than in the worm, although the fly has fewer pseudogenes. This puzzling observation can be explained by a higher deletion rate in the fly genome. We also surveyed under-represented patterns, finding 23 in the fly, 12 in the worm, 18 in human and two in yeast. If intergenic sequences were truly random, we would expect an equal number of over and under-represented patterns. The fact that for each organism the number of over-represented patterns is greater than the number of under-represented ones implies that a fraction of the intergenic regions consist of ancient protein fragments that, due to accumulated disablements, have become unrecognizable by conventional techniques for gene and pseudogene identification. Moreover, we find that in aggregate the over-represented pseudomotif patterns occupy a substantial fraction of the intergenic regions. Further information is available at http://pseudogene.org

Global perspectives on proteins: comparing genomes in terms of folds, pathways and beyond

The sequencing of complete genomes provides us with a global view of all the proteins in an organism. Proteomic analysis can be done on a purely sequence-based level, with a focus on finding homologues and grouping them into families and clusters of orthologs. However, incorporating protein structure into this analysis provides valuable simplification; it allows one to collect together very distantly related sequences, thus condensing the proteome into a minimal number of 'parts.' We describe issues related to surveying proteomes in terms of structural parts, including methods for fold assignment and formats for comparisons (eg top-10 lists and whole-genome trees), and show how biases in the databases and in sampling can affect these surveys. We illustrate our main points through a case study on the unique protein properties evident in many thermophile genomes (eg more salt bridges). Finally, we discuss metabolic pathways as an even greater simplification of genomes. In comparison to folds these allow the organization of many more genes into coherent systems, yet can nevertheless be understood in many of the same terms.

GenomeHistory: a software tool and its application to fully sequenced genomes

We present a publicly available software tool (http://www.unm.edu/~compbio/software/GenomeHistory) that identifies all pairs of duplicate genes in a genome and then determines the degree of synonymous and non-synonymous divergence between each duplicate pair. Using this tool, we analyze the relations between (i) gene function and the propensity of a gene to duplicate and (ii) the number of genes in a gene family and the family's rate of sequence evolution. We do so for the complete genomes of four eukaryotes (fission and budding yeast, fruit fly and nematode) and one prokaryote (Escherichia coli). For some classes of genes we observe a strong relationship between gene function and a gene's propensity to undergo duplication. Most notably, ribosomal genes and transcription factors appear less likely to undergo gene duplication than other genes. In both fission and budding yeast, we see a strong positive correlation between the selective constraint on a gene and the size of the gene family of which this gene is a member. In contrast, a weakly negative such correlation is seen in multicellular eukaryotes.

A systematic investigation identifies a significant number of probable pseudogenes in the Escherichia coli genome

Pseudogenes are open reading frames (ORFs) encoding dysfunctional proteins with high homology to known protein-coding genes. Although pseudogenes were reported to exist in the genomes of many eukaryotes and bacteria, no systematic search for pseudogenes in the Escherichia coli genome has been carried out. Genome comparisons of E. coli strains K-12 and O157 revealed that many protein-coding sequences have prematurely terminated orthologs encoding unstable proteins. To systematically screen for pseudogenes, we selected ORFs generated by premature termination of the orthologous protein-coding genes and subsequently excluded those possibly arising from sequence errors. Lastly we eliminated those with close homologs in this and other species, as these shortened ORFs may actually have functions. The process produced 95 and 101 pseudogene candidates in K-12 and O157, respectively. The assigned three-dimensional structures suggest that most of the encoded proteins cannot fold properly and thus are dysfunctional, indicating that they are probably pseudogenes. Therefore, the existence of a significant number of probable pseudogenes in E. coli is predicted, awaiting experimental verification. Most of them were found to be genes with paralogs or horizontally transferred genes or both. We suggest that pseudogenes constitute a small fraction of the genomes of free-living bacteria in general, reflecting the faster elimination than production of pseudogenes.

Comprehensive analysis of amino acid and nucleotide composition in eukaryotic genomes, comparing genes and pseudogenes

Based on searches for disabled homologs to known proteins, we have identified a large population of pseudogenes in four sequenced eukaryotic genomes-the worm, yeast, fly and human (chromosomes 21 and 22 only). Each of our nearly 2500 pseudogenes is characterized by one or more disablements mid-domain, such as premature stops and frameshifts. Here, we perform a comprehensive survey of the amino acid and nucleotide composition of these pseudogenes in comparison to that of functional genes and intergenic DNA. We show that pseudogenes invariably have an amino acid composition intermediate between genes and translated intergenic DNA. Although the degree of intermediacy varies among the four organisms, in all cases, it is most evident for amino acid types that differ most in occurrence between genes and intergenic regions. The same intermediacy also applies to codon frequencies, especially in the worm and human. Moreover, the intermediate composition of pseudogenes applies even though the composition of the genes in the four organisms is markedly different, showing a strong correlation with the overall A/T content of the genomic sequence. Pseudogenes can be divided into 'ancient' and 'modern' subsets, based on the level of sequence identity with their closest matching homolog (within the same genome). Modern pseudogenes usually have a much closer sequence composition to genes than ancient pseudogenes. Collectively, our results indicate that the composition of pseudogenes that are under no selective constraints progressively drifts from that of coding DNA towards non-coding DNA. Therefore, we propose that the degree to which pseudogenes approach a random sequence composition may be useful in dating different sets of pseudogenes, as well as to assess the rate at which intergenic DNA accumulates mutations. Our compositional analyses with the interactive viewer are available over the web at http://genecensus.org/pseudogene.

Mutational equilibrium model of genome size evolution

The paper describes a mutational equilibrium model of genome size evolution. This model is different from both adaptive and junk DNA models of genome size evolution in that it does not assume that genome size is maintained either by positive or stabilizing selection for the optimum genome size (as in adaptive theories) or by purifying selection against too much junk DNA (as in junk DNA theories). Instead the genome size is suggested to evolve until the loss of DNA through more frequent small deletions is equal to the rate of DNA gain through more frequent long insertions. The empirical basis for this theory is the finding of a strong correlation and of a clear power-function relationship between the rate of mutational DNA loss (per bp) through small deletions and genome size in animals. Genome size scales as a negative 1.3 power function of the deletion rate per nucleotide. Such a relationship is not predicted by either adaptive or junk DNA theories. However, if genome size is maintained at equilibrium by the balance of mutational forces, this empirilical relationship can be readily accommodated. Within this framework, this finding would imply that the rate of DNA gain through large insertions scales up a quarter-power function of genome size. On this view, as genome size grows, the rate of growth through large insertions is increasing as a quarter power function of genome size and the rate of DNA loss through small deletions increases linearly, until eventually, at the stable equilibrium genome size value, rates of growth and loss equal each other. The current data also suggest that the long-term variation is genome size in animals is brought about to a significant extent by changes in the intrinsic rates of DNA loss through small deletions. Both the origin of mutational biases and the adaptive consequences of such a mode of evolution of genome size are discussed.

Did evolution leap to create the protein universe?

The genomes of over 60 organisms from all three kingdoms of life are now entirely sequenced. In many respects, the inventory of proteins used in different kingdoms appears surprisingly similar. However, eukaryotes differ from other kingdoms in that they use many long proteins, and have more proteins with coiled-coil helices and with regions abundant in regular secondary structure. Particular structural domains are used in many pathways. Nevertheless, one domain tends to occur only once in one particular pathway. Many proteins do not have close homologues in different species (orphans) and there could even be folds that are specific to one species. This view implies that protein fold space is discrete. An alternative model suggests that structure space is continuous and that modern proteins evolved by aggregating fragments of ancient proteins. Either way, after having harvested proteomes by applying standard tools, the challenge now seems to be to develop better methods for comparative proteomics.

Studying genomes through the aeons: protein families, pseudogenes and proteome evolution

Protein families can be used to understand many aspects of genomes, both their "live" and their "dead" parts (i.e. genes and pseudogenes). Surveys of genomes have revealed that, in every organism, there are always a few large families and many small ones, with the overall distribution following a power-law. This commonality is equally true for both genes and pseudogenes, and exists despite the fact that the specific families that are enlarged differ greatly between organisms. Furthermore, because of family structure there is great redundancy in proteomes, a fact linked to the large number of dispensable genes for each organism and the small size of the minimal, indispensable sub-proteome. Pseudogenes in prokaryotes represent families that are in the process of being dispensed with. In particular, the genome sequences of certain pathogenic bacteria (Mycobacterium leprae, Yersinia pestis and Rickettsia prowazekii) show how an organism can undergo reductive evolution on a large scale (i.e. the dying out of families) as a result of niche change. There appears to be less pressure to delete pseudogenes in eukaryotes. These can be divided into two varieties, duplicated and processed, where the latter involves reverse transcription from an mRNA intermediate. We discuss these collectively in yeast, worm, fly, and human. The fly has few pseudogenes apparently because of its high rate of genomic DNA deletion. In the other three organisms, the distribution of pseudogenes on the chromosome and amongst different families is highly non-uniform. Pseudogenes tend not to occur in the middle of chromosome arms, and tend to be associated with lineage-specific (as opposed to highly conserved) families that have environmental-response functions. This may be because, rather than being dead, they may form a reservoir of diverse "extra parts" that can be resurrected to help an organism adapt to its surroundings. In yeast, there may be a novel mechanism involving the [PSI+] prion that potentially enables this resurrection. In worm, the pseudogenes tend to arise out of families (e.g. chemoreceptors) that are greatly expanded in it compared to the fly. The human genome stands out in having many processed pseudogenes. These have a character very different from those of the duplicated variety, to a large extent just representing random insertions. Thus, their occurrence tends to be roughly in proportion to the amount of mRNA for a particular protein and to reflect the extent of the intergenic sequences. Further information about pseudogenes is available at http://genecensus.org/pseudogene

Evidence Suggesting That a Fifth of Annotated Caenorhabditis elegans Genes May Be Pseudogenes

Only a minority of the genes, identified in theCaenorhabditis elegans genome sequence data by computer analysis, have been characterized experimentally. We attempted to determine the expression patterns for a random sample of the annotated genes using reporter gene fusions. A low success rate was obtained for evolutionarily recently duplicated genes. Analysis of the data suggests that this is not due to conditional or low-level expression. The remaining explanation is that most of the annotated genes in the recently duplicated category are pseudogenes, a proportion corresponding to 20% of all of the annotated C. elegansgenes. Further support for this surprisingly high figure was sought by comparing sequences for families of recently duplicated C. elegans genes. Although only a preliminary analysis, clear evidence for a gene having been recently inactivated by genetic drift was found for many genes in the recently duplicated category. At least 4% of the annotated C. elegans genes can be recognized as pseudogenes simply from closer inspection of the sequence data. Lessons learned in identifying pseudogenes in C. elegans could be of value in the annotation of the genomes of other species where, although there may be fewer pseudogenes, they may be harder to detect.

[Online supplementary material available atwww.genome.org.]

SNPs on human chromosomes 21 and 22 -- analysis in terms of protein features and pseudogenes

SNPs are useful for genome-wide mapping and the study of disease genes. Previous studies have focused on SNPs in specific genes or SNPs pooled from a variety of different sources. Here, a systematic approach to the analysis of SNPs in relation to various features on a genome-wide scale, with emphasis on protein features and pseudogenes, is presented. We have performed a comprehensive analysis of 39,408 SNPs on human chromosomes 21 and 22 from the SNP consortium (TSC) database, where SNPs are obtained by random sequencing using consistent and uniform methods. Our study indicates that the occurrence of SNPs is lowest in exons and higher in repeats, introns and pseudogenes. Moreover, in comparing genes and pseudogenes, we find that the SNP density is higher in pseudogenes and the ratio of nonsynonymous to synonymous changes is also much higher. These observations may be explained by the increased rate of SNP accumulation in pseudogenes, which presumably are not under selective pressure. We have also performed secondary structure prediction on all coding regions and found that there is no preferential distribution of SNPs in a -helices, b -sheets or coils. This could imply that protein structures, in general, can tolerate a wide degree of substitutions. Tables relating to our results are available from http://genecensus.org/pseudogene.

Evidence suggesting that a fifth of annotated Caenorhabditis elegans genes may be pseudogenes

Only a minority of the genes, identified in the Caenorhabditis elegans genome sequence data by computer analysis, have been characterized experimentally. We attempted to determine the expression patterns for a random sample of the annotated genes using reporter gene fusions. A low success rate was obtained for evolutionarily recently duplicated genes. Analysis of the data suggests that this is not due to conditional or low-level expression. The remaining explanation is that most of the annotated genes in the recently duplicated category are pseudogenes, a proportion corresponding to 20% of all of the annotated C. elegans genes. Further support for this surprisingly high figure was sought by comparing sequences for families of recently duplicated C. elegans genes. Although only a preliminary analysis, clear evidence for a gene having been recently inactivated by genetic drift was found for many genes in the recently duplicated category. At least 4% of the annotated C. elegans genes can be recognized as pseudogenes simply from closer inspection of the sequence data. Lessons learned in identifying pseudogenes in C. elegans could be of value in the annotation of the genomes of other species where, although there may be fewer pseudogenes, they may be harder to detect.

Recognizing shorter coding regions of human genes based on the statistics of stop codons

With the quick progress of the Human Genome Project, a great amount of uncharacterized DNA sequences needs to be annotated copiously by better algorithms. Recognizing shorter coding sequences of human genes is one of the most important problems in gene recognition, which is not yet completely solved. This paper is devoted to solving the issue using a new method. The distributions of the three stop codons, i.e., TAA, TAG and TGA, in three phases along coding, noncoding, and intergenic sequences are studied in detail. Using the obtained distributions and other coding measures, a new algorithm for the recognition of shorter coding sequences of human genes is developed. The accuracy of the algorithm is tested based on a larger database of human genes. It is found that the average accuracy achieved is as high as 92.1% for the sequences with length of 192 base pairs, which is confirmed by sixfold cross-validation tests. It is hoped that by incorporating the present method with some existing algorithms, the accuracy for identifying human genes from unannotated sequences would be increased.

A question of size: the eukaryotic proteome and the problems in defining it

We discuss the problems in defining the extent of the proteomes for completely sequenced eukaryotic organisms (i.e. the total number of protein-coding sequences), focusing on yeast, worm, fly and human. (i) Six years after completion of its genome sequence, the true size of the yeast proteome is still not defined. New small genes are still being discovered, and a large number of existing annotations are being called into question, with these questionable ORFs (qORFs) comprising up to one-fifth of the 'current' proteome. We discuss these in the context of an ideal genome-annotation strategy that considers the proteome as a rigorously defined subset of all possible coding sequences ('the orfome'). (ii) Despite the greater apparent complexity of the fly (more cells, more complex physiology, longer lifespan), the nematode worm appears to have more genes. To explain this, we compare the annotated proteomes of worm and fly, relating to both genome-annotation and genome evolution issues. (iii) The unexpectedly small size of the gene complement estimated for the complete human genome provoked much public debate about the nature of biological complexity. However, in the first instance, for the human genome, the relationship between gene number and proteome size is far from simple. We survey the current estimates for the numbers of human genes and, from this, we estimate a range for the size of the human proteome. The determination of this is substantially hampered by the unknown extent of the cohort of pseudogenes ('dead' genes), in combination with the prevalence of alternative splicing. (Further information relating to yeast is available at http://genecensus.org/yeast/orfome)

A small reservoir of disabled ORFs in the yeast genome and its implications for the dynamics of proteome evolution

We surveyed the sequenced Saccharomyces cerevisiae genome (strain S288C) comprehensively for open reading frames (ORFs) that could encode full-length proteins but contain obvious mid-sequence disablements (frameshifts or premature stop codons). These pseudogenic features are termed disabled ORFs (dORFs). Using homology to annotated yeast ORFs and non-yeast proteins plus a simple region extension procedure, we have found 183 dORFs. Combined with the 38 existing annotations for potential dORFs, we have a total pool of up to 221 dORFs, corresponding to less than approximately 3% of the proteome. Additionally, we found 20 pairs of annotated ORFs for yeast that could be merged into a single ORF (termed a mORF) by read-through of the intervening stop codon, and may comprise a complete ORF in other yeast strains. Focussing on a core pool of 98 dORFs with a verifying protein homology, we find that most dORFs are substantially decayed, with approximately 90% having two or more disablements, and approximately 60% having four or more. dORFs are much more yeast-proteome specific than live yeast genes (having about half the chance that they are related to a non-yeast protein). They show a dramatically increased density at the telomeres of chromosomes, relative to genes. A microarray study shows that some dORFs are expressed even though they carry multiple disablements, and thus may be more resistant to nonsense-mediated decay. Many of the dORFs may be involved in responding to environmental stresses, as the largest functional groups include growth inhibition, flocculation, and the SRP/TIP1 family. Our results have important implications for proteome evolution. The characteristics of the dORF population suggest the sorts of genes that are likely to fall in and out of usage (and vary in copy number) in a strain-specific way and highlight the role of subtelomeric regions in engendering this diversity. Our results also have important implications for the effects of the [PSI+] prion. The dORFs disabled by only a single stop and the mORFs (together totalling 35) provide an estimate for the extent of the sequence population that can be resurrected readily through the demonstrated ability of the [PSI+] prion to cause nonsense-codon read-through. Also, the dORFs and mORFs that we find have properties (e.g. growth inhibition, flocculation, vanadate resistance, stress response) that are potentially related to the ability of [PSI+] to engender substantial phenotypic variation in yeast strains under different environmental conditions. (See genecensus.org/pseudogene for further information.)

Genome and protein evolution in eukaryotes

The past year has seen the completion of the genome sequence of the flowering plant Arabidopsis thaliana and the initial sequence reports of the human genome. The availability of completely sequenced eukaryotic genomes from disparate phylogenetic lineages has opened the door to comparative analyses and a better understanding of the evolutionary processes shaping genomes. Complex many-to-many relationships between genes from different species appear to be the norm, suggesting that transfer of detailed functional annotation will not be straightforward. In addition to expansion and contraction of gene families, new genes evolve from recombination of pre-existing domains, although some domain families do appear to have evolved recently and to be specific to restricted phylogenetic lineages. The overall picture is of a huge diversity of gene content within eukaryotic genomes, reflecting different functional demands in different species.

Molecular fossils in the human genome: identification and analysis of the pseudogenes in chromosomes 21 and 22

We have developed an initial approach for annotating and surveying pseudogenes in the human genome. We search human genomic DNA for regions that are similar to known protein sequences and contain obvious disablements (i.e., mid-sequence stop codons or frameshifts), while ensuring minimal overlap with annotations of known genes. Pseudogenes can be divided into "processed" and "nonprocessed"; the former are reverse transcribed from mRNA (and therefore have no intron structure), whereas the latter presumably arise from genomic duplications. We annotate putative processed pseudogenes based on whether there is a continuous span of homology that is >70% of the length of the closest matching human protein (i.e., with introns removed), or whether there is evidence of polyadenylation. We have applied our approach to chromosomes 21 and 22, the first parts of the human genome completely sequenced, finding 190 new pseudogene annotations beyond the 264 reported by the sequencing centers. In total, on chromosomes 21 and 22, there are 189 processed pseudogenes, 195 nonprocessed pseudogenes, and, additionally, 70 pseudogenic immunoglobulin gene segments. (Detailed assignments are available at http://bioinfo.mbb.yale.edu/genome/pseudogene or http://genecensus.org/pseudogene.) By extrapolation, we predict that there could be up to approximately 20,000 pseudogenes in the whole human genome, with a little more than half of them processed. We have determined the main populations and clusters of pseudogenes on chromosomes 21 and 22. There are notable excesses of pseudogenes relative to genes near the centromeres of both chromosomes, indicating the existence of pseudogenic "hot-spots" in the genome. We have looked at the distribution of InterPro families and Gene Ontology (GO) functional categories in our pseudogenes. Overall, the families in both processed and nonprocessed pseudogene populations occur according to a similar power-law distribution as that found for the occurrence of gene families, with a few big families and many small ones. The processed population is, in particular, enriched in highly expressed ribosomal-protein sequences (approximately 20%), which appear fairly evenly distributed across the chromosomes. We compared processed pseudogenes of different evolutionary ages, observing a high degree of similarity between "ancient" and "modern" subpopulations. This may be attributable to the consistently high expression of ribosomal proteins over evolutionary time. Finally, we find that chromosome 22 pseudogene population is dominated by immunoglobulin segments, which have a greater rate of disablement per amino acid than the other pseudogene populations and are also substantially more diverged.

The dominance of the population by a selected few: power-law behaviour applies to a wide variety of genomic properties

BACKGROUND

The sequencing of genomes provides us with an inventory of the 'molecular parts' in nature, such as protein families and folds, and their functions in living organisms. Through the analysis of such inventories, it has been shown that different genomes have very different usage of parts; for example, the common folds in the worm are very different from those in Escherichia coli.

RESULTS

Despite these differences, we find that the genomic occurrence of generalized parts follows a well-known mathematical framework called the power law, with a few parts occurring many times and most occurring only a few times. This observation is true in a wide variety of genomic contexts. Earlier studies found power laws in a few specific cases, such as the occurrence of protein families. Here, we find many further cases of power-law behavior, for example in the occurrence of pseudogenes and in levels of gene expression. We show comprehensively that this behavior applies across many different genomes, for many different types of parts (DNA words, InterPro families, protein superfamilies and folds, pseudogene families and pseudomotifs), and for the many disparate attributes associated with these parts (their functions, interactions and expression levels).

CONCLUSIONS

Power-law behavior provides a concise mathematical description of an important biological feature: the sheer dominance of a few members over the overall population. We present this behavior in a unified framework and propose that all these observations are connected to an underlying DNA duplication process as genomes evolved to their current state.

The transposable elements of the Drosophila melanogaster euchromatin: a genomics perspective

BACKGROUND

Transposable elements are found in the genomes of nearly all eukaryotes. The recent completion of the Release 3 euchromatic genomic sequence of Drosophila melanogaster by the Berkeley Drosophila Genome Project has provided precise sequence for the repetitive elements in the Drosophila euchromatin. We have used this genomic sequence to describe the euchromatic transposable elements in the sequenced strain of this species.

RESULTS

We identified 85 known and eight novel families of transposable element varying in copy number from one to 146. A total of 1,572 full and partial transposable elements were identified, comprising 3.86% of the sequence. More than two-thirds of the transposable elements are partial. The density of transposable elements increases an average of 4.7 times in the centromere-proximal regions of each of the major chromosome arms. We found that transposable elements are preferentially found outside genes; only 436 of 1,572 transposable elements are contained within the 61.4 Mb of sequence that is annotated as being transcribed. A large proportion of transposable elements is found nested within other elements of the same or different classes. Lastly, an analysis of structural variation from different families reveals distinct patterns of deletion for elements belonging to different classes.

CONCLUSIONS

This analysis represents an initial characterization of the transposable elements in the Release 3 euchromatic genomic sequence of D. melanogaster for which comparison to the transposable elements of other organisms can begin to be made. These data have been made available on the Berkeley Drosophila Genome Project website for future analyses.

Beyond synexpression relationships: local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions

The complexity of biological systems provides for a great diversity of relationships between genes. The current analysis of whole-genome expression data focuses on relationships based on global correlation over a whole time-course, identifying clusters of genes whose expression levels simultaneously rise and fall. There are, of course, other potential relationships between genes, which are missed by such global clustering. These include activation, where one expects a time-delay between related expression profiles, and inhibition, where one expects an inverted relationship. Here, we propose a new method, which we call local clustering, for identifying these time-delayed and inverted relationships. It is related to conventional gene-expression clustering in a fashion analogous to the way local sequence alignment (the Smith-Waterman algorithm) is derived from global alignment (Needleman-Wunsch). An integral part of our method is the use of random score distributions to assess the statistical significance of each cluster. We applied our method to the yeast cell-cycle expression dataset and were able to detect a considerable number of additional biological relationships between genes, beyond those resulting from conventional correlation. We related these new relationships between genes to their similarity in function (as determined from the MIPS scheme) or their having known protein-protein interactions (as determined from the large-scale two-hybrid experiment); we found that genes strongly related by local clustering were considerably more likely than random to have a known interaction or a similar cellular role. This suggests that local clustering may be useful in functional annotation of uncharacterized genes. We examined many of the new relationships in detail. Some of them were already well-documented examples of inhibition or activation, which provide corroboration for our results. For instance, we found an inverted expression profile relationship between genes YME1 and YNT20, where the latter has been experimentally documented as a bypass suppressor of the former. We also found new relationships involving uncharacterized yeast genes and were able to suggest functions for many of them. In particular, we found a time-delayed expression relationship between J0544 (which has not yet been functionally characterized) and four genes associated with the mitochondria. This suggests that J0544 may be involved in the control or activation of mitochondrial genes. We have also looked at other, less extensive datasets than the yeast cell-cycle and found further interesting relationships. Our clustering program and a detailed website of clustering results is available at http://www.bioinfo.mbb.yale.edu/expression/cluster (or http://www.genecensus.org/expression/cluster).

On new hypotheses about autosomal dominant polycystic kidney disease type 1

The purpose of this paper is to suggest a partial explanation of the aetiology of autosomal dominant polycystic kidney disease type 1, one of the most common genetic diseases in humans. To this aim we put forward a number of interconnected ideas, based on a number of experimental evidences and plausibility arguments. We stress the major role played by the instability of some genomic tandem repeats, together with the DNA structures known as quadruplexes, the pseudogenes and the gene conversion. The model we propose can be considered a multi-hit generalization of the well-known two-hit model, a generalization that could well have a validity also outside the specific context. We finally provide an indication of the likely guilty DNA segment for the above disease, and we propose a possible simple experimental line of action aimed to confirm or disproof our suggestion.

Complementary expression patterns of six nonessential Caenorhabditis elegans core 2/I N-acetylglucosaminyltransferase homologues

The Caenorhabditis elegans genome contains 18 sequences related to mammalian core 2/I N-acetylglucosaminyltransferases. The six most closely related genes (gly-1 and gly-15 to gly-19) likely encode active enzymes, because are all transcribed and do not appear to be pseudogenes. Polypeptide divergence and the gene structures are both concordant with a common ancestor at the time of radiation from mammals that underwent three rounds of duplication and, most recently, a tandem duplication. Polypeptide alignments with mammalian homologues do not indicate whether the enzyme specificities are core 2, 4, or I-like or novel, but do clearly demonstrate the secondary structure characteristics of glycosyltransferases. The six homologues have essentially nonoverlapping expression patterns, unrelated by tissue type or cell lineage. The extent varies widely; gly-15 is expressed only in two gland cells, whereas gly-18 is broadly expressed in diverse cell types. gly-1, -15, -18 and -19 are expressed during adulthood; gly-16 and gly-17 appear to be restricted to embryonic or early larval stages. The parsimonious interpretation of the expression pattern and sequence data is that the catalytic activities are similar but with diverged promoters. Null alleles of three of the genes were generated without causing gross abnormality in homozygous animals. RNA-mediated interference experiments also failed to induce defects in the four genes tested. Nevertheless, the nematode has evolved six diverged core 2 GlcNAc-T-like genes, and we postulate that these arose in response to selection pressures to which C. elegans is not ordinarily subjected in the laboratory.

Annotation transfer for genomics: measuring functional divergence in multi-domain proteins

Annotation transfer is a principal process in genome annotation. It involves "transferring" structural and functional annotation to uncharacterized open reading frames (ORFs) in a newly completed genome from experimentally characterized proteins similar in sequence. To prevent errors in genome annotation, it is important that this process be robust and statistically well-characterized, especially with regard to how it depends on the degree of sequence similarity. Previously, we and others have analyzed annotation transfer in single-domain proteins. Multi-domain proteins, which make up the bulk of the ORFs in eukaryotic genomes, present more complex issues in functional conservation. Here we present a large-scale survey of annotation transfer in these proteins, using scop superfamilies to define domain folds and a thesaurus based on SWISS-PROT keywords to define functional categories. Our survey reveals that multi-domain proteins have significantly less functional conservation than single-domain ones, except when they share the exact same combination of domain folds. In particular, we find that for multi-domain proteins, approximate function can be accurately transferred with only 35% certainty for pairs of proteins sharing one structural superfamily. In contrast, this value is 67% for pairs of single-domain proteins sharing the same structural superfamily. On the other hand, if two multi-domain proteins contain the same combination of two structural superfamilies the probability of their sharing the same function increases to 80% in the case of complete coverage along the full length of both proteins, this value increases further to > 90%. Moreover, we found that only 70 of the current total of 455 structural superfamilies are found in both single and multi-domain proteins and only 14 of these were associated with the same function in both categories of proteins. We also investigated the degree to which function could be transferred between pairs of multi-domain proteins with respect to the degree of sequence similarity between them, finding that functional divergence at a given amount of sequence similarity is always about two-fold greater for pairs of multi-domain proteins (sharing similarity over a single domain) in comparison to pairs of single-domain ones, though the overall shape of the relationship is quite similar. Further information is available at http://partslist.org/func or http://bioinfo.mbb.yale.edu/partslist/func.

Interrelating different types of genomic data, from proteome to secretome: 'oming in on function

With the completion of genome sequences, the current challenge for biology is to determine the functions of all gene products and to understand how they contribute in making an organism viable. For the first time, biological systems can be viewed as being finite, with a limited set of molecular parts. However, the full range of biological processes controlled by these parts is extremely complex. Thus, a key approach in genomic research is to divide the cellular contents into distinct sub-populations, which are often given an "-omic" term. For example, the proteome is the full complement of proteins encoded by the genome, and the secretome is the part of it secreted from the cell. Carrying this further, we suggest the term "translatome" to describe the members of the proteome weighted by their abundance, and the "functome" to describe all the functions carried out by these. Once the individual sub-populations are defined and analyzed, we can then try to reconstruct the full organism by interrelating them, eventually allowing for a full and dynamic view of the cell. All this is, of course, made possible because of the increasing amount of large-scale data resulting from functional genomics experiments. However, there are still many difficulties resulting from the noisiness and complexity of the information. To some degree, these can be overcome through averaging with broad proteomic categories such as those implicit in functional and structural classifications. For illustration, we discuss one example in detail, interrelating transcript and cellular protein populations (transcriptome and translatome). Further information is available at http://bioinfo.mbb.yale.edu/what-is-it.

Advances in sequence analysis

In its early days, the entire field of computational biology revolved almost entirely around biological sequence analysis. Over the past few years, however, a number of new non-sequence-based areas of investigation have become mainstream, from the analysis of gene expression data from microarrays, to whole-genome association discovery, and to the reverse engineering of gene regulatory pathways. Nonetheless, with the completion of private and public efforts to map the human genome, as well as those of other organisms, sequence data continue to be a veritable mother lode of valuable biological information that can be mined in a variety of contexts. Furthermore, the integration of sequence data with a variety of alternative information is providing valuable and fundamentally new insight into biological processes, as well as an array of new computational methodologies for the analysis of biological data.

PartsList: a web-based system for dynamically ranking protein folds based on disparate attributes, including whole-genome expression and interaction information

As the number of protein folds is quite limited, a mode of analysis that will be increasingly common in the future, especially with the advent of structural genomics, is to survey and re-survey the finite parts list of folds from an expanding number of perspectives. We have developed a new resource, called PartsList, that lets one dynamically perform these comparative fold surveys. It is available on the web at http://bioinfo.mbb.yale.edu/partslist and http://www.partslist.org. The system is based on the existing fold classifications and functions as a form of companion annotation for them, providing 'global views' of many already completed fold surveys. The central idea in the system is that of comparison through ranking; PartsList will rank the approximately 420 folds based on more than 180 attributes. These include: (i) occurrence in a number of completely sequenced genomes (e.g. it will show the most common folds in the worm versus yeast); (ii) occurrence in the structure databank (e.g. most common folds in the PDB); (iii) both absolute and relative gene expression information (e.g. most changing folds in expression over the cell cycle); (iv) protein-protein interactions, based on experimental data in yeast and comprehensive PDB surveys (e.g. most interacting fold); (v) sensitivity to inserted transposons; (vi) the number of functions associated with the fold (e.g. most multi-functional folds); (vii) amino acid composition (e.g. most Cys-rich folds); (viii) protein motions (e.g. most mobile folds); and (ix) the level of similarity based on a comprehensive set of structural alignments (e.g. most structurally variable folds). The integration of whole-genome expression and protein-protein interaction data with structural information is a particularly novel feature of our system. We provide three ways of visualizing the rankings: a profiler emphasizing the progression of high and low ranks across many pre-selected attributes, a dynamic comparer for custom comparisons and a numerical rankings correlator. These allow one to directly compare very different attributes of a fold (e.g. expression level, genome occurrence and maximum motion) in the uniform numerical format of ranks. This uniform framework, in turn, highlights the way that the frequency of many of the attributes falls off with approximate power-law behavior (i.e. according to V(-b), for attribute value V and constant exponent b), with a few folds having large values and most having small values.

What does a worm want with 20,000 genes?

The number of genes predicted for the Caenorhabditis elegans genome is remarkably high: approximately 20,000, if both protein-coding and RNA-coding genes are counted. This article discusses possible explanations for such a high value.