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Zhaolei Zhang

Publications and source records attributed to Zhaolei Zhang.

At least 19 recordsLinked to original sources
PubMed2006

Pseudogene.org: a comprehensive database and comparison platform for pseudogene annotation.

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.

Databases, Genetic↗
PubMed2006

PseudoPipe: an automated pseudogene identification pipeline.

MOTIVATION: Mammalian genomes contain many 'genomic fossils' i.e. pseudogenes. These are disabled copies of functional genes that have been retained in the genome by gene duplication or retrotransposition events. Pseudogenes are important resources in understanding the evolutionary history of genes and genomes. RESULTS: We have developed a homology-based computational pipeline ('PseudoPipe') that can search a mammalian genome and identify pseudogene sequences in a comprehensive and consistent manner. The key steps in the pipeline involve using BLAST to rapidly cross-reference potential "parent" proteins against the intergenic regions of the genome and then processing the resulting "raw hits" -- i.e. eliminating redundant ones, clustering together neighbors, and associating and aligning clusters with a unique parent. Finally, pseudogenes are classified based on a combination of criteria including homology, intron-exon structure, and existence of stop codons and frameshifts.

Algorithms↗
PubMed2006

Enhancing the prediction of transcription factor binding sites by incorporating structural properties and nucleotide covariations.

A problem faced by many algorithms for finding transcription factor (TF) binding sites is the high number of false positive hits that result with the increased sensitivity of their prediction. A main contributing factor to this is the short and degenerate nature of these sites which results in a low signal-to-noise ratio. In order to counter this problem, one needs to look beyond the assumption that individual bases of a TF binding site act independently from each other when binding to a transcription factor. In this paper, we present a new method based on templates, designed to exploit the discriminatory features, nucleotide polymorphism, and structural homology present in TF binding sites for distinguishing them from nonbinding sites.

Binding Sites↗
PubMed2006

Accounting for structural properties and nucleotide co-variations in the quantitative prediction of binding affinities of protein-DNA interactions.

We describe a quantitative model for predicting the binding affinity of protein-DNA interactions. The described model is based on templates capable of providing a global representation of the modelled transcription factor (TF) binding sites. Templates can capture non independent nucleotide variations and structural properties present in these sites. Tests carried out on the p50p50 and p50p65 variants of the transcription factor NF-kappa B demonstrate a high correlation between the observed binding affinities and the binding affinities predicted by the templates. Only a small subset of training data spanning the space of the binding sites is required to train the templates.

Animals↗
PubMed2005

Alternative signaling pathways: when, where and why?

Alternative cell signal transduction pathways have been demonstrated in some experimental systems. The importance of their existence has not been completely appreciated. In this review we present the cases of alternative pathways resulted from a survey of the available experimental data. The alternative pathways could show different relationships, i.e., synergistic, redundant, additive, opposite and competitive effects. They could have distinct time courses and cell, organ, sex or species specification. Further, they could happen during physiological or pathological situations, and display differentiated sensitivity. These case studies together imply that alternative signal pathways could be involved in the regulation of cell functions at the pathway level. In-depth understanding of the importance of the alternative pathways will rely on building and exploration of mathematical models.

Sensitivity and Specificity↗
PubMed2005

Transcribed processed pseudogenes in the human genome: an intermediate form of expressed retrosequence lacking protein-coding ability.

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.

Amino Acid Sequence↗
PubMed2005

Integrated pseudogene annotation for human chromosome 22: evidence for transcription.

Pseudogenes are inheritable genetic elements formally defined by two properties: their similarity to functioning genes and their presumed lack of activity. However, their precise characterization, particularly with respect to the latter quality, has proven elusive. An opportunity to explore this issue arises from the recent emergence of tiling-microarray data showing that intergenic regions (containing pseudogenes) are transcribed to a great degree. Here we focus on the transcriptional activity of pseudogenes on human chromosome 22. First, we integrated several sets of annotation to define a unified list of 525 pseudogenes on the chromosome. To characterize these further, we developed a comprehensive list of genomic features based on conservation in related organisms, expression evidence, and the presence of upstream regulatory sites. Of the 525 unified pseudogenes we could confidently classify 154 as processed and 49 as duplicated. Using data from tiling microarrays, especially from recent high-resolution oligonucleotide arrays, we found some evidence that up to a fifth of the 525 pseudogenes are potentially transcribed. Expressed sequence tags (EST) comparison further validated a number of these, and overall we found 17 pseudogenes with strong support for transcription. In particular, one of the pseudogenes with both EST and microarray evidence for transcription turned out to be a duplicated pseudogene in the cat eye syndrome critical region. Although we could not identify a meaningful number of transcription factor-binding sites (based on chromatin immunoprecipitation-chip data) near pseudogenes, we did find that approximately 12% of the pseudogenes had upstream CpG islands. Finally, analysis of corresponding syntenic regions in the mouse, rat and chimp genomes indicates, as previously suggested, that pseudogenes are less conserved than genes, but more preserved than the intergenic background (all notation is available from http://www.pseudogene.org).

Animals↗
PubMed2004

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).

Alu Elements↗
PubMed2003

Patterns of nucleotide substitution, insertion and deletion in the human genome inferred from pseudogenes.

Nucleotide substitution, insertion and deletion (indel) events are the major driving forces that have shaped genomes. Using the recently identified human ribosomal protein (RP) pseudogene sequences, we have thoroughly studied DNA mutation patterns in the human genome. We analyzed a total of 1726 processed RP pseudogene sequences, comprising more than 700 000 bases. To be sure to differentiate the sequence changes occurring in the functional genes during evolution from those occurring in pseudogenes after they were fixed in the genome, we used only pseudogene sequences originating from parts of RP genes that are identical in human and mouse. Overall, we found that nucleotide transitions are more common than transversions, by roughly a factor of two. Moreover, the substitution rates amongst the 12 possible nucleotide pairs are not homogeneous as they are affected by the type of immediately neighboring nucleotides and the overall local G+C content. Finally, our dataset is large enough that it has many indels, thus allowing for the first time statistically robust analysis of these events. Overall, we found that deletions are about three times more common than insertions (3740 versus 1291). The frequencies of both these events follow characteristic power-law behavior associated with the size of the indel. However, unexpectedly, the frequency of 3 bp deletions (in contrast to 3 bp insertions) violates this trend, being considerably higher than that of 2 bp deletions. The possible biological implications of such a 3 bp bias are discussed.

Algorithms↗
PubMed2003

The human genome has 49 cytochrome c pseudogenes, including a relic of a primordial gene that still functions in mouse.

Using a computational approach, we have identified 49 cytochrome c (cyc) pseudogenes in the human genome. Analysis of these provides a detailed description of the molecular evolution of the cyc gene. Almost all of the pseudogenes are full-length, and we have concluded that they mostly originated from independent retrotransposition events (i.e. they are processed). Based on phylogenetic analysis and detailed sequence comparison, we have further divided these pseudogenes into two groups. The first, consisting of four young pseudogenes that were dated to be between 27 and 34 Myr old, originated from a gene almost identical to the modern human cyc gene. The second group of pseudogenes is much older and appears to have descended from ancient genes similar to modern rodent cyc genes. Thus, our results support the observation that accelerated evolution in cyc sequence had occurred in the primate lineage. The oldest pseudogene in the second group, dated to be over 80 Myr old, resembles the testis-specific cyc gene in modern rodents. It is likely that the mammalian ancestor had both the somatic and the testis-specific cyc genes. While the testis-specific gene is still functional in modern rodents, the human has lost it, retaining only a pseudogene in its place. Thus, our study may have identified a pseudogene that is a dead relic of a gene that has completely died off in the human lineage.

Amino Acid Sequence↗
PubMed2003

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.

Animals↗
PubMed2003

Identification and characterization of over 100 mitochondrial ribosomal protein pseudogenes in the human genome.

The human (nuclear) genome encodes at least 79 mitochondrial ribosomal proteins (MRPs), which are imported into the mitochondria. Using a comprehensive approach, we find 41 of these give rise to 120 pseudogenes in the genome. The majority of the MRP pseudogenes are of processed origin and can be aligned to match the entire coding region of the functional MRP mRNAs. One processed pseudogene was found to have originated from an alternatively spliced mRNA transcript. We also found two duplicated pseudogenes that are transcribed in the cell as confirmed by screening the human EST database. We observed a significant correlation between the number of processed pseudogenes and the gene CDS length (R = -0.40; p < 0.001), i.e., the relatively shorter genes tend to have more processed pseudogenes. There is also a weaker correlation between the number of processed pseudogenes and the gene CDS GC content. Our study provides a catalogue of human MRP pseudogenes, which will be useful in the study of functional MRP genes. It also provides a molecular record of the evolution of these genes. More details are available at http://pseudogene.org/.

Animals↗
PubMed2003

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.

Animals↗
PubMed2002

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.

Animals↗
PubMed2002

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.

Amino Acid Sequence↗