Search

The accumulation of complete genomic sequences enhances the need for functional annotation. Associating existing functional annotation of orthologs can speed up the annotation process and even examine the existing annotation. However, current protein sequence-based ortholog databases provide ambiguous and incomplete orthology in eukaryotes. It is because that isoforms, derived by alternative splicing (AS), often share higher sequence similarity to interfere the sequence-based identification. Gene-Oriented Ortholog Database (GOOD) employs genomic locations of transcripts to cluster AS-derived isoforms prior to ortholog delineation to eliminate the interference from AS. From the gene-oriented presentation, isoforms can be clearly associated to their genes to provide comprehensive ortholog information and further be discriminated from paralogs. Aside from, displaying clusters of isoforms between orthologous genes can present the evolution variation at the transcription level. Based on orthology, GOOD additionally comprises functional annotation from the Gene Ontology (GO) database. However, there exist redundant annotations, both parent and child terms assigned to the same gene, in the GO database. It is difficult to precisely draw the numerical comparison of term counts between orthologous genes annotated with redundant terms. Instead of the description only, GOOD further provides the GO graphs to reveal hierarchical-like relationships among divergent functionalities. Therefore, the redundancy of GO terms can be examined, and the context among compared terms is more comprehensive. In sum, GOOD can improve the interpretation in the molecular function from experiments in the model organism and provide clear comparative genomic annotation across organisms. Database URL: http://goods.ibms.sinica.edu.tw/goods/

Orthology is a widely used concept in comparative and evolutionary genomics. In addition to prokaryotic orthology, delineating eukaryotic orthology has provided insight into the evolution of higher organisms. Indeed, many eukaryotic ortholog databases have been established for this purpose. However, unlike prokaryotes, alternative splicing (AS) has hampered eukaryotic orthology assignments. Therefore, existing databases likely contain ambiguous eukaryotic ortholog relationships and possibly misclassify alternatively spliced protein isoforms as in-paralogs, which are duplicated genes that arise following speciation. Here, we propose a new approach for designating eukaryotic orthology using processed transcription units, and we present an orthology database prototype using the human and mouse genomes. Currently existing programs cover less than 69% of the human reference sequences when assigning human/mouse orthologs. In contrast, our method encompasses up to 80% of the human reference sequences. Moreover, the ortholog database presented herein is more than 92% consistent with the existing databases. In addition to managing AS, this approach is capable of identifying orthologs of embedded genes and fusion genes using syntenic evidence. In summary, this new approach is sensitive, specific and can generate a more comprehensive and accurate compilation of eukaryotic orthologs.

Nine protein arginine methyltransferases (PRMTs) are conserved in mammals and fish. Among these, PRMT1 is the major type I PRMT for asymmetric dimethylarginine (ADMA) formation and is the most conserved and widely distributed one. Two chicken prmt1 splicing variants were assembled and confirmed by RT-PCR experiments. However, only two scaffolds containing single separate prmt1 exon with high GC contents are present in the current chicken genome assembly. Besides, prmt1 exons are scattered in separate small scaffolds in most avian species. Complete prmt1 gene has only been predicted from two falcon species with few neighboring genes. Crocodilians are considered close to the common ancestor shared by crocodilians and birds. The gene arrangements around prmt1 in American alligator are different from that in birds but are largely conserved in human. Orthologues of genes in a large segment of human chromosomal 19 around PRMT1 are missing or not assigned to the current chicken chromosomes. In comparison, prmt8, the prmt1 paralogue, is on chicken chromosome 1 with the gene arrangements downstream of prmt8 highly conserved in birds, crocodilians, and human. However, the ones upstream vary greatly in birds. Biochemically, we found that though prmt1 transcripts were detected, limited or none PRMT1 protein was present in chicken tissues. Moreover, a much higher level of PRMT8 protein was detected in chicken brain than in mouse brain. While PRMT8 is brain specific in other vertebrate species studied, low level of PRMT8 was present in chicken but not mouse liver and muscle. We also showed that the ADMA level in chicken was similar to that in mouse. This study provides the critical information of chicken PRMT1 and PRMT8 for future analyses of the function of protein arginine methyltransferases in birds. [ABSTRACT FROM AUTHOR]

Background: Orthologs are genes derived from the same ancestor gene loci after speciation events. Orthologous proteins usually have similar sequences and perform comparable biological functions. Therefore, ortholog identification is useful in annotations of newly sequenced genomes. With rapidly increasing number of sequenced genomes, constructing or updating ortholog relationship between all genomes requires lots of effort and computation time. In addition, elucidating ortholog relationships between distantly related genomes is challenging because of the lower sequence similarity. Therefore, an efficient ortholog detection method that can deal with large number of distantly related genomes is desired. Results: An efficient ortholog detection pipeline DODO (DOmain based Detection of Orthologs) is created on the basis of domain architectures in this study. Supported by domain composition, which usually directly related with protein function, DODO could facilitate orthologs detection across distantly related genomes. DODO works in two main steps. Starting from domain information, it first assigns protein groups according to their domain architectures and further identifies orthologs within those groups with much reduced complexity. Here DODO is shown to detect orthologs between two genomes in considerably shorter period of time than traditional methods of reciprocal best hits and it is more significant when analyzed a large number of genomes. The output results of DODO are highly comparable with other known ortholog databases. Conclusions: DODO provides a new efficient pipeline for detection of orthologs in a large number of genomes. In addition, a database established with DODO is also easier to maintain and could be updated relatively effortlessly. The pipeline of DODO could be downloaded from http://140.109.42.19:16080/dodo_web/home.htm [ABSTRACT FROM AUTHOR]

Identification of microRNAs (miRNAs) is essential to studying their physiological functions. Due to the difficulties in discovering truly expressed miRNAs from genomic random hairpin secondary structure sequences, it is beneficial to predict them from expressed sequences—expressed sequence tags (ESTs) and intronic sequences. We used a modified scanning pipeline using criteria based on the features of known pre-miRNAs and phylogenetic conservation for predicting intronic miRNAs. Upon examination, we found that 25% of known human miRNAs belong to intronic regions of known protein-coding genes. About 50% of these intronic miRNAs reside in introns whose length is longer than 5,000 bps. It is likely that these intronic miRNAs can have their own independently regulated transcription units, which can be regulated by RNA polymerase II (Pol II) or RNA polymerase III (Pol III). It was recently demonstrated that RNA Pol III could transcribe human miRNAs through associated repetitive elements. Since various repetitive elements are often found to be present in the intronic regions, the distribution of intronic miRNAs and their possible transcription regulation are presented. Although the intronic miRNAs and their host genes could be regulated independently, it is possible that the intronic miRNA can still down-regulate its own host protein-coding gene by targeting the untranslated region (UTR) of the host gene. Another biological implication is that intronic miRNAs could play an important role as negative feedback regulators. We propose hypothetical models of such feedback regulation on host protein-coding genes by selecting the transcription factors as miRNA targets or by protein-protein interactions between intronic miRNA host gene product and miRNA target gene products. [ABSTRACT FROM AUTHOR]

Background: MicroRNAs (miRNAs) function in many physiological processes, and their discovery is beneficial for further studying their physiological functions. However, many of the miRNAs predicted from genomic sequences have not been experimentally validated to be authentic expressed RNA transcripts, thereby decreasing the reliability of miRNA discovery. To overcome this problem, we examined expressed transcripts - ESTs and intronic sequences - to identify novel miRNAs as well as their target genes. Results: To facilitate our approach, we developed our scanning method using criteria based on the features of 207 known human pre-miRNAs to discriminate miRNAs from random sequences. We identified 208 candidate hairpins in human ESTs and human reference gene intronic sequences, 52 of which are known pre-miRNAs. The discovery pipeline performance was further assessed using 130 newly updated pre-miRNA and randomly selected sequences. We achieved sensitivity of 85% (110/130) and overall specificity of 49.7% using this method. Because miRNAs are evolutionarily conserved regulators of gene expression, it is expected that their host genes and target genes should have respective phylogenetic orthologs. Our results confirmed that, in certain mammals, the host genes carrying the same miRNAs are orthologs, as previously reported. Moreover, this observation is also the case for some of the miRNA target genes. Conclusion: We have predicted 208 human pre-miRNA candidates and over 10,000 putative human target genes. Using sequence information from ESTs and introns ensures that the predicted pre-miRNA candidates are expressed and the combined expression transcription information from ESTs and introns makes our prediction results more decisive with regard to expressed premiRNAs. [ABSTRACT FROM AUTHOR]

The round-spotted pufferfish Tetraodon fluviatilis has a genome size of 380 Mb which is slightly smaller than that of another pufferfish, Fugu rubripes rubripes (Fugu). Due to their compact genome and small introns, both pufferfishes have been proposed as model organisms for genome studies. In this study, we have used genomic DNA as template to perform PCR to screen for protein kinase (pk) genes. Forty-one T. fluviatilis pk genes encoding 7 receptor tyrosine kinases, 14 nonreceptor tyrosine kinases, 16 serine/threonine kinases, 1 dual kinase and 3 novel kinases have been identified. The success of this approach depends on the size and location of the introns. Most of the identified pk gene fragments contain introns, ranging from 71 to 300 bp, with an average of 120 bp. It is noteworthy that the intron/exon boundaries of certain genes which belong to the same family are identical. We also analyzed by specific RT-PCR primers the expression profile of those 3 novel genes as well as some selected pk genes in a variety of tissues. We found that erbB3, pku α, mrk, CaMK I, CaMK IIγ, and two novel kinase genes (133 and 3–26) are expressed in all tissues examined. However, the novel clone 146 is strongly expressed in the brain and weakly in the intestine, kidney and heart. [ABSTRACT FROM AUTHOR]

Abstract: Overlapping genes are pairs of adjacent genes whose genomic regions partially overlap. They are notable by their potential intricate regulation, such as cis-regulation of nested gene-promoter configurations, and post-transcriptional regulation of natural antisense transcripts. The originations and consequent detailed regulation remain obscure. Herein, we propose a unified framework comprising biological classification rules followed by extensive analyses, namely, exon-sharing analysis, a human–mouse conservation study, and transcriptome analysis of hundreds of microarrays and transcriptome sequencing data (mRNA-Seq). We demonstrate that the tail-to-tail architecture would result from sharing functional elements in 3′-untranslated regions (3′-UTRs) of pre-existing genes. Dissimilarly, we illustrate that the other gene overlaps would originate from a new gene arising in a pre-existing gene locus. Interestingly, these types of coupled overlapping genes may influence each other synergistically or competitively during transcription, depending on the promoter configurations. This framework discloses distinctive characteristics of overlapping genes to be a foundation for a further comprehensive understanding of them. [Copyright &y& Elsevier]