Analyzing gene expression data in mice with the Neuro Behavior Ontology

We have applied the Neuro Behavior Ontology (NBO), an ontology for the annotation of behavioral gene functions and behavioral phenotypes, to the annotation of more than 1,000 genes in the mouse that are known to play a role in behavior. These annotations can be explored by researchers interested in genes involved in particular behaviors and used computationally to provide insights into the behavioral phenotypes resulting from differences in gene expression. We developed the OntoFUNC tool and have applied it to enrichment analyses over the NBO to provide high-level behavioral interpretations of gene expression datasets. The resulting increase in the number of gene annotations facilitates the identification of behavioral or neurologic processes by assisting the formulation of hypotheses about the relationships between gene, processes, and phenotypic manifestations resulting from behavioral observations.     

Identification and analysis of genes and pseudogenes within duplicated regions in the human and mouse genomes

The identification and classification of genes and pseudogenes in duplicated regions still constitutes a challenge for standard automated genome annotation procedures. Using an integrated homology and orthology analysis independent of current gene annotation, we have identified 9,484 and 9,017 gene duplicates in human and mouse, respectively. On the basis of the integrity of their coding regions, we have classified them into functional and inactive duplicates, allowing us to define the first consistent and comprehensive collection of 1,811 human and 1,581 mouse unprocessed pseudogenes. Furthermore, of the total of 14,172 human and mouse duplicates predicted to be functional genes, as many as 420 are not included in current reference gene databases and therefore correspond to likely novel mammalian genes. Some of these correspond to partial duplicates with less than half of the length of the original source genes, yet they are conserved and syntenic among different mammalian lineages. The genes and unprocessed pseudogenes obtained here will enable further studies on the mechanisms involved in gene duplication as well as of the fate of duplicated genes.     

Questionable 16S ribosomal RNA gene annotations are frequent in completed microbial genomes

According to recent reports, many ribosomal RNA gene annotations are still questionable, and the use of inappropriate tools for annotation has been blamed. However, we believe that the abundant 16S rRNA partial sequence in the databases, mainly created by culture-independent PCR methods, is another main cause of the ambiguous annotations of 16S rRNA. To examine the current status of 16S rRNA gene annotations in complete microbial genomes, we used as a criterion the conserved anti-SD sequence, located at the 3′ end of the 16S rRNA gene, which is commonly overlooked by culture-independent PCR methods. In our large survey, 859 16S rRNA gene sequences from 252 different species of the microbial complete genomes were inspected. 67 species (234 genes) were detected with ambiguous annotations. The common anti-SD sequence and other conserved 16S rRNA sequence features could be detected in the downstream-intergenic regions for almost every questionable sequence, indicating that many of the 16S rRNA genes were annotated incorrectly. Furthermore, we found that more than 91.5% of the 93,716 sequences of the available 16S rRNA in the main databases are partial sequences. We also performed BLAST analysis for every questionable rRNA sequence, and most of the best hits in the analysis were rRNA partial sequences. This result indicates that partial sequences are prevalent in the databases, and that these sequences have significantly affected the accuracy of microbial genomic annotation. We suggest that the annotation of 16S rRNA genes in newly complete microbial genomes must be done in more detail, and that revision of questionable rRNA annotations should commence as soon as possible.     

MaXML: mouse annotation XML

Although the sequencing of the human genome and several model organisms is almost complete, the number of genes in the human is still in debate. cDNA (complementary DNA) is generated from mRNA that is transcribed from the genome and can be regarded as a gene itself; therefore, decoding cDNA sequences is important in characterizing genes. Recently, biologists have been able to describe more knowledge about genes in order to characterize them, and this information is generally called 'annotation.' Furthermore, annotation is important in understanding the systems of organisms in various fields of research. We therefore constructed the MaXML (Mouse annotation XML) format with which mouse cDNA annotation data can be exchanged and shared between laboratories more efficiently. Defining strict data types for annotations is difficult, but we consider XML a feasible format for describing them. We have used the MaXML format to express mouse annotation data in FANTOM DB. We have also developed tools and systems utilizing these MaXML data, including a parser and a server to provide data on-the-fly.     

Identification of a U7snRNA homologue mapping to the human Xq27.1 region,between the DXS1232 and DXS119 loci

To contribute to the identification and analysis of novel genes, we undertook the study of a cosmid clone in the Xq27 region of human DNA. The cloned fragment was previously observed to have a high number of evolutionarily conserved sequences. In this genomic stretch of DNA we have identified sequence homologous to the U7 RNA gene including its potential regulatory elements. This paper describes the genomic organisation of this gene and its mapping to the Xq27.1 genomic sub-interval between the DXS1232 and DXS119 loci.     

Use of comparative physical and sequence mapping to annotate mouse chromosome 16 and human chromosome 21

Distal mouse chromosome 16 (MMU16) shares conserved linkage with human chromosome 21 (HSA21), trisomy for which causes Down syndrome (DS). A 4.5-Mb physical map extending from Cbr1 to Tmprss2 on MMU16 provides a minimal tiling path of P1 artificial chromosomes (PACs) for comparative mapping and genomic sequencing. Thirty-four expressed sequences were positioned on the mouse map, including 19 that were not physically mapped previously. This region of the mouse:human comparative map shows a high degree of evolutionary conservation of gene order and content, which differs only by insertion of one gene (in mouse) and a small inversion involving two adjacent genes. "Low-pass" (2.2x) mouse sequence from a portion of the contig was ordered and oriented along 510 kb of finished HSA21 sequence. In combination with 68 kb of unique PAC end sequence, the comparison provided confirmation of genes predicted by comparative mapping, indicated gene predictions that are likely to be incorrect, and identified three candidate genes in mouse and human that were not observed in the initial HSA21 sequence annotation. This comparative map and sequence derived from it are powerful tools for identifying genes and regulatory regions, information that will in turn provide insights into the genetic mechanisms by which trisomy 21 results in DS.     

Nance-Horan syndrome: linkage analysis in 4 families refines localization in Xp22.31–p22.13 region

Nance-Horan syndrome (NHS) is an X-linked disease characterized by severe congenital cataract with microcornea, distinctive dental findings, evocative facial features and mental impairment in some cases. Previous linkage studies have placed the NHS gene in a large region from DXS143 (Xp22.31) to DXS451 (Xp22.13). To refine this localization further, we have performed linkage analysis in four families. As the maximum expected Lod score is reached in each family for several markers in the Xp22.31–p22.13 region and linkage to the rest of the X chromosome can be excluded, our study shows that NHS is a genetically homogeneous condition. An overall maximum two-point Lod score of 9.36 (θ = 0.00) is obtained with two closely linked markers taken together, DXS207 and DXS1053 in Xp22.2. Recombinant haplotypes indicate that the NHS gene lies between DXS85 and DXS1226. Multipoint analysis yields a maximum Lod score of 9.45 with the support interval spanning a 15-cM region that includes DXS16 and DXS1229/365. The deletion map of the Xp22.3–Xp21.3 region suggests that the phenotypic variability of NHS is not related to gross rearrangement of sequences of varying size but rather to allelic mutations in a single gene, presumably located proximal to DXS16 and distal to DXS1226. Comparison with the map position of the mouse Xcat mutation supports the location of the NHS gene between the GRPR and PDHA1 genes in Xp22.2. Received: 14 June 1996 / Revised: 10 October 1996     

On the Use of Gene Ontology Annotations to Assess Functional Similarity among Orthologs and Paralogs: A Short Report

A recent paper (Nehrt et al., PLoS Comput. Biol. 7:e1002073, 2011) has proposed a metric for the "functional similarity" between two genes that uses only the Gene Ontology (GO) annotations directly derived from published experimental results. Applying this metric, the authors concluded that paralogous genes within the mouse genome or the human genome are more functionally similar on average than orthologous genes between these genomes, an unexpected result with broad implications if true. We suggest, based on both theoretical and empirical considerations, that this proposed metric should not be interpreted as a functional similarity, and therefore cannot be used to support any conclusions about the "ortholog conjecture" (or, more properly, the "ortholog functional conservation hypothesis"). First, we reexamine the case studies presented by Nehrt et al. as examples of orthologs with divergent functions, and come to a very different conclusion: they actually exemplify how GO annotations for orthologous genes provide complementary information about conserved biological functions. We then show that there is a global ascertainment bias in the experiment-based GO annotations for human and mouse genes: particular types of experiments tend to be performed in different model organisms. We conclude that the reported statistical differences in annotations between pairs of orthologous genes do not reflect differences in biological function, but rather complementarity in experimental approaches. Our results underscore two general considerations for researchers proposing novel types of analysis based on the GO: 1) that GO annotations are often incomplete, potentially in a biased manner, and subject to an "open world assumption" (absence of an annotation does not imply absence of a function), and 2) that conclusions drawn from a novel, large-scale GO analysis should whenever possible be supported by careful, in-depth examination of examples, to help ensure the conclusions have a justifiable biological basis.     

A semantic analysis of the annotations of the human genome

The correct interpretation of any biological experiment depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are ubiquitous and used by all life scientists in most experiments. However, it is well known that such databases are incomplete and many annotations may also be incorrect. In this paper we describe a technique that can be used to analyze the semantic content of such annotation databases. Our approach is able to extract implicit semantic relationships between genes and functions. This ability allows us to discover novel functions for known genes. This approach is able to identify missing and inaccurate annotations in existing annotation databases, and thus help improve their accuracy. We used our technique to analyze the current annotations of the human genome. From this body of annotations, we were able to predict 212 additional gene-function assignments. A subsequent literature search found that 138 of these gene-functions assignments are supported by existing peer-reviewed papers. An additional 23 assignments have been confirmed in the meantime by the addition of the respective annotations in later releases of the Gene Ontology database. Overall, the 161 confirmed assignments represent 75.95% of the proposed gene-function assignments. Only one of our predictions (0.4%) was contradicted by the existing literature. We could not find any relevant articles for 50 of our predictions (23.58%). The method is independent of the organism and can be used to analyze and improve the quality of the data of any public or private annotation database.     

Defining characteristics and conservation of poorly annotated genes in Caenorhabditis elegans using WormCat 2.0

Omics tools provide broad datasets for biological discovery. However, the computational tools for identifying important genes or pathways in RNA-seq, proteomics, or GWAS (Genome-Wide Association Study) data depend on Gene Ontogeny annotations and are biased toward well-described pathways. This limits their utility as poorly annotated genes, which could have novel functions, are often passed over. Recently, we developed an annotation and category enrichment tool for Caenorhabditis elegans genomic data, WormCat, which provides an intuitive visualization output. Unlike Gene Ontogeny-based enrichment tools, which exclude genes with no annotation information, WormCat 2.0 retains these genes as a special UNASSIGNED category. Here, we show that the UNASSIGNED gene category enrichment exhibits tissue-specific expression patterns and can include genes with biological functions identified in published datasets. Poorly annotated genes are often considered to be potentially species-specific and thus, of reduced interest to the biomedical community. Instead, we find that around 3% of the UNASSIGNED genes have human orthologs, including some linked to human diseases. These human orthologs themselves have little annotation information. A recently developed method that incorporates lineage relationships (abSENSE) indicates that the failure of BLAST to detect homology explains the apparent lineage specificity for many UNASSIGNED genes. This suggests that a larger subset could be related to human genes. WormCat provides an annotation strategy that allows the association of UNASSIGNED genes with specific phenotypes and known pathways. Building these associations in C. elegans, with its robust genetic tools, provides a path to further functional study and insight into these understudied genes.     

Detection of a molecular deletion at the DXS732 locus in a patient with X-linked hypohidrotic ectodermal dysplasia (EDA), with the identification of a unique junctional fragment.

X-linked hypohidrotic ectodermal dysplasia (EDA) has been localized to the Xq12-q13.1 region. A panel of genomic DNA samples from 80 unrelated males with EDA has been screened for deletions at seven genetic loci within the Xq12-13 region. A single individual was identified with a deletion at the DXS732 locus by hybridization with the mouse genomic probe pcos169E/4. This highly conserved DNA probe is from locus DXCrc169, which is tightly linked to the Ta locus, the putative mouse homologue of EDA. The proband had the classical phenotype of EDA, with no other phenotypic abnormalities, and a normal cytogenetic analysis. A human genomic DNA clone, homologous to pcos169E/4, was isolated from a human X-chromosome cosmid library. On hybridization with the cosmid, the proband was found to be only partially deleted at the DXS732 locus, with a unique junctional fragment identified in the proband and in three of his maternal relatives. This is the first determination of carrier status for EDA in females, by direct mutation analysis. Failure to detect deletion of the other loci tested in the proband suggests that the DXS732 locus is the closest known locus to the EDA gene. Since the DXS732 locus contains a highly conserved sequence, it must be considered to be a candidate locus for the EDA gene itself.     

Comparative mapping of human Chromosome 14q11.2-q13 genes with mouse homologous gene regions

An examination of the synteny blocks between mouse and human chromosomes aids in understanding the evolution of chromosome divergence between these two species. We comparatively mapped the human (HSA) Chromosome (Chr) 14q11.2-q13 cytogenetic region with the intervals of orthologous genes on mouse (MMU) chromosomes. A lack of conserved gene order was identified between the human cytogenetic region and the interval of orthologs on MMU 12. The evolutionary breakpoint junction was defined within 2.5 Mb, where the conserved synteny of genes on HSA 14 changes from MMU 12 to MMU 14. At the evolutionary breakpoint junction, a human EST (GI: 1114654) with identity to the human and mouse BCL2 interacting gene, BNIP3, was mapped to mouse Chr 3. New gene homologs of LAMB1, MEOX2, NRCAM, and NZTF1 were identified on HSA 7 and on the proximal cytogenetic region of HSA 14 by mapping mouse genes recently reported to be genetically linked within the relevant MMU 12 interval. This study contributes to the identification of homology relationships between the genes of HSA 14q11.2-q13 and mouse Chr 3, 12, and 14. Received: 16 March 2000 / Accepted: 16 June 2000