Jason M. Inman

A Mammalian microRNA Expression Atlas Based on Small RNA Library Sequencing

MicroRNAs (miRNAs) are small noncoding regulatory RNAs that reduce stability and/or translation of fully or partially sequence-complementary target mRNAs. In order to identify miRNAs and to assess their expression patterns, we sequenced over 250 small RNA libraries from 26 different organ systems and cell types of human and rodents that were enriched in neuronal as well as normal and malignant hematopoietic cells and tissues. We present expression profiles derived from clone count data and provide computational tools for their analysis. Unexpectedly, a relatively small set of miRNAs, many of which are ubiquitously expressed, account for most of the differences in miRNA profiles between cell lineages and tissues. This broad survey also provides detailed and accurate information about mature sequences, precursors, genome locations, maturation processes, inferred transcriptional units, and conservation patterns. We also propose a subclassification scheme for miRNAs for assisting future experimental and computational functional analyses.

Genomic Islands in the Pathogenic Filamentous Fungus Aspergillus fumigatus

We present the genome sequences of a new clinical isolate of the important human pathogen, Aspergillus fumigatus, A1163, and two closely related but rarely pathogenic species, Neosartorya fischeri NRRL181 and Aspergillus clavatus NRRL1. Comparative genomic analysis of A1163 with the recently sequenced A. fumigatus isolate Af293 has identified core, variable and up to 2% unique genes in each genome. While the core genes are 99.8% identical at the nucleotide level, identity for variable genes can be as low 40%. The most divergent loci appear to contain heterokaryon incompatibility (het) genes associated with fungal programmed cell death such as developmental regulator rosA. Cross-species comparison has revealed that 8.5%, 13.5% and 12.6%, respectively, of A. fumigatus, N. fischeri and A. clavatus genes are species-specific. These genes are significantly smaller in size than core genes, contain fewer exons and exhibit a subtelomeric bias. Most of them cluster together in 13 chromosomal islands, which are enriched for pseudogenes, transposons and other repetitive elements. At least 20% of A. fumigatus-specific genes appear to be functional and involved in carbohydrate and chitin catabolism, transport, detoxification, secondary metabolism and other functions that may facilitate the adaptation to heterogeneous environments such as soil or a mammalian host. Contrary to what was suggested previously, their origin cannot be attributed to horizontal gene transfer (HGT), but instead is likely to involve duplication, diversification and differential gene loss (DDL). The role of duplication in the origin of lineage-specific genes is further underlined by the discovery of genomic islands that seem to function as designated “gene dumps” and, perhaps, simultaneously, as “gene factories”.

PanOCT: automated clustering of orthologs using conserved gene neighborhood for pan-genomic analysis of bacterial strains and closely related species

Pan-genome ortholog clustering tool (PanOCT) is a tool for pan-genomic analysis of closely related prokaryotic species or strains. PanOCT uses conserved gene neighborhood information to separate recently diverged paralogs into orthologous clusters where homology-only clustering methods cannot. The results from PanOCT and three commonly used graph-based ortholog-finding programs were compared using a set of four publicly available strains of the same bacterial species. All four methods agreed on ∼70% of the clusters and ∼86% of the proteins. The clusters that did not agree were inspected for evidence of correctness resulting in 85 high-confidence manually curated clusters that were used to compare all four methods.

Comparative genome analysis of 19 Ureaplasma urealyticum and Ureaplasma parvum strains

BackgroundUreaplasma urealyticum (UUR) and Ureaplasma parvum (UPA) are sexually transmitted bacteria among humans implicated in a variety of disease states including but not limited to: nongonococcal urethritis, infertility, adverse pregnancy outcomes, chorioamnionitis, and bronchopulmonary dysplasia in neonates. There are 10 distinct serotypes of UUR and 4 of UPA. Efforts to determine whether difference in pathogenic potential exists at the ureaplasma serovar level have been hampered by limitations of antibody-based typing methods, multiple cross-reactions and poor discriminating capacity in clinical samples containing two or more serovars.ResultsWe determined the genome sequences of the American Type Culture Collection (ATCC) type strains of all UUR and UPA serovars as well as four clinical isolates of UUR for which we were not able to determine serovar designation. UPA serovars had 0.75−0.78 Mbp genomes and UUR serovars were 0.84−0.95 Mbp. The original classification of ureaplasma isolates into distinct serovars was largely based on differences in the major ureaplasma surface antigen called the multiple banded antigen (MBA) and reactions of human and animal sera to the organisms. Whole genome analysis of the 14 serovars and the 4 clinical isolates showed the mba gene was part of a large superfamily, which is a phase variable gene system, and that some serovars have identical sets of mba genes. Most of the differences among serovars are hypothetical genes, and in general the two species and 14 serovars are extremely similar at the genome level.ConclusionsComparative genome analysis suggests UUR is more capable of acquiring genes horizontally, which may contribute to its greater virulence for some conditions. The overwhelming evidence of extensive horizontal gene transfer among these organisms from our previous studies combined with our comparative analysis indicates that ureaplasmas exist as quasi-species rather than as stable serovars in their native environment. Therefore, differential pathogenicity and clinical outcome of a ureaplasmal infection is most likely not on the serovar level, but rather may be due to the presence or absence of potential pathogenicity factors in an individual ureaplasma clinical isolate and/or patient to patient differences in terms of autoimmunity and microbiome.

TheViral MetaGenome Annotation Pipeline(VMGAP):an automated tool for the functional annotation of viral Metagenomic shotgun sequencing data

In the past few years, the field of metagenomics has been growing at an accelerated pace, particularly in response to advancements in new sequencing technologies. The large volume of sequence data from novel organisms generated by metagenomic projects has triggered the development of specialized databases and tools focused on particular groups of organisms or data types. Here we describe a pipeline for the functional annotation of viral metagenomic sequence data. The Viral MetaGenome Annotation Pipeline (VMGAP) pipeline takes advantage of a number of specialized databases, such as collections of mobile genetic elements and environmental metagenomes to improve the classification and functional prediction of viral gene products. The pipeline assigns a functional term to each predicted protein sequence following a suite of comprehensive analyses whose results are ranked according to a priority rules hierarchy. Additional annotation is provided in the form of enzyme commission (EC) numbers, GO/MeGO terms and Hidden Markov Models together with supporting evidence.

Sensitive and specific method for detecting G protein-coupled receptor mRNAs.

G protein–coupled receptors (GPCRs) mediate effects of extracellular signaling molecules in all the bodys cells. These receptors are encoded by scarce mRNAs; therefore, detecting their transcripts with conventional microarrays is difficult. We present a method based on multiplex PCR and array detection of amplicons to assay GPCR gene expression with as little as 1 μg of total RNA, and using it, we profiled three human bone marrow stromal cell (BMSC) lines.

Host Genetic Control of the Oral Microbiome in Health and Disease

Host-associated microbial communities are influenced by both host genetics and environmental factors. However, factors controlling the human oral microbiome and their impact on disease remain to be investigated. To determine the combined and relative effects of host genotype and environment on oral microbiome composition and caries phenotypes, we profiled the supragingival plaque microbiome of 485 dizygotic and monozygotic twins aged 5-11. Oral microbiome similarity always increased with shared host genotype, regardless of caries state. Additionally, although most of the variation in the oral microbiome was determined by environmental factors, highly heritable oral taxa were identified. The most heritable oral bacteria were not associated with caries state, did not tend to co-occur with other taxa, and decreased in abundance with age and sugar consumption frequency. Thus, while the human oral microbiome composition is influenced by host genetic background, potentially cariogenic taxa are likely not controlled by genetic factors.

LOCUST: a custom sequence locus typer for classifying microbial isolates

Summary LOCUST is a custom sequence locus typer tool for classifying microbial genomes. It provides a fully automated opportunity to customize the classification of genome-wide nucleotide variant data most relevant to biological research. Availability and Implementation Source code, demo data, and detailed documentation are freely available at http://sourceforge.net/projects/locustyper . Contact lbrinkac@jcvi.org. Supplementary information Supplementary data are available at Bioinformatics online.

PanACEA: a bioinformatics tool for the exploration and visualization of bacterial pan-chromosomes

BackgroundBacterial pan-genomes, comprised of conserved and variable genes across multiple sequenced bacterial genomes, allow for identification of genomic regions that are phylogenetically discriminating or functionally important. Pan-genomes consist of large amounts of data, which can restrict researchers ability to locate and analyze these regions. Multiple software packages are available to visualize pan-genomes, but currently their ability to address these concerns are limited by using only pre-computed data sets, prioritizing core over variable gene clusters, or by not accounting for pan-chromosome positioning in the viewer.ResultsWe introduce PanACEA (Pan-genome Atlas with Chromosome Explorer and Analyzer), which utilizes locally-computed interactive web-pages to view ordered pan-genome data. It consists of multi-tiered, hierarchical display pages that extend from pan-chromosomes to both core and variable regions to single genes. Regions and genes are functionally annotated to allow for rapid searching and visual identification of regions of interest with the option that user-supplied genomic phylogenies and metadata can be incorporated. PanACEA’s memory and time requirements are within the capacities of standard laptops. The capability of PanACEA as a research tool is demonstrated by highlighting a variable region important in differentiating strains of Enterobacter hormaechei.ConclusionsPanACEA can rapidly translate the results of pan-chromosome programs into an intuitive and interactive visual representation. It will empower researchers to visually explore and identify regions of the pan-chromosome that are most biologically interesting, and to obtain publication quality images of these regions.

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BackgroundBacterial pan-genomes, comprised of conserved and variable genes across multiple sequenced bacterial genomes, allow for identification of genomic regions that are phylogenetically discriminating or functionally important. Pan-genomes consist of large amounts of data, which can restrict researchers ability to locate and analyze these regions. Multiple software packages are available to visualize pan-genomes, but currently their ability to address these concerns are limited by using only pre-computed data sets, prioritizing core over variable gene clusters, or by not accounting for pan-chromosome positioning in the viewer.ResultsWe introduce PanACEA (Pan-genome Atlas with Chromosome Explorer and Analyzer), which utilizes locally-computed interactive web-pages to view ordered pan-genome data. It consists of multi-tiered, hierarchical display pages that extend from pan-chromosomes to both core and variable regions to single genes. Regions and genes are functionally annotated to allow for rapid searching and visual identification of regions of interest with the option that user-supplied genomic phylogenies and metadata can be incorporated. PanACEA’s memory and time requirements are within the capacities of standard laptops. The capability of PanACEA as a research tool is demonstrated by highlighting a variable region important in differentiating strains of Enterobacter hormaechei.ConclusionsPanACEA can rapidly translate the results of pan-chromosome programs into an intuitive and interactive visual representation. It will empower researchers to visually explore and identify regions of the pan-chromosome that are most biologically interesting, and to obtain publication quality images of these regions.