@article {49595, title = {Developmental expression of chicken FOXN1 and putative target genes during feather development.}, volume = {58}, year = {2014}, month = {2014}, pages = {57-64}, abstract = {

FOXN1 is a member of the forkhead box family of transcription factors. FOXN1 is crucial for hair outgrowth and thymus differentiation in mammals. Unlike the thymus, which is found in all amniotes, hair is an epidermal appendage that arose after the last shared common ancestor between mammals and birds, and hair and feathers differ markedly in their differentiation and gene expression. Here, we show that FOXN1 is expressed in embryonic chicken feathers, nails and thymus, demonstrating an evolutionary conservation that goes beyond obvious homology. At embryonic day (ED) 12, FOXN1 is expressed in some feather buds and at ED13 expression extends along the length of the feather filament. At ED14 FOXN1 mRNA is restricted to the proximal feather filament and is not detectable in distal feather shafts. At the base of the feather, FOXN1 is expressed in the epithelium of the feather sheath and distal barb and marginal plate, whereas in the midsection FOXN1 transcripts are mainly detected in the barb plates of the feather filament. FOXN1 is also expressed in claws; however, no expression was detected in skin or scales. Despite expression of FOXN1 in developing feathers, examination of chick homologs of five putative mammalian FOXN1 target genes shows that, while these genes are expressed in feathers, there is little similarity to the FOXN1 expression pattern, suggesting that some gene regulatory networks may have diverged during evolution of epidermal appendages.

}, keywords = {Amino Acid Sequence, Animals, Biological Evolution, Blotting, Western, Cell Differentiation, Cells, Cultured, Chick Embryo, Chickens, Cloning, Molecular, Embryo, Nonmammalian, Epidermis, Feathers, Forkhead Transcription Factors, Gene Expression Regulation, Developmental, In Situ Hybridization, Molecular Sequence Data, Morphogenesis, Phylogeny, Real-Time Polymerase Chain Reaction, Reverse Transcriptase Polymerase Chain Reaction, RNA, Messenger, Sequence Homology, Amino Acid}, issn = {1696-3547}, doi = {10.1387/ijdb.130023sy}, author = {Darnell, Diana K and Zhang, Li S and Hannenhalli, Sridhar and Yaklichkin, Sergey Y} } @article {38358, title = {A large-scale, higher-level, molecular phylogenetic study of the insect order Lepidoptera (moths and butterflies)}, journal = {PLoS OnePLoS One}, volume = {8}, year = {2013}, type = {10.1371/journal.pone.0058568}, abstract = {

BACKGROUND: Higher-level relationships within the Lepidoptera, and particularly within the species-rich subclade Ditrysia, are generally not well understood, although recent studies have yielded progress. We present the most comprehensive molecular analysis of lepidopteran phylogeny to date, focusing on relationships among superfamilies.

METHODOLOGY PRINCIPAL FINDINGS: 483 taxa spanning 115 of 124 families were sampled for 19 protein-coding nuclear genes, from which maximum likelihood tree estimates and bootstrap percentages were obtained using GARLI. Assessment of heuristic search effectiveness showed that better trees and higher bootstrap percentages probably remain to be discovered even after 1000 or more search replicates, but further search proved impractical even with grid computing. Other analyses explored the effects of sampling nonsynonymous change only versus partitioned and unpartitioned total nucleotide change; deletion of rogue taxa; and compositional heterogeneity. Relationships among the non-ditrysian lineages previously inferred from morphology were largely confirmed, plus some new ones, with strong support. Robust support was also found for divergences among non-apoditrysian lineages of Ditrysia, but only rarely so within Apoditrysia. Paraphyly for Tineoidea is strongly supported by analysis of nonsynonymous-only signal; conflicting, strong support for tineoid monophyly when synonymous signal was added back is shown to result from compositional heterogeneity. CONCLUSIONS SIGNIFICANCE: Support for among-superfamily relationships outside the Apoditrysia is now generally strong. Comparable support is mostly lacking within Apoditrysia, but dramatically increased bootstrap percentages for some nodes after rogue taxon removal, and concordance with other evidence, strongly suggest that our picture of apoditrysian phylogeny is approximately correct. This study highlights the challenge of finding optimal topologies when analyzing hundreds of taxa. It also shows that some nodes get strong support only when analysis is restricted to nonsynonymous change, while total change is necessary for strong support of others. Thus, multiple types of analyses will be necessary to fully resolve lepidopteran phylogeny.

}, keywords = {Animals, Butterflies, Moths, Phylogeny}, author = {Regier, Jerome C. and Mitter, Charles and Zwick, Andreas and Adam L. Bazinet and Michael P. Cummings and Kawahara, Akito Y. and Sohn, Jae-Cheon and Zwickl, Derrick J. and Cho, Soowon and Davis, Donald R. and Baixeras, Joaquin and Brown, John and Parr, Cynthia and Weller, Susan and Lees, David C. and Mitter, Kim T.} } @article {49774, title = {Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage.}, journal = {ISME J}, volume = {6}, year = {2012}, month = {2012 Jun}, pages = {1186-99}, abstract = {

Bacteria in the 16S rRNA clade SAR86 are among the most abundant uncultivated constituents of microbial assemblages in the surface ocean for which little genomic information is currently available. Bioinformatic techniques were used to assemble two nearly complete genomes from marine metagenomes and single-cell sequencing provided two more partial genomes. Recruitment of metagenomic data shows that these SAR86 genomes substantially increase our knowledge of non-photosynthetic bacteria in the surface ocean. Phylogenomic analyses establish SAR86 as a basal and divergent lineage of γ-proteobacteria, and the individual genomes display a temperature-dependent distribution. Modestly sized at 1.25-1.7 Mbp, the SAR86 genomes lack several pathways for amino-acid and vitamin synthesis as well as sulfate reduction, trends commonly observed in other abundant marine microbes. SAR86 appears to be an aerobic chemoheterotroph with the potential for proteorhodopsin-based ATP generation, though the apparent lack of a retinal biosynthesis pathway may require it to scavenge exogenously-derived pigments to utilize proteorhodopsin. The genomes contain an expanded capacity for the degradation of lipids and carbohydrates acquired using a wealth of tonB-dependent outer membrane receptors. Like the abundant planktonic marine bacterial clade SAR11, SAR86 exhibits metabolic streamlining, but also a distinct carbon compound specialization, possibly avoiding competition.

}, keywords = {Computational Biology, Gammaproteobacteria, Genome, Bacterial, Genomic Library, metagenomics, Oceans and Seas, Phylogeny, plankton, Rhodopsin, Rhodopsins, Microbial, RNA, Ribosomal, 16S, Seawater}, issn = {1751-7370}, doi = {10.1038/ismej.2011.189}, author = {Dupont, Chris L and Rusch, Douglas B and Yooseph, Shibu and Lombardo, Mary-Jane and Richter, R Alexander and Valas, Ruben and Novotny, Mark and Yee-Greenbaum, Joyclyn and Selengut, Jeremy D and Haft, Dan H and Halpern, Aaron L and Lasken, Roger S and Nealson, Kenneth and Friedman, Robert and Venter, J Craig} } @article {38316, title = {Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage}, journal = {The ISME journalThe ISME journal}, volume = {6}, year = {2012}, note = {http://www.ncbi.nlm.nih.gov/pubmed/22170421?dopt=Abstract}, type = {10.1038/ismej.2011.189}, abstract = {Bacteria in the 16S rRNA clade SAR86 are among the most abundant uncultivated constituents of microbial assemblages in the surface ocean for which little genomic information is currently available. Bioinformatic techniques were used to assemble two nearly complete genomes from marine metagenomes and single-cell sequencing provided two more partial genomes. Recruitment of metagenomic data shows that these SAR86 genomes substantially increase our knowledge of non-photosynthetic bacteria in the surface ocean. Phylogenomic analyses establish SAR86 as a basal and divergent lineage of γ-proteobacteria, and the individual genomes display a temperature-dependent distribution. Modestly sized at 1.25-1.7 Mbp, the SAR86 genomes lack several pathways for amino-acid and vitamin synthesis as well as sulfate reduction, trends commonly observed in other abundant marine microbes. SAR86 appears to be an aerobic chemoheterotroph with the potential for proteorhodopsin-based ATP generation, though the apparent lack of a retinal biosynthesis pathway may require it to scavenge exogenously-derived pigments to utilize proteorhodopsin. The genomes contain an expanded capacity for the degradation of lipids and carbohydrates acquired using a wealth of tonB-dependent outer membrane receptors. Like the abundant planktonic marine bacterial clade SAR11, SAR86 exhibits metabolic streamlining, but also a distinct carbon compound specialization, possibly avoiding competition.}, keywords = {Computational Biology, Gammaproteobacteria, Genome, Bacterial, Genomic Library, metagenomics, Oceans and Seas, Phylogeny, plankton, Rhodopsin, RNA, Ribosomal, 16S, Seawater}, author = {Dupont, Chris L. and Rusch, Douglas B. and Yooseph, Shibu and Lombardo, Mary-Jane and Richter, R. Alexander and Valas, Ruben and Novotny, Mark and Yee-Greenbaum, Joyclyn and J. Selengut and Haft, Dan H. and Halpern, Aaron L. and Lasken, Roger S. and Nealson, Kenneth and Friedman, Robert and Venter, J. Craig} } @article {49777, title = {ProPhylo: partial phylogenetic profiling to guide protein family construction and assignment of biological process.}, journal = {BMC Bioinformatics}, volume = {12}, year = {2011}, month = {2011}, pages = {434}, abstract = {

BACKGROUND: Phylogenetic profiling is a technique of scoring co-occurrence between a protein family and some other trait, usually another protein family, across a set of taxonomic groups. In spite of several refinements in recent years, the technique still invites significant improvement. To be its most effective, a phylogenetic profiling algorithm must be able to examine co-occurrences among protein families whose boundaries are uncertain within large homologous protein superfamilies.

RESULTS: Partial Phylogenetic Profiling (PPP) is an iterative algorithm that scores a given taxonomic profile against the taxonomic distribution of families for all proteins in a genome. The method works through optimizing the boundary of each protein family, rather than by relying on prebuilt protein families or fixed sequence similarity thresholds. Double Partial Phylogenetic Profiling (DPPP) is a related procedure that begins with a single sequence and searches for optimal granularities for its surrounding protein family in order to generate the best query profiles for PPP. We present ProPhylo, a high-performance software package for phylogenetic profiling studies through creating individually optimized protein family boundaries. ProPhylo provides precomputed databases for immediate use and tools for manipulating the taxonomic profiles used as queries.

CONCLUSION: ProPhylo results show universal markers of methanogenesis, a new DNA phosphorothioation-dependent restriction enzyme, and efficacy in guiding protein family construction. The software and the associated databases are freely available under the open source Perl Artistic License from ftp://ftp.jcvi.org/pub/data/ppp/.

}, keywords = {algorithms, Archaea, Archaeal Proteins, DNA, Methane, Phylogeny, software}, issn = {1471-2105}, doi = {10.1186/1471-2105-12-434}, author = {Basu, Malay K and Selengut, Jeremy D and Haft, Daniel H} } @article {38452, title = {ProPhylo: partial phylogenetic profiling to guide protein family construction and assignment of biological process}, journal = {BMC bioinformaticsBMC Bioinformatics}, volume = {12}, year = {2011}, note = {http://www.ncbi.nlm.nih.gov/pubmed/22070167?dopt=Abstract}, type = {10.1186/1471-2105-12-434}, abstract = {BACKGROUND: Phylogenetic profiling is a technique of scoring co-occurrence between a protein family and some other trait, usually another protein family, across a set of taxonomic groups. In spite of several refinements in recent years, the technique still invites significant improvement. To be its most effective, a phylogenetic profiling algorithm must be able to examine co-occurrences among protein families whose boundaries are uncertain within large homologous protein superfamilies. RESULTS: Partial Phylogenetic Profiling (PPP) is an iterative algorithm that scores a given taxonomic profile against the taxonomic distribution of families for all proteins in a genome. The method works through optimizing the boundary of each protein family, rather than by relying on prebuilt protein families or fixed sequence similarity thresholds. Double Partial Phylogenetic Profiling (DPPP) is a related procedure that begins with a single sequence and searches for optimal granularities for its surrounding protein family in order to generate the best query profiles for PPP. We present ProPhylo, a high-performance software package for phylogenetic profiling studies through creating individually optimized protein family boundaries. ProPhylo provides precomputed databases for immediate use and tools for manipulating the taxonomic profiles used as queries. CONCLUSION: ProPhylo results show universal markers of methanogenesis, a new DNA phosphorothioation-dependent restriction enzyme, and efficacy in guiding protein family construction. The software and the associated databases are freely available under the open source Perl Artistic License from ftp://ftp.jcvi.org/pub/data/ppp/.}, keywords = {algorithms, Archaea, Archaeal Proteins, DNA, Methane, Phylogeny, software}, author = {Basu, Malay K. and J. Selengut and Haft, Daniel H.} } @article {49648, title = {The Alveolate Perkinsus marinus: biological insights from EST gene discovery.}, journal = {BMC Genomics}, volume = {11}, year = {2010}, month = {2010}, pages = {228}, abstract = {

BACKGROUND: Perkinsus marinus, a protozoan parasite of the eastern oyster Crassostrea virginica, has devastated natural and farmed oyster populations along the Atlantic and Gulf coasts of the United States. It is classified as a member of the Perkinsozoa, a recently established phylum considered close to the ancestor of ciliates, dinoflagellates, and apicomplexans, and a key taxon for understanding unique adaptations (e.g. parasitism) within the Alveolata. Despite intense parasite pressure, no disease-resistant oysters have been identified and no effective therapies have been developed to date.

RESULTS: To gain insight into the biological basis of the parasite{\textquoteright}s virulence and pathogenesis mechanisms, and to identify genes encoding potential targets for intervention, we generated>31,000 5{\textquoteright} expressed sequence tags (ESTs) derived from four trophozoite libraries generated from two P. marinus strains. Trimming and clustering of the sequence tags yielded 7,863 unique sequences, some of which carry a spliced leader. Similarity searches revealed that 55\% of these had hits in protein sequence databases, of which 1,729 had their best hit with proteins from the chromalveolates (E-value

CONCLUSIONS: Our transcriptome analysis of P. marinus, the first for any member of the Perkinsozoa, contributes new insight into its biology and taxonomic position. It provides a very informative, albeit preliminary, glimpse into the expression of genes encoding functionally relevant proteins as potential targets for chemotherapy, and evidence for the presence of a relict plastid. Further, although P. marinus sequences display significant similarity to those from both apicomplexans and dinoflagellates, the presence of trans-spliced transcripts confirms the previously established affinities with the latter. The EST analysis reported herein, together with the recently completed sequence of the P. marinus genome and the development of transfection methodology, should result in improved intervention strategies against dermo disease.

}, keywords = {Alveolata, Animals, Expressed Sequence Tags, Ostreidae, Phylogeny}, issn = {1471-2164}, doi = {10.1186/1471-2164-11-228}, author = {Joseph, Sandeep J and Fern{\'a}ndez-Robledo, Jos{\'e} A and Gardner, Malcolm J and El-Sayed, Najib M and Kuo, Chih-Horng and Schott, Eric J and Wang, Haiming and Kissinger, Jessica C and Vasta, Gerardo R} } @proceedings {38374, title = {MetaPhyler: Taxonomic profiling for metagenomic sequences}, year = {2010}, month = {2010}, publisher = {IEEE}, type = {10.1109/BIBM.2010.5706544}, abstract = {A major goal of metagenomics is to characterize the microbial diversity of an environment. The most popular approach relies on 16S rRNA sequencing, however this approach can generate biased estimates due to differences in the copy number of the 16S rRNA gene between even closely related organisms, and due to PCR artifacts. The taxonomic composition can also be determined from whole-metagenome sequencing data by matching individual sequences against a database of reference genes. One major limitation of prior methods used for this purpose is the use of a universal classification threshold for all genes at all taxonomic levels. We propose that better classification results can be obtained by tuning the taxonomic classifier to each matching length, reference gene, and taxonomic level. We present a novel taxonomic profiler MetaPhyler, which uses marker genes as a taxonomic reference. Results on simulated datasets demonstrate that MetaPhyler outperforms other tools commonly used in this context (CARMA, Megan and PhymmBL). We also present interesting results obtained by applying MetaPhyler to a real metagenomic dataset.}, keywords = {Bioinformatics, CARMA comparison, Databases, Genomics, Linear regression, marker genes, matching length, Megan comparison, metagenomic sequences, metagenomics, MetaPhyler, microbial diversity, microorganisms, molecular biophysics, molecular configurations, Pattern classification, pattern matching, phylogenetic classification, Phylogeny, PhymmBL comparison, reference gene database, Sensitivity, sequence matching, taxonomic classifier, taxonomic level, taxonomic profiling, whole metagenome sequencing data}, isbn = {978-1-4244-8306-8}, author = {Liu, Bo and Gibbons, T. and Ghodsi, M. and M. Pop} } @article {49779, title = {Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL): adapting the Partial Phylogenetic Profiling algorithm to scan sequences for signatures that predict protein function.}, journal = {BMC Bioinformatics}, volume = {11}, year = {2010}, month = {2010}, pages = {52}, abstract = {

BACKGROUND: Comparative genomics methods such as phylogenetic profiling can mine powerful inferences from inherently noisy biological data sets. We introduce Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL), a method that applies the Partial Phylogenetic Profiling (PPP) approach locally within a protein sequence to discover short sequence signatures associated with functional sites. The approach is based on the basic scoring mechanism employed by PPP, namely the use of binomial distribution statistics to optimize sequence similarity cutoffs during searches of partitioned training sets.

RESULTS: Here we illustrate and validate the ability of the SIMBAL method to find functionally relevant short sequence signatures by application to two well-characterized protein families. In the first example, we partitioned a family of ABC permeases using a metabolic background property (urea utilization). Thus, the TRUE set for this family comprised members whose genome of origin encoded a urea utilization system. By moving a sliding window across the sequence of a permease, and searching each subsequence in turn against the full set of partitioned proteins, the method found which local sequence signatures best correlated with the urea utilization trait. Mapping of SIMBAL "hot spots" onto crystal structures of homologous permeases reveals that the significant sites are gating determinants on the cytosolic face rather than, say, docking sites for the substrate-binding protein on the extracellular face. In the second example, we partitioned a protein methyltransferase family using gene proximity as a criterion. In this case, the TRUE set comprised those methyltransferases encoded near the gene for the substrate RF-1. SIMBAL identifies sequence regions that map onto the substrate-binding interface while ignoring regions involved in the methyltransferase reaction mechanism in general. Neither method for training set construction requires any prior experimental characterization.

CONCLUSIONS: SIMBAL shows that, in functionally divergent protein families, selected short sequences often significantly outperform their full-length parent sequence for making functional predictions by sequence similarity, suggesting avenues for improved functional classifiers. When combined with structural data, SIMBAL affords the ability to localize and model functional sites.

}, keywords = {algorithms, Amino Acid Sequence, Gene Expression Profiling, Molecular Sequence Data, Phylogeny, Proteins, Sequence Analysis, Protein, Structure-Activity Relationship}, issn = {1471-2105}, doi = {10.1186/1471-2105-11-52}, author = {Selengut, Jeremy D and Rusch, Douglas B and Haft, Daniel H} } @article {38506, title = {Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL): adapting the Partial Phylogenetic Profiling algorithm to scan sequences for signatures that predict protein function}, journal = {BMC bioinformaticsBMC Bioinformatics}, volume = {11}, year = {2010}, note = {http://www.ncbi.nlm.nih.gov/pubmed/20102603?dopt=Abstract}, type = {10.1186/1471-2105-11-52}, abstract = {BACKGROUND: Comparative genomics methods such as phylogenetic profiling can mine powerful inferences from inherently noisy biological data sets. We introduce Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL), a method that applies the Partial Phylogenetic Profiling (PPP) approach locally within a protein sequence to discover short sequence signatures associated with functional sites. The approach is based on the basic scoring mechanism employed by PPP, namely the use of binomial distribution statistics to optimize sequence similarity cutoffs during searches of partitioned training sets. RESULTS: Here we illustrate and validate the ability of the SIMBAL method to find functionally relevant short sequence signatures by application to two well-characterized protein families. In the first example, we partitioned a family of ABC permeases using a metabolic background property (urea utilization). Thus, the TRUE set for this family comprised members whose genome of origin encoded a urea utilization system. By moving a sliding window across the sequence of a permease, and searching each subsequence in turn against the full set of partitioned proteins, the method found which local sequence signatures best correlated with the urea utilization trait. Mapping of SIMBAL "hot spots" onto crystal structures of homologous permeases reveals that the significant sites are gating determinants on the cytosolic face rather than, say, docking sites for the substrate-binding protein on the extracellular face. In the second example, we partitioned a protein methyltransferase family using gene proximity as a criterion. In this case, the TRUE set comprised those methyltransferases encoded near the gene for the substrate RF-1. SIMBAL identifies sequence regions that map onto the substrate-binding interface while ignoring regions involved in the methyltransferase reaction mechanism in general. Neither method for training set construction requires any prior experimental characterization. CONCLUSIONS: SIMBAL shows that, in functionally divergent protein families, selected short sequences often significantly outperform their full-length parent sequence for making functional predictions by sequence similarity, suggesting avenues for improved functional classifiers. When combined with structural data, SIMBAL affords the ability to localize and model functional sites.}, keywords = {algorithms, Amino Acid Sequence, Gene Expression Profiling, Molecular Sequence Data, Phylogeny, Proteins, Sequence Analysis, Protein, Structure-Activity Relationship}, author = {J. Selengut and Rusch, Douglas B. and Haft, Daniel H.} } @article {38556, title = {Unexpected abundance of coenzyme F(420)-dependent enzymes in Mycobacterium tuberculosis and other actinobacteria}, journal = {Journal of bacteriologyJournal of bacteriology}, volume = {192}, year = {2010}, note = {http://www.ncbi.nlm.nih.gov/pubmed/20675471?dopt=Abstract}, type = {10.1128/JB.00425-10}, abstract = {Regimens targeting Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), require long courses of treatment and a combination of three or more drugs. An increase in drug-resistant strains of M. tuberculosis demonstrates the need for additional TB-specific drugs. A notable feature of M. tuberculosis is coenzyme F(420), which is distributed sporadically and sparsely among prokaryotes. This distribution allows for comparative genomics-based investigations. Phylogenetic profiling (comparison of differential gene content) based on F(420) biosynthesis nominated many actinobacterial proteins as candidate F(420)-dependent enzymes. Three such families dominated the results: the luciferase-like monooxygenase (LLM), pyridoxamine 5{\textquoteright}-phosphate oxidase (PPOX), and deazaflavin-dependent nitroreductase (DDN) families. The DDN family was determined to be limited to F(420)-producing species. The LLM and PPOX families were observed in F(420)-producing species as well as species lacking F(420) but were particularly numerous in many actinobacterial species, including M. tuberculosis. Partitioning the LLM and PPOX families based on an organism{\textquoteright}s ability to make F(420) allowed the application of the SIMBAL (sites inferred by metabolic background assertion labeling) profiling method to identify F(420)-correlated subsequences. These regions were found to correspond to flavonoid cofactor binding sites. Significantly, these results showed that M. tuberculosis carries at least 28 separate F(420)-dependent enzymes, most of unknown function, and a paucity of flavin mononucleotide (FMN)-dependent proteins in these families. While prevalent in mycobacteria, markers of F(420) biosynthesis appeared to be absent from the normal human gut flora. These findings suggest that M. tuberculosis relies heavily on coenzyme F(420) for its redox reactions. This dependence and the cofactor{\textquoteright}s rarity may make F(420)-related proteins promising drug targets.}, keywords = {Actinobacteria, Amino Acid Sequence, Binding Sites, Coenzymes, Flavonoids, Gene Expression Profiling, Gene Expression Regulation, Bacterial, Genome, Bacterial, molecular biology, Molecular Sequence Data, Molecular Structure, Mycobacterium tuberculosis, Phylogeny, Protein Conformation, Riboflavin}, author = {J. Selengut and Haft, Daniel H.} } @article {49778, title = {Unexpected abundance of coenzyme F(420)-dependent enzymes in Mycobacterium tuberculosis and other actinobacteria.}, journal = {J Bacteriol}, volume = {192}, year = {2010}, month = {2010 Nov}, pages = {5788-98}, abstract = {

Regimens targeting Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), require long courses of treatment and a combination of three or more drugs. An increase in drug-resistant strains of M. tuberculosis demonstrates the need for additional TB-specific drugs. A notable feature of M. tuberculosis is coenzyme F(420), which is distributed sporadically and sparsely among prokaryotes. This distribution allows for comparative genomics-based investigations. Phylogenetic profiling (comparison of differential gene content) based on F(420) biosynthesis nominated many actinobacterial proteins as candidate F(420)-dependent enzymes. Three such families dominated the results: the luciferase-like monooxygenase (LLM), pyridoxamine 5{\textquoteright}-phosphate oxidase (PPOX), and deazaflavin-dependent nitroreductase (DDN) families. The DDN family was determined to be limited to F(420)-producing species. The LLM and PPOX families were observed in F(420)-producing species as well as species lacking F(420) but were particularly numerous in many actinobacterial species, including M. tuberculosis. Partitioning the LLM and PPOX families based on an organism{\textquoteright}s ability to make F(420) allowed the application of the SIMBAL (sites inferred by metabolic background assertion labeling) profiling method to identify F(420)-correlated subsequences. These regions were found to correspond to flavonoid cofactor binding sites. Significantly, these results showed that M. tuberculosis carries at least 28 separate F(420)-dependent enzymes, most of unknown function, and a paucity of flavin mononucleotide (FMN)-dependent proteins in these families. While prevalent in mycobacteria, markers of F(420) biosynthesis appeared to be absent from the normal human gut flora. These findings suggest that M. tuberculosis relies heavily on coenzyme F(420) for its redox reactions. This dependence and the cofactor{\textquoteright}s rarity may make F(420)-related proteins promising drug targets.

}, keywords = {Actinobacteria, Amino Acid Sequence, Binding Sites, Coenzymes, Flavonoids, Gene Expression Profiling, Gene Expression Regulation, Bacterial, Genome, Bacterial, molecular biology, Molecular Sequence Data, Molecular Structure, Mycobacterium tuberculosis, Phylogeny, Protein Conformation, Riboflavin}, issn = {1098-5530}, doi = {10.1128/JB.00425-10}, author = {Selengut, Jeremy D and Haft, Daniel H} } @article {38561, title = {Validating the systematic position of {\i}t Plationus Segers, Murugan \& Dumont, 1993 (Rotifera: Brachionidae) using sequences of the large subunit of the nuclear ribosomal DNA and of cytochrome C oxidase}, journal = {HydrobiologiaHydrobiologia}, volume = {644}, year = {2010}, type = {DOI 10.1007/s10750-010-0203-1}, abstract = {Members of the family Brachionidae are free-living organisms that range in size from 170 to 250 microns. They comprise part of the zooplankton in freshwater and marine systems worldwide. Morphologically, members of the family are characterized by a single piece loricated body without furrows, grooves, sulci or dorsal head shields, and a malleate trophi. Differences in these structures have been traditionally used to recognize 217 species that are classified into seven genera. However, the validity of the species, Plationus patulus, P. patulus macracanthus P. polyacanthus, and P. felicitas have been confused because they were alternatively assigned in Brachionus or Platyias, when considering only morphological and ecological characters. Based on scanning electron microscope (SEM) images of the trophi, these taxa were assigned in a new genus, Plationus. In this study, we examined the systematic position of P. patulus and P. patulus macracanthus using DNA sequences of two genes: the cytochrome oxidase subunit 1 (cox1) and domains D2 and D3 of the large subunit of the nuclear ribosomal RNA (LSU). In addition, the cox1 and LSU sequences representing five genera of Brachionidae (Anuraeopsis, Brachionus, Keratella, Plationus, and Platyias) plus four species of three families from the order Ploima were used as the outgroup. The maximum likelihood (ML) analyses were conducted for each individual gene as well as for the combined (cox1 + LSU) data set. The ML tree from the combined data set yielded the family Brachionidae as a monophyletic group with weak bootstrap support (< 50\%). Five main clades in this tree had high (> 85\%) bootstrap support. The first clade was composed of three populations of P. patulus + P. patulus macracanthus. The second clade was composed of a single species of Platyias. The third clade was composed of six species of Brachionus. The fourth clade included a single species of the genus Anuraeopsis, and the fifth clade was composed of three species of the genus Keratella. The genetic divergence between Plationus and Platyias ranged from 18.4 to 19.2\% for cox1, and from 4.5 to 4.9\% for LSU, and between Brachionus and Plationus, it ranged from 16.9 to 23.1\% (cox1), and from 7.3 to 9.1\% (LSU). Morphological evidence, the amount of genetic divergence, the systematic position of Plationus within the family Brachionidae, and the position of Plationus as a sister group of Brachionus and Platyias support the validity of Plationus patulus and P. patulus macracanthus into the genus Plationus.}, keywords = {Cox1, likelihood, LSU, maximum, Phylogeny, Plationus}, author = {Reyna-Fabian, M. E. and Laclette, J. P. and Michael P. Cummings and Garc{\'\i}a-Varela, M.} } @article {49780, title = {Three genomes from the phylum Acidobacteria provide insight into the lifestyles of these microorganisms in soils.}, journal = {Appl Environ Microbiol}, volume = {75}, year = {2009}, month = {2009 Apr}, pages = {2046-56}, abstract = {

The complete genomes of three strains from the phylum Acidobacteria were compared. Phylogenetic analysis placed them as a unique phylum. They share genomic traits with members of the Proteobacteria, the Cyanobacteria, and the Fungi. The three strains appear to be versatile heterotrophs. Genomic and culture traits indicate the use of carbon sources that span simple sugars to more complex substrates such as hemicellulose, cellulose, and chitin. The genomes encode low-specificity major facilitator superfamily transporters and high-affinity ABC transporters for sugars, suggesting that they are best suited to low-nutrient conditions. They appear capable of nitrate and nitrite reduction but not N(2) fixation or denitrification. The genomes contained numerous genes that encode siderophore receptors, but no evidence of siderophore production was found, suggesting that they may obtain iron via interaction with other microorganisms. The presence of cellulose synthesis genes and a large class of novel high-molecular-weight excreted proteins suggests potential traits for desiccation resistance, biofilm formation, and/or contribution to soil structure. Polyketide synthase and macrolide glycosylation genes suggest the production of novel antimicrobial compounds. Genes that encode a variety of novel proteins were also identified. The abundance of acidobacteria in soils worldwide and the breadth of potential carbon use by the sequenced strains suggest significant and previously unrecognized contributions to the terrestrial carbon cycle. Combining our genomic evidence with available culture traits, we postulate that cells of these isolates are long-lived, divide slowly, exhibit slow metabolic rates under low-nutrient conditions, and are well equipped to tolerate fluctuations in soil hydration.

}, keywords = {Anti-Bacterial Agents, bacteria, Biological Transport, Carbohydrate Metabolism, Cyanobacteria, DNA, Bacterial, Fungi, Genome, Bacterial, Macrolides, Molecular Sequence Data, Nitrogen, Phylogeny, Proteobacteria, Sequence Analysis, DNA, Sequence Homology, Soil Microbiology}, issn = {1098-5336}, doi = {10.1128/AEM.02294-08}, author = {Ward, Naomi L and Challacombe, Jean F and Janssen, Peter H and Henrissat, Bernard and Coutinho, Pedro M and Wu, Martin and Xie, Gary and Haft, Daniel H and Sait, Michelle and Badger, Jonathan and Barabote, Ravi D and Bradley, Brent and Brettin, Thomas S and Brinkac, Lauren M and Bruce, David and Creasy, Todd and Daugherty, Sean C and Davidsen, Tanja M and DeBoy, Robert T and Detter, J Chris and Dodson, Robert J and Durkin, A Scott and Ganapathy, Anuradha and Gwinn-Giglio, Michelle and Han, Cliff S and Khouri, Hoda and Kiss, Hajnalka and Kothari, Sagar P and Madupu, Ramana and Nelson, Karen E and Nelson, William C and Paulsen, Ian and Penn, Kevin and Ren, Qinghu and Rosovitz, M J and Selengut, Jeremy D and Shrivastava, Susmita and Sullivan, Steven A and Tapia, Roxanne and Thompson, L Sue and Watkins, Kisha L and Yang, Qi and Yu, Chunhui and Zafar, Nikhat and Zhou, Liwei and Kuske, Cheryl R} } @article {38528, title = {Three genomes from the phylum Acidobacteria provide insight into the lifestyles of these microorganisms in soils}, journal = {Applied and environmental microbiologyApplied and environmental microbiology}, volume = {75}, year = {2009}, note = {http://www.ncbi.nlm.nih.gov/pubmed/19201974?dopt=Abstract}, type = {10.1128/AEM.02294-08}, abstract = {The complete genomes of three strains from the phylum Acidobacteria were compared. Phylogenetic analysis placed them as a unique phylum. They share genomic traits with members of the Proteobacteria, the Cyanobacteria, and the Fungi. The three strains appear to be versatile heterotrophs. Genomic and culture traits indicate the use of carbon sources that span simple sugars to more complex substrates such as hemicellulose, cellulose, and chitin. The genomes encode low-specificity major facilitator superfamily transporters and high-affinity ABC transporters for sugars, suggesting that they are best suited to low-nutrient conditions. They appear capable of nitrate and nitrite reduction but not N(2) fixation or denitrification. The genomes contained numerous genes that encode siderophore receptors, but no evidence of siderophore production was found, suggesting that they may obtain iron via interaction with other microorganisms. The presence of cellulose synthesis genes and a large class of novel high-molecular-weight excreted proteins suggests potential traits for desiccation resistance, biofilm formation, and/or contribution to soil structure. Polyketide synthase and macrolide glycosylation genes suggest the production of novel antimicrobial compounds. Genes that encode a variety of novel proteins were also identified. The abundance of acidobacteria in soils worldwide and the breadth of potential carbon use by the sequenced strains suggest significant and previously unrecognized contributions to the terrestrial carbon cycle. Combining our genomic evidence with available culture traits, we postulate that cells of these isolates are long-lived, divide slowly, exhibit slow metabolic rates under low-nutrient conditions, and are well equipped to tolerate fluctuations in soil hydration.}, keywords = {Anti-Bacterial Agents, bacteria, Biological Transport, Carbohydrate Metabolism, Cyanobacteria, DNA, Bacterial, Fungi, Genome, Bacterial, Macrolides, Molecular Sequence Data, Nitrogen, Phylogeny, Proteobacteria, Sequence Analysis, DNA, Sequence Homology, Soil Microbiology}, author = {Ward, Naomi L. and Challacombe, Jean F. and Janssen, Peter H. and Henrissat, Bernard and Coutinho, Pedro M. and Wu, Martin and Xie, Gary and Haft, Daniel H. and Sait, Michelle and Badger, Jonathan and Barabote, Ravi D. and Bradley, Brent and Brettin, Thomas S. and Brinkac, Lauren M. and Bruce, David and Creasy, Todd and Daugherty, Sean C. and Davidsen, Tanja M. and DeBoy, Robert T. and Detter, J. Chris and Dodson, Robert J. and Durkin, A. Scott and Ganapathy, Anuradha and Gwinn-Giglio, Michelle and Han, Cliff S. and Khouri, Hoda and Kiss, Hajnalka and Kothari, Sagar P. and Madupu, Ramana and Nelson, Karen E. and Nelson, William C. and Paulsen, Ian and Penn, Kevin and Ren, Qinghu and Rosovitz, M. J. and J. Selengut and Shrivastava, Susmita and Sullivan, Steven A. and Tapia, Roxanne and Thompson, L. Sue and Watkins, Kisha L. and Yang, Qi and Yu, Chunhui and Zafar, Nikhat and Zhou, Liwei and Kuske, Cheryl R.} } @article {38279, title = {A GENEALOGICAL APPROACH TO QUANTIFYING LINEAGE DIVERGENCE}, journal = {EvolutionEvolution}, volume = {62}, year = {2008}, type = {10.1111/j.1558-5646.2008.00442.x}, abstract = {We introduce a statistic, the genealogical sorting index (gsi), for quantifying the degree of exclusive ancestry of labeled groups on a rooted genealogy and demonstrate its application. The statistic is simple, intuitive, and easily calculated. It has a normalized range to facilitate comparisons among different groups, trees, or studies and it provides information on individual groups rather than a composite measure for all groups. It naturally handles polytomies and accommodates measures of uncertainty in phylogenetic relationships. We use coalescent simulations to explore the behavior of the gsi across a range of divergence times, with the mean value increasing to 1, the maximum value when exclusivity within a group reached monophyly. Simulations also demonstrate that the power to reject the null hypothesis of mixed genealogical ancestry increased markedly as sample size increased, and that the gsi provides a statistically more powerful measure of divergence than FST. Applications to data from published studies demonstrated that the gsi provides a useful way to detect significant exclusivity even when groups are not monophyletic. Although we describe this statistic in the context of divergence, it is more broadly applicable to quantify and assess the significance of clustering of observations in labeled groups on any tree.}, keywords = {Ancestral polymorphism, congruence, exclusivity, genealogy, lineage sorting, monophyly, paraphyly, Phylogeny, polyphyly, speciation, species}, isbn = {1558-5646}, author = {Michael P. Cummings and Neel, Maile C. and Shaw, Kerry L.} } @proceedings {38555, title = {Uncovering Genomic Reassortments among Influenza Strains by Enumerating Maximal Bicliques}, year = {2008}, month = {2008}, publisher = {IEEE}, type = {10.1109/BIBM.2008.78}, abstract = {The evolutionary histories of viral genomes have received significant recent attention due to their importance in understanding virulence and the corresponding ramifications to public health. We present a novel framework to detect reassortment events in influenza based on the comparison of two distributions of phylogenetic trees, rather than a pair of, possibly unreliable, consensus trees. We show how to detect all high-probability inconsistencies between two distributions of trees by enumerating maximal bicliques within a defined incompatibility graph. In the process, we give the first quadratic delay algorithm for enumerating maximal bicliques within general bipartite graphs. We demonstrate the utility of our approach by applying it to several sets of influenza genomes (both human- and avian-hosted) and successfully identify all known reassortment events and a few novel candidate reassortments. In addition, on simulated datasets, our approach correctly finds implanted reassortments and rarely detects reassortments where none were introduced.}, keywords = {avian hosted influenza genome, Bioinformatics, Capacitive sensors, Delay, diseases, Event detection, general bipartite graphs, genomic reassortments, Genomics, graph theory, high probability inconsistencies, History, human hosted influenza genome, incompatibility graph, Influenza, influenza strain, maximal biclique, maximal biclique enumeration, microorganisms, phylogenetic trees, Phylogeny, Public healthcare, quadratic delay algorithm, reassortment, reassortment event detection, Tree graphs, viral genome evolutionary history, virulence}, isbn = {978-0-7695-3452-7}, author = {Nagarajan, N. and Kingsford, Carl} } @article {49677, title = {Evolution of genes and genomes on the Drosophila phylogeny.}, journal = {Nature}, volume = {450}, year = {2007}, month = {2007 Nov 8}, pages = {203-18}, abstract = {

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

}, keywords = {Animals, Codon, DNA Transposable Elements, Drosophila, Drosophila Proteins, Evolution, Molecular, Gene Order, Genes, Insect, Genome, Insect, Genome, Mitochondrial, Genomics, Immunity, Multigene Family, Phylogeny, Reproduction, RNA, Untranslated, sequence alignment, Sequence Analysis, DNA, Synteny}, issn = {1476-4687}, doi = {10.1038/nature06341}, author = {Clark, Andrew G and Eisen, Michael B and Smith, Douglas R and Bergman, Casey M and Oliver, Brian and Markow, Therese A and Kaufman, Thomas C and Kellis, Manolis and Gelbart, William and Iyer, Venky N and Pollard, Daniel A and Sackton, Timothy B and Larracuente, Amanda M and Singh, Nadia D and Abad, Jose P and Abt, Dawn N and Adryan, Boris and Aguade, Montserrat and Akashi, Hiroshi and Anderson, Wyatt W and Aquadro, Charles F and Ardell, David H and Arguello, Roman and Artieri, Carlo G and Barbash, Daniel A and Barker, Daniel and Barsanti, Paolo and Batterham, Phil and Batzoglou, Serafim and Begun, Dave and Bhutkar, Arjun and Blanco, Enrico and Bosak, Stephanie A and Bradley, Robert K and Brand, Adrianne D and Brent, Michael R and Brooks, Angela N and Brown, Randall H and Butlin, Roger K and Caggese, Corrado and Calvi, Brian R and Bernardo de Carvalho, A and Caspi, Anat and Castrezana, Sergio and Celniker, Susan E and Chang, Jean L and Chapple, Charles and Chatterji, Sourav and Chinwalla, Asif and Civetta, Alberto and Clifton, Sandra W and Comeron, Josep M and Costello, James C and Coyne, Jerry A and Daub, Jennifer and David, Robert G and Delcher, Arthur L and Delehaunty, Kim and Do, Chuong B and Ebling, Heather and Edwards, Kevin and Eickbush, Thomas and Evans, Jay D and Filipski, Alan and Findeiss, Sven and Freyhult, Eva and Fulton, Lucinda and Fulton, Robert and Garcia, Ana C L and Gardiner, Anastasia and Garfield, David A and Garvin, Barry E and Gibson, Greg and Gilbert, Don and Gnerre, Sante and Godfrey, Jennifer and Good, Robert and Gotea, Valer and Gravely, Brenton and Greenberg, Anthony J and Griffiths-Jones, Sam and Gross, Samuel and Guigo, Roderic and Gustafson, Erik A and Haerty, Wilfried and Hahn, Matthew W and Halligan, Daniel L and Halpern, Aaron L and Halter, Gillian M and Han, Mira V and Heger, Andreas and Hillier, LaDeana and Hinrichs, Angie S and Holmes, Ian and Hoskins, Roger A and Hubisz, Melissa J and Hultmark, Dan and Huntley, Melanie A and Jaffe, David B and Jagadeeshan, Santosh and Jeck, William R and Johnson, Justin and Jones, Corbin D and Jordan, William C and Karpen, Gary H and Kataoka, Eiko and Keightley, Peter D and Kheradpour, Pouya and Kirkness, Ewen F and Koerich, Leonardo B and Kristiansen, Karsten and Kudrna, Dave and Kulathinal, Rob J and Kumar, Sudhir and Kwok, Roberta and Lander, Eric and Langley, Charles H and Lapoint, Richard and Lazzaro, Brian P and Lee, So-Jeong and Levesque, Lisa and Li, Ruiqiang and Lin, Chiao-Feng and Lin, Michael F and Lindblad-Toh, Kerstin and Llopart, Ana and Long, Manyuan and Low, Lloyd and Lozovsky, Elena and Lu, Jian and Luo, Meizhong and Machado, Carlos A and Makalowski, Wojciech and Marzo, Mar and Matsuda, Muneo and Matzkin, Luciano and McAllister, Bryant and McBride, Carolyn S and McKernan, Brendan and McKernan, Kevin and Mendez-Lago, Maria and Minx, Patrick and Mollenhauer, Michael U and Montooth, Kristi and Mount, Stephen M and Mu, Xu and Myers, Eugene and Negre, Barbara and Newfeld, Stuart and Nielsen, Rasmus and Noor, Mohamed A F and O{\textquoteright}Grady, Patrick and Pachter, Lior and Papaceit, Montserrat and Parisi, Matthew J and Parisi, Michael and Parts, Leopold and Pedersen, Jakob S and Pesole, Graziano and Phillippy, Adam M and Ponting, Chris P and Pop, Mihai and Porcelli, Damiano and Powell, Jeffrey R and Prohaska, Sonja and Pruitt, Kim and Puig, Marta and Quesneville, Hadi and Ram, Kristipati Ravi and Rand, David and Rasmussen, Matthew D and Reed, Laura K and Reenan, Robert and Reily, Amy and Remington, Karin A and Rieger, Tania T and Ritchie, Michael G and Robin, Charles and Rogers, Yu-Hui and Rohde, Claudia and Rozas, Julio and Rubenfield, Marc J and Ruiz, Alfredo and Russo, Susan and Salzberg, Steven L and Sanchez-Gracia, Alejandro and Saranga, David J and Sato, Hajime and Schaeffer, Stephen W and Schatz, Michael C and Schlenke, Todd and Schwartz, Russell and Segarra, Carmen and Singh, Rama S and Sirot, Laura and Sirota, Marina and Sisneros, Nicholas B and Smith, Chris D and Smith, Temple F and Spieth, John and Stage, Deborah E and Stark, Alexander and Stephan, Wolfgang and Strausberg, Robert L and Strempel, Sebastian and Sturgill, David and Sutton, Granger and Sutton, Granger G and Tao, Wei and Teichmann, Sarah and Tobari, Yoshiko N and Tomimura, Yoshihiko and Tsolas, Jason M and Valente, Vera L S and Venter, Eli and Venter, J Craig and Vicario, Saverio and Vieira, Filipe G and Vilella, Albert J and Villasante, Alfredo and Walenz, Brian and Wang, Jun and Wasserman, Marvin and Watts, Thomas and Wilson, Derek and Wilson, Richard K and Wing, Rod A and Wolfner, Mariana F and Wong, Alex and Wong, Gane Ka-Shu and Wu, Chung-I and Wu, Gabriel and Yamamoto, Daisuke and Yang, Hsiao-Pei and Yang, Shiaw-Pyng and Yorke, James A and Yoshida, Kiyohito and Zdobnov, Evgeny and Zhang, Peili and Zhang, Yu and Zimin, Aleksey V and Baldwin, Jennifer and Abdouelleil, Amr and Abdulkadir, Jamal and Abebe, Adal and Abera, Brikti and Abreu, Justin and Acer, St Christophe and Aftuck, Lynne and Alexander, Allen and An, Peter and Anderson, Erica and Anderson, Scott and Arachi, Harindra and Azer, Marc and Bachantsang, Pasang and Barry, Andrew and Bayul, Tashi and Berlin, Aaron and Bessette, Daniel and Bloom, Toby and Blye, Jason and Boguslavskiy, Leonid and Bonnet, Claude and Boukhgalter, Boris and Bourzgui, Imane and Brown, Adam and Cahill, Patrick and Channer, Sheridon and Cheshatsang, Yama and Chuda, Lisa and Citroen, Mieke and Collymore, Alville and Cooke, Patrick and Costello, Maura and D{\textquoteright}Aco, Katie and Daza, Riza and De Haan, Georgius and DeGray, Stuart and DeMaso, Christina and Dhargay, Norbu and Dooley, Kimberly and Dooley, Erin and Doricent, Missole and Dorje, Passang and Dorjee, Kunsang and Dupes, Alan and Elong, Richard and Falk, Jill and Farina, Abderrahim and Faro, Susan and Ferguson, Diallo and Fisher, Sheila and Foley, Chelsea D and Franke, Alicia and Friedrich, Dennis and Gadbois, Loryn and Gearin, Gary and Gearin, Christina R and Giannoukos, Georgia and Goode, Tina and Graham, Joseph and Grandbois, Edward and Grewal, Sharleen and Gyaltsen, Kunsang and Hafez, Nabil and Hagos, Birhane and Hall, Jennifer and Henson, Charlotte and Hollinger, Andrew and Honan, Tracey and Huard, Monika D and Hughes, Leanne and Hurhula, Brian and Husby, M Erii and Kamat, Asha and Kanga, Ben and Kashin, Seva and Khazanovich, Dmitry and Kisner, Peter and Lance, Krista and Lara, Marcia and Lee, William and Lennon, Niall and Letendre, Frances and LeVine, Rosie and Lipovsky, Alex and Liu, Xiaohong and Liu, Jinlei and Liu, Shangtao and Lokyitsang, Tashi and Lokyitsang, Yeshi and Lubonja, Rakela and Lui, Annie and MacDonald, Pen and Magnisalis, Vasilia and Maru, Kebede and Matthews, Charles and McCusker, William and McDonough, Susan and Mehta, Teena and Meldrim, James and Meneus, Louis and Mihai, Oana and Mihalev, Atanas and Mihova, Tanya and Mittelman, Rachel and Mlenga, Valentine and Montmayeur, Anna and Mulrain, Leonidas and Navidi, Adam and Naylor, Jerome and Negash, Tamrat and Nguyen, Thu and Nguyen, Nga and Nicol, Robert and Norbu, Choe and Norbu, Nyima and Novod, Nathaniel and O{\textquoteright}Neill, Barry and Osman, Sahal and Markiewicz, Eva and Oyono, Otero L and Patti, Christopher and Phunkhang, Pema and Pierre, Fritz and Priest, Margaret and Raghuraman, Sujaa and Rege, Filip and Reyes, Rebecca and Rise, Cecil and Rogov, Peter and Ross, Keenan and Ryan, Elizabeth and Settipalli, Sampath and Shea, Terry and Sherpa, Ngawang and Shi, Lu and Shih, Diana and Sparrow, Todd and Spaulding, Jessica and Stalker, John and Stange-Thomann, Nicole and Stavropoulos, Sharon and Stone, Catherine and Strader, Christopher and Tesfaye, Senait and Thomson, Talene and Thoulutsang, Yama and Thoulutsang, Dawa and Topham, Kerri and Topping, Ira and Tsamla, Tsamla and Vassiliev, Helen and Vo, Andy and Wangchuk, Tsering and Wangdi, Tsering and Weiand, Michael and Wilkinson, Jane and Wilson, Adam and Yadav, Shailendra and Young, Geneva and Yu, Qing and Zembek, Lisa and Zhong, Danni and Zimmer, Andrew and Zwirko, Zac and Jaffe, David B and Alvarez, Pablo and Brockman, Will and Butler, Jonathan and Chin, CheeWhye and Gnerre, Sante and Grabherr, Manfred and Kleber, Michael and Mauceli, Evan and MacCallum, Iain} } @article {49681, title = {Spliceosomal small nuclear RNA genes in 11 insect genomes.}, journal = {RNA}, volume = {13}, year = {2007}, month = {2007 Jan}, pages = {5-14}, abstract = {

The removal of introns from the primary transcripts of protein-coding genes is accomplished by the spliceosome, a large macromolecular complex of which small nuclear RNAs (snRNAs) are crucial components. Following the recent sequencing of the honeybee (Apis mellifera) genome, we used various computational methods, ranging from sequence similarity search to RNA secondary structure prediction, to search for putative snRNA genes (including their promoters) and to examine their pattern of conservation among 11 available insect genomes (A. mellifera, Tribolium castaneum, Bombyx mori, Anopheles gambiae, Aedes aegypti, and six Drosophila species). We identified candidates for all nine spliceosomal snRNA genes in all the analyzed genomes. All the species contain a similar number of snRNA genes, with the exception of A. aegypti, whose genome contains more U1, U2, and U5 genes, and A. mellifera, whose genome contains fewer U2 and U5 genes. We found that snRNA genes are generally more closely related to homologs within the same genus than to those in other genera. Promoter regions for all spliceosomal snRNA genes within each insect species share similar sequence motifs that are likely to correspond to the PSEA (proximal sequence element A), the binding site for snRNA activating protein complex, but these promoter elements vary in sequence among the five insect families surveyed here. In contrast to the other insect species investigated, Dipteran genomes are characterized by a rapid evolution (or loss) of components of the U12 spliceosome and a striking loss of U12-type introns.

}, keywords = {Animals, Base Sequence, Bees, Computational Biology, Diptera, Evolution, Molecular, Genes, Insect, Genome, Insect, Molecular Sequence Data, Nucleic Acid Conformation, Phylogeny, Promoter Regions, Genetic, RNA Splicing, RNA, Small Nuclear, Sequence Analysis, RNA, Spliceosomes}, issn = {1355-8382}, doi = {10.1261/rna.259207}, author = {Mount, Stephen M and Gotea, Valer and Lin, Chiao-Feng and Hernandez, Kristina and Makalowski, Wojciech} } @article {38530, title = {TIGRFAMs and Genome Properties: tools for the assignment of molecular function and biological process in prokaryotic genomes}, journal = {Nucleic acids researchNucleic Acids Research}, volume = {35}, year = {2007}, note = {http://www.ncbi.nlm.nih.gov/pubmed/17151080?dopt=Abstract}, type = {10.1093/nar/gkl1043}, abstract = {TIGRFAMs is a collection of protein family definitions built to aid in high-throughput annotation of specific protein functions. Each family is based on a hidden Markov model (HMM), where both cutoff scores and membership in the seed alignment are chosen so that the HMMs can classify numerous proteins according to their specific molecular functions. Most TIGRFAMs models describe {\textquoteright}equivalog{\textquoteright} families, where both orthology and lateral gene transfer may be part of the evolutionary history, but where a single molecular function has been conserved. The Genome Properties system contains a queriable set of metabolic reconstructions, genome metrics and extractions of information from the scientific literature. Its genome-by-genome assertions of whether or not specific structures, pathways or systems are present provide high-level conceptual descriptions of genomic content. These assertions enable comparative genomics, provide a meaningful biological context to aid in manual annotation, support assignments of Gene Ontology (GO) biological process terms and help validate HMM-based predictions of protein function. The Genome Properties system is particularly useful as a generator of phylogenetic profiles, through which new protein family functions may be discovered. The TIGRFAMs and Genome Properties systems can be accessed at http://www.tigr.org/TIGRFAMs and http://www.tigr.org/Genome_Properties.}, keywords = {Archaeal Proteins, Bacterial Proteins, Databases, Protein, Genome, Bacterial, Genomics, Internet, Phylogeny, software, User-Computer Interface}, author = {J. Selengut and Haft, Daniel H. and Davidsen, Tanja and Ganapathy, Anurhada and Gwinn-Giglio, Michelle and Nelson, William C. and Richter, R. Alexander and White, Owen} } @article {38161, title = {Comparative genomics of emerging human ehrlichiosis agents}, journal = {PLoS geneticsPLoS genetics}, volume = {2}, year = {2006}, note = {http://www.ncbi.nlm.nih.gov/pubmed/16482227?dopt=Abstract}, type = {10.1371/journal.pgen.0020021}, abstract = {Anaplasma (formerly Ehrlichia) phagocytophilum, Ehrlichia chaffeensis, and Neorickettsia (formerly Ehrlichia) sennetsu are intracellular vector-borne pathogens that cause human ehrlichiosis, an emerging infectious disease. We present the complete genome sequences of these organisms along with comparisons to other organisms in the Rickettsiales order. Ehrlichia spp. and Anaplasma spp. display a unique large expansion of immunodominant outer membrane proteins facilitating antigenic variation. All Rickettsiales have a diminished ability to synthesize amino acids compared to their closest free-living relatives. Unlike members of the Rickettsiaceae family, these pathogenic Anaplasmataceae are capable of making all major vitamins, cofactors, and nucleotides, which could confer a beneficial role in the invertebrate vector or the vertebrate host. Further analysis identified proteins potentially involved in vacuole confinement of the Anaplasmataceae, a life cycle involving a hematophagous vector, vertebrate pathogenesis, human pathogenesis, and lack of transovarial transmission. These discoveries provide significant insights into the biology of these obligate intracellular pathogens.}, keywords = {Animals, Biotin, DNA Repair, Ehrlichia, Ehrlichiosis, Genome, Genomics, HUMANS, Models, Biological, Phylogeny, Rickettsia, Ticks}, author = {Dunning Hotopp, Julie C. and Lin, Mingqun and Madupu, Ramana and Crabtree, Jonathan and Angiuoli, Samuel V. and Eisen, Jonathan A. and Eisen, Jonathan and Seshadri, Rekha and Ren, Qinghu and Wu, Martin and Utterback, Teresa R. and Smith, Shannon and Lewis, Matthew and Khouri, Hoda and Zhang, Chunbin and Niu, Hua and Lin, Quan and Ohashi, Norio and Zhi, Ning and Nelson, William and Brinkac, Lauren M. and Dodson, Robert J. and Rosovitz, M. J. and Sundaram, Jaideep and Daugherty, Sean C. and Davidsen, Tanja and Durkin, Anthony S. and Gwinn, Michelle and Haft, Daniel H. and J. Selengut and Sullivan, Steven A. and Zafar, Nikhat and Zhou, Liwei and Benahmed, Faiza and Forberger, Heather and Halpin, Rebecca and Mulligan, Stephanie and Robinson, Jeffrey and White, Owen and Rikihisa, Yasuko and Tettelin, Herv{\'e}} } @article {38247, title = {Exopolysaccharide-associated protein sorting in environmental organisms: the PEP-CTERM/EpsH system. Application of a novel phylogenetic profiling heuristic}, journal = {BMC biologyBMC biology}, volume = {4}, year = {2006}, note = {http://www.ncbi.nlm.nih.gov/pubmed/16930487?dopt=Abstract}, type = {10.1186/1741-7007-4-29}, abstract = {BACKGROUND: Protein translocation to the proper cellular destination may be guided by various classes of sorting signals recognizable in the primary sequence. Detection in some genomes, but not others, may reveal sorting system components by comparison of the phylogenetic profile of the class of sorting signal to that of various protein families. RESULTS: We describe a short C-terminal homology domain, sporadically distributed in bacteria, with several key characteristics of protein sorting signals. The domain includes a near-invariant motif Pro-Glu-Pro (PEP). This possible recognition or processing site is followed by a predicted transmembrane helix and a cluster rich in basic amino acids. We designate this domain PEP-CTERM. It tends to occur multiple times in a genome if it occurs at all, with a median count of eight instances; Verrucomicrobium spinosum has sixty-five. PEP-CTERM-containing proteins generally contain an N-terminal signal peptide and exhibit high diversity and little homology to known proteins. All bacteria with PEP-CTERM have both an outer membrane and exopolysaccharide (EPS) production genes. By a simple heuristic for screening phylogenetic profiles in the absence of pre-formed protein families, we discovered that a homolog of the membrane protein EpsH (exopolysaccharide locus protein H) occurs in a species when PEP-CTERM domains are found. The EpsH family contains invariant residues consistent with a transpeptidase function. Most PEP-CTERM proteins are encoded by single-gene operons preceded by large intergenic regions. In the Proteobacteria, most of these upstream regions share a DNA sequence, a probable cis-regulatory site that contains a sigma-54 binding motif. The phylogenetic profile for this DNA sequence exactly matches that of three proteins: a sigma-54-interacting response regulator (PrsR), a transmembrane histidine kinase (PrsK), and a TPR protein (PrsT). CONCLUSION: These findings are consistent with the hypothesis that PEP-CTERM and EpsH form a protein export sorting system, analogous to the LPXTG/sortase system of Gram-positive bacteria, and correlated to EPS expression. It occurs preferentially in bacteria from sediments, soils, and biofilms. The novel method that led to these findings, partial phylogenetic profiling, requires neither global sequence clustering nor arbitrary similarity cutoffs and appears to be a rapid, effective alternative to other profiling methods.}, keywords = {Amino Acid Motifs, Amino Acid Sequence, bacteria, Bacterial Proteins, Biofilms, Genome, Bacterial, Markov chains, Molecular Sequence Data, Phylogeny, Polysaccharides, Bacterial, Protein Sorting Signals, Protein Transport, Seawater, sequence alignment, Soil Microbiology}, author = {Haft, Daniel H. and Paulsen, Ian T. and Ward, Naomi and J. Selengut} } @article {38287, title = {Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial "pan-genome"}, journal = {Proceedings of the National Academy of Sciences of the United States of AmericaProceedings of the National Academy of Sciences of the United States of America}, volume = {102}, year = {2005}, note = {http://www.ncbi.nlm.nih.gov/pubmed/16172379?dopt=Abstract}, type = {10.1073/pnas.0506758102}, abstract = {The development of efficient and inexpensive genome sequencing methods has revolutionized the study of human bacterial pathogens and improved vaccine design. Unfortunately, the sequence of a single genome does not reflect how genetic variability drives pathogenesis within a bacterial species and also limits genome-wide screens for vaccine candidates or for antimicrobial targets. We have generated the genomic sequence of six strains representing the five major disease-causing serotypes of Streptococcus agalactiae, the main cause of neonatal infection in humans. Analysis of these genomes and those available in databases showed that the S. agalactiae species can be described by a pan-genome consisting of a core genome shared by all isolates, accounting for approximately 80\% of any single genome, plus a dispensable genome consisting of partially shared and strain-specific genes. Mathematical extrapolation of the data suggests that the gene reservoir available for inclusion in the S. agalactiae pan-genome is vast and that unique genes will continue to be identified even after sequencing hundreds of genomes.}, keywords = {Amino Acid Sequence, Bacterial Capsules, Base Sequence, Gene expression, Genes, Bacterial, Genetic Variation, Genome, Bacterial, Molecular Sequence Data, Phylogeny, sequence alignment, Sequence Analysis, DNA, Streptococcus agalactiae, virulence}, author = {Tettelin, Herv{\'e} and Masignani, Vega and Cieslewicz, Michael J. and Donati, Claudio and Medini, Duccio and Ward, Naomi L. and Angiuoli, Samuel V. and Crabtree, Jonathan and Jones, Amanda L. and Durkin, A. Scott and DeBoy, Robert T. and Davidsen, Tanja M. and Mora, Marirosa and Scarselli, Maria and Margarit y Ros, Immaculada and Peterson, Jeremy D. and Hauser, Christopher R. and Sundaram, Jaideep P. and Nelson, William C. and Madupu, Ramana and Brinkac, Lauren M. and Dodson, Robert J. and Rosovitz, Mary J. and Sullivan, Steven A. and Daugherty, Sean C. and Haft, Daniel H. and J. Selengut and Gwinn, Michelle L. and Zhou, Liwei and Zafar, Nikhat and Khouri, Hoda and Radune, Diana and Dimitrov, George and Watkins, Kisha and O{\textquoteright}Connor, Kevin J. B. and Smith, Shannon and Utterback, Teresa R. and White, Owen and Rubens, Craig E. and Grandi, Guido and Madoff, Lawrence C. and Kasper, Dennis L. and Telford, John L. and Wessels, Michael R. and Rappuoli, Rino and Fraser, Claire M.} } @article {38325, title = {A guild of 45 CRISPR-associated (Cas) protein families and multiple CRISPR/Cas subtypes exist in prokaryotic genomes}, journal = {PLoS computational biologyPLOS Computational Biology}, volume = {1}, year = {2005}, note = {http://www.ncbi.nlm.nih.gov/pubmed/16292354?dopt=Abstract}, type = {10.1371/journal.pcbi.0010060}, abstract = {Clustered regularly interspaced short palindromic repeats (CRISPRs) are a family of DNA direct repeats found in many prokaryotic genomes. Repeats of 21-37 bp typically show weak dyad symmetry and are separated by regularly sized, nonrepetitive spacer sequences. Four CRISPR-associated (Cas) protein families, designated Cas1 to Cas4, are strictly associated with CRISPR elements and always occur near a repeat cluster. Some spacers originate from mobile genetic elements and are thought to confer "immunity" against the elements that harbor these sequences. In the present study, we have systematically investigated uncharacterized proteins encoded in the vicinity of these CRISPRs and found many additional protein families that are strictly associated with CRISPR loci across multiple prokaryotic species. Multiple sequence alignments and hidden Markov models have been built for 45 Cas protein families. These models identify family members with high sensitivity and selectivity and classify key regulators of development, DevR and DevS, in Myxococcus xanthus as Cas proteins. These identifications show that CRISPR/cas gene regions can be quite large, with up to 20 different, tandem-arranged cas genes next to a repeat cluster or filling the region between two repeat clusters. Distinctive subsets of the collection of Cas proteins recur in phylogenetically distant species and correlate with characteristic repeat periodicity. The analyses presented here support initial proposals of mobility of these units, along with the likelihood that loci of different subtypes interact with one another as well as with host cell defensive, replicative, and regulatory systems. It is evident from this analysis that CRISPR/cas loci are larger, more complex, and more heterogeneous than previously appreciated.}, keywords = {Genes, Archaeal, Genes, Bacterial, Genes, Fungal, Genome, Genome, Bacterial, Haloarcula marismortui, Markov chains, Multigene Family, Oligonucleotide Array Sequence Analysis, Phylogeny, Prokaryotic Cells, Proteins, Repetitive Sequences, Nucleic Acid, Yersinia pestis}, author = {Haft, Daniel H. and J. Selengut and Mongodin, Emmanuel F. and Nelson, Karen E.} } @article {38302, title = {Genome sequence of Silicibacter pomeroyi reveals adaptations to the marine environment}, journal = {NatureNature}, volume = {432}, year = {2004}, note = {http://www.ncbi.nlm.nih.gov/pubmed/15602564?dopt=Abstract}, type = {10.1038/nature03170}, abstract = {Since the recognition of prokaryotes as essential components of the oceanic food web, bacterioplankton have been acknowledged as catalysts of most major biogeochemical processes in the sea. Studying heterotrophic bacterioplankton has been challenging, however, as most major clades have never been cultured or have only been grown to low densities in sea water. Here we describe the genome sequence of Silicibacter pomeroyi, a member of the marine Roseobacter clade (Fig. 1), the relatives of which comprise approximately 10-20\% of coastal and oceanic mixed-layer bacterioplankton. This first genome sequence from any major heterotrophic clade consists of a chromosome (4,109,442 base pairs) and megaplasmid (491,611 base pairs). Genome analysis indicates that this organism relies upon a lithoheterotrophic strategy that uses inorganic compounds (carbon monoxide and sulphide) to supplement heterotrophy. Silicibacter pomeroyi also has genes advantageous for associations with plankton and suspended particles, including genes for uptake of algal-derived compounds, use of metabolites from reducing microzones, rapid growth and cell-density-dependent regulation. This bacterium has a physiology distinct from that of marine oligotrophs, adding a new strategy to the recognized repertoire for coping with a nutrient-poor ocean.}, keywords = {Adaptation, Physiological, Carrier Proteins, Genes, Bacterial, Genome, Bacterial, marine biology, Molecular Sequence Data, Oceans and Seas, Phylogeny, plankton, RNA, Ribosomal, 16S, Roseobacter, Seawater}, author = {Moran, Mary Ann and Buchan, Alison and Gonz{\'a}lez, Jos{\'e} M. and Heidelberg, John F. and Whitman, William B. and Kiene, Ronald P. and Henriksen, James R. and King, Gary M. and Belas, Robert and Fuqua, Clay and Brinkac, Lauren and Lewis, Matt and Johri, Shivani and Weaver, Bruce and Pai, Grace and Eisen, Jonathan A. and Rahe, Elisha and Sheldon, Wade M. and Ye, Wenying and Miller, Todd R. and Carlton, Jane and Rasko, David A. and Paulsen, Ian T. and Ren, Qinghu and Daugherty, Sean C. and DeBoy, Robert T. and Dodson, Robert J. and Durkin, A. Scott and Madupu, Ramana and Nelson, William C. and Sullivan, Steven A. and Rosovitz, M. J. and Haft, Daniel H. and J. Selengut and Ward, Naomi} } @article {38291, title = {Genome of Geobacter sulfurreducens: metal reduction in subsurface environments}, journal = {Science (New York, N.Y.)Science (New York, N.Y.)}, volume = {302}, year = {2003}, note = {http://www.ncbi.nlm.nih.gov/pubmed/14671304?dopt=Abstract}, type = {10.1126/science.1088727}, abstract = {The complete genome sequence of Geobacter sulfurreducens, a delta-proteobacterium, reveals unsuspected capabilities, including evidence of aerobic metabolism, one-carbon and complex carbon metabolism, motility, and chemotactic behavior. These characteristics, coupled with the possession of many two-component sensors and many c-type cytochromes, reveal an ability to create alternative, redundant, electron transport networks and offer insights into the process of metal ion reduction in subsurface environments. As well as playing roles in the global cycling of metals and carbon, this organism clearly has the potential for use in bioremediation of radioactive metals and in the generation of electricity.}, keywords = {Acetates, Acetyl Coenzyme A, Aerobiosis, Anaerobiosis, Bacterial Proteins, Carbon, Chemotaxis, Chromosomes, Bacterial, Cytochromes c, Electron Transport, Energy Metabolism, Genes, Bacterial, Genes, Regulator, Genome, Bacterial, Geobacter, Hydrogen, Metals, Movement, Open Reading Frames, Oxidation-Reduction, Phylogeny}, author = {Meth{\'e}, B. A. and Nelson, K. E. and Eisen, J. A. and Paulsen, I. T. and Nelson, W. and Heidelberg, J. F. and Wu, D. and Wu, M. and Ward, N. and Beanan, M. J. and Dodson, R. J. and Madupu, R. and Brinkac, L. M. and Daugherty, S. C. and DeBoy, R. T. and Durkin, A. S. and Gwinn, M. and Kolonay, J. F. and Sullivan, S. A. and Haft, D. H. and J. Selengut and Davidsen, T. M. and Zafar, N. and White, O. and Tran, B. and Romero, C. and Forberger, H. A. and Weidman, J. and Khouri, H. and Feldblyum, T. V. and Utterback, T. R. and Van Aken, S. E. and Lovley, D. R. and Fraser, C. M.} } @article {38531, title = {The TIGRFAMs database of protein families}, journal = {Nucleic acids researchNucleic Acids Research}, volume = {31}, year = {2003}, note = {http://www.ncbi.nlm.nih.gov/pubmed/12520025?dopt=Abstract}, abstract = {TIGRFAMs is a collection of manually curated protein families consisting of hidden Markov models (HMMs), multiple sequence alignments, commentary, Gene Ontology (GO) assignments, literature references and pointers to related TIGRFAMs, Pfam and InterPro models. These models are designed to support both automated and manually curated annotation of genomes. TIGRFAMs contains models of full-length proteins and shorter regions at the levels of superfamilies, subfamilies and equivalogs, where equivalogs are sets of homologous proteins conserved with respect to function since their last common ancestor. The scope of each model is set by raising or lowering cutoff scores and choosing members of the seed alignment to group proteins sharing specific function (equivalog) or more general properties. The overall goal is to provide information with maximum utility for the annotation process. TIGRFAMs is thus complementary to Pfam, whose models typically achieve broad coverage across distant homologs but end at the boundaries of conserved structural domains. The database currently contains over 1600 protein families. TIGRFAMs is available for searching or downloading at www.tigr.org/TIGRFAMs.}, keywords = {Animals, Databases, Protein, Markov chains, Mixed Function Oxygenases, Phylogeny, Proteins, Pyruvate Carboxylase, Sequence Homology, Amino Acid}, author = {Haft, Daniel H. and J. Selengut and White, Owen} } @article {49687, title = {The draft genome of Ciona intestinalis: insights into chordate and vertebrate origins.}, journal = {Science}, volume = {298}, year = {2002}, month = {2002 Dec 13}, pages = {2157-67}, abstract = {

The first chordates appear in the fossil record at the time of the Cambrian explosion, nearly 550 million years ago. The modern ascidian tadpole represents a plausible approximation to these ancestral chordates. To illuminate the origins of chordate and vertebrates, we generated a draft of the protein-coding portion of the genome of the most studied ascidian, Ciona intestinalis. The Ciona genome contains approximately 16,000 protein-coding genes, similar to the number in other invertebrates, but only half that found in vertebrates. Vertebrate gene families are typically found in simplified form in Ciona, suggesting that ascidians contain the basic ancestral complement of genes involved in cell signaling and development. The ascidian genome has also acquired a number of lineage-specific innovations, including a group of genes engaged in cellulose metabolism that are related to those in bacteria and fungi.

}, keywords = {Alleles, Animals, Apoptosis, Base Sequence, Cellulose, Central Nervous System, Ciona intestinalis, Computational Biology, Endocrine System, Gene Dosage, Gene Duplication, genes, Genes, Homeobox, Genome, Heart, Immunity, Molecular Sequence Data, Multigene Family, Muscle Proteins, Organizers, Embryonic, Phylogeny, Polymorphism, Genetic, Proteins, Sequence Analysis, DNA, Sequence Homology, Nucleic Acid, Species Specificity, Thyroid Gland, Urochordata, Vertebrates}, issn = {1095-9203}, doi = {10.1126/science.1080049}, author = {Dehal, Paramvir and Satou, Yutaka and Campbell, Robert K and Chapman, Jarrod and Degnan, Bernard and De Tomaso, Anthony and Davidson, Brad and Di Gregorio, Anna and Gelpke, Maarten and Goodstein, David M and Harafuji, Naoe and Hastings, Kenneth E M and Ho, Isaac and Hotta, Kohji and Huang, Wayne and Kawashima, Takeshi and Lemaire, Patrick and Martinez, Diego and Meinertzhagen, Ian A and Necula, Simona and Nonaka, Masaru and Putnam, Nik and Rash, Sam and Saiga, Hidetoshi and Satake, Masanobu and Terry, Astrid and Yamada, Lixy and Wang, Hong-Gang and Awazu, Satoko and Azumi, Kaoru and Boore, Jeffrey and Branno, Margherita and Chin-Bow, Stephen and DeSantis, Rosaria and Doyle, Sharon and Francino, Pilar and Keys, David N and Haga, Shinobu and Hayashi, Hiroko and Hino, Kyosuke and Imai, Kaoru S and Inaba, Kazuo and Kano, Shungo and Kobayashi, Kenji and Kobayashi, Mari and Lee, Byung-In and Makabe, Kazuhiro W and Manohar, Chitra and Matassi, Giorgio and Medina, Monica and Mochizuki, Yasuaki and Mount, Steve and Morishita, Tomomi and Miura, Sachiko and Nakayama, Akie and Nishizaka, Satoko and Nomoto, Hisayo and Ohta, Fumiko and Oishi, Kazuko and Rigoutsos, Isidore and Sano, Masako and Sasaki, Akane and Sasakura, Yasunori and Shoguchi, Eiichi and Shin-i, Tadasu and Spagnuolo, Antoinetta and Stainier, Didier and Suzuki, Miho M and Tassy, Olivier and Takatori, Naohito and Tokuoka, Miki and Yagi, Kasumi and Yoshizaki, Fumiko and Wada, Shuichi and Zhang, Cindy and Hyatt, P Douglas and Larimer, Frank and Detter, Chris and Doggett, Norman and Glavina, Tijana and Hawkins, Trevor and Richardson, Paul and Lucas, Susan and Kohara, Yuji and Levine, Michael and Satoh, Nori and Rokhsar, Daniel S} } @article {49631, title = {A new, expressed multigene family containing a hot spot for insertion of retroelements is associated with polymorphic subtelomeric regions of Trypanosoma brucei.}, journal = {Eukaryot Cell}, volume = {1}, year = {2002}, month = {2002 Feb}, pages = {137-51}, abstract = {

We describe a novel gene family that forms clusters in subtelomeric regions of Trypanosoma brucei chromosomes and partially accounts for the observed clustering of retrotransposons. The ingi and ribosomal inserted mobile element (RIME) non-LTR retrotransposons share 250 bp at both extremities and are the most abundant putatively mobile elements, with about 500 copies per haploid genome. From cDNA clones and subsequently in the T. brucei genomic DNA databases, we identified 52 homologous gene and pseudogene sequences, 16 of which contain a RIME and/or ingi retrotransposon inserted at exactly the same relative position. Here these genes are called the RHS family, for retrotransposon hot spot. Comparison of the protein sequences encoded by RHS genes (21 copies) and pseudogenes (24 copies) revealed a conserved central region containing an ATP/GTP-binding motif and the RIME/ingi insertion site. The RHS proteins share between 13 and 96\% identity, and six subfamilies, RHS1 to RHS6, can be defined on the basis of their divergent C-terminal domains. Immunofluorescence and Western blot analyses using RHS subfamily-specific immune sera show that RHS proteins are constitutively expressed and occur mainly in the nucleus. Analysis of Genome Survey Sequence databases indicated that the Trypanosoma brucei diploid genome contains about 280 RHS (pseudo)genes. Among the 52 identified RHS (pseudo)genes, 48 copies are in three RHS clusters located in subtelomeric regions of chromosomes Ia and II and adjacent to the active bloodstream form expression site in T. brucei strain TREU927/4 GUTat10.1. RHS genes comprise the remaining sequence of the size-polymorphic "repetitive region" described for T. brucei chromosome I, and a homologous gene family is present in the Trypanosoma cruzi genome.

}, keywords = {Amino Acid Sequence, Animals, Base Sequence, Cloning, Molecular, DNA Primers, DNA, Protozoan, Escherichia coli, Genes, Protozoan, Molecular Sequence Data, Multigene Family, Mutagenesis, Insertional, Phylogeny, Polymorphism, Genetic, Protozoan Proteins, Pseudogenes, Retroelements, sequence alignment, Sequence Homology, Amino Acid, Telomere, Trypanosoma brucei brucei, Trypanosoma cruzi}, issn = {1535-9778}, author = {Bringaud, Frederic and Biteau, Nicolas and Melville, Sara E and Hez, St{\'e}phanie and El-Sayed, Najib M and Leech, Vanessa and Berriman, Matthew and Hall, Neil and Donelson, John E and Baltz, Th{\'e}o} }