Coding RNA Genes Research Articles

Age-Related Accumulation of Somatic Mitochondrial DNA Mutations in Adult-Derived Human iPSCs

The genetic integrity of iPSCs is an important consideration for therapeutic application. In this study, we examine the accumulation of somatic mitochondrial genome (mtDNA) mutations in skin fibroblasts, blood, and iPSCs derived from young and elderly subjects (24-72 years). We found that pooled skin and blood mtDNA contained low heteroplasmic point mutations, but a panel of ten individual iPSC lines from each tissue or clonally expanded fibroblasts carried an elevated load of heteroplasmic or homoplasmic mutations, suggesting that somatic mutations randomly arise within individual cells but arenot detectable in whole tissues. The frequency of mtDNA defects in iPSCs increased with age, andmany mutations were non-synonymous or resided in RNA coding genes and thus can lead torespiratory defects. Our results highlight a need tomonitor mtDNA mutations in iPSCs, especially those generated from older patients, and to examine themetabolic status of iPSCs destined for clinical applications.

GtRNAdb 2.0: an expanded database of transfer RNA genes identified in complete and draft genomes.

Transfer RNAs represent the largest, most ubiquitous class of non-protein coding RNA genes found in all living organisms. The tRNAscan-SE search tool has become the de facto standard for annotating tRNA genes in genomes, and the Genomic tRNA Database (GtRNAdb) was created as a portal for interactive exploration of these gene predictions. Since its published description in 2009, the GtRNAdb has steadily grown in content, and remains the most commonly cited web-based source of tRNA gene information. In this update, we describe not only a major increase in the number of tRNA predictions (>367000) and genomes analyzed (>4370), but more importantly, the integration of new analytic and functional data to improve the quality and biological context of tRNA gene predictions. New information drawn from other sources includes tRNA modification data, epigenetic data, single nucleotide polymorphisms, gene expression and evolutionary conservation. A richer set of analytic data is also presented, including better tRNA functional prediction, non-canonical features, predicted structural impacts from sequence variants and minimum free energy structural predictions. Views of tRNA genes in genomic context are provided via direct links to the UCSC genome browsers. The database can be searched by sequence or gene features, and is available at http://gtrnadb.ucsc.edu/.

Chloroplast phylogenomic analysis of chlorophyte green algae identifies a novel lineage sister to the Sphaeropleales (Chlorophyceae).

BackgroundThe class Chlorophyceae (Chlorophyta) includes morphologically and ecologically diverse green algae. Most of the documented species belong to the clade formed by the Chlamydomonadales (also called Volvocales) and Sphaeropleales. Although studies based on the nuclear 18S rRNA gene or a few combined genes have shed light on the diversity and phylogenetic structure of the Chlamydomonadales, the positions of many of the monophyletic groups identified remain uncertain. Here, we used a chloroplast phylogenomic approach to delineate the relationships among these lineages.ResultsTo generate the analyzed amino acid and nucleotide data sets, we sequenced the chloroplast DNAs (cpDNAs) of 24 chlorophycean taxa; these included representatives from 16 of the 21 primary clades previously recognized in the Chlamydomonadales, two taxa from a coccoid lineage (Jenufa) that was suspected to be sister to the Golenkiniaceae, and two sphaeroplealeans. Using Bayesian and/or maximum likelihood inference methods, we analyzed an amino acid data set that was assembled from 69 cpDNA-encoded proteins of 73 core chlorophyte (including 33 chlorophyceans), as well as two nucleotide data sets that were generated from the 69 genes coding for these proteins and 29 RNA-coding genes. The protein and gene phylogenies were congruent and robustly resolved the branching order of most of the investigated lineages. Within the Chlamydomonadales, 22 taxa formed an assemblage of five major clades/lineages. The earliest-diverging clade displayed Hafniomonas laevis and the Crucicarteria, and was followed by the Radicarteria and then by the Chloromonadinia. The latter lineage was sister to two superclades, one consisting of the Oogamochlamydinia and Reinhardtinia and the other of the Caudivolvoxa and Xenovolvoxa. To our surprise, the Jenufa species and the two spine-bearing green algae belonging to the Golenkinia and Treubaria genera were recovered in a highly supported monophyletic group that also included three taxa representing distinct families of the Sphaeropleales (Bracteacoccaceae, Mychonastaceae, and Scenedesmaceae).ConclusionsOur phylogenomic study advances our knowledge regarding the circumscription and internal structure of the Chlamydomonadales, suggesting that a previously unrecognized lineage is sister to the Sphaeropleales. In addition, it offers new insights into the flagellar structures of the founding members of both the Chlamydomonadales and Sphaeropleales.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-015-0544-5) contains supplementary material, which is available to authorized users.

The complete mitochondrial genome of Papilio glaucus and its phylogenetic implications

Due to the intriguing morphology, lifecycle, and diversity of butterflies and moths, Lepidoptera are emerging as model organisms for the study of genetics, evolution and speciation. The progress of these studies relies on decoding Lepidoptera genomes, both nuclear and mitochondrial. Here we describe a protocol to obtain mitogenomes from Next Generation Sequencing reads performed for whole-genome sequencing and report the complete mitogenome of Papilio (Pterourus) glaucus. The circular mitogenome is 15,306bp in length and rich in A and T. It contains 13 protein-coding genes (PCGs), 22 transfer-RNA-coding genes (tRNA), and 2 ribosomal-RNA-coding genes (rRNA), with a gene order typical for mitogenomes of Lepidoptera. We performed phylogenetic analyses based on PCG and RNA-coding genes or protein sequences using Bayesian Inference and Maximum Likelihood methods. The phylogenetic trees consistently show that among species with available mitogenomes Papilio glaucus is the closest to Papilio (Agehana) maraho from Asia.

Genomic and comparative genomic analyses of Rickettsia heilongjiangensis provide insight into its evolution and pathogenesis

Rickettsia heilongjiangensis, the causative agent of far eastern spotted fever, is an obligate intracellular gram-negative bacterium that belongs to the spotted fever group rickettsiae. To understand the evolution and pathogenesis of R. heilongjiangensis, we analyzed its genome and compared it with other rickettsial genomes available in GenBank. The R. heilongjiangensis chromosome contains 1333 genes, including 1297 protein coding genes and 36 RNA coding genes. The genome also contains 121 pseudogenes, 54 insertion sequences, and 39 tandem repeats. Sixteen genes encoding the major components of the type IV secretion systems were identified in the R. heilongjiangensis genome. In total, 37 β-barrel outer membrane proteins were predicted in the genome, eight of which have been previously confirmed to be outer membrane proteins. In addition, 266 potential virulence factor genes, seven partially deleted antibiotic resistance genes, and a genomic island were identified in the genome. The codon usage in the genome is compatible with its low GC content, and the amino acid usage shows apparent bias. A comparative genomic analysis showed that R. heilongjiangensis and R. japonica share one unique fragment that may be a target sequence for a diagnostic assay. The orthologs of 37 genes of R. heilongjiangensis were found in pathogenic R. rickettsii str. Sheila Smith but not in non-pathogenic R. rickettsii str. Iowa, which may explain why R. heilongjiangensis is pathogenic. Pan-genome analysis showed that R. heilongjiangensis and 42 other rickettsiae strains share 693 core genes with a pan-genome size of 4837 genes. The pan-genome-based phylogeny showed that R. heilongjiangensis was closely related to R. japonica.

Genome Sequencing of a Mung Bean Plant Growth Promoting Strain of P. aeruginosa with Biocontrol Ability.

Pseudomonas aeruginosa PGPR2 is a mung bean rhizosphere strain that produces secondary metabolites and hydrolytic enzymes contributing to excellent antifungal activity against Macrophomina phaseolina, one of the prevalent fungal pathogens of mung bean. Genome sequencing was performed using the Ion Torrent Personal Genome Machine generating 1,354,732 reads (6,772,433 sequenced bases) achieving ~25-fold coverage of the genome. Reference genome assembly using MIRA 3.4.0 yielded 198 contigs. The draft genome of PGPR2 encoded 6803 open reading frames, of which 5314 were genes with predicted functions, 1489 were genes of known functions, and 80 were RNA-coding genes. Strain specific and core genes of P. aeruginosa PGPR2 that are relevant to rhizospheric habitat were identified by pangenome analysis. Genes involved in plant growth promoting function such as synthesis of ACC deaminase, indole-3-acetic acid, trehalose, mineral scavenging siderophores, hydrogen cyanide, chitinases, acyl homoserine lactones, acetoin, 2,3-butanediol, and phytases were identified. In addition, niche-specific genes such as phosphate solubilising 3-phytase, adhesins, pathway-specific transcriptional regulators, a diguanylate cyclase involved in cellulose synthesis, a receptor for ferrienterochelin, a DEAD/DEAH-box helicase involved in stress tolerance, chemotaxis/motility determinants, an HtpX protease, and enzymes involved in the production of a chromanone derivative with potent antifungal activity were identified.

Circulating RNA coding genes regulating apoptosis in maternal blood in severe early onset fetal growth restriction and pre-eclampsia

To determine whether the intrinsic apoptosis pathway is differentially expressed in placenta and maternal blood in severe preterm fetal growth restriction (FGR) and pre-eclampsia (PE), and to examine whether circulating RNA in maternal blood may be potential biomarkers. Maternal blood samples and placental biopsies were collected from women with preterm: FGR (n=20), PE without FGR (n=8) and controls (n=20). Real-time PCR examined the expression of genes in the intrinsic apoptosis pathway in FGR and PE, stratified according to the severity of placental insufficiency. Severe preterm FGR, with or without PE, was associated with increased expression of BCL2, BCL-XL, BIM, BAD and Survivin in both the placenta and maternal blood (1.6 to 3.3-fold, P<0.05). In preterm PE, but not FGR, there was increased placental expression of BCL-XL and BCL2 (1.6 to 2.5-fold, P<0.05), but only BCL2 was significantly increased in the maternal blood (1.8-fold, P<0.05). Increased expression of genes of the intrinsic apoptosis pathway reflected the severity of FGR as determined by deteriorations in umbilical artery Doppler velocimetry. In severe early onset FGR there was increased expression of genes regulating intrinsic apoptosis in both the placenta and maternal blood. Circulating RNA regulating placenta apoptosis may be used to develop noninvasive novel biomarkers for FGR.

Gene expression analyses for osteoporosis research

SummaryGene expression describes the process of converting the information encoded in the genome into functional gene products like proteins or functional RNAs in the case of non coding RNA genes. Gene expression analysis seeks to identify those genes that are expressed and the level at which they are expressed under certain circumstances. As changes of gene expression are associated with both physiological and pathological processes, gene expression analysis provides a powerful tool to understand the molecular basis of biological processes like cellular differentiation, aging or adaptive responses to the environment and to provide a comprehensive understanding of the molecular basis of complex diseases. In the field of osteology, gene expression analysis has contributed substantially to novel insights into fundamental processes like osteoblast and osteoclast differentiation, bone formation and mineralization, and to novel insights into molecular changes occurring in complex diseases such as osteoporosis or rheumatoid arthritis. This review is aimed at giving an overview on the different techniques available to quantify gene expression and its application in osteoporosis research.

Identification of copy number variants in horses

Copy number variants (CNVs) represent a substantial source of genetic variation in mammals. However, the occurrence of CNVs in horses and their subsequent impact on phenotypic variation is unknown. We performed a study to identify CNVs in 16 horses representing 15 distinct breeds (Equus caballus) and an individual gray donkey (Equus asinus) using a whole-exome tiling array and the array comparative genomic hybridization methodology. We identified 2368 CNVs ranging in size from 197 bp to 3.5 Mb. Merging identical CNVs from each animal yielded 775 CNV regions (CNVRs), involving 1707 protein- and RNA-coding genes. The number of CNVs per animal ranged from 55 to 347, with median and mean sizes of CNVs of 5.3 kb and 99.4 kb, respectively. Approximately 6% of the genes investigated were affected by a CNV. Biological process enrichment analysis indicated CNVs primarily affected genes involved in sensory perception, signal transduction, and metabolism. CNVs also were identified in genes regulating blood group antigens, coat color, fecundity, lactation, keratin formation, neuronal homeostasis, and height in other species. Collectively, these data are the first report of copy number variation in horses and suggest that CNVs are common in the horse genome and may modulate biological processes underlying different traits observed among horses and horse breeds.

Digital gene expression data, cross-species conservation and noncoding RNA

http://www.lirmm.fr/~rivalRecently developed sequencing technologies offer massively parallel production of short reads and become the technology of choice for a variety of sequencing-based assays, including gene expression. Among them, digital gene expression analysis (DGE), which combines generation of short tag signatures for cellular transcripts with massively parallel sequencing, offers a large dynamic range to detect transcripts and is limited only by sequencing depth. As recently described (Philippe et al, 2009), tag signatures can easily be mapped to a reference genome and used to perform gene discovery. This procedure distinguishes between transcripts originating from both DNA strands and categorizes tags corresponding to protein coding gene (CDS and 3’UTR), antisense, intronic or intergenic transcribed regions. Here, we have applied an integrated bioinformatics approach to investigate tags’ properties, including cross-species conservation, and the ability to reveal novel transcripts located outside the boundaries of known protein or RNA coding genes. We mapped the tags from a human DGE library obtained with Solexa sequencing, against the human, chimpanzee, and mouse genomic sequences. We considered the subset of uniquely mapped tags in the human genome, and given their genomic location, determined according to Ensembl if they fall within a region annotated by a gene (CDS, UTR and intron) or an intergenic region. We found that 76.4 % of the tags located in human also matched to the chimpanzee genome. The level of conservation between human and chimpanzee varied among annotation categories: 85 % of conserved tags in the CDS, 81 % in the UTR, 76% and 73% respectively in intron and intergenic regions. With the same procedure applied to human and mouse, we obtained 11% of conserved tags in the CDS, 7% in UTR, 1% and 3% respectively in intronic and intergenic regions. We analysed in depth the common CDS and UTR tags in human and mouse for their functional relevance: 90% of them correspond to orthologous genes with a common HUGO. We used DAVID database to extract biological features, the gene clustering revealed specific molecular functions belonging to transcription cofactor and regulator activity, nucleotide binding, ligase and protein kinase, hormone receptor, histone methyltransferase or GTPase activity, and also important signaling pathways like WNT pathway. Indeed, intergenic transcription includes mainly new, non protein-coding RNAs (npcRNAs), which could represent an important class of regulatory molecules. By integrating also SAGE genie and RNA-seq expression data, we selected intergenic tags conserved across species and assayed experimentally the npcRNA transcriptome with Q-PCR. We validated 80% of the 32 tested biological cases. These results demonstrate that considering tag conservation helps to identify conserved genes and functions, which is of great relevance when investigating expressed tags located in intergenic regions.

Implementing a cumulative supermatrix approach for a comprehensive phylogenetic study of the Teloschistales (Pezizomycotina, Ascomycota)

The resolution of the phylogenetic relationships within the order Teloschistales (Ascomycota, lichen-forming-fungi), with nearly 2000 known species and outstanding phenotypic diversity, has been hindered by the limitation in the resolving power that single-locus or two-locus phylogenetic studies have provided to date. In this context, an extensive taxon sampling within the Teloschistales with more loci (especially nuclear protein-coding genes) was needed to confront the current taxonomic delimitations and to understand evolutionary trends within this order. Comprehensive maximum likelihood and Bayesian analyses were performed based on seven loci using a cumulative supermatrix approach, including protein-coding genes RPB1 and RPB2 in addition to nuclear and mitochondrial ribosomal RNA-coding genes. We included 167 taxa representing 12 of the 15 genera recognized within the currently accepted Teloschistineae, 22 of the 43 genera within the Physciineae, 49 genera of the closely related orders Lecanorales, Lecideales, and Peltigerales, and the dubiously placed family Brigantiaeaceae and genus Sipmaniella. Although the progressive addition of taxa (cumulative supermatrix approach) with increasing amounts of missing data did not dramatically affect the loss of support and resolution, the monophyly of the Teloschistales in the current sense was inconsistent, depending on the loci-taxa combination analyzed. Therefore, we propose a new, but provisional, classification for the re-circumscribed orders Caliciales and Teloschistales (previously referred to as Physciineae and Teloschistineae, respectively). We report here that the family Brigantiaeaceae, previously regarded as incertae sedis within the subclass Lecanoromycetidae, and Sipmaniella, are members of the Teloschistales in a strict sense. Within this order, one lineage led to the diversification of the mostly epiphytic crustose Brigantiaeaceae and Letrouitiaceae, with a circumpacific center of diversity and found mostly in the tropics. The other main lineage led to another epiphytic crustose family, mostly tropical, and with an Australasian center of diversity – the Megalosporaceae – which is sister to the mainly rock-inhabiting, cosmopolitan, and species rich Teloschistaceae, with a diversity of growth habits ranging from crustose to fruticose. Our results confirm the use of a cumulative supermatrix approach as a viable method to generate comprehensive phylogenies summarizing relationships of taxa with multi-locus to single locus data.

CloVR-Microbe: Assembly, gene finding and functional annotation of raw sequence data from single microbial genome projects – standard operating procedure, version 1.0

AbstractThe CloVR-Microbe pipeline performs the basic processing and analysis steps required for standard microbial single-genome sequencing projects: A) Whole-genome shotgun sequence assembly; B) Identification of protein and RNA-coding genes; and C) Functional gene annotation. B) and C) are based on the IGS Annotation Engine (http://ae.igs.umaryland.edu/), which is described elsewhere (K Galens et al. submitted). The assembly component of CloVR- Microbe can be executed independently from the gene identification and annotation components. Alternatively, pre-assembled sequence contigs can be used to perform gene identifications and annotations. The pipeline input may consist of unassembled raw sequence reads from the Sanger, Roche/454 GS FLX or Illumina GAII or HiSeq sequencing platforms or of combinations of Sanger and Roche/454 sequence data. The pipeline output consists of results and summary files generated during the different pipeline steps. Annotated sequence files are generated that are compatible with common genome browser tools and can be submitted to the GenBank repository at NCBI. This protocol is available in CloVR beta versions 0.5 and 0.6.

CloVR-Microbe: Assembly, gene finding and functional annotation of raw sequence data from single microbial genome projects – standard operating procedure, version 1.0

The CloVR-Microbe pipeline performs the basic processing and analysis steps required for standard microbial single-genome sequencing projects: A) Whole-genome shotgun sequence assembly; B) Identification of protein and RNA-coding genes; and C) Functional gene annotation. B) and C) are based on the IGS Annotation Engine (http://ae.igs.umaryland.edu/), which is described elsewhere (K Galens et al. submitted). The assembly component of CloVR- Microbe can be executed independently from the gene identification and annotation components. Alternatively, pre-assembled sequence contigs can be used to perform gene identifications and annotations. The pipeline input may consist of unassembled raw sequence reads from the Sanger, Roche/454 GS FLX or Illumina GAII or HiSeq sequencing platforms or of combinations of Sanger and Roche/454 sequence data. The pipeline output consists of results and summary files generated during the different pipeline steps. Annotated sequence files are generated that are compatible with common genome browser tools and can be submitted to the GenBank repository at NCBI. This protocol is available in CloVR beta versions 0.5 and 0.6.

CloVR-Microbe: Assembly, gene finding and functional annotation of raw sequence data from single microbial genome projects – standard operating procedure, version 1.0

The CloVR-Microbe pipeline performs the basic processing and analysis steps required for standard microbial single-genome sequencing projects: A) Whole-genome shotgun sequence assembly; B) Identification of protein and RNA-coding genes; and C) Functional gene annotation. B) and C) are based on the IGS Annotation Engine (http://ae.igs.umaryland.edu/), which is described elsewhere (K Galens et al. submitted). The assembly component of CloVR- Microbe can be executed independently from the gene identification and annotation components. Alternatively, pre-assembled sequence contigs can be used to perform gene identifications and annotations. The pipeline input may consist of unassembled raw sequence reads from the Sanger, Roche/454 GS FLX or Illumina GAII or HiSeq sequencing platforms or of combinations of Sanger and Roche/454 sequence data. The pipeline output consists of results and summary files generated during the different pipeline steps. Annotated sequence files are generated that are compatible with common genome browser tools and can be submitted to the GenBank repository at NCBI. This protocol is available in CloVR beta versions 0.5 and 0.6.

High-quality annotation of promoter regions for 913 bacterial genomes

The number of bacterial genomes being sequenced is increasing very rapidly and hence, it is crucial to have procedures for rapid and reliable annotation of their functional elements such as promoter regions, which control the expression of each gene or each transcription unit of the genome. The present work addresses this requirement and presents a generic method applicable across organisms. Relative stability of the DNA double helical sequences has been used to discriminate promoter regions from non-promoter regions. Based on the difference in stability between neighboring regions, an algorithm has been implemented to predict promoter regions on a large scale over 913 microbial genome sequences. The average free energy values for the promoter regions as well as their downstream regions are found to differ, depending on their GC content. Threshold values to identify promoter regions have been derived using sequences flanking a subset of translation start sites from all microbial genomes and then used to predict promoters over the complete genome sequences. An average recall value of 72% (which indicates the percentage of protein and RNA coding genes with predicted promoter regions assigned to them) and precision of 56% is achieved over the 913 microbial genome dataset. The binary executable for 'PromPredict' algorithm (implemented in PERL and supported on Linux and MS Windows) and the predicted promoter data for all 913 microbial genomes are available at http://nucleix.mbu.iisc.ernet.in/prombase/.

GtRNAdb: a database of transfer RNA genes detected in genomic sequence

Transfer RNAs (tRNAs) represent the single largest, best-understood class of non-protein coding RNA genes found in all living organisms. By far, the major source of new tRNAs is computational identification of genes within newly sequenced genomes. To organize the rapidly growing collection and enable systematic analyses, we created the Genomic tRNA Database (GtRNAdb), currently including over 74 000 tRNA genes predicted from 740 species. The web resource provides overview statistics of tRNA genes within each analyzed genome, including information by isotype and genetic locus, easily downloadable primary sequences, graphical secondary structures and multiple sequence alignments. Direct links for each gene to UCSC eukaryotic and microbial genome browsers provide graphical display of tRNA genes in the context of all other local genetic information. The database can be searched by primary sequence similarity, tRNA characteristics or phylogenetic group. The database is publicly available at http://gtrnadb.ucsc.edu.

Computational methods in noncoding RNA research

Non protein-coding RNAs (ncRNAs) are a research hotspot in bioinformatics. Recent discoveries have revealed new ncRNA families performing a variety of roles, from gene expression regulation to catalytic activities. It is also believed that other families are still to be unveiled. Computational methods developed for protein coding genes often fail when searching for ncRNAs. Noncoding RNAs functionality is often heavily dependent on their secondary structure, which makes gene discovery very different from protein coding RNA genes. This motivated the development of specific methods for ncRNA research. This article reviews the main approaches used to identify ncRNAs and predict secondary structure.

Affordable assays for genotyping single nucleotide polymorphisms in insects

Insect genome projects and DNA sequence databases are providing unprecedented amounts of information about variation at specific nucleotides in protein- and RNA-coding genes. Single nucleotide polymorphisms (SNPs) are abundant in all insect species so far examined and are proving useful in population genetics, linkage mapping and marker-assisted selection. A number of studies has already identified SNPs associated with insecticide resistance, especially mutations conferring reduced target site sensitivity. Unfortunately, most modern, high-throughput, automated SNP detection technologies are expensive or require the use of expensive equipment and are therefore not accessible to laboratories on a limited budget or to our colleagues in developing countries. In this review, we provide a chronological and comprehensive list of all SNP methods. We emphasize and explain those techniques in which genotypes can be identified by eye or that only require agarose gel electrophoresis. We provide examples where these techniques have or are currently being applied to insects.

Phylogenetic comparison of protein-coding versus ribosomal RNA-coding sequence data: A case study of the Lecanoromycetes (Ascomycota)

The resolving power and statistical support provided by two protein-coding ( RPB1 and RPB2) and three ribosomal RNA-coding (nucSSU, nucLSU, and mitSSU) genes individually and in various combinations were investigated based on maximum likelihood bootstrap analyses on lichen-forming fungi from the class Lecanoromycetes (Ascomycota). Our results indicate that the optimal loci (single and combined) to use for molecular systematics of lichen-forming Ascomycota are protein-coding genes ( RPB1 and RPB2). RPB1 and RPB2 genes individually were phylogenetically more efficient than all two- and three-locus combinations of ribosomal loci. The 3rd codon position of each of these two loci provided the most characters in support of phylogenetic relationships within the Lecanoromycetes. Of the three ribosomal loci we used in this study, mitSSU contributed the most to phylogenetic analyses when combined with RPB1 and RPB2. Except for the mitSSU, ribosomal genes were the most difficult to recover because they often contain many introns, resulting in PCR bias toward numerous and intronless co-extracted contaminant fungi (mainly Dothideomycetes, Chaetothyriomycetes, and Sordariomycetes in the Ascomycota, and members of the Basidiomycota), which inhabit lichen thalli. Maximum likelihood analysis on the combined five-locus data set for 82 members of the Lecanoromycetes provided a well resolved and well supported tree compared to existing phylogenies. We confirmed the monophyly of three recognized subclasses in the Lecanoromycetes, the Acarosporomycetidae, Ostropomycetidae, and Lecanoromycetideae; the latter delimited as monophyletic for the first time, with the exclusion of the family Umbilicariaceae and Hypocenomyce scalaris. The genus Candelariella (formerly in the Candelariaceae, currently a member of the Lecanoraceae) represents the first evolutionary split within the Lecanoromycetes, before the divergence of the Acarosporomycetidae. This study provides a foundation necessary to guide the selection of loci for future multilocus phylogenetic studies on lichen-forming and allied ascomycetes.

Essential genes of a minimal bacterium

Mycoplasma genitalium has the smallest genome of any organism that can be grown in pure culture. It has a minimal metabolism and little genomic redundancy. Consequently, its genome is expected to be a close approximation to the minimal set of genes needed to sustain bacterial life. Using global transposon mutagenesis, we isolated and characterized gene disruption mutants for 100 different nonessential protein-coding genes. None of the 43 RNA-coding genes were disrupted. Herein, we identify 382 of the 482 M. genitalium protein-coding genes as essential, plus five sets of disrupted genes that encode proteins with potentially redundant essential functions, such as phosphate transport. Genes encoding proteins of unknown function constitute 28% of the essential protein-coding genes set. Disruption of some genes accelerated M. genitalium growth.