RESUMO
The freshwater cnidarian Hydra was first described in 1702 and has been the object of study for 300 years. Experimental studies of Hydra between 1736 and 1744 culminated in the discovery of asexual reproduction of an animal by budding, the first description of regeneration in an animal, and successful transplantation of tissue between animals. Today, Hydra is an important model for studies of axial patterning, stem cell biology and regeneration. Here we report the genome of Hydra magnipapillata and compare it to the genomes of the anthozoan Nematostella vectensis and other animals. The Hydra genome has been shaped by bursts of transposable element expansion, horizontal gene transfer, trans-splicing, and simplification of gene structure and gene content that parallel simplification of the Hydra life cycle. We also report the sequence of the genome of a novel bacterium stably associated with H. magnipapillata. Comparisons of the Hydra genome to the genomes of other animals shed light on the evolution of epithelia, contractile tissues, developmentally regulated transcription factors, the Spemann-Mangold organizer, pluripotency genes and the neuromuscular junction.
Assuntos
Genoma/genética , Hydra/genética , Animais , Antozoários/genética , Comamonadaceae/genética , Elementos de DNA Transponíveis/genética , Transferência Genética Horizontal/genética , Genoma Bacteriano/genética , Hydra/microbiologia , Hydra/ultraestrutura , Dados de Sequência Molecular , Junção Neuromuscular/ultraestruturaRESUMO
sigma(28) RNA polymerase is an alternative RNA polymerase that has been proposed to have a role in late developmental gene regulation in Chlamydia, but only a single target gene has been identified. To discover additional sigma(28)-dependent genes in the Chlamydia trachomatis genome, we applied bioinformatic methods using a probability weight matrix based on known sigma(28) promoters in other bacteria and a second matrix based on a functional analysis of the sigma(28) promoter. We tested 16 candidate sigma(28) promoters predicted with these algorithms and found that 5 were active in a chlamydial sigma(28) in vitro transcription assay. hctB, the known sigma(28)-regulated gene, is only expressed late in the chlamydial developmental cycle only, and two of the newly identified sigma(28) target genes (tsp and tlyC_1) also have late expression profiles, providing support for sigma(28) as a regulator of late gene expression. One of the other novel sigma(28)-regulated genes is dnaK, a known heat shock-responsive gene, suggesting that sigma(28) RNA polymerase may be involved in the response to cellular stress. Our sigma(28) prediction algorithm can be applied to other bacteria, and by performing a similar analysis on the Escherichia coli genome, we have predicted and functionally identified five previously unknown sigma(28)-regulated genes in E. coli.
Assuntos
Chlamydia trachomatis/genética , Biologia Computacional/métodos , RNA Polimerases Dirigidas por DNA/genética , Escherichia coli K12/genética , Regiões Promotoras Genéticas , Algoritmos , Proteínas da Membrana Bacteriana Externa/genética , Sequência de Bases , Regulação Bacteriana da Expressão Gênica , Genes Bacterianos , Proteínas de Choque Térmico/genética , Dados de Sequência Molecular , Transcrição GênicaRESUMO
BACKGROUND: Cis-regulatory modules (CRMs) are short stretches of DNA that help regulate gene expression in higher eukaryotes. They have been found up to 1 megabase away from the genes they regulate and can be located upstream, downstream, and even within their target genes. Due to the difficulty of finding CRMs using biological and computational techniques, even well-studied regulatory systems may contain CRMs that have not yet been discovered. RESULTS: We present a simple, efficient method (HexDiff) based only on hexamer frequencies of known CRMs and non-CRM sequence to predict novel CRMs in regulatory systems. On a data set of 16 gap and pair-rule genes containing 52 known CRMs, predictions made by HexDiff had a higher correlation with the known CRMs than several existing CRM prediction algorithms: Ahab, Cluster Buster, MSCAN, MCAST, and LWF. After combining the results of the different algorithms, 10 putative CRMs were identified and are strong candidates for future study. The hexamers used by HexDiff to distinguish between CRMs and non-CRM sequence were also analyzed and were shown to be enriched in regulatory elements. CONCLUSION: HexDiff provides an efficient and effective means for finding new CRMs based on known CRMs, rather than known binding sites.
Assuntos
Algoritmos , Motivos de Aminoácidos/genética , Drosophila/genética , Análise de Sequência de DNA/métodos , Animais , Regulação da Expressão GênicaAssuntos
Proteínas de Bactérias/genética , Transferência Genética Horizontal/genética , Hydra/genética , Trichomonas vaginalis/genética , Sequência de Aminoácidos , Animais , Sequência de Bases , DNA Complementar/genética , Dados de Sequência Molecular , RNA Líder para Processamento/genética , Alinhamento de Sequência , Análise de Sequência de DNARESUMO
High throughput gene expression profiling with DNA microarray provides an opportunity to analyze transcriptional regulation of hundreds or thousands of similarly regulated genes. Transcriptional regulation of gene expression plays an important role in myocardial remodeling. We have studied cardiac muscle gene expression with DNA microarray and used a computational strategy to identify common promoter motifs that respond to insulin-like growth factor 1 (IGF-1) stimulation in cardiac muscle cells. The analysis showed that the Sp1 binding site is a likely target of IGF-1 action. Further experiments with gel shift assay indicated that IGF-1 regulated the Sp1 site in cardiomyocytes, by increasing the abundance of Sp1 and Sp3 proteins. Using firefly luciferase as reporter gene, additional experiments showed that IGF-1 activated the promoter of cyclin D3 and Glut1. Both promoters contain one Sp1 site. The effect of IGF-1 on these two promoters was abolished with siRNA for Sp1. Thus, the transcriptional activation of these two promoters by IGF-1 requires the induction of Sp1 protein. These experiments suggest that the global transcriptional regulatory actions of IGF-1 involve activation of the Sp1 site in cardiac muscle. The computational model we have developed is a prototypical method that may be further developed to identify unique cis- and trans-acting elements in response to hormonal stimulation during cardiac muscle growth, repair, and remodeling in normal and abnormal cardiac muscle.
Assuntos
Fator de Crescimento Insulin-Like I/farmacologia , Miócitos Cardíacos/efeitos dos fármacos , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Fator de Transcrição Sp1/metabolismo , Animais , Sítios de Ligação/genética , Western Blotting , Linhagem Celular Tumoral , Células Cultivadas , Ciclina D3 , Ciclinas/genética , Proteínas de Ligação a DNA/genética , Proteínas de Ligação a DNA/metabolismo , Ensaio de Desvio de Mobilidade Eletroforética , Regulação da Expressão Gênica/efeitos dos fármacos , Transportador de Glucose Tipo 1 , Humanos , Luciferases/genética , Luciferases/metabolismo , Proteínas de Transporte de Monossacarídeos/genética , Miócitos Cardíacos/citologia , Miócitos Cardíacos/metabolismo , Oligonucleotídeos/genética , Oligonucleotídeos/metabolismo , Regiões Promotoras Genéticas/genética , RNA Interferente Pequeno/genética , RNA Interferente Pequeno/metabolismo , Ratos , Ratos Sprague-Dawley , Proteínas Recombinantes de Fusão/genética , Proteínas Recombinantes de Fusão/metabolismo , Fator de Transcrição Sp1/genética , Fator de Transcrição Sp3 , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismo , Transcrição Gênica/genética , Transfecção , Regulação para Cima/efeitos dos fármacosRESUMO
MOTIVATION: Over-represented k-mers in genomic DNA regions are often of particular biological interest. For example, over-represented k-mers in co-regulated families of genes are associated with the DNA binding sites of transcription factors. To measure over-representation, we introduce a statistical background model based on single-mismatches, and apply it to the pooled 500 bp ORF Upstream Regions (USRs) of yeast. More importantly, we investigate the context and spatial distribution of over-represented k-mers in yeast USRs. RESULTS: Single and double-stranded spatial distributions of most over-represented k-mers are highly non-random, and predominantly cluster into a small number of classes that are robust with respect to over-representation measures. Specifically, we show that the three most common distribution patterns can be related to DNA structure, function, and evolution and correspond to: (a) homologous ORF clusters associated with sharply localized distributions; (b) regulatory elements associated with a symmetric broad hill-shaped distribution in the 50-200 bp USR; and (c) runs of As, Ts, and ATs associated with a broad hill-shaped distribution also in the 50-200 bp USR, with extreme structural properties. Analysis of over-representation, homology, localization, and DNA structure are essential components of a general data-mining approach to finding biologically important k-mers in raw genomic DNA and understanding the 'lexicon' of regulatory regions.