A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria-2

<p><b>Copyright information:</b></p><p>Taken from "A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria"</p><p>http://www.biomedcentral.com/1471-2164/8/375</p><p>BMC Genomics 2007;8():375-375.</p><p>Published online 17 Oct 2007</p><p>PMCID:PMC2190773.</p><p></p>). Base pair colors indicate the number of different base pairs which occur in the different sequences at this position (red = 1, yellow = 2, green = 3 and blue = 4) and their shading resembles the frequency of base pairing, i.e. the number of sequences where this base pair is not present. The unpaired sequence is given as a sequence logo prepared using WebLogo [23]

A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria-0

<p><b>Copyright information:</b></p><p>Taken from "A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria"</p><p>http://www.biomedcentral.com/1471-2164/8/375</p><p>BMC Genomics 2007;8():375-375.</p><p>Published online 17 Oct 2007</p><p>PMCID:PMC2190773.</p><p></p>respective strain numbers are prefixed "Pro" and "Syn" for and . B. Sequence/structure model for putative Yfr1 RNAs from 15 different and as shown in part A. Sequence is given in IUPAC-notation (R: A or G; Y: C or U; S: G or C; K: G or U; B: G, U or C; V: G, C or A; D: G, U or A; H: A, C or U). Base pair colors indicate the number of different base pairs which occur in the different sequences at this position (red = 1, yellow = 2, green = 3) and their shading resembles the frequency of base pairing, i.e. the number of sequences where this base pair is not present

A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria-5

<p><b>Copyright information:</b></p><p>Taken from "A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria"</p><p>http://www.biomedcentral.com/1471-2164/8/375</p><p>BMC Genomics 2007;8():375-375.</p><p>Published online 17 Oct 2007</p><p>PMCID:PMC2190773.</p><p></p>respective strain numbers are prefixed "Pro" and "Syn" for and . B. Sequence/structure model for putative Yfr1 RNAs from 15 different and as shown in part A. Sequence is given in IUPAC-notation (R: A or G; Y: C or U; S: G or C; K: G or U; B: G, U or C; V: G, C or A; D: G, U or A; H: A, C or U). Base pair colors indicate the number of different base pairs which occur in the different sequences at this position (red = 1, yellow = 2, green = 3) and their shading resembles the frequency of base pairing, i.e. the number of sequences where this base pair is not present

A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria-1

<p><b>Copyright information:</b></p><p>Taken from "A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria"</p><p>http://www.biomedcentral.com/1471-2164/8/375</p><p>BMC Genomics 2007;8():375-375.</p><p>Published online 17 Oct 2007</p><p>PMCID:PMC2190773.</p><p></p>last line. The perfectly conserved sequence motif within the unpaired region is given in capital, red letters

A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria-3

<p><b>Copyright information:</b></p><p>Taken from "A motif-based search in bacterial genomes identifies the ortholog of the small RNA Yfr1 in all lineages of cyanobacteria"</p><p>http://www.biomedcentral.com/1471-2164/8/375</p><p>BMC Genomics 2007;8():375-375.</p><p>Published online 17 Oct 2007</p><p>PMCID:PMC2190773.</p><p></p>, sp. PCC 7120 (Nos. 7120), (Nos. punct.) and PCC 7421 (Gloe. 7421) was analyzed by staining a 10% polyacrylamide gel with ethidium bromide.. Northern blot hybridization with DNA oligonucleotides for the presence of Yfr1 (lower part) and, as a control, the 6S RNA (upper part)

Image_3_GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence.PDF

<p>Bacterial small RNAs (sRNAs) are important post-transcriptional regulators of gene expression. The functional and evolutionary characterization of sRNAs requires the identification of homologs, which is frequently challenging due to their heterogeneity, short length and partly, little sequence conservation. We developed the GLobal Automatic Small RNA Search go (GLASSgo) algorithm to identify sRNA homologs in complex genomic databases starting from a single sequence. GLASSgo combines an iterative BLAST strategy with pairwise identity filtering and a graph-based clustering method that utilizes RNA secondary structure information. We tested the specificity, sensitivity and runtime of GLASSgo, BLAST and the combination RNAlien/cmsearch in a typical use case scenario on 40 bacterial sRNA families. The sensitivity of the tested methods was similar, while the specificity of GLASSgo and RNAlien/cmsearch was significantly higher than that of BLAST. GLASSgo was on average ∼87 times faster than RNAlien/cmsearch, and only ∼7.5 times slower than BLAST, which shows that GLASSgo optimizes the trade-off between speed and accuracy in the task of finding sRNA homologs. GLASSgo is fully automated, whereas BLAST often recovers only parts of homologs and RNAlien/cmsearch requires extensive additional bioinformatic work to get a comprehensive set of homologs. GLASSgo is available as an easy-to-use web server to find homologous sRNAs in large databases.</p

Data_Sheet_1_GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence.ZIP

<p>Bacterial small RNAs (sRNAs) are important post-transcriptional regulators of gene expression. The functional and evolutionary characterization of sRNAs requires the identification of homologs, which is frequently challenging due to their heterogeneity, short length and partly, little sequence conservation. We developed the GLobal Automatic Small RNA Search go (GLASSgo) algorithm to identify sRNA homologs in complex genomic databases starting from a single sequence. GLASSgo combines an iterative BLAST strategy with pairwise identity filtering and a graph-based clustering method that utilizes RNA secondary structure information. We tested the specificity, sensitivity and runtime of GLASSgo, BLAST and the combination RNAlien/cmsearch in a typical use case scenario on 40 bacterial sRNA families. The sensitivity of the tested methods was similar, while the specificity of GLASSgo and RNAlien/cmsearch was significantly higher than that of BLAST. GLASSgo was on average ∼87 times faster than RNAlien/cmsearch, and only ∼7.5 times slower than BLAST, which shows that GLASSgo optimizes the trade-off between speed and accuracy in the task of finding sRNA homologs. GLASSgo is fully automated, whereas BLAST often recovers only parts of homologs and RNAlien/cmsearch requires extensive additional bioinformatic work to get a comprehensive set of homologs. GLASSgo is available as an easy-to-use web server to find homologous sRNAs in large databases.</p

Image_1_GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence.TIF

<p>Bacterial small RNAs (sRNAs) are important post-transcriptional regulators of gene expression. The functional and evolutionary characterization of sRNAs requires the identification of homologs, which is frequently challenging due to their heterogeneity, short length and partly, little sequence conservation. We developed the GLobal Automatic Small RNA Search go (GLASSgo) algorithm to identify sRNA homologs in complex genomic databases starting from a single sequence. GLASSgo combines an iterative BLAST strategy with pairwise identity filtering and a graph-based clustering method that utilizes RNA secondary structure information. We tested the specificity, sensitivity and runtime of GLASSgo, BLAST and the combination RNAlien/cmsearch in a typical use case scenario on 40 bacterial sRNA families. The sensitivity of the tested methods was similar, while the specificity of GLASSgo and RNAlien/cmsearch was significantly higher than that of BLAST. GLASSgo was on average ∼87 times faster than RNAlien/cmsearch, and only ∼7.5 times slower than BLAST, which shows that GLASSgo optimizes the trade-off between speed and accuracy in the task of finding sRNA homologs. GLASSgo is fully automated, whereas BLAST often recovers only parts of homologs and RNAlien/cmsearch requires extensive additional bioinformatic work to get a comprehensive set of homologs. GLASSgo is available as an easy-to-use web server to find homologous sRNAs in large databases.</p

Analysis of loci encoding proteins of the CP43/IsiA/Pcb family.

<p><b>A.</b> Organization of the chromosomal region harboring the <i>isiA</i> and <i>psbC</i>-like genes (<i>psbC-lk1-3</i>) of <i>N. spumigena</i> and the separate <i>psbDC</i> operon. The PsaL–coding domain in <i>psbC-lk2</i> (<i>nsp37500</i>) is highlighted in orange. <b>B.</b> Phylogenetic analysis of CP43, IsiA and related chlorophyll-binding proteins from <i>N. spumigena</i> and of selected other cyanobacteria was inferred using the Minimum Evolution method. The optimal tree with the sum of branch length = 3,97009738 is shown. The percentage of replicate trees in which the associated taxa clustered in the bootstrap test (1000 replicates) are shown next to the branches. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and are in the units of the number of amino acid substitutions per site. All positions containing gaps and missing data were eliminated from the dataset (complete deletion option). There were a total of 279 positions in the final dataset. <b>C.</b> Transcriptional organization around the <i>isiA, isiB</i> and <i>psbC</i>-like gene cluster. There are three mapped TSS in the region displayed in <b>Fig. 3A</b>, all associated with or close to the 5′ end of <i>nsp37510.</i> TSS are indicated by blue arrows and the number of cDNA reads associated with them are given as approximation for their activity. One gTSS gives rise to the 83 nt long 5′ UTR upstream of <i>nsp37510</i> (blue) and the gene or operon mRNA. An antisense RNA originates from a single aTSS in the opposite direction (purple). The third TSS is a putative nTSS driving the transcription of an ncRNA in the <i>nsp37510</i>- <i>nsp37520</i> intergenic spacer. Except for the <i>nsp37510</i> 5′ UTR, all TSS displayed are drawn with a 100 nt-long box that corresponded to the maximum read length in the dRNAseq approach.</p

Classification of the predicted <i>N. spumigena</i> CCY9414 proteome.

<p><b>A.</b> Comparison of all predicted proteins of <i>N. spumigena</i> (N_spumi) against the proteomes of other well-studied Nostocales, <i>Nostoc punctiforme</i> sp. PCC 73102 (N_punct), <i>Anabaena variabilis</i> sp. ATCC 29413 (A_var) and <i>Anabaena</i> PCC 7120 (N_7120) based on MCL clustering of BLASTp results (minimum e-value: 10^-8). The numbers refer to the number of protein clusters in each category, the numbers in brackets to the total number of individual proteins. <b>B.</b> Taxonomic top hits for the 1,098 <i>N. spumigena</i> CCY9414 singletons from part A (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060224#pone.0060224.s005" target="_blank">Table S3</a>) visualized by MEGAN.</p