Bioinformatic predictions have facilitated the identiﬁca- tion of many sRNAs. In particular, comparative genomic searches of intergenic regions have proven productive, using criteria such as orphaned promoter sequences, orphaned terminator sequences, and conserved secondary structure in related organisms (13–17). More direct approaches to sRNA identiﬁcation have involved the cloning of sRNA species (as cDNAs) from total RNA samples (18), microarray analysis of intergenic regions (9,17,19,20) and immunoprecipitation of sRNAs asso- ciated with the RNA chaperone Hfq (21,22). Hfq plays an important role in mediating the interaction of trans- encoded sRNAs with their mRNA targets, presumably stabilizing the inherently imperfect basepairing between these two RNA molecules (23). Searching for sRNAs in S. coelicolor presents a number of challenges. For one, S. coelicolor has no obvious Hfq orthologue (24). The S. coelicolor genome is also extre- mely G + C rich (>70%) (2), and thus the identiﬁcation of rho-independent terminators is not straightforward. The Institute for Genomic Research (TIGR—http://rice. tigr.org/tigr-scripts/CMR2/terminators_genome.spl?db= ntsc02) predicts there to be 38 rho-independent termina- tors within the 8.7 Mb S. coelicolor chromosome [using algorithms developed by Ermolaeva et al. (25)]; while 110 757 transcription terminators are predicted within the same genomic sequence using the TransTermHP pro- gram (26). The identiﬁcation of promoter sequences is equally challenging, as S. coelicolor has 65 sigma factors, only a handful of which have been characterized, and thus there is no clear deﬁnition of what comprises a promoter in S. coelicolor. There are, however, multiple actinomycete genome sequences available, including four publically available Streptomyces genomes (2,27,28, http://www. sanger.ac.uk/Projects/S_scabies/). Here, we describe the use of a combined bioinformatic and experimental approach to identify and characterize nine novel sRNAs in S. coelicolor, ranging in size from 34 to 288 nt. These were shown to be expressed at deﬁned stages during the S. coelicolor life cycle, and in several instances, expression was determined to be completely dependent upon speciﬁc nutritional conditions. We exam- ined the expression of each sRNA in mutant strains defec- tive in antibiotic production, aerial hyphae formation and sporulation, and found ﬁve of them to have reproducibly diﬀerent transcription proﬁles from that observed in the wild-type. MATERIALS AND METHODS Intergenic sequence extraction and comparative genomic analysis Intergenic (IG) sequences were extracted from the S. coelicolor genome sequence, using annotation informa- tion from Sco.tab and DNA sequence information from Sco.dna (both data sets are available through the Sanger Institute at ftp://ftp.sanger.ac.uk/pub/S_coelicolor/whole_ genome/). 833 intergenic sequences larger than 200 nt were selected from the conserved core region of the S. coelicolor chromosome (extending from SCO1413 to Nucleic Acids Research, 2008, Vol. 36, No. 22 7241 SCO5820—genes are annotated in increasing numerical order along the length of the linear chromosome), and were subjected to analysis using BLAST against all sequences in the database (as of August 2008) (Supple- mentary Table S1). Any intergenic sequences that did not exhibit similarity to other sequences with an expected value of <0.001 were considered to be S. coelicolor speciﬁc and were excluded from further analyses. Also excluded were intergenic regions where the primary similarity was to tRNAs or rRNAs. The location of sequence similarity, relative to the ﬂanking coding sequences, was also evalu- ated, and regions where similarity was within 40 nt of either ﬂanking gene were excluded, so as to remove possible riboswitches, and conserved operator sequences. sRNAFinder The program sRNAFinder was used to predict candidate sRNA genes throughout intergenic regions of the S. coelicolor genome (13). sRNAFinder uses a hidden Markov model to integrate primary sequence data with comparative genomics information for the purpose of predicting non-coding RNA genes. Primary sequence data includes dinucleotide frequency information and evidence of transcription termination signals. Compara- tive genomics information includes evidence of compensa- tory basepair mutations that conserve RNA secondary structure. For the comparative genomics analysis, the following genomes were employed: Burkholderia pseudo- mallei, Mycobacterium avium, Nocardia farcinica, Pseudo- monas aeruginosa, S. avermitilis, S. coelicolor and Xanthomonas citri. Along with each sRNA gene predic- tion, sRNAFinder reports a measure of conﬁdence or like- lihood, for the prediction (see Supplementary Table S1). Cloning of small RNAs sRNA species smaller than 50 nt were cloned from RNA samples harvested from 24 h cultures grown on solid MS medium (29), as outlined in Haiser et al. (30). Bacterial strains and culture conditions S. coelicolor strains used are summarized in Table 1, and were grown at 308C on either solid R2YE (rich medium—RM) or minimal medium (MM) supplemented with 0.5% mannitol (w/v) (29). E. coli strains (DH5a or TOP10F0) were grown in liquid LB medium or on solid LB agar at 378C. Table 1. Streptomyces coelicolor strains Streptomyces coelicolor strain M600 M145 J1501 N985 J1700 J2400 J2402 Genotype SCP1 SCP2 SCP1 SCP2 hisAl uraAl strAl pgl SCP1 SCP2 M145 bldB::aphI J1501 bldA39 M145 whiG::hyg M145 whiB::hyg References (50) (29) (51) (52) (53) (54) (54)