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  • 1
    Language: English
    In: Genome biology, 11 October 2011, Vol.12(10), pp.R98
    Description: Gene function analysis of the obligate intracellular bacterium Chlamydia pneumoniae is hampered by the facts that this organism is inaccessible to genetic manipulations and not cultivable outside the host. The genomes of several strains have been sequenced; however, very little information is available on the gene structure and transcriptome of C. pneumoniae. Using a differential RNA-sequencing approach with specific enrichment of primary transcripts, we defined the transcriptome of purified elementary bodies and reticulate bodies of C. pneumoniae strain CWL-029; 565 transcriptional start sites of annotated genes and novel transcripts were mapped. Analysis of adjacent genes for co-transcription revealed 246 polycistronic transcripts. In total, a distinct transcription start site or an affiliation to an operon could be assigned to 862 out of 1,074 annotated protein coding genes. Semi-quantitative analysis of mapped cDNA reads revealed significant differences for 288 genes in the RNA levels of genes isolated from elementary bodies and reticulate bodies. We have identified and in part confirmed 75 novel putative non-coding RNAs. The detailed map of transcription start sites at single nucleotide resolution allowed for the first time a comprehensive and saturating analysis of promoter consensus sequences in Chlamydia. The precise transcriptional landscape as a complement to the genome sequence will provide new insights into the organization, control and function of genes. Novel non-coding RNAs and identified common promoter motifs will help to understand gene regulation of this important human pathogen.
    Keywords: Genome, Bacterial ; Transcriptome ; Chlamydophila Pneumoniae -- Genetics ; Gene Expression Profiling -- Methods ; RNA, Bacterial -- Genetics
    ISSN: 14656906
    E-ISSN: 1474-760X
    E-ISSN: 14656914
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  • 2
    In: Jiang, Yuxiang; Oron, Tal Ronnen; Clark, Wyatt T. Bankapur, Asma R.; D’Andrea, Daniel; Lepore, Rosalba; Funk, Christopher S.; Kahanda, Indika; Verspoor, Karin M.; Ben-Hur, Asa; Koo, Da Chen Emily; Penfold-Brown, Duncan; Shasha, Dennis; Youngs, Noah; Bonneau, Richard; Lin, Alexandra; Sahraeian, Sayed M. E.; Martelli, Pier Luigi; Profiti, Giuseppe; Casadio, Rita; Cao, Renzhi; Zhong, Zhaolong; Cheng, Jianlin; Altenhoff, Adrian; Skunca, Nives; Dessimoz, Christophe; Dogan, Tunca; Hakala, Kai; Kaewphan, Suwisa; Mehryary, Farrokh; Salakoski, Tapio; Ginter, Filip; Fang, Hai; Smithers, Ben; Oates, Matt; Gough, Julian; Törönen, Petri; Koskinen, Patrik; Holm, Liisa; Chen, Ching-Tai; Hsu, Wen-Lian; Bryson, Kevin; Cozzetto, Domenico; Minneci, Federico; Jones, David T.; Chapman, Samuel; BKC, Dukka; Khan, Ishita K.; Kihara, Daisuke; Ofer, Dan; Rappoport, Nadav; Stern, Amos; Cibrian-Uhalte, Elena; Denny, Paul; Foulger, Rebecca E.; Hieta, Reija; Legge, Duncan; Lovering, Ruth C.; Magrane, Michele; Melidoni, Anna N.; Mutowo-Meullenet, Prudence; Pichler, Klemens; Shypitsyna, Aleksandra; Li, Biao; Zakeri, Pooya; ElShal, Sarah; Tranchevent, Léon-Charles; Das, Sayoni; Dawson, Natalie L.; Lee, David; Lees, Jonathan G.; Sillitoe, Ian; Bhat, Prajwal; Nepusz, Tamás; Romero, Alfonso E.; Sasidharan, Rajkumar; Yang, Haixuan; Paccanaro, Alberto; Gillis, Jesse; Sedeño-Cortés, Adriana E.; Pavlidis, Paul; Feng, Shou; Cejuela, Juan M.; Goldberg, Tatyana; Hamp, Tobias; Richter, Lothar; Salamov, Asaf; Gabaldon, Toni; Marcet-Houben, Marina; Supek, Fran; Gong, Qingtian; Ning, Wei; Zhou, Yuanpeng; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Toppo, Stefano; Ferrari, Carlo; Giollo, Manuel; Piovesan, Damiano; Tosatto, Silvio C.E.; del Pozo, Angela; Fernández, José M.; Maietta, Paolo; Valencia, Alfonso; Tress, Michael L.; Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Rehman, Hafeez Ur; Re, Matteo; Mesiti, Marco; Valentini, Giorgio; Bargsten, Joachim W.; van Dijk, Aalt D. J.; Gemovic, Branislava; Glisic, Sanja; Perovic, Vladmir; Veljkovic, Veljko; Veljkovic, Nevena; Almeida-e-Silva, Danillo C.; Vencio, Ricardo Z. N.; Sharan, Malvika; Vogel, Jörg; Kansakar, Lakesh; Zhang, Shanshan; Vucetic, Slobodan; Wang, Zheng; Sternberg, Michael J. E.; Wass, Mark N.; Huntley, Rachael P.; Martin, Maria J.; O’Donovan, Claire; Robinson, Peter N.; Moreau, Yves; Tramontano, Anna; Babbitt, Patricia C.; Brenner, Steven E.; Linial, Michal; Orengo, Christine A.; Rost, Burkhard; Greene, Casey S.; Mooney, Sean D.; Friedberg, Iddo; Radivojac, Predrag (2016). An expanded evaluation of protein function prediction methods shows an improvement in accuracy. Genome Biology 17 ,
    Description: Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.
    Keywords: Protein Function Prediction ; Disease Gene Prioritization ; Disintegrin ; Ontology ; Adam
    ISBN: 0003834282000
    ISSN: 1474-760X
    ISSN: 14747596
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