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We show here that colonization of the small intestine of mice with a single commensal microbe, segmented filamentous bacterium (SFB), is sufficient to induce the appearance of CD4(+) T helper cells that produce IL-17 and IL-22 (Th17 cells) in the lamina propria. How commensal microbiota influence the host immune system is poorly understood. The gastrointestinal tract of mammals is inhabited by hundreds of distinct species of commensal microorganisms that exist in a mutualistic relationship with the host. Clustal Omega also has powerful features for adding sequences to and exploiting information in existing alignments, making use of the vast amount of precomputed information in public databases like Pfam. On larger data sets, Clustal Omega outperforms other packages in terms of execution time and quality. The accuracy of the package on smaller test cases is similar to that of the high-quality aligners.
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In this paper, we describe a new program called Clustal Omega, which can align virtually any number of protein sequences quickly and that delivers accurate alignments. Some methods allow computation of larger data sets while sacrificing quality, and others produce high-quality alignments, but scale badly with the number of sequences. These methods are starting to become a bottleneck in some analysis pipelines when faced with data sets of the size of many thousands of sequences. Most alignments are computed using the progressive alignment heuristic. Documentation includes a user's guide with a tutorial, a discussion of file formats and user options, and additional details on methods implemented in the sequence alignments are fundamental to many sequence analysis methods.
#DDTANK SYSTEM 5.5 PORTABLE#
Infernal is freely licensed under the GNU GPLv3 and should be portable to any POSIX-compliant operating system, including Linux and Mac OS/X. Source code, documentation, and the benchmark are downloadable from. This enables a roughly 100-fold acceleration over the previous version and roughly a 10,000-fold acceleration over exhaustive, non-filtered CM searches. Version 1.1 of Infernal introduces a new filter pipeline for RNA homology search based on accelerated profile HMM methods and HMM-banded CM alignment methods. Infernal uses CMs to search for new family members in sequence databases, and to create potentially large multiple sequence alignments. Infernal builds probabilistic profiles of the sequence and secondary structure of an RNA family called covariance models (CMs) from structurally annotated multiple sequence alignments given as input. Our results support the use of UniRef clusters as a comprehensive and scalable alternative to native sequence databases for similarity searches and reinforces its reliability for use in functional annotation. To examine coverage in similarity results, BLASTP searches against UniRef50 followed by expansion of the hit lists with cluster members demonstrated advantages compared with searches against UniProtKB sequences the searches are concise (∼7 times shorter hit list before expansion), faster (∼6 times) and more sensitive in detection of remote similarities (>96% recall at e-value <0.0001). Results show that UniRef clusters bring together proteins of identical molecular function in more than 97% of the clusters, implying that clusters are useful for annotation and can also be used to detect annotation inconsistencies.
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Intra-cluster molecular function consistency was examined by analysis of Gene Ontology terms. Our hypothesis is that these improvements would enhance the speed and sensitivity of similarity searches and improve the consistency of annotation within clusters.
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Non-redundancy and intra-cluster homogeneity in UniRef were recently improved by adding a sequence length overlap threshold. UniRef databases provide full-scale clustering of UniProtKB sequences and are utilized for a broad range of applications, particularly similarity-based functional annotation.