The All-Species Living Tree project: a 16S rRNA-based phylogenetic tree of all sequenced type strains.

By Pablo Yarza, Michael Richter, Jörg Peplies, J. Euzéby, R. Amann, K. Schleifer, Wolfgang Ludwig, Frank Oliver Glöckner, Ramon Rosselló-Mora. Systematic and Applied Microbiology, 2008

914 citations recorded by the source corpus.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/48e5a883132545e5aeed45b0d1cfa9be85c8b9e4

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Citations in the corpus

The first 1000 cultured species of the human gastrointestinal microbiota (2014, methodology): “The phylogenetic trees presented here were extracted from the reference phylogenetic tree of the SILVA database (Yarza et al., 2008).”
Benchmarking of Methods for Genomic Taxonomy (2014, methodology): “It has previously been noted that some of the isolates present in public databases and, hence, used in this study, are wrongly annotated (17, 46, 47).”
Shifting the genomic gold standard for the prokaryotic species definition (2009, background): “However, the current species catalog of 8,000 validly published names (34) is far from the estimated actual number of classifiable taxa, which is expected to be several orders of magnitude higher (44).”
A Proposed Genus Boundary for the Prokaryotes Based on Genomic Insights (2014, background): “A new proposed genus would have approximately 6% divergence in 16S rRNA gene sequence from its closest genus (10).”
Taxonomic Classification of Bacterial 16S rRNA Genes Using Short Sequencing Reads: Evaluation of Effective Study Designs (2013, methodology): “We selected the ,8,500 bacterial sequences and their corresponding taxonomic annotation from ‘‘The All-Species Living Tree’’ project (LTP; [41,42]) as a test set, considering each time only the subsequences relevant for the experimental design in question.”
25 years of serving the community with ribosomal RNA gene reference databases and tools. (2017, background): “Partner projects and collaborations such as LTP are shown as well.”
Primer, Pipelines, Parameters: Issues in 16S rRNA Gene Sequencing (2021, methodology): “Our finding illustrated that the Silva and RDP databases were the most accurate 16S rRNA gene databases, showing similar performances consistently superior to those of GRD, LTP, and GG in terms of true positives at the genus level.”
DECIPHER, a Search-Based Approach to Chimera Identification for 16S rRNA Sequences (2011, methodology): “The small subunit (SSU) rRNA molecule has been used extensively as a phylogenetic marker since the late 1980s (18), and nowadays, 16S rRNA sequences are essential for microbial identification (2, 19).”
The SILVA ribosomal RNA gene database project: improved data processing and web-based tools (2012, background): “In addition to the tag ‘(T)’ used by EMBL-Bank to mark a sequence as type strain, the following tags are used by SILVA: . the label ‘e[G]’ is added if an entry is part of the list of genomes offered by the EMBL-Bank, . the label ‘l[T]’ is added if the entry is part of the type strain datasets of ‘Th”
Notes on the characterization of prokaryote strains for taxonomic purposes. (2010, background): “A recent article (Yarza et al., 2008) has also indicated that a ‘lower cut-off window’ of 95 % 16S rRNA gene sequence similarity may be reasonable, but it must be emphasized that this was based on the evaluation of taxa that are delineated by a broad spectrum of methods and not on 16S rRNA gene…”
The human milk microbiome changes over lactation and is shaped by maternal weight and mode of delivery. (2012, methodology): “Sequences were assigned to each sample by the 8-bp barcode and passed through the Ribosomal Database Project classifier software (21), where each sequence was assigned a phylum, class, family, and genus, as long as the taxonomic assignment was unambiguous within an 80% confidence threshold.”
Genome-Based Taxonomic Classification of the Phylum Actinobacteria (2018, background): “Comprehensive, aligned, near full-length 16S rRNA gene sequence data for theActinobacteria andChloroflexiwere initially taken from the All-Species Living Tree Project (Yarza et al., 2008) and considerably augmented by screening the more recent taxonomic literature (the complete DSMZ reference collec”
Likelihood Ratios for Out-of-Distribution Detection (2019, background): “We choose the mutation rate as 10%, because the average identity between bacteria is estimated 96.4% at the genus level, and 90.1% at the family level (Yarza et al., 2008).”