# Title:

## greengenes: Chimera-checked 16S rRNA gene database and workbench compatible with ARB

## Authors:

DeSantis, T.Z.^1^

Hugenholtz, P.^2^

Larsen, N.^3^

Rojas, M.^4^

Brodie, E.L.^1^

Keller, K.^5^

Huber, T.^6^

Dalevi, D.^7^

Hu, P.^1^

Andersen, G.L.^1^

^1^Center for Environmental Biotechnology

Lawrence Berkeley National Laboratory

1 Cyclotron Road, Mail Stop 70A-3317

Berkeley, CA 94720

USA

^2^Microbial Ecology Program

DOE Joint Genome Institute

2800 Mitchell Drive Bldg 400-404

Walnut Creek, CA 94598

USA

^3^Danish Genome Institute

Gustav Wieds vej 10 C

DK-8000 Aarhus C

Denmark

^4^Department of Bioinformatics

Baylor University

P.O. Box 97356, 1311 S. 5th St.

Waco, TX 76798-7356

USA

^5^Department of Bioengineering

University of California

Berkeley, CA 94720

USA

^6^Departments of Biochemistry and Mathematics

The University of Queensland

Brisbane Qld 4072

Australia

^7^Department of Computer Science

Chalmers University of Technology

SE-412 96

Göteborg, Sweden

To whom correspondence should be addressed:

GLAndersen@lbl.gov

Abstract

A 16S rRNA gene database
([http://greengenes.lbl.gov](http://greengenes.lbl.gov/)) addresses
limitations of public repositories by providing chimera-screening,
standard alignments and taxonomic classification using multiple
published taxonomies. Putative chimeras existed in 5% of environmental
sequences and 0.5% of records derived from isolates. Environmental
sequences were classified in 100 phylum-level lineages within archaea
and bacteria.

# Abstract

An online full-length small-subunit rRNA gene (SSU) database called
"greengenes", that keeps pace with public submissions of both archaeal
and bacterial 16S SSU rDNA sequences, has been established at
http://greengenes.lbl.gov. It addresses a number of limitations
currently associated with SSU records in the public databases by
providing automated chimera-screening, taxonomic placement of
unclassified environmental sequences using multiple published taxonomies
for each record, multiple standard alignments and uniform
sequence-associated information curated from GenBank records.
Manipulation of 72,918 SSU records revealed putative chimeras in 5%
(1,901 of 38,412) of environmental sequences and, surprisingly, 0.5%
(201/36,643) of records derived from isolates. Environmental sequences
were classified in 78 bacterial phyla and 22 archaeal phylum-level
lineages. Greengenes also provides a suite of tools for manipulation of
sequences including an aligner and has been streamlined to interface
with the widely used ARB program.

Comparative analysis of 16S small sub-unit rRNA genes (hereafter
abbreviated as 16S) is commonly applied to survey the constituents of
microbial communities (4, 13, 24, 25), to infer bacterial and archaeal
evolution (14, 19), and to design monitoring and analysis tools such as
microarrays (5, 9, 17, 20, 30, 31). Because the production rate of 16S
sequence records from uncultured organisms now exceeds that from their
cultured counterparts, taxonomic placement of sequences lags behind. In
fact, 43% of full-length 16S records in GenBank are amalgamated into
pseudo-divisions "environmental samples" or "unclassified". Annotation
styles are inconsistent creating barriers for computational
categorization of biological sources. Furthermore, since rRNA genes from
environmental DNA are usually PCR amplified, it is suspected that many
clandestine chimeric sequences are intercalated into the public
databases. From a small sample of 1,399 sequence records from known
phyla, it was estimated that 3% of the public data might contain
chimeras (2). The permeation of these poor quality data along with
barriers in exchanging nomenclature have led to several conflicting
taxonomies. The probability of mistakenly adopting a chimeric sequence
in a phylogenetic inference or as a reference for probe/primer design is
rising noticeably. Lastly, ARB (21) database administration needs to be
streamlined for those who maintain 16S collections on their local
computers.

Greengenes addresses these concerns by providing four features: a
standardized set of descriptive fields, taxonomic assignment, chimera
screening and ARB compatibility. Heuristics are used to consider the
author's annotations and categorize each source as a named or unnamed
isolate, an unnamed symbiont, or an uncultured organism. Other standard
descriptors include sequence quality measurements, authors, and a
"study_id" that links all the records associated with a project.
Greengenes maintains a consistent multiple sequence alignment of both
archaeal and bacterial 16S genes to facilitate taxonomic placement.
Taxonomy proposed by independent curators (NCBI, RDP (Bergey's) (7),
Wolfgang Ludwig (21), Phil Hugenholtz (16) and Norm Pace (24)) is
tracked to promote user awareness of several estimations of phylogenetic
descent allowing a balanced approach to node nomenclature when
generating dendrograms. Comprehensive chimera assessment is a
distinguishing characteristic of the greengenes data assembly process.
Each sequence is scored for chimeric potential, a break point is
estimated and parent sequences are identified. Furthermore, since
biologists often collect and visualize 16S relationships using the
freely available ARB software, greengenes simplifies the chore of
keeping a research groups private ARB database current by providing
standardized alignments and an import filter (greengenes.ift) that
imports the alignment and other standardized fields from 16S records
vetted weekly from GenBank.

To exemplify the utility of the greengenes data assembly process, and to
interrogate the validity of prokaryotic candidate phyla, we aligned and
chimera-checked over 72,000 public 16S sequences. Taxonomic
classifications were applied from the major curators where available.
Sequence data were imported from NCBI for complete or nearly complete
gene sequences (\>1250 nt in length) deposited as of September 21, 2005.
Alignment of both archaeal and bacterial sequences was performed with
the NAST aligner (8) against templates selected from a phylogenetically
broad collection (16). The resulting multiple sequence alignment (MSA)
was formatted so that each sequence occupies a consistent 7,682
characters or 4,182 characters, the later enabling compatibility with
RDP v8.1(22) alignments. Both these formats were concise enough for
browsing in common MSA graphical interfaces such as ClustalX(29),
MEGA(18) and the platform independent Jalview(6) as well as ARB. Other
standard expansions such as the \>20,000-character Ludwig alignment will
be an alternate format available in future releases to give maximum
flexibility to researchers.

For high-throughput chimera screening of the aligned sequences, the
program Bellerophon (15) was used with two modifications. First, the
algorithm was modified to reduce the number of potential parents
considered in the partial trees allowing run time to scale linearly
rather than logarithmically with the count of candidate sequences in a
collection. Secondly, a new metric was implemented that weights the
likelihood of a sequence being chimeric according to the similarity of
the parent sequences. The more distantly related the parent sequences
are to each other, the greater the likelihood that the inferred chimera
is real. The metric, called the divergence ratio, uses the average
sequence identity between the two fragments of the candidate and their
corresponding parent sequences as the numerator, and the sequence
identity between the parent sequences as the denominator. All
calculations were made using a 300 base pair window on either side of
the most likely break point. A divergence ratio of 1.1 was empirically
determined to be the threshold for classifying sequences as putatively
chimeric.

Taxonomy was linked to each record by various methods. NCBI and RDP
taxonomic nomenclature were extracted directly from the respective
Genbank-formatted records. The Pace and Ludwig annotations were exported
from curated ARB databases. The Hugenholtz taxonomy was also derived
from a curated ARB database in which tree topologies had been verified
using RAxML-VI (28) for maximum likelihood inference. The general time
reversible model of evolution (GTR) was applied together with
optimization of substitution rates and site-specific rates according to
a gamma distribution. Different search algorithms were considered
depending on the run-time of the standard hill-climb (SHC) search
method. If running in less than 8 hours, simulating annealing (SA) was
processed with the default starting temperature and a termination time
set to approximately 24 hours. If SA was not used and SHC terminated
within 24 hours, SHC was used. Further, the rapid hill-climb (RHC) was
used in all other cases when its running time was less than 24 hours.
The evolutionary diameter of the RHC search was specified explicitly
when all taxa were closely related to improve the search. If RHC did not
terminate within the set limit, the number of taxa was reduced. After
100 bootstrap replications, a consensus tree was calculated using
Concense (12) and imported into ARB. This database (greengenes.arb) is
available for download through greengenes and is updated periodically.

Of the 72,000 NCBI records analyzed, 52% were derived from uncultured
organisms, the majority of which have been deposited over the last five
years (Figure 1). Only two studies have submitted greater than one
thousand full-length clones, however, we expect the number of large 16S
surveys to rise due to the availability and falling cost of high
throughput sequencing. Bellerophon detection of putative chimeras in 5%
of the 38,412 sequences from uncultured organisms was not unexpected
considering initial estimates (2). Surprisingly, 0.5% of sequences
derived from pure cultures were also determined to be putative chimeras.
In addition, 2,573 full-length, 16S-annotated GenBank records only
partially aligned with NAST, which suggests that an even greater
abundance of poor quality data exist in the public repositories taken as
a whole. Discovery of chimeras in 16S data collections is crucial if the
data set will be a foundation for applied bioinformatics. They pose a
fundamental problem when used as templates with probe selection
software, a growing concern with the recent increase in 16S microarray
probe development (3, 8, 11). The 15 to 30 bases surrounding the
chimeric break-point can appear sufficiently unique from all other
records in a database causing a probe selection algorithm to justifiably
identify this region as a target's signature and suggest complementary
probes to be synthesized. These probes would appear highly valuable
considering their minimal mis-hybridization potential, but, in fact,
they would rarely be useful since they target non-existent organisms.
Chimera test results from greengenes allow greater control over input to
probe selection software, will aid in avoiding artificial T-RFLP pattern
predictions from the ARB-compatible TRF-CUT (26) and can increase the
accuracy of sampling rarefaction curves (27).

The fraction of putative chimeras within the deposited sequences from an
individual study varies from none (10) to over 20% (23) (Figure 1)
suggesting that chimera screening is still not being uniformly applied
by researchers. This was mainly found to occur in sparsely populated
candidate phyla. For instance, bacterial phyla 'SPAM', 'SAM', and '5'
and the class SA2 (Euryarchaeota) may require re-evaluation. Likewise
the genera *Catabacter, Dyadobacter* and *Symbiobacterium* are currently
anchored by sequences with evidence of chimeric composition. Additional
sequences could lead to the empirical rejection of certain
classifications or may aid in defining the true breadth of sequence
variation for these taxa.

Comparison of five different taxonomies uncovered a surprisingly large
disparity between expert curators. Loosely interpreting "phyla" to be
any labeled grouping or division immediately subordinate to the domains
Archaea or Bacteria, the five curations were compared in a Venn diagram
(Figure 2). The main source of the disparity arises from discordant
naming of novel candidate phyla, or absence of names for candidate
phyla. For example Pace and Hugenholtz have independently named over a
dozen phylum-level lineages many of which are the same lineages and RDP
has not named any of these lineages. This is a consequence of the huge
number of environmental sequences in the public databases and frequent
redundant naming of environmental lineages in the literature. We hope
that making multiple taxonomic classifications available through
greengenes will aid in standardizing classification, particularly
classification of environmental lineages.

Greengenes is also a functional workbench to assist in analysis of
user-generated 16S sequences. Batches of sequencing reads can be
uploaded for quality-based trimming and creation of multiple sequence
alignments. Three types of similarity searches are available; seed
extension by BLAST (1), similarity based on shared 7-mers by a tool
entitled "Simrank", or direct degenerative pattern match for
probe/primer evaluation. Results are displayed using user-preferred
taxonomic nomenclature and can be saved between sessions.

In summary, greengenes offers annotated, chimera-checked, full-length
SSU 16S rRNA gene sequences in standard alignment formats. The
relational database links taxonomies from multiple curators and multiple
sequences from a single study. It was revealed that incongruent
taxonomic nomenclature exists among curators even at the phylum-level.
Bellerophon found putative chimeras in sequences derived from both
uncultured and isolated organisms. The data set can be compared to
user-provided sequences via web interface or can be imported directly
into ARB for advanced analyses. We anticipate that greengenes will be
valuable to researchers conducting environmental surveys and in SSU
microarray design.

**Acknowledgments**

We thank Kirk Harris and Norm Pace for sharing their ARB database with
us and Richard Phan for assistance with web graphics. The computational
infrastructure was provided in part by the Virtual Institute for
Microbial Stress and Survival (http://VIMSS.lbl.gov) supported by the U.
S. Department of Energy, Office of Science, Office of Biological and
Environmental Research, Genomics:GTL Program and the Natural and
Accelerated Bioremediation Research Program through contract
DE-AC02-05CH11231 between Lawrence Berkeley National Laboratory and the
U. S. Department of Energy. Web application development was funded in
part by the Department of Homeland Security under grant number
HSSCHQ04X00037.

Figure 1. 16S rRNA gene sequencing projects producing at least 150
full-length records. All projects were submitted to Genbank between
October 1999 and October 2005. Sequences were generated from
gastrointestinal (GI), soil (SO), vaginal (VG), aerosol (AR), culture
collection (CC), insect (IN), water (WA), waste treatment (WT) or fecal
(FC) sources as labeled on the x-axis and. Projects are ordered by
sequence count.

![](media/image1.jpeg){width="6.0in" height="5.433333333333334in"}

Figure 2. Phyla-level nomenclature shared among independent curators
represented as a five-way Venn diagram. Yellow spheres represent the 126
Phyla or Candidate Division names used in at least one of the five
taxonomy systems (Pace, Hugenholtz, Ludwig, RDP, or NCBI). Numbers in
parentheses are the count of Phyla or Candidate Division names
recognized by an individual curator. Clusters of yellow spheres
connected by more than one colored web are names used by multiple
curators. Image rendered by AutoFocus software (Aduna B.V., The
Netherlands). A complete table of phyla-level nomenclature comparisons
is available at:
http://greengenes.lbl.gov/Download/Taxonomic_Outlines/Comparing_Phyla_from_5_Curators_v9-14-05.html

![](media/image2.png){width="4.946527777777778in"
height="5.472222222222222in"}

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