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few previous studies have explicitly investigated
the mechanism of species recognition in hybrid
zones. Even fewer studies have provided additional information on the genetics of hybrid
fitness and the preferred traits, or evidence for
reinforcement (22–25). Nevertheless, disproportionately many genes involved in reproductive
isolation seem to be located on the sex chromosomes (15, 26, 27). In Lepidoptera, which also
have heterogametic females, sex-linked traits seem
to be more associated with reproductive isolation
than in other insects (28), and it has been suggested that ornaments and preferences for these
ornaments evolve more readily in organisms with
ZW than with XY sex chromosomes (26, 29).
Although speciation would benefit from any kind
of linkage (or other recombination-suppressing
mechanism) that can maintain these genetic associations, traits involved in pre-zygotic isolation may
simply be more likely to occur on sex chromosomes than on autosomes and possibly more
likely on Z than on X chromosomes (27). Sex
chromosomes in general, and the Z in particular,
may therefore be hotspots for speciation genes.
References and Notes
1. T. Dobzhansky, Am. Nat. 74, 312 (1940).
2. M. R. Servedio, M. A. F. Noor, Annu. Rev. Ecol. Syst. 34,
339 (2003).
3. J. A. Coyne, H. A. Orr, Speciation (Sinauer, Sunderland,
MA, 2004).
4. M. Kirkpatrick, V. Ravigné, Am. Nat. 159, 865 (2000).
5. J. Felsenstein, Evol. Int. J. Org. Evol. 35, 124 (1981).
6. D. Ortíz-Barrientos, M. A. F. Noor, Science 310, 1467
(2005).
7. C. ten Cate, D. R. Vos, Adv. Stud. Behav. 28, 1
(1999).
8. D. E. Irwin, T. Price, Heredity 82, 347 (1999).
9. M. R. Servedio, S. A. Sæther, G.-P. Sætre, Evol. Ecol., in
press, available at www.springerlink.com/content/
ut50156832448324/.
10. A. J. Trickett, R. K. Butlin, Heredity 73, 339 (1994).
Microbial Population Structures
in the Deep Marine Biosphere
Julie A. Huber,1* David B. Mark Welch,1 Hilary G. Morrison,1 Susan M. Huse,1
Phillip R. Neal,1 David A. Butterfield,2 Mitchell L. Sogin1
The analytical power of environmental DNA sequences for modeling microbial ecosystems depends
on accurate assessments of population structure, including diversity (richness) and relative
abundance (evenness). We investigated both aspects of population structure for microbial
communities at two neighboring hydrothermal vents by examining the sequences of more than
900,000 microbial small-subunit ribosomal RNA amplicons. The two vent communities have
different population structures that reflect local geochemical regimes. Descriptions of archaeal
diversity were nearly exhaustive, but despite collecting an unparalleled number of sequences,
statistical analyses indicated additional bacterial diversity at every taxonomic level. We predict that
hundreds of thousands of sequences will be necessary to capture the vast diversity of microbial
communities, and that different patterns of evenness for both high- and low-abundance taxa may
be important in defining microbial ecosystem dynamics.
T
he interrogation of DNA from environmental samples has revealed new dimensions
in microbial diversity and community-
wide metabolic potential. The first analysis of a
dozen polymerase chain reaction (PCR) amplicons
of ribosomal RNA (rRNA) sequence from a
www.sciencemag.org
SCIENCE
VOL 318
11. M. R. Servedio, Evol. Int. J. Org. Evol. 54, 21 (2000).
12. D. Ortíz-Barrientos et al., Genetica 116, 167 (2002).
13. M. R. Servedio, G.-P. Sætre, Proc. R. Soc. London Ser.
B 270, 1473 (2003).
14. D. W. Hall, M. Kirkpatrick, Evol. Int. J. Org. Evol. 60, 908
(2006).
15. A. R. Lemmon, M. Kirkpatrick, Genetics 173, 1145
(2006).
16. G.-P. Sætre et al., Nature 387, 589 (1997).
17. T. Veen et al., Nature 411, 45 (2001).
18. G.-P. Sætre et al., Proc. R. Soc. London Ser. B 270, 53
(2003).
19. See methods in supporting material on Science Online.
20. G.-P. Sætre, M. Král, S. Bureš, J. Avian Biol. 28, 259
(1997).
21. M. J. O'Neill et al., Dev. Gen. Evol. 210, 18 (2000).
22. J. W. Grula, O. R. J. Taylor, Evol. Int. J. Org. Evol. 34, 688
(1980).
23. P. R. Grant, R. B. Grant, Biol. J. Linn. Soc. 60, 317
(1997).
24. V. K. Iyengar, H. K. Reeve, T. Eisner, Nature 419, 830
(2002).
25. M. A. F. Noor et al., Proc. Natl. Acad. Sci. U.S.A. 98, 12084
(2001).
26. M. Kirkpatrick, D. W. Hall, Evol. Int. J. Org. Evol. 58, 683
(2004).
27. V. B. Kaiser, H. Ellegren, Evol. Int. J. Org. Evol. 60, 1945
(2006).
28. M. G. Ritchie, S. D. F. Phillips, in Endless Forms: Species
and Speciation, D. J. Howard, S. H. Berlocher, Eds.
(Oxford Univ. Press, Oxford, 1998), pp. 291–308.
29. H. K. Reeve, D. F. Pfenning, Proc. Natl. Acad. Sci. U.S.A.
100, 1089 (2003).
30. We thank T. F. Hansen, Ø. H. Holen, A. J. van Noordwijk,
K. van Oers, F. Pulido, T. O. Svennungsen, and M. Visser
for suggestions. The study was supported by grants from
the Swedish Research Council, the Research Council of
Norway, Formas, the Netherlands Organization for
Scientific Research, NSF, the Czech Ministry of Education,
and the Czech Science Foundation.
Downloaded from www.sciencemag.org on November 19, 2007
Moreover, they are not expected to occur in birds
according to one predominant theory of the evolution of genomic imprinting, and genes that are
imprinted in mammals show ordinary bi-allelic
expression in birds (21). We therefore conclude
that species-assortative mating preferences in
flycatcher hybrid zones are mainly due to Zlinked genes.
All three major components of reproductive
isolation (species recognition, species-specific
male traits, and hybrid incompatibilities) being
Z linked in flycatchers should facilitate an evolutionary response to natural selection against
hybridization. This is because genetic associations between the male and the female components of pre-zygotic barriers to gene flow, as well
as between pre-zygotic and post-zygotic barriers,
can easily be maintained (see supporting online
text for further discussion of the flycatcher system). Our results suggest that some organisms
may be prone to speciation through reinforcement because of the mediating role of the sex
chromosomes. Compared to autosomally inherited species recognition, both sex linkage and
sexual imprinting may allow incipient species to
avoid a collapse in assortative mating during secondary contact and be less likely to succumb to
gene flow and fusion (9). However, paternal sexual imprinting requires that females be socially
exposed to their father, which is not always true
even in birds. Conversely, because reduced hybrid fitness is commonly caused by sex-linked
incompatibilities (3), sex linkage of species recognition might provide a general connection
between key components of reproductive isolation, which facilitates adaptive speciation in the
face of gene flow.
Sex-chromosome linkage of species-assortative
female mate preferences may be widespread, but
Supporting Online Material
www.sciencemag.org/cgi/content/full/318/5847/95/DC1
Materials and Methods
SOM Text
References
20 February 2007; accepted 15 August 2007
10.1126/science.1141506
mixed bacterioplankton population revealed the
ubiquitous SAR11 cluster (1), and a recent environmental shotgun sequence survey of microbial communities in the surface ocean has
identified 6.1 million predicted proteins (2, 3).
To realize the full potential of metagenomics for
modeling energy and carbon flow, microbial
biogeography, and the relationship between
microbial diversity and ecosystem function, it
is necessary to estimate both the richness and
evenness of microbial population structures.
We used a tag sequencing strategy that combines the use of amplicons of the V6 hypervariable region of small-subunit (SSU) rRNA as
proxies for the presence of individual phylotypes
[operational taxonomic units (OTUs)] with massively parallel sequencing. Our goal was to provide assessments of microbial diversity, evenness,
and community structure at a resolution two to
three orders of magnitude greater than that afforded by cloning and capillary sequencing of
longer SSU rRNA amplicons (4). We used this
strategy to attempt an exhaustive characterization of the bacterial and archaeal diversity at two
5 OCTOBER 2007
97
Purpose/Questions
1. Proof of principle for the method
2. How big is microbial diversity?
3. What is the community composition of
these environments?
4. How similar are the microbial communities
in these two nearby similar environments?
Approach
Sample
Isolate DNA
rRNA PCR
Sequence
Divide into groups
Phylogenetic analysis
Approach
Traditional
Sample
Isolate DNA
rRNA PCR
Sequence
Divide into groups
Phylogenetic analysis
This paper
Approach
Traditional
Sample
This paper
Isolate DNA
Entire ssu-rRNA
1000-1500bp
rRNA PCR
Sequence
Divide into groups
Phylogenetic analysis
Variable region 6
50-75bp
Approach
Traditional
Sample
This paper
Isolate DNA
Entire ssu-rRNA
1000-1500bp
Sequencing
hundreds of sequences
rRNA PCR
Variable region 6
Sequence
454 Pyrosequencing
50-75bp
hundreds of thousands of sequences
Divide into groups
Phylogenetic analysis
Approach
Traditional
Sample
This paper
Isolate DNA
Entire ssu-rRNA
1000-1500bp
Sequencing
hundreds of sequences
OTUs
rRNA PCR
Variable region 6
Sequence
454 Pyrosequencing
50-75bp
hundreds of thousands of sequences
Divide into groups Diversity metrics
Phylogenetic analysis
Approach
Traditional
Sample
This paper
Isolate DNA
Entire ssu-rRNA
1000-1500bp
Sequencing
hundreds of sequences
OTUs
Trees
rRNA PCR
Variable region 6
Sequence
454 Pyrosequencing
50-75bp
hundreds of thousands of sequences
Divide into groups Diversity metrics
Phylogenetic analysis Taxonomic bins
Competing methods
• Cultivation
• Traditional environmental rRNA sequencing
• rRNA DGGE
• rRNA tRFLP
• Metagenomics
Competing methods
• Cultivation
• Traditional environmental rRNA sequencing
• rRNA DGGE
• rRNA tRFLP
• Metagenomics
Competing methods
• Cultivation
• Traditional environmental rRNA sequencing
• rRNA DGGE
• rRNA tRFLP
• Metagenomics
Competing methods
• Cultivation
• Traditional environmental rRNA sequencing
• rRNA DGGE
• rRNA tRFLP
• Metagenomics
Competing methods
• Cultivation
• Traditional environmental rRNA sequencing
• rRNA DGGE
• rRNA tRFLP
• Metagenomics
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A
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150
A
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G
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ACUACUGG
A GGGG
G GG CCUCUU G
A
C
G
C
- Canonical base pair (A-U, G-C)
A
U
CGCC
CGA UGGC A
U CC GGGGA G
A
A
G
U
U
- G-U base pair
A
AG
UA A
U
200 A
A
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- G-A base pair
A
A
C
C
C
G
U
U
- Non-canonical base pair
A
U
G
C
G
A
Every 10th nucleotide is marked with a tick mark,
A C
II
III
I
Escherichia coli
(J01695)
1. Bacteria 2. Proteobacteria 3. gamma subdivision
4. Enterobacteriaceae and related symbionts
5. Enterobacteriaceae 6. Escherichia
Nov 1999
Symbols Used In This Diagram:
1046R
967F
A A
U
G
U
U
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C
G
C 1100
G
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GC
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700
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A
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CCUUA
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CC
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A GGGG
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A
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- Canonical base pair (A-U, G-C)
A
U
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CGA UGGC A
U CC GGGGA G
A
A
G
U
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- G-U base pair
A
AG
UA A
U
200 A
A
G
A
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A
A
C
C
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G
U
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A
U
G
C
G
A
Every 10th nucleotide is marked with a tick mark,
A C
V6
61nt in E.coli
II
III
I
Escherichia coli
(J01695)
1. Bacteria 2. Proteobacteria 3. gamma subdivision
4. Enterobacteriaceae and related symbionts
5. Enterobacteriaceae 6. Escherichia
Nov 1999
Symbols Used In This Diagram:
rarefaction curves (Fig. 2) indicated that our sam-
assigned fewer than 1% of tags to phylotypes (20).
Table 1. Chemical and SSU rRNA tag characteristics of the two sites.
Vent name
Sample year
Volume filtered (ml)
Cells ml−1 (range)
Culturable* hyper/thermophilic
heterotrophs per liter
DNA recovered (mg)
Total number of archaeal V6
tag sequences†
Total number of bacterial V6 tag
sequences†
Total number of e-proteobacterial V6 tag
sequences†
Depth (m)
Latitude and longitude
Average temperature (°C)
Maximum temperature (°C)
H2S/DT (mmol kg−1 °C−1)
pH
Mg (mmol/kg)
Alkalinity (meq/liter)
Mn (mmol/kg)
Fe (mmol/kg)
Silica (mmol/kg)
FS312
FS396
Bag City
2003
1003
1.21 × 105
(9.77 × 104 to 1.26 × 105)
140 to 4200
Marker 52
2004
2000
1.57 × 105
(1.02 × 105 to 2.12 × 105)
20 to 720
0.9
200,199
2.4
16,428
442,058
247,662
122,823
147,515
1,537
45.92°N, 129.99°W
31.2
31.4
7.2
6.26
48.3
2.4
19.8
0.8
1.46
1,529
45.94°N, 129.99°W
24.4
24.9
18.9
5.08
50.8
3.7
4.8
7.9
1.07
*Cultured at 70° or 90°C in 0.3% yeast extract and peptone with elemental sulfur; Ar headspace.
passed quality control [as described in (11)].
†Trimmed reads that
Downloaded from www.sciencemag.org on November 19, 2007
mpled on
sampled
sites had
ube worm
and most
52 has a
elevated
of which
t; Marker
.
archaeal
two sites.
% [genercies (11)]
ulate rare13). Taxdifferences
le overlap
is particstructure
mple, ale 10° to
strate the
(14), the
al families
1). Nearsequences
ns, raising
diversity
Sequences
of microoxidizing
al phylo-
s
7
-
Mg (mmol/kg)
Alkalinity (meq/liter)
Mn (mmol/kg)
Fe (mmol/kg)
Silica (mmol/kg)
48.3
2.4
19.8
0.8
1.46
50.8
3.7
4.8
7.9
1.07
*Cultured at 70° or 90°C in 0.3% yeast extract and peptone with elemental sulfur; Ar headspace.
passed quality control [as described in (11)].
†Trimmed reads that
Table 2. Sequencing information and diversity estimates for all bacteria and archaea.
Total number of V6 tag sequences*
Total unique V6 tag sequences
Total OTUs at 3% difference (phylotypes)
Chao1 estimator of richness at 3% difference (95% CI)
ACE estimator of richness at 3% difference (95% CI)
Bray-Curtis similarity index at 3% difference†
Jaccard similarity index at 3% difference†
*Trimmed reads that passed quality control [as described in (11)].
on a scale of 0 to 1 (where 1 represents identical communities).
BER 2007
VOL 318
SCIENCE
Bacteria
Archaea
689,720
30,108
18,537
36,869
(36,108 to 37,663)
37,038
(36,613 to 37,473)
0.08
0.12
216,627
5,979
1,931
2,754
(2,594 to 2,952)
2,678
(2,616 to 2,745)
0.01
0.08
†Similarity between communities at sites FS312 and FS396
www.sciencemag.org
ε
Downloaded from www.sciencemag.org on November 19, 2007
ε
Epsilon Proteobacteria
The Epsilon proteobacteria consist of only a few genera, mainly the curved to spirilloid Wolinella,
Helicobacter, and Campylobacter. Most of the known species inhabit the digestive tract of animals and
humans and serve as symbionts (Wolinella in cows) or pathogens (Helicobacter in the stomach,
Campylobacter in the duodenum). There have also been numerous environmental sequences of epsilons
recovered from hydrothermal vent and cold seep habitats. (Wikipedia)
•
Proteobacteria
other Bacteria
•
•
Campylobacterales
◦
Campylobacteraceae
▪
Arcobacter
▪
Campylobacter
▪
Candidatus Thioturbo
▪
Sulfurospirillum
◦
Helicobacteraceae
▪
Flexispira
▪
Helicobacter
▪
Sulfuricurvum
▪
Sulfurimonas
▪
Thiovulum
▪
Wolinella
◦
Hydrogenimonaceae
▪
Hydrogenimonas
Nautiliales
◦
Nautiliaceae
▪
Caminibacter
▪
Lebetimonas
▪
Nautilia
unclassified Epsilonproteobacteria
◦
Nitratifractor
◦
Nitratiruptor
◦
Sulfurovum
◦
Thioreductor
◦
Geospirillium sp. KoFum
◦
Thiomicrospira sp. CVO
REPORTS
Fig. 2. Rarefaction curves for total bacterial and
archaeal communities at the two sampling sites
FS312 and FS396 at 3% and 6% difference levels.
plications for our ability to sample and identify all
the ecologically relevant members of microbial
communities in other high-diversity habitats, such
as soils (22), microbial mats (23), and communities
In addition, the importance of mi
cannot be overlooked, and metagenom
nity reconstructions from the two ve
here would likely be largely chimeric
of sequences from closely related
which may mask important biological
Methods such as the massively para
quencing approach used here, combin
multitude of other quantitative and
tools now available to microbial eco
serve as necessary accompaniments
nomic gene surveys as we strive to
the impact of diversity on ecosyste
and long-term stability (24).
References and Notes
1. S. J. Giovannoni, T. B. Britschgi, C. L. Moy
Nature 345, 60 (1990).
2. D. B. Rusch et al., PLoS Biol. 5, e77 (200
3. S. Yooseph et al., PLoS Biol. 5, e16 (2007
4. M. L. Sogin et al., Proc. Natl. Acad. Sci. U
12115 (2006).
Supplementary Figure 2. Rarefaction curves at 3% difference for bacterial phylotypes
within (a) FS312 alpha-proteobacteria, (b) FS396 alpha-proteobacteria, (c) FS312 betaproteobacteria, (d) FS396 beta-proteobacteria, (e) FS312 delta-proteobacteria, (f) FS396
Supplementary Figure 2 Continued
delta-proteobacteria, (g) FS312 !-proteobacteria, (h) FS396"! -proteobacteria, (i) FS312
gamma-proteobacteria, (j) FS396 gamma-proteobacteria, (k) FS312 Anaerolineae, (l)
FS396 Anaerolineae, (m) FS312 Clostridia, (n) FS396 Clostridia, (o) FS312
Flavobacteria, (p) FS396 Flavobacteria, (q) FS312 Arcobacter spp., and (r) FS396
Sulfurovum spp.
Supplementary Figure 2 Continued
Sogin, et al., 2006 PNAS 103:12115
Similarity of 454 sequence tags from FS396 to the V6RefDB database. ʻʻAll tag distributionʼʼ plots the number of tag
sequences for all samples versus the percentage difference from the best-matching sequence in V6RefDB. ʻʻPercent
unique readsʼʼ from all samples shows the percentage difference between each distinct tag sequence and its best match
in V6RefDB. ʻʻPercent total tagsʼʼ plots the cumulative percentage of reads in all samples at or below a given percentage
difference from best matches in V6RefDB.
Purpose/Questions
1. Proof of principle for the method √
2. How big is microbial diversity? Huge!
3. What is the community composition of
these environments? Lots of
proteobacteria, especially epsilons
4. How similar are the microbial communities
in these two nearby similar environments?
Very different at all phylogenetic levels
Not only are there billions and billions of Bacteria,
there are billions and billions of kinds of Bacteria.