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Archaea. 2007 May; 2(2): 137–143. Published online 2007 March 7. | PMCID: PMC2686384 |
Copyright © 2007 Heron Publishing—Victoria, Canada Gene decay in archaea M. W.J. van Passel,*1 C. S. Smillie,1 and H. Ochman1 1 Department of Biochemistry and Molecular Biophysics, University of Arizona, 1007 East Lowell Street, Tucson, AZ 85721, USA Received November 17, 2006; Accepted February 19, 2007.
The gene-dense chromosomes of archaea and bacteria were long thought
to be devoid of pseudogenes, but with the massive increase in
available genome sequences, whole genome comparisons between closely
related species have identified mutations that have rendered numerous
genes inactive. Comparative analyses of sequenced archaeal genomes
revealed numerous pseudogenes, which can constitute up to 8.6% of the
annotated coding sequences in some genomes. The largest proportion of
pseudogenes is created by gene truncations, followed by frameshift
mutations. Within archaeal genomes, large numbers of pseudogenes
contain more than one inactivating mutation, suggesting that
pseudogenes are deleted from the genome more slowly in archaea than in
bacteria. Although archaea seem to retain pseudogenes longer than do
bacteria, most archaeal genomes have unique repertoires of
pseudogenes.
Keywords: comparative genomics, pseudogenes
Genomic studies have allowed for the in-depth analysis of the genetic
structure of organisms from all domains of life. Unfortunately, archaea
are rather poorly represented among the more than 400 fully sequenced
genomes, due in part to the difficulties associated with their
cultivation and genetic manipulation
( Schleper et al. 2005). Although
the Eukarya and the Archaea are sister taxa
( Ciccarelli et al. 2006), the
overall organization of archaeal genes and genomes is more similar to
that of the Bacteria. Like bacteria, archaea usually contain a single
circular chromosome and have a high gene density, with genes organized
in operons and lacking introns.
The elucidation of complete genome sequences has instigated large-scale
experimental and computational analyses that have attempted to identify
and annotate all genes encoded in a genome. Despite such efforts, up to
40% of the predicted coding sequences in many archaeal genomes lack a
predicted function ( Galperin and Koonin
2004, Fricke et al. 2006).
It has been suggested that, within virtually all genomes, there are
annotated genes that have been mutationally inactivated and can never be
assigned a function ( Ochman and Davalos
2006). Eukaryotic genomes have long been known to contain large
numbers of non-functional genes ( Vanin
1985), but the full extent of their pseudogene contents was not
evident until whole genome sequences became available. Genome-wide
analyses of the nematode ( Harrison et
al. 2001) and human ( Torrents et
al. 2003) genomes have detected massive amounts of now-defunct
genes, whose numbers likely exceed the number of functional genes in
each genome.
Because of the small size and high gene density of bacterial genomes, it
was originally thought that prokaryotes would contain few, if any,
pseudogenes ( Lawrence et al.
2001). In addition, the majority of pseudogenes in higher
eukaryotes are generated by retrotransposition
( Vanin 1985), a process unknown
in bacteria or archaea. Nevertheless, pseudogenes are now known to be a
common feature of many bacterial genomes
( Lerat and Ochman 2004,
2005) and may constitute nearly
half of the annotated coding sequences (CDSs) in the genomes of some
pathogens ( Andersson et al. 1998,
Cole et al. 2001,
Toh et al. 2006).
A previous assessment of prokaryotic genomes estimated that up to 5% of
the annotated genes in archaeal genomes may, in fact, be pseudogenes
( Liu et al. 2004). This analysis,
in which the contents of 53 bacterial and 11 archaeal genome sequences
were compared, suggested that the pseudogenes originated predominantly
from failed horizontal gene transfer events (as opposed to the
mutational inactivation of resident genes). However, this analysis
included comparisons of genes over broad phylogenetic distances, did not
discriminate between orthologous and paralogous genes, and ignored genes
without an assigned function. As such, this approach could lead to
inaccurate appraisals of the pseudogene contents, particularly in the
Archaea, which were not densely sampled and in which the functions of
many genes have not been characterized. Moreover, if archaea have more
split genes than bacteria, as suggested previously
( Snel et al. 2000), the
recognition of pseudogenes through inter-domain comparisons becomes less
straightforward.
An alternative approach, one in which closely related genome sequences
are compared, can enhance the resolution of pseudogenes because larger
fractions of the genome are shared and there are fewer problems in
assigning orthology. Most bacterial genomes have been found to contain
largely unique sets of pseudogenes, suggesting that pseudogenes are
constantly formed in, and rapidly eliminated from, the genome
( Lerat and Ochman 2004); however,
the frequencies with which pseudogenes are generated, maintained and
removed from archaeal genomes are unknown. With the current availability
of numerous archaeal genome sequences, including multiple members of
particular genera, we sought to identify and enumerate the pseudogenes
in archaea, and assessed their mechanisms of formation and erosion.
Selection of phylogenetically related species
We used 16S rDNA sequences to determine the phylogenetic relationships
of archaea for which genome sequences were available at NCBI as of
April 1, 2006. Using the MEGA3.1 software package
( Kumar et al. 2004), we applied
a Minimum Evolution bootstrap test of phylogeny with pairwise deletion
and 10,000 replicates. The relationships, accession numbers and
genomic properties of the 15 selected species are presented in
.
Pseudogene identification
Pseudogenes were identified by comparing the genome contents of
sequenced members of the same clade, as shown in
. Full genome sequences
and sets of GenBank annotated proteins for the corresponding genomes
were obtained from NCBI (http://www.ncbi.nih.gov). Inclusion
thresholds for aligned sequences were as described previously
( Lerat and Ochman 2005):
E-values of < 1 0 –15 and sequence identity of >
75% for clades containing species with 16S rDNA identity > 95%
(i.e., Pyrococcus spp., Methanosarcina
spp., Thermoplasma spp.; highlighted in grey
in ); and E-values of
< 1 0 –10and sequence identity of > 49% for
clades containing species with 16S rDNA identity < 95% (i.e.,
Halobacterium/ Haloarcula,
Methanococcus/ Methanocaldococcus,
Sulfolobus spp.).
Within each clade of closely related organisms, the annotated proteins
within the genome of one species were queried against the complete
nucleotide sequence of another species from the same clade. This was
done reciprocally for all crosswise comparisons within each clade
using the TBLASTN search tool ( Altschul
et al. 1997). The Y –F program suite, developed to
recognize truncated and otherwise mutationally altered CDSs
( Lerat and Ochman 2004), was
applied to the TBLASTN output, returning a list of candidate
pseudogenes that was then curated manually. One way in which Y
–F recognizes potential pseudogenes is by identifying internal
stop codons in a query gene. For the comparisons of the three
Methanosarcina spp., it was necessary to disable this
feature for the amber stop codon TAG, which instead codes for
pyrrolysine in this genus ( James et
al. 2001). In addition, all pseudogenes were curated manually
for known recoding events
( Cobucci-Ponzano et al. 2005).
Pseudogenes detected by the comparative analysis of full genome
sequences can be either positional homologs or non-positional homologs
of CDSs in the reciprocal genomes, based on gene context conservation:
positional pseudogenes are those that share at least one neighboring
gene with the corresponding functional copy in the related genome.
To identify gene-inactivating mutations, the putative pseudogenes were
aligned with their counterparts using CLUSTALW 1.83
( Thompson et al. 1994).
Gene-inactivating mutations were partitioned into five classes:
frameshifts (insertions or deletions of 1 or 2 nucleotides in length),
deletions (> 2 nucleotides in length), insertions (> 2
nucleotides in length), truncations (large deletions at either or both
ends of a coding sequence), and nonsense mutations. In cases where
more than one gene-inactivating mutation was identified in an
alignment, the mutation was classified as a combination of two or more
of these classes.
Pseudogene content analyses in archaeal genomes
We assessed the pseudogene contents of 15 species, representing eight
genera of archaea, by comparing the full genome sequences of the most
closely related taxa. The fractions of predicted pseudogenes range
from 0.3% to 8.6% of the total number of annotated protein coding
sequences, including unannotated pseudogenes, i.e., intergenic regions
that contain the eroded remnants of genes that have been annotated as
CDS in a related genome (). Applying identical methods, the range and the average
pseudogene fractions are much lower in archaea than in pathogenic
bacteria but similar to those of free-living bacteria
( Lerat and Ochman 2004,
2005).
There are almost equal fractions of positional (i.e., sharing at least
one neighboring gene with its counterpart in a related genome) and
non-positional pseudogenes in most genomes, and within both classes,
there are large numbers of unannotated pseudogenes
( Table 1). Across taxa, the
fraction of these unannotated pseudogenes increases with the total
number of detected pseudogenes. As expected, large proportions of
predicted pseudogenes are annotated as having hypothetical functions
( Table 1). Inactivated mobile
element-associated genes are more abundant among non-positional
pseudogenes, especially in Sulfolobus spp. and
Methanosarcina spp. The lists of the predicted
pseudogenes are provided in Supplementary Tables
S1
and
S2.
| Table 1.
Numbers, proportions and characteristics of pseudogenes in the
Archaea. Numbers depicted are the total number of predicted
pseudogenes, with bracketed numbers indicating the number of
positional (more ...) |
Mechanisms of gene inactivation
When compared to bacterial pseudogenes, archaeal
pseudogenes are more highly decayed, with a larger fraction containing
more than one inactivating mutation
(). In both archaea and
bacteria, non-positional pseudogenes show greater gene decay than do
positional pseudogenes. Truncations, frameshifts, and combinations
thereof, are the most widespread mechanisms by which genes are
inactivated in archaea (Supplementary
Figure
S1).
A total of six pseudogenes were inactivated by changes in the lengths
of a homopolymeric stretch spanning more than six nucleotides, and all
of these frameshifts occurred in A/T tracts (data not shown). Unlike
the situation observed in bacterial pathogens, the interruption of
genes by insertion sequences is relatively rare in archaea, with only
5 and 28 IS-inactivated genes from a total of 550 positional and 711
non-positional pseudogenes, respectively. Among the non-positional
pseudogenes, 22 of the 28 IS-inactivated genes occur in S.
solfataricus, which contains exceptionally large numbers of
mobile elements ( She et al.
2001).
Because pseudogenes are under no functional constraint and are
evolutionarily neutral, such regions can divulge the underlying rate
and pattern of mutations within a genome
( Li et al. 1981,
Mira et al. 2001). In general,
deletions occur more frequently than insertions in archaeal
pseudogenes ().
Thermoplasma volcanium is the only archaeal species
in which the cumulative indel length is positive (i.e., more DNA is
inserted than deleted in the detected pseudogenes), and this is due to
a single 88-bp duplication in the NADH ubiquinone oxidoreductase gene.
Although their overall indel lengths are negative, in the
non-positional pseudogenes of species within the
Methanosarcina clade, insertions outnumber deletions,
with most cases involving the insertional inactivation of transposases
within mobile elements.
GC content of archaeal genes with pseudogene counterparts
Previous analyses have reported a significant difference between the
nucleotide composition of genes that have a pseudogene counterpart and
those that do not ( Lerat and Ochman
2004). We searched for this in archaea for the functional
counterparts of both positional and non-positional pseudogenes
(Supplementary
Table
S3) and found no consistent trend. Genes with positional or
non-positional pseudogene counterparts have higher GC contents than
genes without pseudogene counterparts in Methanocaldococcus
jannaschii, Methanococcus maripaludis and the
Sulfolobus spp . genomes. Genes with
non-positional pseudogene counterparts have a significantly lower GC
percentage in the Methanosarcina clade. In this case,
the difference in GC contents is due to the many inactivated mobile
elements, which typically have a different GC content than that of
their hosts.
Shared pseudogenes between closely related archaeal genomes
The occurrence of only a single inactivating mutation in the vast
majority of bacterial pseudogenes implies that pseudogenes are rapidly
generated in, and removed from, these genomes. This process has
resulted in genomes containing largely nonoverlapping pseudogene
inventories, even among strains averaging only 1% in sequence
divergence ( Lerat and Ochman
2004). Although archaea seem to retain pseudogenes longer than
do bacteria (as evident from the higher incidence of pseudogenes
containing multiple inactivating mutations), most archaeal genomes
have unique repertoires of pseudogenes. Among Pyrococcus
spp ., which average 30 positional
pseudogenes, not more than three are shared between any two strains.
Higher fractions of shared pseudogenes are observed in
Sulfolobus and Methanosarcina, which
can be ascribed, in part, to shared inactivated transposases that
occur in multiple copies (Supplementary Tables
S1
and
S2).
Comparative analyses of full genome sequences show that pseudogenes can
occur at high frequencies and often outnumber the functional copies of
genes. Even among bacteria, which have relatively small and streamlined
genomes, up to half of the genome of some facultative pathogens, such as
Rickettsia prowazekii and Mycobacterium
tuberculosis ( Andersson et al.
1998, Cole et al. 2001),
is relegated to pseudogenes. In our analyses of 15 archaeal genomes
representing eight genera, we found that the predicted fractions of
pseudogenes range from 0.3% to 8.6%, corresponding to 4 to 260
pseudogenes per genome. These numbers are lower than the pseudogene
contents found in most bacteria by the same approach; however, previous
studies focused primarily on bacterial pathogens, which are known to
have more severely degraded genomes than non-pathogenic bacteria. The
pseudogene contents of archaea are likely to be more similar to those
non-pathogenic, free-living bacteria, although relatively few bacterial
genomes have been evaluated by these methods.
The available annotations of many of the completed archaeal genomes
identify no pseudogenes. Although the original publications of the
genomes of M. jannaschii
( Bult et al. 1996),
S. solfataricus ( She et
al. 2001), S. acidocaldarius
( Chen et al. 2005),
T. acidophilum ( Ruepp
et al. 2000) and T. volcanium
( Kawashima et al. 2000) each
describe certain genes as being inactivated, they are not classified as
such in the most commonly used public databases (e.g., NCBI, www.
ncbi.nlm.nih.gov). Among the genomes that we analyzed, only the
annotations of M. mazei and M. barkeri
contain pseudogenes (112 and 136 compared with the 90 and 153 that we
identified in these genomes, respectively). And similar to our
observations for S. solfataricus,
She et al. (2001) identified 43
partial transposases.
In contrast to NCBI, the IMG database (img.jgi.doe.gov)
( Markowitz et al. 2006) provides
re-annotated archaeal genomes and lists somewhat different numbers of
total genes as well as pseudogenes for these genomes. Because the
specific annotation can impact the identification of pseudogenes (IMG
predicts on average 2.5% more protein coding genes than does NCBI), it
is not possible to compare directly the numbers of pseudogenes listed at
IMG with those detected in the present study.
Perrodou et al. (2006) have
pointed out an association between different genome annotation
approaches and pseudogene prediction, noting that, in some genomes,
pseudogenes might be attributable to sequencing errors. Because a
minority of the pseudogenes is formed by the most common sequencing
errors, such artifacts have probably contributed little to the sets of
pseudogenes that we recognized. Although it has been found that, in
Pyrobaculum aerophilum, a putative deficiency in
mismatch repair genes has created a variety of long and variable
mononucleotide runs ( Fitz-Gibbon et al.
2002), intraspecific variation in homopolymeric tract lengths are
not a major source of gene inactivation in the archaeal genomes
considered in this study.
Liu et al. (2004) also applied a
comparative approach to identify the pseudogenes in 64 sequenced
genomes, including 11 archaeal species. Their analyses compared species
from different domains (e.g., the Archaea versus the Bacteria), which
can make assignments of orthology difficult. To refine their analyses
and to safeguard against the inclusion of annotation artifacts, they
limited their comparisons to protein coding genes with assigned
functions, thereby excluding all those annotated as
“hypothetical.” Such restrictions, though valid, preclude
accurate assessments of the full complement of pseudogenes in a genome.
On one hand, the numbers of pseudogenes detected by such methods might
be overestimated because orthologous genes from divergent taxa might
remain functional despite extreme length or sequence differences. And
this may be complicated by the occurence of more split genes in archaea
than in bacteria ( Snel et al.
2000). On the other hand, most pseudogenes detected through
comparisons of closely related genomes are functionally annotated as
“hypothetical,” which is not surprising since expendable
genes are less likely to be among those whose functions have been
assigned. Therefore, excluding these genes would result in
underestimates of the actual number of pseudogenes. Despite these
caveats, the pseudogene contents of archaea reported by
Liu et al. (2004) are
qualitatively similar to those identified with Y –F; both
approaches indicate that archaeal genomes contain fewer pseudogenes than
do pathogenic bacteria, and both indicate that archaeal pseudogenes are
more decayed than bacterial pseudogenes. Also, in both our and Liu et
al.’s analyses, S. solfataricus contains the
largest number of pseudogenes of all surveyed archaeal genomes.
In addition to cataloging archaeal pseudogenes, our analyses provide
insights into the mutational processes that occur within these genomes.
In bacteria, strand slippage in mononucleotide repeats is considered a
common mutagenic mechanism; however, few archaeal pseudogenes are
attributable to variation in mononucleotide repeats. The association of
strand slippage with immune evasion in bacterial pathogens
( van der Woude and Baumler 2004)
may explain the lower incidence of this type of frameshift in archaea.
Strand slippage is evident in some of the mobile-element associated
genes in S. acidocaldarius (IS1-family pseudogenes) and
S. solfataricus (IS1048-family pseudogenes), many of
which were modified by frameshifts in adenine mononucleotide repeats
larger than six residues. Because mobile elements have recently been
shown to create different functional proteins by strand slippage
( Baranov et al. 2006), such events
might not always indicate an inactivated gene. In addition, recent
evidence has indicated that recoding may occur in Sulfolobus
( Cobucci-Ponzano et al.
2003, 2005).
We find that the primary mechanism of gene inactivation in archaea is by
truncation, which is responsible for the formation of over 30% of all
pseudogenes. Among pseudogenes that have been inactivated by a single
truncation event, unannotated pseudogenes are, on average, shorter than
annotated pseudogenes, and non-positional pseudogenes are shorter than
positional pseudogenes. Defunct transposable elements contain more
inactivating mutations than other pseudogenes in S.
tokodaii, S. solfataricus, M.
acetivorans and M. barkeri. Whether the higher
decay observed in transposable elements is caused by unsuccessful
transposition events is unclear, although previous studies in
Sulfolobus have shown that the rate of precise excision
of mobile elements was low ( Blount and
Grogan 2005).
Pseudogene contents, as predicted by most comparative studies, still
represent rather conservative estimates of the actual numbers of
inactivated genes within a genome. Several classes of pseudogenes, such
as those caused by missense mutations that abolish protein function as
well as regulatory mutations that disrupt gene expression, will go
undetected by this approach. Such comparative analyses also ignore
strain-specific genes (i.e., ORFans) for which there are no homologous
sequences available for comparison. Although many ORFans are thought to
be functional ( Daubin and Ochman
2004), they are unlikely to be essential to cell function and are
prone to inactivation and loss.
Pseudogene detection by comparative analyses relies on the quality of
the genome annotation, which can deviate substantially among different
approaches ( Brenner 1999).
Increases in the availability of genome sequences from closely related
species, which are still in short supply for archaea, have greatly
facilitated genome annotation. As more genome sequences become
available, we suspect that there will be less need to rely on
experimental evidence to make accurate functional predictions about the
majority of genes in a genome.
Supplementary Table S1. List of archaeal positional pseudogenes.
Supplementary Table S2. List of archaeal non-positional pseudogenes.
Supplementary Figure S1. Numbers of pseudogenes and their mechanisms
of inactivation in each of the archaeal genomes considered.
Supplementary Table S3. The GC percentages of gene sets that do and do
not contain a pseudogene counterpart.
The authors thank Emmanuelle Lerat for assistance with the computational
analyses and Becky Nankivell for assistance in the preparation of this
manuscript. This work is supported by a research grant No. GM56120 from
the National Institutes of Health to H.O.
R1. Altschul S.F., Madden T.L., Schaffer A.A., Zhang J., Zhang Z., Miller W., Lipman D.J. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25:3389–3402. [PubMed] R2. Andersson S.G., Zomorodipour A., Andersson J.O., et al. The genome sequence of Rickettsia prowazekii and the origin of mitochondria. Nature. 1998;396:133–140. [PubMed] R3. Baranov P.V., Fayet O., Hendrix R.W., Atkins J.F. Recoding in bacteriophages and bacterial IS elements. Trends Genet. 2006;22:174–181. [PubMed] R4. Blount Z.D., Grogan D.W. New insertion sequences of Sulfolobus: functional properties and implications for genome evolution in hyperthermophilic archaea. Mol. Microbiol. 2005;55:312–325. [PubMed] R5. Brenner S.E. Errors in genome annotation. Trends Genet. 1999;15:132–133. [PubMed] R6. Bult C.J., White O., Olsen G.J., et al. Complete genome sequence of the methanogenic archaeon, Methanococcus jannaschii
. Science. 1996;273:1058–1073. [PubMed] R7. Chen L., Skovgaard M., et al. The genome of Sulfolobus acidocaldarius, a model organism of the Crenarchaeota. J. Bacteriol. 2005;187:4992–4999. [PubMed] R8. Ciccarelli F.D., Doerks T., Von mering C., Creevey C.J., Snel B., Bork P. Toward automatic reconstruction of a highly resolved tree of life. Science. 2006;311:1283–1287. [PubMed] R9. Cobucci-Ponzano B., Trincone A., Giordano A., Rossi M., Moracci M. Identification of an archaeal a-L-fucosidase encoded by an interrupted gene. Production of a functional enzyme by mutations mimicking programmed –1 frameshifting. J. Biol. Chem. 2003;278:14622–14631. [PubMed] R10. Cobucci-Ponzano B., Rossi M., Moracci M. Recoding in archaea. Mol. Microbiol. 2005;55:339–348. [PubMed] R11. Cole S.T., Eiglmeier K., Parkhill J., et al. Massive gene decay in the leprosy bacillus. Nature. 2001;409:1007–1011. [PubMed] R12. Daubin V., Ochman H. Bacterial genomes as new gene homes: the genealogy of ORFans in E. coli. Genome Res. 2004;14:1036–1042. [PubMed] R13. Fitz-Gibbon S.T., Ladner H., Kim U.J., Stetter K.O., Simon M.I., Miller J.H. Genome sequence of the hyperthermophilic crenarchaeon Pyrobaculum aerophilum
. Proc. Natl. Acad. Sci. USA. 2002;99:984–989. [PubMed] R14. Fricke W.F., Seedorf H., Henne A., Kruer M., Liesegang H., Hedderich R., Gottschalk G., Thauer R.K. The genome sequence of Methanosphaera stadtmanae reveals why this human intestinal archaeon is restricted to methanol and H2 for methane formation and ATP synthesis. J. Bacteriol. 2006;188:642–658. [PubMed] R15. Galperin M.Y., Koonin E.V. ‘Conserved hypothetical’ proteins: prioritization of targets for experimental study. Nucleic Acids Res. 2004;32:5452–5463. [PubMed] R16. Harrison P.M., Echols N., Gerstein M.B. Digging for dead genes: an analysis of the characteristics of the pseudogene population in the Caenorhabditis elegans genome. Nucleic Acids Res. 2001;29:818–830. [PubMed] R17. James C.M., Ferguson T.K., Leykam J.F., Krzycki J.A. The amber codon in the gene encoding the monomethylamine methyltransferase isolated from Methanosarcina barkeri is translated as a sense codon. J. Biol. Chem. 2001;276:34252–34258. [PubMed] R18. Kawashima T., Amano N., Koike H., et al. Archaeal adaptation to higher temperatures revealed by genomic sequence of Thermoplasma volcanium
. Proc. Natl. Acad. Sci. USA. 2000;97:14257–14262. [PubMed] R19. Kumar S., Tamura K., Nei M. MEGA3: integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment. Brief. Bioinform. 2004;5:150–163. [PubMed] R20. Lawrence J.G., Hendrix R.W., Casjens S. Where are the pseudogenes in bacterial genomes? Trends Microbiol. 2001;9:535–540. [PubMed] R21. Lerat E., Ochman H. Y –F: exploring the outer limits of bacterial pseudogenes. Genome Res. 2004;14:2273–2278. [PubMed] R22. Lerat E., Ochman H. Recognizing the pseudogenes in bacterial genomes. Nucleic Acids Res. 2005;33:3125–3132. [PubMed] R23. Li W.H., Gojobori T., Nei M. Pseudogenes as a paradigm of neutral evolution. Nature. 1981;292:237–239. [PubMed] R24. Liu Y., Harrison P.M., Kunin V., Gerstein M. Comprehensive analysis of pseudogenes in prokaryotes: widespread gene decay and failure of putative horizontally transferred genes. Genome Biol. 2004;5:R64. [PubMed] R25. Markowitz V.M., Korzeniewski F., Palaniappan K., et al. The integrated microbial genomes (IMG) system. Nucleic Acids Res. 2006;34:D344–348. [PubMed] R26. Mira A., Ochman H., Moran N.A. Deletional bias and the evolution of bacterial genomes. Trends Genet. 2001;17:589–596. [PubMed] R27. Ochman H., Davalos L.M. The nature and dynamics of bacterial genomes. Science. 2006;311:1730–1733. [PubMed] R28. Perrodou E., Deshayes C., Muller J., Schaeffer C., Van dorsselaer A., Ripp R., Poch O., Reyrat J.M., Lecompte O. ICDS database: interrupted CoDing sequences in prokaryotic genomes. Nucleic Acids Res. 2006;34:D338–343. [PubMed] R29. Ruepp A., Graml W., Santos-martinez M.L., et al. The genome sequence of the thermoacidophilic scavenger Thermoplasma acidophilum
. Nature. 2000;407:508–513. [PubMed] R30. Schleper C., Jurgens G., Jonuscheit M. Genomic studies of uncultivated archaea. Nat. Rev. Microbiol. 2005;3:479–488. [PubMed] R31. She Q., Singh R.K., Confalonieri F., et al. The complete genome of the crenarchaeon Sulfolobus solfataricus P2. Proc. Natl. Acad. Sci. USA. 2001;98:7835–7840. [PubMed] R32. Snel B., Bork P., Huynen M. Genome evolution. Gene fusion versus gene fission. Trends Genet. 2000;16:9–11. [PubMed] R33. Thompson J.D., Higgins D.G., Gibson T.J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994;22:4673–4680. [PubMed] R34. Toh H., Weiss B.L., Perkin S.A., Yamashita A., Oshima K., Hattori M., Aksoy S. Massive genome erosion and functional adaptations provide insights into the symbiotic lifestyle of Sodalis glossinidius in the tsetse host. Genome Res. 2006;16:149–156. [PubMed] R35. Torrents D., Suyama M., Zdobnov E., Bork P. A genome-wide survey of human pseudogenes. Genome Res. 2003;13:2559–2567. [PubMed] R36. van der Woude M.W., Baumler A.J. Phase and antigenic variation in bacteria. Clin. Microbiol. Rev. 2004;17:581–611. [PubMed] R37. Vanin E.F. Processed pseudogenes: characteristics and evolution. Annu. Rev. Genet. 1985;19:253–272. [PubMed]
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