Functional analysis of internal transcribed spacer 2 of Saccharomyces cerevisiae ribosomal DNA.

Using the previously described "tagged ribosome" (pORCS) system for in vivo mutational analysis of yeast rDNA, we show that small deletions in the 5'-terminal portion of ITS2 completely block maturation of 26 S rRNA at the level of the 29 SB precursor (5.8 S rRNA-ITS2-26 S rRNA). Various deletions in the 3'-terminal part, although severely reducing the efficiency of processing, still allow some mature 26 S rRNA to be formed. On the other hand, none of the ITS2 deletions affect the production of mature 17 S rRNA. Since all of the deletions severely disturb the recently proposed secondary structure of ITS2, these findings suggest an important role for higher order structure of ITS2 in processing. Analysis of the effect of complete or partial replacement of S. cerevisiae ITS2 with its counterpart sequences from Saccharomyces rosei or Hansenula wingei, points to helix V of the secondary structure model as an important element for correct and efficient processing. Direct mutational analysis shows that disruption of base-pairing in the middle of helix V does not detectably affect 26 S rRNA formation. In contrast, introduction of clustered point mutations at the apical end of helix V that both disrupt base-pairing and change the sequence of the loop, severely reduces processing. Since a mutant containing only point mutations in the sequence of the loop produces normal amounts of mature 26 S rRNA, we conclude that the precise (secondary and/or primary) structure at the lower end of helix V, but excluding the loop, is of crucial importance for efficient removal of ITS2.     

Domain III of Saccharomyces cerevisiae 25 S ribosomal RNA: its role in binding of ribosomal protein L25 and 60 S subunit formation

Domain III of Saccharomyces cerevisiae 25 S rRNA contains the recognition site for the primary rRNA-binding ribosomal protein L25, which belongs to the functionally conserved EL23/L25 family of ribosomal proteins. The EL23/L25 binding region is very complex, consisting of several irregular helices held together by long-distance secondary and tertiary interactions. Moreover, it contains the eukaryote-specific V9 (D7a) expansion segment. Functional characterisation of the structural elements of this site by a detailed in vitro and in vivo mutational analysis indicates the presence of two separate regions that are directly involved in L25 binding. In particular, mutation of either of two conserved nucleotides in the loop of helix 49 significantly reduces in vitro L25 binding, thus strongly supporting their role as attachment sites for the r-protein. Two other helices appear to be primarily required for the correct folding of the binding site. Mutations that abolish in vitro binding of L25 block accumulation of 25 S rRNA in vivo because they stall pre-rRNA processing at the level of its immediate precursor, the 27 S(B) pre-rRNA. Surprisingly, several mutations that do not significantly affect L25 binding in vitro cause the same lethal defect in 27 S(B) pre-rRNA processing. Deletion of the V9 expansion segment also leads to under-accumulation of mature 25 S rRNA and a twofold reduction in growth rate. We conclude that an intact domain III, including the V9 expansion segment, is essential for normal processing and assembly of 25 S rRNA.     

Variable copy number, intra-genomic heterogeneities and lateral transfers of the 16S rRNA gene in Pseudomonas

Even though the 16S rRNA gene is the most commonly used taxonomic marker in microbial ecology, its poor resolution is still not fully understood at the intra-genus level. In this work, the number of rRNA gene operons, intra-genomic heterogeneities and lateral transfers were investigated at a fine-scale resolution, throughout the Pseudomonas genus. In addition to nineteen sequenced Pseudomonas strains, we determined the 16S rRNA copy number in four other Pseudomonas strains by Southern hybridization and Pulsed-Field Gel Electrophoresis, and studied the intra-genomic heterogeneities by Denaturing Gradient Gel Electrophoresis and sequencing. Although the variable copy number (from four to seven) seems to be correlated with the evolutionary distance, some close strains in the P. fluorescens lineage showed a different number of 16S rRNA genes, whereas all the strains in the P. aeruginosa lineage displayed the same number of genes (four copies). Further study of the intra-genomic heterogeneities revealed that most of the Pseudomonas strains (15 out of 19 strains) had at least two different 16S rRNA alleles. A great difference (5 or 19 nucleotides, essentially grouped near the V1 hypervariable region) was observed only in two sequenced strains. In one of our strains studied (MFY30 strain), we found a difference of 12 nucleotides (grouped in the V3 hypervariable region) between copies of the 16S rRNA gene. Finally, occurrence of partial lateral transfers of the 16S rRNA gene was further investigated in 1803 full-length sequences of Pseudomonas available in the databases. Remarkably, we found that the two most variable regions (the V1 and V3 hypervariable regions) had probably been laterally transferred from another evolutionary distant Pseudomonas strain for at least 48.3 and 41.6% of the 16S rRNA sequences, respectively. In conclusion, we strongly recommend removing these regions of the 16S rRNA gene during the intra-genus diversity studies.     

Soil Bacterial Diversity Screening Using Single 16S rRNA Gene V Regions Coupled with Multi-Million Read Generating Sequencing Technologies

The novel multi-million read generating sequencing technologies are very promising for resolving the immense soil 16S rRNA gene bacterial diversity. Yet they have a limited maximum sequence length screening ability, restricting studies in screening DNA stretches of single 16S rRNA gene hypervariable (V) regions. The aim of the present study was to assess the effects of properties of four consecutive V regions (V3-6) on commonly applied analytical methodologies in bacterial ecology studies. Using an in silico approach, the performance of each V region was compared with the complete 16S rRNA gene stretch. We assessed related properties of the soil derived bacterial sequence collection of the Ribosomal Database Project (RDP) database and concomitantly performed simulations based on published datasets. Results indicate that overall the most prominent V region for soil bacterial diversity studies was V3, even though it was outperformed in some of the tests. Despite its high performance during most tests, V4 was less conserved along flanking sites, thus reducing its ability for bacterial diversity coverage. V5 performed well in the non-redundant RDP database based analysis. However V5 did not resemble the full-length 16S rRNA gene sequence results as well as V3 and V4 did when the natural sequence frequency and occurrence approximation was considered in the virtual experiment. Although, the highly conserved flanking sequence regions of V6 provide the ability to amplify partial 16S rRNA gene sequences from very diverse owners, it was demonstrated that V6 was the least informative compared to the rest examined V regions. Our results indicate that environment specific database exploration and theoretical assessment of the experimental approach are strongly suggested in 16S rRNA gene based bacterial diversity studies.     

Paramecium mitochondrial genes. I. Small subunit rRNA gene sequence and microevolution

The sequences of the small subunit mitochondrial rRNA genes from two divergent species of Paramecium (primaurelia and tetraurelia) were determined. The gene lies near the center of the linear mitochondrial genome, on the same strand as are all other currently identified genes. The sequences generally resemble their counterparts found in cytoplasmic, procaryotic, and other mitochondrial sources. The rDNA gene boundaries were located by nuclease S1 protection. Small subunit rDNA spans about 1680 nucleotides, including an extraneous 83-base pair sequence very near the 3' end which is unique to Paramecium mitochondria. This "insert" occurs at the apex of the highly variable in length penultimate helix, according to proposed models for small subunit rRNA secondary structure. A discontinuity occurs in isolated rRNA near the start of the insert, resulting in a stable 13 S RNA species and a small segment containing the remaining 3' portion of the gene. The overall rRNA gene sequence was 94% conserved between the two species, and the nucleotide differences consisted of 53% transitions, 37% transversions, and 9% insertions plus deletions. These substitutions were somewhat clustered, and the two most divergent regions coincided with the gene boundaries. The sequence was aligned with Escherichia coli 16 S rRNA for direct comparison of sequence and structure.     

Dissection of the 16S rRNA binding site for ribosomal protein S4

The ribosomal protein S4 from Escherichia coli is essential for initiation of assembly of 30S ribosomal subunits. We have undertaken the identification of specific features required in the 16S rRNA for S4 recognition by synthesizing mutants bearing deletions within a 460 nucleotide region which contains the minimum S4 binding site. We made a set of large nested deletions in a subdomain of the molecule, as well as individual deletions of nine hairpins, and used a nitrocellulose filter binding assay to calculate association constants. Some small hairpins can be eliminated with only minor effects on S4 recognition, while three hairpins scattered throughout the domain (76-90, 376-389 and 456-476) are essential for specific interaction. The loop sequence of hairpin 456-476 is important for S4 binding, and may be directly recognized by the protein. Some of the essential features are in phylogenetically variable regions; consistent with this, Mycoplasma capricolum rRNA is only weakly recognized by S4, and no specific binding to Xenopus laevis rRNA can be detected.     

Separate structural elements within internal transcribed spacer 1 of Saccharomyces cerevisiae precursor ribosomal RNA direct the formation of 17S and 26S rRNA.

Structural features of Internal Transcribed Spacer 1 (ITS1) that direct its removal from Saccharomyces cerevisiae pre-rRNA during processing were identified by an initial phylogenetic approach followed by in vivo mutational analysis of specific structural elements. We found that S. cerevisiae ITS1 can functionally be replaced by the corresponding regions from the yeasts Torulaspora delbrueckii, Kluyveromyces lactis and Hansenula wingei, indicating that structural elements required in cis for processing are evolutionarily conserved. Despite large differences in size, all ITS1 regions conform to the secondary structure proposed by Yeh et al. [Biochemistry 29 (1990) 5911-5918], showing five domains (I-V; 5'-->3') of which three harbour an evolutionarily highly conserved element. Removal of most of domain II, including its highly conserved element, did not affect processing. In contrast, highly conserved nucleotides directly downstream of processing site A2 in domain III play a major role in production of 17S, but not 26S rRNA. Domain IV and V are dispensable for 17S rRNA formation although an alternative, albeit inefficient, processing route to mature 17S rRNA may be mediated by a conserved region in domain IV. Each of these two domains is individually sufficient for efficient production of 26S rRNA, suggesting two independent processing pathways. We conclude that ITS1 is organized into two functionally and structurally distinct halves.     

The primary and secondary structure of yeast 26S rRNA.

We present the sequence of the 26S rRNA of the yeast Saccharomyces carlsbergensis as inferred from the gene sequence. The molecule is 3393 nucleotides long and consists of 48% G+C; 30 of the 43 methyl groups can be located in the sequence. Starting from the recently proposed structure of E. coli 23S rRNA (see ref. 25) we constructed a secondary structure model for yeast 26S rRNA. This structure is composed of 7 domains closed by long-range base pairings as n the bacterial counterpart. Most domains show considerable conservation of the overall structure; unpaired regions show extended sequence homology and the base-paired regions contain many compensating base pair changes. The extra length of the yeast molecule is due to a number of insertions in most of the domains, particularly in domain II. Domain VI, which is extremely conserved, is probably part of the ribosomal A site. alpha-Sarcin, which apparently inhibits the EF-1 dependent binding of aminoacyl-tRNA, causes a cleavage between position 3025 and 3026 in a conserved loop structure, just outside domain VI. Nearly all of the located methyl groups, like in E. coli, are present in domain II, V and VI and clustered to a certain extent mainly in regions with a strongly conserved primary structure. The only three methyl groups of 26S rRNA which are introduced relatively late during the processing are found in single stranded loops in domain VI very close to positions which have been shown in E. coli 23S rRNA to be at the interface of the ribosome.     

Nucleolar protein Nop12p participates in synthesis of 25S rRNA in Saccharomyces cerevisiae

A genetic screen for mutations synthetically lethal with temperature sensitive alleles of nop2 led to the identification of the nucleolar proteins Nop12p and Nop13p in Saccharomyces cerevisiae. NOP12 was identified by complementation of a synthetic lethal growth phenotype in strain YKW35, which contains a single nonsense mutation at codon 359 in an allele termed nop12-1. Database mining revealed that Nop12p was similar to a related protein, Nop13p. Nop12p and Nop13p are not essential for growth and each contains a single canonical RNA recognition motif (RRM). Both share sequence similarity with Nsr1p, a previously identified, non-essential, RRM-containing nucleolar protein. Likely orthologs of Nop12p were identified in Drosophila and Schizosaccharomyces pombe. Deletion of NOP12 resulted in a cold sensitive (cs) growth phenotype at 15°C and slow growth at 20 and 25°C. Growth of a nop12Δ strain at 15 and 20°C resulted in impaired synthesis of 25S rRNA, but not 18S rRNA. A nop13 null strain did not produce an observable growth phenotype under the laboratory conditions examined. Epitope-tagged Nop12p, which complements the cs growth phenotype and restores normal 25S rRNA levels, was localized to the nucleolus by immunofluorescence microscopy. Epitope-tagged Nop13p was distributed primarily in the nucleolus, with a lesser portion localizing to the nucleoplasm. Thus, Nop12p is a novel nucleolar protein required for pre-25S rRNA processing and normal rates of cell growth at low temperatures.     

Taxonomic Resolutions Based on 18S rRNA Genes: A Case Study of Subclass Copepoda

Biodiversity studies are commonly conducted using 18S rRNA genes. In this study, we compared the inter-species divergence of variable regions (V1–9) within the copepod 18S rRNA gene, and tested their taxonomic resolutions at different taxonomic levels. Our results indicate that the 18S rRNA gene is a good molecular marker for the study of copepod biodiversity, and our conclusions are as follows: 1) 18S rRNA genes are highly conserved intra-species (intra-species similarities are close to 100%); and could aid in species-level analyses, but with some limitations; 2) nearly-whole-length sequences and some partial regions (around V2, V4, and V9) of the 18S rRNA gene can be used to discriminate between samples at both the family and order levels (with a success rate of about 80%); 3) compared with other regions, V9 has a higher resolution at the genus level (with an identification success rate of about 80%); and 4) V7 is most divergent in length, and would be a good candidate marker for the phylogenetic study of Acartia species. This study also evaluated the correlation between similarity thresholds and the accuracy of using nuclear 18S rRNA genes for the classification of organisms in the subclass Copepoda. We suggest that sample identification accuracy should be considered when a molecular sequence divergence threshold is used for taxonomic identification, and that the lowest similarity threshold should be determined based on a pre-designated level of acceptable accuracy.     

Hypervariable regions (V1–V9) of the dinoflagellate 18S rRNA using a large dataset for marker considerations

DNA sequencing methods have been used for the molecular taxonomic discrimination of dinoflagellate protists, particularly using partial 18S rRNA sequences. This study evaluated the taxonomic discrimination power of rRNA gene hypervariable regions (V1 to V9) in dinoflagellates from a large dataset. These included 77 dinoflagellate species (9 orders, 17 families, 40 genera). The complete 18S rRNA sequences of the dinoflagellates ranged from 1,787 to 1,813?bp in length, and consisted of eight V regions with a total combined length of 678 to 699?bp. Regions longer than 100?bp were recoded for V2, V4, and V8 regions; high nucleotide divergences were detected in V1, V2, and V4 regions. Statistic tests showed that the divergences of individual V regions were significantly different (t-test, P?<?0.05) compared with the complete 18S rRNA. The V2 region showed the highest score (83.5%) for PI sites. Moreover, intra-genus DNA similarities of the V2 were considerably low (<93%). Neighbor-joining analyses showed that phylogenetic resolution in the V2–V4 region was 1.32-fold higher than that of the complete 18S rRNA. These results demonstrate that V2 has the highest taxonomic resolving power within the 18S rRNA gene of dinoflagellates, suggesting the V2 and adjacent regions (e.g., V1 to V4) may be the best for marker considerations.     

Cotranscription and processing of 23S, 4.5S and 5S rRNA in chloroplasts from Zea mays

The termini of rRNA processing intermediates and of mature rRNA species encoded by the 3' terminal region of 23S rDNA, by 4.5S rDNA, by the 5' terminal region of 5S rDNA and by the 23S/4.5S/5S intergenic regions from Zea mays chloroplast DNA were determined by using total RNA isolated from maize chloroplasts and 32P-labelled rDNA restriction fragments of these regions for nuclease S1 and primer extension mapping. Several processing sites detectable by both 3' and 5' terminally labelled probes could be identified and correlated to the secondary structure for the 23S/4.5S intergenic region. The complete 4.5S/5S intergenic region can be reverse transcribed and a common processing site for maturation of 4.5S and 5S rRNA close to the 3' end of 4.5S rRNA was detected. It is therefore concluded that 23S, 4.5S and 5S rRNA are cotranscribed.     

Structural organization of ribosomal RNAs from Novikoff hepatoma. II. Characterization of possible binding sites of 5 S rRNA and 5.8 S rRNA to 28 S rRNA

Interrelationships among 5 S, 5.8 S, and 28 S rRNA were probed by methods employed in the accompanying report (Choi, Y. C. (1985) J. Biol. Chem. 260, 12769-12772). Two complexes were isolated from 20 S ribonucleoprotein (RNP) fraction and 60 S subunit. The 20 S RNP fraction was found to contain the 3'-340 nucleotide fragment (domain VII) in association with 5 S rRNA. The 60 S subunit contained a stable complex consisting of the 5'-upstream portion (4220-4462, domain VI and VII), the 3'-downstream portion (4463-4802, domain VII) of 3'-583 nucleotides fragment, and 5.8 S rRNA. By computer analysis and hybridization, the 5'-upstream portion was found to contain the 5.8 S rRNA contact site. By affinity chromatography, the 3'-downstream portion was found to contain the 5 S rRNA association site. Furthermore, by comparison with the secondary structure of 28 S rRNA proposed by Hadjiolov et al. (Hadjiolov, A. A., Georgiev, O. I., Nosikov, V. V., and Yavachev, L. P. (1984) Nucleic Acids Res. 12, 3677-3693), it was found that domain VII is capable of binding 5.8 S rRNA and 5 S rRNA juxtaposed to each other. Accordingly, a model was proposed to indicate that a possible contact site for 5.8 S rRNA is within the region surrounding the alpha-sarcin site (4333-4350) and is a possible association site of 5 S rRNA within the 3'-downstream portion (4463-4802) of the 3'-583 nucleotide fragment (4220-4802).     

Evolution of Hypervariable Regions, V4 and V7, of Insect 18S rRNA and Their Phylogenetic Implications

We compared primary and secondary structures of V4 (helices E23-2 to E23-5) and V7 (helix 43) regions of 18S rRNAs in insects and the other three major arthropod groups (crustaceans, myriapods, and chelicerates) known so far. We found that the lengths of primary sequences and the shapes of secondary structures of these two hypervariable regions of insect 18S rRNA even at infraclass levels are phylogenetically informative and reflect major steps in insect evolution. The long sequence insertion and bifurcated shape of helices E23-2 to E23-5 in the V4 region are unique synapomorphic characters for winged insects (Pterygota). The long sequence insertion and expanded stem length of helix 43 in the V7 region are synapomorphic characters for holometabolous insects which conduct complete metamorphosis. The strongly conserved secondary structures suggest the possibility that these hypervariable regions may be related with certain important cellular functions unknown thus far. The comparison with insect fossil records revealed that the pterygote synapomorphy (V4) and the holometabolous synapomorphy (V7) were established prior to the acquisition of insect wings (flight system) and prior to the development of complete metamorphosis, respectively. These synapomorphies have been also relatively stable over at least 300 Myr and 280 Myr, respectively as well. It implies that the expansion events of the V4 and V7 regions have not occurred simultaneously but independently at different periods during the insect evolution. Then this suggests that V4 and V7 regions are not functionally correlated as recently suggested by Crease and Coulbourn.     

Development of an Analysis Pipeline Characterizing Multiple Hypervariable Regions of 16S rRNA Using Mock Samples

Objectives

There is much speculation on which hypervariable region provides the highest bacterial specificity in 16S rRNA sequencing. The optimum solution to prevent bias and to obtain a comprehensive view of complex bacterial communities would be to sequence the entire 16S rRNA gene; however, this is not possible with second generation standard library design and short-read next-generation sequencing technology.

Methods

This paper examines a new process using seven hypervariable or V regions of the 16S rRNA (six amplicons: V2, V3, V4, V6-7, V8, and V9) processed simultaneously on the Ion Torrent Personal Genome Machine (Life Technologies, Grand Island, NY). Four mock samples were amplified using the 16S Ion Metagenomics Kit^™ (Life Technologies) and their sequencing data is subjected to a novel analytical pipeline.

Results

Results are presented at family and genus level. The Kullback-Leibler divergence (D_KL), a measure of the departure of the computed from the nominal bacterial distribution in the mock samples, was used to infer which region performed best at the family and genus levels. Three different hypervariable regions, V2, V4, and V6-7, produced the lowest divergence compared to the known mock sample. The V9 region gave the highest (worst) average D_KL while the V4 gave the lowest (best) average D_KL. In addition to having a high D_KL, the V9 region in both the forward and reverse directions performed the worst finding only 17% and 53% of the known family level and 12% and 47% of the genus level bacteria, while results from the forward and reverse V4 region identified all 17 family level bacteria.

Conclusions

The results of our analysis have shown that our sequencing methods using 6 hypervariable regions of the 16S rRNA and subsequent analysis is valid. This method also allowed for the assessment of how well each of the variable regions might perform simultaneously. Our findings will provide the basis for future work intended to assess microbial abundance at different time points throughout a clinical protocol.     

Sequence and secondary structure of Drosophila melanogaster 5.8S and 2S rRNAs and of the processing site between them.

Drosophila melanogaster 5.8S and 2S rRNAs were end-labeled with 32p at either the 5' or 3' end and were sequenced. 5.8S rRNA is 123 nucleotides long and homologous to the 5' part of sequenced 5.8S molecules from other species. 2S rRNA is 30 nucleotides long and homologous to the 3' part of other 5.8S molecules. The 3' end of the 5.8S molecule is able to base-pair with the 5' end of the 2S rRNA to generate a helical region equivalent in position to the "GC-rich hairpin" found in all previously sequenced 5.8S molecules. Probing the structure of the labeled Drosophila 5.8S molecule with S1 nuclease in solution verifies its similarity to other 5.8S rRNAs. The 2S rRNA is shown to form a stable complex with both 5.8S and 26S rRNAs separately and together. 5.8S rRNA can also form either binary or ternary complexes with 2S and 26S rRNA. It is concluded that the 5.8S rRNA in Drosophila melanogaster is very similar both in sequence and structure to other 5.8 rRNAs but is split into two pieces, the 2S rRNA being the 3' part. 2S anchors the 5.8S and 26S rRNA. The order of the rRNA coding regions in the ribosomal DNA repeating unit is shown to be 18S - 5.8S - 2S - 26S. Direct sequencing of ribosomal DNA shows that the 5.8S and 2S regions are separated by a 28 nucleotide spacer which is A-T rich and is presumably removed by a specific processing event. A secondary structure model is proposed for the 26S-5.8S ternary complex and for the presumptive precursor molecule.     

Comparison of Species Richness Estimates Obtained Using Nearly Complete Fragments and Simulated Pyrosequencing-Generated Fragments in 16S rRNA Gene-Based Environmental Surveys

Pyrosequencing-based 16S rRNA gene surveys are increasingly utilized to study highly diverse bacterial communities, with special emphasis on utilizing the large number of sequences obtained (tens to hundreds of thousands) for species richness estimation. However, it is not yet clear how the number of operational taxonomic units (OTUs) and, hence, species richness estimates determined using shorter fragments at different taxonomic cutoffs correlates with the number of OTUs assigned using longer, nearly complete 16S rRNA gene fragments. We constructed a 16S rRNA clone library from an undisturbed tallgrass prairie soil (1,132 clones) and used it to compare species richness estimates obtained using eight pyrosequencing candidate fragments (99 to 361 bp in length) and the nearly full-length fragment. Fragments encompassing the V1 and V2 (V1+V2) region and the V6 region (generated using primer pairs 8F-338R and 967F-1046R) overestimated species richness; fragments encompassing the V3, V7, and V7+V8 hypervariable regions (generated using primer pairs 338F-530R, 1046F-1220R, and 1046F-1392R) underestimated species richness; and fragments encompassing the V4, V5+V6, and V6+V7 regions (generated using primer pairs 530F-805R, 805F-1046R, and 967F-1220R) provided estimates comparable to those obtained with the nearly full-length fragment. These patterns were observed regardless of the alignment method utilized or the parameter used to gauge comparative levels of species richness (number of OTUs observed, slope of scatter plots of pairwise distance values for short and nearly complete fragments, and nonparametric and parametric species richness estimates). Similar results were obtained when analyzing three other datasets derived from soil, adult Zebrafish gut, and basaltic formations in the East Pacific Rise. Regression analysis indicated that these observed discrepancies in species richness estimates within various regions could readily be explained by the proportions of hypervariable, variable, and conserved base pairs within an examined fragment.Culture-independent 16S rRNA gene surveys are now routinely utilized to examine the microbial diversity in various environmental habitats. However, in surveys of highly diverse ecosystems, the size of clone libraries typically constructed (100 to 500 clones) allows for the identification only of members of the community that are present in high abundance (2, 13, 14, 17, 24, 51). In addition to the failure to detect the rare members of the ecosystem, these relatively small datasets provide inaccurate estimates when used for computing species richness within an ecosystem. Regardless of the approach utilized to estimate species richness, the estimates obtained are highly dependent on sample size, and smaller datasets typically result in the underestimation of species richness (14, 44, 47, 55).The use of a pyrosequencing-based approach (40) in 16S gene-based diversity surveys promises to overcome both of the above-mentioned problems associated with inadequate sampling. The large number of 16S rRNA gene sequences produced (hundreds of thousands) allows access to rare members of the community (25; J. M. Tiedje, presented at the 108th General Meeting of the American Society for Microbiology, Boston, MA, 2008), as well as a relatively more accurate estimation of species richness. However, with the introduction of this new technology, it is necessary to correlate the results obtained from newer pyrosequencing-based surveys to the extensive collection of longer, capillary sequence-generated 16S rRNA gene sequences that has been deposited in public databases during the last 2 decades. Several recent studies have examined the utility of pyrosequencing fragments in providing an accurate survey of overall community structure (36) and investigated the ability of various fragments spanning the 16S rRNA gene to accurately predict the phylogenetic affiliation of pyrosequencing-generated fragments at various taxonomic cutoffs (35, 54). As such, these admirable efforts gave useful insights into the advantages and limitations of the pyrosequencing approach in 16S-based community surveys, pinpointed specific regions that provide better phylogenetic resolution than other pyrosequencing-generated regions, and provided a quantitative assessment of binning accuracy at various empirical cutoffs.However, while issues regarding correlating phylogenies of shorter and longer fragments are actively being addressed, efforts to calibrate species richness data obtained from various pyrosequencing fragments at various taxonomic cutoffs to estimates obtained using longer 16S rRNA gene fragments are still lacking. It is unclear how pairwise distances and, hence, operational taxonomic unit (OTU) assignments and species richness estimates computed using various shorter fragments spanning various regions of the 16S rRNA gene will correlate to pairwise distances computed using the nearly complete 16S rRNA gene. Elucidating such differences between shorter and nearly complete fragments, as well as between shorter fragments representing different regions in the 16S rRNA gene, is absolutely necessary for accurate meta-analysis of species richness in previously published and future datasets constructed using various sequencing approaches.Here, we constructed, sequenced, and analyzed a 16S rRNA library of 1,132 clones generated from an undisturbed tallgrass prairie soil in central Oklahoma and compared the numbers of OTUs and species richness values obtained using the full-length data sets (with and without the application of the Lane mask filter that excludes hypervariable regions from the phylogenetic analysis) (32) and fragments simulating pyrosequencing output generated by clipping where known conserved bacterial primers are encountered in the 16S rRNA gene. The lengths of the chosen simulated-pyrosequencing fragments represent amplicons that have been generated using the original GS20 pyrosequencing platform (≈100 bp) (25, 44, 48), similar to those currently being generated using the GS FLX pyrosequencing platform (≈250 bp) (1, 20, 35) or amplicons produced using the anticipated increase in the new GS XLR pyrosequencing platform (>250 bp). We show that the choice of the pyrosequenced fragment could indeed impact the number of OTUs calculated at different taxonomic cutoffs, with some fragments underestimating and others overestimating such parameters compared to the results with longer, nearly complete 16S rRNA gene fragments. We also show that even more marked differences could be encountered when comparing two pyrosequencing fragments within the same molecule. Further, we established a regression analysis that explains the nature of the observed discrepancies using the proportions of the hypervariable, variable, and conserved bases within fragments.