Conservative Fragments in Bacterial16S rRNA Genes and Primer Design for16S Ribosomal DNA Amplicons in Metagenomic Studies
Yong Wang1,2,Pei-Yuan Qian1*
1KAUST Global Partnership Program,Department of Biology,Hong Kong University of Science and Technology,Clear Water Bay,Hong Kong,China,2King Abdullah University of Science and Technology,Jeddah,Saudi Arabia
Abstract
Bacterial16S ribosomal DNA(rDNA)amplicons have been widely used in the classification of uncultured bacteria inhabiting environmental niches.Primers targeting conservative regions of the rDNAs are used to generate amplicons of variant regions that are informative in taxonomic assignment.One problem is that the percentage coverage and application scope of the primers used in previous studies are largely unknown.In this study,conservative fragments of available rDNA sequences were first mined and then used to search for candidate primers within the fragments by measuring the coverage rate defined as the percentage of bacterial sequences containing the target.Thirty predicted primers with a high coverage rate(.90%)were identified,which were basically lo
cated in the same conservative regions as known primers in previous reports,whereas30%of the known primers were associated with a coverage rate of,90%.The application scope of the primers was also examined by calculating the percentages of failed detections in bacterial phyla.Primers A519–539,E969–983,E1063–1081,U515and E517,are highly recommended because of their high coverage in almost all phyla.As expected, the three predominant phyla,Firmicutes,Gemmatimonadetes and Proteobacteria,are best covered by the predicted primers.The primers recommended in this report shall facilitate a comprehensive and reliable survey of bacterial diversity in metagenomic studies.
Citation:Wang Y,Qian P-Y(2009)Conservative Fragments in Bacterial16S rRNA Genes and Primer Design for16S Ribosomal DNA Amplicons in Metagenomic Studies.PLoS ONE4(10):e7401.doi:10.1371/journal.pone.0007401
Editor:Dawn Field,NERC Centre for Ecology and Hydrology,United Kingdom
Received June23,2009;Accepted September13,2009;Published October9,2009
Copyright:ß2009Wang,Qian.This is an open-access article distributed under the terms of the Creative Commons Attribution License,which permits unrestricted use,distribution,and reproduction i
n any medium,provided the original author and source are credited.
Funding:KAUST Global Partnership.The funders had no role in study design,data collection and analysis,decision to publish,or preparation of the manuscript.
Competing Interests:The authors have declared that no competing interests exist.
*E-mail:boqianpy@ust.hk
Introduction
In prokaryotes,the16S ribosomal RNA(rRNA)genes are essential and occur in at least one copy in a genome[1].They are also present in all mitochondrial genomes,which have lost most of their ancestral gene content in the long evolutionary history of symbiosis[2].The universality of the genes makes them an ideal target for phylogenetic studies and taxonomic classification[3]. The products of the rRNA genes can fold into a complex,stable secondary structure,consisting of stems and loops[4].The sequences of some of the loops are conservative across nearly all bacterial species because of the essential functions involved, whereas the features of the structural parts are largely variant and specific to one or more classes[5,6].Since the invention of the polymerase chain reaction
(PCR)technique[7],the variant regions,V1–V9,of the16S rRNA genes(rDNAs)have been used for species identification[8].
The appropriate primers for a PCR reaction are critical because an over-relaxed match between a primer and its target leads to PCR failure.For16S rDNAs,the primers(15–20nucleotides(nt)) are located in the conservative regions that flank a target region used for phylogenetic analysis[8].The first sets of primers were designed by using conservative regions of16S rDNA sequences from different species and were named according to their positions on Escherichia coli16S rDNA[8];this has become the protocol for subsequent primer design.For example,primer E685corresponds to eubacterial P4region[9]and primer A344targets the archaeal H339region[10].In the recent decades,more primers have been designed for bacterial studies with tools such as ARB[11],as the number of known16S rDNA sequences increases.Moreover, primers targeting a specified phylum have recently been designed [12].However,known polymorphisms also accumulate in the conservative regions,when a large number of16S rDNA sequences were generated and deposited in public databases,such as the Ribosomal Database Project(RDP)database[13]. Consequently,the originally widely used primers may not be suitable for a small group of bacteria,as noticed in recent studies [14,15,16].
The problem of primer selection is even more difficult and has attracted attention because of recent advances in metagenomic studies.Massive parallel sequencing techniques allow unprecedent-edly rapid and economical DNA sequencing.Nearly one million sequences of400nt can be generated by the Roche454FLX Titanium machine,allowing the deep sequencing of environmental bacterial genomes[17].In many experiments,amplicons of the V3 and/or V6regions have been subjected to the pyrosequencing[18]. These two variant regions in16S rDNA can provide sufficient phylogenetic information about the bacteria in samples[19,20]. The accumulation of known polymorphisms in the conserved regions means that the coverage rates of some primers are
declining[6].This might cause problems in using widely accepted primers if they fail to recover a high percentage of bacterial species in uncultured environmental samples,as expected.Using wrong primers will lead to failure to detect some bacterial species and consequently incomplete surveys in metagenomic studies. Previous studies have found that Archaea-and Eubacteria-specific primers cannot target a spectrum of classes[14,16].The known primers for the Archaea are not always suitable for amplifying the16S rRNA amplicons for Korarchaeota or Nanoarchaeota[16].Using the RDP classifier and the BLAST program,Baker et al.(2003)and Huws et al.(2007)have investigated the species specificity and coverage spectrum of the known primers.However,the results of both stud
ies are preliminary in that the coverage rates of the primers were not given.Moreover,the latter study did not consider degeneracies in these primers.In a recent work,the coverage of several known primers was surveyed using several sets of metagenomic data,and the primers with better performance were recommended for future work[21].All these studies used known primers and provided brief information of their phylum specificity.But we still do not have a ranking of the capacities of the known primers useful for environmental samples and a list of all candidate primers for bacterial16S rRNA genes.
In this study,we identified conservative fragments in16S rRNA genes from the RDP database and compiled a list of candidate primers.The predicted primers reported in this study comprise nearly a full-set of primers for prokaryotic16S rRNA genes and largely overlapped with known primers,regardless of any shift in positions.The average coverage rate of our primers is96%, markedly higher than that of other known primers.We also studied the scope of their application,which should provide guidance for metagenomic studies.
Results
Designing predicted primers using conserved fragments of16S rDNA sequences
We identified continuous conservative sites(.14nt)in the Archaea and Eubacteria separately.They were positioned on the E. coli16S rRNA gene by using a pairwise alignment and converted to
conservative fragments.There were8archaea-specific and11 eubacteria-specific conservative fragments of various lengths.Most of the conservative archaeal and eubacterial fragments were numbered according to approximate positions on li16S rRNA gene,and only four fragments lacked any counterparts: eubacterial fragments104–120,683–707,and1177–1197,and archaeal fragment1225–1242(Table1).Among the overlapping fragments,we found obvious sequence variations such as between archaeal344–367and eubacterial314–368.The differences in these fragments possibly reflect the major characteristics of the functional parts of the16S rRNA transcripts,which probably developed after the divergence of the Archaea and Eubacteria. Next,we selected candidate primers(15nt)from the fragments by checking their coverage rates.A high coverage rate indicates a high percentage of bacteria in our dataset with a target site for the candidate primer.Every candidate primer was examined with a sliding window,which was moved across the fragments(Fig.1). Although all the sites were highly conservative,the coverage rates of the candidate primers on the same fragment varied markedly and might be distributed across a larger range than that shown in Figure 1.The candidate primers containing degenerate sites clearly corres
ponded to low coverage rates(Fig.1),suggesting that introduction of the degeneracies could not ensure complete matches between the primers and their targets,and that the degeneracies by themselves pointed to the positions of weak sites in the candidate primers as well as in the conservative fragments. After we filtered out the candidate primers with a coverage rates below90%,the remaining overlapping primers were merged again and new coverage rates were measured for them(Table2). Thirty candidate primers(13for the Archaea and17for the Eubacteria)were identified and are of potential use in designing forward and reverse primers.Notably,eubacterial conservative fragment104–120did not contain candidate primers that met the selection criteria.Some primers for the Archaea and Eubacteria were not only numbered with the li rDNA positions but were also highly homologous in their pattern.Therefore,they were defined as predicted universal primers:U515–532,U785–800,U909–928,and U1052–1071(Table2).
Coverage rates of predicted and known primers
To evaluate the accuracy of our prediction,the predicted primers were compared with29known primers including13 Archaea-specific,9Eubacteria-specific,and7universal primers (Table3).After cleaning the overlapping primers,we found that our predicted primers contained a novel primer,A884–898,which has not been reported previously.Although nearly all the predicted and know
n primers were located in the same regions, Table1.The conservative fragments in archaeal and eubacterial16S rDNAs.
Bacteria Position Conservative fragment
E104–120GGCGVACGGGTGAGTAA
E314–368CAYTGGRACTGAGACACGGYCCARACTCCTACGGG
AGGCAGCAGTRRGGAATHTT
A344–367AYGGGGYGCAGCAGGCGRGAAARC
E505–539GGCTAACTHCGTGCCAGCAGCCGCGGTAATACGDA A506–547GGYAAGDCYGGTGYCAGCCGCCGCGGTAAHACCRC
CDRTGGCGAA
E683–707GTGTAGRGGTGAAATKCGYAGAKAT
E764–806CGAAAGYGTGGGKAKCRCAGGATTAGATACCCTGGT
AGTCC
A779–806CRAACSGGATTAGATACCCSGGTAGTCC
E879–893CCRCCTGGGGAGTAC
A882–936CCTGGGRAGTACGKHCGCAAGDRTGAAACTTAAAGG
AATTGGCGGGGGAGCAC
E909–940ACTCAAAKGAATTGACGGGGRCCCGCACAAGC
A947–973GCSTGCGGYTYAATTGGABTCAACGCC
E949–964ATGTGGTTTAATTCGA
E969–985ACGCGARGAACCTTACC
A1043–1073GAGAGGWGGTGCATGGCCGYCGYCAGYTCGT
E1048–1114GTGSTGCATGGYTGTCGTCAGCTCGTGYCGTGAGRT
GTYGGGTTAAGTCCCRYAACGAGCGCAACCC
A1094–1111GTCAGRYAACGARCGAGA
E1177–1197GGAAGGYGGGGAYGACGTCAA
A1225–1242ACACGCGSGCTRCAAWGG
The conservative fragments were generated from multiple alignments among 6,624Archaea(A)and275,057Eubacteria(E)in RDP database.The positions are determined according to relative positions li16S rDNA genome.Y:C or T; R:A or G;W:A or T;K:G or T;M:C or A;S:C or G;V:not T;H:not G;B:not A;D: not C.
doi:10.1371/journal.pone.0007401.t001
some of the known primers were probably problematic because of the lack of sufficient degeneracies and the low degree of conservation at some sites in the primers.Therefore,the coverage rates of these primers were compared with those of the predicted primers.
For the predicted primers,the average coverage rates of the archaeal and eubacterial primers were 9
6%and 96.2%,respectively.The average coverage rate of the predicted universal primers was 96%.The values for the known archaeal,eubacterial,and universal primers were 85%,77.4%,and 84.3%,respectively.Overall,the coverage rates of all the predicted primers were above 90%,whereas the coverage rates of the 11known primers (30.6%of all known primers)were lower than 90%(Table 3).The coverage rates of the predicted primers were significantly higher than those of the known primers (Spearman test;P ,0.00001).Our results also cast doubt on the validity of some known universal primers,as three out of the seven showed poor coverage in Archaea or Eubacteria:the coverage rate of U779in Archaea was only 5%.The remaining primers,U341F,U519F,U789F,and U1053F,are highly recommended for their high coverage rates in all bacteria.U341F was not included among our predicted universal primers,as polymorphisms and dissimilarities in this region would introduce too many degeneracies when both the Archaea and Eubacteria are considered.
Phylum specificity of predicted and known primers
As described above,we generated a list of predicted and known primers with a high coverage rate for both the Archaea and Eubacteria.However,it was a challenge to amplify the 16S rRNA sequences of all the bacteria in environmental samples.Generally,the dominant and well-characterized bacterial phyla could be detected easily according to the principles of primer design.The problem was how to i
dentify the minority bacterial phyla;occasionally,a whole phylum was missed.In the RDP database,the numbers of bacteria from different phyla differed substantially,and the failure to detect a small phylum might simply result in less than 1%loss of coverage rate.Therefore,it was necessary to assess the phylum specificity of our predicted primers,as a supplemen-tary evaluation other than coverage rate.
We first displayed coverage spectrum of 13Archaea-specific primers.In the Crenarchaeota and Euryarchaeota,the percentage of failed detections was below 10%for the primers,indicating that
the coverage of these Archaea was rather stable (Fig.2).However,the coverage of Korarchaeota and Nanoarchaeota varied remarkably in a range of 0%–100%.Primers A785–800,A899–913,and A905–936were not suitable for Korarchaeota,as indicated by their 100%of failure rates.The highly variant coverage rates of these primers in Nanoarchaeota were not surprising because there were only three representatives of this taxon (.1200nt)in the database.In light of the spectrum found in this test,A519–539could provide the best coverage of all archaeal phyla.Although some primers failed to cover Korarchaeota completely,they provided location information for the design of Korarchaeota-specific primers.Among the 12known Archaea-specific and universal primers examined,U906F and U1053F performed better than the others (Fig.S1).And the result confirms that the Archaea-specific p
rimers do not have high coverage rates in Korarchaeota and/or Nanoarchaeota.
The same test was performed with 17predicted Eubacteria-specific primers on 25eubacterial phyla.Most of the primers showed a weakness in finding targets in a small spectrum of eubacteria phyla (Fig.3).E969–983was the best primers because it displayed the lowest average rate (1%)of failed detections,followed by E1063–1081with an average failure percentage of 4.6%.The highest average failure percentage (32.8%)was observed for E1177–1193.Surprisingly,the difference between E783–797and E785–806was 9%,although the major part of E783–797lies within E785–806except for the first two nucleotides.Therefore,different primers show clear phylum specificity,and fine adjustment of the primer target could achieve better coverage.This was verified by variant rates of failed detections observed for the same phylum dataset using different primers.We thus measured the average of the rates for individual phyla to determine the bacteria phyla that were most easily detected,and the results showed that Firmicutes,Gemmatimona-detes and Proteobacteria were the phyla with the highest rates of match to the primers.In ascending order,the average percentages of failed detections were 1.47%,1.54%,and 1.9%,respectively,for three phyla.In contrast,Planctomycetes and TM7were associated with the highest average rates of failed detections (40%and 31.8%,respectively)with large standard deviation (42%and 43%,respectively),indicating that
the coverage of the primers in these two phyla is not stable.These results could be foreseen because the overwhelming number of representatives from Firmicutes and Proteobacteria (Fig.3)caused a bias in primer design.The polymorphisms in the minority phyla were largely ignored,leading to insufficient degeneracies in the primers.
The performance of known primers was also assessed.Of the top three phyla,Firmicutes and Proteobacteria were most easily detected with the known primers (Fig.S2).A minor phylum,Deferribacteres,was the phylum best covered by the known primers,with the lowest average rate (0.45%)of failed detections,followed by Deinococcus and Acidobacteria.This finding suggests that the 16S rDNA sequences collected previously from the RDP and GenBank were less biased in collection of certain phyla.However,the usefulness of the known primers for Verrucomicrobia was limited,and half the known primers showed .50%failed detections,perhaps reflecting the lack of representatives of this phylum when the primers were designed.Among the known primers,U515and E517are highly recommended in light of their wide spectrum of perfect coverage.E1099F also had an overall high coverage rate,although it failed to detect most of Planctomycetes (Fig.S2).
Assessment of Cyanobacteria-specific primers
The above results are useful for studies that focus on a specific phylum.By designing primers for a phylum of interest,only
the
Figure 1.Coverage rates of candidate primers within a conservative fragment.The coverage rates (%)of eight candidate primers within the conservative fragment 59-CAAGDMTGAAACTTAAAG-GAAT-39were determined using all archaeal 16S rDNA sequences (.1,200nt)as the reference dataset.The coverage rate is the percentage of the rDNA sequences that have a target fragment matching a given candidate primer.One mismatch is allowed in the match.doi:10.1371/journal.pone.0007401.g001
16S rDNA of the desired bacterial species is amplified for subsequent studies.We examined three Cyanobacteria-specific primers,CYA106F,CYA359F,and CYA781R[12].The coverage rate for all Eubacteria was31.7%for primer CYA106F, 7.4%for CYA359F,and2.3%for CYA781R.We classified the identified bacteria species and found that CYA106F was not specific for the Cyanobacteria.CYA106F,CYA359F and CYA781R could be used to identify80%,98%,and92%of the 4655Cyanobacterial sequences in our collection,independently. Moreover,CYA106F and CYA359F had many targets in Firmicutes:75%of94475Firmicutes sequences were targets of CYA106F and9%were targets of CYA359F.However, CYA781R had an extremely low coverage rate(0.001%)in Firmicutes.An appropriate combination of forward and reverse primers could avoid generating a mixture of amplicons from Firmicutes.These primers designed,based on previous database collection,are still useful today.
firmicutes
Distance of the primers to variant regions of16S rRNA genes
We put the predicted and known primers onto the same map to compare their relative distances to the16S rRNA variant regions. Three of these regions(V3,V5,and V6)li are shown in Figure4.The primers were concentrated in six narrow regions, spanning the three variant regions.For those primers with high coverage rates,the predicted and known primers overlapped
Table2.The coverage rate of predicted primers.
Bacteria Position Sequence Average rate Coverage rate
E321–336ACTGAGACACGGYCCA95.7%96.1%
E329–343ACGGYCCARACTCCT95.3%96.0%
E338–358ACTCCTACGGGAGGCAGCAGT97.3%96.3%
A346–361GGGGYGCAGCAGGCG94.2%94.3%
E350–364GGCAGCAGTRRGGAA95.1%95.5%
E505–524GGCTAACTHC GTGCCAGCAG95.3%95.1%
A514–528GGTGYCAGCCGCCGC97.3%98.5%
E515–532GTGCCAGCAGCCGCGGTA92.6%91.0%
U515–532GTGYCAGCMGCCGCGGTA-96.9%/96.9%
A519–539CAGCCGCCGCGGTAAHACCRC96.7%97.1%
E683–700GTGTAGMGGTGAAATKCG92.6%90.5%
E783–797CAGGATTAGATACCC97.9%97.9%
E785–806GGATTAGATACCCTGGTAGTCC95.9%94.6%
A785–800GGATTAGATACCCSGG98.1%98.4%
U785–800GGATTAGATACCCBGG-98.4%/97.1%
A884–898TGGGRAGTACGKHCG97.1%97.1%
A899–913CAAGDMTGAAACTTA97.6%97.6%
A905–920TGAAACTTAAAGGAA98.3%98.3%
A921–936TTGGCGGGGGAGCAC98%97%
E909–926ACTCAAAKGAATTGACGG98.5%97.9%
U909–928ACTYAAAKGAATTGRCGGGG-93.2%/92.1%
E919–939ATTGACGGGGRCCCGCACAAG96.3%96.1%
A947–964GCSTGCGGYTYAATTGGA91.6%90.5%
E949–964ATGTGGTTTAATTCGA93.5%93.5%
A958–973AATTGGABTCAACGCC90.6%93.5%
E969–984ACGCGARGAACCTTAC97.4%97.1%
A1045–1059GAGGWGGTGCATGGC95.7%97.4%
A1052–1071TGCATGGCCGYCGYCAGYTC96.6%95.1%
E1052–1072TGCATGGYTGTCGTCAGCTCG97.1%99.0%
U1052–1071TGCATGGYYGYCGYCAGYTC-95.1%/98.8%
E1063–1081CGTCAGCTCGTGYCGTGAG99.2%99.3%
E1096–1114CCCRYAACGAGCGCAACCC96.8%95.6%
E1177–1193GGAAGGYGGGGAYGACG98.2%98.2%
A1226–1242CACGCGSGCTRCAAWGG93.8%93.5%
The primers in this table were fragments within the conservative fragments in Table1.If coverage rates of neighboring candidate primers were all above95%,they were merged.If no predicted primers in a fragment,the cutoff rate decreased to90%.The average coverage rate was thus calculated for the neighboring primers.Universal primers(U)were obtained by referring to archaeal(A)and eubacterial(E)predicted primers at the same positions li genome.The coverage rate was measured for the merged primer.For the universal primers,both were provided(A/E).Abbreviated names for bacteria and the positions were listed as those in Table1.
doi:10.1371/journal.pone.0007401.t002
strongly.The‘‘hot’’regions where the primers bind were:321–364,505–539,783–806,884–939,947–984,and1045–1081.The sizes of the amplicons from the V3region and V5–V6region were about180nt and270nt,respectively.Both could be completely sequenced with the454FLX platform.
Discussion
In this study,we predicted all the potential primers for bacterial 16S rDNA amplicon.Their positions are largely consistent with those of known primers,but the average coverage rate is higher than that of known primers.Some of the known primers used in previous studies have been found to be unsuitable for the amplification of16S rDNA fragments from uncultured samples. We also confirmed that most of the primers in hand are highly specific for a spectrum of bacterial species,and definitely cannot be used to amplify all bacteria in uncultured samples.Our result should be helpful in the design of primer for species-specific amplicons,when research interests are restricted to a certain species.As well as from16S rDNAs,the protocol provided in this study can also be applied to the detection of genetic variations in other essential genes in bacterial communities[22],all of which are important in metagenomic studies.
With recent advances in massively parallel sequencing tech-niques,the bacteria world in untouched ecological niches can be explored to survey its biodiversity and niche-specific metabolic pathways.The use of16S rDNA amplicon sequencing allows us to estimate the abundance and diversity of these bacteria,whereas the exhaustive detection of rare species is difficult to achieve.In recent metagenomics studies,the number of phylotypes in the same number of16S rDNA sequences
varied substantially for samples from different environments and geographical sites [23,24,25].Despite this,we cannot exclude the possibility that amplification efficacy of the different16S rDNA primers used in these studies led to the underestimation of bacterial richness. Primer usage is undoubtedly one of the most critical limiting factors affecting16S rDNA analysis[18].Although V3and V6are the most popular regions examined in recent metagenomic studies, the primers used differ[18].This may lead to different capture depths of the bacteria in environmental samples,attributable to varying amplification efficiencies and coverage rates of the primers.
In an attempt to compare the results of different studies, research groups have tended to use the same primers.In several studies of microbial communities in the human gut and seawater, primers967F and1046R have been used to amplify the V6region to avoid the bias caused by primer selection[19,23,25,26].Our study provides a reliable set of candidate primers for researchers to achieve an approximately full coverage of bacterial16S rDNAs and comparable results among different studies.
The recently updated Roche454Titanium platform yields about one million reads per run,with reads up to about400nt [17].The increase in read lengths allows us to analyze longer amplicons from the variant regions of16S rDNAs.However,we are still far from being able to sequence amplicons spanni
ng both V3and V6(Figure4).Among all the primers discussed,E683–700 is important because it can be used as a reverse primer to generate amplicons of,340nt from the V3region or a forward primer designed to generate,400nt amplicons spanning the V5and V6 regions.The closest primers to it are at least100nt away,and it is the only primer that allows the full utilization of the sequencing capacity of the new454platform.However,a potential problem is its relatively low coverage rate of91%for the Eubacteria.Notably, no predicted or known primer has been found for the Archaea in this region.Therefore,the amplicons obtained with E683–700 from an uncultured environmental sample will specifically belong to Eubacteria.
One limitation of this study is that the primer design depended on the data in the RDP database.The bacteria in rare biospheres can never be identified if the employed primers are not applicable to them.New primers cannot be invented in case of lack of representatives of those bacteria in the RDP database.Although numerous16S rRNA genes had been collected in databases,the real bacterial world in environmental samples will still be invisible under the current protocol for16S rDNA detection.In this study, three nearly full-length Nanoarchaeota were used as references for primer design.The unstable coverage rate observed is an obstacle to evaluating the efficiency of the predicted and known primers at all sub-levels.Fortunately,ongoing and completed metagenomic proje
cts may help us by providing nearly full-length16S rRNA genes and by increasing the representatives of the rRNA genes particularly from rare biospheres.As the number of16S rRNA
Table3.Coverage rate of known primers.
Primer[Ref]Primer sequence59-39Position Coverage rate
A333F[16]TCCAGGCCCTACGGG333–34857.4%
E334F[14]CCAGACTCCTACGGGAGGCAGC334–35674.2%
A340F[16]CCCTACGGGGYGCASCAG340–35888.3%
U341F[16]CCTACGGGRSGCAGCAG341–35891.1%/96.9% E343F[20]TACGGRAGGCAGCAG343–35798.7%
A344F(A)[15]GGGGYGCASCAGGSG344–36090.8%
A344F(B)[15]ACGGGGCGCAGCAGGCGCGA344–36374.2%
U515F[16]GTGCCAGCMGCCGCGGTAA515–53463.3%/99.0% E517F[20]GCCAGCAGCCGCGGT
AA517–53399.1%
A519R[15]GGTDTTACCGCGGCKGCTG519–53798.0%
A519F[15]CAGCMGCCGCGGTAA519–53398.6%
U519F[16]CAGCMGCCGCGGTAATWC519–53796.7%/98.5% A685R[27]TTACGGGATTTCACTCCTAC685–70419.5%
E685R[28]ATCTACGCATTTCACCGCTAC685–70579.8%
U779F[16]GCTAASSGGATTAGATACCC779–79989.9%/5.0%
E786F[14]GATTAGATACCCTGGTAG786–80395.2%
U789F[16]TAGATACCCSSGTAGTCC789–80797.7%/94.8% A806R[15]GGACTACVSGGGTATCTAAT787–80696.4%
E806R[14]GGACTACCAGGGTATCTAAT787–80695.1%
U906F[16]GAAACTTAAAKGAATTG906–92398.3%/54.2% A906R[15]CCCGCCAATTCCTTTAAGTT
TC906–92797.3%
E917F[20]GAATTGACGGGRCCC917–93292.5%
A915R[15]GTGCTCCCCCGCCAATTCCT915–93497.1%
E939R[14]CTTGTGCGGGCCCCCGTCAATTC917–93993.1%
A976R[16]CCGGCGTTGAMTCCAATT957–97692.7%
A1040F[16]GAGAGGWGGTGCATGGCC1040–105895.2%
U1053F[16]GCATGGCYGYCGTCAG1053–106897.2%/97.2% A1098F[16]GGCAACGAGCGMGACCC1098–111567.0%
E1099F[20]GYAACGAGCGCAACCC1099–111497.0%
The source of the known primers is labeled.The degenerated sites are defined in Table1.The names of Archaea-specific,Eubacteria-specific,and universal primers are started with‘A’,‘E’and‘U’,respectively.For the universal primers, the coverage rates for both the Archaea and Eubacteria are given(A/E). doi:10.1371/journal.pone.0007401.t003
豫公网安备41160202000603
站长QQ:729038198
关于我们
投诉建议