Efficient screening for expressed sequence tag polymorphisms (ESTPs) byDNA pool sequencing and denaturing gradient gel electrophoresis (DGGE)in spruces

Betty Pelgas1, Nathalie Isabel1,2 and Jean Bousquet1,*1Chaire de recherche du Canada en génomique forestière et environnementale, Centre de recherche enbiologie forestière, Pavillon Charles-Eugène-Marchand, Université Laval, Sainte-Foy, Québec Canada G1K7P4; 2Service Canadien des Forêts, Ressources naturelles Canada, Centre de foresterie des Laurentides, 1055du PEPS, C.P. 3800, Sainte-Foy, Québec, Canada G1V 4C7; *Author for correspondence (e-mail:bousquet@rsvs.ulaval.ca; tel.: 418-656-3493; fax: 418-656-7493)

Received 19 May 2003; accepted in revised form 3 November 2003.

Key words: Codominant markers, Conifers, Consensus mapping, Insertion-deletion, Picea, Single nucleotidepolymorphism

Abstract

There is an urgent need to accelerate the development of informative codominant markers of coding regions suchas ESTPs �expressed sequence tag polymorphisms� to estimate map synteny within and among taxa. A set ofprimer pairs for 207 ESTs or cDNAs from Picea and Pinus taxa was screened on three distantly-related taxa inthe genus Picea, P. mariana �Mill.� B.S.P., P. glauca �Moench� Voss and P. abies �L.� Karst. Of these, 118 �57%�resulted in positive amplification of single-locus gene products in the first two species. To detect polymorphism,these 118 markers were further screened on a panel of 10 pedigree parents for each of P. mariana and P. glauca,either by agarose gel electrophoresis �AGE� or by parallel denaturing gradient gel electrophoresis �DGGE� withstandard conditions of 15-45% urea-formamide. Of these, 87 and 74 were found polymorphic in P. mariana andP. glauca, respectively, and 65 were polymorphic in both species. DNA pool sequencing has been explored as apossible strategy to increase economically the detection throughput of SNPs and small indels, and to characterizethe types of DNA polymorphism detected by DGGE. Different DNA samples of known sequences were pooledin different ratio mixtures before and after PCR amplifications to determine their minimum relative abundancefor detection of DNA polymorphisms by sequencing. For detection of a polymorphism in the DNA pools, theminimum level of relative abundance was 10%. Pooling DNA samples before or after PCR amplification had noeffect on the detection of polymorphism by sequencing. For each species panel, the DNAs were pooled and thenamplified and sequenced for the 118 primer pairs. With this strategy, the number of ESTPs increased to 107 in P.mariana and 106 in P. glauca, and the number of ESTPs shared by both species increased to 99. About half ofthe ESTP markers displayed both SNP and indel polymorphisms while the other half displayed only SNPs. Mostof the additional ESTPs were amenable to detection by DGGE or CAPS �Cleaved Amplified Polymorphic Se-quence� for mapping purposes.

Introduction

Synteny between genetic linkage maps is increasinglybeing investigated for the study of genome evolution

within and between taxa �for a review see Paterson etal. 2000�. To anchor linkage maps, informative multi-allelic homologous markers are ideally sought. ESTPs�expressed sequence tag polymorphisms� are DNA

© 2004 Kluwer Academic Publishers. Printed in the Netherlands.263Molecular Breeding 13: 263–279, 2004.

markers of coding regions, that might be useful to lo-cate potential candidate genes. They are often foundin transcribed but untranslated regions, which are un-der less selective constraints and thus, offer more nu-merous opportunities for substitutions �single nucle-otide polymorphisms, SNPs� and insertions/deletions�indels� �Perry and Bousquet 1998a; Perry et al. 1999;Picoult-Newberg et al. 1999; Grivet et al. 2003�. ES-TPs are usually codominant �Harry et al. 1998; Perryand Bousquet 1998a�, thus they should be more in-formative than dominant markers to anchor linkagemaps �e.g., Plomion et al. 1999; Brown et al. 2001;Gosselin et al. 2002�. Marker homology betweenpedigrees and species can be easily ascertained, forcross-genome comparative mapping. In addition,when primers are designed for conserved regions,ESTPs show a high potential of transferability amongcongeneric species in the conifers �Tsumura et al.1997; Perry and Bousquet 1998b; Temesgen et al.2001; Fournier et al. 2002�.

One of the main challenges with the developmentof ESTP markers in large numbers for use in map-ping projects is to accelerate marker discovery andkeep the detection of DNA polymorphisms simpleand affordable, whether SNPs or indels. Severalmethods are available for such a purpose, includingpolyacrylamide or agarose gel electrophoresis�PAGE-AGE� of PCR products with or withoutdigestion by restriction endonucleases, single strandconformation polymorphism �SSCP; Orita et al.1989�, denaturing gradient gel electrophoresis�DGGE; Myers et al. 1987�, cleaved amplified poly-morphic sequence �CAPS; Konieczny and Ausubel1993�, denaturing high-performance liquid chromato-graphy �DHPLC; Oefner et al. 1994�, and DNA se-quencing. Although SSCP is a highly sensitivemethod to detect mutations within PCR products�Fournier et al. 2002�, DGGE and DHPLC appearedto be more sensitive on many occasions �Choy et al.1999; Numakura et al. 2002�. DGGE is sensitive toSNPs, it is less costly than DHPLC �Choy et al. 1999�and conformational polymorphisms can be revealedwithin a few hours, contrary to SSCP �Fournier et al.2002�.

While DGGE is more cost effective than DNA se-quencing to genotype progeny in large-scale mappingprojects, the scaling of hundreds of markers forDGGE is labor intensive because it is dependent onoptimizing primers and separation conditions for eachmarker �Miller et al. 1999; Temesgen et al. 2001�,without knowing a priori the presence and the type

of DNA polymorphisms. At the other end of the fi-nancial spectrum, DNA sequencing of single geno-types is fully informative but still costly for mappingpurposes. However, one could consider sequencingDNA pools encompassing several or many distinctgenotypes in order to check for marker polymorphismbefore delineating the best DGGE conditions for agiven marker. While common polymorphisms arelikely to be detected beyond background noise withsuch a preparative step to DGGE, the intent is not todetect all polymorphisms within a nucleotide se-quence but to render the marker informative by flag-ging some of the most common polymorphisms. Inno case do we propose to extend such a DNA pool-ing strategy for estimating allele frequencies in asample. In line with our hypothesis, the pooling ofgenomic samples from different individuals prior tosequencing has been considered as a useful methodto efficiently screen for multiple alleles derived fromSNPs �Kwok et al. 1994; Shubitowski et al. 2001�.

The aim of this study was to develop a new cohortof codominant ESTP markers for cross-genome com-parative mapping in the genus Picea, and to test amodified approach for the screening of polymor-phisms in gene coding regions, using a DNA pool se-quencing strategy prior to detection by parallelDGGE. With this combined approach, all pedigreeparents of a same species were regrouped into a com-mon DNA pool, then sequenced to detect polymor-phisms. This study demonstrates an increased sim-plicity to generate rapidly a large number of commonanchor markers for consensus genome mapping be-tween two distantly-related congeneric taxa.

Materials and methods

PCR primers

A total of 207 primer pairs previously developed fromESTs or cDNAs from black spruce �Picea mariana��Perry and Bousquet 1998a�, Norway spruce �Piceaabies� �Schubert et al. 2001; Plomion personnal com-munication; www.pierroton.inra.fr/genetics/pinus/primers.html�, loblolly pine �Pinus taeda� �Harry etal. 1998; Plomion et al. 1999; Brown et al. 2001; Te-mesgen et al. 2001; www.pierroton.inra.fr/genetics/pinus/primers.html�, maritime pine �Pinus pinaster��www.pierroton.inra.fr/genetics/pinus/primers.html�,Scots pine �Pinus sylvestris� �Plomion et al. 1999�,japanese black pine �Pinus thunbergii� �www.pierro-

264

ton.inra.fr/genetics/pinus/primers.html� and jack pine�Pinus banksiana� �www.pierroton.inra.fr/genetics/pi-nus/primers.html� were screened for amplificationand for polymorphism on a panel of 10 diploid pedi-gree parents �20 alleles� for each of black spruce andwhite spruce �Picea glauca�. They were also screenedfor positive amplification and absence of multiple-banding pattern with two individuals of Norwayspruce.

DNA extraction and amplification

Genomic DNA was extracted from each individualwith the DNeasy® Plant Mini Kit �Qiagen, Missis-sauga, Ontario�. DNA concentrations were assessedby GeneSpec spectrophotometer �MiraiBio, Alameda,California� before PCR amplification. PCR reactionswere based on the protocol of Perry and Bousquet�1998a�, with some modifications. DNA amplifica-tions were performed in volumes of 15�l containing1x of reaction buffer, 2mM of MgCl2, 200 �M ofeach dNTP, 120 �M of each primer and 1 unit Plati-num® Taq DNA polymerase �Invitrogen, Carlsbad,California�. To reduce the occurrence of multiple-banding pattern, three PCR programs were used de-pending on the primer pairs tested: �1� 4 min at 95 °Cfor initial denaturation, 40 cycles of 30 s at 95 °C, 30s at 55 °C and 1 min at 72 °C, followed by 10 min at72 °C; �2� 4 min at 94 °C, then 35 cycles of 45 s at94 °C, 45 s at 60 °C and 1 min 30 s at 72 °C, fol-lowed by 10 min at 72 °C; and �3� 5 min at 94 °C,then 14 cycles of 45 s at 94 °C, 45 s at 65 °C �tem-perature decrease of 1 °C per two cycles until 58 °C�and 1 min 30 s at 72 °C, followed by 30 cycles at58 °C annealing temperature, then followed by 10min at 72 °C. To further optimize DNA amplificationfor some markers, the annealing temperatures of thefirst and second programs were modified �AppendixA�. DNA samples were amplified on a PTC-225 ther-mal cycler �MJ Research, Waltham, Massachusetts�.

General strategy for screening EST polymorphisms

For each individual and each primer pair, amplifica-tion products were visualized on 2% agarose gelstained with EtBr to verify amplification and optimizePCR conditions. The presence of polymorphisms wasalso checked on 2% agarose gel and if no detectablepolymorphisms were observed, by DGGE, using asingle standard parallel gradient gel of 15-45% urea-formamide �Temesgen et al. 2001; 100% is defined as

7M urea with 40% �v/v� formamide� with 10% poly-acrylamide �37.5:1; acrylamide:bisacrylamide�. De-naturing gels were subjected to electrophoresis at 175V for 4 hrs, stained with EtBr and visualized on anImager 2000 �Appligene Instrumentation, Illkirch,France�.

For each species panel, DNA samples of the 10parents were also pooled in equal amounts �4 ngDNA/parent� before PCR amplification, then ampli-fied for each candidate primer pair that lead to posi-tive amplification of single-locus product �total of 118primer pairs, see Results� and sequenced on the twoDNA strands to identify putative SNPs or small in-dels �see below for sensitivity analysis�. Such proce-dure enabled: 1- the discovery of additional ESTPmarkers not revealed by standard AGE or DGGE �seeabove�; 2- to characterize at the DNA sequence levelthe types of polymorphism revealed or not revealedby standard DGGE; and 3- for each ESTP detectedby DNA pool sequencing, optimize DGGE conditionswhenever necessary to visualize polymorphisms bytesting additional denaturing parallel gradients, from15-50% to 40-80%. When optimized DGGE couldnot reveal polymorphisms detected by sequencingDNA pools, digestion of PCR products with restric-tion endonucleases was conducted in order to detectCAPS whenever the possibility was indicated by se-quencing information. For each assay, 15 �l of PCRproducts were digested overnight at 37 °C or 65 °Cin a total reaction volume of 24 �l containing 2.4 �lof enzyme buffer �10X�, 6.5 �l H2O and 0.12 unitsof appropriate restriction enzyme. The restrictionproducts were separated on non-denaturing polyacry-lamide gel �10%�, then stained with EtBr.

Testing the sensitivity of DNA pool sequencing

The sensitivity of DNA pool sequencing was deter-mined using different concentrations of two knownalleles/haplotypes into a pool. Primers for the genesSb06 �acyl-CoA oxidase� and Sb12 �RNA bindingprotein� �Perry and Bousquet 1998a� were used forthis purpose as polymorphism was detected usingDGGE with standard parallel gradient of 15-45%urea-formamide. PCR was conducted as describedabove. For each locus, alleles/haplotypes a and bwere amplified and sequenced a priori from needleDNA samples of two selected homozygous individu-als of P. glauca �individual 1: aa; individual 2 : bb�.After identification of SNPs between both individu-als, DNA samples from both alleles/haplotypes were

265

mixed in various ratios to obtain the different DNApools, before or after the amplification step �see be-low�. Final volumes of the PCR reactions were 60�l,including 40�l of master mix and 40ng of total DNAat a concentration of 2ng/�l for each DNA pool.

Experiment 1To verify any competition effect between alleles/hap-lotypes during the amplification process of pooledsamples, the two DNA samples were: A� pooled fol-lowing various ratios �0% allele a and 100% allele b,5-95%, 25-75%, and 50-50%� before the amplifica-tion step; B� amplified individually and then pooledafter amplification but before the purification stepprior to sequencing, and; C� pooled after the purifi-cation step. Purification was done with Microcon-PCR filter units �Millipore, Bedford, Massachusetts�.Both DNA strands were sequenced using the Big-Dye™ Terminator v3.0 Cycle Sequencing Ready Re-action Kit �Applied Biosystems, Foster City, Califor-nia� and an ABI Prism® 3700 Genetic Analyser�Applied Biosystems, Foster City, California�. Eachsequencing reaction was repeated three times.

Experiment 2To determine the sensitivity of DNA pool sequencing,the following pools were constructed from genomicDNA samples before PCR amplification: 100% allelea and 0% allele b, 95-5%, 90-10%, 85-15%, 80-20%,75-25%, 50-50%, 25-75%, 20-80%, 15-85%, 10-90%, 5-95%, 0-100%, respectively. The various poolswere amplified, and purification and sequencing fol-lowed methods described above. Both DNA strandswere sequenced and each sequencing reaction wasrepeated three times to verify consistency.

Analysis of sequencing chromatograms

The sequencing chromatograms of the various DNApools were compared with the chromatograms pro-duced from homozygotes used to construct the pools.Polymorphic sites were identified by visual inspectionof the chromatograms, where superimposed peakshigher than the baseline level were taken as evidenceof potential SNPs. The analysis of the second DNAstrand was done independently and consistencyacross the repeats for each DNA strand and betweenDNA strands was verified a posteriori. Indel poly-morphisms were detected by the presence of a con-tinuous superimposed sequence. Both the beginningand the end of the indel could be deduced from theforward and reverse DNA strands, respectively. Eachanalysis was duplicated with a second scoringobserver.

Results

Detection of polymorphisms by AGE and DGGE

Out of 207 primer pairs tested, 108 �52%� were origi-nally developed from ESTs or cDNAs of Picea and99 �48%� from Pinus. Of these 207 primer pairs, 118�57%� resulted in positive single-locus amplificationswithout multiple-banding pattern for both Piceamariana and P. glauca, of which 79 �67%� and 39�33%� were originally developed from Picea and Pi-nus, respectively �Table 1�. As expected, the successrate was much higher for primers derived from Picea�73%� than for those derived from Pinus �39%�. The207 primer pairs were also tested on P. abies, with104 �50%� primer pairs resulting in positive single-

Table 1. Number of positive PCR amplifications without multiple-banding pattern from 207 primer pairs developed for gene coding regionsfrom Picea and Pinus taxa.

Group Number of positive amplifications without multiple-banding patternout of 207 primer pairs

Out of 108 primerpairs from PiceaESTs or cDNAs

Out of 99 primerpairs from PinusESTs or cDNAs

Total

P. mariana 79 39 118P. glauca 79 39 118In common between P. mariana and P. glauca 79 39 118P. abies 71 33 104In common between P. mariana, P. glauca and P. abies 71 33 104

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locus amplifications without multiple-banding pattern�Table 1�.

For each of P. mariana and P. glauca, respectively,87 �74%� and 74 �63%� of the 118 primer pairs re-sulted in single-locus polymorphisms �Table 2�, de-tected either by AGE or by standard DGGE �15-45%urea-formamide gradient�, which was used whenAGE failed to detect fragment length polymorphism.A total of 65 primer pairs �55%� revealed single-lo-cus polymorphisms in both species, either by usingAGE or standard DGGE when AGE failed �Table 2�.

When DGGE revealed polymorphisms, it was notalways fully informative. For instance, when analys-ing the progeny of one P. glauca cross for the markerSb12, four genotypes involving three different allelescould be deduced by DGGE, whereas four alleles �in-stead of three� were clearly detected by sequencingindividually parents and progenies �Figure 1�. Be-cause two of the four alleles could not be distin-guished from each other by DGGE �b vs d�, theseparation pattern obtained by DGGE was not fullyinformative: while being truly heterozygous some ofthe progeny were detected as homozygous, suggest-ing that parents had one allele in common. However,sequencing revealed that parental genotypes werefully informative, harboring four different alleles.Similar results were documented with at least oneother marker, Sb06 �data not shown�.

Testing the sensitivity of DNA pool sequencing

As a prerequisite to testing the sensitivity of DNApool sequencing, the markers Sb12 and Sb06 from P.glauca were fully characterized at the sequence level.For Sb12, four polymorphic sites for SNPs were ob-served between two homozygous individuals, at po-sitions 209 bp �T/A�, 392 bp �G/A�, 470 bp �G/A�,and 491 bp �C/T� of the sequence, resulting in twoalleles/haplotypes: TGGC and AAAT �nucleotide po-sitions referring to the reverse complement of Gen-bank accession AF051208 sequence�. For the markerSb06, three polymorphic sites for SNPs were also de-tected between two homozygous individuals at posi-tions 106 bp �G/T�, 122 bp �A/G�, and 269 bp �A/C�of the sequence �nucleotide positions referring to thereverse complement of Genbank accession AF127432sequence�, resulting also in two alleles/haplotypes:GAA and TGC.

The pooling of DNA samples before or after PCRamplification, or before or after DNA purification,had no effect on the detection of SNPs by sequencing

DNA pools �data not shown�. Thus, DNA pools canbe constructed from genomic DNA samples beforethe amplification step, reducing cost �one PCR reac-tion� and saving additional time and energy at theamplification and purification steps. Following thesequencing of the DNA pools of various ratios, eachposition with a SNP was easily detected at moderatelyasymmetric ratios �from 10% to 90% relativefrequency� �Figure 2� but not at highly asymmetricratios �below 10% or above 90% relative frequency�.In all pools from 20% to 80% relative frequency, thedetection of polymorphism was obvious from the twoDNA strands. For pools from 10% to 15% and from85% to 90%, the detection of polymorphism was ob-vious from at least one DNA strand and sometimesfrom the second DNA strand �see Figure 2�.

Detection of polymorphic markers by DNA poolsequencing

For each species panel, a DNA pool containing anequal amount of genomic DNA from each of the 10diploid parents �20 alleles� was constructed before theamplification step. For each species, each of the 118primer pairs resulting in the positive amplification ofsingle-locus products without multiple-banding pat-tern was screened by DNA pool sequencing and thetypes of polymorphism observed are reported in Table2. For indel polymorphisms, a clear series of hetero-geneous positions was observed from the site of theindel, because of the shift in sequence �Figure 3�. Se-quences with indels could also harbor SNPs but be-cause of the shift in sequence, these SNPs could notbe confirmed on both DNA strands. Thus, only indelpolymorphisms were considered in such situations.DNA pool sequencing disclosed more polymorphicmarkers than those detected by AGE or parallelDGGE with standard conditions. Polymorphism wasrevealed for 91% and 90% of the 118 candidatemarkers for each of P. mariana and P. glauca,respectively �Table 2�. In comparison to numbers ofmarkers shown to be polymorphic by AGE or stan-dard DGGE, DNA pool sequencing identified 20�17%� and 32 �27%� additional ESTP markers for P.mariana and P. glauca, respectively �Table 2�. Theincrease was most notable in the number of markersfound simultaneously polymorphic for both species,with an increase of 34 �29%� ESTPs. However, forone marker in each species �SODchl for P. marianaand Sb19 for P. glauca, see Appendix A�, one indi-vidual out of 10 parents was observed polymorphic

267

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268

by DGGE, whereas no polymorphism was detectedby DNA pool sequencing. This result was likelycaused by one heterozygous parent for the marker,thus decreasing to 5% the frequency of the variant inthe DNA pool �one out of 20 alleles derived from 10diploid individuals�, below the minimum detectionlevel of 10% by DNA pool sequencing �see above�.

There were slightly more markers harboring onlySNPs only than those harboring indels, with respec-tive numbers of 56 and 51 for P. mariana and 56 and50 for P. glauca �Table 2�. On average, there was oneSNP per 100 bp �1.0%� and one indel per 555 bp�0.18%� in P. mariana, and one SNP per 122 bp�0.82%� and one indel per 575 bp �0.17%� in P.glauca. When coupling SNPs and indels, the overallrate of polymorphism was one per 85 bp �1.18 %� inP. mariana and one per 101 bp �0.99 %� in P. glauca.The estimates of SNP rates should be considered as

conservative: when indels were detected by DNApool sequencing, a shift in DNA sequence was vis-ible on the chromatograms from the position of theindel, preventing SNPs to be confirmed on both DNAstrands. Thus, these SNPs were not considered andscored.

Optimization of DGGE

Using information from DNA pool sequencing,DGGE conditions were further optimized to revealadditional markers in the mapping populations, or byusing CAPS �Table 2�. The rates of conversion of thenew polymorphic markers discovered by DNA poolsequencing to additional markers detectable by opti-mized DGGE or CAPS were 95% additional markersfor P. mariana �19 out of 20 new polymorphic mark-ers�, 78% for P. glauca �25 out of 32� and 88% �30

Figure 1. The relative efficiency of DNA sequencing and DGGE at detecting allelic variation for the marker Sb12 in Picea glauca: �A� fourdifferent genotypes �ab: #225; ac: #221; bc: #224; and bb: #238; ht is the heterodimer� were observed by DGGE �parallel gradient of 15-45%urea-formamide�, resulting in only three different alleles deduced �a, b, and c, with b as a heterogenous class containing two indiscerniblealleles�; �B� whereas four different alleles �a, b, c, and d� were clearly detected by sequencing.

269

out of 34� additional markers common to both spe-cies �Table 2�. Only a few markers shown to be poly-morphic by DNA pool sequencing remained mono-morphic by using these refined procedures �seeAppendix A�.

Regarding the markers shown to be polymorphicby DNA pool sequencing in P. mariana �107� and inP. glauca �106� �Table 1�, DGGE could achieve thedetection of polymorphism for 91% �97 out of 107�and 89% �94 out of 106� of them, respectively, usingeither standard or optimized conditions �see Appen-dix A�. The DNA fragment size class below 300 bpwas more frequently recovered than other size classes

by DGGE with 20-55% or 35%� parallel gradients,as opposed to DGGE with 15-45% parallel gradient�Table 3�. Of the markers detected polymorphic byDGGE on P. mariana and for which information wasavailable from DNA pool sequencing, 56% harboredSNPs only �54 out of 96 markers� while this propor-tion was 51% �47 out of 93� for P. glauca �Table 3�.The rest of the markers harbored indels with or with-out SNPs.

Figure 2. Sensitivity of SNP detection by DNA pool sequencing for the marker Sb12 in Picea glauca. To avoid overloading, only results forthe second SNP �A; position 392� and the fourth SNP �B; position 491� are shown. Under each chromatogram, variant alleles are indicatedby percent fraction �50 to 0%� in the DNA pools. The variant nucleotides are underlined. The P. glauca DNA sequence is indicated aboveeach chromatogram. SNPs could be detected with frequencies equal to or higher than 10% �ratios of a:b haplotypes equal to or above 2:20�in the DNA pools �A and B�.

270

Discussion

Two different sets of primer pairs specific toexpressed sequence tags or cDNAs were screened forpolymorphisms in this study, one developed from Pi-cea taxa and the other from Pinus taxa. With genomicDNA from spruce species, positive amplificationwithout multiple-banding pattern was twice more fre-quent and amplification conditions were more easilyoptimized with primer pairs derived from Picea taxathan with those from Pinus. A similar trend was re-ported for a set of primers developed from Picea byPerry and Bousquet �1998b� where marker transferwas highest between Picea taxa, and much lower be-tween Picea and Pinus. As for the rate of detection ofpolymorphisms, there was no difference between theprimer pairs derived from Picea or from Pinus, whichwas expected �Table 2�.

Denaturing gradient gel electrophoresis is moresensitive than agarose gel electrophoresis for the de-

tection of DNA polymorphisms, and more affordablethan sequencing for the step of scoring DNApolymorphisms in large mapping populations. How-ever, it usually requires fine tuning and a DNAsequence, for each marker screened, in order to de-termine the melting profile and optimize primers�Miller et al. 1999; Temesgen et al. 2001�. Our strat-egy was to use DNA pool sequencing as a prepara-tive step to DGGE in order to identify polymorphicmarkers a priori and avoid developing DGGE forotherwise unknown invariant markers. In doing so,efforts could be specifically devoted at optimizingDGGE conditions for polymorphic markers known apriori when standard denaturing conditions of 15-45% urea-formamide failed to reveal polymorphism.Thus, many markers could be made more informativeby DGGE. In our hands, DNA pool sequencing ap-peared to represent a high-throughput, efficient andsensitive method for detection of SNPs and indels atthe screening stage of markers. DNA pooling strate-

Figure 3. Detection of insertion/deletion by DNA pool sequencing for the marker Ptxmyb413 in 10 diploid individuals of Picea glauca. Notethe frameshift starting at position 552 bp of the reverse sequence.

Table 3. Number of polymorphic markers revealed on parallel DGGE in Picea mariana and P. glauca.

Marker attribute DGGE gradient Total

15-45% 20-55% 35%�

P. mariana P. glauca P. mariana P. glauca P. mariana P. glauca P. mariana P. glauca

� 300 bp 23 19 8 11 3 4 34 34301-500 bp 29 25 3 2 2 – 34 27� 500 27 27 2 6 – – 29 23Total 79a 71a 13 19 5 4 97a 94a

Harboring at least one indelb 37 39 5 6 – 1 42 46Harboring SNPs only 41 31 8 13 5 3 54 47

aIncluding one rare marker revealed by DGGE for each species but not detected by DNA pool sequencing �see Appendix A�, thus with noinformation regarding indels or SNPs.bOnly indel polymorphisms were considered since SNPs could not be confirmed on both DNA strands by DNA pool sequencing when indelsoccurred �see text�.

271

gies have been used successfully in other situations,notably with microsatellite markers to detect diseaseloci by marker association �Barcellos et al. 1997;Shaw et al. 1998�, for SNPs discovery by kineticreal-time quantitative PCR �Germer et al. 2000� andmore recently, to assess the sensitivity of BigDye™Terminator sequencing in detecting polymorphismwithin DNAs of F1 plants of potato cultivars �Rickertet al. 2002�.

In the present study, alleles in frequency lower than10% �2 out of 20 alleles� in the DNA pools could notbe scored reliably using BigDye™ Terminator se-quencing and two cases of false negatives were ob-served �see Appendix A� where a rare polymorphismwas observed by DGGE but not detected by sequenc-ing DNA pools. In some cases, alleles in frequencybetween 10% and 20% could not be detected reliablywith the sequence of only one DNA strand and se-quencing the two DNA strands generally appearedessential �see Figure 2�. While sequencing DNA poolsmust not be perceived as a panacea, low frequencyalleles are likely to be detected more efficiently withmore refined methods such as DHPLC �Wolford et al.2000�, although at a higher cost to startup the method�Choy et al. 1999�. While rare variants could be de-tected at a significant portion of ESTP loci in sprucepopulation studies �Perron et al. 2000; Jaramillo-Cor-rea et al. 2001; Perry and Bousquet 2001; Gamacheet al. 2003�, they appear to be minimally useful forconsensus genome mapping and association studies,where alleles with intermediate frequencies are likelyto be more powerful to detect associations �Goddardet al. 2000�. Thus, DNA pool sequencing is likely tobe an effective strategy to develop such markers, be-cause of its bias towards detecting common alleles.

As for false positives �false double-peaks� detectedby DNA pool sequencing, their exact proportion ap-pears difficult to evaluate. Within the limits of ourexperiments to scale up the method with known DNAsequences and SNPs, false positives were not notedwhen relying on good quality sequences and profilesfrom both DNA strands. Given that most markersfound polymorphic by DNA pool sequencing couldbe converted to polymorphic markers by AGE,DGGE or CAPS �98% and 92%, respectively, for P.mariana and P. glauca, see below�, and given thatAGE, DGGE and CAPS might fail altogether to re-veal all truly polymorphic markers, the proportion offalse positives obtained by DNA pool sequencing ap-pears to be low.

The 10 diploid individuals representing 20 allelesused for each species panel during the screening stageof markers by DNA pool sequencing represents theminimum number of individuals to detect more than96% of SNPs having a minimal frequency of 10%�Kruglyak and Nickerson, 2001�. Previous investiga-tions have shown that common alleles having a fre-quency higher than 10 to 20% �Taillon-Miller et al.1999� could be detected within a population of 10 in-dividuals �20 alleles� pooled �Lai et al. 1998; Shubi-towski et al. 2001�. For recalcitrant primer pairs instandard DGGE conditions, that is, those resulting inmonomorphic gel pattern, DNA pool sequencinghelped identify markers with SNPs or indels, so thata larger range of DGGE conditions were tested forthese primer pairs, or new primer pairs could be de-signed to frame the genomic regions harboring thesepolymorphisms.

Overall, for the 107 and 106 markers revealedpolymorphic by DNA pool sequencing in P. marianaand P. glauca, respectively, 105 �98%� and 98 �92%�could be converted to an affordable detection methodfor screening mapping populations, either AGE, stan-dard or optimized parallel DGGE, or CAPS. Thetransfer rate to DGGE was high. However, in a fewinstances, DGGE could not be optimized even aftertesting a range of denaturing conditions and by de-signing new primers. While relying on CAPS as analternative solution, we periodically encounteredproblems in getting a reliable DNA cleavage by cer-tain restriction endonucleases, echoing the results ob-tained by Shifman et al. �2002�. For the few markersfor which several SNPs were observed among parentsby DNA pool sequencing but not with the othermethods of detection tested, a possible solutionremains to develop allele-specific primer pairs toframe single-SNP regions. Several methods with dif-ferent advantages/disadvantages and/or limitationsexist for this purpose �Imyanitov et al. 2002; Neff etal. 2002; Latorra et al. 2003; for a recent review, seeAhmadian and Lundeberg 2002�.

The rates of SNP and indel detection observed inthis study must be taken as proxies because they re-flect the number of polymorphisms in a DNA pool.However, SNPs were four to five times more frequentthan indels, which is similar to results from an-giosperm mitochondrial introns �Laroche et al. 1997�.The rates of SNP detection observed in P. marianaand P. glauca are also in the same range as those ob-served in sugar beet �Schneider et al. 2001� and rice�Nasu et al. 2002�. These results support the sugges-

272

tion of Gupta et al. �2001� that SNPs are more fre-quent in plant genomes than in mammalian genomes�Wang et al. 1998; Cargill et al. 1999; Sachidanan-dam et al. 2001�. However, the rate of indel detectionwas lower than that observed in maize �Bhattramakkiet al. 2002; Ching et al. 2002�. When coupling bothSNPs and indels, one polymorphism was observedevery 92 bp �or 1.09 %�, on average, for both Piceaspecies. This rate of polymorphism is higher than thatestimated in barley from a sequenced gene pool�Kanazin et al. 2002�.

DNA pool sequencing indicated high rates ofmarker polymorphism in P. mariana and P. glauca�91 and 90%, respectively�, which appears to be en-couraging for estimating consensus maps in the ge-nus Picea. Comparative mapping requires commonanchor markers such as microsatellites or ESTPs inorder to estimate synteny and colinearity of linkagegroups between species. In Angiosperms, studies of

synteny and colinearity are in progress �Babula et al.2003� and in Gymnosperms, such studies are con-ducted within the genus Pinus �Brown et al. 2001; D.Neale, USDA Forest Services, UC Davis, CA, pers.comm.�. It is to be expected that the markers reportedin this study will help achieve a similar goal in thegenus Picea and more generally, in conifers.

Acknowledgements

We thank S. Plante and S. Senneville �CRBF, Univ.Laval� for help and support in the laboratory, C. Plo-mion �INRA-Bordeaux� for providing some of theprimer sequences, and two anonymous reviewers fortheir helpful suggestions. This research was supportedby a National Sciences and Engineering ResearchCouncil of Canada grant �Genomics Program� to J.B.and N.I.

273

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