Editor F. Roux
Novel SNP development and analysis at a NADP+-specific IDH enzyme gene in a four species mixed oak forest
Article first published online: 22 MAY 2012
© 2012 German Botanical Society and The Royal Botanical Society of the Netherlands
Special Issue: Woody Plant Performance in a Changing Climate. Guest Editor: M.S. Günthardt-Goerg. The German Botanical Society, the Royal Botanical Society of the Netherlands and Wiley have published this supplement without financial support.
Volume 15, Issue Supplement s1, pages 126–137, January 2013
How to Cite
Vidalis, A., Curtu, A. L. and Finkeldey, R. (2013), Novel SNP development and analysis at a NADP+-specific IDH enzyme gene in a four species mixed oak forest. Plant Biology, 15: 126–137. doi: 10.1111/j.1438-8677.2012.00575.x
- Issue published online: 21 DEC 2012
- Article first published online: 22 MAY 2012
- Received: 18 July 2011; Accepted: 23 January 2012
- Isocitrate dehydrogenase;
- Quercus spp.;
- single nucleotide polymorphisms
- Top of page
- Material and methods
- Supporting Information
Closely related Quercus species generally exhibit low levels of genetic differentiation despite their ecological and morphological differences. However, at a few so-called ‘outlier’ loci they seem to remain genetically distinct. Isocitrate dehydrogenases (IDH) are key enzymes involved in the metabolic pathway of the citrate cycle. IDH has also been characterised as an ‘outlier’ marker, significantly differentiating the closely related Q. robur and Q. petraea with the isozyme technique. This ability to differentiate the species was tested here at molecular level: 13 single nucleotide polymorphism (SNP) markers were identified and developed within a NADP+-specific IDH gene in Quercus spp. and applied as molecular markers in a four species mixed oak forest in eastern Europe, where Q. robur, Q. petraea, Q. pubescens and Q. frainetto naturally co-exist. From the 13 developed SNPs, three groups were formed: non-synonymous, synonymous and non-coding SNPs. The levels of total gene diversity were moderate for all species investigated. The non-synonymous SNPs showed lower levels of gene diversity. Overall, the four closely related Quercus spp. were significantly differentiated (except Q. petraea with Q. frainetto). Analysis of non-random association of alleles revealed no clear physical clustering of the SNP sites in significant linkage disequilibrium (LD). However, separate LD analysis for each species showed a lower number of sites in significant LD for Q. robur than for the other species, possibly reflecting the history of the species in this specific geographical site and less efficient recombination effect due to the larger effective population size of Q. robur. Eleven statistically significant associations were found between seven SNPs and morphological traits that are commonly used to differentiate oak species.
- Top of page
- Material and methods
- Supporting Information
Over the past two decades, new molecular techniques have had an important impact on the different fields of ecology, genetics and evolution. The use of single nucleotide polymorphisms (SNPs), as a marker for association studies but also to address common questions in population evolutionary history and genetics, becomes increasingly valuable. Their occurrence throughout the whole genome makes them ideal for analysis of speciation and demography, given a large number of nuclear unlinked loci to be analysed (Brumfield et al. 2003; Rosenberg et al. 2003). SNPs are in their majority bi-allelic markers, abundant and widespread in the coding and non-coding regions of the genome. SNP markers are therefore the markers of choice for the identification of gene loci that might be responsible for phenotypic trait variation, or involved in more complex physiological functions and for studying the dynamics of these genes in natural populations (Morin et al. 2004). Genome scans (Akey et al. 2002; Schlotterer 2004; Montesinos et al. 2009; Slate et al. 2009; Seeb et al. 2011), or candidate gene approaches targeting specific gene sequences, are the most common appications of SNP markers. However, although the last is more applicable to the large genomes of most forest trees (Scotti-Saintagne et al. 2004; Porth et al. 2005; González-Martínez et al. 2007; Eveno et al. 2008; Ingvarsson et al. 2008), the method is practically more difficult for important species with no available genome sequence, such as oaks.
Quercus species are excellent model species to study adaptation of forest trees to variable environments due to their wide geographical range and the large variation in climatic and edaphic conditions that they occupy (Gailing et al. 2009; Sork et al. 2010). The ecological significance of the different species and the genetic relationships among them makes the identification of SNPs in candidate genes important for understanding the role of selection in species formation. However, the identification of SNPs specifically for Quercus spp. can be challenging because of the lack of a reference oak genome sequence and the species’ close genetic relationship and hybridisation. It is necessary that the sequence of candidate genes within a species be obtained before SNPs can be identified and developed. Regarding Q. robur and Q. petraea, and despite their ecological and morphological differences, these two most widely distributed European oak species generally show very low genetic differentiation, both for nuclear and chloroplast DNA markers (Coart et al. 2002; Mariette et al. 2002; Petit et al. 2002a,b). However, a few so-called ‘outlier loci’ show high interspecific differentiation and are potentially involved in the different local genetic adaptation that maintains the species genetically distinct (Finkeldey 2001; Gömöry et al. 2001; Scotti-Saintagne et al. 2004; Muir & Schlotterer 2005; Curtu et al. 2007a; Neophytou et al. 2010). Indeed, markers that are directly subject to selection or linked to the target of selection are expected to show higher genetic differentiation than neutral markers (Beaumont 2005). Concerning the differentiation between other oak species, few reports exist in the literature; in general, Q. frainetto is considered genetically more similar to Q. pubescens than to the two other species (Curtu et al. 2007a). Additionally, Q. pubescens exhibits low genetic differentiation and high levels of genetic admixture with Q. petraea in mixed or pure stands (Curtu et al. 2009; Salvini et al. 2009). It has been suggested by many authors that diversifying selection has been the source of speciation among closely related Quercus species (speciation through local adaptation) (Lexer & Widmer 2008; Via 2009). Hence, the species differentiation can be seen as adaptation under different environmental circumstances, and can be maintained by selection acting upon genes in different directions, either directly (‘speciation genes’) or through ‘hitchhiking’ effects (Le Corre & Kremer 2003; Petit et al. 2004; Scotti-Saintagne et al. 2004; Lexer et al. 2006; Alberto et al. 2010). Therefore, and based on the above, our study focused on a gene reported in the relevant literature (see above) as highly differentiating among oak species, and thus is a candidate for local adaptation through the action of natural selection: IDH.
NADP+ IDH is a key enzyme of the citrate cycle that has been suggested to be involved in the production of essential amino acids (Palomo et al. 1998; Hodges et al. 2003). Isocitrate dehydrogenases have been reported in many different studies and organisms as potentially adaptive; in terms of isozyme electrophoretic separation, NADP+ IDH has been characterised as an ‘outlier’ locus, strongly differentiating among Quercus species. In particular, after analysing 21 pure and mixed oak populations (Q. robur and Q. petraea) in Switzerland using 17 isozyme gene loci, only three of them showed strong genetic differentiation between the two species, with IDH among those three markers (Finkeldey 2001). Similarly, 25 oak populations in Eastern Europe (Q. robur and Q. petraea) analysed for eight isozyme systems showed significant differentiation between the species only at IDH-B. This was the result for isozymes reliably scored in all 25 populations and when considering only differences based on frequent alleles (Gömöry et al. 2001). In a wide genome scan of the same oak species sampled within the range of their sympatric distribution, a set of 389 markers was applied (isozymes, AFLPs, SCARs, SSRs and SNPs; Scotti-Saintagne et al. 2004). Only 12% of the markers exhibited significant levels of genetic differentiation, while most markers showed low species differentiation (Gst < 0.01). The isozyme IDH marker was among the few loci that strongly differentiated the two species. Additionally, a correlation of specific alleles with the extent of beech scale insect (Cryptococcus fagisuga) infestation was found for Fagus sylvatica (Ziehe 1996a,b). Other examples of the adaptive significance of the NADP+ IDH genes in different species include differences in kinetic performance of the enzyme across thermal environments in cricket (Allonemobius socius) (Huestis et al. 2009), up-regulation of NADP+ IDH in poplar (Populus tremula × P. alba) after treatment with PPT (phosphinothricin, a common herbicide used in agriculture) in a transgenic PPT-resistance background (Pascual et al. 2008a), enhancement of expression of the gene after drought and salt stresses in Zea mays (Liu et al. 2010) and in ectomycorrhizal roots compared to non-mycorrhizal roots of Eucalyptus globulus (Boiffin et al. 1998) and, in a recent study, the association of a mutative NADP+ IDH-1 gene with glioma tumours in humans (Dang et al. 2009).
In the present study, the hypothesis of strong differentiation among different sympatric oak species at the molecular level of SNP markers within the IDH gene was examined. For this, SNP sites in coding and non-coding regions of the NADP+ IDH gene in Quercus spp. were developed and genotyped. The rationale of this study was that the different ecological requirements of the different oak species could have led to enhanced differentiation among them at the IDH gene. Despite the high levels of hybridisation among them, the different oak species might have evolved towards their different ecological optima, thus maintaining their differentiation regarding loci under selection. The choice of study site for our hypothesis testing was a rare sympatric four species (Q. robur, Q. petraea, Q. pubescens and Q. frainetto) oak forest (the four species rarely co-exist) that enabled focusing on the differentiation among closely related tree species with different ecological demands without interference from climatic or other environmental differences. In particular, Q. robur grows in deep, well-watered and nutrient-rich soils. It copes better with hard winters and late frosts than Q. petraea. On the other hand, Q. petraea is more drought-tolerant than Q. robur. Q. pubescens occurs on dry sites and shallow soils. Q. frainetto is better adapted to very compact, heavy clay soils and prefers long summers and mild winters. Q. pubescens and Q. frainetto are characterised as thermophilous species (Ellenberg 1988). Patterns of genetic variation and differentiation among the four species were determined for the non-synonymous, synonymous and non-coding SNPs. A direct comparison of the absolute allelic frequencies per SNP at all pairs of SNPs was conducted, given that the allelic frequencies provide the highest resolution of information obtained by any genotyping analysis. Linkage disequilibrium between the SNP loci was also estimated separately for each of the four Quercus spp., to obtain an insight into the recent history of the different species in this region obtained from the IDH locus and the newly developed SNPs. The results of previous investigations in the same study plot on leaf morphology and nuclear SSR markers of the same tree samples (Curtu et al. 2007a, 2007b) allowed us to conduct an association analysis of our SNP markers (which were found to significantly differentiate the species) with leaf morphological traits that significantly differentiate the species (in the abovementioned studies with the same individuals). The expectation was to find positive or even significant associations. Of course, leaf morphological traits are complex traits controlled by more than a single gene locus. Thus, a significant association between morphology and IDH SNP markers would not necessarily be attributed to a causal relationship, but could alternatively point to possible linkage or hitchhiking effects in markers targeted through selection.
Material and methods
- Top of page
- Material and methods
- Supporting Information
A total of 253 oak individuals (65 Q. robur, 65 Q. petraea, 73 Q. pubescens and 50 Q. frainetto) were investigated. The sampling was exhaustive and was conducted at the Bejan forest (45°51′ N, 22°53′ E), a four oak species natural reserve of about 4.5 ha, located in central-western Romania (for details see Curtu et al. 2007a). Extraction of genomic DNA from buds was done as described in Curtu et al. (2007a).
The genome of Quercus spp. is not yet sequenced and available in gene banks. Therefore, in order to develop SNP markers for a gene and apply them in Quercus spp., the relevant sequence must be identified. Based on the sequence of the NADP+-dependent IDH gene identified for Quercus spp. (sequences submitted to the European Nucleotide Archive (EMBL Bank): http://www.ebi.ac.uk, accession numbers FR717626–FR717629), five sequences per species were obtained to initially screen for variation using the BigDye system (Applied Biosystems, Foster City, CA, USA) on an ABI Prism® 3100 genetic analyser (Applied Biosystems), and were manually edited. Deriving from their multiple alignments using the Clustal W algorithm (Thompson et al. 1994) as applied in the BioEdit software (Hall 1999), the potential SNP sites were identified and confirmed by SNP genotyping, using SNP primers designed based on the obtained IDH sequences. The verified and unambiguous non-synonymous SNPs were chosen for further genotyping of all individuals. Similar number of synonymous SNPs and SNPs in the non-coding regions were verified by genotyping and were selected for genotyping on the whole sample.
SNP genotyping was performed using the ‘minisequencing’ single nucleotide primer extension method (Pastinen et al. 1997) with an ABI Prism® SNaPshot™ Multiplex Kit (Applied Biosystems) and following the manufacturer’s protocol, with modifications. The PCR amplified fragments of the NADP+-dependent IDH gene were pooled for use as template in the primer extension reactions. All SNP primers used were designed using the web-based software Primer3 (Rozen & Skaletsky 2000). The quality of the primers was determined with the software GeneRunner® (1994, Hastings Software Inc., Las Vegas, NV, USA). The sequences of the SNP primers developed, validated and used for further analysis, their direction and the nucleotide substitution that they genotype are provided in Table 1.
|SNP||primer||location on the gene||substitution||amino acid replacement||direction and oligo sequence 5′–3′|
|non-synonymous||1||1-325||2nd exon||a/g||isoleucine – valine||>t(19)cag gag atg aaa tga ctc ga|
|2||4-268b||8th exon||a/g||asparagine – serine||>t(26)gga ata tct gca gta ccc a|
|3||4-490b||9th exon||c/t||histidine – arginine||<t(32)gaa gcc tca gca aaa gca|
|4||7-325c||14th exon||g/c||glycine – arginine||>t(40)aat tgg aag cag cct gtg tt|
|synonymous||5||3-352s||6th exon||a/g||–||>t(18)ttc atc ccc cgt ctt gtc cc|
|6||2-70||3rd exon||a/g||–||<t(21)ctt gag cac ttt caa ttg taa c|
|7||7-97s||13th exon||t/a||–||>t(35)aca aac agc ata gca tcc at|
|8||7-330s||14th exon||c/g||–||<t(42)agt cat ctt tcc tga ttc cac|
|non-coding||9||1-51nc||1st intron||a/g||–||>t(16)gtt cat cat cta tta caa tca tgt ttt|
|10||2-419nc||3rd intron||g/c||–||<t(27)att gct aca ttg tac cta gaa agg|
|11||3-696nc||7th intron||a/g||–||>t(36)tcc atc aat gcc ttc ata c|
|12||6-171nc||11th intron||g/t||–||<t(39)aga gca agc acc ttt cca tt|
|13||7-392nc||14th intron||t/c||–||>t(43)tca tgg gcc caa gta att tc|
The SNP primers were pooled for multiplex primer-extension reactions (minisequencing), generating at most seven SNPs per reaction. For multiplexing, the SNP primers had 4–8 bp differences in size; separation of the different SNP genotypes was accomplished by addition of a poly (T)n tail at their 5′-end. The primer extension reaction was performed using the SNaPshot Multiplex Ready Reaction Mix ABI Prism® SNaPshot™ Multiplex Kit protocol (Applied Biosystems) on a PTC-200 Peltier thermal cycler (MJResearch Inc., Waltham, MA, USA). For electrophoretic separation, the purified primer extended fragments were loaded on an ABI Prism® 3100xl genetic analyser (Applied Biosystems). Capillary electrophoresis was performed on a POP7® polymer and buffered with EDTA (Applied Biosystems) with 36-cm long capillary columns. Data analysis was performed with GeneMapper® software v. 4.0 (Applied Biosystems).
The novel SNP data set was analysed in terms of gene diversity (HS) and inbreeding coefficient (FIS) within species using the software FSTAT v. 220.127.116.11 (Goudet 1995). The significance of the deviation of the observed FIS values from those expected in Hardy–Weinberg (HW) equilibrium was tested with 52,000 randomisations. Species differentiation in terms of pair-wise FST between all pairs of species was analysed with the software Arlequin v. 3.5 (Excoffier & Lischer 2010). The significance of the FST statistics was tested by 10,000 permutations of the individuals over the populations (species in this study). For a more direct test of the ability of each SNP to differentiate pairs of the four species, a simple homogeneity chi-square test was applied to compare the observed absolute allele frequencies for each pair of species with the expected allele frequencies under the null hypothesis of no difference between the pairs.
Linkage disequilibrium between all pairs of SNPs for each species separately was analysed with the likelihood ratio test, in which empirical distribution was obtained by 16,000 permutations (Slatkin & Excoffier 1996), as implemented in Arlequin v. 3.5 (Excoffier & Lischer 2010), using an expectation-maximisation (EM) algorithm to estimate haplotype frequencies in the case of genotype data with unknown gametic phase (Dempster et al. 1977; Excoffier & Slatkin 1998). For the total data set, LD was analysed as the squared correlation between all possible combinations of alleles (r2) in the case of two alleles being present. In the case of multiple alleles, a weighted average of r2 was calculated according to the allele’s frequency (Farnir et al. 2000). The corresponding P-values were determined with a two-sided Fisher’s exact test. For the total sample set, the analysis and plotting were conducted with the software TASSEL v. 2.1 (Bradbury et al. 2007).
The possible association of each investigated SNP with leaf morphological traits was tested. In particular, the morphological traits that were chosen for the association analysis were traits that were used to differentiate the four species (Kremer et al. 2002), as measured in the morphological analysis conducted on the same tree material as in our study (Curtu et al. 2007b). The leaf morphological traits are: lamina length (LL), petiole length (PL), sinus width (SW), basal shape of lamina (BS), lobe width (LW), length of lamina at largest width (WP), number of lobes (NL), number of intercalary veins (NV), and petiole ratio (PR). The last character was transformed from the above raw traits as suggested in Kremer et al. (2002): PR = 100 × PL/(LL + PL) and was found to strongly differentiate the oak material of this study (Curtu et al. 2007b). For the association analysis, we examined the possible associations between all the SNP markers with these morphological characters, using the statistical model: y = marker + Q + ε, (where y corresponds to the phenotypic values, the marker component represents the SNP marker effect, Q is the genetic structure effects and ε is the residual term). We also ran the model without Q (structure component). The morphological data were additionally transformed by standardisation through subtraction of the trait’s mean and division by its standard deviation. The association analysis was done using F-tests after 100,000 permutations under the above general linear model (GLM) implemented in TASSEL v. 2.1 (Bradbury et al. 2007). For this analysis, the genetic structure of the samples was also taken into account, as the main factor of false positive associations (Marchini et al. 2004; Hirschhorn & Daly 2005). In particular, data of genetic structure for the total sample set were used for the analysis as covariates. The structure data were obtained using six nuclear SSR markers and the Bayesian approach of population assignment implemented in STRUCTURE 2.3.3 (Pritchard et al. 2000) and published in a previous work (Curtu et al. 2007b) when analysing the same individuals. Association between SNPs and leaf morphological traits within different species was also tested. Kinship data derived from the SNPs were also used under a mixed linear model (MLM) to test any positives of the first model.
- Top of page
- Material and methods
- Supporting Information
From a total of 20 sequences (five sequences per species) of an NADP+-dependent IDH gene (3481 bp in size), 224 potential SNP positions were identified, excluding the simple sequence repeat (SSR) motifs and insertions or/and deletions. Thirty-eight of the potentially polymorphic sites were within the coding region of the gene. After confirming one-by-one all the potential SNPs of the non-synonymous sites with SNP genotyping, four non-synonymous SNPs were finally chosen for further analyses; others either turned out to be false due to possible amplification errors or led to spurious scoring due to double amplifications or primer mismatches. The same number of synonymous SNPs was chosen to be included in the analysis, together with five additional SNPs from the non-coding regions; all SNPs were distributed throughout the total obtained sequence of the gene, covering almost the complete gene sequence (Fig. 1).
The location of each SNP analysed on the gene and the amino acid replacement caused is provided in Table 1. Accordingly, among the four non-synonymous SNPs that were analysed, two cause no charge change through their amino acid replacement (SNP 1 and SNP 2) whereas the other two SNPs cause amino acid replacement with different charge (SNP 3 and SNP 4).
Genetic variation within species
Overall, estimates of gene diversity at the polymorphic SNPs varied in our sample from 0.014 in Q. pubescens at SNP 2 to 0.507 in Q. petraea at SNP 12. SNP 2 was monomorphic for Q. robur and Q. frainetto, while for the other species it only showed low diversity. The estimates for non-coding SNPs were in general higher than those of SNPs in coding regions, as expected due to the conserved coding sequence of a gene enzyme. In particular, the non-coding SNP 11 and SNP 12 showed the highest levels of diversity over all species (Table 2). On average, among similar values of gene diversity over species, Q. robur exhibited the lowest whereas Q. frainetto displayed the highest mean values. SNP 7, SNP 12 and SNP 13 revealed a third allele present only once in each case.
|SNPs||Quercus robur||Quercus petraea||Quercus pubescens||Quercus frainetto|
The inbreeding coefficient in most of the cases was negative or close to zero. However, the non-coding SNPs for Q. robur and the non-synonymous SNPs for Q. frainetto had the most elevated FIS values (0.387 at SNP 11 and 0.300 at SNP 4, respectively). Over all loci, a heterozygote deficit was positive in Q. robur, while in the other species FIS was negative, yet, in all cases this was not significantly different from Hardy–Weinburg expectations.
Genetic differentiation among species
Pair-wise FST values over all SNPs were generally low but significant for all pairs of species except Q. petraea and Q. frainetto. The separate analysis of coding and non-coding SNPs revealed higher differentiation within the first group of markers among all pairs, with the exception of Q. pubescens and Q. frainetto (Table 3).
|Quercus robur||Quercus petraea||Quercus pubescens||Quercus frainetto|
The pattern of almost all groups of markers (non-coding, coding and synonymous SNPs) suggested that among all species, Q. robur and Q. frainetto were most highly differentiated (FST = 0.122 for synonymous SNPs). Only the non-synonymous SNPs resulted in higher FST values between Q. robur against Q. petraea first and Q. pubescens second. In particular, all pairs of species showed lower levels of differentiation with the non-synonymous SNPs alone, apart from the species pair Q. robur–Q. pubescens, which was better differentiated with the non-synonymous SNPs. Additionally, Q. petraea and Q. frainetto were the least differentiated species, regardless of which SNPs were analysed. Regarding the non-synonymous SNPs alone, Q. frainetto was not significantly differentiated from any other species, as opposed to the synonymous and coding SNPs, as well as the overall SNP set (Table 3).
Moreover, the chi-square test carried out for the species pair-wise absolute allelic frequencies for each SNP marker showed significant differences (P < 0.05) at five SNPs for the pair Q. robur–Q. petraea (SNP 4, SNP 6, SNP 9, SNP 11 and SNP 13), six SNPs for the pair Q. robur–Q. frainetto (SNP 6, SNP 7, SNP 8, SNP 11, SNP 12, SNP 13), six SNPs for the pair Q. petraea–Q. pubescens (SNP 1, SNP 2, SNP 3, SNP 6, SNP 9, SNP 10), four SNPs for the pair Q. robur–Q. pubescens (SNP 1, SNP 8, SNP 11 and SNP 13) and three SNPs for the pairs Q. petraea–Q. frainetto and Q. pubescens–Q. frainetto (SNP 2, SNP 5, SNP 7 and SNP 6, SNP 10, SNP 12, respectively; Table 4).
Linkage disequilibrium and association analysis
Linkage disequilibrium (LD) analysis showed varying patterns of LD across the NADP+ IDH gene over the different SNPs, but the overall effects of LD were relatively low. For the total sample set, among 78 pairs of comparisons 31 SNP pairs showed evidence of significant LD after 10,000 permutations (39.7%). However, there was no clear physical clustering of sites in LD (Fig. 2). In particular, several sites of close physical distance (a few nucleotides apart) showed levels of LD close to zero (e.g. SNP 4, SNP 8 and SNP 13), whereas other sites with physical distance larger than 1000 nucleotides were found to be significantly linked (e.g. SNP 1 and SNP 13).
The analysis of LD among the 13 different SNP sites for each species separately revealed some differences among the species. In particular, Q. frainetto had the highest numbers of significant (P < 0.05) correlations (28 pairs), despite the fact that SNP 2 was monomorphic for this population (Table 5). Q. robur had 15 pairs of significant squared allelic correlations (r2); Q. petraea and Q. pubescens had 27 and 24 pairs of significant LD, respectively. Table 5 provides a summary of SNPs that are in significant LD (P < 0.05) using the EM algorithm (Slatkin & Excoffier 1996) for estimating haplotype frequencies for unphased data. Q. robur exhibited the smallest number of SNPs in LD (14), with the other species having almost twice the number of significantly linked SNPs beyond neutral expectations and spanning larger physical distances.
|SNP||Quercus robur||Quercus petraea||Quercus. pubescens||Quercus frainetto|
|1||–||9, 11, 12, 13||9||8, 9, 11|
|2||Monomorphic||3, 6, 13||3, 5, 6||Monomorphic|
|3||5, 11, 12||2, 6, 13||2, 5, 7, 10||5, 10, 11, 12|
|4||6, 13||6, 10, 11, 13||13||6, 13|
|5||3||–||2, 3, 6, 11||3, 10, 11|
|6||4, 10, 12, 13||2, 3, 4, 10, 11, 12, 13||2, 5, 10, 11, 13||4, 10, 11, 12|
|7||–||8, 9, 10, 11||3, 8, 9, 10, 11, 12, 13||8, 9, 10, 11, 12, 13|
|8||–||7||7, 13||1, 7, 13|
|9||10, 11, 12||1, 7||1, 7||1, 7, 10, 11|
|10||6, 9, 11, 12||4, 6, 7, 11, 12, 13||3, 6, 7, 11, 12||3, 5, 6, 7, 9, 11, 12|
|11||3, 9, 10, 12||1, 4, 6, 7, 10, 12, 13||5, 6, 7, 10, 12, 13||1, 3, 5, 6, 7, 9, 10, 12, 13|
|12||3, 6, 9, 10, 11||1, 6, 10, 11, 13||7, 10, 11||3, 6, 7, 10, 11, 13|
|13||4, 6||1, 2, 3, 4, 6, 10, 11, 12||4, 6, 7, 8, 11||4, 7, 8, 11, 12|
The possible association of each investigated SNP with leaf morphological traits was examined for the measured morphological traits that best differentiated the species (Curtu et al. 2007b) after 100,000 permutations under a GLM, and taking into account the genetic structure of the samples, as being the most serious systematic bias that can create false positive associations. The association analysis between the SNPs and the leaf morphological traits for each species separately resulted in different associations. However, in a few cases, the same SNP was associated with a given trait in more than one species. These traits were mainly related to the lobes and veins, or length of the lamina (see Supporting information). A test of our data under a MLM including kinship data as covariate also resulted in the same positives. For seven SNPs the analysis showed significant (P < 0.05) associations with one or two of the nine traits (Table 6). More than twice as many associations were found from the association analysis without considering the Q component (the genetic structure of the samples; Table 7). Between the two types of analysis (with and without Q), only three associations remained valid: SNP 2 – PL, SNP 4 – LW, SNP 5 – LW (Tables 6 and 7: highlighted in bold). However the R2 percentage of the total variation explained by each mutation (SNP) was generally low (below 4%).
|SNP3||Number of intercalary veins||2||4.196||0.0162||0.0171|
|Basal shape of lamina||2||4.022||0.0191||0.0098|
|SNP5||Number of intercalary veins||1||4.918||0.0275||0.0097|
|Basal shape of lamina||1||4.2281||0.0408||0.017|
|Basal shape of lamina||2||3.6974||0.0262||0.0287|
|Number of lobes||2||3.5751||0.0295||0.0278|
|Length of lamina (at largest width)||2||3.2697||0.0396||0.0255|
|Length of lamina (at largest width)||1||8.2474||0.0044||0.0322|
|Number of intercalary veins||1||7.6280||0.0062||0.0298|
|Basal shape of lamina||1||5.7733||0.017||0.0227|
|SNP6||Number of lobes||2||8.1739||3.67E-04||0.063|
|Number of intercalary veins||2||5.3142||0.0055||0.0419|
|Basal shape of lamina||2||3.2766||0.0394||0.0263|
|SNP7||Number of lobes||3||4.5819||0.0038||0.0529|
|SNP8||Number of lobes||2||3.6548||0.0273||0.0289|
|SNP13||Basal shape of lamina||3||5.5921||0.001||0.0636|
|Number of intercalary veins||3||4.4331||0.0047||0.0511|
- Top of page
- Material and methods
- Supporting Information
In the present study, a candidate gene-targeted approach for SNP analysis of a NADP+ IDH gene was followed. This approach was based on the consideration of IDH as a candidate gene for species differentiation and therefore as candidate for speciation due to local adaptation (Lexer & Widmer 2008). The use of SNPs in candidate genes for organisms where their genome has not yet been fully sequenced is still evolving because of practical difficulties in identification of the sequences (Helyar et al. 2011; Seeb et al. 2011). However, similar approaches have been used recently, but based on EST databases for salmon species differentiation (Campbell & Narum 2011) or detection of selection on human populations (Quintana-Murci et al. 2008; Quintana-Murci & Barreiro 2010). In our study, the total number of possible SNP positions – not taking into account the SSR motifs and insertions and/or deletions – was much higher (ca. 1.5–3-fold: 224 sites in a total sequence of 3481 bp) than that reported previously for Quercus spp. (Vornam et al. 2007; Quang et al. 2008, 2009; Derory et al. 2010), as well as for other plant genera (Ingvarsson 2005; Yamasaki et al. 2005; Zhu et al. 2007). One explanation for this might be possible PCR amplification or sequencing errors, or even cases of unspecific amplifications, as not all SNPs were re-sequenced. The SNPs that were finally analysed and genotyped were tested for reproducible patterns of chromatographs and for clear undisputed scoring. Among the four non-synonymous SNPs analysed, only two revealed a change in the charge of the amino acid that they code for, leading to potential structural differences and thus being potentially adaptive.
The levels of gene diversity measured for the total number of SNPs were generally similar to those revealed in isozyme investigations for the same sample set (HS = 0.211). The measurement of HS for Q. robur in this study (HS = 0.208) was slightly lower than that for the other three species (HS = 0.252, 0.274 and 0.283 for Q. petraea, Q. pubescens and Q. frainetto, respectively), with the highest value found for Q. frainetto, in contrast to the isozyme investigation of Curtu et al. (2007a), which found that this species had the lowest HS value (0.182). This was attributed to the smaller sample size examined for this species. Indeed, bi-allelic SNP markers might be less influenced by the smaller sample size in terms of gene diversity than markers with a larger number of alleles and higher mutation rate, such as nuclear SSRs. In comparisons of the two most widely distributed in Europe, Q. robur and Q. petraea, similar to other studies of mixed or pure stands (Gömöry et al. 2001; Mariette et al. 2002; Finkeldey & Mátyás 2003), this study also found higher variability for the latter species.
The genetic differentiation among the four species was overall significant in almost all pairs of species, with the exception of Q. frainetto and Q. petraea. However, the high levels of hybridisation among the different species pairs might keep the pair-wise FST values (although significant) relatively low. The non-synonymous SNPs alone failed to significantly distinguish Q. frainetto from any other species. On the other hand, the synonymous SNPs revealed the largest significance not only in differentiating Q. frainetto from the other species, but also all the other species pairs. Similar but stronger results of the direct pair-wise comparison of the absolute allelic frequencies per SNP (comparison of the more informative raw data set) were obtained with a chi-square significance test. In particular, all pairs of species were significantly differentiated for at least three SNP markers (P < 0.05), with the genetically most related species pair (Q. robur–Q. petraea) being significantly differentiated in all groups of SNPs and with a large proportion of the SNP markers (five SNPs). In almost all groups of SNP markers the present results confirm previous findings, in that among the four species, Q. robur and Q. frainetto are the most differentiated (Schwarz 1993; Curtu et al. 2007a). There was a surprising exception to this rule within the group of non-synonymous (and thus potentially associated with a given phenotype) SNPs (SNP 1, SNP 2, SNP 3 and SNP 4), where the highest differentiation was between the pair Q. robur–Q. petraea, as opposed to the results of the neutral markers used on the same material in Curtu et al. (2007a), where the same species pair was the least differentiated. With the same group of SNP markers, Q. frainetto was least differentiated from Q. robur, in accordance with a phylogenetic study of Italian oaks based on sequence comparison of the ITS1 and ITS2 regions of the 5.8S RNA encoding ribosomal DNA (Bellarosa et al. 2005), where a closer relationship between Q. robur and Q. frainetto was found as compared to Q. pubescens and Q. petraea.
The estimates for non-random linkage of different alleles among pairs of SNPs in the total sample set revealed evidence for significant LD in 39.7% of all possible comparisons. This percentage is generally high compared to that of other forest tree species (Neale & Savolainen 2004; Neale 2007). The high percentage observed can be explained by the location of all SNPs within the same gene, despite the relatively large size of the gene. However, significant associations were not necessarily found between SNPs of closer proximity. Nevertheless, as illustrated in Fig. 2, the estimates of r2 are low, with very few comparisons exceeding 0.2–0.3, as it would be expected for a predominantly out-crossing species (Neale & Savolainen 2004; Morrell et al. 2005; Zhang & Zhang 2005; Ingvarsson et al. 2008). In all such cases, the physical distance of the SNPs was larger than 0.5 kb (see Fig. 2, Table 1). In the LD analysis of each species separately, the low number of linked loci in the case of Q. robur might reflect the highest effectiveness of recombination, due to a larger effective population size. Q. frainetto possibly reflects a founder effect on the higher number of significant associations spanning larger physical distances, since the stand in this study is at the edge of its distribution (Bartha 2006). The same could be the case for Q. pubescens since Romania is close to the northeastern part of the species’ range (Bussotti 2006), but the genetic admixture with other sympatric oak species could better explain the high number of linked polymorphic sites over larger physical distances. Indeed, higher hybridisation and admixture between Q. petraea and Q. pubescens was reported in paternity analyses (Curtu et al. 2009) in the same stand. In this study, even if a few are admixed or hybridised, it is unlikely that all SNP markers are linked to selection targets or are under direct selection. However, inferences about demography and recent history based on SNP markers should be considered reliable only when information from multiple unlinked loci – including neutral loci – is combined (Brumfield et al. 2003).
The association study of all SNPs with leaf morphological traits (see Curtu et al. 2007b), after considering population structure (Q), revealed 11 significant associations. In many cases multiple associations were found for one trait (Table 6). Among the 11 statistically associated loci, SNP 2, SNP 3 and SNP4 are interestingly non-synonymous mutations. The similar level of associations with morphological traits between non-synonymous and synonymous SNPs (which is higher than that of non-coding SNPs) suggests that the SNPs do not represent causal variants for the morphological traits tested, but rather might be independently linked to some of the real causal variants through LD (Hindorff et al. 2009).
The comparison of association tests with and without considering population structures (Q) showed not only a much lower number of significant associations in the first case, but also lower R2 values. This indicates that population structure not only biases the number of associations between phenotypes and genotypes, but also the percentage of phenotypic variation explained by a given marker. In the present study, even though the four species co-exist in sympatry and frequently hybridise, their genetic structure remains high and influences both the number of associations and the percentage of phenotypic variation explained by each SNP.
In the case of association mapping within species (see Supporting information), interestingly, the SNPs that were present in any significant association for more than one species were associated with traits related to the length of the lamina or number of lobes and veins over different species pairs. Also related to these traits were the common associations between SNPs and phenotypic observations of the total sample size with and without considering the Q component (Tables 6 and 7). These results suggest a possible link of the IDH SNPs developed and analysed in the present work to the specific leaf traits, and therefore could confirm the possible role of IDH in protection against environmental stress in plants (Leterrier et al. 2007; Liu et al. 2010).
In conclusion, this study has shown that the newly developed and analysed SNP markers of the NADP+ IDH gene can significantly differentiate closely related oak species. Nevertheless, these markers should be replicated in other mixed oak forests in order to determine their power as potential markers of differentiation or/and speciation through local adaptation. Among the SNPs, there was evidence of several being in significant linkage disequilibrium. The analysis of linkage disequilibrium of the SNPs in each population separately suggested a possible founder effect for the population of Q. frainetto, and high levels of admixture and hybridisation among the sympatric oak species, which keeps the differentiation indices low but still significant. Moreover, to answer questions with regard to adaptive variation of oaks, and for more powerful association analyses, many more genes should be additionally investigated and analysed. The obtained significant associations of eleven SNPs with nine different traits of leaf morphology should be further tested for verification with QTL mapping applications on Quercus pedigrees that segregate for leaf morphological traits.
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- Material and methods
- Supporting Information
We thank O. Gailing for useful comments on the manuscript, and A. C. Papageorgiou and M. Ziehe for suggestions on the analyses. A. L. Curtu was supported by CNCS-TE-73/2010.
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- Material and methods
- Supporting Information
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- Material and methods
- Supporting Information
Table S1. Significant (P < 0.05)associations between SNPs and morphological traits (F), degrees offreedom (df) and the percentage of phenotypic variation explainedby the corresponding SNP (R2) forQ. robur.
Table S2. Significant (P < 0.05)associations between SNPs and morphological traits (F), degrees offreedom (df) and the percentage of phenotypic variation explainedby the corresponding SNP (R2) forQ. petraea.
Table S3. Significant (P < 0.05)associations between SNPs and morphological traits (F), degrees offreedom (df) and the percentage of phenotypic variation explainedby the corresponding SNP (R2) forQ. pubescens.
Table S4. Significant (P < 0.05)associations between SNPs and morphological traits (F), degrees offreedom (df) and the percentage of the phenotypic variationexplained by the corresponding SNP (R2) forQ. frainetto.
|plb575_sm_TableS1-4.doc||96K||Supporting info item|
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