Gene 540 (2014) 117–121
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Gene journal homepage: www.elsevier.com/locate/gene
Short Communication
Next generation sequencing based development of intron-targeting markers in tetraploid potato and their transferability to other Solanum species Rahim Ahmadvand a,b,c,⁎, Péter Poczai d, Ramin Hajianfar a,c, Balázs Kolics b, Ahmad Mousapour Gorji c, Zsolt Polgár a, János Taller b a
Potato Research Centre, Centre of Agricultural Sciences, University of Pannonia, H-8360 Keszthely, Festetics u. 7, Hungary Department of Plant Science and Biotechnology, Georgikon Faculty, University of Pannonia, H-8360 Keszthely, Festetics u. 7, Hungary c Seed and Plant Improvement Institute, Mahdasht Ave. 3185, Karaj, Iran d Department of Biosciences, University of Helsinki, PO Box 65, FIN-00014 Helsinki, Finland b
a r t i c l e
i n f o
Article history: Accepted 18 February 2014 Available online 26 February 2014 Keywords: Intron-targeting Molecular marker Next generation sequencing Potato Transcriptome analysis
a b s t r a c t Intron-targeting (IT) markers were developed from next generation sequencing (NGS) derived transcript sequencing data from the potato cultivar White Lady. The applicability of the IT markers was analyzed in other potato genotypes, and their transferability was studied in other Solanum species: section Archaesolanum (5 species), sect. Solanum (6 species) and a Solanum nigrum population (11 genotypes). Out of 250 randomly chosen transcript sequences, 144 intron harboring loci could be identified for which primer pairs were designed on exons flanking the putative introns. The usefulness of the IT primers was experimentally analyzed on a subset of 40 randomly chosen loci. Statistical analysis of diversity parameters was performed using the ATETRA and POPGENE software packages. By localizing the detected 17 polymorphic loci 11 of the 12 potato chromosomes could be identified. Specificity of the designed IT primers was tested by sequence analysis of amplified IT fragments in a randomly chosen locus. The results revealed the efficiency of NGS derived IT marker development and indicated their utility in diverse molecular analyses including their applicability for cross-species studies. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Potato is the world's most important non-grain food crop and plays a major role in global food security. Knowledge of the potato genome has increased dramatically over the last decade, and recent publication of the potato genome sequence has provided new insights to potato genetics (Potato Genome Sequencing Consortium). Detailed sequence
Abbreviations: IT, intron-targeting; NGS, next generation sequencing; RNA-Seq, RNA sequencing using NGS; Life Tech SOLiD, Life Technology-sequencing by oligonucleotide ligation and detection; NCBI, National Center for Biotechnology Information; SGN, Solanum Genomics Network; TC, transcriptome; SNP, single nucleotide polymorphism; SSR, simple sequence repeats; dNTP, deoxyribonucleoside triphosphate; BLASTN, Basic Local Alignment Search Tool-nucleotide; PCR, polymerase chain reaction; HC, heterozygosity corrected for sample size; Hc′, Shannon index corrected for sample size; h, expected heterozygosity or Nei's gene diversity; I, Shannon's information index of phenotypic diversity; HT, panmictic heterozygosity or total genetic diversity; HS, intra-population genetic diversity; FST, Wright's fixation index; CDDP, conserved DNA-derived polymorphism. ⁎ Corresponding author at: Potato Research Centre, Centre of Agricultural Sciences, University of Pannonia, H-8360 Keszthely, Festetics u. 7, Hungary. E-mail addresses: [email protected] (R. Ahmadvand), [email protected] (P. Poczai), [email protected] (R. Hajianfar), [email protected] (A.M. Gorji), [email protected] (Z. Polgár), [email protected] (J. Taller).
http://dx.doi.org/10.1016/j.gene.2014.02.045 0378-1119/© 2014 Elsevier B.V. All rights reserved.
information enables the development of functional markers, which are considered to be more effective for most molecular genetic studies than other marker types. An efficient method to generate genespecific markers for mapping in plants is the intron-targeting (IT) method (Choi et al., 2004). Introns are widespread and abundant in eukaryotic genomes and they possess variable amount of polymorphism. IT primers are complementary to the sequences of exons flanking the targeted intron. Since intron sequences are generally less conserved than exons, the amplified products may display polymorphism due to length/nucleotide variation among the introns alleles of the targeted gene. On the other hand, the higher level of sequence conservation in the exons ensures that all alleles can be effectively amplified. Advances in sequencing technology have enabled deep sequencing of complete transcriptomes (RNA-seq) (Clarke et al., 2009). Highthroughput transcriptome sequencing has the advantage to generate large transcript sequence data sets for gene discovery and molecular marker development. In the present study, the efficiency of the development of introntargeting markers from next generation sequencing (NGS) derived transcripts was analyzed, and in addition, the applicability and transferability of these IT markers to related potato and wild Solanum species with different ploidy levels was confirmed.
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2. Materials and methods
3. Results
2.1. Plant materials
3.1. Development of IT markers
Twenty four individuals of a tetraploid F1 population of a cross of the cultivar, White Lady and the breeding line S440, as well as 24 potato cultivars from different origins were involved in the analysis (Supplementary Table 1). To analyze the applicability of potato NGS derived IT markers in related Solanum species, three populations of wild Solanum species were also examined. The species and their ploidy level are listed in the Supplementary Table 2.
By the NGS sequencing more than 12 million reads were obtained, and each read had a maximum size of 50 nucleotides. From the reads 38 675 contigs (TC) could be constructed using the CLC Genomics Workbench software 4.8 (64 bit) version. Out of these, 250 contigs were randomly chosen and analyzed for the presence of introns using the NCBI as well as the SOL Genomics Network database, and 144 transcript sequences were identified as potentially harboring introns. Locus specific primer pairs were designed for each sequence, and 40 randomly chosen loci were experimentally analyzed for the assumed intron length polymorphisms. While for all 40 loci PCR products were obtained, 25 loci showed length polymorphism in the analyzed populations.
2.2. Development of NGS derived intron-targeting markers mRNA was extracted from young leaves of potato cultivar White Lady with RNAzol (MRC, USA). For NGS sequencing, the Life Tech SOLiD RNA Sequencing Kit (Life Technologies, USA) was used according to the manufacturer's recommendations. Sequencing was performed using a 5500xl SOLiD (Life Technologies, USA) sequencer. Sequence reads were assembled into contigs using the CLC Genomics Workbench 4.8 (64 bit) software. Genes for the generated transcript data set were identified, aligned and annotated with potato genome sequence (Potato Genome Sequencing Consortium, 2011) in NCBI database using BLASTn (nr and Whole-genome shotgun contigs) with the E-value 10−20 up to June 2012. The program Sim4 (Florea et al., 1998) was applied to align transcript sequences to the corresponding genes in potato in order to find putative intron regions. In addition, the SOL Genomics Network (Mueller et al., 2005) was used to predict intron regions. Introntargeting primers were designed on the exon sequences flanking the putative introns with the PRIMER3 v. 0.4.0 software (Rozen and Skaletsky, 2000). 2.3. Genomic DNA extraction and PCR amplification Total genomic DNA of all genotypes was isolated from young leaves using the method of Walbot and Warren (1988). Final volume of the PCR reaction mixture was 12 μl, with 40 ng DNA template, 0.5 μM of each primer, 2.0 mM dNTP (Fermentas, Lithuania), 1.5 μl of 10 × PCR Dream Taq Green Buffer provided by the manufacturer (Fermentas, Lithuania) and 0.1 μl of 5 U/μl Dream Taq DNA polymerase. The PCR conditions were as follows: 3 min 94 °C for initial denaturation, 35 cycles of 20 s denaturation at 94 °C, a 20 s annealing at the temperature indicated for each primer pair (Supplementary Table 3), 1 min extension at 72 °C and a final extension at 72 °C for 5 min. PCR products were separated on 1.5% agarose gel and visualized after ethidium–bromide staining with a GenGenius Bio Imaging System (Syngene, UK). The experiment was started with optimization of PCR conditions where for each primer pair a subset of individuals of each population was examined and the repeatability of amplified fragments was confirmed for each primer pair. In addition, the specificity of amplified fragments was examined in the randomly chosen Cin locus with sequencing and alignment in randomly chosen F1 and commercial cultivar individuals. 2.4. Data analysis The banding patterns were scored based on the size and presence/ absence of a sharp band. All genetic analyses were carried out under the assumption of the Hardy–Weinberg equilibrium. For all populations the POPGENE version 1.31 program (Yeh et al., 1997) designed for haploid and diploid data analysis was used. In addition, ATETRA v. 1.2 software (Van Puyvelde et al., 2010), designed to analyze tetraploid microsatellite data, was also applied to estimate the same genetic parameters. The SOL Genomics Network (SGN) was applied to determine the chromosomal location of each polymorphic intron marker.
3.2. IT length polymorphism in the potato genotypes Out of the 40 analyzed loci, 17 showed different levels of length polymorphism both in the F1 population and among the potato cultivars, while the remaining 23 were monomorphic. The number of alleles per locus ranged from 2 to 5 in both populations. Results of statistical analysis obtained with the ATETRA as well with the POPGENE software on heterozygosity are shown in the Supplementary Table 4. Because the analyzed potato cultivars originate from different genetic backgrounds, the observed diversity in the population of the 24 cultivars was high (HS = 0.24) (Table 1). 3.3. IT length polymorphism in the wild Solanum species All 40 IT primer pairs which were designed based on the potato transcriptome sequences resulted one or more PCR products in one, two or in all three wild Solanum groups. Out of the 40 analyzed loci, the number of polymorphic loci was 21 in sect. Archaesolanum, 22 in sect. Solanum and 16 in accessions of S. nigrum (Supplementary Table 5). The number of polymorphic bands per locus ranged from 2 to 10. Interestingly, while polymorphism could not be detected in the potato populations for the Mresis, Cad, Winsh, Str, PT11, Pe54, Cop12 and Cunf34 loci, they showed variation among wild Solanum species. On the other hand, for the LBR57 and RP3a loci, which were polymorphic in the potato populations, only a monomorphic band was observed among wild Solanums. The locus RPB36 displayed polymorphism only in Archaesolanum species. On the contrary, loci R1L333 and Winsh were only monomorphic in sect. Archaesolanum. Most of the IT markers amplified significant length variation among the three wild Solanum populations (Fig. 1; Supplementary Table 5). The overall Wright's fixation index (FST) across all wild Solanum population was 0.33 suggesting great population differentiations, which is not surprising as these groups represented distantly related lineages. Summary statistical data for the potato- and wild Solanum populations obtained with ATETRA and POPGENE are shown in Table 1. 3.4. Localization of the IT markers in the potato genome Using the Solanum Genomics Network database, the genomic location of 21 loci out of the 25 detected polymorphic IT markers was determined. These markers resided on potato chromosomes I to XII (Supplementary Table 3) the only exception being chromosome X. SGN-based map locations of the remaining 15 loci that were monomorphic in each populations are given in the Supplementary Table 6. 3.5. Specificity analysis of the amplified IT fragments Specificity of the amplified IT fragments was tested in the randomly chosen Cin locus by sequencing all IT fragments in 8 randomly chosen F1 genotypes (ID No. 85, 90, 95, 114, 286, 446, 442, 467), in their parents
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Table 1 Statistical summary of all populations using ATETRA software and POPGENE software. Marker
PKF11 LBR57 AVTPSH PGRSH RP3a35 NB89 PTA-83-1 RL333 ATP-218 Cin TSWVP TREPSH TRP77 Nitsh RPB36 Cat Mresis Cad Winsh Str PT11 Pe54 Antiv1 Cop12 Cunf34 Mean
No. of individuals
48 22 48 48 22 48 22 48 48 22 48 22 48 22 48 22 48 22 48 22 48 22 48 48 21 48 22 48 20 48 22 48 13 48 22 48 20 48 22 48 20 48 21 48 21 48 21
Genotype
F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum
ATETRA analysis
POPGENE analysis
Hc
H′c
h
I
HT
HS
Fst
0.51 0.83 0.73 –a 0.70 0.80 0.78 0.55 0.75 – 0.51 0.68 0.65 0.75 0.52 0.15 0.57 0.42 0.66 0.80 0.59 0.50 0.66 0.44 0.51 0.80 0.42 0.79 0.41 0.19 0.10 0.60 – 0.47 – 0.58 – 0.65 – 0.46 – 0.61 – 0.78 0.74 0.83 – 0.77 – 0.88 0.58 0.62
0.91 1.86 1.20 – 1.21 1.63 1.19 1.46 1.34 – 0.84 1.55 1.13 1.50 0.94 0.71 1.06 0.90 1.18 1.53 1.04 0.69 1.05 0.91 0.89 1.57 0.73 2.22 0.60 0.92 0.21 1.81 – 0.65 – 0.98 – 1.06 – 0.92 – 1.01 – 1.67 1.15 1.34 – 1.67 – 1.70 0.98 1.32
0.20 0.25 0.40 – 0.24 0.18 0.45 0.25 0.35 – 0.22 0.20 0.33 0.33 0.18 0.05 0.27 0.20 0.26 0.35 0.26 0.30 0.15 0.13 0.13 0.24 0.19 0.16 0.32 0.14 0.05 0.13 – 0.23 – 0.31 – 0.25 – 0.18 – 0.24 – 0.19 0.34 0.31 – 0.19 – 0.23 0.26 0.22
0.33 0.38 0.59 – 0.37 0.30 0.64 0.39 0.53 – 0.37 0.34 0.48 0.49 0.27 0.11 0.42 0.33 0.40 0.52 0.39 0.48 0.21 0.23 0.21 0.38 0.31 0.28 0.49 0.27 0.11 0.24 – 0.32 – 0.48 – 0.34 – 0.30 – 0.36 – 0.32 0.52 0.47 – 0.32 – 0.39 0.39 0.35
0.20 0.25 0.40 – 0.24 0.18 0.45 0.28 0.35 – 0.38 0.21 0.34 0.37 0.18 0.06 0.27 0.24 0.26 0.38 0.26 0.37 0.15 0.12 0.13 0.23 0.20 0.17 0.32 0.20 0.05 0.14 – 0.25 – 0.39 – 0.25 – 0.15 – 0.27 – 0.20 0.34 0.31 – 0.20 – 0.24 0.27 0.24
0.19 0.15 0.38 – 0.17 0.17 0.40 0.17 0.32 – 0.35 0.19 0.33 0.16 0.17 0.04 0.25 0.13 0.21 0.11 0.24 0.13 0.08 0.11 0.08 0.17 0.19 0.12 0.31 0.15 0.05 0.12 – 0.12 – 0.21 – 0.13 – 0.13 – 0.21 – 0.18 0.33 0.29 – 0.14 – 0.18 0.24 0.15
0.05 0.40 0.05 – 0.29 0.06 0.11 0.39 0.09 – 0.08 0.10 0.03 0.57 0.06 0.33 0.07 0.46 0.19 0.71 0.08 0.65 0.47 0.08 0.38 0.26 0.05 0.29 0.03 0.25 0.00 0.14 – 0.52 – 0.46 – 0.48 – 0.13 – 0.22 – 0.10 0.03 0.06 – 0.30 – 0.25 0.13 0.33
HC: Heterozygosity corrected for sample size; Hc′: Shannon index corrected for sample size; h: Expected heterozygosity or Nei's gene diversity; I: Shannon's information index of phenotypic diversity; HT: panmictic heterozygosity or total genetic diversity; HS: intra-population genetic diversity; FST: Wright's fixation index; a: Monomorphic.
(White Lady and S440), as well as in the randomly chosen cultivars Ditta, Katica, Agria, Franciella and Bzura (Supplementary Table 7.). Similarity of the sequenced fragments indicated that all the detected IT
fragments represent the Cin locus. The number of detected alleles was between 2 and 4. Besides the indels all alleles in each genotype could also be distinguished by SNP-s. All allelic sequences of the F1 genotypes
Fig. 1. Polymorphism pattern of wild Solanum populations using PKF11 primer pairs in 1.5% agarose gel. Samples: M: 100 bp plus DNA ladder, lanes 1–5: sect. Archaesolanum species, lanes 6–11: sect. Solanum species, lanes 12–22: S. nigrum individuals.
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were present also in the parents, while SNP-s could be detected among the alleles of the cultivars which showed to be same size in an agarose gel.
4. Discussion Due to the presence of highly repetitive transposable elements and paralogous sequences, especially in polyploid species, plant genome sequences are complicated. Therefore, detection of genetic variation via NGS has mainly been focused on transcript sequences (Deschamps and Campbell, 2010). Although single nucleotide polymorphism (SNP) and simple sequence repeats (SSR) are commonly identified by NGS, IT markers can serve as a suitable alternative due to their simple detection (agarose-based), locus specificity, co-dominant nature and efficiency in covering the genome. Considering that transcript sequences of the tetraploid cultivar were annotated based on their similarity to the published potato genome sequence, which is from a Solanum tuberosum group Phureja doubled monoploid line (PGS Consortium, 2011), the identification of 144 intron harboring genes out of 250 randomly chosen sequences reveals the efficiency of our strategy. It should also be emphasized that cultivated potato is highly heterozygous and the cultivar White Lady has also different wild potato ancestors, including S. stoloniferum, S. acaule, S. demissum and S. tuberosum subsp. andigena. The intron marker Cat-in2 was developed earlier to localize the Rysto gene in the potato genome (Cernak et al., 2008). One to four alleles per IT-locus were observed in a tetraploid potato genotype indicating polyploidy that prevents the calculation of a range of standard genetic statistics, including deviations from the Hardy– Weinberg principle and from linkage equilibriums (Thurlby et al., 2011). The level of calculated genetic diversity by the POPGENE program was lower than that of ATETRA analyzed data under MonteCarlo simulations. The reason for this discrepancy might be that POPGENE estimated the values under diploid and dominant marker condition, while the analyzed potato samples are auto tetraploid and tetrasomic in which the allelic combinations are produced in equal frequencies (Ronfort et al., 1998). The other non-potato species consisted of different ploidy level species from diploid to octaploid. It was proven that NGS-derived IT markers developed in one potato genotype can be effectively used in other cultivars, and they can be successfully transferred to the other distantly related Solanum species with different ploidy levels ranging from diploid to octaploid. The higher number of polymorphic IT markers in non-potato species compared to the potato genotypes (23 compared to 17 IT markers) might be due to genetics bottleneck phenomenon that occurred in domestication process of modern cultivated potato (Tanksley and McCouch, 1997). In another study, intron targeting makers from potato expressed sequence tags (ESTs) and NCBI database records were successfully applied for the detection of genetic variability in another solanaceaus species, S. nigrum, which is in consistence with our results (Poczai et al., 2010). The genetic diversity within and among populations of a collection of bittersweet (S. dulcamara), originating from different European countries, was also evaluated using conserved DNA-derived polymorphism (CDDP) and IT markers (Poczai et al., 2011). In our study, since all the expected products could be detected for all 40 analyzed loci, it seems the shared syntenies of the targeted sites as well as their sequence features are relatively conserved. Such conservation of priming sites flanking exon–intron junctions may result from similar gene content and order of solanaceous plants due to few genome rearrangements and duplications (Mueller et al., 2005). This allowed easy transfer of primers between species developed for potato (S. tuberosum) of sect. Petota to black nightshades (sect. Solanum) or even to kangaroo apples (sect. Archaesolanum). The genomes of analyzed species may be highly similar or very closely related (e.g. sect. Archaesolanum) and it is very likely that intron variability may increase
with taxonomic distance. However, the size of the conserved intervening sequences amplified by intron-targeting can be highly variable. This phenomenon may be valuable for generating functional markers directly related to gene regions and to facilitate the discovery of specific markers linked to a given phenotype. For further studies this observation could be important, since the high heterozygosity of potato cultivars and breeding lines may limit the cross-amplification of non-functional molecular markers. It is suggested that the novelNGS derived potato IT markers could potentially be utilized in phylogenetic studies of Solanum the largest genus that constitutes approximately half the species (~1400) in Solanaceae, and also in higher taxonomic levels. The developed markers could also be very useful for molecular studies of neglected and orphan solanaceous crops (e.g. S. scabrum), or for poorly known taxonomic groups of Solanaceae where further sequence information is needed. However, intron-targeting markers may be less polymorphic at intra-specific level (see Supplementary Tables 5 and 6) but they proved to be useful at inter-species differentiation. In general, intronic regions are more polymorphic than exonic ones, thus IT markers are increasingly used as fingerprinting tools, as it has been reported for example for species such as Rhododendron (De Keyser et al., 2009; Wei et al., 2005), Lolium, Festuca (Tamura et al., 2009) and species of the Rosaceae family (Sargent et al., 2009). Sequencing large number of genes in different crops suggested higher frequency of single nucleotide polymorphism (SNP) in intronic regions of genes (Ching et al., 2002; Rajesh and Muehlbauer, 2008). Hence, sequencing and multiple sequence alignment of the identified intron regions could also be used for SNP detection. Intron-targeting markers directly reflect variations that occurring within genes (Han et al., 2006), their localization in the potato genome would enhance the efficiency of molecular marker based breeding and the development of functional gene targeted markers. Generating transcriptome data where there is an available reference sequence has the advantage of the ability to localize the marker in the chromosome. The IT markers developed here were identified as locating to chromosomes I, II, III, IV, V, VI, VII, VIII, IX, XI and XII in potato genotypes, using SGN, and could be used as anchor markers in mapping studies. Representative sequence analysis of the amplified IT fragments in the Cin locus indicated the reliability of the designed IT primers, since all amplified fragments showed to be similar to the Cin reference sequence of the potato DM line. While among the potato cultivars for some alleles length polymorphism could not be detected on agarose gel, SNP-s clearly differentiated them. In the F1 genotypes no new alleles were observed, but all allelic sequence of them could also be found in the parents. Sequencing of the different sized IT fragments of the Cin locus proved the hypothesized specificity of the IT primers, and indicated that while the detection of length polymorphism is cheap, more allelic variations could be detected by SNP analysis of the IT products. The observed levels of polymorphisms and genetic diversity suggest that the developed markers are fully adequate for characterizing genetic variation and provide efficient tools for potato genetic studies, namely DNA fingerprinting, marker-assisted selection, genetic mapping and diversity analysis. Once a comprehensive transcriptome database is generated the number of NGS-derived IT markers that could be utilized for fine mapping and in various types of molecular analysis may rapidly increase. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2014.02.045. Conflict of interest There is no conflict of interest. Acknowledgments The authors are grateful to Dan Milbourne for editing of the manuscript. This research was supported by the OTKA (76485) fund of the Hungarian Academy of Sciences.
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Gene journal homepage: www.elsevier.com/locate/gene
Short Communication
Next generation sequencing based development of intron-targeting markers in tetraploid potato and their transferability to other Solanum species Rahim Ahmadvand a,b,c,⁎, Péter Poczai d, Ramin Hajianfar a,c, Balázs Kolics b, Ahmad Mousapour Gorji c, Zsolt Polgár a, János Taller b a
Potato Research Centre, Centre of Agricultural Sciences, University of Pannonia, H-8360 Keszthely, Festetics u. 7, Hungary Department of Plant Science and Biotechnology, Georgikon Faculty, University of Pannonia, H-8360 Keszthely, Festetics u. 7, Hungary c Seed and Plant Improvement Institute, Mahdasht Ave. 3185, Karaj, Iran d Department of Biosciences, University of Helsinki, PO Box 65, FIN-00014 Helsinki, Finland b
a r t i c l e
i n f o
Article history: Accepted 18 February 2014 Available online 26 February 2014 Keywords: Intron-targeting Molecular marker Next generation sequencing Potato Transcriptome analysis
a b s t r a c t Intron-targeting (IT) markers were developed from next generation sequencing (NGS) derived transcript sequencing data from the potato cultivar White Lady. The applicability of the IT markers was analyzed in other potato genotypes, and their transferability was studied in other Solanum species: section Archaesolanum (5 species), sect. Solanum (6 species) and a Solanum nigrum population (11 genotypes). Out of 250 randomly chosen transcript sequences, 144 intron harboring loci could be identified for which primer pairs were designed on exons flanking the putative introns. The usefulness of the IT primers was experimentally analyzed on a subset of 40 randomly chosen loci. Statistical analysis of diversity parameters was performed using the ATETRA and POPGENE software packages. By localizing the detected 17 polymorphic loci 11 of the 12 potato chromosomes could be identified. Specificity of the designed IT primers was tested by sequence analysis of amplified IT fragments in a randomly chosen locus. The results revealed the efficiency of NGS derived IT marker development and indicated their utility in diverse molecular analyses including their applicability for cross-species studies. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Potato is the world's most important non-grain food crop and plays a major role in global food security. Knowledge of the potato genome has increased dramatically over the last decade, and recent publication of the potato genome sequence has provided new insights to potato genetics (Potato Genome Sequencing Consortium). Detailed sequence
Abbreviations: IT, intron-targeting; NGS, next generation sequencing; RNA-Seq, RNA sequencing using NGS; Life Tech SOLiD, Life Technology-sequencing by oligonucleotide ligation and detection; NCBI, National Center for Biotechnology Information; SGN, Solanum Genomics Network; TC, transcriptome; SNP, single nucleotide polymorphism; SSR, simple sequence repeats; dNTP, deoxyribonucleoside triphosphate; BLASTN, Basic Local Alignment Search Tool-nucleotide; PCR, polymerase chain reaction; HC, heterozygosity corrected for sample size; Hc′, Shannon index corrected for sample size; h, expected heterozygosity or Nei's gene diversity; I, Shannon's information index of phenotypic diversity; HT, panmictic heterozygosity or total genetic diversity; HS, intra-population genetic diversity; FST, Wright's fixation index; CDDP, conserved DNA-derived polymorphism. ⁎ Corresponding author at: Potato Research Centre, Centre of Agricultural Sciences, University of Pannonia, H-8360 Keszthely, Festetics u. 7, Hungary. E-mail addresses: [email protected] (R. Ahmadvand), [email protected] (P. Poczai), [email protected] (R. Hajianfar), [email protected] (A.M. Gorji), [email protected] (Z. Polgár), [email protected] (J. Taller).
http://dx.doi.org/10.1016/j.gene.2014.02.045 0378-1119/© 2014 Elsevier B.V. All rights reserved.
information enables the development of functional markers, which are considered to be more effective for most molecular genetic studies than other marker types. An efficient method to generate genespecific markers for mapping in plants is the intron-targeting (IT) method (Choi et al., 2004). Introns are widespread and abundant in eukaryotic genomes and they possess variable amount of polymorphism. IT primers are complementary to the sequences of exons flanking the targeted intron. Since intron sequences are generally less conserved than exons, the amplified products may display polymorphism due to length/nucleotide variation among the introns alleles of the targeted gene. On the other hand, the higher level of sequence conservation in the exons ensures that all alleles can be effectively amplified. Advances in sequencing technology have enabled deep sequencing of complete transcriptomes (RNA-seq) (Clarke et al., 2009). Highthroughput transcriptome sequencing has the advantage to generate large transcript sequence data sets for gene discovery and molecular marker development. In the present study, the efficiency of the development of introntargeting markers from next generation sequencing (NGS) derived transcripts was analyzed, and in addition, the applicability and transferability of these IT markers to related potato and wild Solanum species with different ploidy levels was confirmed.
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2. Materials and methods
3. Results
2.1. Plant materials
3.1. Development of IT markers
Twenty four individuals of a tetraploid F1 population of a cross of the cultivar, White Lady and the breeding line S440, as well as 24 potato cultivars from different origins were involved in the analysis (Supplementary Table 1). To analyze the applicability of potato NGS derived IT markers in related Solanum species, three populations of wild Solanum species were also examined. The species and their ploidy level are listed in the Supplementary Table 2.
By the NGS sequencing more than 12 million reads were obtained, and each read had a maximum size of 50 nucleotides. From the reads 38 675 contigs (TC) could be constructed using the CLC Genomics Workbench software 4.8 (64 bit) version. Out of these, 250 contigs were randomly chosen and analyzed for the presence of introns using the NCBI as well as the SOL Genomics Network database, and 144 transcript sequences were identified as potentially harboring introns. Locus specific primer pairs were designed for each sequence, and 40 randomly chosen loci were experimentally analyzed for the assumed intron length polymorphisms. While for all 40 loci PCR products were obtained, 25 loci showed length polymorphism in the analyzed populations.
2.2. Development of NGS derived intron-targeting markers mRNA was extracted from young leaves of potato cultivar White Lady with RNAzol (MRC, USA). For NGS sequencing, the Life Tech SOLiD RNA Sequencing Kit (Life Technologies, USA) was used according to the manufacturer's recommendations. Sequencing was performed using a 5500xl SOLiD (Life Technologies, USA) sequencer. Sequence reads were assembled into contigs using the CLC Genomics Workbench 4.8 (64 bit) software. Genes for the generated transcript data set were identified, aligned and annotated with potato genome sequence (Potato Genome Sequencing Consortium, 2011) in NCBI database using BLASTn (nr and Whole-genome shotgun contigs) with the E-value 10−20 up to June 2012. The program Sim4 (Florea et al., 1998) was applied to align transcript sequences to the corresponding genes in potato in order to find putative intron regions. In addition, the SOL Genomics Network (Mueller et al., 2005) was used to predict intron regions. Introntargeting primers were designed on the exon sequences flanking the putative introns with the PRIMER3 v. 0.4.0 software (Rozen and Skaletsky, 2000). 2.3. Genomic DNA extraction and PCR amplification Total genomic DNA of all genotypes was isolated from young leaves using the method of Walbot and Warren (1988). Final volume of the PCR reaction mixture was 12 μl, with 40 ng DNA template, 0.5 μM of each primer, 2.0 mM dNTP (Fermentas, Lithuania), 1.5 μl of 10 × PCR Dream Taq Green Buffer provided by the manufacturer (Fermentas, Lithuania) and 0.1 μl of 5 U/μl Dream Taq DNA polymerase. The PCR conditions were as follows: 3 min 94 °C for initial denaturation, 35 cycles of 20 s denaturation at 94 °C, a 20 s annealing at the temperature indicated for each primer pair (Supplementary Table 3), 1 min extension at 72 °C and a final extension at 72 °C for 5 min. PCR products were separated on 1.5% agarose gel and visualized after ethidium–bromide staining with a GenGenius Bio Imaging System (Syngene, UK). The experiment was started with optimization of PCR conditions where for each primer pair a subset of individuals of each population was examined and the repeatability of amplified fragments was confirmed for each primer pair. In addition, the specificity of amplified fragments was examined in the randomly chosen Cin locus with sequencing and alignment in randomly chosen F1 and commercial cultivar individuals. 2.4. Data analysis The banding patterns were scored based on the size and presence/ absence of a sharp band. All genetic analyses were carried out under the assumption of the Hardy–Weinberg equilibrium. For all populations the POPGENE version 1.31 program (Yeh et al., 1997) designed for haploid and diploid data analysis was used. In addition, ATETRA v. 1.2 software (Van Puyvelde et al., 2010), designed to analyze tetraploid microsatellite data, was also applied to estimate the same genetic parameters. The SOL Genomics Network (SGN) was applied to determine the chromosomal location of each polymorphic intron marker.
3.2. IT length polymorphism in the potato genotypes Out of the 40 analyzed loci, 17 showed different levels of length polymorphism both in the F1 population and among the potato cultivars, while the remaining 23 were monomorphic. The number of alleles per locus ranged from 2 to 5 in both populations. Results of statistical analysis obtained with the ATETRA as well with the POPGENE software on heterozygosity are shown in the Supplementary Table 4. Because the analyzed potato cultivars originate from different genetic backgrounds, the observed diversity in the population of the 24 cultivars was high (HS = 0.24) (Table 1). 3.3. IT length polymorphism in the wild Solanum species All 40 IT primer pairs which were designed based on the potato transcriptome sequences resulted one or more PCR products in one, two or in all three wild Solanum groups. Out of the 40 analyzed loci, the number of polymorphic loci was 21 in sect. Archaesolanum, 22 in sect. Solanum and 16 in accessions of S. nigrum (Supplementary Table 5). The number of polymorphic bands per locus ranged from 2 to 10. Interestingly, while polymorphism could not be detected in the potato populations for the Mresis, Cad, Winsh, Str, PT11, Pe54, Cop12 and Cunf34 loci, they showed variation among wild Solanum species. On the other hand, for the LBR57 and RP3a loci, which were polymorphic in the potato populations, only a monomorphic band was observed among wild Solanums. The locus RPB36 displayed polymorphism only in Archaesolanum species. On the contrary, loci R1L333 and Winsh were only monomorphic in sect. Archaesolanum. Most of the IT markers amplified significant length variation among the three wild Solanum populations (Fig. 1; Supplementary Table 5). The overall Wright's fixation index (FST) across all wild Solanum population was 0.33 suggesting great population differentiations, which is not surprising as these groups represented distantly related lineages. Summary statistical data for the potato- and wild Solanum populations obtained with ATETRA and POPGENE are shown in Table 1. 3.4. Localization of the IT markers in the potato genome Using the Solanum Genomics Network database, the genomic location of 21 loci out of the 25 detected polymorphic IT markers was determined. These markers resided on potato chromosomes I to XII (Supplementary Table 3) the only exception being chromosome X. SGN-based map locations of the remaining 15 loci that were monomorphic in each populations are given in the Supplementary Table 6. 3.5. Specificity analysis of the amplified IT fragments Specificity of the amplified IT fragments was tested in the randomly chosen Cin locus by sequencing all IT fragments in 8 randomly chosen F1 genotypes (ID No. 85, 90, 95, 114, 286, 446, 442, 467), in their parents
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Table 1 Statistical summary of all populations using ATETRA software and POPGENE software. Marker
PKF11 LBR57 AVTPSH PGRSH RP3a35 NB89 PTA-83-1 RL333 ATP-218 Cin TSWVP TREPSH TRP77 Nitsh RPB36 Cat Mresis Cad Winsh Str PT11 Pe54 Antiv1 Cop12 Cunf34 Mean
No. of individuals
48 22 48 48 22 48 22 48 48 22 48 22 48 22 48 22 48 22 48 22 48 22 48 48 21 48 22 48 20 48 22 48 13 48 22 48 20 48 22 48 20 48 21 48 21 48 21
Genotype
F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum F1 & cultivars Wild Solanum
ATETRA analysis
POPGENE analysis
Hc
H′c
h
I
HT
HS
Fst
0.51 0.83 0.73 –a 0.70 0.80 0.78 0.55 0.75 – 0.51 0.68 0.65 0.75 0.52 0.15 0.57 0.42 0.66 0.80 0.59 0.50 0.66 0.44 0.51 0.80 0.42 0.79 0.41 0.19 0.10 0.60 – 0.47 – 0.58 – 0.65 – 0.46 – 0.61 – 0.78 0.74 0.83 – 0.77 – 0.88 0.58 0.62
0.91 1.86 1.20 – 1.21 1.63 1.19 1.46 1.34 – 0.84 1.55 1.13 1.50 0.94 0.71 1.06 0.90 1.18 1.53 1.04 0.69 1.05 0.91 0.89 1.57 0.73 2.22 0.60 0.92 0.21 1.81 – 0.65 – 0.98 – 1.06 – 0.92 – 1.01 – 1.67 1.15 1.34 – 1.67 – 1.70 0.98 1.32
0.20 0.25 0.40 – 0.24 0.18 0.45 0.25 0.35 – 0.22 0.20 0.33 0.33 0.18 0.05 0.27 0.20 0.26 0.35 0.26 0.30 0.15 0.13 0.13 0.24 0.19 0.16 0.32 0.14 0.05 0.13 – 0.23 – 0.31 – 0.25 – 0.18 – 0.24 – 0.19 0.34 0.31 – 0.19 – 0.23 0.26 0.22
0.33 0.38 0.59 – 0.37 0.30 0.64 0.39 0.53 – 0.37 0.34 0.48 0.49 0.27 0.11 0.42 0.33 0.40 0.52 0.39 0.48 0.21 0.23 0.21 0.38 0.31 0.28 0.49 0.27 0.11 0.24 – 0.32 – 0.48 – 0.34 – 0.30 – 0.36 – 0.32 0.52 0.47 – 0.32 – 0.39 0.39 0.35
0.20 0.25 0.40 – 0.24 0.18 0.45 0.28 0.35 – 0.38 0.21 0.34 0.37 0.18 0.06 0.27 0.24 0.26 0.38 0.26 0.37 0.15 0.12 0.13 0.23 0.20 0.17 0.32 0.20 0.05 0.14 – 0.25 – 0.39 – 0.25 – 0.15 – 0.27 – 0.20 0.34 0.31 – 0.20 – 0.24 0.27 0.24
0.19 0.15 0.38 – 0.17 0.17 0.40 0.17 0.32 – 0.35 0.19 0.33 0.16 0.17 0.04 0.25 0.13 0.21 0.11 0.24 0.13 0.08 0.11 0.08 0.17 0.19 0.12 0.31 0.15 0.05 0.12 – 0.12 – 0.21 – 0.13 – 0.13 – 0.21 – 0.18 0.33 0.29 – 0.14 – 0.18 0.24 0.15
0.05 0.40 0.05 – 0.29 0.06 0.11 0.39 0.09 – 0.08 0.10 0.03 0.57 0.06 0.33 0.07 0.46 0.19 0.71 0.08 0.65 0.47 0.08 0.38 0.26 0.05 0.29 0.03 0.25 0.00 0.14 – 0.52 – 0.46 – 0.48 – 0.13 – 0.22 – 0.10 0.03 0.06 – 0.30 – 0.25 0.13 0.33
HC: Heterozygosity corrected for sample size; Hc′: Shannon index corrected for sample size; h: Expected heterozygosity or Nei's gene diversity; I: Shannon's information index of phenotypic diversity; HT: panmictic heterozygosity or total genetic diversity; HS: intra-population genetic diversity; FST: Wright's fixation index; a: Monomorphic.
(White Lady and S440), as well as in the randomly chosen cultivars Ditta, Katica, Agria, Franciella and Bzura (Supplementary Table 7.). Similarity of the sequenced fragments indicated that all the detected IT
fragments represent the Cin locus. The number of detected alleles was between 2 and 4. Besides the indels all alleles in each genotype could also be distinguished by SNP-s. All allelic sequences of the F1 genotypes
Fig. 1. Polymorphism pattern of wild Solanum populations using PKF11 primer pairs in 1.5% agarose gel. Samples: M: 100 bp plus DNA ladder, lanes 1–5: sect. Archaesolanum species, lanes 6–11: sect. Solanum species, lanes 12–22: S. nigrum individuals.
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were present also in the parents, while SNP-s could be detected among the alleles of the cultivars which showed to be same size in an agarose gel.
4. Discussion Due to the presence of highly repetitive transposable elements and paralogous sequences, especially in polyploid species, plant genome sequences are complicated. Therefore, detection of genetic variation via NGS has mainly been focused on transcript sequences (Deschamps and Campbell, 2010). Although single nucleotide polymorphism (SNP) and simple sequence repeats (SSR) are commonly identified by NGS, IT markers can serve as a suitable alternative due to their simple detection (agarose-based), locus specificity, co-dominant nature and efficiency in covering the genome. Considering that transcript sequences of the tetraploid cultivar were annotated based on their similarity to the published potato genome sequence, which is from a Solanum tuberosum group Phureja doubled monoploid line (PGS Consortium, 2011), the identification of 144 intron harboring genes out of 250 randomly chosen sequences reveals the efficiency of our strategy. It should also be emphasized that cultivated potato is highly heterozygous and the cultivar White Lady has also different wild potato ancestors, including S. stoloniferum, S. acaule, S. demissum and S. tuberosum subsp. andigena. The intron marker Cat-in2 was developed earlier to localize the Rysto gene in the potato genome (Cernak et al., 2008). One to four alleles per IT-locus were observed in a tetraploid potato genotype indicating polyploidy that prevents the calculation of a range of standard genetic statistics, including deviations from the Hardy– Weinberg principle and from linkage equilibriums (Thurlby et al., 2011). The level of calculated genetic diversity by the POPGENE program was lower than that of ATETRA analyzed data under MonteCarlo simulations. The reason for this discrepancy might be that POPGENE estimated the values under diploid and dominant marker condition, while the analyzed potato samples are auto tetraploid and tetrasomic in which the allelic combinations are produced in equal frequencies (Ronfort et al., 1998). The other non-potato species consisted of different ploidy level species from diploid to octaploid. It was proven that NGS-derived IT markers developed in one potato genotype can be effectively used in other cultivars, and they can be successfully transferred to the other distantly related Solanum species with different ploidy levels ranging from diploid to octaploid. The higher number of polymorphic IT markers in non-potato species compared to the potato genotypes (23 compared to 17 IT markers) might be due to genetics bottleneck phenomenon that occurred in domestication process of modern cultivated potato (Tanksley and McCouch, 1997). In another study, intron targeting makers from potato expressed sequence tags (ESTs) and NCBI database records were successfully applied for the detection of genetic variability in another solanaceaus species, S. nigrum, which is in consistence with our results (Poczai et al., 2010). The genetic diversity within and among populations of a collection of bittersweet (S. dulcamara), originating from different European countries, was also evaluated using conserved DNA-derived polymorphism (CDDP) and IT markers (Poczai et al., 2011). In our study, since all the expected products could be detected for all 40 analyzed loci, it seems the shared syntenies of the targeted sites as well as their sequence features are relatively conserved. Such conservation of priming sites flanking exon–intron junctions may result from similar gene content and order of solanaceous plants due to few genome rearrangements and duplications (Mueller et al., 2005). This allowed easy transfer of primers between species developed for potato (S. tuberosum) of sect. Petota to black nightshades (sect. Solanum) or even to kangaroo apples (sect. Archaesolanum). The genomes of analyzed species may be highly similar or very closely related (e.g. sect. Archaesolanum) and it is very likely that intron variability may increase
with taxonomic distance. However, the size of the conserved intervening sequences amplified by intron-targeting can be highly variable. This phenomenon may be valuable for generating functional markers directly related to gene regions and to facilitate the discovery of specific markers linked to a given phenotype. For further studies this observation could be important, since the high heterozygosity of potato cultivars and breeding lines may limit the cross-amplification of non-functional molecular markers. It is suggested that the novelNGS derived potato IT markers could potentially be utilized in phylogenetic studies of Solanum the largest genus that constitutes approximately half the species (~1400) in Solanaceae, and also in higher taxonomic levels. The developed markers could also be very useful for molecular studies of neglected and orphan solanaceous crops (e.g. S. scabrum), or for poorly known taxonomic groups of Solanaceae where further sequence information is needed. However, intron-targeting markers may be less polymorphic at intra-specific level (see Supplementary Tables 5 and 6) but they proved to be useful at inter-species differentiation. In general, intronic regions are more polymorphic than exonic ones, thus IT markers are increasingly used as fingerprinting tools, as it has been reported for example for species such as Rhododendron (De Keyser et al., 2009; Wei et al., 2005), Lolium, Festuca (Tamura et al., 2009) and species of the Rosaceae family (Sargent et al., 2009). Sequencing large number of genes in different crops suggested higher frequency of single nucleotide polymorphism (SNP) in intronic regions of genes (Ching et al., 2002; Rajesh and Muehlbauer, 2008). Hence, sequencing and multiple sequence alignment of the identified intron regions could also be used for SNP detection. Intron-targeting markers directly reflect variations that occurring within genes (Han et al., 2006), their localization in the potato genome would enhance the efficiency of molecular marker based breeding and the development of functional gene targeted markers. Generating transcriptome data where there is an available reference sequence has the advantage of the ability to localize the marker in the chromosome. The IT markers developed here were identified as locating to chromosomes I, II, III, IV, V, VI, VII, VIII, IX, XI and XII in potato genotypes, using SGN, and could be used as anchor markers in mapping studies. Representative sequence analysis of the amplified IT fragments in the Cin locus indicated the reliability of the designed IT primers, since all amplified fragments showed to be similar to the Cin reference sequence of the potato DM line. While among the potato cultivars for some alleles length polymorphism could not be detected on agarose gel, SNP-s clearly differentiated them. In the F1 genotypes no new alleles were observed, but all allelic sequence of them could also be found in the parents. Sequencing of the different sized IT fragments of the Cin locus proved the hypothesized specificity of the IT primers, and indicated that while the detection of length polymorphism is cheap, more allelic variations could be detected by SNP analysis of the IT products. The observed levels of polymorphisms and genetic diversity suggest that the developed markers are fully adequate for characterizing genetic variation and provide efficient tools for potato genetic studies, namely DNA fingerprinting, marker-assisted selection, genetic mapping and diversity analysis. Once a comprehensive transcriptome database is generated the number of NGS-derived IT markers that could be utilized for fine mapping and in various types of molecular analysis may rapidly increase. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2014.02.045. Conflict of interest There is no conflict of interest. Acknowledgments The authors are grateful to Dan Milbourne for editing of the manuscript. This research was supported by the OTKA (76485) fund of the Hungarian Academy of Sciences.
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