Journal of Heredity Advance Access originally published online on June 30, 2005
Journal of Heredity 2005 96(5):529-535; doi:10.1093/jhered/esi069
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Discovery of SNPs in Soybean Genotypes Frequently Used as the Parents of Mapping Populations in the United States and Korea
From the Department of Plant Science, Seoul National University, Seoul 151-921, Republic of Korea (Van, Hwang, Kim, and Lee); Biosafety Division, National Institute of Agricultural Biotechnology, Suwon 441-707, Republic of Korea (Park); and Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD 20705 (Hwang and Cregan)
Address correspondence to S.-H. Lee at the address above, or e-mail: sukhalee{at}snu.ac.kr.
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Abstract |
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Single nucleotide polymorphisms (SNPs) including insertion/deletions (indels) serve as useful and informative genetic markers. The availability of high-throughput and inexpensive SNP typing systems has increased interest in the development of SNP markers. After fragments of genes were amplified with primers derived from 110 soybean GenBank ESTs, sequencing data of PCR products from 15 soybean genotypes from Korea and the United States were analyzed by SeqScape software to find SNPs. Among 35 gene fragments with at least one SNP among the 15 genotypes, SNPs occurred at a frequency of 1 per 2,038 bp in 16,302 bp of coding sequence and 1 per 191 bp in 16,960 bp of noncoding regions. This corresponds to a nucleotide diversity (
) of 0.00017 and 0.00186, respectively. Of the 97 SNPs discovered, 78 or 80.4% were present in the six North American soybean mapping parents. The addition of "Hwaeomputkong," which originated from Japan, increased the number to 92, or 94.8% of the total number of SNPs present among the 15 genotypes. Thus, Hwaeomputkong and the six North American mapping parents provide a diverse set of soybean genotypes that can be successfully used for SNP discovery in coding DNA and closely associated introns and untranslated regions.
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Introduction |
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TopAbstractIntroductionMaterials and MethodsResults and DiscussionReferences |
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The development of DNA-based markers is important for selection and improvement of varieties and hybrids in plant breeding programs (Gupta et al. 2001; Kota et al. 2003). Single nucleotide polymorphisms (SNPs) including insertion/deletions (indels) can provide a rich source of useful molecular markers in genetic analysis. In the human genome, about 90% of sequence variants are SNPs. In some instances, these SNPs are actually the causal mutations of genetic diseases, such as cystic fibrosis (Kuppuswamy et al. 1991; Collins et al. 1998; Brookes 1999; Kwok and Gu 1999). SNPs are the most abundant type of sequence variation in plant genomes also (Cho et al. 1999). Much progress has been made in the discovery of sequence diversity in crop plants. The frequency of SNPs in maize (Zea mays ssp. mays L.) was reported as 1 SNP per 104 bp (Tenaillon et al. 2001). A total of 112 SNPs were found at 38 of 54 loci in barley (Hordeum vulgare L.) (Kanazin et al. 2002). Recently, a total of 280 SNPs were discovered among 25 diverse soybean (Glycine max L. Merr.) genotypes in more than 76 kb of sequence of polymerase chain reaction (PCR) products amplified using primers designed for 116 genes and 27 nongenic regions (Zhu et al. 2003). Additionally, many SNP detection methods have been developed, such as denaturing high-performance liquid chromatography (DHPLC), oligonucleotide ligation, primer extension, DNA sequencing, PCR primer mismatch, pyrosequencing, and heteroduplex assays (Wu and Wallance 1989; Kuppuswamy et al. 1991; Ronaghi et al. 1998; Hoogendoorn et al. 1999; Pastinen et al. 2000; Wolford et al. 2000; Ye et al. 2001).
Because SNPs can be analyzed using high-throughput and inexpensive systems, they are useful for construction of high-density genetic maps as well as for genetic association studies (Cho et al. 1999; Picoult-Newberg et al. 1999; Nairz et al. 2002; Rafalski 2002; Kota et al. 2003). The relatively high level of linkage disequilibrium (LD) that would be anticipated in self-fertilizing plant species such as soybean (Zhu et al. 2003) may permit whole genome scans using SNPs for QTL discovery. In contrast, the lower levels of LD in outcrossing species such as maize (Zea mays sp. mays L.) (Tenaillon et al. 2001) will require the use of the candidate gene approach to discover the specific gene(s) underlying phenotypic changes (Rafalski 2002).
Mutations in coding DNA sequences (cSNPs) may change amino acid sequences and affect gene function and could therefore be valuable as markers (Collins et al. 1998; Brookes 1999; Marth et al. 1999; Picoult-Newberg et al. 1999). Expressed sequence tag (EST) data serve as a useful source of DNA sequences in which SNPs can be discovered. The Soybean EST Project database contained more than 342,000 publicly available ESTs from 84 libraries (www.ncbi.nlm.nih.gov/dbest/dbest_summary.html) as of December 2004. This resource provides an excellent source for the development of gene-derived SNP markers.
This study reports results from the screening of 110 soybean EST-derived PCR primer pairs to identify and compare SNPs in nine cultivated soybean genotypes from Korea (Van et al. 2004) and six parents of North American mapping populations that were previously analyzed for their sequence diversity (Zhu et al. 2003). Thus, an important objective of this research was the identification of a subset of soybean genotypes that can maximize the discovery of SNPs in coding and noncoding perigenic DNA.
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Materials and Methods |
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TopAbstractIntroductionMaterials and MethodsResults and DiscussionReferences |
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Plant Materials and Genomic DNA Extraction
A set of 15 soybean genotypes was used for SNP discovery. Nine Korean cultivated genotypes were included: Sinpaldalkong 2, SS2-2, Danbaekkong, Taekwangkong, Jinpumkong 2, Pureunkong, Daewonkong, Dongsan 163, and Hwaeomputkong (Van et al. 2004). These cultivated genotypes not only these possess interesting phenotypes (Van et al. 2004) but also are the parents of various recombinant inbred line mapping populations in Korea.
Six additional lines, including "Archer," PI 209332, "Peking," "Minsoy," Noir 1, and "Evans" (Table 1) that have been used as the parents of mapping populations in the United States (Mansur et al. 1996; Concibido et al. 1997; Mudge et al. 1997; Cregan et al. 1999; Orf et al. 1999; Qiu et al. 1999) were also included. The six North American genotypes had previously been identified by Zhu et al. (2003) as a good subset of genotypes for SNP discovery because the sequence analysis of these six genotypes identified 85% of the total SNPs and 93% of the common SNPs (frequency > 0.1) discovered in a larger set of 25 genotypes. Van et al. (2004) described method of genomic DNA extractions from the 15 homozygous soybean genotypes.
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Designing and Testing of PCR Primers
After a total of 110 soybean ESTs were selected from GenBank, designing primers were followed by Van et al. (2004). Lists of selected soybean ESTs and their primer information are available in Van et al. (2004). Each PCR primer set was used to amplify genomic DNA of Sinpaldalkong 2 for testing. PCRs were performed in a 50 µl volume with 2 U Taq DNA polymerase (Vivagen, Sungnam, Korea) following the manufacturer's recommended protocols and cycling conditions. Gel electrophoresis on an ethidium bromide–stained 1.0% agarose gel confirmed the presence of amplified products. The primer sets that produced a single amplicon with Sinpaldalkong 2 genomic DNA were selected and used in identical amplification reactions with the other 14 soybean genotypes using the same conditions just described.
Purification and Sequence Analysis of PCR Products
After PCR amplicons were purified using NucleoSpin Extract (Machery-Nagel, Düren, Germany), one of the primers used in the PCR amplification was used as the primer in the sequencing reaction. Sequence analysis was performed for all 15 cultivars using BigDye Terminator Cycle Sequencing (Applied Biosystems, Forster City, CA) as described by Kim et al. (2004). The sequencing reaction mixture was ethanol-precipitated and resuspended in 10 µl water, and an ABI 3700 sequencer (Applied Biosystems) was used for the sequence analysis.
SNP Survey and Nucleotide Diversity ()
With default conditions for "basecaller" and ending base, mixed-base settings, clear range methods, and filter settings, ABI trace files were aligned and mutations were identified using ABI Prism SeqScape Software version 2.0 (Applied Biosystems), for detection of SNPs among the 15 soybean cultivars (Van et al. 2004).
Calculations of nucleotide diversity () were followed by Halushka et al. (1999):
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Results and Discussion |
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TopAbstractIntroductionMaterials and MethodsResults and DiscussionReferences |
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Single nucleotide changes in coding regions can lead to alteration of amino acid sequences or early termination of translation and can therefore affect gene function (Brookes 1999; Collins et al. 1998; Marth et al. 1999; Picoult-Newberg et al. 1999). These functional SNPs would be valuable markers if the altered gene function or altered phenotype was of value for breeding purposes. However, even SNPs that do not alter the amino acid sequence but that are in or near a gene can be very useful as genetic markers. Thus, our SNP discovery research in soybean was focused on gene fragments amplified using PCR primers designed to EST sequences using 15 different genotypes (Table 1). These genotypes are the parents of soybean recombinant inbred line mapping populations that have been used in Korea or the United States.
Among 110 randomly chosen soybean ESTs from GenBank for which primers were designed (Van et al. 2004), only 70% of them amplified a single PCR product and high-quality sequence data were obtained from only 60% of the 110 primer sets. This was likely the result of two or more amplicons of similar size but with slightly different sequences (Van et al. 2004).
Characterizations of SNPs discovered in all fifteen genotypes as well as in the subsets of mapping parents from Korea and the United States are presented in Table 2. A total of 16,302 bp of coding sequence, 7,372 bp of 5' UTR, 6,659 bp of intron and 2,929 bp of 3' UTR were surveyed. At least 1 SNP was discovered in 35 of the 66 gene fragments for which data were obtained. The analysis of the complete set of 15 genotypes indicated that that SNPs occurred at a frequency of 1 per 2,038 bp ( = 0.00017) and 1 per 191 bp ( = 0.00186), in coding and noncoding regions, respectively.
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A total of 97 SNPs, including 8 indels, were discovered in the 15 genotypes, but the number of SNPs discovered was less within either the Korean or North American groups of mapping parents (Table 2). The SNP frequency was higher in noncoding regions in both the Korean and U.S. mapping parents. Among the Korean lines, 1 SNP occurred every 3,260 bp in coding sequence and every 278 bp in noncoding sequence. A total of 66 polymorphisms were discovered, and the overall frequency of SNPs was 1 every 504 bp (Van et al. 2004). Among the U.S. soybean mapping parents, frequencies of SNPs in both coding and noncoding regions were greater than among the Korean cultivars. The distribution of minor allele frequencies in all 15 genotypes is given in Figure 1. Of 97 SNPs, 67 SNPs (69%) could be classified as common, occurring at a frequency greater than 0.10. In contrast to the nucleotide diversity (
) reported in maize (Tenaillon et al. 2001), the 15 cultivars had about a ninefold lower diversity ( = 0.00103) in the 33,262 bp of sequenced amplicons. A similar result was reported by Zhu et al. (2003). As would be anticipated, the frequency of single base substitutions or indels was higher in the 15 cultivars versus within either the Korean or North American subpopulations. The Korean soybean lines had slightly lower nucleotide diversity than the six U.S. mapping parents.
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In humans, about 2/3 of the SNP types are transitions (purine to purine or pyrimidine to pyrimidine) and about 1/3 are transversions (purine/pyrimidine) (Wang et al. 1998; Brookes 1999). Our study showed a similar ratio of transitions to transversions among the 15 genotypes. However, there was a relative greater proportion of transitions over transversions within the American soybean mapping parents. This result contrasts with Zhu et al. (2003), who reported essentially equal numbers of transitions and transversions. A summary of single and multiple nucleotide substitutions as well as single and multiple base indels is presented in Table 3. Three examples of triallelic SNPs were discovered, and a number of dinucleotide and trinucleotide SNPs were observed. One-, two-, and six-base indels were also detected (Table 3). A relatively small number of indels were observed, and these were all in noncoding DNA (Table 2).
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Because the set of six diverse North American genotypes, Archer, PI 209332, Peking, Minsoy, Noir 1, and Evans, was identified by Zhu et al. (2003) as the minimum needed to maximize the discovery of sequence variation in the United States, each of the Korean lines was added to this set to determine if a significant increase in SNP discovery would result (Table 4). The number of SNPs discovered by adding either Pureunkong or Hwaeomputkong to the set of six U.S. mapping parents is presented in Table 4. Adding Pureunkong resulted in an increase in total SNPs discovered from 78 to 84 (86.6% of the total SNPs). The addition of Hwaeomputkong increased the number of SNPs discovered from 78 to 92 (94.8% of the total SNPs), suggesting that the addition of Hwaeomputkong as a seventh genotype would clearly increase the efficiency of SNP discovery in soybean.
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There were five gene fragments in which Hwaeomputkong-specific SNPs were discovered. The length of the amplified regions (5' UTR, exon, intron, or 3' UTR), the sequenced length of each gene fragment, the position of the mutation and the allele present in Hwaeomputkong as well as in the six U.S. mapping parents is presented in Table 5. The allele present in two genotypes, PI 209332 and Minsoy, could not be determined in GenBank accession number AF327903 (functional candidate resistance protein, KR1) despite several sequencing attempts. Of the 32 gene fragments in which SNPs were discovered in this subset of 7 genotypes, 14 had a single SNP and multiple SNP loci were detected in the remainder (data not shown). Interestingly, AJ003246 [GenBank] (putatively encoding 2-hydroxydihydrodaidzein reductase) contained 12 SNPs and 1 indel in these seven mapping parents (Table 5). Eight SNP loci were discovered in the exon in these seven genotypes (data not shown). In the coding region, five synonymous changes were identified as well as three nonsynonymous changes each of which had a single base substitution in the first position. Boldface characters in Table 5 indicate the additional SNPs discovered by the inclusion of Hwaeomputkong as the seventh genotype. Among 13 SNP loci unique to Hwaeomputkong, 9 were discovered in just one GenBank accession (AJ003246). These SNPs unique to Hwaeomputkong suggested that it is genetically distinct from the U.S. mapping parents at six SNP fragments because one small fragment had 8 of 13 SNPs. Phenotypic characteristics of Hwaeomputkong (including early maturity, short plant height, and large seed size) as well as its use as a vegetable soybean also suggest that this genotype is very unique among the nine Korean mapping parents.
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In summary, we identified a total of 97 SNPs from 110 soybean genes in all 15 soybean genotypes. These data indicated the presence of abundant sequence diversity in the soybean cultivars assayed. The North American mapping parents showed greater genetic diversity than the Korean mapping parents. The addition of Hwaeomputkong to the six parents of the North American mapping populations increased the number of SNPs discovered from to 78 to 92. Thus, these seven genotypes could be helpful for discovery of cSNPs and gene-targeted map constructions. If these and other SNPs were determined to be the causal mutations associated with phenotypic traits, the development of these functional markers could lead to the errorless marker assisted selection in soybean breeding.
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Acknowledgments |
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This work was supported by a grant (code number CG3121) from Crop Functional Genomic Center of the 21st Century Frontier Research Program funded by the Ministry of Science and Technology and Rural Development Administration of the Republic of Korea. We thank National Instrumentation Center for Environmental Management at Seoul National University in Korea.
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Footnotes |
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Corresponding Editor: J. Perry Gustafson
Received January 4, 2005
Accepted March 31, 2005
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