J Plant Biotechnol 2016; 43(2): 174-180
Published online June 30, 2016
https://doi.org/10.5010/JPB.2016.43.2.174
© The Korean Society of Plant Biotechnology
Correspondence to : e-mail: artemisia@korea.kr
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Licorice plant (
Keywords
Our experimental focus for this study was to analyze the genetic relationship between the collections of licorice plant (
Divergence of wild populations has been analyzed using several molecular markers. Molecular genetic diversity studies for
A total of 22
Table 1
No. | Sample name | ?Species | Location |
---|---|---|---|
1 | 1A | KOR | |
2 | 1B | ˝ | |
3 | 1C | ˝ | |
4 | 2A | CAN | |
5 | 2B | ˝ | |
6 | 2D | ˝ | |
7 | 2E | ˝ | |
8 | 3A | MNG | |
9 | 3C | ˝ | |
10 | 3E | ˝ | |
11 | 4C | MNG | |
12 | 5A | MNG | |
13 | 5B | ˝ | |
14 | 5C | ˝ | |
15 | 5D | ˝ | |
16 | 5E | ˝ | |
17 | 6A | UZB | |
18 | 6B | ˝ | |
19 | 7A | CHN | |
20 | 7B | ˝ | |
21 | 7C | ˝ | |
22 | 7E | ˝ |
KOR, Korea; CAN, Canada; MNG, Mongolia; UZB, Uzbekistan; CHN, China
All available
Table 2 Statistics on EST sequences in
????Contents | Numbers |
---|---|
Total number of sequences downloaded | 56,089 |
Total size of downloaded sequences (bp) | 26,955,389 |
Number of cleaned EST sequences | 55,942 |
Total number of sequences examined | 4,821 |
Total number of identified SSRs | 5,536 |
Number of SSRs containing sequences | 3,053 |
Number of sequences containing more than one EST-SSR | 1,484 |
A total of 4,821 unigenes obtained from the assembly were subjected to SSRIT to identify SSRs (Temnykh et al. 2001) and to design primers using Primer3 (Koressaar and Remm 2007; Untergrasser et al. 2012). The default settings of the program were used with some adjustments: product size 250 ~ 500 bp, optimum 300 bp; primer size 18 ~ 25 nt, optimum 22 nt; primer Tm 55 ~ 60°C, optimum 57°C; primer GC content 40 ~ 60%, optimum 50%. Single PCRs were carried out for the 22 accessions with 8 EST-based microsatellite primers. The PCR mix contained 2 pmol and FAM-labelled primers and 2 pmol of the forward primer in a 25 ml reaction volume with 2.5 ml PCR buffer, 0.2 mM dNTPs, 2 mM MgCl2, 50 ~ 100 ng template DNA, and 1 U Taq DNA polymerase. Conditions for all PCR amplifications were as follows: 94°C for 5 min, then 30 cycles of 94°C for 30 s, 58°C for 45 s and 72°C for 45 s, final extension at 72°C for 10 min. PCR products were separated in a 2.0% agarose gel to visualize PCR amplification. PCR primer sets used in these experiments are listed in Table 2. Forward primers were labeled with a virtual dye 6-FAM, NED, VIC or PET (Applied Biosystems). After PCR amplification, 0.2 ml of PCR products was mixed with 9.8 ml Hi-Di formamide (Applied Biosystems) and 0.2 ml of GeneScanTM 500 LIZ? size standard (Applied Biosystems, Foster City, CA, USA). The mixture was denatured at 95°C for 5 min and placed on ice. The amplified fragments were separated by capillary electrophoresis on the ABI 3730 DNA analyzer (Applied Biosystems) using a 50-cm capillary with a DS-33 install standard as a matrix. We analyzed the amplicon size using the GeneMapper software (version 4.0; Applied Biosystems).
For each accession, fragments amplified with the EST-based microsatellite markers were scored as present (1) or absent (0). Genetic parameters including major allele frequency (MAF), number of alleles (NA), genetic diversity (GD), expected heterozygosity (HE), and polymorphic information content (PIC) were measured by calculating the shared allele frequencies using the PowerMarker software (version 3.25) (Liu and Muse 2005). The data were then used to compute the PIC value for each polymorphic marker fragment according to the formula: PICi = 2fi (1-fi) where fi is the frequency of band presence (Rold?n-Ruiz et al. 2000). The correlation of geographic and genetic distances from principal coordinate analysis (PCoA) was performed using NTSYS software v. 2.2 (Rohlf 2000; Rohlf 2004). A dendrogram was made using unweighted neighbour-joining method. Bootstrap analysis was performed with 1,000 replications. Mantel’s test was used to determine the correlation of the dissimilarity matrix and the dendrogram.
A total of 56,089 EST sequence reads from a publicly available
Hexa-nucleotide repeats ranked in highest abundance, accounting for 63.78% of the SSRs. Hepta-, di-, and tri- nucleotide repeats were next in abundance, accounting for 10.77, 8.27, and 6.97% of the SSRs. Penta-, octa-, nona-, and tetra-nucleotide repeats were rarer (2.87, 2.87, 2.82, and 1.28 %, respectively), and deca-nucleotides together accounted for less than 1% of the identified SSRs. Among di-nucleotide repeats, (AG/CT)n accounted for 44.71% of di-nucleotide repeats (Table 3). Among tri-nucleotide repeats, (GAA/TTC)n and (AGA/TCT)n were the most abundant repeat motifs and represented 10.37 and 10.16% of tri-nucleotides, respectively. Among the tetra-nucleotide repeats, (CAAG/CTTG)n was most abundant, with each accounting for 11.89% of the tetra-nucleotides. Only one motif (CATAC/GTATG)n accounted for 17.96% of hepta-nucleotides (Table 4).
Table 3 Frequencies of microsatellite repeat by type in the
???Repeat types | Number of SSRs | Proportion of all SSRs (%) |
---|---|---|
Dinucleotide | 458 | 8.27 |
Trinucleotide | 386 | 6.97 |
Tetranucleotide | 71 | 1.28 |
Pentanucleotide | 159 | 2.87 |
Hexanucleotide | 3,531 | 63.78 |
Hepta-nucleotide | 596 | 10.77 |
Octa-nucleotide | 159 | 2.87 |
Nona-nucleotide | 156 | 2.82 |
Deca-nucleotide | 20 | 0.36 |
Total | 5,536 | 100.00 |
Table 4 The most abundant microsatellite motifs in the EST database. Only motifs accounting for 5% or more of each repeat type (i.e. di-, tri-, tetra-nucleotide, etc.) are included
?SSR type | ?SSR motif | Number of SSR motifs | Percentage of SSR motif |
---|---|---|---|
Di-nucleotide | AG/CT | 1,421 | 44.71 |
GA/TC | 903 | 28.41 | |
AC/GT | 355 | 11.17 | |
CA/TG | 241 | 7.58 | |
AT/AT | 169 | 5.32 | |
Tri-nucleotide | GAA/TTC | 300 | 10.37 |
AGA/TCT | 294 | 10.16 | |
ACA/TGT | 226 | 7.81 | |
AAG/CTT | 224 | 7.74 | |
AAC/GTT | 178 | 6.15 | |
CAA/TTG | 168 | 5.81 | |
CAC/GTG | 147 | 5.08 | |
Tetra-nucleotide | CAAG/CTTG | 61 | 11.89 |
AAAT/ATTT | 47 | 9.16 | |
AAAC/GTTT | 28 | 5.46 | |
TATG/CATA | 27 | 5.26 | |
Penta-nucleotide | CATAC/GTATG | 201 | 17.96 |
Marker evaluation and polymorphism detection
A total of 125 primer pairs were designed from di- to tetra- nucleotide EST-SSRs. The EST-SSR primers were selected based on high G/C content, melting temperature of 55 ~ 60°C. These primers were tested on a subset of
Table 5 Primers used for
Marker | Accession No. | SSR Modif. | SSR specific primer (5’→3’) | Product size (bp) | |
---|---|---|---|---|---|
Forward | Reverse | ||||
GlySSR1 | FS239000 | (tatg)5 | GACTGGAATCTCAAACGCAATA | AAAATCAAAGCGTGACCAGATA | 330-352 |
GlySSR2 | FS239076 | (ttctc)6…(aag)7 | TTCTTTGACTCACTCACCCCTA | AGTGATTCACGAGTTCATCGTC | 260-291 |
GlySSR3 | FS239091 | (gaat)6 | CGGTATAGCGTGGTAGTCTGAG | TTTTTGAAGCTGTTGAATGGTT | 287-341 |
GlySSR4 | FS239392 | (catggg)9 | CTGTTTTCCCCTGTTTTCTTCT | TCTGTTGCTCCTCTGTTTGAGT | 260-290 |
GlySSR5 | FS239689 | (ag)18 | TTGCGAGTGAGAGGAAGTTAAG | CCAGAGTACACACGATTTTGGT | 382-407 |
GlySSR7 | FS240731 | (ag)18 | CCAAGGAATTAGAACTGCGACT | AGTGCCATGAGAGAAGTTGAAA | 270-311 |
GlySSR10 | FS238963 | (aac)6…(tgg)6 | ATGGCAGGTATCATTCACAAGAT | TGTCCTTGATCTTCTCCACAAAC | 332-344 |
GlySSR11 | FS238990 | (gga)7 | GTAATGCCGTTGGAGGATGAC | AGGGCAGAATCTAAGTGCAGAA | 352-375 |
Table 6 Characteristics of 8 polymorphic microsatellite loci from
Marker | MAF | NA | GD | HE | PIC |
---|---|---|---|---|---|
GlySSR1 | 0.62 | 4 | 0.56 | 0.32 | 0.52 |
GlySSR2 | 0.28 | 6 | 0.79 | 0.48 | 0.76 |
GlySSR3 | 0.88 | 3 | 0.22 | 0.08 | 0.20 |
GlySSR4 | 0.42 | 5 | 0.71 | 0.44 | 0.66 |
GlySSR5 | 0.32 | 7 | 0.79 | 0.44 | 0.76 |
GlySSR7 | 0.50 | 6 | 0.67 | 0.32 | 0.63 |
GlySSR10 | 0.64 | 5 | 0.55 | 0.28 | 0.52 |
GlySSR11 | 0.70 | 4 | 0.47 | 0.40 | 0.44 |
Mean | 0.55 | 5 | 0.60 | 0.35 | 0.56 |
MAF, major allele frequency; NA, number of alleles; GD, genetic diversity; HE, expected heterozygosity; PIC, polymorphism information content
Major allele frequency (MAF) varied from 0.28 for GlySSR2 to 0.88 for GlySSR3 with average MAF of 0.55. A total of 40 alleles, ranging from 3 for GlySSR3 to 7 for GlySSR5, were observed among 22
A total of 40 polymorphic fragments from 8 EST based microsatellite markers were used to assess genetic diversity in the
Dendrogram of the
Eight microsatellite markers would be useful for studies of the genetic diversity, population structure, and evolutionary relationships among
The development of functional markers such as EST-based microsatellite is becoming a valuable study for plants, especially in marker-assisted breeding one. However, the number of EST-based microsatellite markers for
This work was carried out with the support of “Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ01028801)” Rural Development Administration, Republic of Korea.
J Plant Biotechnol 2016; 43(2): 174-180
Published online June 30, 2016 https://doi.org/10.5010/JPB.2016.43.2.174
Copyright © The Korean Society of Plant Biotechnology.
Yurry Um, Mei-Lan Jin, Yi Lee, Mok Hur, Seon Woo Cha, Chan Sik Jung, Seong Min Kim, and Jeong-Hoon Lee
Department of Herbal Crop Research, National Institute of Horticultural and Herbal Science, Rural Development Administration, Eumseong 27709, Korea,
Department of Industrial Plant Science and Technology, Chungbuk National University, Cheongju 28644, Korea,
Department of Plant Resources, College of Industrial Science, Kongju National University, Yesan 32439, Korea
Correspondence to:e-mail: artemisia@korea.kr
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Licorice plant (
Keywords:
Our experimental focus for this study was to analyze the genetic relationship between the collections of licorice plant (
Divergence of wild populations has been analyzed using several molecular markers. Molecular genetic diversity studies for
A total of 22
Table 1 .
No. | Sample name | ?Species | Location |
---|---|---|---|
1 | 1A | KOR | |
2 | 1B | ˝ | |
3 | 1C | ˝ | |
4 | 2A | CAN | |
5 | 2B | ˝ | |
6 | 2D | ˝ | |
7 | 2E | ˝ | |
8 | 3A | MNG | |
9 | 3C | ˝ | |
10 | 3E | ˝ | |
11 | 4C | MNG | |
12 | 5A | MNG | |
13 | 5B | ˝ | |
14 | 5C | ˝ | |
15 | 5D | ˝ | |
16 | 5E | ˝ | |
17 | 6A | UZB | |
18 | 6B | ˝ | |
19 | 7A | CHN | |
20 | 7B | ˝ | |
21 | 7C | ˝ | |
22 | 7E | ˝ |
KOR, Korea; CAN, Canada; MNG, Mongolia; UZB, Uzbekistan; CHN, China.
All available
Table 2 . Statistics on EST sequences in
????Contents | Numbers |
---|---|
Total number of sequences downloaded | 56,089 |
Total size of downloaded sequences (bp) | 26,955,389 |
Number of cleaned EST sequences | 55,942 |
Total number of sequences examined | 4,821 |
Total number of identified SSRs | 5,536 |
Number of SSRs containing sequences | 3,053 |
Number of sequences containing more than one EST-SSR | 1,484 |
A total of 4,821 unigenes obtained from the assembly were subjected to SSRIT to identify SSRs (Temnykh et al. 2001) and to design primers using Primer3 (Koressaar and Remm 2007; Untergrasser et al. 2012). The default settings of the program were used with some adjustments: product size 250 ~ 500 bp, optimum 300 bp; primer size 18 ~ 25 nt, optimum 22 nt; primer Tm 55 ~ 60°C, optimum 57°C; primer GC content 40 ~ 60%, optimum 50%. Single PCRs were carried out for the 22 accessions with 8 EST-based microsatellite primers. The PCR mix contained 2 pmol and FAM-labelled primers and 2 pmol of the forward primer in a 25 ml reaction volume with 2.5 ml PCR buffer, 0.2 mM dNTPs, 2 mM MgCl2, 50 ~ 100 ng template DNA, and 1 U Taq DNA polymerase. Conditions for all PCR amplifications were as follows: 94°C for 5 min, then 30 cycles of 94°C for 30 s, 58°C for 45 s and 72°C for 45 s, final extension at 72°C for 10 min. PCR products were separated in a 2.0% agarose gel to visualize PCR amplification. PCR primer sets used in these experiments are listed in Table 2. Forward primers were labeled with a virtual dye 6-FAM, NED, VIC or PET (Applied Biosystems). After PCR amplification, 0.2 ml of PCR products was mixed with 9.8 ml Hi-Di formamide (Applied Biosystems) and 0.2 ml of GeneScanTM 500 LIZ? size standard (Applied Biosystems, Foster City, CA, USA). The mixture was denatured at 95°C for 5 min and placed on ice. The amplified fragments were separated by capillary electrophoresis on the ABI 3730 DNA analyzer (Applied Biosystems) using a 50-cm capillary with a DS-33 install standard as a matrix. We analyzed the amplicon size using the GeneMapper software (version 4.0; Applied Biosystems).
For each accession, fragments amplified with the EST-based microsatellite markers were scored as present (1) or absent (0). Genetic parameters including major allele frequency (MAF), number of alleles (NA), genetic diversity (GD), expected heterozygosity (HE), and polymorphic information content (PIC) were measured by calculating the shared allele frequencies using the PowerMarker software (version 3.25) (Liu and Muse 2005). The data were then used to compute the PIC value for each polymorphic marker fragment according to the formula: PICi = 2fi (1-fi) where fi is the frequency of band presence (Rold?n-Ruiz et al. 2000). The correlation of geographic and genetic distances from principal coordinate analysis (PCoA) was performed using NTSYS software v. 2.2 (Rohlf 2000; Rohlf 2004). A dendrogram was made using unweighted neighbour-joining method. Bootstrap analysis was performed with 1,000 replications. Mantel’s test was used to determine the correlation of the dissimilarity matrix and the dendrogram.
A total of 56,089 EST sequence reads from a publicly available
Hexa-nucleotide repeats ranked in highest abundance, accounting for 63.78% of the SSRs. Hepta-, di-, and tri- nucleotide repeats were next in abundance, accounting for 10.77, 8.27, and 6.97% of the SSRs. Penta-, octa-, nona-, and tetra-nucleotide repeats were rarer (2.87, 2.87, 2.82, and 1.28 %, respectively), and deca-nucleotides together accounted for less than 1% of the identified SSRs. Among di-nucleotide repeats, (AG/CT)n accounted for 44.71% of di-nucleotide repeats (Table 3). Among tri-nucleotide repeats, (GAA/TTC)n and (AGA/TCT)n were the most abundant repeat motifs and represented 10.37 and 10.16% of tri-nucleotides, respectively. Among the tetra-nucleotide repeats, (CAAG/CTTG)n was most abundant, with each accounting for 11.89% of the tetra-nucleotides. Only one motif (CATAC/GTATG)n accounted for 17.96% of hepta-nucleotides (Table 4).
Table 3 . Frequencies of microsatellite repeat by type in the
???Repeat types | Number of SSRs | Proportion of all SSRs (%) |
---|---|---|
Dinucleotide | 458 | 8.27 |
Trinucleotide | 386 | 6.97 |
Tetranucleotide | 71 | 1.28 |
Pentanucleotide | 159 | 2.87 |
Hexanucleotide | 3,531 | 63.78 |
Hepta-nucleotide | 596 | 10.77 |
Octa-nucleotide | 159 | 2.87 |
Nona-nucleotide | 156 | 2.82 |
Deca-nucleotide | 20 | 0.36 |
Total | 5,536 | 100.00 |
Table 4 . The most abundant microsatellite motifs in the EST database. Only motifs accounting for 5% or more of each repeat type (i.e. di-, tri-, tetra-nucleotide, etc.) are included.
?SSR type | ?SSR motif | Number of SSR motifs | Percentage of SSR motif |
---|---|---|---|
Di-nucleotide | AG/CT | 1,421 | 44.71 |
GA/TC | 903 | 28.41 | |
AC/GT | 355 | 11.17 | |
CA/TG | 241 | 7.58 | |
AT/AT | 169 | 5.32 | |
Tri-nucleotide | GAA/TTC | 300 | 10.37 |
AGA/TCT | 294 | 10.16 | |
ACA/TGT | 226 | 7.81 | |
AAG/CTT | 224 | 7.74 | |
AAC/GTT | 178 | 6.15 | |
CAA/TTG | 168 | 5.81 | |
CAC/GTG | 147 | 5.08 | |
Tetra-nucleotide | CAAG/CTTG | 61 | 11.89 |
AAAT/ATTT | 47 | 9.16 | |
AAAC/GTTT | 28 | 5.46 | |
TATG/CATA | 27 | 5.26 | |
Penta-nucleotide | CATAC/GTATG | 201 | 17.96 |
Marker evaluation and polymorphism detection.
A total of 125 primer pairs were designed from di- to tetra- nucleotide EST-SSRs. The EST-SSR primers were selected based on high G/C content, melting temperature of 55 ~ 60°C. These primers were tested on a subset of
Table 5 . Primers used for
Marker | Accession No. | SSR Modif. | SSR specific primer (5’→3’) | Product size (bp) | |
---|---|---|---|---|---|
Forward | Reverse | ||||
GlySSR1 | FS239000 | (tatg)5 | GACTGGAATCTCAAACGCAATA | AAAATCAAAGCGTGACCAGATA | 330-352 |
GlySSR2 | FS239076 | (ttctc)6…(aag)7 | TTCTTTGACTCACTCACCCCTA | AGTGATTCACGAGTTCATCGTC | 260-291 |
GlySSR3 | FS239091 | (gaat)6 | CGGTATAGCGTGGTAGTCTGAG | TTTTTGAAGCTGTTGAATGGTT | 287-341 |
GlySSR4 | FS239392 | (catggg)9 | CTGTTTTCCCCTGTTTTCTTCT | TCTGTTGCTCCTCTGTTTGAGT | 260-290 |
GlySSR5 | FS239689 | (ag)18 | TTGCGAGTGAGAGGAAGTTAAG | CCAGAGTACACACGATTTTGGT | 382-407 |
GlySSR7 | FS240731 | (ag)18 | CCAAGGAATTAGAACTGCGACT | AGTGCCATGAGAGAAGTTGAAA | 270-311 |
GlySSR10 | FS238963 | (aac)6…(tgg)6 | ATGGCAGGTATCATTCACAAGAT | TGTCCTTGATCTTCTCCACAAAC | 332-344 |
GlySSR11 | FS238990 | (gga)7 | GTAATGCCGTTGGAGGATGAC | AGGGCAGAATCTAAGTGCAGAA | 352-375 |
Table 6 . Characteristics of 8 polymorphic microsatellite loci from
Marker | MAF | NA | GD | HE | PIC |
---|---|---|---|---|---|
GlySSR1 | 0.62 | 4 | 0.56 | 0.32 | 0.52 |
GlySSR2 | 0.28 | 6 | 0.79 | 0.48 | 0.76 |
GlySSR3 | 0.88 | 3 | 0.22 | 0.08 | 0.20 |
GlySSR4 | 0.42 | 5 | 0.71 | 0.44 | 0.66 |
GlySSR5 | 0.32 | 7 | 0.79 | 0.44 | 0.76 |
GlySSR7 | 0.50 | 6 | 0.67 | 0.32 | 0.63 |
GlySSR10 | 0.64 | 5 | 0.55 | 0.28 | 0.52 |
GlySSR11 | 0.70 | 4 | 0.47 | 0.40 | 0.44 |
Mean | 0.55 | 5 | 0.60 | 0.35 | 0.56 |
MAF, major allele frequency; NA, number of alleles; GD, genetic diversity; HE, expected heterozygosity; PIC, polymorphism information content.
Major allele frequency (MAF) varied from 0.28 for GlySSR2 to 0.88 for GlySSR3 with average MAF of 0.55. A total of 40 alleles, ranging from 3 for GlySSR3 to 7 for GlySSR5, were observed among 22
A total of 40 polymorphic fragments from 8 EST based microsatellite markers were used to assess genetic diversity in the
Dendrogram of the
Eight microsatellite markers would be useful for studies of the genetic diversity, population structure, and evolutionary relationships among
The development of functional markers such as EST-based microsatellite is becoming a valuable study for plants, especially in marker-assisted breeding one. However, the number of EST-based microsatellite markers for
This work was carried out with the support of “Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ01028801)” Rural Development Administration, Republic of Korea.
Dendrogram of the
Table 1 .
No. | Sample name | ?Species | Location |
---|---|---|---|
1 | 1A | KOR | |
2 | 1B | ˝ | |
3 | 1C | ˝ | |
4 | 2A | CAN | |
5 | 2B | ˝ | |
6 | 2D | ˝ | |
7 | 2E | ˝ | |
8 | 3A | MNG | |
9 | 3C | ˝ | |
10 | 3E | ˝ | |
11 | 4C | MNG | |
12 | 5A | MNG | |
13 | 5B | ˝ | |
14 | 5C | ˝ | |
15 | 5D | ˝ | |
16 | 5E | ˝ | |
17 | 6A | UZB | |
18 | 6B | ˝ | |
19 | 7A | CHN | |
20 | 7B | ˝ | |
21 | 7C | ˝ | |
22 | 7E | ˝ |
KOR, Korea; CAN, Canada; MNG, Mongolia; UZB, Uzbekistan; CHN, China.
Table 2 . Statistics on EST sequences in
????Contents | Numbers |
---|---|
Total number of sequences downloaded | 56,089 |
Total size of downloaded sequences (bp) | 26,955,389 |
Number of cleaned EST sequences | 55,942 |
Total number of sequences examined | 4,821 |
Total number of identified SSRs | 5,536 |
Number of SSRs containing sequences | 3,053 |
Number of sequences containing more than one EST-SSR | 1,484 |
Table 3 . Frequencies of microsatellite repeat by type in the
???Repeat types | Number of SSRs | Proportion of all SSRs (%) |
---|---|---|
Dinucleotide | 458 | 8.27 |
Trinucleotide | 386 | 6.97 |
Tetranucleotide | 71 | 1.28 |
Pentanucleotide | 159 | 2.87 |
Hexanucleotide | 3,531 | 63.78 |
Hepta-nucleotide | 596 | 10.77 |
Octa-nucleotide | 159 | 2.87 |
Nona-nucleotide | 156 | 2.82 |
Deca-nucleotide | 20 | 0.36 |
Total | 5,536 | 100.00 |
Table 4 . The most abundant microsatellite motifs in the EST database. Only motifs accounting for 5% or more of each repeat type (i.e. di-, tri-, tetra-nucleotide, etc.) are included.
?SSR type | ?SSR motif | Number of SSR motifs | Percentage of SSR motif |
---|---|---|---|
Di-nucleotide | AG/CT | 1,421 | 44.71 |
GA/TC | 903 | 28.41 | |
AC/GT | 355 | 11.17 | |
CA/TG | 241 | 7.58 | |
AT/AT | 169 | 5.32 | |
Tri-nucleotide | GAA/TTC | 300 | 10.37 |
AGA/TCT | 294 | 10.16 | |
ACA/TGT | 226 | 7.81 | |
AAG/CTT | 224 | 7.74 | |
AAC/GTT | 178 | 6.15 | |
CAA/TTG | 168 | 5.81 | |
CAC/GTG | 147 | 5.08 | |
Tetra-nucleotide | CAAG/CTTG | 61 | 11.89 |
AAAT/ATTT | 47 | 9.16 | |
AAAC/GTTT | 28 | 5.46 | |
TATG/CATA | 27 | 5.26 | |
Penta-nucleotide | CATAC/GTATG | 201 | 17.96 |
Marker evaluation and polymorphism detection.
Table 5 . Primers used for
Marker | Accession No. | SSR Modif. | SSR specific primer (5’→3’) | Product size (bp) | |
---|---|---|---|---|---|
Forward | Reverse | ||||
GlySSR1 | FS239000 | (tatg)5 | GACTGGAATCTCAAACGCAATA | AAAATCAAAGCGTGACCAGATA | 330-352 |
GlySSR2 | FS239076 | (ttctc)6…(aag)7 | TTCTTTGACTCACTCACCCCTA | AGTGATTCACGAGTTCATCGTC | 260-291 |
GlySSR3 | FS239091 | (gaat)6 | CGGTATAGCGTGGTAGTCTGAG | TTTTTGAAGCTGTTGAATGGTT | 287-341 |
GlySSR4 | FS239392 | (catggg)9 | CTGTTTTCCCCTGTTTTCTTCT | TCTGTTGCTCCTCTGTTTGAGT | 260-290 |
GlySSR5 | FS239689 | (ag)18 | TTGCGAGTGAGAGGAAGTTAAG | CCAGAGTACACACGATTTTGGT | 382-407 |
GlySSR7 | FS240731 | (ag)18 | CCAAGGAATTAGAACTGCGACT | AGTGCCATGAGAGAAGTTGAAA | 270-311 |
GlySSR10 | FS238963 | (aac)6…(tgg)6 | ATGGCAGGTATCATTCACAAGAT | TGTCCTTGATCTTCTCCACAAAC | 332-344 |
GlySSR11 | FS238990 | (gga)7 | GTAATGCCGTTGGAGGATGAC | AGGGCAGAATCTAAGTGCAGAA | 352-375 |
Table 6 . Characteristics of 8 polymorphic microsatellite loci from
Marker | MAF | NA | GD | HE | PIC |
---|---|---|---|---|---|
GlySSR1 | 0.62 | 4 | 0.56 | 0.32 | 0.52 |
GlySSR2 | 0.28 | 6 | 0.79 | 0.48 | 0.76 |
GlySSR3 | 0.88 | 3 | 0.22 | 0.08 | 0.20 |
GlySSR4 | 0.42 | 5 | 0.71 | 0.44 | 0.66 |
GlySSR5 | 0.32 | 7 | 0.79 | 0.44 | 0.76 |
GlySSR7 | 0.50 | 6 | 0.67 | 0.32 | 0.63 |
GlySSR10 | 0.64 | 5 | 0.55 | 0.28 | 0.52 |
GlySSR11 | 0.70 | 4 | 0.47 | 0.40 | 0.44 |
Mean | 0.55 | 5 | 0.60 | 0.35 | 0.56 |
MAF, major allele frequency; NA, number of alleles; GD, genetic diversity; HE, expected heterozygosity; PIC, polymorphism information content.
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