Molecular identification of mung bean accessions

Full text

Turn on search term navigation

INTRODUCTION

Mung bean (Vigna radiata (L.) R. Wilczek) is an important grain legume with a long history of planting in China and is widely used as a nutritional complement in different types of foods due to its rich protein, calcium and vitamin C contents (Liu et al., ). The northeast is the main production area of mung bean in China, with a total output of 192,000 tons, accounting for 29% of the total output in the country. With the improvement of people's living standards and the enhancement of dietary nutrition consciousness, mung bean has become favored for its rich nutritional value, which plays an important role in human health and life. The rapid development of variety trade with the introduction and popularization of varieties has repeatedly led to a ban on counterfeit and mixed seedlings, which have caused great losses in agricultural production. Variety protection and identification are important issues worldwide. The International Union for the Protection of New Varieties of Plants (UPOV) is an intergovernmental organization with the mission to provide and promote an effective system of plant variety protection in order to encourage the development of new varieties of plants for the benefit of society. The UPOV encourages members to breed plants by granting breeders of new plant varieties intellectual property rights. Plant breeder's rights (PBRs) are exclusive commercial rights for a registered plant variety; they are a form of intellectual property that allows the breeder to choose whether to become the exclusive marketer of the variety. Therefore, the establishment of an efficient and accurate method for identifying the authenticity of mung bean varieties would provide technical support for the sustainable development of mung bean and lay a foundation for the protection of intellectual property rights related to mung bean.

Variety identification is one of the most important research areas in agriculture. Traditional approaches including observation and analysis of morphological characters, which are less informative and time consuming and not precise enough due to influences of the surrounding environment (Hue et al., ). The development of molecular technology has provided more simple and efficient tools for genetic analysis and identification. A number of molecular marker technologies, such as random amplification of polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), restriction fragment length polymorphism (RFLP), and simple sequence repeat (SSR) (Done et al., ), have been extensively applied in crops. In addition, a third‐generation molecular marker technology, single‐nucleotide polymorphism (SNP), has undergone rapid development and has become one of the best choices for genetic analysis and fingerprinting. However, it is unrealistic to use SNP technology for many mung bean varieties due to its cost and the extreme difficulty of SNP genotyping (Zhao et al., ). Therefore, SSR is considered the most efficient and valuable technology for genetic diversity analysis and variety identification due to their rich polymorphism, high stability, and good repeatability (Dong et al., ). Rahmani, Debbabi, and Ferchichi () researched the efficiency of SSR technology using 10 SSR primer pairs to identify 15 Tunisian olive cultivars, indicating the importance of SSR in olive germplasm management and molecular database establishment. Bantte and Mogus () amplified 39 SSR markers to identify 12 sorghum accessions and constructed a DNA fingerprint database of 11 accessions with 32 SSRs, providing essential information related to the selection of elite parents and the protection of elite hybrids. Islam et al. () studied the genetic diversity and fingerprinting of eight cotton varieties in Bangladesh with three primer pairs used for the identification and conservation of elite cotton germplasm.

SSR markers have been commonly used in genetic linkage map construction, quantitative trait locus (QTL) mapping, resistance, and transferability studies in mung bean. Wang, Zhang, Cheng, and Wang () constructed a new genetic linkage map covering the entire genome of mung bean with 95 SSR markers, which had a total length of 1,457.47 cM across 11 linkage groups and revealed 37 QTLs for young stem color, main stem color, and growth habit. Kitsanachandee et al. () used 122 mung bean genotypes to evaluate their resistance to mung bean yellow mosaic India virus (MYMIV) in India and Pakistan using SSR and detected five QTLs that explained 9.33%, 10.61%, 12.55%, 21.93%, and 6.24% of the variation in disease responses, respectively. Zhong, Cheng, Wang, and Wang () used 1,205 mung bean genomic SSRs to test their transferability in different Vigna sps (cowpea, adzuki bean, and rice bean) with the transferability rate of more than 50%, indicating the efficiency of SSR for further genetic and breeding studies. However, mung bean has received little attention from the scientific community, and the genomic resources available for this crop are very limited compared with those for other crops, such as rice and soybean, which restricts in‐depth research on this species. Several studies have used SSR markers for genetic diversity analysis and fingerprinting of mung bean varieties. Md, Iftekhar, Motiar, Md, and Md () detected 42 mung bean varieties by five SSR markers and constructed a fingerprinting that identified all the samples by 1–4 primers. Lestari, Kim, Reflinur, Yang, and Lee () used 30 SSR markers to amplify 83 mung bean accessions from Indonesia, and 107 alleles were detected with a mean polymorphism information content (PIC) value of 0.33, which revealed the narrow genetic background and low genetic similarity of mung bean in Indonesia. Gwag et al. () assessed the genetic diversity and population structure of 692 mung bean accessions collected from 27 countries in nine different geographic regions using 15 SSR markers, which showed the importance of varieties from East and Central Asia for further germplasm preservation and crossbreeding programs. Nevertheless, there are still few reports on fingerprinting and identification of the mung bean. To better identify mung bean varieties, it is necessary to analyze fingerprint data, which are often ignored, in detail.

At present, the common method for gene detection and isolation is polyacrylamide gel electrophoresis (PAGE), which cannot reveal the accurate size of target DNA fragments and has a relatively low detection efficiency. In addition, it is difficult to effectively integrate and accurately compare DNA fingerprinting data from large‐scale samples and different batches of samples. Capillary electrophoresis with fluorescence‐labeled SSR marker technology, based on DNA sequences, can accurately determine the size of detected fragments with a high degree of automation and can identify subtle differences between 1‐bp and 2‐bp fragments (Cheng, Xia, Gong, & Yang, ). Three different colors of fluorescent dyes are used to label microsatellite primers, and polymerase chain reaction (PCR) products with different fluorescence markers and standard molecular weight samples (internal standard) are used for electrophoresis in the same lane. The results are recorded on a computer, and the images are collected and analyzed by fragment analysis software automatically, which can calculate the degree of microsatellite allelic variation accurately. (Chen et al., ). The use of capillary electrophoresis with fluorescence‐labeled SSR markers increases the accuracy of fingerprint data, and the specific sites with small differences among the varieties can be identified, showing the strong identification ability.

In this study, a set of simple, rapid and reliable SSR markers was used to detect 151 mung bean varieties from Northeast China, which highlighted the differences among these varieties at the DNA level and established an efficient and accurate method for identification that is devoted to traceability management, identification of authenticity, and protection of origins.

MATERIALS AND METHODS

Plant materials

We sampled a total of 151 mung bean accessions, which were collected from four provinces in Northeast China, which are the main mung bean‐growing regions in China. Among the accessions, 15, 39, 33, and 64 originated from Heilongjiang Province, Jilin Province, Liaoning Province, and the Inner Mongolia Autonomous Region, respectively. All 151 mung bean accessions were provided by the Institute of Crop Science, Chinese Academy of Agricultural Sciences. Detailed information on the samples including accession name, system number and origin region is provided in Appendix 1. Six blind‐selected mung bean varieties for DNA database verification were purchased from a local supermarket.

DNA extraction

Young leaves were collected from each sample after approximately 15‐day germination for which genomic DNA would be extracted and immediately frozen in liquid nitrogen. Genomic DNA was extracted using the TIANGEN Plant Genomic DNA Kit according to the manufacturer's protocol. The quality and quantity of the DNA samples were detected using 1% agarose gels and the NanoDrop 2000 spectrophotometer, respectively. The concentration of the DNA samples was adjusted to approximately 300 ng/μl, and the DNA samples were stored at −80°C until use.

SSR markers and PCR amplification

A total of 200 primer pairs provided by the Institute of Crop Science, Chinese Academy of Agricultural Sciences, were synthesized at Sangon Biotech Co., Ltd. Among the 200 primer pairs, the eight primer pairs producing clear and repeated bands were selected and synthesized for further analysis by ABI Biotech Co., Ltd. PCR was performed in a total volume of 20 μl containing 2 μl of genomic DNA (30 ng/μl), 0.6 μl of each primer (2 μmol/L), 0.2 μl of Taq polymerase (2.5 U/μl), 0.4 μl of dNTPs (10 mmol/L), 1.0 μl of MgCl₂ (20 mmol/L), 2 μl of 10× buffer, and enough ddH₂O to reach 20 µl. PCR amplification was conducted at 94°C for 5 min, followed by 35 cycles of 94°C for 30 s, 54°C for 35 s, and 72°C for 40 s, with a final extension step at 72°C for 3 min.

Capillary electrophoresis detection

Eight pairs of fluorescent primers were obtained with the fluorescent dyes FAM, TMRA, and HEX. A mixture of highly deionized‐formamide (HIDI) and LIZ500 molecular weight internal standard at a volume ratio of 100:1 was placed in a 96‐well reaction plate with a continuous pipette, with each well containing a total volume of 9 μl, to which 1 μl of PCR amplification product diluted 10 times was added. Then, the samples were detected using an ABI 3730XL sequence analyzer followed by analysis of the initial data by GeneMarker to compare the peak position of each sample with the molecular weight internal standard in each pool, after which the fragment size was obtained.

Data analysis

Genetic statistics for the eight primer pairs, including the number of alleles (Na), the effective number of alleles (Ne), observed heterozygosity (Ho), PIC, Shannon's information index (I*), and Nei's genetic diversity (H*), were obtained using POPGENE version 1.32 and PIC‐Calc version 6.0. GenAlEx 6.5 (Peakall & Smouse, ) was used to calculate the probability of identity (PI) for each marker and their combinations (PIs) to assess the fingerprinting power. GeneMapper was used to calculate the number of observed genotypes and the number of accessions with unique genotypes. The power of discrimination (PD) was calculated with the formula PD = 1−ΣGi², where Gi is the frequency of the i^th genotype at locus I (Kloosterman, Budowle, & Daselaar, ). Principal component analysis (PCA) and the unweighted pair group method with arithmetic averages (UPGMA) (Sneath & Sokal, ), both of which were used to analyze the relationships among the tested accessions, were performed in MEGA 6.0 (Tamura, Stecher, Peterson, Filipski, & Kumar, ).

Construction of the fingerprint database and query system

To make the numerous fragments detected more convenient for analysis and the calculation of statistics, the electrophoresis peak at the same alleles was identified and recorded as “1” if present and “0” if absent, forming a 0/1 system in which all the samples were eventually represented by a series of 0/1 numbers. After converting the data and putting them into a text file, the SSR fingerprinting pattern was constructed by ClusterProject software. A query system was also established that could transform the ID number of an unidentified variety into a 0/1 string first. Then, the 0/1 string was compared with the varieties from Northeast China in the fingerprint database, and genetic information was shown in the system.

RESULTS

Selection of core SSR primers

Ten mung bean varieties with different agronomic traits and geographical sources were selected from the four tested areas as templates, and 200 pairs of SSR primers were selected for primary screening. After the amplification of the 10 mung bean samples using the 200 primer pairs, eight primer pairs showing clear bands, good reproducibility, and high PIC values were chosen as core primers for further analysis (Table and Figure ). A total of 151 mung bean varieties were detected by the eight primer pairs and generated a total of 59 bands (Table ), which varied from 4 (X34) to 11 (X148), with an average of 7.4. The PIC for each primer ranged from 0.385 (X34) to 0.781 (X55), with an average of 0.560. Among these primer pairs, X34 and X55 were moderately polymorphic (0.25 < PIC<0.5), and the other six primers were all highly polymorphic (PIC > 0.5). Ne* ranged from 1.999 to 5.166, with an average of 2.754. Alleles with gene frequencies less than 0.05 were considered rare alleles. All eight primer pairs detected rare alleles, with a total of 30, accounting for 50.85% of all the alleles. H* varied from 0.499 to 0.806, with an average of 0.540. I* varied from 0.738 to 1.843, with an average of 1.243. Ho varied from 0.820 to 0.993, with an average of 0.900. He varied from 0.501 to 0.809, with an average of 0.610. The eight primer pairs were highly polymorphic, providing valuable resources for genomic analysis and SSR fingerprinting of mung bean varieties.

Results for the 8 SSR primers

Primer	Na	Ne*	PIC	Shannon (I*)	Nei's diversity (H*)	Ho	He
X20	7	2.490	0.564	1.232	0.598	0.946	0.600
X34	4	2.000	0.384	0.738	0.500	0.874	0.501
X46	10	2.512	0.576	1.329	0.601	0.933	0.604
X55	9	5.17	0.781	1.843	0.806	0.824	0.809
X62	5	2.090	0.483	1.013	0.521	0.993	0.523
X87	6	2.654	0.550	1.171	0.623	0.820	0.625
X148	11	2.779	0.610	1.461	0.640	0.913	0.642
X168	7	2.346	0.530	1.600	0.574	0.900	0.576
Mean	7.375	0.373	0.560	1.243	0.608	0.900	0.610

Example of fingerprint profiles generated by primer X168: (a) Lv Dou (C0689), (b) Xiao Lv Dou (C0844), and (c) Lv Xiao Dou (C0712)

Alleles amplified by each SSR primer

Primer	Amplified allele sizes	PD value
X20	195, 197, 199, 201, 203, 205, 211	0.621
X34	141, 143, 145, 147	0.600
X46	107, 111, 113, 115, 117, 119, 121, 123, 125, 127	0.634
X55	131, 133, 135, 137, 139, 142, 144, 146, 148	0.862
X62	181, 183, 185, 187, 189	0.523
X87	213, 215, 217, 219, 221, 223	0.600
X148	182, 188, 190, 192, 194, 196, 198, 200, 202, 204, 206	0.677
X168	159, 161, 163, 165, 207, 209, 211	0.640
Mean (total)	59	0.645

Screening of primer combinations

Eight core primer pairs were used to amplify the 151 mung bean varieties, resulting in 100 detectable genotypes, which varied from 5 to 23, with an average of 12.5. The number of mung bean varieties that had unique genotypes at different loci ranged from 1 to 10, with an average of 5.125 (Table ). More detected genotypes and the higher PIC can reflect more genetic differences among varieties. Three primer pairs (X55, X46, and X148) revealed more genotypes and the higher PIC than the average value, accounting for 37.5% of the total. The number and type of primer combinations caused their identification efficiencies to differ. Among these primers, X55 was the most informative primer that could differentiate 10 mung bean varieties from the others. By contrast, X87 was the least informative primer that could differentiate only 1 mung bean variety from the others. It is difficult to identify all varieties by only one primer pair; therefore, primer combinations are usually used. Notably, the selection of primer combinations should meet the requirement that the minimum number of primers is used to distinguish the most varieties, thereby avoiding unnecessary information (Li, Xu, Wu, Zhang, & Zhang, ). Accordingly, the primer combinations used here were established based on a stepwise increase in the number of primers to distinguish all of the samples.

Key genetic statistics for the 8 SSR primers

Primer	No. of observed genotypes	No. of varieties with unique genotypes	PI	PIs	Fragment size (bp)
X20	11	5	0.313	0.578	195–211
X34	5	2	0.377	0.603	141–147
X46	16	8	0.200	0.494	107–127
X55	23	10	0.093	0.393	131–148
X62	6	2	0.360	0.612	181–189
X87	9	1	0.268	0.528	213–223
X148	18	8	0.260	0.535	182–206
X168	12	5	0.270	0.547	159–211
Mean	12.5	5.125	1.49176E‐05	6.4054E‐03	‐

The eight primer pairs were grouped into combinations of 3–7 pairs to determine their identification rate for the 151 mung bean varieties (Table ). The combination of X46, X55, and X148 showed the higher identification rate of 43.7% among the three‐primer combinations and could identify 66 mung bean varieties. The effectiveness of the established primer combinations increase step by step based on these three primers due to their higher genotype detection rate and PIC values. The combination of X46, X55, X148, and X168 obtained the higher identification rate of 62.9% among the four‐primer combinations and could identify 95 mung bean varieties. Adding X20 to this combination leads to the higher identification rate of 82.1% among the five‐primer combinations, allowing the identification of 124 mung bean varieties. Furthermore, the combination of X46, X55, X148, X168, X20, and X34 obtained a higher identification rate (90.7%) than the combination of X46, X55, X148, X87, X20, and X34 among the six‐primer combinations and could identify 137 mung bean varieties. Although these two combinations showed the same identification rate, there were differences between their genotype and unique genotype detection rates. The primer combination of X20, X34, X46, X55, X62, X148, and X168 showed the highest identification rate of 98.7% among the seven‐primer combinations, with the ability to identify 149 varieties. By contrast, X3, X46, X55, X62, X87, X148, and X168 was the least informative primer combination, with an identification rate of 92.7% and the ability to identify only 140 varieties.

Summary of the identification rate with stepwise increases in combinations

		Average PIC	Total observed genotypes	Total unique genotypes	Number of identified varieties	Identification rate (%)
Three‐primer combinations	X46, X55, X148	0.660	57	26	66	43.7
Four‐primer combinations	X46, X55 X148, X168	0.624	69	31	95	62.9
X46, X55, X148, X20	0.632	68	31	93	61.6
Five‐primer combinations	X46, X55, X148, X168, X20	0.612	80	36	124	82.1
X46, X55, X148, X87, X20	0.616	77	32	120	79.5
X46, X55, X148, X34, X20	0.583	73	33	113	74.8
X46, X55, X148, X62, X20	0.582	74	33	110	72.8
Six‐primer combinations	X46, X55, X148, X168 X20, X34	0.574	85	38	137	90.7
X46, X55, X148, X87, X20, X34	0.577	82	34	137
X46, X55, X148, X62, X20, X168	0.590	86	38	135	89.4
X46, X55, X148, X168, X20, X87	0.601	89	37	132	87.4
X46, X55, X148, X62, X20, X34	0.566	79	35	129	85.4
X46, X55, X148, X62, X20, X87	0.593	83	34	128	84.8
Seven‐primer combinations	X20, X34, X46, X55, X62, X148, X168	0.561	91	40	149	98.7
X20, X34, X46, X55, X62, X87, X148,	0.564	88	36	146	96.7
X20, X34, X46, X55, X87, X148, X168	0.570	94	39	143	94.7
X20, X46, X55, X62, X87, X148, X168	0.584	95	39	141	93.4
X34, X46, X55, X6, X87, X148, X168	0.559	89	46	140	92.7

To evaluate the fingerprinting power of the eight markers, two pivotal parameters of PI and PIs were calculated (Table ). The PI ranged from 0.093 to 0.377, with an average of 0.267 for each primer, and the probability of two random individuals possessing the same genotypes at the 8 loci was estimated to be 1.49 × 10^–5, assuming that all SSR marker loci segregated independently. As the upper limit of PI, PIs varied from 0.393 to 0.612, with an average of 0.536, and the combined PIs value was 6.40 × 10^–3. Based on these results, the SSR marker combinations were evaluated for their ability to discriminate these mung bean varieties (Figure ). Both PI and PIs showed extremely low values, indicating the elegant fingerprinting power of these eight markers.

Evaluation of the probability of identification of SSR markers

The frequency of each genotype ranged from 0.0002 to 0.6400 at different SSR loci (Appendix 2). Assuming that the genotype frequency at each locus was independent, these eight primer pairs showed a very high identification accuracy with error probabilities less than 3.7E‐04. Allele sizes and frequencies for the eight SSR markers were also summarized based on the genotypes of 151 mung bean varieties (Figure ).

Allele sizes and frequencies for the 8 SSR markers: (a) X20, X34, X46, and X55; (b) X62, X87, X148, and X168

Genetic relationship analysis

The genetic similarity among the 151 mung bean varieties ranged from 0.682 to 0.985, with an average of 0.853, based on the eight primer pairs. Among the 151 mung bean varieties, the minimum genetic similarity coefficient was detected between Lv Dou (C3784) and Lv Dou (C0623), and the maximum genetic similarity coefficient was detected between Qing Lv Dou (C0713) and Ming Lv Dou (C0787). UPGMA analysis was used to evaluate the genetic relationships among the 151 mung bean varieties and showed that individuals largely grouped according to their genetic characteristics rather than according to their geographical origin, and the mung bean varieties from the same regions were not clearly clustered into the same group (Figure ). Notably, Ji Dou (C0693) and Lv Dou (C3839) were grouped separately, which indicated that the genetic distance between them and the other varieties was relatively long and that their consanguinity was low. The PCA result also showed that the 151 mung bean varieties were not clustered together according to region, which was generally consistent with the result of the UPGMA analysis (Figure ). The majority of the varieties from Heilongjiang Province and Jilin Province were dispersed; however, the majority of the varieties from the Inner Mongolia Autonomous Region were relatively closely grouped, which was consistent with the diversity index. These results indicated that the 151 mung bean varieties had high levels of genetic similarity and distinct fingerprint profiles, which further showed the reliability of SSR markers for identification of mung bean varieties.

UPGMA results for the 151 mung bean varieties in Northeast China based on 8 SSR markers

PCA of the 151 mung bean varieties from Northeast China

Construction of the SSR‐based fingerprint database and query system

To distinguish the 151 mung bean varieties from one another, we analyzed the DNA fragments amplified by eight markers. All of the 151 mung bean varieties could be completely distinguished and showed unique fingerprint patterns, indicating the utility of these eight SSR markers in the identification of mung bean (Appendix 3). The SSR fingerprint of each variety was converted into a digital fingerprint following computer language (1, presence; 0, absence). Each mung bean variety was described with a binary matrix that could be easily processed by a computer (Appendix 4). The fingerprint patterns of some samples tested with eight markers are shown in Figure .

SSR fingerprint patterns for some mung bean varieties

The alleles amplified by the eight markers were arranged in ascending order and numbered from 1 to 9 (named from A to Z in the case of more than nine amplified alleles) to form a unique ID card for each sample. For example, seven alleles were detected in which the smallest fragment was 195 bp and the largest fragment was 211 bp using X20; therefore, the 195‐bp genotype was assigned 1, and the 211‐bp genotype was assigned 7. In contrast, loci with no genotypes were recorded as *. The ID cards of 151 mung bean varieties are shown in Appendix 4. The string based on the order of the eight primers was converted into a unique DNA barcode for each variety using bar coding technology that contained a system code, an accession name, an origin region, unique fingerprint data, and a unique ID. For example, the DNA barcode for Zhong Lv Dou (C0831) is shown in Figure .

Barcode of the molecular identification card for Zhong Lv Dou (C0831)

A query system (https://www.bomeng.ink/gct) was established according to the fingerprint database. When the ID number of an unknown variety is put into this system and the "Compute" button is clicked, the related information and genetic similarity index of the three varieties that are most closely related to the unknown variety tested will appear in the result box of the system. Based on the results in the system, whether the unknown variety is an existing variety (similarity: 100%) in the fingerprint database from Northeast China can be assessed and it also could be determined where the unknown variety might come from based on the three most closely related varieties if the variety is not included in the fingerprint database.

To verify the identification ability of SSR markers and the application of the DNA database, six blind‐selected mung bean samples were collected and assigned letters from A to F. Samples A, B, and C were ambiguously called “mung bean.” Samples D and E were uniformly called “Xiao Lv Dou” and had the same name as several varieties in the query system database. Sample F was called “Da Ye Lv.” Eight core SSR markers were used to analyze the six blind‐selected mung bean samples and revealed their unique fingerprint patterns, indicating that the samples could be completely distinguished by the six core SSR markers. When the data were entered into the query system, samples B and C showed the same ID as Da Lv Dou (C0826) and Ying Ge Dou (C0733), respectively, figuring out what the unknown samples are. Although samples D and E had the same name as some varieties in the query system, their IDs were different, indicating the existence of homonym issues. Samples A and F were not included in the database based on the fact that their IDs were not matched in the system. The three varieties with the highest similarity to sample A in the database were Lv Dou (C3766; 89.831%), Lv Dou (C0601; 86.441%), and Lv Dou (C3772; 84.746%), which were all collected from the Mongolia Autonomous Region; therefore, it is inferred that sample A may also come from Mongolia Autonomous Region.

DISCUSSION

As one of the most popular molecular technologies, SSR markers have the advantages of high polymorphism, codominance, and good reproducibility compared with other technologies and thus play a significant role in genetic assessment (Cheng et al., ). Therefore, SSR have been widely applied for identification and diversity analysis in many crop species, including rice (Ahmed, Joel, Wariara, & Steven, ), soybean (Chakraborty, Patel, Parmar, Dhaduk, & Sasidharan, ), cotton (Bilwal, Vadodariya, & Rajkumar, ), and Ethiopian cowpea (Gupta & Gopalakrishna, ), and many other plant species, including cherry (Liang et al., ), sweet potato (Wang et al., ), and Populus deltoides (Liu et al., ). For mung bean, there have been some research reports on genetic diversity (Chontira, Akito, Norihiko, Duncan, & Peerasak, ), genetic linkage map construction (Liu, Liu, et al., ) and disease susceptibility (Akbar, Aslam, Atif, & Nawaz‐Ul‐Rehman, ), but SSR fingerprinting for identification has been rarely reported. In our study, PCR products were analyzed by an ABI 3730, which enabled the exact size of the target DNA fragments to be obtained with automatic collection and data processing. Such a method overcomes the deficiency of the silver staining method and can distinguish 1–2 bp fragments, which has overwhelming advantages, including time and labor savings and a higher efficiency and accuracy compared with conventional gels or PAGE.

The effectiveness and success of SSR rely considerably on the quality of the markers and the accuracy of the genotyping data. In this study, we focused on the selection of primers and selected eight primer pairs from 200 SSR markers for further analysis. PIC is an important index for the assessment of effectiveness of SSR markers that reflects their polymorphism information. The PIC value ranged from 0.385 to 0.781, with an average of 0.560, which was much greater than the value reported in several previous studies of mung bean varieties (Liu et al., ; Ren, Cheng, Xu, Gao, & Shang, ; Wang, Cheng, Wang, Liu, & Liang, ), implying that these eight SSR markers are more informative and have higher discriminatory power. This is possibly because some of these SSR motifs are located in the nontranscribed regions with a relatively low level of conservation (Liu, Liu, et al., ). Another explanation is that the higher resolution of the capillary DNA fragments contributed tremendously to the higher polymorphism used to score alleles, which is consistent with the theory that capillary electrophoresis can minimize the chance of scoring undesirable alleles (Pan, Cordeiro, Richard, & Henry, ).

In this study, a genetic toolkit for mung bean identification consisting of eight primer pairs was developed and could completely distinguish each of 151 mung bean varieties according to their unique electrophoresis profiles. In addition, these varieties could be identified with very high accuracy due to their ideal genotype frequencies at the molecular level (Appendix 2). Among these eight markers, X55, X46, and X148 showed strong discrimination ability, with more alleles amplified than the average. By contrast, X34, X62, and X87 were less informative. The PD values for these eight SSR markers ranged from 0.523 to 0.862, with an average of 0.645, which provided quantitative information with which to measure the genetic diversity and construct the fingerprints. The eight primer pairs were grouped into combinations of 3–7 pairs based on a stepwise increase to test their identification rate among the 151 mung bean varieties, which achieves the goal of distinguishing the most varieties using the smallest number of primers. The number of primers greatly influenced the identification ability of the primer combinations, whereby specific combinations of primers with high informativeness significantly improved the identification rates. It is thus clear that the selection of appropriate primers is important for identifying mung bean varieties and for further fingerprint construction. However, the identification rate can decrease with a continuous increase in the number of varieties, and some samples can have the same fingerprint, making them difficult to distinguish (Li et al., ). Thus, it is crucial to update and replace the core primer group continuously to ensure its identification efficiency and ability.

PI is an important parameter revealing the average probability of two random individuals sharing the same genotype, while PIs reflects the overall probability of finding two individuals with the same genotype in a population due to chance. PI and PIs are two important parameters for evaluating the power of fingerprinting in molecular technology (Tan et al., ). In our study, the combined PI of eight markers was 1.49 × 10^–5, meaning that it was almost impossible to find two random samples sharing the same fingerprint profile. Notably, the PI values were influenced by the existence of the population substructure, and the assumption of independent segregation of loci is just estimated, so, the theoretical PI may have been overestimated. Therefore, it is important to select mung bean varieties with high genetic variation to reduce the influence of population substructure. PIs is the conservative upper boundary of PI, which was also relatively low (6.41 × 10^–3) in our study. It has been suggested that a PI of 1 × 10^–4 to 1 × 10^–2 is sufficiently low for most natural populations (Tan et al,), which revealed that the PI and PIs of these eight core markers in our study were sufficiently low for fingerprinting construction of the 151 mung bean varieties; thus, these eight core markers should be adequate to discriminate all samples in this study.

In the present study, the genetic similarity ranged from 0.682 to 0.985, with an average of 0.853, based on UPGMA analysis and PCA, reflecting the genetic relationships among the 151 mung bean varieties. The results revealed that the mung bean varieties evaluated in this study could not be clustered by their regions of origin. The lack of or weak relatedness of varieties from the same region have occurred may be due to the fact that elite varieties are reused frequently and germplasm is exchanged extensively among different geographical regions, which leads to a narrow genetic background and results in many mixed groups, which was consistent with the result of some previous studies in mung bean. Gwag et al. () used 15 newly developed SSR markers to detect genetic variation in mung bean, and the clustering pattern was not strongly consistent with the geographical origins. Similar results were reported by Poehlman ( ), who indicated that geographic diversity of geographic origins was not always held in mung bean since many strains were distributed extensively and their origin is frequently obscured. Malhotra, Singh, and Singh () failed to identify associations between genetic and geographical diversity in germplasm. Chen, DeL, and Li () assessed the genetic diversity of 59 olive samples, and most varieties did not cluster according to geographical origin but according to the main materials used, which was consistent with the results of previous studies by Besnard, Breton, Baradat, and Bervillé () and Rotondi, Magli, Ricciolini, and Baldoni (). Therefore, genetic relationships are related not only to the geographical sources of the samples but also to other factors, such as plant taxonomical characteristics, the growth environment, function, and energy use. Furthermore, the number of primers was slightly low and the polymorphism of primers was insufficient in this study, which may also have prevented the primers from depicting the genome information well. Therefore, the development of more primers with high polymorphism will be helpful in clarifying the genetic relationships and genetic background of mung bean varieties. Moreover, Northeast China may be dominated mainly by the genetic background of the Inner Mongolia Autonomous Region, which exhibited the highest genetic similarity (0.800) among the regions. The genetic diversity of these varieties may reflect their genetic backgrounds, but a weaker association with geographical diversity may result from dispersal and a wide distribution. The genetic similarity of mung bean varieties in Northeast China is clearly relatively high, and the genetic diversity is not sufficiently rich. The genetic differences among varieties in the same geographical areas tended to be small, and there was a certain degree of inbreeding. Therefore, on the one hand, it is necessary to increase the collection and preservation of high‐quality mung bean resources in Northeast China to protect the genetic diversity of the resources; on the other hand, it is necessary to strengthen germplasm innovation and introduce and utilize the abundant mung bean germplasm resources in other regions to broaden the genetic diversity needed for mung bean breeding.

In this study, alleles amplified by eight specific primers were arranged and used to produce ID cards, which illustrated the abstract genetic differences among varieties and made these genetic characteristics simpler and more intuitive. Additionally, as one of the new technologies in identification that has not yet been applied in mung bean, DNA barcodes were from unique strings, which could be identified rapidly and conveniently using a barcode scanning machine, instead of reading the 0/1 strings by eye, which prevented the issues associated with manual reading and the influence of the surrounding environment. In addition, there are some issues in the mung bean market in China, such as some varieties with differences in parentage, amounts of nutrients and uses having the same name. A query system was established that could identify unknown mung bean varieties directly and accurately that also can be replenished and updated when new varieties are generated to enrich the database, enhancing the identification ability of this query system. Undoubtedly, the wide application of SSR fingerprinting, molecular ID cards, and the query system is of great significance for germplasm resource management and intellectual property right protection. Thus far, there are few related research reports on the application of SSR fingerprinting in mung bean varieties.

Varieties are members of a species with some characteristics that distinguish them from one another. They are of the same species but have different physical characteristics and usually are from different geographic regions. Accessions are collections of germplasm used as test material when collecting, preserving, identifying, and evaluating germplasm resources, and their core value lies in certain DNA sequences that can express certain traits (Wu, ). In this study, we screened eight pairs of highly polymorphic SSR primers to develop a powerful toolkit for genetic diversity analysis and SSR fingerprinting of 151 mung bean varieties from Northeast China, which enriched the mung bean primer resources that can be used for identification, traceability management, protection of origins, and intellectual property rights. The results also provide essential technical support for revealing the level of genetic diversity and the degree of differentiation at the molecular level and providing a preliminary reference for breeding and germplasm innovation and rational utilization of mung bean varieties in Northeast China.

ACKNOWLEDGMENT

Major project of Applied Technology and Development in Heilongjiang Province (GA14B104).

CONFLICT OF INTEREST

None declared.

1 APPENDIX

Detailed information on the 151 samples

Order number	System number	Accession name	Code	Origin region
1	C0831	Zhonglvdou	HLJ10	Heilongjiang Province
2	C0832	Lvdou	HLJ11	Heilongjiang Province
3	C0369	Heilongjiang3	HLJ2	Heilongjiang Province
4	C0843	XiaoLiLvDou3	HLJ21	Heilongjiang Province
5	C0844	XiaoLvDou	HLJ22	Heilongjiang Province
6	C0845	DaLvDou	HLJ23	Heilongjiang Province
7	C0849	62Lv3	HLJ27	Heilongjiang Province
8	C0852	63Lv8	HLJ29	Heilongjiang Province
9	C0370	Heilongjiang4	HLJ3	Heilongjiang Province
10	C0854	63Lv10	HLJ30	Heilongjiang Province
11	C0856	63Lv17	HLJ31	Heilongjiang Province
12	C0858	XiaoLvDou	HLJ33	Heilongjiang Province
13	C0859	XiaoLvDou	HLJ34	Heilongjiang Province
14	C0826	DaLvDou	HLJ5	Heilongjiang Province
15	C0827	DaliLvDou	HLJ6	Heilongjiang Province
16	C0688	LvDou	JL1	Jilin Province
17	C0706	XiaoYingGeDou	JL13	Jilin Province
18	C0708	XiaoLvDou	JL15	Jilin Province
19	C0709	DaYanLvDou	JL16	Jilin Province
20	C0712	LvXiaoDou	JL19	Jilin Province
21	C0689	LvDou	JL2	Jilin Province
22	C0713	QingLvDou	JL20	Jilin Province
23	C0715	LvDou	JL22	Jilin Province
24	C0724	XiaoLvDou	JL24	Jilin Province
25	C0725	XiaoLvDou	JL25	Jilin Province
26	C0731	XiaoLvDou	JL27	Jilin Province
27	C0733	YingGeDou	JL29	Jilin Province
28	C0734	XiaoLvDou	JL30	Jilin Province
29	C0740	XiaoLvDou	JL31	Jilin Province
30	C0742	XiaoLvDou	JL32	Jilin Province
31	C0743	DaLvDou	JL33	Jilin Province
32	C0744	XiaoLiLvDou	JL34	Jilin Province
33	C0747	LvXiaoDou	JL36	Jilin Province
34	C0752	LvXiaoDou	JL41	Jilin Province
35	C0753	XiaoLvDou	JL42	Jilin Province
36	C0756	LvXiaoDou	JL44	Jilin Province
37	C0759	XiaoLvDou	JL46	Jilin Province
38	C0771	XiaoLvDou	JL47	Jilin Province
39	C0776	HuangLvDou	JL48	Jilin Province
40	C0778	HuangLvDou	JL49	Jilin Province
41	C0693	JiDou	JL5	Jilin Province
42	C4448	GCM8703‐H‐3	JL55	Jilin Province
43	C0694	DaLvDou	JL6	Jilin Province
44	C4456	GCM8703‐H‐8	JL63	Jilin Province
45	C4458	GCM8708‐2–1	JL65	Jilin Province
46	C0721	XiaoLvDou	JL68	Jilin Province
47	C0723	XiaoLvDou	JL69	Jilin Province
48	C0700	YingGeDou	JL7	Jilin Province
49	C0722	XiaoLvDou	JL70	Jilin Province
50	C0726	XiaoLvDou	JL71	Jilin Province
51	C0727	XiaoLvDou	JL72	Jilin Province
52	C0728	XiaoLvDou	JL73	Jilin Province
53	C0729	XiaoLvDou	JL74	Jilin Province
54	C0702	XiaoLvDou	JL9	Jilin Province
55	C0661	YingGeDou	LN1	Liaoning Province
56	C0672	LvDou	LN10	Liaoning Province
57	C0673	LvDou	LN11	Liaoning Province
58	C0674	YingGeDou	LN12	Liaoning Province
59	C0676	LvDou	LN13	Liaoning Province
60	C0677	XiaoLvDou	LN14	Liaoning Province
61	C0786	YingGeDou	LN17	Liaoning Province
62	C0787	MingLvDou	LN18	Liaoning Province
63	C0663	XiaoLvDou	LN2	Liaoning Province
64	C3808	LvDou	LN23	Liaoning Province
65	C3809	XiaoLvDou	LN24	Liaoning Province
66	C3811	LvDou	LN26	Liaoning Province
67	C3812	LvDou	LN27	Liaoning Province
68	C3813	LvDou	LN28	Liaoning Province
69	C3814	LvDou	LN29	Liaoning Province
70	C0664	MingLvYuAnLv	LN3	Liaoning Province
71	C3815	LvDou	LN30	Liaoning Province
72	C3817	LvDou	LN32	Liaoning Province
73	C3818	WuLvDou	LN33	Liaoning Province
74	C3819	LvDou	LN34	Liaoning Province
75	C3823	LvDou	LN35	Liaoning Province
76	C3825	LvDou	LN37	Liaoning Province
77	C3826	LvDou	LN38	Liaoning Province
78	C3829	LvDou	LN41	Liaoning Province
79	C3832	LvDou	LN42	Liaoning Province
80	C3835	LvDou	LN44	Liaoning Province
81	C3837	LvDou	LN45	Liaoning Province
82	C3839	LvDou	LN47	Liaoning Province
83	C0667	XiaoLvDou	LN5	Liaoning Province
84	C0668	DaLvDou	LN6	Liaoning Province
85	C0669	XiaoLvDou	LN7	Liaoning Province
86	C0670	XiaoLvDou	LN8	Liaoning Province
87	C0671	LvDou	LN9	Liaoning Province
88	C0601	LvDou	NMG1	Inner Mongolia Autonomous Region
89	C0610	LvDou	NMG10	Inner Mongolia Autonomous Region
90	C0612	XiaoLvDou	NMG12	Inner Mongolia Autonomous Region
91	C0613	LvDou	NMG13	Inner Mongolia Autonomous Region
92	C0614	LvDou	NMG14	Inner Mongolia Autonomous Region
93	C0615	YingGeDou	NMG15	Inner Mongolia Autonomous Region
94	C0616	LvDou	NMG16	Inner Mongolia Autonomous Region
95	C0617	LvDou	NMG17	Inner Mongolia Autonomous Region
96	C0618	LvDou	NMG18	Inner Mongolia Autonomous Region
97	C0619	LvDou	NMG19	Inner Mongolia Autonomous Region
98	C0602	XiaoLvDou	NMG2	Inner Mongolia Autonomous Region
99	C0622	LvDou	NMG22	Inner Mongolia Autonomous Region
100	C0623	LvDou	NMG23	Inner Mongolia Autonomous Region
101	C0624	XiaoLvDou	NMG24	Inner Mongolia Autonomous Region
102	C0626	DangDiJiDou	NMG26	Inner Mongolia Autonomous Region
103	C0629	XiaoLvDou	NMG29	Inner Mongolia Autonomous Region
104	C0630	XiaoLvDou	NMG30	Inner Mongolia Autonomous Region
105	C0631	XiaoLvDou	NMG31	Inner Mongolia Autonomous Region
106	C0632	XiaoLvDou	NMG32	Inner Mongolia Autonomous Region
107	C0633	XiaoLvDou	NMG33	Inner Mongolia Autonomous Region
108	C0634	XiaoLvDou	NMG34	Inner Mongolia Autonomous Region
109	C0636	XiaoLvDou	NMG36	Inner Mongolia Autonomous Region
110	C0637	DaBaJiao	NMG37	Inner Mongolia Autonomous Region
111	C0638	XiaoMingLvDou	NMG38	Inner Mongolia Autonomous Region
112	C0604	LvDou	NMG4	Inner Mongolia Autonomous Region
113	C0644	LvDou	NMG43	Inner Mongolia Autonomous Region
114	C0645	WuDou	NMG44	Inner Mongolia Autonomous Region
115	C0646	MaoJiaoLvDou	NMG45	Inner Mongolia Autonomous Region
116	C0647	XiaoLvDou	NMG46	Inner Mongolia Autonomous Region
117	C0648	XiaoLvDou	NMG47	Inner Mongolia Autonomous Region
118	C0656	XiaoLvDou	NMG49	Inner Mongolia Autonomous Region
119	C0605	XiaoLvDou	NMG5	Inner Mongolia Autonomous Region
120	C0660	MaoLvDou	NMG52	Inner Mongolia Autonomous Region
121	C0678	LvDou	NMG53	Inner Mongolia Autonomous Region
122	C0680	DaMinLvDou	NMG54	Inner Mongolia Autonomous Region
123	C0681	LvDou	NMG55	Inner Mongolia Autonomous Region
124	C0684	LvDou	NMG58	Inner Mongolia Autonomous Region
125	C0686	WuLvDou	NMG59	Inner Mongolia Autonomous Region
126	C0606	LvDou	NMG6	Inner Mongolia Autonomous Region
127	C3751	XiaoHuiLvDou	NMG60	Inner Mongolia Autonomous Region
128	C3753	LvDou	NMG62	Inner Mongolia Autonomous Region
129	C3757	LvDou	NMG66	Inner Mongolia Autonomous Region
130	C3760	DaLvDou	NMG69	Inner Mongolia Autonomous Region
131	C0607	LvDou	NMG7	Inner Mongolia Autonomous Region
132	C3761	LvDou	NMG70	Inner Mongolia Autonomous Region
133	C3763	LvDou	NMG72	Inner Mongolia Autonomous Region
134	C3764	LvDou	NMG73	Inner Mongolia Autonomous Region
135	C3765	HuiPiLvDou	NMG74	Inner Mongolia Autonomous Region
136	C3766	LvDou	NMG75	Inner Mongolia Autonomous Region
137	C3767	XiaoLvDou	NMG76	Inner Mongolia Autonomous Region
138	C3768	DaLvDou	NMG77	Inner Mongolia Autonomous Region
139	C3769	LvDou	NMG78	Inner Mongolia Autonomous Region
140	C3770	HuiLvDou	NMG79	Inner Mongolia Autonomous Region
141	C0608	LvDou	NMG8	Inner Mongolia Autonomous Region
142	C3772	LvDou	NMG81	Inner Mongolia Autonomous Region
143	C3773	XiaoLvDou	NMG82	Inner Mongolia Autonomous Region
144	C3774	DaLvDou	NMG83	Inner Mongolia Autonomous Region
145	C3776	LvDou	NMG85	Inner Mongolia Autonomous Region
146	C3777	XiaoLvDou	NMG86	Inner Mongolia Autonomous Region
147	C3778	HuiPiLvDou	NMG87	Inner Mongolia Autonomous Region
148	C3779	LvDou	NMG88	Inner Mongolia Autonomous Region
149	C3782	HuiLvDou	NMG91	Inner Mongolia Autonomous Region
150	C3783	MingLvDou	NMG92	Inner Mongolia Autonomous Region
151	C3784	LvDou	NMG93	Inner Mongolia Autonomous Region

2 APPENDIX

Genotype frequencies of 151 mungbean varieties at each SSR locus

Sample	Genotype frequency with each primer	Error for discrimination
X20	X34	X46	X55	X62	X87	X148	X168
HLJ10	0.490	0.111	0.040	0.004	0.040	0.218	0.640	0.360	1.9E‐08
HLJ11	0.090	0.111	0.054	0.071	0.640	0.218	0.640	0.040	1.4E‐07
HLJ2	0.490	0.444	0.171	0.004	0.640	0.218	0.640	0.040	5.9E‐07
HLJ21	0.420	0.444	0.054	0.071	0.640	0.218	0.640	0.360	2.3E‐05
HLJ22	0.490	0.444	0.054	0.071	0.640	0.218	0.640	0.360	2.7E‐05
HLJ23	0.490	0.444	0.004	0.218	0.640	0.218	0.040	0.360	4.2E‐07
HLJ27	0.090	0.111	0.004	0.071	0.640	0.218	0.640	0.040	1.1E‐08
HLJ29	0.490	0.111	0.134	0.018	0.640	0.218	0.640	0.360	4.2E‐06
HLJ3	0.490	0.444	0.134	0.218	0.640	0.004	0.640	0.028	3.2E‐07
HLJ30	0.090	0.444	0.004	0.218	0.040	0.218	0.640	0.040	8.6E‐09
HLJ31	0.490	0.444	0.040	0.218	0.640	0.218	0.640	0.360	6.1E‐05
HLJ33	0.090	0.444	0.040	0.018	0.040	0.218	0.640	0.028	4.4E‐09
HLJ34	0.490	0.444	0.134	0.218	0.640	0.218	0.640	0.200	1.1E‐04
HLJ5	0.490	0.444	0.134	0.218	0.640	0.218	0.040	0.360	1.3E‐05
HLJ6	0.490	0.111	0.134	0.218	0.640	0.218	0.040	0.360	3.2E‐06
JL1	0.593	0.333	0.168	0.003	0.605	0.290	0.138	0.304	6.8E‐07
JL13	–	0.179	0.168	–	–	0.290	0.138	0.304	3.7E‐04
JL15	0.593	0.333	0.168	0.117	–	0.001	0.006	0.011	1.6E‐10
JL16	0.593	0.179	0.037	0.117	0.605	0.148	0.263	0.003	2.8E‐08
JL19	0.593	0.179	0.020	0.025	0.038	0.003	0.263	0.072	1.0E‐10
JL2	0.593	0.488	0.168	0.039	0.605	0.414	0.138	0.297	2.0E‐05
JL20	0.593	0.333	0.168	0.001	0.001	0.290	0.263	0.304	4.1E‐10
JL22	0.593	0.179	0.037	0.117	0.605	0.148	0.263	0.072	7.8E‐07
JL24	0.018	0.488	0.116	0.021	0.605	0.414	0.039	0.297	6.3E‐08
JL25	0.003	0.333	0.032	0.117	0.605	0.290	0.263	0.072	1.2E‐08
JL27	0.001	0.333	0.037	0.135	0.605	0.290	0.006	0.304	3.8E‐10
JL29	0.003	0.333	0.168	0.039	0.038	0.290	0.263	0.304	5.6E‐09
JL30	0.593	0.333	0.168	0.003	0.605	0.290	0.381	0.304	1.9E‐06
JL31	0.593	0.333	0.003	0.025	0.038	0.290	0.263	0.304	1.1E‐08
JL32	0.593	0.179	0.020	0.025	0.038	0.290	0.263	0.304	4.6E‐08
JL33	0.018	0.179	0.020	0.003	0.605	0.003	0.138	0.072	2.9E‐12
JL34	0.593	0.333	0.147	0.135	0.605	0.148	0.138	0.297	1.4E‐05
JL36	0.021	0.488	0.037	0.004	0.605	0.148	0.263	0.297	1.1E‐08
JL41	0.593	0.179	0.168	0.117	0.605	0.148	0.263	0.072	3.6E‐06
JL42	0.593	0.333	0.020	0.025	0.605	0.290	0.263	0.304	1.4E‐06
JL44	0.593	0.488	0.032	0.135	0.605	0.414	0.138	0.304	1.3E‐05
JL46	0.593	0.179	0.037	0.001	0.605	0.148	0.006	0.304	4.4E‐10
JL47	0.593	0.488	0.020	0.006	0.038	0.290	0.263	0.297	3.1E‐08
JL48	0.593	0.333	0.001	0.025	0.038	0.290	0.263	0.304	2.8E‐09
JL49	0.018	0.179	0.032	0.117	0.605	0.148	0.263	0.304	8.8E‐08
JL5	–	0.333	0.032	0.039	–	0.148	0.138	0.001	5.6E‐09
JL55	0.593	0.333	0.032	0.004	0.605	0.290	0.263	0.072	9.2E‐08
JL6	0.593	0.488	0.069	0.108	0.605	0.414	0.381	0.011	2.2E‐06
JL63	0.593	0.179	0.168	0.039	0.605	0.148	0.263	0.072	1.2E‐06
JL65	0.593	0.179	0.037	0.117	0.605	0.148	0.138	0.304	1.7E‐06
JL68	0.593	0.488	0.168	0.006	0.605	0.290	0.381	0.304	6.2E‐06
JL69	0.593	0.333	0.168	0.117	0.605	0.290	0.001	0.304	3.1E‐07
JL7	0.018	0.333	0.168	0.039	0.605	0.290	0.138	0.011	1.0E‐08
JL70	0.593	0.333	0.032	0.117	0.605	0.148	0.138	0.072	6.7E‐07
JL71	0.593	0.179	0.003	0.117	0.605	0.290	0.138	0.304	2.4E‐07
JL72	0.593	0.333	0.168	0.003	0.605	0.148	0.138	0.304	3.5E‐07
JL73	0.593	0.179	0.037	0.117	0.038	0.148	0.263	0.003	1.8E‐09
JL74	0.018	0.333	0.168	0.006	0.605	0.290	0.263	0.304	8.9E‐08
JL9	0.593	0.333	0.168	0.039	0.605	0.290	0.138	0.011	3.3E‐07
LN1	0.481	0.459	0.444	0.117	0.055	0.153	0.250	0.621	1.5E‐05
LN10	0.481	0.167	0.444	0.088	0.004	0.334	0.009	0.023	8.3E‐10
LN11	0.481	0.167	0.444	0.088	0.391	0.153	0.250	0.023	1.1E‐06
LN12	0.481	0.314	0.006	0.035	0.391	0.334	0.004	0.621	9.7E‐09
LN13	0.004	0.314	0.033	0.088	0.391	0.153	0.020	0.621	2.8E‐09
LN14	0.026	0.314	0.033	0.035	0.391	0.153	0.020	0.621	7.0E‐09
LN17	0.026	0.314	0.444	0.098	0.001	0.334	0.250	0.621	1.8E‐08
LN18	0.481	0.314	0.444	0.004	0.002	0.334	0.250	0.621	3.0E‐08
LN2	0.481	0.167	0.444	0.098	0.055	0.153	0.250	0.004	2.7E‐08
LN23	0.481	0.314	0.444	0.098	0.391	0.153	0.035	0.621	8.5E‐06
LN24	0.481	0.314	0.020	0.039	0.391	0.452	0.250	0.621	3.3E‐06
LN26	0.045	0.459	0.444	0.098	0.391	0.452	0.035	0.621	3.4E‐06
LN27	0.481	0.167	0.001	0.004	0.391	0.334	0.035	0.621	8.2E‐10
LN28	0.481	0.167	0.444	0.004	0.055	0.153	0.009	0.023	2.4E‐10
LN29	0.026	0.167	0.444	0.098	0.391	0.334	0.035	0.621	5.4E‐07
LN3	0.026	0.167	0.006	0.035	0.391	0.334	0.004	0.621	2.8E‐10
LN30	0.481	0.167	0.444	0.088	0.391	0.334	0.250	0.621	6.4E‐05
LN32	0.481	0.167	0.444	0.098	0.391	0.334	0.020	0.621	5.6E‐06
LN33	0.481	0.314	0.444	0.088	0.055	0.334	0.250	0.621	1.7E‐05
LN34	0.481	0.167	0.444	0.098	0.391	0.334	0.035	0.621	1.0E‐05
LN35	0.004	0.167	0.444	0.098	0.391	0.334	0.035	0.621	8.6E‐08
LN37	0.045	0.314	0.028	0.088	0.391	0.153	0.250	0.621	3.2E‐07
LN38	0.481	0.314	0.033	0.035	0.391	0.334	0.250	0.621	3.6E‐06
LN41	–	0.314	0.444	0.004	0.391	0.334	0.250	0.621	1.1E‐05
LN42	0.481	0.314	0.444	0.004	0.391	0.001	0.250	0.621	1.6E‐08
LN44	0.026	0.314	0.033	0.088	0.391	0.153	0.250	0.621	2.2E‐07
LN45	0.481	0.459	0.444	0.037	0.022	0.334	0.250	0.621	4.1E‐06
LN47	–	0.001	0.001	–	–	–	–	0.004	3.1E‐09
LN5	0.481	0.314	0.242	0.088	0.055	0.153	0.250	0.239	1.6E‐06
LN6	0.481	0.314	0.444	0.088	0.004	0.334	0.009	0.023	1.6E‐09
LN7	0.022	0.314	0.033	0.006	0.055	0.452	0.004	0.239	3.5E‐11
LN8	0.481	0.167	0.444	0.035	0.055	0.452	0.020	0.621	3.8E‐07
LN9	0.001	0.314	0.444	0.098	0.391	0.452	0.250	0.621	3.9E‐07
NMG1	0.005	0.381	0.006	0.116	0.334	0.027	0.002	0.053	1.6E‐13
NMG10	0.041	0.381	0.006	0.116	0.334	0.191	0.316	0.300	7.0E‐08
NMG12	0.005	0.381	0.545	0.018	0.012	0.191	0.316	0.053	7.2E‐10
NMG13	0.030	0.141	0.000	0.022	0.334	0.191	0.316	0.008	3.5E‐12
NMG14	0.030	0.381	0.545	0.061	0.334	0.098	0.316	–	3.8E‐06
NMG15	0.171	0.141	0.545	0.092	0.334	0.273	0.044	0.053	2.6E‐07
NMG16	0.171	0.141	0.000	0.116	0.334	0.191	0.316	0.053	7.6E‐10
NMG17	0.030	0.381	0.545	0.116	0.334	0.191	0.316	0.053	7.7E‐07
NMG18	0.043	0.463	–	0.008	0.334	0.103	0.002	0.252	2.9E‐09
NMG19	0.171	0.463	0.545	0.092	0.334	0.273	0.044	0.300	4.8E‐06
NMG2	0.041	0.381	0.545	0.061	0.048	0.191	0.003	0.011	1.5E‐10
NMG22	0.058	0.463	0.545	0.004	0.334	0.273	0.020	0.300	3.2E‐08
NMG23	0.003	0.141	0.010	0.016	0.334	0.273	0.035	0.053	1.1E‐11
NMG24	0.005	0.141	0.006	0.116	0.334	0.191	0.316	0.053	5.5E‐10
NMG26	0.030	0.141	0.545	0.116	0.334	0.191	0.316	0.053	2.8E‐07
NMG29	0.171	0.381	0.545	0.116	0.334	0.273	0.002	0.008	4.4E‐09
NMG30	0.016	0.010	0.004	0.060	0.334	0.273	0.316	0.300	3.1E‐10
NMG31	0.041	0.381	0.545	0.168	0.048	0.273	0.004	0.113	9.1E‐09
NMG32	0.171	0.463	0.545	0.004	0.334	0.273	0.316	0.300	1.5E‐06
NMG33	0.171	0.381	0.545	0.005	0.334	0.191	0.020	0.300	6.9E‐08
NMG34	0.016	0.381	0.001	0.116	0.009	0.098	0.316	0.300	5.7E‐11
NMG36	0.171	0.141	0.545	0.168	0.012	0.273	0.044	0.300	9.5E‐08
NMG37	0.030	0.381	0.004	0.061	0.334	0.191	0.316	0.008	4.2E‐10
NMG38	0.171	0.381	0.003	0.008	0.009	0.191	0.316	0.300	2.5E‐10
NMG4	0.030	0.381	0.545	0.061	0.048	0.027	0.003	0.011	1.5E‐11
NMG43	0.016	0.463	0.545	0.116	0.334	0.191	0.316	0.300	2.8E‐06
NMG44	0.016	0.463	0.545	0.031	0.334	0.273	0.316	0.300	1.1E‐06
NMG45	0.041	0.141	0.545	0.061	0.334	0.273	0.316	0.300	1.7E‐06
NMG46	0.171	0.381	0.545	0.116	0.009	0.098	0.316	0.300	3.4E‐07
NMG47	0.171	0.381	0.545	0.092	0.009	0.098	0.316	0.300	2.7E‐07
NMG49	0.041	0.141	0.003	0.061	0.009	0.098	0.316	0.300	8.8E‐11
NMG5	0.005	0.381	0.545	0.005	0.048	0.191	0.020	0.011	1.0E‐11
NMG52	0.171	0.463	0.545	0.019	0.334	0.098	0.020	0.252	1.4E‐07
NMG53	0.171	0.381	0.545	0.168	0.334	0.191	0.020	0.300	2.3E‐06
NMG54	0.171	0.141	0.545	0.008	0.012	0.098	0.020	0.300	6.9E‐10
NMG55	0.171	0.381	0.094	0.061	0.012	0.273	0.316	0.300	1.2E‐07
NMG58	0.171	0.141	0.006	0.018	0.334	0.191	0.316	0.300	1.7E‐08
NMG59	0.171	0.381	0.545	0.008	0.012	0.098	0.316	0.300	3.0E‐08
NMG6	0.002	0.381	0.545	0.035	0.048	0.001	0.003	0.008	1.5E‐14
NMG60	0.171	0.381	0.545	0.116	0.334	0.191	0.020	0.300	1.6E‐06
NMG62	0.171	0.381	0.545	0.116	0.334	0.191	0.002	0.300	1.7E‐07
NMG66	0.030	0.141	0.545	0.004	0.048	0.024	0.316	0.011	3.7E‐11
NMG69	0.171	0.381	0.545	0.116	0.334	0.027	0.002	0.300	2.5E‐08
NMG7	0.171	0.463	0.545	0.049	0.334	0.273	0.316	0.008	4.6E‐07
NMG70	0.171	0.381	0.545	0.116	0.334	0.098	0.316	0.300	1.3E‐05
NMG72	0.030	0.381	0.545	0.061	0.048	0.027	0.316	0.018	2.7E‐09
NMG73	0.171	0.381	0.545	0.024	0.334	0.191	0.018	0.011	1.0E‐08
NMG74	0.171	0.141	0.004	0.001	0.048	0.000	0.316	0.053	1.9E‐14
NMG75	0.041	0.381	0.545	0.061	0.334	0.027	0.002	0.053	3.8E‐10
NMG76	0.041	0.381	0.545	0.018	0.334	0.027	0.316	0.300	1.3E‐07
NMG77	0.030	0.381	0.545	0.116	0.334	0.027	0.002	0.300	4.2E‐09
NMG78	0.171	0.141	0.545	0.001	0.334	0.098	0.316	0.300	2.3E‐08
NMG79	0.171	0.141	0.545	0.005	0.012	0.024	0.004	0.300	2.0E‐11
NMG8	0.030	0.141	0.009	0.060	0.334	0.191	0.316	0.300	1.3E‐08
NMG81	0.016	0.381	0.545	0.061	0.048	0.027	0.001	0.053	1.3E‐11
NMG82	0.171	0.141	0.545	0.009	0.048	0.024	0.316	0.001	2.5E‐11
NMG83	0.041	0.141	0.545	0.018	0.048	0.001	0.002	0.053	2.2E‐13
NMG85	0.041	0.381	0.003	0.018	0.012	0.027	0.316	0.300	2.7E‐11
NMG86	0.016	0.141	0.545	0.061	0.334	0.098	0.316	0.300	2.2E‐07
NMG87	0.016	0.381	0.001	0.116	0.334	0.273	0.316	0.300	6.1E‐09
NMG88	0.041	0.141	0.545	–	0.009	0.002	0.020	0.300	2.5E‐10
NMG91	0.041	0.381	0.545	0.018	0.048	0.191	0.004	0.053	3.0E‐10
NMG92	0.041	0.381	0.545	0.061	0.048	0.191	0.004	0.002	3.0E‐11
NMG93	0.041	0.381	0.545	0.061	0.048	0.027	0.004	0.011	2.8E‐11

Note: “–” means no data.

3 APPENDIX

The amplification result of 8 primer pairs among 151 mung bean varieties

	X20(bp)	X34(bp)	X46(bp)	X55(bp)	X62(bp)	X87(bp)	X148(bp)	X168(bp)
HLJ10	199	199	145	145	115	115	144	144	185	185	221	221	194	194	163	163
HLJ11	201	201	145	145	121	121	142	142	187	187	215	215	194	194	209	209
HLJ2	199	199	141	141	113	121	135	135	187	187	215	215	194	194	163	207
HLJ21	201	201	141	141	121	121	142	142	187	187	221	221	194	194	163	163
HLJ22	199	199	141	141	121	121	142	142	187	187	221	221	194	194	163	163
HLJ23	199	199	141	141	127	127	133	133	187	187	215	215	190	190	163	163
HLJ27	201	201	145	145	123	123	142	142	187	187	215	215	194	194	209	209
HLJ29	199	199	145	145	113	113	139	139	187	187	221	221	194	194	163	163
HLJ3	199	199	141	141	113	113	133	133	187	187	223	223	194	194	211	211
HLJ30	201	201	141	141	125	125	133	133	185	185	215	215	194	194	209	209
HLJ31	199	199	141	141	115	115	133	133	187	187	215	215	194	194	163	163
HLJ33	201	201	141	141	115	115	139	139	185	185	215	215	194	194	211	211
HLJ34	199	199	141	141	113	113	133	133	187	187	221	221	194	194	163	211
HLJ5	199	199	141	141	113	113	133	133	187	187	221	221	190	190	163	163
HLJ6	199	199	145	145	113	113	133	133	187	187	221	221	190	190	163	163
JL1	199	199	145	145	113	113	131	131	187	187	221	221	190	190	163	163
JL13	–	–	141	141	113	113	–	–	–	–	221	221	190	190	163	163
JL15	199	199	145	145	113	113	133	133	–	–	223	223	192	192	161	161
JL16	199	199	141	141	115	115	133	133	187	187	215	215	194	194	211	211
JL19	199	199	141	141	121	121	142	142	185	185	213	213	194	194	209	209
JL2	199	199	141	145	113	113	144	144	187	187	215	221	190	190	163	209
JL20	199	199	145	145	113	113	148	148	189	189	221	221	194	194	163	163
JL22	199	199	141	141	115	115	133	133	187	187	215	215	194	194	209	209
JL24	197	197	141	145	113	121	135	142	187	187	215	221	188	194	163	209
JL25	201	201	145	145	125	125	133	133	187	187	221	221	194	194	209	209
JL27	203	203	145	145	115	115	133	144	187	187	221	221	192	192	163	163
JL29	201	201	145	145	113	113	144	144	185	185	221	221	194	194	163	163
JL30	199	199	145	145	113	113	131	131	187	187	221	221	190	194	163	163
JL31	199	199	145	145	123	123	142	142	185	185	221	221	194	194	163	163
JL32	199	199	141	141	121	121	142	142	185	185	221	221	194	194	163	163
JL33	197	197	141	141	121	121	146	146	187	187	213	213	190	190	209	209
JL34	199	199	145	145	113	125	133	144	187	187	215	215	190	190	163	209
JL36	195	199	141	145	115	115	135	135	187	187	215	215	194	194	163	209
JL41	199	199	141	141	113	113	133	133	187	187	215	215	194	194	209	209
JL42	199	199	145	145	121	121	142	142	187	187	221	221	194	194	163	163
JL44	199	199	141	145	125	125	133	144	187	187	215	221	190	190	163	163
JL46	199	199	141	141	115	115	139	139	187	187	215	215	192	192	163	163
JL47	199	199	141	145	121	121	137	137	185	185	221	221	194	194	163	209
JL48	199	199	145	145	119	119	142	142	185	185	221	221	194	194	163	163
JL49	197	197	141	141	125	125	133	133	187	187	215	215	194	194	163	163
JL5	–	–	145	145	125	125	144	144	–	–	215	215	190	190	207	207
JL55	199	199	145	145	125	125	135	135	187	187	221	221	194	194	209	209
JL6	199	199	141	145	115	125	133	142	187	187	215	221	190	194	161	161
JL63	199	199	141	141	113	113	144	144	187	187	215	215	194	194	209	209
JL65	199	199	141	141	115	115	133	133	187	187	215	215	190	190	163	163
JL68	199	199	141	145	113	113	137	137	187	187	221	221	190	194	163	163
JL69	199	199	145	145	113	113	133	133	187	187	221	221	188	188	163	163
JL7	197	197	145	145	113	113	144	144	187	187	221	221	190	190	161	161
JL70	199	199	145	145	125	125	133	133	187	187	215	215	190	190	209	209
JL71	199	199	141	141	123	123	133	133	187	187	221	221	190	190	163	163
JL72	199	199	145	145	113	113	146	146	187	187	215	215	190	190	163	163
JL73	199	199	141	141	115	115	133	133	185	185	215	215	194	194	211	211
JL74	197	197	145	145	113	113	137	137	187	187	221	221	194	194	163	163
JL9	199	199	145	145	113	113	144	144	187	187	221	221	190	190	161	161
LN1	199	199	141	145	113	113	139	144	185	185	215	215	194	194	163	163
LN10	199	199	141	141	113	113	142	142	183	183	221	221	204	204	209	209
LN11	199	199	141	141	113	113	142	142	187	187	215	215	194	194	209	209
LN12	199	199	145	145	115	115	139	139	187	187	221	221	196	196	163	163
LN13	201	201	145	145	121	121	142	142	187	187	215	215	192	192	163	163
LN14	197	197	145	145	121	121	139	139	187	187	215	215	192	192	163	163
LN17	197	197	145	145	113	113	144	144	181	181	221	221	194	194	163	163
LN18	199	199	145	145	113	113	146	146	189	189	221	221	194	194	163	163
LN2	199	199	141	141	113	113	144	144	185	185	215	215	194	194	161	161
LN23	199	199	145	145	113	113	144	144	187	187	215	215	190	190	163	163
LN24	199	199	145	145	113	123	133	144	187	187	215	221	194	194	163	163
LN26	199	203	141	145	113	113	144	144	187	187	215	221	190	190	163	163
LN27	199	199	141	141	125	125	133	133	187	187	221	221	190	190	163	163
LN28	199	199	141	141	113	113	146	146	185	185	215	215	204	204	209	209
LN29	197	197	141	141	113	113	144	144	187	187	221	221	190	190	163	163
LN3	197	197	141	141	115	115	139	139	187	187	221	221	196	196	163	163
LN30	199	199	141	141	113	113	142	142	187	187	221	221	194	194	163	163
LN32	199	199	141	141	113	113	144	144	187	187	221	221	192	192	163	163
LN33	199	199	145	145	113	113	142	142	185	185	221	221	194	194	163	163
LN34	199	199	141	141	113	113	144	144	187	187	221	221	190	190	163	163
LN35	201	201	141	141	113	113	144	144	187	187	221	221	190	190	163	163
LN37	199	203	145	145	115	121	142	142	187	187	215	215	194	194	163	163
LN38	199	199	145	145	121	121	139	139	187	187	221	221	194	194	163	163
LN41	–	–	145	145	113	113	137	137	187	187	221	221	194	194	163	163
LN42	199	199	145	145	113	113	137	137	187	187	223	223	194	194	163	163
LN44	197	197	145	145	121	121	142	142	187	187	215	215	194	194	163	163
LN45	199	199	141	145	113	113	133	142	185	189	221	221	194	194	163	163
LN47	–	–	143	143	107	107	–	–	–	–	–	–	–	–	161	161
LN5	199	199	145	145	113	121	142	142	185	185	215	215	194	194	163	209
LN6	199	199	145	145	113	113	142	142	183	183	221	221	204	204	209	209
LN7	199	211	145	145	121	121	139	148	185	185	215	221	192	198	163	209
LN8	199	199	141	141	113	113	139	139	185	185	215	221	192	192	163	163
LN9	195	195	145	145	113	113	144	144	187	187	215	221	194	194	163	163
NMG1	203	203	145	145	125	125	133	133	187	187	217	217	188	188	209	209
NMG10	197	197	145	145	125	125	133	133	187	187	215	215	194	194	163	163
NMG12	203	203	145	145	113	113	144	144	185	185	215	215	194	194	209	209
NMG13	201	201	141	141	123	123	133	146	187	187	215	215	194	194	161	161
NMG14	201	201	145	145	113	113	142	142	187	187	221	221	194	194	–	–
NMG15	199	199	141	141	113	113	133	144	187	187	215	221	190	194	209	209
NMG16	199	199	141	141	117	117	133	133	187	187	215	215	194	194	209	209
NMG17	201	201	145	145	113	113	133	133	187	187	215	215	194	194	209	209
NMG18	195	201	141	145	–	–	139	139	187	187	217	221	182	192	163	209
NMG19	199	199	141	145	113	113	133	144	187	187	215	221	190	194	163	163
NMG2	197	197	145	145	113	113	142	142	183	183	215	215	206	206	207	207
NMG22	199	203	141	145	113	113	131	131	187	187	215	221	192	192	163	163
NMG23	201	211	141	141	121	125	133	148	187	187	215	221	194	198	209	209
NMG24	203	203	141	141	125	125	133	133	187	187	215	215	194	194	209	209
NMG26	201	201	141	141	113	113	133	133	187	187	215	215	194	194	209	209
NMG29	199	199	145	145	113	113	133	133	187	187	215	221	190	190	161	161
NMG30	195	195	145	147	121	121	133	139	187	187	215	221	194	194	163	163
NMG31	197	197	145	145	113	113	133	142	183	183	215	221	202	206	163	207
NMG32	199	199	141	145	113	113	131	131	187	187	215	221	194	194	163	163
NMG33	199	199	145	145	113	113	137	137	187	187	215	215	192	192	163	163
NMG34	195	195	145	145	111	111	133	133	189	189	221	221	194	194	163	163
NMG36	199	199	141	141	113	113	133	142	185	185	215	221	190	194	163	163
NMG37	201	201	145	145	121	121	142	142	187	187	215	215	194	194	161	161
NMG38	199	199	145	145	115	115	139	139	189	189	215	215	194	194	163	163
NMG4	201	201	145	145	113	113	142	142	183	183	217	217	206	206	207	207
NMG43	195	195	141	145	113	113	133	133	187	187	215	215	194	194	163	163
NMG44	195	195	141	145	113	113	131	142	187	187	215	221	194	194	163	163
NMG45	197	197	141	141	113	113	142	142	187	187	215	221	194	194	163	163
NMG46	199	199	145	145	113	113	133	133	189	189	221	221	194	194	163	163
NMG47	199	199	145	145	113	113	133	144	189	189	221	221	194	194	163	163
NMG49	197	197	141	141	115	115	142	142	189	189	221	221	194	194	163	163
NMG5	203	203	145	145	113	113	137	137	183	183	215	215	192	192	207	207
NMG52	199	199	141	145	113	113	137	144	187	187	221	221	192	192	163	209
NMG53	199	199	145	145	113	113	133	142	187	187	215	215	192	192	163	163
NMG54	199	199	141	141	113	113	139	139	185	185	221	221	192	192	163	163
NMG55	199	199	145	145	113	121	142	142	185	185	215	221	194	194	163	163
NMG58	199	199	141	141	125	125	144	144	187	187	215	215	194	194	163	163
NMG59	199	199	145	145	113	113	139	139	185	185	221	221	194	194	163	163
NMG6	195	205	145	145	113	113	137	142	183	183	219	219	206	206	161	161
NMG60	199	199	145	145	113	113	133	133	187	187	215	215	192	192	163	163
NMG62	199	199	145	145	113	113	133	133	187	187	215	215	200	200	163	163
NMG66	201	201	141	141	113	113	131	131	183	183	213	221	194	194	165	209
NMG69	199	199	145	145	113	113	133	133	187	187	217	217	200	200	163	163
NMG7	199	199	141	145	113	113	133	137	187	187	215	221	194	194	161	161
NMG70	199	199	145	145	113	113	133	133	187	187	221	221	194	194	163	163
NMG72	201	201	145	145	113	113	142	142	183	183	217	217	194	194	161	207
NMG73	199	199	145	145	113	113	139	144	187	187	215	215	192	204	207	207
NMG74	199	199	141	141	121	121	146	146	183	183	223	223	194	194	209	209
NMG75	197	197	145	145	113	113	142	142	187	187	217	217	202	202	209	209
NMG76	197	197	145	145	113	113	144	144	187	187	217	217	194	194	163	163
NMG77	201	201	145	145	113	113	133	133	187	187	217	217	200	200	163	163
NMG78	199	199	141	141	113	113	148	148	187	187	221	221	194	194	163	163
NMG79	199	199	141	141	113	113	137	146	185	185	213	221	198	204	163	163
NMG8	201	201	141	141	115	125	133	139	187	187	215	215	194	194	163	163
NMG81	195	195	145	145	113	113	142	142	183	183	217	217	198	198	209	209
NMG82	199	199	141	141	113	113	131	137	183	183	213	221	194	194	165	165
NMG83	197	197	141	141	113	113	144	144	183	183	219	219	202	202	209	209
NMG85	197	197	145	145	115	115	144	144	185	185	217	217	194	194	163	163
NMG86	195	195	141	141	113	113	142	142	187	187	221	221	194	194	163	163
NMG87	195	195	145	145	111	111	133	133	187	187	215	221	194	194	163	163
NMG88	197	197	141	141	113	113	–	–	189	189	213	213	192	192	163	163
NMG91	197	197	145	145	113	113	144	144	183	183	215	215	204	204	209	209
NMG92	197	197	145	145	113	113	142	142	183	183	215	215	204	204	159	207
NMG93	197	197	145	145	113	113	142	142	183	183	217	217	204	204	207	207

Note: “–” means no data.

4 APPENDIX

Fingerprinting data and molecular ID cards of 151 mung bean varieties at 8 SSR locus

System NO.	Name	SSR fingerprinting data	ID cards
C0831	HLJ10	0010000‐0010‐0001000000‐000000100‐00100‐000010‐00001000000‐0010000	33473553
C0832	HLJ11	0001000‐0010‐0000001000‐000001000‐00010‐010000‐00001000000‐0000010	43764256
C0369	HLJ2	0010000‐1000‐0010001000‐001000000‐00010‐010000‐00001000000‐0010100	313/734253/5
C0843	HLJ21	0001000‐1000‐0000001000‐000001000‐00010‐000010‐00001000000‐0010000	41764553
C0844	HLJ22	0010000‐1000‐0000001000‐000000000‐00010‐000010‐00001000000‐0010000	31764553
C0845	HLJ23	0010000‐1000‐0000000001‐010000000‐00010‐010000‐00100000000‐0010000	31A24233
C0849	HLJ27	0001000‐0010‐0000000100‐000001000‐00010‐010000‐00001000000‐0000010	43864256
C0852	HLJ29	0010000‐0010‐0010000000‐000010000‐00010‐000010‐00001000000‐0010000	33354553
C0370	HLJ3	0010000‐1000‐0010000000‐010000000‐00010‐000001‐00001000000‐0000001	31324657
C0854	HLJ30	0001000‐1000‐0000000010‐010000000‐00100‐010000‐00001000000‐0000010	41923256
C0856	HLJ31	0010000‐1000‐0001000000‐010000000‐00010‐010000‐00001000000‐0010000	31424253
C0858	HLJ33	0001000‐1000‐0001000000‐000010000‐00100‐010000‐00001000000‐0000001	41453257
C0859	HLJ34	0010000‐1000‐0010000000‐010000000‐00010‐000010‐00001000000‐0010001	31324553/7
C0826	HLJ5	0010000‐1000‐0010000000‐010000000‐00010‐000010‐00100000000‐0010000	31324533
C0827	HLJ6	0010000‐0010‐0010000000‐010000000‐00010‐000010‐00100000000‐0010000	33324533
C0688	JL1	0010000‐0010‐0010000000‐100000000‐00010‐000010‐00100000000‐0010000	33314533
C0706	JL13	0000000‐1000‐0010000000‐000000000‐00000‐000010‐00100000000‐0010000	13533
C0708	JL15	0010000‐0010‐0010000000‐010000000‐00000‐000001‐00010000000‐0100000	3332642
C0709	JL16	0010000‐1000‐0001000000‐010000000‐00010‐010000‐00001000000‐0000001	31424257
C0712	JL19	0010000‐1000‐0000001000‐000001000‐00100‐100000‐00001000000‐0000010	31763156
C0689	JL2	0010000‐1010‐0010000000‐000000100‐00010‐010010‐00100000000‐0010010	31/33742/533/6
C0713	JL20	0010000‐0010‐0010000000‐000000000‐00001‐000010‐00001000000‐0010000	33395553
C0715	JL22	0010000‐1000‐0001000000‐010000000‐00010‐010000‐00001000000‐0000010	31424256
C0724	JL24	0100000‐1010‐0010001000‐001000000‐00010‐010010‐01001000000‐0010010	21/33/73/642/52/53
C0725	JL25	0001000‐0010‐0000000010‐010000000‐00010‐000010‐00001000000‐0000010	43924556
C0731	JL27	0000100‐0010‐0001000000‐010000100‐00010‐000010‐00010000000‐0010000	5342/74543
C0733	JL29	0001000‐0010‐0010000000‐000000000‐00100‐000010‐00001000000‐0010000	43373553
C0734	JL30	0010000‐0010‐0010000000‐100000000‐00010‐000010‐00101000000‐0010000	3331453/53
C0740	JL31	0010000‐0010‐0000000100‐000001000‐00100‐000010‐00001000000‐0010000	33863553
C0742	JL32	0010000‐1000‐0000001000‐000001000‐00100‐000010‐00001000000‐0010000	31763553
C0743	JL33	0100000‐1000‐0000001000‐000000010‐00010‐100000‐00100000000‐0000010	21784136
C0744	JL34	0010000‐0010‐0010000010‐010000100‐00010‐010000‐00100000000‐0010010	333/92/74233/6
C0747	JL36	1010000‐1010‐0001000000‐001000000‐00010‐010000‐00001000000‐0010010	1/31/3434253/6
C0752	JL41	0010000‐1000‐0010000000‐010000000‐00010‐010000‐00001000000‐0000010	31324256
C0753	JL42	0010000‐0010‐0000001000‐000001000‐00010‐000010‐00001000000‐0010000	33764553
C0756	JL44	0010000‐1010‐0000000010‐010000100‐00010‐010010‐00100000000‐0010000	31/392/742/533
C0759	JL46	0010000‐1000‐0001000000‐000010000‐00010‐010000‐00010000000‐0010000	31454243
C0771	JL47	0010000‐1010‐0000001000‐000100000‐00100‐000010‐00001000000‐0010010	31/3743553/6
C0776	JL48	0010000‐0010‐0000010000‐000001000‐00100‐000010‐00001000000‐0010000	33663553
C0778	JL49	0100000‐1000‐0000000010‐010000000‐00010‐010000‐00001000000‐0010000	21924253
C0693	JL5	0000000‐0010‐0000000010‐000000100‐00000‐010000‐00100000000‐0000100	397235
C4448	JL55	0010000‐0010‐0000000010‐001000000‐00010‐000010‐00001000000‐0000010	33934556
C0694	JL6	0010000‐1010‐0001000010‐010001000‐00010‐010010‐00101000000‐0100000	31/34/92/642/53/52
C4456	JL63	0010000‐1000‐0010000000‐000000100‐00010‐010000‐00001000000‐0000010	31374256
C4458	JL65	0010000‐1000‐0001000000‐010000000‐00010‐010000‐00100000000‐0010000	31424233
C0721	JL68	0010000‐1010‐0010000000‐000100000‐00010‐000010‐00101000000‐0010000	31/334453/53
C0723	JL69	0010000‐0010‐0010000000‐010000000‐00010‐000010‐01000000000‐0010000	33324523
C0700	JL7	0100000‐0010‐0010000000‐000000100‐00010‐000010‐00100000000‐0100000	23374532
C0722	JL70	0010000‐0010‐0000000010‐010000000‐00010‐010000‐00100000000‐0000010	33924236
C0726	JL71	0010000‐1000‐0000000100‐010000000‐00010‐000010‐00100000000‐0010000	31824533
C0727	JL72	0010000‐0010‐0010000000‐000000010‐00010‐010000‐00100000000‐0010000	33384233
C0728	JL73	0010000‐1000‐0001000000‐010000000‐00100‐010000‐00001000000‐0000001	31423257
C0729	JL74	0100000‐0010‐0010000000‐000100000‐00010‐000010‐00001000000‐0010000	23344553
C0702	JL9	0010000‐0010‐0010000000‐000000100‐00010‐000010‐00100000000‐0100000	33374532
C0661	LN1	0010000‐1010‐0010000000‐000010000‐00100‐010000‐00001000000‐0010000	31/335/73253
C0672	LN10	0010000‐1000‐0010000000‐000001000‐01000‐000010‐00000000010‐0000010	313625A6
C0673	LN11	0010000‐1000‐0010000000‐000001000‐00010‐010000‐00001000000‐0000010	31364256
C0674	LN12	0010000‐0010‐0001000000‐000010000‐00010‐000010‐00000000000‐0010000	33454563
C0676	LN13	0001000‐0010‐0000001000‐000001000‐00010‐010000‐00010000000‐0010000	43764243
C0677	LN14	0100000‐0010‐0000001000‐000010000‐00010‐010000‐00010000000‐0010000	23754243
C0786	LN17	0100000‐0010‐0010000000‐000000100‐10000‐000010‐00001000000‐0010000	23371553
C0787	LN18	0010000‐0010‐0010000000‐000000010‐00001‐000010‐00001000000‐0010000	33385553
C0663	LN2	0010000‐1000‐0010000000‐000000100‐00100‐010000‐00001000000‐0100000	31373252
C3808	LN23	0010000‐0010‐0010000000‐000000100‐00010‐010000‐00100000000‐0010000	33374233
C3809	LN24	0010000‐0010‐0010000100‐010000100‐00010‐010010‐00001000000‐0010000	333/82/742/553
C3811	LN26	0010100‐1010‐0010000000‐000000100‐00010‐010010‐00100000000‐0010000	3/51/33742/533
C3812	LN27	0010000‐1000‐0000000010‐010000000‐00010‐000010‐00100000000‐0010000	31924533
C3813	LN28	0010000‐1000‐0010000000‐000000010‐00100‐010000‐00000000010‐0000010	313832A6
C3814	LN29	0100000‐1000‐0010000000‐000000100‐00010‐000010‐00100000000‐0010000	21374533
C0664	LN3	0100000‐1000‐0001000000‐000010000‐00010‐000010‐00000100000‐0010000	21454563
C3815	LN30	0010000‐1000‐0010000000‐000001000‐00010‐000010‐00001000000‐0010000	31364553
C3817	LN32	0010000‐1000‐0010000000‐000000100‐00010‐000010‐00010000000‐0010000	31374543
C3818	LN33	0010000‐0010‐0010000000‐000001000‐00100‐000010‐00001000000‐0010000	33363553
C3819	LN34	0010000‐1000‐0010000000‐000000100‐00010‐000010‐00100000000‐0010000	31374533
C3823	LN35	0001000‐1000‐0010000000‐000000100‐00010‐000010‐00100000000‐0010000	41374533
C3825	LN37	0010100‐0010‐0001001000‐000001000‐00010‐010000‐00001000000‐0010000	3/534/764253
C3826	LN38	0010000‐0010‐0000001000‐000010000‐00010‐000010‐00001000000‐0010000	33754553
C3829	LN41	0000000‐0010‐0010000000‐000100000‐00010‐000010‐00001000000‐0010000	*3344553
C3832	LN42	0010000‐0010‐0010000000‐000100000‐00010‐000001‐00001000000‐0010000	33344653
C3835	LN44	0100000‐0010‐0000001000‐000001000‐00010‐010000‐00001000000‐0010000	23764253
C3837	LN45	0010000‐1010‐0010000000‐010001000‐00101‐000010‐00001000000‐0010000	31/332/63/5553
C3839	LN47	0000000‐0100‐1000000000‐000000000‐00000‐000000‐00000000000‐0100000	21***2
C0667	LN5	0010000‐0010‐0010001000‐000001000‐00100‐010000‐00001000000‐0010010	333/763253/6
C0668	LN6	0010000‐0010‐0010000000‐000001000‐01000‐000010‐00000000010‐0000010	333625A6
C0669	LN7	0010001‐0010‐0000001000‐000010001‐00100‐010010‐00010010000‐0010010	3/7375/932/54/73/6
C0670	LN8	0010000‐1000‐0010000000‐000010000‐00100‐010010‐00010000000‐0010000	313532/543
C0671	LN9	1000000‐0010‐0010000000‐000000100‐00010‐010010‐00001000000‐0010000	133742/553
C0601	NMG1	0000100‐0010‐0000000010‐010000000‐00010‐001000‐01000000000‐0000010	53924326
C0610	NMG10	0100000‐0010‐0000000010‐010000000‐00010‐010000‐00001000000‐0010000	23924253
C0612	NMG12	0000100‐0010‐0010000000‐000000100‐00100‐010000‐00001000000‐0000010	53373256
C0613	NMG13	0001000‐1000‐0000000100‐010000010‐00010‐010000‐00001000000‐0100000	4182/84252
C0614	NMG14	0001000‐0010‐0010000000‐000001000‐00010‐000010‐00001000000‐0000000	4336455*
C0615	NMG15	0010000‐1000‐0010000000‐010000100‐00010‐010010‐00101000000‐0000010	3132/742/53/56
C0616	NMG16	0010000‐1000‐0000100000‐010000000‐00010‐010000‐00001000000‐0000010	31524256
C0617	NMG17	0001000‐0010‐0010000000‐010000000‐00010‐010000‐00001000000‐0000010	43324256
C0618	NMG18	1001000‐1010‐0000000000‐000010000‐00010‐001010‐10010000000‐0010010	1/41/3*543/51/43/6
C0619	NMG19	0010000‐1010‐0010000000‐010000100‐00010‐010010‐00101000000‐0010000	31/332/742/53/53
C0602	NMG2	0100000‐0010‐0010000000‐000001000‐01000‐010000‐00000000001‐0000100	233622B5
C0622	NMG22	0010100‐1010‐0010000000‐100000000‐00010‐010010‐00010000000‐0010000	3/51/33142/543
C0623	NMG23	0001001‐1000‐0000001010‐010000001‐00010‐010010‐00001010000‐0000010	4/717/92/942/55/76
C0624	NMG24	0000100‐1000‐0000000010‐010000000‐00010‐010000‐00001000000‐0000010	51924256
C0626	NMG26	0001000‐1000‐0010000000‐010000000‐00010‐010000‐00001000000‐0000010	41324256
C0629	NMG29	0010000‐0010‐0010000000‐010000000‐00010‐010010‐00100000000‐0100000	333242/532
C0630	NMG30	1000000‐0011‐0000001000‐010010000‐00010‐010010‐00001000000‐0010000	13/472/542/553
C0631	NMG31	0100000‐0010‐0010000000‐010001000‐01000‐010010‐00000000101‐0010100	2332/622/59/B3/5
C0632	NMG32	0010000‐1010‐0010000000‐100000000‐00010‐010010‐00001000000‐0010000	31/33142/553
C0633	NMG33	0010000‐0010‐0010000000‐000100000‐00010‐010000‐00010000000‐0010000	33344243
C0634	NMG34	1000000‐0010‐0100000000‐010000000‐00001‐000010‐00001000000‐0010000	13225553
C0636	NMG36	0010000‐1000‐0010000000‐010001000‐00100‐010010‐00101000000‐0010000	3132/632/53/53
C0637	NMG37	0001000‐0010‐0000001000‐000001000‐00010‐010000‐00001000000‐0100000	43764252
C0638	NMG38	0010000‐0010‐0001000000‐000010000‐00001‐010000‐00001000000‐0010000	33455253
C0604	NMG4	0001000‐0010‐0010000000‐000001000‐01000‐001000‐00000000001‐0000100	433623B5
C0644	NMG43	1000000‐1010‐0010000000‐010000000‐00010‐010000‐00001000000‐0010000	11/3324253
C0645	NMG44	1000000‐1010‐0010000000‐100001000‐00010‐010010‐00001000000‐0010000	11/331/642/553
C0646	NMG45	0100000‐1000‐0010000000‐000001000‐00010‐010010‐00001000000‐0010000	213642/553
C0647	NMG46	0010000‐0010‐0010000000‐010000000‐00001‐000010‐00001000000‐0010000	33325553
C0648	NMG47	0010000‐0010‐0010000000‐010000100‐00001‐000010‐00001000000‐0010000	3332/75553
C0656	NMG49	0100000‐1000‐0001000000‐000001000‐00001‐000010‐00001000000‐0010000	21465553
C0605	NMG5	0000100‐0010‐0010000000‐000100000‐01000‐010000‐00010000000‐0000100	53342245
C0660	NMG52	0010000‐1010‐0010000000‐000100100‐00010‐000010‐00010000000‐0010010	31/334/74543/6
C0678	NMG53	0010000‐0010‐0010000000‐010001000‐00010‐010000‐00010000000‐0010000	3332/64243
C0680	NMG54	0010000‐1000‐0010000000‐000010000‐00100‐000010‐00010000000‐0010000	31353543
C0681	NMG55	0010000‐0010‐0010001000‐000001000‐00100‐010010‐00001000000‐0010000	333/7632/553
C0684	NMG58	0010000‐1000‐0000000010‐000000100‐00010‐010000‐00001000000‐0010000	31974253
C0686	NMG59	0010000‐0010‐0010000000‐000010000‐00100‐000010‐00001000000‐0010000	33353553
C0606	NMG6	1000010‐0010‐0010000000‐000101000‐01000‐000100‐00010000001‐0100000	1/6334/624B2
C3751	NMG60	0010000‐0010‐0010000000‐010000000‐00010‐010000‐00010000000‐0010000	33324243
C3753	NMG62	0010000‐0010‐0010000000‐000000000‐00010‐010000‐00000001000‐0010000	33324283
C3757	NMG66	0001000‐1000‐0010000000‐100000000‐01000‐100010‐00001000000‐0001010	413121/554/6
C3760	NMG69	0010000‐0010‐0010000000‐010000000‐00010‐001000‐00000001000‐0010000	33324383
C0607	NMG7	0010000‐1010‐0010000000‐010100000‐00010‐010010‐00001000000‐0100000	31/332/442/552
C3761	NMG70	0010000‐0010‐0010000000‐010000000‐00010‐000010‐00001000000‐0010000	33324553
C3763	NMG72	0001000‐0010‐0010000000‐000001000‐01000‐001000‐00001000000‐0100100	43362352/5
C3764	NMG73	0010000‐0010‐0010000000‐000010100‐00010‐010000‐00010000010‐0000100	3335/7424/A5
C3765	NMG74	0010000‐1000‐0000001000‐000000010‐01000‐000001‐00001000000‐0000010	31782656
C3766	NMG75	0100000‐0010‐0010000000‐000001000‐00010‐001000‐00000000100‐0000010	23364396
C3767	NMG76	0100000‐0010‐0010000000‐000000100‐00010‐001000‐00001000000‐0010000	23374353
C3768	NMG77	0001000‐0010‐0010000000‐010000000‐00010‐001000‐00000001000‐0010000	43324383
C3769	NMG78	0010000‐1000‐0010000000‐000000001‐00010‐000010‐00001000000‐0010000	31394553
C3770	NMG79	0010000‐1000‐0010000000‐000100010‐00100‐100010‐00000010010‐0010000	3134/831/57/A3
C0608	NMG8	0001000‐1000‐0001000010‐010010000‐00010‐010000‐00001000000‐0010000	414/92/54253
C3772	NMG81	1000000‐0010‐0010000000‐000000000‐01000‐001000‐00000010000‐0000010	13362376
C3773	NMG82	0010000‐1000‐0010000000‐100100000‐01000‐100010‐00001000000‐0001000	3131/421/554
C3774	NMG83	0100000‐1000‐0010000000‐000000100‐01000‐000100‐00000000100‐0000010	21372496
C3776	NMG85	0100000‐0010‐0001000000‐000000100‐00100‐001000‐00001000000‐0010000	23473353
C3777	NMG86	1000000‐1000‐0010000000‐000001000‐00010‐000010‐00001000000‐0010000	11364553
C3778	NMG87	1000000‐0010‐0100000000‐010000000‐00010‐010010‐00001000000‐0010000	132242/553
C3779	NMG88	0100000‐1000‐0010000000‐000000000‐00001‐100000‐00010000000‐0010000	2135143
C3782	NMG91	0100000‐0010‐0010000000‐000000100‐01000‐010000‐00000000010‐0000010	233722A6
C3783	NMG92	0100000‐0010‐0010000000‐000001000‐01000‐010000‐00000000010‐1000100	233622A1/5
C3784	NMG93	0100000‐0010‐0010000000‐000001000‐01000‐001000‐00000000010‐0000100	233623A5

Word count: 11930

Show less

© 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

The purpose of this study was to construct the DNA fingerprinting and query system with which to identify mung bean varieties from Northeast China. Eight primer pairs for fluorescent‐labeled simple sequence repeat markers with high polymorphism and a strong discrimination ability were used to detect 151 mung bean varieties from Northeast China. A total of 59 bands were detected, ranging from 4 to 11 with an average of 7.4. An unweighted pair group method analysis was used to cluster the mung bean varieties into five separate groups according to their genetic characteristics, which were consistent with the results of principal component analysis. Unique identification cards and barcodes with which each variety can be identified were established according to fingerprinting. A query system was also established which can provide the information and genetic relationships among some indefinite variety and mung bean varieties from Northeast China. This research will significantly assist in identification, traceability management, protection of origin, and intellectual property rights. It will also provide essential technical support for revealing the level of genetic diversity for breeding and germplasm innovation of mung bean varieties in Northeast China.

Details

Title

Molecular identification of mung bean accessions ( Vigna radiata L.) from Northeast China using capillary electrophoresis with fluorescence‐labeled SSR markers

Author

Zhao, Yanan¹

; Wang, Ying²; Wang, Lixia³; Zhang, Dongjie¹

¹ College of Food Science, Heilongjiang Bayi Agricultural University, Heilongjiang, China
² College of Food Science, Heilongjiang Bayi Agricultural University, Heilongjiang, China; National Coarse Cereals Engineering Research Center, Heilongjiang, China
³ Institute of Crop Sciences, Chinese Academic of Agriculture Science, Beijing, China

Section

ORIGINAL RESEARCH

Publication year

2020

Publication date

Feb 2020

Publisher

John Wiley & Sons, Inc.

e-ISSN

20483694

Source type

Scholarly Journal

Language of publication

English

DOI

https://doi.org/10.1002/fes3.182

ProQuest document ID

2357161405

Molecular identification of mung bean accessions ( Vigna radiata L.) from Northeast China using capillary electrophoresis with fluorescence‐labeled SSR markers

Jump to:

Full text

Abstract

Details

Suggested sources