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Genetic Diversity of Grasspea and Its Relative Species Revealed by SSR Markers

  • Fang Wang ,

    ‡ These authors are co-first authors on this work.

    Affiliation The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China

  • Tao Yang ,

    ‡ These authors are co-first authors on this work.

    Affiliation The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China

  • Marina Burlyaeva,

    Affiliation Department of Leguminous Crops Genetic Resources, N. I. Vavilov Research Institute of Plant Industry, St. Petersburg 190000, Russia

  • Ling Li,

    Affiliation Institute of Cash Crops, Liaoning Academy of Agricultural Sciences, Liaoyang 111000, China

  • Junye Jiang,

    Affiliation The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China

  • Li Fang,

    Affiliation The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China

  • Robert Redden ,

    zongxuxiao@caas.cn (XXZ); bob.redden@depi.vic.gov.au (RR)

    Affiliation Australian Temperate Field Crops Collection, Grains Innovation Park, The Department of Primary Industries, Horsham, Victoria 3401, Australia

  • Xuxiao Zong

    zongxuxiao@caas.cn (XXZ); bob.redden@depi.vic.gov.au (RR)

    Affiliation The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Genetic Diversity of Grasspea and Its Relative Species Revealed by SSR Markers

  • Fang Wang, 
  • Tao Yang, 
  • Marina Burlyaeva, 
  • Ling Li, 
  • Junye Jiang, 
  • Li Fang, 
  • Robert Redden, 
  • Xuxiao Zong
PLOS
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Correction

17 Apr 2015: The PLOS ONE Staff (2015) Correction: Genetic Diversity of Grasspea and Its Relative Species Revealed by SSR Markers. PLOS ONE 10(4): e0126453. https://doi.org/10.1371/journal.pone.0126453 View correction

Abstract

The study of genetic diversity between Lathyrus sativus L. and its relative species may yield fundamental insights into evolutionary history and provide options to meet the challenge of climate changes. 30 SSR loci were employed to assess the genetic diversity and population structure of 283 individuals from wild and domesticated populations from Africa, Europe, Asia and ICARDA. The allele number per loci ranged from 3 to 14. The average gene diversity index and average polymorphism information content (PIC) was 0.5340 and 0.4817, respectively. A model based population structure analysis divided the germplasm resources into three subgroups: the relative species, the grasspea from Asia, and the grasspea from Europe and Africa. The UPGMA dendrogram and PCA cluster also demonstrated that Asian group was convincingly separated from the other group. The AMOVA result showed that the cultivated species was quite distinct from its relative species, however a low level of differentiation was revealed among their geographic origins. In all, these results provided a molecular basis for understanding genetic diversity of L. sativus and its relatives.

Introduction

The genus Lathyrus L. includes as many as 187 species [1,2]. These are distributed throughout temperate regions of the Northern Hemisphere and extend into tropical East Africa and South America. However, the main centers of diversity include the Mediterranean and Irano-Turanian regions [3]. Grasspea (Lathyrus sativus L.) is the only species widely cultivated as a food crop in the genus Lathyrus, whereas other species (Lathyrus cicera L. and Lathyrus ochrus L.) are cultivated to a lesser extent [4]. Moreover, grasspea has great agronomic potential as a grain and forage legume in the fragile agro-ecosystems, because of its ability to survive under extreme climatic conditions such as drought, flood and salinity [5].

There have been recent studies of genetic diversity in Lathyrus sativus. PCR-based molecular markers utilized so far in L. sativus and its relative species include random amplification of polymorphic DNA (RAPD) [6,7], restriction fragment length polymorphism (RFLP) [8] which was indicated the highly similarity between L. sylvestris L. and L. latifolius L., amplified fragment length polymorphism (AFLP) [9] clarified that 20 central Italy grasspea accessions were divided into the Household populations and the Commercial populations which was useful for the grasspea bereeding in central Italy, and inter-simple sequence repeat (ISSR) was used for exploring the genetic diversity among L. sativus, L. cicera, and L. ochrus [10].

Up to now, there was little study of genetic diversity in Lathyrus sativus using simple repeat sequence (SSR) markers [1113] (Table 1). Lioi et al. searched for EST sequences of L. sativus with the European Molecular Biology Laboratory (EMBL) nucleotide sequence database. Amplification was successful only in 10 out of 20 of the SSR primers, with only 6 of these exhibiting size polymorphism and subsequently used in genetic diversity analysis for 13 Italian landraces [11]. Shiferaw et al. used 11 EST-SSRs developed from L. sativus. EST-SSRs derived from Medicago truncatula L. to investigate the genetic diversity among 20 grasspea accessions from Ethiopia [12].

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Table 1. SSR markers used in grasspea researches from literature and this study.

https://doi.org/10.1371/journal.pone.0118542.t001

Using the 454 FLX Titanium pyrosequencing technique, a large-scale microsatellite approach was developed in Lathyrus sativus [13]. Potentially these SSR primers can make a significant contribution to genomics enabled improvement of grasspea. To broaden the genetic variation of cultivated grasspea in the future for China, it is necessary to perform a more comprehensive analysis of genetic diversity and population structure in the national genebank. We used 30 polymorphic genomic-SSR markers developed by Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China (ICS/CAAS) [13], to study the genetic diversity among 266 accessions from L. sativus and 17 accessions from its cultivated and wild relatives (Fig. 1).

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Fig 1. Geographic distribution of Lathyrus sativus based on the results of structure analysis and the Lathyrus sativus relative species.

Gray indicates accessions from Asia, and black means the accessions from Africa/Europe as respective proportion of circles for distribution of number of accessions at each location; the hollow triangle means the distribution of L. sativus relative species.

https://doi.org/10.1371/journal.pone.0118542.g001

Materials and methods

Plant materials

A total of 266 grasspea accessions (Table 2) and 17 relative accessions (Table 3) were collected and tested in the protected field of experimental farm within CAAS campus (39° 57' 38" N, 116° 19' 27" E). For Lathyrus sativus, European germplasm comprised 100 accessions from 14 countries, while Asian germplasm contained 20 accessions from China and 98 non-Chinese accessions. African germplasm included 33 accessions and ICARDA comprised 15 accessions (Fig. 1). The 17 accessions of 9 relative species are from Europe, Asia, and Africa (Fig. 1). Seed supplies direct from collected samples were sourced from ICS/CAAS, as well as from N. I. Vavilov Research Institute of Plant Industry, St. Petersburg, Russia. Maps of the genus Lathyrus collection sites were conducted with DIVA-GIS based on latitude and longitude coordinates [14].

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Table 2. Geographic origin of 266 Lathyrus sativus accessions used in this study.

https://doi.org/10.1371/journal.pone.0118542.t002

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Table 3. Geographic origin of 17 accessions from nine different Lathyrus sativus relative species used in this study.

https://doi.org/10.1371/journal.pone.0118542.t003

DNA extraction

Genomic DNA was extracted from pooled ten random young seedlings of each accession using the CTAB method [15,16] with 1% PVP added.

Polymerase chain reactions (PCR) amplification

Polymerase chain reactions (PCR) were performed in 10 μl reaction volumes containing 5 μl 2 x TaqPCR MasterMix (Hooseen, Beijing, China), 1 μl primer, 1.5 μl of genomic DNA (30 ng) and dd H2O 2.5 μl. Microsatellite loci were amplified on a K960 Thermal Cycler (Jingle, Hangzhou, China) with the following cycle: 5 min initial denaturation at 95°C; 35 cycles of 30 s at 95°C, 30 s at the optimized annealing temperature (Table 4), 45 s of elongation at 72°C, and a final extension at 72°C for 10 min. The PCR products were separated on 8% non-denaturing polyacrylamide gel electrophoresed under 280 V and 50 W and visualized by 0.1% silver nitrate staining.

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Table 4. Characteristics of 30 polymorphic microsatellite loci used in this study (FP = forward primer, RP = reverse primer, Ta = annealing temperature).

https://doi.org/10.1371/journal.pone.0118542.t004

Data analysis

The genetic diversity parameters and polymorphism information content (PIC) of each primer pair were calculated by Powermarker v3.25 [17] using the following formulas: Gene diversity: ; PIC = ∑(1—pi2)/n, where pi is the frequency of the ith allele, n is the total number of genotypes [18]. POPGENE version 1.32 [19] was used to calculate Nei's genetic distance [20]. The program STRUCTURE V2.3.3 [21,22] was used to examine population structure and differentiation. The simulations were run with a burn-in of 100,000 iterations and from K = 1 through 10. Runs for each K were replicated 160 times and the true K was determined according to the method described by Evanno et al. [23]. The number of subgroups (K) was identified based on maximum likelihood and delta K (ΔK) values. The cluster analysis of different geographical groups was carried out using unweighted pair-group method with arithmetic average (UPGMA), and the dendrogram was drawn by MEGA 5.02 [24]. Analysis of molecular variance (AMOVA) was used to assess the variance among and within populations from different geographical origin with GenAlEx 6.41 software [25]. Principal component analysis (PCA) was applied to show the distribution of individual accessions in scatter diagram and two-dimension PCA graph was drawn using the NTSYSpc 2.2 statistical package [26].

Results

SSRs polymorphic testing

120 SSR markers were randomly selected to validate polymorphism at first. 25% of them were polymorphic (Table 4). 30 SSR makers amplified 258 polymorphic bands with an average of 8.6, ranged from 3 to 14 per primer pair (Table 5). Gene diversity was from 0.0708 to 0.8505, and the average was 0.5340. Meanwhile, polymorphism information content (PIC) of each primer pair ranged from 0.0688 to 0.8338 with an average of 0.4817. These results demonstrated polymorphic SSR markers which we used were good enough for further genetic diversity analysis.

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Table 5. Results of primer screening through 283 diversified accessions in genus Lathyrus.

https://doi.org/10.1371/journal.pone.0118542.t005

Genetic diversity and classification analysis among populations of Lathyrus sativus and its relative species

The population structure of Lathyrus sativus and its relatives was inferred by using STRUCTURE V2.3.3 based on 30 SSR markers. At K = 2, all the germplasm were divided into L. sativus and its relatives. But, according to the method described by Evanno et al. [23], three populations should be identified theoretically based on delta K (ΔK) values (Fig. 2), therefore the genetic structure of 283 accessions can be described with greatest probability and no gain in discrimination. At K = 3, the related accessions were in one subgroup and the L. sativus also divided into 2 subgroups (Fig. 3). One subgroup contained 79 accessions mainly from Asia. The other subgroup contained 187 accessions and most of them came from European and African countries.

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Fig 2. ΔK was used to determine the most appropriate K value for population structure in the Lathyrus genus.

https://doi.org/10.1371/journal.pone.0118542.g002

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Fig 3. Population structure of K = 3 inferred by Bayesian clustering approaches based on 30 microsatellite markers showing relatives of L. sativus and separation of L. sativus into Asian and African/European subgroups.

https://doi.org/10.1371/journal.pone.0118542.g003

Genetic relationships analysis

The Lathyrus sativus relatives as a group were marginally more similar to the Asian than to the African and European sources of L. sativus, whereas the African and European sources of L. sativus were more closely related than either to the Asian source (Table 6, Fig. 4). All Lathyrus accessions were clustered according to Nei’s genetic distance [20] (Fig. 4). The largest genetic distance (0.6360) was between Lathyrus sativus relatives and European grasspea, and the smallest genetic distance (0.0038) was between African and European grasspea. Based on the origin of L. sativus accessions, the genetic distance between Africa and Asia (0.0141) was larger than it between Europe and Asia (0.0118). These result matched with structure analysis above.

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Fig 4. UPGMA dendrogram of Nei’s (1978) Genetic Distance among all Lathyrus accessions used in this study.

https://doi.org/10.1371/journal.pone.0118542.g004

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Table 6. Pairwise estimated of genetic identity and genetic distance based on 30 SSR markers among relatives (17 accessions), African (33 accessions), Asian (133 accessions) and European (100 accessions) of Lathyrus sativus.

https://doi.org/10.1371/journal.pone.0118542.t006

There were 17 accessions from nine different relative Lathyrus sativus species used in this study. Nei’s genetic distance of 0.7247 between L. sativus and L. cicera was the smallest in our study among L. sativus and its nine relative species (Table 7). This result matched morphological [27] and cytogenetical [28] researches which suggest that L. cicera is the most probable progenitor of L. sativus. Among L. sativus relative species, the relationship between L. latifolius and L. sylvestris was the closest (Table 7). Meanwhile, the closer phylogenetic relationship between L. latifolius and L. sylvestris revealed in our research was also detected by Ceccarelli et al. [29] using satellite DNA and Asmussen and Liston [30] using chloroplast DNA study.

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Table 7. Pairwise estimated of Nei’s genetic distance based on 30 SSR markers among Lathyrus sativus and 17 relative species accessions.

https://doi.org/10.1371/journal.pone.0118542.t007

Clustering analysis based on Nei’s genetic distance divided all the 10 species under genus Lathyrus accessions into two major groups (Fig. 5). One group included L. sativus, L. cicera L., L. tingitanus L., L. aphaca L., and L. hirsutus L., which were all annual species. The second group comprised Lathyrus clymenum L., L. ochrus (L.) DC, L. pratensis L., L. sylvestris L. and L. latifolius L. In general, L. clymenum and L. ochrus were annual species, however, L. pratensis, L. sylvestris, and L. latifolius were perennial species.

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Fig 5. UPGMA dendrogram of Nei’s (1978) Genetic Distance among Lathyrus sativus and its relatives.

https://doi.org/10.1371/journal.pone.0118542.g005

Classification and PCA analysis of all the accessions used in this study

The genetic relationship of individual accessions was analyzed using principal component analysis (PCA); all the cultivated accessions were labeled according to their geographical origin. Within cultivated species, accessions from Asia were somewhat associated with their geographical origin and were different from other accessions (Fig. 6), especially, eight accessions from Bangladesh were quite apart from African and European accessions. The first two principal components explained 43.42% and 29.17% of the molecular variance, respectively.

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Fig 6. Two-dimension principal component analysis (PCA) of Lathyrus sativus.

Asia accessions (hollow triangle), and European accessions (open square) and African accessions (open pentagram) are based on the geographical origin.

https://doi.org/10.1371/journal.pone.0118542.g006

Analysis of molecular variance

First of all, we evaluated genetic differentiation between Lathyrus sativus and its relatives by analysis of molecular variance (AMOVA). The results showed that the cultivated species was significantly distinct from its relatives at P-value of 0.0001 (Table 8). Among population variance explained 40% and within population explained 60% of genetic diversity. Secondly, significant genetic differentiation among the three population structure classified subgroups was detected by AMOVA at P-value of 0.0001 (Table 9). The results of AMOVA also indicated that the majority of the genetic variation among all the 283 accessions was due to within population variation (84%). Finally, we evaluated the genetic differentiation among accessions of grasspea (Table 10). The results show a low level of differentiation (3%) among Asia, Europe, and Africa.

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Table 8. Analysis of genetic differentiation between Lathyrus sativus and its relatives by AMOVA.

https://doi.org/10.1371/journal.pone.0118542.t008

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Table 9. Analysis of genetic differentiation among all the accessions based on structure by AMOVA.

https://doi.org/10.1371/journal.pone.0118542.t009

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Table 10. Analysis of genetic differentiation among accessions of Lathyrus sativus based on geographic origins by AMOVA.

https://doi.org/10.1371/journal.pone.0118542.t010

Discussion

Use of genetic diversity

Grasspea, as a neglected and underutilized species, is very popular among the resource poor farmers in marginal areas due to the ease with which it can be grown successfully under adverse agro-climatic conditions without much production inputs [5]. Genetic diversity is a source of traits for increased agricultural production and resistance to biotic and abiotic stresses [31]. Knowledge of genetic diversity will assist germplasm utilization in Lathyrus sativus breeding, and more climate-resilient varieties would be bred in the near future. There may be opportunities to exploit wiser genetic diversity in grasspea by combining germplasm between Asia and Africa/Europe, especially taking note of eco-geographical origins for complementation of extreme stress traits for drought tolerance, reproductive heat stress and salinity, for the breeding demands of specific target environments.

Further such exploration of diversity could include the more closely related L. sativus relatives which have more limited geographic range in cultivation, and attention to sources of low toxin to reduce the risk of poisoning in situations where grasspea is a major component of human diet.

Comparison of grasspea genetic diversity

EST-SSRs have been used to detect the variability in grasspea accessions and to evaluate genetic diversity [11,12]. These markers were developed from Lathyrus sativus and transferable EST-SSRs from L. japonicus L. and Medicago truncatula respectively and the number was limited. In this study, the SSRs were developed by NGS sequencing of L. sativus genomic DNA [13]. Compared with the previous study [11,12], the genetic diversity of 283 accessions was higher, as the average allele number per locus was 8.6, and the average PIC value was 0.4817. In comparison with the L. sativus relatives, the cultivated germplasm, which came from Africa, Europe, Asia, and ICARDA, had much wider diversity than local germplasm, such as Ethiopia [12] and Italy [11], respectively. The level of polymorphism detected with genomic-SSRs was higher than that of EST-SSRs matching with the previous reports [32,33].

Possibility of Genetic Flow

All the Lathyrus accessions were divided into three subgroups, under cultivated subgroups the accessions were classified according to geographical origins. The Lathyrus sativus relatives were separated from L. sativus clearly. Within the cultivated species, European and African accessions were aggregated together, and partially overlapped with some Asian accessions due to possibility of flow between the two subgroups. For example, Island Cyprus and ICARDA located in Asia, but 21 and 13 accessions were divided into European and African subgroup and only 1 and 2 accessions consisted to Asian subgroup, respectively [34,35].

Richness of genetic diversity

The PCA of cultivated accessions by geographical distribution indicates that the first two principal components explained over 72% of the total genetic variation. Although most European and African materials flowed together, Asian accessions dispersed in much more extensive scope, as the PCA indicated (Fig. 6). More interestingly, the eight accessions from Bangladesh were relatively separated from others, as showed in Fig. 6. It means that the genetic diversity of cultivated accessions of grasspea originated from Asia is much richer than that from Europe and Africa.

Genetic relationship and origin of Lathyrus sativus

Our accessions used in this study occupied vast territories of Southwestern, Western and Eastern Asia. It also occurred on isolated sites in Africa (Ethiopia and Eritrea). The European accessions were widespread throughout Southern and partly Central Europe, penetrating to the northern coast of Africa (Algeria, Morocco and Tunisia). The result of structure demonstrated that Lathyrus sativus divided into 2 population (Fig. 3). One contained 79 accessions and most of them distributed in Asia. The other included 187 accessions and most of them came from European and African countries. The UPGMA dendrogram (Fig. 4) also supported this hypothesis that there was a smaller genetic distance between African and European accessions than that of Asian accessions. AMOVA based on geographic origins (cultivated species divided into Asian, African, and European accessions) revealed that, in the total genetic variance, geographic-related variance was very limited (Table 10). Although Vavilov described Central Asia and Abyssinia as the centers of origin for L. sativus [36], our research results based on genotyping method partially supported the hypothesis that India together with adjacent areas was the primary centre of origin [37] which based on traditional phenotyping method. In conclusion, the natural distribution of L. sativus was obscured by cultivation, making it difficult to precisely locate its center of origin as described by Singh et al [38].

Acknowledgments

We are grateful to Mr. Jianwu Chang and Mr. Xiaopeng Hao in Shanxi Academy of Agricultural Sciences for their technical assistance.

Author Contributions

Conceived and designed the experiments: RR XXZ. Performed the experiments: FW. Analyzed the data: TY LL JYJ LF. Contributed reagents/materials/analysis tools: MB. Wrote the paper: TY.

References

  1. 1. Allkin R, Goyder DJ, Bisby FA, White RJ. List of species and subspecies in the Vicieae. Vicieae Database Project. 1983; 1: 4–11.
  2. 2. Allkin R, Goyder DJ, Bisby FA, White RJ. Names and synonyms of species and subspecies in the Vicieae. Vicieae Database Project. 1986; 7: 1–75.
  3. 3. Kupicha FK. The infrageneric structure of Lathyrus. Notes Royal Botanic Garden. Edinburg. 1983; 41: 209–244.
  4. 4. Shehadeh A, Amri A, Maxted N. Ecogeographic survey and gap analysis of Lathyrus L. species. Genetic Resources and Crop Evolution. 2013; 60: 2101–2113.
  5. 5. Kumar S, Bejiga G, Ahmed S, Nakkoul H, Sarker A. Genetic improvement of grass pea for low neurotoxin (β-ODAP) content. Food and Chemical Toxicology. 2011; 49: 589–600. pmid:20659523
  6. 6. Barik D, Acharya L, Mukherjee A, Chand P. Analysis of genetic diversity among selected grasspea (Lathyrus sativus L.) genotypes using RAPD markers. Zeitschrift fu¨r Naturforschung. 2007; 62: 869–874.
  7. 7. Croft A, Pang E, Taylor P. Molecular analysis of Lathyrus sativus L. (grasspea) and related Lathyrus species. Euphytica. 1999; 107: 167–176.
  8. 8. Chtourou-Ghorbel N, Lauga B, Combes D, Marrakchi M. Comparative genetic diversity studies in the genus Lathyrus using RFLP and RAPD markers. Lathyrus Lathyrism Newsletter. 2001; 2: 62–68.
  9. 9. Tavoletti S, Iommarini L. Molecular marker analysis of genetic variation characterizing a grasspea (Lathyrus sativus) collection from central Italy. Plant Breeding. 2007; 126: 607–611.
  10. 10. Belaid Y, Chtourou-Ghorbel N, Marrakchi M, Trifi-Farah N. Genetic diversity within and between populations of Lathyrus genus (Fabaceae) revealed by ISSR markers. Genetic Resources and Crop Evolution. 2006; 53: 1413–1418.
  11. 11. Lioi L, Sparvoli F, Sonnante G, Laghetti G, Lupo F, Zaccardelli M. Characterization of Italian grass pea (Lathyrus sativus L.) germplasm using agronomic traits, biochemical and molecular markers. Genetic Resources and Crop Evolution. 2011; 58: 425–437.
  12. 12. Shiferaw E, Pe ME, Porceddu E, Ponnaiah M. Exploring the genetic diversity of Ethiopian grass pea (Lathyrus sativus L.) using EST-SSR markers. Molecular Breeding. 2012; 30: 789–797. pmid:22924019
  13. 13. Yang T, Jiang J, Burlyaeva M, Hu J, Coyne CJ, Kumar S, et al. Large-scale microsatellite development in grasspea (Lathyrus sativus L.), an orphan legume of the arid areas. BMC Plant Biology. 2014; 14: 65. pmid:24635905
  14. 14. Hijmans RJ, Guarino L, Cruz M, Rojas E. Computer tools for spatial analysis of plant genetic resources data: 1. DIVA-GIS. Plant Genetic Resources Newsletter. 2001; 127: 15–19.
  15. 15. Dellaporta S, Wood J, Hicks J. A plant DNA minipreparation: Version II. Plant Molecular Biology Reporter. 1983; 1: 19–21.
  16. 16. Doyle J, Doyle J. A rapid total DNA preparation procedure for fresh plant tissue. Focus. 1990; 12: 13–15.
  17. 17. Liu K, Muse SV. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics. 2005; 21: 2128–2129. pmid:15705655
  18. 18. Weir BS. Genetic data analysis II. Sunderland, MA: Sinauer Associates, Inc; 1996.
  19. 19. Yeh F, Boyle T. Population genetic analysis of co-dominant and dominant markers and quantitative traits. Belgian Journal of Botany. 1997; 129: 157.
  20. 20. Nei M. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics. 1978; 89: 583–590. pmid:17248844
  21. 21. Falush D, Stephens M, Pritchard JK. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics. 2003; 164: 1567–1587. pmid:12930761
  22. 22. Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000; 155: 945–959. pmid:10835412
  23. 23. Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software structure: a simulation study. Molecular Ecology. 2005; 14: 2611–2620. pmid:15969739
  24. 24. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular Biology Evolution. 2011; 28: 2731–2739. pmid:21546353
  25. 25. Peakall ROD, Smouse PE. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes. 2006; 6: 288–295.
  26. 26. Rohlf FJ. NTSYSpc: Numerical Taxonomy System (ver. 2.2). Setauket, NY: Exeter Publishing, Ltd; 2006.
  27. 27. Jackson MT, Yunus AG. Variation in the grass pea (Lathyrus sativus L.) and wild species. Euphytica. 1984; 33: 549–559.
  28. 28. Hopf M. Archaeological evidence of the spread and use of some members of Leguminosae. The original and domestication of cultivated plants. Oxford: Elsevier, Barigozzi C. (Ed.); 1986. pp. 35–60.
  29. 29. Ceccarelli M, Sarri V, Polizzi E, Andreozzi G, Cionini PG. Characterization, evolution and chromosomal distribution of two satellite DNA sequence families in Lathyrus species. Cytogenetic & Genome Research. 2010; 128: 236–244.
  30. 30. Asmussen CB, Liston A. Chloroplast DNA characters, phylogeny, and classification of Lathyrus (Fabaceae). American Journal of Botany. 1998; 85: 387–401. pmid:21684923
  31. 31. Sthapit B, Padulosi S, Mal B. Role of on-farm/in situ conservation and underutilized crops in the wake of climate change. Indian Journal of Plant Genetic Resources. 2010; 23: 145–156.
  32. 32. Chabane K, Ablett GA, Cordeiro GM, Valkoun J, Henry RJ. EST versus genomic derived microsatellite markers for genotyping wild and cultivated barley. Genetic Resources and Crop Evolution. 2005; 52: 903–909.
  33. 33. Gupta PK, Rustgi S, Sharma S, Singh R, Kumar N, Balyan HS. Transferable EST-SSR markers for the study of polymorphism and genetic diversity in bread wheat. Molecular genetics and genomics. 2003; 270: 315–323. pmid:14508680
  34. 34. Zhang XY, Blair MW, Wang SM. Genetic diversity of Chinese common bean (Phaseolus vulgaris L.) landraces assessed with simple sequence repeat markers. Theoretical and Applied Genetics. 2008; 117: 629–640. pmid:18548226
  35. 35. Blair MW, Soler A, Cortes AJ. Diversification and Population Structure in Common Beans (Phaseolus vulgaris L.). Plos One. 2012; 7(11): e49488. pmid:23145179
  36. 36. Vavilov NI. The origin, variation, immunity and breeding of cultivated plants. Chronica Botany. 1951; 13: 13–47.
  37. 37. Zalkind FL. Cultivated Flora of the USSR. In: Grass Pea. Leningrad: Selkhozgiz; 1937. pp. 171–227.
  38. 38. Singh M, Upadhyaya HD, Bisht IS. Genetic and Genomic Resources of Grain Legume Improvement. In: Grass Pea. Elsevier; 2013. pp. 269–285.