GENETIC DIVERSITY OF BIO-FORTIFIED LENTILS ( LENS CULINARIS MEDIK.) THROUGH SIMPLE SEQUENCE REPEAT MARKERS

Nepalese lentils are comparatively rich in iron and zinc, making it a potential crop of whole food solution to aid in the global battle against the micronutrient malnutrition. Understanding the genetic basis for uptake of grain iron and zinc is required to increase their stable concentrations along with these minerals in lentils. This study aimed at characterizing genetic variation in micronutrient high grain iron and zinc concentrations and exploring the potential in lentil accessions. A set of 25 lentil accessions was evaluated in two seasons across the three locations and genotyped by using 40 simple sequence repeat (SSR) markers that are linked with lentil iron and zinc concentrations. Out of the 40 SSR markers, 23 markers were found polymorphic while 12 were monomorphic, and 5 markers were null. These 23 polymorphic markers produced a total of 584 alleles, of which 52 were polymorphic alleles, and average alleles per locus was 11.49. The linkage disequilibrium (LD) analysis was done using a mixed linear model (MLM) that identified three SSR markers, PBALC 13, PBALC 206, and GLLC 563, associated with grain Fe concentration, explaining 9% to 11% phenotypic variation, respectively, and four SSR markers (PBALC 353, SSR 317–1, PLC 62, and PBALC 217) associated with grain Zn concentration, explaining 14% to 21% phenotypic variation, respectively. The pairwise genetic similarity index among 25 lentil accessions varied from 0.16 to 0.83. The identified SSRs exhibited consistent performance across two seasons and have potential for utilization in lentil molecular breeding program.


INTRODUCTION
Lentil (Lens culinaris Medikus), is an autogamous diploid (2n = 2x = 14) species with haploid genome size of 4063 Mbp, and the most important pulse crop in Nepal often called the "poor man's meat" for its rich in protein content (28%) for human consumption and its straw is a valued animal feed consisted of minerals (2%) and carbohydrates (59%) (Frederick et al., 2006).Besides, it is low-fat food, i.e., lowglycemic carbohydrate, and helps to prevent chronic diseases such as diabetes and heart disease.Globally, it is cultivated for its protein-rich grains in as many as 52 countries on a 3.64-million-hectare area with an annual production of 3.60 million tons (FAOSTAT, 2011).However, about 95% of the global production comes from just ten countries-Canada, India, Turkey, Nepal, Australia, China, Iran, the USA, Syria, and Ethiopia.India accounts for 39% (1.47 million ha) of the global acreage with 0.90 million tons of production.Currently, annual world lentil production is approximately 4 million metric tons (MT), more than 85% of which is in five specific regions: India, Nepal, and Bangladesh (32%); western Canada (29%); Turkey and northern Syria (18%); and Australia (4%).In Nepal, lentil shares about 62% and 64% of the total legume acreage rea and production (MOAD, 2012), respectively.Nepalese lentil is highly preferred because of its quick cooking quality and tasty pink-red cotyledons, with high micronutrient contents and is popular in the international market (Dev et al., 2007).Bangladesh, Singapore, Sri Lanka, Germany, Korea, the UK, and Indonesia are the major export markets for Nepalese lentil (Gharti et al., 2014).
Nepalese lentil has potential for mineral biofortification as its nutritional profile is rich in Fe, Zn, and Se (Thavarajah et al., 2011;USDA National Nutrient Database, 2015).Alghamdi et al., (2014) evaluated 35 advanced ICARDA breeding lines in Saudi Arabia at one field location over two seasons and reported significant variation for Fe, Zn, Cu, Ca, Mg, P, K, and Mn concentrations.The mean iron concentration in both cultivated and wild lentils was reported 61 mg kg-1 across all 26 lentil genotypes.Among the 20 L. culinaris genotypes, Fe concentration ranged from 26 (IG72830) to 92 mg kg-1 (CDC Red Rider) with a mean of 58 mg kg-1 .
Simple sequence repeat markers are inexpensive and readily adaptable technique for routine germplasm fingerprinting and evaluation of genetic relationship between accessions or genotypes (Sardana et al., 1998;Dixit et al., 2004, Edossa et al., 2007) and construction of genetic linkage maps (Abo-Elwafa et al., 1995).This technique has been used to assess genetic diversity in germplasm collection (Gilbert et al., 1999;Salimath et al., 1995), to identify cultivars (Prevost et al., 1999).Till date, in Nepal, there has been very little study on molecular breeding in lentil breeding improvement, which takes a longer breeding process and mostly follows classical breeding.There is a big gap in the breeding improvement process, and for fast-track breeding, the present investigation was undertaken to assess the diversity and genetic relatedness of Nepalese, Indian, and exotic lentil genotypes with the objectives of studying the polymorphism and genetic relationship among them and identifying genotype-specific markers.

Plant material
A core collection of lentil germplasm available at GLRP was developed by selecting a small set of Fe and Zn rich accessions representing the diversity of the entire collection, based on passport available in Gene bank or ICARDA website, laboratory and morphological data.This collection consists of 25 genotypes (Table 1).These accessions were from the SAARC region, and for this study, 11 ICARDA breeding lines and 14 lines (Nepal 7, India 6, Bangladesh 1) were employed.

DNA extraction and PCR amplification
Total DNA was extracted according to the Cetyltrimethyl Ammonium Bromide Method (CTAB method), described by Rogers and Bendich (1985).Bulk genomic DNA of each lentil accession were isolated from 100mg of young fresh leaf tissue of 5 individual seedlings of 2-week-old using CTAB method (50mM Tris-HCL, 25mM EDTA, 1M NaCl, 1% CTAB, 0.15% 2-mercaptoethanol).The DNA extract in the form of pellet was suspended in 100μl of TE buffer and prepared the 5% working DNA solution with deionized water and used for Polymerase Chain Reaction (PCR) amplification of SSRs.Forty-four SSR markers that are linked to lentil iron and zinc concentration reported by Hamweieh et al. (2005), fifty-eight SSR markers reported by Kaur et al. (2011), and 18 EST SSR markers developed in IARI's laboratory exhibiting polymorphosis across Lens species were assayed for identification of polymorphic SSR markers.The SSR markers developed by Creganetal (1999) were used in the present study.A total of 40 SSRs were initially screened for their ability to produce polymorphic patterns across the 25 lentil accessions.The details of SSR markers, their sequences and motifs are given in supplementary (Table 2).This genotyping was performed in Seed Science and Technology Division, National Agriculture Research Institute, Khumaltar, Lalitpur.PCR was carried out using a PE 9600 thermo cycler (Perkin-Elmer, Foster City, CA).After initial denaturation of 3 min at 94 0 C, followed by 30 cycles performed for 30 s at 94°C, annealing for 30 s at either 52°C, 53°C, 54°C or 55°C (depending on the locus) and elongation for 1 min at 72°C, followed by final extension step of 5 min at 72°C.Amplified products were detected on a Mega BACE 500 Capillary System (Amersham Pharmacia Biotech, Piscataway, NJ).Samples were prepared by adding 1 μl of diluted PCR products to 9 μl formamide and samples included 1% (v/v) ET-Rox 900 bp DNA size standard (Amersham Bioscience).Microsatellite fragment sizes were estimated using the Mega BACE Genetic Profiler Version 2.0 (Amersham Pharmacia Biotech).The amplified SSR products were measured using a UV illuminator as bands on visualization gel.The analysis only used the trustworthy bands.

SSR allele scoring and data analysis
The presence or absence of SSR fragments in each accession was recorded for all the polymorphic SSR markers.The SSR bands appearing without ambiguity were scored as 1 (present) and 0 (absent) for each primer.The size of the amplified product was calculated on the basis of its mobility relative to the molecular mass of the marker., Thermo Scientific, USA).The polymorphism information content (PIC) a measure of the allelic diversity at a locus, was determined by using the formula described by Botstein et al. (1980).

PIC = 1-ΣPi2
Where, Pi is the frequency of the ith allele for its marker in the set of accessions analyzed, calculated for SSR locus.The genetic similarity among accessions was estimated based on Jaccard's similarity coefficient.The resulting similarity matrix was further analyzed using the unweighted pair-group method arithmetic average (UPGMA) clustering algorithm for construction of dendogram; the computations were carried out using MINITAB Inc. File version 14.13.0.0.  3 ).PBALC0353 SSR alleles were found rare with a frequency of 0.14 in the whole sample studied (Table 3).The three accessions RL-79, ILL4605 and RL-49 amplified unique alleles as well as rare alleles in SSR 107 marker.These three accessions may serve as good sources for identification of new alleles of important genes.Three SSR markers (PBALC 13,PBALC 206,and GLLC 563)

Molecular diversity analysis (Cluster Analysis)
The choice of parental genotypes for the formation of segregated populations and varieties benefits from knowledge of the genetic diversity of germplasm.Genetic variety based on molecular markers is unaffected by environmental variables, making it highly repeatable and dispersed across the genome.Understanding molecular diversity is crucial to expand the genetic basis of lentil accessions in an effective manner.In the present study, to assess the genetic resemblances among the accessions, Jaccard's similarity coefficients were calculated for all 40 SSR alleles detected 25 lentil accessions.The pairwise genetic similarity among 25 accessions varied from 0.16 to 0.83.The similarity coefficients matrix was used for UPGMA cluster analysis.The dendogram or cladogram constructed based on the genetic similarities between accessions showed that the 25 accessions formed five major clusters (Fig. 2).Likely lentil accessions were grouped into five clusters based on the neighbor-joining cluster analysis, with a dissimilarity min value of 0.028 and a dissimilarity max value of 0.55 (Fig. 2).In the cladogram, cluster II also contains the highest number of lentil accessions, followed by cluster III and cluster V.The closest related accessions in Cluster I were RL-6 and RL-12 at a similarity coefficient of 0.83, followed by ILL8006 at a similarity coefficient of 0.79.Lentil accessions.ILL-3490 was closely related to Khajura-2 (PL639) at a similarity coefficient of 0.72, while the popular and released variety Simal (LG7) was closely related to Shital (ILL2580) at a similarity coefficient of 0.70.Cluster IV and Cluster V had high genetic distances (4.66-4.74)from the centroids that determined the possible candidates with Cluster I or other clusters for the hybridization program (Table 4).This cluster pictorial indicated that there was genetic diversity among the high-grain Fe and Zn concentration lentil accessions due to the different sources of origin and diverse genetic formation.These diverse genetic materials may be used for genetic improvements in lentil accessions.

CONCLUSION
Genetic variations in lentil have continued to narrow down due to continuous selection pressure for specific traits like high yield, disease and insect resistance and has jeopardized the potential for long term genetic improvement.Therefore, it is extremely important to study the genetic relationship of the existing modern-day genotypes in comparison with their ancestors and related species.In this study, genomic diversity was studied in 25 varieties.Out of 40 SSR markers tested, 23 produced unambiguous polymorphisms.Amplified markers produced easily scorable bands ranging from 100-600 bp in length.A total of 584 SSR fragments were amplified, with an average of 11.49 alleles per marker.The three accessions RL-79, ILL4605 and RL-49 amplified unique alleles as well as rare alleles in SSR 107 marker.These three accessions may serve as good sources for identification of new alleles of important genes.
Fig. 1 below shows different marker systems used in plant breeding in Nepal.

Figure 1 .
Figure 1.Different Marker Systems used in Nepal

Table 1 .
Details of 25 lentil accessions used for molecular characterization and genetic diversity analysis based on the source of origin

Table 2 .
Forward and reverse primer sequences and annealing temperatures used for amplifications microsatellite loci SSR 48, SSR 130 had comparatively lower PI, 2009) and hence were less informative.This study revealed the divergence among lentil accessions which can be further used in lentil breeding programs.All accessions involved in this study exhibited wide range of genetic variability due to different center of origin, different genetic constitution.The genetic relatedness detected in this study might be the foundation base for future systematic lentil breeding programs.Similar results have been reported by several authorsYadav, NK et al. 2016, Hamwieh et.al.(2005,2009)andDikshitet al., 2014.
579, 0.124, and 0.640, respectively.PIC values, a measure of the allelic diversity of SSRs, ranged from 0.14 in PBALC0353 to 0.57 in SSR 28, with an average PIC value of 0.46.Markers with PIC values of 0.5 or higher are highly informative for genetic studies and are extremely useful in distinguishing the polymorphism rate of a marker at a specific locus.Babayeva et al. (2009)found 33 alleles determined, ranging from 3-8 per locus.The estimated gene diversity value for 33 loci was 0.66 in lentil.Hamweih  et al. (2009)reported large variation among microsatellite markers for both allele numbers and gene diversity among lentil species.Highly informative and detectable polymorphic markers for this study were found in SSR 28, SSR 124, SSR 107, SSR 113, SSR 154, SSR 156, PLC 16, and GLLC 511, which indicated the power and higher resolution of those marker systems in detecting molecular diversity.Similarly,  markers SSR 33, PLC 22, PLC 10, PLC 17, SSR 132 RN, GLLC 563, PLC 21, SSR  19, SSR 46, SSR 34, PLC 35, SSR 48, and SSR 130had comparatively the lowest PIC value, which was less informative.This study revealed the divergence among lentil accessions, which can be further used in lentil breeding programs.The information on genetic diversity among these lentil accessions will be helpful to lentil breeders in selection of appropriate hybridizing parents in developing superior accessions.