Genetic Characterization and Population Structure of Pea (Pisum sativum L.)...

[Full title: Genetic Characterization and Population Structure of Pea (Pisum sativum L.) by Molecular Markers against Rust (Uromyces viciae-fabae) in Newly Developed Genotypes]

Citation: Yadav, A.S.; Singh, A.K.; Chand, R.; Vaish, S.S. Genetic Characterization and Population Structure of Pea ( Pisum sativum L.) by Molecular Markers against Rust ( Uromyces viciae-fabae ) in Newly Developed Genotypes Sustainability 2022 , 14 , 15082. https://doi.org/ 10.3390/su 142215082 Academic Editor: Svein Øivind Solberg Received: 9 August 2022 Accepted: 23 September 2022 Published: 14 November 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations Copyright: © 2022 by the authors Licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/) sustainability Article Genetic Characterization and Population Structure of Pea ( Pisum sativum L.) by Molecular Markers against Rust ( Uromyces viciae-fabae ) in Newly Developed Genotypes Anmol Singh Yadav 1 , Anil Kumar Singh 2 , Ramesh Chand 1 and Shyam Saran Vaish 1, * 1 Department of Mycology and Plant Pathology, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221 005, India 2 Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221 005, India * Correspondence: ssvaishmyco@bhu.ac.in; Tel.: +91-945-136-1998 Abstract: The understanding of the genetic diversity of germplasm of any crop is necessary for genetic improvement. Pea ( Pisum sativum L.) is a very important legume crop that provides protein and several essential vitamins, carbohydrates, and minerals. The genetic diversity and population structure of pea germplasm consisted of 115 entries of Australian accessions and 4 entries of Indian varieties used as checks with varying responses and severities of rust, which were analysed using 31 polymorphic SSR (Simple Sequence Repeats) markers. The combination of the markers revealed that 78 alleles were present at 32 loci. It was also observed that each marker had three alleles with an average PIC (Polymorphic Information Content) value of 0.272. The population structure analysis showed the genetic differentiation of the entries. The model-based population structure grouped the entries into three sub-populations of SP 1, SP 2, and SP 3 having 37, 35, and 32 entries, respectively with 15 entries as admixtures. AMOVA (Analysis of Molecular Variance) disclosed that there was 56% variation among the individuals and 20% within the population. A mean fixation index (Fst) of 0.240 among the pea entries exhibited relatively significant variation in population. This study provides basic information to select parental lines for developing rust resistant varieties to meet the ultimate goal of sustainable agriculture Keywords: Pisum sativum ; genetic diversity; population structure; SSR markers; AMOVA 1. Introduction Pea, Pisum sativum L. (2 n = 14), is one of the most significant pulse crops grown around the world. It belongs to Fabaceae and has a genome size of about 4500 Mb [ 1 ]. Pea is a good source of protein with high levels of amino acids such as tryptophan and lysine in addition to vitamins, carbohydrates, and minerals [ 2 ]. Among the various biotic stresses to pea, rust ( Uromyces viciae-fabae ) is considered as one of the major diseases as it causes considerable yield losses ranging from 10 to 60 per cent [ 3 ]. The efforts have been made for the improvement of disease resistance and plant architecture, and mitigate lodging to increase the yield of pea to meet the global protein demand of a rising population under various breeding programs since three decades [ 4 , 5 ]. Crop species with a narrow genetic diversity are more sensitive to new diseases and other abiotic stresses, resulting in reduction in adaptability as well as yield. Hence, the wider genetic diversity of any germplasm is considered as a reason behind its beauty that is governed by gene diversity The variants of high significance can be exploited for the development of desired crop varieties [ 6 ]. The necessity of collecting and exploiting genetic diversity for further progress has been acknowledged by several geneticists and breeders [ 7 , 8 ] Since the use of traditional morphological or biochemical markers are not completely trustworthy because of environmental impact, morphological and molecular traits have Sustainability 2022 , 14 , 15082. https://doi.org/10.3390/su 142215082 https://www.mdpi.com/journal/sustainability

Sustainability 2022 , 14 , 15082 2 of 11 been found as key estimates for the evaluation of a germplasm. Seeds per pod, seed fresh weight and germination percentage have been used as morphological features to understand the diversity among pea genotypes [ 8 , 9 ]. The use of molecular markers is a precise and strong technique for assessing relationship among entries of a germplasm based on the genetic similarity estimates. The simple sequence repeats (SSR) markers owing to its abundance in the genome of plant species, high polymorphism, multi-allelic variation, co-dominance, high reproducibility and easy detection by polymerase chain reaction have been found very appropriate for understanding genetic diversity of pea and fiber crops [ 9 – 17 ]. They have been used for the identification of population structure and reconstruction of the evolutionary history of pea [ 18 ]. However, only a few studies on genetic diversity of pea using molecular tools have been done so far in India [ 8 , 18 ]. The identification of promising genotypes for various breeding purposes requires proper evaluation of genetic diversity and population structure of any germplasm to meet the ultimate goal of sustainable agriculture. Therefore, the present work is aimed to determine the genetic diversity and population structure of 119 entries of pea germplasm, consisting of 115 Australian accessions and 4 Indian varieties using the SSR markers to find out the amount of existing variation and its grouping based on their rust reactions 2. Materials and Methods 2.1. Planting Materials and Experimental Design One hundred and nineteen entries of pea germplasm were used for studies on genetic characterization and population structure (Table 1 ). The germplasm consisted of 115 Australian accessions obtained from the National Bureau of Plant Genetic Resources (NBPGR), New Delhi, and 4 Indian varieties as checks against rust. The experiment was conducted at the Agriculture Research Farm, Banaras Hindu University, Varanasi (25 ◦ 15 0 20.3 00 N; 82 ◦ 59 0 10.3 00 E) during 2016–2017 and 2017–2018.The planting of each of the entries of the germplasm was done in a single row of three meters with a row spacing of 40 cm and plant to plant of 15 cm within a row in a RBD (Randomised Block Design) with two replications Table 1. Showing the details of the germplasm used in the present studies Origin Accession Number Australia EC 865919, EC 865920, EC 865921, EC 865922, EC 865923, EC 865924, EC 865925, EC 865926, EC 865927, EC 865928, EC 865929, EC 865930, EC 865931, EC 865932, EC 865933, EC 865934, EC 865935, EC 865936, EC 865937, EC 865938, EC 865939, EC 865940, EC 865941, EC 865942, EC 865943, EC 865944, EC 865945, EC 865946, EC 865947, EC 865948, EC 865949, EC 865950, EC 865951, EC 865952, EC 865953, EC 865954, EC 865955, EC 865956, EC 865957, EC 865958, EC 865959, EC 865960, EC 865961, EC 865962, EC 865963, EC 865964, EC 865965, EC 865966, EC 865967, EC 865968, EC 865969, EC 865970, EC 865971, EC 865972, EC 865973, EC 865974, EC 865975, EC 865976, EC 865977, EC 865978, EC 865979, EC 865980, EC 865981, EC 865982, EC 865983, EC 865984, EC 865985, EC 865986, EC 865987, EC 865988, EC 865989, EC 865990, EC 865991, EC 865992, EC 865993, EC 865994, EC 865995, EC 865996, EC 865997, EC 865998, EC 865999, EC 866000, EC 866001, EC 866002, EC 866003, EC 866004, EC 866005, EC 866006, EC 866007, EC 866008, EC 866009, EC 866010, EC 866011, EC 866012, EC 866013, EC 866014, EC 866015, EC 866016, EC 866017, EC 866018, EC 866019, EC 866020, EC 866021, EC 866022, EC 866023, EC 866024, EC 866025, EC 866026, EC 866027, EC 866028, EC 866029, EC 866030, EC 866031, EC 866032, EC 866033 India HUDP-15, HFP-8909, HFP-4, HFP-9907 2.2. DNA Extraction, Amplification and Electrophoresis Genomic DNA of each of the entries of the test material was extracted from freshly growing leaves collected from 15-days-old plants by using the CTAB method [ 19 ]. This method was used following some minor modifications. Thirty-one SSR markers were used

Sustainability 2022 , 14 , 15082 3 of 11 to screen the test entries through polymerase chain reaction (Table 2 ). For the preparations of the master mix solution, 1.5 µ L 10 × reaction buffer, 0.2 µ L dNTPs, 0.2 µ L MgCl 2 , 0.2 µ L Taq polymerase, 0.6 µ L of each forward and reverse primers, and 10.9 µ L nuclease free water were mixed with 0.8 µ L desired genomic DNA of each of the test entries The polymerase chain reaction (PCR) amplification was carried out in a thermocycler (Eppendorf 5333 Master Cycler Gradient Thermal Cycle). The PCR was programmed for initial denaturation at 95 ◦ C for 15 min, denaturation at 94 ◦ C for 30 s, annealing according to primer for 1 min, extension at 72 ◦ C for 2 min, and the cycle was repeated 40 times and the final extension for 5 min at 72 ◦ C [ 20 , 21 ]. Thereafter, the amplified PCR product was resolved through electrophoresis in 2% ( w/v ) agarose gel containing 0.5 µ g/mL ethidium bromide Table 2. Showing genetic diversity of the germplasm on the basis of polymorphic characteristics of SSR markers No SSR Marker No of Alleles (Na) Major Allele Frequency (A) Gene Diversity (H e ) Heterozygosity (H o ) PIC * 1 AA 135 2 0.588 0.484 0.000 0.367 2 AA 176 2 0.907 0.167 0.000 0.153 3 AA 206 2 0.991 0.016 0.000 0.016 4 AA 345-145 2 0.932 0.125 0.000 0.117 5 AA 372.1 2 0.705 0.415 0.000 0.329 6 AA 416 2 0.563 0.492 0.000 0.371 7 AA 446 2 0.806 0.311 0.000 0.263 8 AA 505 2 0.529 0.498 0.000 0.374 9 AA 57 4 0.617 0.505 0.697 0.419 10 AA 61 2 0.983 0.033 0.000 0.032 11 AA 98 4 0.714 0.412 0.563 0.334 12 AB 24 2 0.949 0.095 0.000 0.091 13 AB 60 2 0.655 0.451 0.000 0.349 14 AD 146 2 0.789 0.331 0.000 0.276 15 AD 147 2 0.991 0.016 0.000 0.016 16 AD 237 4 0.403 0.657 0.000 0.584 17 AD 70290 2 0.991 0.016 0.000 0.016 18 B 14 2 0.537 0.497 0.000 0.373 19 B 16 9 0.420 0.630 0.352 0.555 20 P 46 2 0.806 0.311 0.000 0.263 21 PSAB 60 2 0.529 0.498 0.000 0.374 22 S 244 2 0.857 0.244 0.000 0.214 23 CAASESP 527 2 0.882 0.207 0.000 0.186 24 S 144 2 0.974 0.049 0.000 0.047 24 S 85 3 0.680 0.439 0.000 0.350 26 B 179 2 0.899 0.181 0.000 0.164 27 CAASESP 1173 2 0.907 0.167 0.000 0.153 28 P 282 3 0.672 0.494 0.000 0.443 29 CAASESP 524 2 0.781 0.341 0.000 0.283 30 CAASESP 1193 2 0.672 0.440 0.000 0.343 31 P 255 3 0.420 0.653 0.000 0.579 Mean 3 0.747 0.328 0.052 0.272 Max 9 0.991 0.657 0.697 0.584 Min 2 0.403 0.016 0.000 0.016 *, denotes Polymorphic Information Content The gel was visualized and documented through a gel documentation system (Protein Simple Alpha Imager HP system). A DNA ladder of 100 bp was used for identifying the band size of amplified products. The polymorphic bands were evaluated as binary data based on whether each amplicon was present (1) or absent (0). Thereafter, the obtained similarity matrix was subjected to the UPGMA (Unweighted Pair Group Method with an Arithmetical Mean) by DARwin software [ 22 ]. The un-rooted phylogenetic tree was prepared according to the scale and the p -distance method was used to compute the distances.

Sustainability 2022 , 14 , 15082 4 of 11 2.3. Population Structure and Gene Flow Population structure was evaluated by the Structure v 2.3.4 software using the data acquired from SSR profiling [ 23 ]. The optimum number of population (K) was selected by testing K = 1 to K = 10 using five independent runs of 100,000 burns in period length followed by 100,000 MCMC (Markov Chain Monte Carlo) replication. Further, the population structure was envisaged using the online tool structure harvester. The K value was estimated by the log probability LnP (D) based on in its rate change between successive Ks 2.4. Genetic Diversity Analysis and Analysis of Molecular Variance (AMOVA) In order to evaluate the genetic diversity, gene diversity (expected heterozygosity), observed heterozygosity, major allele frequency, and polymorphic information content, PIC for each SSR locus was obtained by using Power marker software 3.25 [ 24 ]. The number of sub-populations obtained through analysis in Structure v 2.3.4 software was used for AMOVA (Genetic Diversity Analysis and Analysis of Molecular Variance) as well as for Nei’s genetic distance analysis in GenAlEx v 6.503 [ 25 ]. The fixation index (Fst) and gene flow of the population were derived from AMOVA 3. Results 3.1. Polymorphic Levels of Simple Sequence Repeats Loci The existing genetic diversity of the present pea germplasm was understood by assessing the polymorphic level of SSR (Simple Sequence Repeats) loci on the basis of the different parameters, viz., number of alleles per locus, major allele frequency, gene diversity, heterozygosity, and polymorphic information content (Table 2 ). A total of 78 alleles, detected from 31 SSR loci, were amplified among the 119 pea entries. The number of alleles counted for 32 loci varied from two to nine with an average of three alleles for each SSR marker. The lowest number of alleles per locus was observed from AA 135, AA 176, AA 206, AA 345 AA 372.1, AA 416, AA 446, AA 505, AA 61, AB 24, AB 60, AD 146, A 147, AD 70290, B-14, P 46, PSAB 60, S 244, S 144, B 179, CAASESPS 527, CAASESPS 1173, CAASESPS 524, and CAASESPS 1193 markers. The maximum number of alleles was nine and they were located at the B 16 locus. The PIC (Polymorphic Information Content) value of the SSR markers ranged from 0.016 to 0.584 with an average of 0.272. Three markers such as AD 237, B 16, and P 255, showed a PIC value of >0.5 indicating a higher polymorphism. Further, they were more informative of all the SSRs used. The observed heterozygosity values varied from 0.0 to 0.697 with a mean of 0.052. The gene diversity ranged from 0.016 to 0.65 with a mean of 0.32 (Table 2 ). Markers P 255 and AA 206 had the highest and the lowest gene diversity, respectively. The major allele frequency varied from 0.40 to 0.99 with a mean of 0.74 (Table 2 ). Markers AD 237 and AA 206 showed the lowest and the highest major allele frequency, respectively. The PIC values and diversity score of most of the SSR markers disclosed enough variability to distinguish all the 119 entries. The marker AD 237 located on chromosome number VII that exhibited the highest gene diversity (0.657) and PIC (0.585) was followed by P 255 with 0.653 and 0.579 values for gene diversity and PIC, respectively 3.2. Genetic Relationship among Pea Germplasm Population The changing block colors within the entries shows the changes in allele size and the different color blocks in the bar plot represent the genetic diversity among the present population (Figure 1 a). Based on the ∆ K (Delta K) values, the population structure of 119 entries was determined and the ∆ K was 3. The population structure with SSRs yielded into a dramatic peak of the probability following the adjustment of the number of populations to three. Further, it helped to divide these pea entries into three sub-populations. By matching the LnP(D) and Evanno’s ∆ K values by cumulative K from 2 to 10, we observed an increase in LnP(D) values up to K = 3 with the highest log probability score at the same position (Figure 1 a). It was also noticed that the population of 119 entries contains 104 pure entries and 15 admixtures. Out of the 104 pure entries, 37 entries belonged to sub

Sustainability 2022 , 14 , 15082 5 of 11 population-1 (SP 1), 35 to sub population-2 (SP 2), and 32 to sub population-3 (SP 3) which are shown in green, blue, and red, respectively (Figure 1 b). Figure 1. Population structure analysis of pea germplasm (119 entries) based on 31 SSR markers using STRUCTURE harvester 2.3. ( a ) Graphical plot of ∆ K values showing the maximum value at K = 3; ( b ) Distribution of 119 pea genotypes into three different sub-populations; sub population-1 (SP 1), sub population-2 (SP 2), and sub population-3 (SP 3) shown in green, blue, and red color, respectively The UPGMA (Unweighted Pair Group Method with an Arithmetical Mean) analysis based on the genetic dissimilarity using the neighbour-joining method with DARwin categorized the pea germplasm into three groups (Figure 2 ). Group I consisted of 41 entries with 33 and 8 entries in Sub-groups Ia and Ib, respectively; whereas, Group II had 72 entries that were further clustered into three Sub-groups namely IIa, IIb, and IIc with 6, 23, and 43 entries, respectively The Group III had six entries with no further Sub-group. Out of the four Indian varieties used as differentials, the variety HFP-4 belonged to Group I, and two varieties (HFP-8909 and HFP-9907) were to Group III; however, the variety HUDP-15 was found at the admixture group of both Australian and Indian entries (Figure 1 b). The area under disease progress curve (AUDPC) for pea rust disclosed that the five accessions, i.e., EC 865975, EC 865921, EC 865951, EC 865929, and

Sustainability 2022 , 14 , 15082 6 of 11 EC 866033, were distributed over all the three groups and exhibited lower AUDPC (Area Under Disease Progress Curve) values varying from 292 to 351 (Table 3 ) Figure 2. Illustrating the Unrooted Neighbour joining (U-NJ) tree of pea germplasm (119 entries) prepared using DARwin software The analysis of molecular variance showed 24% variation among the population and 56% among the individuals; whereas, the variation within the individuals was 20% The calculation of Wright’s F statistic of all SSR loci exhibited an inbreeding coefficient (Fis) of 0.733; however, the Fit coefficient was 0.797. The determination of the mean fixation index (Fst) for the polymorphic loci across all the entries revealed that it was 0.240. The low haploid Nm of 0.791 indicated good gene exchange among the populations. Further, the analysis demonstrated low and high genetic differentiation among sub-populations and within sub-populations, respectively.

Sustainability 2022 , 14 , 15082 7 of 11 Table 3. Depicting the development of pea rust ( Uromyces viciae-fabae ) Entry No. Accession No. AUDPC Entry No. Accession No. AUDPC Entry No. Accession No. AUDPC 1 EC 865919 592 41 EC 865959 872 81 EC 865999 745 2 EC 865920 700 42 EC 865960 1091 82 EC 866000 547 3 EC 865921 334 43 EC 865961 560 83 EC 866001 481 4 EC 865922 834 44 EC 865962 476 84 EC 866002 543 5 EC 865923 723 45 EC 865963 575 85 EC 866003 876 6 EC 865924 698 46 EC 865964 843 86 EC 866004 679 7 EC 865925 463 47 EC 865965 546 87 EC 866005 881 8 EC 865926 537 48 EC 865966 628 88 EC 866006 845 9 EC 865927 794 49 EC 865967 527 89 EC 866007 507 10 EC 865928 682 50 EC 865968 491 90 EC 866008 530 11 EC 865929 344 51 EC 865969 544 91 EC 866009 744 12 EC 865930 469 52 EC 865970 871 92 EC 866010 562 13 EC 865931 824 53 EC 865971 850 93 EC 866011 872 14 EC 865932 833 54 EC 865972 794 94 EC 866012 436 15 EC 865933 799 55 EC 865973 756 95 EC 866013 796 16 EC 865934 538 56 EC 865974 849 96 EC 866014 539 17 EC 865935 540 57 EC 865975 292 97 EC 866015 845 18 EC 865936 536 58 EC 865976 782 98 EC 866016 861 19 EC 865937 868 59 EC 865977 839 99 EC 866017 878 20 EC 865938 826 60 EC 865978 459 100 EC 866018 853 21 EC 865939 572 61 EC 865979 896 101 EC 866019 746 22 EC 865940 762 62 EC 865980 873 102 EC 866020 650 23 EC 865941 723 63 EC 865981 860 103 EC 866021 548 24 EC 865942 676 64 EC 865982 842 104 EC 866022 843 25 EC 865943 452 65 EC 865983 869 105 EC 866023 527 26 EC 865944 389 66 EC 865984 550 106 EC 866024 576 27 EC 865945 871 67 EC 865985 861 107 EC 866025 588 28 EC 865946 706 68 EC 865986 861 108 EC 866026 383 29 EC 865947 852 69 EC 865987 546 109 EC 866027 916 30 EC 865948 881 70 EC 865988 524 110 EC 866028 382 31 EC 865949 876 71 EC 865989 656 111 EC 866029 857 32 EC 865950 886 72 EC 865990 910 112 EC 866030 853 33 EC 865951 344 73 EC 865991 549 113 EC 866031 345 34 EC 865952 883 74 EC 865992 565 114 EC 866032 383 35 EC 865953 825 75 EC 865993 550 115 EC 866033 351 36 EC 865954 915 76 EC 865994 492 116 * HUDP-15 371 37 EC 865955 757 77 EC 865995 542 117 * HFP-8909 851 38 EC 865956 569 78 EC 865996 866 118 * HFP-4 1136 39 EC 865957 849 79 EC 865997 566 119 * HFP-9907 514 40 EC 865958 860 80 EC 865998 864 *, Denotes differential; AUDPC, stands for area under disease progress curve 4. Discussion In the present work, the average PIC value of 0.272 justifies enough allelic variation in the population for studies on genetic diversity. The observed variation in their values may be due to genotypic variation. Similar results were obtained by Ram et al. [ 26 ] who studied 24 pea genotypes for genetic diversity by using the SSR markers and detected 2.91 alleles per locus with a mean PIC value of 0.39. However, the varying PIC values have also been obtained by previous workers owing to variation in the number of SSR markers and number of genotypes used in their studies [ 1 , 7 , 8 , 18 , 27 – 30 ]. Mohamed et al. [ 30 ] evaluated 12 pea local lines and found an average of 0.44 PIC value per locus. Jain et al. [ 1 ] studied 96 cultivars of pea using 31 SSR markers and found the PIC values that varied from 0.01–0.56 among the SSR markers. Haliloglu et al. [ 31 ] evaluated 62 forage pea specimens collected from the northeastern Anatolia region of Turkey by using the 28 SSR markers and found an average PIC value of 0.41 that ranged from 0.03–0.70. Sharma et al. [ 32 ] evaluated 40 pea genotypes using

Sustainability 2022 , 14 , 15082 8 of 11 24 EST-SSR markers and noticed an average PIC value of 0.349 that ranged from 0.095–0.500 Although the higher PIC value was reported by Singh et al. [ 18 ], they characterized 47 garden peas by using 34 SSR markers and found a 0.55 PIC value. Similarly, Bouhadida et al. [ 27 ] evaluated 19 pea accessions by using eight SSR markers and observed a PIC value of 0.62, and Duque-Zapata et al. [ 28 ] studied 50 pea accessions using 16 polymorphic SSR markers and obtained an average PIC value of 0.62.On the other hand, Kimaro et al. [ 17 ] evaluated the genetic diversity of 48 pigeon pea genotypes using 33 SSR markers and found an average PIC value of 0.46.The present study also justifies that the test markers, due to their polymorphic nature, may be used for the categorization of the germplasm.The inclusion of some traitlinked SSR markers and the removal of the monomorphic and spurious bands from the analysis may have contributed to the lower number of alleles in the current study. Haliloglu et al. [ 31 ] observed that the number of alleles (Na) per primer varied from 2 to 4 with a mean of 2.89 alleles per locus. Teshome et al. [ 33 ] found 13 out of 15 EST SSR markers were polymorphic and observed a total of 37 alleles in 46 pea accessions. The study also revealed an average number of alleles per locus was 3.1. Kimaro et al. [ 17 ] noticed a total of 155 alleles at 33 loci and detected an average of 4.78 alleles per marker. Out of the studied SSR markers, four markers, namely AA 146, AA 416, AA 446, and AA 505, have also been used by Rai et al. [ 34 ] and Singh et al. [ 20 ]. Further, they reported that these markers to be linked to Quantitative Trait Loci (QTLs) responsible for rust resistance The gene diversity (He) for the SSR loci ranged from 0.016–0.657 with a mean of 0.328 A similar range of gene diversity of 0.03–0.62 was reported by Jain et al. [ 1 ]. Handerson et al. [ 29 ] and Ram et al. [ 26 ] have found an average of 0.46 gene diversity in their studies. The major allele frequency was 0.747 which indicates that the alleles’ distribution in the pea germplasm was averagely common. Similarly, an average of 0.65 and 0.66 major allele frequency was reported by Mohamed et al. [ 30 ] and Ram et al. [ 26 ], respectively. In the present study, the observed heterozygosity (Ho) values ranged from 0.00 to 0.697 with a mean of 0.052. It is obvious that in a self-pollinated species, the observed heterozygosity is found to be very low (on average, 6%) [ 29 , 35 ]. Similarly, in our study we have also found a low averaged Ho of 5.20% In general, every population can be assessed based on its geographical distribution, but it is also frequently based on additional factors such as the phenotype, behavior, and ecology of the individuals collected. In this investigation, the ∆ K value was found to be 3 clustering the 119 pea entries into three genetically distinct groups. This was also confirmed by UPGMA analysis. The finding indicates that there is no correlation between genetic diversity of a germplasm and the place of origin. The conducted work helped to differentiate the germplasm into three groups on the basis of their genetic diversity. Similarly, Mohamed et al. [ 30 ] concluded that the place of origin does not represent a major reason for differentiation following grouping of 12 pea accessions into three sub-groups. Rana et al. [ 7 ] identified three groups for 151 pea accessions collected from the different parts of the world Ahmad et al. [ 36 ] found four groups for 34 pea genotypes of different origins. However, Ferradini et al. [ 37 ] noticed two peaks at delta K graph, i.e.,K = 2. Hanci and Cebeci [ 38 ] evaluated wild pea accessions, local varieties, and commercial pea varieties. They observed two major groups among all the 15 accessions. Similarly, Duque-Zapata et al. [ 28 ] have also seen two clusters among 50 pea accessions. Bouhadida et al. [ 27 ] reported two groups among 19 pea accessions by using the eight simple sequence repeats (SSR) markers. Ram et al. [ 26 ] concluded two major clusters with sub-cluster 1 and sub-cluster 2 with a total of 11 and 10 pea lines, respectively. Singh et al. [ 18 ] also identified two major groups I and II among 47 garden pea genotypes representing dwarf and tall, respectively. Haliloglu et al. [ 31 ] found three clusters of 61 forage pea land races through UPGMA analysis In this study, three Indian varieties formed the group with Australian accessions which indicates that they have similar genetic constitution. This may be possible due to a gene flow between the populations. The admixture found in one Indian variety may be due to having one parent each from Australian and Indian lines. Further, it also suggests that the ancestors from various distant geographical places exchanged lineages of distinct gene pools or accessions representing diverse gene pools during the cultivation at an early

Sustainability 2022 , 14 , 15082 9 of 11 stage of pea domestication [ 39 ]. Similarly, Rana et al. [ 7 ] also observed similarities and dissimilarities between pea accessions of various countries and found three major groups. However, Ahmad et al. [ 36 ] reported four population structure groups corresponding to patterns of geographical distribution Five genotypes distributed in all the three groups showing moderately resistant reactions against rust disclosed enough diversity among them. It significantly indicates that there may be a horizontal distribution of rust resistant genes. Hence, these accessions can be used as breeding material to develop a new rust resistant variety through gene pyramiding The analysis of molecular variance of the population revealed a high genetic variance among the individuals (56%). This genetic differentiation among the individuals in the population may be due to the inclusion of genotypes from the different places of origin for rust resistance. Ferradini et al. [ 37 ] made a brief account of pea genotypes and found 68% genetic diversity among individuals. Alike, Scaerano et al. [ 35 ] found 68% genetic difference among the landraces and 32% within the landraces of common bean. Mohamed et al. [ 30 ] also reported genetic diversity among and within the local pea accessions of 90% and 10%, respectively A low percent of variance (20%) within the individuals was observed indicating a high purity of germplasm without any mixture. However, the genetic variance explained among the population was low (24%) regardless of their geographical distance that may be due to an increase in the spread of alleles among various populations. Similar low variance among the population was also reported by Ram et al. [ 26 ] and Ferradini et al. [ 37 ]. The Wright’s F Statistic used demonstrated a deviation from the Hardy–Weinberg law However, there was a low fixation index (Fst = 0.240) of alleles which might be attributed to a lot of variation among the individual genotypes within the groups. This high variability within the groups was most likely to be attributed to the fact that the entries were heterogeneous pure lines or homozygous, particularly at all loci, but with genetic constitutions that differed from one another. Jain et al. [ 1 ] reported Fst values ranging from 0.11 to 0.19 in four sub-populations of pea genotypes indicating low to high genetic differentiation Tahir et al. [ 40 ] found Fst values of Subgroup 1 and 2 were 0.0478 and 0.267, respectively 5. Conclusions The analysis of genetic diversity of pea germplasm using 31 SSR markers infers considerable diversity and divides the germplasm into three groups. Further, it discloses that there are five accessions having resistance to rust. The used SSR markers could be used as a potential tool for germplasm characterization and its utilization in pea breeding program. Eventually, it would not be an exaggeration to state that the present outputs would be helpful in achieving the ultimate goal of global zero hunger, also known as Sustainable Development Goal-2 (SDG 2), to mitigate hunger, achieve food security with improved nutrition, and promote sustainable agriculture Author Contributions: The experiments were planned and designed by S.S.V. and R.C. A.K.S. provided technical advice during the course of the study. A.S.Y. executed all the concerned experiments, viz., DNA isolation, PCR reaction, rust scoring, SSR and data analysis. All the authors contributed to writing, editing and finalizing the manuscript in the present shape. All authors have read and agreed to the published version of the manuscript Funding: This research received no external funding Data Availability Statement: All the new data were presented in this article Acknowledgments: Authors are highly thankful to the Grain Research Development Corporation (GRDC), Australia and National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India for providing the material. We are indebted for facilities of the DST-FIST of the Department of Mycology and Plant Pathology and Bio-control laboratory of the Institute of Agricultural Sciences, Banaras Hindu University. The technical help of Sudhir Navathe, Agharkar Research Institute, Pune, Prahlad Masurkar, Basavraj Teli, and Phanindra P.V., Department of Mycology and Plant Pathology, Institute of Agricultural Sciences, BHU is also highly appreciable.

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