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Article

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

by
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
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(22), 15082; https://doi.org/10.3390/su142215082
Submission received: 9 August 2022 / Revised: 16 September 2022 / Accepted: 23 September 2022 / Published: 14 November 2022
(This article belongs to the Section Sustainable Agriculture)
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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 SP1, SP2, and SP3 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.

1. Introduction

Pea, Pisum sativum L. (2n = 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 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 [9,10,11,12,13,14,15,16,17]. 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′20.3″ N; 82°59′10.3″ 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.

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 to screen the test entries through polymerase chain reaction (Table 2). For the preparations of the master mix solution, 1.5 µL 10× reaction buffer, 0.2 µL dNTPs, 0.2 µL MgCl2, 0.2 µL Taq polymerase, 0.6 µL of each forward and reverse primers, and 10.9 µL nuclease free water were mixed with 0.8 µL 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 μg/mL ethidium bromide.
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.

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 v6.503 [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 AA135, AA176, AA206, AA345 AA372.1, AA416, AA446, AA505, AA61, AB24, AB60, AD146, A147, AD70290, B-14, P46, PSAB 60, S244, S144, B179, CAASESPS527, CAASESPS1173, CAASESPS524, and CAASESPS1193 markers. The maximum number of alleles was nine and they were located at the B16 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 AD237, B16, and P255, 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 P255 and AA206 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 AD237 and AA206 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 AD237 located on chromosome number VII that exhibited the highest gene diversity (0.657) and PIC (0.585) was followed by P255 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 1a). Based on the ΔK (Delta K) values, the population structure of 119 entries was determined and the ΔK 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 ΔK 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 1a). 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 population-1 (SP1), 35 to sub population-2 (SP2), and 32 to sub population-3 (SP3) which are shown in green, blue, and red, respectively (Figure 1b).
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 1b). The area under disease progress curve (AUDPC) for pea rust disclosed that the five accessions, i.e., EC865975, EC865921, EC865951, EC865929, and EC866033, were distributed over all the three groups and exhibited lower AUDPC (Area Under Disease Progress Curve) values varying from 292 to 351 (Table 3).
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.

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 [1,7,8,18,27,28,29,30]. 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 north-eastern 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 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 trait-linked 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 AA146, AA416, AA446, and AA505, 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 ΔK 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 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 (SDG2), 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.

Conflicts of Interest

The authors declare no conflict of interest.

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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 (SP1), sub population-2 (SP2), and sub population-3 (SP3) shown in green, blue, and red color, respectively.
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 (SP1), sub population-2 (SP2), and sub population-3 (SP3) shown in green, blue, and red color, respectively.
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Figure 2. Illustrating the Unrooted Neighbour joining (U-NJ) tree of pea germplasm (119 entries) prepared using DARwin software.
Figure 2. Illustrating the Unrooted Neighbour joining (U-NJ) tree of pea germplasm (119 entries) prepared using DARwin software.
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Table
Table 1. Showing the details of the germplasm used in the present studies.
Table 1. Showing the details of the germplasm used in the present studies.
OriginAccession Number
AustraliaEC865919, EC865920, EC865921, EC865922, EC865923, EC865924, EC865925, EC865926, EC865927, EC865928, EC865929, EC865930, EC865931, EC865932, EC865933, EC865934, EC865935, EC865936, EC865937, EC865938, EC865939, EC865940, EC865941, EC865942, EC865943, EC865944, EC865945, EC865946, EC865947, EC865948, EC865949, EC865950, EC865951, EC865952, EC865953, EC865954, EC865955, EC865956, EC865957, EC865958, EC865959, EC865960, EC865961, EC865962, EC865963, EC865964, EC865965, EC865966, EC865967, EC865968, EC865969, EC865970, EC865971, EC865972, EC865973, EC865974, EC865975, EC865976, EC865977, EC865978, EC865979, EC865980, EC865981, EC865982, EC865983, EC865984, EC865985, EC865986, EC865987, EC865988, EC865989, EC865990, EC865991, EC865992, EC865993, EC865994, EC865995, EC865996, EC865997, EC865998, EC865999, EC866000, EC866001, EC866002, EC866003, EC866004, EC866005, EC866006, EC866007, EC866008, EC866009, EC866010, EC866011, EC866012, EC866013, EC866014, EC866015, EC866016, EC866017, EC866018, EC866019, EC866020, EC866021, EC866022, EC866023, EC866024, EC866025, EC866026, EC866027, EC866028, EC866029, EC866030, EC866031, EC866032, EC866033
IndiaHUDP-15, HFP-8909, HFP-4, HFP-9907
Table
Table 2. Showing genetic diversity of the germplasm on the basis of polymorphic characteristics of SSR markers.
Table 2. Showing genetic diversity of the germplasm on the basis of polymorphic characteristics of SSR markers.
NoSSR MarkerNo of Alleles (Na)Major Allele Frequency (A)Gene Diversity (He)Heterozygosity (Ho)PIC *
1AA13520.5880.4840.0000.367
2AA17620.9070.1670.0000.153
3AA20620.9910.0160.0000.016
4AA345-14520.9320.1250.0000.117
5AA372.120.7050.4150.0000.329
6AA41620.5630.4920.0000.371
7AA44620.8060.3110.0000.263
8AA50520.5290.4980.0000.374
9AA5740.6170.5050.6970.419
10AA6120.9830.0330.0000.032
11AA9840.7140.4120.5630.334
12AB2420.9490.0950.0000.091
13AB6020.6550.4510.0000.349
14AD14620.7890.3310.0000.276
15AD14720.9910.0160.0000.016
16AD23740.4030.6570.0000.584
17AD7029020.9910.0160.0000.016
18B1420.5370.4970.0000.373
19B1690.4200.6300.3520.555
20P4620.8060.3110.0000.263
21PSAB6020.5290.4980.0000.374
22S24420.8570.2440.0000.214
23CAASESP52720.8820.2070.0000.186
24S14420.9740.0490.0000.047
24S8530.6800.4390.0000.350
26B17920.8990.1810.0000.164
27CAASESP117320.9070.1670.0000.153
28P28230.6720.4940.0000.443
29CAASESP52420.7810.3410.0000.283
30CAASESP119320.6720.4400.0000.343
31P25530.4200.6530.0000.579
Mean30.7470.3280.0520.272
Max.90.9910.6570.6970.584
Min.20.4030.0160.0000.016
*, denotes Polymorphic Information Content.
Table
Table 3. Depicting the development of pea rust (Uromyces viciae-fabae).
Table 3. Depicting the development of pea rust (Uromyces viciae-fabae).
Entry No.Accession No.AUDPCEntry No.Accession
No.		AUDPCEntry No.Accession
No.		AUDPC
1EC86591959241EC86595987281EC865999745
2EC86592070042EC865960109182EC866000547
3EC86592133443EC86596156083EC866001481
4EC86592283444EC86596247684EC866002543
5EC86592372345EC86596357585EC866003876
6EC86592469846EC86596484386EC866004679
7EC86592546347EC86596554687EC866005881
8EC86592653748EC86596662888EC866006845
9EC86592779449EC86596752789EC866007507
10EC86592868250EC86596849190EC866008530
11EC86592934451EC86596954491EC866009744
12EC86593046952EC86597087192EC866010562
13EC86593182453EC86597185093EC866011872
14EC86593283354EC86597279494EC866012436
15EC86593379955EC86597375695EC866013796
16EC86593453856EC86597484996EC866014539
17EC86593554057EC86597529297EC866015845
18EC86593653658EC86597678298EC866016861
19EC86593786859EC86597783999EC866017878
20EC86593882660EC865978459100EC866018853
21EC86593957261EC865979896101EC866019746
22EC86594076262EC865980873102EC866020650
23EC86594172363EC865981860103EC866021548
24EC86594267664EC865982842104EC866022843
25EC86594345265EC865983869105EC866023527
26EC86594438966EC865984550106EC866024576
27EC86594587167EC865985861107EC866025588
28EC86594670668EC865986861108EC866026383
29EC86594785269EC865987546109EC866027916
30EC86594888170EC865988524110EC866028382
31EC86594987671EC865989656111EC866029857
32EC86595088672EC865990910112EC866030853
33EC86595134473EC865991549113EC866031345
34EC86595288374EC865992565114EC866032383
35EC86595382575EC865993550115EC866033351
36EC86595491576EC865994492116 *HUDP-15371
37EC86595575777EC865995542117 *HFP-8909851
38EC86595656978EC865996866118 *HFP-41136
39EC86595784979EC865997566119 *HFP-9907514
40EC86595886080EC865998864
*, Denotes differential; AUDPC, stands for area under disease progress curve.
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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/su142215082

AMA Style

Yadav AS, Singh AK, Chand R, Vaish SS. 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(22):15082. https://doi.org/10.3390/su142215082

Chicago/Turabian Style

Yadav, Anmol Singh, Anil Kumar Singh, Ramesh Chand, and Shyam Saran Vaish. 2022. "Genetic Characterization and Population Structure of Pea (Pisum sativum L.) by Molecular Markers against Rust (Uromyces viciae-fabae) in Newly Developed Genotypes" Sustainability 14, no. 22: 15082. https://doi.org/10.3390/su142215082

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