Next Article in Journal
Special Issue “Recent Advances in Genomics, Genetic Resources Evaluation and Breeding of Cucurbitaceae Crops”
Previous Article in Journal
Improvement of Fruit Quality and Phytochemical Components of Pomegranate by Spraying with B2O3 and ZnO Nanoparticles
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 13
Issue 9
10.3390/agronomy13092307
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Assessment of Genetic Diversity and Protein Content of Scandinavian Peas (Pisum sativum)

by
Louise Winther
,
Søren Kjærsgaard Rasmussen
,
Gert Poulsen
and
Conny Bruun Asmussen Lange
*
Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, DK-1871 Copenhagen, Denmark
*
Author to whom correspondence should be addressed.
Agronomy 2023, 13(9), 2307; https://doi.org/10.3390/agronomy13092307
Submission received: 18 July 2023 / Revised: 28 August 2023 / Accepted: 30 August 2023 / Published: 31 August 2023
(This article belongs to the Special Issue Molecular Genetics, Genomics and Biotechnology of Crop Plants Breeding—Series III)
Browse Figures
Review Reports Versions Notes

Abstract

:
We produced homogeneous lines of 227 pea accessions from the Nordic Genetic Resource Center via single seed descent. The genetic diversity among these, mostly Scandinavian accessions, was investigated using three microsatellite markers, A9, AC58 and AA5. The microsatellites were highly informative and separated 153 of 194 accessions on a Neighbor Joining topology. The high polymorphism information content (PIC) values between 0.87 and 0.91 indicated that the gene bank material contains a large number of pea accessions with different breeding histories. The peas were grown in the field for two years and seed protein content showed variation between 9.3% and 34.1% over the years and accessions, respectively. The mean thousand seed weight was 152.05 g. More than 10 accessions had a protein content above 28%, showing that the collection has potential as breeding nursery for high-protein pea cultivars.

Graphical Abstract

1. Introduction

Peas (Pisum sativum L.) have been grown in Denmark since 500–1500 AD and sweet and soft pea types for human consumption since 1600 [1]. Pisum sativum, originating in the Mediterranean region, has been adapted to the temperate climate and long days of Denmark. The world production of peas is 10.5 mill hectares [2]. Pisum sativum belongs to the legume family, Fabaceae, and is a self-pollinated, diploid species with 2n = 14 and a very large genome of 3.92 Gb [3]. Peas were the model plant used by Gregor Mendel to discover general rules for genetic heredity [4]. Peas are currently an important crop for food, feed and sidechain products, with a great potential for future farming. The content of dietary proteins in different pea cultivars ranges from 24.3 to 32.6%. The starch content is between 33.4 and 47.5% and peas contain fibers as well as mineral nutrients [5,6]. Others found that the protein content of pea cultivars varies with environmental and agronomic factors [7,8,9] with a typical span in protein content from 14.5% to 28% [10,11]. The symbiosis with nitrogen-fixing soil bacteria favors the growing of peas in low-input farming systems because it reduces the need for nitrogen fertilizers, and when used in crop rotation, peas add nitrogen to the soil [3,12].
The genetic diversity in peas has been studied using microsatellites also named simple sequence repeats (SSR). A worldwide collection of 372 pea cultivars and landraces has been analyzed using 29 different microsatellite markers [13]; a collection of 175 pea cultivars from the Czech Republic has been analyzed using seven microsatellite markers [14], and 130 pea landraces from Turkey were analyzed using 14 markers [15]. The genetic diversity measured as polymorphism information content (PIC) ranges from 0.15 to 0.96 for different types and numbers of microsatellites [15]. The microsatellite technique is also efficient when analyzing smaller dedicated pea collections such as garden peas, forage peas, landraces and historical collections from various countries, e.g., Tunisia, Anatolia, Australia, India, and from gene banks [16,17,18,19,20,21,22,23,24,25]. These studies included between 8 and 34 microsatellites showing PIC values ranging from 0.19 to 0.84. Specific microsatellite markers are developed for a collection of field pea cultivars from Ethiopia, which also identify private alleles [26]. A recent study of a forage pea collection of landraces from Anatolia successfully differentiated the accessions into subgroups of locally adapted genotypes [17]. With the SSR markers already available in the literature cited above, the initial cost of employing SSR markers to the present study is low.
The polymorphic information content (PIC) describes the polymorphism and thus the informational value of the microsatellite. Generally, PIC values above 0.5 are highly informative, between 0.25 and 0.5 reasonably informative, and below 0.25 slightly informative [27]. In a study based on the pea genome, 309 microsatellites were constructed and 235 were polymorphic in either the first or second set of tests [28]. The number of PCR fragments (alleles) per microsatellite is between two and seven. The PIC value of the microsatellites varies from 0.04 to 1 with a mean of 0.63, thus showing a wide range of information from slightly to highly informative [27,28]. A comparison of the genetic variation and morphological features of 65 pea cultivars and 21 wild pea accessions [29] found 51% polymorphic information content and the dendrogram shows that diversity among the varieties from Europe is narrower than in the rest of the accessions. Furthermore, the study supports the assumption that the topology of the dendrogram reflects the pattern of refinement of the cultivars [29]. In an analysis of 19 pea cultivars primarily from Australia and Russia, five of eight microsatellites successfully produced 34 PCR fragments in total with 3 to 13 fragments per microsatellite [30]. The PIC values ranged from 0.18 to 0.79 with a mean of 0.62 and classified the microsatellites as highly informative. The genetic diversity among 35 pea accession was assessed with 15 microsatellites, which produced 41 different fragments, and all genotypes were identified on a UPGMA tree [31]. The PIC values ranged from 0.05 to 0.66 with a mean of 0.46. Jain et al. [32] investigated the genetic diversity among 96 cultivars from all over the world using 31 microsatellites along with 42 expressed sequence tag markers and 11 modern markers. The microsatellites identified 83 PCR fragments with an average of 2–6 per microsatellite and the PIC values varied from 0.01 to 0.56 with a mean of 0.29. Nasiri et al. [33] investigated 77 pea accessions from 17 countries using 10 microsatellites. The results included 59 PCR fragments, which varied from 2 to 8 per microsatellite. The PIC values ranged between 0.56 and 0.84, with a mean of 0.72. Kumari et al. [34] investigated 28 pea genotypes with 32 microsatellites, which resulted in 44 fragments with 2 to 4 fragments per microsatellites. The PIC values were between 0.31 and 0.66 with a mean of 0.49.
The current study surveyed a subset of the approximately 2500 pea accessions of Peas at the Nordic Genetic Resource Center, NordGen, https://www.nordgen.org/ (accessed on 16 March 2023), many of which were from the Weibullsholm Pisum collection. The accessions were primarily chosen based on prior knowledge of potential high protein content. The investigations were a first step in a pre-breeding process towards selecting and developing pea cultivars with a high protein content to meet the demand for plant-based protein for human consumption and as an alternative source of protein for husbandry. We address the following three questions: (1) What is the genetic diversity among the accessions and is the diversity structured? (2) What is the polymorphic information content? (3) What is the level of protein content and the thousand seed weight of accessions?

2. Materials and Methods

2.1. Plant Material

The plant material included in this study originated from the Nordic Genetic Resource Center, https://www.nordgen.org/ (accessed on 16 March 2023; Table 1. Most accessions originated from the Nordic countries and information on the specific location of origin, pedigree relationships, and proper cultivar name is in general sparse but some information may be retrieved in the seed database at https://www.nordic-baltic-genebanks.org/gringlobal/search.aspx (accessed on 16 March 2023). A total of 227 pea accessions were grown from a single seed in pots in the greenhouse. Plants were grown to maturity and the seeds were collected for further studies in the field.
Of the 227 accessions grown in the greenhouse, 199 were chosen for total nitrogen analyses based on previous information of high protein content. These were grown at the experimental farm of University of Copenhagen in Taastrup (55°40′ N; 12°18′ E), Denmark in the years 2017, 2018 and 2019. One individual per accession per year was analyzed. The seeds were hand-sown at approximately 1 seed per 10 cm in a two meter single row, and nets supported the growing plants. Both greenhouse plants and plants grown in the field were organized in the order of the Nordic Genbank number. Automatic irrigation was used when needed. At maturity, whole plants were harvested keeping accessions separate and then air-dried. Pods were collected from the dry plants and threshed by hand.

2.2. Microsatellites

Total genomic DNA was extracted from green leaf material of 194 pea accessions via the CTAB method [35]. The DNA was dissolved in 50 μL 1× TE buffer and the quality of the total genomic DNA was assessed via agarose gel electrophoresis (Electrophoresis Consort EV265, Cohasset, MA, USA) and spectrophotometry on an Uvidoc (Buch & Holm, Herlev, Denmark).
The microsatellite markers AA5, AC58 and A9 were chosen after initial screening of a larger set of microsatellite markers and based on previous success reported by Loridon et al. [28]. When tested AA5, AC58 and A9 produced consistently good quality data across the large number of accessions. All forward primers had an M13-tail (CACGACGTTGTAAAACGAC) with a dye attached. The forward primer of AA5 had a FAM, A9 a NED and AC58 a VIC dye (Table 2).
Each PCR sample consisted of 1 μL total genomic DNA, 7.25 μL double-distilled water, 1 μL 10× Dreamtaq buffer (20 mM Mg Cl2), 0.4 μL dNTP (2.5 μM), 0.125 μL forward primer with M13-tail and color (10 μM), 0.125 μL reverse primer (10 μM), and 0.1 μL Dreamtaq Polymerase. The samples were mixed and run on a T100 Thermal Cycler (Bio-Rad Laboratories, Copenhagen, Denmark) using the following protocol: 94 °C for 4 min, 19 cycles of 94 °C for 1 min, 64 °C for 30 s (annealing), and 1 min of 72 °C. The annealing temperature was decreased half a degree for every cycle ending at 55 °C. Then, an additional 19 cycles were conducted with the same steps using a constant annealing temperature of 55 °C, followed by 10 min at 72 °C, and a final cooling to 4 °C.
The PCR products were diluted 1:5, and 3 μL of the diluted PCR product was mixed with 10 μL formamide and 0.5 μL GeneScan™ 120 LIZ™ (standard). The samples were denatured at 95 °C for 5 min and put on ice for 2 min. The samples were applied to an ABI 3130xl Genetic Analyzer (Hitachi, Tokyo, Japan) using the program Genetic Mapper Instrument protocol Fragment36_POP7_G5, and the resulting fragments were visualized on GeneScan® 3.7 Analysis Software (Applied Biosystems, Roskilde Denmark).
The resulting microsatellite band patterns were treated as binary characters where the presence of a given PCR fragment was marked as 1, absence as 0 and lacking results were marked as “?”. All data from the three microsatellite markers were combined into one Microsoft Excel file and later converted to a text file (.txt) to generate the full matrix.

2.3. Thousand Seed Weight and Protein Content

Thousand seed weight (TSW) was determined by seed counting on a Contador Seed counter (Pfeuffer, Kitzingen, Germany) and then weighed.
Total N was determined via the Dumas method on a Vario Macro Cube (Elementar) [36] and crude protein content (%, w/w) was calculated using the conversion factor 5.44 [37,38].

2.4. Data Analysis

2.4.1. Polymorphism Information Content

Polymorphism information content (PIC) was calculated for the microsatellite data. The values were calculated using the following equation, where p i is the frequence of the i allele [27] (see also [28]):
P I C = 1 − ∑ p i 2

2.4.2. Neighbor Joining Tree

A Neighbor Joining tree was constructed based on the binary matrix in PAUP 4.0a169 [39]. The parameters were set to BioNJ method with mean character difference as distance measure, and all characters were given equal weight. A Neighbor Joining bootstrap analysis was run with 2000 repetitions. Bootstrap values of 50% or above were manually added to the Neighbor Joining tree.

2.4.3. Principal Coordinate Analysis of Microsatellite Data

A Principal Coordinate analysis (PCoA) was performed in GenAlEx [40,41] on the microsatellite data. Binary data were converted into columns of codominant genotypic microsatellite data with loci scored as fragment size in accordance with the GenAlEx-formats. A genetic distance tri-matrix was then made in GenAlEx, from which a PCoA was performed.

2.4.4. ANOVA of Crude Protein across Years

A one-way ANOVA was performed in Microsoft Excel, comparing the difference between protein content across the three years. A Tukey–Kramer post hoc test was performed in Excel to compare the mean between each pairwise combination of years.

3. Results

Single seed descent was used to obtain a homogeneous seed stock of 227 genebank accessions for further field evaluations and for DNA extractions, molecular identification and phylogenetic analysis.

3.1. Plant Material

All seeds germinated and leaf material from all plants were collected for DNA extraction.

3.2. Microsatellites

DNAs were successfully extracted from all 194 samples selected for microsatellite analyses. PCRs from the marker AA5 resulted in 185 successful amplifications (95.4%), marker AC58 and A9 both resulted in 186 (95.8%) successful amplifications (Table 1). All together, a total of 25 accessions lacked results for one of the three primer pairs: SKR 8, 27, 42, 78, 97, 99, 100, 103, 106, 110, 117–119, 123, 125, 129, 131, 134, 135, 138, 182, 200, 202, 216 and 218 (Table 1).
The final matrix included 77 different PCR fragments from the three primer pairs. Marker AA5 provided 21 PCR fragments, marker AC58 27 PCR fragments, and marker A9 had 29 PCR fragments. The length of the PCR fragments varied from 110 to 407 base pairs (bp), where the smallest fragments were from AA5 and the largest from A9.
For the marker AA5, 5 of 21 PCR fragments were uninformative. The most common PCR fragment for AA5 was present in 64 samples and the length was 127 bp. For the marker AC58, 9 of 27 PCR fragments were uninformative. The most common in AC58 was present in 37 samples. For marker A9, 9 of 29 PCR fragments were uninformative. In A9, the most frequent PCR fragment was present in 26 accessions and had the length of 387 bp.

3.3. Thousand Seed Weight and Protein Content

Thousand seed weight (TSW) was determined for 102 field grown accessions in 2017 as a measure of seed size and ranged from 64 to 254.2 g (Table 1; Figure 1) with a mean of 152.05 g. The distribution (Figure 1) indicated that the majority of the accessions had a TSW between 120 and 180 g.
The protein content was successfully determined for field grown material, with 199 accession in 2017, 95 accessions in 2018 and 30 accessions in 2019 (Table 1). The protein content varied from 9.3% (SKR 182, NGB102130) to 34.1% (SKR 64, NGB105862) for all years (Table 1) and most samples had a protein content between 16% and 28% protein content (Figure 2). All years showed a Gaussian distribution of protein content of the accessions. The average was 20.7% in 2017, 26.2% in 2018 and 22.7% in 2019, and 13 accessions had a protein content above 28% (five above 30%) in 2017, 19% (five above 30%) in 2018 and 0 in 2019. Of the 10 accessions with the highest protein content in 2017, only 1 was in the top ten in 2018, although the 95 pea accessions selected for 2018 generally had a higher protein content and were chosen among the 199 accessions with the highest protein content in 2017. One-way ANOVA revealed a highly significant difference in protein content across the three years (F2.21 = 66.05, p = 9.44 × 10−25). Tukey–Kramer post hoc test found that the protein content was significantly different among years.

3.3.1. Polymorphism Information Content

The PIC values for marker AA5, AC58 and AA9 were 0.87, 0.90 and 0.91, respectively. The average PIC value was 0.89.

3.3.2. Neighbor Joining Tree

The Neighbor Joining analyses resulted in a tree topology with 107 groups of 194 accessions (Figure 3). The bootstrap analysis resulted in branch support for 11 groups ranging between 50% and 89%. Most groups did not have bootstrap support (Figure 3). We had cultivar names for 77 of the 194 accessions included in the NJ analysis. Fifty-three cultivars were represented by only one accession. Twelve accessions were from the cultivar Pisum sativum “chlorotica”, four from “variomaculata”, two from “compactum”, two from “costata”, two from “New Wales”, and two from “Lilaska” (Figure 3; Table 1). The “chlorotica” cultivars were resolved in several different groups on the NJ tree, but most of them clustered around the same few branches (Figure 3). The other cultivars resolved far apart on the NJ tree.

3.3.3. Principal Coordinates of Microsatellite Data

The first two principal components of the PCoA accounted for 16.62% of the variance between the accessions of the three microsatellites combined (Figure 4). The pattern of variation mirrored the placement of samples in the NJ tree.

3.3.4. Nitrogen Content and Thousand Seed Weight in Relation to Genetic Diversity

The results from the total N analyses showed no apparent relationship between the protein content and the genetic diversity among the pea accessions. The accessions with high protein content did not cluster either in the NJ tree or in the PCoA.

4. Discussion

The primary goal of this study was to examine the genetic diversity in pea accessions, which have primarily been grown and collected in Scandinavia. The genetic variation was investigated using three microsatellite markers, which all functioned well and resulted in high genetic variation. Furthermore, the protein content was determined for different subsets of the accessions over three years and thousand seed weight was measured for one year.

4.1. Microsatellites

The microsatellite AC58 produced 186 PCR fragments that varied between 210 and 263 bp. The number of fragments were higher than other studies where 1–11 fragments are reported, but the lengths were within what other studies have found: 200–263 bp [15,19,28,31,34]. The microsatellite AA5 produced 185 different PCR fragments of lengths from 110 to 264 bp. The number of fragments were higher than other studies where 1–3 fragments are reported, and the lengths spanned a wider range than the 225 to 250 bp reported in other studies find [15,28,34]. The microsatellite A9 produced 186 different PCR fragments with lengths that varied between 325 and 407 bp. The number of fragments were higher than in other studies, where one to six fragments were reported, and the lengths spanned a somewhat wider range than the 330–390 bp observed in previous studies [14,17,18,21,28,31].
To sum up, most previous studies produced 2–4 DNA fragments for each microsatellite, except for the study of Hagenblad et al. [19], where 14–33 DNA fragments were found. Hagenblad et al. [19], like in our study, used Scandinavian pea accessions from NordGen. This indicates that the collection of Scandinavian pea accessions at NordGen are genetically diverse. The results could have been even more discriminating if more than three microsatellites had been analyzed.

4.2. Polymorphism Information Content

The PIC values in this study (0.87–0.91) were high when compared to other studies. The reported PIC values for pea accessions fall within a wide range from 0.3 to 1.0 for individual microsatellite markers. The variation in PIC values is higher in studies developing microsatellites, e.g., PICs varied between 0.04 and 1.0 with an average of 0.63 in Loridon et al. [28]. Many studies focus on the genetic diversity within a specific group of accessions and use already tested microsatellites. The PIC values of these studies do not span the same variation as Loridon et al. [28] did. A few studies did find PIC values as high as in this study. Burstin et al. [13] use a large number of accessions and many microsatellites and obtained PIC values between 0.46 and 0.97 with a mean of 0.8 for 372 wild and cultivated pea accessions using 29 microsatellites. Nasiri et al. [33] found an average PIC value of 0.72 for 77 pea accessions from 17 different countries with 10 microsatellites. However, most studies found lower PIC values than our study, between 0.3 and 0.65, most using a larger number of microsatellites [14,16,17,18,20,21,22,23,24,28,30,31,32]. Singh et al. [20] use 20 microsatellites to assess the genetic diversity of 47 pea accessions from India and obtained an average PIC value of 0.55, ranging from 0.04 to 0.85. Another study [22] assessed 40 pea accessions with five microsatellites and obtained PIC values between 0.14 to 0.82. Of all studies assessing genetic variation in peas [13,14,15,16,17,18,19,20,21,22,23,24,25,26,29,30,31,32,33,34], only three studies [13,15,33] reported results where all the microsatellites had a PIC value of 0.46 or higher.
The PIC values are mainly affected by the variation among the included individuals; however, the number of microsatellites may affect the outcome of the average PIC value because the number affects the statistical strength by potentially adding more variation [27,31]. The genome of Pisum sativum is large, approximately 4.45 giga base pairs [3], and therefore the results of this study could be affected by the low number of microsatellites included three.
The PIC values in this project varied between 0.87 and 0.91 with an average of 0.89. For the same specific microsatellites, Loridon et al. [28] finds PIC values of 0.69 (A9), 0.84 (AC58) and 0.78 (AA5). Other studies using the A9, AC58 and AA5 microsatellites find PIC values between 0.61 and 0.78 [14,15,17,18,19,31,34] except for the A9 microsatellite of Haliloglu et al. [17], which has a low PIC value of 0.03.
The PIC values of this study were therefore among the highest reported for genetic variation among pea accessions [13,14,15,16,17,18,19,20,21,22,23,24,25,26,28,29,30,31,32,33,34]. The average PIC value is not only affected by the variation among individuals for each microsatellite included but also by the number of accessions, because the chance of identifying different alleles rises with the number of accessions included [27,31]. Thus, the higher PIC values in the present study could partially be explained by the larger number of accessions (194) compared to most studies [16,17,18,19,20,21,22,23,26,28,29,31,32,33,34]. Some studies included more than 100 accessions [13,14,15], however, and few more than 500 [24,25,30].
This study, along with most of the studies on genetic diversity of peas, placed the microsatellites used in the category, “highly informative”, because the PIC values are above 0.5 [27]. The high PIC values of this and other studies could be explained by the selection of the most polymorphic markers from the study of Loridon et al. [28] or similar studies where a large number of microsatellites were included. The high average PIC value of this study could be interpreted as a reflection of a high genetic variation in general among the 194 accessions included. This high genetic variation indicates that the accessions had not undergone a targeted breeding for specific agronomical traits and homozygosity [32]. The high PIC values might thus be explained by the inclusion of a large number of pea accessions with different breeding histories.

4.3. Neighbor Joining Tree

The Neighbor Joining tree uniquely identified 153 of the 194 accessions (78%) and 108 groups were resolved as monophyletic using three microsatellites (Figure 3). Jain et al. [32] uniquely identify all 96 individuals included in the study in the NJ topology, but they included 42 polymorphic markers, distributed throughout the genome. Many studies using more microsatellites have produced a full resolution of the NJ tree [26,31,32]. One study using three microsatellites obtained 95% resolution of the topology, but this study was partly at the species level [29], whereas the present study was below the species level. In the study by Bouhadida et al. [30], 18 of 19 accessions (94.7%) are uniquely identified on an unweighted pair group method (UPGMA) topology through the use of five microsatellite markers. The UPGMA and NJ methods use the same underlying model, but UPGMA assumes a similar rate of evolution rate along the branches of the tree (molecular clock) [42]. The bootstrap support values of our study were low (Figure 3) [43]. The low bootstrap support and the lack of resolution in the NJ topology is mainly explained by a lack of variation due to insufficient DNA fragments of each microsatellite. A total of 77 variable DNA fragments is not enough to fully resolve 194 accessions [43]. Another possible explanation for the low bootstrap support is the taxonomic level. For studies below the species level, bootstrap values cannot always be expected to be high [43]. A third factor affecting the outcome of the NJ topology in this study is missing results for some individuals. Twenty-five accessions lacked data for one of the three microsatellites, which contributed to greater uncertainty in the branching pattern and collapse of branches [44].
The genetic diversity of named cultivars was expected to be structured such that accessions with the same cultivar name would be included in the same monophyletic group. However, such a structure did not appear. The 12 cultivars for which we had more than one accession were resolved in different positions on the NJ tree (Figure 3, colored cultivars). One group included accessions from “chlorotica”, “reductus”, “superaeromaculata” and “compactum” (Figure 3, colored cultivars). This lack of structure could partly be explained by the lack of sufficient data [3,24,34]. However, the resolution of individuals from the same cultivar at different places in the NJ tree may also be the result of genetic variation among individuals. This variation may be due to separation in time creating genetic diversity because of crosspollination resulting in polymorphism [29]. Peas from Ethiopia are genetically similar and resolve as a monophyletic group, whereas accessions from other countries, e.g., USA and Norway, do not show such similarity and do not resolve as monophyletic [33]. This lack of similarity can be explained by a gene flow between countries, e.g., use of genetic material from more than one country. The lack of a clear pattern among cultivars included in this study might be due to a high exchange of genetic material among breeding companies in Scandinavia, because the accessions of the same cultivar were not necessarily from the same source.

4.4. Thousand Seed Weight and Protein Content

Seed size is an important agronomic trait for yield and productivity that is inherited and characteristic of specific cultivars. Seed size is a quantitative trait controlled by many genes. Thousand seed weight is a simple method for measuring seed size. We found large variation from 64.4 g (SKR 46, NGB103568) to 251.2 g (SKR 218, NGB103607).
Protein content varied from 9.3% (SKR 182, NGB102130) to 34.1% (SKR 64 NGB105862) over all years and accessions. One goal of this study was to identify high-protein pea accessions, and 13 were found to have a protein content above 28% in 2017 and 19 in 2018, but none in 2019. This emphasizes the variation in protein content across the years, as the accessions with determined protein content for the years following 2017 was selected for high protein content. The selection of peas with a high protein in 2017 for analyses in 2018 moved the distribution to the right (Figure 2). We expected the protein content of the 2019 samples to show the same pattern and be placed even further to the right, but this was not the case. Year to year variation in protein content is well documented and is assumed to be due to differences in weather [45]. In comparison to other studies, the protein content was 23.9 ± 2.5% and TSW 195.9 ± 16.9 g for a collection of 1222 accession of cultivars and landraces cultivated during 1979–1982 with irrigation and standard management in Sweden [46]. A recent study of 50 accessions assessed for their potential in the Arctic region showed an average protein content of 26% in Denmark, 24% in Sweden and 20% in Finland [47].
An analysis of 198 peas (Pisum sativum L. cv. Trapper) from Saskatchewan farmers showed a protein content of 14.5% to 28.5% with a Gaussian distribution [11]. The protein content was determined from the Kjel-Foss method with a conversion factor of 6.25. Wang and Daun [10] determined the protein content via the Dumas method (N × 6.25) for six samples of four different pea varieties with a crude protein content ranging from 20.2% to 26.7%. Thus, the studies show that there is natural variation among peas. The variation in our study was more wide-ranging, and while some accessions had a lower protein content than that reported in previous studies, there were accessions that were higher than in most other reports. Only Slinkard [48] reported a protein content above 30%.

4.5. Future Perspectives

The next step could be to investigate the history of and characterize the cultivars and accessions included in this study. These accessions were primarily from Scandinavia and all from Nordic Gene bank and they were chosen primarily because there were some indications but not necessarily confirmations of high protein content.
A high genetic diversity among pea accessions from a gene bank is valuable because researchers want to preserve as much diversity as possible for future breeding. By targeted crossing of genetically diverse individuals, a selection of plants with desirable traits such as high protein, high resistance or tolerance to drought, followed by breeding towards homozygosity, it is possible to actively use the preserved genetic diversity to develop pea cultivars for the future [3,12,32].
Microsatellites are only one of several methods to study genetic diversity. Microsatellites are popular due to their co-dominance and high polymorphism. Methods in which differences across the genome are targeted give more data and are more likely to resolve genetic diversity among accessions. An example of such a method is Diversity Array Technology (DArT), [49].
Our results increase our understanding of genetic diversity across pea varieties, and could contribute to the sustainable cultivation of peas and adaptation to climate change.

5. Conclusions

Homogeneous lines of 227 pea accessions from seed stocks at NordGen were produced via single seed descent. The peas were grown in a field for 2 years and the seed protein content showed a variation between 9.3% and 34.1% over years and accessions and thousand seed weight were on average 152.05 g. More than 10 accessions had a protein content above 28%, showing that the collection has potential as breeding nursery for high-protein pea cultivars. Three microsatellites were highly informative. The microsatellites separated 153 of 194 accessions and had PIC values between 0.87 and 0.91, indicating that the gene bank material contains a large number of pea accessions with different breeding.

Author Contributions

Conceptualization, S.K.R., G.P. and C.B.A.L.; methodology, S.K.R. and C.B.A.L.; software, L.W. and C.B.A.L.; validation, C.B.A.L. and L.W.; formal analysis, C.B.A.L., L.W. and S.K.R.; investigation, C.B.A.L., S.K.R. and L.W.; data curation, L.W. and C.B.A.L.; writing—original draft preparation, L.W.; writing—review and editing, L.W., S.K.R. and C.B.A.L.; visualization, L.W. and C.B.A.L.; supervision, C.B.A.L. and S.K.R.; project administration, S.K.R.; funding acquisition, S.K.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by The Danish Agricultural Agency, Genetic Resources, grant numbers 16-3262-000061 and 18-26051-000011; and organic RDD Peas & Love project 34009-21-1895.

Data Availability Statement

Data are available from the Dryad Digital Repository: at https://doi.org/10.5061/dryad.d7wm37q6b, accessed on 29 August 2023.

Acknowledgments

We thank NordGen for providing seeds of pea accessions, Didde Hedegaard Sørensen and Vinnie Deichmann for support in the lab, Weiyao Fan for help with the field trails, the anonymous reviewers for helpful comments on the manuscript, and Jacob Weiner for editorial support.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Davies, D.R. Peas, Pisum sativum. In Evolution of Crop Plants, 2nd ed.; Smartt, J., Simmonds, N.W., Eds.; Longman Scientific & Technical: London, UK, 1995; pp. 294–296. ISBN 0-582-08643-4. [Google Scholar]
  2. FAOstat. 2022. Available online: https://www.fao.org/faostat/en/#data (accessed on 15 November 2022).
  3. Kreplak, J.; Madoui, M.-A.; Cápal, P.; Novak, P.; Labadie, K.; Aubert, G.; Bayer, P.E.; Gali, K.; Syme, R.A.; Main, D.; et al. A reference genome for pea provides insight into legume genome evolution. Nat. Genet. 2019, 51, 1411–1422. [Google Scholar] [CrossRef]
  4. Mendel, G. Versuche über Plflanzenhybriden. Verhandlungen des Naturforschenden Vereines in Brünn, Bd. IV für das Jahr 1865, Abhandlungen. 1866, pp. 3–47. Available online: http://www.esp.org/foundations/genetics/classical/gm-65.pdf (accessed on 17 July 2023).
  5. Bastianelli, D.; Grosjean, F.; Peyronnet, C.; Duparque, M.; Regnier, J.M. Feeding value of pea (Pisum sativum, L.). Chemical composition of different categories of pea. Anim. Sci. 1998, 67, 609–619. [Google Scholar] [CrossRef]
  6. Nikolopoulou, D.; Grigorakis, K.; Stasini, M.; Alexis, M.; Iliadis, K. Differences in chemical composition of field pea (Pisum sativum) cultivars: Effects of cultivation area and year. Food Chem. 2007, 103, 847–852. [Google Scholar] [CrossRef]
  7. Holl, F.B.; Vose, J.R. Carbohydrate and protein accumulation in the developing field pea seed. Can. J. Plant Sci. 1980, 60, 1109–1114. [Google Scholar] [CrossRef]
  8. McLean, L.A.; Sosulski, F.W.; Youngs, C.G. Effects of nitrogen and moisture on yield and protein in field peas. Can. J. Plant Sci. 1974, 54, 301–305. [Google Scholar] [CrossRef]
  9. Robertson, R.N.; Highkin, H.R.; Smydzuk, J.; Went, F.W. The Effect of Environmental Conditions on the Development of Pea Seeds. Aust. J. Biol. Sci. 1962, 15, 1–15. [Google Scholar] [CrossRef]
  10. Wang, N.; Daun, J.K. Effect of variety and crude protein content on nutrients and certain antinutrients in field peas (Pisum sativum). J. Sci. Food Agric. 2004, 84, 1021–1029. [Google Scholar] [CrossRef]
  11. Reichert, R.D.; MacKenzie, S.L. Composition of peas (Pisum sativum) varying widely in protein content. J. Agric. Food Chem. 1982, 30, 312–317. [Google Scholar] [CrossRef]
  12. Smykal, P.; Aubert, G.; Burstin, J.; Coyne, C.J. Pea (Pisum sativum L.) in the Genomic Era. Agronomy 2012, 2, 74–115. [Google Scholar] [CrossRef]
  13. Burstin, J.; Salloignon, P.; Chabert-Martinello, M.; Magnin-Robert, J.-B.; Siol, M.; Jacquin, F.; Chauveau, A.; Pont, C.; Aubert, G.; Delaitre, C.; et al. Genetic diversity and trait genomic prediction in a pea diversity panel. BMC Genom. 2015, 16, 105. [Google Scholar] [CrossRef]
  14. Cieslarova, J.; Hybl, M.; Griga, M.; Smykal, P. Molecular analysis of temporal genetic structuring in pea (Pisum sativum L.) cultivars bred in the Czech Republic and in former Czechoslovakia since the mid-20th century. Czech J. Genet. Plant Breed. 2012, 48, 61–73. [Google Scholar] [CrossRef]
  15. Hanci, F. Genetic variability in peas (Pisum sativum L.) from Turkey asssessed with molecular and morphological markers. Folia Hortic. 2019, 31, 101–116. [Google Scholar] [CrossRef]
  16. Sharma, A.; Sharma, S.; Kumar, N.; Rana, R.S.; Sharma, P.; Kumar, P.; Rani, M. Morpho-molecular genetic diversity and population structure analysis in garden pea genotypes using simple sequence repeat markers. PLoS ONE 2022, 17, e0273499. [Google Scholar] [CrossRef]
  17. Haliloglu, K.; Turkoglu, A.; Tan, M.; Poczai, P. SSR-Based Molecular Identification and Population Structure Analysis for Forage Pea (Pisum sativum var arvense L.) Landraces. Genes 2022, 13, 1086. [Google Scholar] [CrossRef]
  18. Mohamed, A.; García-Martínez, S.; Loumerem, M.; Carbonell, P.; Ruiz, J.J.; Boubaker, M. Assessment of genetic diversity among local pea (Pisum sativum L.) accessions cultivated in the arid regions of Southern Tunisia using agro-morphological and SSR molecular markers. Genet. Resour. Crop Evol. 2019, 66, 1189–1203. [Google Scholar] [CrossRef]
  19. Hagenblad, J.; Boström, E.; Nygårds, L.; Leino, M.W. Genetic diversity in local cultivars of garden pea (Pisum sativum L.) conserved ‘on farm’ and in historical collections. Genet. Resour. Crop Evol. 2014, 61, 413–422. [Google Scholar] [CrossRef]
  20. Singh, J.; Dhall, R.K.; Vikal, Y. Genetic diversity studies in Indian germplasm of pea (Pisum sativum L.) using morphological and microsatellite markers. Genetika 2021, 53, 473–491. [Google Scholar] [CrossRef]
  21. Dribnokhodova, O.P.; Gostimsky, S.A. Allele polymorphism of microsatellite loci in pea Pisum sativum L. lines, varieties, and mutants. Russ. J. Genet. 2009, 45, 788–793. [Google Scholar] [CrossRef]
  22. Gainullina, K.P.; Kuluev, B.R.; Davletov, F.A. Genetic diversity assessment in pea cultivars and lines using the SSR analysis. Proc. Appl. Bot. Genet. Breed. 2020, 181, 70–80. [Google Scholar] [CrossRef]
  23. Ram, H.; Hedau, N.K.; Chaudhari, G.V.; Choudhary, M.; Kant, L. Genetic Diversity Assessment in Pea (Pisum sativum L.) using Microsatellite Markers. Int. J. Bio Resour. Stress Manag. 2021, 12, 402–408. [Google Scholar] [CrossRef]
  24. Wu, X.; Li, N.; Hao, J.; Hu, J.; Zhang, X.; Blair, M.W. Genetic Diversity of Chinese and Global Pea (Pisum sativum L.) Collections. Crop Sci. 2017, 57, 1574–1584. [Google Scholar] [CrossRef]
  25. Zong, X.-X.; Guan, J.-P.; Wang, S.-M.; Liu, Q.-C.; Redden, R.R.; Ford, R. Genetic Diversity and Core Collection of Alien Pisum sativum L. Germplasm. Acta Agron. Sin. 2008, 34, 1518–1528. [Google Scholar] [CrossRef]
  26. Teshome, A.; Bryngelsson, T.; Dagne, K.; Geleta, M. Assessment of genetic diversity in Ethiopian field pea (Pisum sativum L.) accessions with newly developed EST-SSR markers. BMC Genet. 2015, 16, 102. [Google Scholar] [CrossRef]
  27. Botstein, D.; White, R.L.; Skolnick, M.; Davis, R.W. Construction of a genetic linkage map in man using restriction length polymorphisms. Am. J. Hum. Genet. 1980, 32, 314–331. [Google Scholar] [PubMed]
  28. Loridon, K.; McPhee, K.; Morin, J.; Dubreuil, P.; Pilet-Nayel, M.L.; Aubert, G.; Rameau, C.; Baranger, A.; Coyne, C.; Lejeune-Hénaut, I.; et al. Microsatellite marker polymorphism and mapping in pea (Pisum sativum L.). Theor. Appl. Genet. 2005, 111, 1022–1031. [Google Scholar] [CrossRef] [PubMed]
  29. Tar’an, B.; Zhang, C.; Warkentin, T.; Tullu, A.; Vandenberg, A. Genetic diversity among varieties and wild species accessions of pea (Pisum sativum L.) based on molecular markers, and morphological and physiological characters. Genome 2005, 48, 257–272. [Google Scholar] [CrossRef] [PubMed]
  30. Bouhadida, M.; Srarfi, F.; Saadi, I.; Kharrat, M.M. Molecular characterization of pea (Pisum sativum L.) using microsatellite markers. IOSR J. Appl. Chem. 2013, 5, 57–61. [Google Scholar] [CrossRef]
  31. Ahmad, S.; Singh, M.; Lamb-Palmer, N.D.; Lefsrud, M.; Singh, J. Assessment of genetic diversity in 35 Pisum sativum accessions using microsatellite markers. Can. J. Plant Sci. 2012, 92, 1075–1081. [Google Scholar] [CrossRef]
  32. Jain, S.; Kumar, A.; Mamidi, S.; McPhee, K. Genetic diversity and population structure among pea (Pisum sativum L.) cultivars as revealed by simple sequence repeat and novel genic markers. Mol. Biotechnol. 2014, 56, 925–938. [Google Scholar] [CrossRef]
  33. Nasiri, J.; Haghnazari, A.; Saba, J. Genetic diversity among varieties and wild species accessions of pea (Pisum sativum L.) based on SSR markers. Afr. J. Biotechnol. 2009, 8, 3405–3417. [Google Scholar] [CrossRef]
  34. Kumari, P.; Basal, N.; Singh, A.K.; Rai, V.P.; Srivastava, C.P.; Singh, P.K. Genetic diversity studies in pea (Pisum sativum L.) using simple sequence repeat markers. Genet. Mol. Res. 2013, 12, 3540–3550. [Google Scholar] [CrossRef] [PubMed]
  35. Doyle, J.J.; Doyle, J.L. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem. Bull. 1987, 19, 11–15. [Google Scholar]
  36. Saint-Denis, T.; Goupy, J.  Optimization of a nitrogen analyses based on the Dumas method. Anal. Chim. Acta 2004, 515, 191–198. [Google Scholar] [CrossRef]
  37. Mosse, J. Nitrogen to Protein Conversion Factor for Ten Cereals and Six Legumes or Oilseeds. A Reappraisal of Its Definition and Determination. Variation According to Species and to Seed Protein Content. J. Agric. Food Chem. 1990, 38, 18–24. [Google Scholar] [CrossRef]
  38. Coyne, C.; Grusak, M.; Razai, L.; Baik, B. Variation for pea seed protein concentration in the USDA core collection.  Pisum Genet. 2005, 37, 5–9. [Google Scholar]
  39. Swofford, D.L. PAUP*. Phylogenetic Analysis Using Parsimony (*and Other Methods); Version 4; Sinauer Associates: Sunderland, MA, USA, 2003. [Google Scholar]
  40. Peakall, R.; Smouse, P.E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—An update. Bionformatics 2012, 28, 2537–2539. [Google Scholar] [CrossRef]
  41. Peakall, R.; Smouse, P.E. GENALEX6: Genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 2006, 6, 288–295. [Google Scholar] [CrossRef]
  42. Kalinowski, S. How well do evolutionary trees describe genetic relationships among populations? Heredity 2009, 102, 506–513. [Google Scholar] [CrossRef] [PubMed]
  43. Soltis, P.S.; Soltis, D.E. Applying the Bootstrap in Phylogeny Reconstruction. Stat. Sci. 2003, 18, 256–267. [Google Scholar] [CrossRef]
  44. Wiens, J.J. Missing data and the design of phylogenetic analyses. J. Biomed. Inform. 2006, 39, 34–42. [Google Scholar] [CrossRef]
  45. Klein, A.; Houtin, H.; Rond-Coissieux, C.; Naudet-Huart, M.; Touratier, M.; Marget, P.; Burstin, J. Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea. Sci. Rep. 2020, 10, 15925. [Google Scholar] [CrossRef] [PubMed]
  46. Solberg, S.Ø.; Yndgaard, F.; Poulsen, G.; von Bothmer, R. Seed yield and protein content in the Weibullsholm Pisum collection. Genet. Resour. Crop Evol. 2017, 64, 2035–2047. [Google Scholar] [CrossRef]
  47. Carlson-Nilsson, U.; Aloisi, K.; Vågen, I.M.; Rajala, A.; Mølmann, J.B.; Rasmussen, S.K.; Niemi, M.; Wojciechowska, E.; Pärssinen, P.; Poulsen, G.; et al. Trait Expression and Environmental Responses of Pea (Pisum sativum L.) Genetic Resources Targeting Cultivation in the Arctic. Front. Plant Sci. 2021, 12, 688067. [Google Scholar] [CrossRef] [PubMed]
  48. Slinkard, A.E. Percent Protein in the USDA World Collection of Peas Grown at Saskatoon in 1971; Crop Science Department, University of Saskatchewan: Saskatoon, SK, Canada, 1972. [Google Scholar]
  49. Wittenberg, A.H.J.; van der Lee, T.A.J.; Visser, R.G.F.; Schouten, H.J.; Kilian, A. Genome-Wide Profiling Using Diversity Arrays Technology (DArT); Theoretical Considerations and Practical Protocols. In Genetic Mapping Using the Diversity Arrays Technology (DArT)—Application and Validation Using the Whole-Genome Sequences of Arabidopsis Thaliana and the Fungal Wheat Pathogen Mycosphaerella Graminicola; Wittenberg, A.H.J., Ed.; Wageningen University: Wageningen, The Netherlands, 2007; Chapter 2; pp. 25–59. [Google Scholar]
Agronomy 13 02307 g001
Figure 1. Thousand seed weight of pea accessions in grams (n = 102). The peas were grown with irrigation and standard agricultural management in 2017 and harvested at maturity.
Figure 1. Thousand seed weight of pea accessions in grams (n = 102). The peas were grown with irrigation and standard agricultural management in 2017 and harvested at maturity.
Agronomy 13 02307 g001
Agronomy 13 02307 g002
Figure 2. Protein content (%, w/w) of pea accessions. Blue represents accession were from 2017 (n = 199), Green from 2018 (n = 95) and Black 2019 (n = 30).
Figure 2. Protein content (%, w/w) of pea accessions. Blue represents accession were from 2017 (n = 199), Green from 2018 (n = 95) and Black 2019 (n = 30).
Agronomy 13 02307 g002
Agronomy 13 02307 g003aAgronomy 13 02307 g003b
Figure 3. Neighbor Joining tree of 194 pea accessions with bootstrap values on supported branches. Highlighting indicates cultivars represented by more than one accession. Green: “costata”; orange: “chlorotica”; red: “compactum”; purple: “New Wales”; yellow: “Lilaska”; blue: “variomaculata”.
Figure 3. Neighbor Joining tree of 194 pea accessions with bootstrap values on supported branches. Highlighting indicates cultivars represented by more than one accession. Green: “costata”; orange: “chlorotica”; red: “compactum”; purple: “New Wales”; yellow: “Lilaska”; blue: “variomaculata”.
Agronomy 13 02307 g003aAgronomy 13 02307 g003b
Agronomy 13 02307 g004
Figure 4. Principal coordinates analysis of the microsatellite results. X- and y-axis represent PC1 and PC2, respectively.
Figure 4. Principal coordinates analysis of the microsatellite results. X- and y-axis represent PC1 and PC2, respectively.
Agronomy 13 02307 g004
Table 1. List of Pisum sativum accessions included in this study. SKR is the working number given to the accession in this study. Accession is the number from NordGen, www.NordGen.org (accessed on 16 March 2023). Name included cultivar name, if existing, WBH designate a pre-breeding line from Weibuhlholm. AA5, AC58 and AA9 were the microsatellites used and x indicate that the accession produced a result. TSW were the thousand seed weight and then seed protein content in % for 2017, 2018 and 2019.
Table 1. List of Pisum sativum accessions included in this study. SKR is the working number given to the accession in this study. Accession is the number from NordGen, www.NordGen.org (accessed on 16 March 2023). Name included cultivar name, if existing, WBH designate a pre-breeding line from Weibuhlholm. AA5, AC58 and AA9 were the microsatellites used and x indicate that the accession produced a result. TSW were the thousand seed weight and then seed protein content in % for 2017, 2018 and 2019.
SKR. No.AccessionNameAA5AC58AA9TSW 2017 (g) Protein 2017 (%)Protein 2018 (%)Protein 2019 (%)
SKR1NGB103441WBH 3441xxx178.123.426.9
SKR2NGB101418WBH 1418xxx107.320.320.8
SKR3NGB103563WBH 3563xxx 16.0
SKR4NGB101515WBH 1515xxx
SKR5NGB100756WBH 756xxx185.025.029.925.0
SKR6NGB101687WBH 1687xxx 19.7
SKR7NGB105795multimicrodentatusxxx 15.6
SKR8NGB103423Latah xx 14.3
SKR9NGB100463WBH 463xxx 16.0
SKR10NGB103565WBH 3565xxx 12.0
SKR11NGB101735Improved Harbingerxxx24421.025.6
SKR12NGB101736rouge C15xxx 17.7
SKR13NGB101339Bonnevillexxx180.226.422.0
SKR14NGB101741New Seasonxxx 19.5
SKR15NGB101603WBH 1603xxx
SKR16NGB103546W.S.U.-28xxx 22.325.9
SKR17NGB101772Wellensiek’s testerxxx 18.6
SKR18NGB101325WBH 1325xxx
SKR19NGB101330WBH 1330xxx 20.0
SKR20NGB101165WBH 1165xxx142.223.024.1
SKR21NGB103436WBH 3436xxx 18.3
SKR22NGB102963Wilt Resistant Thomas Laxton 172.824.725.8
SKR23NGB101889 xxx
SKR24NGB103439WBH 3439xxx 13.9
SKR25NGB103429WBH 3429xxx 20.624.1
SKR26NGB103583WBH 3583xxx
SKR27NGB100592WBH 592 xx
SKR28NGB103452WBH 3452xxx
SKR29NGB102158WBH 2158xxx135.518.621.5
SKR30NGB103422Alaskaxxx 18.2
SKR31NGB103449Feltham Firstxxx178.921.524.4
SKR32NGB103426Juneauxxx 17.8
SKR33NGB103442WBH 3442xxx 14.4
SKR34NGB103576WBH 3576xxx18731.7
SKR35NGB103578WBH 3578xxx19325.626.120.5
SKR36NGB100851procumbensxxx16523.428.5
SKR37NGB101338Salzmunder Edelperlexxx 17.1
SKR38NGB103433WBH 3433xxx 16.6
SKR39NGB102177WBH 2177xxx13223.727.3
SKR40NGB103438WBH 3438xxx 20.1
SKR41NGB101608WBH 1608xxx
SKR42NGB103435WBH 3435x x 12.1
SKR43NGB102058WBH 2058xxx 20.0
SKR44NGB101524patelliformisxxx
SKR45NGB101570WBH 1570xxx 13.1
SKR46NGB103568WBH 3568xxx64.421.722.2
SKR47NGB103581WBH 3581xxx
SKR48NGB105136chloroticaxxx76.430.022.924.4
SKR49NGB102184New Eraxxx 16.6
SKR50NGB102160WBH 2160xxx144.422.428.5
SKR51NGB103580WBH 3580xxx15623.721.3
SKR52NGB102022WBH 2022xxx10430.223.8
SKR53NGB102663WBH 2663xxx
SKR54NGB102203WBH 2203xxx 15.6
SKR55NGB102217chloroticaxxx 19.9
SKR56NGB105350/chlorina 157.227.324.8
SKR57NGB102431Laxtonian 19323.824.824.1
SKR58NGB105124ageotropumxxx 17.0
SKR59NGB102496 xxx15132.1
SKR60NGB102214chloroticaxxx12323.328.9
SKR61NGB102210chloroticaxxx14523.824.3
SKR62NGB102136WBH 2136xxx16225.426.3
SKR63NGB102216chloroticaxxx104.829.430.624.3
SKR64NGB105862densinodosum 15520.934.1
SKR65NGB105428chloroticaxxx 15.6
SKR66NGB102574Betaxxx150.122.424.6
SKR67NGB102622 xxx16422.424.921.1
SKR68NGB102988WBH 2988xxx 20.2
SKR69NGB106051reduced in waxxxx166.621.429.0
SKR70NGB102432Hundredfoldxxx 18.2
SKR71NGB105789/compactumxxx 19.0
SKR72NGB106060supaeromaculata 16.3
SKR73NGB102239 xxx 20.3
SKR74NGB102369WBH 2369xxx129.221.925.2
SKR75NGB105051/compactumxxx
SKR76NGB105432reductusxxx8426.225.1
SKR77NGB106080WBH 6080xxx 17.4
SKR78NGB102579 x x23127.023.1
SKR79NGB102581 xxx 24.5
SKR80NGB105765chlorotica 13220.926.1
SKR81NGB103431WBH 3431xxx 18.1
SKR82NGB102823Austrian Winterxxx 13.1
SKR83NGB103571WBH 3571xxx 14.4
SKR84NGB103572WBH 3572xxx
SKR85NGB103573WBH 3573xxx 17.3
SKR86NGB103585WBH 3585xxx 13.5
SKR87NGB101452WBH 1452xxx15922.322.0
SKR88NGB101192WBH 1192 15228.324.624.8
SKR89NGB101391WBH 1391xxx
SKR90NGB101689WBH 1689xxx 25.1
SKR91NGB101017WBH 1017xxx151.424.928.9
SKR92NGB101351WBH 1351xxx
SKR93NGB105534supaeromaculata 68xxx113.128.928.723.4
SKR94NGB102188WBH 2188xxx181.8722.627.7
SKR95NGB103420WA 788xxx 14.6
SKR96NGB103434WBH 3434 18.3
SKR97NGB103421Lilaska xx 18.9
SKR98NGB103428WBH 3428 18.5
SKR99NGB103432WBH 3432 xx 19.6
SKR100NGB102070Puke xx 16.2
SKR101NGB103577WBH 3577xxx174.821.926.0
SKR102NGB100909WBH 909 16022.024.0
SKR103NGB101500WBH 1500 xx99.120.526.3
SKR104NGB103437WBH 3437 6723.724.6
SKR105NGB102069Pateaxxx212.422.019.4
SKR106NGB103561WBH 3561 xx 21.2
SKR107NGB103567WBH 3567xxx 17.0
SKR108NGB105310cerosaxxx108.826.427.022.5
SKR109NGB103574WBH 3574xxx
SKR110NGB103575WBH 3575xx
SKR111NGB103579WBH 3579xxx 17.0
SKR112NGB103584WBH 3584xxx
SKR113NGB103602WBH 3602xxx 11.2
SKR114NGB103603WBH 3603xxx 18.7
SKR115NGB102901 xxx 12.8
SKR116NGB103430WBH 3430xxx 18.3
SKR117NGB103427WBH 3427xx 17.1
SKR118NGB102159WBH 2159xx 18.5
SKR119NGB102844 x x 19.2
SKR120NGB102185New Walesxxx20924.625.423.0
SKR121NGB101132WBH 1132xxx
SKR122NGB103570WBH 3570xxx 19.5
SKR123NGB103582WBH 3582 xx 18.7
SKR124NGB103604WBH 3604xxx 12.4
SKR125NGB103605WBH 3605xx 13.3
SKR126NGB101784Mrkos horizontalexxx
SKR127NGB102063WBH 2063xxx17224.426.920.7
SKR128NGB105765chlorotica 125.126.125.1
SKR129NGB102578 x x14833.626.021.2
SKR130NGB102537 19.1
SKR131NGB103458 x x118.420.626.722.2
SKR132NGB105161costataxxx9225.823.3
SKR133NGB102999WBH 2999xxx 17.4
SKR134NGB102687WBH 2687xx 178.521.226.922.7
SKR135NGB105267variomaculatax x14827.329.822.0
SKR136NGB105814chloroticaxxx11821.926.8
SKR137NGB102037WBH 2037xxx 17.2
SKR138NGB102190WBH 2190x x22328.826.122.4
SKR139NGB102763Wonder Van Amerika I2048xxx14222.227.4
SKR140NGB106000vixcerata 23229.428.623.0
SKR141NGB102582 19.5
SKR142NGB105449variomaculataxxx120.222.927.5
SKR144NGB102370WBH 2370xxx 22.2
SKR145NGB102621 xxx 19.2
SKR146NGB102927 xxx 17.5
SKR147NGB103459 xxx15025.525.7
SKR148NGB105820/xanthaxxx
SKR149NGB102521 xxx23820.527.322.4
SKR150NGB102617 16.8
SKR151NGB103457 xxx14422.821.7
SKR152NGB105410variomaculataxxx130.626.226.923.3
SKR153NGB105981precocious yellowingxxx10724.529.123.6
SKR154NGB102480 xxx124.425.529.521.4
SKR155NGB102588 xxx
SKR156NGB105961chloroticaxxx156.623.229.0
SKR157NGB102205chloroticaxxx13422.225.8
SKR158NGB102497 19331.6
SKR159NGB102533 19.7
SKR160NGB102831 xxx14924.225.2
SKR161NGB103052WBH 3052xxx12328.727.524.0
SKR162NGB103061WBH 3061xxx
SKR163NGB103116 xxx 19.4
SKR164NGB105261variomaculataxxx15024.333.120.0
SKR165NGB105806chloroticaxxx13123.525.722.5
SKR166NGB105983precocious yellowing 9025.626.923.2
SKR167NGB102005Nischkes Riesengefärgs Wi. Erbsexxx 17.2
SKR168NGB100993WBH 993xxx17327.932.019.9
SKR169NGB103559WBH 3559xxx 12.7
SKR170NGB102405Supergradexxx19421.924.621.8
SKR171NGB101742New Walesxxx18222.529.9
SKR172NGB101888 xxx
SKR173NGB102423Senatorxxx 18.4
SKR174NGB103560WBH 3560 10.9
SKR175NGB102429Gradus 19.7
SKR176NGB103569WBH 3569xxx 12.9
SKR177NGB103545Pugetxxx
SKR178NGB103566WBH 3566xxx 16.2
SKR179NGB103484Dhamarxxx
SKR180NGB103425WBH 3425xxx 18.7
SKR181NGB103547Grantxxx14522.425.6
SKR182NGB102130WBH 2130xx 9.3
SKR183NGB103609WBH 3609 17.2
SKR184NGB101979Ambrosiaxxx14424.027.421.8
SKR185NGB100800Primusxxx14922.526.8
SKR186NGB101721Midfreezerxxx 19.1
SKR187NGB101395WBH 1395xxx14824.427.123.1
SKR188NGB101677Mexique 4xxx 16.7
SKR189NGB103440WBH 3440xxx14322.726.8
SKR190NGB101462WBH 1462xxx 25.024.2
SKR191NGB101362claviculaxxx15617.0
SKR192NGB100640WBH 640xxx 18.4
SKR193NGB103450Meteorxxx 18.6
SKR195NGB103562WBH 3562xxx16420.926.5
SKR196NGB101463Sigynxxx13223.224.9
SKR198NGB101341Klema Veredunaxxx 20.1
SKR199NGB103424WBH 3424xxx 16.2
SKR200NGB103544Rangerxx 21421.725.2
SKR201NGB103564WBH 3564xxx 16.9
SKR202NGB103610WBH 3610x x 15.7
SKR203NGB105454viridisxxx16122.825.3
SKR204NGB105995vixcerataxxx13429.028.826.4
SKR205NGB102212chloroticaxxx 18.7
SKR206NGB102688WBH 2688xxx
SKR207NGB105271costataxxx 17.2
SKR208NGB105565chloroticaxxx 23.7
SKR209NGB105848fasciataxxx 26.0
SKR210NGB106116narrow leaflet basexxx 21.1
SKR211NGB102178Thomas Laxtonxxx22522.033.0
SKR212NGB102737WW 709xxx 17.0
SKR213NGB102071Pirixxx 18.6
SKR214NGB102183Darkskin Perfectionxxx15422.225.2
SKR215NGB103451Lilaskaxxx 16.7
SKR216NGB102072Paniaxx 17520.827.4
SKR217NGB103606WBH 3606xxx
SKR218NGB103607WBH 3607 xx254.223.926.3
SKR219NGB103628ramosusxxx9621.625.1
SKR220NGB101304WBH 1304-1 15922.427.9
SKR221NGB101304WBH 1304-2 16.1
SKR222NGB101304WBH 1304-3 15022.427.7
SKR223NGB101304WBH 1304-4 18.3
SKR224NGB101304WBH 1304-5 14.6
SKR225NGB101304WBH 1304-6 19.1
SKR226NGB101304WBH 1304-7 16322.123.6
SKR227NGB101304WBH 1304-8 15421.420.9
SKR228NGB101304WBH 1304-9 14.5
SKR229NGB101304WBH 1304-10 10221.326.5
SKR230NGB1018361 12320.925.1
Table 2. The three microsatellite markers AA5, A9 and AC58 [28], the forward and reverse primer sequences of the markers, and the color attached to the M13-tail of the forward primer. The sequence of the M13-tail was: CACGACGTTGTAAAACGAC.
Table 2. The three microsatellite markers AA5, A9 and AC58 [28], the forward and reverse primer sequences of the markers, and the color attached to the M13-tail of the forward primer. The sequence of the M13-tail was: CACGACGTTGTAAAACGAC.
Marker Forward Primer (5′—3′)Reverse Primer (5′—3′)Color
AA5tgccaatcctgaggtattaacacc + M13catttttgcagttgcaatttcgt FAM, Blue
A9gtgcagaagcatttgttcagat + M13cccacatatatttggttggtca NED, Yellow
AC58Tccgcaatttggtaacactg + M13cgtcaatttcttttatgctgagVIC, Green
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Winther, L.; Rasmussen, S.K.; Poulsen, G.; Lange, C.B.A. Assessment of Genetic Diversity and Protein Content of Scandinavian Peas (Pisum sativum). Agronomy 2023, 13, 2307. https://doi.org/10.3390/agronomy13092307

AMA Style

Winther L, Rasmussen SK, Poulsen G, Lange CBA. Assessment of Genetic Diversity and Protein Content of Scandinavian Peas (Pisum sativum). Agronomy. 2023; 13(9):2307. https://doi.org/10.3390/agronomy13092307

Chicago/Turabian Style

Winther, Louise, Søren Kjærsgaard Rasmussen, Gert Poulsen, and Conny Bruun Asmussen Lange. 2023. "Assessment of Genetic Diversity and Protein Content of Scandinavian Peas (Pisum sativum)" Agronomy 13, no. 9: 2307. https://doi.org/10.3390/agronomy13092307

APA Style

Winther, L., Rasmussen, S. K., Poulsen, G., & Lange, C. B. A. (2023). Assessment of Genetic Diversity and Protein Content of Scandinavian Peas (Pisum sativum). Agronomy, 13(9), 2307. https://doi.org/10.3390/agronomy13092307

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop