Crop Science Illumina
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Published online 30 July 2007
Published in Crop Sci 47:1718-1727 (2007)
© 2007 Crop Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kottapalli, K. R.
Right arrow Articles by Puppala, N.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Kottapalli, K. R.
Right arrow Articles by Puppala, N.
Agricola
Right arrow Articles by Kottapalli, K. R.
Right arrow Articles by Puppala, N.
Related Collections
Right arrow Plant Genetic Resources
Right arrow Crop Genetics

PLANT GENETIC RESOURCES

Molecular Characterization of the U.S. Peanut Mini Core Collection Using Microsatellite Markers

Kameswara Rao Kottapallia, Mark D. Burowb, Gloria Burowc, John Burkec and Naveen Puppalaa,*

a Agric. Sci. Cent. at Clovis, New Mexico State Univ., 2346 SR 288 Clovis, NM 88101
b Texas Agric. Exp. Stn., Texas A&M Univ., Lubbock, TX 79403, and Texas Tech Univ., Dep. of Plant and Soil Science, Lubbock, TX 79409
c USDA-ARS, Plant Stress and Germplasm Development Unit, Cropping Systems Research Lab, 3810 4th Street, Lubbock, TX 79415. This research was supported by a USDA grant (2004-34186-14533) through the Southwest Consortium for Plant Genetics and Water Resources and New Mexico State University Agric. Exp. Stn. Mention of trademark or proprietary product does not constitute a guarantee or warranty of a product by the USDA and does not imply its approval to the exclusion of other products that may also be suitable

* Corresponding author (npuppala{at}nmsu.edu).


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Peanut (Arachis hypogaea L.) is the secondmost important legume crop in the United States. A limitation to increased peanut productivity is that peanut improvement is hampered by relatively low genetic variability in the germplasm commonly used by breeding programs. To facilitate accessibility to diverse germplasm sources for breeding applications, a core subset of the USDA peanut germplasm was previously established that later was further refined and developed into a mini core collection consisting of 112 accessions. This report details an extensive characterization of genetic diversity and relationships in the U.S. peanut mini core using microsatellite or simple sequence repeat (SSR) markers. Seventy-two peanut accessions from the U.S. peanut mini core were genotyped with 73 SSR markers; all but six produced reliable, polymorphic bands. Moderate levels of genetic variation were found with genetic distances (D) values among accessions ranging from 0.088 to 0.254. Distinct groupings of the accessions based on subspecies classification and on botanical (market) type groupings were established. Twelve of the markers, mapped previously to the A genome, were found to be sufficient to identify both subspecies and botanical types and gave a clustering pattern very similar to the entire 67 SSR marker set. The genetic variation observed within U.S. peanut mini core can be utilized for selection of diverse parents for breeding and development of mapping populations.

Abbreviations: AFLP, amplified fragment length polymorphism • SSR, simple sequence repeat


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
GENETIC VARIABILITY is key to progress in crop improvement programs. However, the cultivated tetraploid peanut (Arachis hypogaea L.) has limited genetic variability, which has been explained as the result of a genetic bottleneck resulting from a single domestication event approximately 3500 yr ago (Simpson et al., 2002). Recent studies by Milla et al. (2005) using amplified fragment length polymorphism (AFLP) verified previous findings by Kochert et al. (1996) that limited molecular polymorphism was found in the cultigen. In addition to paucity of genetic variation in the species, commercial peanut breeding programs further reduced genetic variation due to the predominance of few common elite parents, for example ‘Dixie Giant’ and ‘Small White Spanish-1’ (Knauft and Gorbet, 1989), in the ancestry of many varieties. The consequence is a reduced level of exploitable genetic variation and, therefore, a limited response to selection. For example, the peanut crop is vulnerable to numerous pests and diseases due to its narrow genetic base. To sustain progress in peanut breeding and minimize genetic vulnerability, it is essential to broaden the genetic base of the elite U.S. germplasm used by breeders. However, commercial breeders are hesitant to use wild or exotic relatives directly to increase the genetic diversity of elite germplasm because it takes considerable resources to develop adapted, high- performing materials from crosses between elite and wild or exotic genotypes. While it is ideal that breeders can tap the available germplasm in collections such as the Agricultural Research Services (ARS) Germplasm Resource Information Network (GRIN) database (http://www.ars-grin.gov), detailed passport data on the features and variation generally available in the large collection are limited. For peanut it may be the ultimate objective to characterize the available collection but this is quite laborious and time consuming and it will take some time for these types of data to become available. A pragmatic solution to this problem is the use of a characterized subset of cultivated germplasm accessions, referred to as a core collection, for transfer of agronomically important and complex traits. A core collection is a subset of accessions from the entire collection that capture most of the available genetic diversity of the species (Brown, 1989).

Core collections have been developed for many crops, including peanut. Holbrook et al. (1993) developed a core collection of 831 accessions from a set of 7432 accessions in the U.S. peanut germplasm collection based on six morphological variables. Subsequently, a core consisting of 1704 accessions (14 morphological descriptors on 14310 accessions) was developed using the ICRISAT peanut collection (Upadhyaya et al., 2003), and a core of 582 accessions was established by random selection from the almost 6000 accessions of the Chinese peanut germplasm collection (Holbrook et al., 2004). However, when the size of collection is too large and a core collection (10% of entire collection) becomes unmanageable, Upadhyaya and Ortiz (2001) suggested a strategy of selecting a mini core (core of core) collection (10% of the core or 1% of the entire collection). Using this strategy, mini cores of 184 accessions from the ICRISAT core collection (Upadhyaya et al., 2002) and of 112 accessions from the U.S. core collection (Holbrook and Dong, 2005) were developed. The peanut core and mini core collections have been evaluated for various traits, and new sources of variation are reported for tolerance to drought (Upadhyaya, 2005); early maturity (Upadhyaya et al., 2006); high yield and other agronomic traits (Upadhyaya et al., 2005); resistances to peanut root-knot nematode [Meloidogyne arenaria (Neal)] (Holbrook et al., 2000), Tomato spotted wilt virus (Anderson et al., 1996), cylindrocladium black rot [caused by Cylindrocladium crotalariae (Loos) Bell and Sobers] and early leafspot (caused by Cercospora arachidicola Hori) (Isleib et al., 1995), rhizoctonia limb rot (caused by Rhizoctonia solani Kühn) (Franke et al., 1999), sclerotinia blight [caused by Sclerotinia minor Jagger and S. sclerotiorum (Lib.) de Bary], pepper spot [caused by Leptosphaerulina crassiasca (Sechet) Jackson and Bell] (Damicone et al., 2003); and reduced preharvest aflatoxin contamination (Holbrook et al., 1998). The use of these diverse sources can help in bringing in much needed diversity to broaden the genetic base of cultivars.

Germplasm descriptions may be based on morphological descriptors, agronomic descriptors, and/or molecular markers. Morphological descriptors have been used widely for classification of species. Use of discrete, character state data has the advantage of being less subject to environmental variation than continuously variable traits. For classification within a species, some discrete character state descriptors are available, but classification of large numbers of accessions by these has some practical difficulties. In addition, most of the traits useful for improvement are quantitative in nature. However, these are influenced strongly by environment, and repeated screening often leads to conflicting results. Additionally, the cost of large scale experimentation to generate such data is prohibitive. Recently, germplasm characterization based on molecular markers has gained importance due to the speed and quality of data generated. The smaller core or mini core germplasm accessions were characterized initially using DNA markers such as random amplified polymorphic DNA (RAPDs) in common bean (Phaseolus vulgaris L.) (Skroch et al., 1998) and potato (Solanum tuberosum L.) (Ghislain et al., 1999). AFLP markers have been used for studying the variation in core subsets of oats (Fu et al., 2005) and in combination with SSRs and isozymes in cassava (Manihot esculenta Crantz) (Chavarriaga-Aguirre et al., 1999). Microsatellite (SSR) markers were utilized to reveal genetic identities, diversity, and relationships in apple (Malus spp.) core collections (Hokanson et al., 1998). SSR and RFLP markers were used to characterize a diverse subset of rice cultivars for use in the development of the U.S. rice (Oryza sativa L.) core collection (Xu et al., 2004). Single nucleotide polymorphism (SNP) markers associated with cooking qualities of rice were used for characterization of a core subset of rice germplasm collections maintained at the USDA-ARS National Small Grains Collection (McClung et al., 2004).

Among various DNA markers, microsatellites are well known for their potentially high information content and versatility as molecular tools. They are also amenable to high throughput genotyping and have proven to be highly versatile and useful markers for germplasm characterization. In peanuts, SSRs detected genetic diversity among 48 valencia genotypes (Krishna et al., 2004) and also differentiated botanical types (He et al., 2005). Two other studies (Ferguson et al., 2004a; Moretzsohn et al., 2004) used SSRs to determine the genetic diversity of cultivated peanut and its wild relatives. However, the mini core collections developed recently in peanuts have been characterized only using morphological descriptors and few agronomic traits (Upadhyaya, 2005). The specific goals of the present study are: (i) to characterize the U.S. peanut mini core collection utilizing simple sequence repeat (SSR) DNA markers, (ii) to assess genetic affinity of peanut botanical and market types based on mapped markers, and (iii) to determine whether the molecular diversity within the collection is correlated to geographical origin of the accessions.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Plant Materials
The core subset of the U.S. peanut mini core collection consists of 112 accessions (Holbrook and Dong, 2005), and the 99 available accessions were graciously provided by C. Holbrook, USDA, ARS-Coastal Plain Experiment Station, Tifton, GA. These were planted at the Texas Tech University experimental farm in Lubbock, TX, and in the greenhouse of the New Mexico State University Agricultural Sciences Center at Clovis, NM. Of these 99, 27 accessions appeared to segregate for multiple morphological characteristics in the field and were excluded from the analysis, leaving 72 accessions representing the two subspecies and four botanical varieties of peanut grown in the United States. The segregating accessions were excluded because of uncertainty whether the segregation represented contamination of seed lots or natural variation within these accessions.

Information about the accessions used (accession identity as designated by PI number, core collection number, botanical type, proposed market type, and country of origin) is listed in Table 1. Information on market types are based on plant, pod, and seed characteristics observed in the field and after harvest. These took into account growth habit, pod and seed size and shape, and number of seeds per pod.


View this table:
[in this window]
[in a new window]

  		Table 1. List of cultivated accessions comprising the US peanut mini core collection used in the study.

 
Genomic DNA Extraction and SSR Genotyping
DNA was extracted using the Qiagen DNeasy Plant minikit (Qiagen Inc., Valencia, CA) following the manufacturer's protocol, except that the quantity of starting material was reduced to 75 to 100 mg and the final purified DNA was eluted in 120 µL of elution buffer. The 73 SSR primers employed to analyze the accessions are given in Table 2. A modified M13-tagged forward and normal reverse primer was used for each marker. Briefly, a 20mer M13 oligo (GAC GTT GTA AAA CGA CGG CC) was concatenated to the 5' end of each forward primer, generating an M13-tagged primer. To facilitate detection, a 20mer M13 oligo labeled with one of three fluorescent dyes, 6-HEX, FAM, or NED, was added to the polymerase chain reaction (PCR) mix to label SSR products of each marker. PCR was performed in a volume of 5 or 10 µL, containing 1x PCR buffer (10 mM Tris-HCl pH 8.3, 50 mM KCl, 1.5 mM MgCl2), 0.2 mM of each dNTP, 0.25 units Hotstart Taq DNA polymerase (Qiagen Inc.), 5 pmol of each M13-tagged forward and normal reverse primer, 0.02 pmol of fluorescently labeled 20mer M13 primer (labeled with either HEX, NED, or FAM), and 20 ng of template genomic DNA. Amplifications were performed using a PTC-225 (MJ Research, Waltham, MA) Peltier thermal cycler with the following conditions for the PG series of primers: 94°C initial denaturation for 17 min (1 cycle); 35 cycles of 94°C for 45 s, 60°C for 60 s, 72°C for 30 s; and a final extension at 72°C for 10 min. The PCR conditions used for primer sets were as follows: for the AH series primers, according to Hopkins et al. (1999); for the PGP and PGS series primers, Ferguson et al. (2004a, 2004b); for PM series primers, He et al. (2003); and for the RKN series primers, Burow et al. (1996).


View this table:
[in this window]
[in a new window]

  		Table 2. List of primers used in the study and corresponding number of bands resolved, polymorphism information content (PIC), and source of primer (reference).

 
The 73 primer sets were tested first using DNA of four accessions for optimizing the PCR conditions and concentrations of the reaction mix, and products were visualized on 1.5% agarose gels. All the primers amplified PCR products. These primers were used for genotyping the 72 available, homogeneous accessions of the U.S. peanut mini core. After initial fragment analysis, 18 primers were used to reamplify the missing genotypes and test the repeatability of patterns. During the process of reamplification, one sample with only sterile water was used as template (negative control) in the PCR and was used to detect and eliminate artifacts. Repeatability of banding pattern was totally consistent for all primers tested, whereby detection of major band sizes was observed at 100% (data not presented).

Markers were amplified separately using the set of 72 accessions and were size separated by capillary electrophoresis using an ABI Prism 3100 DNA Analyzer (Applied Biosystems, Foster City, CA) at the USDA-ARS Plant Stress and Germplasm Development Unit (Lubbock, TX). Multiplexing of three differentially labeled PCR products per well was performed to increase efficiency. The multiplexing protocol enabled the study of the entire set of accessions with 73 primers in 3 to 4 wk.

SSRs were analyzed with Genescan 3.1.2 software (Applied Biosystems) and scored using Gene Mapper V3.0 software (Applied Biosystems) as binary data.

Data Analysis
Pairwise comparisons of genetic distances were calculated using Nei's formula (Nei, 1972). Genetic distances were also calculated using Chord's distance formula (Cavalli-Sforza and Edwards, 1967) as it generates correct tree topologies regardless of the microsatellite mutation model (Takezaki and Nei, 1996). A genetic distance matrix was established and subsequently used to construct a dendrogram based on the Neighbor Joining (NJ) clustering procedure implemented in NTSYSpc2.2 (Rohlf, 1998; Exeter Software, Setauket, NY) and PowerMarker3.0 (Liu and Muse 2005; http://www.powermarker.net). Bootstrapping was performed by performing 1000 bootstrap resamplings using PowerMarker and Winboot (Yap and Nelson, 1996). A goodness of fit test was performed for the cophenetic matrix of the NJ tree to the genetic distance matrix by the Mantel test (Mantel, 1967). Similarly, a test was made on the goodness of fit of the cophenetic matrix of the NJ tree from the 12 mapped SSRs to the genetic distance matrix based on the entire set of 67 SSRs. All procedures were performed using the MXCOMP module of the NTSYSpc software 2.2. PowerMarker was used to calculate the average number of bands per SSR primer pair, gene diversity, and polymorphism information content (PIC) values. PIC is defined as: PIC = 1 – {Sigma}pi2, where pi is the frequency of the ith allele.


   RESULTS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Microsatellite Polymorphism
The 72 available, phenotypically uniform accessions of the core subset of the U.S. peanut mini core collection were amplified using 73 SSR primer pairs. Two primer pairs, which did not amplify most of the accessions, were eliminated from the analysis. Of the 71 remaining primer pairs, four produced monomorphic patterns and were not considered further. The remaining 67 primers amplified 528 polymorphic bands with an average of 7.88 bands per primer pair (Table 3). The number of bands scored ranged from 2 to 28 per primer pair. Notably, some of the primers generated genotype-specific bands, which can be used as molecular identity data for specific genotypes. The PIC for all the genotyped bands was estimated using PowerMarker and ranged from 0.063 to 0.918. The gene diversity for all the 528 bands ranged from 0.027 to 0.50, which is relatively high due to the presence of genotype-specific bands.


View this table:
[in this window]
[in a new window]

  		Table 3. Summary statistics for all the accessions of Arachis hypogaea and each subspecies.

 
In the subspecies fastigiata, 462 polymorphic bands (87.5% polymorphism) were found with an average number of 6.9 bands per primer pair (Table 3). The average gene diversity and PIC values were similar to the entire mini core collection values. There were 66 fastigiata-specific bands accounting for 12.5% of the total amplified bands and 14.3% of the polymorphic bands. The number of group-specific bands per genotype was only 1.69. Among the hypogaea subspecies, 390 polymorphic bands were observed (73.9% polymorphism). The average number of bands per primer pair, average gene diversity, and PIC values (5.8, 0.16 and 0.13 respectively) were lower than the values of the entire mini core collection. However, the number of group-specific bands (138) and their percentage of the total amplified bands (26%) was twice the number observed for fastigiata group.

Analysis of Genetic Relationship in the U.S. Peanut Mini core
The NJ tree based on Nei's genetic distances is shown in Fig. 1 . The genotypes were grouped into 2 major clusters, which corresponded to the subspecies groupings; subspecies fastigiata and hypogaea (Fig. 1). The group of accessions from two clusters hypogaea and fastigiata were separated by a genetic distance of 0.26. But the genotypes within the fastigiata group (largest group) were separated by an average genetic distance of 0.23, indicating low to moderate genetic diversity in the entire collection. However, the estimates of genetic distances observed with tree have clearly distinguished 94% of the mini core collection accessions into the major botanical types. Groupings of the accessions based on market types were also observed and the grouping was in agreement with morphological descriptors with a mixture of ~5% in both subspecies (Table 1 and Fig. 1). Both virginia and runner market types grouped together while valencia and spanish market types showed 88 and 60% (15 out of 17 and 12 out of 20) true types, respectively. The correlation between genetic distance and NJ tree cophenetic matrix was highly significant with an r value of 0.78, which indicated that the cluster generated by NJ was a good fit to the matrix.


Figure 1
View larger version (49K):
[in this window]
[in a new window]

  		Figure 1. Neighbor-joining dendrogram of 72 A. hypogaea accessions from the U.S. peanut mini core revealed by using similarity coefficients based on Nei's genetic distance. The letters after each accession number refer to market types as: val, subsp. fastigiata/fastigiata/valencia; spa, subsp. fastigiata/vulgaris/spanish; vir, subsp. hypogaea/hypogaea/virginia; run, subsp hypogaea/hypogaea/runner; ???, intermediate market type. Country of origin is abbreviated as the first three letters of the country after the subspecies (for e.g., IND = India). The dashed line indicates groupings of accessions into the two major subspecies and dotted lines indicate grouping under each subspecies into market types. The numbers inside the parentheses indicate bootstrap values for groupings with >50% bootstrap support based on 1000 bootstrap samples.

 
Clustering and Grouping Using Mapped SSR Markers
Twelve SSR primer pairs that were mapped previously onto seven linkage groups (Moretzsohn et al., 2005) were used for clustering (Table 4). Another mapped marker, Ah-75, was also analyzed in the present study but it resulted in monomorphic bands. The mapped SSR loci amplified from 2 to 20 bands per primer pair, with an average of 9.16 bands per primer pair. The gene diversity ranged from 0.03 to 0.50. The data from 12 SSR primer sets (mapped markers AH-193, AH-229, PM-3, PM-32, PM-35, PM-36, PM-42, PM-45, PM-65, PM-188, PM-204, and PM-238) were used to classify the four market types prevalent in the United States. The NJ tree based on Chord's 1967 genetic distance unambiguously differentiated the market types into four major groups with the valencia and spanish market types (var. fastigiata) as out groups (Fig. 2 ). Virginia and runner market types (var. hypogaea) grouped together as expected. The cophenetic matrix for the NJ tree based on 12 markers was significantly correlated with the genetic distance matrix derived from the 67 primer sets. The r value for this comparison was 0.72, which indicates that the 12 mapped markers that were distributed among seven different linkage group are very promising candidates for studies of genetic diversity.


View this table:
[in this window]
[in a new window]

  		Table 4. Linkage group location, size range and number of alleles as well as gene diversity detected for 72 mini core collection accessions based on 12 mapped simple sequence repeat markers (Moretzsohn et al., 2005)

 

Figure 2
View larger version (10K):
[in this window]
[in a new window]

  		Figure 2. Dendrogram of four market types of the peanut accessions from the U.S. mini core based on 12 mapped simple sequence repeat (SSR) markers used in the study. The numbers inside the parentheses indicate bootstrap values for groupings with >50% bootstrap support based on 1000 bootstrap samples.

 
Phylogeographic Pattern of Genetic Diversity
Geographic diversity of the accessions of the mini core collection was examined within marker-derived groupings of subspecies hypogaea and fastigiata. Two major clades were observed in hypogaea subspecies with larger number of accessions from South America and Africa in clade I and II respectively (Fig. 1). Three major clades were formed in fastigiata group that contained genotypes from multiple countries of origin (Table 1 and Fig. 1). The Valencia clade of fastigiata subspecies contained high percentage of accessions from South America and Spanish clade I mostly contained five accessions from South America and four from Africa. Spanish clade II had large number of accessions from Africa. Seven accessions representing valencia market type were from Argentina.


   DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Differentiation of Genotypes
This study presents a genotypic characterization of a peanut mini core subset germplasm collection. In contrast to reports generated using RFLP and AFLP markers (Kochert et al., 1996; Milla et al., 2005), SSR markers were able to identify genetic variability among accessions of the cultivated species A. hypogaea, with a moderate level of molecular variation being observed in this study. In contrast to other studies using SSR markers, where as wide a genetic diversity as possible was used to identify polymorphisms (e.g., Ferguson et al., 2004a), the current study used a data set deemed to be more representative of the variability within the cultigen. The molecular data generated in the present study can be utilized by peanut breeders for selection of parents and genotyping of mapping populations. Molecular patterns generated for the mini core can also be compared with the existing database as well as with the patterns of newly reported germplasm to avoid genotype redundancy (Khadari et al., 2003). This in turn will enable efficient management of peanut germplasm.

Several genotype-specific bands were generated with more than 20 bands identified for some primer pairs. The average number of bands per primer pair was as expected for peanut SSRs (Krishna et al., 2004; He et al., 2005; Ferguson et al., 2004a). Between the two subspecies, fastigiata had more polymorphic bands but half the number of group-specific bands. The reason for such a deviation may be attributed to the origin of the accessions within the subspecies.

Differentiation of Subspecies
The core collection was mainly compiled using the two major subspecies, fastigiata and hypogaea, including only the four market types cultivated in the United States. The clustering based on Chord's distance and primer sets corresponding to 12 mapped markers could consistently differentiate the two major botanical types. The primer PM-188 located on linkage group 8 was also used by He et al. (2005) and could distinguish fastigiata and hypogaea.

The distinction between subspecies accords with the major morphological differences distinguishing them. Among these are erect vs. spreading growth habit, flowers present vs. absent on the mainstem, and alternate vs. sequential branching. Other important differences that are typical are early vs. late maturity, small light-pigmented vs. large dark-pigmented leaves, and absence or presence of seed dormancy. Previous studies using AFLP markers failed to group the subspecies of cultivated peanut (Herselman, 2003). This may be due to the nature of AFLP markers used in the study. The map position of these markers is unknown, but it is possible that they clustered into a small portion of the genome (as is common with AFLP markers), thus limiting the genomic region that was scanned. With the recent development of SSRs and knowing their positions on the genetic map, it is now possible to scan the genome for variability. This underscores the need for further development of genetic maps of cultivated peanut using SSR markers or PCR-based markers, which would enhance their application in marker-assisted breeding.

Differentiation of Market Classes
We report using mapped SSR markers to distinguish cultivated U.S. market types of peanut. Ferguson et al. (2004b) was able to differentiate six botanical types of peanut (including var. peruviana, hirsuta, and aequatoriana that are not included in the core subset of the U.S. core collection) using 10 SSR primer pairs. He et al. (2005) also reported a separate set of six SSR primer sets providing markers specific to botanical varieties and different from those used in the present study. As suggested, these markers may be linked to genes involved in the expression of morphological traits. In our study, all 12 primer pairs that correspond to mapped loci on seven linkage groups could differentiate the major market types. Both virginia and runner market types were grouped in the same cluster, this could be due to low molecular variation within the hypogaea subspecies. This work dealt with distinguishing runner and virginia types based on mapped markers. However, with the larger number of 67 SSR primer sets, only Valencia and Spanish market types were grouped separately with few mixtures in each group. The instance of clustering of a valencia or spanish market type in the hypogaea subspecies and virginia or runner in fastigiata subspecies of the tree based on 67 primer sets could be due to the inefficiency of some primers either to amplify or fail to amplify a similar DNA fragment in both the genotypes. A similar result was obtained by Garris et al. (2005) while grouping rice genotypes into two major indica and japonica subspecies.

Geographic Distribution of Accessions
From the phylogeographic point of view, the mini core collection had genotypes from 19 countries in the fastigiata group and 18 countries in the hypogaea group (Table 1). Although there is overrepresentation from Argentina (South America) in the fastigiata group, this is not unusual because valencia peanut is abundant in the region and Argentina is a possible center of diversity of the market type (Ferguson et al., 2004b). Among hypogaea's, runner market types were underrepresented in the mini core collection. However, generally there is a consistency of selection of genotypes from diverse origins. Ferguson et al. (2004b) also noted that there was greater differentiation among subspecies than among continents, that is, the differences among subspecies is greater than the geographic differences.

In this study it was shown that moderate levels of genetic variation could be detected effectively in peanut using SSR markers. The grouping at the accession level indicated a clear distinction between subspecies and among the accepted major botanical types grown in the US. This is an extensive molecular study of the U.S. peanut mini core and has provided useful information toward parental selections and specific SSR marker that can be used for varietal identification.


   ACKNOWLEDGMENTS
 
The authors wish to thank Dr. Corley Holbrook for providing germplasm lines for this research and Halee Hughes, Jacob Sanchez, and Jamie Ayers for their technical assistance. We also thank Dr. S.L. Dwivedi for critical review of an earlier version of this manuscript.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Received for publication June 21, 2006.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 





This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kottapalli, K. R.
Right arrow Articles by Puppala, N.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Kottapalli, K. R.
Right arrow Articles by Puppala, N.
Agricola
Right arrow Articles by Kottapalli, K. R.
Right arrow Articles by Puppala, N.
Related Collections
Right arrow Plant Genetic Resources
Right arrow Crop Genetics

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
The SCI Journals Agronomy Journal Vadose Zone Journal
Journal of Natural Resources
and Life Sciences Education		 Soil Science Society of America Journal
Journal of Plant Registrations Journal of
Environmental Quality		 The Plant Genome