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. 2013 May 28;8(5):e64062. doi: 10.1371/journal.pone.0064062

Development of DArT Marker Platforms and Genetic Diversity Assessment of the U.S. Collection of the New Oilseed Crop Lesquerella and Related Species

Von Mark V Cruz 1,3, Andrzej Kilian 2, David A Dierig 1,*
Editor: Matthew E Hudson4
PMCID: PMC3665832  PMID: 23724020

Abstract

The advantages of using molecular markers in modern genebanks are well documented. They are commonly used to understand the distribution of genetic diversity in populations and among species which is crucial for efficient management and effective utilization of germplasm collections. We describe the development of two types of DArT molecular marker platforms for the new oilseed crop lesquerella (Physaria spp.), a member of the Brassicaceae family, to characterize a collection in the National Plant Germplasm System (NPGS) with relatively little known in regards to the genetic diversity and traits. The two types of platforms were developed using a subset of the germplasm conserved ex situ consisting of 87 Physaria and 2 Paysonia accessions. The microarray DArT revealed a total of 2,833 polymorphic markers with an average genotype call rate of 98.4% and a scoring reproducibility of 99.7%. On the other hand, the DArTseq platform developed for SNP and DArT markers from short sequence reads showed a total of 27,748 high quality markers. Cluster analysis and principal coordinate analysis indicated that the different accessions were successfully classified by both systems based on species, by geographical source, and breeding status. In the germplasm set analyzed, which represented more than 80% of the P. fendleri collection, we observed that a substantial amount of variation exists in the species collection. These markers will be valuable in germplasm management studies and lesquerella breeding, and augment the microsatellite markers previously developed on the taxa.

Introduction

Lesquerella (Physaria sp.), a member of the Brassicaceae, is a North American genus which has more than 90 member species thriving mostly in dry and arid habitats usually mixed with sparse vegetation [1], [2]. Commonly known as bladderpod, it has been identified by the U.S. Department of Agriculture and the U.S. Department of Energy as very promising species for the production of lubricants, engine oils, waxes, coatings and a source of natural estolides with valuable application in the automobile and biofuel industries [3], [4], [5]. There has been an increasing trend in research activities in the crop since its oil was first characterized for novel properties [6]. The fatty acid profile of lesquerella oil has been found to vary. Species found east of the Mississippi have mostly densipolic acid, those in the western U.S. mostly lesquerolic acid, and a species from Oklahoma predominantly with auricolic acid [7]. Lesquerella could be grown successfully as a winter annual in the southwest U.S. producing an average seed yield of 1.7 tons/ha [8]. At present, there are more than eight advanced breeding lines of P. fendleri ready for commercialization and a corresponding substantial germplasm collection has been assembled in the U.S. National Plant Germplasm System [9].

Molecular characterization of germplasm collections supplements phenotypic assessment of diversity and is important in the effective management of genetic resources. Molecular markers have been very useful in efforts to accurately identify gaps and redundancy within and among individual germplasm collections and have helped resolve important genebank management issues [10], [11], [12]. Examples of markers used in specific Brassicaceae collections include microsatellites for examining diversity in B. napus [13], [14], [15], lesquerella [16] and wild relatives such as Capsella, Crambe and Sinapis [17]; AFLPs in B. oleracea [18] and Lepidium [19]; and RAPD markers in Raphanus [20].

Compared to the previously mentioned molecular marker systems, Diversity Array Technology (DArT) markers are relatively new and were developed only in the early 2000. DArT markers overcame the difficulties in correlating bands on gels with allelic variants by utilizing hybridization-based methods and solid state surfaces [21]. They have been increasingly utilized as evidenced by the number of publications reporting successful implementation [22]. Among its advantages over other marker systems include high throughput capability allowing rapid germplasm characterization in a single experiment, independence of sequence data, and ability to detect single base changes and indels [23]. To date, DArT markers have been successfully applied in genetic diversity analysis, linkage mapping and in finding out population structure of collections in various crop species [24]. Their application in minor crops are likewise increasing due to their potential to accelerate gene discovery and initiate molecular breeding because of their whole genome coverage without relying on prior sequence data information [25], [26].

In lesquerella, allozymes have previously been used [27] and microsatellite markers have been developed [16]. But the small number of markers that are available presents a limitation in linkage mapping and in the study of genetic resources collections. At present, only fifteen microsatellites have demonstrated utility across different Physaria species. We present in this paper the development of two platforms of high density DArT markers for lesquerella and the results obtained after testing them to analyze the genetic diversity of Physaria and Paysonia national germplasm collection. This new molecular marker system for the new crop species will serve as an additional resource to augment the existing systems to assist crop improvement efforts, germplasm management activities and genetic studies.

Materials and Methods

Tissue Sampling

The lesquerella germplasm set was obtained from collections of the USDA-ARS National Arid Land Plant Genetic Resources Unit, Parlier, CA and the USDA-ARS Arid Land Agricultural Research Center, Maricopa, AZ. The samples used in this study were selected based on each accession’s geographic location, sampling within distinct counties in each State when possible. Seven advanced P. fendleri breeding lines, WCL-LH1, WCL-LO1, WCL-LO2, WCL-LO4, WCL-LY1, WCL-SL1 and WCL-YS1 were included among the samples. DNA was extracted from fresh leaf tissue obtained from five week old seedlings using Qiagen DNeasy 96 Plant Kits (Qiagen Inc., Valencia, CA). Two DArT platforms were developed for lesquerella as described below. The platform development utilized 86 Physaria accessions (see Table 1), representing 11 species and one Paysonia accession since the latter is a sister genus of Physaria and only recently was there a recognized taxonomic delineation between them [2].

Table 1. Passport information of accessions used in Physaria DArT and DArTseq platform development.

Collection No.and ID Accession No. Species Country State/Prov. County Latitude Longitude Elevation (m)
1809 W6 20822 P. fendleri United States AZ Cochise 31.75600 −110.05500 134.15
1817 W6 20823 P. fendleri United States AZ Cochise 31.74100 −109.96800 1493.90
1818 W6 20824 P. fendleri United States AZ Cochise 31.50000 −110.00000 1432.56
1819 W6 20825 P. fendleri United States AZ Santa Cruz 31.72400 −110.52600 1493.90
1826 W6 20856 P. fendleri United States AZ Santa Cruz 31.72300 −110.52400 1463.41
1833 W6 20833 P. gordonii United States NM Hidalgo 31.93333 −108.95000 1024.13
1834 PI 641918 P. fendleri United States NM Hidalgo 31.93333 −108.93333 1292.35
1835 – P. fendleri United States NM Luna 32.21667 −107.41667 1277.11
1840 W6 20858 P. fendleri United States NM Eddy 32.61667 −104.40000 1042.42
1841 PI 596417 P. fendleri United States NM Eddy 32.31667 −104.25000 1130.81
1842 W6 20860 P. fendleri United States NM Eddy 32.53333 −103.98333 1060.70
1843 PI 596418 P. fendleri United States NM Eddy 32.75000 −104.10000 1082.04
1844 PI 596419 P. fendleri United States NM Lincoln 33.68333 −105.83333 1636.78
1845 PI 596420 P. fendleri United States NM Lincoln 33.68333 −105.91667 1572.77
1848 PI 596421 P. fendleri United States AZ Graham 33.25000 −110.28333 795.53
1851 W6 20826 P. fendleri United States AZ Cochise 31.91667 −109.16667 1493.52
1852 W6 20861 P. fendleri United States AZ Cochise 31.65000 −110.01667 1447.80
1874 PI 596423 P. fendleri United States AZ Apache 34.56667 −109.50000 1755.65
1889 PI 596425 P. fendleri United States NM Socorro 33.88333 −106.40000 1661.16
1904 W6 20865 P. fendleri United States AZ Apache 34.35000 −109.36667 1859.28
1906 PI 596426 P. fendleri United States NM Socorro 34.41667 −106.65000 1645.92
1909 W6 20868 P. fendleri United States NM Guadalupe 33.56667 −105.05000 1697.74
1910 PI 596428 P. fendleri United States NM De Baca 34.46667 −104.30000 1149.10
1912 PI 596429 P. fendleri United States NM Guadalupe 34.73333 −104.46667 1359.41
1919 PI 596430 P. fendleri United States NM San Juan 36.60000 −108.91667 1758.70
1920 PI 596431 P. fendleri United States NM San Juan 36.58333 −108.96667 1932.43
1924 W6 20851 P. rectipes United States AZ Luna 35.86667 −109.60000 1912.00
1932 PI 596433 P. fendleri United States AZ Graham 33.28333 −110.38333 877.82
2212 W6 20863 P. argyraea United States TX Uvalde 29.15000 −99.70000 228.60
2226 W6 20828 P. fendleri United States TX Webb 27.36667 −98.98333 243.84
2232 PI 643174 P. lindheimeri United States TX Nueces 27.06667 −97.06667 107.00
2243 W6 20835 Paysonia grandiflora United States TX Wilson 29.16667 −97.93333 91.44
2250 W6 20854 P. recurvata United States TX Medina 29.53333 −99.21667 434.34
2255 PI 596435 P. fendleri United States TX El Paso 31.83333 −106.01667 1341.12
2256 PI 596436 P. fendleri United States TX Hudspeth 31.70000 −105.41667 1240.54
2260 PI 596439 P. fendleri United States TX Hudspeth 31.81667 −105.13333 1219.20
2262 PI 596441 P. fendleri United States TX Culberson 31.36667 −104.81667 944.88
2269 PI 596447 P. fendleri United States TX Pecos 30.71667 −103.18333 975.36
2273 PI 596450 P. fendleri United States TX Brewster 30.20000 −103.56667 1554.48
2277 PI 596452 P. fendleri United States TX Brewster 29.78333 −103.18333 853.44
2278 PI 596453 P. fendleri United States TX Brewster 30.20000 −103.20000 1310.64
2281 PI 596454 P. fendleri United States TX Crockett 30.93333 −101.86667 640.08
2282 PI 596455 P. fendleri United States TX Pecos 30.96667 −101.96667 563.88
2286 PI 596456 P. fendleri United States TX Andrews 32.31667 −102.50000 807.72
2290 PI 596457 P. fendleri United States TX Winkler 31.78333 −103.26667 853.44
2291 PI 596458 P. fendleri United States TX Reeves 31.11667 −103.71667 944.88
2292 PI 596459 P. fendleri United States TX Reeves 31.01667 −103.73333 1005.84
2294 PI 596461 P. fendleri United States TX Jeff Davis 30.53333 −104.10000 1722.12
2295 PI 596462 P. fendleri United States TX Jeff Davis 30.55000 −103.91667 1676.40
2296 PI 596463 P. fendleri United States TX Jeff Davis 30.43333 −103.96667 1554.48
2299 PI 596464 P. fendleri United States TX Presidio 30.15000 −104.08333 1402.08
2300 PI 596465 P. fendleri United States TX Brewster 30.31667 −103.78333 1493.52
2301 PI 596466 P. fendleri United States TX Presidio 30.26667 −103.90000 1432.56
2302 PI 596467 P. fendleri United States TX Jeff Davis 30.53333 −104.31667 1493.52
2303 PI 596468 P. fendleri United States TX Jeff Davis 30.71667 −104.66667 1280.16
2304 W6 20872 P. fendleri United States TX Culberson 30.83333 −104.78333 1188.72
2305 W6 20830 P. fendleri United States TX Hudspeth 31.03333 −104.90000 1310.64
2928 W6 20834 P. gracilis United States OK Choctaw 34.01667 −95.35000 137.00
3009 W6 20319 Paysonia auriculata United States OK Caddo 35.54173 −98.57041 475.00
4005 PI 643177 P. fendleri Mexico COA – 28.73861 −100.91250 330.00
4008 – P. fendleri Mexico COA – 28.69328 −100.57672 270.97
4015 – P. fendleri Mexico COA – 25.11048 −101.11323 2097.00
4016 PI 643179 P. fendleri Mexico ZAC – 24.37749 −101.38860 1840.00
4024 PI 641924 P. fendleri Mexico DUR – 24.59139 −103.92303 1935.00
4042 – P. fendleri Mexico COA – 28.49582 −100.70158 312.72
4043 – P. fendleri Mexico COA – 28.53963 −100.48233 271.27
4044 – P. fendleri Mexico ZAC – 24.24713 −101.43585 1897.68
4045 – P. fendleri Mexico ZAC – 24.23212 −101.44367 1908.05
4046 – P. fendleri Mexico ZAC – 24.06105 −101.44598 1909.27
4047 – P. fendleri Mexico NLE – 25.10865 −100.65158 1919.94
4048 – P. fendleri Mexico ZAC – 24.21158 −101.45683 1935.18
4049 – P. fendleri Mexico ZAC – 24.39118 −101.45952 1933.35
4050 – P. fendleri Mexico ZAC – 24.19925 −101.46575 1930.91
4058 – P. fendleri United States NM McKinley 36.44348 −108.13162 2232.66
4085 – P. fendleri United States NM San Miguel 35.30000 −104.25385 1368.00
4087 – P. kathyrn United States ME – – – –
4092 PARL 812 P. pallida * United States TX – – – –
4094 PARL 814 P. pallida * United States TX – – – –
4057b – P. fendleri United States NM McKinley – – –
DDMC2010-1 PARL 859 P. fendleri United States NM Socorro 34.13115 −106.90907 1424.00
DDMC2010-19 PARL 874 P. fendleri United States TX Jeff Davis 30.79047 −104.16759 1668.00
DDMC2010-6 PARL 863 P. gordonii United States TX Hudspeth 31.74230 −105.10552 1141.00
WCL-LO2 – P. fendleri United States – – – – –
WCL-LO4 P. fendleri United States – – – – –
WCL-SL1 PI 613132 P. fendleri United States – – – – –
WCL-YS1 PI 610492 P. fendleri United States – – – – –
– PARL 817 P. thamnophila United States TX – – – –
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*

exact geographic coordinates of P. pallida are not supplied since they are in the federal and state list of endangered species.

Microarray DArT Platform Development

The microarray DArT was developed by first testing combinations of the rare-cutting restriction enzyme PstI with several restriction endonucleases that cut frequently on DNA samples from 8 representative accessions to determine the restriction enzyme combination that provided the best complexity reduction. Final genomic representations were prepared using PstI/BstNI combinations. Approximately 50 ng of genomic DNA was digested with PstI/BstNI combinations and the resulting fragments ligated to a PstI overhang compatible oligonucleotide adapter. A primer annealing to this adapter was used in PCR reaction to amplify complexity-reduced representation of a sample. Amplification products were either used for cloning a in marker development process or labeled with fluorescent dyes and hybridized to DArT array in the genotyping process. Library construction was subsequently performed using 80 P. fendleri accessions and 16 accessions of wild related Brassica species. The amplified PstI restriction fragments from all accessions were cloned into pCR2.1-TOPO vector (Invitrogen, Australia) as described by Jaccoud et al. [21] and four libraries were generated. The white colonies containing genomic fragments inserted into pCR2.1-TOPO vector were picked into individual wells of 384-well microtiter plates filled with ampicillin/kanamycin-supplemented freezing medium. A total of 3,456 clones from Physaria were obtained –1,920 from three libraries of P. fendleri and 1,536 from the related species. Inserts from these clones were amplified using M13F and M13R primers in 384 plate format, a subset of PCR products were assessed for quality (10% of 25 µl PCR reaction) through gel electrophoresis, and all remaining PCR products dried, washed and dissolved in a spotting buffer. A total of 6,144 clones were printed with spot duplication on SuperChip poly-L-lysine slides (Thermo Scientific, Australia) using a MicroGrid arrayer (Genomics Solutions, UK). The microarrays included 1,920 Brassica clones and 768 Arabidopsis clones in addition to the Physaria clones.

Each sample was assayed using methods described above for library construction. Genomic representations were assessed for quality through gel electrophoresis in 1.2% agarose and labeled with fluorescent dyes (Cy3 and Cy5). Labelled targets were then hybridized to printed DArT arrays for 16 hours at 62°C in a water bath. Slides were washed as described by Kilian et al. [28], dried initially by centrifugation at 500 × g for 7 min and later by a desiccator under vacuum for 30 min. The slides were scanned using Tecan LS300 scanner (Tecan Group Ltd, Männedorf, Switzerland) generating three images per array: one image scanned at 488 nm for reference signal measures the amount of DNA within the spot based on hybridization signal of FAM-labeled fragment of a TOPO vector multiple cloning site fragment and two images for “target” signal measurement: one scanned at 543 nM (for Cy3 labeled targets) and one at 633 nM (for Cy5 labeled targets). All DArT techniques applied for this work were recently described in much more detail by Kilian et al. [28].

DArTseq Platform Development

For the sequencing-based DArT genotyping, four complexity reduction methods optimized for several other plant species at DArT P/L were used. PstI-RE site specific adapter was tagged with 96 different barcodes enabling encoding a plate of DNA samples to run within a single lane on an Illumina Genome Analyzer IIx (Illumina Inc., San Diego, CA). PstI adapter included also a sequencing primer site, so that the tags generated were always reading into the genomic fragments from the PstI sites. After the sequencing run, the FASTQ files were quality filtered using the threshold of 90% confidence for at least 50% of the bases and in addition filtered more stringently for barcode sequences. Two lanes of GAIIx were run with all samples providing fully replicated sequencing data. The filtered data were split into their respective target (individual) data using barcode splitting script. Each sample had on average 500,000 counts per replicate. After producing various QC statistics and trimming of the barcode the sequences were aligned against the reference created from the tags identified in the sequence reads generated from all the samples. In addition the short sequence tags were aligned against Arabidopsis thaliana’s genome available in Genbank. Arabidopsis is a close relative of Physaria in the Brassicaceae [29]. The output files from alignment generated using Bowtie software [30] were processed using an analytical pipeline developed by DArT P/L to produce “DArT score” tables and “SNP” tables.

Genotyping

Both DArT on array platform and DArTseq use a set of quality parameters to select markers which are of use for a specific application. One of these parameters is reproducibility of markers in technical replicates for a subset of samples. In diversity analysis, the reproducibility parameter threshold is set usually at 97% which translates to average reproducibility of the dataset around 99.7%. A total of 87 common accessions were genotyped using both the microarray DArT and DArTseq platforms. A total of 11 Physaria species, 1 interspecific hybrid, and 2 Paysonia species were analyzed by microarray DArT. Additional accessions were genotyped using the DArTseq platform comprised of 17 Physaria and 7 Paysonia species. Overall, there was a total of 177 accessions represented by single plant samples genotyped using the two platforms, majority of which are P. fendleri (Tables 1 and 2). The marker sequences and genotype data will be stored in the U.S. Germplasm Resources Information Network (GRIN) database (http://www.ars-grin.gov) along with the accessions’ phenotypic observations and germplasm passport data curated by the U.S. National Plant Germplasm System.

Table 2. Passport information of additional Physaria and Paysonia accessions genotyped using DArTseq.

Collection No.and ID Accession No. Species Country State/Prov. County Latitude Longitude Elevation (m)
715 PI 293027 P. fendleri United States TX Brewster 29.32768 −103.20527 1139.00
720 PI 293028 P. fendleri United States TX Val Verde 29.84683 −101.68152 519.00
Barclay 998 PI 279650 P. fendleri United States NM – – – –
1836 W6 20857 P. fendleri United States NM Luna 32.23333 −107.38333 1264.92
1838 PI 596415 P. fendleri United States NM Chaves 32.86667 −105.03333 1621.54
1839 PI 596416 P. fendleri United States NM Eddy 32.83333 −104.80000 1301.50
1854 W6 23374 P. gordonii United States AZ Cochise 31.85000 −109.96667 1732.79
1855 PI 596422 P. fendleri United States AZ Cochise 31.96667 −109.46667 1548.38
1871 W6 20862 P. fendleri United States AZ Navajo 34.88333 −110.11667 1546.86
1879 W6 20838 P. intermedia United States AZ Navajo 34.35000 −110.16667 1828.80
1880 PI 596424 P. fendleri United States AZ Navajo 34.36667 −110.15000 1825.75
1902 P. kaibabensis United States AZ Coconino 36.73333 −112.11667 2237.23
1907 PI 596427 P. fendleri United States NM Torrance 34.55000 −106.13333 1850.14
1926 PI 596432 P. fendleri United States AZ Navajo 34.75000 −110.16667 1615.44
1934 W6 20869 P. fendleri United States AZ Graham 33.23333 −110.25000 908.30
2097 PI 331165 P. fendleri United States AZ Graham 33.38333 −110.38333 917.00
2202 W6 20819 P. densiflora United States TX Gillespie 30.20000 −98.93333 434.34
2203 P. recurvata United States TX Kerr 30.00000 −99.36667 518.16
2217 PI 643172 Paysonia lasiocarpa United States TX Frio 28.63333 −99.38333 198.12
2228 W6 20840 Paysonia lasiocarpa United States TX Duval 27.58333 −98.56667 137.16
2246 W6 20836 Paysonia grandiflora United States TX Atascosa 28.85000 −98.35000 121.92
2247 W6 20837 Paysonia grandiflora United States TX Frio 29.06667 −98.85000 121.92
2257 PI 596437 P. fendleri United States TX Hudspeth 31.73333 −105.21667 1097.28
2258 W6 20829 P. fendleri United States TX Hudspeth 31.83333 −105.20000 1219.20
2259 PI 596438 P. fendleri United States TX Hudspeth 31.81667 −105.13333 1188.72
2264 W6 20870 P. fendleri United States TX Reeves 30.91667 −103.78333 914.40
2265 PI 596443 P. fendleri United States TX Jeff Davis 30.86667 −103.78333 1127.76
2267 PI 596445 P. fendleri United States TX Jeff Davis 30.68333 −103.78333 1234.44
2268 PI 596446 P. fendleri United States TX Jeff Davis 30.48333 −103.75000 1554.48
2270 PI 596448 P. fendleri United States TX Brewster 30.38333 −103.58333 1402.08
2274 P. fendleri United States TX Brewster 30.03333 −103.56667 1280.16
2276 W6 20871 P. fendleri United States TX Brewster 29.66667 −103.11667 822.96
2279 W6 20844 P. mcvaughiana United States TX Pecos 30.46667 −102.91667 1432.56
2293 PI 596460 P. fendleri United States TX Jeff Davis 31.00000 −104.18333 1310.64
2297 W6 20859 P. fendleri United States TX Presidio 30.28333 −104.01667 1463.04
2401 P. douglasii United States WA Grant 46.63333 −119.73333 89.61
2819 W6 20873 P. fendleri – – – – – –
2894 Paysonia densipila United States TN Williamson 35.82861 −86.69722 208.00
2997 W6 20859 P. fendleri United States AZ Apache 34.48333 −109.51667 1899.00
3029 P. intermedia United States UT Garfield 38.02044 −112.36819 1944.00
3011 W6 20320 Paysonia auriculata United States OK Blaine 35.79325 −98.42029 454.00
3000 Paysonia lyrata United States AL Colbert – – –
3030 PI 337050 P. fendleri United States NM Sierra 33.36355 −107.28041 1500.00
3042 W6 20843 P. ludoviciana United States UT Garfield 37.76753 −112.06660 1791.00
3050 P. acutifolia United States UT San Juan 37.50160 −109.64779 1410.00
3058 PI 345712 Paysonia auriculata United States OK Garfield 36.43716 −97.58647 360.00
3083 PI 355037 P. fendleri United States TX Kinney 29.15197 −100.38664 288.00
3085 P. acutifolia United States CO Mesa 38.83627 −108.56218 2073.00
3091 PI 355041 Paysonia perforata United States TN Wilson 36.23255 −86.38455 182.00
3092 PI 355042 Paysonia stonensis United States TN Rutherford 35.98204 −86.41221 158.00
319b P. argyraea – – – – – –
3219 W6 20847 P. pallida United States TX – – – –
3370 PI 275769 Paysonia lyrata United States AL Franklin – – –
3344 PI 643175 P. mexicana Mexico COA – 27.03333 −102.30000 1500.00
3347 PI 275771 Paysonia stonensis United States TN Rutherford 35.99628 −86.44516 172.00
4001 P. fendleri Mexico COA – 27.59103 −101.18092 394.41
4002 PI 643176 P. fendleri Mexico COA – 28.13173 −101.12267 396.54
4006 P. fendleri Mexico COA – 28.87570 −100.61240 304.80
4007 PI 641923 P. fendleri Mexico COA – 28.61252 −100.50212 277.67
4014 PI 643178 P. argyraea Mexico COA – 25.16667 −101.00000 2500.00
4055 P. intermedia United States AZ Navajo 34.43717 −110.53613 2233.23
4061 P. fendleri United States – – – – –
4063 P. inflata Mexico NLE – 25.64967 −100.70617 1303.96
4064 P. fendleri United States – – – – –
4088 P. valida United States NM Otero 32.94567 −105.35584 1821.00
4091 PARL 811 P. pallida United States TX – – – –
4093 PARL 813 P. pallida United States TX – – – –
19224 PI 293005 P. fendleri United States TX Val Verde 30.53333 −102.15000 500.00
19230 PI 293008 P. fendleri United States TX Loving 32.23333 −103.90000 861.28
19231 PI 283700 P. fendleri United States TX Loving 31.73413 −103.55457 855.00
19239 PI 293013 P. fendleri United States TX Reeves 32.35000 −104.35000 1000.30
19242 PI 293015 P. fendleri United States TX Reeves 32.06667 −103.86667 861.28
19992 PI 293016 P. fendleri United States TX Hudspeth 32.26667 −105.61667 1300.30
20634 PI 299412 P. fendleri United States AZ Conchise 31.83791 −110.34341 1386.00
WCL-LO1 PI 596363 P. fendleri – – – – – –
WCL-LY1 PI 596362 P. fendleri – – – – – –
WCL-LH1 PI 596364 P. fendleri – – – – – –
DDMC2010-2 – P. fendleri United States NM Lincoln 33.68458 −105.91996 1598.00
DDMC20103 PARL 860 P. fendleri United States NM Lincoln 33.73022 −105.96510 1666.00
DDMC2010-4 PARL 861 P. fendleri United States NM Eddy 32.91352 −104.43478 1041.00
DDMC2010-5 PARL 862 P. fendleri United States TX Loving 31.73557 −103.55061 855.00
DDMC2010-7 PARL 864 P. gordonii United States NM Dona Ana 32.25027 −107.17893 1324.00
DDMC2010-8 PARL 865 P. fendleri United States NM Dona Ana 32.24291 −107.18271 1319.00
DDMC2010-9 PARL 866 P. fendleri United States AZ Conchise 31.51705 −110.01781 1447.80
DDMC2010-10 PARL 867 P. fendleri United States AZ Conchise 31.81811 −110.01729 1458.47
DDMC2010-11 PARL 868 P. fendleri United States AZ Conchise 31.83494 −110.01163 1505.10
DDMC2010-12 PARL 869 P. fendleri United States TX Culberson 30.93663 −104.81040 1207.92
DDMC2010-13 PARL 870 P. fendleri United States TX Presidio 30.30604 −104.03443 1444.45
DDMC2010-14 – P. fendleri United States TX Brewster 30.50022 −103.44561 1200.91
DDMC2010-15 PARL 871 P. fendleri United States TX Pecos 30.90170 −102.91230 929.34
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exact geographic coordinates of P. pallida are not supplied since they are in the federal and state list of endangered species.

Data Analysis

All the images from DArT platforms were analyzed using DArTsoft v.7.4.7 (DArT P/L, Canberra, Australia). The markers were scored as binary data (1/0), indicating presence or absence of a marker in genomic representation of each sample as described by Wenzl et al. [31]. For quality control, 30% of genotypes were genotyped in full technical replication. Clones with P>77%, a call rate >97% and >98% allele-calling consistency across the replicates were selected as markers. P value represents the allelic-states variance of the relative target hybridization intensity as a percentage of the total variance. The informativeness of the DArT markers was determined by calculating the polymorphism information content (PIC) within the panel of diverse accessions according to Anderson et al. [32]. The P. fendleri data were used in GenAlEx v.6.41 [33] to determine 2D spatial autocorrelation of the DArT microarray and Arlequin v.3.5.1.3 [34] to assess the amount of variation among the assigned regional groupings by AMOVA. To summarize the relationships among all examined accessions, cluster analysis was performed on Dice similarity values with the SAHN procedure using the unweighted pair-group method done using NTSYS-pc v. 2.21 m [35]. The Dice coefficient was preferred over simple matching coefficient because DArT is a dominant marker system and there were several non-Physaria species in the sample set [36], [37]. In addition, a Bayesian model-based clustering was performed on microarray DArT markers using STRUCTURE v.2.3.4 [38] testing 3 independent runs with K from 1 to 8, each run with a burn-in period of 50,000 iterations and 300,000 Monte Carlo Markov Chain (MCMC) iterations, assuming an admixture model and correlated allele frequencies. The STRUCTURE data was subsequently analyzed by HARVESTER v.06.92 [39]. Mantel tests were made to determine if there are significant correlations between the dendrogram representations and the distance matrices, between the matrices of geographic and genetic distances, and between the distance matrices from the two DArT platforms used in the P. fendleri. The missing geographic coordinates of collection sites of ten accessions (PI 293027, PI 293028, PI 337050, PI 345712, PI 355037, PI 355041, PI 355042, PI 275771, PI 283700 and PI 299412) in the GRIN database were estimated using Google Earth v. 6.1.0.5001 based on available locality description and collectors’ notes and the information included in the analysis. Map projections of the analyzed P. fendleri accessions were made using ArcGIS Explorer v.2.0.0.1750 (ESRI, Redlands, CA) and non-parametric correlation tests done using JMP v.9 (SAS Institute, Cary, NC).

Results

Relationships among Accessions from Microarray DArT Analysis

A total of 2,833 polymorphic markers were found using microarray DArT, with an average genotype call rate of 98.4% and a scoring reproducibility of 99.7%. The average PIC value was 0.21 and the median 0.19. About 20% of the markers have values in the range of 0.06 to 0.10, and almost an equal proportion of 12% of markers on the following PIC classes - 0.11 to 0.15, 0.16 to 0.20, and 0.21 to 0.25 (Figure 1). Overall, the distribution of PIC values was asymmetrical and skewed towards the lower values.

Figure 1. Distribution of marker PIC values by DArT platform.

Figure 1

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Cluster analysis and principal coordinate analysis (PC plot not shown) indicated that the different accessions were successfully classified by the marker system based on species, by geographical source, and breeding status (Figure 2), except for one new collection of P. gordonii, DDMC2010-6, which clustered with the P. fendleri accessions. The cophenetic correlation coefficient between the dendrogram and the distance matrix was highly significant (r = 0.98, t = 10.30, prob random Z<obs. Z = 1.00, 3000 permutations) indicating that the tree is a very good representation of the distance matrix. All P. fendleri accessions grouped in a separate cluster from the other species. The main cluster has two subgroups from Mexico, and a subgroup with a majority of accessions from Texas. There was no single group of P. fendleri accessions from Arizona and New Mexico. Most accessions from these States were associated with other accessions from Texas.

Figure 2. Cluster analysis of Physaria and Paysonia accessions based on 2,833 DArT markers.

Figure 2

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The labels denote the germplasm collection numbers and origin. Suffixes indicate respective species (PAR: P. argyraea, PAU: P. auriculata, PFE: P. fendleri, PGO: P. gordonii, PGF: P. grandiflora, PGR: P. gracilis, PKN: P. ‘kathryn’, PLI: P. lindheimeri, PPL: P. pallida, PRC: P. recurvata, PRT: P. rectipes, and PTH: P. thamnophila).

The four advanced P. fendleri breeding lines were partitioned into two clusters. The breeding lines WCL-SL1 and WCL-YS1 were found to be more genetically distant to WCL-LO2 and WCL-LO4. The last two lines were determined to be more similar to the rest of the P. fendleri from North America than WCL-SL1 and WCL-YS1.

Among the different species, the most similar to P. fendleri was determined to be P. argyraea while the least similar was P. thamnophila. The P. pallida accessions grouped in one cluster along with P. lindheimeri and other accessions representing the species, P. gracilis, P. gordonii, P. recurvata, and P. rectipes. The two accessions of Paysonia auriculata (3009) and Paysonia grandiflora (2243) grouped together in a separate cluster along with the interspecific hybrid swarm ‘Kathryn’ (4087) from five Paysonia species.

The analysis of molecular variance considering P. fendleri accessions only, showed that there was a much greater proportion of variation within groups (90%) than among groups (10%) in the species (Table 3). Among the unimproved germplasm set, the pairwise Fst values that showed the greatest differentiation was between Arizona accessions and those from New Mexico and the least amount of differentiation between Mexico and Arizona (Table 4). There was a significant correlation found between the computed genetic distance and geographic distance matrices from Mantel test (r = 0.33, t = 5.94, prob random Z<obs z = 1.00, 3000 permutations), indicating that distant accession pairs are more different genetically, supporting the previously mentioned result (Figure 3).

Table 3. Analysis of molecular variance in P. fendleri accessions.

Source df SS Variance components %
A. Microarray DArT
Among Groups 4 1597.506 17.19956 9.66%
Within Groups 69 11094.561 160.79074 90.34%
Total 73 12692.068 177.99031 100%
B. DArTseq
Among Groups 4 14299.235 98.59559 7.22%
Within Groups 123 155895.234 1267.44093 92.78%
Total 127 170194.469 1366.03651 100%
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Table 4. Comparison of population pairwise Fst values using microarray DArT and DArTseq.

Arizona Advancedlines Mexico New Mexico Texas
Arizona 0.10717 0.13076 0.03055 0.04049
Advanced lines 0.13854 0.22289 0.10951 0.08193
Mexico 0.00448 0.13043 0.12926 0.10552
New Mexico 0.16823 0.17758 0.16280 0.03056
Texas 0.01547 0.12599 0.02649 0.16289
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Values in bold are significant at α = 0.05. Values below diagonal are from microarray DArT and those above diagonal are from DArTseq.

Figure 3. GenAlEx plot of geographic distance (GGD) and genetic distance (GD) from microarray DArT markers.

Figure 3

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Relationships among Accessions from DArTseq Analysis

There was a total of 27,748 markers obtained using the Physaria DArTseq platform. The average genotype call rate was 98.8% and a scoring reproducibility of 99.7%. The average PIC value was 0.12 and the median was 0.09. About 57% of markers have PIC values in the range of 0.06 to 0.10, while 20% and 11% on PIC classes 0.11–0.15 and 0.01–0.05, respectively (Figure 1). The `distribution of the PIC values of DArTseq markers follows the same skewed pattern as the DArT microarray markers presented earlier.

Cluster analysis using the markers from this platform resulted in a relationship that follows that of the taxonomic groupings based on general morphological affinities presented by Rollins and Shaw [1]. The results did not deviate from those when the first platform with fewer markers used. Four accessions of P. fendleri (2258, 2274, 3083, and DDMC2010-8) clustered with the other Physaria species – P. gordonii and P. gracilis, indicating higher genetic similarity to representative accessions of these species than the rest of P. fendleri. These four P. fendleri accessions will be further examined for misidentification and for oil and morphological trait variation when verified.

The cophenetic correlation coefficient between the dendrogram and the distance matrix was highly significant (r = 0.94, t = 49.20, prob random Z<obs. Z = 1.00, 3,000 permutations) indicating that the tree is a very good representation of the distance matrix. The cluster of P. fendleri showed a distinct group of accessions from Mexico and a cluster comprised of all other germplasm from North America (Figure 4). The DArTseq platform indicated two separate clusters for the advanced lines. The breeding lines WCL-LH1, WCL-LO1, and WCL-LY1 are all in a group with greater similarity to accessions from Texas. WCL-LO2, WCL-LO4, WCL-SL1, and WCL-YS1 grouped together in one cluster indicating greater genetic similarity to accessions from Arizona and Mexico. WCL-LO2 was derived from the WCL-LO1 and the remaining three from WCL-LO2. It appears from these data that perhaps more genotypes from the Arizona accession were integrated into WCL-LO2.

Figure 4. Cluster analysis of Physaria and Paysonia accessions based on 27,748 DArTseq markers.

Figure 4

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The labels denote the germplasm collection numbers and origin. Suffixes indicate respective species (PAC: P. acutifolia, PAR: P. argyraea, PAU: P. auriculata, PDE: P. densipila, PDF: P. densiflora, PDO: P. douglasii, PFE: P. fendleri, PGO: P. gordonii, PGF: P. grandiflora, PGR: P. gracilis, PIF: P. inflata, PIN: P. intermedia, PKA: P. kaibabensis, PKN: P. ‘kathryn’, PYL: P. lasiocarpa, PLI: P. lindheimeri, PLT: P. lyrata, PLU: P. ludoviciana, PMC: P. mcvaughiana, PMX: P. mexicana, PPF: P. perforata, PPL: P. pallida, PRC: P. recurvata, PRT: P. rectipes, PST: P. stonensis, PTH: P. thamnophila and PVA: P. valida).

Similar to results from the microarray DArT, the accessions of the following species formed distinct groups consistent with the classification by Rollins and Shaw [1]: a) P. intermedia, P. valida, and P. rectipes, b) P. gordonii, P. gracilis, P. rectipes, and P. lindheimeri, and c) P. auriculata, P. densipila, P. lyrata, P. stonensis, P. grandiflora, and P. perforata. The two accessions of P. lasiocarpa (2217 and 2228) were most genetically similar to the accessions of P. grandiflora. This last group of species comprised of annual, auriculate-leaved types whose taxonomic nomenclature was segregated from Physaria and transferred to Paysonia based on leaf-trichome morphology, chromosome number, and molecular data from analyzing internal transcribed spacers of nuclear ribosomal DNA [40]. Apart from the accession of Physaria mexicana nested within the Paysonia cluster, the results of this genetic analysis using both microarray DArT and DArTseq platforms support the previous segregation of Physaria from Paysonia as proposed by O’Kane and Al-Shehbaz [40] indicating that the group of Paysonia species to be the least genetically similar to the P. fendleri and other Physaria accessions.

Results of the analysis of molecular variance when DArTseq markers were used correspond to that from microarray DArT. A greater proportion of variation within groups (93%) than among groups (7%) in the species was found (Table 3).

The average genetic similarity in the P. fendleri group when using microarray DArT was 0.86, while only 0.44 when DArTseq was used. This is in line with the assumption that more differences may be found when more markers are used because of the increased sensitivity and resolution to detect genetic distinctiveness [41]. The genetic similarity matrices of P. fendleri obtained using the two platform systems showed a good fit when compared by a Mantel test (r = 0.48, t = 11.28, prob random Z<obs z = 1.00, 3,000 permutations).

Population Structure Analysis of P. fendleri

Using results from microarray DArT, the population structure of the P. fendleri samples was determined. The plot of ΔK for each K value is shown in Figure 5a. It was estimated through the method of Evanno et. al. [42] that there are 4 groups contributing significant genetic information in the P. fendleri collection. The bar plot of the population assignment test when K = 4 is shown in Figure 5b. Three of the four accessions of P. fendleri breeding lines are shown to have mixed backgrounds. Of the other P. fendleri accessions, twelve (16%) have close to homogeneous genetic background (>98% probability) while 63 accessions (84%) are highly heterogeneous showing intermediate and/or highly mixed composition. A majority of the accessions from Texas are assigned to one cluster, while those from New Mexico have myriad cluster assignments suggesting the greater diversity of P. fendleri in this U.S. state. When the cluster assignments of the P. fendleri accessions were projected on a map, the segregation among clusters was evident in their geographic location (Figure 6). Further testing for association between the assigned clusters and available site elevation data by computing Spearman’s rank correlation coefficient showed a very weak positive correlation (Spearman ρ = 0.11, p = 0.33).

Figure 5. Plot of ΔK from K = 2 to 7 (a) and the population structure of 75 P. fendleri accessions at K = 4 (b).

Figure 5

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Figure 6. Geographic locations of the P. fendleri accessions and their respective cluster assignments (indicated by different icons) based on Bayesian model-based clustering methods.

Figure 6

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Discussion

The importance of understanding genetic diversity in germplasm collections is critical for the effective management of accessions in genebanks. Molecular characterization supplements morphological evaluation of germplasm and allows measurements to help resolve numerous operational, logistical, and biological questions that face genebank managers and conservation biologists [43], [44]. The Physaria collection in the U.S. NPGS has not been well characterized before for genetic diversity, though there have been preliminary studies on subsets of accessions using a limited number of microsatellite markers [16], and an extensive evaluation for diversity in oil characteristics and other morphological characters [45]. In this study, the new DArT platforms for Physaria were found both acceptable and provided robust information about the genetic variability of the collection.

The development and utilization of DArT markers allowed us to determine the genetic diversity of the Physaria collection. The 2,833 microarray DArT markers were found to be useful in providing a picture of genetic diversity in the Physaria germplasm collection using a large set of accessions. Overall, the average PIC of the Physaria and Paysonia microarray DArT markers was found to be lower than that observed in other species where similar markers were developed, like wheat (0.44) [46], cassava (0.42) [47], and sorghum (0.41) [48], but comparable to that observed in sugar beet (0.28) [49] and Asplenium fern (0.21) [50]. The average PIC of the DArTseq markers is much less than that of the microarray DArT. However, the more numerous DArTseq markers may have the capability of providing a better picture of diversity by sampling more points in the genome. The distribution of these almost 30,000 new DArT markers in the Physaria and Paysonia genome remains to be determined. However, based on the information from a large number of organisms in which DArT system was applied more broadly including genetic mapping and/or sequence-based physical mapping, we can assume that DArT marker from both platforms will be distributed throughout the genome with marker density highly correlated to gene density [28], [51]. Compared to microsatellite markers, DArT markers are very suitable for high-throughput work and previously have been determined to have clear advantages in cost and time aspects of genotyping as demonstrated in other crops [52]. Both microarray DArT and DArTseq platforms have the same development costs. However, the higher number of markers obtained in DArTseq resulted to an overall lower cost per datapoint than microarray DArT. This higher cost effectiveness of DArTseq is in parallel to other sequenced-based genotyping strategies which can provide substantial cost savings compared to microarrays when conducting genetic diversity studies [53], [54]. Importantly, when comparing effectiveness of the two platforms one has to keep in mind that it may vary according to specific application: in genetic ID and product quality testing (i.e. seed purity) modest number of array-based DArT markers may perform as well as DArTseq platform and currently for a better price. A further cost reduction of sequencing may however push even this balance towards DArTseq platform in the future.

The relationships found among the accessions are in line with the previously proposed evolution within the genus. Taxonomists assert that P. auriculata is the most primitive species due to its very distinct evolutionarily primitive characters such as large siliques, large number of ovules around the replum, and predominance of simple trichomes [1]. P. auriculata has been proposed to be closely related to P. grandiflora and this relationship is supported by the results of the molecular marker analysis between the accessions representative of these species (2243 and 3009) showing high genetic similarities. Likewise, P. gordonii and P. gracilis grouped in the same cluster with P. rectipes, P. recurvata, and P. thamnophila which is in agreement with their previously known taxonomic groupings based on very general morphological similarities. The high genetic similarity between the P. argyraea accessions (2212 and 319 b) to the P. fendleri group supports phylogenetic subsectional grouping based on pod morphology.

Overall, there was higher genetic similarity found among accessions of the other Physaria and Paysonia species than among accessions of P. fendleri. In particular, species that are included in the federal or state threatened and endangered species list, like P. pallida and P. stonensis [55], have very low genetic diversity as indicated by results of DArTseq markers. In P. pallida, the representative accessions (4091 and 4093) were found to be highly similar. The limited geographic range and the proximity of the collection sites of these two samples suggest that they might have been from just one population. Likewise for P. stonensis, there was a very high genetic similarity found on both of the representative accessions (3092 and 3347). Because only a limited number of accessions were included in these other species, a follow up study that includes additional accessions is recommended to validate if this is a general trend.

Physaria ‘Kathryn’ (4087) is a cultivar from interspecific hybridization developed by allowing five species (P. densipila, P. lescurii, P. lyrata, P. perforata, and P. stonensis) to intermate for twenty two generations [56]. P. ‘Kathryn’ was determined to be most closely related to P. auriculata in our analysis using microarray DArT. However, with the expanded set of accessions included in the DArTseq analysis, it grouped with the representative samples of its parent species – P. lyrata (3000 and 3370), P. perforata (3091), and P. stonensis (3092, 3347). These species were also found most genetically similar to P. mexicana (3344) which is the only perennial type in the species cluster. P. mexicana is a previously undescribed species in Mexico and is among the more recent species reported by Rollins [57].

DDMC2010-6 was from a more recent germplasm collecting trip and it was entered in the database as P. gordonii. However, based on results of DArT markers, it clustered with the P. fendleri accessions after using both DArT platforms, indicating the need to review its species assignment. The species identity of this particular accession will again be verified using its plant voucher specimen as well as in the NPGS site handling the germplasm when it is regenerated in the future.

The two clusters of P. fendleri breeding lines - WCL-LO2, WCL-LO4, WCL-SL1, and WCL-YS1 in one cluster, while the other set of breeding lines WCL-LO1, WCL-LH1, and WCL-LY1 in another, indicates the possibility of developing genetically differentiated lines for crop improvement and may have applications in future hybrid development work. The lines WCL-LH1, WCL-LO1 and WCL-LY1 are the first three germplasm lines that were publicly released in 1996. These were developed using recurrent selection on a population made by bulking seeds of one accession that came from Arizona and nine from Texas in 1986 [58]. The bulked seeds were also the starting material for other breeding lines. WCL-LO4 was derived from mass selection from WCL-LO3 and WCL-LY2 (both not included in this study) which has WCL-LY1 as the source population [59], [60]. The other breeding lines were developed through phenotypic selection: WCL-YS1 was a selection from PI 311165, one of the initial accession from Arizona that comprise the original bulk in 1986 [61], while WCL-SL1 came from plants that survived at the highest salinity levels during a salt tolerance screening study when seeds from the original bulked seeds were planted [62].

The accessions of P. fendleri from Mexico are genetically similar as indicated by the cluster analyses. The range of Physaria species has been reported as limited to the northeastern part of country and concentrated on mountain and high plains of Coahuila, Nuevo León, and Zacatecas [57]. This limited geographic distribution likely prevented their further genetic differentiation. A similar investigation focusing on the other Physaria species in this region could confirm this trend.

The array of P. fendleri germplasm consisted of 75 accessions analyzed using microarray DArT and 128 accessions using DArTseq. There is ample genetic variability in the P. fendleri collection found, as indicated by the cluster analysis as well as analysis of population structure. This is expected for a cross pollinating species that has not been fully domesticated [63]. However, the higher within group variation detected by AMOVA using data from both DArT platforms suggests that there is only a small amount of genetic differentiation among groups in the sample as a whole. Results from the Bayesian clustering approach when comparing the geographical sources of the accessions suggested that there is more variability in New Mexico than the other P. fendleri locations and that there is a spatial pattern evident in the microarray DArT results. This pattern of genetic differentiation occurs outward from central Texas, the region identified as the putative origin of Physaria as proposed earlier by Payson [64].

An increased population differentiation has been reported in many plant species between source populations and new ones when plants colonize new habitats [65]. The more dynamic nature of Physaria populations in distant locations from Texas has been reported by Payson [64] and he attributed part of the process as caused by barriers that separate populations, such as soil properties and moisture availability which are very important to survival of ephemeral populations of the taxon. In P. fendleri, Dierig et al. [66] stated that temperature and elevation effects can also account for significant differences in reproductive capacity. Selection patterns have also been investigated by past studies reporting that non-random mating, sexual selection and dormancy characteristics play a significant role in how traits evolved in the species [67], [68]. Seed dormancy characteristics in particular cause a persistent soil seed bank which may prevent genetic differentiation in the species because certain genotypes are reintroduced back during subsequent seasons [69], [70]. In terms of genetic resources conservation of P. fendleri germplasm, the DArT results suggest the existence of more variable genotypes in New Mexico and it is recommended that future collecting missions select this geographic area to possibly expand the genetic diversity in the species collection.

Conclusion

The availability of genetic diversity information of the P. fendleri collection will enable better germplasm management and conservation of the species. In this study we report the successful development of two DArT marker platforms that were utilized for genotyping Physaria and Paysonia accessions. This marker system complements the microsatellite markers developed previously for Physaria. The high number of DArT markers allows a greater resolution of genetic differences among accessions and enabled us to examine the extent of variation in the P. fendleri collection, as well as provide support to known taxonomic classification and recent nomenclatural changes of certain Physaria species to Paysonia. We intend to further utilize the DArT markers in developing a linkage map in Physaria to assist breeding efforts and for future genetic mapping studies.

Acknowledgments

USDA is an equal opportunity provider and employer. Mention of companies or commercial products does not imply recommendation or endorsement by the USDA over others not mentioned. USDA neither guarantees nor warrants the standard of any product mentioned. Product names are mentioned solely to report factually on available data and to provide specific information. We would like to thank David Ellis and Chris Richards for the valuable suggestions during the conduct of the study.

Funding Statement

Funding for the study was provided by U.S. Department of Agriculture (USDA) - Agricultural Research Service Project No. 5402-21000-007-00. The acquisition of new germplasm in 2010 was supported by the NPGS Plant Exploration/Exchange Program. No additional external funding was received or used for this study. USDA determines the research priorities of all research that it funds. Publication of research is subject to review of USDA officials. Specific study design, data collection, data analysis, and preparation of the manuscript is under the control of the individual researchers.

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