(potato) Germplasm - PubAg - USDA

2 downloads 0 Views 446KB Size Report
Apr 23, 2010 - Resumen Una pregunta básica que se hace cuando se ... La conclusión práctica es que .... Peaks from base camp at Anita spring. HUA e ...

Am. J. Pot Res (2010) 87:277–284 DOI 10.1007/s12230-010-9133-8

Comparison of “Remote” Versus “Easy” In Situ Collection Locations for USA Wild Solanum (potato) Germplasm John Bamberg & Alfonso del Rio & Charles Fernandez & Alberto Salas & Sandra Vega & Cinthya Zorrilla & Willy Roca & David Tay

Published online: 23 April 2010 # Potato Association of America 2010

Abstract A basic question in germplasm collecting is whether the in situ genetic diversity in a given geographic range has been adequately sampled. While one would ideally sample all diverse sites with appropriate habitat, there is usually a practical bias against visiting relatively inaccessible sites. For wild potato in the USA, mountain habitats often include easy access locations (near roads, usually at lower altitudes), and relatively remote locations (usually high altitude crests that can be accessed only by trail hiking and camping). This work used AFLP markers to compare three southeastern Arizona mountain ranges for which multiple “easy” and “remote” Solanum fendleri populations had been collected. Of the total markers detected, 24%, 6% and 3% were unique to the “remote” locations, and 3%, 21% and 34% were unique to “easy” locations. This case study demonstrates that populations at such locations are not identical, but the most unique alleles are sometimes captured at the remote location, sometimes at the easy. The practical conclusion is that both locations need to be sampled and compared empirically in the lab for unique allele richness to identify locations with highest priority for additional collecting. Resumen Una pregunta básica que se hace cuando se colecta germoplasma, es si la diversidad genética in situ

dentro de un area geográfica determinada ha sido muestreada adecuadamente. Mientras que idealmente es posible muestrear todos los sitios diversos con el hábitat apropiado, generalmente hay una predisposición práctica en contra de visitar sitios relativamente inaccesibles. En cuanto a especies silvestres de papa en los EUA, los hábitats montañosos a menudo incluyen localidades de fácil acceso (cerca de caminos, generalmente a altitudes bajas), y los lugares relativamente remotos (generalmente lugares de gran altura a los que se tiene acceso solo por rutas de a pie y acampando). En este trabajo se usaron marcadores AFLP para comparar tres montañas del sureste de Arizona en donde se colectaron poblaciones múltiples “fáciles” y “remotas” de Solanum fendleri. Del total de marcadores detectados, 24%, 6% y 3% fueron únicos de las localidades “remotas”, y 3%, 21% y 34% fueron únicas de los lugares “fáciles”. Este estudio demuestra que las poblaciones de tales localidades no son idénticas, pero los alelos mas exclusivos se captan algunas veces en la localidad remota y en otras ocasiones en la fácil. La conclusión práctica es que ambas localidades necesitan muestrearse y compararse empíricamente en el laboratorio, para determinar abundancia de alelos únicos e identificar lugares de la más alta prioridad para colectas adicionales. Keywords stoloniferum

J. Bamberg (*) : A. del Rio : C. Fernandez : S. Vega US Potato Genebank, USDA-Agricultural Research Service, 4312 Hwy 42, Sturgeon Bay, WI 54235, USA e-mail: [email protected] A. Salas : C. Zorrilla : W. Roca : D. Tay International Potato Center, Lima, Peru

Introduction The goal of germplasm collecting from natural (i.e., in situ) sites is to capture the maximum genetic diversity (Allard 1970). Of course, there are practical limitations. First, collecting more samples than the genebank has capacity to preserve is a waste of effort (Lawrence et al. 1995).


Second, efficient sampling depends on information that is often unavailable, such as breeding system, population size, optimal sample size, geographic range, life cycle, taxonomic class, and successional status (Loveless and Hamrick 1984; Hamrick and Godt 1990; Silvertown and Charlesworth 2001). Lockwood et al. (2007) note that much more study has been done to predict the most effective sampling within a population than to address the problem of which populations should be sampled. Thus, an iterative empirical process has been recommended by which initial collections are assessed for diversity, after which follow-up expeditions are planned based on the patterns of diversity detected. In potato, empirical results from such testing of USA populations suggest that capture of diversity is not very well predicted by habitat differentiation or geographic dispersion (Bamberg et al. 2003; Bamberg and del Rio 2005). This implies a strategy of initial widespread collecting of many populations (del Rio et al 2001). Collectors are limited by time, funds and the physical demands of germplasm exploration. So there will be a bias against collecting in areas that require more of these inputs per population. Hijmans et al. (2000, 2002) quantified this “infrastructure bias” by showing that 60% of wild potato collections from Bolivia had been made within 2 km of a road while one would expect only 22% if geographically representative sampling been done. Correll (1962, p. 11) describes the challenge of representative sampling, which is probably still valid nearly 50 years later: When one considers the vast geographical area where indigenous potatoes are to be found and the comparatively infinitesimal part that has been covered by the combined efforts of all collectors during the past 125 years, especially since 1925, one realizes that the surface has been scarcely scratched, as it were. As one flies for hours over, or parallel to, such regions as the vastness of the Andean system this is more fully realized. This Gargantuan land mass, that rises from near sea level to be culminated by Cord. Aconcagua at 7,000 m (23,080 ft.) altitude extends north and south for 4,000 mi and sometimes becomes as much as 200 mi in width, offers limitless possibilities for variations and complications in any group of plants that may occur there.” Regarding areas needing more exploration Correll (1962, p. 11) remarks, “In the United States, the region that holds the greatest possibilities for field investigators lies in Arizona. Several of the mountain ranges of that state, namely, the Chiricahua and Huachuca, need to be explored more fully”. But since then, new populations on the relatively inaccessible crests of these ranges have only been discovered and documented as a few herbarium

Am. J. Pot Res (2010) 87:277–284

records, and none had been sampled for germplasm until the authors did so in 2004–2006. Populations at sites that can only be accessed by hiking and camping are usually at higher altitude and have less human impact than those at roadside sites of the same mountain range, perhaps reasons to hypothesize that they are genetically distinct (Hijmans et al. 2000). This study tested that hypothesis. All practical work done with germplasm depends on the quality of the sample originally captured in the genebank. Thus, this study relates to a foundational genebank question: How does the diversity in the genebank compare to what exists in nature, and how should finite resources be deployed to maximize diversity capture?

Materials and Methods Collecting Details Populations were examined from three mountain ranges in southeastern Arizona, USA, called “sky islands” because they are relatively small and rise steeply to some 5,000 ft (1,500 m) above the surrounding desert. Mountain ranges were in relation to major Arizona cities as follows: Chiricahuas (CHI) are about 35 mi (56 km) SE of Wilcox, Huachucas (HUA) about 5 mi (8 km) SW of Sierra Vista, Rincons (RIN) about 10 mi (16 km) E and NE of Tucson. These three mountain ranges approximately define the points of an equilateral triangle with sides about 75 mi (120 km) long (Fig. 1). Electronic maps “Topo USA-7” from DeLorme, Inc., Yarmouth, ME were used to plan expeditions and manage collection data. For each mountain range, multiple populations of each of two location classes, “easy” and “remote” were collected and analyzed. Easy populations were collected near roads, while remote populations were usually near hiking trails. Remote (r) populations were distinguished as being practically accessible only to collectors with the time required to reach them traveling by foot, physical stamina to cover the sometimes steep and rough trails carrying supplies, and the considerable extra preparation and planning needed for wilderness camping several nights. All remote collections were made by authors Bamberg, del Rio and Fernandez in 2004 (CHI), 2005 (HUA) and 2006 (RIN). The easy (e) collections were made by the authors, J.G. Hawkes (1958), or D. Ugent and R. Ruhde (1978). Collections were typically made in the form of botanical seeds (i.e., fruit). In general, collecting locations were distinguished as follows: CHI e populations were along or close to roads accessing the Chiricahua mountains from the north, particularly Pinery Canyon road to Rustler Park. CHI r populations were at sites proceeding south along the crest trails from Rustler Park toward Raspberry and Sentinel Peaks from base camp at Anita spring. HUA e populations

Am. J. Pot Res (2010) 87:277–284


Fig. 1 Southeast Arizona showing mountain ranges from which easy and remote samples originated

were collected from NE-facing and SW-facing lower canyons while HUA r populations were collected along the crest trails between Miller Peak and Fort Huachuca from a base camp at Bathtub spring. RIN e were collected along the General Hitchcock highway from Tucson to Mount Lemmon on the southern side of the Santa Catalina mountains. RIN r were collected along trails near Mica Mountain from a base camp at Manning Camp in the Rincon mountains. Terms All plant materials collected and examined were Solanum fendleri referred to by its historic name, although recently subsumed under S. stoloniferum (Spooner et al. 2004). We report in the English units of measure which are standard at these collecting locations. Although AFLP bands are not alleles at distinct loci, we refer to them using genetic terms for convenience under the assumption that they have parallel characteristics. As above, the three collection areas will be designated by the term “mountain ranges” and the populations grouped as easy (e) and remote (r) within them will be designated by the term “locations”. Easy location collections for the mountain range designated “RIN” were actually made in the Santa Catalina mountains but we designate both locations of this pair under the term

RIN for simplicity. Table 1 gives basic information about the 53 individual population origins. Tissue Sampling and Rationale Seedlings from USPG multiplication of original propagules were used for the genetic analysis via AFLP markers. Twenty-seven seedlings of each population were grown at USPG and their tissue bulked for DNA extraction. A large number of seedlings ensures abundant supply of tissue and also is necessary to minimize sample variation in heterogeneous populations (Bamberg and del Rio 2004). This latter consideration was not important for S. fendleri, however, since it is a highly homogeneous inbred (Nybom and Bartish 2000; Bamberg and del Rio 2004; Hamrick and Godt 1990; Schoen and Brown 1991). This homogeneity within populations had the practical benefit of allowing the scoring of AFLP blanks as unique “alleles”. That is, we assumed that when a given band was observed in a population, that band was fixed, and the population did not contain the “recessive” blank allele obscured by the dominant expression of AFLPs. AFLP Bands Generation, Scoring and Documentation Genomic DNA was digested with EcoRI and MseI restriction enzymes, following the protocol described by Vos et al.


Am. J. Pot Res (2010) 87:277–284

Table 1 Population origin information Population

PI number

Site description


Elev ft

Elev m


632334 585113 592405 592406 275163 275164 564026 564028

Barfoot Park entrance road Picket Park Rustler Park Barfoot Park Rustler Park Picket Park Pinery Campground Rustler Park

2002 1994 1995 1995 1958 1958 1992 1992

8400 5680 8500 8120 8500 5680 7000 8500

CHI r 115 CHI r 117 CHI r 118C CHI r 118S CHI r 120 CHI r 121 CHI r 122 CHI r 123 CHI r 124 CHI r 125 CHI r 126 CHI r 127 CHI r 128 CHI r 130 HUA e HAW1216 HUA e HAW1209 HUA e 143 HUA e HAW1217 HUA e SBV03

636399 636401 636402 636402 636404 636405 636406 636407 636408 636409 636410 636411 636412 636414 283100 275165 641038 275167 564025

West of Chiricahua peak Between Chiricahua and Raspberry peaks Between Chiricahua and Raspberry peaks Between Chiricahua and Raspberry peaks Between Chiricahua and Sentinel peaks Between Chiricahua and Sentinel peaks Between Chiricahua and Sentinel peaks Anita Camp Between Anita camp and Cima Park Greenhouse Trail E of Cima Park North of Flys Park Saulsbury trail W from Flys Peak Centella Point Between Rustler Park and Flys Peak Wakefield mine Ramsey Canyon Lutz canyon Wakefield mine Ramsey Canyon

2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 1958 1958 2005 1958 1992


e 132 e 133 r 135 r 136 r 137 r 138

641027 641028 641030 641031 641032 641033

Scotia Canyon near Parker Lake Ida Canyon Bear Creek trail Carr Peak trail Trail 106 campsite 8400 From Bear Saddle SE

HUA r 139 HUA r 140 HUA r 141 HUA r 142 RIN e 145 RIN e BAM01 RIN e BAM06 RIN e 144 RIN e SBV01 RIN e UGR15-78 RIN r 147 RIN r 148

641034 641035 641036 641037 641040 578234 585112 641039 564024 458421 643993 643994


643995 643996 643997 643998

e e e e e e e e

r r r r

108 BAM07 BAM22 BAM23 HAW1180 HAW1204 SBV04 SBV06

149 150 151 152



2560 1731 2591 2475 2591 1731 2134 2591

31.918 32.027 31.905 31.915 31.905 32.027 31.933 31.905

−109.273 −109.360 −109.281 −109.283 −109.281 −109.360 −109.271 −109.281

9200 9000 9030 9030 9000 9000 9600 9500 9400 8800 9000 9100 9300 8800 6080 6200 6100 6300 6200

2804 2743 2752 2752 2743 2743 2926 2896 2865 2682 2743 2774 2835 2682 1853 1890 1859 1920 1890

31.847 31.838 31.838 31.838 31.821 31.832 31.845 31.851 31.859 31.862 31.890 31.873 31.881 31.892 31.403 31.438 31.378 31.405 31.438

−109.295 −109.300 −109.301 −109.301 −109.260 −109.277 −109.288 −109.288 −109.289 −109.275 −109.284 −109.288 −109.270 −109.281 −110.352 −110.318 −110.270 −110.348 −110.318

2005 2005 2005 2005 2005 2005

5500 5800 7550 8500 8400 8600

1676 1768 2301 2591 2560 2621

31.418 31.374 31.402 31.416 31.405 31.395

−110.430 −110.332 −110.327 −110.303 −110.311 −110.304

Between Bear Saddle and Pat Scott Peak Between Bear Saddle and Pat Scott Peak Between Bathtub Spring and Miller Peak Miller Peak summit Bear Campground Palisade Horse corral Near Bear Wallow Campground Near UA Observatory N Mt Lemmon Road junction Between Soldiers Camp and Summerhaven Devils Bathtub trail Devils Bathtub trail

2005 2005 2005 2005 2006 1993 1994 2006 1992 1978 2006 2006

8300 8300 8600 9460 5900 7940 7800 8200 7875 8000 7500 7560

2530 2530 2621 2883 1798 2420 2377 2499 2400 2438 2286 2304

31.415 31.420 31.396 31.393 32.373 32.410 32.423 32.416 32.448 32.440 32.197 32.197

−110.336 −110.339 −110.305 −110.293 −110.692 −110.716 −110.735 −110.733 −110.755 −110.752 −110.551 −110.548

Devils Bathtub Devils Bathtub trail Spudrock Cabin Manning Camp

2006 2006 2006 2006

7520 7560 7450 7950

2292 2304 2271 2423

32.198 32.195 32.203 32.208

−110.545 −110.542 −110.533 −110.554

Am. J. Pot Res (2010) 87:277–284


Table 1 (continued) Population

PI number

Site description


Elev ft

Elev m


643999 644000 644001 644003

Between Manning Camp and Mica Mt Between Manning Camp and Mica Mt Bonita Trail E of Mica Mountain North Slope trail E of Helen's Dome

2006 2006 2006 2006

8000 8400 8560 8200

2438 2560 2609 2499

r r r r

153 154 155 157



32.212 32.216 32.221 32.217

−110.549 −110.544 −110.539 −110.557

Population designated by mountain range (CHI, HUA, RIN), location (r, e), and collectors’ code. LAT and LON datum in WGS84. Additional details are available at the USDA Germplasm Resources Information Network (GRIN) website: http://www.ars-grin.gov/

(1995) with some modifications to detect the AFLP fragments in the LICOR 4300 System. For the pre-selective amplification, we used unlabelled primers without selective nucleotides obtained from Invitrogen (Invitrogen, USA). The 25 µL pre-selective PCR mixture contained 5 µL of four fold diluted template mixture, 50 ng of each EcoRI+0 and MseI+0 primers, 250 µM dNTPs, 10 mM Tris-HCl (pH 8.3), 1.5 mM MgCl2, 50 mM KCl, and 1 unit Taq polymerase. The cycle profile was: 94C×30 s, 56C×30 s, 72C×60 s for 20 cycles. For the selective amplification, we used primers with three selective nucleotides, EcoRI+3 and MseI+3. The EcoRI+3 primers labeled with either 700 or 800 infrared dyes were obtained from LICOR (LICOR Biosciences, USA). The selective PCR reaction

Fig. 2 Comparisons of AFLP band relationships in easy and remote locations within mountain ranges. Replication of analysis accomplished by separate generation of AFLPs in 2007 and 2008 for CHI and HUA mountain ranges as shown

mix was conducted in a final volume of 10 µL containing 5 µL of ten fold diluted pre-amplification reaction, 300 µM dNTPs, 3 ng Eco-labeled primer, 10 ng Mseunlabelled primer, and 1 unit Taq polymerase. The PCR program was the following: 94C × 2 min for initial denaturation; 94C×20 s, 66C×30 s and 72C×2 min for one cycle; annealing temperature was lowered 1C per cycle during the next ten cycles; 94C×20 s, 56C×30 s and 72C ×2 min for ten cycles; and 60C ×30 s for final extension. Scores were recorded using Saga MX GT Generation 2 Software (LICOR Biosciences, USA). The AFLP band profile of each accession was recorded in a binary matrix of bands presence (1) and absence (0) using MS Excel.


RIN e UGR15-75





HUA e HAW1209

HUA e 143




20% 15% 10%

5% 0%

CHI r 126

CHI r 124

HUA e 132

45% 40%


HUA e CHI r 130

CHI r 125


HUA e HAW1217 CHI r 121

CHI r 118S CHI r 122

CHI r 118C

CHI r 123

CHI r 117

CHI r 115

CHI r127

CHI r 128


RIN e 145

Am. J. Pot Res (2010) 87:277–284 HUA e HAW1216


CHIr Fig. 3 Variation of populations for richness in unique alleles. Values are the percentage of the indicated location’s unique alleles contained in the indicated population (only the three locations with prevalent unique alleles are shown—see Fig. 2)

Statistic of Interest Within mountain ranges (CHI, HUA, RIN), AFLP alleles (bands and blanks) were classified by location as 1) common to easy and remote, 2) unique in easy, or 3) unique in remote; and the percentage of each class was calculated. Replication Conclusions from this work depended on the assumption that AFLP patterns were consistent regardless of the particular bands examined or time at which they were generated. In 2007, 101 AFLP bands were produced on populations from the CHI and HUA mountain ranges, and subsequently in 2008 when RIN populations were available, 337 new AFLP bands were produced on all populations from all three mountain ranges. This duplication for CHI and HUA populations provided a technical replication that made it possible to assess the consistency of AFLP evidence for the relationship of bands among these populations. The proportions of each allele class in 2007 and 2008 data were compared with Newcombe’s (1998) test. Comparisons of Results from Different Mountain Ranges Newcombe’s (1998) test was used to compare the percentages

of AFLP alleles in the three classes (common to easy and remote, unique in easy, or unique in remote) among the three mountain ranges. Populations with Disproportionate Richness in Unique Alleles When easy or remote locations were identified as having unique alleles, it was of interest to examine whether populations within those locations varied for richness for those alleles. The number of within-location unique alleles was counted for each population in that location, and the total was calculated for each location. Each population’s richness in unique alleles was expressed as the percent of the total. Relationships of Alleles Among Mountain Ranges The 2008 generation of AFLPs produced loci that compared all three mountain ranges. Each allele from these loci that was unique within a location within at least one mountain range was classified by its status in the other mountain ranges: unique in (e), unique in (r), common to both (e) and (r), or missing in both (e) and (r). The percentage of these alleles falling into each classification was calculated.

Am. J. Pot Res (2010) 87:277–284


Table 2 Relationships of 282 location-unique alleles among mountain ranges CHI





m ur ur ur m c m m ur ue ue m c

m m ue m ue c ue ur ue ue m ur c

ue m ue ue ue ue m m c ue ue ue ur

40 33 39 23 30 15 13 7 6 5 5 5 4

14% 12% 14% 8% 11% 5% 5% 2% 2% 2% 2% 2% 1%

c c ue m ur ur ur c c ue m m m ur ur ur c c

ue ue m c c ue ur m ue c ue m ur c ue ur ue m

c ue m ue ue ur m ue m m c ur ur c m ue ur ur

4 4 4 4 4 4 4 3 2 2 2 2 2 2 2 2 1 1

1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1%

Suggest Documents