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a Dep. of Agronomy, Univ. of Wisconsin-Madison, WI 53706-1597 USA
b USDA-ARS, U.S. Dairy Forage Research Center, 1925 Linden Dr. West, Madison, WI 53706-1108
* Corresponding author (mdcasler{at}wisc.edu).
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ABSTRACT |
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 TOPNOTES ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Abbreviations: IVDMD, in vitro dry matter digestibility • MAS, marker-assisted selection • NDF, neutral detergent fiber • PCR, polymerase chain reaction • QTL, quantitative trait loci • RAPD, random amplified polymorphic DNA
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INTRODUCTION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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A forage sample consists of a cell-contents fraction soluble in neutral detergent and an insoluble cell-wall fraction (neutral detergent fiber, NDF), largely containing cellulose, hemicellulose, pectin, and lignin. The concentration of NDF is the single most effective laboratory predictor of an animal's ability to consume a forage ad libitum (Van Soest, 1994). However, it is not clear whether the mechanism of intake is regulated by negative feedback from ruminal tract distension due to the high bulk density of high-fiber forages (physiological regulation) or hormonal signals indicating satiety, a fulfilling of current nutritional requirements (metabolic regulation) (Van Soest, 1994). The concentration of NDF is the most common selection criterion to improve the intake potential of forage crops. Also, preference or palatability has been found to be associated with low fiber concentration and high digestibility (Falkner and Casler, 1998; Gangstad, 1964).
Genetic studies and germplasm research through intensive selection and breeding efforts have provided a solid scientific basis for improving forage quality of smooth bromegrass. However, selection designs have been inefficient in estimating independently the effects of some nutrients or constituents on forage nutritional value or separating negative associations between some forage quality traits and forage yield or disease resistance (Casler, 2001; Casler and Vogel, 1999). Therefore, a long-term divergent selection program for NDF was undertaken initially to create more variability in smooth bromegrass populations, and to establish relatively unconfounded populations differing in NDF concentration capable of addressing some important genetic and breeding questions.
Over time and selection cycles, population phenotypes change as a result of changes in the frequencies of favorable alleles. Allele frequencies may change as a result of selection or drift. Selection responses will occur for alleles under direct selection pressure and those within their linkage blocks. Although most molecular markers are considered to be selectively neutral, changes in marker frequencies associated with changes in population performance have been reported (Keithley and Bulfield, 1993; Ollivier et al., 1997; Stuber and Moll, 1972; Stuber et al., 1980). Consistent frequency changes in molecular markers, without effects of drift, may be a mechanism to identity linkages between markers and quantitative trait loci (QTL), potentially improving selection efficiency.
The objectives of this study were (i) to create divergent populations for NDF concentration and (ii) to identify RAPD marker changes during two cycles of divergent selection for NDF concentration, for eventual application of MAS to improve the efficiency and cost-effectiveness of phenotypic selection for reduced NDF concentration.
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MATERIALS AND METHODS |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Selection for Neutral Detergent Fiber—Cycle 1
Cycle 1 was completed by Casler (2002). Seed of the four germplasm pools was planted in early spring 1991 in the greenhouse. Three hundred 70-d-old seedlings for each population were transplanted to the field in a spaced-plant nursery on 1.0-m centers on a Plano silt loam (fine-silty, mixed, mesic Typic Argiudoll) in May 1992 at Arlington Agricultural Research Station, WI (Casler, 2002). Four germplasm pools were planted in separate selection nurseries with 4 m between germplasm pools. Plants within each population were arranged in ten blocks of 30 plants each, with a spacing of 0.9 m between all adjacent plants. Weeds were controlled by pre-emergence herbicide applications (Falkner and Casler, 1998). Plants were fertilized with 112 kg N ha–1 in late June.
A leaf tissue sample was clipped from each plant at a vegetative growth in mid-August 1992, with a stubble height of 10 cm. Tissue samples were placed in paper bags and dried at 55°C. Dried samples were ground through a 1-mm screen of Wiley-type mill and reground through a 1-mm screen of cyclone mill. Two independent subsets of each sample were scanned on a near-infrared reflectance spectrophotometer (NIRS). Two random plants from each block of each population comprised a stratified random subset of 80 plants that was subjected to wet-laboratory analysis. Concentration of NDF was determined using the procedure of Van Soest et al. (1991), omitting the 
-amylase step. Data on NDF of the 80-plant subset were used to calibrate the NIRS for prediction of the entire set of 2400 scanned samples (four germplasm pools x 300 plants x two scanned subsets). Means over the two scanned subsets of each sample were computed before selection. Some field and laboratory variability was removed from the estimates of plant phenotypes by processing samples in numerical order and computing t scores to adjust for differences among block means (Casler, 1992): tj = (Xij – Mj)/sj, where tj is the t score for NDF of the ijth plant, Xij the raw datum for the ijth plant, Mj the mean of the jth block, and sj the standard deviation of the jth block.
Ten plants within each population were selected in spring 1993 from the selection nursery as the most extreme plants in two categories: high NDF and low NDF. Each group of ten selected plants were transplanted into a four-replicate crossing block using 60 cm plant spacing. During an 8- to 12-d period of anthesis, pollen from plants was wind-dispersed among selected plants in each crossing block. The crossing blocks were isolated at the Arlington Agricultural Research Station by at least 100 m from each other and from other smooth bromegrass to avoid contamination. The crossing blocks were fertilized in spring at the rate of 56 kg N ha–1.
One cycle of divergent selection for NDF concentration in four germplasm pools (WB19e, Alpha, WB88S, and Lincoln) was completed with the harvest of seed from individual clones in each crossing block in August 1993 (Casler, 2002). Seed for each clone was individually harvested, dried, cleaned, and weighed. Balanced bulks of seed were made for each population. Selected germplasm pools were identified as C-1 (low NDF) and C+1 (high NDF).
Selection for Neutral Detergent Fiber—Cycle 2
Seed from the C-1 and C+1 cycles of all four germplasm pools generated in the first cycle, was germinated in January 1996 in the greenhouse. Three hundred fifty seedlings from each population were transplanted to the field at Arlington on a Plano silt loam (fine-silty, mixed, mesic Typic Argiudoll) in May 1996 in a spaced-plant nursery on 1.0-m centers. Eight populations were planted in separate selection nurseries with 4m between populations, and plants within each population were arranged in ten blocks of 35 plants each, with a spacing of 1 m between all adjacent plants. Plants were mowed twice during the establishment year. Weeds were controlled with herbicide (Falkner and Casler, 1998). Plants were fertilized with 112 kg N ha–1 in late June and sampled for laboratory analysis.
Neutral detergent fiber was determined on a random sample of approximately 20 tillers clipped from each of the 350 plants of each population in May 1997 at a 9-cm stubble height. Plants were approximately 20 to 30 cm tall and consisted entirely of leaves. Thirty-five plants were harvested from each block and always processed together throughout the drying, grinding, and laboratory processes. Plant samples were placed in perforated paper bags, dried at 55°C, ground through a 1-mm screen in a Wiley-type mill, reground through a 1-mm screen in a cyclone mill to improve their particle size uniformity, and scanned by NIRS. An 80-plant calibration set was chosen, analyzed for NDF concentration, and used to predict NDF for the remaining samples as described for Cycle 1. The only change from Cycle 1 was the method of choosing the calibration set, which was based on a cluster analysis of the samples, using their individual wavelength reflectance data (Shenk and Westerhaus, 1991).
Ten plants within each population were selected in spring 1998 from the selection nursery as the most extreme plants in two categories: high NDF and low NDF. Each group of 10 selected plants were transplanted into a four-replicate crossing block using 60 cm plant spacing. The crossing blocks were isolated at the Arlington Agricultural Research Station by at least 100 m from each other and from other smooth bromegrass to avoid contamination. The crossing blocks were fertilized in spring at the rate of 56 kg N ha–1.
Two cycles of divergent selection for NDF concentration in four germplasm pools (WB19e, Alpha, WB88S, and Lincoln) were completed with the harvest of seed for the second cycle of selection in July 1999. Seed for each clone was individually harvested, dried, cleaned, and weighed. Balanced bulks of seeds were made for each population. Selected populations were identified as C-2 (low NDF) and C+2 (high NDF).
Field Experiment
Seedlings of 20 populations (C-2, C-1, C0, C+1, and C+2 for each of the four germplasm pools) were transplanted in the field in May 2000. The field experiment was established at Arlington, WI, [43°20' N, 89°23' W; Plano silt loam (fine-silty, mixed, mesic Typic Argiudoll)] and Marshfield, WI, [44°40' N, 91°53' W; Withee silt loam (fine-loamy, mixed, frigid, Aeric Glossoboralf)]. The experimental design was a randomized complete block with four replicates at each location. Plot size was 1 x 3 m with 30 plants per plot and 30-cm centers. Weeds were controlled with herbicide (Falkner and Casler, 1998). Field plots at each location were fertilized with 112 kg N ha–1.
In 2001, field plots at Arlington and Marshfield were fertilized with 112 kg N ha–1 in April and June. Forage samples were hand-clipped at a 9-cm stubble height in May (immediately after heading) and August (vegetative growth stage, with 3 to 4 nodes per sterile culm), by taking a small sample of tillers from within each of thirty 0.3 x 0.3-m grids. Samples were dried at 55°C and ground to pass through a 1.0-mm screen in a wiley-type mill and a cyclone mill. Samples were analyzed for NDF concentration by NIRS as described for the Cycle-2 selection phase (80 samples in the calibration set).
DNA Isolation
Seed from the C-2, C-1, C0, C+1, and C+2 cycles divergently selected for NDF from all four germplasm pools was germinated in the greenhouse in 1999. A random sample of seedlings from the 20 populations were maintained in the greenhouse for RAPD marker analysis. The RAPD marker data and NDF data were collected on different random samples of plants from the 20 populations because we felt it was important to save the RAPD-genotyped plants for use in future studies. Because of the rhizomatous nature of smooth bromegrass, this would have been impossible with plants transplanted to the field.
DNA was extracted from 14 to 25 individual seedlings from each population as described by Skroch and Nienhuis (1995). Approximately 0.5 to 0.75 g of fresh tissue was harvested and ground with 500 µL of potassium ethyl xanthogenate (PEX) (Sigma-Aldrich, St. Louis, MO) at maximum speed of 5.0 m s–1 for 40 s with the Bio 101 (Vista, CA) Savant FP120 Fast PrepTM. After grinding, tissue was transferred to centrifuge tubes and allowed to incubate for 30 min in a 65°C water bath. After organic and aqueous phases of the extraction mixture were separated by centrifugation (Eppendorf 5415C microfuge), nucleic acids were precipitated by adding a 6:1 mixture of 95% (v/v) ethanol and 7.5 M ammonium acetate. After removing RNA (with 100 µg/mL RNase A for 1 h at 37°C) and any remaining debris, DNA was reprecipitated by the addition of 10:1 solution of ethanol and 3 M sodium acetate. After a 70% (v/v) ethanol wash and pelleting, DNA was hydrated in TE buffer (1 mM Tris, pH = 8.0, 0.1 mM EDTA, pH = 8.0). DNA concentrations were quantified in a logical numerical order with a Hoefer Scientific TKO-100 Fluorometer (Amersham Pharmacia Biotech, Piscataway, NJ).
RAPD Reactions
RAPD reactions were performed as described in Johns et al. (1997) in an M.J. Research, Inc. (Wattham, MA) PTC-100 Programmable Thermal Controller. Cycling temperature settings were 91°C for denaturation, 42°C for annealing, and 72°C for elongation. In the first cycle, cycling times were 60 s for denaturation, 15 s for annealing, and 70 s for elongation. During the subsequent 39 cycles, denaturation was set for 15 s, annealing for 15 s, and elongation for 70 s.
Polymerase chain reaction (PCR) amplifications were performed in a final reaction volume of 10 µL, containing the following reaction buffer: 50 mM Tris, pH 8.5, 20 mM KCl, 2 mM MgCl2, 500 µg/mL of bovine serum albumin (BSA), 2.5% (w/v) ficoll 400, and 0.02% (w/v) xylene cyanol. Reactant concentrations were 100 µM dNTPs (deoxy nucleotide triphosphates) (Promega, Madison, WI), 2 ng/µL of DNA template, 0.4 µM of decamer primer Operon Technologies, Inc. (Alameda, CA) and University of British Columbia, (Vancouver, BC, Canada), and 0.6 unit (5 units/µL) of Taq DNA polymerase (Promega, Madison, WI). All RAPD reaction products were electrophoresed in 20 x 25 cm, 1.5% (w/v) agarose gels in 1x TBE (Tris, Boric Acid, EDTA) buffer. Gels were run for 2 h at 300 V in Gibco/BRL Life Technologies (Invitrogen, Carlsbad, CA) H4 gel apparatus, stained with ethidium bromide, and illuminated by UV light and subsequently photographed with Polaroid 667 film.
Primer Screening
To enhance the probability of detecting a relationship between RAPD marker frequencies and NDF selection responses, primers were prescreened for a correlation between band frequencies and NDF concentration. Seventeen RAPD primers used by Diaby and Casler (2003) were evaluated by correlation analysis with NDF data from 27 smooth bromegrass populations, obtained from Casler et al., 2000). The four original populations included in this study were also included in the study of Casler et al. (2000). Seven primers had a relatively high frequency of polymorphic bands that had frequencies correlated with NDF concentration of the 27 populations (0.35 < |r| < 0.65). These primers (A09, A18, AE12, AF06, AF14, and AG14 from Operon Technologies Inc., Alameda, CA, and UBC318 from University of British Columbia, Vancouver, BC, Canada) were used on the 433 plants of this study, generating 83 polymorphic RAPD markers. The frequency of each marker (scored as "1" for presence of the band or "0" for absence of the band for each individual plant and stored as a binary matrix) was computed for each of the 20 populations.
Data Collection and Statistical Analysis
Field-plot NDF values over two harvests and two locations were analyzed by general linear models analysis of variance (SAS, 1999). Replicates and locations were assumed to be random effects, while populations, cycles, and harvests were fixed effects. Linear regression for mean divergent selection responses and contrasts for the linear effect of selection cycles (cycles-linear) were computed in the four germplasm pools. Significance of linear regressions were tested by contrasts in the analysis of variance.
From the 83 polymorphic RAPD markers transformed into a binary matrix, a pairwise Jaccard similarity coefficient matrix was computed by NTSYS-PC 2.01 (Rohlf, 1997) on all individuals across populations. The similarity matrix Sij (similarity between individual plants i and j) was converted to a Euclidean distance matrix by the elementwise formula: (1 – Sij)0.5. Euclidean distances, converted from Jaccard similarity coefficients, were used as the measure of genetic distance between all individuals.
Analysis of molecular variance (AMOVA; Excoffier et al., 1992; Schneider et al., 1997) was performed on all individuals, partitioning the Euclidean distance matrix into three sources of variation: among populations, among cycles within populations, and plants within populations and cycles. Variance components were estimated by equating AMOVA mean squares to their expectations. Variance components were tested by nonparametric permutation tests (Schneider et al., 1997). Cluster analysis, based on the unweighted pair-group method of arithmetic averages (UPGMA; SAS, 1999) was used to construct a distance dendrogram for the 20 populations.
Divergent selection for NDF utilized only additive genetic variation for NDF, and linear regressions of phenotype or marker frequencies across selection cycles are measures of additive effects (slopes) and additive genetic variation (variance due to regression) (Falconer and Mackey, 1996). Moreover, selection for NDF concentration was practiced in divergent directions, under the same effective population sizes and selection intensities. Therefore, the effects of drift and selection are largely independent across selection cycles. The effect of drift, measured as asymmetry of selection responses about the base population mean (Casler, 1999; Clayton et al., 1957; Falconer, 1953), is orthogonal to the linear effect of selection in this selection scheme. Nevertheless, to increase the rigor of the marker selection process, statistical procedures developed by Wilson (1980) were used to test whether fluctuations in frequencies from cycle to cycle could be attributed to genetic drift alone or whether divergent selection had occurred. Linear trends were tested by chi-square tests incorporating sampling variation due to restricted population size and restricted number of plants sampled for genotypic analysis. If significant deviations from random drift were detected, and significant directional changes as represented by linear trends were observed, then evidence would be judged sufficient to suggest that the particular marker locus may be linked to one or more loci affecting NDF.
Finally, RAPD marker regressions on cycle number were tested for homogeneity across germplasm pools, by contrasts within a generalized linear model (GENMOD) for binomial data (SAS, 1999). The LOGISTIC procedure (SAS, 1999) was used to fit a linear regression model for binary data to selected markers by maximum likelihood estimation.
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RESULTS |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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At least one germplasm pool had a significant drift effect for seven of the eight markers (Table 5). Often the significance of drift caused the chi-square test for linear selection response to be nonsignificant. Only one marker, AG14.0825, had nonsignificant drift effects (P > 0.10) and significant linear selection response (P < 0.05) for all four germplasm pools. This marker also had the most consistent and linear logistic regressions. The linearity, consistency, and goodness-of-fit of these selection responses is demonstrated in Fig. 5 .
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DISCUSSION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The large within-population variation observed for all germplasm groups reflected the outcrossing mode of reproduction and probably the complex genome organization of smooth bromegrass (Armstrong, 1979). The variation partitioned between and within populations is dependent on the material under study and on the breeding system of the species. The patterns of variation observed in this study were similar to those found in several outcrossing grass species, including smooth and meadow bromegrass (Bromus riparius Rehm.) (Ferdinandez et al., 2001), blue grama (Bouteloua gracilis [H.B.K.] Lag. ex. Steud.) (Phan, 2000), buffalograss (Buchloë dactyloides [Nutt.] Engelm) (Peakall et al., 1995), and perennial ryegrass (Lolium perenne L.) (Huff, 1997) where within-population variation was much higher than between-population variation.
Despite the large amount of within-population variation, variation among cycles was significant, indicating genetic differentiation among populations divergently selected for NDF for each smooth bromegrass germplasm pool. The high genetic similarity of WB19e with Alpha and Lincoln as revealed by AMOVA was not surprising, because Alpha and Lincoln represent half of the pedigree of WB19e. The relatively large intergroup variation values for all the WB88S comparisons confirm the unique nature of this germplasm pool relative to the other three germplasm pools in this study. WB88S is a wild germplasm and represents the meadow climatype of smooth bromegrass, while the other three germplasms are cultivated forms of the steppe climatype of smooth bromegrass. The meadow and steppe climatypes of smooth bromegrass are phenotypically and genetically distinct from each other (Casler et al., 2000; Diaby and Casler, 2003).
Genetic changes due to selection were confirmed by genetic distance analyses. The tendency of high-NDF or low-NDF populations to cluster together, particularly Cycle-1 and Cycle-2 populations within common germplasm pools, suggested that rapid changes occurred as a result of selection and/or drift. Furthermore, these pairs of consecutive cycles within the cluster dendrogram suggested that some RAPD markers were linked to QTL for NDF and that changes in RAPD marker frequency, in some cases, were a direct result of selection on linkage blocks. Each additional cycle of selection resulted in an average 0.024 increase in genetic distance between pairs of cycles. Conversely, the relatively large genetic distances between germplasm pools, regardless of the cycle of selection, suggested that these linkage blocks were rarely collinear across germplasm pools. Furthermore, the increase in genetic distances in both the high-NDF and low-NDF directions suggested that the four germplasm pools were more divergent after selection than before selection. Differential linkage disequilibria across the four germplasm pools is the most likely explanation for this observation. Selection appears to have acted on different markers in each germplasm pool, largely based on differential linkage relationships with QTL for NDF.
Development of reliable linkage maps in most forage crops (complex polyploids with polysomic inheritance) is more complicated than in simple diploids. Furthermore, because of differences in linkage relationships and allelic composition, linkage maps have limited usefulness across different populations and germplasms (Lübberstedt et al., 1997; 1998). Identification of individual markers associated with high-NDF vs. low-NDF plants within an array of germplasms could facilitate MAS in highly heterogeneous populations of cross-pollinated smooth bromegrass, without the need for a linkage map.
Phan (2000) found four RAPD bands from four different primers that distinguish between original, ecovar, and cultivar populations of blue grama on the basis of differences in the band frequencies among the assayed populations. In the present study, among the eight most discriminating bands across selection cycles, only one marker, AG14.0825, had R2 values sufficiently high for all four germplasm pools that it might serve as a selectable marker for NDF concentration in all four germplasms.
This study confirms the potentially strong effect of drift due to restricted effective population size (Kahler, 1983; Guse et al., 1988; Falconer, 1953). However, linear responses for marker AG14.0825, after accounting for drift, were significant across all four germplasm pools of smooth bromegrass. These significant linear trends observed across all germplasm pools through cycles could be attributed to divergent selection for NDF concentration. Furthermore, the linear selection response, due to change in allele frequency of this marker, accounted for 86 to 96% of the variation among cycles.
The remaining markers showed some selection responses, but were inconsistent or had weak linear trends across germplasm pools, implying that they were specific for a subset of germplasm pools or there may be unknown factors accounting for the variability observed for some markers. The majority of markers showing inconsistency in their linear trend across all germplasm pools suggest the presence of variable levels of association between markers and QTL for NDF in the four germplasm pools of smooth bromegrass. Germplasm pools may have differed in the number of linkage blocks dragged from one cycle to another during selection for NDF concentration. Chromosome blocks containing QTL for NDF were variable among germplasm pool genomes, reflecting probably different forms of alleles in the complex biochemical pathways that contribute to NDF accumulation.
In a randomly mating population, only polymorphisms with extremely tight linkage to a locus with phenotypic effects are likely to demonstrate significant marker-QTL associations (Falconer and Mackay, 1996; Weir, 1996; Labate et al., 2000). In this study, the logistic regression revealed evidence for different levels of association between markers and potential QTL for NDF concentration across four germplasm pools of smooth bromegrass. Neutral detergent fiber appears to be under the control of many effective factors in the smooth bromegrass genome. The NDF fraction consists of several compounds—lignin, cellulose, hemicellulose, proteins, pectins, and minerals—with complex chemical composition and biosynthetic pathways (Casler, 2001; Boudet et al., 1995). Changes in most of these compounds could lead to changes in NDF concentration. Moreover, the germplasm pools of smooth bromegrass used in the divergent selection experiment have different genetic backgrounds, contributing to variable linkage disequilibrium states and variable allele frequencies. Identification of QTL for ADF (acid detergent fiber, closely related to NDF) was strongly dependent on the tester used to create maize (Zea mays L.) testcrosses, showing almost no correspondence in QTL across testers (Lübberstedt et al., 1997).
This is the first report of association of a quantitative character with a molecular marker gene locus in smooth bromegrass. A statistically significant association of QTL for NDF with the presence of a marker indicates either that the marker locus resides within a QTL for NDF (pleiotropy) or that the marker locus is linked with one or more QTL for NDF. The strength of the association of a marker with a QTL depends on the degree of linkage and of the size of the effects of the QTL alleles. The consistency of linear responses to marker AG14.0825 among germplasm pools and the lack of drift effects for this marker suggest that it may be pleiotropic with a QTL for NDF concentration, although this is relatively improbable.
In conclusion, we identified several dominant PCR-based markers potentially detecting QTL for NDF concentration in selected populations of smooth bromegrass. Although RAPD markers can be applied in high throughput analyses required by most breeding programs, they are dominant markers and their reaction sensitivity may be an impediment where methodological conditions cannot be repeated or when the genotype scoring process is subject to error. The conversion of RAPD bands to sequence characterized amplified repeats (SCAR) markers will provide more specific and stable markers. Using a combination of SCAR markers, developed from this study, and codominant markers to identify linkage relationships, it should be possible to create interval maps of putative QTL for NDF within each germplasm pool and to utilize these QTL in a marker-selection or MAS program.
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ACKNOWLEDGMENTS |
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NOTES |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Received for publication October 8, 2003.
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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