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Effect of Advanced Cycle Breeding on Genetic Diversity in Barley Breeding Germplasm

Dep. of Agronomy and Plant Genetics, Univ. of Minnesota, St. Paul, MN 55108; present address for F. Condón: INIA La Estanzuela, Rta 50 km 11, CC 39173, Colonia, Uruguay

^* Corresponding author (smith376{at}umn.edu).

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Plant breeding that emphasizes crosses among elite parents in a closed population (advanced cycle breeding) is presumed to decrease genetic diversity. To assess the effect of plant breeding on allelic diversity, we evaluated regional ancestors, parental lines, and cultivar candidates from the University of Minnesota six-rowed barley (Hordeum vulgare L.) breeding program between 1958 and 1998 using pedigree information, 70 simple sequence repeat (SSR) markers, and a gene specific marker. Pedigree and SSR allelic diversity indices revealed a decrease in genetic diversity, from an average of 5.89 alleles per locus in the ancestors group to 2.34 alleles per locus in the fourth decade of breeding. A correspondence analysis showed differentiation in the germplasm with time. At specific loci, we detected both reductions and no change in the number of alleles over time. Several marker loci that demonstrated a reduction in number of alleles were associated with major loci for disease resistance or malting quality and were presumably under selection during breeding. Assessment of locus-specific allelic variation across the genome in breeding germplasm should identify both the regions of the genome that should be conserved and the regions of the genome where there are opportunities to introgress new allelic diversity without disrupting desirable gene complexes.

Abbreviations: A-GD, average of genetic diversity • NSGC, National Small Grains Collection • PCR, Polymerase chain reaction • P-GD, Pair-wise pedigree genetic diversity • SM-GD, simple matching coefficient

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
PLANT BREEDING THAT RELIES on crossing of good by good parents within a single germplasm pool is known as advanced cycle breeding (Bernardo, 1998, 2002). This strategy leads to significant genetic gains in quantitative traits through the accumulation of favorable alleles and is postulated to widen the gap between elite and unimproved germplasm (Rasmusson and Phillips, 1997). Advanced cycle breeding could also increase genetic vulnerability (National Research Council, 1993), because of the loss of disease resistance genes and the evolution of plant pathogen populations, and diminish responses to selection as a consequence of the depletion of genetic diversity. As plant breeding programs mature, it will be increasingly necessary to monitor genetic diversity. A retrospective analysis of genetic diversity within a breeding program can provide information to design strategies to maintain favorable alleles and introduce novel diversity.

Molecular marker data can be used to estimate genetic diversity in breeding populations. Genetic diversity estimates over a large geographic area and various breeding programs using molecular markers in wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) have reported increases in genome-wide diversity over time (Donini et al., 2000; Christiansen et al., 2001; Parker et al., 2002; Smale et al., 2002; Koebner et al., 2003; Maccaferri et al., 2003; Khalestkina et al., 2004) as well as decreases (Kim and Ward, 1997; Russell et al., 2000; Matus and Hayes, 2002; Rousell et al., 2004). On the other hand, genetic diversity assessments within plant breeding programs are less common and have generally revealed reductions. Lu and Bernardo (2001) reported a 35% reduction in number of alleles per locus for maize (Zea mays L.) inbreds after 12 cycles of recurrent selection. Similar results were reported by Hagdorn et al., (2003) who found about a 26% reduction in genetic diversity after 15 cycles of recurrent selection in maize.

More recent studies of genetic diversity using molecular markers have made it possible to examine locus-specific changes in diversity. For example, De Koeyer et al., (1999 and 2001) reported significant frequency changes at eight RFLP loci in an oat (Avena sativa L.) recurrent selection program after seven cycles of selection and Backes et al. (2003) found reductions in allelic diversity at specific loci in European barley cultivars. Fu et al. (2003; 2005) detected no changes in genome-wide genetic diversity in Canadian oat and hard red spring wheat cultivars, but did observe a reduction in the number of alleles at specific simple sequence repeat (SSR) loci (Fu et al., 2006).

In the North American Midwest, breeding for malting barley has concentrated on a suite of traits that define malting quality and has resulted in the release of highly related cultivars (Horsley et al., 1995). Although this germplasm pool has been characterized as narrow, using pedigree (Wych and Rasmusson, 1983; Martin et al., 1991; Horsley et al., 1995; Rasmusson and Phillips, 1997;) and molecular marker data (Dahleen, 1997; Hoffman and Dahleen, 2002), significant genetic gains have been documented for traits under selection (Wych and Rasmusson, 1983; Horsley et al., 1995; Condón et al., unpublished). The widespread deployment of major durable disease resistance genes for spot blotch (causal agent Cochliobolus sativus (Ito & Kuribayashi) Drechs. ex Dastur) and stem rust (Puccinia graminis f. sp. tritici pathotype MCC/QCC) have also contributed to the narrowing of the Midwest barley germplasm (Steffenson, 1992; Steffenson et al., 1996).

Barley improvement began at the University of Minnesota in the early 1900s and was the part-time responsibility of H. K. Hayes, L. Powers, and F.R. Immer. With the arrival of D.C. Rasmusson in 1958, the breeding program began to implement advanced cycle breeding. This breeding population offers the opportunity to assess the effect of plant breeding on genome-wide and locus-specific genetic diversity in a nearly closed population. In this study, our objectives were to (i) determine genetic diversity among historical ancestors for Midwest barley breeding and elite breeding lines developed from 1958 to 1998 using pedigree and SSR data; (ii) determine the effect of advanced cycle breeding on locus-specific genetic diversity; and (iii) determine whether breeding resulted in the differentiation of breeding germplasm from their ancestors.

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Germplasm
For the molecular marker study, 98 genotypes (Table 1 ) were used, including a sample of the regional ancestors used for breeding in the North American Midwest, significant parental lines used by the Minnesota breeding program, and a representative sample of elite lines produced between 1958 and 1998. Seed was obtained from the University of Minnesota breeding program stocks and the USDA-ARS National Small Grains Collection (NSGC) maintained at Aberdeen Idaho. The regional ancestors were nine historical lines previously identified as the main ancestors for the Midwest germplasm pool (Martin et al., 1991) and from which there was seed available from the breeding program seed stock or the NSGC. The parental lines were 27 of the 34 parents that were crossed to generate the elite lines used in this study. This set was as comprehensive as possible, but to assure genetic identity, only those lines for which seed was available from the breeding program seed stock were used. Finally, the elite lines were 62 of the 108 breeding lines designated as cultivar candidates between 1958 and 1998. The elite lines were selected to represent the diversity available within the elite germplasm, avoiding sister lines, and including those most commonly used as parents in the breeding program. The elite lines included lines developed to fit the industry malting quality profile, but also included lines with a breeding emphasis on plant height (Mickelson and Rasmusson, 1994; Hellewell et al., 2000), resistance to kernel discoloration (de la Peña et al., 1999; Gebhardt et al., 1992), and high yield using European two-rowed germplasm (Peel and Rasmusson, 2000). These elite lines were assigned into four groups according to the decade in which the cross that created the line was made (Table 1). The groups were named according to the periods in which the lines were developed: EL58–67 (14 lines), EL68–77 (17 lines), EL78–87 (14 lines) and EL88–98 (17 lines). For the pedigree data study, all the genotypes included in the full pedigree were considered, including those not available for the molecular marker study.

To compare the information provided by co-ancestry and SSR data, genome-wide genetic diversity was assessed using pair-wise indices. Pair-wise pedigree genetic diversity (P-GD) was calculated as one minus the co-ancestry coefficient between all line pairs included in the study. The pair-wise genetic diversity using molecular marker data was calculated using NTSys PC 2.1 (Rohlf, 2002) as one minus the simple matching coefficient (SM-GD) (Lynch, 1990) for all the lines genotyped in this study:

where n_xy is the number of fragments that are in common between x and y, n_x is the number of bands for genotype x and n_y is the number of bands for genotype y.

Genetic diversity, for a single locus in a given group q, is calculated as:

where l is a given locus from a total of m loci, and p is the observed frequency of the u^th allele. A-GD was calculated as the average of GD across all loci using the software Powermarker (Liu and Muse, 2005) as recommended for lines in inbreeding species (Weir, 1996). Standard deviations and confidence intervals for A-GD were calculated using a bootstrapping procedure by re-sampling 10,000 times without replacement (Weir, 1996). To estimate the genome-wide change in genetic diversity over time, P-GD and A-GD were averaged among lines within the six germplasm groups. Analysis of molecular variance (AMOVA) (Excoffier et al., 1992) was conducted using the software Arlequin (Excoffier et al., 2005) to estimate the magnitude of the molecular variation among and within groups explained by the proposed groupings.

To assess the effect of breeding on the number of alleles genome-wide and at specific loci, a re-sampling permutation test as described by Fu et al. (2003) using SAS (SAS, 2004) was applied to the number of alleles observed throughout the genome and at each marker locus. This procedure was used to test the hypothesis of whether the difference between the observed and expected numbers of alleles could be due to sampling error.

To establish if the breeding process has led to the differentiation of the germplasm over time, correspondence analysis of the raw allele scores was conducted. This procedure establishes a dimensional reduction of qualitative data (Hair et al., 1998) similar to a principal component analysis, but is applicable to qualitative data. It was conducted using SAS (SAS, 2004) and the two principal components of variation were plotted for the genotypes.

	RESULTS AND DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Ancestral and Parental Base
Genetic diversity in a population can be affected by genetic drift and selection. We used pedigree information to calculate a co-ancestry matrix and estimate the contribution of individual ancestors and parental lines, including those not listed in Table 1, to the elite lines included in this study. Only a few ancestors and parental lines made a significant contribution to the elite lines studied. Six ancestors had individual contributions higher than 3% and accounted for a total of 60% of the breeding program elite lines (‘Lion’ 19%, ‘Manchuria’ 11%, ‘Oderbrucker’ 13%, ‘Trebi’ 10%, CIho7117 4%, and Mich 1807 3%) which agrees with Martin et al. (1991). Of the 34 parental lines used to generate the elite lines, seven parental lines contributed 71.4% of the breeding program elite lines (‘Trail’ 18%, ‘Dickson’ 17.7%, ‘Bonanza’, 13.5%, ‘Parkland’ 8%, ‘Larker’ 5.7%, ‘Vantage’ 4.2% and ND B112 4.2%). Of all the parental lines to which the elite lines trace, only three (‘Bumper’, ‘Bowers’, and ‘Azure’) were introduced to the breeding program in the third decade and five (Femina, Cheri, ‘Chevron’, HB627, and 63ab298732) were introduced in the fourth decade of breeding. These parental lines accounted for 0.24 and 4.2% of the parentage of the EL 78–87 and EL 88–97 groups, respectively. The narrow genetic base of the germplasm is further illustrated by a pedigree tree for the last seven malting barley cultivars released from the Minnesota six-rowed barley breeding program which includes 11 of the 27 parental lines described in this study (Fig. 1 ).

View larger version (23K): [in this window] [in a new window]   Figure 1. Pedigree from an advanced cycle breeding program including the last seven malting barley cultivar candidates released from the University of Minnesota. Bold letter names correspond to released cultivars. Boxes with thick gray border correspond to crosses made in the breeding program. Boxes without names refer to unknown intermediate genotypes. Round boxes correspond to genotypes with pedigrees not included in the figure. The different types of connecting lines are drawn to clarify the relationships among the breeding lines.

The estimates for P-GD were numerically higher than A-GD (Table 3). This difference could be due to the assumption for P-GD that regional ancestors with unknown pedigrees are unrelated. In the Midwest barley pool, this assumption would be false because breeders used reselections from mixtures of Manchurian-type barley populations found in farmers fields (Harlan and Martini, 1936). Similarities among related lines with unknown pedigrees would be revealed by SSR alleles that are identical by descent. Also, since co-ancestry does not account for selection or drift, P-GD estimates could differ from A-GD for breeding lines that are under selection.

Correlation between Molecular and Pedigree Data
We found a significant correlation between pairwise P-GD and SM-GD (r² = 0.75, p < 0.0001) based on the Mantel test (Mantel, 1967). These values were higher than those reported for triticale germplasm (Tams et al., 2004), European maize inbreds (Lubberstedt et al., 2000), and wheat (Manifesto et al., 2001; Almanza-Pinzon et al., 2003), but similar to those reported for U.S. maize inbreds (Bernardo et al., 2000). When the regional ancestors and parental lines were removed from the dataset, the correlation between P-GD and the SM-GD was reduced to r² = 0.55 p < 0.0001, indicating that the molecular data was more sensitive to the lower dispersion between the highly related elite lines. Tams et al. (2004) and Bernardo et al. (2000) found similar results for triticale germplasm and maize inbreds, respectively, indicating that pedigree and molecular information are correlated, but molecular data were more sensitive in estimating actual parental contributions.

Locus-Specific Changes in Genetic Diversity
The reduction in the number of alleles at specific loci was not uniform across the genome (Table 2). An example of this is marker Bmag877 on chromosome 3H where seven alleles were detected among the nine regional ancestors, 10 alleles were detected among the 27 parental lines, significant reductions to four and two alleles occurred in EL58–67 and EL68–77, and fixation to a single allele occurred in EL78–87 and EL88–98. In contrast, marker Bmag120 on chromosome 7H showed no evidence of selection during breeding. Evidence of change in allelic diversity starts to appear in EL58–67, with nine loci exhibiting reduction in the number of alleles (Table 2). By EL88–98, a total of twenty loci were fixed, representing 28% of the loci studied. This is similar to the 29% of loci observed to be fixed in the Illinois High Protein selection population in the 65th cycle of selection (Mikkilineni and Rocheford, 2004). Thus, we can speculate that response to selection for quantitative traits can still occur within the Minnesota six-rowed barley breeding population as has been documented in the long term maize experiment (Dudley and Lambert, 2004).

Traits under selection in the Minnesota breeding program included disease-resistance genes and multiple characteristics important for good malting quality. One example is the stem rust resistance allele at the Rpg1 locus on chromosome 7H, which has provided durable resistance to stem rust for over 40 years (Steffenson, 1992; Rasmusson and Phillips, 1997). This allele was fixed in the breeding germplasm since 1969. Near Rpg1 is a spot blotch QTL that is linked to Hvm004 (Spaner et al., 1998). The regional ancestor Manchuria and the parental line NDB 112 both carry the 193 bp allele for Hvm004. NDB 112 is the presumed source of spot blotch resistance and thus selection for spot blotch resistance could explain why the 193 bp allele is one of the two alleles remaining in the fourth decade of breeding.

Selection for favorable malting quality traits is a major focus of this breeding program. A major malting quality QTL on the short arm of chromosome 7H has been mapped, validated, and fine mapped using the Steptoe/Morex population (Han et al., 1997; Han et al., 2004). This region contains a cluster of QTL including malt extract percentage, alpha-amylase activity, and diastatic power. For this region, the 175 bp allele at Bmag110a has been fixed for the last three decades of breeding. Two markers adjacent to Bmag110a, Bmac273, and Bmag010, have one and two alleles, respectively, in the EL 88–98 (Table 2). Another malting quality region on chromosome 4H identified by Gao et al. (2004) contains the marker Hvm040 which exhibited significant reduction in number of alleles during advanced cycle breeding (Table 2). These regions that are associated with a gene or QTL that was likely under selection, provide compelling explanations for associated reduction in genetic diversity. However, the effect of genetic drift cannot be discarded as an important factor in the reduction of allelic diversity and it is not possible to determine the relative contributions of drift and selection.

There is also strong evidence for selection at other loci including Bmag877 on chromosome 3H, which has been reported to be linked to the Denso locus (Laurie et al., 1995); Hvm040 on chromosome 4H, which is also linked to an alpha amylase activity QTL in the Harrington/Morex population (Marquez-Cedillo et al., 2000) as well as the malting quality QTL mentioned above (Gao et al., 2004). The linked markers Bmag138 and Hvm067 on chromosome 4H also show a significant reduction in the number of alleles and are linked to a days-to-heading QTL (Pillen et al., 2003). The marker loci Bmag518 on 2H, Ebmac705 on 3H, Bmag808 and Bmac310 on 4H, and Bmag005 on 5H also exhibited reduction in number of alleles, but there are no obvious mapped genes or QTL that would suggest selection at these loci.

Germplasm Differentiation
AMOVA showed that 86% of the molecular variance partitioned within the six germplasm groups shown in Table 3 and 14% partitioned among groups. Differences among all pairs of groups were highly significant (p < 0.001) indicating that the genotypes within a group are more similar compared to genotypes among groups. These values are similar to the 12.5% molecular variation reported among six periods of breeding for Canadian wheat cultivars between 1845 and 2004 (Fu et al., 2005).

To further characterize the relationship among the germplasm groups, we conducted a principle correspondence analysis. The first two principle components of the correspondence analysis explained 28.4% of the total variation. The bi-plot for components one and two shows that the regional ancestors and parental lines are dispersed widely across the upper and lower left quadrants (Fig. 2 ). Most of the EL58–67 lines dispersed with the parental and regional ancestral lines. In contrast, most of the EL88–98 lines cluster together in the lower right quadrant and are separate from regional ancestors, parental lines, and EL58–67 lines. Two exceptions are MNS93 and Royal, which were selected primarily for kernel discoloration resistance and short stature, respectively. A similar analysis by Tams et al. (2004) explained 22% of the molecular variation in winter triticale cultivars, but was unable to detect grouping of germplasm based on breeding programs. Hagdorn et al. (2003) studying maize germplasm was able to observe clustering of parental and elite lines derived through advanced cycle breeding of two different heterotic groups while Duvick et al. (2004) observe clustering of maize lines according to their heterotic group using principal component analysis of 298 SSR markers. The grouping pattern observed in the Midwest ancestors and Minnesota breeding program suggests there is a growing gap between the contemporary elite breeding germplasm and its ancestral base that is occurring simultaneously with a reduction in genome-wide genetic diversity.

View larger version (12K): [in this window] [in a new window]   Figure 2. Biplot for the PC1 and PC2 of the Correspondence analysis. Gray solid circles are the regional ancestors, open circles are the parental lines, black solid triangles are EL58–67, open triangles EL68–77, gray solid squares EL78–87, black solid squares EL88–98. Oblong circles enclose at least 80% of lines in EL58–67 and EL88–98.

Another potential benefit of examining genetic diversity of breeding programs would be to implement the identification of QTL within breeding germplasm using association genetics (Yu et al., 2006). Association mapping in breeding germplasm would favor the identification of desirable alleles that are free of linkage drag often associated with the introduction of exotic sources of genetic diversity. The approach of association mapping within advanced cycle breeding populations may offer the opportunity to maintain genetic gains using MAS without the need to introduce novel alleles.

	ACKNOWLEDGMENTS

 
We thank the American Malting Barley Association and INIA Uruguay for support of this research.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
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Received for publication November 26, 2007.

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