Crop Science Journal of Natural Resources and Life Sciences Education
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Published in Crop Sci 39:1652-1657 (1999)
© 1999 Crop Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (26)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Orf, J.H.
Right arrow Articles by Lark, K.G.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Orf, J.H.
Right arrow Articles by Lark, K.G.
Agricola
Right arrow Articles by Orf, J.H.
Right arrow Articles by Lark, K.G.
Crop Science 39:1652-1657 (1999)
© 1999 Crop Science Society of America

CROP BREEDING, GENETICS & CYTOLOGY

Genetics of Soybean Agronomic Traits

II. Interactions between Yield Quantitative Trait Loci in Soybean

J.H. Orfa, K. Chaseb, F.R. Adlerb, L.M. Mansurc and K.G. Larkb

a Dep. of Agronomy and Plant Genetics, Univ. of Minnesota, St. Paul, MN 55108 USA
b Dep. of Biology, Univ. of Utah, Salt Lake City, UT 84112 USA
c Facultad de Agronomia, Universidad Catholica de Valpariso, Casilla 4-D, Quillota, Chile

orfxx001{at}maroon.tc.umn.edu


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 Materials and methods
 Results
 Discussion
 REFERENCES
 
In order to breed efficiently, it is necessary to identify individual quantitative trait loci (QTLs) as well as interactions between these loci and to determine which QTLs produce phenotypes that are environment specific. This can be done by linking QTLs to molecular markers. The objective of this research was to carry out such an analysis for yield, one of the most complex agronomic traits. To do this, recombinant inbred lines of soybean [Glycine max (L.) Merrill] were characterized for molecular genetic markers and analyzed for yield in different environments. Interactions between QTLs were identified by subdividing the segregants into four sub-populations defined by molecular alleles at pairs of unlinked loci. Differences in the mean yields of these sub-populations defined interactions between QTLs. Measurements of yield in genotyped, recombinant inbred populations derived from crosses of `Minsoy' with `Archer' (MA population) and `Noir 1' with Archer (NA population) have identified a pair of interacting yield QTLs whose effect was independent of environment as well as a pair of loci whose interaction was environment specific. Each example of epistasis, involved an allele specific interaction between the two QTLs. In the NA population, a pair of QTLs was identified in which Noir 1 alleles interact to specify a significant increase in yield that is not environment specific. These loci, located on linkage groups (LG) U3 and U9, do not affect either height or maturity. In all environments, the interaction between the QTLs was significant. In the MA population, a pair of QTLs was identified in which the Minsoy alleles interact to specify a significant increase in yield. However, this significant interaction is environment specific. One of the loci (on LG U14) is also associated with effects on height, seed weight, and maturity that are found in other environments, but these latter effects do not appear to involve any interactions with other loci. The data from the MA population support the concept that interactions between QTLs also can result in location-specific effects on quantitative traits.

Abbreviations: cM, centimorgan • QTLs quantitative trait loci • RI, recombinant inbred • RFLP, restriction fragment length polymorphism • SSR, simple sequence repeat


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
Materials and methods
 Results
 Discussion
 REFERENCES
 
BREEDING TO IMPROVE AN AGRONOMIC TRAIT

is difficult when the trait is genetically complex with low heritability or if the assay for the trait is laborious or expensive (Jinks, 1981). Identifying individual genetic components, QTLs, which contribute to the trait can simplify this task (Dudley, 1993). The process can be further simplified by the use of marker selection (Tanksley et al., 1989).

In marker selection, a closely linked, easily identified, qualitative genetic marker is used as a surrogate for the QTL being introgressed. By tracing the appropriate allele of this surrogate marker extensive field testing can be avoided during the backcrossing required to introduce the desired QTL allele. For this process to be effective, it is important that the QTL in question function independently of the genetic background in which it is located or that interactions with other genetic loci can be defined and those loci identified. Recently, we have presented evidence suggesting that epistatic effects may be common in soybean (Lark et al., 1995). We also have described a method for identifying interactions and locating the loci involved (Chase et al., 1997).

Yield is one of the most important agronomic traits, but it is also one of the most difficult to study (Brim, 1973). Its assay is laborious and it integrates many physiological processes that may have complex underlying genetics. Identification of surrogate molecular genetic markers linked to yield QTLs can simplify such assays and lead to an increased understanding of the genetic basis for yield. The objective of this research was to identify genes that control yield and the interactions between such genes.


   Materials and methods
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
Results
 Discussion
 REFERENCES
 
Descriptions of the experimental conditions and methods used to obtain the data are presented elsewhere (Orf et al., 1999). Those include the field conditions used to measure the traits, analysis of correlations between traits, the measurement and mapping of molecular markers, as well as mapping of QTLs and estimating their significance. Briefly, the segregant populations consisted of 233 recombinant inbred (RI ) lines derived from the parents Minsoy and Archer (MA population) and 240 RI lines derived from the parents Noir 1 and Archer (NA population). The F7-derived RI lines were evaluated in four environments for several traits including height (HT), flowering date (R1), maturity (R8), reproductive period (RP, measured as R8-R1), seed weight (SW), yield (YD) and seed number (YD/SW). The field conditions used to measure these traits were described in detail in the preceding paper (Orf et al., 1999). Plots were considered mature (R8) when 95% of the plants in the plots had pods that were their mature color. Yield was measured on plots 1.54 m wide by 3.7 m long end trimmed to 2.4 m. A small plot combine was used for harvesting.

Correlation between trait values for the individual RI lines was determined as described by Press et al. (1996). Each RI segregant also was characterized for a large number (>400) of molecular genetic markers (Orf et al., 1999) and a composite genetic map constructed. QTLs for the traits were determined by linkage to these markers using interval mapping (Lincoln and Lander, 1993; Utz and Melchinger, 1996). The methodologies used for evaluating interactions between QTLs (lack of additivity) also have been presented in detail previously (Chase et al., 1997). Beginning with identified QTLs, interacting QTLs were sought with the computer program Epistat. Epistat was used to evaluate the interactions (as lack of additivity ) and to create graphic comparisons of sub-populations. Epistat can be obtained electronically from the website www.larklab.4biz.net (verified 13 May 1999).

Heritabilities were calculated as described by Hanson et al. (1956). Heritable variation was calculated by two-way ANOVA where one factor was the RI genotype and the other was the environment (SAS, 1988).


   Results
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results
Discussion
 REFERENCES
 
An Interaction between QTLs for Yield Occurring Across Environments
As described by Orf et al. (1999), several QTLs for yield were identified with segregants from the recombinant inbred population (NA) derived from a cross between Noir 1 and Archer. In Fig. 1 , we present evidence for the presence of a yield QTL, linked to Satt277 in LG U9. Table 1 presents segregation data for height, maturity, and yield linked to this marker. As can be seen, the Noir 1 allele is associated with high yield accounting for an average increase of 172 kg/hectare. The QTL identification was highly significant (P = 0.0000005). In contrast, Satt277 is not significantly associated with variation for height or maturity.



View larger version (30K):
[in this window]
[in a new window]
  		Fig. 1 Yield (—) and maturity (R8) (- -) LOD scores graphed across the linkage maps of U9 and U3 by simple interval mapping. LOD scores (y-axis) are graphed against genome position (x-axis). Molecular markers on the linkage groups are shown. (Additional markers can be obtained from website http://www.larklab.4biz.net/; verified 13 May 1999) LOD scores above 3.7 are significant at an experiment-wide threshold of 0.05

 

View this table:
[in this window]
[in a new window]
  		Table 1 Segregation data averaged over three environments for different traits associated with the marker Satt277

 
Figure 1 also presents data for the variation in yield or maturity associated with LG U3. No significant loci could be identified (all LOD < 2). However, the region linked to locus B172_2 and Satt315 in this linkage group controls the variation in yield associated with Satt277, as can be seen by examining the four genotypes corresponding to the Noir 1 or Archer alleles at the two marker loci (Fig. 2) .



View larger version (32K):
[in this window]
[in a new window]
  		Fig. 2 Segregation of yield QTLs linked to Satt277 and B172_2 — sub-populations corresponding to the two alleles at each locus or to each of the four alleles of the pair of interacting loci. The average of three environments is shown in (a) as well as the values for each of the three individual environments in (b, c, and d). For each panel (1–4) the plants in each allelic sub-population are ranked along the y-axis according to increasing yield value (x-axis). Panels 1 and 4 show the two allelic sub-populations at the Satt277 or B172_2 loci respectively. An open triangle represents the sub-population with the Noir l allele and a closed triangle represents the sub-population with the Archer allele. Panels 2 and 3 show the four allelic sub-populations corresponding to segregants at both loci: (•) Archer allele of B172_2 and Noir allele of Satt277; ({circ}) = Archer allele of both; ({blacksquare}) = Noir1 allele of both; ({square}) = Noir allele of B172_2 and Archer allele of Satt277

 
Figure 2 presents the segregation of yield in the four genotypes associated with Satt277 and B172_2. Figure 2a presents the results from averaging two reps at three locations. The results from individual locations are shown in Fig. 2b through d. The outer panels show the striking difference in the mean yield associated with Noir 1 or Archer alleles of Satt277 (Panel 1) and the lack of difference associated with the parental alleles at locus B172_2 (Panel 4). The inner panels present yield for the four genotypes involving both loci. In the presence of the Noir 1 allele of B172_2, segregants with the Noir 1 allele at Satt277 have a much larger yield than those with the Archer allele (Fig. 2, Panel 3). In contrast, no difference in yield is observed between Satt277 segregants which carry the Archer B172_2 allele (Fig. 2, Panel 2). By analysis of variance, we have found that the segregation of yield associated with Satt277 accounts for 16.2% of the heritable variation in the NA population. This variation is conditional upon the presence of the Noir 1 allele of B172_2. The significance of this interaction has been calculated (employing "Epistat" and simulation techniques [Chase et al., 1997]) as P < 0.000001 (P ~ 3.3 x 10-11), where P is the probability that this result would be observed if the two loci acted additively and independently.

The same pattern of epistasis is observed in all locations. Although the heritability of yield (h2 = 71%) is reasonably high, correlation coefficients between yield and maturity in different locations (Table 2) varied considerably. Yield was not correlated with maturity (R8) in Chile or Minnesota 1997 (MN '97). It was negatively correlated with R8 in Minnesota 1996 (MN '96). That is, an unusual environmental condition existed in MN '96 such that early maturing plants tended to have higher yields. Despite this, epistatic effects were observed in 1996 (Fig. 2c). In summary, the QTL linked to Satt277 accounts for 16% of the heritable variation in yield, is operational in different environments, is conditional in all environments on a QTL linked to B172_2, and may either be independent of maturity or have a preferential effect on early maturing plants as in Minnesota 1996.


View this table:
[in this window]
[in a new window]
  		Table 2 Correlation coefficients between maturity (R8) and yield (YD) for different locations

 
An Interaction between Yield QTLs Which Is Restricted to One Environment
Another QTL for yield was identified in the Minsoy-Archer (MA) RI population linked to Satt561 in LG U14 (Table 3) . However, this QTL was identified only in the field tests in Minnesota in 1997 (Table 3). This region of the genome also is associated with QTLS for height (HT), seed weight (SW), maturity (R8), and flowering date (R1).


View this table:
[in this window]
[in a new window]
  		Table 3 Segregation data for different traits in Minnesota 1997 associated with the markers Satt561 and Satt507

 
Major QTLS for height and seed weight had already been observed in the MA population in different environments (Orf et al., 1999) and QTLs for R1 and R8 had been observed in this genomic region using other RI populations in various environments (Orf et al., 1999). However, in the Minnesota '97 experiment (Table 4) , the QTL for yield was only moderately correlated with height, maturity, and reproductive period (RP) and even less with seed weight and flowering date (R1).


View this table:
[in this window]
[in a new window]
  		Table 4 Correlation coefficients between different traits in Minnesota 1997

 
Analysis of this yield associated locus (Satt561) identified a strong interaction with the marker Satt507, on LG U8. Figure 3a shows that expression of the QTL for yield associated with Satt561 is conditional upon the presence of the Archer allele of the QTL linked to Satt507. The significance of this epistatic interaction was very high (P = 3 x 10-6). No such dependence was observed for the QTLs for seed weight (Fig. 3b), or for height or maturity (data not shown.). That is, the differences in seed weight between subpopulations with the Satt561 Archer or Minsoy alleles persist irrespective of the alleles at the Satt507 locus (Fig. 3b, Panels 1, 2, and 3).



View larger version (31K):
[in this window]
[in a new window]
  		Fig. 3 Segregation of yield (a) and seed weight (b) QTLs linked to Satt561 and Satt507 in Minnesota in 1997— sub-populations corresponding to the two alleles at each locus or to each of the four alleles of the pair of interacting loci. For each panel (1–4) the plants in each allelic sub-population are ranked along the y-axis according to increasing yield or seed weight values (x-axis). Panels 1 and 4 show the allelic sub-populations of the Satt561 or Satt507 loci, respectively. An open triangle represents the population with the Minsoy allele and a closed triangle represents the population with the Archer allele. Panels 2 and 3 show the four allelic sub-populations corresponding to segregants at the two loci: (•) Archer allele of Satt507 and Minsoy allele of Satt561; ({circ}) = Archer allele of both; ({blacksquare}) = Minsoy allele of both; ({square}) = Minsoy allele of Satt507 and Archer allele of Satt561

 
Figure 4 presents data from another environment, Chile '95. There is no evidence for a QTL for yield linked to Satt561 (Fig. 4a). Nevertheless, the QTL for seed weight linked to Satt561 was identified, again without epistatic effects (Fig. 4b).



View larger version (30K):
[in this window]
[in a new window]
  		Fig. 4 Segregation of yield (a) and seed weight (b) QTLs linked to Satt561 and Satt507 in Chile in 1995— sub-populations corresponding to the two alleles at each locus or to each of the four alleles of the pair of interacting loci. For each panel (1–4) the plants in each allelic sub-population are ranked along the y-axis according to increasing yield or seed weight values (x-axis). Panels 1 and 4 show the allelic sub-populations of the Satt561 or Satt507 loci, respectively. An open triangle represents the population with the Minsoy allele and a closed triangle represents the population with the Archer allele. Panels 2 and 3 show the four allelic sub-populations corresponding to segregants at the two loci: (•) Archer allele of Satt507 and Minsoy allele of Satt561; ({circ}) = Archer allele of both; ({blacksquare}) = Minsoy allele of both; ({square}) = Minsoy allele of Satt507 and Archer allele of Satt561

 

   Discussion
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results
 Discussion
REFERENCES
 
Much of the segregation of yield which we have observed in the NA and MA populations results from interactions between QTLs linked to Satt277 and B172_2 (in LG U9 and U3) or Satt561 and Satt507 (in LG U14 and U8), respectively. The QTLs linked to B172_2 and to Satt507 could not have been detected by single locus analysis. However, they appear to exert an allele specific control over the expression of the yield loci with which they interact (linked to Satt277 and Satt561 respectively). This facilitated their identification (Fig. 2, 3, and 4). The yield locus associated with Satt277 represents the introduction of an QTL allele for increased yield from Noir 1, an exotic source (Tanksley and McCouch, 1997), whereas the increase associated with Satt561 is due to an allele from the elite line, Archer. In both cases, the controlling alleles also came from the parent that contributed the high yielding allele. The regulatory region on LG U3, which conditions the increase in yield, also contains loci which regulate seed coat color (Bernard and Weiss, 1973) and cyst nematode resistance (Matson and Williams, 1965). It is therefore possible that B172_2 is linked to a cluster of regulatory genes or a single pleiotropic regulatory gene.

Archer is an elite line derived from the narrow gene pool that underlies the northern U.S. germplasm (Cianzio et al., 1991). If it is representative of other northern U.S. elite cultivars, introduction of the two interacting yield QTL alleles from the "exotic" cultivar Noir 1 holds great promise for increasing yield in the northern U.S. germplasm as well as in southern U.S. germplasm. On the other hand, the Archer alleles of the loci linked to Satt561 and Satt507 are probably already in northern U.S. germplasm and therefore may only be useful in southern U.S. germplasm. Moreover, the association with major height and maturity genes may compromise the usefulness of the Archer alleles.

In both cases, breeding to increase yield will require the simultaneous introgression of two QTLs into new germplasm. Marker selection should facilitate this. Satt277 is flanked by SSR (simple sequence repeat) markers Satt286 and Satt489 (Fig. 1). These additional flanking markers can be used to reduce the possibility of recombination in this region during backcrossing. Similarly, B172_2 is flanked by the SSR markers Satt187 and GMENOD2B on one side and Satt315 on the other. Experiments to introgress the Noir1 yield alleles into both northern and southern germplasms are now underway. The Archer alleles on LG U8 and U14 also are associated with useful SSR markers for marker selection (Cregan et al., 1999; Orf et al., 1999), which should facilitate their introduction into southern germplasm.

Specific environmental effects on quantitative trait values (most notably yield) have been known for a long time (Brim, 1973). We have already obtained evidence for epistatic effects which may occur across environments (Lark et al., 1995; Orf et al., 1999). The data presented here, as well as data for other traits in these three populations to be presented elsewhere, suggest that specific environmental effects can be the result of specific interactions between loci.SAS Institute 1988


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 Materials and methods
 Results
 Discussion
 REFERENCES
 
Contribution of Minnesota Agric. Exp. Stn. Paper No. 981130073, Minnesota Scientific Journal Series. Work supported in part from grants from the United Soybean Board, Minnesota Soybean Research and Promotion Council and a grant to KGL from the National Institutes of Health Grant GM 42337.

Received for publication July 15, 1998.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results
 Discussion
 REFERENCES
 




This article has been cited by other articles:


Home page
 Crop Sci.Home page
P. S. Guzman, B. W. Diers, D. J. Neece, S. K. St. Martin, A. R. LeRoy, C. R. Grau, T. J. Hughes, and R. L. Nelson
QTL Associated with Yield in Three Backcross-Derived Populations of Soybean
Crop Sci., January 22, 2007; 47(1): 111 - 122.
[Abstract] [Full Text] [PDF]

Home page
 Crop Sci.Home page
D. R. Walker, A. M. Scaboo, V. R. Pantalone, J. R. Wilcox, and H. R. Boerma
Genetic Mapping of Loci Associated with Seed Phytic Acid Content in CX1834-1-2 Soybean
Crop Sci., January 24, 2006; 46(1): 390 - 397.
[Abstract] [Full Text] [PDF]

Home page
 Crop Sci.Home page
C. D. Messina, J. W. Jones, K. J. Boote, and C. E. Vallejos
A Gene-Based Model to Simulate Soybean Development and Yield Responses to Environment
Crop Sci., January 24, 2006; 46(1): 456 - 466.
[Abstract] [Full Text] [PDF]

Home page
 Crop Sci.Home page
V. S. Primomo, V. Poysa, G. R. Ablett, C.-J. Jackson, M. Gijzen, and I. Rajcan
Mapping QTL for Individual and Total Isoflavone Content in Soybean Seeds
Crop Sci., October 27, 2005; 45(6): 2454 - 2464.
[Abstract] [Full Text] [PDF]

Home page
 J HeredHome page
N. T. Cach, J. C. Perez, J. I. Lenis, F. Calle, N. Morante, and H. Ceballos
Epistasis in the Expression of Relevant Traits in Cassava (Manihot esculenta Crantz) for Subhumid Conditions
J. Hered., September 1, 2005; 96(5): 586 - 592.
[Abstract] [Full Text] [PDF]

Home page
 Crop Sci.Home page
S. K. Stombaugh, J. H. Orf, H. G. Jung, K. Chase, K. G. Lark, and D. A. Somers
Quantitative Trait Loci Associated with Cell Wall Polysaccharides in Soybean Seed
Crop Sci., November 1, 2004; 44(6): 2101 - 2106.
[Abstract] [Full Text] [PDF]

Home page
 Agron. J.Home page
K. J. Boote, J. W. Jones, W. D. Batchelor, E. D. Nafziger, and O. Myers
Genetic Coefficients in the CROPGRO-Soybean Model: Links to Field Performance and Genomics
Agron. J., January 1, 2003; 95(1): 32 - 51.
[Abstract] [Full Text] [PDF]

Home page
 Crop Sci.Home page
A. A. Mahama, K. S. Lewers, and R. G. Palmer
Genetic Linkage in Soybean: Classical Genetic Linkage Groups 6 and 8
Crop Sci., September 1, 2002; 42(5): 1459 - 1464.
[Abstract] [Full Text] [PDF]

Home page
 Crop Sci.Home page
J. Yuan, V. N. Njiti, K. Meksem, M. J. Iqbal, K. Triwitayakorn, My. A. Kassem, G. T. Davis, M. E. Schmidt, and D. A. Lightfoot
Quantitative trait loci in Two Soybean Recombinant Inbred Line Populations Segregating for Yield and Disease Resistance
Crop Sci., January 1, 2002; 42(1): 271 - 277.
[Abstract] [Full Text] [PDF]

Home page
 Crop Sci.Home page
N. Reyna and C. H. Sneller
Evaluation of Marker-Assisted Introgression of Yield QTL Alleles into Adapted Soybean
Crop Sci., July 1, 2001; 41(4): 1317 - 1321.
[Abstract] [Full Text] [PDF]

Home page
 Crop Sci.Home page
J.E. Specht, K. Chase, M. Macrander, G.L. Graef, J. Chung, J.P. Markwell, M. Germann, J.H. Orf, and K.G. Lark
Soybean Response to Water: A QTL Analysis of Drought Tolerance
Crop Sci., March 1, 2001; 41(2): 493 - 509.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (26)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Orf, J.H.
Right arrow Articles by Lark, K.G.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Orf, J.H.
Right arrow Articles by Lark, K.G.
Agricola
Right arrow Articles by Orf, J.H.
Right arrow Articles by Lark, K.G.

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