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CELL BIOLOGY & MOLECULAR GENETICS

Molecular Mapping of Loci for Agronomic Traits on Chromosome 3A of Bread Wheat

^a Dep. of Agronomy, Univ. of Nebraska, Lincoln, NE 68583-0915 USA
^b Dep. of Biology/Microbiology, South Dakota State Univ., Brookings, SD 57007 USA
^c Dep. of Agronomy, Univ. of Wisconsin, Madison, WI 53706 USA
^d Regional Agricultural Research Center, Diyatalawa Road, Bandarawela, Sri Lanka

pbaenziger1{at}unl.edu

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION Materials and methods Results and discussion REFERENCES

 
Chromosome 3A of bread wheat (Triticum aestivum L.) cultivar `Wichita' (WI) was previously found to differ from that of `Cheyenne' (CNN) for genes affecting a number of agronomically important traits such as grain yield (GYLD), kernel number spike^-1 (KPS), 1000-kernel weight (TKWT), spike number m^-2 (SPSM), grain volume weight (GVWT), plant height (PHT), and anthesis date (influenced by Eps locus). This study was designed to map the Eps locus and to identify regions of chromosome 3A of wheat associated with agronomic traits. A population of 3A recombinant inbred chromosome lines (RICLs-3A) was previously evaluated in replicated field trials. Thirteen RFLPs and one morphological marker locus, Eps, were used to develop a genetic linkage map and to identify QTLs associated with agronomic traits. Individual loci explained from 8.9 to 38.2% of the total phenotypic variation for the measured traits. The major locus Eps was mapped distal to an RFLP marker locus Xcdo549 on the short arm of chromosome 3A and explained 38.2% of the total phenotypic variation for PHT, and 17.4% for both KPS and TKWT. Additional QTLs for PHT, TKWT, and KPS were identified on the chromosome. A QTL for SPSM on the long arm of chromosome 3A was tightly linked to QTL for PHT and KPS. QTLs for GYLD were identified only in a few individual environments whereas no QTL was detected for GVWT. No epistasis was detected between markers associated with QTLs. The QTLs identified across environments were consistent in all or most environments, hence should be useful in future marker assisted selection programs for breeding wheat cultivars.

Abbreviations: CNN, `Cheyenne' • Eps, Earliness per se • GVWT, grain volume weight • G x E, genotype by environment interaction • GYLD, grain yield • KPS, kernel number per spike • PHT, plant height • QTL, quantitative trait locus • RFLP, restriction fragment length polymorphism • RICL, recombinant inbred chromosome line • RIL, recombinant inbred line • TKWT, thousand kernel weight • SPSM, spike number per square meter • WI, `Wichita'

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION Materials and methods Results and discussion REFERENCES

 
ABETTER GENETIC UNDERSTANDING of agronomic traits such as grain yield and its component traits in wheat is needed to improve this important food crop. Genetic analyses of wheat agronomic traits have been facilitated by chromosomal manipulation, especially chromosome substitution lines and RICLs (Law, 1966; Morris et al., 1960–1984; Worland and Law, 1985; Yen and Baenziger, 1992; Berke et al., 1992a,b; Joppa et al., 1997, Shah et al., 1999). Chromosome substitution lines allow the effect of a whole chromosome to be studied, while RICLs allow chromosomal effects to be partitioned into chromosomal-segmental effects.

Recombinant inbred chromosome lines (also called `recombinant substitution lines') can be used to identify and map gene(s) controlling agronomic traits by biometrical approaches (Law, 1966; Yen and Baenziger, 1992; Shah et al., 1999) and by linkage with molecular markers (Lander and Botstein, 1989; Paterson et al., 1990; Joppa et al., 1997). Recombinant inbred chromosome lines are superior to recombinant inbred lines (RILs) for studying the effect of a specific chromosomal region because they have a more uniform genetic background and knowing the targeted chromosome facilitates molecular marker selection. Recombinant inbred chromosome line populations have been used to construct genetic linkage maps in tetraploid wheat (T. turgidum L.) for chromosome 6A and 6B (Chen et al., 1994) and to map grain protein content gene(s) on chromosome 6B (Joppa et al., 1997). In hexaploid wheat, RICLs have been used to map major genes and their pleiotropic effects on important quantitative traits. Law (1966) mapped two genes for days to ear emergence; single genes for each of the characters purple culm, powdery mildew (incited by Blumeria graminis DC. f. sp. tritici Em. Marchal) resistance, and leaf rust (incited by Puccinia recondita f. sp. tritici Roberge. ex. Desmaz.) resistance on chromosome 7B, which were then used as marker loci for locating PHT, grain weight, grain number, and tiller number on 7B (Law, 1967). Law et al. (1976) mapped genes for ear-emergence time on chromosome 5A and 5D. Worland and Law (1985) mapped two genes each for the time to ear-emergence and PHT on chromosome 2D by the use of a RICL-population. Molecular markers coupled with RICL-population were used to identify QTLs controlling tissue-culture response on chromosome 2B (Ben Amer et al., 1997). Molecular marker-QTL associations were also established for agronomic traits such as GYLD, TKWT, protein concentration, and kernel hardness in a population of BC₂F₁ lines developed between winter wheat and T. tauschii L. (Fritz et al., 1995). However, there have been no attempts to map the loci on specific chromosome(s) controlling important agronomic traits such as GYLD and its component traits in common wheat, specifically in a population derived from a cross of well-adapted genotypes which is of greatest interest to wheat breeders.

Previously, a single locus, Eps, segregating for anthesis date and its association with PHT and TKWT was identified by evaluating a RICLs-3A population (Shah et al., 1999) over diverse environments. The group 3 chromosomes were reported by Miura and Worland (1994) to affect earliness per se (chromosome 3A), vernalization (chromosome 3B), and photoperiod sensitivity (chromosome 3D). In a later study, Miura et al. (1999) identified two genes affecting earliness per se on chromosome 3A. Using ditelosomic lines, they suggested one gene was located on the short arm and one gene was on located on the long arm. The objectives of this study were to develop a genetic linkage map and to identify molecular markers associated with the Eps locus and with QTLs controlling agronomic traits on chromosome 3A of wheat.

	Materials and methods

TOP NOTES ABSTRACT INTRODUCTION Materials and methods Results and discussion REFERENCES

 
Plant Materials and Field Evaluation
The plant materials used in this study were the parental cultivar CNN, chromosome substitution line CNN(WI3A), and a set of 50 CNN(RICL-3A) developed by R. Morris and Y. Yen between CNN and CNN(WI3A) following the method described by Law (1966). Briefly, RICLs-3A population was developed by crossing the chromosome substitution line CNN(WI3A) to CNN. In the F₁ , the only effective recombination occurs between WI3A and CNN3A chromosomes as all the other chromosomes are from CNN. The F₁ was crossed as a male to CNN monosomic for chromosome 3A. Monosomic progeny (2N - 1 = 41) were selected from this cross, which are hemizygous recombinant monosomic lines. The male parent (F₁ in this case) transmits a euploid gamete (1N = 21) and the female monosomic plant produces aneuploid (1N - 1 = 20) or euploid (1N = 21) gametes. The recombinant monosomic progeny resulting from the fertilization of a male euploid gamete with a female aneuploid gamete were selected. The disomic progeny (2N = 42) resulting from the fertilization of a male euploid gamete with a female euploid gamete were discarded. Upon selfing the recombinant monosomic line and selecting the disomic progeny, 50 homozygous RICLs-3A were developed in CNN background. The seed of each line was increased in the greenhouse and the lines were then used in field trials. The RICL-3A population, CNN, and CNN(W13A) were evaluated in four to eight diverse Nebraska environments during 1994–1996 for agronomic performance as described previously by Shah et al. (1999).

RFLP Analyses
Genomic DNA was extracted from leaves of 2 to 4-wk-old greenhouse grown plants by the CTAB method (Saghai-Maroof et al., 1984) with modifications. Briefly, 0.2 to 0.4 g of lyophilized or 2 to 4 g fresh leaf tissue was powdered by grinding either in liquid nitrogen or sterile fine sand and incubated in DNA extraction buffer [1 M Tris pH 7.5, mixed alkyltrimethyl-ammonium bromide (CTAB), 5 M NaCl, 0.5 M EDTA pH 8.0, and 2-ß-mercaptoethanol] at 60°C for 1 to 3 h. The slurry was extracted with 0.8 volume of chloroform-octanol (24:1 v/v). The DNA was precipitated from the supernatant by adding one volume of cold isopropanol. The DNA precipitate was washed with 76% (v/v) ethanol (EtOH) containing 0.2 M sodium acetate for 20 min, rinsed with 76% EtOH containing 10 mM ammonium acetate, and dissolved in Tris-EDTA. The DNA was purified by phenol purification procedures (Maniatis et al., 1982) and recovered by ethanol precipitation.

Clones known to hybridize to DNA fragments located in homoeologous group 3 chromosomes of wheat were used. The cDNA and gDNA clones used as probes were kindly provided by the USDA-ARS central probes repository, Albany, CA, and Dr. A. Graner, Federal Center for Breeding Research on Cultivated Plants, Grünbach, Germany.

Genomic DNA digestion, southern blot analyses, probe labeling and purification, hybridization, and autoradiography were performed as described by Gill et al. (1991). Substitution line CNN(WI3A) coupled with CNN and WI facilitated the identification of RFLPs specific for chromosome 3A, while RICLs-3A were included for segregation analysis of marker loci and QTL identification on the chromosome.

Linkage Analysis and Map Construction
Thirteen of the chromosome 3A specific RFLP probes polymorphic between CNN and WI and a morphological marker locus influencing anthesis date (Eps) previously identified (Shah et al., 1999) were used to construct chromosome 3A linkage map. A bimodal distribution for anthesis date caused by Eps in the RICL population was used as evidence of a single locus segregation (Shah et al., 1999). A break between the two classes occurred at 38.3 d after May 1 which was roughly equal to parental means [CNN or CNN(WI3A)] plus or minus one standard error unit. When the RICLs were grouped with early anthesis date (<38.3 d after May 1) and grouped with late anthesis date (>38.3 d after May 1), a chi-square test (² = 2.88, P = 0.09) indicated 1:1 segregation for two alleles at a single locus. Alleles at this locus have been given the tentative gene symbols, EpsWi for the dominant allele for earliness per se from WI and epsCnn for the recessive allele from CNN (R. McIntosh, 1999, personal communication). Goodness-of-fit to a 1:1 segregation ratio for all molecular marker loci was also tested using a Chi-square analysis (P < 0.05).

The linkage analysis was performed with the data obtained from RICL-3A population, with computer program `MAP MANAGER', which helps analyze the results of genetic mapping experiments using intercrosses with codominant markers, backcrosses, or RIL in experimental plants or animals (Manly, 1993). A logarithm of odds (LOD) score of 4.0 was used as a linkage threshold to construct the linkage map, with maximum recombination fraction as 0.30. The map constructed for chromosome 3A using CNN(RICL-3A) population was compared with the previously published group 3-chromosome maps of wheat to determine if the order of the loci was similar.

QTL Analysis
For each marker locus, QTL identification was performed by comparing the phenotypic means combined over environments of the marker genotype classes. The QTL analysis for each trait was also carried out in each environment (data not shown). The data of all marker loci (including Eps locus) characterized on chromosome 3A were used as independent marker variables in the QTL analysis. Initially, a single-factor analysis of variance (ANOVA) was performed with PROC GLM (SAS Institute Inc., Cary, NC) on each pairwise combination of quantitative trait and marker locus for significant association between a marker locus and a quantitative trait. Significance at the P 0.05 level was considered suggestive of a QTL at or near the marker locus. The markers which indicated a significant association with agronomic traits from the single-factor ANOVA were then subjected to multiple regression analysis by PROC REG (SAS Institute Inc., Cary, NC) statement to select the best set of markers in the final model. The coefficient of multiple determination (R²) from the single-factor ANOVA and the regression models for each significant marker were used as an indication of the proportion of total phenotypic variation explained by the set of markers. Molecular marker loci that were significant at P 0.05 for a trait of interest in a final model by the multiple regression analysis were tested for significant interactions (P 0.05) by two-way ANOVA with PROC GLM (SAS Institute Inc., Cary, NC), to determine if QTLs controlling a trait were epistatic.

In the situation where RICL population was non-significant for a trait of interest from the combined ANOVA (Shah et al., 1999), a Bonferroni test was used (Milliken and Johnson, 1984) to limit the probability of making a type 1 error when testing for marker-QTL contrasts in single factor ANOVA. This approach was justified on the basis that (i) the size of differences between the RICL means are very small relative to experimental error, and (ii) the initial analysis is based on the combined ANOVA results (Shah et al., 1999) and protected post-hoc comparisons are appropriate.

	Results and discussion

TOP NOTES ABSTRACT INTRODUCTION Materials and methods Results and discussion REFERENCES

 
Genetic Map of Chromosome 3A
The segregation of 10 RFLP loci in CNN(RICL-3A) population fit the expected 1:1 genetic ratio, indicating monogenic segregation, while three loci (Xbcd1555, Xbcd141, and Xbcd372) showed a slight distortion segregation biased towards CNN parent (² values of 4.3, 5.7, and 5.7 (respectively), 0.01< P < 0.05). The marker order on chromosome 3A (Fig. 1) developed here was compared with previously published maps of group 3 chromosomes (ITMI; McGuire and Qualset, 1996) and the order of the loci was found to be the same. Most of the chromosome maps of wheat indicate that the gene order on each of the homoeologous chromosomes is almost identical (Chao et al., 1989). This information can be utilized to increase the map density for each chromosome utilizing the probes mapped across the genomes.

View larger version (17K): [in this window] [in a new window]   Fig. 1 Chromosome 3A map of wheat (Triticum aestivum L.) showing the locations of loci controlling anthesis date (Eps), plant height (PHT), kernel number per spike1 (KPS), 1000-kernel weight (TKWT), and spike number per square meter (SPSM), associated with RFLP markers (P < 0.05). The map was developed with a population of recombinant inbred chromosome lines for chromosome 3A made from CNN(WI3A) and its parent cultivar Cheyenne (CNN). The marker order is shown on right hand side while the genetic distance is on left hand side of the map. A break is shown between Eps, and Xcdo549 and Xbcd907 because the distance between the loci would indicate they are close to independent. The centromere is designated by `C' and was located from the ITMI map (McGuire and Qualset, 1996)

QTL Detection
The results from single-factor ANOVA for the agronomic traits combined over environments and markers associations indicated three to eight significant (P 0.05) marker locus-trait associations for different agronomic traits. The most significant markers associated with a QTL for each trait from single-factor ANOVA were selected and used for multiple regression analysis. Individual loci explained from 8.9% (Xcdo638 for TKWT) to 38.2% (Eps for PHT) of the phenotypic variation by regression analysis (Table 1) .

Multiple QTLs were found for some traits at different regions of the chromosome indicating that chromosome 3A contains multiple genes affecting some traits. Two QTLs for PHT, three for KPS, two for TKWT, and one for SPSM were detected using the multiple regression model. However, by the Bonferroni test for the two traits where the RICLs were not significantly different (KPS and SPSM) in the initial combined ANOVA, only one QTL would have been identified for KPS (Eps) and SPSM (Xbdc141) by the single factor analysis. Hence the number of QTLs on chromosome 3A affecting KPS is most likely at least one and possibly three. The number of QTLs affecting SPSM was unchanged on the basis of either estimation procedure. No digenic epistasis (P < 0.05) was found between any of the markers significantly associated with QTLs controlling PHT, KPS, and TKWT.

It is interesting that all of the alleles giving the highest phenotypic values at the QTLs detected here were contributed by one parent. This result is in agreement with Shah et al. (1999) not finding transgressive segregation. In many cases, it is assumed that the genes of agronomic importance are in repulsion phase; however, for genes on chromosome 3A, this was not the case. It is also important to note that the QTLs for PHT, TKWT, KPS, and SPSM that were identified across environments, were also found in all or most of the individual environments (data not shown) with similar magnitude of their effects. This consistency of the QTL detection across the environments supported the utility of these markers associated with QTLs.

The percentage of phenotypic variation (R²) explained by Eps locus for the traits PHT (38.2%), TKWT (17.4%), and KPS (17.4%), indicated that much of the genetic variation in these traits was explained by this region. In Shah et al. (1999), there were significant correlations among the RICL-3A lines between anthesis date and PHT (r = 0.59**) and anthesis date and TKWT (r = -0.56**). There was also a significant correlation between TKWT and PHT (r = -0.32**). Shah et al. (1999) suggested that pleiotropy or linkage, or the presence of additional loci affecting these traits may explain these correlations and the identification of a few RICLs having the CNN(WI3A) phenotype for one trait, but the CNN phenotype for the other correlated trait. While the region near to Eps locus exerted a larger effect on PHT and TKWT, a region near Xbcd1555 had high association with QTLs affecting PHT (Fig. 1) indicating a second region with additional gene(s) influencing PHT. Similarly, a second region near Xcdo638 affected TKWT. Hence while pleiotropy cannot be ruled out for genes at the Eps locus, additional loci do affect PHT and TWKT. A few lines (two or three) were similar to CNN(WI3A) for one trait and similar to CNN for a second trait which suggested that the Eps locus may be linked to genes controlling the other traits, rather than a pleiotropic effect. The correlation between TKWT and PHT can be explained by their QTLs also sharing similar regions on the chromosome.

In summary, we were able to develop an initial genetic linkage map of chromosome 3A using RFLP markers and mapped an earliness per se locus (Eps) on the short arm of the chromosome that explained significant variation for PHT, TKWT, and KPS. We identified more than one QTL for agronomic traits such as TKWT, PHT, and KPS on specific regions of the chromosome. Two major regions or clusters of the QTLs were found on the chromosome. These regions need to be saturated with additional markers especially to determine if alleles at the Eps locus are linked or pleiotropic to alleles controlling PHT, KPS, and TKWT. Grain yield is a complex trait genetically and we were unable to identify GYLD QTLs across environments. Grain yield QTLs were identified only in a few individual environments. The relatively small population size and few replications within each environment used here, and the large G x E interaction, may have limited our ability to analyze this trait genetically. Other limiting factors for detecting QTLs for GYLD may be the low density of our chromosome 3A map or that yield might be influenced by many genes, each with relatively minor effects, scattered along the chromosome. It is quite possible that the yield components or other yield attributes are responsible for GYLD QTLs revealed by previous chromosome substitution studies and there might not be QTLs for GYLD per se. The methods and procedures developed here will be a ready tool to identify and map additional gene(s) on chromosome 3A and on other chromosomes in RICL populations. The markers associated with QTLs for important traits may be useful in future marker assisted selection programs to breed better wheat cultivars.Maniatis Fritsch Sambrook 1989; Morris 1960; SAS Institute Inc 1990

	ACKNOWLEDGMENTS

 
The authors wish to gratefully acknowledge Dr. Dermot P. Coyne, Professor, Department of Horticulture, University of Nebraska, and Dr. Robert A. Graybosch, Research Geneticist, USDA-ARS and Department of Agronomy, University of Nebraska for their reviews and valuable suggestions on the manuscript.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION Materials and methods Results and discussion REFERENCES

 
Contribution from Nebraska Agric. Res. Div., Journal Series No. 12379.

Received for publication October 5, 1998.

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